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Kuang X, Tian L, Chen S, Fang J, Ding P, Li J, Wang L, Shi H. Body mass index trajectories in older adulthood and all-cause mortality: a cohort study in China. BMC Public Health 2025; 25:1311. [PMID: 40197247 PMCID: PMC11977917 DOI: 10.1186/s12889-025-22458-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2024] [Accepted: 03/24/2025] [Indexed: 04/10/2025] Open
Abstract
BACKGROUND Many studies have explored the association between Body Mass Index (BMI) trajectory and mortality, but the association between BMI trajectory during old age and mortality remains underreported, particularly in the Chinese population. This study aimed to investigate the association between BMI trajectories in older adulthood and all-cause mortality in China, and to analyze potential mediating mechanisms. METHODS We analyzed data from the Chinese Longitudinal Healthy Longevity Survey with latent class growth modeling to identity BMI trajectories at 3 follow-up visits (2008, 2011 and 2014). All-cause mortality was assessed from baseline to July 31,2019. Cox proportional hazard regression was used to estimate the association between BMI trajectories and all-cause mortality. RESULTS Among 3676 older adults (female: 52.3%, median (IQR) age was 77 (70, 85) years), after 12,516 person-years of follow-up, 1,331 all-cause deaths were recorded. Three distinct BMI trajectories were identified: low-normal stable trajectory (47.33%), normal slight increase trajectory (44.45%), and overweight to obesity trajectory (8.22%). In the fully adjusted model, compared to the normal slight increase trajectory, the risk of all-cause mortality was significantly increased in the low-normal stable trajectory (HR = 1.39, 95%CI: 1.22, 1.60), while the risk of mortality was not statistically different in the overweight to obesity trajectory (HR = 1.16, 95%CI: 0.83, 1.61). Both stratified and sensitivity analyses confirmed these findings. Mediation analysis suggested that cognitive impairment and lack of leisure activities might partially mediate this association. Threshold analysis indicated that the risk of mortality gradually decreases with increasing BMI when BMI is below 26 kg/m2 (HR = 0.95, 95%CI: 0.93, 0.97) and then remains stable after 26 kg/m2. CONCLUSION AND RELEVANCE Compared with normal slight increase trajectory, low-normal stable BMI trajectory during old age may increase the risk of all-cause mortality. These insights hold significant implications for future health management strategies and interventions, aiming to enhance the overall health status and quality of life among older adults.
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Affiliation(s)
- Xiaodan Kuang
- Department of Epidemiology and Health Statistics, School of Public Health, Wenzhou Medical University, University Town, Chashan, Wenzhou, 325035, Zhejiang, China
| | - Liuhong Tian
- Department of Epidemiology and Health Statistics, School of Public Health, Wenzhou Medical University, University Town, Chashan, Wenzhou, 325035, Zhejiang, China
| | - Shulei Chen
- Department of Epidemiology and Health Statistics, School of Public Health, Wenzhou Medical University, University Town, Chashan, Wenzhou, 325035, Zhejiang, China
| | - Jiaming Fang
- Department of Epidemiology and Health Statistics, School of Public Health, Wenzhou Medical University, University Town, Chashan, Wenzhou, 325035, Zhejiang, China
| | - Pan Ding
- School of Mental Health, Wenzhou Medical University, Wenzhou, China
| | - Jinghai Li
- Department of Epidemiology and Health Statistics, School of Public Health, Wenzhou Medical University, University Town, Chashan, Wenzhou, 325035, Zhejiang, China
| | - Lingfang Wang
- Department of Epidemiology and Health Statistics, School of Public Health, Wenzhou Medical University, University Town, Chashan, Wenzhou, 325035, Zhejiang, China
| | - Hongying Shi
- Department of Epidemiology and Health Statistics, School of Public Health, Wenzhou Medical University, University Town, Chashan, Wenzhou, 325035, Zhejiang, China.
