Orange_716_ppt_wide Orange_716_ppt_small The rising expectations of the past 150 years have led to a shift away from viewing health in terms of survival when life expectancy was about 40 years in most countries, through a phase of defining it in terms of freedom from disease, thence to an emphasis on the person’s ability to perform his daily activities, and more recently to an emphasis on positive themes of happiness, social and emotional well-being (pocit pohody), and quality of life. Orange_716_ppt_wide Outline •What is health and what is population health? •Rate, proportions, incidence and prevalence • Orange_716_ppt_wide What is health? • •Health is a multifaceted concept and not easily measurable. •WHO definition: –Health is a state of complete physical and mental well-being and not merely the absence of disease or infirmity (WHO, 1948) –stav kompletní fyzické, duševní a sociální pohody a nikoliv pouhé nepřítomnosti nemoci či vady – Define ill health, disability, Hands up if you meet that definition of health? Is health positive and negative? Can we measure health on a continuum? Is health different from disease, illness or sickness Orange_716_ppt_wide Criticisms of the WHO definition • • •Is it achievable? •Can it be measured? •Change in the burden of health since 1948 • •But various estimates show that among 70-95% of individuals could be classified as unhealthy on the basis of WHO definition • – Orange_716_ppt_wide A better definition? •Bircher (2005): “a dynamic state of well-being characterised by a physical and mental potential, which satisfies the demands of life commensurate with age, culture and personal responsibility” •OR •Huber et al (2011): “the ability to adapt and self manage in the face of social, physical and emotional challenges” Huber: schopnost adaptace tvari v tvar socialnim, fyzickym a emocnim vyzvam. Vidime, ze ta definice zdravi se stave cim dal vic obecnejsi Orange_716_ppt_wide What is population health? •“The health outcomes of a group of individuals, including the distribution of such outcomes within the group.” Kinding and Stoddart (2003) • •What do we mean by outcomes? •What do we mean by groups? •What do we mean by distribution? Orange_716_ppt_wide Population health outcomes •Mortality –Rates of death –Life expectancy •Morbidity –Disease: biochemical (e.g. blood glucose), physiological (e.g. blood pressure), and pathological (e.g. tumour size) –Disability or impairment –Self-reported and patient-based measures •General and composite measures • • No single measure can capture the health of the nation wide array of measures from which to choose. However, most of the commonly used measures have a shared goal: to meaningfully quantify and summarise some dimension of health or disease in a population. However, measures such as mortality rates and life expectancy only capture part of a community’s experience of health and disease - Most health outcome negative, but very few people have these conditions which leaves about 80% population healthy, but we don’t know how healthy. Have moved on from measuring inputs and throughputs in health systems such as number of people seen within certain time frame because they don’t necessarily mean the population health is better. Orange_716_ppt_wide Tools of measurement (I) •Numbers – actual number of events –Example: 100 cases of TB in Camden in 2003 Orange_716_ppt_wide Tools of measurement (II) •Proportion – a type of ratio in which the numerator is included in the denominator, often expressed as a percentage –Example: proportion of diabetics in the population •Rate – frequency with which an event occurs in a defined population, usually in a specified period of time –Example: mortality rate in 2014 Orange_716_ppt_wide Numerators and denominators •The number of cancer cases in the UK is 247,667 whereas in Belgium it is 47,948. •The UK has a bigger problem in numerical terms. •But do Belgians have lower risk of getting cancer? –Numerators alone are meaningless –We need both numerators AND denominators • Orange_716_ppt_wide Numerators and denominators •The number of cancer cases in the UK is 247,667 whereas in Belgium it is 47,948. •The UK has a bigger problem in numerical terms. •But do Belgians have lower risk of getting cancer? –Numerators alone are meaningless –We need both numerators AND denominators •UK: 247 667 / 60 000 000 = 0.00413 = 413 per 100 000 •Belgium: 47 948 / 10 000 000 = 0.00479 = 479 per 100 000 Orange_716_ppt_wide Type of rates •Crude rates: apply to the total population in a given area •Specific rates: apply to specific subgroups in the population (e.g. age, sex) or specific conditions •Standardised rates: used to permit comparison of rates in the population in which differ in structure (e.g. age structure) Orange_716_ppt_wide Population at risk •People who are potentially susceptible to the event •Populations are not static as a result of births, deaths and migration Orange_716_ppt_wide “Conventional” measures •Prevalence of a disease / exposure •Incidence of a disease •Mortality –all causes vs. cause-specific rates –all ages vs. age-specific rates •Life expectancy –At birth –At specific age Orange_716_ppt_wide Prevalence •No. of existing cases / number of persons in study •Per 100 (=%), per 1000 etc • Orange_716_ppt_wide Prevalence •Prevalence –Frequency of existing cases in a defined population at a given point in time. –Measure of disease burden –Can tell us point prevalence: the probability of people with a condition at a given point in time, or over a short period of time, period prevalence –All person with a condition/total population at risk –Often expressed per 1000 when frequency is small relative to population Orange_716_ppt_wide Adult prevalence by BMI status Health Survey for England (2008-2010 average) Adult (aged 16+) BMI thresholds Underweight: <18.5kg/m2 Healthy weight: 