scholarly journals The affective neuroscience of socioeconomic status: implications for mental health – CORRIGENDUM

2021 ◽  
pp. 1-1
Author(s):  
Yu Hao ◽  
Martha J. Farah
Keyword(s):  
Mental Health ◽  
Socioeconomic Status ◽  
Affective Neuroscience

scholarly journals The affective neuroscience of socioeconomic status: implications for mental health

2020 ◽  
Vol 44 (5) ◽  
pp. 202-207 ◽  
Author(s):  
Yu Hao ◽  
Martha J. Farah
Keyword(s):  
Mental Health ◽  
Socioeconomic Status ◽  
Emotion Regulation ◽  
Mental Disorders ◽  
Emotional Processing ◽  
Science Research ◽  
Neural Mechanisms ◽  
Affective Neuroscience ◽  
Neuroscience Research ◽  
Cortical Regions

SummaryWe review basic science research on neural mechanisms underlying emotional processing in individuals of differing socioeconomic status (SES). We summarise SES differences in response to positive and negative stimuli in limbic and cortical regions associated with emotion and emotion regulation. We discuss the possible relevance of neuroscience to understanding the link between mental health and SES. We hope to provide insights into future neuroscience research on the etiology and pathophysiology of mental disorders relating to SES.

Prevalence of Mental Disorders by Socioeconomic Status in Australia: A Cross-Sectional Epidemiological Study

2020 ◽  
pp. 089011712096865
Author(s):  
Rubayyat Hashmi ◽  
Khorshed Alam ◽  
Jeff Gow ◽  
Sonja March
Keyword(s):  
Mental Health ◽  
Risk Factors ◽  
Socioeconomic Status ◽  
Mental Disorders ◽  
National Health Survey ◽  
Cross Sectional ◽  
Lower Odds ◽  
Socioeconomic Groups ◽  
Income Groups ◽  
Weighted Prevalence

Purpose: To present the prevalence of 3 broad categories of mental disorder (anxiety-related, affective and other disorders) by socioeconomic status and examine the associated socioeconomic risk factors of mental disorders in Australia. Design: A population-based, cross-sectional national health survey on mental health and its risk factors across Australia. Setting: National Health Survey (NHS), 2017-2018 conducted by the Australian Bureau of Statistics (ABS) Participants: Under aged: 4,945 persons, Adult: 16,370 persons and total: 21,315 persons Measures: Patient-reported mental disorder outcomes Analysis: Weighted prevalence rates by socioeconomic status (equivalised household income, education qualifications, Socio-Economic Index for Areas (SEIFA) scores, labor force status and industry sector where the adult respondent had their main job) were estimated using cross-tabulation. Logistic regression utilizing subsamples of underage and adult age groups were analyzed to test the association between socioeconomic status and mental disorders. Results: Anxiety-related disorders were the most common type of disorders with a weighted prevalence rate of 20.04% (95% CI: 18.49-21.69) for the poorest, 13.85% (95% CI: 12.48-15.35) for the richest and 16.34% (95% CI: 15.7-17) overall. The weighted prevalence rate for mood/affective disorders were 20.19% (95% CI: 18.63-21.84) for the poorest, 9.96% (95% CI: 8.79-11.27) for the richest, and 13.57% (95% CI: 12.99-14.17) overall. Other mental disorders prevalence were for the poorest: 9.07% (95% CI: 7.91-10.39), the richest: 3.83% (95% CI: 3.14-4.66), and overall: 5.93% (95% CI: 5.53-6.36). These patterns are also reflected if all mental disorders were aggregated with the poorest: 30.97% (95% CI: 29.15-32.86), the richest: 19.59% (95% CI: 18.02-21.26), and overall: 23.93% (95% CI: 23.19-24.69). The underage logistic regression model showed significant lower odds for the middle (AOR: 0.75, 95% CI: 0.53 -1.04, p < 0.1), rich (AOR: 0.71, 95% CI: 0.5-0.99, p < 0.05) and richest (AOR: 0.6, 95% CI: 0.41-0.89, p < 0.01) income groups. Similarly, in the adult logistic model, there were significant lower odds for middle (AOR: 0.84, 95% CI: 0.72-0.98, p < 0.05), rich (AOR: 0.73, 95% CI: 0.62-0.86, p < 0.01) and richest (AOR: 0.76, 95% CI: 0.63-0.91, p < 0.01) income groups. Conclusion: The prevalence of mental disorders in Australia varied significantly across socioeconomic groups. Knowledge of different mental health needs in different socioeconomic groups can assist in framing evidence-based health promotion and improve the targeting of health resource allocation strategies.

