Title : Quality of life profiles and its association with predictors amongst older Chinese adults in nursing homes: A latent profile analysis
This study aimed to examine self-reported quality of life (QoL) profiles in Chinese older adults and explore the association of QoL profiles with demographic and psychosocial characteristics.
A sample of 354 older adults in nursing homes was recruited from Guangdong Province, China, between November 2020 and January 2021. Latent Profile Analysis (LPA) was conducted to explore QoL profiles using the four WHOQOL-BREF domains as input variables. Multinomial logistic regression was performed to explore the association between latent profiles and demographic and psychosocial characteristics.
LPA identified three distinctive QoL profiles: “low QoL with poor psychological health” (18.1%), “moderate QoL” (46.0%) and “high QoL” (35.9%). Gender, educational level, activity frequency of physical weekly activity and average time spent on physical activity (P<0.05) were statistically significantly different within the three profiles. The activity frequency (≥7times/per week), optimism, gratitude, and social support were associated with the increased likelihood of belonging to the moderate-to-high QoL classes. Furthermore, Class 2(moderate QoL group, reference) was compared with Class3(high QoL group), higher frequency of weekly physical activity (≥7times) and spending more time on physical activity (≥1 hour) exhibited higher odds of belonging to high QoL class. Older adults with multiple chronic diseases were more likely to belong to the low-to-moderate QoL
category. Also, the high QoL group displayed higher levels of optimism and social support.
Using the domains of the WHOQOL-BREF scale, the QoL profiles Chinese older adults can be identified. We found that psychosocial variables and demographic characteristic, including lower level of optimism and gratitude, lack of social support, low frequency of physical activity, shorter activity duration time, and presence of chronic disease, heighten risk for lower levels of QoL. Identifying classification may help focus on those at elevated risk for poor QoL and for developing tailored QoL improvement programs.
Keywords: Quality of life; Older adults; Nursing home; Latent profile analysis; Gerontology