1. Determinants of self-rated health among shanghai elders: a cross-sectional study
- Author
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Jin Wan, Anjiang Sun, Weizhen Dong, Ge Bai, Lyuying Fang, Yanjun Xu, Yinghua Yang, Ying Wang, and Chun Chen
- Subjects
Male ,medicine.medical_specialty ,China ,Activities of daily living ,Cross-sectional study ,Health Status ,education ,Shanghai ,Health Risk Behaviors ,03 medical and health sciences ,Social support ,Diagnostic Self Evaluation ,0302 clinical medicine ,Residence Characteristics ,Environmental health ,Self-rated Health ,Medicine ,Humans ,030212 general & internal medicine ,Socioeconomic status ,Self-rated health ,Aged ,Aged, 80 and over ,030505 public health ,business.industry ,Elders ,lcsh:Public aspects of medicine ,Public health ,Public Health, Environmental and Occupational Health ,Social Support ,lcsh:RA1-1270 ,Middle Aged ,Mental health ,Health Surveys ,Health promotion ,Cross-Sectional Studies ,Socioeconomic Factors ,Female ,0305 other medical science ,business ,Research Article - Abstract
Background As the most populous nation in the world, China has now becoming an emerging ageing society. Shanghai is the first city facing the challenge of ageing demographics. Against this background, a study that employs self-rated health (SRH) assessment system was designed to explore the health status of Shanghai elders, and learn their attitudes toward health issues; as well as to investigate the determinants of SRH among Shanghai elders. Understanding SRH is crucial for finding appropriate solutions that could effectively tackle the increasing eldercare demand. Methods This study adopted a quantitative research strategy. Using a multistage stratified cluster sampling method, we conducted a questionnaire survey in August 2011 in Shanghai, which collected 2001 valid survey responses. SRH assessments were categorized by five levels: very good, fairly good, average, fairly poor, or poor. The respondents’ functional status was evaluated using the Barthel index of activities for daily living. In the data analysis, we used chi-squared test to determine differences in socio-demographic characteristics among various groups. Along with statistics, several logistic regression models were designed to determine the associations between internal influence factors and SRH. Results Younger age (χ2 = 27.5, p
- Published
- 2017