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Original Article How does socio economic position link to health behaviour? Sociological pathways and perspectives for health promotion Simone Weyers1, Nico Dragano1, Matthias Richter2 and Hans Bosma3 Abstract: Socio economic inequalities in adult health behaviour are consistently observed. Despite a well-documented pattern, social determinants of variations in health behaviour have not been suffi- ciently clarified. This article therefore presents sociological pathways to explain the existing inequal- ities in health behaviour. At a micro level, control beliefs have been part of several behavioural theories. We suggest that these beliefs might bridge the gap between sociology and psychology by emphasising their roots in fundamental socio-economic environments. At a meso level, social net- works and support have not been explicitly considered as behavioural determinants. This contribu- tion states that these social factors influence health behaviour while being unequally distributed across society. At a macro level, characteristics of the neighbourhood environment influence health behaviour of its residents above and beyond their individual background. Providing further oppor- tunity for policy makers, it is shown that peer and school context equalise inequalities in risky behav- iour in adolescence. As a conclusion, factors such as control expectations, social networks, neighbourhood characteristics, and school context should be included as strategies to improve health behaviour in socially disadvantaged people. (Global Health Promotion, 2010; 17(2): pp. 25–33) Key words: behaviour, control, inequalities, neighbourhood, school, social networks Introduction Socio-economic inequalities in adult health behaviour are consistently observed. Comparative analyses across Europe have shown that we mostly find an inverse social gradient of smoking, physi- cal inactivity, and unfavourable nutrition (1,2). Despite this well-documented pattern, the psycho- logical and social determinants of variations in health behaviour have not been sufficiently clarified. Theories of health behaviour are mostly psycho- logical and contextual aspects are seldom recog- nized – if any, only in an indirect way. For instance, norms and values leading to planned behaviour (3) 1. Correspondence to: Simone Weyers, Department of Medical Sociology, Heinrich-Heine-University, Universitätsstrasse 1 Duesseldorf 40225, Germany. Tel: +49 (211) 81–14825; Fax: +49 (211) 81–12390. ([email protected]) 2. Institute of Social and Preventive Medicine, University of Bern, Switzerland. 3. Social Medicine, CAPHRI, Maastricht University, Netherlands. (This manuscript was submitted on May 26, 2009. Following blind peer review, it was accepted for publication on September 24, 2009.) Global Health Promotion 1757-9759; Vol 17(2): 25–33; 365232 Copyright © The Author(s) 2010, Reprints and permissions: http://www.sagepub.co.uk/journalspermissions.nav DOI: 10.1177/1757975910365232 http://g.
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Assignment Overview: Cyber is a relatively new word that did not gain prominence until three short decades ago. Since then, words such as cyberwar, cyber-attack, cyber-crime, cyberterrorism, and cybersecurity have emerged. In April 2015, Loretta Lynch became the nation's new attorney general. At the forefront of the attorney general's security concerns are social media technology, ISIS systematically exploiting the Internet, and the threat of cyber-attack. According to Lynch, a cyber-attack by the Islamic State is perhaps the terror group’s biggest emerging threat. "Concern that ISIS or any of our foreign enemies might develop that capacity … is the thing that keeps me and many of my colleagues in law enforcement up at night,” Lynch told ABC’s News' Pierre Thomas. Understanding cyber threats begins with understanding the history of technology. Assignment Task: History and advancing technology make it imperative to examine the cyber significance of the years 1945, 1963, 1969, 1970, 1979, 1983, and 1984 to better understand how these advancements have historically influenced modern day cybersecurity. From your research, discuss how ISIS-type organizations have exploited advancements in technology. Describe how these historical influences have affected national security. Key Concepts in Public Health Determinants of Health Contributors: Soumen Sengupta Edited by: Frances Wilson & Mzwandile Mabhala Book Title: Key Concepts in Public Health Chapter Title: "Determinants of Health" Pub. Date: 2009 Access Date: February 16, 2020 Publishing Company: SAGE Publications Ltd City: London Print ISBN: 9781412948807 Online ISBN: 9781446216736 DOI: http://dx.doi.org/10.4135/9781446216736.n4 Print pages: 16-20 © 2009 SAGE Publications Ltd All Rights Reserved. This PDF has been generated from SAGE Knowledge. Please note that the pagination of the online version will vary from the pagination of the print book. javascript:void(0); javascript:void(0); http://dx.doi.org/10.4135/9781446216736.n4 Determinants of Health SoumenSengupta Definition Health is classically defined as ‘a state of complete physical, social and mental health, and not merely the absence of disease or infirmity’ (WHO, 1948). As such, health is as much a social construct as a biological characteristic. It is the product of a complex interaction of different factors: this is true at both individual and population levels. These determinants include not just an individual's particular characteristics and behav- iours but also their economic, physical and social environments (Ashton and Seymour, 1992). Key Points • Health is created by a complicated interaction of different factors, only some of which can be directly influenced by individuals. • Social determinants tend to have a greater impact on population health status than healthcare ser- vices. • Different determinants have a differential influence on different groups of people: this can contribute t ...
