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Correlates and aetiological factors associated with hedonic well-being among an ageing population of US men and women: secondary data analysis of a national survey.
BMJ Open 2018 November 14
OBJECTIVE: To understand the gender-specific factors that uniquely contribute to successful ageing in a US population of men and women, 57-85 years of age. This was achieved through the examination of the correlates of subjective well-being defined by health-related quality of life (HRQoL), across several biological and psychosocial determinants of health.
DESIGN: Cross-sectional study.
SETTING: The National Social Life, Health and Ageing Project (NSHAP), 2010-2011 a representative sample of the US population.
PARTICIPANTS: 3377 adults aged 57-85 (1538 men, 1839 women) from the NSHAP.
MAIN OUTCOME MEASURES: The biopsychosocial factors of biological/physiological function, symptom status, functional status, general health perceptions and HRQoL happiness.
METHOD: HRQoL was measured using the NSHAP wave 2 multistage, stratified area probability sample of US households (n=3377). Variable selection was guided by the Wilson and Cleary model (WCM) that classifies health outcomes at five main levels and characteristics.
RESULTS: Our findings indicate differences in biopsychosocial factors comprised in the WCM and their relative importance and unique impact on HRQoL by gender. Women reported significantly lower HRQoL than men (t=3.5, df=3366). The most significant contributors to HRQoL in women were mental health (B=0.31; 0.22, 0.39), loneliness (B=-0.26; -0.35, -0.17), urinary incontinence (B=-0.22; -0.40, -0.05) and support from spouse/partner (B=0.27; 0.10, 0.43) and family B=0.12; 0.03, 0.20). Men indicated mental health (B=0.21; 0.14, 0.29), physical health (B=0.17; 0.10, 0.23), functional difficulties (B=0.38; 0.10, 0.65), loneliness (B=-0.20; -0.26, -0.12), depression (B=-0.36; -0.58, -0.15) and support from friends (B=0.06; 0.10, 0.11) as significant contributors. Those with greater social support had better HRQoL (F=4.22, df=4). Lack of companionship and reliance on spouse/partner were significant HRQoL contributors in both groups.
CONCLUSION: Our findings offer insight into ageing, gender and subjective well-being. The results provide an opportunity to identify biopsychosocial factors to inform interventions to support successful ageing.
DESIGN: Cross-sectional study.
SETTING: The National Social Life, Health and Ageing Project (NSHAP), 2010-2011 a representative sample of the US population.
PARTICIPANTS: 3377 adults aged 57-85 (1538 men, 1839 women) from the NSHAP.
MAIN OUTCOME MEASURES: The biopsychosocial factors of biological/physiological function, symptom status, functional status, general health perceptions and HRQoL happiness.
METHOD: HRQoL was measured using the NSHAP wave 2 multistage, stratified area probability sample of US households (n=3377). Variable selection was guided by the Wilson and Cleary model (WCM) that classifies health outcomes at five main levels and characteristics.
RESULTS: Our findings indicate differences in biopsychosocial factors comprised in the WCM and their relative importance and unique impact on HRQoL by gender. Women reported significantly lower HRQoL than men (t=3.5, df=3366). The most significant contributors to HRQoL in women were mental health (B=0.31; 0.22, 0.39), loneliness (B=-0.26; -0.35, -0.17), urinary incontinence (B=-0.22; -0.40, -0.05) and support from spouse/partner (B=0.27; 0.10, 0.43) and family B=0.12; 0.03, 0.20). Men indicated mental health (B=0.21; 0.14, 0.29), physical health (B=0.17; 0.10, 0.23), functional difficulties (B=0.38; 0.10, 0.65), loneliness (B=-0.20; -0.26, -0.12), depression (B=-0.36; -0.58, -0.15) and support from friends (B=0.06; 0.10, 0.11) as significant contributors. Those with greater social support had better HRQoL (F=4.22, df=4). Lack of companionship and reliance on spouse/partner were significant HRQoL contributors in both groups.
CONCLUSION: Our findings offer insight into ageing, gender and subjective well-being. The results provide an opportunity to identify biopsychosocial factors to inform interventions to support successful ageing.
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