Socioeconomic inequality in recovery from poor physical and mental health in mid-life and early old age: prospective Whitehall II cohort study

Metabolic syndrome traits exhibit genotype-by-environment interaction in relation to socioeconomic status in the Mexican American family heart study

Background: Socioeconomic Status (SES) is a potent environmental determinant of health. To our knowledge, no assessment of genotype-environment interaction has been conducted to consider the joint effects of socioeconomic status and genetics on risk for metabolic disease. We analyzed data from the Mexican American Family Studies (MAFS) to evaluate the hypothesis that genotype-by-environment interaction (GxE) is an essential determinant of variation in risk factors for metabolic syndrome (MS). Methods: We employed a maximum likelihood estimation of the decomposition of variance components to detect GxE interaction. After excluding individuals with diabetes and individuals on medication for diabetes, hypertension, or dyslipidemia, we analyzed 12 MS risk factors: fasting glucose (FG), fasting insulin (FI), 2-h glucose (2G), 2-h insulin (2I), body mass index (BMI), waist circumference (WC), leptin (LP), high-density lipoprotein-cholesterol (HDL-C), triglycerides (TG), total serum cholesterol (TSC), systolic blood pressure (SBP), and diastolic blood pressure (DBP). Our SES variable used a combined score of Duncan's socioeconomic index and education years. Heterogeneity in the additive genetic variance across the SES continuum and a departure from unity in the genetic correlation coefficient were taken as evidence of GxE interaction. Hypothesis tests were conducted using standard likelihood ratio tests. Results: We found evidence of GxE for fasting glucose, 2-h glucose, 2-h insulin, BMI, and triglycerides. The genetic effects underlying the insulin/glucose metabolism component of MS are upregulated at the lower end of the SES spectrum. We also determined that the household variance for systolic blood pressure decreased with increasing SES. Conclusion: These results show a significant change in the GxE interaction underlying the major components of MS in response to changes in socioeconomic status. Further mRNA sequencing studies will identify genes and canonical gene pathways to support our molecular-level hypotheses.

The Semmelweis Study: a longitudinal occupational cohort study within the framework of the Semmelweis Caring University Model Program for supporting healthy aging

The Semmelweis Study is a prospective occupational cohort study that seeks to enroll all employees of Semmelweis University (Budapest, Hungary) aged 25 years and older, with a population of 8866 people, 70.5% of whom are women. The study builds on the successful experiences of the Whitehall II study and aims to investigate the complex relationships between lifestyle, environmental, and occupational risk factors, and the development and progression of chronic age-associated diseases. An important goal of the Semmelweis Study is to identify groups of people who are aging unsuccessfully and therefore have an increased risk of developing age-associated diseases. To achieve this, the study takes a multidisciplinary approach, collecting economic, social, psychological, cognitive, health, and biological data. The Semmelweis Study comprises a baseline data collection with open healthcare data linkage, followed by repeated data collection waves every 5 years. Data are collected through computer-assisted self-completed questionnaires, followed by a physical health examination, physiological measurements, and the assessment of biomarkers. This article provides a comprehensive overview of the Semmelweis Study, including its origin, context, objectives, design, relevance, and expected contributions.

Factors Associated with Symptoms of Depression among People with Obesity: Analysis of a 3-Year-Peruvian National Survey

INTRODUCTION

Obesity and depression contribute to the global burden of economic cost, morbidity, and mortality. Nevertheless, not all people with obesity develop depression.

OBJECTIVE

To determine the factors associated with depressive symptoms among people aged 15 or older with obesity from the National Demographic and Family Health Survey (ENDES in Spanish 2019-2021).

METHODS

Cross-sectional analytical study. The outcome of interest was the presence of depressive symptoms, assessed using the Patient Health Questionnaire-9 (PHQ-9). Crude (cPR) and adjusted (aPR) prevalence ratios were estimated using GLM Poisson distribution with robust variance estimates.

RESULTS

The prevalence of depression symptoms was 6.97%. In the multivariate analysis, a statistically significant association was found between depressive symptoms and female sex (PRa: 2.59; 95% CI 1.95-3.43); mountain region (PRa: 1.51; 95% CI 1.18-1.92); wealth index poor (PRa: 1.37; 95% CI 1.05-1.79, medium (PRa: 1.49; 95% CI 1.11-2.02), and rich (PRa: 1.65; 95% CI 1.21-2.26); daily tobacco use (PRa: 2.05, 95% CI 1.09-3.87); physical disability (PRa: 1.96, 95% CI 1.07-3.57); and a history of arterial hypertension (PRa: 2.05; 95% CI 1.63-2.55).

