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Chen Y, Koirala B, Ji M, Commodore-Mensah Y, Dennison Himmelfarb CR, Perrin N, Wu Y. Obesity paradox of cardiovascular mortality in older adults in the United States: A cohort study using 1997-2018 National Health Interview Survey data linked with the National Death Index. Int J Nurs Stud 2024; 155:104766. [PMID: 38703694 DOI: 10.1016/j.ijnurstu.2024.104766] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2023] [Revised: 03/25/2024] [Accepted: 03/26/2024] [Indexed: 05/06/2024]
Abstract
BACKGROUND Large-scale, population-based investigations primarily investigating the association between body mass index (BMI) and cardiovascular disease (CVD) mortality among older and younger adults in the United States (U.S.) are lacking. OBJECTIVE To evaluate the relationship between BMI and CVD mortality in older (≥65 years) and younger (<65 years) adults and to identify the nadir for CVD mortality. DESIGN This cohort study used serial cross-sectional data from the 1997 to 2018 National Health Interview Survey (NHIS) linked with the National Death Index. NHIS is an annual nationally representative household interview survey of the civilian noninstitutionalized U.S. POPULATION SETTING Residential units of the civilian noninstitutionalized population in the U.S. PARTICIPANTS The target population for the NHIS is the civilian noninstitutionalized U.S. population at the time of the interview. We included all adults who had BMI data collected at 18 years and older and with mortality data being available. To minimize the risk of reverse causality, we excluded adults whose survival time was ≤2 years of follow-up after their initial BMI was recorded and those with prevalent cancer and/or CVD at baseline. METHODS We used the BMI record obtained in the year of the NHIS survey. Total CVD mortality used the NHIS data linked to the latest National Death Index data from the survey inception to December 31, 2019. We performed multivariable Cox proportional hazards regression models to estimate adjusted hazard ratios (aHRs) and 95 % confidence intervals (CIs). RESULTS The study included 425,394 adults; the mean (SD) age was 44 (16.7) years. During a median follow-up period of 11 years, 12,089 CVD-related deaths occurred. In older adults, having overweight was associated with a lower risk of CVD mortality (aHR 0.92 [95 % CI, 0.87-0.97]); having class I obesity (1.04 [0.97-1.12]) and class II obesity (1.12 [1.00-1.26]) was not significantly associated with an increased CVD mortality; and having class III obesity was associated with an increased risk of CVD mortality (1.63 [1.35-1.98]), in comparison with adults who had a normal BMI. Yet, in younger adults, having overweight, class I, II, and III obesity was associated with a progressively higher risk of CVD mortality. The nadir for CVD mortality is 28.2 kg/m2 in older adults and 23.6 kg/m2 in younger adults. CONCLUSION This U.S. population-based cohort study highlights the significance of considering age as a crucial factor when providing recommendations and delivering self-care educational initiatives for weight loss to reduce CVD mortality.
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Affiliation(s)
- Yuling Chen
- School of Nursing, Johns Hopkins University, Baltimore, MD, USA; School of Nursing, Capital Medical University, Beijing, China.
| | - Binu Koirala
- School of Nursing, Johns Hopkins University, Baltimore, MD, USA
| | - Meihua Ji
- School of Nursing, Capital Medical University, Beijing, China
| | - Yvonne Commodore-Mensah
- School of Nursing, Johns Hopkins University, Baltimore, MD, USA; Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Cheryl R Dennison Himmelfarb
- School of Nursing, Johns Hopkins University, Baltimore, MD, USA; Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA; School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Nancy Perrin
- School of Nursing, Johns Hopkins University, Baltimore, MD, USA
| | - Ying Wu
- School of Nursing, Capital Medical University, Beijing, China.