18.5 to <25kg/m2 Overweight: 25 to <30kg/m2 Obese: ≥30kg/m2 © NOO 2012 Healthy weight prevalence is much lower for men than for women (even though obesity prevalence is marginally higher for women than for men). This is because there is a much higher prevalence of overweight in men than in women. The published Health Survey for England data used to produce this chart are available from: http://www.ic.nhs.uk/statistics-and-data-collections/health-and-lifestyles-related-surveys/health-s urvey-for-england/health-survey-for-england--2010-trend-tables Orange_716_ppt_wide Incidence •No. of new cases / number of persons in study •Denominator: –Free of disease at the beginning of follow up –At risk: can develop the disease (e.g. non-vaccinated) •Per 100 (=%), per 1000 etc. • Orange_716_ppt_wide Incidence •Incidence –Number of new events in a defined population within a specified period of time. –Direct measure of risk that healthy people will develop a condition during a specified period of time –Tells us the rate at which new conditions occur in a defined, previously condition-free group of people –Number of new cases/ total population at risk • Cumulative indicidence and incidence rate Orange_716_ppt_wide Relationship between prevalence and incidence •The prevalence of a health-related outcome depends both on the incidence rate and the time between onset and recovery or death. •Prevalence = Incidence x Average disease duration •E.g. volume of water in watertank depends on –Inflow –Outflow Orange_716_ppt_wide Life expectancy Orange_716_ppt_wide Numbers of women expected to die at each age, out of 100,000 born, assuming mortality rates stay the same as 2010-2012. The expectation is 83 (mean), median 86, the most likely value (mode) is 90. Orange_716_ppt_wide Survival and health curves Orange_716_ppt_wide Healthy life expectancy (HALE) • •Healthy life expectancy (HLE), or health-adjusted life expectancy (HALE) measures the number of years that a person at a given age can expect to live in good health, accounting for mortality and disability •= the average number of years that a newborn can expect to live in "full health"—in other words, not hampered by disabling illnesses or injuries. •Summarises mortality and non-fatal outcomes in a single measure of average population health •Can compare health between countries or measure changes over time •Can inform policy questions dependent on how morbidity changes as mortality decreases • Orange_716_ppt_wide Life expectancy (LE), healthy life expectancy (HLE) and proportion of life in "Good" health for males and females at birth in England, 2011 to 2013 (ONS 2015) Figure 1.png Orange_716_ppt_wide Healthy life expectancy at birth by country, 2010 The Lancet 2012 380, 2144-2162 A – male HALE ; B – female HALE Orange_716_ppt_wide Epidemiology •The study of the distribution and determinants of the frequency of health-related outcomes in specified populations • •Quantitative discipline • •Measurement of disease / condition / risk factor frequency is central to epidemiology • •Comparisons require measurements Orange_716_ppt_wide Much of epidemiological research is taken up trying •to establish associations between exposures and disease rates •to measure the extent to which risk changes as the level of exposure changes •to establish whether the associations observed may be truly causal (rather than being just consequence of bias or chance) Orange_716_ppt_wide Measures of association •Risk of disease, rate of disease in different groups of population •Comparison of risks/rates • Orange_716_ppt_wide Measures of effect •We have 2 groups of individuals: •An exposed group (group with risk factor of interest) and unexposed group (without such factor of interest) •We are interested in comparing the amount of disease (mortality or other health outcome) in the exposed group to that in the unexposed group Orange_716_ppt_wide Risk ratio •we calculate the risk ratio (RR) as: •RR=r1/r0 Risk difference •the absolute difference between two risks (or rates) RD = r1 – r0 Orange_716_ppt_wide Example: cohort study of oral contraceptive use and heart attack Myocardial infarction Yes No Total OC use Yes 25 400 425 No 75 1500 1575 Total 100 1900 2000 Risk (exposed) = 25/425=0.059 Risk (unexposed) = 75/1575=0.048 Relative risk = 0.059/0.048 = 1.23 Orange_716_ppt_wide Risk or rate difference the absolute difference between two risks (or rates) RD = r1 – r0 Measure of the absolute effect Similar for rates = rate difference = incidence rate in exposed – incidence rate in unexposed Orange_716_ppt_wide Measures of population impact •Population attributable risk (PAR) is the absolute difference between the risk (or rate) in the whole population and the risk or rate in the unexposed group • PAR = r – r0 • Orange_716_ppt_wide Population attributable risk fraction (PARF or PAR%) •It is a measure of the proportion of all cases in the study population (exposed and unexposed) that may be attributed to the exposure, on the assumption of a causal association •It is also called the aetiologic fraction, the percentage population attributable risk or the attributable fraction Orange_716_ppt_wide •If r is rate in the total population • PAF = PAR/r • PAR = r – r0 • PAF = (r-r0)/r Orange_716_ppt_wide References •Bircher, Johannes. 2005. “Towards a Dynamic Definition of Health and Disease.” Medicine, Health Care and Philosophy 8(3): 335–41. http://dx.doi.org/10.1007/s11019-005-0538-y. •Huber, Machteld et al. 2011. “How Should We Define Health?” BMJ 343. •Kindig, David, and Greg Stoddart. 2003. “What Is Population Health?” American Journal of Public Health 93(3): 380–83. http://dx.doi.org/10.2105/AJPH.93.3.380. •World Health Organisation (WHO). 1948. Preamble to the Constitution of the World Health Organisation as adopted by the International Health Conference, New York, 19-22 June 1948. •