Zhimin Yan1, Xun Yang1, Lei Wang2, Yuhan Zhao1, Lin Yu1. 1. Faculty of Psychology,Southwest University,No. 2 Tiansheng Road,Beibei District,Chongqing,400715,P. R. China. 2. Department of Internal Medicine V,Medical Clinic,University Clinic Heidelberg,69120,Heidelberg,Germany.
Abstract
BACKGROUND: In China, rapid economic growth and increasing social problems constitute the two basic characteristics underlying contemporary social change. With dramatic social change, loneliness in older adults may have changed across birth cohorts, thus altering older adults' mental health. The present study aims to identify birth cohort changes in Chinese older adults' loneliness and the social indicators underlying these changes. METHODS: Cross-temporal meta-analysis was utilized to investigate changes in Chinese older adults' loneliness from 1995 to 2011. We analyzed 25 studies (N = 13,280 adults; age ≥ 60 years) employing the University of California at Los Angeles Loneliness Scale. We correlated loneliness scores with social indicators and matched these correlations for three periods: ten years before the data collection, five years before data collection, and during the year of data collection. RESULTS: Loneliness levels in Chinese older adults have increased by 1.02 standard deviations from 1995 to 2011. Social indicators such as increased urbanization level, personal medical expenditure, divorce rate, the Gini coefficient, and unemployment rate significantly predicted loneliness in Chinese older adults. Decrease in social connectedness and increase in levels of health threat may be responsible for the observed increase in levels of loneliness. CONCLUSIONS: Cross-temporal meta-analysis revealed a birth cohort increase in loneliness among Chinese older adults. We conclude that changes in social connectedness and levels of health threat likely play an important role in predicting loneliness in the population of Chinese elderly adults.
BACKGROUND: In China, rapid economic growth and increasing social problems constitute the two basic characteristics underlying contemporary social change. With dramatic social change, loneliness in older adults may have changed across birth cohorts, thus altering older adults' mental health. The present study aims to identify birth cohort changes in Chinese older adults' loneliness and the social indicators underlying these changes. METHODS: Cross-temporal meta-analysis was utilized to investigate changes in Chinese older adults' loneliness from 1995 to 2011. We analyzed 25 studies (N = 13,280 adults; age ≥ 60 years) employing the University of California at Los Angeles Loneliness Scale. We correlated loneliness scores with social indicators and matched these correlations for three periods: ten years before the data collection, five years before data collection, and during the year of data collection. RESULTS: Loneliness levels in Chinese older adults have increased by 1.02 standard deviations from 1995 to 2011. Social indicators such as increased urbanization level, personal medical expenditure, divorce rate, the Gini coefficient, and unemployment rate significantly predicted loneliness in Chinese older adults. Decrease in social connectedness and increase in levels of health threat may be responsible for the observed increase in levels of loneliness. CONCLUSIONS: Cross-temporal meta-analysis revealed a birth cohort increase in loneliness among Chinese older adults. We conclude that changes in social connectedness and levels of health threat likely play an important role in predicting loneliness in the population of Chinese elderly adults.
Authors: Ellen E Lee; Colin Depp; Barton W Palmer; Danielle Glorioso; Rebecca Daly; Jinyuan Liu; Xin M Tu; Ho-Cheol Kim; Peri Tarr; Yasunori Yamada; Dilip V Jeste Journal: Int Psychogeriatr Date: 2019-10 Impact factor: 3.878
Authors: Wenwen Wu; Wenru Wang; Zhuangzhuang Dong; Yaofei Xie; Yaohua Gu; Yuting Zhang; Mengying Li; Xiaodong Tan Journal: Int J Environ Res Public Health Date: 2018-09-19 Impact factor: 3.390
Authors: Hui-Chuan Hsu; Jersey Liang; Dih-Ling Luh; Chen-Fen Chen; Ying-Wei Wang Journal: Int J Environ Res Public Health Date: 2019-08-20 Impact factor: 3.390