Culture, Socioeconomic Status, and Physical and Mental Health in Brazil

1998 ◽  
Vol 12 (4) ◽  
pp. 424-446 ◽  
Author(s):  
William W. Dressler ◽  
Mauro Campos Balieiro ◽  
Jose Ernesto Dos Santos
Keyword(s):  
Mental Health ◽  
Socioeconomic Status ◽  
Physical And Mental Health

Socioeconomic disparities in psychological distress in a nationally representative sample of Japanese adolescents: A time trend study

2016 ◽  
Vol 51 (3) ◽  
pp. 278-286 ◽  
Author(s):  
Yuko Kachi ◽  
Aya Abe ◽  
Emiko Ando ◽  
Tomoyuki Kawada
Keyword(s):  
Mental Health ◽  
Socioeconomic Status ◽  
Psychological Distress ◽  
Confidence Interval ◽  
Household Income ◽  
Odds Ratio ◽  
Representative Sample ◽  
Mental Health Problems ◽  
Japanese Adolescents ◽  
Nationally Representative

Objective: Socioeconomic status as a determinant of mental health problems has received scant attention in Japan, which has long been considered an egalitarian society. This study examined the association between socioeconomic status and psychological distress and its trends over 6 years among Japanese adolescents. Methods: We used data from a nationally representative sample of 9491 adolescents aged 12–18 years who participated in three repeated cross-sectional surveys between 2007 and 2013. The K6 scale was used to assess psychological distress. Socioeconomic status indicators included household income, parental education, parental working status and household structure. Results: Psychological distress prevalence decreased significantly from 2007 (10.7%) to 2013 (7.6%). However, the socioeconomic status patterns of psychological distress were consistent through the study period. Adolescents living in both lower (odds ratio = 1.61; 95% confidence interval = [1.27, 2.05]) and higher income households (odds ratio = 1.30; 95% confidence interval = [1.03, 1.62]) were more likely to report psychological distress than their middle-income counterparts. Adolescents with low household income were more likely to feel stress from interpersonal relationships and less likely to have help-seeking behaviors, while those with high household income were more likely to feel stress about school achievement. Psychological distress was also associated with parental poor education and single parenthood. Conclusions: Socioeconomic status disparities in adolescent psychological distress were evident and consistent during the 6-year period. There is a unique U-shaped relationship between household income and psychological distress among adolescents in Japan, unlike those from other countries. However, the underlying mechanisms may differ by income status. Future prevention efforts should consider socioeconomic status as a determinant of adolescent mental health problems.

Assessing sex, gender identity, sexual orientation, race, ethnicity, socioeconomic status, and mental health concerns in tobacco use disorder treatment research: Measurement challenges and recommendations from a Society for Research on Nicotine and Tobacco (SRNT) pre-conference workshop

2021 ◽  
Author(s):  
Andrea H Weinberger ◽  
Marc L Steinberg ◽  
Sarah D Mills ◽  
Sarah S Dermody ◽  
Jaimee L Heffner ◽  
...  
Keyword(s):  
Mental Health ◽  
Socioeconomic Status ◽  
Sexual Orientation ◽  
Gender Identity ◽  
Tobacco Use ◽  
Health Concerns ◽  
Tobacco Use Disorder ◽  
Lower Socioeconomic ◽  
Treatment Research ◽  
Mental Health Concerns

Abstract This paper reports on topics discussed at a Society for Research on Nicotine and Tobacco (SRNT) pre-conference workshop at the 2019 annual SRNT meeting. The goal of the preconference workshop was to help develop a shared understanding of the importance of several tobacco-related priority groups in tobacco use disorder treatment research and to highlight challenges in measurement related to these groups. The workshop focused on persons with minoritized sex, gender identity, and sexual orientation identities; persons with minoritized racial and ethnic backgrounds; persons with lower socioeconomic status (SES); and persons with mental health concerns. In addition to experiencing commercial tobacco-related health disparities, these groups are also underrepresented in tobacco research, including tobacco use disorder (TUD) treatment studies. Importantly, there is wide variation in how and whether researchers are identifying variation within these priority groups. Best practices for measuring and reporting sex, gender identity, sexual orientation, race, ethnicity, SES, and mental health concerns in TUD treatment research are needed. This paper provides information about measurement challenges when including these groups in TUD treatment research and specific recommendations about how to measure these groups and assess potential disparities in outcomes. The goal of this paper is to encourage TUD treatment researchers to use measurement best practices in these priority groups in an effort to conduct meaningful and equity-promoting research. Increasing the inclusion and visibility of these groups in TUD treatment research will help to move the field forward in decreasing tobacco-related health disparities. Implications Tobacco-related disparities exist for a number of priority groups including, among others, women, individuals with minoritized sexual and gender identities, individuals with minoritized racial and ethnic backgrounds, individuals with lower socioeconomic status, and individuals with mental health concerns. Research on tobacco use disorder (TUD) treatments for many of these subgroups is lacking. Accurate assessment and consideration of these subgroups will provide needed information about efficacious and effective TUD treatments, about potential mediators and moderators, and for accurately describing study samples, all critical elements for reducing tobacco-related disparities, and improving diversity, equity, and inclusion in TUD treatment research.

Socioeconomic status groups: Their mental health composition.

2005 ◽  
pp. 210-239 ◽  
Author(s):  
Leo Srole ◽  
Thomas S. Langner
Keyword(s):  
Mental Health ◽  
Socioeconomic Status
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