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Determinants of self-rated health among shanghai elders: a cross-sectional study

Overview of attention for article published in BMC Public Health, October 2017
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Title
Determinants of self-rated health among shanghai elders: a cross-sectional study
Published in
BMC Public Health, October 2017
DOI 10.1186/s12889-017-4718-5
Pubmed ID
Authors

Weizhen Dong, Jin Wan, Yanjun Xu, Chun Chen, Ge Bai, Lyuying Fang, Anjiang Sun, Yinghua Yang, Ying Wang

Abstract

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. 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. Younger age (χ(2) = 27.5, p < 0.05), male sex (χ(2) = 11.5, p < 0.1), and living in the suburbs (χ(2) = 55.1, p < 0.05) were associated with better SRH scores. Higher SRH scores were also linked with health behaviour of the respondents; namely, do not smoke (χ(2) = 18.0, p < 0.1), do not drink (χ(2) = 18.6, p < 0.1), or engage in regular outdoor activities (χ(2) = 69.3, p < 0.05). The respondents with better social support report higher SRH scores than those without. Respondents' ability to hear (χ(2) = 38.7, p < 0.05), speak (χ(2) = 16.1, p < 0.05) and see (χ(2) = 78.3, p < 0.05) impacted their SRH scores as well. Meanwhile, chronic illness except asthma was a major influence factor in low SRH score. Applying multiple regression models, a series of determinants were analysed to establish the extent to which they contribute to SRH. The impact of these variables on SRH scores were 6.6% from socio-demographic and health risk behaviours, 2.4% from social support, 8.5% from mental health, 20% from physical conditions, and13% from chronic diseases. This is the first study that examines the determinants of SRH among Shanghai elders. Nearly 40% of our study's respondents reported their health status as "good". The main determinants of SRH among elders include living condition, health risk behaviour, social support, health status, and the economic status of the neighbourhood.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 86 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 86 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 21 24%
Student > Doctoral Student 9 10%
Researcher 6 7%
Student > Bachelor 4 5%
Student > Postgraduate 4 5%
Other 12 14%
Unknown 30 35%
Readers by discipline Count As %
Medicine and Dentistry 13 15%
Nursing and Health Professions 11 13%
Social Sciences 11 13%
Psychology 6 7%
Unspecified 3 3%
Other 12 14%
Unknown 30 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 October 2017.
All research outputs
#15,481,888
of 23,006,268 outputs
Outputs from BMC Public Health
#11,438
of 14,988 outputs
Outputs of similar age
#203,964
of 325,895 outputs
Outputs of similar age from BMC Public Health
#123
of 165 outputs
Altmetric has tracked 23,006,268 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 14,988 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.0. This one is in the 16th percentile – i.e., 16% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 325,895 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 165 others from the same source and published within six weeks on either side of this one. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.