Income inequality and health: A causal review

Pickett, Kate E.; Wilkinson, Richard G.

doi:10.1016/j.socscimed.2014.12.031

Cited by 1,395 publications

(1,132 citation statements)

References 114 publications

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“…These results help to verify the antecedent-consequence conditions in the association between income inequality and health, which is a necessary -though not sufficient -condition of a causal relationship (Gordis, 2013;Pickett & Wilkinson, 2015b). The notion that income inequality acts as a universal, structural determinant of health was previously inferred from its correlations with health and social constructs at the ecological level (e.g., low social trust, violence, mortality).…”

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confidence: 59%

“…5 inequality is socially corrosive in that it intensifies socioeconomic hierarchies, erodes social capital that supports health, and consequently contributes to stress-related health and social problems (Chiavegatto Filho, Kawachi, Wang, Viana, & Andrade, 2013;Pickett & Wilkinson, 2015b;Wilkinson & Pickett, 2010). Support for this pathway was recently reported by Rözer and Volker (2016).…”

Section: Accepted Manuscriptmentioning

confidence: 99%

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Early-life income inequality and adolescent health and well-being

Elgar

Gariépy

Torsheim

et al. 2017

Social Science & Medicine

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A prevailing hypothesis about the association between income inequality and poor health is that inequality intensifies social hierarchies, increases stress, erodes social and material resources that support health, and subsequently harms health. However, the evidence in support of this hypothesis is limited by cross-sectional, ecological studies and a scarcity of developmental studies. To address this limitation, we used pooled, multilevel data from the Health Behaviour in School-aged Children study to examine lagged, cumulative, and trajectory associations between early-life income inequality and adolescent health and well-being. Psychosomatic symptoms and life satisfaction were assessed in surveys of 11-to 15-year-olds in 40 countries between 1994 and 2014. We linked these data to national Gini indices of income inequality for every life year from 1979 to 2014. The results showed that exposure to income inequality from 0 to 4 years uniquely predicted psychosomatic symptoms and lower life satisfaction after controlling lifetime mean income inequality, national per capita income, family affluence, age, and cohort and period effects.Income inequality from 5 to 9 years also related to symptoms and low life satisfaction in females.The cumulative income inequality exposure in infancy and childhood (i.e., average Gini index from birth to age 10) related to more symptoms and lower life satisfaction in adolescence. Finally, individual trajectories in early-life inequality (i.e., linear slopes in Gini indices from birth to 10 years) related to fewer symptoms and higher life satisfaction, indicating that earlier exposures mattered more to predicting adolescent health and wellbeing. These results help to establish the antecedent-consequence conditions in the association between income inequality and health and suggest that both the magnitude and timing of income inequality in early life have developmental consequences that manifest in reduced health and well-being in adolescence. M A N U S C R I P T A C C E P T E D ACCEPTED MANUSCRIPT3 Keywords: Income inequality; adolescents; children; health; well-being; Health Behaviour in School-aged Children. M A N U S C R I P T A C C E P T E D ACCEPTED MANUSCRIPT4 Early-life income inequality and adolescent health and well-being Socioeconomic contexts shape and constrain adolescent health and well-being (Chen & Paterson, 2006). Recent evidence suggests that socioeconomic differences in adolescent health have widened due to rising income inequality (Elgar et al., 2015; Viner et al., 2012). Income inequality also correlates with poor health and social outcomes (Kondo et al., 2009; Wilkinson & Pickett, 2010). An analysis of adolescent health in 34 mostly high-income countries found that national income inequality related to higher body mass indices, less physical activity, and more self-rated mental and physical health symptoms (Elgar et al., 2015). Other research on children and youth found that national or regional income inequality relates to poor self-rated health (Rözer ...

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mentioning

confidence: 59%

Section: Accepted Manuscriptmentioning

confidence: 99%

Early-life income inequality and adolescent health and well-being

Elgar

Gariépy

Torsheim

et al. 2017

Social Science & Medicine

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“…This argument is borne out by the extensive literature that provides evidence of the causal role that material, economic and social factors have in creating patterns of health inequalities across society (Dorling 2013;Marmot 2010Marmot , 2015Marmot and Wilkinson 2005;Pickett and Wilkinson 2015). These social epidemiological studies clearly demonstrate that the social determinants of health-the conditions in which people are born, grow, live, work and age, and the ways in which these conditions are affected by the relative distribution of money, resources, power, recognition and status-create patterns of unequal health across society.…”

Section: Substantive-relational Autonomy Over Healthmentioning

confidence: 99%

‘My Fitbit Thinks I Can Do Better!’ Do Health Promoting Wearable Technologies Support Personal Autonomy?

Owens

Cribb

2017

Philos. Technol.

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This paper critically examines the extent to which health promoting wearable technologies can provide people with greater autonomy over their health. These devices are frequently presented as a means of expanding the possibilities people have for making healthier decisions and living healthier lives. We accept that by collecting, monitoring, analysing and displaying biomedical data, and by helping to underpin motivation, wearable technologies can support autonomy over health. However, we argue that their contribution in this regard is limited and that-even with respect to their 'autonomy enhancing' potential-these devices may deliver costs as well as benefits. We proceed by rehearsing the distinction that can be drawn between procedural autonomy (which refers to processes of psychological deliberation) and substantiverelational autonomy (which refers to the opportunities people have for exercising potential actions). While the information provided by wearable technologies may support deliberation and decision-making, in isolation these technologies do little to provide substantive opportunities to act and achieve better health. As a consequence, wearable technologies risk generating burdens of anxiety and stigma for their users and reproducing existing health inequalities. We then reexamine the extent to which wearable technologies actually support autonomous deliberation. We argue that wearable technologies that subject their users to biomedical and consumerist epistemologies, norms and values also risk undermining processes of genuinely autonomous deliberation.

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“…Larger values on this index reflect greater income inequality. We accounted for income inequality since it has been causally linked to health problems (Pickett and Wilkinson, 2015).…”

Section: Income Inequalitymentioning

confidence: 99%

Racial bias is associated with ingroup death rate for Blacks and Whites: Insights from Project Implicit

Leitner

Hehman

Ayduk

et al. 2016

Social Science & Medicine

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a b s t r a c tRationale: Research suggests that, among Whites, racial bias predicts negative ingroup health outcomes. However, little is known about whether racial bias predicts ingroup health outcomes among minority populations. Objective: The aim of the current research was to understand whether racial bias predicts negative ingroup health outcomes for Blacks. Method: We compiled racial bias responses from 250,665 Blacks and 1,391,632 Whites to generate county-level estimates of Blacks' and Whites' implicit and explicit biases towards each other. We then examined the degree to which these biases predicted ingroup death rate from circulatory-related diseases. Results: In counties where Blacks harbored more implicit bias towards Whites, Blacks died at a higher rate. Additionally, consistent with previous research, in counties where Whites harbored more explicit bias towards Blacks, Whites died at a higher rate. These links between racial bias and ingroup death rate were independent of county-level socio-demographic characteristics, and racial biases from the outgroup in the same county. Conclusion: Findings indicate that racial bias is related to negative ingroup health outcomes for both Blacks and Whites, though this relationship is driven by implicit bias for Blacks, and explicit bias for Whites.

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Income inequality and health: A causal review

Cited by 1,395 publications

References 114 publications

Early-life income inequality and adolescent health and well-being

Early-life income inequality and adolescent health and well-being

‘My Fitbit Thinks I Can Do Better!’ Do Health Promoting Wearable Technologies Support Personal Autonomy?

Racial bias is associated with ingroup death rate for Blacks and Whites: Insights from Project Implicit

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