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Lv Y, Zhang Y, Li X, Gao X, Ren Y, Deng L, Xu L, Zhou J, Wu B, Wei Y, Cui X, Xu Z, Guo Y, Qiu Y, Ye L, Chen C, Wang J, Li C, Luo Y, Yin Z, Mao C, Yu Q, Lu H, Kraus VB, Zeng Y, Tong S, Shi X. Body mass index, waist circumference, and mortality in subjects older than 80 years: a Mendelian randomization study. Eur Heart J 2024:ehae206. [PMID: 38626306 DOI: 10.1093/eurheartj/ehae206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/07/2023] [Revised: 02/17/2024] [Accepted: 03/19/2024] [Indexed: 04/18/2024] Open
Abstract
BACKGROUND AND AIMS Emerging evidence has raised an obesity paradox in observational studies of body mass index (BMI) and health among the oldest-old (aged ≥80 years), as an inverse relationship of BMI with mortality was reported. This study was to investigate the causal associations of BMI, waist circumference (WC), or both with mortality in the oldest-old people in China. METHODS A total of 5306 community-based oldest-old (mean age 90.6 years) were enrolled in the Chinese Longitudinal Healthy Longevity Survey (CLHLS) between 1998 and 2018. Genetic risk scores were constructed from 58 single-nucleotide polymorphisms (SNPs) associated with BMI and 49 SNPs associated with WC to subsequently derive causal estimates for Mendelian randomization (MR) models. One-sample linear MR along with non-linear MR analyses were performed to explore the associations of genetically predicted BMI, WC, and their joint effect with all-cause mortality, cardiovascular disease (CVD) mortality, and non-CVD mortality. RESULTS During 24 337 person-years of follow-up, 3766 deaths were documented. In observational analyses, higher BMI and WC were both associated with decreased mortality risk [hazard ratio (HR) 0.963, 95% confidence interval (CI) 0.955-0.971 for a 1-kg/m2 increment of BMI and HR 0.971 (95% CI 0.950-0.993) for each 5 cm increase of WC]. Linear MR models indicated that each 1 kg/m2 increase in genetically predicted BMI was monotonically associated with a 4.5% decrease in all-cause mortality risk [HR 0.955 (95% CI 0.928-0.983)]. Non-linear curves showed the lowest mortality risk at the BMI of around 28.0 kg/m2, suggesting that optimal BMI for the oldest-old may be around overweight or mild obesity. Positive monotonic causal associations were observed between WC and all-cause mortality [HR 1.108 (95% CI 1.036-1.185) per 5 cm increase], CVD mortality [HR 1.193 (95% CI 1.064-1.337)], and non-CVD mortality [HR 1.110 (95% CI 1.016-1.212)]. The joint effect analyses indicated that the lowest risk was observed among those with higher BMI and lower WC. CONCLUSIONS Among the oldest-old, opposite causal associations of BMI and WC with mortality were observed, and a body figure with higher BMI and lower WC could substantially decrease the mortality risk. Guidelines for the weight management should be cautiously designed and implemented among the oldest-old people, considering distinct roles of BMI and WC.