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Assignment Overview: Cyber is a relatively new word that did not gain prominence until three short decades ago. Since then, words such as cyberwar, cyber-attack, cyber-crime, cyberterrorism, and cybersecurity have emerged. In April 2015, Loretta Lynch became the nation's new attorney general. At the forefront of the attorney general's security concerns are social media technology, ISIS systematically exploiting the Internet, and the threat of cyber-attack. According to Lynch, a cyber-attack by the Islamic State is perhaps the terror group’s biggest emerging threat. "Concern that ISIS or any of our foreign enemies might develop that capacity … is the thing that keeps me and many of my colleagues in law enforcement up at night,” Lynch told ABC’s News' Pierre Thomas. Understanding cyber threats begins with understanding the history of technology. Assignment Task: History and advancing technology make it imperative to examine the cyber significance of the years 1945, 1963, 1969, 1970, 1979, 1983, and 1984 to better understand how these advancements have historically influenced modern day cybersecurity. From your research, discuss how ISIS-type organizations have exploited advancements in technology. Describe how these historical influences have affected national security. Key Concepts in Public Health Determinants of Health Contributors: Soumen Sengupta Edited by: Frances Wilson & Mzwandile Mabhala Book Title: Key Concepts in Public Health Chapter Title: "Determinants of Health" Pub. Date: 2009 Access Date: February 16, 2020 Publishing Company: SAGE Publications Ltd City: London Print ISBN: 9781412948807 Online ISBN: 9781446216736 DOI: http://dx.doi.org/10.4135/9781446216736.n4 Print pages: 16-20 © 2009 SAGE Publications Ltd All Rights Reserved. This PDF has been generated from SAGE Knowledge. Please note that the pagination of the online version will vary from the pagination of the print book. javascript:void(0); javascript:void(0); http://dx.doi.org/10.4135/9781446216736.n4 Determinants of Health SoumenSengupta Definition Health is classically defined as ‘a state of complete physical, social and mental health, and not merely the absence of disease or infirmity’ (WHO, 1948). As such, health is as much a social construct as a biological characteristic. It is the product of a complex interaction of different factors: this is true at both individual and population levels. These determinants include not just an individual's particular characteristics and behav- iours but also their economic, physical and social environments (Ashton and Seymour, 1992). Key Points • Health is created by a complicated interaction of different factors, only some of which can be directly influenced by individuals. • Social determinants tend to have a greater impact on population health status than healthcare ser- vices. • Different determinants have a differential influence on different groups of people: this can contribute t.
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Commentary _social_epidemiology__questionable answers and answerable questions
1.