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Kan Y, Liu L, Li X, Pang J, Bi Y, Zhang L, Zhang N, Yuan Y, Gong W, Zhang Y. Association between distinct body mass index trajectories according to the group-based trajectory modeling and the risk of incident diabetes: A systematic review. Obes Rev 2022; 23:e13508. [PMID: 36269000 DOI: 10.1111/obr.13508] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 08/16/2022] [Accepted: 09/27/2022] [Indexed: 11/29/2022]
Abstract
We aimed to determine the association between distinct body mass index (BMI) trajectories, using group-based trajectory modeling, and the subsequent risk of incident diabetes. Five databases were systematically searched. Fourteen population-based cohort studies that summarized the association between different BMI trajectories and subsequent diabetes, with the four most common BMI trajectories including the "stable," "increasing," "decreasing," and "turning" groups, were included. The rapid increase and stable high-level BMI groups showed the strongest association with the subsequent risk of diabetes compared with the stable normal BMI group. Increased baseline BMI levels resulted in a steeper slope and greater risk of subsequent diabetes. In the decreasing BMI group, one study reported that those aged >50 years showed the highest incidence of subsequent diabetes, whereas the other two studies reported no association between these two variables. In the turning group, an increase followed by a decrease in BMI levels from adolescence to late adulthood could reduce the risk of developing diabetes, although the residual risk remained. By contrast, the incidence of subsequent diabetes remained high in the middle-aged BMI-turning group. This study can provide further insights for identifying populations at high risk of diabetes and for developing targeted prevention strategies.
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Affiliation(s)
- Yinshi Kan
- School of Nursing, Yangzhou University, Yangzhou, China
| | - Lin Liu
- School of Nursing, Yangzhou University, Yangzhou, China
| | - Xiangning Li
- School of Nursing, Yangzhou University, Yangzhou, China
| | - Juan Pang
- School of Nursing, Yangzhou University, Yangzhou, China
| | - Yaxin Bi
- School of Nursing, Yangzhou University, Yangzhou, China
| | - Lu Zhang
- School of Nursing, Yangzhou University, Yangzhou, China
| | - Ning Zhang
- School of Nursing, Yangzhou University, Yangzhou, China
| | - Yuan Yuan
- Affiliated Hospital of Yangzhou University, Yangzhou, China
| | - Weijuan Gong
- Department of Basic Medicine, School of Medicine, Yangzhou University, Yangzhou, China
| | - Yu Zhang
- School of Nursing, Yangzhou University, Yangzhou, China.,Jiangsu Key Laboratory of Integrated Traditional Chinese and Western Medicine for Prevention and Treatment of Senile Diseases, Yangzhou, China
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Catov JM, Sun B, Lewis CE, Bertolet M, Gunderson EP. Prepregnancy weight change associated with high gestational weight gain. Obesity (Silver Spring) 2022; 30:524-534. [PMID: 35080338 PMCID: PMC9996907 DOI: 10.1002/oby.23354] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Revised: 10/19/2021] [Accepted: 11/05/2021] [Indexed: 01/03/2023]
Abstract
OBJECTIVE Gestational weight gain (GWG) above recommendations is a risk factor for adverse maternal, perinatal, and long-term outcomes. This study hypothesized that prepregnancy weight gain may portend excess GWG. METHODS Among 1,126 women (51% of whom were of Black race) in the Coronary Artery Risk Development in Young Adults (CARDIA) study with post-baseline births, the prepregnancy annual rate of BMI change per woman was estimated (slope; 5 years before pregnancy) and was related to the risk of GWG above Institute of Medicine recommendations using mixed-effects models (binary) and GWG z score (continuous), adjusting for confounders, and stratified by prepregnancy overweight/obesity status. RESULTS A total of 626 women (56%) had excess GWG. Each standard deviation increase in prepregnancy BMI (0.16 kg/m2 per year) was associated with an 18% increased risk of excess GWG (95% CI: 1.13-1.23), adjusted for covariates. Stratified results showed an association for women without overweight or obesity (adjusted relative risk = 1.71 [95% CI: 1.38-2.13]) but not among those with overweight or obesity (adjusted relative risk = 0.98 [95% CI: 0.91-1.05]). When evaluated as a z score, prepregnancy weight gain was associated with higher GWG among women with and without overweight or obesity (mean = 0.24 [0.10] and 0.28 [0.12] z score, respectively). CONCLUSIONS Weight gain before pregnancy is associated with higher GWG during pregnancy. Assessment of prepregnancy weight changes may identify those at risk for high GWG.
