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      Present and future of health inequalities: Rationale for investing in the biological capital

      a , a , b , c , *

      EClinicalMedicine

      Elsevier

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          Abstract

          Good health is not, and probably never has been, equally distributed across countries and individuals. Social conditions can predict and stratify patterns in health in a population far better than any biological feature, risk factor or other variable [1]. Disadvantaged groups experience far worse health outcomes than their more affluent fellows, as, for instance, recently documented by the International Agency for Research on Cancer in a comprehensive review of social inequalities in cancer [1]. The different magnitude of health inequalities across countries and over time strongly suggests that some health systems fare better than others in supporting health for individuals, even when countries are experiencing economic downturns. Also, there is good evidence that health inequalities start in early life. Following the 2007–2008 financial crisis, Case and Deaton reported an unexpected inversion of the long-lasting increase in life expectancy in the U.S. [2]. Premature mortality in the U.S., affecting particularly white poor/middle class, was predominantly due to reasons related to social problems, e.g., increasing drug abuse and alcohol poisoning, suicide, liver disease, and was significantly exacerbated by the 2007/2008 recession [2]. In contrast, the average life expectancy in the World Health Organization (WHO) European Region has continued to steadily rise from 76.7 years in 2010 to 77.8 years in 2015. The more favorable scenario in Europe is likely due to the beneficial impact of the Welfare approach to health that acted as a buffer against the decline in health of sectors of the underserved population [3]. However, despite relatively strong commitment to providing social protection (i.e., access to health care, basic income security, access to nutrition, education, care and any other necessary goods and services) for all citizens, Europe is not immune from major health inequalities either. The recent WHO “Healthy, prosperous lives for all: the European Health Equity Status Report” describes the current status of health inequalities across the continent and the major driving factors [4]. Worryingly, deindustrialization has progressively led to high unemployment levels and declining income security while, concurrently, the average country expenditure on social protection has also plummeted. On average, 17 out of 100 people live in relative poverty (defined as the percentage of people living on or below 60% of median household disposable income after taxes and transfers) across the Region, i.e., an increase from 15 out of 100 in the year 2005. The overwhelming evidence showing that premature mortality in mid- and late-adulthood disproportionately affects socially disadvantaged people [5] is linked to social patterning observed in physical functioning, physiological wear-and-tear, and in molecular processes including epigenetic age acceleration [6]. All these changes are also mediated by risk factors including smoking, BMI and metabolic disorders, such as fatty liver and diabetes. However, the biological consequences of early exposure to social disadvantage begin well before a person has fully taken up individual health behaviors like smoking or poor diet. Overall, the accumulation of biological fingerprints of adverse conditions and hazardous exposures has an impact on the individual's biological capital, a concept that is not yet well characterized but that adds to the well-known concepts of economic, social and cultural capitals as proposed long ago by the sociologist Pierre Bourdieu [7]. Whereas preventive measures in the adult phase of life can only be based on a harm reduction approach, by promoting better health and mitigating the risks of previous exposures, recent empirical research highlights the importance of addressing also early life to magnify the benefits of these interventions and to mitigate social inequalities in health at all ages. Thus, it is necessary to simultaneously intervene on both traditional risk factors – such as smoking, alcohol, diet, overweight and obesity, and physical activity - and also on factors that lead to social deprivation, beginning in childhood [4]. Expenditure and investment in primary prevention in a child's early years of life could be more effective and cheaper than later interventions or mitigation. The Welfare State is key in buffering health inequalities, and social protection nets should be increasing, not shrinking, in order to reduce health disparities. Policies should be coordinated so that they impact each life stage, starting in infancy, if not at conception. A better understanding of the underlying mechanisms and of the biological capital is necessary to effectively implement primary prevention, avoid or interrupt exposure to hazardous behaviors and environments, and enable timely identification of health damage though appropriate early detection tools. Disclaimer Where authors are identified as personnel of the International Agency for Research on Cancer / World Health Organization, the authors alone are responsible for the views expressed in this article and they do not necessarily represent the decisions, policy or views of the International Agency for Research on Cancer / World Health Organization. Declaration of Competing Interest The authors have no conflict of interest to disclose.

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          Most cited references 4

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          Rising morbidity and mortality in midlife among white non-Hispanic Americans in the 21st century.

