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Several studies have documented associations between social isolation and poor physical health or well-being. However, little is known of the importance of social support among older adults on specific topics about their quality of life. The purpose of the present study was to determine the relationship between social isolation and quality of life among older adults.
A cross-sectional study.
1,252 subjects aged ≥ 60 years living at home.
We used the Abbreviated Version of the Lubben Social Network Scale (LSNS-6) to assess social isolation and the World Health Organization Quality of Life Instrument-Older Adults Module (WHOQOL-Old) to assess quality of life. Socio-demographic and health factors were collected through face-to-face interviews. A series of linear regression analyses were used to investigate relationship between social isolation and quality of life. The statistical models were controlled for socio-demographic and health factors.
A total of 750 women (60%) and 502 men (40%) participated in the study. According to their LSNS-6 scores, 426 participants (34.0%) were classified into the highest group of isolation (range 0-10 points). Older adults with higher scores of social isolation exhibited lower quality of life. Regression analyses indicated that social isolation correlated with lower levels of global quality of life, autonomy, intimacy, and past, present, and future activities.
Coping with life from a socially isolated situation entails serious difficulties concerning quality of life. Interventions that foster environments where older adults can forge social bonds might improve their quality of life.
Little is known about the joint mental health effects of air pollution and tobacco smoking in low- and middle-income countries.
To investigate the effects of exposure to ambient fine particulate matter pollution (PM2.5) and smoking and their combined (interactive) effects on depression.
Multilevel logistic regression analysis of baseline data of a prospective cohort study (n=41785). The 3-year average concentrations of PM2.5 were estimated using US National Aeronautics and Space Administration satellite data, and depression was diagnosed using a standardised questionnaire. Three-level logistic regression models were applied to examine the associations with depression.
The odds ratio (OR) for depression was 1.09 (95% CI 1.01–1.17) per 10 μg/m3 increase in ambient PM2.5, and the association remained after adjusting for potential confounding factors (adjusted OR = 1.10, 95% CI 1.02–1.19). Tobacco smoking (smoking status, frequency, duration and amount) was also significantly associated with depression. There appeared to be a synergistic interaction between ambient PM2.5 and smoking on depression in the additive model, but the interaction was not statistically significant in the multiplicative model.
Our study suggests that exposure to ambient PM2.5 may increase the risk of depression, and smoking may enhance this effect.
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