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Affiliation(s)
- Janet M Catov
- Department of Obstetrics, Gynecology and Reproductive Sciences, School of Medicine, Magee-Women's Research Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Baiyang Sun
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Cora E Lewis
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Marnie Bertolet
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Erica P Gunderson
- Division of Research, Kaiser Permanente Northern California, Oakland, California, USA
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Cheng YJ, Chen ZG, Wu SH, Mei WY, Yao FJ, Zhang M, Luo DL. Body mass index trajectories during mid to late life and risks of mortality and cardiovascular outcomes: Results from four prospective cohorts. EClinicalMedicine 2021; 33:100790. [PMID: 33778436 PMCID: PMC7985466 DOI: 10.1016/j.eclinm.2021.100790] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 02/19/2021] [Accepted: 02/22/2021] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND Our understanding of the weight-outcome association mainly comes from single-time body mass index (BMI) measurement. However, data on long-term trajectories of within-person changes in BMI on diverse study outcomes are sparse. Therefore, this study is to determine the associations of individual BMI trajectories and cardiovascular outcomes. METHODS The present analysis was based on data from 4 large prospective cohorts and restricted to participants aged ≥45 years with at least two BMI measurements. Hazard ratios (HR) and 95% confidence intervals(95%CI) for each outcome according to different BMI trajectories were calculated in Cox regression models. FINDINGS The final sample comprised 29,311 individuals (mean age 58.31 years, and 77.31% were white), with a median 4 BMI measurements used in this study. During a median follow-up of 21.16 years, there were a total of 10,192 major adverse cardiovascular events (MACE) and 11,589 deaths. A U-shaped relation was seen with all study outcomes. Compared with maintaining stable weight, the multivariate adjusted HR for MACE were 1.53 (95%CI 1.40-1.66), 1.26 (95%CI 1.16-1.37) and 1.08 (95%CI 1.02-1.15) respectively for rapid, moderate and slow weight loss; 1.01 (95%CI 0.95-1.07), 1.13 (95%CI 1.05-1.21) and 1.29 (95%CI 1.20-1.40) respectively for slow, moderate and rapid weight gain. Identical patterns of association were observed for all other outcomes. The development of BMI differed markedly between the outcome-free individuals and those who went on to experience adverse events, generally beginning to diverge 10 years before the occurrence of the events. INTERPRETATION Our findings may signal an underlying high-risk population and inspire future studies on weight management. FUNDING National Natural Science Foundation of China, Guangdong Natural Science Foundation.
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Affiliation(s)
- Yun-Jiu Cheng
- From the Department of Cardiology, the First Affiliated Hospital, Sun Yat-Sen University, Guangzhou 510700, China
- From Key Laboratory on Assisted Circulation, Ministry of Health, Guangzhou, China
- Corresponding authors.
| | - Zhen-Guang Chen
- From the Department of Thoracic Surgery, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Su-Hua Wu
- From the Department of Cardiology, the First Affiliated Hospital, Sun Yat-Sen University, Guangzhou 510700, China
- From Key Laboratory on Assisted Circulation, Ministry of Health, Guangzhou, China
| | - Wei-Yi Mei
- From the Department of Cardiology, the First Affiliated Hospital, Sun Yat-Sen University, Guangzhou 510700, China
- From Key Laboratory on Assisted Circulation, Ministry of Health, Guangzhou, China
| | - Feng-Juan Yao
- From the Department of Medical Ultrasonics, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Ming Zhang
- From the Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Dong-Ling Luo
- From the Department of Cardiology, the Eighth Affiliated Hospital, Sun Yat-Sen University, Shenzhen 518033, China
- Corresponding authors.