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Affiliation(s)
- Yuebin Lv
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, #7 Panjiayuan Nanli, Chaoyang, Beijing 100021, China
| | - Yue Zhang
- Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China
| | - Xinwei Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, #7 Panjiayuan Nanli, Chaoyang, Beijing 100021, China
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China
| | - Xiang Gao
- Department of Nutrition and Food Hygiene, School of Public Health, Institute of Nutrition, Fudan University, Shanghai, China
| | - Yongyong Ren
- Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China
| | - Luojia Deng
- Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China
| | - Lanjing Xu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, #7 Panjiayuan Nanli, Chaoyang, Beijing 100021, China
- Department of Big Data in Health Science, School of Public Health, Zhejiang University, Hangzhou, China
| | - Jinhui Zhou
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, #7 Panjiayuan Nanli, Chaoyang, Beijing 100021, China
| | - Bing Wu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, #7 Panjiayuan Nanli, Chaoyang, Beijing 100021, China
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Yuan Wei
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, #7 Panjiayuan Nanli, Chaoyang, Beijing 100021, China
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China
| | - Xingyao Cui
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, #7 Panjiayuan Nanli, Chaoyang, Beijing 100021, China
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China
| | - Zinan Xu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, #7 Panjiayuan Nanli, Chaoyang, Beijing 100021, China
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, China
| | - Yanbo Guo
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, #7 Panjiayuan Nanli, Chaoyang, Beijing 100021, China
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China
| | - Yidan Qiu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, #7 Panjiayuan Nanli, Chaoyang, Beijing 100021, China
- Department of Big Data in Health Science, School of Public Health, Zhejiang University, Hangzhou, China
| | - Lihong Ye
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, #7 Panjiayuan Nanli, Chaoyang, Beijing 100021, China
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Chen Chen
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, #7 Panjiayuan Nanli, Chaoyang, Beijing 100021, China
| | - Jun Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, #7 Panjiayuan Nanli, Chaoyang, Beijing 100021, China
| | - Chenfeng Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, #7 Panjiayuan Nanli, Chaoyang, Beijing 100021, China
- Department of Occupational Health and Environment Health, School of Public Health, Anhui Medical University, Hefei, China
| | - Yufei Luo
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, #7 Panjiayuan Nanli, Chaoyang, Beijing 100021, China
- Department of Occupational Health and Environment Health, School of Public Health, Anhui Medical University, Hefei, China
| | - Zhaoxue Yin
- Division of Non-Communicable Disease and Healthy Aging Management, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Chen Mao
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, China
| | - Qiong Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China
| | - Hui Lu
- Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China
| | - Virginia Byers Kraus
- Department of Medicine, Duke Molecular Physiology Institute and Division of Rheumatology, Duke University School of Medicine, Durham, NC, USA
| | - Yi Zeng
- Center for Study of Healthy Aging and Development Studies, Peking University, Beijing, China
| | - Shilu Tong
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, #7 Panjiayuan Nanli, Chaoyang, Beijing 100021, China
- School of Public Health and Social Work, Queensland University of Technology, Brisbane, Australia
| | - Xiaoming Shi
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, #7 Panjiayuan Nanli, Chaoyang, Beijing 100021, China
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Guo J, Dove A, Shang Y, Marseglia A, Johnell K, Rizzuto D, Xu W. Associations Between Mid- to Late-Life Body Mass Index and Chronic Disease-Free Survival: A Nationwide Twin Study. J Gerontol A Biol Sci Med Sci 2024; 79:glad111. [PMID: 37096341 PMCID: PMC10733179 DOI: 10.1093/gerona/glad111] [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: 09/29/2022] [Indexed: 04/26/2023] Open
Abstract
BACKGROUND Some studies have linked late-life overweight to a reduced mortality risk compared to normal body mass index (BMI). However, the impact of late-life overweight and its combination with mid-life BMI status on healthy survival remains unclear. We aimed to investigate whether and to what extent mid- and/or late-life overweight are associated with chronic disease-free survival. METHODS Within the Swedish Twin Registry, 11 597 chronic disease-free twins aged 60-79 years at baseline were followed up for 18 years. BMI (kg/m2) was recorded at baseline and 25-35 years before baseline (ie, midlife) and divided as underweight (<20), normal (≥20-25), overweight (≥25-30), and obese (≥30). Incident chronic diseases (cardiovascular diseases, type 2 diabetes, and cancer) and deaths were ascertained via registries. Chronic disease-free survival was defined as years lived until the occurrence of any chronic diseases or death. Data were analyzed using multistate survival analysis. RESULTS Of all participants, 5 640 (48.6%) were overweight/obese at baseline. During the follow-up, 8 772 (75.6%) participants developed at least 1 chronic disease or died. Compared to normal BMI, late-life overweight and obesity were associated with 1.1 (95% CI, 0.3, 2.0) and 2.6 (1.6, 3.5) years shorter chronic disease-free survival. Compared to normal BMI through mid- to late life, consistent overweight/obesity and overweight/obesity only in mid-life led to 2.2 (1.0, 3.4) and 2.6 (0.7, 4.4) years shorter disease-free survival, respectively. CONCLUSIONS Late-life overweight and obesity may shorten disease-free survival. Further research is needed to determine whether preventing overweight/obesity from mid- to late life might favor longer and healthier survival.