THE CHANGING FACE
OF EPIDEMIOLOGY Editors’ note: This series addresses topics of interest to epidemiologists across a range of specialties. Commentaries start as invited talks at symposia organized by the E ditors. This paper was presented at the Third North American Congress of Epidemiology held in Montreal in June 2011. Social Epidemiology Questionable Answers and Answerable Questions Sam Harpera and Erin C. Strumpf a,b S ocial epidemiology encompasses the study of relationships between health and a broad range of social factors such as race, social class, gender, social policies, and so on. One could broadly partition the work of social epidemiology into surveillance (ie, descriptive relationships between social factors and health, tracking of health inequalities over time) and etiology (ie, causal effects of social exposures on health).1 Many social epidemiolo- gists believe these twin pursuits should ultimately serve to structure interventions aimed at reducing health-damaging social exposures or increasing exposure to social factors that enhance health. SOCIAL EPIDEMIOLOGY RISING Two decades ago one could have argued that social epidemiology was a fringe sub- discipline; now it is as prominent as any other specialization within epidemiology. Many schools of public health now offer concentrations in social epidemiology, most countries have public health goals aimed specifically at reducing social inequalities in health, and no fewer than three general and two methodological textbooks on social epidemiology are now in circulation. More importantly, social epidemiology now occupies an important place in the realm of public health policy. The World Health Organization’s landmark Commission on the Social Determinants of Health Report,2 published in 2008, attempted to bring world- wide attention to social determinants of health and to affect policy decisions in ways that would reduce social inequalities in health. The Commission’s report would not have been possible without the pathbreaking work on health inequalities that developed in the United Kingdom after the Black Report3 in 1980, which subsequently led to two full-scale reports on health inequalities in the United Kingdom.4,5 Each of these reports has used evidence assembled by social epidemiologists to advocate for policies aimed at reducing health inequalities, and yet, after the most recent report5—which found little evidence that health inequalities in England have decreased— there seems to be considerable consternation about the potential for policies to reduce social inequalities in health. Johan Mackenbach, who has produced as much evidence on health inequalities across the European region as anyone, seemed especially pessimistic: “The main conclusion therefore is that reducing health inequalities is currently beyond our means. That is the sad but inevitable conclusion from the story of the English strat- egy to reduce health inequalities.”6 Echoing these same concerns, Bambra and colleagues From the aDepartment of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada; and bDepartment of Economics, McGill University, Montreal, Quebec, Canada. Supported by a Chercheur Boursier Junior 1 from the Fonds de la Recherche du Québec–Santé (to S.H.) and from the Fonds de la Recherche du Québec–Santé and the Ministère de la Santé et des Services sociaux du Québec (to E.S.). Editors’ note: Related articles appear on pages 785, 787, and 790. Correspondence: Sam Harper, Department of Epidemiology, Biostatistics & Occupational Health, McGill University, 1020 Pine Avenue West, Purvis Hall, Room 34, Montreal, Quebec, Canada H3A 1A2. E-mail: sam.harper@mcgill.ca. Copyright © 2012 by Lippincott Williams & Wilkins ISSN:1044-3983/12/2306-0795 DOI:10.1097/EDE.0b013e31826d078d Epidemiology • Volume 23, Number 6, November 2012 www.epidem.com | 795
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Harper and Strumpf
Epidemiology • Volume 23, Number 6, November 2012 were dismayed by the similarity of the conclusions of each of health is not strong enough to overwhelm the effect of social the English reports more than 30-odd years and questioned causation.16,17 These studies typically ask the descriptive ques- the purpose of accumulating evidence from social epidemi- tion of whether those in higher status occupations have better ology, given the fact that the policy conclusions never seem health (controlling for a range of covariates), rather than the to change.7 These self-critical remarks among committed question of whether intervening to change occupational status researchers are concordant with evidence from policymak- would lead to improved health outcomes. Case and Paxson,18 ers who charge social epidemiologists (and the broader social however, use the Whitehall data to reframe the question and determinants of health movement) with providing “policy-free ask whether changes in occupational grade affect changes in evidence” and the “right answers to the wrong questions.”8 health and, in a parallel fashion, whether changes in health affect changes in occupational grade. Using a fixed-effects CRITIQUES OF THE SOCIAL APPROACH design that controls for unmeasured time-invariant individual The gap between the questions policymakers want characteristics, they find no