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Socioeconomic differences in health have been consistently observed worldwide. Physical health deteriorates more rapidly with age among men and women with lower socioeconomic status (SES) than among those with higher SES. The biological processes underlying these differences are best understood by adopting a life course approach. In this paper we introduce the pan- European LIFEPATH project which uses multiple cohorts - including biomarker data - to investigate ageing as a phenomenon with two broad stages across life: build-up and decline. The ‘build-up’ stage, from conception and early intra-uterine life to late adolescence or early twenties, is characterised by rapid successions of developmentally and socially sensitive periods. The second stage, starting in early adulthood, is a period of ‘decline’ from maximum attained health to loss of function, overt disease and death. LIFEPATH adopts a study design that integrates social science and public health approaches with biology (including molecular epidemiology), using well-characterised population cohorts and omics measurements (particularly epigenomics). LIFEPATH includes information and biological samples from 17 cohorts, including several with extensive phenotyping and repeat biological samples, and a very large cohort (1 million individuals) without biological samples (WHIP, from Italy). The countries that are covered by the cohorts are France, Italy, Portugal, Ireland, UK, Finland, Switzerland and Australia. These cohorts are only a small proportion of all cohorts available in Europe, but we have chosen them for the combination of good measures of socioeconomic status, risk factors for non-communicable diseases (NCDs) and biomarkers already measured (or availability of blood samples for further testing). The majority of cohorts include ‘hard’ outcomes (diabetes, cancer, Cardiovascular Disease (CVD), total mortality), and the extensively phenotyped cohorts also include several measurements of the functional components of healthy ageing, including frailty, impaired vision, cognitive function, renal and brain function, osteoporosis, sleep disturbances and mental health. All age groups are represented with two birth cohorts, one cohort of adolescents and several cohorts encompassing young adults (age 18 and above). Furthermore, there is a strong representation of elderly subjects in seven cohorts. The specific objectives of the project are: (a) to show that healthy ageing is an achievable goal for society; (b) to improve the understanding of the mechanisms through which healthy ageing pathways diverge by SES, by investigating life course biological pathways using omic technologies; (c) to examine the consequences of the current economic recession on health and the biology of ageing (and the consequent increase in social inequalities); (d) to provide updated, relevant and innovative evidence for healthy ageing policies (particularly ‘health in all policies’) using both observational studies and an experimental approach based on a reanalysis of data from a ‘conditional cash transfer’ randomised experiment in New York and new data collected as part of an earned income tax credit randomised experiment in Atlanta and New York. To achieve these objectives, data are used from three categories of studies: 1. national census-based followup data to obtain mortality by socioeconomic status; 2. cohorts with intense phenotyping and repeat biological samples; 3. large cohorts with biological samples. With these objectives and methodologies, LIFEPATH seeks to provide updated, relevant and innovative evidence to underpin future policies and strategies for the promotion of healthy ageing, targeted disease prevention and clinical interventions that address the issue of social disparities in ageing and the social determinants of health. The present paper describes the design and some initial results of LIFEPATH as an example of the integration of social and biological sciences to provide evidence for public health policies.

Background/objectives: In the African region, little is known about weight misperception among overweight or obese adults. We assessed the prevalence of weight misperception and predictors of weight misperception among overweight or obese adults in Mauritius. Height, weight, and self-perception of weight status data from 5736 adults (≥19 years of age), sampled in a population-based survey in 2009 were analysed. Weight status was defined using BMI calculated on the basis of measured height and weight. Information regarding self-perceived body weight, socio-demographic and self-rated health data were collected using a questionnaire. Results: Overall 41% of overweight or obese adults misclassified their own weight status. Among adults who were overweight or obese, weight misperception was increasingly less likely among those with increasing education (men: p = 0.02; women: p ≤ 0.001) but was more likely among those who perceived their overall health as good or excellent (men: PR = 1.29, 95% CI 1.10—1.52; women: PR = 1.42, 95% CI 1.26—1.60). Adults who were overweight or obese, weight misperception was increasingly less likely with increasing income (men: p = 0.025; women: p ≤ 0.001). Among women who were overweight or obese, weight misperception was increasingly more likely with increasing age (p ≤ 0.001) and those who self-reported Chinese ethnicity (PR = 1.48, 95% CI 1.22—1.78). Conclusion: A large proportion of adults in Mauritius misperceive their own weight status, with variation by socio-demographic characteristics and self-rated health. Future studies are needed to examine if correcting misperceptions of weight status may support obesity prevention and control efforts in Mauritius.