CONCLUSION

There are several sociodemographic factors (such as being female and living in the Andean region) and individual factors (daily use of tobacco and history of hypertension) associated with depressive symptoms in Peruvian inhabitants aged 15 or older with obesity. In this study, the COVID-19 pandemic was associated with an increase in depressive symptoms.

Long-Term Change and Predictors of Change in Physical and Mental Function after Rehabilitation: A Multi-Centre Study

OBJECTIVE

To investigate changes and predictors of change in physical and mental function over a 3-year period after rehabilitation.

DESIGN

Prospective cohort.

PARTICIPANTS

Patients, across diseases, living in western Norway, accepted for somatic specialized interprofessional rehabilitation (n = 984).

METHODS

Physical and mental function were assessed at admittance (baseline), and after 1 and 3 years using the Medical Outcome Study Short Form 36 (SF-36). Associations between changes in SF-36 component summary scores and sense of coherence, pain, disease group (musculoskeletal, neoplasm, cardiovascular, neurological, other), exercise habits and demographic variables were analysed using linear mixed modelling.

RESULTS

In the total group, mean (standard deviation) physical component summary scores improved by 2.9 (8.4) and 3.4 (9.3) points at 1 and 3 years, respectively. Mental component summary scores improved by 2.1 (9.7) and 1.6 (10.8) points. Improvement in physical component summary was significantly greater for patients with higher sense of coherence (b = 0.09, p = 0.001) and for the neoplasm disease group (b = 2.13, p = 0.046). Improvement in mental component summary was significantly greater for patients with low sense of coherence (b = -0.13, p = < 0.001) and higher level of education (b = 3.02, p = 0.0302). Interaction with age (physical component summary: b = 0.22, p = 0.039/mental component summary b = 0.51, p = 0.006) indicated larger effect at 1 year than at 3 years.

CONCLUSION

Physical and mental function improved in the total study group over the 3-year period. Sense of coherence at baseline was associated with improved physical and mental function, suggesting that coping resources are important in rehabilitation.

Inequalities in recovery or methodological artefact? A comparison of models across physical and mental health functioning

Considerable attention has been paid to inequalities in health. More recently, focus has also turned to inequalities in ‘recovery’; with research, for example, suggesting that lower grade of employment is strongly associated with slower recovery from both poor physical and poor mental health. However, this research has tended to operationalise recovery as ‘return to baseline’, and we know less about patterns and predictors when recovery is situated as a ‘process’. This paper seeks to address this gap. Drawing on data from the UK Household Longitudinal Study, we operationalise recovery as both an ‘outcome’ and as a ‘process’ and compare patterns and predictors across the two models. Our analysis demonstrates that the determinants of recovery from poor health, measured by the SF-12, are robust, regardless of whether recovery is operationalised as an outcome or as a process. For example, being employed and having a higher degree were found to increase the odds of recovery both from poor physical and mental health functioning, when recovery was operationalised as an outcome. These variables were also important in distinguishing health functioning trajectories following a poor health episode. At one and the same time, our analysis does suggest that understandings of inequalities in recovery will depend in part on how we define it. When recovery is operationalised as a simple transition from poor health state to good, it loses sight of the fact that there may be inequalities (i) within a ‘poor health’ state, (ii) in how individuals are able to step into the path of recovery, and (iii) in whether health states are maintained over time. We therefore need to remain alert to the additional nuance in understanding which comes from situating recovery as a process; as well as possible methodological artefacts in population research which come from how recovery is operationalised.

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There is no consensus on what recovery is and how it should be operationalised.

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Understanding of inequalities in recovery across health conditions remains scarce.

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We operationalised recovery both as an outcome and as a process.

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We found robust inequalities in recovery across the two approaches.

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Considering recovery as a process revealed more nuanced patterns in inequalities.

Comorbid depression and obesity among adults in Germany: Effects of age, sex, and socioeconomic status

BACKGROUND

Depression and obesity are common health problems with major public health implications. These conditions frequently co-occur, adversely affecting the course of the other. The sociodemographic and socioeconomic risk factors for comorbid depression and obesity in the German adult population have not yet been reported.