evidence that civil service grade answered and the kinds of questions social epidemiologists affects health, but some evidence that health affects future have been answering is evident in a series of commentar- employment. They also find that future civil service grade ies on the most recent report9 by Michael Marmot on health predicts current health, suggesting health-related selection or inequalities in the United Kingdom. While social epide- unmeasured confounding. Although this identification strat- miologists largely praised the report (some even chided the egy trades off a lot of precision for a reduction in bias,19 it is UK committee for not being radical enough in their policy probably closer to the kind of question that we would ask if recommendations),10 others questioned whether the report we could design a randomized trial to evaluate the effects of had provided sufficient evidence to back its strong policy occupational grade on health. recommendations.11,12 Critics accused social epidemiologists A second example comes from a randomized trial of being “casual about causality” and argued that there was, called the Moving to Opportunity study. The backdrop here in fact, little evidence to suggest causal effects of income or is an abundance of observational research showing that education on health (although there is better evidence for the neighborhood characteristics such as poverty concentration association between early-life conditions and health in later are associated with a wide range of health and social life). The discrepant readings of this evidence may be a conse- outcomes.20 In the randomized study, nearly 5000 families quence of social epidemiologists generally answering descrip- living in high-poverty urban neighborhoods in five U.S. cities tive questions (whether socially disadvantaged individuals were randomly assigned one of two treatments, one of which have poorer health), but interpreting their findings causally required relocating to a more prosperous neighborhood. (whether socially disadvantaged individuals would have bet- The intervention was successful in reducing exposure to ter health if they were to become advantaged, or vice versa). concentrated poverty, but intention-to-treat (ITT) estimates Such interpretation implies both an intervention and a causal on social and health outcomes (in the presence of substantial effect of that intervention. Social epidemiologists often pres- non-compliance) were largely null.21 Sociologists Clampet- ent their results in counterfactual terms that imply causation: Lundquist and Massey used the same data but analyzed it if clerical workers had the same mortality as administrators,13 as an observational study, arguing that the ITT estimate can if blacks had the same mortality as whites,14 if everyone had “measure the effects of the policy initiative, but is not well the same mortality rates as those with a university educa- suited to capturing neighborhood effects.”22 This quote seems tion,15 the reduction in disease burden would be substantial. to reflect some of the tension mentioned above between the Furthermore, such counterfactuals often do not correspond to kind of evidence wanted by policymakers (causal effect any known or feasible interventions. We suggest that the epi- of the policy) and the kind of evidence being delivered by demiologic question should be reframed and that changing the social epidemiology. The investigators found evidence that question can make an important difference both to the answer increased exposure to low poverty areas is beneficial— one gets about the impact of social conditions on health and although by breaking the randomization they reintroduced to one’s ability to provide useful information to policymakers. precisely the same kinds of selection effects that led to the Some examples follow. concerns cited above about being “casual about causality.”23 This does not mean that randomized experiments are the only REFRAMING THE QUESTION solution. Sampson and colleagues,24 for example, were able to The UK Whitehall studies have provided numerous “recover” the randomization study estimates on verbal IQ by analyses demonstrating positive associations between civil explicitly mimicking the design of a trial in observational data service occupational grade and health, but concerns are often from Chicago neighborhoods. raised about the potential for social gradients to arise because A third example of reframing concerns the effect of of unmeasured confounding or health-related selection. education on mortality. Countless social epidemiologic stud- Whitehall investigators have largely attributed their results to ies have followed persons with high versus low education social causation, arguing that any social selection based on and found substantially increased mortality among the less 796 | www.epidem.com © 2012 Lippincott Williams & Wilkins
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Epidemiology • Volume
