17
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Obesity and lipid indices as predictors of depressive symptoms in middle-aged and elderly Chinese: insights from a nationwide cohort study

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Depressive symptoms are one of the most common psychiatric disorders, with a high lifetime prevalence rate among middle-aged and elderly Chinese. Obesity may be one of the risk factors for depressive symptoms, but there is currently no consensus on this view. Therefore, we investigate the relationship and predictive ability of 13 obesity- and lipid-related indices with depressive symptoms among middle-aged and elderly Chinese.

          Methods

          The data were obtained from The China Health and Retirement Longitudinal Study (CHARLS). Our analysis includes individuals who did not have depressive symptoms at the baseline of the CHARLS Wave 2011 study and were successfully follow-up in 2013 and 2015. Finally, 3790 participants were included in the short-term (from 2011 to 2013), and 3660 participants were included in the long-term (from 2011 to 2015). The average age of participants in short-term and long-term was 58.47 years and 57.88 years. The anthropometric indicators used in this analysis included non-invasive [e.g. waist circumference (WC), body mass index (BMI), and a body mass index (ABSI)], and invasive anthropometric indicators [e.g. lipid accumulation product (LAP), triglyceride glucose index (TyG index), and its-related indices (e.g. TyG-BMI, and TyG-WC)]. Receiver operating characteristic (ROC) analysis was used to examine the predictive ability of various indicators for depressive symptoms. The association of depressive symptoms with various indicators was calculated using binary logistic regression.

          Results

          The overall incidence of depressive symptoms was 20.79% in the short-term and 27.43% in the long-term. In males, WC [AUC = 0.452], LAP [AUC = 0.450], and TyG-WC [AUC = 0.451] were weak predictors of depressive symptoms during the short-term ( P < 0.05). In females, BMI [AUC = 0.468], LAP [AUC = 0.468], and TyG index [AUC = 0.466] were weak predictors of depressive symptoms during the long-term ( P < 0.05). However, ABSI cannot predict depressive symptoms in males and females during both periods ( P > 0.05).

          Conclusion

          The research indicates that in the middle-aged and elderly Chinese, most obesity- and lipid-related indices have statistical significance in predicting depressive symptoms, but the accuracy of these indicators in prediction is relatively low and may not be practical predictors.

          Related collections

          Most cited references79

          • Record: found
          • Abstract: not found
          • Article: not found

          The CES-D Scale: A Self-Report Depression Scale for Research in the General Population

          L Radloff (1977)
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Cohort profile: the China Health and Retirement Longitudinal Study (CHARLS).

            The China Health and Retirement Longitudinal Study (CHARLS) is a nationally representative longitudinal survey of persons in China 45 years of age or older and their spouses, including assessments of social, economic, and health circumstances of community-residents. CHARLS examines health and economic adjustments to rapid ageing of the population in China. The national baseline survey for the study was conducted between June 2011 and March 2012 and involved 17 708 respondents. CHARLS respondents are followed every 2 years, using a face-to-face computer-assisted personal interview (CAPI). Physical measurements are made at every 2-year follow-up, and blood sample collection is done once in every two follow-up periods. A pilot survey for CHARLS was conducted in two provinces of China in 2008, on 2685 individuals, who were resurveyed in 2012. To ensure the adoption of best practices and international comparability of results, CHARLS was harmonized with leading international research studies in the Health and Retirement Study (HRS) model. Requests for collaborations should be directed to Dr Yaohui Zhao (yhzhao@nsd.edu.cn). All data in CHARLS are maintained at the National School of Development of Peking University and will be accessible to researchers around the world at the study website. The 2008 pilot data for CHARLS are available at: http://charls.ccer.edu.cn/charls/. National baseline data for the study are expected to be released in January 2013.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Obesity and Cardiovascular Disease: A Scientific Statement From the American Heart Association