Healthy People 2010 identifies 10 Leading Health Indicators (LHIs),which may be used to monitor the nation’s progress in improving its public health efforts. These LHIs are listed in Table1. Each of these indicators is a global behavioral risk factor, collection of diseases, or social factor that can be measured and tracked. Regardless of the nature of the indicator,each is associated with multiple illnesses or conditions. Presently, the nation’s progress towards improving health outcomes related to these measures is tracked via changes in incidence rates, mortality rates, as well as other objective-specific outcomes via large national data sets.

Background: The cumulative effects of adverse social factors on the diabetes risk remains to be clarified. Design: Cross-sectional analysis of the US National Health and Nutrition Examination Survey (NHANES) 1999–2006. Methods: We included 10,276 adults aged ≥20 years. Diabetes mellitus was defined by physician diagnosis or fasting plasma glucose (≥126 mg/dl) or glycated hemoglobin (≥6.5%). Social risk factors (low family income, low education level, minority racial/ethnic group status, and single-living status) and health-related behaviors (physical activity and dietary intake) were self-reported. Social risk factors were combined in a cumulative social risk index (range 0 to ≥3) and logistic regression used to assess the association of cumulative social risk and diabetes, taking into account complex survey design and sampling weights. Results: Of 10,276 participants, 1515 (weighted proportion – 10%) had diabetes, 3295 (32.3%) and 1830 (9.0%) were exposed to ≥1 adverse social risk factor and ≥3 social risk factors, respectively. Diabetes was associated with increasing cumulative social risk in a graded manner (p for trend

Introduction: Lower-income Americans are suffering from declines in income, health, and longevity over time. Income and employment policies have been proposed as a potential nonmedical solution to this problem. Methods: An interrupted time series analysis of state-level incremental supplements to the Earned Income Tax Credit (EITC) program was performed using data from 1993 to 2010 Behavioral Risk Factor Surveillance System surveys and state-level life expectancy. The cost effectiveness of state EITC supplements was estimated using a microsimulation model, which was run in 2015. Results: Supplemental EITC programs increased health-related quality of life and longevity among the poor. The program costs about $7,786/quality-adjusted life-year gained (95% CI¼$4,100, $13,400) for the average recipient. This ratio increases with larger family sizes, costing roughly $14,261 (95% CI¼$8,735, $19,716) for a family of three. Conclusions: State supplements to EITC appear to be highly cost effective, but randomized trials are needed to confirm these findings.

Background Adults in the United States (U.S) can be simultaneously exposed to more than one social risk factor over their lifetime. However, cancer epidemiology tends to focus on single social risk factors at a time. We examined the prospective association between cumulative social risk exposure and deaths from cancer in a nationally representative sample of U.S. adults. Methods The study included 8745 adults (aged ≥ 40 years) in the NHANES Survey III Mortality Study over a median follow-up of 13.5 years (1988-1994 enrollment dates and 1988 through 2006 for mortality data). Social risk factors (low family income, low education level, minority race, and single-living status) were summed to create a cumulative social risk score (0 to ≥3). We used Cox proportional hazard models to estimate age- and sex-adjusted hazard ratios (HRs) and 95 % confidence intervals (95 % CI) for the association between cumulative social risk with deaths from all-cancers combined, tobacco-related cancers, and screening-detectable cancers. Results Deaths from all-cancers combined (P for trend = 0.001), tobacco-related cancers (P for trend =

Background: This study compares differences in quality-adjusted life expectancy across the eight original National Occupational Research Agenda (NORA) industry sectors. Methods: Data from the 1997 to 2012 National Health Interview Survey (NHIS) were used to estimate quality-adjusted life years (QALYs) for all workers and by NORA sector. Differences in QALYs were calculated and translated into economic values using estimates of the societal willingness-to-pay per QALY. Results: Mean QALYs across workers was 29.17 years. Among NORA sectors, wholesale, and retail trade workers had the highest average QALYs remaining (35.88), while mining workers had the lowest QALYs (31.4). The economic value of this difference ranges from $604,843 to $1,155,287 per worker depending on the societal willingness-to-pay per QALY. Conclusion: The value of life lost within some industries is very high relative to others. Additional investments in occupational safety, benefits, and health promotion initiatives may reduce these losses, but experimental research is needed to assess the effectiveness of such programs.