          This paper documents a marked increase in the all-cause mortality of middle-aged white non-Hispanic men and women in the United States between 1999 and 2013. This change reversed decades of progress in mortality and was unique to the United States; no other rich country saw a similar turnaround. The midlife mortality reversal was confined to white non-Hispanics; black non-Hispanics and Hispanics at midlife, and those aged 65 and above in every racial and ethnic group, continued to see mortality rates fall. This increase for whites was largely accounted for by increasing death rates from drug and alcohol poisonings, suicide, and chronic liver diseases and cirrhosis. Although all education groups saw increases in mortality from suicide and poisonings, and an overall increase in external cause mortality, those with less education saw the most marked increases. Rising midlife mortality rates of white non-Hispanics were paralleled by increases in midlife morbidity. Self-reported declines in health, mental health, and ability to conduct activities of daily living, and increases in chronic pain and inability to work, as well as clinically measured deteriorations in liver function, all point to growing distress in this population. We comment on potential economic causes and consequences of this deterioration.
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            Socioeconomic status and the 25 × 25 risk factors as determinants of premature mortality: a multicohort study and meta-analysis of 1·7 million men and women

            Summary Background In 2011, WHO member states signed up to the 25 × 25 initiative, a plan to cut mortality due to non-communicable diseases by 25% by 2025. However, socioeconomic factors influencing non-communicable diseases have not been included in the plan. In this study, we aimed to compare the contribution of socioeconomic status to mortality and years-of-life-lost with that of the 25 × 25 conventional risk factors. Methods We did a multicohort study and meta-analysis with individual-level data from 48 independent prospective cohort studies with information about socioeconomic status, indexed by occupational position, 25 × 25 risk factors (high alcohol intake, physical inactivity, current smoking, hypertension, diabetes, and obesity), and mortality, for a total population of 1 751 479 (54% women) from seven high-income WHO member countries. We estimated the association of socioeconomic status and the 25 × 25 risk factors with all-cause mortality and cause-specific mortality by calculating minimally adjusted and mutually adjusted hazard ratios [HR] and 95% CIs. We also estimated the population attributable fraction and the years of life lost due to suboptimal risk factors. Findings During 26·6 million person-years at risk (mean follow-up 13·3 years [SD 6·4 years]), 310 277 participants died. HR for the 25 × 25 risk factors and mortality varied between 1·04 (95% CI 0·98–1·11) for obesity in men and 2 ·17 (2·06–2·29) for current smoking in men. Participants with low socioeconomic status had greater mortality compared with those with high socioeconomic status (HR 1·42, 95% CI 1·38–1·45 for men; 1·34, 1·28–1·39 for women); this association remained significant in mutually adjusted models that included the 25 × 25 factors (HR 1·26, 1·21–1·32, men and women combined). The population attributable fraction was highest for smoking, followed by physical inactivity then socioeconomic status. Low socioeconomic status was associated with a 2·1-year reduction in life expectancy between ages 40 and 85 years, the corresponding years-of-life-lost were 0·5 years for high alcohol intake, 0·7 years for obesity, 3·9 years for diabetes, 1·6 years for hypertension, 2·4 years for physical inactivity, and 4·8 years for current smoking. Interpretation Socioeconomic circumstances, in addition to the 25 × 25 factors, should be targeted by local and global health strategies and health risk surveillance to reduce mortality. Funding European Commission, Swiss State Secretariat for Education, Swiss National Science Foundation, the Medical Research Council, NordForsk, Portuguese Foundation for Science and Technology.
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              Trends in health inequalities in 27 European countries

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                Author and article information

                Contributors
                Journal
                EClinicalMedicine
                EClinicalMedicine
                EClinicalMedicine
                Elsevier
                2589-5370
                04 February 2020
                February 2020
                04 February 2020
                : 19
                Affiliations
                [a ]International Agency for Research on Cancer, Lyon, France
                [b ]Imperial College London, London, United Kingdom
                [c ]Italian Institute of Technology, Genoa, Italy
                Author notes
                [* ]Corresponding author. p.vineis@ 123456imperial.ac.uk
                Article
                S2589-5370(20)30005-5 100261
                10.1016/j.eclinm.2020.100261
                7005444
                © 2020 Published by Elsevier Ltd.

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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