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Long-term trends in the body mass index and obesity risk in Estonia: an age-period-cohort approach. Int J Public Health 2020; 65:859-869. [PMID: 32725394 DOI: 10.1007/s00038-020-01447-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2020] [Revised: 07/15/2020] [Accepted: 07/21/2020] [Indexed: 01/02/2023] Open
Abstract
OBJECTIVES To analyse the age, period and cohort effects on the mean body mass index (BMI) and obesity over the past two decades in Estonia. METHODS Study used data from nationally representative repeated cross-sectional surveys on 11,547 men and 16,298 women from 1996 to 2018. The independent effects of age, period and cohort on predicted mean BMI and probability of obesity (BMI ≥ 30 kg/m2) were modelled using hierarchical age-period-cohort analysis. RESULTS Curvilinear association between age and mean BMI was found for men, whereas the increase in mean BMI was almost linear for women. The predicted mean BMI for 40-year-old men had increased by 6% and probability of obesity by 1.8 times over 1996-2018; the period effects were slightly smaller for women. Men from the 1970s birth cohort had higher mean BMI compared to the average, whereas no significant cohort effects were found for obesity outcome. CONCLUSIONS Population-level BMI changes in Estonia during 1996-2018 were mostly driven by period rather than cohort-specific changes.
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Dai H, Li F, Bragazzi NL, Wang J, Chen Z, Yuan H, Lu Y. Distinct developmental trajectories of body mass index and diabetes risk: A 5-year longitudinal study of Chinese adults. J Diabetes Investig 2020; 11:466-474. [PMID: 31454166 PMCID: PMC7078171 DOI: 10.1111/jdi.13133] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/11/2019] [Revised: 08/08/2019] [Accepted: 08/25/2019] [Indexed: 12/24/2022] Open
Abstract
AIMS/INTRODUCTION This longitudinal study aimed to explore whether distinct developmental trajectories of body mass index (BMI) would be predictive of diabetes risk in general Chinese adults. MATERIALS AND METHODS A total of 4,519 participants aged >18 years who were free of diabetes in 2011 (baseline of the current analysis) were enrolled in this study. All participants completed a medical examination every year during 2011-2016, and BMI levels were measured two to six (average 5.6) times. Group-based trajectory modeling was applied to identify BMI trajectories over time. New-onset diabetes was confirmed in 2016. RESULTS During 2011-2016, four distinct BMI trajectories were identified according to BMI range and changing pattern over time: "low" (19.6%), "moderate" (33.4%), "moderate-high" (33.4%) and "high" (13.6%). A total of 168 (3.7%) new-onset diabetes cases were confirmed in 2016. Compared with the "low" BMI trajectory, participants in the "high" BMI trajectory were at significantly higher risk for new-onset diabetes (adjusted relative risk 3.24, 95% confidence interval 1.27-8.24). Notably, BMI trajectories based on the first four or three annual BMI tests yielded similar results. By contrast, no significant correlation was found between categories of baseline BMI and new-onset diabetes in 2016 after multivariate adjustment. CONCLUSIONS The present results show that distinct BMI trajectories, even identified using just four or three annual BMI tests, are significantly associated with new-onset diabetes. Monitoring BMI trajectories over time might provide an important approach to identify subpopulations at higher risk for developing diabetes.
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Affiliation(s)
- Haijiang Dai
- Center of Clinical PharmacologyThe Third Xiangya HospitalCentral South UniversityChangshaHunanChina
- Center for Disease ModelingDepartment of Mathematics and StatisticsYork UniversityTorontoOntarioCanada
| | - Fei Li
- Center of Clinical PharmacologyThe Third Xiangya HospitalCentral South UniversityChangshaHunanChina
| | - Nicola Luigi Bragazzi
- Center for Disease ModelingDepartment of Mathematics and StatisticsYork UniversityTorontoOntarioCanada
| | - Jiangang Wang
- Department of Health ManagementThe Third Xiangya HospitalCentral South UniversityChangshaHunanChina
| | - Zhiheng Chen
- Department of Health ManagementThe Third Xiangya HospitalCentral South UniversityChangshaHunanChina
| | - Hong Yuan
- Center of Clinical PharmacologyThe Third Xiangya HospitalCentral South UniversityChangshaHunanChina
| | - Yao Lu
- Center of Clinical PharmacologyThe Third Xiangya HospitalCentral South UniversityChangshaHunanChina
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