2017
DOI: 10.3390/ijerph14101210
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Socioeconomic Differences and Trends in the Place of Death among Elderly People in China

Abstract: China is facing a dramatic aging of its population. Little is known about the factors that influence the place of death and the trends in the place of death for elderly people in China. The purposes of this study were: (1) to examine the impact of the socioeconomic status (SES) on place of death for elderly Chinese residents; and (2) to assess temporal trends in the place of death over the last 15 years. Data were derived from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) (1998–2012). Place-of-deat… Show more

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Cited by 30 publications
(30 citation statements)
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“…Further older adults, who may utilize care more often with increasing age may also serve as targets for outreach. [18] Possible platforms for knowledge dissemination include using emerging media outlets such as WeChat, microblogging, and traditional media such as newspapers simultaneously to spread public awareness and knowledge regarding NHMS.…”
Section: Conclusion and Policy Implicationsmentioning
confidence: 99%
“…Further older adults, who may utilize care more often with increasing age may also serve as targets for outreach. [18] Possible platforms for knowledge dissemination include using emerging media outlets such as WeChat, microblogging, and traditional media such as newspapers simultaneously to spread public awareness and knowledge regarding NHMS.…”
Section: Conclusion and Policy Implicationsmentioning
confidence: 99%
“…The CLHLS is a community-based longitudinal cohort with the aim of examining factors that promote longevity and quality of life among the older adults. However, we have noticed that the CLHLS study has been limited principally to social science research,3–18 whereas other objective medical aspects such as biomarkers are not available. As a result, such a major obstacle has been preventing us from developing a complete understanding of the determinants of healthy aging.…”
Section: Introductionmentioning
confidence: 99%
“…To deal with these missing values, we followed the methods used in Guerriere et al [ 23 ] and Yang et al [ 24 ] wherein observations with missing data were recognized as a single separate category. In our study, continuous variables were reclassified as categorical variables by dividing the data into quartiles, as performed by Cai et al [ 25 ].…”
Section: Methodsmentioning
confidence: 99%