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Distinct depressive symptom trajectories are associated with incident diabetes among Chinese middle-aged and older adults: The China Health and Retirement Longitudinal Study. J Psychosom Res 2023; 164:111082. [PMID: 36379076 DOI: 10.1016/j.jpsychores.2022.111082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/05/2022] [Revised: 11/05/2022] [Accepted: 11/06/2022] [Indexed: 11/11/2022]
Abstract
OBJECTIVE Previous studies have reported that depression and depressive symptom are associated with diabetes incident. However, the association between long-term depressive symptom patterns and risk of diabetes remains unknown. The aim of present study was to evaluate the association between depressive symptom trajectories and risk of diabetes. METHODS We used data of 8806 participants (≥45 years old) from the China Health and Retirement Longitudinal Study (CHARLS). Trajectories of depressive symptom were identified by latent mixture modeling. Multivariable logistic regression model was used to examine the association of depressive symptom trajectories with diabetes. RESULTS Five depressive symptom trajectories were identified, characterizing by maintaining a low CES-D scores throughout the follow-up (low-stable; 3227 participants [36.65%]); maintaining a moderate CES-D scores throughout the follow-up (moderate-stable; 3402 participants [38.63%]); moderate starting CES-D scores then increasing scores (moderate-increasing; 681 participants [7.73%%]); high starting CES-D scores but then decreasing scores (high-decreasing; 1061 participants [12.05%]); and maintained high CES-D scores throughout the follow-up (high-stable; 435 participants [4.94%]). During 2015 to 2018 (Wave 3 to Wave 4), a total of 312 respondents experienced diabetes. Compared with participants in the low-stable depressive symptom trajectory, those following a high-decreasing (ORs = 2.04; 95%CIs 1.48-2.98) and high-stable depressive symptom trajectories (ORs = 3.26; 95%CIs 2.06-5.16) were at substantially higher risk of developing diabetes. CONCLUSIONS Individuals with high-decreasing and high-stable depressive symptom trajectories over time were associated with increased risk of incident diabetes. Long-term depressive symptom may be a strong predictor of having diabetes.
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Liu Y, Chen L, Zhou H, Guan H, Feng Y, Yangji B, Liu Q, Liu X, Xia J, Li J, Zhao X. Does awareness of diabetic status increase risk of depressive or anxious symptoms? Findings from the China Multi-Ethnic cohort (CMEC) study. J Affect Disord 2023; 320:218-229. [PMID: 36191641 DOI: 10.1016/j.jad.2022.09.135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Revised: 09/24/2022] [Accepted: 09/27/2022] [Indexed: 02/02/2023]
Abstract
INTRODUCTION People with diabetes mellitus (DM) have increased risk of depressive symptoms (DS) or anxious symptoms (AS). This study explores whether awareness of DM will contribute to prevalence of DS or AS. METHODS The baseline data including 81,717 adults from Southwest China was analyzed. DS and AS were assessed using PHQ-2 and GAD-2. Exposures were defined as 1) having self-reported physician diagnosis of diabetes (self-reported DM), 2) no prior diagnosis of diabetes but meeting diagnostic criteria (newly diagnosed DM), 3) having self-reported physician diagnosis or meeting criteria of non-diabetic diseases (non-diabetic patients), 4) healthy participants. Generalized linear mixed models were used to assess impact of presence and awareness of DM on DS or AS, adjusting for regional and individual related factors. RESULTS The prevalence of DS in self-reported DM, newly diagnosed DM, non-diabetic patient and healthy participants was 7.08 %, 4.30 %, 5.37 % and 3.17 %. The prevalence of AS was 7.80 %, 5.77 %, 6.37 % and 3.91 %. After adjusting for related factors, compared with healthy participants, self-reported DM and non-diabetic patients were associated with DS [AORDS, self-reported = 1.443(1.218,1.710), AORDS, nondiabetic patients = 1.265(1.143,1.400)], while the association between newly diagnosed DM and DS was not statistically significant. The associations between self-reported DM, newly diagnosed DM, non-diabetic patients and AS were all statistically significant. LIMITATIONS DS and AS were assessed through self-report and may suffer recall or information bias. CONCLUSIONS The association between awareness of diabetes and DS/AS suggests to pay attention to distinguish between self-reported and newly diagnosed DM and screening for DS and AS in diabetic population.
