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Integrating social science and behavioral genetics: testing the origin of socioeconomic disparities in depression using a genetically informed design.

ABSTRACT: OBJECTIVES:We tested 3 hypotheses-social causation, social drift, and common cause-regarding the origin of socioeconomic disparities in major depression and determined whether the relationship between socioeconomic status (SES) and major depression varied by genetic liability for major depression. METHODS:Data were from a sample of female twins in the baseline Virginia Adult Twin Study of Psychiatric and Substance Use Disorders interviewed between 1987 and 1989 (n = 2153). We used logistic regression and structural equation twin models to evaluate these 3 hypotheses. RESULTS:Consistent with the social causation hypothesis, education (odds ratio [OR] = 0.78; 95% confidence interval [CI] = 0.66, 0.93; P < .01) and income (OR = 0.93; 95% CI = 0.89, 0.98; P < .01) were significantly related to past-year major depression. Upward social mobility was associated with lower risk of depression. There was no evidence that childhood SES was related to development of major depression (OR = 0.98; 95% CI = 0.89, 1.09; P > .1). Consistent with a common genetic cause, there was a negative correlation between the genetic components of major depression and education (r(2) = -0.22). Co-twin control analyses indicated a protective effect of education and income on major depression even after accounting for genetic liability. CONCLUSIONS:This study utilized a genetically informed design to address how social position relates to major depression. Results generally supported the social causation model.

SUBMITTER: Mezuk B

PROVIDER: S-EPMC3786755 | biostudies-literature | 2013 Oct

REPOSITORIES: biostudies-literature

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Integrating social science and behavioral genetics: testing the origin of socioeconomic disparities in depression using a genetically informed design.

Mezuk Briana B Myers John M JM Kendler Kenneth S KS

American journal of public health 20130808

<h4>Objectives</h4>We tested 3 hypotheses-social causation, social drift, and common cause-regarding the origin of socioeconomic disparities in major depression and determined whether the relationship between socioeconomic status (SES) and major depression varied by genetic liability for major depression.<h4>Methods</h4>Data were from a sample of female twins in the baseline Virginia Adult Twin Study of Psychiatric and Substance Use Disorders interviewed between 1987 and 1989 (n = 2153). We used ...[more]

PMID: 23927513

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Project description:BACKGROUND:Obesity and its associated diseases are major health problems characterized by extensive metabolic disturbances. Understanding the causal connections between these phenotypes and variation in metabolite levels can uncover relevant biology and inform novel intervention strategies. Recent studies have combined metabolite profiling with genetic instrumental variable (IV) analysis (Mendelian randomization) to infer the direction of causality between metabolites and obesity, but often omitted a large portion of untargeted profiling data consisting of unknown, unidentified metabolite signals. METHODS:We expanded upon previous research by identifying body mass index (BMI)-associated metabolites in multiple untargeted metabolomics datasets, and then performing bidirectional IV analysis to classify metabolites based on their inferred causal relationships with BMI. Meta-analysis and pathway analysis of both known and unknown metabolites across datasets were enabled by our recently developed bioinformatics suite, PAIRUP-MS. RESULTS:We identified ten known metabolites that are more likely to be causes (e.g., alpha-hydroxybutyrate) or effects (e.g., valine) of BMI, or may have more complex bidirectional cause-effect relationships with BMI (e.g., glycine). Importantly, we also identified about five times more unknown than known metabolites in each of these three categories. Pathway analysis incorporating both known and unknown metabolites prioritized 40 enriched (p?<?0.05) metabolite sets for the cause versus effect groups, providing further support that these two metabolite groups are linked to obesity via distinct biological mechanisms. CONCLUSIONS:These findings demonstrate the potential utility of our approach to uncover causal connections with obesity from untargeted metabolomics datasets. Combining genetically informed causal inference with the ability to map unknown metabolites across datasets provides a path to jointly analyze many untargeted datasets with obesity or other phenotypes. This approach, applied to larger datasets with genotype and untargeted metabolite data, should generate sufficient power for robust discovery and replication of causal biological connections between metabolites and various human diseases.

Project description:BackgroundFew studies have examined socioeconomic disparities in health and behavioral risk factors by gender in Asian countries and in South Korea, specifically. We investigated the relationship between socioeconomic position (education, income, and occupation) and subjective and acute and chronic health outcomes and behavioral risk factors by gender, and compared results from 1998 and 2005, in the Republic of Korea.MethodsWe examined data from a nationally representative stratified random sample of 4213 men and 4618 women from the 1998 Korea National Health and Nutrition Examination Survey, and 8289 men and 8827 women from the 2005 Korea National Health and Nutrition Examination Survey using General Linear Modeling and multiple logistic regression methods.ResultsControlling for behavioral risk factors (smoking, drinking, obesity, exercise, and sleep), those in lower socioeconomic positions had poorer health outcomes in both self-reported acute and chronic disease and subjective measures; differences were especially pronounced among women. A socioeconomic gradient for education and income was found for both men and women for morbidity and self-reported health status, but the gradient was more pronounced in women. In 1998, the odds ratios (ORs) of higher morbidity for illiterate vs. college educated females was 5.4:1 and 1.9:1 for females in the lowest income quintile vs. the highest. The OR for education decreased in 2005 to 2.9:1 and that for income quintiles remained the same at 1.9:1. The OR of lower self-reported health status for illiterate vs. college educated females was 2.9:1 and 1.6:1 for females in the lowest income quintile vs. the highest in 1998, and 3.3:1 and 2.3:1 in 2005.ConclusionsAmong Korean adults, men and women in lower socioeconomic position, as denoted by education, income, and somewhat less by occupation, experience significantly higher levels of morbidity and lower self-reported health status, even after controlling for standard behavioral risk factors. Disparities were more pronounced for women than for men. Efforts to reduce health disparities in South Korea require attention to the root causes of socioeconomic inequality and gender differences in the impact of socioeconomic position on health.

Project description:Background:In contrast to the extensive research on socioeconomic gaps in reading and math achievement, little attention has been given to socioeconomic disparities in science skills, particularly during the early years of schooling. This emphasis on later years may be problematic because large socioeconomic disparities emerge in the early years, thus it is crucial to document the size of disparities in science achievement and begin unpacking the range of factors that contribute to these disparities. Additionally, it is crucial to know which components of socioeconomic status are more strongly linked to children's science skills so that resources can be more effectively targeted to address disparities. Using nationally representative data from the Early Childhood Longitudinal Study, Kindergarten Class of 1998-99 (N?=?9250), this study examines disparities in science achievement across elementary and middle school related to parental income and parental education separating their effects from each other and from a range of confounding factors. Additionally, it considers whether characteristics of children, families, and schools are pathways through which socioeconomic disparities emerge. Results:Results show moderate gaps in science achievement related to both household income and parental education. The primary pathways through which parental education and family income influenced science achievement was through mathematics and reading achievement. For parental education gaps, smaller indirect effects also operated through access to informal science learning opportunities both inside and outside of the home environment. Conclusion:First, this study highlights the importance of considering the contributions of multiple measures of socioeconomic status, instead of a composite. Second, it shows that socioeconomic disparities in science achievement emerge early and that programs and policies aimed at addressing these gaps may need to target children during the early elementary and preschool years. Third, our findings suggest that elementary instructional approaches that simultaneously address science instruction with reading and/or mathematics instruction will likely be especially important for improving overall science outcomes.

Dataset Information

Integrating social science and behavioral genetics: testing the origin of socioeconomic disparities in depression using a genetically informed design.

Publications

Integrating social science and behavioral genetics: testing the origin of socioeconomic disparities in depression using a genetically informed design.

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