The analysis of
specific factors
influencing health
related quality of life:
large scale studies on
women population
age 12 to 85.
Magdalena Wiacek-Zubrzycka
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TABLE OF CONTENTS
Table of Contents
ABSTRACT 1
INTRODUCTION 2
Health Related Quality of Life 2
Blood pressure: Systolic and Diastolic Blood Pressure 3
Blood Pressure: The Role of Blood Lipids Levels - Total
Cholesterol, LDL Cholesterol and HDL Cholesterol. 6
Blood Pressure: The role of Triglycerides Levels. 8
Blood Pressure: The Role of Serum Uric Acid Level. 10
Blood Pressure: The Role of Serum Creatinine Level. 12
Blood Pressure: The Role of Body Mass Index. 13
METHODS 15
Subjects 15
BMI Analysis 16
Alcohol Consumption and Tobacco Smoking 19
Pregnancy, Breastfeeding, and Contraception. 21
Blood Pressure Measurements 24
Triglyceride Measurements 26
LDL Cholesterol Measurements 28
HDL Cholesterol Measurements 30
Total Cholesterol Measurements 32
Serum Uric Acid Measurements 34
Serum Creatinine Measurements 36
Statistical Analyses 38
RESULTS AND DISCUSSION 40
Association Between BMI and Tobacco Smoking Status.
41
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Association Between BMI and Alcohol Consumption
Status. 42
Association Between BMI and Pregnancy Status. 43
Association Between BMI and Chemotherapy Status. 44
Association Between BMI and Breastfeeding Status. 45
Association Between BMI and Contraception Use. 46
Association Between BMI and Total Cholesterol Levels
47
Association Between BMI and HDL Cholesterol Levels.
48
Association Between BMI and LDL Cholesterol Levels.
49
Association Between BMI and Triglyceride Levels. 50
Association Between BMI and Glomerular Flow Rate
(GFR). 51
Association Between BMI and Serum Uric Acid Level.52
Association Between Pregnancy Status and Levels of
Total Cholesterol. 53
Association Between Pregnancy Status and Levels of
HDL Cholesterol. 54
Association Between Pregnancy Status and Levels of
LDL Cholesterol. 55
Association Between Pregnancy Status and Levels of
Triglycerides. 56
Association Between Breastfeeding Status and Levels
of Total Cholesterol. 57
Association Between Breastfeeding Status and Levels
of HDL Cholesterol. 58
Association Between Breastfeeding Status and Levels
of LDL Cholesterol. 59
Association Between Breastfeeding Status and Levels
of Triglycerides. 60
Association Between Tobacco Smoking Status and
Levels of Total Cholesterol. 61
Association Between Tobacco Smoking Status and
Levels of HDL Cholesterol. 62
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Association Between Tobacco Smoking Status and
Levels of LDL Cholesterol. 63
Association Between Tobacco Smoking Status and
Triglyceride Levels. 64
Association Between Alcohol Consumption Status and
Levels of Total Cholesterol. 65
Association Between Alcohol Consumption Status and
Levels of HDL Cholesterol. 66
Association Between Alcohol Consumption Status and
Levels of LDL Cholesterol. 67
Association Between Alcohol Consumption Status and
Levels of Triglycerides. 68
Association Between Chemotherapy and Levels of Total
Cholesterol. 70
Association Between Chemotherapy and Levels of HDL
Cholesterol. 72
Association Between Chemotherapy and Levels of LDL
Cholesterol. 73
Association Between Chemotherapy and Triglyceride
Levels. 74
Association Between Contraception Use and Levels of
Serum Total Cholesterol. 75
Association Between Contraception Use and HDL
Cholesterol Levels. 76
Association Between Contraception Use and LDL
Cholesterol Levels. 77
Association Between Contraception Use and
Triglyceride Levels. 78
Association Between Glomerular Filtration Rate and
Levels of Serum Total Cholesterol. 79
Association Between Glomerular Filtration Rate and
Levels of HDL Cholesterol. 80
Association Between Glomerular Filtration Rate and
Levels of LDL Cholesterol. 81
Association Between Glomerular Filtration Rate and
Levels of Triglycerides. 82
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Association Between Serum Uric Acid Level and Levels
of Serum Total Cholesterol. 83
Association Between Serum Uric Acid Level and HDL
Cholesterol Levels. 84
Association Between Serum Uric Acid Level and LDL
Cholesterol Levels. 85
Association Between Serum Uric Acid Level and
Triglyceride Levels. 86
Association Between Hypertension and Serum Total
Cholesterol Levels. 87
Association Between Hypertension and Serum HDL
Cholesterol Levels. 88
Association Between Hypertension and Serum LDL
Cholesterol Levels. 89
Association Between Hypertension and Serum
Triglyceride Levels. 90
Association Between Hypertension and Glomerular
Filtration Rate. 91
Association Between Hypertension and Serum Uric
Acid Levels. 92
SUMMARY AND CONCLUSIONS 93
APPENDIX 99
REFERENCES 208
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ABSTRACT
Objective: The objective of this study if to verify currently accepted
clinical descriptions of normotension, hypertension, hyperlipidemia, and
hyperuricemia versus the extended data set. Design: Women age 12 to 85
encompassed by NHANES III and NHANES 1999-2000, 2001-2002,
2003-2004, and 2005-2005 datasets were included in the study. The
analysis of the combined data set allowed for the analysis of the large
sample comprising of 20022 subjects. The association between the
clinically accepted values of the specific factors such as for example, total
cholesterol levels, HDL cholesterol levels, LDL cholesterol levels versus
tobacco smoking status, alcohol consumption status, pregnancy status and
others were analyzed using Pearson Chi-Square Statistics and CochranMantel-Haenszel
Statistics. Results: The analysis of the results of the tests
for general association confirmed the majority of recent reports indicating
correlations between the studied parameters. However, in some cases
significant discrepancies between this report and others were found.
Conclusions: The presented report is among a very few ever performed
on such a large scale. The confirmation of some of the recent reports
indicates that current trends of research that are focused on large scale
analysis of a variety epidemiological data leads to congruent results. Thus,
the assessment of health related quality of life based on currently accepted
clinical values is possible however, a caution have to be exercised.
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INTRODUCTION
Health Related Quality of Life
For many years both clinicians and policymakers are engaged in
development of a universal measure of health-related quality of life
(HRQL). Among multiple means that may be employed for assessment of
HRQL are self – or interviewer-administered questionnaires and analytical
methods allowing following the changes in homeostasis in response to a
variety of environmental factors. However, the gravity of a variety of
factors influences HRQL. This in turn requires a robust definition or
HRQL. Following the definition proposed by Patric et al. 1 health related
quality of life encompasses health status, functional status, and quality of
life. HQRL may be utilized for measuring the impact of many chronic
diseases such as, for example, chronic heart disease 2. Another reason for
measurement the health related quality of life is an assessment of personal
response to clinical criteria that are similar among different subjects.
Additionally, clinicians and policy makers should be able to differentiate
between people with different level of HRQLs 3.
Currently there are two approaches the allows to characterize HRQL:
the first comprises generic instruments such as single indicators or health
profiles; the second comprises specific instruments 4. The Sickness Impact
Profile, a part of health profile is an instrument allowing to measure
physical dimension (ambulation, mobility and movement) in concordance
with psychosocial dimension (social interaction, behavior, and
communication).
Among different approaches to quality-of-life measurement there are
also specific instruments; it is the instruments allowing to assess the health
status as a function of specific factors. These are the instruments that are
used primarily by clinicians. In the presented study we decided to
undertake the analysis of HRQL expressed as clinically accepted blood
pressure. We analyze the changes in blood pressure in a large women
population as a function of a variety of factors such as serum blood lipids,
body mass index, kidney disease, and serum uric acid level and compare
the derived results with those previously reported.
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Blood pressure: Systolic and Diastolic Blood Pressure
We know that en elevation of systolic blood pressure may be used
for prediction of a cardiovascular disease5-6. Although, this method of
health assessment is currently quite obvious we had to walk a long way
before understanding what we measure. The measurement of pulse
palapation was already carried in ancient Egypt. However, only in the
eighteen century Stephen Hales performed the first mensuration of blood
pressure (BP) and till mid-nineteen century there was no other means of
arterial blood assessment than puncture of an artery. In 1855 Vierordt
proposed an indirect and noninvasive technique employing a counter
pressure to force the pulsation in an artery. In 1856, Faivre was the first
clinician who managed to accurately estimate the blood pressure with the
following parameters: 120 mm Hg in the femoral artery and 115-120 mm
Hg in the brachial artery. In early 1900 a Russian surgeon N.C. Korotkoff
reported that when he listen to the blood flow using the stethoscope
placed over the brachial artery at the cubital fossa, distal to the Riva-Rocci
cuff, tapping sound could be heard. This is his technique that is currently
used with practically no changes. It was also a corner stone in work of Pal
Wood and William Evans 7.
However, the applicability of isolated systolic (SBP) and diastolic
(DPB) blood pressures was recognized only two decades ago 8. Since then
many studies on SBP as a function of a variety of factors, such as age 9,
height, body mass index 10, body weight 11, serum creatinine, and serum
uric acid 12, were performed. Some of the studies were also focused on
changes of the blood pressure as a function of specific biological events
such as, for example, menopause 13-14.
In the recent decade an extensive analysis of assonant changes in
SPB and DPB revealed specific age dependent between the SPB, DPB,
and the mean arterial pressure (MAP) 9. The results of studies indicated
the progressive increase in blood pressure as a function of age 15-16. It was
also shown that SPB rise continuously to the ninth decade. This
phenomenon is associated by a congruent two phase increase the pulse
pressure (PP). The first phase comprises age below 50 years of age and the
second above this age. The changes in the DBP have different pattern;
DBP rises until age of 50 where it may level for the rest of the live or fall
later in life 9.
The last few decades of study on hypertension related health risk
indicated that the specific attention should be given to SPB changes, since
these are the main risk factors for cardiovascular diseases. Franklin at al.9
4 | P a g e
also indicated that diastolic hypertension predominates before age 50 and
that the prevalence of systolic hypertension increases with age.
Hypertension is also a problem during pregnancy. Studies have shown that
at the beginning of the first trimester there is a gradual decrease in SBP
caused by prostacyclin and nitric oxide induced vasolidation. It continues
till reaching nadir about 22-24 week and from this point in time it rises
again. Women whose blood pressure was normal throughout pregnancy
may however, experience transient hypertension in the early post partum
period 17-19.
The analysis of the third National Health and Nutrition
Examination Survey (NHANES III) indicated that almost 80% of subjects
aged 50 or over with high BP, at least on a single occasion, had systolic
hypertension 20 This and the other studies also showed that this type of
hypertension was the least well managed, perhaps because it particularly
affects the elderly21.
The majority of studies describing age-dependent BP dynamics
are cross-sectional studies. However, longitudinal studies reported the
analogous pattern 22. The recent cohort study indicate age dependent
increase in BP to hypertensive levels 23. Fifty percent of those 65 years and
older have BP in the 130–139/85–89 mmHg range and only 26 percent
have BP between 120–129/80–84 mmHg range 23. This observation
combined with the observation derived from Framingham Heart Study
indicating that BP values above 120/80 mmHg are associated with a
significant increase in relative risk from cardiovascular disease (CVD) 24,
exposes imminent need for periodical BP monitoring along the aging
process.
The striking is that data previously accepted as non correlated
with risk of hypertension appeared to be correlated with high frequency of
CVD. These observations gave ground to the new Joint National
Committee on Prevention, Detection, Evaluation, and Treatment of High
Blood Pressure (JNC) 7 report 25, which introduced the new classification
including the term “prehypertension”. This new term applies for those
with SBPs ranging from 120–139 mmHg and/or DBP from 80–89
mmHg.
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Table 1. Blood pressure classification according to JNC 6 26 and JNC
7 25.
JNC 6 category SBP/DBP JNC 7 Category
OPTIMAL < 120/80 NORMAL
NORMAL 120-129/80-84
PREHYPERTENSION
BORDERLINE 130-139/85-89
HYPERTENSION ≥ 140/90 HYPERTENSION
STAGE 1 140-159/90-99 STAGE 1
STAGE 2 160-179/100-109
STAGE 2
STAGE 3 ≥ 180/110
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Blood Pressure: The Role of Blood Lipids Levels - Total
Cholesterol, LDL Cholesterol and HDL Cholesterol.
Lipids play an enormous role in the homeostasis. For example,
cholesterol present in cell membranes gates its integrity and fluidity. It also
serves other multiple purposes in human organism and one of its most
important roles is biosynthesis of cortisone-like hormones; testosterone,
estrogen, and cortisone. It is also used in biosynthesis of bile acids which
are essential for digestion of fats. Lipids are also present in the human
organism as a lipid-protein combination. Among lipoproteins there are
three classes present in human serum that play a paramount physiological
role: low density lipoproteins (LDL), high density lipoproteins (HDL), and
very low density lipoproteins (VLDL).
The observed relationship between total cholesterol and coronary
heart disease (CHD) implied that an elevated LDL level is a powerful risk
factor and that the serum total cholesterol level can be used as a surrogate
for LDL cholesterol concentration which typically makes up 60 to 70
percent of the total serum cholesterol. The large scale epidemiological
studies, The Framingham Heart Study27 and the Multiple Risk Factor
Intervention Trial (MRFIT)28 have found a direct relationship between
LDL cholesterol concentration and the rate of new-onset of CHD in men
and women initially not threaten by this disease. It also appears that LCL
concentration above 2.59 mmol/L (100 mg/dL) is atherogenic. The
results of the recent clinical trials indicate a direct proportional relation in
LDL cholesterol level and CHD risk. Thus a 1 percent decrease in LDL
concentration leads to the reduction of CHD risk by 1 percent. Large
population study also indicate that cohorts maintaining low level of
cholesterol are exposed to much lower risk for CHD than cohorts
generally defined by an increased cholesterol level 29-30.
HDL cholesterol normally makes up 20–30 percent of the total
serum cholesterol. Epidemiological studies have shown that the level of
serum HLD cholesterol is reverse proportionally correlated with CHD
morbidity and mortality 27, 31 to such an extent that 1 percent decrease in
HDL cholesterol yield 2 to 3 percent increase in CHD risk32. It has been
shown that HDL is a direct cause of atherosclerosis but can also be an
indicator of the other health risk correlates 33-35. It is now clear that low
concentration of HDL caused by increased obesity or low level of physical
activity predicts CHD. Taking these facts into account Adult Treatment
Panel II 36 (ATP II) specified that low HDL cholesterol concentration i.e.
the concentration less than <35 mg/dL is one of the major risk factors
used to modify the therapeutic goal for LDL cholesterol. The same range
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of low HDL is proposed for both genders. ATP III 37 panel adjusted the
cut point of HDL cholesterol at 40 mg/dL, for both men and women
indicating that subjects having the cholesterol concentration less than 40
mg/dL should be classified as low cholesterol subjects and those with the
level of cholesterol greater than 40 mg/dL should be classified as high
cholesterol subjects.
The ongoing analysis of a variety of epidemiological studies lead
to reassessment of ATPII lipid classification and the new classification,
ATPIII classification, of total cholesterol, LDL cholesterol and HDL
cholesterol with the CHD risk and has been proposed, Table 2.
Table 2. Classification of Total Cholesterol, LDL Cholesterol, and
HDL Cholesterol Accordingly to ATP III Panel 37.
Total Cholesterol
(mg/dL)
LDL Cholesterol
(mg/dL)
HDL Cholesterol
(mg/dL)
< 100 Optimal < 40 Low
< 200 Desirable 100-129
near
optimal/
above
optimal 40-60 Normal
200-239
Borderline
High
130-159
Borderline
High
≥ 240 High 160-189 High
≥60 High
≥ 190 Very High
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Blood Pressure: The role of Triglycerides Levels.
Although early analyses did not identify triglycerides as an
independent risk factor for CHD 38 a number of current studies indicates
that there is a direct proportional relation between the concentration of
serum triglyceride and CHD 33, 39-40. The primary failure in finding
triglycerides as CHD risk factor is associated with its integral linking with a
number of physiological covariates such as total cholesterol, LDL
cholesterol, and HDL cholesterol. Triglycerides levels dynamics is also a
function of obesity, hypertension, and cigarette smoking 41. All
aforementioned associations indicate that subjects with elevated serum
triglycerides concentrations are at increased risk for CHD. This
observation is strengthen by results of the recent study 39-40 indicating that
in fact triglycerides can be considered as an independent risk factor for
CHD.
Elevation in blood triglyceride levels is a derivative of a variety of
factors which can be divided into two groups. The first group comprises
the factors related to quality of life and the second to diseases inducing
elevation of triglyceride level. Thus, the fist group comprises obesity,
physical inactivity, tobacco smoking, excess alcohol intake, and highcarbohydrate
diet. The second group comprises type 2 diabetes, chronic
renal failure, nephrotic syndrome, and genetic factors. However, the most
common are obesity and physical inactivity 8, 42-44. At current state of
knowledge we assume that a healthy subject not exposed to any of
aforementioned factors is defined by an average serum triglyceride levels
of 100 mg/dL 44.
Triglyceride-raising factors may increase triglyceride levels about
150 to 200 percent that is related to concentration range 150 to 200
mg/dL 43-44. The analysis of correlations between serum triglycerides levels
and CHD resulted in recognition of the fact that blood triglyceride levels
can be adopted as risk markers for CHD. The recent findings indicate that
triglyceride level≥ 200 mg/dL is consonant with an elevated level of
atherogenic factors that increase the risk for CHD significantly more than
triglycerides alone 45-46. Taking into account the applicability of serum
triglycerides levels in predicting the risk for CHD, ATPIII proposed the
updated triglyceride classification.
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Table 3. Triglyceride categories accordingly to ATP II 36 and ATP
III 37.
Triglyceride Category ATP II Levels ATP III Levels
Normal triglycerides <200 mg/dL <150 mg/dL
Borderline-high
triglycerides
200–399 mg/dL 150–199 mg/dL
High triglycerides 400–1000 mg/dL 200–499 mg/dL
Very high triglycerides ≥1000 mg/dL ≥500 mg/dL
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Blood Pressure: The Role of Serum Uric Acid Level.
Uric acid is a product of purine metabolism. In humans it is
catabolized by the urate oxidase (EC 1.7.3.3) to allantoin excreted with
urine. The level of uric acid in humans is generally higher than in other
mammals and is generally greater than 2 mg/dL. The level of uric acid is a
function of a specific diet, alcohol consumption or a disease. For example
reduction in glomerular filtration rate increases the level of serum uric acid
47. The physiological state described by an elevated level of serum uric acid
is called hyperuricemia and is usually defined as > 7.0 mg/dL in men and
>6.0 mg/dL in women. A number of reports indicated correlation
between an elevated level of serum uric acid level and CHD 48-53. The
recent study on association between serum uric acid concentration and the
risk of CHD indicates that subjects with baseline serum uric acid values in
the top 33 percent of the population are defined by about a 10 percent
greater risk of CHD than those in the bottom 33 percent 54.It has also
been shown that correlation between serum uric acid and CHD risk is
stronger in females than in males 54-55.
It has been observed that the level of uric acid in postmenopausal
women is higher than in premenopausal and in perimenopausal women 49.
Also obese subjects and subjects with impairment of renal urate excretion
are described by an increased level of serum uric acid. For over fifty years
we know that the level of uric acid is directly proportional to BP51. One of
the possible explanation of this phenomenon is that an increase in serum
uric acid may be due to the decrease in renal blood flow 52.
Elevation in serum uric acid level can also be caused by factors such
as alcohol drinking 56, obesity, and use of diuretic. The recent studies
indicated that serum uric acid level is a function of multiple and per se
merely mark increased risk of cardiovascular diseases 57-58 (Table 4).Thus,
hyperuricemia is consider benign if is not assonant to kidney stones 59-60.
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Table 4. Studies on Uric Acid Level as a Function of CHD since
1990.
Study
Univariate correlation with
cardiovascular risk
Framingham
1999 61 yes
Honolulu Heart
1995 62 yes
1999 63 yes
NHANES I
1995 55 yes
2000 64 yes
ARIC (Atherosclerosis Risk in Communities Study)
2000 65 yes
British Regional Hart Study
1997 66 yes
MONICA (Monitoring Trends and Determinants in
Cardiovascular Diseases)
1999 67 yes
CASTEL (Cardiovascular Study in the Elderly)
1993 68 yes
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Blood Pressure: The Role of Serum Creatinine Level.
One of the markers of chronic kidney disease (CKD) is a ratio of 30
mg/g or greater of urine albumin to creatinine ratio (UCAR) 69. A normal
UACR in women is less than 30 mg/g 70. It has been shown that reduction
in UACR id directly proportional to incidence of cardiovascular disease 71.
A variety of studies focused on the specific groups of subjects, such as
hypertensive subjects, elderly, subjects with recent stroke of survives of
myocardial infarction, have shown that serum creatinine level may be
consider an independent predictor of cardiovascular disease 72-75.
The extensive study on applicability of serum creatine level 76 as a
marker for long-term effects of elevated blood pressure indicated that
about 14 percent of hypertensive subjects were defined by a serum
creatinine level greater or equal to 116 µmol/L. However, this study also
indicated that a single measurement of serum creatinine level is not
satisfactory to assess with high probability a risk of cardiovascular disease.
Another marker considered to be useful for assessment of the risk of
cardiovascular disease is creatinine clearance, which is a significantly more
sensitive measurement of kidney function as compared to serum creatinine
(Table 5). It has been shown that creatinine clearance lower than 60
ml/min per 1.73 m2 is associated with an increased risk of cardiovascular
disease 77. Large scale analysis of NHNAES II data 78 indicated that about
14.2 percent of subjects with hypertension had glomerular flow rate (GFR)
below 60 mL per minute per 1.73 m2 and that prevalence of low GFR
progressively increases with age. However the recent study 79 on the
subject using predicted creatinine clearance values 80 did not confirmed the
direct applicability of this factor in prognosis of cardiovascular risk.
Table 5. Stages of Chronic Kidney Disease 81
Stage GFR (mL per minute per 1.73 m2)
1 ≥ 90
2 60 - 89
3 30 - 59
4 15 - 29
5 < 15
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Blood Pressure: The Role of Body Mass Index.
Body Mass Index (BMI) is a ratio of weight-to-height allowing to
classify underweight, overweight and obesity in adults. It is defined as the
weight in kilograms divided by the square of the height in meters (kg/m2).
Currently the World Health Organization 82 in its web database presents
the following classification of obesity: underweight, normal range,
overweight, pre-obese, and obese (Table 6).
Table 6. Body Mass Index (BMI) classification accordingly to the
World Health Organization (WHO) 82.
Classification BMI (kg/m2)
Principal cut-off points
Underweight
Severe thinness < 16.00
Moderate thinness 16.00-16.99
Mild thinness 17.00-18.49
Normal range 18.50-24.99
Overweight
Pre-obese 25-29.99
Obese
Obese class I 30.00-34.99
Obese class II 35.00-39.99
Obese class III ≥40.00
The general believe is that the risk of hypertention is reverse
proportionally associated with cardiorespiratory fitness and regular
physical activity. Although, it has been shown that exercise training usually
lowers elevated BP, the individual differences are largely driven by
intrapersonal genetic factors. A number of epidemiological studies
confirmed that risk of developing hypertension is lower in subjects that are
physically active 83-87 and fit88-91. The intervention studies indicated a
14 | P a g e
decrease in SPB on the order of 2 to 11 mm Hg and in DPB on the order
of 1 to 8 mm Hg after moderate-intensity endurance training 92-98. A
variety of study also showed that obesity is directly proportional to an
increased risk of hypertension and CHD 99-100 and that body mass loss
results in lowering BP 100-101. These observations have their reflection in
the outcome of Nurses' Health Study indicating that weight gain after age
of 18 years is significantly associated with increased hypertension risk
whereas weight-stable women or those that lost weight are exposed to
significantly lower risk of hypertension 100
The HERITAGE family study indicated that changes in blood
pressure in response to exercise training is significantly influenced by
intrapersonal factors 102. On average the observed decrease in BP is
between 7 to 3.5 mm Hg. However, in some individuals a slight increase
of BP after exercise training may be observed 102-103.
The TROMSO study 11 exposed that obese women experience a
greater increase in SBP and DBP than normal BMI women. The
researchers have also observed that an increase in BMI induces
significantly higher hypertension in women than in men. It has also been
confirmed that there is a direct proportional association between increase
in BMI and BP however, no mechanism driving this association is
currently known as well the aethiology of this correlation in not fully
understood. Nevertheless, it was noticed that consonant increase in BMI
and blood pressure are correlated with increased serum glucose, insulin
and rennin levels 104-105.
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METHODS
Subjects
The National Health and Nutrition Examination Surveys (NHANES)
are national, cross-sectional, population-based studies of noninstitutionalized
civilian persons conducted by the National Center for
Health Statistics, USA. Sampling in the NHANES survey is designed in
such a way that it allows for representation of the U.S. population of all
ages and ethnic groups. Health examination procedures are performed in
mobile centers, and interviews are conducted in respondents’ homes. Data
collection includes in-person interviews, physical examinations, and
laboratory procedures. The NHANES survey is an ongoing project run in
separate stages since 1971. Since 1999, NHANES results have been
presented to the scientific community in two-year batches 106-109.
Table 7. Subjects Frequency Table by Database NHANES III 110and
NHANES 1999-2006 106-109.
ORIGIN Frequency Percent
Cumulative
Frequency
Cumulative
Percent
NHANES III 9401 46.95 9401 46.95
NHANES
1999-2006
10621 53.05 200223 100.00
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BMI Analysis
Using the WHO guidance 111, we divided the studied sample into two
body mass index (BMI) groups. The subjects with a BMI less than 18.5
were classified as an underweight BMI class and subjects with a BMI
greater than or equal to 18.5 and less than or equal to 24.99 were classified
as a normal BMI class. The subjects defined by a BMI greater than 24.99
were classified as an obese BMI class.
The combination of NHANES datasets for 1999-2000, 2001-2002,
2003-2005, and 2005-2006 yielded the primary sample size of women aged
1-85 equal to 22,908. There are 7079 subjects in the normal BMI class,
9552 in overweight BMI class and 6277 in underweight BMI class.
NHANES III
Measurements of standing height were performed on the stadiometer.
The subject had to stand in an erect position with hers back to the vertical
backboard. The weight should be evenly distributed on both feet. The
arms should hang freely by the sides of the trunk with palms facing the
thighs. The special persuasion was taken that hairs does not obscure the
scale. All the measurements were recorded to the nearest 0.1 cm
All the measurements of body weight were performed using the
electronic digital scale should. Before a measurement the scale was tarred.
The subject was asked to stand in the center of weighing platform. All the
measurements were recorded to the nearest 0.01 kg.
Body Mass Index was calculated using the following formula:
𝐵𝐵𝐵𝐵𝐵𝐵 =
𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 (𝑘𝑘𝑘𝑘)
(ℎ𝑒𝑒𝑒𝑒 𝑒𝑒ℎ𝑡𝑡 (𝑚𝑚))2
17 | P a g e
NHANES 1999-2000, 2001-2002, 2003-2004, and 2005-2006
Standing height was measured by means of a stadiometer. To measure
the stature properly the measured subject was asked to remove any hair
ornaments from the top of the head. The body weight should be evenly
distributed and both feet flat on the floor. The arms and shoulders should
be fully relaxed. All the measurements were recorder to the nearest 0.1 cm.
Measurements of body weight were performed by mean a Toledo
digital scale. All the measurements are taken in pounds and electronically
converted to the SI system. All adults are weight in the underwear. All the
measurements were recorded to the nearest 0.01 kg.
Body Mass Index was calculated using the following formula:
𝐵𝐵𝐵𝐵𝐵𝐵 =
𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 (𝑘𝑘𝑘𝑘)
(ℎ𝑒𝑒𝑒𝑒 𝑒𝑒ℎ𝑡𝑡 (𝑚𝑚))2
18 | P a g e
Table 8. BMI Class by Origin: NHANES III and NHANES 1999-
2006. The Normal Class Comprises BMI≤ 18.49, the Underweight
Class Comprises BMI≥ 18.50 and ≤ 24.99, the Overweight Class
Comprises BMI ≥ 25.
BMICLASS
Frequency
Percent
ORIGIN Total
NHANES
III
NHANES
1999-2006
NORMAL
3595
17.76
3686
17.91
7181
35.87
OVERWEIGHT
5483
27.38
5341
26.68
10824
54.06
UNDERWEIGHT
323
1.61
1694
8.46
2017
10.07
Total
9401
46.95
10621
53.05
20022
100.00
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Alcohol Consumption and Tobacco Smoking
NHANES III and NHANES 1999-2000, 2001-2002, 2003-2004,
and 2005-2006
The following exclusion rules were applied to both data sets: current
smoking status: NHANESIII data set - if a mean of cigarettes, pipes, and
cigars smoked in the past five days from the first and the second
examination was greater than 0, then the subject was classified as an active
smoker and excluded from further study. NHANES 1999-2002: if the
answer to the question “Do you now smoke cigarettes?” or “Do you now
smoke a pipe?” or “Do you now smoke cigars?” was “yes” or “some
days”, then the subject was treated as an active smoker and excluded from
further study.