The association between education or income and mortality has been explored in great detail. These measures capture both the effects of material disadvantage on health and the psychosocial impacts of a low socioeconomic position on health. When explored independently of educational attainment and income, occupational prestige – a purely perceptual measure – serves as a measure of the impact of a psychosocial phenomenon on health. For instance, a fire-fighter, academician or schoolteacher may carry the social benefits of a higher social status without actually having the income (in all cases) or the educational credentials (in the case of the fire-fighter) to match. We explored the independent influence of occupational prestige on mortality. We applied Cox proportional hazards models to a nationally representative sample of over 380,000 US workers who had worked at any time between 1986 and 1994 with mortality follow up through 2002. We found that occupational prestige is associated with a decrease in the risk of all-cause, cancer, cardiovascular and respiratory-related mortality after controlling for household income and educational attainment. We further investigated the question of whether the effects of prestige are moderated by sex and broader occupational groupings. Prestige effects operate in white-collar occupations for men only and within service occupations for all workers.

In a letter to the editor, authors Peter A. Meunnig and Sherry A. Glied reply to Norman Edelman piece. They say that medical interventions that improve one’s quality of life certainly play an important role in the US health system. But they also play a role in other countries’ health systems.

People with more education typically live longer and healthier lives. High school graduates, for example, live about six to nine years longer than high school dropouts. They also are less likely to suffer from illness or disability in a variety of forms. In this chapter I seek to measure these benefits in dollar terms. I focus on the association between educational attainment and (1) reductions in morbidity and mortality and (2) reductions in government spending on health care. I examine these effects using a large, comprehensive health data set, the Medical Expenditure Panel Survey, covering the non-institutionalized civilian population in the United States. On the basis of conservative assumptions, I conclude that each additional high school graduate represents a health-related gain to the government of at least $39,000 in discounted lifetime medical expenditures. Monetized gains in health and longevity amount to an additional $183,000. I also discuss the limitations of this analysis.

Background: High school graduates live six to nine years longer than high school dropouts. Those with less education are more likely to die prematurely of cardiovascular disease, cancer, infectious disease, diabetes, lung disease, and injury than those with more education. Although there is growing evidence that the education-health relationship is causal, and some mechanisms linking education to health have been proposed, there is no gestalt for thinking about the health production function of education. Purpose: The purpose of this article is to outline the mechanisms through which education may produce health. Design: I explore the health risk factors that are more prevalent among those with lower educational attainment to ascertain whether such risk factors plausibly cause the diseases for which the less educated are at risk. To examine these relationships, I conduct a review of the public health, economics, endocrinology, sociology, neurosciences, and other literatures. Conclusions: A remarkably clear path can be drawn between what we now believe to be the risk factors for disease and the primary causes of death among those with lower attainment. Although hypothetical, the pathways outlined in this article can be used as a basis for thinking about the health production function of education. These mechanisms may better allow policy makers to understand the relationship between education and health. They may also be used to guide future research on the health benefits of education. Finally, although the proposed pathways are hypothetical, there is good overall evidence that education produces health. Therefore, health benefits should be included as core outcome measures in future education research.

In the past, states spent more on K–12 education than on any other budget item. However, in recent years, rising medical costs have changed this pattern; in 2003, health care expenses surpassed education as the largest item in states’ budgets. In fiscal year 2006, Medicaid alone is estimated to account for approximately 22 percent of total state spending, while all health care costs will account for about 32 percent of states’ expenditures (National Governors Association & National Association of State Budget Officers, 2006). These costs keep going up, and absent some drastic change, there is every indication that they will continue to outpace most states’ economic growth (Pew Research Center, 2006).

This paper examines social entrepreneurship in a Burmese refugee community as it strives to provide primary education to its children. Despite facing discrimination and fearing Thai authorities, our project leaders exemplified social entrepreneurship, most notably building social capital and agency within the refugee community, and surprisingly resolving intractable problems. Key processes included helping parents claim ownership of the program, depoliticizing the children's access to education, and encouraging high expectations of school performance. Social relationships built an internally sustainable project at virtually no cost and established bridges across antipathetic parties. We argue that the social entrepreneurship model is useful in contexts where poor communities cannot access non-governmental organizations or government agencies.