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Affiliation(s)
- Yuanyuan Liu
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Liling Chen
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, China
| | - Hanwen Zhou
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Han Guan
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Guizhou Medical University, Guiyang, Guizhou, China
| | - Yuemei Feng
- School of Public Health, Kunming Medical University, Kunming, Yunnan, China
| | - Baima Yangji
- School of Medicine, Tibet University, Lhasa, Tibet Autonomous Region, China
| | - Qiaolan Liu
- Department of Health Behavior and Social Medicine, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xiang Liu
- Department of Health Behavior and Social Medicine, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Jinjie Xia
- Chengdu Center for Disease Control and Prevention, Chengdu, Sichuan, China
| | - Jingzhong Li
- Tibet Center for Disease Control and Prevention, Lhasa, Tibet Autonomous Region, China
| | - Xing Zhao
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
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Liu X, Li Y, Guan L, He X, Zhang H, Zhang J, Li J, Zhong D, Jin R. A Systematic Review and Meta-Analysis of the Prevalence and Risk Factors of Depression in Type 2 Diabetes Patients in China. Front Med (Lausanne) 2022; 9:759499. [PMID: 35620713 PMCID: PMC9127805 DOI: 10.3389/fmed.2022.759499] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Accepted: 03/21/2022] [Indexed: 11/16/2022] Open
Abstract
Background The prevalence of type 2 diabetes mellitus (T2DM) is increasing in China. Depression in patients with T2DM interferes with blood glucose management, leads to poor treatment outcomes, and has a high risk of dementia and cardiovascular event. We conducted this systematic review and meta-analysis to evaluate the prevalence of depression in patients with T2DM in China and explore potential risk factors associated with depression in T2DM. Methods We conducted a literature search in MEDLINE/PubMed, EMBASE, the Cochrane Library, the Chinese Biomedical Literature Database (CBM), the China National Knowledge Infrastructure (CNKI), the Chinese Science and Technology Periodical Database (VIP), and the Wanfang Database from their inception to February 25, 2022 to include population-based, cross-sectional surveys that investigated the prevalence of depression in Chinese T2DM patients and studied possible risk factors. Gray literature and reference lists were also manually searched. We used the Agency for Healthcare Research and Quality methodology checklist to assess the risk of bias in the included studies. Two reviewers screened studies, extracted data, and evaluated the risk of bias independently. The primary outcome was the pooled prevalence of depression in Chinese T2DM patients, and the secondary outcomes included potential risk factors for depression in T2DM patients. R (version 3.6.1) and Stata (version 12.0) software were used for data synthesis. Results We included 48 reports that identified 108,678 subjects. Among the included reports, 4 were rated as low risk of bias, 40 moderate risks of bias, and 4 high risks of bias. The prevalence of depression in T2DM patients in China was 25.9% (95% CI 20.6%-31.6%). The prevalence of depression was higher in women (OR = 1.36, 95% CI 1.19-1.54), subjects ≥60 years (OR = 1.56, 95% CI 1.14-2.14), with a primary school or lower education (vs. middle or high school education (OR = 1.49, 95% CI 1.16 - 1.92); vs. college degree or higher education (OR = 1.84, 95% CI 1.16 - 2.92), with a duration of T2DM ≥ 10 years (OR = 1.68, 95% CI 1.11-2.54), with complications (OR = 1.90, 95% CI 1.53-2.36), insulin users (OR = 1.46, 95% CI 1.09-1.96) and individuals living alone (OR = 2.26, 95% CI 1.71-2.98). T2DM patients with current alcohol use had a lower prevalence of depression (OR = 0.70, 95% CI 0.58-0.86). Prevalence varied from 0.8 to 52.6% according to different instruments used to detect depression. Conclusion The prevalence of depression in T2DM patients is remarkable in China. Potential risk factors of depression in T2DM patients included women, age ≥ 60 years, low educational level, complications, duration of diabetes ≥ 10 years, insulin use, and living alone. High-quality epidemiological investigations on the prevalence of depression in Chinese T2DM patients are needed to better understand the status of depression in T2DM. Systematic Review Registration https://www.crd.york.ac.uk/PROSPERO/, identifier: CRD42020182979.