23, Number 6, November 2012 Social Epidemiology educated—an association that is in most cases robust to con- is to inform policy then our questions should be motivated by trols for additional socioeconomic, behavioral, and biologic identifying causal relationships that can be of the most use to factors.25 These observational studies ask whether more edu- policymakers. It goes without saying that in this short essay cated individuals have lower mortality, but generally do not we have painted social epidemiology with perhaps too broad ask what policymakers want to know: what would the health a brush—many social epidemiologists undoubtedly produce effects be of intervening to increase a person’s amount of high-quality evidence on the impact of social exposures on education, or their achievement of a certain educational qual- health. Yet, our concern here is that much of social epidemiol- ification? Most observational study designs cannot answer ogy is providing questionable answers to important questions, this question, because it is very difficult to control for the rather than focusing on answerable questions. Batty35 recently multitude of factors that jointly determine both education and lamented the lack of interest among the research community health.26 However, more recent studies have used changes in in generating experimental or quasi-experimental evidence on schooling policies that are more plausibly independent of social determinants of health. To focus on answerable ques- unobserved individual characteristics and their health out- tions, social epidemiologists may need to sharpen their focus comes (eg, minimum age required for leaving school) to on specific questions that are more narrow in scope, but for minimize unmeasured confounding. These studies bring us which experimental or quasi-experimental data exist. closer to answering the question of whether intervening to The major strength of experimental and quasi-experi- increase educational achievement is likely to have effects on mental designs lies in their robustness to unobserved con- mortality, and the results are decidedly more mixed.25 Several founding. Such designs also have conceptual strengths that studies provide evidence that exogenous changes in school- come from asking specific causal questions. Trials have their ing resulting from policies reduce mortality,27–29 but several own limitations and will never answer some social epidemi- other studies do not, even for different analyses of the same ologic hypotheses, but attempting to mimic the randomized country.29–32 The contrast between the consistency of studies trial one would hypothetically conduct to answer an important answering descriptive questions and the mixed evidence for question would seem to be a good place to start.36,37 Finally, (more approximately) causal questions suggests that this dis- we would also argue that greater transparency in methods tinction matters. and reporting would increase the value of replication stud- A final example comes from our own work, but again ies38 that can directly address the question of how sensitive reflects the importance of focusing on a well-specified causal research findings in social epidemiology may be to measure- question. A recent article found that U.S. states with medi- ment error, model selection, unmeasured confounding, and cal marijuana laws had higher adolescent marijuana use.33 other potential biases.39,40 Greater attention to both research The authors focused on two comparisons: (1) the difference design and rigorous analysis can help social epidemiologists in marijuana use between states passing laws and states with answer important questions rather than continuing to generate no laws and no history of such laws and (2) the difference in questionable answers. marijuana use between states that had already passed laws and states that had never passed a law. Neither of these contrasts ABOUT THE AUTHORS represent the causal question facing policymakers in a state Sam Harper and Erin Strumpf are Assistant Professors in currently without a medical marijuana law; namely, what is the Department of Epidemiology, Biostatistics & Occupational likely to happen to marijuana use among adolescents if we Health at McGill University, where Erin Strumpf also holds legalize medical marijuana? Yet the data do permit asking an appointment in the Department of Economics. precisely this question. Using difference-in-differences esti- Sam Harper works on measuring social inequalities in mation, we compared the change in marijuana use among health and how they change over time. Erin Strumpf's research adolescents after a medical marijuana law is passed to cor- in health economics focuses on measuring the causal impacts responding changes over the same period in states that do not of health and health care policies on spending and health pass a law and found little evidence of any effect.34 Although outcomes overall, and in inequalities across groups. this strategy obviously does not approach randomization to a medical marijuana law, it provides better control for con- REFERENCES founding by unmeasured state characteristics and overall 1. Kaufman JS. Social epidemiology. In: Rothman KJ, Greenland S, Lash TL, eds. Modern Epidemiology. 3rd ed. Philadelphia: Wolters Kluwer secular trends. More importantly, the analytic strategy follows Health/Lippincott Williams & Wilkins; 2008:533–548. directly from asking a specific question about social policy. 2. WHO Commission on Social Determinants of Health. 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