A number of intervention strategies to improve the rate of early stage breast cancer detection have been proposed and evaluated. Though good effectiveness data exist, policymakers and medical administrators may be reluctant to implement such interventions because of cost considerations. Few cost-effectiveness analyses have been conducted on culturally-sensitive interventions that increase mammography screening rates or reduce barriers to receiving timely diagnostic testing and treatment for African-American women. This paper discusses an innovative cost effectiveness model, funded by the National Cancer Institute, and presents microeconomic estimates the cost of twelve community-based intervention strategies designed to improve early stage breast cancer detection rates and appropriate follow-up after an abnormal mammogram among African-American women. An innovation in the estimates is to include the value of women’s time. Community-based program costs range from $47 to $161 per patient on an ongoing basis. Same day scheduling of a mammogram with or without patient transportation, public service announcements, physician education, physician audit with feedback, and same day scheduling of a biopsy cost $47-$53 per patient per year on an ongoing basis. Interventions that require fulltime personnel to maintain the program, such as patient reminder letters, theory-based education, physician reminders, and telephone counseling, are more expensive and cost approximately $54- $57 per patient on an ongoing basis. The three most expensive interventions are the mobile mammography van, lay health workers, and church based navigators, costing approximately $67- $161 per patient In conclusion, the added costs of community-based cancer control programs for vulnerable African-American women are small and have the potential to be offset by the gains in quality-adjusted life years saved as a result of detection at an earlier stage of diagnosis and improved follow-up and treatment, particularly among high-risk communities.

Background. Health adjusted life years (HALYs) are used for estimating burden of disease and as outcomes in cost-effectiveness analyses of medical care and public health interventions. Objectives. The impact of use of health-related quality of life (HRQL) scores associated with the disability-adjusted life year (DALY), the quality-adjusted life year (QALY), and the years of healthy life (YHL) measure on burden of disease estimates by income and race for five illnesses was studied. Research Design. Abridged life tables were constructed using 1997 death certificate data from the National Center for Health Statistics. These tables were then quality-adjusted using prevalence data from the National Health Interview Survey and HRQL scores obtained using the Quality of Well-Being scale, the DALY, and the YHL measure to estimate burden of disease for five common diseases. Separate estimates were made for low and higher income families as well as black persons and white persons. Results. Measure-related burden of disease estimates differed substantially from one another. Rank order of disease burden was not maintained across measures. Discrepancies in the rank order of disease were greater when different sociodemographic groups were examined. Conclusions. Diseases and demographic groups will receive differing priorities for intervention or research depending on which measurement system is used to inform decision-making. Refinement and standardization of measures is necessary to enhance their utility for medical care and public health policy applications.

Background: The quality-adjusted life year (QALY) is an attractive outcome measure because it captures both health-related quality of life (HRQL) and life expectancy in a single metric. We present a method for calculating QALYs that is simple, utilizes data that are free of charge, and may improve consistency in burden-of-disease investigations. Methods: For purposes of illustration, we calculated the burden of disease due to stroke using two abridged life tables, each adjusted for HRQL. The first life table was generated using all-cause mortality and morbidity data (a reference cohort) and the second was generated using all diseases except stroke (a stroke-free cohort). The difference in total QALYs and in quality-adjusted life expectancy (QALE) was determined by subtraction. Results: Approximately 61,328 (95% CI=60,272, 62,383) QALYs were lost to stroke in the life-table cohort. Stroke is responsible for a decrement of 0.03 years of life expectancy and 0.61 years of QALE in the United States. Conclusions: The “years of health life”measure affords a rapid, inexpensive, and sensitive means for estimating the burden of disease for local health priorities and may assist research efforts in including QALYs as an outcome measure.

At present time, there is uncertainty regarding whether influenza-like illness in healthy adults is best managed by preventive efforts that use the trivalent influenza vaccine, administration of neuraminidase inhibitors at the onset of illness, or recommendation of supportive care alone at the onset of illness. We conducted a cost-effectiveness analysis that examined these 3 strategies for managing influenza-like illness. Vaccination with inactivated trivalent vaccine would save approximately $25 per person while resulting in a net gain of ∼3.2 quality-adjusted hours relative to providing treatment with the neuraminidase inhibitor oseltamivir. A quality-adjusted hour is a fraction of a quality-adjusted life-year, which is the equivalent of 1 year lived in perfect health. Treatment with oseltamivir was associated with an incremental cost-effectiveness of approximately $27,619 per quality-adjusted life-year gained relative to providing supportive care. Vaccination is cost-saving relative to providing either treatment with oseltamivir or providing supportive care alone.