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Affiliation(s)
- Jie Guo
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - Abigail Dove
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - Ying Shang
- Department of Medicine, Huddinge, Karolinska Institutet, Stockholm, Sweden
| | - Anna Marseglia
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Kristina Johnell
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Debora Rizzuto
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
- Stockholm Gerontology Research Center, Stockholm, Sweden
| | - Weili Xu
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
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Huang Y, Peng J, Wang W, Zheng X, Qin G, Xu H. Age-Dependent Association Between Body Mass Index and All-Cause Mortality Among Patients with Hypertension: A Longitudinal Population-Based Cohort Study in China. Clin Epidemiol 2023; 15:1159-1170. [PMID: 38089006 PMCID: PMC10712248 DOI: 10.2147/clep.s442162] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Accepted: 11/28/2023] [Indexed: 01/18/2024] Open
Abstract
PURPOSE The association between body mass index (BMI) and all-cause mortality may vary among hypertensive patients of different ages. This study aimed to investigate the age-dependent association between BMI and all-cause mortality among patients with hypertension. PATIENTS AND METHODS A total of 212,394 participants with hypertension aged 20-85 years from Minhang Hypertension Standardization Management System in Shanghai of China were included. Follow-up began at the time when individuals were first recorded and ended at death, loss to follow-up, or December 31, 2018, whichever came first. Additive Cox proportional hazards models with thin plate smoothing functions and conventional Cox proportional hazards models were adopted to examine the relationship between BMI, age, and mortality. The joint effect of BMI and age on mortality was assessed using a bivariate response model. RESULTS We found that the BMI-mortality relationship followed a U-shaped pattern, with a trough at 26-27 kg/m2. Compared with normal weight, underweight was associated with a 50% increased risk of premature mortality (hazard ratio 1.50, 95% confidence interval 1.43 to 1.57). Whereas among those aged 45-59 and 60-85 years, overweight was associated with 13% (0.87, 0.80 to 0.94) and 18% (0.82, 0.80 to 0.84) reduction in risk of death, respectively. Bivariate response model indicated a significant interaction between BMI and age (P < 0.05). Among younger and older patients, we found a descending trend for mortality risk, with BMI increasing at different age levels, whereas a reverse J-shaped relation pattern was observed among middle-aged patients. CONCLUSION The impact of BMI on all-cause mortality in hypertensive patients varies with age, and moderate weight gain may benefit longevity in middle-aged and older patients.
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Affiliation(s)
- Yifang Huang
- Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, People’s Republic of China
- Department of Biostatistics, National Health Commission Key Laboratory of Health Technology Assessment, Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, People’s Republic of China
| | - Jiahuan Peng
- Department of Biostatistics, National Health Commission Key Laboratory of Health Technology Assessment, Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, People’s Republic of China
| | - Weibing Wang
- Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, People’s Republic of China
| | - Xueying Zheng
- Department of Biostatistics, National Health Commission Key Laboratory of Health Technology Assessment, Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, People’s Republic of China
| | - Guoyou Qin
- Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, People’s Republic of China
- Department of Biostatistics, National Health Commission Key Laboratory of Health Technology Assessment, Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, People’s Republic of China
| | - Huilin Xu
- Shanghai Minhang Center for Disease Control and Prevention, Shanghai, People’s Republic of China
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Visaria A, Setoguchi S. Body mass index and all-cause mortality in a 21st century U.S. population: A National Health Interview Survey analysis. PLoS One 2023; 18:e0287218. [PMID: 37405977 DOI: 10.1371/journal.pone.0287218] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 06/01/2023] [Indexed: 07/07/2023] Open
Abstract
