Informal caregiving and metabolic markers in the UK Household Longitudinal Study

Amyotrophic Lateral Sclerosis and Its Management during the COVID-19 Pandemic: A Qualitative Study with Thematic Analysis of Patients and Caregivers Who Participated in Self-Help Groups

This study employs a qualitative methodology to explore the effects of the pandemic on the lives of ALS patients and their caregivers. It aims to understand whether and how online self-help groups have assisted families dealing with amyotrophic lateral sclerosis (ALS) patients. ALS is a neurodegenerative disease with both physical and psychosocial implications. Consequently, it significantly affects the lives of patients' caregivers. In 2020, the COVID-19 pandemic exacerbated this situation. The results show that the pandemic has had a negative impact on the well-being of ALS caregivers and patients. Furthermore, bereavement and death were dealt with in different ways by the families involved. The pandemic aggravated the health of ALS patients and increased the workload of their caregivers; however, online psychological support was appreciated for its role in providing emotional help and diminishing social isolation.

Gender differences in the relationships between housework and metabolic markers: a longitudinal cohort study in China

Background

Metabolic syndrome has become a major health threat throughout the world, but there are few studies that focus on the effects of housework on human metabolism. This study explores the association between housework and metabolic markers and examines whether there are gender differences in the relationship of housework intensity on these markers.

Methods

We obtained data for 2,624 participants from the China Health and Nutrition Survey and used binary logistic regression to analyze the association between housework and metabolic markers (triglycerides, high- and low-density lipoprotein cholesterol, hemoglobin, blood glucose, cholesterol, and blood pressure).

Results

We observed no association between housework and metabolic markers for men. However, we find that women who engaged in housework had a higher risk of triglycerides than those who did not (OR=1.16, 95% CI: 1.16, 4.25). Compared with low-intensity, we also find that women who performed moderate- and high-housework intensity had a higher risk of triglycerides (moderate-intensity: OR=1.78, 95% CI: 1.14, 2.78; high-intensity: OR=1.91, 95% CI: 1.22, 2.98), MetS (OR=1.54, 95% CI: 0.98, 2.43; OR=1.68, 95% CI: 1.07, 2.66), pre-hypertension (OR=1.68, 95% CI: 1.08, 2.62; OR=1.63, 95% CI: 1.04, 2.55), and obesity (OR=1.65, 95% CI: 1.01, 2.70; OR=1.66, 95% CI: 1.01, 2.72).

Conclusion

In women, we find that housework is positively associated with the metabolic markers, triglycerides, MetS, and pre-hypertension. However, we did not find evidence that this relationship exists in men, f or any biomarkers we considered. One possible explanation is that people who engage in high-intensity housework are more stressed and sleep less, which could be a mechanism by which housework becomes associated with metabolic disease.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-12566-6.

Girls' transition to adulthood and their later life socioeconomic attainment: Findings from the English longitudinal study of ageing

Transitions to adulthood represent a sensitive period for setting young people into particular life course trajectories, and the nature of these transitions have varied more for girls, historically, than for boys. We aim to investigate the long-term significance of different transitions out of full-time education for socioeconomic attainment in later life amongst postwar young women in England. Our data are from the English Longitudinal Study of Ageing for girls born during World War II and the post-war period (1939-1952, n = 1798). Using sequence analysis, we identified six types of transition out of full-time education between ages 14 and 26: Early-Work, Mid-Work, Late-Work, Early-Domestic, Late-Domestic, and Part-time Mixed. We used linear and multinomial regression models to examine associations between transition types and socioeconomic attainment outcomes from age 50, including individual income, household income and wealth, and occupational class. Our study found that later transitions into employment (Mid-Work and Late-Work) were associated with higher socioeconomic attainment after age 50 compared with women who made early transitions from education to employment (Early-Work); much of the advantage of making later transitions to employment was due to higher educational attainment. We also found that early transitions to domestic work (Early-Domestic) set young women onto trajectories of lower socioeconomic attainment than compared with those who made early transitions to employment, suggesting the nature of the transition from full-time education is as important as the timing, perhaps uniquely for women. A pathway of cumulative advantage/disadvantage is also evident in our study; results suggest a partial mediating role for educational attainment in associations between childhood social class and later life socioeconomic attainment.

How does mental health stigma get under the skin? Cross-sectional analysis using the Health Survey for England

Despite increased awareness of mental health problems, stigma persists. Little research has examined potential health and wellbeing outcomes associated with stigma. The aim of this study was to investigate relationships between mental health stigma, metabolic and cardiovascular biomarkers, as well as wellbeing and quality of life among people with no mental disorder, common mental disorders and severe mental illness. Data were taken from adults aged 16 + years participating in the Health Survey for England in 2014 (N = 5491). Mental health stigma was measured using the 12-item Community Attitudes towards the Mentally Ill (CAMI) scale, intended to measure attitudes around prejudice and exclusion, and tolerance and support for community care. Individuals were divided into six groups based on their mental health (no mental disorder, common mental disorder, severe mental illness) and whether they exhibited more (≤25^th percentile) or less (>25^th percentile) stigmatising attitudes. Metabolic and cardiovascular biomarker outcomes included systolic and diastolic blood pressure; total cholesterol; high-density lipoprotein (HDL) cholesterol; glycated haemoglobin, body mass index (BMI), waist-hip ratio and resting pulse rate. Biomarkers were analysed individually and as an allostatic load score. Wellbeing was measured using Warwick-Edinburgh Mental Wellbeing Scale (WEMWBS) and quality of life via Euro-QoL-5D (EQ-5D). Linear regression models were calculated adjusted for confounders. Compared to individuals with less stigmatising attitudes, results suggested that those with more negative attitudes exhibited poorer wellbeing and quality of life across all mental disorder/stigma groups, including those with no mental disorder (WEMWBS (range 14–70): b = -1.384, 95% CI: -2.107 to -0.661). People with severe mental illness generally had unhealthier biomarker profiles and allostatic load scores, but results were inconsistent for any additional influence of mental health stigma. Reducing stigma may be beneficial for population wellbeing, but further research is needed to clarify whether stigma contributes to adverse biomarkers amongst people with mental illness.

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Few studies have researched the consequences of mental health stigma.

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More stigmatising attitudes relate to poorer wellbeing amongst all groups.

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People with severe mental illness had more adverse biomarker profiles.

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Results were inconclusive for any additional influence of mental health stigma.