              The global obesity epidemic is well established, with increases in obesity prevalence for most countries since the 1980s. Obesity contributes directly to incident cardiovascular risk factors, including dyslipidemia, type 2 diabetes, hypertension, and sleep disorders. Obesity also leads to the development of cardiovascular disease and cardiovascular disease mortality independently of other cardiovascular risk factors. More recent data highlight abdominal obesity, as determined by waist circumference, as a cardiovascular disease risk marker that is independent of body mass index. There have also been significant advances in imaging modalities for characterizing body composition, including visceral adiposity. Studies that quantify fat depots, including ectopic fat, support excess visceral adiposity as an independent indicator of poor cardiovascular outcomes. Lifestyle modification and subsequent weight loss improve both metabolic syndrome and associated systemic inflammation and endothelial dysfunction. However, clinical trials of medical weight loss have not demonstrated a reduction in coronary artery disease rates. In contrast, prospective studies comparing patients undergoing bariatric surgery with nonsurgical patients with obesity have shown reduced coronary artery disease risk with surgery. In this statement, we summarize the impact of obesity on the diagnosis, clinical management, and outcomes of atherosclerotic cardiovascular disease, heart failure, and arrhythmias, especially sudden cardiac death and atrial fibrillation. In particular, we examine the influence of obesity on noninvasive and invasive diagnostic procedures for coronary artery disease. Moreover, we review the impact of obesity on cardiac function and outcomes related to heart failure with reduced and preserved ejection fraction. Finally, we describe the effects of lifestyle and surgical weight loss interventions on outcomes related to coronary artery disease, heart failure, and atrial fibrillation.
                Bookmark

                Author and article information

                Contributors
                yaoran2008@163.com
                Journal
                BMC Psychiatry
                BMC Psychiatry
                BMC Psychiatry
                BioMed Central (London )
                1471-244X
                10 May 2024
                10 May 2024
                2024
                : 24
                : 351
                Affiliations
                [1 ]Department of Graduate School, Wannan Medical College, ( https://ror.org/037ejjy86) 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province People’s Republic of China
                [2 ]Student Health Center, Wannan Medical College, ( https://ror.org/037ejjy86) 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province People’s Republic of China
                [3 ]Department of Surgical Nursing, School of Nursing, Jinzhou Medical University, ( https://ror.org/008w1vb37) No.40, Section 3, Songpo Road, Linghe District, Jinzhou City, Liaoning Province People’s Republic of China
                [4 ]Department of Occupational and Environmental Health, Key Laboratory of Occupational Health and Safety for Coal Industry in Hebei Province, School of Public Health, North China University of Science and Technology, ( https://ror.org/04z4wmb81) Tangshan, Hebei Province People’s Republic of China
                [5 ]Obstetrics and Gynecology Nursing, School of Nursing, Wannan Medical College, ( https://ror.org/037ejjy86) 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province People’s Republic of China
                [6 ]Department of Emergency and Critical Care Nursing, School of Nursing, Wannan Medical College, ( https://ror.org/037ejjy86) 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province People’s Republic of China
                [7 ]Department of Internal Medicine Nursing, School of Nursing, Wannan Medical College, ( https://ror.org/037ejjy86) 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province People’s Republic of China
                [8 ]Department of Pediatric Nursing, School of Nursing, Wannan Medical College, ( https://ror.org/037ejjy86) 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province People’s Republic of China
                [9 ]Department of Surgical Nursing, School of Nursing, Wannan Medical College, ( https://ror.org/037ejjy86) 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province People’s Republic of China
                [10 ]Rehabilitation Nursing, School of Nursing, Wannan Medical College, ( https://ror.org/037ejjy86) 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province People’s Republic of China
                Article
                5806
                10.1186/s12888-024-05806-z
                11088055
                38730360
                ddf1ae8e-3247-4c07-99d8-4d37a3aa7dcc
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 30 January 2023
                : 2 May 2024
                Funding
                Funded by: NSFC
                Award ID: 70910107022, 71130002
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000049, National Institute on Aging;
                Award ID: R03-TW008358-01; R01-AG037031-03S1
                Award Recipient :
                Funded by: World Bank
                Award ID: 7159234
                Award Recipient :
                Funded by: the Support Program for Outstanding Young Talents from the Universities and Colleges of Anhui Province for Lin Zhang
                Award ID: gxyqZD2021118
                Award Recipient :
                Categories
                Research
                Custom metadata
                © BioMed Central Ltd., part of Springer Nature 2024

                Clinical Psychology & Psychiatry
                depressive symptoms,obesity,lipid-related index,anthropometric indicators,middle-aged and elderly,cohort study

                Comments

                Comment on this article