Meta analysis on correlation between living quality of Chinese empty-nest elderly and social support based on Pearson correlation coefficient / 重庆医学

ABSTRACT

Objective To adopt the meta analysis to evaluate the living quality of empty-nest elderly based on Pearson and Spearson correlation coefficients.Methods The databases including Cochmne library,PubMed,PIDQuest,Medline,Springerlink,CMB,CNKI,VIP and WanFang Data were retrieved by using the network databases with the retrieval time limit until July 2016.The literatures on the correlation between the social support and living quality of Chinese empty-nest elderly were searched.The included studies were screened according to the inclusion and exclusion criteria.After extracting data and appraising the quality of the included studies,the meta analysis was conducted by using STATA11.0 software.Results Five articles were included.The literature quality was good as a whole.The total sample amounts were 2 485 subjects,including 1 201 males and 1 284 females.The meta analysis showed that merge correlation coefficient of social support and living quality,and 95 ％ confidence interval(CI)were 0.287 (0.252,0.329);which of social support utilization degree and living quality were 0.232 (0.191,0.274);which of subjective support and living quality were 0.260 (0.224,0.298),which of objective support and living quality were 0.139 (0.101,0.179),after merge,the correlation coefficient of social support was highest.The living quality and social support total score were increased with the samples amounts increase,and the correlation was accordingly decreased.The correlation coefficient measured by random sample method was higher than that measured by the non-random sample method.The correlation coefficient and social support in southern empty-nest elderly was higher than that of northern empty-nest elderly.Conclusion The living quality in Chinese empty-nest elderly has a correlation with the social support,which is mainly affected by subjective support and support utilization degree.