INTRODUCTION Much of the data on BMI-mortality associations stem from 20th century U.S. cohorts. The purpose of this study was to determine the association between BMI and mortality in a contemporary, nationally representative, 21st century, U.S. adult population. METHODS This was a retrospective cohort study of U.S. adults from the 1999-2018 National Health Interview Study (NHIS), linked to the National Death Index (NDI) through December 31st, 2019. BMI was calculated using self-reported height & weight and categorized into 9 groups. We estimated risk of all-cause mortality using multivariable Cox proportional hazards regression, adjusting for covariates, accounting for the survey design, and performing subgroup analyses to reduce analytic bias. RESULTS The study sample included 554,332 adults (mean age 46 years [SD 15], 50% female, 69% non-Hispanic White). Over a median follow-up of 9 years (IQR 5-14) and maximum follow-up of 20 years, there were 75,807 deaths. The risk of all-cause mortality was similar across a wide range of BMI categories: compared to BMI of 22.5-24.9 kg/m2, the adjusted HR was 0.95 [95% CI 0.92, 0.98] for BMI of 25.0-27.4 and 0.93 [0.90, 0.96] for BMI of 27.5-29.9. These results persisted after restriction to healthy never-smokers and exclusion of subjects who died within the first two years of follow-up. A 21-108% increased mortality risk was seen for BMI ≥30. Older adults showed no significant increase in mortality between BMI of 22.5 and 34.9, while in younger adults this lack of increase was limited to the BMI range of 22.5 to 27.4. CONCLUSION The risk of all-cause mortality was elevated by 21-108% among participants with BMI ≥30. BMI may not necessarily increase mortality independently of other risk factors in adults, especially older adults, with overweight BMI. Further studies incorporating weight history, body composition, and morbidity outcomes are needed to fully characterize BMI-mortality associations.
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Affiliation(s)
- Aayush Visaria
- Rutgers Institute for Health, Center for Pharmacoepidemiology and Treatment Sciences, New Brunswick, NJ, United States of America
| | - Soko Setoguchi
- Rutgers Institute for Health, Center for Pharmacoepidemiology and Treatment Sciences, New Brunswick, NJ, United States of America
- Department of Medicine, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ, United States of America
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Crane B, Nichols E, Carlson M, Deal J, Gross A. Body Mass Index and Cognition: Associations Across
Mid- to Late Life and Gender Differences. J Gerontol A Biol Sci Med Sci 2023; 78:988-996. [PMID: 36638277 PMCID: PMC10235201 DOI: 10.1093/gerona/glad015] [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: 08/30/2022] [Indexed: 01/15/2023] Open
Abstract
BACKGROUND Higher mid-life body mass index (BMI) is associated with lower late-life cognition. Associations between later-life BMI and cognition are less consistent; evidence suggests reverse causation may play a role. We aimed to characterize associations between BMI and cognition across a wide age range during mid- to late life (55-85 years) and examine whether associations vary by gender. METHODS We used data from the Health and Retirement Study (HRS) (N = 39,153) to examine the association between BMI and 3 cognitive outcomes: cognitive level, cognitive decline, and cognitive impairment. We used a series of linear regression, mixed effects regression, and logistic regression models, adjusting for potential confounders. RESULTS Higher BMI before age 65 (midlife) was associated with lower cognitive performance, faster rates of cognitive decline, and higher odds of cognitive impairment in late life. Averaging across analyses assessing associations between BMI measured before age 60 and late-life cognition, a 5-unit higher level of BMI was associated with a 0.26 point lower cognitive score. Beyond age 65, associations flipped, and higher BMI was associated with better late-life cognitive outcomes. Associations in both directions were stronger in women. Excluding those with BMI loss attenuated findings among women in older ages, supporting the reverse causation hypothesis. CONCLUSIONS In this sample, age 65 represented a critical turning point between mid- and late life for the association between BMI and cognition, which has important implications for recruitment strategies for studies focused on risk factors for late-life cognitive outcomes. Evidence of gender differences raises the need to further investigate plausible mechanisms.
