Zhi Hu

Prof. Zhi Hu


Research Focus & Metrics

Academic Career Length

16Years (2011-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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16 October 2020 in BMC Public Health
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ZBZhongliang Bai
Zhongliang Bai
ZXZhiwei Xu
Zhiwei Xu
XXXiaoru Xu
Xiaoru Xu
XQXia Qin
Xia Qin
WHWenbiao Hu
Wenbiao Hu
ZHZhi Hu
Zhi Hu
Background: To examine the relationship between social capital and depression among community-dwelling older adults in Anhui Province, China. Methods: A cross-sectional study was conducted among older people selected from three cities of Anhui Province, China using a multi-stage stratified cluster random sampling method. Data were collected through questionnaire interviews and information on demographic characteristics, social capital, and depression was collected. The generalized linear model and classification and regression tree model were employed to assess the association between social capital and depression. Results: Totally, 1810 older people aged ≥60 years were included in the final analysis. Overall, all of the social capital dimensions were positively associated with depression: social participation (coefficient: 0.35, 95% CI: 0.22–0.48), social support (coefficient:0.18, 95% CI:0.07–0.28), social connection (coefficient: 0.76, 95% CI:0.53–1.00), trust (coefficient:0.62, 95% CI:0.33–0.92), cohesion (coefficient:0.31, 95% CI:0.17–0.44) and reciprocity (coefficient:0.30, 95% CI:0.11–0.48), which suggested that older people with higher social capital had a smaller chance to develop depression. A complex joint effect of certain social capital dimensions on depression was also observed. The association with depression and the combinative effect of social capital varied among older adults across the cities. Conclusions: Our study suggests that improving social capital could aid in the prevention of depression among older adults.

27 February 2021 in BMC Public Health
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ZWZijing Wang
Zijing Wang
WPWenjia Peng
Wenjia Peng
MLMengying Li
Mengying Li
XLXinghui Li
Xinghui Li
TYTingting Yang
Tingting Yang
YWYing Wang
Ying Wang
Background: Functional disability and multimorbidity are common among older people. However, little is known about the relationship between functional disability and different multimorbidity combinations. We aimed to identify multimorbidity patterns and explore the associations between these patterns and functional disability. Methods: We investigated a multi-stage random sample of 1871 participants aged ≥60 years and covered by long-term care insurance in Shanghai, China. Multimorbidity was defined as the simultaneous presence of two or more chronic diseases in an individual. Participants completed scales to assess basic and instrumental activities of daily living (BADL and IADL, respectively). Multimorbidity patterns were identified via exploratory factor analysis. Binary logistic regression models were used to determine adjusted associations between functional disability and number and patterns of multimorbidity. Results: Multimorbidity was present in 74.3% of participants. The prevalence of BADL disability was 50.7% and that of IADL disability was 90.7%. There was a strong association between multimorbidity and disability. We identified three multimorbidity patterns: musculoskeletal, cardio-metabolic, and mental-degenerative diseases. The cardio-metabolic disease pattern was associated with both BADL (OR 1.28, 95%CI 1.16–1.41) and IADL (OR 1.41, 95%CI 1.19–1.68) disability. The mental-degenerative disease pattern was associated with BADL disability (OR 1.55, 95%CI 1.40–1.72). Conclusions: Multimorbidity and functional disability are highly prevalent among older people covered by long-term care insurance in Shanghai, and distinct multimorbidity patterns are differentially associated with functional disability. Appropriate long-term healthcare and prevention strategies for older people may help reduce multimorbidity, maintain functional ability, and improve health-related quality of life.

7 January 2021 in BMC Geriatrics
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ZBZhongliang Bai
Zhongliang Bai
ZWZijing Wang
Zijing Wang
TSTiantai Shao
Tiantai Shao
XQXia Qin
Xia Qin
ZHZhi Hu
Zhi Hu
Background: We aimed to examine the association between social capital and loneliness in Anhui Province, China.Methods: Data were collected from a cross-sectional study using a multi-stage stratified cluster sampling strategy. Data on demographic characteristics, socioeconomic factors, social capital, and loneliness in 1810 older adults (aged 60 years and older) were used for analysis. Binary logistic regression models and a classification and regression tree model were performed to assess the association of social capital and loneliness.Results: Our results indicated that social capital in terms of lower level of social participation (AOR = 1.38; 95% CI: 1.10–1.74), social connection (AOR = 1.51; 95% CI: 1.18–1.93), and reciprocity (AOR = 1.47; 95% CI: 1.13–1.90) were associated with higher odds of developing loneliness. We noted the interactive effect of different social capital dimensions on loneliness, suggesting that the risk for suffering loneliness was greatest in older people limited in functional ability, with less trust, less social connection, and less social participation.Conclusions: Our findings show that social capital is associated with loneliness in older adults. This implies that social capital, especially in terms of trust, social connection, and social participation may be significant for alleviating loneliness in later life.

