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Sun Q, Xia X, He F. Longitudinal association between Body mass index (BMI), BMI trajectories and the risk of frailty among older adults: A systematic review and meta-analysis of prospective cohort studies. Arch Gerontol Geriatr 2024; 124:105467. [PMID: 38728821 DOI: 10.1016/j.archger.2024.105467] [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: 01/16/2024] [Revised: 04/15/2024] [Accepted: 04/30/2024] [Indexed: 05/12/2024]
Abstract
OBJECTIVE We aimed to determine whether BMI categories and BMI trajectories were longitudinally associated with frailty in older adults via systematic review and meta-analysis of prospective cohort studies. METHOD 3 databases (PubMed/MEDLINE, EMBASE and Web of Science) were systematically searched from inception to 8 September 2023. Two independent reviewers extracted data and appraised study quality. The quality of the studies was assessed using the Newcastle-Ottawa Scale. Data were pooled using random-effects models. RESULTS 7 prospective cohort studies with 23043 participants were included in final BMI categories analyses, and 3 studies included BMI trajectory(23725 individuals). Compared with normal weight, we found a positive association between obesity (odds ratios(OR) = 1.74, 95 % confidence interval (CI): 1.21-2.51, P = 0.003), underweight (OR = 1.70, 95 % CI: 1.13-2.57, P = 0.011) and frailty in older adults. In middle age subgroup, compared with normal weight, OR of 2.21 (95 % CI: 1.44-3.38;I2 = 0 %) for overweight and OR of 5.20 (95 % CI: 2.56-10.55; I2 = 0 %) for obesity were significantly associated with frailty. In old age subgroup, compared with normal weight, only OR of 1.41 (95 % CI: 1.13-1.77; I2 = 65 %) for obesity was significantly associated with frailty. The results of BMI trajectories found that decreasing BMI (OR = 3.25, 95 % CI: 2.20-4.79, P < 0.0001) and consistently high BMI (OR = 3.66, 95 % CI: 2.03-6.61, P < 0.0001) increase the risk of frailty compared to consistently normal or overweight. CONCLUSION Overweight and obesity in middle age were associated with significantly higher frailty in older adults, while obesity and underweight in old age were associated with relatively higher frailty in older adults. Early weight control may be beneficial for old age.
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Affiliation(s)
- Qianqian Sun
- The Center of Gerontology and Geriatrics and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
| | - Xin Xia
- The Center of Gerontology and Geriatrics and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
| | - Fuqian He
- The Center of Gerontology and Geriatrics and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China.
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Espeland MA, Harada ASM, Ross J, Bancks MP, Pajewski NM, Simpson FR, Walkup M, Davis I, Huckfeldt PJ. Cross-sectional and longitudinal associations among healthcare costs and deficit accumulation. J Am Geriatr Soc 2024. [PMID: 38946518 DOI: 10.1111/jgs.19053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 05/27/2024] [Accepted: 06/09/2024] [Indexed: 07/02/2024]
Abstract
BACKGROUND Type 2 diabetes mellitus and overweight/obesity increase healthcare costs. Both are also associated with accelerated aging. However, the contributions of this accelerated aging to increased healthcare costs are unknown. METHODS We use data from a 8-year longitudinal cohort followed at 16 U.S. clinical research sites. Participants were adults aged 45-76 years with established type 2 diabetes and overweight or obesity who had enrolled in the Action for Health in Diabetes clinical trial. They were randomly (1:1) assigned to either an intensive lifestyle intervention focused on weight loss versus a comparator of diabetes support and education. A validated deficit accumulation frailty index (FI) was used to characterize biological aging. Discounted annual healthcare costs were estimated using national databases in 2012 dollars. Descriptive characteristics were collected by trained and certified staff. RESULTS Compared with participants in the lowest tertile (least frail) of baseline FI, those in the highest tertile (most frail) at Year 1 averaged $714 (42%) higher medication costs, $244 (22%) higher outpatient costs, and $800 (134%) higher hospitalization costs (p < 0.001). At Years 4 and 8, relatively greater increases in FI (third vs. first tertile) were associated with an approximate doubling of total healthcare costs (p < 0.001). Mean (95% confidence interval) relative annual savings in healthcare costs associated with randomization to the intensive lifestyle intervention were $437 ($195, $579) per year during Years 1-4 and $461 ($232, $690) per year during Years 1-8. These were attenuated and the 95% confidence interval no longer excluded $0 after adjustment for the annual FI differences from baseline. CONCLUSIONS Deficit accumulation frailty tracks well with healthcare costs among adults with type 2 diabetes and overweight or obesity. It may serve as a useful marker to project healthcare needs and as an intermediate outcome in clinical trials.
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Affiliation(s)
- Mark A Espeland
- Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
- Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
| | - Ann S M Harada
- Leonard D. Schaeffer Center for Health Policy & Economics, University of Southern California, California, Los Angeles, USA
- Sol Price School of Public Policy, University of Southern California, California, Los Angeles, USA
| | - Johnathan Ross
- Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
- Department of Mathematics, Winston-Salem State University, Winston-Salem, North Carolina, USA
| | - Michael P Bancks
- Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
| | - Nicholas M Pajewski
- Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
| | - Felicia R Simpson
- Department of Mathematics, Winston-Salem State University, Winston-Salem, North Carolina, USA
| | - Michael Walkup
- Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
| | - Ian Davis
- School of Pharmacy, University of Southern California, California, Los Angeles, USA
| | - Peter J Huckfeldt
- Division of Health Policy and Management, University of Minnesota School of Public Health, Minneapolis, Minnesota, USA
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Jiang M, Ren X, Han L, Zheng X. Reply - Letter to the editor. Clin Nutr 2024; 43:1499-1500. [PMID: 38723304 DOI: 10.1016/j.clnu.2024.04.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2024] [Accepted: 04/17/2024] [Indexed: 05/31/2024]
Affiliation(s)
- Minglan Jiang
- Public Health Research Center and Department of Public Health and Preventive Medicine, Wuxi School of Medicine, Jiangnan University, Wuxi, Jiangsu, 214122, China
| | - Xiao Ren
- Public Health Research Center and Department of Public Health and Preventive Medicine, Wuxi School of Medicine, Jiangnan University, Wuxi, Jiangsu, 214122, China
| | - Longyang Han
- Public Health Research Center and Department of Public Health and Preventive Medicine, Wuxi School of Medicine, Jiangnan University, Wuxi, Jiangsu, 214122, China
| | - Xiaowei Zheng
- Public Health Research Center and Department of Public Health and Preventive Medicine, Wuxi School of Medicine, Jiangnan University, Wuxi, Jiangsu, 214122, China.