Table 9. Frequency Table of Tobacco Smoking Status by Data Sets
NHANES III or NHANES 1999-2006. Smoking Analysis Include
Two Cases; (1) Smoking One or More Cigarettes, Pipes, Cigars per
day and (2) Smoking Within 30 Minutes Before Measurement of
Blood Pressure. 1- Smoking, 2- no Smoking.
SMOKE
Frequency
Percent
ORIGIN
Total
NHANES III
NHANES
1999-2006
1
101
0.50
1278
6.38
1379
6.98
2
9300
46.45
9343
46.66
18643
93.11
Total
9401
46.95
10621
53.05
20022
100.00
20 | P a g e
It has been shown that subjects drinking alcohol beverages containing
higher level of alcohol had borderline higher systemic hypertension (HTN)
than those drinking predominantly beer or wine 112. Additionally the
majority of the data indicate no important role of the type of an alcohol
beverage on HTN113. The recent studies 113-114 have also shown that BP
increase cannot be considered as immediate effect of alcohol use. Thus, at
current stage the athopysiological coupling between alcohol consumption
and BP remains unknown and the effects of alcohol in BP increase are
rather speculative 112. However, one has to take into account the fact that
intense alcohol consumption influences the daily style of life. The recent
study performed by Saarni et al 115 indicates that extensive use of alcohol
beverages is reverse proportional with health utility, quality of life (QoL)
and mental distress. However, the moderate consumption alcohol has
minimal if not none influence on every-day well being. Although this
information indicates that moderate alcohol drinking should not affect BP
we still decided to elucidate this group of subject from the main group of
“healthy” women and study this group separately.
Table 10. Frequency Table of Alcohol Consumption Status by Data
Sets NHANES III or NHANES 1999-2006. The Consumption
Analysis Includes Two Cases; (1) Drinking One or More Alcohol
Beverages Per Day and (2) Drinking Within 30 Minutes Before
Measurement of Blood Pressure. 1- Drinking, 2 – no Drinking.
DRINK
Frequency
Percent
ORIGIN
Total
NHANES III
NHANES
1999-2006
1
97
0.48
3217
16.07
3314
16.55
2
9304
46.4751
7404
36.98
16708
83.45
Total
9401
46.95
10621
5305
20022
100.00
21 | P a g e
Pregnancy, Breastfeeding, and Contraception.
NHANES III and NHANES 1999-2000, 2001-2002, 2003-2004,
and 2005-2006.
It is know that hypertension in pregnancy comprises at least four
different factors 116-117: (1) chronic hypertension which may predate
pregnancy, (2) pregnancy induced hypertension developing after 20 weeks
of gestation, (3) gestational hypertension and (4) pre­eclampsia, pregnancy
induced hypertension in association with proteinuria or oedema.
Taking into account these facts we decided to create a spate group of
pregnant women and exclude them from the “healthy” women. Thus, 280
subjects from the NHANES III and 332 subjects from the NHANES
1999-2006 were assigned to a separate group because of pregnancy, Table
11.
Although no one ever reported that breastfeeding leads to elevation or
decrease of BP we decided to elucidate a separate group comprising
breastfeeding women. The decision was made on the assumption that it is
a specific stage in biological life of women and as such should be treated
separately. Thus, hundred one subjects from NHANES III and nineteen
subjects from NHANES 1999-2002 were excluded because of current
breastfeeding, Table 12.
Although present there is no agreement as to the contraception
induced hypertension. However, we still decided to exclude this group
from the main study group. This approach resulted in exclusion of nine
hundred thirty two subjects from the NHANES III. In this case, the
exclusion criterion was a combination of three questions: “How many
months ago stop taking BC pills?” (code: MAPF32S), “Do you now have
NORPLANT implanted under your skin?” (code: MAPF34B), and “Days
since stopped birth control pills” (code: HXRH16S). If the answer to the
first question indicated a time period of less than a month, or the answer
to the second question indicated that the subject was currently using a
NORPLANT implant, or the answer to the third question concurred a
time period less than one month from stopping the use of birth control
pills, then the subject was treated as currently using contraceptives and
excluded from further study. In NHANES 1999-2002, contraceptivebased
exclusion was based on the following rule: If the answer to the
question “Taking birth control pills now?” (code: RHD440 for 1999-2000
and 2001-2002, and RHD442 for 2003-2004 and 2005-2006) or “Now
using Depo-Provera or injectables?” (code: RHQ520) was “yes” , then the
22 | P a g e
subject was treated as using contraception and excluded from further
study, Table 13.
Table 11. Pregnancy Status by Origin: NHANES III and NHANES
1999-2006. 1- Pregnant 2- no Pregnant.
PREGNANT
Frequency
Percent
ORIGIN
Total
NHANES III
NHANES
1999-2006
1
280
1.40
332
1.66
612
3.06
2
9121
45.55
10289
51.39
19410
96.94
Total
9401
46.95
10621
53.05
20022
100.00
Table 12. Breastfeeding Status by Origin: NHANES III and
NHANES 1999-2006. 1 - Breastfeeding 2- no Breastfeeding.
BREAST
Frequency
Percent
ORIGIN
Total
NHANES III
NHANES
1999-2006
1
101
0.50
19
0.09
120
0.60
2
9300
46.45
10602
52.95
19902
99.40
Total
9401
46.95
10621
53.05
20022
100.00
23 | P a g e
Table 13. Contraception Status by Origin: NHANES III and
NHANES 1999-2006. 1 – Use Contraception 2- Do Not Use
Contraception.
CONTRACEPTION
USE
Frequency
Percent
ORIGIN
Total
NHANES III
NHANES
1999-2006
1
932
4.65
515
2.57
1447
7.23
2
8469
42.30
10106
50.47
18575
92.77
Total
9401
46.952
10621
53.05
20022
100.00
24 | P a g e
Blood Pressure Measurements
NHANES III
Each blood pressure measurement session comprises of the three sets
of blood pressure measurements taken in the examination center. For the
age group 5 to 19 years three Korotkoff sounds were recorded: K1
(systolic); K4, muffling of pulse sounds (diastolic); and K5, disappearance
of pulse sounds (diastolic). For adults older than 20 years of age, only K1
(systolic) and K5 (diastolic) measurements were collected. All
measurements were recorded to the nearest even number. All the
measurements were performed by means of a mercury
sphygmomanometer (W. A. Baum Co., Inc, Copiague, NY) according to
the standardized blood pressure measurement protocols recommended by
the American Heart Association 118. The contingency table of hypertension
classification in shown below, Table 14.
NHANES 1999-2000, 2001-2002, 2003-2004, and 2005-2006
Blood pressure, SPB and DBP were measured for subjects eight years
and older. In majority of the cases three measurements of systolic and
diastolic blood pressure were taken. All the measurements were taken in
the mobile examination center or at examinee’s home using a mercury
sphygmomanometer. Final blood pressure was calculated an arithmetical
average of successful measurements. If only one blood pressure reading
was obtained that reading is the average. However, it there is more than
one blood pressure measurement that first measurement is always
excluded for the average. In case of two measurements the second reading
is an average. Blood measurement protocol follows the recommendations
of American Heart Association Human Blood Pressure Determination by
sphygmomanometers 119. The contingency table of hypertension
classification in shown below, Table 14.
25 | P a g e
Table 14. Hypertension Classification Accordingly to JNC 7 of
Woman Age 12 and Older.
Hypertension
classification
Frequency
Percent
ORIGIN
Total
NHANES III
NHANES
1999-2006
Normal
4868
24.31
7176
35.84
12044
60.15
Prehypertension
4526
22.61
3437
17.17
7963
39.77
Hypertension Stage 1
7
0.03
8
0.04
15
0.07
Total
9401
46.95
10621
53.05
20022
100.00
26 | P a g e
Triglyceride Measurements
NHANES III
The subject’s fasting status was not taken into consideration when
measuring serum triglyceride level (TG). The enzymatic procedure based
on the set of consecutive reactions was used for serum or plasma
triglycerides level. In the first reaction lipase converts triglycerides to
glycerol and fatty acids in the second glycerokinase converts glycerol and
ATP into glycerol -3-phosphate and ADP. This reaction is followed by
enzymatic oxidation of glycerol by means of glycerol oxidase in the
presence of H2O2 and the concentration of the product of this reaction is
assessed by means of absorbance measurement at 500 nm. The resulting
absorbance value is directly proportional to TG level. All the analyses were
performed using Hitachi 704 Analyzer (Boehringer Mannheim
Diagnostics, Indianapolis, IN). The contingency table of triglyceride
classification is presented below, Table 15.
NHANES 1999-2000, 2001-2002, 2003-2004, and 2005-2006
The serum concentration of triglycerides was assessed enzymatically
by means of four coupled reactions. The first comprised lipase that
converts triglycerides into glycerol and fatty acids. The second
glycerolkinase converts glycerol to glycerol-2-phosohate and the third
glycerophosphate oxidase converts glycerol-3-phosphate into
dihydroxyacetone phosphate. In the fourth, the final reaction, the enzyme
peroxidase produce 4-(p-benzoquinone-monoimino)-phenazone which
concentration is directly proportional to the triglyceride concentration and
can be spectrophotometrically measured at λ=500 nm. All the analyses
were performed using Hitachi 704 Analyzer (Boehringer Mannheim
Diagnostics, Indianapolis, IN). The contingency table of triglyceride
classification is presented below, Table 15.
27 | P a g e
Table 15. Triglyceride Classification by Origin: NHANES III and
NHANES 1999-2006. Normal < 150 mg/dL (1.68 mmol/L)
≤Borderline High < 200mg/dL (2.24 mmol/L) ≤ High < 500
mg/dL (5.6 mmol/L) ≤ High.
Triglyceride
Classification
ORIGIN
Total
NHANES III
NHANES
1999-2006
borderline high
1191
5.95
438
2.19
1629
8.14
high
1251
6.25
408
2.04
1659
8.29
normal
6856
34.24
9756
48.73
16612
82.97
very high
103
0.51
19
0.09
122
0.61
Total
9401
46.95
10621
53.05
20022
100.00
28 | P a g e
LDL Cholesterol Measurements
NHANES III
It is known that circulating cholesterol can found in three major
fractions: very low density lipoproteins (VLDLs), low density lipoprotein
(LDLs), and high density lipoprotein (HDLs) 120. They are bound by the
following formula: Total Cholesterol = VLDL + LDL + HDL. The serum
level of LDL cholesterol was calculated using the values of total
cholesterol, triglycerides and HDL-cholesterol according to the formula:
LDL = total cholelsterol – HDL- (TG/5). The last term in the equation is an
estimate of VLDL. All the values in the formula are expressed in mg/dL.
The blood sample volume for the measurement of serum LDL level was
0.2 ml. All the analyses were performed using Hitachi 704 Analyzer
(Boehringer Mannheim Diagnostics, Indianapolis, IN). Frequency of LDL
cholesterol classification is shown in Table 16.
NHANES 1999-2000, 2001-2002, 2003-2004, and 2005-2006
Analogous to the NHANES III approach LDL cholesterol
concentration was assessed by means of the following formula: LDL =
total cholelsterol – HDL- (TG/5). All the values in the formula are expressed
in mg/dL. The blood sample volume for the measurement of serum LDL
level was 0.2 ml. All the analyses were performed using Hitachi 704
Analyzer (Boehringer Mannheim Diagnostics, Indianapolis, IN).
Frequency of LDL cholesterol classification is shown in Table 16.
29 | P a g e
Table 16. LDL Cholesterol Classification by Origin: NHANES III
and NHANES 1999-2006. Optimal < 100 mg/dL (2.6 mmol/L)
≤Near Optimall < 130mg/dL (3.741 mmol/L) ≤ Borderline High <
160 mg/dL (4.16 mmol/L)≤ High < 190 mg/dL (4.94 mmol/L) ≤
High.
LDL Cholesterol
Class
ORIGIN
Total
NHANES III
NHANES
1999-2006
optimal
6636
33.14
7692
38.42
14328
71.56
near optimal
1224
6.11
1250
6.24
2474
13.36
borderline high
913
4.56
904
4.52
1817
9.08
high
410
2.05
472
2.36
882
4.41
very high
218
1.09
303
1.51
674
2.60
Total
9401
46.95
10621
53.05
20022
100.00
30 | P a g e
HDL Cholesterol Measurements
NHANES III
The level of HDL-cholesterol was measured on the bases of the
precipitation of the other lipoproteins with a polyanion/divalent cation
mixture. The required sample volume was 0.2 ml. All the analyses were
performed using Hitachi 704 Analyzer. The sample preparation for HDL
cholesterol measurements comprised the following steps: (1) addition of
100 μL of heparin sulfate-MnCl mixture to the serum for each sample; (2)
removal of precipitate by centrifuging at 1500 x g for 30 min; (3) mixing of
supernatant and sodium bicarbonate; (4) measurement of HDL cholesterol
in clear supernatant. All the analyses were performed using Hitachi 704
Analyzer (Boehringer Mannheim Diagnostics, Indianapolis, IN). HDL
cholesterol classification is summarized in Table 17.
NHANES 1999-2000, 2001-2002, 2003-2004, and 2005-2006
In NHANES 1999-2006, two methods were employed for HDLcholesterol
measurement. In the first method a heparin-manganese (Mn)
precipitation method combined with a direct immunoassay technique were
used. However, for the subjects no heparin-manganese HDL-cholesterol
the direct HDL-cholesterol measurement method was used. In the
heparin-Mn precipitation method lipoproteins bound to apolipoprotein-B
are removed with a mixture of heparin sulfate and MnCl2 and HDLcholesterol
is measured in clear supernatant. In the direct immunoassay
method HDL concentration is used in the serum. The method employs
the set of reactions combining apo lipoproteins-B, α-cyclodextrin, Mg
ionsm dextran SO4 in the first reaction; HDL-cholesteryl esters and PEGcholesteryl
esterase in the second reaction and 5-aminophenazone, Nethyl-N-(3-methylphenyl)-N′-succinyl
ethylene diamine and H
+
peroxidase
which converts into quinoneimine dye. The absorbance of quinoneimine
dye is measured at 600 nm and its concentration is directly proportional to
the concentration of HDL-cholesterol. All the analyses were performed
using Hitachi 704 Analyzer (Boehringer Mannheim Diagnostics,
Indianapolis, IN). HDL cholesterol classification is summarized in Table
17.
31 | P a g e
Since it has been noticed that measurements of HDL cholesterol in
NHANES 1999-2000 to 2005-2006 are approximately 6 percent lower
than the measurement obtained in NHANES III the NHANES 1999-
2006 HDL-cholesterol values for both the precipitated and direct methods
were adjusted using the following formula:
𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 𝐻𝐻𝐻𝐻𝐻𝐻
=
(𝑆𝑆𝑆𝑆𝑆𝑆 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 𝐻𝐻𝐻𝐻𝐻𝐻 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐. ) ∗ (𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 𝐻𝐻𝐻𝐻𝐻𝐻 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐. )
(𝑄𝑄𝑄𝑄𝑄𝑄𝑄𝑄𝑄𝑄𝑄𝑄𝑄𝑄 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 𝐻𝐻𝐻𝐻𝐻𝐻 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐. 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 𝑤𝑤𝑤𝑤𝑤𝑤ℎ 𝑡𝑡ℎ𝑒𝑒 𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝 )
Table 17. HDL Cholesterol Class by Origin: NHANES III and
NHANES 1999-2006. Low < 40 mg/dL (1.04 mmol/L)≤Normal <
60 mg/dL (1.56 mmol/L) ≤ High.
HDL Cholesterol Class
ORIGIN
Total
NHANES III
NHANES
1999-2006
normal
4717
23.56
3283
16.40
8000
39.96
low
2005
10.01
2157
10.77
4162
20.79
high
2679
13.38
5181
25.88
7860
39.26
Total
9401
46.95
10621
53.05
20022
100.00
32 | P a g e
Total Cholesterol Measurements
NHANES III
Cholesterol is measured enzymatically121-122 in serum or plasma in a
series of coupled reactions that hydrolyze cholesterol esters and oxidize
the 3-OH group of cholesterol. The reaction byproduct proportional to
cholesterol concentration is quantitatively measured through absorbance at
500 nm. The required sample for the total cholesterol measurement is 0.2
mL. All the analyses were performed using Hitachi 704 Analyzer
(Boehringer Mannheim Diagnostics, Indianapolis, IN). Frequency of total
cholesterol classes is shown in Table 18.
NHANES 1999-2000, 2001-2002, 2003-2004, and 2005-2006
Serum or plasma total cholesterol was measured using a set of
enzymatic reactions using cholesteryl ester hydrolase, cholesterol oxidase,
and peroxidase. These three enzymes catalize three step reaction from
cholesteryl ester to 4-(p-benzoquinonemonoimino)-phenazone which
concentration can be assessed by colorimetry. Absorbance of 4-(pbenzoquinonemonoimino)-phenazone
is measured at λ = 500 nm and its
value is proportional to cholesterol concentration. All the analyses were
performed using Hitachi 704 Analyzer (Boehringer Mannheim
Diagnostics, Indianapolis, IN). Frequency of total cholesterol classes is
shown in Table 18.
33 | P a g e
Table 18. Total Cholesterol Class by Origin: NHANES III and
NHANES 1999-2006. Desirable < 200 mg/dL (5.2 mmol/L)
≤Borderline High < 240 mg/dL (6.24 mmol/L) ≤ High
Total Cholesterol
Class
Frequency
Percent
ORIGIN
Total
NHANES
III
NHANES
1999-2006
Desirable
4941
24.68
7364
36.78
12305
61.46
Borderline High
2636
13.17
2076
10.37
4712
23.53
High
1824
9.11
1181
5.90
3005
15.01
Total
9401
46.95
10621
53.05
20022
100.00
34 | P a g e
Serum Uric Acid Measurements
NHANES III
Uric Acid measurement employed the specificity of the oxidation
of uric acid by uricase to alantoin and H2O2, which in turn reacts with
2,4,6-tribromo-3- hydroxybenzoic acid and 4-aminophenazone forming
quinone-imine dye that is proportional to the uric acid concentration. The
spectrophotometric measurement of uric acid is linear up to 20.0 mg/dL.
The sample with the concentration of uric acid higher than 20.0 mg/dL
were twofold diluted and the results were multiplied by 2 to account for
dilution. Frequency of serum uric acid tierces is presented in Table 19.
NHANES 1999-2000, 2001-2002, 2003-2004, and 2005-2006
All the uric acid measurements were commenced using the uric
acid oxidization product which is allantoin and hydrogen peroxide. In the
presence of peroxidase hydrogen peroxide reacts with 2,4,6-tribromo-3- 2
2 2 2 hydroxybenzoic acid (TBHB) and 4-aminophenazone and form
quinone-imine dye and hydrogen bromide (HBr). The intensity of the red
color proportional to the uric acid concentration can be measured by
means of colorimetry. Analogous to NHANES III approach the sample
with the concentration of uric acid greater than 20.0 mg/dL were twofold
diluted and the resultant concentration was multiplied by two. Frequency
of serum uric acid tierces is presented in Table 19.
35 | P a g e
Table 19. Tierces of serum uric acid concentration by Origin:
NHANES III and NHANES 1999-2006. 1- the first tierce, 2- the
second tierce, and 3- the third tierce. Division accordingly to
findings of Wheeler at al.54
Tierces of Uric Acid
Level
ORIGIN
Total
NHANES III
NHANES
1999-2006
1
4992
24.93
5326
26.60
10318
51.53
2
3740
18.68
3442
17.19
7182
35.87
3
669
3.34
1853
9.25
2522
12.60
Total
9401
46.95
10621
53.05
20022
100.00
36 | P a g e
Serum Creatinine Measurements
NHANES III
Serum creatinine measurement is based on Jaffe reaction and modified
by Popper, Seeling, and Wuest. The measurement utilized the property
that in an alkaline medium, creatinine forms a yellow-orange-colored
complex with picric acid. The light absorbance is proportional to the
concentration of creatinine and may be measured photometrically.
NHANES 1999-2000, 2001-2002, 2003-2004, and 2005-2006
Analogous to NHANES III approach the creatinine concentration
was assessed by means of the modified Jaffe reaction. A yellow-orangecolored
complex, a product of creatinine and piric acid in an alkaline
solution was measured phtometrically. The light absorbance is
proportional to creatinine concentration.
Analysis of glomerular filtration rate GFR and Kidney
Disease Stage
Creatinine clearance was calculated accordingly to the KD-EPI
equation 123-124 where GFR is glomerular filtration rate (mL/min per 1.73
m2) and Src is serum creatinine concentration (mg/dL).
(1) black female and serum creatinine concentration is less or equal to
62 µmol/L (≤ 0.7mg/dL)
𝐺𝐺𝐺𝐺𝐺𝐺 = 166 ∗ (𝑆𝑆𝑆𝑆𝑆𝑆/0.7)−0.329
∗ (0.993)𝐴𝐴𝐴𝐴𝐴𝐴
(2) black female and serum creatinine concentration is greater than 62
µmol/L (> 0.7mg/dL)
𝐺𝐺𝐺𝐺𝐺𝐺 = 166 ∗ (𝑆𝑆𝑆𝑆𝑆𝑆/0.7)−1.209
∗ (0.993)𝐴𝐴𝐴𝐴𝐴𝐴
(3) white female and serum creatinine concentration is less or equal
to 62 µmol/L (≤ 0.7mg/dL)
37 | P a g e
𝐺𝐺𝐺𝐺𝐺𝐺 = 144 ∗ (𝑆𝑆𝑆𝑆𝑆𝑆/0.7)−0.329
∗ (0.993)𝐴𝐴𝐴𝐴𝐴𝐴
(2) black female and serum creatinine concentration is greater than 62
µmol/L (> 0.7mg/dL)
𝐺𝐺𝐺𝐺𝐺𝐺 = 144 ∗ (𝑆𝑆𝑆𝑆𝑆𝑆/0.7)−1.209
∗ (0.993)𝐴𝐴𝐴𝐴𝐴𝐴
The frequency of Kidney Disease Stage as a function of glomerular
filtration rate is shown in Table 20.
Table 20 Kidney Disease Stage by Origin: NHANES III and
NHANES 1999-2006. Stage 1 – GFR ≥ 90; Stage 2- GFR < 90 and
GFR ≥ 60; Stage 3 – GFR < 60 and GFR≥ 30; Stage 4 – GFR < 30
and GFR≥ 15 and Stage 5 – GFR < 15. Glomerular Flow Rate
(mL/min per 1.73 m2) was calculated accordingly to KD-EPI
equation124.
Kidney Disease Stage
ORIGIN
Total
NHANES III
NHANES
1999-2006
1
1238
6.18
5803
28.98
7041
35.17
2
4729
23.62
1965
9.81
6694
33.43
3
1259
6.29
456
2.28
1715
8.57
4
142
0.71
74
0.37
216
1.08
5
2033
10.15
2323
11.60
4356
21.76
Total 9401 10621 20022
38 | P a g e
Kidney Disease Stage
ORIGIN
Total
NHANES III
NHANES
1999-2006
46.95 53.05 100.00
Statistical Analyses
Test for Association
The scale of measurement defined the statistical technique used for
the data analysis. Categorical response variables can be divided into (1)
dichotomous, (2) ordinal, (3) nominal, (4) discrete counts, and (5) grouped
survival times. Dichotomous responses always have two possible outcomes
“yes” or “no”. Categorical response data that are possible to order and
represent more than two outcomes have an ordinal scale of measurements.
However, in there is no inherent ordering to the categories, the response
data are measured on the nominal measurement scale. In specific cases
categorical response variables fall into discrete counts. Thus instead of yes
and no the discrete numbers 1 and 2 are used. The response variable may
also fall into the category of survival times. With this type of data one may
track the subject with certain outcome over time.
In a test for association the objective is to evaluate the association
between the independent variable and the response variable while
adjusting for the effect of the stratification variables.
The test per se involves calculating the differences between the
observed and expected frequencies. Large differences between these two
frequencies indicate the presence of association the small in turn indicate
the lack of association. The test statistics is calculated using the following
formula:
� �
�𝑂𝑂𝑖𝑖𝑖𝑖 − 𝐸𝐸𝑖𝑖𝑖𝑖 �
2
𝐸𝐸𝑖𝑖𝑖𝑖
𝑐𝑐
𝑗𝑗=1
𝑟𝑟
𝑖𝑖=1
39 | P a g e
, where Oij is the observed frequency and Eij is the expected frequency in
the cell.; i is a row number and j is a column number. The calculated test
statistic approximately follows a χ2 distribution with (r - 1) × (c - 1)
degrees of freedom. Thus, the χ2 test indicates whether there is an
association between two categorical variables. However, the statistics itself
does not reflect the strength of association. This can be done be residual
standardization using the following rule: the larger the absolute value of
the residual, the more significant the association between the two
variables.
40 | P a g e
RESULTS AND DISCUSSION
41 | P a g e
Association Between BMI and Tobacco Smoking Status.
In our study the association between body mass index (BMI) and the
tobacco smoking status was measured by means of a test for general
association. In the sufficiently large sample as in this case, with the
expected cell counts greater than 5, Pearson “QP” has approximately the
χ2
distribution with (s-1)(r-1) degrees of freedom whereas randomization
statistic “Mantel-Haenszel Chi-Squares statistics” is described by the
following equation: 𝑄𝑄 =
𝑛𝑛−1
𝑛𝑛
𝑄𝑄𝑝𝑝.
The analysis of contingency table of body mass index by tobacco
smoking status, Output 1, reveals that the majority of the studied subjects
in all BMI classes do not smoke tobacco. The examination of Pearson chisquare
statistics, it is the analysis of an association between BMI class and
smoking status, Output 2, reveals the statistics value of Qp = 46.8 with
two degrees of freedom, df = 2, that results in p < 0.0001. The evaluation
of Mantel-Haenszel (MH) statistics, Output 3, reveals the Q value of
“General Association“ of 46.8066 with two degrees of freedom and the p
value significantly less than 0.01. Both results indicate an association
between the tobacco smoking status and BMI classes. Since contingency
table is on interval scale we may employ the Pearson correlation
coefficient for measurement of the strength of an association. The analysis
of measures of the strength of association between BMI classes and the
smoking status, Output 4, clearly indicates a very week positive association
between BMI classes, underweight, normal, and overweight with tobacco
smoking status. In other words an increase in body mass index is coupled
with a smoking habit. Our results are in agreement with some of the
previous reports. However, they also contradict a few. It is because current
research on associations between BMI and tobacco smoking yields
contradicting results. Some of the studies indicate an inverse association
125-126 while others exposed positive association 127 or no association at all
128. There are also study presenting a mixed association between BMI and
smoking such as, for example, Tromso study 129 that indicate the Ushaped
relationship between smoking and BMI. The study on relations
between BMI vs. tobacco smoking status indicates that former smoker are
defined by higher BMI that non smokers or current smokers 130-131. Results
of one of the largest project that undertook the analysis of correlations
between tobacco smoking and body mass that is MONICA Project 132,
indicate that independently of a gender smokers are described by less body
mass that individuals who had never smoked.
42 | P a g e
Association Between BMI and Alcohol Consumption Status.
The analysis of the contingency table of BMI class by an alcohol
consumption status, Output 5Output 5, reveals a clear increase in alcohol
consumption between the underweight BMI and normal and overweight
BMI classes. There are also clear intra-class differences in alcohol
consumption statuses. Thus in the overweight BMI the ratio of nodrinking
subjects to alcohol drinking subjects is 4:1 whereas in the
underweight BMI class the ratio is equal about 15:1. The test for general
association between BMI class and alcohol consumption status, under the
null hypothesis of no association, yields both p values, it is p value for χ2
statistics, Output 6, and p value for Cochran-Mantel-Haenszel statistics
Output 7, significantly less than 0.01 indicating the presence of an
association between the BMI classes and alcohol consumption status. The
analysis of the strength of the correlation, Output 8, yields the Pearson
correlation value r equal to -0.0991 which is indicative of extremely week
association between body mass index and alcohol drinking habits. In other
word, more subjects in the overweight BMI then in the underweight BMI
class consume alcohol.
A multitude of studies on drinking and BMI 130, 133-141 indicated that
moderate drinkers had the BMI values lower than frequent alcohol
drinkers. However there are also reports indicating the opposite i.e. an
increase in BMI associated with alcohol consumption 142-143. Thus the
latter confirm and are confirmed by our results.
43 | P a g e
Association Between BMI and Pregnancy Status.