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Affiliation(s)
- Breanna M Crane
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Emma Nichols
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Michelle C Carlson
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Jennifer A Deal
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Alden L Gross
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
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Rantanen AT, Kautiainen H, Korhonen PE. Depressive symptoms and mortality - effect variation by body mass index: a prospective study in a primary care population. Int J Obes (Lond) 2023; 47:512-519. [PMID: 36977790 DOI: 10.1038/s41366-023-01296-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 03/06/2023] [Accepted: 03/14/2023] [Indexed: 03/30/2023]
Abstract
BACKGROUND/OBJECTIVE Pre-existing diseases have been found to affect the relationship between body mass index (BMI) and mortality. However, psychiatric disorders common in general population have not been previously addressed. The aim of this study was to assess the relationship of depressive symptoms and BMI with all-cause mortality. METHODS A prospective cohort study in Finnish primary care setting was conducted. A population survey identified 3072 middle-aged subjects who had elevated cardiovascular risk. Subjects who attended clinical examination and completed Beck's Depression Inventory (BDI) (n = 2509) were included in this analysis. Effect of depressive symptoms and BMI on all-cause mortality after 14 years follow-up was estimated in models adjusted for age, sex, education years, current smoking, alcohol use, physical activity, total cholesterol, systolic blood pressure, and glucose disorders. RESULTS When subjects with and without increased depressive symptoms were compared, the fully adjusted hazard ratios (HR) for all-cause mortality in the BMI categories (<25.0, 25.0-29.9, 30.0-34.9, ≥35.0 kg/m2) were 3.26 (95% CI 1.83 to 5.82), 1.31 (95% CI 0.83 to 2.06), 1.27 (95% CI 0.76 to 2.11), and 1.25 (95% CI 0.63 to 2.48), respectively. The lowest risk of death was among non-depressive subjects who had BMI < 25.0 kg/m2. CONCLUSIONS Effect of increased depressive symptoms on all-cause mortality risk seems to vary with BMI. Elevated mortality risk is especially apparent among depressive subjects with normal weight. Among individuals with overweight and obesity, increased depressive symptoms seem not to further increase all-cause mortality.
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Affiliation(s)
- Ansa Talvikki Rantanen
- Department of General Practice, University of Turku and Turku University Hospital, 20520, Turku, Finland.
| | - Hannu Kautiainen
- Folkhälsan Research Center, Helsinki, Finland
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
| | - Päivi Elina Korhonen
- Department of General Practice, University of Turku and Turku University Hospital, 20520, Turku, Finland
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Müller MJ, Bosy-Westphal A. On Appropriate Phenotypes of Patients With Obesity. J Clin Endocrinol Metab 2022; 107:e3526-e3527. [PMID: 35435966 DOI: 10.1210/clinem/dgac226] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Indexed: 11/19/2022]
Affiliation(s)
- Manfred J Müller
- Institute of Human Nutrition and Food Science, Christian-Albrechts University Kiel, Kiel, Germany
| | - Anja Bosy-Westphal
- Institute of Human Nutrition and Food Science, Christian-Albrechts University Kiel, Kiel, Germany
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Jadhav R, Markides KS, Al Snih S. Body mass index and 12-year mortality among older Mexican Americans aged 75 years and older. BMC Geriatr 2022; 22:236. [PMID: 35313825 PMCID: PMC8939224 DOI: 10.1186/s12877-022-02945-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Accepted: 03/15/2022] [Indexed: 11/15/2022] Open
Abstract