15 August 2015 in BMC Public Health
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FHFu-yong Hu
Fu-yong Hu
LNLi Niu
Li Niu
RCRen Chen
Ren Chen
YMYing Ma
Ying Ma
XQXia Qin
Xia Qin
ZHZhi Hu
Zhi Hu
To investigate the association between social capital and quality of life among type 2 diabetes patients in Anhui province, China. In a cross-sectional study, 436 adults with type 2 diabetes were interviewed. The two domains of Quality of life, physical component summary (PCS) and mental component summary (MCS), were measured using the Short-Form Health Survey (SF-36). A modified instrument scale was used to measure cognitive and structural social capital. Multiple logistic regression models were used to assess the associations between social capital and quality of life, adjusting for social economic status and risk factors for health. 24.3 % of participants (106) were in poor PCS and 25.0 % (109) in poor MCS. The proportions of participants who had low cognitive and structural social capital were 47.0 % (205) and 64.4 % (281), respectively. Results of logistic regression models showed that cognitive social capital was positively associated with PCS (OR = 1.84; 95 % CI: 1.12, 3.02) and MCS (OR = 1.65; 95 % CI: 1.03, 2.66). However, the associations between structural social capital and PCS (OR = 0.80, 95 % CI: 0.48, 1.34) and MCS (OR = 0.62; 95 % CI: 0.38, 1.01) were not statistically significant. It is the first study in China to investigate associations between quality of life and social capital in type 2 diabetes. Findings document that cognitive social capital is associated with the quality of life of type 2 diabetes patients. Our study suggests that the social capital theory may provide a new approach to increase physical resources in diabetes prevention and control, especially in Low and Middle Income countries (LMICs).

21 September 2011 in International Journal of Geriatric Psychiatry
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Ruoling ChenRuoling Chen
Ruoling Chen
YMYing Ma
Ying Ma
KWKen Wilson
Ken Wilson
ZHZhi Hu
Zhi Hu
DSDavid Sallah
David Sallah
JCJohn R Copeland
John R Copeland
Background: Previous studies indicated overall relatively low prevalence of dementia in older people in China, which may be biased by studied samples or methods. We determined the prevalence of dementia cases and subcases in China and examined their socio‐economic correlates.Methods: Using the Geriatric Mental State interview, we examined random samples of 2917 participants aged ≥ 65 years in urban and rural Anhui, China in 2001–2003, and 3327 in four other provinces in 2008–2009. Dementia cases and subcases were diagnosed by Geriatric Mental State‐Automated Geriatric Examination for Computer Assisted Taxonomy.Results: Age‐standardised prevalence for cases and subcases of dementia in the Anhui elders was 7.20% (95%CI 6.29%–8.20%) and 10.5% (9.38%–11.6%), and in the four provinces, 9.86% (8.80%–10.9%) and 8.51% (7.51%–9.52%). The matched figures among the participants who were literate were 3.05% (2.08%–4.02%) and 10.0% (8.38%–11.6%), and 4.92% (3.89%–5.96%) and 6.76% (5.55%–7.96%), respectively. There were higher prevalence rates of dementia cases and subcases in the rural elders than in the urban. Both the Anhui and four‐province studies showed an obvious association of dementia with higher and lower incomes among elders who had lower educational levels or had the lowest occupational class. The highest risk of dementia was found in those who were illiterate but had the highest income or had the job of business/nonmanual labouring.Conclusions: People in China have a higher prevalence of dementia than previously reported. Its U‐shaped relationship with income and the excess subcases prevalence predicates a significant burden of disease, both now and for the future, suggesting preventive strategy for dementia in China. Copyright © 2011 John Wiley & Sons, Ltd.

16 July 2015 in AIDS and Behavior
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YZYe Zhao
Ye Zhao
YMYing Ma
Ying Ma
RCRen Chen
Ren Chen
FLFeng Li
Feng Li
XQXia Qin
Xia Qin
ZHZhi Hu
Zhi Hu