In this study we perform the primary analysis of the association
between body mass index and the pregnancy status using the contingency
table of BMI classes vs. pregnancy status; pregnant, no-pregnant. Since the
main objective of this study is to analyze changes in BP versus different
health quality related factors we decided to check if pregnancy is a
covariate of BP. The contingency table of BMI versus the pregnancy
status for the NHANES III and NHANES 1999-2000, 2001-2002, 2003-
2004, and 2005-2006 data is shown in Output 9. The test for general
association under the null hypothesis of no association yields both p
values, p value for χ2 statistics, Output 10, and p value for CochranMantel-Haenszel
statistics, Output 11, significantly less than 0.01. This
indicates an association between defined BMI classes and pregnancy
status. The analysis of the strength of the association indicates extremely
week negative association between BMI and pregnancy status, Output 12.
This observation confirms an increase of body weight during pregnancy.
However, across all ages and ethnic groups this change is rather weak.
The analysis of current literature on this subject indicates that changes
of body mass during pregnancy have a paramount influence on both
mother and infant health risk 144-148. For example, results of subsequent
twenty one years of study 149 indicated that women experiencing
hypertensive disorders of pregnancy have elevated weight gain when
compared to these not experiencing such disorder. It has also been shown
that postpartum weight gain is driven mainly by en excessive gain during
pregnancy period 150-153. The adverse implications of an excessive
gestational weight elevation on multiple health related issues, among them
hypertension, can however be both prevented and monitored through the
weight development during pregnancy 153-157.
44 | P a g e
Association Between BMI and Chemotherapy Status.
Accordingly to Dorland’s Medical Dictionary “chemotherapy is the
treatment of illness by chemical means (medication); the term was first applied to the
treatment of infectious diseases, but it now is used primarily to refer to treatment of
mental illness and cancer. adj., chemotherapeutic”. Taking into account the
invasive nature of chemotherapy we may expect chemotherapy induced
changes in BMI. The recent studies on the subject indicated significant
increase in body mass index in response to chemotherapy treatment of
testicular cancer 158. Similar results were reported for adjuvant
chemotherapy in women with breast cancer 159. It has also been shown
that cranial irradiation may also induce increase in body mass index in
survivors of childhood acute lymphoblastic leukemia 160. All these
information indicate that chemotherapy, if administered, should be
considered and important factor when assessing BMI induced changes in
hypertension. The analysis of the prevalence of chemotherapy patients in
the NHANES III and NHANES 1999-2006 data sets results indicate
significantly greater number of subject undergoing chemotherapy among
the overweight subjects than this observed for normal and underweight
BMI classes, Output 13.
The test for general association under the null hypothesis of no
association yields both p values, it is p value for χ2 statistics, Output 14,
and p value for Cochran-Mantel-Haenszel statistics, Output 15,
significantly less than 0.01 indicating the presence of an association
between defined BMI classes and administration of chemotherapy.
However, the analysis of the strength of the association, Output 16,
indicates extremely week negative association between BMI and
chemotherapy. In other words there is an increase in BMI in
chemotherapy administered patients.
45 | P a g e
Association Between BMI and Breastfeeding Status.
The literature on the subject of correlations between pregnancy and
body mass gain had shown that during pregnancy women gain total body
weight and accrue body fat. To prevent undesirable weight gain and BMI
gain lactation, due to its high energy cost, is often suggested as an efficient
means of postpartum weight loss 161-165. In the recent study on correlations
of breastfeeding and maternal body composition 166 the researchers have
shown that breastfeeding not only prevents postpartum maternal obesity
gain but also accelerate return to pre-pregnancy state. This may obviously
correlate with improvement in health related quality of life. Taking this
into account we analyzed frequency table of self reported breastfeeding
status and BMI classes as well as performed the test for general association
for these two parameters.
The test for general association yields p value for χ2 statistics, Output
18, and p value for Cochran-Mantel-Haenszel statistics, Output 19,
significantly less than 0.01 indicating for an association between defined
BMI classes and breastfeeding. The analysis of the strength of the
association, Output 20, indicates extremely week negative association
between both parameters. In other words the analysis of the strength of
the association contradicts the trend observed by others. However, taking
into account the strength of the association from statistical point of view
our results are rather inconclusive.
46 | P a g e
Association Between BMI and Contraception Use.
There is a general believe that hormonal contraceptive induce
elevation in body weight 167. The random survey among 1753 randomly
selected women aged 15-45 performed in Great Britain at the beginning of
1990s indicated that contraceptive use results in weight gain 168. The early
observation derived from the Great Britain study was later confirmed by
the two independent reports 169-170. Similar study performed in the United
States indicated that a majority of contraceptive pills users were much
concerned about their weight gain 171. As reported letter 170 not only
weight gain is associated with contraception use, but also nausea, headache
and menstrual abnormalities. These factors are also among the causes of
discontinuation of contraception 170, 172. All these observations are
supported by the newer studies on the subject 173-174. However, they also
indicated that although there is an increase in body mass after
administering contraception, the observed increase is no significant. To
analyze the association between BMI and contraception use we arranged
the NHANE III and NHANES 1999-2006 data into contingency table,
Output 21, and performed a test for general association. The analysis of p
values of χ2 association statistics, Output 22, and Cochran-MantelHaenszel
statistics, output 23, yields the presence of an association
between BMI and contraception use. The analysis of the strength of the
association reveals very weak, positive association between these two
parameters Output 24. This observation indicates that indeed the
administration of contraception may lead to an increase in body mass.
47 | P a g e
Association Between BMI and Total Cholesterol Levels
A number of studies demonstrated a directly proportional relation
between blood cholesterol and age 175-179 and body mass index 180-182.
However, there are also studies indicating the absence of direct
correlations between body mass index and total cholesterol level 183-186. For
many years the majority of the studies on rather small size groups of
subjects which might lead to significant bias in the obtained results. This
was overcome by the WHO Multinational Monitoring of Trends and
Determinants in Cardiovascular Disease (MONICA) - the study initiated
in the early 1980s187. Although the main objective of this study was to
assess risk factors in CHD one of the reports based on MONICA results
undertook the task of analysis of correlations between BMI and blood
total cholesterol 188. The results of this study indicate that prevalence of
hypercholesterolaemia (PHC) defined as cholesterol level > 6.5 mmol/l
increases with age. Statistically significant a positive association between
hypercholesterolaemia and BMI was also observed. However, the strength
of the correlation between PHC and BMI decreases along the progressing
age resulting in the absence of statistically significant association in females
older than 50 years of age. To verify the previously made observation
against the NHANES III and NHANES 1999-2006 we analyzed
contingency table of BMI classes by total cholesterol levels, Output 25 and
probability values of Pearson chi-square, Output 26, and Cochran-MantelHaenszel
Statistics, Output 27, for the test for association. We have to
point there that in our study we do not stratify for age and in this regard
our study differs from those of Gostynski et al. 188. The visual scrutiny of
contingency table reveals that underweight BMI class is defined by
significantly less subjects with high serum total cholesterol levels than
normal and overweight BMI classes. The tests for association yield the
presence of an association between BMI class and total cholesterol class.
The analysis of the Pearson correlation, Output 28, between BMI and total
cholesterol classes yield week positive association indicating the indeed
overweight subjects are defined by undesirable high levels of total
cholesterol.
48 | P a g e
Association Between BMI and HDL Cholesterol Levels.
It has been shown that BMI is reverse-proportionally associated with
levels of HDL cholesterol 189-190. However, the effect of the gender on age
dependent HDL levels change is at current stage not clear. For example
the study on nondiabetic american indians 191 revealed clinically significant
changes in HDL-C and BMI ratio in men but not in women. Anderson et
al. 192 also indicates that there are no statistically significant differences in
lipoprotein levels between men and women. The results reported by Choi
et al. 193 indicates the opposite correlation between HDL-C and total body
fat (TFB) between men and women. Thus, in men there is a reverse
proportional relation between HDL-C and TFB and in women a
proportional relation between HDL-C and TFB. To assess the presence of
an association between BMI and HDL-C levels as well as to analyze the
strength and direction of this association we grouped the NHANES III
and NHANES 1999-2006 data into contingency table, Output 29, and
performed chi-square, Output 30, and Cochran-Mantel-Haenszel , Output
31, tests for association, and analyzed the strength of the association by
means of Pearson correlation, Output 32. The analysis of the results yields
the very week positive association between BMI classes and HDL-C levels.
49 | P a g e
Association Between BMI and LDL Cholesterol Levels.
Although the subject of correlations between BMI and LDL-C
should, because of its direct connection with HQoL, attract a lot of
attention only a few reports undertook the topic. Though recent studies
on relationships of body mass index with serum lipids in elementary
school students reveals significant correlation between BMI an LDL-C 194.
However, the study analyzing body mass dependent lipid profiles in
women from Kaduna, Northern Nigeria 195 reveal the lack of statistically
significant differences between different body mass index groups. This
result is at least partially contradicted by the results of the recent research
on correlation of dyslipidemia with BMI in Iranian adults 196 indicating
week correlation between LDL-C and BMI index. To assess the presence
of correlations between LDL-C and BMI as well as to analyze the strength
of this correlation, under the null hypothesis that such is present, we
grouped the data into contingency table, Output 33 and performed χ2 and
Cochran-Mantel-Haenszel test for association. The results of these tests
are shown in Outputs 34 and 35. The analysis of the results of association
tests reveals the presence of the association between body mass index and
the level of LDL cholesterol. The analysis of the strength of this
association, measured by means or Pearson coefficient, Output 36, yields
the weak value of 0.15. In other words an increase in body mass is
accompanied by an increase in LDL-C levels.
50 | P a g e
Association Between BMI and Triglyceride Levels.
A number of reports indicated the association of lipid profiles with a
lifestyle 197-198, age 199, obesity 191 and BMI 200. The progressing increase in
obesity 201-203 and the metabolic syndrome 204-205 indicate that industrial
development may lead to increase of a rate of cardiovascular disease in
highly developed nations. However, the recent study indicates that the
situation is not that dramatic. The Framingham study exposed a
progressing decrease in triglyceride level in US population between 1998-
2001 and 1990-1994 206. Independently of this observation dyslipidemia
accompanies obesity and as such is among the main risk factors of CVD.
Similar pattern of increase in triglycerides level as a function of obesity was
observed for men 44, women 207, and children 208.
To confirm the previously reported observations it is to verify that an
increase in body mass index is directly proportional to an increase in
triglyceride level, which has its reflection if increased risk of CVD, we
performed the analysis of the association between BMI classes and ATP
III defined triglyceride categories. The analysis of the contingency table,
Output 37, of BMI class by triglyceride category reveals that obesity if
accompanied by an increase in subjects defined by debilitated triglyceride
levels. The analysis of probability values of Person chi-square statistics and
Cochran-Mantel-Haenszel statistics reveals the presence of an association
between BMI class and triglyceride level, Outputs 38 and 39. The analysis
of the strength of association performed by means Pearson correlation,
Output 40, yields directly proportional association weak association. Thus,
an increase in BMI index class is associated by an increase in the
triglyceride class.
51 | P a g e
Association Between BMI and Glomerular Flow Rate (GFR).
The recent studies indicate obesity as a potential risk factor in renal
function loss. However, this only applies to condition such a unilateral
nephrecomy 209 or renal transplant 210-215. Clinical studies have also shown
a direct proportional increase in renal risk in subject without overt
comorbidity 209, 216-218. Studies on correlations between BMI and renal
function within the non obese subjects indicated a higher BMI is
associated with an elevated GFR relative to effective renal plasma flow
(ERPF) 219. However, the recent study on age depended correlations
between age and chronic kidney disease (CKD) 220 which can be measured
by changes in GFR 221 indicate positive correlation between age and CKD.
The analysis of correlations between the BMI and GFR expressed as
stages of chronic kidney disease results in the contingency table shown in
Output 41. The chi-square statistics, Output 42, and Cochran-MantelHaenszel
statistics, Output 43, p values reveal the presence of an
association between BMI and stages of chronic kidney disease. The
analysis of the strength of the association, Output 44, yields a weak reverse
proportional relation between BMI and CKD. This result is somehow
surprising since it indicate that underweight subjects are defined by failure
in renal function which contradicts the earlier findings.
52 | P a g e
Association Between BMI and Serum Uric Acid Level.
In the recent years epidemiological studies indicated that serum uric
acid level (SUA) is related, among others, to risk of hypertension and
coronary heart disease 222. In clinical and epidemiological studies, serum
uric acid (SUA) has been found to be related not only to risk of gout, but
also to risk of hypertension 223-226, coronary heart disease 67, 227-229, and
diabetes mellitus 230-231. It has also been shown that the level of SUA is
correlated with age gender and body weight 232-234. A number of studies
also found directly proportional relation between BMI and SUA 233, 235-239.
Also in this report we analyze the correlation between body mass
index and tierces of serum uric acid in NHANES III and NHANES 1999-
2006 comprised samples. The contingency table of BMI and a SUA tierce
is shown in Output 45. The visual analysis of contingency table reveals
that underweight sample is defined by the highest frequency in the third
tierce of SUA. The results of the association analysis performed by means
of χ2 and Cochran-Mantel-Haenszel Statistics reveals the presence of an
association between BMI and tierces of serum uric acid levels, Output 45
and 46. However, contrary to the previous reports we observe very week
negative correlation between BMI and tierces of serum uric acid level;
Output 48.
53 | P a g e
Association Between Pregnancy Status and Levels of Total
Cholesterol.
Six years longitudinal study on a cohort of 831 Dutch women revealed
statistically higher total cholesterol level than non pregnant women 240,
thus confirming the previous observations 241. However the analysis of
changes of total cholesterol level stratified by pregnancy trimesters
revealed a decrease in TC level during the first trimester and peaking
during the third trimester 242. This result is partially confirmed by the
comparative study on two groups pregnant and non-pregnant which
indicate that the level of total cholesterol increased considerably during the
second trimester and peaked during the third trimester 243. However, on
this study the researchers did not observe previously described first
trimester related changes. During post-partum the level of total cholesterol
decreased significantly.
The statistical analysis of NHANES III and NHANES 1999-2006
data encompassed by contingency table, Output 49, reveals the presence
of an association between pregnancy and total cholesterol level, Output 50
and 51. The analysis of the strength of the association points to extremely
weak and negative association between these two parameters, indicating
that pregnancy is very weakly associated with undesirable changes in total
cholesterol level, Output 52.
54 | P a g e
Association Between Pregnancy Status and Levels of HDL
Cholesterol.
The longitudinal study on a cohort of Dutch women revealed
statistically higher HDL cholesterol level than non pregnant women 240.
This result is in agreement with the earlier study reporting extreme
increase in HDL-C level increase during pregnancy 241. The results of the
recent study on pregnancy-related hyperlipidemia confirm the previous
observation and indicate that pregnancy is accompanied by significant
increase in HDL-C cholesterol 244.
The analysis of the contingency table, Output 53, of pregnancy status
versus HLD-C levels reveals higher ratio of High Class/Normal Class in
HDL-C level among pregnant women as compared to non-pregnant. The
analysis of the result of test for association, Output 54 and Output 55,
reveals the presence of an association between pregnancy status and
predefined HDL-C levels. The association strength analysis reveals very
week and negative association between studied parameters, Output 56,
indicating an increase in HDL cholesterol among pregnant women. In this
regard our findings support the previous reports.
55 | P a g e
Association Between Pregnancy Status and Levels of LDL
Cholesterol.
The study on LDL level changes as a function of pregnancy revealed
that LDL-C profile remained unchanged throughout pregnancy 245. These
observations are contradicted by results of the study on Asian vegetarians
and non-vegetarians, and in Caucasian meat eating mothers indicating that
LDL cholesterol concentration rises during pregnancy period 241. The
results of this study are congruent with the recent data indicating
significant increase in the level of LDL cholesterol during pregnancy 244.
However, the study on pregnancy induced hypertension indicates also an
increase in serum LDL-C concentration 246.
The analysis of the NHANES III and NHANES 1999-2006 data
yields contingency table, Output 57, used for the test of association
between pregnancy status and LCL cholesterol levels. The analysis of the
tests for association, Outputs 58 and Output 59, reveals the presence of an
association between pregnancy status and levels of LDL cholesterol. The
analysis of the strength of the association indicates a very week negative
association between these two parameters, Output 60. Thus, the analysis
of NHANES III and NHANES 1999-2006 confirms the previous results.
56 | P a g e
Association Between Pregnancy Status and Levels of
Triglycerides.
The early study on correlations between pregnancy and triglyceride
levels reported dramatic increase in triglyceride concentrations during
pregnancy 241. It was also observed that triglyceride levels increased
significantly during the second trimester, peaked in the third trimester and
significantly decreased during post-partum 243. These results are
concomitant with the recent data indicating significant increase in
triglyceride levels during pregnancy 244. The analysis of serum lipid and
apolipoprotein levels in pregnancy-induced hypertension revealed
pregnancy induced increase in serum triglyceride level 247.
The analysis of the NHANES III and NHANES 1999-2006 data
results in contingency table, Output 61 indicating extremely low frequency
of high triglyceride levels among pregnant women. The analysis of Pearson
chi-square statistics, Output 62, and Cochran-Mantel-Haenszel statistics,
Output 63, indicates an association between pregnancy status and
triglyceride levels category. The analysis of the strength of the association
reveals the presence of a week negative association between pregnancy
status and triglyceride levels, Output 64. In other words an increase in
triglyceride levels concomitant with pregnancy.
57 | P a g e
Association Between Breastfeeding Status and Levels of Total
Cholesterol.
The study on an influence of lactation on lipid metabolism in women
with recent gestational diabetes revealed that lactation plays a salubrious
role on lipid metabolism 245. The study on serum cholesterol levels during
prolonged lactation 248 revealed that mean levels of serum total cholesterol
significantly decreases during the first six months of lactation. However, it
was observed that in some women total cholesterol levels increased two
month after ceasing of lactation.
The statistical analysis of contingency table, Output 65, comprising
NHANES III and NHANES 1999-2006 breastfeeding status by levels of
total cholesterol results reveals the lack of association between
breastfeeding and total cholesterol levels, Outputs 66 and 67.
58 | P a g e
Association Between Breastfeeding Status and Levels of HDL
Cholesterol.
The analysis of the current literature on the subject exposed extremely
scarce information on correlations between breastfeeding status and
maternal blood HDL cholesterol levels. One of the recent studies on the
subject indicates that HDL-C levels increase during lactation period 249.
The same study has also shown that in smoking lactating mothers HDL
cholesterol levels were lower than in non smoking mothers.
The analysis of Pearson Chi-Square Statistics, Output 69, and
Cochran-Mantel-Haenszel Statistics, Output 70 based on the content of
contingency table, Output 68, indicates the presence of statistically
significant association between breastfeeding status and HDL-C levels.
The analysis of the strength of the association, Output 71 reveals week
positive association between the studied parameters. This observation
contradicts the previous report and indicates that breastfeeding is not
associated by an increase in HDL-C levels
59 | P a g e
Association Between Breastfeeding Status and Levels of LDL
Cholesterol.
The mean value of LDL cholesterol concentrations decreased
significantly between delivery and 6 months of exclusive lactation 248. This
observation was confirmed by the study revealing a decrease in LDL-C
levels during three months of lactation 249. It has also been shown that
smoking during lactation induces an increase in LDL cholesterol levels 249.
The statistical analysis of contingency table of NHANES III and
NHANES 1999-2006 data, Output 72, reveals the presence of an
association, at an alfa level of 0.05 but not at 0.01, between breastfeeding
status and LDL cholesterol levels, Outputs 73 and Output 74. Thus, the
analysis of the combined data, i.e. the data comprising NHANES III and
NHANES 1999-2006 data, yields the results that contradict those reported
previously.
60 | P a g e
Association Between Breastfeeding Status and Levels of
Triglycerides.
The analysis of the dynamics of blood triglyceride levels changes as a
function of lactation revealed that women who did not breastfeed their
infants maintained an elevated level of triglycerides longer that those
breastfeeding 242. It has also been shown that the lactation period leads to
a decrease in triglyceride levels in both smoking and nonsmoking mothers
249.
The statistical analysis of contingency table of breastfeeding by
predefined serum triglyceride levels, Output 75, indicates the lack of
association between the analyzed parameters, Outputs 76 and Output 77.
Thus, the analysis of NHANES III and NHANES 1999-2006 data
disproves the earlier statements indicating changes in serum triglyceride
levels as a function of breastfeeding status.
61 | P a g e
Association Between Tobacco Smoking Status and Levels of
Total Cholesterol.
Smoking may be a cause of a multitude of diseases 250. However,
cancer is the most prevalent among them 250. A very high death rate has
also been reported for smokers 251. It has also been shown that current
smoking is coupled with an acute increase of hypertension 252.
Nonetheless, results on smoking and increased blood pressure are
obscure. Some of the earlier studies indicated that lower blood pressure
accompany higher level of cigarette smoking 253-254. The recent study on
correlations between cigarette consumption and blood pressure revealed
that older men smokers are defined by significantly higher SBPs and
comparable DBPs to never smokers. Nevertheless, in non-clinical samples
a higher blood pressure was found in former or never smokers than in
current smokers 252, 255-257. These results are coupled with observations that
consumption of cigarettes is congruent with consumption of alcoholic
beverages 258 and gives an indication as to the etiology of smoking induced
changes in systolic blood pressure. The recent findings also indicate that
increased smoking burden is per se a factor leading to a small increase in
total cholesterol levels 259. It has been shown that smoking intensifies the
effect of total cholesterol and HDL cholesterol on CHD 260-261.
Additionally an observation has been made that smoking is directly
associated with detrimental lipid changes which are do not directly affect
an increase in the risk of CHD 262. Smoking also has a significant influence
on changes in the HDL cholesterol/total cholesterol ratio 263. However, it
affects HDL cholesterol levels more than total cholesterol levels.
In our study we analyze the contingency table of smoking status by
levels of total cholesterol, Output 78, by means of chi-square, Output 79
and Cochran-Mantel-Haenszel statistics, Output 80. The analysis of the
respective p values, 0.3928 and 0.805, exposes the lack of association
between smoking status and total cholesterol levels predefined by ATP III
panel 37. In conclusion, our results do not confirm the statement indicating
that tobacco smoking induced changes in total cholesterol levels.
62 | P a g e
Association Between Tobacco Smoking Status and Levels of
HDL Cholesterol.
The study on the association between quitting smoking and weight
gain indicted that there is a significant independent and favorable effect of
smoking cessation on HDL cholesterol levels 263-267 . The Israeli CORDIS
study 268 partially supports the findings indicating that smoking cessation
results in a non-significant increase in serum HDL cholesterol levels.
These results combined with the recent data indicate that an increased
exposure to tobacco smoking is associated with a small decrease in
HDL-C levels 259, as well as confirm tobacco smoking relation to health
risk. The results of the previous study on an association between blood
lipid and smoking habits among 18 year-old men also indicated that
tobacco smoking is associated with a non significant decrease in HDL-C
levels 269.
The statistical analysis of NHANESIII and NHANES 1999-2006 data
on smoking status and HDL-C classification, Output 81, yields the p
values for chi-square, Output 82, and Cochran-Mantel-Haenszel statistics,
Output 83, less than 0.01. This observation indicates that there is a general
association between tobaccos and HDL cholesterol levels. The analysis of
the strength of the association, Output 84, reveals very week negative
association between these two parameters. Thus, our study confirms the
previous findings and indicates that tobacco consumption decreases
HDL-C levels.
63 | P a g e
Association Between Tobacco Smoking Status and Levels of
LDL Cholesterol.
It has recently been shown that smoking habit is associated with a
small increase in LDL-C levels 259. This result contradicts the earlier
reports on tobacco smoking and blood lipids correlations indicating a
small and statistical non significant increase in LDL-C levels among young
smoking men 269. However, the study on smoking cessation blood lipids
driven changes indicates that tobacco smoking cessation results in a non
significant increase in serum LDL-C levels 268.
The statistical analysis of NHANESIII and NHANES 1999-2006 data
reported in smoking status by LDL-C levels contingency table, Output 85,
yields the p values for chi-square, Output 86, and Cochran-MantelHaenszel
statistics, Output 87, less than 0.01 that indicates the presence of
general association between tobacco smoking status and HDL cholesterol
levels. The analysis of the Pearson correlation coefficient indicates an
extremely week negative association between these two parameters,
Output 88 that confirms the earlier findings that indicate an increase in
LDL-C levels as a function of tobacco consumption.
64 | P a g e
Association Between Tobacco Smoking Status and
Triglyceride Levels.
The recent studies on cigarette consumption and serum blood lipids
levels revealed that smoking is associated with small increase in blood
triglycerides levels 259. Smoking cessation, however, correlates with a slight
decrease in serum triglycerides levels 268.
The statistical analysis of NHANESIII and NHANES 1999-2006
data, Output 89, yields the p values for chi-square, Output 90, and
Cochran-Mantel-Haenszel statistics, Output 91, less than 0.01. This allows
to draw a conclusion that there is an association between tobacco smoking
status and blood HDL cholesterol levels. The analysis of the Pearson
correlation coefficient indicates an extremely week negative association
between these two parameters, Output 92. Thus a conclusion can be
drawn that tobacco smoking is accompanied by an increase in blood
triglyceride levels.
65 | P a g e
Association Between Alcohol Consumption Status and Levels
of Total Cholesterol.
Alcohol consumption my influence total cholesterol levels 270.
However, the changes in total cholesterol levels are more extreme when
excessive alcohol consumption is combined with nutritional deficiencies.
In such a case total serum cholesterol 271 levels are decreased. However,
this observation is not conclusive since another study has reported the lack
of alcohol induced changes in total plasma cholesterol 272. It has also been
shown that in non-smoking men total cholesterol levels are positively
correlated with alcohol intake and that an association between total
cholesterol and alcohol consumption is significantly influenced by cigarette
smoking 273.
The analysis of the results of chi-square statistics as well as CochranMantel-Haenszel
Statistics, Output 94 and 95, based on contingency table
of alcohol consumption by total cholesterol category, Output 93, yields an
association between alcohol consumption and total cholesterol levels. The
analysis of the strength of an association by means of the Pearson “r”
factor, Output 96, indicates a very weak and negative association between
these two parameters. In other words tobacco smoking is associated with
an increase in total cholesterol levels.
66 | P a g e
Association Between Alcohol Consumption Status and Levels
of HDL Cholesterol.
It has been shown that HDL concentration raises together with
moderate alcohol consumption274-279 , which in turn may play protective
role against CHD 32. The study performed in two Serbian cohorts of the
Seven Countries indicated that men consuming one or more alcoholic
beverages per day have 16.5% higher HDL-C levels than those abstaining
alcohol 280. It was, however, shown that the significance of a change is
defined by the type of an alcohol. Thus, changes arestatistically significant
only after beer and spirits, consumption. On the other hand, wine
consumption does not results in statistically significant changes in HDL-C
levels 281. However, the study on correlations between alcohol
consumption including beer and wine and health indicators such as HDL
cholesterol levels indicated alcohol induced increase in HDL cholesterol
levels 282. Similar results were reported for Japanese population. Another
study also indicated that an increase in the HDL cholesterol levels is
independent of the kind of an alcoholic beverage 283. It has also been
shown that among postmenopausal women fed a controlled diet, HDL
cholesterol levels increases after consumption of 30 g of ethanol per day
over a period of eight weeks 284. The study on alcohol consumption and
HDL cholesterol level among premenopausal women also indicated an
increase in HDL cholesterol levels 285. The new finding also reports an
association between the body mass influence on an association between
alcohol consumption and hypertension as well as the lack of an influence
of body mass on association between alcohol consumption and HDL-C
levels 286.
The analysis of the results of chi-square statistics as well as CochranMantel-Haenszel
Statistics, Output 98 and 99, based on contingency table
of alcohol consumption by total cholesterol category, Output 97, indicates
the presence of an association between alcohol consumption and HDL
cholesterol levels. The analysis of the association strength by means of the
Pearson “r” factor, Output 100, indicates a very weak and negative
association between these two parameters revealing that alcohol
consumption is weakly associated with an increase in blood HDL-C levels.
67 | P a g e
Association Between Alcohol Consumption Status and Levels
of LDL Cholesterol.
It has been shown that LDL-cholesterol levels have a statistically
significant negative relationship 283 with alcohol consumption. Similar
results were reported for six year follow up in the Copenhagen male study
287. The study on correlations between alcohol consumption and LDL-C
levels among older adults also indicated negative relationship between
alcohol consumption and LDL cholesterol levels 288. The report on alcohol
consumption driven serum lipids changes among premenopausal women
indicated eight percent decrease in blood LDL cholesterol levels 285
associated with alcohol consumption. Congruent results were obtained in
the study on postmenopausal women 284 indicating that plasma LDL
cholesterol levels decreases after consumption of 15 g ethanol per day 284.
These observation were confirmed by a multicenter, randomized, clinical
intervention trial 289.
The analysis of the results of chi-square statistics as well as CochranMantel-Haenszel
Statistics, Outputs 102 and 103, based on contingency
table of alcohol consumption table by total cholesterol category, Output
101, exposed an association between alcohol consumption and blood LDL
cholesterol levels. The analysis of the association strength by means of the
Pearson “r” factor, Output 104, indicates extremely weak and negative
association between these two parameters. In our opinion the design of
our experiment is so much different presented by the others that the
obtained level of the strength of the association is rather inconclusive.
