Journal ArticleDOI
Socioeconomic status in health research: one size does not fit all.
Paula Braveman,Catherine Cubbin,Susan Egerter,Sekai Chideya,Kristen S. Marchi,Marilyn Metzler,Samuel F. Posner +6 more
TLDR
Evidence shows that conclusions about nonsocioeconomic causes of racial/ethnic differences in health may depend on the measure-eg, income, wealth, education, occupation, neighborhood socioeconomic characteristics, or past socioeconomic experiences used to "control for SES," suggesting that findings from studies that have measured limited aspects of SES should be reassessed.Abstract:
Problems with measuring socioeconomic status (SES)—frequently included in clinical and public health studies as a control variable and less frequently as the variable(s) of main interest—could affect research findings and conclusions, with implications for practice and policy.Wecritically examine standard SES measurement approaches, illustrating problems with examples from new analyses and the literature. For example, marked racial/ethnic differences in income at a given educational level and in wealth at a given income level raise questions about the socioeconomic comparability of individuals who are similar on education or income alone. Evidence also shows that conclusions about nonsocioeconomic causes of racial/ethnic differences in health may depend on the measure—eg, income, wealth, education, occupation, neighborhood socioeconomic characteristics, or past socioeconomic experiences—used to “control for SES,” suggesting that findings from studies that have measured limited aspects of SES should be reassessed. We recommend an outcome- and social group–specific approach to SES measurement that involves (1) considering plausible explanatory pathways and mechanisms, (2) measuring as much relevant socioeconomic information as possible, (3) specifying the particular socioeconomic factors measured (rather than SES overall), and (4) systematically considering how potentially important unmeasured socioeconomic factors may affect conclusions. Better SES measures are needed in data sources, but improvements could be made by using existing information more thoughtfully and acknowledging its limitations.read more
Citations
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Journal ArticleDOI
The Social Determinants of Health: It's Time to Consider the Causes of the Causes:
Paula Braveman,Laura M. Gottlieb +1 more
TL;DR: Evidence has accumulated pointing to socioeconomic factors such as income, wealth, and education as the fundamental causes of a wide range of health outcomes, and plausible pathways and biological mechanisms that may explain their effects are reviewed.
Posted Content
The Global Economic Burden of Noncommunicable Diseases
David E. Bloom,Elizabeth T. Cafiero,Eva Jané-Llopis,Shafika Abrahams-Gessel,Lakshmi Reddy Bloom,Sana F. Fathima,Andrea B. Feigl,Tom Gaziano,Ali Hamandi,Mona Mowafi,Danny O’Farrell,Emre Özaltin,Ankur Pandya,Klaus Prettner,Larry Rosenberg,Benjamin Seligman,Adam Z. Stein,Cara Weinstein,Jonathan Weiss +18 more
TL;DR: New estimates of the global economic burden of non-communicable diseases in 2010 are developed, and the size of the burden through 2030 is projected, to capture the thinking of the business community about the impact of NCDs on their enterprises.
Journal ArticleDOI
The Social Determinants of Health: Coming of Age
TL;DR: Current knowledge about health effects of social (including economic) factors, knowledge gaps, and research priorities are reviewed, focusing on upstream social determinants that fundamentally shape the downstream determinants, such as behaviors, targeted by most interventions.
Journal ArticleDOI
Socioeconomic status and the developing brain
TL;DR: These studies indicate that SES is an important predictor of neurocognitive performance, particularly of language and executive function, and that S ES differences are found in neural processing even when performance levels are equal.
Journal ArticleDOI
Socioeconomic Disparities in Health in the United States: What the Patterns Tell Us
TL;DR: Health in the United States is often, though not invariably, patterned strongly along both socioeconomic and racial/ethnic lines, suggesting links between hierarchies of social advantage and health.
References
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Book
Generalized Linear Models
Peter McCullagh,John A. Nelder +1 more
TL;DR: In this paper, a generalization of the analysis of variance is given for these models using log- likelihoods, illustrated by examples relating to four distributions; the Normal, Binomial (probit analysis, etc.), Poisson (contingency tables), and gamma (variance components).
Journal ArticleDOI
Generalized Linear Models
TL;DR: This is the rst book on generalized linear models written by authors not mostly associated with the biological sciences, and it is thoroughly enjoyable to read.
Journal ArticleDOI
Neighborhoods and Violent Crime: A Multilevel Study of Collective Efficacy
TL;DR: Multilevel analyses showed that a measure of collective efficacy yields a high between-neighborhood reliability and is negatively associated with variations in violence, when individual-level characteristics, measurement error, and prior violence are controlled.
Journal ArticleDOI
Protective and Damaging Effects of Stress Mediators
TL;DR: The long-term effect of the physiologic response to stress is reviewed, which I refer to as allostatic load, which is the ability to achieve stability through change.
Journal ArticleDOI
ASSESSING "NEIGHBORHOOD EFFECTS": Social Processes and New Directions in Research
TL;DR: In this article, the cumulative results of a new "neighborhood-effects" literature that examines social processes related to problem behaviors and health-related outcomes are assessed and synthesized.