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Affiliation(s)
- Xiaobo Liu
- School of Health Preservation and Rehabilitation, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Yuxi Li
- School of Health Preservation and Rehabilitation, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Li Guan
- Department of Rehabilitation, Fushun County People's Hospital, Zigong, China
| | - Xia He
- Affiliated Rehabilitation Hospital of Chengdu University of Traditional Chinese Medicine /Sichuan Province Rehabilitation Hospital, Chengdu, China
| | - Huiling Zhang
- School of Health Preservation and Rehabilitation, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Jun Zhang
- School of Health Preservation and Rehabilitation, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Juan Li
- School of Health Preservation and Rehabilitation, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Dongling Zhong
- School of Health Preservation and Rehabilitation, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Rongjiang Jin
- School of Health Preservation and Rehabilitation, Chengdu University of Traditional Chinese Medicine, Chengdu, China
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Di N, Li S, Xiang H, Xie Y, Mao Z, Hou J, Liu X, Huo W, Yang B, Dong G, Wang C, Chen G, Guo Y. Associations of Residential Greenness with Depression and Anxiety in Rural Chinese Adults. Innovation (N Y) 2020; 1:100054. [PMID: 34557719 PMCID: PMC8454668 DOI: 10.1016/j.xinn.2020.100054] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Accepted: 10/29/2020] [Indexed: 12/27/2022] Open
Abstract
Background Depression and anxiety are top contributors to non-fatal health loss globally. Several studies have indicated the association between residential greenness and mental health. Method The participants (n = 27,366) were recruited from four counties in Henan Province, China during 2015–2017. Symptoms of depression and anxiety were evaluated using the Patient Health Questionnaire-2 (PHQ-2) and the Generalized Anxiety Disorder-2 (GAD-2) in the baseline survey. The level of residential greenness during the 3-year period before the baseline survey was assessed using the Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). The mixed-effect linear regression model was applied to examine the associations of residential greenness with depression and anxiety. Results The results of adjusted models showed that the score of PHQ-2 (Δscore and 95% confidence interval [CI]) decreased by −0.024 (−0.041, −0.006) and −0.022 (−0.038, −0.004) with an interquartile range (IQR) increase in NDVI and EVI within a 1,000-m buffer radius, respectively. The score of GAD-2 (Δscore and 95% CI) decreased by −0.024 (−0.040, −0.006) and −0.028 (−0.044, −0.011), in relation to an IQR increase in NDVI and EVI within a 1,000-m buffer radius, respectively. Conclusions A higher level of residential greenness was significantly associated with lower risk of depression and anxiety in rural areas of Henan Province. Improving residential greenness accessibility may help to promote the mental health of rural populations. Mental disorders, particularly depression and anxiety, have become one of the most serious public health issues globally. Symptoms of depression and anxiety and level of residential greenness were investigated for 27,366 participants from the Henan Rural Cohort. The mixed effect linear regression model was used to examine the associations between level of residential greenness and depression and anxiety in rural areas of Henan Province, China. Higher residential greenness was significantly associated with lower risks of depression and anxiety. Stronger effects of residential greenness were observed in males and in those with higher income and education level.
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Affiliation(s)
- Niu Di
- Global Health Institute; Department of Global Health, School of Health Sciences, Wuhan University, Wuhan 430071, Hubei, China
| | - Shanshan Li
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Hao Xiang
- Global Health Institute; Department of Global Health, School of Health Sciences, Wuhan University, Wuhan 430071, Hubei, China
| | - Yinyu Xie
- Global Health Institute; Department of Global Health, School of Health Sciences, Wuhan University, Wuhan 430071, Hubei, China
| | - Zhenxing Mao
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou 450001, Henan, China
| | - Jian Hou
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou 450001, Henan, China
| | - Xiaotian Liu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou 450001, Henan, China
| | - Wenqian Huo
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou 450001, Henan, China
| | - Boyi Yang
- Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment; Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, 74 Zhongshan 2 Road, Yuexiu District, Guangzhou 510080, Guangdong, China
| | - Guanghui Dong
- Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment; Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, 74 Zhongshan 2 Road, Yuexiu District, Guangzhou 510080, Guangdong, China
| | - Chongjian Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou 450001, Henan, China
| | - Gongbo Chen
- Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment; Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, 74 Zhongshan 2 Road, Yuexiu District, Guangzhou 510080, Guangdong, China
| | - Yuming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
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