68 | P a g e
Association Between Alcohol Consumption Status and Levels
of Triglycerides.
The study on an influence of tobacco and alcohol consumption on
serum lipid levels indicated that in non-smoking men triglyceride levels are
positively associated with an alcohol intake and that association between
total cholesterol levels and alcohol consumption is influenced by cigarette
smoking 273. The study on effects of an alcohol on plasma lipoproteins and
cholesterol levels in hospitalized patients fed with a defined diet indicated
that alcohol consumption did not cause any changes in low density
lipoprotein levels 290. However the study on correlations between specific
alcohol consumption and triglycerides levels indicated significantly lower
levels of the latter among beer drinking subjects 283. Hence, the report
based on results of The British Regional Heart Study on alcohol
consumption and the levels of blood lipids indicated that among nonsmokers
triglyceride levels are significantly and positively associated with
alcohol consumption 273. The contradicting results were reported by
German National Health Survey indicating that in moderate alcohol
drinkers there is no significant relationship between triglyceride levels and
alcohol consumption 282. The recent study performed on a population with
high alcohol consumption indicated that triglyceride levels are higher
among non drinkers than heavy drinkers 291.
Summarizing, we may say that levels of lipoproteins are defined by a
variety of factors such as gender: HDL-C is higher in prememopausal
women than in men of the same age; age: total cholesterol levels increase
with age and HDL-C cholesterol levels decrease with age; diet: total
cholesterol levels, HDL-C levels, triglyceride levels increase when exposed
to fat rich diet; physical exercise: HDL-C levels increase and triglyceride
level decrease as a function of physical exercise.
Diseases may also influence changes in triglyceride levels. For example
diabetes leads to an increase in total cholesterol levels, HDL-C levels and
triglyceride levels. All the aforementioned phenomena can be stimulated
or decreased by an alcohol consumption as well as cigarette smoking.
Thus, in our opinion the analysis of alcohol consumption on levels of
lipoproteins is extreme importance when assessing health related quality of
life.
The analysis of the results of chi-square statistics as well as CochranMantel-Haenszel
Statistics, Output 106 and Output 107, based on
contingency table of alcohol consumption table by total cholesterol
category, Output 105, yields the presence of an association between these
69 | P a g e
two variables. The analysis of the association strength, Output 108, reveals
an extremely weak and positive association between these two parameters.
In other word alcohol consumption is associated with a decrease in serum
triglyceride levels.
70 | P a g e
Association Between Chemotherapy and Levels of Total
Cholesterol.
Chemotherapy is associated by a variety of side effects such as
anemia, appetite changes, bleeding problems, constipation, diarrhea,
fatigue, hair loss (llopecia), increased susceptibility to infections, memory
changes, mouth and throat diseases, nausea and vomiting, nerve changes,
pain, sexual and fertility changes, skin and nail changes, and swelling (fluid
retention). Since chemotherapy induce toxicities (or side-effects) that on
the scale from one to five have is median around 2 to 3 we may definitely
expect its influence on a variety of physiological factors and among them
changes in blood lipids levels; it is changes in total cholesterol levels,
HDL-C, LDL-C, and triglyceride levels.
The study on blood serum lipid changes as a function of
chemotherapy in patients with chemosensitive cancers revealed significant
increase in serum total cholesterol levels among the patients who
responded favorably to the chemotherapy procedure 292.
The study on serum lipids in 61 breast cancer patients undergoing
cancer therapy revealed that levels of serum total cholesterol decreases
significantly after breast cancer therapy 293. On the other hand, there are
the study on chemotherapy induced changes in total cholesterol levels,
performed on 40 patients with hematological malignancies, that indicated
the lack of significant changes in total cholesterol levels within a short time
after therapy 294.
Partially contradicting results are presented for the patients treated
with adjuvant chemotherapy for early stages of breast cancer 295. The
results reported by this study indicate that changes in total cholesterol
levels are a function of an ovarian function. Thus, total cholesterol levels
increased in patients that developed ovarian dysfunction or amenorrhoea.
However, among the patients who preserved regular menstruation after
chemotherapy the serum total cholesterol levels did not change. This
observation are in agreement with the previous reports indicating that
chemotherapy induces changes of serum lipids but only with association
with ovarian dysfunction 296.
The statistical analysis of contingency table, Output 109, comprising
chemotherapy status by levels of total cholesterol results reveals the lack
of association between chemotherapy and total cholesterol levels, Output
110 and Output 111. In the design presented here our study does not
confirm the earlier findings indicating chemotherapy induced changes in
71 | P a g e
serum total cholesterol levels. However, it has to be stressed that we study
general influence of chemotherapy on total cholesterol levels and this may
differ from the specific treatments of the specific cancers.
72 | P a g e
Association Between Chemotherapy and Levels of HDL
Cholesterol.
The study on subjects treated using chemotherapy for chemosensitive
cancers revealed the lack of significant changes in HDL cholesterol levels
among patients that favorably responded to the treatment 292. Two other
studies reported assonantiall results as to the level and direction of changes
in blood HDL cholesterol in response the chemotherapy. Thus,
Rzymowska et al. 297 report a non-significant increase in HDL-C
cholesterol levels in breast cancer chemotherapy patients 297. Similar
observation was reported earlier of Subramaniam at al. 298. Congruent
observation was also reported by Vehmanen at al. 295. We have to point
that although the authors state that “HDL cholesterol levels slightly
decreased regardless of menstrual function” the analysis of Table 1 in the
original report indicates the opposite, it is non-significant increase in
HDL-C levels irrespectively of regular menses, irregular menses or
amenorrhoa.
The statistical analysis of contingency table, Output 112, comprising
chemotherapy by levels of total cholesterol results reveals the lack of
association between chemotherapy status and total cholesterol levels,
Output 113 and Output 114. The tests for general association between
serum HDL levels and chemotherapy status do not confirm the previous
findings.
73 | P a g e
Association Between Chemotherapy and Levels of LDL
Cholesterol.
It has been shown that among untreated breast cancer patients LDL
cholesterol levels decreased significantly after a chemotherapy treatment
293. The studies on changes of LDL cholesterol concentrations in response
to a chemotherapy of chemosensitive cancers revealed that patients
favorably responding to the therapy were defined by an increase in LDL
cholesterol levels 292. Similar observation was reported in the study on
tamoxifen treatment and chemotherapy-induced ovarian failure 295. An
increase in LDL-C levels was observed among patients with irregular
menses, amenorrhoa in six months follow up after the treatment. In
regular menses patients a U-shaped change in LDL-C levels was observed.
These results partially contradicts those reported by Rzymowska et al 297
that indicate a significant decrease in chemotherapy induced LDL-C
changes in pre- and postmenopausal women. Different pattern of changes
in levels was reported in the study on serum lipids levels in chemotherapy
patients for disseminated and nonseminomatous testicular cancer. In the
study an elevation in LDL-C levels in the majority of the patients was
reported 299.
The statistical analysis of contingency table, Output 115, comprising
chemotherapy status by serum total cholesterol levels reveals the lack of
association, at a significance level of 0.01, between chemotherapy status
and total cholesterol levels, Output 116 and Output 117. Thus, we
conclude that the analysis of NHANES III and NHANES 1999-2006 data
does not confirm the previous findings. This observation may be driven
by the fact that we do not distinguished between chemotherapy treatments
for different cancers. Our study are an attempt of generalization of the
problem which in this case indicate that there is no change in serum LDL
cholesterol levels in response to broadly defined chemotherapy.
74 | P a g e
Association Between Chemotherapy and Triglyceride Levels.
The study on changes in serum triglyceride levels as a function of
chemotherapy of four different chemosensitive cancers, i.e., malignant
lymphomas, breast carcinomas, small-cell lung carcinomas, and urothelialcell
carcinomas revealed an increase in serum triglyceride levels only in
patients treated for breast carcinomas 292. Another study focused on the
analysis of changes in blood triglyceride levels according to menstrual
status of chemotherapy patients across a time period of 12 months
revealed a non-significant increase in triglyceride level 295. This observation
is partially in agreement with the previous reports indicating nonsignificant
changes in serum lipid levels in patients treated for testis cancer
300.
The statistical analysis of contingency table, Output 118, comprising
chemotherapy by serum triglyceride levels reveals the lack of association
between chemotherapy and total cholesterol levels, Output 119 and
Output 120. This observation is in partial agreement with the previous
studies indicating statistically non significant changes in serum triglyceride
levels in response to chemotherapy treatment.
75 | P a g e
Association Between Contraception Use and Levels of Serum
Total Cholesterol.
The study on 17-year-old girls using oral contraceptives revealed an
elevation in serum total cholesterol levels in response to contraceptives
administration 301. However, the studies on changes in plasma cholesterol
levels among Nigerian long term oral contraception users report the lack
of statistically significant differences in total cholesterol levels between
women using oral contraception and those in the control group 302.
The analysis of the current literature on the subject indicates that
changes in blood total cholesterol levels depend on the type of the used
contraception. Thus, a comparative study of three contraception methods
indicates that total cholesterol levels increased in subject administered with
ethinyl estradiol and norgestrel, and medroxyprogesterone acetate. The
group receiving levonorgestrel is described by a decrease in the total
cholesterol levels after six month of contraception use 303. The recent
study on the influence of transdermal contraception on blood total
cholesterol levels reveals a statistically significant increase in total
cholesterol concentrations after using contraceptive patches 304. However,
the studies on an influence of levonorgestrel-releasing intrauterine system
on total cholesterol levels yield the lack of statistically significant changes
in blood total cholesterol 305.
Primarily to data analysis and discussion we have to state that our
analysis does not differentiate between types of contraception. The
analysis of the contingency table, Output 121, indicates that there is an
association between contraception use and serum total cholesterol levels,
Output 122 and Output 123. The analysis of the association strength,
Output 124, reveals extremely week positive association between these
two factors. This observation indicates that contraception use, regardless
of its type, i.e., oral, patches or intrauterine system, leads to a decrease in
serum total cholesterol levels. Thus in this regard our results confirm the
previous findings.
76 | P a g e
Association Between Contraception Use and HDL Cholesterol
Levels.
One of the early studies on the oral contraceptive use and HDL
cholesterol levels indicted the lack of statistically significant changes in
response to oral contraceptive use 306. However, the recent study on the
influence of progestogen-only contraceptives on serum lipids levels
indicated that use of levonorgestrel is correlated with a moderate increase
of HDL-C levels whereas use of oral norethisterone or lynestrenol, or
depot medroxyprogesterone acetate is associated with a high increase in
HDL cholesterol levels 307. This observation contradicts the earlier
observation indicating that use of oral contraception is associated with a
decrease in HDL cholesterol levels 308. The study on correlations between
an oral contraceptive and serum lipids profile among teenage women
revealed the lack of statistically significant changes in response to
contraceptive administration 309. Thus, the physiological response if
different from this observed for adult women.
The analysis of the contingency table, Output 125, indicates the
presence of an association between contraception use and serum HDL
cholesterol levels, Output 126 and Output 127. The analysis of the
association strength, Output 128, reveals extremely week negative
association between the studied factors indicating an increase in
contraception induced HDL cholesterol levels. Thus, our findings confirm
some of the earlier reports.
77 | P a g e
Association Between Contraception Use and LDL Cholesterol
Levels.
There is a difference between LDL cholesterol changes in response to
oral contraception between adult and teenage women 309-310. Thus, the
recent study on LDL cholesterol changes as a function of oral
contraception use among young women revealed significant increase in
LDL-C level 309. However, Lobo et al. 310 indicated a decrease in LDL-C
level among women administered with desogestrel-30 micrograms ethinyl
E2. The early study on an influence of different formulations of oral
contraceptive on serum lipids levels revealed that LDL cholesterol levels
were reduced by 14 to 12 percent between women administered with
desogestrel and those administered with low-dose norethindrone 308. The
recent study on an oral contraception formulation with drospirenone
(Yasmin®) on lipid metabolism also indicates a decrease in LDL-C levels
311. However, the latest results on an association between an oral
contraceptive and serum lipids levels contradict the earlier observations
and indicate that there is no change in LDL-C levels in the response to
oral contraceptive administration 312.
The statistical analyses, Output 130 and Output 131, base on
contingency table, Output 129, indicate that there is an association
between contraception use and serum LDL cholesterol levels. The analysis
of the association strength, Output 132, reveals extremely week positive
association between the studied parameters. On one hand our results
confirm those reported by Lobo et al. 310 in the same time disproving the
results presented by Berenson et al 312. Since we do not distinguish
between types of the contraception used i.e. oral or patches our data are a
general description of physiological response to contraception
administration and as such indicate a marginal decrease in LDL-C levels in
women using contraceptives.
78 | P a g e
Association Between Contraception Use and Triglyceride
Levels.
The latest study on blood lipid changes in response to nonhormonal
injectable and oral contraception indicate an increase in levels of blood
triglycerides for both types. However, it has been noticed the increase
caused by oral contraceptives is significantly greater than this induced by
injective nonhormonal contraceptives 312. Similar response is reported for
the study on drospirenone induced blood lipid changes 311. The study on
an influence of oral contraceptive on blood lipid levels in teenage women
also confirms the finding related to adult women and indicates a
significant increase in blood triglyceride levels in response to
contraception 309. Thus, the results of the earlier study on effects of oral
contraceptive agents on blood triglyceride levels 308 are thoroughly
confirmed.
In our study the analysis of contingency table comprising NHANES
III and NHANES 1999-20006 data, Output 133, reveals statistically
significant association between contraception use and serum triglyceride
levels, Output 134 and Output 135. Surprisingly, the analysis of the
strength of the association between these two parameters, Output 136,
yields the positive r factor between contraception use and serum
triglyceride levels. This observation indicates a decrease in serum
triglyceride levels as a function of contraception use. Thus, our results
contradict those previously reported. This phenomenon may be partially
due to lack of division between the types of contraception as well as lack
of the stratification for the age.
79 | P a g e
Association Between Glomerular Filtration Rate and Levels of
Serum Total Cholesterol.
The recent study on correlations between serum creatinine, glomerular
flow rate (GFR), and the profile of serum lipids a revealed very week
negative association between GFR and serum total cholesterol levels 313.
This result is contradicted by the earlier study indicating a positive
association with eGFR and total serum cholesterol 314 that in turn is in
agreement with the Korea Medical Institute Study on associations between
renal function and serum lipids profile 315. Another study on a glomerular
filtration rate in non-insulin-dependent diabetic subjects indicated an
inverse relationship between GFR and blood total cholesterol levels 316
confirming the results reported previously by Lin et al 313. Thus, currently
results on the association between glomerular filtration rate and serum
total cholesterol levels are non-conclusive and study design dependent.
This may indicate that serum cholesterol may not be an independent
predictor of the end-stage of renal disease 317
The statistical analysis based on contingency table, Output 137,
indicates that there is an association glomerular filtration rate represented
as a kidney disease stage and serum total cholesterol levels, Output 138
and Output 139. The analysis of the strength of the association, Output
140, reveals extremely week positive association between these two
factors. This in turn is in agreement with the previous study indicating a
negative association between GFR and serum total cholesterol levels.
80 | P a g e
Association Between Glomerular Filtration Rate and Levels of
HDL Cholesterol.
The recent study on the correlations between glomerular filtration rate
and its association with HDL-C levels indicates the lack statistically
significant correlations between GFR and HDL-C levels 318. However the
study on glomerular hyperfiltration 319 indicated that low HDL cholesterol
increased the multivariate-adjusted odds ratio of glomerular
hyperfiltration. The recent study on glomerular filtration rate and low
HDL-C in patients with and without chronic kidney disease indicated that
low HDL-C is prevalent in patients with chronic kidney disease but there
is not obvious correlation between the severity of the disease and low
HDL-C level 320.
The analysis of contingency table, Output 141 indicates that there is
an association between glomerular filtration rate and serum HDL
cholesterol levels, Output 142 and Output 143. The analysis of the
association strength, Output 144, reveals week negative association
between these two factors. This observation reveals assonantial decrease in
glomerular flow and HDL-C levels that is in agreement with the previous
results.
81 | P a g e
Association Between Glomerular Filtration Rate and Levels of
LDL Cholesterol.
The study on correlations between glomerular filtration rate and its
association with LDL-C levels indicates the lack statistically significant
correlations between GFR and LDL-C 318. However, another study on this
subject indicated that plasma levels of LDL-C decreases congruently with
GFR 321 The study on glomerular filtration rates as a function of, among
others, serum lipids in obese women indicated a significant increase in the
level of LDL-C in low GFR group≤92 ml/ min/1.73 m2 as compared to
high GRF group > 92 ml/min/1.73 m2 322.
The analysis of contingency table, Output 145 indicates the presence
of an association between glomerular filtration rate and LDL-C levels,
Output 146 and Output 147. The analysis of the strength of the
association, Output 148, yields extremely week negative association
between these two factors. This observation indicates a parallel decrease in
GFR and LDL-C. Thus, our results confirm those of Morita et al. 321.
82 | P a g e
Association Between Glomerular Filtration Rate and Levels of
Triglycerides.
The recent study on effects of alcohol consumption on estimated
glomerular rate (eGFR) and creatinine clearance rate indicated that serum
triglycerides are indirectly, it is through alcohol consumption, positively
correlated with eGFR 323. This result confirms the data presented by
Bayraktaroglu et al. 322 indicating a significant increase in blood triglyceride
levels as a function of eGFR. These observations are contradicted by the
earlier data presented by Tozawa at al. 324 indicating that in women high
triglyceride levels may predict the decline of renal function.
The analysis of contingency table, Output 149 reveals the presence of
an association between glomerular filtration rate and serum triglyceride
levels, Output 150 and Output 151. The analysis of the association
strength, Output 152, reveals very week positive association between these
two factors. It is a decrease in glomerular filtration rate is associated with a
decrease in triglyceride levels. This results in turn confirms the results
presented by Tozawa et al. 324.
83 | P a g e
Association Between Serum Uric Acid Level and Levels of
Serum Total Cholesterol.
The study of correlations between serum uric acid levels and primary
pulmonary hypertension revealed the lack of significant differences
between serum uric acid level and serum total cholesterol levels 325. The
recent study by Forman et al. 326 indicated that an increase in uric acid level
is associated by an increase in serum total cholesterol. Similar observation
was made in study on population dependent correlations between serum
uric acid level and total cholesterol levels in Bankok and Mual Pol groups
327. Another reports also indicated that total cholesterol levels are an
independent positive predictor of serum uric acid level 328.
The analysis of the contingency table, Output 153, indicates that there
is an association between serum uric acid level and serum total cholesterol
levels, Output 154 and Output 155. The analysis of the strength of the
association, Output 156, reveals a very week negative association between
these two factors. Thus our results partially contradict the previous data
and indicate that an increase in uric acid tierce is associated with a decrease
in serum total cholesterol levels. However, the strength of the association
is extremely week and significantly diminishes the strength of the
conclusion.
84 | P a g e
Association Between Serum Uric Acid Level and HDL
Cholesterol Levels.
The study on correlations between serum uric acid level and metabolic
syndrome in Japanese subjects revealed the assonantial stepwise graded
decrease in HDL-C levels with the uric acid levels quartiles 227. In the
recent study on serum uric acid influence on specific components of
metabolic syndrome an observation contradicting the latter was reported.
Thus, serum uric acid level was significantly higher in subjects with
abnormally high level of HDL-C 329.
The analysis of the contingency table, Output 157, yields an
association between serum uric acid level and HDL cholesterol levels,
Output 158 and Output 159. The analysis of the strength of the
association, Output 160, reveals a very week negative association between
these two factors. This, in turn indicate that HDL-C levels decrease as
serum uric acid level increase what is in agreement with the results
reported by Ishizaka et al. 227. However, the strength of the association
may render our data inconclusive.
85 | P a g e
Association Between Serum Uric Acid Level and LDL
Cholesterol Levels.
In the recent study on associations of an elevated level of serum uric
acid as micro vascular function in patients with idiopathic dilated
cardiomyopathy 330 a negative correlation between serum uric acid and
LDL-C levels was reported. This, however, is incongruous with the results
of the study on serum uric acid association with cardiovascular mortality
331. In this study subjects defined by the upper tertile of serum uric acid
levels are defined by higher LDL cholesterol levels. This observation is in
agreement with the report on association between serum uric acid levels
and suspected coronary artery disease: in this case an increase in LDL-C
cholesterol levels is associated with significant increase in SUA level 332.
The analysis of contingency table, Output 161 indicates an association
between serum uric acid level and serum LDL cholesterol levels, Output
162 and Output 163. The analysis of the strength of the association,
Output 164, yields a very week negative association between these two
factors. Thus, the observed association indicates a negative correlation
between LDL-C levels and serum uric acid level and confirms the results
reported by Zopini et al. 330. The strength of the association may render
the observed relation as inconclusive.
86 | P a g e
Association Between Serum Uric Acid Level and Triglyceride
Levels.
It has been shown that higher serum uric acid level is correlated with a
variety of metabolic abnormalities and among them higher triglyceride
levels 325, 333-336. These results are confirmed by the study on correlations
between plasma uric acid level and the risk for hypertension 326. They are
also in agreement with the observation of Lin et al. 329 indicating an
increase in blood triglyceride levels as a function of an increase in serum
uric acid level.
The analysis of the contingency table, Output 165 reveals the presence
of an association between serum uric acid level and serum triglyceride
levels, Output 166 and Output 167. The analysis of the association
strength, Output 168 reveals a very week positive association between
these two factors. Thus, an increase in level of serum uric acid is
accompanied by an increase in serum triglyceride levels. We may state that
our data confirms the previously presented results.
87 | P a g e
Association Between Hypertension and Serum Total
Cholesterol Levels.
The recent studies on correlations between serum total cholesterol
levels and hypertension indicated an increase of the former as a function
of blood pressure 337. Similar observation was also reported by Chehrei et
el 338. Thus, statistically significant difference in total cholesterol levels
between hypertensive and normotensive patients was observed. This
observation was also confirmed in the recent studies by Sarkar et al. 337.
Summarizing, we may say that all the current studies indicate that
hypertension is associated by an elevated serum cholesterol levels.
The analysis of contingency table, Output 165, yields an association
between hypertension stage and serum total cholesterol levels, Output 166
and Output 167. The analysis of the strength of the association, Output
168, reveals a week and positive association between the studied
parameters. In other words hypertension is associated with an increase in
blood total cholesterol levels and our result confirms those presented by
others.
88 | P a g e
Association Between Hypertension and Serum HDL
Cholesterol Levels.
Research on correlation between serum lipid levels and hypertension
reports as the most frequent combination an arterial hypertension
accompanied by low HDL cholesterol levels 339. Statistically significant
decrease in serum HDL-C levels as a function of hypertension class was
also observed in the recent report by Lungu et al 340 on dyslipidemia in
hypertensive patients in a primary care. The significant drop in HDL-C
levels among hypertensive patients was also observed in hypertensive
patients in the northern region of Bangladesh 341.
The analysis of contingency table, Output 165, yields an association
between predefined hypertension stages and serum HDL cholesterol
levels, Output 174 and Output 175. The analysis of the association
strength, Output 168, reveals extremely week positive association between
the studied factors. In the light of the previous results this observation is
somehow puzzling. However, when taking into account the strength of
the observed association obtained result may be, in our opinion, treated as
inconclusive.
89 | P a g e
Association Between Hypertension and Serum LDL
Cholesterol Levels.
The analysis of the current literature on serum LDL cholesterol levels
changes as a function of hypertension unanimously indicates that the
concentration of serum LDL cholesterol is greater in hypertensive patients
than this observed for normotensive patients 196, 337-338, 341.
The analysis of contingency table, Output 177, reveals the presence of
an association between predefined hypertension stage and serum LDL
cholesterol levels, Output 178 and Output 179. The analysis of the
association strength, Output 180, also reveals a week and positive
association between these two factors. Thus, an increase in blood pressure
is accompanied by an increase in LDL cholesterol levels. Thus, we may
confidently state that obtained results confirmed those reported by others.
90 | P a g e
Association Between Hypertension and Serum Triglyceride
Levels.
The recent studies congruently indicate that triglyceride levels are
greater in hypertensive than in normotensive patients 196, 337. This
observation is strengthen by the fact that similar phenomenon is observed
among children 2 to 18 years of age 342.
The analysis of contingency table, Output 181, also reveals an
association between hypertension stages and serum HDL cholesterol
levels, Output 182 and Output 183. The analysis of the association
strength, Output 184, confirms the reports presented by other and indicate
a congruent increase in serum triglyceride levels and blood pressure.
91 | P a g e
Association Between Hypertension and Glomerular Filtration
Rate.
The recent study has shown that an impaired renal function is
independently associated with hypertension 318. It has also been shown
that an elevation in SBP and DBP may be correlated with low GFR 343.
Similar observation it is a reduction in GFR in hypertensive patients was
also observed in elderly 344. Summarizing, we may say that the current
scientific reports are congruent in description of hypertension associated
changes in glomerular flow rate.
The analysis of contingency table, Output 185, reveals the presence of
an association between hypertension stages and serum HDL cholesterol
levels, Output 186 and Output 187. The analysis of the association
strength, Output 188, indicates a congruent elevation in kidney disease
stage which is reverse proportionally associated with glomerular flow rate
and blood pressure. Thus out results confirm previously presented results.
92 | P a g e
Association Between Hypertension and Serum Uric Acid
Levels.
One of the recent reports on a pathogenetic role of uric acid in
hypertension suggests that an increase in serum uric acid level may lead to
hypertension 345. However, the recent studies on serum uric acid level as a
function of hypertension among Chinese nonagenarians/centenarians 346
indicate the lack of statistical differences in serum uric acid level between
normotensive and hypertensive patients. However, this study contradicts
the earlier observations indicating that serum uric acid is positively
associated with an increase in BP 347 which in turn are in agreement with
three year longitudinal study indicating that elevated serum uric acid level
is correlated with an elevation in blood pressure 348.
The analysis of contingency table, Output 189, yields the presence of
an association between hypertension stages and serum uric acid levels,
Output 190 and Output 191. The analysis of the association strength,
Output 192, indicates an assonantial increase in serum uric acid levels and
blood pressure and as such confirms some of the previous results.
93 | P a g e
Summary and Conclusions
Accordingly to our knowledge the presented study is among the most
extensive ever that undertook the analysis of associations between such a
wide ranges of health inducing factors.
In this study we attempt to evaluate currently accepted clinical values
of blood pressure, serum total cholesterol levels, serum HDL cholesterol
levels, serum LDL cholesterol levels, serum triglyceride levels, glomerular
filtration rate expressed as a function of serum creatinine clearance and
kidney disease stage, and serum uric acid level.
This study is spurred by the simple fact that these parameters are the
reference values for the majority of clinicians and a used for defining of
health related quality of life.
The presented study is a combination on very extensive literature
analysis and state of the art analysis of the combined data of the largest
publicly available databases, i.e. the NHANES III and NHANES 1999-
2000, 2001-2002, 2003-2004, and 2005-2006.
The National Health and Nutrition Examination Survey (NHANES)
is an ongoing project lasting currently for more than twenty years. Its
uniqueness is driven by the fact that it combines interviews and physical
examinations. Thus, it gives the majority of researchers unexampled
opportunity to study and examine a variety of different factors that may
influence or influence our daily life.
The frequency of utilization of NHANES database can easily be
visualized through the search of PubMed: a service of the US National
Library of Medicine that provide free access to indexed citations and
abstracts to medical, nursing, dental, veterinary, health care, and preclinical
sciences journal articles. Thus, the recent search of PubMed entries
comprising NHANES phase in the title or abstract returns 17,130
citations. This number per se is a good example how important is
NHANES and how often it is used in a multitude of scientific research.
In our study we concentrated on the analysis of an elevated blood
pressure, it is hypertension, and its direct and indirect associations with a
variety of epidemiological factors. We have to firmly state that the
presented study does not “saturate “ this subject. However, the study is
,our opinion, a very important step in a large scale assessment of currently
94 | P a g e
accepted clinical threshold values of serum lipids, creatinine clearance, and
serum uric acid.
The analysis of the content of the consecutive chapters results in
Tables 21-30.
Table 21. The Analysis of Associations Between Predefined Values
of Body Mass Index and Tobacco Smoking, Alcohol Consumption,
Pregnancy Status, Chemotherapy Status, Breastfeeding,
Contraception Use, Total Cholesterol Levels, HDL Cholesterol
Levels, LDL Cholesterol Levels, Triglyceride Levels, Kidney Disease
Stage, and Serum Uric Acid Level. The study elucidated association:
p –positive, n-negative, ?-non conclusive. Agreement with the
majority of current research: n- the study does not confirm the
majority of the previous reports, c- the study confirms the majority
of the previous reports.
Variable Variable
Elucidated
association
Agreement
with the
majority of
current
research
Body Mass Index Tobacco Smoking p n
Body Mass Index Alcohol Consumption n c
Body Mass Index Pregnancy Status n not comp
Body Mass Index Chemotherapy Status p c
Body Mass Index Breastfeeding ?