Background Violence toward children (childhood victimization) is a major public health problem, with long-term consequences on economic well-being. The purpose of this study was to determine whether childhood victimization affects occupational prestige and income in young adulthood. We hypothesized that young adults who experienced more childhood victimizations would have less prestigious jobs and lower incomes relative to those with no victimization history. We also explored the pathways in which childhood victimization mediates the relationships between background variables, such as parent’s educational impact on the socioeconomic transition into adulthood. Methods A nationally representative sample of 8,901 young adults aged 18–28 surveyed between 1999–2009 from the National Longitudinal Survey of Youth 1997 (NLSY) were analyzed. Covariate-adjusted multivariate linear regression and path models were used to estimate the effects of victimization and covariates on income and prestige levels and on income and prestige trajectories. After each participant turned 18, their annual 2002 Census job code was assigned a yearly prestige score based on the 1989 General Social Survey, and their annual income was calculated via self-reports. Occupational prestige and annual income are time-varying variables measured from 1999–2009. Victimization effects were tested for moderation by sex, race, and ethnicity in the multivariate models. Results Approximately half of our sample reported at least one instance of childhood victimization before the age of 18. Major findings include 1) childhood victimization resulted in slower income and prestige growth over time, and 2) mediation analyses suggested that this slower prestige and earnings arose because victims did not get the same amount of education as non-victims. Conclusions Results indicated that the consequences of victimization negatively affected economic success throughout young adulthood, primarily by slowing the growth in prosperity due to lower education levels.

Introduction Many US workers are increasingly delaying retirement from work, which may be leading to an increase in chronic disease at the workplace. We examined the association of older adults’ health status with their employment/occupation and other characteristics. Methods National Health Interview Survey data from 1997 through 2011 were pooled for adults aged 65 or older (n = 83,338; mean age, 74.6 y). Multivariable logistic regression modeling was used to estimate the association of socioeconomic factors and health behaviors with 4 health status measures: 1) self-rated health (fair/poor vs good/very good/excellent); 2) multimorbidity (≤1 vs ≥2 chronic conditions); 3) multiple functional limitations (≤1 vs ≥2); and 4) Health and Activities Limitation Index (HALex) (below vs above 20th percentile). Analyses were stratified by sex and age (young–old vs old–old) where interactions with occupation were significant. Results Employed older adults had better health outcomes than unemployed older adults. Physically demanding occupations had the lowest risk of poor health outcomes, suggesting a stronger healthy worker effect: service workers were at lowest risk of multiple functional limitations (odds ratio [OR], 0.82; 95% confidence interval [CI], 0.71–0.95); and blue-collar workers were at lowest risk of multimorbidity (OR, 0.84; 95% CI, 0.74–0.97) and multiple functional limitation (OR, 0.84; 95% CI, 0.72–0.98). Hispanics were more likely than non-Hispanic whites to report fair/poor health (OR, 1.62; 95% CI, 1.52–1.73) and lowest HALex quintile (OR, 1.21; 95% CI, 1.13–1.30); however, they were less likely to report multimorbidity (OR, 0.78; 95% CI, 0.73–0.83) or multiple functional limitations (OR, 0.82; 95% CI, 0.77–0.88). Conclusion A strong association exists between employment and health status in older adults beyond what can be explained by socioeconomic factors (eg, education, income) or health behaviors (eg, smoking). Disability accommodations in the workplace could encourage employment among older adults with limitations.

OBJECTIVE Compare differences in health-related quality of life among blacks and whites to examine if race, diabetes, and visual impairment (VI) present a triple disadvantage in terms of quality-adjusted life expectancy. RESEARCH DESIGN AND METHODS Data were analyzed from the 2000–2003 Medical Expenditure Panel Survey, a nationally representative survey that contains the EuroQol 5D (EQ-5D). The EQ-5D generates health utility values that provide a measure of the morbidity associated with various health states, such as having moderate or severe problems with mobility. The EQ-5D score can be linked with life expectancy data to calculate quality-adjusted life-years (QALYs), the number of years of optimal health an individual is expected to live. Multivariate analyses were conducted to estimate and compare differences in QALYs by diabetes status, VI status, and race. RESULTS Whites had a higher quality-adjusted life expectancy across all diabetes/VI comparisons. Overall, blacks with diabetes and VI had the fewest number of QALYs remaining (19.6 years), and whites with no impairment had the greatest number of QALYs remaining (31.6 years). Blacks with diabetes only had 1.7 fewer years of optimal health (fewer QALYs) than whites with diabetes. Within individuals with both diabetes and VI, however, this gap more than doubled, with blacks experiencing 3.5 fewer QALYs than whites. CONCLUSIONS Although efforts to target and reduce racial health disparities associated with diabetes appear to be effective, black communities may be contributing to a greater overall burden of illness given poorer infrastructure and less accommodation for disabilities such as VI.