Background The role of obesity in mortality in the very old and old-oldest Hispanic population has not been studied. The objective of this study was to examine the effect of body mass index (BMI) on 12-year mortality among older Mexican Americans aged 75 years and older. Methods Twelve year prospective cohort study consisting of a population-based sample of 1415 non-institutionalized Mexican American men and women aged 75 and older from 5 southwestern states: Arizona, California, Colorado, New Mexico, and Texas. Data was from Wave 5 of the Hispanic Established Population for the Epidemiologic Study of the Elderly (2004/2005–2016). Socio-demographics, body mass index (BMI), self-reported medical conditions, disability, depressive symptoms, falls, Mini-Mental-State-Examination (MMSE), and Short Physical Performance Battery (SPPB) were assessed at baseline during 2004–2005. BMI (Kg/m2) was classified as underweight (< 18.5), normal weight (18.5 to < 25), overweight (25 to < 30), obesity category I (30 to < 35), and obesity category II/morbid obesity (≥ 35). For assessment of mortality, deaths were ascertained through the National Death Index and report from relatives. Cox proportional hazards regression analysis was performed to estimate the hazard ratio (HR) of 12-year mortality as a function of BMI categories at baseline. Results The mean BMI was 27.5 ± 1.7 with participants classified as 1.8% underweight, 30.8% normal weight, 39.2% overweight, 20.7% obesity category I, and 7.6% obesity category II/morbid obesity. Mexican Americans aged ≥75 years with overweight or obesity category I had a reduced HR of death (0.82, 95% CI = 0.70–0.96 and 0.75, 95% CI = 0.62–0.91, respectively) over 12-years of follow-up. The HR of death for underweight and obesity category II/morbid obesity participants was 1.59 (95% CI = 1.03–2.45) and 1.12 (95% CI = 0.85–1.46), respectively. Female participants and those with high scores in the MMSE and SPPB had decreased risk of death. Conclusions This study showed the protective effect of overweight and obesity on mortality in Mexican Americans above 75 years of age, which might have implications when treating older adults with overweight and obesity.
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Affiliation(s)
- Reshma Jadhav
- School of Medicine, University of Texas Medical Branch, Galveston, TX, USA
| | - Kyriakos S Markides
- Department of Preventive Medicine and Population Health, University of Texas Medical Branch, Galveston, TX, USA.,Sealy Center on Aging, University of Texas Medical Branch, 301 University Blvd., Galveston, TX, USA
| | - Soham Al Snih
- Sealy Center on Aging, University of Texas Medical Branch, 301 University Blvd., Galveston, TX, USA. .,Department of Nutrition, Metabolism, and Rehabilitation Sciences/School of Health Professions, University of Texas Medical Branch, Galveston, TX, USA. .,Division of Geriatrics & Palliative Medicine /Department of Internal Medicine/School of Medicine, University of Texas Medical Branch, Galveston, TX, USA.
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Effects of weight change on all causes, digestive system and other causes mortality in Southern Italy: a competing risk approach. Int J Obes (Lond) 2022; 46:113-120. [PMID: 34522001 DOI: 10.1038/s41366-021-00954-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 07/30/2021] [Accepted: 08/18/2021] [Indexed: 02/08/2023]
Abstract
Weight change is associated with all causes of death, cardiovascular, and cancer mortality and a heterogeneous group of other causes of death. We aimed to estimate the effect of weight change on all causes and cause-specific mortality in a cohort with a high prevalence of deaths due to diseases of the digestive system.MethodsIn this prospective cohort study, 2230 subjects aged 30 to 50 years were examined. The study consisted of a 32-year longitudinal study period (January 1985 to December 2017) and mortality follow-up. Outcomes were mortality from all causes and deaths from gastrointestinal disease. Root Mean Squared Error (RMSE) was evaluated to capture individual residual variation in Body Mass Index (BMI) after adjustment for baseline BMI, and the relationship of residual variation with mortality was calculated as cumulative incidence function and cause-specific hazard (CSH) rate.ResultsIn total, 793 participants died during the follow-up, 96 of them due to Digestive system causes. Magnitude of residual variation weight in the last quintile was associated with all-cause mortality (relative risk, 2.00; 95% CI, 1.54-2.59) and Digestive system causes (relative risk, 3.82; 95% CI, 1.86-7.81).ConclusionThe findings suggest an association between weight change and gastrointestinal disease mortality. Epidemiological works studying the correlation between weight change and mortality should consider this aspect.
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