Body Mass Index Contraception use p c
Body Mass Index Total cholesterol Levels p c
Body Mass Index HDL cholesterol levels p c
Body Mass Index LDL cholesterol levels p c
Body Mass Index Triglyceride levels p c
Body Mass Index Kidney Disease Stage n n
Body Mass Index Serum uric acid level n n
95 | P a g e
Table 22. The Analysis of Associations Between Pregnancy Status
and Total Cholesterol Levels, HDL Cholesterol Levels, LDL
Cholesterol Levels, Triglyceride Levels. The study elucidated
association: p –positive, n-negative, ?-non conclusive. Agreement
with the majority of current research: n- the study does not confirm
the majority of the previous reports, c- the study confirms the
majority of the previous reports.
Pregnancy Status Total cholesterol Levels p c
Pregnancy Status HDL cholesterol levels p c
Pregnancy Status LDL cholesterol levels n c
Pregnancy Status Triglyceride levels p c
Table 23. The Analysis of Associations Between Breastfeeding
Status and Total Cholesterol Levels, HDL Cholesterol Levels, LDL
Cholesterol Levels, Triglyceride Levels. The study elucidated
association: p –positive, n-negative, ?-non conclusive. Agreement
with the majority of current research: n- the study does not confirm
the majority of the previous reports, c- the study confirms the
majority of the previous reports.
Breastfeeding Total cholesterol Levels 0 n
Breastfeeding HDL cholesterol levels p n
Breastfeeding LDL cholesterol levels 0 n
Breastfeeding Triglyceride levels 0 n
Table 24. The Analysis of Associations Between Tobacco Smoking
Status and Total Cholesterol Levels, HDL Cholesterol Levels, LDL
Cholesterol Levels, Triglyceride Levels. The study elucidated
association: p –positive, n-negative, ?-non conclusive. Agreement
with the majority of current research: n- the study does not confirm
the majority of the previous reports, c- the study confirms the
majority of the previous reports.
Tobacco Smoking Total cholesterol Levels 0 n
Tobacco Smoking HDL cholesterol levels n c
Tobacco Smoking LDL cholesterol levels p c
Tobacco Smoking Triglyceride levels p c
96 | P a g e
Table 25. The Analysis of Associations Between Alcohol
Consumption Status and Total Cholesterol Levels, HDL Cholesterol
Levels, LDL Cholesterol Levels, Triglyceride Levels. The study
elucidated association: p –positive, n-negative, ?-non conclusive.
Agreement with the majority of current research: n- the study does
not confirm the majority of the previous reports, c- the study
confirms the majority of the previous reports.
Alcohol Consumption Total cholesterol Levels p c
Alcohol Consumption HDL cholesterol levels p c
Alcohol Consumption LDL cholesterol levels ?
Alcohol Consumption Triglyceride levels p c
Table 26. The Analysis of Associations Between Chemotherapy
Status and Total Cholesterol Levels, HDL Cholesterol Levels, LDL
Cholesterol Levels, Triglyceride Levels. The study elucidated
association: p –positive, n-negative, ?-non conclusive. Agreement
with the majority of current research: n- the study does not confirm
the majority of the previous reports, c- the study confirms the
majority of the previous reports.
Chemotherapy Status Total cholesterol Levels 0 n
Chemotherapy Status HDL cholesterol levels 0 n
Chemotherapy Status LDL cholesterol levels 0 n
Chemotherapy Status Triglyceride levels 0 c
Table 27. The Analysis of Associations Between Contraception Use
and Total Cholesterol Levels, HDL Cholesterol Levels, LDL
Cholesterol Levels, Triglyceride Levels. The study elucidated
association: p –positive, n-negative, ?-non conclusive. Agreement
with the majority of current research: n- the study does not confirm
the majority of the previous reports, c- the study confirms the
majority of the previous reports.
Contraception Use Total cholesterol Levels n c
Contraception Use HDL cholesterol levels n c
Contraception Use LDL cholesterol levels p c
Contraception Use Triglyceride levels 0 c
97 | P a g e
Table 28. The Analysis of Associations Between Kidney Disease
Stage and Total Cholesterol Levels, HDL Cholesterol Levels, LDL
Cholesterol Levels, Triglyceride Levels. The study elucidated
association: p –positive, n-negative, ?-non conclusive. Agreement
with the majority of current research: n- the study does not confirm
the majority of the previous reports, c- the study confirms the
majority of the previous reports.
Kidney Disease Stage Total cholesterol Levels 0 c
Kidney Disease Stage HDL cholesterol levels n c
Kidney Disease Stage LDL cholesterol levels n c
Kidney Disease Stage Triglyceride levels ?
Table 29. The Analysis of Associations Between Serum Uric Acid
Level and Total Cholesterol Levels, HDL Cholesterol Levels, LDL
Cholesterol Levels, Triglyceride Levels. The study elucidated
association: p –positive, n-negative, ?-non conclusive. Agreement
with the majority of current research: n- the study does not confirm
the majority of the previous reports, c- the study confirms the
majority of the previous reports.
Serum Uric Acid Level Total cholesterol Levels ?
Serum Uric Acid Level HDL cholesterol levels n c
Serum Uric Acid Level LDL cholesterol levels ?
Serum Uric Acid Level Triglyceride levels n c
98 | P a g e
Table 30. The Analysis of Associations Between Hypertension
Status and Total Cholesterol Levels, HDL Cholesterol Levels, LDL
Cholesterol Levels, Triglyceride Levels. The study elucidated
association: p –positive, n-negative, ?-non conclusive. Agreement
with the majority of current research: n- the study does not confirm
the majority of the previous reports, c- the study confirms the
majority of the previous reports.
Hypertension Status Total cholesterol Levels p c
Hypertension Status HDL cholesterol levels ?
Hypertension Status LDL cholesterol levels p c
Hypertension Status Triglyceride levels p c
Hypertension Status Kidney Disease Stage p c
Hypertension Status Serum Uric Acid Level p c
The analysis of Tables 21-30 reveals that our observations in majority
of cases supports previously observed relation. There are, however, a few
cases in which we were not able to obtain conclusive results or the
observed association differs from some of the reported in current
literature on the subject. We have to stress that we compared our data to
the majority of the reports and in many cases there are the reports
contradicting those to which we are referring to in above presented table.
We also have to indicate that the majority of the observed associations are,
from statistical point of view, week and thus are more indicative of trends.
In the appendix to this study we attached the list of all the original
computations including contingency tables, tests for associations and the
analysis of the strength of association. If the reader will find such a need as
to verify his hers analysis against our data analysis we hope he/she will
find the additional material very useful.
99 | P a g e
Appendix
Output 1. Frequency Table of Body Mass Index Class (Normal
Class: BMI≤ 18.49; Underweight Class: BMI ≥ 18.50 and ≤ 24.99;
Overweight Class BMI≥ 25.0) by Tobacco Smoking Status (1 Smoking,
2-no Smoking).
BMI CLASS
SMOKING
Frequency
Row Pct
1 2 Total
UNDERWEIGHT
209
10.36
1808
89.64
2017
NORMAL
431
6.00
6750
94.00
7181
OVERWEIGHT
739
6.83
10085
93.17
10824
Total 1379 18643 20022
Output 2. Pearson Chi-Square Statistics of the Association Test
between BMI Class and Tobacco Smoking Status.
Statistic DF Value Prob
Chi-Square 2 46.8090 <.0001
Likelihood Ratio Chi-Square 2 42.4284 <.0001
Mantel-Haenszel Chi-Square 1 10.1962 0.0014
Phi Coefficient 0.0484
Contingency Coefficient 0.0483
Cramer's V 0.0484
100 | P a g e
Output 3. Cochran-Mantel-Haenszel Statistics for the Association
Test between BMI Class and Tobacco Smoking Status
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 10.1962 0.0014
2
Row Mean Scores
Differ
2 46.8066 <.0001
3 General Association 2 46.8066 <.0001
Output 4. Measures of the strength of association between BMI
classes and Tobacco Smoking Status.
Statistic Value
95%
Confidence Limits
Gamma 0.0509 0.0006 0.1011
Kendall's Tau-b 0.0141 0.0000 0.0281
Stuart's Tau-c 0.0076 -0.0000 0.0152
Somers' D C|R 0.0067 -0.0000 0.0134
Somers' D R|C 0.0296 0.0000 0.0592
Pearson Correlation 0.0226 0.0075 0.0377
Spearman Correlation 0.0146 -0.0000 0.0291
Lambda Asymmetric C|R 0.0000 0.0000 0.0000
Lambda Asymmetric R|C 0.0000 0.0000 0.0000
Lambda Symmetric 0.0000 0.0000 0.0000
Uncertainty Coefficient C|R 0.0042 0.0016 0.0069
Uncertainty Coefficient R|C 0.0011 0.0004 0.0019
Uncertainty Coefficient
Symmetric
0.0018 0.0007 0.0029
101 | P a g e
Output 5. Frequency Table of Body Mass Index Class (Normal
Class: BMI≤ 18.49; Underweight Class: BMI ≥ 18.50 and ≤ 24.99;
Overweight Class BMI≥ 25.0) by Alcohol Consumption Status (1 Drinking,
2-no Drinking).
BMI CLASS
Alcohol Consumption
(1-yes, 2-no) Total
Frequency
Row Pct
1 2
UNDERWEIGHT
125
6.20
1892
93.80
2017
NORMAL
1113
15.50
6068
84.50
7181
OVERWEIGHT
2076
19.18
8748
80.82
10824
Total 3314 16708 20022
Output 6. Pearson Chi-Square Statistics of the Association Test
Between BMI Class and Alcohol Consumption Status.
Statistic DF Value Prob
Chi-Square 2 216.4411 <.0001
Likelihood Ratio Chi-Square 2 254.8644 <.0001
Mantel-Haenszel Chi-Square 1 196.4525 <.0001
Phi Coefficient 0.1040
Contingency Coefficient 0.1034
Cramer's V 0.1040
102 | P a g e
Output 7 Cochran-Mantel-Haenszel Statistics for the Association
Test Between BMI Class and Alcohol Consumption Status.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 196.4525 <.0001
2 Row Mean Scores
Differ
2 216.4303 <.0001
3 General Association 2 216.4303 <.0001
Output 8. Measures of the Strength of Association Between BMI
Classes and Alcohol Consumption Status.
Statistic Value
95%
Confidence Limits
Gamma -0.2330 -0.2661 -0.1999
Kendall's Tau-b -0.0886 -0.1009 -0.0763
Stuart's Tau-c -0.0703 -0.0802 -0.0604
Somers' D C|R -0.0618 -0.0704 -0.0531
Somers' D R|C -0.1272 -0.1449 -0.1095
Pearson Correlation -0.0991 -0.1111 -0.0870
Spearman Correlation -0.0918 -0.1046 -0.0790
Lambda Asymmetric C|R 0.0000 0.0000 0.0000
Lambda Asymmetric R|C 0.0000 0.0000 0.0000
Lambda Symmetric 0.0000 0.0000 0.0000
Uncertainty Coefficient C|R 0.0142 0.0111 0.0173
Uncertainty Coefficient R|C 0.0068 0.0053 0.0083
Uncertainty Coefficient Symmetric 0.0092 0.0072 0.0112
103 | P a g e
Output 9. Frequency Table of Body Mass Index Class (Normal
Class: BMI≤ 18.49; Underweight Class: BMI ≥ 18.50 and ≤ 24.99;
Overweight Class BMI ≥ 25.0) by Pregnancy Status (1 - Drinking, 2no
Drinking).
BMI CLASS
Pregnancy Status
(1-yes, 2-no)
Total
Frequency
Row Pct
1 2
UNDERWEIGHT
18
0.89
1999
99.11
2017
NORMAL
197
2.74
6984
97.26
7181
OVERWEIGHT
397
3.67
10427
96.33
10824
Total 612 19410 20022
Output 10. Pearson Chi-Square Statistics of the Association Test
Between BMI Class and Drinking Status.
Statistic DF Value Prob
Chi-Square 2 47.9035 <.0001
Likelihood Ratio Chi-Square 2 59.2536 <.0001
Mantel-Haenszel Chi-Square 1 45.3716 <.0001
Phi Coefficient 0.0489
Contingency Coefficient 0.0489
Cramer's V 0.0489
104 | P a g e
Output 11. Cochran-Mantel-Haenszel Statistics for the Association
Test Between BMI Class and Pregnancy Status.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 45.3716 <.0001
2
Row Mean Scores
Differ
2 47.9011 <.0001
3 General Association 2 47.9011 <.0001
Output 12. Measures of the Strength of Association Between BMI
Classes and Pregnancy Status.
Statistic Value
95%
Confidence Limits
Gamma -0.2517 -0.3240 -0.1794
Kendall's Tau-b -0.0433 -0.0552 -0.0313
Stuart's Tau-c -0.0159 -0.0204 -0.0114
Somers' D C|R -0.0140 -0.0179 -0.0100
Somers' D R|C -0.1341 -0.1707 -0.0974
Pearson Correlation -0.0476 -0.0590 -0.0362
Spearman Correlation -0.0448 -0.0572 -0.0325
Lambda Asymmetric C|R 0.0000 0.0000 0.0000
Lambda Asymmetric R|C 0.0000 0.0000 0.0000
Lambda Symmetric 0.0000 0.0000 0.0000
Uncertainty Coefficient C|R 0.0108 0.0061 0.0155
Uncertainty Coefficient R|C 0.0016 0.0009 0.0023
Uncertainty Coefficient
Symmetric
0.0028 0.0016 0.0040
105 | P a g e
Output 13 Frequency Table of Body Mass Index Class (Normal
Class: BMI≤ 18.49; Underweight Class: BMI ≥ 18.50 and ≤ 24.99;
Overweight Class BMI≥ 25.0) by Chemotherapy Status (1 –
Currently Undergoing Chemotherapy, 2-no Chemotherapy).
BMICLASS
CHEMOTHERAPY
(1 - yes, 2- no)
Total
Frequency
Row Pct
1 2
UNDERWEIGHT
11
0.55
2006
99.45
2017
NORMAL
94
1.31
7087
98.69
7181
OVERWEIGHT
187
1.73
10637
98.27
10824
Total 292 19730 20022
Output 14. Pearson Chi-Square Statistics of the Association Test
Between BMI Class and Chemotherapy Status.
Statistic DF Value Prob
Chi-Square 2 18.2750 0.0001
Likelihood Ratio Chi-Square 2 21.6729 <.0001
Mantel-Haenszel Chi-Square 1 17.5509 <.0001
Phi Coefficient 0.0302
Contingency Coefficient 0.0302
Cramer's V 0.0302
106 | P a g e
Output 15. Cochran-Mantel-Haenszel Statistics for the Association
Test Between BMI Class and Chemotherapy Status.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 17.5509 <.0001
2 Row Mean Scores Differ 2 18.2741 0.0001
3 General Association 2 18.2741 0.0001
Output 16. Measures of the Strength of Association Between BMI
Classes and Chemotherapy Status.
Statistic Value
95%
Confidence Limits
Gamma -0.2251 -0.3300 -0.1202
Kendall's Tau-b -0.0271 -0.0392 -0.0150
Stuart's Tau-c -0.0069 -0.0101 -0.0038
Somers' D C|R -0.0061 -0.0089 -0.0033
Somers' D R|C -0.1205 -0.1740 -0.0670
Pearson Correlation -0.0296 -0.0414 -0.0179
Spearman Correlation -0.0281 -0.0406 -0.0155
Lambda Asymmetric C|R 0.0000 0.0000 0.0000
Lambda Asymmetric R|C 0.0000 0.0000 0.0000
Lambda Symmetric 0.0000 0.0000 0.0000
Uncertainty Coefficient C|R 0.0071 0.0018 0.0124
Uncertainty Coefficient R|C 0.0006 0.0001 0.0010
Uncertainty Coefficient Symmetric 0.0011 0.0003 0.0019
107 | P a g e
Output 17. Frequency Table of Body Mass Index Class (Normal
Class: BMI≤ 18.49; Underweight Class: BMI ≥ 18.50 and ≤ 24.99;
Overweight Class BMI≥ 25.0) by BreastFeeding Status (1 –
Currently Breastfeeding, 2-no Breastfeeding).
BMI CLASS
BREASTFEEEDING
(1- yes, 2-no)
Total
Frequency
Row Pct
1 2
UNDERWEIGHT
4
0.20
2013
99.80
2017
NORMAL
57
0.79
7124
99.21
7181
OVERWEIGHT
59
0.55
10765
99.45
10824
Total 120 19902 20022
Output 18. Pearson Chi-Square Statistics of the Association Test
Between BMI Class and Breastfeeding Status.
Statistic DF Value Prob
Chi-Square 2 10.5360 0.0052
Likelihood Ratio Chi-Square 2 12.0470 0.0024
Mantel-Haenszel Chi-Square 1 0.0919 0.7617
Phi Coefficient 0.0229
Contingency Coefficient 0.0229
Cramer's V 0.0229
108 | P a g e
Output 19. Cochran-Mantel-Haenszel Statistics for the Association
Test Between BMI Class and Breastfeeding Status.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 0.0919 0.7617
2
Row Mean Scores
Differ
2 10.5354 0.0052
3 General Association 2 10.5354 0.0052
Output 20. Measures of the Strength of Association Between BMI
Classes and Breastfeeding Status.
Statistic Value
95%
Confidence Limits
Gamma 0.0234 -0.1269 0.1737
Kendall's Tau-b 0.0019 -0.0104 0.0142
Stuart's Tau-c 0.0003 -0.0017 0.0023
Somers' D C|R 0.0003 -0.0015 0.0020
Somers' D R|C 0.0131 -0.0716 0.0978
Pearson Correlation -0.0021 -0.0138 0.0095
Spearman Correlation 0.0020 -0.0107 0.0147
Lambda Asymmetric C|R 0.0000 0.0000 0.0000
Lambda Asymmetric R|C 0.0000 0.0000 0.0000
Lambda Symmetric 0.0000 0.0000 0.0000
Uncertainty Coefficient C|R 0.0082 0.0000 0.0165
Uncertainty Coefficient R|C 0.0003 0.0000 0.0007
Uncertainty Coefficient
Symmetric
0.0006 0.0000 0.0013
109 | P a g e
Output 21. Frequency Table of Body Mass Index Class (Normal
Class: BMI≤ 18.49; Underweight Class: BMI ≥ 18.50 and ≤ 24.99;
Overweight Class BMI≥ 25.0) by Contraception Use (1 – Currently
Breastfeeding, 2-no Breastfeeding).
BMI CLASS
CONTRACEPTION
(1- yes, 2-no)
Total
Frequency
Row Pct
1 2
UNDERWEIGHT
71
3.52
1946
96.48
2017
NORMAL
792
11.03
6389
88.97
7181
OVERWEIGHT
584
5.40
10240
94.60
10824
Total 1447 18575 20022
Output 22. Pearson Chi-Square Statistics of the Association Test
Between BMI Class and Contraception Use.
Statistic DF Value Prob
Chi-Square 2 250.3239 <.0001
Likelihood Ratio Chi-Square 2 244.2185 <.0001
Mantel-Haenszel Chi-Square 1 25.3619 <.0001
Phi Coefficient 0.1118
Contingency Coefficient 0.1111
Cramer's V 0.1118
110 | P a g e
Output 23. Cochran-Mantel-Haenszel Statistics for the Association
Test Between BMI Class and Contraception Use.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 25.3619 <.0001
2
Row Mean Scores
Differ
2 250.3114 <.0001
3 General Association 2 250.3114 <.0001
Output 24. Measures of the Strength of Association Between BMI
Classes and Contraception Use.
Statistic Value
95%
Confidence Limits
Gamma 0.1836 0.1418 0.2253
Kendall's Tau-b 0.0521 0.0396 0.0645
Stuart's Tau-c 0.0288 0.0218 0.0357
Somers' D C|R 0.0253 0.0191 0.0314
Somers' D R|C 0.1072 0.0818 0.1326
Pearson Correlation 0.0356 0.0235 0.0477
Spearman Correlation 0.0539 0.0411 0.0668
Lambda Asymmetric C|R 0.0000 0.0000 0.0000
Lambda Asymmetric R|C 0.0226 0.0148 0.0304
Lambda Symmetric 0.0195 0.0128 0.0263
Uncertainty Coefficient C|R 0.0235 0.0177 0.0293
Uncertainty Coefficient R|C 0.0065 0.0049 0.0082
Uncertainty Coefficient
Symmetric
0.0102 0.0077 0.0128
111 | P a g e
Output 25 Frequency Table of Body Mass Index Class (Normal
Class: BMI≤ 18.49; Underweight Class: BMI ≥ 18.50 and ≤ 24.99;
Overweight Class BMI≥ 25.0) by Total Cholesterol Category.
Desirable <200 mg/dL ≤ Borderline High < 240 mg/dL ≤ High.
BMI CLASS Total Cholesterol Classification
TotalFrequency
Row Pct
Desirable
Borderline
High
High
UNDERWEIGHT
1781
88.30
173
8.58
63
3.12
2017
NORMAL
4894
68.15
1445
20.12
842
11.73
7181
OVERWEIGHT
5630
52.01
3094
28.58
2100
19.40
10824
Total 12305 4712 3005 20022
Output 26. Pearson Chi-Square Statistics of the Association Test
Between BMI Class and Total Cholesterol Category.
Statistic DF Value Prob
Chi-Square 4 1171.0293 <.0001
Likelihood Ratio Chi-Square 4 1290.3488 <.0001
Mantel-Haenszel Chi-Square 1 1054.9248 <.0001
Phi Coefficient 0.2418
Contingency Coefficient 0.2351
Cramer's V 0.1710
112 | P a g e
Output 27. Cochran-Mantel-Haenszel Statistics for the Association
Test Between BMI Class and Total Cholesterol Category.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 1054.9248 <.0001
2
Row Mean Scores
Differ
2 1058.7995 <.0001
3 General Association 4 1170.9708 <.0001
Output 28. Measures of the Strength of Association Between BMI
Classes and Total Cholesterol Category.
Statistic Value
95%
Confidence Limits
Gamma 0.3970 0.3759 0.4182
Kendall's Tau-b 0.2155 0.2038 0.2271
Stuart's Tau-c 0.1799 0.1700 0.1898
Somers' D C|R 0.2108 0.1993 0.2222
Somers' D R|C 0.2203 0.2083 0.2323
Pearson Correlation 0.2295 0.2179 0.2411
Spearman Correlation 0.2326 0.2200 0.2452
Lambda Asymmetric C|R 0.0000 0.0000 0.0000
Lambda Asymmetric R|C 0.0000 0.0000 0.0000
Lambda Symmetric 0.0000 0.0000 0.0000
Uncertainty Coefficient C|R 0.0349 0.0314 0.0384
Uncertainty Coefficient R|C 0.0346 0.0312 0.0380
Uncertainty Coefficient
Symmetric
0.0347 0.0313 0.0382
113 | P a g e
Output 29. Frequency Table of Body Mass Index Class (Normal
Class: BMI≤ 18.49; Underweight Class: BMI ≥ 18.50 and ≤ 24.99;
Overweight Class BMI≥ 25.0) by HDL Cholesterol Category. Low
< 40 mg/dL ≤ Normal < 60 mg/dL ≤ High.
BMI CLASS HDL Cholesterol Classification
TotalFrequency
Row Pct
Low Normal High
UNDERWEIGHT
1149
56.97
333
16.51
535
26.52
2017
NORMAL
898
12.51
2710
37.74
3573
49.76
7181
OVERWEIGHT
2115
19.54
4957
45.80
3752
34.66
10824
Total 4162 8000 7860 20022
Output 30. Pearson Chi-Square Statistics of the Association Test
Between BMI Class and HDL Cholesterol Level.
Statistic DF Value Prob
Chi-Square 4 2236.9446 <.0001
Likelihood Ratio Chi-Square 4 1937.0700 <.0001
Mantel-Haenszel Chi-Square 1 76.7627 <.0001
Phi Coefficient 0.3343
Contingency Coefficient 0.3170
Cramer's V 0.2364
114 | P a g e
Output 31. Cochran-Mantel-Haenszel Statistics for the Association
Test Between BMI Class and HDL Cholesterol Level.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 76.7627 <.0001
2
Row Mean Scores
Differ
2 1320.6266 <.0001
3 General Association 4 2236.8328 <.0001
Output 32. Measures of the Strength of Association Between BMI
Classes and HDL Cholesterol Level.
Statistic Value
95%
Confidence Limits
Gamma -0.0008 -0.0231 0.0214
Kendall's Tau-b -0.0005 -0.0144 0.0133
Stuart's Tau-c -0.0005 -0.0130 0.0121
Somers' D C|R -0.0006 -0.0153 0.0142
Somers' D R|C -0.0005 -0.0135 0.0125
Pearson Correlation 0.0619 0.0464 0.0774
Spearman Correlation 0.0030 -0.0120 0.0180
Lambda Asymmetric C|R 0.1397 0.1263 0.1530
Lambda Asymmetric R|C 0.0000 0.0000 0.0000
Lambda Symmetric 0.0791 0.0714 0.0868
Uncertainty Coefficient C|R 0.0456 0.0415 0.0498
Uncertainty Coefficient R|C 0.0519 0.0473 0.0566
Uncertainty Coefficient
Symmetric
0.0486 0.0442 0.0530
115 | P a g e
Output 33. Frequency Table of Body Mass Index Class (Normal
Class: BMI≤ 18.49; Underweight Class: BMI≥ 18.50 and ≤ 24.99;
Overweight Class BMI≥ 25.0) by LDL Cholesterol Category.
Optimal < 100 mg/dL≤ Near Optimal < 130 mg/dL ≤ Borderline
High < 160 ≤ High < 190 ≤ Very High.
BMI CLASS LDL-C Classification
TotalFrequency
Row Pct
optimal
near
optimal
borderline
high
high
very
high
UNDERWEIGHT
1792
88.84
139
6.89
54
2.68
24
1.19
8
0.40
2017
NORMAL
5251
73.12
978
13.62
561
7.81
253
3.52
138
1.92
7181
OVERWEIGHT
7285
67.30
1357
12.54
1202
11.10
605
5.59
375
3.46
10824
Total 14328 2474 1817 882 521 20022
Output 34. Pearson Chi-Square Statistics of the Association Test
Between BMI Class and LDL Cholesterol Level.
Statistic DF Value Prob
Chi-Square 4 2236.9446 <.0001
Likelihood Ratio Chi-Square 4 1937.0700 <.0001
Mantel-Haenszel Chi-Square 1 76.7627 <.0001
Phi Coefficient 0.3343
Contingency Coefficient 0.3170
Cramer's V 0.2364
116 | P a g e
Output 35. Cochran-Mantel-Haenszel Statistics for the Association
Test Between BMI Class and LDL Cholesterol Level.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 76.7627 <.0001
2
Row Mean Scores
Differ
2 1320.6266 <.0001
3 General Association 4 2236.8328 <.0001
Output 36. Measures of the Strength of Association Between BMI
Classes and LDL Cholesterol Level.
Statistic
Value
95%
Confidence Limits
Gamma 0.2505 0.2262 0.2748
Kendall's Tau-b 0.1236 0.1118 0.1353
Stuart's Tau-c 0.0950 0.0858 0.1042
Somers' D C|R 0.1113 0.1006 0.1220
Somers' D R|C 0.1371 0.1241 0.1502
Pearson Correlation 0.1456 0.1342 0.1571
Spearman Correlation 0.1336 0.1208 0.1465
Lambda Asymmetric C|R 0.0000 0.0000 0.0000
Lambda Asymmetric R|C 0.0000 0.0000 0.0000
Lambda Symmetric 0.0000 0.0000 0.0000
Uncertainty Coefficient C|R 0.0151 0.0129 0.0173
Uncertainty Coefficient R|C 0.0154 0.0131 0.0177
Uncertainty Coefficient
Symmetric
0.0153 0.0130 0.0175
117 | P a g e
Output 37. Frequency Table of Body Mass Index Class (Normal
Class: BMI≤ 18.49; Underweight Class: BMI ≥ 18.50 and ≤ 24.99;
Overweight Class BMI≥ 25.0) by Triglyceride Category. Normal
<150 mg/dL ≤ High < 200 mg/dL ≤ Borderline High < 500 mg/dL
≤ Very High.
BMI CLASS TRIGLYCERIDE CATEGORY
TotalFrequency
Row Pct
normal high
borderline
high
very high
UNDERWEIGHT
1958
97.07
22
1.09
35
1.74
2
0.10
2017
NORMAL
6464
90.02
309
4.30
387
5.39
21
0.29
7181
OVERWEIGHT
8190
75.67
1328
12.27
1207
11.15
99
0.91
10824
Total 16612 1659 1629 122 20022
Output 38. Pearson Chi-Square Statistics of the Association Test
Between BMI Class and Triglyceride Category.