METHODS

We analyzed the prevalence and sociodemographic and socioeconomic correlates of comorbid depression and obesity using cross-sectional data from the national German health interview and examination survey for adults (DEGS1; n = 7987) and its mental health module (DEGS1-MH; n = 4493). The Composite International Diagnostic Interview was used to diagnose major depressive disorder (CIDI-MDD). Sensitivity was analyzed using the self-reported depression measure and current depressive symptoms measured by Patient Health Questionnaire-9 (PHQ-9). Obesity was defined by body mass index calculated from measured data.

RESULTS

Prevalence of comorbid depression and obesity was 1.3% (95% CI 0.8-2.0) in men and 2.0% (95% CI 1.3-3.0) in women. We found significant sex differences in results from the self-reported depression measure and the PHQ-9, but not from the CIDI-MDD. Low socioeconomic status and poor social support were linked to a higher prevalence of comorbid depression and obesity among women.

LIMITATIONS

Severe depression may have been underreported.

CONCLUSIONS

Depression is statistically more prevalent in women than in men, which accounts for many of the sex differences in the prevalence of comorbid depression and obesity in our models. Targeted public health strategies need to be developed to prevent and treat comorbid depression and obesity in women with a low socioeconomic position.

The Effects of Childhood Circumstances on Health in Middle and Later Life: Evidence From China

Background: This study examined the relationship between childhood circumstances and health in middle and later life. We quantified how childhood circumstances contribute to health in later life, both directly and indirectly, through their effects on potential mediators.

Methods: This study used three waves of data from the national longitudinal survey of the China Health and Retirement Longitudinal Study (CHARLS). The final model in this study included 7,476 eligible respondents aged 45 years and above. We constructed a simple health status measure based on the first principal component of CHARLS survey responses with 25 health-related information. It is a multi-dimensional measurement that comprehensively reflects the individual's healthy aging. We formulated childhood circumstances factors into five domains: childhood health and nutrition, childhood socioeconomic status, access to health care, parental genetics, and adverse childhood experiences. Ordered logit regression was conducted to analyze the relationship between health in middle and later life and childhood circumstances, with other explanatory variables controlled.

Results: Controlling for educational attainment, personal income, and health status in the last wave, adults who experience good childhood health (poor as the base, coefficient 0.448, p < 0.01), and better family financial status (worse as the base, coefficient 0.173, p < 0.01) have significantly better health during their middle and later life, in comparison, being inconvenient to visit a doctor (coefficient −0.178, p < 0.01), and having two or three adverse childhood experiences (0 as the base, coefficient −0.148, p < 0.01) are significantly associated with poorer health. Childhood circumstances appear to act both through a lasting effect of initial health and financial status in childhood and through their impact on achievements in adulthood.

Conclusion: Our findings suggest that investments in health during childhood not only contribute to health in later life but also dynamically improve an individual's educational attainment and personal income, as well as other life prospects. All these returns may extend far beyond childhood and continue throughout the lifespan.

To what extent do socioeconomic inequalities in SRH reflect inequalities in burden of disease? The HELIUS study

BACKGROUND

Self-rated health (SRH), an attractive measure for health monitoring, shows persistent inequalities with regard to socioeconomic status (SES). However, knowledge on the extent to which inequalities in SRH reflect inequalities in disease burden is lacking.

METHODS

Data come from the multi-ethnic HEalthy LIfe in an Urban Setting study (Dutch, South-Asian Surinamese, African Surinamese, Ghanaian, Turkish or Moroccan origin, N = 19 379, aged 18-70). SES was defined by educational and occupational level. Disease burden was operationalized as chronic diseases, physical and mental functioning (measured with SF-12) and depressive symptoms (measured with PHQ-9). We applied logistic regression analyses and reported average marginal effects (AME).

RESULTS

Dutch origin participants with low educational or low occupational level had higher probabilities of reporting fair/poor SRH, compared to the highest levels (AME = 0.20 95% CI: 0.13;0.27; and 0.12 (0.09;0.15), respectively). Associations were attenuated after adjusting for all disease burden indicators, to AME = 0.03 (0.01;0.04) and AME = 0.02 (-0.00;0.04). In all the non-Dutch origin groups, a larger part of the inequalities remained after adjustment.

CONCLUSION

Socioeconomic inequalities in SRH are for a large part explained by higher disease burden in lower socioeconomic groups, but less so in those with non-Dutch origin. Future research should examine if our conclusions also hold for trend data on inequalities in SRH.