Social factors of health-related quality of life in older adults: a multivariable analysis.

PURPOSE: The objective of the analysis was to examine the relationships between sociodemographic, socioeconomic, psychosocial, and behavioural factors and both physical and mental health-related quality of life (HRQOL) in older adults. METHODS: The analysis was based on recent cross-sectional data of 1687 community residents from a whole population postal survey of German adults aged 65 years and older (33% response rate, 52% female, mean age 76 years). HRQOL was assessed using the 36-Item Short Form Survey (SF-36v2). For a differentiated analysis, hierarchical multiple linear regressions were performed. RESULTS: An internal health locus of control, physical activity, social support, and income were positively associated with physical HRQOL (Adj. R2 = 0.34; p < 0.001) and mental HRQOL (Adj. R2 = 0.18; p < 0.001), whereas an external health locus of control and age were negatively associated with both. Alcohol use and educational level were positively associated only with physical HRQOL, whilst female gender was negatively associated only with mental HRQOL. CONCLUSION: Sociodemographic, socioeconomic, psychosocial, and behavioural factors were associated with physical and mental HRQOL. These results highlight the importance of social factors in HRQOL and provide approaches for policy and practice to develop and implement tailored health interventions for older adults. Our findings may be transferable to municipalities in metropolitan areas of high-income European countries. CLINICAL TRIAL REGISTRATION: Not applicable.

Mental health indicators and their lifestyle associations in German students: a gender-specific multivariable analysis.

BACKGROUND: Statistics show that the number of received psychosocial counselling sessions remains at a constantly high level or has even increased since the COVID-19 pandemic situation in 2020. The objective of this work is to identify factors associated with students' mental health to improve prevention and promotion in mental health at universities. METHODS: The analyses were based on a cross-sectional data set collected by an online survey among 1,842 students from a German University of Applied Sciences in 2014. Descriptive statistics as well as nine different multiple linear regression models were calculated with IBM® SPSS® Statistics software. Mental health indicators used were mental health-related quality of life (mental HRQOL), depression, and anxiety, which were analysed in a gender-specific manner. RESULTS: The analyses showed that the mean of the mental HRQOL score of the SF-36 for the student sample (46.68) was lower than the values for German (48.76) or American (51.34) norm samples. A key finding was the differences in mental health indicators between male and female students. Women reported worse mental health status in comparison to men. Female gender (ß of -.09; p < 0.01), age (ß of -1.05; p < 0.01), underweight (ß of -.09; p < 0.05), smoking (ß of -.10; p < 0.05) and drug consumption (ß of -.15; p < 0.001) were negatively associated with mental health indicators. In our sample, a moderate consumption of alcohol within the female population (ß of .12; p < 0.01) and physical activity within the male sample (ß of .09; p < 0.05) were positively associated with mental health indicators. CONCLUSION: The gender-specific differences of students' mental health and its associations could be an important result for counselling services at universities to adjust methods according to gender. Contrary to the general societal perception, students have lower mental health than a norm sample even before the pandemic. Due to the additional mental stress caused by the pandemic, it can be assumed that mental health problems have increased even more. Universities should therefore pay more attention to the mental health of their students.

Social Factors of Dietary Risk Behavior in Older German Adults: Results of a Multivariable Analysis.

With this analysis, we aimed to examine the associations between social factors and dietary risk behavior in older adults. Data were collected through a full-population postal survey of German adults aged 65 years or older (n = 1687, 33% response proportion, 52% female, mean age = 76 years). Using principal component analysis (PCA), a data-driven Dietary Risk Behavior Index (DRB) was computed. Dietary risk behavior was defined as consumption frequencies of vegetables/fruit, whole grains, and dairy products below national dietary recommendations. By performing a multiple linear regression, we analyzed associations between sociodemographic, socioeconomic, psychosocial, and behavioral factors and dietary risk behavior. Physical activity, female gender, socioeconomic status, social support, and age (in the male sample) were negatively associated with dietary risk behavior. Alcohol consumption and smoking were positively associated with dietary risk behavior. A group-specific analysis revealed a higher goodness-of-fit for the low socioeconomic status group, older adults aged 65-79 years, and women. A comprehensive understanding of the relationships between social factors and dietary risk behavior in older adults assists the group-specific targeting of dietary-related interventions. Demand-oriented dietary interventions should account for underlying social conditions to reduce inequity in dietary risk behavior among older adults. The results of this work may be transferable to municipalities in high-income European countries.