Statistic DF Value Prob
Chi-Square 6 957.8060 <.0001
Likelihood Ratio Chi-Square 6 1084.1035 <.0001
Mantel-Haenszel Chi-Square 1 847.9879 <.0001
Phi Coefficient 0.2187
Contingency Coefficient 0.2137
Cramer's V 0.1547
118 | P a g e
Output 39. Cochran-Mantel-Haenszel Statistics for the Association
Test Between BMI Class and Triglyceride Category.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 847.9879 <.0001
2
Row Mean Scores
Differ
2 884.5801 <.0001
3 General Association 6 957.7581 <.0001
Output 40. Measures of the Strength of Association Between BMI
Classes and Triglyceride Category.
Statistic Value
95%
Confidence Limits
Gamma 0.5417 0.5136 0.5697
Kendall's Tau-b 0.2063 0.1956 0.2170
Stuart's Tau-c 0.1274 0.1202 0.1346
Somers' D C|R 0.1493 0.1409 0.1577
Somers' D R|C 0.2850 0.2705 0.2995
Pearson Correlation 0.2058 0.1957 0.2159
Spearman Correlation 0.2184 0.2071 0.2298
Lambda Asymmetric C|R 0.0000 0.0000 0.0000
Lambda Asymmetric R|C 0.0000 0.0000 0.0000
Lambda Symmetric 0.0000 0.0000 0.0000
Uncertainty Coefficient C|R 0.0454 0.0407 0.0501
Uncertainty Coefficient R|C 0.0291 0.0260 0.0322
Uncertainty Coefficient
Symmetric
0.0354 0.0317 0.0392
119 | P a g e
Output 41. Frequency Table of Body Mass Index Class (Normal
Class: BMI≤ 18.49; Underweight Class: BMI ≥ 18.50 and ≤ 24.99;
Overweight Class BMI ≥ 25.0) by Stages of Kidney Chronic Disease.
Stage 1 ≥ 90 > Stage 2 ≥ 60 > Stage 3 ≥30 Stage 4 ≥15 > Stage 5. The
values are given in ml per minute per 1.73 m2.
BMI CLASS Stages of Chronic Kidney Disease
TotalFrequency
Row Pct
1 2 3 4 5
UNDERWEIGHT
534
26.47
256
12.69
77
3.82
13
0.64
1137
56.37
2017
NORMAL
2861
39.84
2529
35.22
533
7.42
61
0.85
1197
16.67
7181
OVERWEIGHT
3646
33.68
3909
36.11
1105
10.21
142
1.31
2022
18.68
10824
Total 7041 6694 1715 216 4356 20022
Output 42. Pearson Chi-Square Statistics of the Association Test
Between BMI Class and Stage of Chronic Kidney Disease.
Statistic DF Value Prob
Chi-Square 8 1738.3027 <.0001
Likelihood Ratio Chi-Square 8 1501.9655 <.0001
Mantel-Haenszel Chi-Square 1 375.6623 <.0001
Phi Coefficient 0.2947
Contingency Coefficient 0.2826
Cramer's V 0.2084
120 | P a g e
Output 43. Cochran-Mantel-Haenszel Statistics for the Association
Test Between BMI Class and Stage of Chronic Kidney Disease.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 375.6623 <.0001
2
Row Mean Scores
Differ
2 1176.6294 <.0001
3 General Association 8 1738.2159 <.0001
Output 44. Measures of the Strength of Association Between BMI
Classes and Stage of Chronic Kidney Disease.
Statistic Value
95%
Confidence Limits
Gamma -0.0752 -0.0958 -0.0547
Kendall's Tau-b -0.0483 -0.0616 -0.0350
Stuart's Tau-c -0.0461 -0.0588 -0.0334
Somers' D C|R -0.0540 -0.0688 -0.0392
Somers' D R|C -0.0433 -0.0552 -0.0313
Pearson Correlation -0.1370 -0.1525 -0.1214
Spearman Correlation -0.0562 -0.0709 -0.0415
Lambda Asymmetric C|R 0.0667 0.0527 0.0807
Lambda Asymmetric R|C 0.0000 0.0000 0.0000
Lambda Symmetric 0.0390 0.0307 0.0474
Uncertainty Coefficient C|R 0.0283 0.0253 0.0313
Uncertainty Coefficient R|C 0.0403 0.0361 0.0444
Uncertainty Coefficient
Symmetric
0.0332 0.0298 0.0367
121 | P a g e
Output 45. Frequency Table of Body Mass Index Class (Normal
Class: BMI≤ 18.49; Underweight Class: BMI ≥ 18.50 and ≤ 24.99;
Overweight Class BMI ≥ 25.0) by Serum Uric Acid Tierces.
BMIC LASS Serum Uric Acid Trit
TotalFrequency
Row Pct
1 2 3
UNDERWEIGHT
697
34.56
242
12.00
1078
53.45
2017
NORMAL
4845
67.47
1754
24.43
582
8.10
7181
OVERWEIGHT
4776
44.12
5186
47.91
862
7.96
10824
Total 10318 7182 2522 20022
Output 46. Pearson Chi-Square Statistics of the Association Test
Between BMI Class and Serum Uric Acid Tierces.
Statistic DF Value Prob
Chi-Square 4 4573.6644 <.0001
Likelihood Ratio Chi-Square 4 3507.5734 <.0001
Mantel-Haenszel Chi-Square 1 170.7060 <.0001
Phi Coefficient 0.4779
Contingency Coefficient 0.4312
Cramer's V 0.3380
122 | P a g e
Output 47. Cochran-Mantel-Haenszel Statistics for the Association
Test Between BMI Class and Serum Uric Acid Tierces.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 170.7060 <.0001
2
Row Mean Scores
Differ
2 2006.2417 <.0001
3 General Association 4 4573.4360 <.0001
Output 48. Measures of the Strength of Association Between BMI
Classes and Serum Uric Acid Tierces.
Statistic Value
95%
Confidence Limits
Gamma 0.0372 0.0134 0.0609
Kendall's Tau-b 0.0228 0.0083 0.0374
Stuart's Tau-c 0.0198 0.0072 0.0324
Somers' D C|R 0.0233 0.0084 0.0381
Somers' D R|C 0.0224 0.0081 0.0367
Pearson Correlation -0.0923 -0.1090 -0.0757
Spearman Correlation 0.0169 0.0012 0.0326
Lambda Asymmetric C|R 0.0815 0.0605 0.1025
Lambda Asymmetric R|C 0.0310 0.0084 0.0535
Lambda Symmetric 0.0569 0.0379 0.0759
Uncertainty Coefficient C|R 0.0903 0.0840 0.0965
Uncertainty Coefficient R|C 0.0940 0.0876 0.1005
Uncertainty Coefficient
Symmetric
0.0921 0.0858 0.0984
123 | P a g e
Output 49. Frequency Table of Pregnancy Status (1 - Pregnant, 2 –
No Pregnant) by Total Cholesterol Category. Desirable <200 mg/dL
≤ Borderline High < 240 mg/dL ≤ High.
PREGNANCY
STATUS
1 - pregnant,
2- no pregnant
Total Cholesterol Classification
Total
Frequency
Row Pct
Desirable Borderline High
1 262
42.81
178
29.08
172
28.10
612
2 12043
62.05
4534
23.36
2833
14.60
19410
Total 12305 4712 3005 20022
Output 50. Pearson Chi-Square Statistics of the Association Test
Between Pregnancy Status and Total Cholesterol Classes.
Statistic DF Value Prob
Chi-Square 2 116.1227 <.0001
Likelihood Ratio Chi-Square 2 105.2958 <.0001
Mantel-Haenszel Chi-Square 1 115.8799 <.0001
Phi Coefficient 0.0762
Contingency Coefficient 0.0759
Cramer's V 0.0762
124 | P a g e
Output 51. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Pregnancy Status and Total Cholesterol Classes.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 115.8799 <.0001
2
Row Mean Scores
Differ
1 115.8799 <.0001
3 General Association 2 116.1169 <.0001
Output 52. Measures of the Strength of Association Between
Pregnancy Status and Total Cholesterol Levels.
Statistic Value
95%
Confidence Limits
Gamma -0.3446 -0.4041 -0.2851
Kendall's Tau-b -0.0711 -0.0855 -0.0567
Stuart's Tau-c -0.0255 -0.0310 -0.0201
Somers' D C|R -0.2155 -0.2584 -0.1727
Somers' D R|C -0.0235 -0.0285 -0.0185
Pearson Correlation -0.0761 -0.0918 -0.0604
Spearman Correlation -0.0741 -0.0891 -0.0591
Lambda Asymmetric C|R 0.0000 0.0000 0.0000
Lambda Asymmetric R|C 0.0000 0.0000 0.0000
Lambda Symmetric 0.0000 0.0000 0.0000
Uncertainty Coefficient C|R 0.0028 0.0017 0.0040
Uncertainty Coefficient R|C 0.0192 0.0117 0.0267
Uncertainty Coefficient
Symmetric
0.0050 0.0030 0.0069
125 | P a g e
Output 53. Frequency Table of Pregnancy Status (1 - Pregnant, 2 –
No Pregnant) by HDL Cholesterol Category. Low < 40 mg/dL≤
Normal < 60 mg/dL ≤ High.
PREGNANCY STATUS
1 - pregnant,
2- no pregnant
HDL Cholesterol Classification
Total
Frequency
Row Pct
Low Normal High
1 62
10.13
158
25.82
392
64.05
612
2 4100
21.12
7842
40.40
7468
38.48
19410
Total 4162 8000 7860 20022
Output 54. Pearson Chi-Square Statistics of the Association Test
Between Pregnancy Status and HDL Cholesterol Classes.
Statistic DF Value Prob
Chi-Square 2 164.9429 <.0001
Likelihood Ratio Chi-Square 2 161.7407 <.0001
Mantel-Haenszel Chi-Square 1 140.0952 <.0001
Phi Coefficient 0.0908
Contingency Coefficient 0.0904
Cramer's V 0.0908
126 | P a g e
Output 55. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Pregnancy Status and HDL Cholesterol Classes.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 140.0952 <.0001
2
Row Mean Scores
Differ
1 140.0952 <.0001
3 General Association 2 164.9346 <.0001
Output 56. Measures of the Strength of Association Between
Pregnancy Status and HDL Cholesterol Levels.
Statistic Value
95%
Confidence Limits
Gamma -0.4290 -0.4935 -0.3646
Kendall's Tau-b -0.0818 -0.0942 -0.0694
Stuart's Tau-c -0.0319 -0.0372 -0.0267
Somers' D C|R -0.2694 -0.3089 -0.2298
Somers' D R|C -0.0248 -0.0289 -0.0207
Pearson Correlation -0.0837 -0.0964 -0.0709
Spearman Correlation -0.0863 -0.0993 -0.0732
Lambda Asymmetric C|R 0.0195 0.0157 0.0233
Lambda Asymmetric R|C 0.0000 0.0000 0.0000
Lambda Symmetric 0.0185 0.0149 0.0221
Uncertainty Coefficient C|R 0.0038 0.0026 0.0050
Uncertainty Coefficient R|C 0.0295 0.0207 0.0384
Uncertainty Coefficient
Symmetric
0.0067 0.0047 0.0088
127 | P a g e
Output 57. Frequency Table of Pregnancy Status (1 – Pregnant, 2no
Pregnant) by LDL Cholesterol Category. Optimal < 100 mg/dL
≤ Near Optimal < 130 mg/dL ≤ Borderline High < 160 ≤ High <
190 ≤ Very High.
PREGNANCY
STATUS
1 - pregnant,
2- no pregnant
LDL Cholesterol Classification
Total
Frequency
Row Pct
optimal
near
optimal
borderline
high
high very high
1 422
68.95
73
11.93
52
8.50
37
6.05
28
4.58
612
2 13906
71.64
2401
12.37
1765
9.09
845
4.35
493
2.54
19410
Total 14328 2474 1817 882 521 20022
Output 58. Pearson Chi-Square Statistics of the Association Test
Between Pregnancy Status and LDL Cholesterol Classes.
Statistic DF Value Prob
Chi-Square 4 14.2274 0.0066
Likelihood Ratio Chi-Square 4 12.1460 0.0163
Mantel-Haenszel Chi-Square 1 7.9094 0.0049
Phi Coefficient 0.0267
Contingency Coefficient 0.0266
Cramer's V 0.0267
128 | P a g e
Output 59. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Pregnancy Status and HDL Cholesterol Classes.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 7.9094 0.0049
2
Row Mean Scores
Differ
1 7.9094 0.0049
3 General Association 4 14.2267 0.0066
Output 60. Measures of the Strength of Association Between
Pregnancy Status and LDL Cholesterol Levels.
Statistic Value
95%
Confidence Limits
Gamma -0.0745 -0.1521 0.0032
Kendall's Tau-b -0.0128 -0.0267 0.0011
Stuart's Tau-c -0.0042 -0.0089 0.0004
Somers' D C|R -0.0357 -0.0746 0.0032
Somers' D R|C -0.0046 -0.0096 0.0004
Pearson Correlation -0.0199 -0.0356 -0.0041
Spearman Correlation -0.0134 -0.0280 0.0012
Lambda Asymmetric C|R 0.0000 0.0000 0.0000
Lambda Asymmetric R|C 0.0000 0.0000 0.0000
Lambda Symmetric 0.0000 0.0000 0.0000
Uncertainty Coefficient C|R 0.0003 0.0000 0.0007
Uncertainty Coefficient R|C 0.0022 0.0000 0.0049
Uncertainty Coefficient
Symmetric
0.0006 0.0000 0.0012
129 | P a g e
Output 61. Frequency Table of Pregnancy Status (1 – Pregnant, 2no
Pregnant) by Triglyceride Category. Normal <150 mg/dL≤
High < 200 mg/dL ≤ Borderline High < 500 mg/dL ≤ Very High.
PREGNANCY
STATUS
1 - pregnant,
2- no pregnant
Triglyceride Classidication
Total
Frequency
Row Pct
normal
borderline
high
high very high
1 400
65.36
83
13.56
127
20.75
2
0.33
612
2 16212
83.52
1546
7.96
1532
7.89
120
0.62
19410
Total 16612 1629 1659 122 20022
Output 62. Pearson Chi-Square Statistics of the Association Test
Between Pregnancy Status and Triglyceride Classes.
Statistic DF Value Prob
Chi-Square 3 165.6601 <.0001
Likelihood Ratio Chi-Square 3 129.7961 <.0001
Mantel-Haenszel Chi-Square 1 138.3938 <.0001
Phi Coefficient 0.0910
Contingency Coefficient 0.0906
Cramer's V 0.0910
130 | P a g e
Output 63. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Pregnancy Status and Triglyceride Classes.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 138.3938 <.0001
2
Row Mean Scores
Differ
1 138.3938 <.0001
3 General Association 3 165.6518 <.0001
Output 64. Measures of the Strength of Association Between
Pregnancy Status and Triglyceride Levels.
Statistic Value
95%
Confidence Limits
Gamma -0.4354 -0.4980 -0.3728
Kendall's Tau-b -0.0829 -0.1003 -0.0654
Stuart's Tau-c -0.0220 -0.0269 -0.0172
Somers' D C|R -0.1859 -0.2245 -0.1472
Somers' D R|C -0.0370 -0.0451 -0.0288
Pearson Correlation -0.0831 -0.1013 -0.0649
Spearman Correlation -0.0847 -0.1026 -0.0669
Lambda Asymmetric C|R 0.0000 0.0000 0.0000
Lambda Asymmetric R|C 0.0000 0.0000 0.0000
Lambda Symmetric 0.0000 0.0000 0.0000
Uncertainty Coefficient C|R 0.0054 0.0034 0.0075
Uncertainty Coefficient R|C 0.0237 0.0149 0.0325
Uncertainty Coefficient
Symmetric
0.0088 0.0055 0.0122
131 | P a g e
Output 65. Frequency Table of Breasfeeding Status (1 - Yes, 2 – No
Pregnant) by Total Cholesterol Category. Desirable <200 mg/dL≤
Borderline High < 240 mg/dL ≤ High.
Breastfeeding Status
1- yes, 2-no
Total Cholesterol Classification
Total
Desirable Borderline High
1
79
65.83
32
26.67
9
7.50
120
2
12226
61.43
4680
23.52
2996
15.05
19902
Total 12305 4712 3005 20022
Output 66. Pearson Chi-Square Statistics of the Association Test
Between Breastfeeding Status and Total Cholesterol Classes.
Statistic DF Value Prob
Chi-Square 2 5.4143 0.0667
Likelihood Ratio Chi-Square 2 6.4108 0.0405
Mantel-Haenszel Chi-Square 1 3.1062 0.0780
Phi Coefficient 0.0164
Contingency Coefficient 0.0164
Cramer's V 0.0164
132 | P a g e
Output 67. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Breastfeeding Status and Total Cholesterol Classes.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 3.1062 0.0780
2
Row Mean Scores
Differ
1 3.1062 0.0780
3 General Association 2 5.4141 0.0667
Output 68. Frequency Table of Breastfeeding Status (1 - yes, 2 – no)
by HDL Cholesterol Category. Low < 40 mg/dL≤ Normal < 60
mg/dL ≤ High.
Breastfeeding Status
1 - yes, 2- no
HDL Cholesterol Classification
Total
Frequency
Row Pct
Low Normal High
1 19
15.83
77
64.17
24
20.00
120
2 4143
20.82
7923
39.81
7836
39.37
19902
Total 4162 8000 7860 20022
133 | P a g e
Output 69. Pearson Chi-Square Statistics of the Association Test
Between Breastfeeding Status and HDL Cholesterol Classes.
Statistic DF Value Prob
Chi-Square 2 30.5390 <.0001
Likelihood Ratio Chi-Square 2 30.4184 <.0001
Mantel-Haenszel Chi-Square 1 4.3607 0.0368
Phi Coefficient 0.0391
Contingency Coefficient 0.0390
Cramer's V 0.0391
Output 70. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Breastfeeding Status and HDL Cholesterol Classes.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 4.3607 0.0368
2
Row Mean Scores
Differ
1 4.3607 0.0368
3 General Association 2 30.5375 <.0001
134 | P a g e
Output 71. Measures of the Strength of Association Between
Breastfeeding Status and HDL Cholesterol.
Statistic Value
95%
Confidence Limits
Gamma 0.1947 0.0765 0.3128
Kendall's Tau-b 0.0168 0.0063 0.0273
Stuart's Tau-c 0.0029 0.0010 0.0048
Somers' D C|R 0.1232 0.0469 0.1995
Somers' D R|C 0.0023 0.0008 0.0038
Pearson Correlation 0.0148 0.0037 0.0258
Spearman Correlation 0.0177 0.0066 0.0288
Lambda Asymmetric C|R 0.0000 0.0000 0.0000
Lambda Asymmetric R|C 0.0000 0.0000 0.0000
Lambda Symmetric 0.0000 0.0000 0.0000
Uncertainty Coefficient C|R 0.0007 0.0002 0.0012
Uncertainty Coefficient R|C 0.0207 0.0066 0.0348
Uncertainty Coefficient
Symmetric
0.0014 0.0004 0.0024
135 | P a g e
Output 72. Frequency Table of Breastfeeding Status (1 – yes, 2- no)
by LDL Cholesterol Category. Optimal < 100 mg/dL≤ Near
Optimal < 130 mg/dL≤ Borderline High < 160 ≤ High < 190 ≤
Very High.
Breastfeeding
1- yes, 2-no
LDL Cholesterol Classification
Total
Frequency
Row Pct
optimal
near
optimal
borderline
high
high very high
1
75
62.50
23
19.17
16
13.33
5
4.17
1
0.83
120
2
14253
71.62
2451
12.32
1801
9.05
877
4.41
520
2.61
19902
Total 14328 2474 1817 882 521 20022
Output 73. Pearson Chi-Square Statistics of the Association Test
Between Breastfeeding Status and LDL Cholesterol Classes.
Statistic DF Value Prob
Chi-Square 4 9.7958 0.0440
Likelihood Ratio Chi-Square 4 9.4223 0.0514
Mantel-Haenszel Chi-Square 1 0.6813 0.4091
Phi Coefficient 0.0221
Contingency Coefficient 0.0221
Cramer's V 0.0221
136 | P a g e
Output 74. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Breastfeeding Status and LDL Cholesterol Classes.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 0.6813 0.4091
2
Row Mean Scores
Differ
1 0.6813 0.4091
3 General Association 4 9.7953 0.0440
Output 75. Frequency Table of Breastfeeding Status (1 – yes, 2- no)
by Triglyceride Category. Normal <150 mg/dL≤ High < 200
mg/dL ≤ Borderline High < 500 mg/dL ≤ Very High.
Breastfeeding
1- yes, 2-no
Triglyceride Classification
Total
Frequency
Row Pct
normal
borderline
high
high very high
1
97
80.83
11
9.17
12
10.00
0
0.00
120
2
16515
82.98
1618
8.13
1647
8.28
122
0.61
19902
Total 16612 1629 1659 122 20022
137 | P a g e
Output 76. Pearson Chi-Square Statistics of the Association Test
Between Breastfeeding Status and LDL Cholesterol Classes.
Statistic DF Value Prob
Chi-Square 3 1.3876 0.7084
Likelihood Ratio Chi-Square 3 2.0865 0.5546
Mantel-Haenszel Chi-Square 1 0.2103 0.6465
Phi Coefficient 0.0083
Contingency Coefficient 0.0083
Cramer's V 0.0083
Output 77. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Breastfeeding Status and HDL Cholesterol Classes.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 0.2103 0.6465
2
Row Mean Scores
Differ
1 0.2103 0.6465
3 General Association 3 1.3876 0.7084
138 | P a g e
Output 78. Frequency Table of Smoking Status (1 - Smoking, 2 – No
Smoking) by Total Cholesterol Category. Desirable <200 mg/dL≤
Borderline High < 240 mg/dL ≤ High.
Smoking Status
1-yes, 2-no
Total Cholesterol Classification
Total
Frequency
Row Pct
Desirable Borderline High
1 834
60.48
345
25.02
200
14.50
1379
2 11471
61.53
4367
23.42
2805
15.05
18643
Total 12305 4712 3005 20022
Output 79. Pearson Chi-Square Statistics of the Association Test
Between Smoking Status and Total Cholesterol Classes.
Statistic DF Value Prob
Chi-Square 2 1.8687 0.3928
Likelihood Ratio Chi-Square 2 1.8463 0.3973
Mantel-Haenszel Chi-Square 1 0.0605 0.8057
Phi Coefficient 0.0097
Contingency Coefficient 0.0097
Cramer's V 0.0097
139 | P a g e
Output 80. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Smoking Status and Total Cholesterol Classes.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 0.0605 0.8057
2
Row Mean Scores
Differ
1 0.0605 0.8057
3 General Association 2 1.8686 0.3929
Output 81. Frequency Table of Tobacco Smoking Status (1 Smoking,
2 – no Smoking) by HDL Cholesterol Category. Low < 40
mg/dL ≤ Normal < 60 mg/dL ≤ High.
Smoking Status
1-yes, 2-no
HDL Cholesterol Classification
Total
Frequency
Row Pct
Low Normal High
1 313
22.70
490
35.53
576
41.77
1379
2 3849
20.65
7510
40.28
7284
39.07
18643
Total 4162 8000 7860 20022
140 | P a g e
Output 82. Pearson Chi-Square Statistics of the Association Test
Between Tobacco Smoking Status and HDL Cholesterol Classes.
Statistic DF Value Prob
Chi-Square 2 12.2334 0.0022
Likelihood Ratio Chi-Square 2 12.3798 0.0020
Mantel-Haenszel Chi-Square 1 0.0948 0.7582
Phi Coefficient 0.0247
Contingency Coefficient 0.0247
Cramer's V 0.0247
Output 83. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Tobacco Smoking Status and HDL Cholesterol
Classes.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 0.0948 0.7582
2
Row Mean Scores
Differ
1 0.0948 0.7582
3 General Association 2 12.2328 0.0022
141 | P a g e
Output 84. Measures of the Strength of Association Between
Tobacco Smoking Status and HDL Cholesterol.
Statistic Value
95%
Confidence Limits
Gamma -0.0138 -0.0607 0.0332
Kendall's Tau-b -0.0040 -0.0175 0.0096
Stuart's Tau-c -0.0023 -0.0101 0.0055
Somers' D C|R -0.0089 -0.0392 0.0214
Somers' D R|C -0.0018 -0.0078 0.0043
Pearson Correlation -0.0022 -0.0165 0.0121
Spearman Correlation -0.0042 -0.0185 0.0101
Lambda Asymmetric C|R 0.0072 0.0018 0.0125
Lambda Asymmetric R|C 0.0000 0.0000 0.0000
Lambda Symmetric 0.0064 0.0017 0.0112
Uncertainty Coefficient C|R 0.0003 0.0000 0.0006
Uncertainty Coefficient R|C 0.0012 0.0000 0.0026
Uncertainty Coefficient
Symmetric
0.0005 0.0000 0.0010
142 | P a g e
Output 85. Frequency Table of Tobacco Smoking Status (1 – yes, 2no)
by LDL Cholesterol Category. Optimal < 100 mg/dL≤ Near
Optimal < 130 mg/dL≤ Borderline High < 160 ≤ High < 190 ≤
Very High.
Smoking
Status
1-yes, 2-no
LDL Cholesterol Classification
Total
Frequency
Row Pct
Optimal
Near
Optimal
Borderline
High
High
Very
High
1
970
70.34
128
9.28
142
10.30
79
5.73
60
4.35
1379
2
13358
71.65
2346
12.58
1675
8.98
803
4.31
461
2.47
18643
Total 14328 2474 1817 882 521 20022
Output 86. Pearson Chi-Square Statistics of the Association Test
Between Tobacco Smoking Status and LDL Cholesterol Classes.
Statistic DF Value Prob
Chi-Square 4 37.3720 <.0001
Likelihood Ratio Chi-Square 4 35.0681 <.0001
Mantel-Haenszel Chi-Square 1 15.7229 <.0001
Phi Coefficient 0.0432
Contingency Coefficient 0.0432
Cramer's V 0.0432
143 | P a g e
Output 87. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Tobacco Smoking Status and LDL Cholesterol
Classes.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 15.7229 <.0001
2
Row Mean Scores
Differ
1 15.7229 <.0001
3 General Association 4 37.3701 <.0001
144 | P a g e
Output 88. Measures of the Strength of Association Between
Tobacco Smoking Status and LDL Cholesterol.
Statistic Value
95%
Confidence Limits
Gamma -0.0565 -0.1108 -0.0023
Kendall's Tau-b -0.0140 -0.0279 -0.0002
Stuart's Tau-c -0.0068 -0.0136 -0.0001
Somers' D C|R -0.0266 -0.0530 -0.0003
Somers' D R|C -0.0074 -0.0147 -0.0001
Pearson Correlation -0.0280 -0.0436 -0.0124
Spearman Correlation -0.0147 -0.0293 -0.0002
Lambda Asymmetric C|R 0.0000 0.0000 0.0000
Lambda Asymmetric R|C 0.0000 0.0000 0.0000
Lambda Symmetric 0.0000 0.0000 0.0000
Uncertainty Coefficient C|R 0.0009 0.0003 0.0016
Uncertainty Coefficient R|C 0.0035 0.0011 0.0059
Uncertainty Coefficient
Symmetric
0.0015 0.0005 0.0025
145 | P a g e
Output 89. Frequency Table of Tobacco Smoking Status (1 –
Smoking, 2- no Smoking) by Triglyceride Category. Normal <150
mg/dL ≤ High < 200 mg/dL ≤ Borderline High < 500 mg/dL ≤
Very High.
Smoking Status
1-yes, 2-no
Triglyceride Classification
Total
Frequency
Row Pct
Normal
Borderline
High
High
Very
High
1
1210
87.74
88
6.38
72
5.22
9
0.65
1379
2
15402
82.62
1541
8.27
1587
8.51
113
0.61
18643
Total 16612 1629 1659 122 20022
Output 90. Pearson Chi-Square Statistics of the Association Test
Between Tobacco Smoking Status and Triglycerides Classes.
Statistic DF Value Prob
Chi-Square 3 26.5092 <.0001
Likelihood Ratio Chi-Square 3 29.2366 <.0001
Mantel-Haenszel Chi-Square 1 22.4163 <.0001
Phi Coefficient 0.0364
Contingency Coefficient 0.0364
Cramer's V 0.0364
146 | P a g e
Output 91. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Tobacco Smoking Status and Triglycerides Classes.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 22.4163 <.0001
2
Row Mean Scores
Differ
1 22.4163 <.0001
3 General Association 3 26.5079 <.0001
Output 92. Measures of the Strength of Association Between
Tobacco Smoking Status and Triglycerides Classes.
Statistic Value
95%
Confidence Limits
Gamma 0.1960 0.1194 0.2727
Kendall's Tau-b 0.0341 0.0222 0.0460
Stuart's Tau-c 0.0133 0.0086 0.0180
Somers' D C|R 0.0520 0.0339 0.0702
Somers' D R|C 0.0224 0.0145 0.0302
Pearson Correlation 0.0335 0.0214 0.0456
Spearman Correlation 0.0349 0.0227 0.0471
Lambda Asymmetric C|R 0.0000 0.0000 0.0000
Lambda Asymmetric R|C 0.0000 0.0000 0.0000
Lambda Symmetric 0.0000 0.0000 0.0000
Uncertainty Coefficient C|R 0.0012 0.0004 0.0021
Uncertainty Coefficient R|C 0.0029 0.0009 0.0049
Uncertainty Coefficient
Symmetric
0.0017 0.0005 0.0029
147 | P a g e
Output 93. Frequency Table of Alcohol Consumption Status (1 - yes,
2 – no Smoking) by Total Cholesterol Category. Desirable <200
mg/dL ≤ Borderline High < 240 mg/dL ≤ High.
Alcohol Drinking
Status
1-yes, 2-no
Total Cholesterol Classification
Total
Frequency
Row Pct
Desirable Borderline High
1
1809
54.59
947
28.58
558
16.84
3314
2
10496
62.82
3765
22.53
2447
14.65
16708
Total 12305 4712 3005 20022
Output 94. Pearson Chi-Square Statistics of the Association Test
Between Alcohol Consumption Status and Total Cholesterol
Classes.
Statistic DF Value Prob
Chi-Square 2 82.2509 <.0001
Likelihood Ratio Chi-Square 2 80.7381 <.0001
Mantel-Haenszel Chi-Square 1 54.7581 <.0001
Phi Coefficient 0.0641
Contingency Coefficient 0.0640
Cramer's V 0.0641
148 | P a g e
Output 95. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Alcohol Consumption Status and Total Cholesterol
Classes.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 54.7581 <.0001
2
Row Mean Scores
Differ
1 54.7581 <.0001
3 General Association 2 82.2468 <.0001
149 | P a g e
Output 96. Measures of the Strength of Association Between Alcohol
Consumption Status and Total Cholesterol Levels.
Statistic Value
95%
Confidence Limits
Gamma -0.1381 -0.1700 -0.1061
Kendall's Tau-b -0.0559 -0.0694 -0.0424
Stuart's Tau-c -0.0433 -0.0538 -0.0328
Somers' D C|R -0.0784 -0.0974 -0.0595
Somers' D R|C -0.0398 -0.0495 -0.0301
Pearson Correlation -0.0523 -0.0664 -0.0382
Spearman Correlation -0.0582 -0.0723 -0.0442
Lambda Asymmetric C|R 0.0000 0.0000 0.0000
Lambda Asymmetric R|C 0.0000 0.0000 0.0000
Lambda Symmetric 0.0000 0.0000 0.0000
Uncertainty Coefficient C|R 0.0022 0.0012 0.0031
Uncertainty Coefficient R|C 0.0045 0.0025 0.0065
Uncertainty Coefficient
Symmetric
0.0029 0.0016 0.0042
150 | P a g e
Output 97. Frequency Table of Alcohol Consumption Status (1 - yes,
2 – no) by HDL Cholesterol Category. Low < 40 mg/dL≤ Normal
< 60 mg/dL ≤ High.
Alcohol Drinking Status
1-yes, 2-no
HDL Cholesterol Classification
Total
Frequency
Row Pct
Low Normal High
1
332
10.02
996
30.05
1986
59.93
3314
2
3830
22.92
7004
41.92
5874
35.16
16708
Total 4162 8000 7860 20022
Output 98. Pearson Chi-Square Statistics of the Association Test
Between Alcohol Consumption Status and HDL Cholesterol
Classes.
Statistic DF Value Prob
Chi-Square 2 751.2583 <.0001
Likelihood Ratio Chi-Square 2 753.7757 <.0001
Mantel-Haenszel Chi-Square 1 693.1164 <.0001
Phi Coefficient 0.1937
Contingency Coefficient 0.1902
Cramer's V 0.1937
151 | P a g e
Output 99. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Alcohol Consumption Status and HDL Cholesterol
Classes.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 693.1164 <.0001
2
Row Mean Scores
Differ
1 693.1164 <.0001
3 General Association 2 751.2208 <.0001
152 | P a g e
Output 100. Measures of the Strength of Association Between
Alcohol Consumption and HDL Cholesterol Levels.
Statistic Value
95%
Confidence Limits
Gamma -0.4288 -0.4571 -0.4005
Kendall's Tau-b -0.1800 -0.1923 -0.1677
Stuart's Tau-c -0.1517 -0.1626 -0.1408
Somers' D C|R -0.2746 -0.2931 -0.2561
Somers' D R|C -0.1180 -0.1264 -0.1095
Pearson Correlation -0.1861 -0.1988 -0.1734
Spearman Correlation -0.1899 -0.2029 -0.1769
Lambda Asymmetric C|R 0.0823 0.0738 0.0909
Lambda Asymmetric R|C 0.0000 0.0000 0.0000
Lambda Symmetric 0.0646 0.0579 0.0712
Uncertainty Coefficient C|R 0.0178 0.0153 0.0202
Uncertainty Coefficient R|C 0.0420 0.0361 0.0478
Uncertainty Coefficient
Symmetric
0.0250 0.0215 0.0284
153 | P a g e
Output 101. Frequency Table of Alcohol Consumption Status (1 –
yes, 2- no) by LDL Cholesterol Category. Optimal < 100 mg/dL≤
Near Optimal < 130 mg/dL≤ Borderline High < 160 ≤ High < 190
≤ Very High.
Alcohol
Drinking Status
1-yes, 2-no
LDL Cholesterol Classification
Total
Frequency
Row Pct
Optimal
Near
optimal
Borderline
high
High
Very
High
1
2178
65.72
394
11.89
388
11.71
216
6.52
138
4.16
3314
2
12150
72.72
2080
12.45
1429
8.55
666
3.99
383
2.29
16708
Total 14328 2474 1817 882 521 20022
Output 102. Pearson Chi-Square Statistics of the Association Test
Between Alcohol Consumption Status and LDL Cholesterol Classes.
Statistic DF Value Prob
Chi-Square 4 127.4400 <.0001
Likelihood Ratio Chi-Square 4 117.1181 <.0001
Mantel-Haenszel Chi-Square 1 119.2549 <.0001
Phi Coefficient 0.0798
Contingency Coefficient 0.0795
Cramer's V 0.0798
154 | P a g e
Output 103. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Alcohol Consumption Status and LDL Cholesterol
Classes.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 119.2549 <.0001
2
Row Mean Scores
Differ
1 119.2549 <.0001
3 General Association 4 127.4336 <.0001
155 | P a g e
Output 104. Measures of the Strength of Association Between
Alcohol Consumption and LDL Cholesterol Levels.
Statistic Value
95%
Confidence Limits
Gamma -0.1664 -0.2007 -0.1322
Kendall's Tau-b -0.0636 -0.0777 -0.0495
Stuart's Tau-c -0.0454 -0.0555 -0.0353
Somers' D C|R -0.0822 -0.1004 -0.0639
Somers' D R|C -0.0492 -0.0601 -0.0382
Pearson Correlation -0.0772 -0.0926 -0.0618
Spearman Correlation -0.0666 -0.0814 -0.0518
Lambda Asymmetric C|R 0.0000 0.0000 0.0000
Lambda Asymmetric R|C 0.0000 0.0000 0.0000
Lambda Symmetric 0.0000 0.0000 0.0000
Uncertainty Coefficient C|R 0.0031 0.0019 0.0042
Uncertainty Coefficient R|C 0.0065 0.0041 0.0090
Uncertainty Coefficient
Symmetric
0.0042 0.0026 0.0058
156 | P a g e
Output 105. Frequency Table of Alcohol Consumption Status (1 –
yes, 2- no) by Triglyceride Category. Normal <150 mg/dL ≤ High <
200 mg/dL ≤ Borderline High < 500 mg/dL ≤ Very High.
Alcohol
Drinking Status
1-yes, 2-no
Triglyceride Classification
Total
Frequency
Row Pct
Normal
Borderline
High
High
Very
High
1
2958
89.26
175
5.28
168
5.07
13
0.39
3314
2
13654
81.72
1454
8.70
1491
8.92
109
0.65
16708
Total 16612 1629 1659 122 20022
Output 106. Pearson Chi-Square Statistics of the Association Test
Between Alcohol Consumption Status and Triglyceride Cholesterol
Levels.
Statistic DF Value Prob
Chi-Square 3 111.3859 <.0001
Likelihood Ratio Chi-Square 3 122.5070 <.0001
Mantel-Haenszel Chi-Square 1 98.7679 <.0001
Phi Coefficient 0.0746
Contingency Coefficient 0.0744
Cramer's V 0.0746
157 | P a g e
Output 107. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Alcohol Consumption Status and Triglyceride
Cholesterol Levels.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 98.7679 <.0001
2
Row Mean Scores
Differ
1 98.7679 <.0001
3 General Association 3 111.3804 <.0001
158 | P a g e
Output 108. Measures of the Strength of Association Between
Alcohol Consumption and Triglyceride Cholesterol Levels.
Statistic Value
95%
Confidence Limits
Gamma 0.2894 0.2376 0.3412
Kendall's Tau-b 0.0728 0.0613 0.0844
Stuart's Tau-c 0.0418 0.0350 0.0486
Somers' D C|R 0.0756 0.0636 0.0877
Somers' D R|C 0.0701 0.0589 0.0813
Pearson Correlation 0.0702 0.0585 0.0820
Spearman Correlation 0.0745 0.0626 0.0863
Lambda Asymmetric C|R 0.0000 0.0000 0.0000
Lambda Asymmetric R|C 0.0000 0.0000 0.0000
Lambda Symmetric 0.0000 0.0000 0.0000
Uncertainty Coefficient C|R 0.0051 0.0034 0.0068
Uncertainty Coefficient R|C 0.0068 0.0045 0.0091
Uncertainty Coefficient
Symmetric
0.0059 0.0039 0.0078
159 | P a g e
Output 109. Frequency Table of Chmotherapy Status (1 - Yes, 2 –
No Pregnant) by Total Cholesterol Category. Desirable <200 mg/dL
≤ Borderline High < 240 mg/dL ≤ High.
Chemotherapy Status
1 – yes, 2 - no
Total Cholesterol Classification
Total
Frequency
Row Pct
Desirable Borderline High
1
177
60.62
75
25.68
40
13.70
292
2
12128
61.47
4637
23.50
2965
15.03
19730
Total 12305 4712 3005 20022
Output 110. Pearson Chi-Square Statistics of the Association Test
Between Chemotherapy Status and Total Cholesterol Classes.
Statistic DF Value Prob
Chi-Square 2 0.9553 0.6202
Likelihood Ratio Chi-Square 2 0.9489 0.6222
Mantel-Haenszel Chi-Square 1 0.0119 0.9132
Phi Coefficient 0.0069
Contingency Coefficient 0.0069
Cramer's V 0.0069
160 | P a g e
Output 111. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Chemotherapy Status and Total Cholesterol Classes.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 0.0119 0.9132
2
Row Mean Scores
Differ
1 0.0119 0.9132
3 General Association 2 0.9553 0.6202
Output 112. Frequency Table of Chemotherapy Status (1 - yes, 2 –
no) by HDL Cholesterol Category. Low < 40 mg/dL ≤ Normal < 60
mg/dL ≤ High.
Chemotherapy Status
1 – yes, 2 - no
HDL Cholesterol Classification
Total
Frequency
Row Pct
Low Normal High
1
47
16.10
117
40.07
128
43.84
292
2
4115
20.86
7883
39.95
7732
39.19
19730
Total 4162 8000 7860 20022
161 | P a g e
Output 113. Pearson Chi-Square Statistics of the Association Test
Between Chemotherapy Status and HDL Cholesterol Levels.
Statistic DF Value Prob
Chi-Square 2 4.7207 0.0944
Likelihood Ratio Chi-Square 2 4.9263 0.0852
Mantel-Haenszel Chi-Square 1 4.4961 0.0340
Phi Coefficient 0.0154
Contingency Coefficient 0.0154
Cramer's V 0.0154
Output 114. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Chemotherapy Status and HDL Cholesterol Levels.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 4.4961 0.0340
2
Row Mean Scores
Differ
1 4.4961 0.0340
3 General Association 2 4.7204 0.0944
162 | P a g e
Output 115. Frequency Table of Chemotherapy Status (1 – yes, 2no)
by LDL Cholesterol Category. Optimal < 100 mg/dL≤ Near
Optimal < 130 mg/dL≤ Borderline High < 160 ≤ High < 190 ≤
Very High.
Chemotherapy
Status
1 – yes, 2 - no
LDL Cholesterol Classification
Total
Frequency
Row Pct
Optimal
Near
Optimal
Borderline
High
High
Very
High
1
199
68.15
28
9.59
39
13.36
18
6.16
8
2.74
292
2
14129
71.61
2446
12.40
1778
9.01
864
4.38
513
2.60
19730
Total 14328 2474 1817 882 521 20022
Output 116. Pearson Chi-Square Statistics of the Association Test
Between Chemotherapy Status and LDL Cholesterol Levels.
Statistic DF Value Prob
Chi-Square 4 10.4062 0.0341
Likelihood Ratio Chi-Square 4 9.5816 0.0481
Mantel-Haenszel Chi-Square 1 3.9776 0.0461
Phi Coefficient 0.0228
Contingency Coefficient 0.0228
Cramer's V 0.0228
163 | P a g e
Output 117. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Chemotherapy Status and LDL Cholesterol Levels.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 3.9776 0.0461
2
Row Mean Scores
Differ
1 3.9776 0.0461
3 General Association 4 10.4057 0.0341
Output 118. Frequency Table of Chemotherapy Status (1 – yes, 2no)
by Triglyceride Category. Normal <150 mg/dL≤ High < 200
mg/dL ≤ Borderline High < 500 mg/dL ≤ Very High.
Chemotherapy
Status
1 – yes, 2 - no
Triglyceride Classification
Total
Frequency
Row Pct
Normal
Borderline
High
High
Very
High
1
252
86.30
18
6.16
20
6.85
2
0.68
292
2
16360
82.92
1611
8.17
1639
8.31
120
0.61
19730
Total 16612 1629 1659 122 20022
164 | P a g e
Output 119. Pearson Chi-Square Statistics of the Association Test
Between Chemotherapy Status and Triglyceride Levels.
Statistic DF Value Prob
Chi-Square 3 2.5783 0.4613
Likelihood Ratio Chi-Square 3 2.7470 0.4323
Mantel-Haenszel Chi-Square 1 1.5908 0.2072
Phi Coefficient 0.0113
Contingency Coefficient 0.0113
Cramer's V 0.0113
Output 120. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Chemotherapy Status and Triglyceride Levels.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 1.5908 0.2072
2
Row Mean Scores
Differ
1 1.5908 0.2072
3 General Association 3 2.5782 0.4613
165 | P a g e
Output 121. Frequency Table of Contraception Use (1 - yes, 2 – no
Smoking) by Total Cholesterol Category. Desirable <200 mg/dL≤
Borderline High < 240 mg/dL ≤ High.
Contraception Use
1- yes, 2 - no
Total Cholesterol Classification
Total
Frequency
Row Pct
Desirable Borderline High
1
1000
69.11
346
23.91
101
6.98
1447
2
11305
60.86
4366
23.50
2904
15.63
18575
Total 12305 4712 3005 20022
Output 122. Pearson Chi-Square Statistics of the Association Test
Between Contraception Use and Total Cholesterol Classes.
Statistic DF Value Prob
Chi-Square 2 81.9368 <.0001
Likelihood Ratio Chi-Square 2 96.8904 <.0001
Mantel-Haenszel Chi-Square 1 69.8550 <.0001
Phi Coefficient 0.0640
Contingency Coefficient 0.0638
Cramer's V 0.0640
166 | P a g e
Output 123. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Contraception Use and Total Cholesterol Classes.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 69.8550 <.0001
2
Row Mean Scores
Differ
1 69.8550 <.0001
3 General Association 2 81.9327 <.0001
Output 124. Measures of the Strength of Association Between
Contraception Use and Total Cholesterol Levels.
Statistic Value
95%
Confidence Limits
Gamma 0.2019 0.1522 0.2517
Kendall's Tau-b 0.0513 0.0394 0.0632
Stuart's Tau-c 0.0277 0.0212 0.0343
Somers' D C|R 0.1034 0.0796 0.1273
Somers' D R|C 0.0255 0.0195 0.0315
Pearson Correlation 0.0591 0.0474 0.0707
Spearman Correlation 0.0535 0.0411 0.0659
Lambda Asymmetric C|R 0.0000 0.0000 0.0000
Lambda Asymmetric R|C 0.0000 0.0000 0.0000
Lambda Symmetric 0.0000 0.0000 0.0000
Uncertainty Coefficient C|R 0.0026 0.0017 0.0036
Uncertainty Coefficient R|C 0.0093 0.0060 0.0126
Uncertainty Coefficient
Symmetric
0.0041 0.0026 0.0056
167 | P a g e
Output 125. Frequency Table of Contraception Use (1 - yes, 2 – no)
by HDL Cholesterol Category. Low < 40 mg/dL≤ Normal < 60
mg/dL ≤ High.
Contraception
Use
1- yes, 2 - no
HDL Cholesterol Classification
Total
Frequency
Row Pct
Low Normal High
1
195
13.48
656
45.34
596
41.19
1447
2
3967
21.36
7344
39.54
7264
39.11
18575
Total 4162 8000 7860 20022
Output 126. Pearson Chi-Square Statistics of the Association Test
Between Contraception Use and HDL Cholesterol Levels.
Statistic DF Value Prob
Chi-Square 2 52.8833 <.0001
Likelihood Ratio Chi-Square 2 57.7391 <.0001
Mantel-Haenszel Chi-Square 1 23.5271 <.0001
Phi Coefficient 0.0514
Contingency Coefficient 0.0513
Cramer's V 0.0514
168 | P a g e
Output 127. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Contraception Use and HDL Cholesterol Levels.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 23.5271 <.0001
2
Row Mean Scores
Differ
1 23.5271 <.0001
3 General Association 2 52.8806 <.0001
Output 128. Measures of the Strength of Association Between
Contraception Use and HDL Cholesterol Levels.
Statistic Value
95%
Confidence Limits
Gamma -0.1020 -0.1448 -0.0592
Kendall's Tau-b -0.0294 -0.0417 -0.0171
Stuart's Tau-c -0.0173 -0.0245 -0.0100
Somers' D C|R -0.0644 -0.0912 -0.0375
Somers' D R|C -0.0134 -0.0190 -0.0078
Pearson Correlation -0.0343 -0.0470 -0.0216
Spearman Correlation -0.0310 -0.0440 -0.0181
Lambda Asymmetric C|R 0.0000 0.0000 0.0000
Lambda Asymmetric R|C 0.0000 0.0000 0.0000
Lambda Symmetric 0.0000 0.0000 0.0000
Uncertainty Coefficient C|R 0.0014 0.0007 0.0020
Uncertainty Coefficient R|C 0.0056 0.0028 0.0083
Uncertainty Coefficient
Symmetric
0.0022 0.0011 0.0033
169 | P a g e
Output 129. Frequency Table of Chemotherapy Status (1 – yes, 2no)
by LDL Cholesterol Category. Optimal < 100 mg/dL≤ Near
Optimal < 130 mg/dL≤ Borderline High < 160 ≤ High < 190 ≤
Very High.
Contraception
Use
1- yes, 2 - no
LDL Cholesterol Classification
Total
Frequency
Row Pct
Optimal
Near
Optimal
Borderline
High
High
Very
High
1
1048
72.43
217
15.00
132
9.12
37
2.56
13
0.90
1447
2
13280
71.49
2257
12.15
1685
9.07
845
4.55
508
2.73
18575
Total 14328 2474 1817 882 521 20022
Output 130. Pearson Chi-Square Statistics of the Association Test
Between Contraception Use and LDL Cholesterol Levels.
Statistic DF Value Prob
Chi-Square 4 38.4575 <.0001
Likelihood Ratio Chi-Square 4 45.4330 <.0001
Mantel-Haenszel Chi-Square 1 14.3561 0.0002
Phi Coefficient 0.0438
Contingency Coefficient 0.0438
Cramer's V 0.0438
170 | P a g e
Output 131. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Contraception Use and LDL Cholesterol Levels.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 14.3561 0.0002
2
Row Mean Scores
Differ
1 14.3561 0.0002
3 General Association 4 38.4556 <.0001
Output 132. Measures of the Strength of Association Between
Contraception Use and LDL Cholesterol Levels.
Statistic Value
95%
Confidence Limits
Gamma 0.0492 -0.0034 0.1018
Kendall's Tau-b 0.0121 -0.0005 0.0246
Stuart's Tau-c 0.0060 -0.0003 0.0122
Somers' D C|R 0.0224 -0.0009 0.0456
Somers' D R|C 0.0065 -0.0003 0.0133
Pearson Correlation 0.0268 0.0151 0.0384
Spearman Correlation 0.0126 -0.0005 0.0258
Lambda Asymmetric C|R 0.0000 0.0000 0.0000
Lambda Asymmetric R|C 0.0000 0.0000 0.0000
Lambda Symmetric 0.0000 0.0000 0.0000
Uncertainty Coefficient C|R 0.0012 0.0006 0.0018
Uncertainty Coefficient R|C 0.0044 0.0021 0.0066
Uncertainty Coefficient
Symmetric
0.0019 0.0009 0.0029
171 | P a g e
Output 133. Frequency Table of Contraception Use (1 – yes, 2- no)
by Triglyceride Category. Normal <150 mg/dL≤ High < 200
mg/dL ≤ Borderline High < 500 mg/dL ≤ Very High.
Contraception
Use
1- yes, 2 - no
Triglyceride Classification
Total
Frequency
Row Pct
Normal
Borderline
High
High
Very
High
1
1258
86.94
113
7.81
73
5.04
3
0.21
1447
2
15354
82.66
1516
8.16
1586
8.54
119
0.64
18575
Total 16612 1629 1659 122 20022
Output 134. Pearson Chi-Square Statistics of the Association Test
Between Contraception Use and Triglyceride Levels.
Statistic DF Value Prob
Chi-Square 3 27.0762 <.0001
Likelihood Ratio Chi-Square 3 31.3540 <.0001
Mantel-Haenszel Chi-Square 1 25.2215 <.0001
Phi Coefficient 0.0368
Contingency Coefficient 0.0367
Cramer's V 0.0368
172 | P a g e
Output 135. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Contraception Use and Triglyceride Levels.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 25.2215 <.0001
2
Row Mean Scores
Differ
1 25.2215 <.0001
3 General Association 3 27.0749 <.0001
Output 136. Measures of the Strength of Association Between
Contraception Use and Triglyceride Levels.
Statistic Value
95%
Confidence Limits
Gamma 0.1693 0.0961 0.2424
Kendall's Tau-b 0.0307 0.0187 0.0427
Stuart's Tau-c 0.0123 0.0075 0.0171
Somers' D C|R 0.0458 0.0279 0.0637
Somers' D R|C 0.0206 0.0125 0.0287
Pearson Correlation 0.0355 0.0240 0.0470
Spearman Correlation 0.0314 0.0191 0.0437
Lambda Asymmetric C|R 0.0000 0.0000 0.0000
Lambda Asymmetric R|C 0.0000 0.0000 0.0000
Lambda Symmetric 0.0000 0.0000 0.0000
Uncertainty Coefficient C|R 0.0013 0.0005 0.0022
Uncertainty Coefficient R|C 0.0030 0.0011 0.0049
Uncertainty Coefficient
Symmetric
0.0018 0.0007 0.0030
173 | P a g e
Output 137. Frequency Table of Kidney Disease Stage Kidney
Disease Stage (Stage 1 – GFR ≥ 90; Stage 2- GFR < 90 and GFR≥
60; Stage 3 – GFR < 60 and GFR ≥ 30; Stage 4 – GFR < 30 and GFR
≥ 15 and Stage 5 – GFR < 15. Glomerular Flow Rate: mL/min per
1.73 m2) by Total Cholesterol Category (Desirable <200 mg/dL≤
Borderline High < 240 mg/dL ≤ High) .
ney Disease Stage Total Cholesterol Classification
TotalFrequency
Row Pct
Desirable Borderline High
Kidney Disease
Stage
Total Cholesterol Classification
Total
Frequency
Row Pct
Desirable Borderline High
1
4932
70.05
1381
19.61
728
10.34
7041
2
3763
56.21
1942
29.01
989
14.77
6694
3
492
28.69
629
36.68
594
34.64
1715
4
80
37.04
63
29.17
73
33.80
216
5
3038
69.74
697
16.00
621
14.26
4356
Total 12305 4712 3005 20022
174 | P a g e
Output 138. Pearson Chi-Square Statistics of the Association Test
Between Kidney Disease Stage and Total Cholesterol Levels.
Statistic DF Value Prob
Chi-Square 8 1444.0107 <.0001
Likelihood Ratio Chi-Square 8 1388.2298 <.0001
Mantel-Haenszel Chi-Square 1 28.1063 <.0001
Phi Coefficient 0.2686
Contingency Coefficient 0.2594
Cramer's V 0.1899
Output 139. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Kidney Disease Stage and Total Cholesterol Levels.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 28.1063 <.0001
2
Row Mean Scores
Differ
4 1252.0704 <.0001
3 General Association 8 1443.9385 <.0001
175 | P a g e
Output 140. Measures of the Strength of Association Between
Kidney Disease Stage and Total Cholesterol Levels.
Statistic Value
95%
Confidence Limits
Gamma 0.1263 0.1074 0.1452
Kendall's Tau-b 0.0804 0.0682 0.0925
Stuart's Tau-c 0.0750 0.0636 0.0863
Somers' D C|R 0.0704 0.0597 0.0811
Somers' D R|C 0.0918 0.0779 0.1057
Pearson Correlation 0.0375 0.0239 0.0510
Spearman Correlation 0.0885 0.0749 0.1021
Lambda Asymmetric C|R 0.0178 0.0093 0.0262
Lambda Asymmetric R|C 0.0633 0.0529 0.0737
Lambda Symmetric 0.0463 0.0391 0.0536
Uncertainty Coefficient C|R 0.0375 0.0336 0.0414
Uncertainty Coefficient R|C 0.0262 0.0235 0.0289
Uncertainty Coefficient
Symmetric
0.0308 0.0276 0.0340
176 | P a g e
Output 141. Frequency Table of Kidney Disease Stage Kidney
Disease Stage (Stage 1 – GFR ≥ 90; Stage 2- GFR < 90 and GFR≥
60; Stage 3 – GFR < 60 and GFR ≥ 30; Stage 4 – GFR < 30 and GFR
≥ 15 and Stage 5 – GFR < 15. Glomerular Flow Rate: mL/min per
1.73 m2) by HDL Cholesterol Category. Low < 40 mg/dL≤ Normal
< 60 mg/dL ≤ High.
Kidney Disease
Stage
HDL Cholesterol Classification
Total
Frequency
Row Pct
Low Normal High
1
449
6.38
2937
41.71
3655
51.91
7041
2
866
12.94
3223
48.15
2605
38.92
6694
3
245
14.29
791
46.12
679
39.59
1715
4
41
18.98
108
50.00
67
31.02
216
5
2561
58.79
941
21.60
854
19.61
4356
Total 4162 8000 7860 20022
177 | P a g e
Output 142. Pearson Chi-Square Statistics of the Association Test
Between Kidney Disease Stage and HDL Cholesterol Levels.
Statistic DF Value Prob
Chi-Square 8 5190.3569 <.0001
Likelihood Ratio Chi-Square 8 4615.3600 <.0001
Mantel-Haenszel Chi-Square 1 3394.0155 <.0001
Phi Coefficient 0.5091
Contingency Coefficient 0.4537
Cramer's V 0.3600
Output 143. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Kidney Disease Stage and HDL Cholesterol Levels.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 3394.0155 <.0001
2
Row Mean Scores
Differ
4 3549.7896 <.0001
3 General Association 8 5190.0977 <.0001
178 | P a g e
Output 144. Measures of the Strength of Association Between
Kidney Disease Stage and HDL Cholesterol Levels.
Statistic Value
95%
Confidence Limits
Gamma -0.4546 -0.4704 -0.4389
Kendall's Tau-b -0.3204 -0.3323 -0.3085
Stuart's Tau-c -0.3247 -0.3370 -0.3124
Somers' D C|R -0.3050 -0.3165 -0.2935
Somers' D R|C -0.3367 -0.3490 -0.3243
Pearson Correlation -0.4117 -0.4249 -0.3986
Spearman Correlation -0.3608 -0.3740 -0.3477
Lambda Asymmetric C|R 0.1945 0.1798 0.2092
Lambda Asymmetric R|C 0.1847 0.1717 0.1978
Lambda Symmetric 0.1894 0.1768 0.2020
Uncertainty Coefficient C|R 0.1087 0.1026 0.1148
Uncertainty Coefficient R|C 0.0870 0.0820 0.0920
Uncertainty Coefficient
Symmetric
0.0966 0.0911 0.1021
179 | P a g e
Output 145. Frequency Table of Kidney Disease Stage Kidney
Disease Stage (Stage 1 – GFR ≥ 90; Stage 2- GFR < 90 and GFR≥
60; Stage 3 – GFR < 60 and GFR ≥ 30; Stage 4 – GFR < 30 and GFR
≥ 15 and Stage 5 – GFR < 15. Glomerular Flow Rate: mL/min per
1.73 m2) by LDL Cholesterol Category. Optimal < 100 mg/dL≤
Near Optimal < 130 mg/dL≤ Borderline High < 160 ≤ High < 190
≤ Very High.
Kidney
Disease
Stage
LDL Cholesterol Classification
Total
Frequency
Row Pct
Optimal
Near
Optimal
Borderline
High
High
Very
High
1
4878
69.28
1061
15.07
632
8.98
284
4.03
186
2.64
7041
2
4564
68.18
963
14.39
694
10.37
306
4.57
167
2.49
6694
3
1085
63.27
180
10.50
245
14.29
119
6.94
86
5.01
1715
4
160
74.07
18
8.33
17
7.87
8
3.70
13
6.02
216
5
3641
83.59
252
5.79
229
5.26
165
3.79
69
1.58
4356
Total 14328 2474 1817 882 521 20022
180 | P a g e
Output 146. Pearson Chi-Square Statistics of the Association Test
Between Kidney Disease Stage and LDL Cholesterol Levels.
Statistic DF Value Prob
Chi-Square 16 575.9996 <.0001
Likelihood Ratio Chi-Square 16 599.6737 <.0001
Mantel-Haenszel Chi-Square 1 113.1199 <.0001
Phi Coefficient 0.1696
Contingency Coefficient 0.1672
Cramer's V 0.0848
Output 147. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Kidney Disease Stage and LDL Cholesterol Levels.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 113.1199 <.0001
2
Row Mean Scores
Differ
4 305.7924 <.0001
3 General Association 16 575.9708 <.0001
181 | P a g e
Output 148. Measures of the Strength of Association Between
Kidney Disease Stage and LDL Cholesterol Levels.
Statistic Value
95%
Confidence Limits
Gamma -0.1176 -0.1383 -0.0969
Kendall's Tau-b -0.0673 -0.0790 -0.0555
Stuart's Tau-c -0.0481 -0.0566 -0.0397
Somers' D C|R -0.0542 -0.0637 -0.0448
Somers' D R|C -0.0834 -0.0980 -0.0688
Pearson Correlation -0.0752 -0.0879 -0.0624
Spearman Correlation -0.0772 -0.0905 -0.0640
Lambda Asymmetric C|R 0.0000 0.0000 0.0000
Lambda Asymmetric R|C 0.0065 0.0000 0.0131
Lambda Symmetric 0.0045 0.0000 0.0091
Uncertainty Coefficient C|R 0.0158 0.0134 0.0182
Uncertainty Coefficient R|C 0.0113 0.0096 0.0130
Uncertainty Coefficient
Symmetric
0.0132 0.0111 0.0152
182 | P a g e
Output 149. Frequency Table of Kidney Disease Stage Kidney
Disease Stage (Stage 1 – GFR ≥ 90; Stage 2- GFR < 90 and GFR≥
60; Stage 3 – GFR < 60 and GFR ≥ 30; Stage 4 – GFR < 30 and GFR
≥ 15 and Stage 5 – GFR < 15. Glomerular Flow Rate: mL/min per
1.73 m2) by Triglyceride Category. Normal <150 mg/dL≤ High <
200 mg/dL ≤ Borderline High < 500 mg/dL ≤ Very High
Kidney
Disease Stage
Triglyceride Classification
Total
Frequency
Row Pct
Normal
Borderline
High
High
Very
High
1
6240
88.62
379
5.38
394
5.60
28
0.40
7041
2
5441
81.28
654
9.77
555
8.29
44
0.66
6694
3
1096
63.91
258
15.04
342
19.94
19
1.11
1715
4
115
53.24
40
18.52
54
25.00
7
3.24
216
5
3720
85.40
298
6.84
314
7.21
24
0.55
4356
Total 16612 1629 1659 122 20022
183 | P a g e
Output 150. Pearson Chi-Square Statistics of the Association Test
Between Kidney Disease Stage and Triglyceride Levels.
Statistic DF Value Prob
Chi-Square 12 815.2294 <.0001
Likelihood Ratio Chi-Square 12 693.7604 <.0001
Mantel-Haenszel Chi-Square 1 45.9262 <.0001
Phi Coefficient 0.2018
Contingency Coefficient 0.1978
Cramer's V 0.1165
Output 151. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Kidney Disease Stage and Triglyceride Levels.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 45.9262 <.0001
2
Row Mean Scores
Differ
4 735.6888 <.0001
3 General Association 12 815.1887 <.0001
184 | P a g e
Output 152. Measures of the Strength of Association Between
Kidney Disease Stage and LDL Triglyceride Levels.
Statistic Value
95%
Confidence Limits
Gamma 0.1680 0.1441 0.1920
Kendall's Tau-b 0.0803 0.0686 0.0921
Stuart's Tau-c 0.0493 0.0420 0.0565
Somers' D C|R 0.0521 0.0444 0.0597
Somers' D R|C 0.1240 0.1060 0.1420
Pearson Correlation 0.0479 0.0349 0.0609
Spearman Correlation 0.0886 0.0756 0.1015
Lambda Asymmetric C|R 0.0000 0.0000 0.0000
Lambda Asymmetric R|C 0.0348 0.0281 0.0415
Lambda Symmetric 0.0276 0.0223 0.0329
Uncertainty Coefficient C|R 0.0290 0.0245 0.0336
Uncertainty Coefficient R|C 0.0131 0.0110 0.0151
Uncertainty Coefficient
Symmetric
0.0180 0.0152 0.0208
185 | P a g e
Output 153. Frequency table of Serum Uric Acid Tierces by Total
Cholesterol Category (Desirable <200 mg/dL≤ Borderline High <
240 mg/dL ≤ High).
Uric Acid
Tierces
Total Cholesterol Classification
Total
Frequency
Row Pct
Desirable Borderline High
1
6478
62.78
2434
23.59
1406
13.63
10318
2
3420
47.62
2216
30.85
1546
21.53
7182
3
2407
95.44
62
2.46
53
2.10
2522
Total 12305 4712 3005 20022
Output 154. Pearson Chi-Square Statistics of the Association Test
Between Serum Uric Acid Tierces and Total Cholesterol Levels.
Statistic DF Value Prob
Chi-Square 4 1836.5523 <.0001
Likelihood Ratio Chi-Square 4 2217.4426 <.0001
Mantel-Haenszel Chi-Square 1 151.5587 <.0001
Phi Coefficient 0.3029
Contingency Coefficient 0.2899
Cramer's V 0.2142
186 | P a g e
Output 155. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Serum Uric Acid Tierces and Total Cholesterol
Levels.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 151.5587 <.0001
2
Row Mean Scores
Differ
2 1566.0461 <.0001
3 General Association 4 1836.4605 <.0001
187 | P a g e
Output 156. Measures of the Strength of Association Between Serum
Uric Acid Tierces and Total Cholesterol Levels.
Statistic Value
95%
Confidence Limits
Gamma -0.0811 -0.1029 -0.0593
Kendall's Tau-b -0.0459 -0.0581 -0.0336
Stuart's Tau-c -0.0390 -0.0495 -0.0285
Somers' D C|R -0.0441 -0.0558 -0.0324
Somers' D R|C -0.0478 -0.0606 -0.0349
Pearson Correlation -0.0870 -0.0990 -0.0750
Spearman Correlation -0.0506 -0.0639 -0.0373
Lambda Asymmetric C|R 0.0000 0.0000 0.0000
Lambda Asymmetric R|C 0.0144 0.0035 0.0253
Lambda Symmetric 0.0080 0.0020 0.0141
Uncertainty Coefficient C|R 0.0599 0.0558 0.0640
Uncertainty Coefficient R|C 0.0571 0.0532 0.0609
Uncertainty Coefficient
Symmetric
0.0585 0.0545 0.0624
188 | P a g e
Output 157. Frequency table of Serum Uric Acid Tierces by HDL
Cholesterol Category. Low < 40 mg/dL ≤ Normal < 60 mg/dL ≤
High.
Uric Acid Tierces HDL Cholesterol Classification
TotalFrequency
Row Pct
Low Normal High
1
783
7.59
4414
42.78
5121
49.63
10318
2
1043
14.52
3486
48.54
2653
36.94
7182
3
2336
92.62
100
3.97
86
3.41
2522
Total 4162 8000 7860 20022
Output 158. Pearson Chi-Square Statistics of the Association Test
Between Serum Uric Acid Tierces and HDL Cholesterol Levels.
Statistic DF Value Prob
Chi-Square 4 9350.2879 <.0001
Likelihood Ratio Chi-Square 4 7810.8341 <.0001
Mantel-Haenszel Chi-Square 1 4772.8994 <.0001
Phi Coefficient 0.6834
Contingency Coefficient 0.5642
Cramer's V 0.4832
189 | P a g e
Output 159. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Serum Uric Acid Tierces and HDL Cholesterol
Levels.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 4772.8994 <.0001
2
Row Mean Scores
Differ
2 6195.8845 <.0001
3 General Association 4 9349.8209 <.0001
190 | P a g e
Output 160. Measures of the Strength of Association Between Serum
Uric Acid Tierces and HDL Cholesterol Levels.
Statistic Value
95%
Confidence Limits
Gamma -0.5760 -0.5918 -0.5602
Kendall's Tau-b -0.3860 -0.3982 -0.3738
Stuart's Tau-c -0.3566 -0.3687 -0.3445
Somers' D C|R -0.4030 -0.4155 -0.3905
Somers' D R|C -0.3697 -0.3817 -0.3577
Pearson Correlation -0.4883 -0.5002 -0.4764
Spearman Correlation -0.4180 -0.4311 -0.4049
Lambda Asymmetric C|R 0.2448 0.2293 0.2603
Lambda Asymmetric R|C 0.1600 0.1497 0.1704
Lambda Symmetric 0.2069 0.1957 0.2182
Uncertainty Coefficient C|R 0.1840 0.1765 0.1915
Uncertainty Coefficient R|C 0.2010 0.1933 0.2087
Uncertainty Coefficient
Symmetric
0.1921 0.1846 0.1997
191 | P a g e
Output 161. Frequency table of Serum Uric Acid Tierces by LDL
Cholesterol Category. Optimal < 100 mg/dL≤ Near Optimal < 130
mg/dL ≤ Borderline High < 160 ≤ High < 190 ≤ Very High.
Uric Acid
Tierces
LDL Cholesterol Classification
Total
Frequency
Row Pct
Optimal
Near
Optimal
Borderline
High
High
Very
High
1
7262
70.38
1495
14.49
913
8.85
403
3.91
245
2.37
10318
2
4616
64.27
949
13.21
889
12.38
460
6.40
268
3.73
7182
3
2450
97.15
30
1.19
15
0.59
19
0.75
8
0.32
2522
Total 14328 2474 1817 882 521 20022
Output 162. Pearson Chi-Square Statistics of the Association Test
Between Serum Uric Acid Tierces and LDL Cholesterol Levels.
Statistic DF Value Prob
Chi-Square 8 1104.8158 <.0001
Likelihood Ratio Chi-Square 8 1446.4431 <.0001
Mantel-Haenszel Chi-Square 1 131.9364 <.0001
Phi Coefficient 0.2349
Contingency Coefficient 0.2287
Cramer's V 0.1661
192 | P a g e
Output 163. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Serum Uric Acid Tierces and LDL Cholesterol Levels.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 131.9364 <.0001
2
Row Mean Scores
Differ
2 813.9866 <.0001
3 General Association 8 1104.7606 <.0001
Output 164. Measures of the Strength of Association Between Serum
Uric Acid Tierces and LDL Cholesterol Levels.
Statistic Value
95%
Confidence Limits
Gamma -0.1384 -0.1617 -0.1152
Kendall's Tau-b -0.0701 -0.0818 -0.0585
Stuart's Tau-c -0.0549 -0.0641 -0.0458
Somers' D C|R -0.0621 -0.0723 -0.0518
Somers' D R|C -0.0793 -0.0925 -0.0660
Pearson Correlation -0.0812 -0.0925 -0.0699
Spearman Correlation -0.0778 -0.0905 -0.0651
Lambda Asymmetric C|R 0.0000 0.0000 0.0000
Lambda Asymmetric R|C 0.0082 0.0008 0.0157
Lambda Symmetric 0.0052 0.0005 0.0099
Uncertainty Coefficient C|R 0.0381 0.0351 0.0411
Uncertainty Coefficient R|C 0.0372 0.0343 0.0401
Uncertainty Coefficient
Symmetric
0.0377 0.0347 0.0406
193 | P a g e
Output 165. Frequency table of Serum Uric Acid Tierces by
Triglyceride Category. Normal <150 mg/dL ≤ High < 200 mg/dL ≤
Borderline High < 500 mg/dL ≤ Very High
Uric Acid
Tierces
Triglyceride Classification
Total
Frequency
Row Pct
Normal
Borderline
High
High
Very
High
1
8921
86.46
722
7.00
640
6.20
35
0.34
10318
2
5245
73.03
879
12.24
975
13.58
83
1.16
7182
3
2446
96.99
28
1.11
44
1.74
4
0.16
2522
Total 16612 1629 1659 122 20022
Output 166. Pearson Chi-Square Statistics of the Association Test
Between Serum Uric Acid Tierces and Triglyceride Levels.
Statistic DF Value Prob
Chi-Square 6 961.2003 <.0001
Likelihood Ratio Chi-Square 6 1058.8144 <.0001
Mantel-Haenszel Chi-Square 1 2.0674 0.1505
Phi Coefficient 0.2191
Contingency Coefficient 0.2140
Cramer's V 0.1549
194 | P a g e
Output 167. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Serum Uric Acid Tierces and Triglyceride Levels.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 2.0674 0.1505
2
Row Mean Scores
Differ
2 871.1453 <.0001
3 General Association 6 961.1523 <.0001
Output 168. Measures of the Strength of Association Between Serum
Uric Acid Tierces and Triglyceride Levels.
Statistic Value
95%
Confidence Limits
Gamma 0.0873 0.0600 0.1147
Kendall's Tau-b 0.0368 0.0251 0.0485
Stuart's Tau-c 0.0232 0.0158 0.0305
Somers' D C|R 0.0262 0.0178 0.0345
Somers' D R|C 0.0518 0.0353 0.0682
Pearson Correlation 0.0102 -0.0010 0.0214
Spearman Correlation 0.0389 0.0264 0.0514
Lambda Asymmetric C|R 0.0000 0.0000 0.0000
Lambda Asymmetric R|C 0.0556 0.0443 0.0670
Lambda Symmetric 0.0412 0.0328 0.0496
Uncertainty Coefficient C|R 0.0443 0.0396 0.0490
Uncertainty Coefficient R|C 0.0272 0.0243 0.0302
Uncertainty Coefficient
Symmetric
0.0338 0.0301 0.0374
195 | P a g e
Output 169. Frequency table of Hypertension Level by Total
Cholesterol Category (Desirable <200 mg/dL≤ Borderline High <
240 mg/dL ≤ High).
Hypertension
classification
Total Cholesterol Classification
Total
Frequency
Row Pct
Desirable Borderline High
Normal
8856
73.53
2163
17.96
1025
8.51
12044
Prehypertension
3437
43.16
2547
31.99
1979
24.85
7963
Hypertension Stage 1
12
80.00
2
13.33
1
6.67
15
Total 12305 4712 3005 20022
Output 170. Pearson Chi-Square Statistics of the Association Test
Between Hypertension Level by Total Cholesterol Category.
Statistic DF Value Prob
Chi-Square 4 1975.2436 <.0001
Likelihood Ratio Chi-Square 4 1976.6433 <.0001
Mantel-Haenszel Chi-Square 1 1879.2612 <.0001
Phi Coefficient 0.3141
Contingency Coefficient 0.2997
Cramer's V 0.2221
196 | P a g e
Output 171. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Hypertension Level by Total Cholesterol Category.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 1879.2612 <.0001
2
Row Mean Scores
Differ
2 1907.2964 <.0001
3 General Association 4 1975.1450 <.0001
Output 172. Measures of the Strength of Association Between
Hypertension Level by Total Cholesterol Category.
Statistic Value
95%
Confidence Limits
Gamma 0.5293 0.5102 0.5484
Kendall's Tau-b 0.3000 0.2872 0.3128
Stuart's Tau-c 0.2300 0.2200 0.2400
Somers' D C|R 0.3195 0.3057 0.3333
Somers' D R|C 0.2817 0.2697 0.2937
Pearson Correlation 0.3064 0.2930 0.3197
Spearman Correlation 0.3128 0.2995 0.3262
Lambda Asymmetric C|R 0.0000 0.0000 0.0000
Lambda Asymmetric R|C 0.1677 0.1480 0.1874
Lambda Symmetric 0.0853 0.0749 0.0956
Uncertainty Coefficient C|R 0.0534 0.0488 0.0580
Uncertainty Coefficient R|C 0.0728 0.0665 0.0791
Uncertainty Coefficient
Symmetric
0.0616 0.0563 0.0669
197 | P a g e
Output 173. Frequency table of Hypertension Level by HDL
Cholesterol Category. Low < 40 mg/dL≤ Normal < 60 mg/dL ≤
High.
Hypertension
classification
Total Cholesterol Classification
Total
Frequency
Row Pct
Desirable Borderline High
Normal
2723
22.61
4631
38.45
4690
38.94
12044
Prehypertension
1436
18.03
3361
42.21
3166
39.76
7963
Hypertension Stage 1
3
20.00
8
53.33
4
26.67
15
Total 4162 8000 7860 20022
Output 174. Pearson Chi-Square Statistics of the Association Test
Between Hypertension Level by HDL Cholesterol Category.
Statistic DF Value Prob
Chi-Square 4 67.3101 <.0001
Likelihood Ratio Chi-Square 4 68.0617 <.0001
Mantel-Haenszel Chi-Square 1 23.8945 <.0001
Phi Coefficient 0.0580
Contingency Coefficient 0.0579
Cramer's V 0.0410
198 | P a g e
Output 175. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Hypertension Level by HDL Cholesterol Category.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 23.8945 <.0001
2
Row Mean Scores
Differ
2 24.9928 <.0001
3 General Association 4 67.3068 <.0001
Output 176. Measures of the Strength of Association Between
Hypertension Level by HDL Cholesterol Category.
Statistic Value
95%
Confidence Limits
Gamma 0.0527 0.0293 0.0762
Kendall's Tau-b 0.0293 0.0163 0.0423
Stuart's Tau-c 0.0244 0.0135 0.0352
Somers' D C|R 0.0339 0.0188 0.0489
Somers' D R|C 0.0253 0.0140 0.0365
Pearson Correlation 0.0345 0.0209 0.0482
Spearman Correlation 0.0309 0.0172 0.0446
Lambda Asymmetric C|R 0.0049 0.0000 0.0206
Lambda Asymmetric R|C 0.0000 0.0000 0.0000
Lambda Symmetric 0.0030 0.0000 0.0124
Uncertainty Coefficient C|R 0.0016 0.0008 0.0024
Uncertainty Coefficient R|C 0.0025 0.0013 0.0037
Uncertainty Coefficient
Symmetric
0.0020 0.0010 0.0029
199 | P a g e
Output 177. Frequency table of Hypertension Level by LDL
Cholesterol Category. Optimal < 100 mg/dL≤ Near Optimal < 130
mg/dL ≤ Borderline High < 160 ≤ High < 190 ≤ Very High.
Hypertension
classification
LDL Cholesterol Classification
Total
Frequency
Row Pct
Optimal
Near
optimal
Borderline
high
High
Very
high
Normal
8990
74.64
1576
13.09
902
7.49
367
3.05
209
1.74
12044
Prehypertension
5328
66.91
894
11.23
915
11.49
514
6.45
312
3.92
7963
Hypertension
Stage 1
10
66.67
4
26.67
0
0.00
1
6.67
0
0.00
15
Total 14328 2474 1817 882 521 20022
Output 178. Pearson Chi-Square Statistics of the Association Test
Between Hypertension Level by LDL Cholesterol Category.
Statistic DF Value Prob
Chi-Square 8 356.6429 <.0001
Likelihood Ratio Chi-Square 8 350.3615 <.0001
Mantel-Haenszel Chi-Square 1 296.7764 <.0001
Phi Coefficient 0.1335
Contingency Coefficient 0.1323
Cramer's V 0.0944
200 | P a g e
Output 179. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Hypertension Level by LDL Cholesterol Category.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 296.7764 <.0001
2
Row Mean Scores
Differ
2 300.1349 <.0001
3 General Association 8 356.6251 <.0001
Output 180. Measures of the Strength of Association Between
Hypertension Level by LDL Cholesterol Category.
Statistic Value
95%
Confidence Limits
Gamma 0.1986 0.1719 0.2253
Kendall's Tau-b 0.0961 0.0827 0.1095
Stuart's Tau-c 0.0679 0.0583 0.0774
Somers' D C|R 0.0943 0.0810 0.1075
Somers' D R|C 0.0980 0.0844 0.1116
Pearson Correlation 0.1218 0.1077 0.1358
Spearman Correlation 0.1008 0.0867 0.1148
Lambda Asymmetric C|R 0.0000 0.0000 0.0000
Lambda Asymmetric R|C 0.0330 0.0193 0.0467
Lambda Symmetric 0.0192 0.0112 0.0273
Uncertainty Coefficient C|R 0.0092 0.0073 0.0111
Uncertainty Coefficient R|C 0.0129 0.0102 0.0156
Uncertainty Coefficient
Symmetric
0.0108 0.0085 0.0130
201 | P a g e
Output 181. Frequency table of Hypertension Level by Triglyceride
Category. Normal <150 mg/dL≤ High < 200 mg/dL ≤ Borderline
High < 500 mg/dL ≤ Very High
Hypertension
classification
Triglyceride Classification
Total
Frequency
Row Pct
Normal
Borderline
high
High
Very
high
Normal
10766
89.39
654
5.43
594
4.93
30
0.25
12044
Prehypertension
5833
73.25
973
12.22
1065
13.37
92
1.16
7963
Hypertension Stage 1
13
86.67
2
13.33
0
0.00
0
0.00
15
Total 16612 1629 1659 122 20022
Output 182. Pearson Chi-Square Statistics of the Association Test
Between Hypertension Level by Triglyceride Levels.
Statistic DF Value Prob
Chi-Square 6 900.8330 <.0001
Likelihood Ratio Chi-Square 6 884.7617 <.0001
Mantel-Haenszel Chi-Square 1 829.7047 <.0001
Phi Coefficient 0.2121
Contingency Coefficient 0.2075
Cramer's V 0.1500
202 | P a g e
Output 183. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Hypertension Level by Triglyceride Levels.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 829.7047 <.0001
2
Row Mean Scores
Differ
2 841.2317 <.0001
3 General Association 6 900.7880 <.0001
Output 184. Measures of the Strength of Association Between
Hypertension Level by Triglyceride Levels.
Statistic Value
95%
Confidence Limits
Gamma 0.4898 0.4623 0.5174
Kendall's Tau-b 0.2062 0.1927 0.2197
Stuart's Tau-c 0.1170 0.1089 0.1251
Somers' D C|R 0.1625 0.1513 0.1737
Somers' D R|C 0.2617 0.2448 0.2786
Pearson Correlation 0.2036 0.1899 0.2172
Spearman Correlation 0.2109 0.1971 0.2248
Lambda Asymmetric C|R 0.0000 0.0000 0.0000
Lambda Asymmetric R|C 0.1068 0.0932 0.1203
Lambda Symmetric 0.0748 0.0653 0.0843
Uncertainty Coefficient C|R 0.0370 0.0323 0.0418
Uncertainty Coefficient R|C 0.0326 0.0283 0.0369
Uncertainty Coefficient
Symmetric
0.0347 0.0302 0.0392
203 | P a g e
Output 185. Frequency table of Hypertension Level by Kidney
Disease Stage. Stage 1 – GFR ≥ 90; Stage 2- GFR < 90 and GFR≥
60; Stage 3 – GFR < 60 and GFR ≥ 30; Stage 4 – GFR < 30 and GFR
≥ 15 and Stage 5 – GFR < 15. Glomerular Flow Rate (mL/min per
1.73 m2) was calculated accordingly to KD-EPI equation124.
Hypertension
classification
Kidney Disease Stage
Total
Frequency
Row Pct
1 2 3 4 5
Normal
5419
44.99
3891
32.31
286
2.37
27
0.22
2421
20.10
12044
Prehypertension
1615
20.28
2799
35.15
1429
17.95
189
2.37
1931
24.25
7963
Hypertension Stage
1
7
46.67
4
26.67
0
0.00
0
0.00
4
26.67
15
Total 7041 6694 1715 216 4356 20022
Output 186. Pearson Chi-Square Statistics of the Association Test
Between Hypertension Level by Kidney Disease Stage.
Statistic DF Value Prob
Chi-Square 8 2446.4643 <.0001
Likelihood Ratio Chi-Square 8 2539.4921 <.0001
Mantel-Haenszel Chi-Square 1 679.7921 <.0001
Phi Coefficient 0.3496
Contingency Coefficient 0.3300
Cramer's V 0.2472
204 | P a g e
Output 187. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Hypertension Level by Kidney Disease Stage.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 679.7921 <.0001
2
Row Mean Scores
Differ
2 686.1876 <.0001
3 General Association 8 2446.3421 <.0001
Output 188. Measures of the Strength of Association Between
Hypertension Level by Kidney Disease Stage.
Statistic Value
95%
Confidence Limits
Gamma 0.3717 0.3528 0.3907
Kendall's Tau-b 0.2268 0.2147 0.2390
Stuart's Tau-c 0.1986 0.1879 0.2093
Somers' D C|R 0.2758 0.2610 0.2906
Somers' D R|C 0.1865 0.1765 0.1965
Pearson Correlation 0.1843 0.1707 0.1978
Spearman Correlation 0.2456 0.2325 0.2588
Lambda Asymmetric C|R 0.0912 0.0816 0.1008
Lambda Asymmetric R|C 0.1636 0.1537 0.1734
Lambda Symmetric 0.1188 0.1120 0.1255
Uncertainty Coefficient C|R 0.0479 0.0444 0.0513
Uncertainty Coefficient R|C 0.0936 0.0867 0.1004
Uncertainty Coefficient
Symmetric
0.0633 0.0588 0.0679
205 | P a g e
Output 189. Frequency table of Hypertension Level by Uric Acid
Tierces.
Hypertension
classification
Serum Uric Acid Tierce
Total
Frequency
Row Pct
1 2 3
Normal
7026
58.34
3142
26.09
1876
15.58
12044
Prehypertension
3288
41.29
4032
50.63
643
8.07
7963
Hypertension Stage 1
4
26.67
8
53.33
3
20.00
15
Total 10318 7182 2522 20022
Output 190. Pearson Chi-Square Statistics of the Association Test
Between Hypertension Level by Uric Acid Tierces.
Statistic DF Value Prob
Chi-Square 4 1293.3399 <.0001
Likelihood Ratio Chi-Square 4 1292.5910 <.0001
Mantel-Haenszel Chi-Square 1 91.4733 <.0001
Phi Coefficient 0.2542
Contingency Coefficient 0.2463
Cramer's V 0.1797
206 | P a g e
Output 191. Cochran-Mantel-Haenszel Statistics for the Association
Test Between Hypertension Level by Uric Acid Tierces.
Cochran-Mantel-Haenszel Statistics
Statistic Alternative Hypothesis DF Value Prob
1 Nonzero Correlation 1 91.4733 <.0001
2
Row Mean Scores
Differ
2 92.3514 <.0001
3 General Association 4 1293.2753 <.0001
Output 192. Measures of the Strength of Association Between
Hypertension Level by Uric Acid Tierces.
Statistic Value
95%
Confidence Limits
Gamma 0.1840 0.1608 0.2072
Kendall's Tau-b 0.1020 0.0888 0.1152
Stuart's Tau-c 0.0814 0.0709 0.0919
Somers' D C|R 0.1131 0.0985 0.1276
Somers' D R|C 0.0920 0.0800 0.1040
Pearson Correlation 0.0676 0.0541 0.0811
Spearman Correlation 0.1063 0.0926 0.1200
Lambda Asymmetric C|R 0.0771 0.0605 0.0937
Lambda Asymmetric R|C 0.1116 0.0919 0.1312
Lambda Symmetric 0.0926 0.0766 0.1087
Uncertainty Coefficient C|R 0.0333 0.0297 0.0368
Uncertainty Coefficient R|C 0.0476 0.0425 0.0527
Uncertainty Coefficient
Symmetric
0.0392 0.0350 0.0434
207 | P a g e
208 | P a g e
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