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Guo Y, Yang F. Spousal education and frailty levels among Chinese older adults: A national longitudinal study. SSM Popul Health 2024; 26:101607. [PMID: 38516527 PMCID: PMC10955636 DOI: 10.1016/j.ssmph.2024.101607] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 01/11/2024] [Indexed: 03/23/2024] Open
Abstract
Background Prior research has identified one's own education level as a risk factor for frailty. However, the association between spousal education and frailty in later life is uncertain. We aim to examine the longitudinal association between spousal education and frailty levels among Chinese older populations. Methods 3856 participants aged 60 and older from the 2011-2018 China Health and Retirement Longitudinal Study were analyzed. A 54-item deficit cumulative frailty index was developed to evaluate frailty levels at each follow-up. Linear mixed-effects models were used to examine the longitudinal association of spousal education with frailty levels, and whether this association varied by sex and own education level. Results Higher spouse education was associated with lower frailty levels, and this association decreased with age. Compared with older adults whose spouses had no formal education, older adults whose spouses had less than middle school education had an 8.82 lower level of frailty (95% CI: 15.05 to -2.58, P < 0.01); those with spouses with middle school education and above had a 23.44 lower level (95% CI: 31.43 to -15.44, P < 0.001). Stratified analysis showed that every additional year of spouse education was also associated with lower frailty levels in non-frail participants at baseline, but stronger among those already frail. The association between high spousal education and lower frailty did not vary by sex or own education. Conclusion This study reveals a significant association between having a more educated spouse and lower later-life frailty levels for both older men and women, regardless of one's own educational background. It emphasizes the importance of leveraging educated spouses to prevent and manage frailty.
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Affiliation(s)
- Yujia Guo
- School of Health Policy & Management, Nanjing Medical University, 101 Longmian Avenue, Jiangning District, Nanjing, 211166, Jiangsu Province, China
| | - Fan Yang
- School of Public Health, NHC Key Lab of Health Technology Assessment (Fudan University), Fudan University, 130 Dong-An Road, Shanghai, 200032, China
- NHC Key Lab of Health Technology Assessment (Fudan University), Fudan University, 130 Dong-An Road, Shanghai, 200032, China
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He D, Yan M, Zhou Y, Ge H, Zhang X, Xu Y, Liu C, Ying K, Zhu Y. Preserved Ratio Impaired Spirometry and COPD Accelerate Frailty Progression: Evidence From a Prospective Cohort Study. Chest 2024; 165:573-582. [PMID: 37499976 DOI: 10.1016/j.chest.2023.07.020] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Revised: 07/16/2023] [Accepted: 07/20/2023] [Indexed: 07/29/2023] Open
Abstract
BACKGROUND COPD has been found to be associated with frailty. However, longitudinal evidence for associations of COPD with frailty progression is inadequate. Furthermore, recent studies revealed a new phenotype of lung function impairment: preserved ratio impaired spirometry (PRISm) findings. Associations of PRISm findings and their transitions with frailty progression are unclear. RESEARCH QUESTION What are the associations of PRISm findings, transitions of PRISm findings, and COPD with frailty progression? STUDY DESIGN AND METHODS To analyze the associations of PRISm findings and COPD with frailty progression, 5,901 patients were included from the English Longitudinal Study of Ageing. Patients were classified into three lung function patterns of normal spirometry (NS) findings, PRISm findings, and COPD. Frailty progression was assessed by repeated measurements of the frailty index (FI) during follow-up. Among these 5,901 patients, 3,765 patients were included to analyze the associations of PRISm findings transitions with frailty progression. PRISm findings transitions were assessed based on the changes of lung function patterns after a 4-year interval. Linear mixed-effect models were used for statistical analyses. RESULTS The median follow-up periods were 9.5 years for the analyses of PRISm findings and COPD with frailty progression and 5.8 years for PRISm findings transitions with frailty progression. When compared with participants with NS findings, patients with PRISm findings and COPD demonstrated accelerated FI progression with additional annual increases of 0.301 (95% CI, 0.211-0.392; P < .001) and 0.172 (95% CI, 0.102-0.242; P < .001), respectively. Patients who transitioned from NS findings to PRISm findings also demonstrated accelerated FI progression when compared with those with stable NS findings (β = 0.242; 95% CI, 0.008-0.476; P = .042). However, no accelerated FI progression was found in patients with PRISm findings who transitioned to NS findings (β = 0.119; 95% CI, -0.181 to 0.418; P = .438). INTERPRETATION Our findings indicate that PRISm findings and COPD are associated with accelerated frailty progression. Further studies are needed to elucidate the causality of the association of PRISm findings and COPD with frailty.
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Affiliation(s)
- Di He
- Department of Epidemiology & Biostatistics, School of Public Health, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Zhejiang, China; Department of Respiratory Disease, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Zhejiang, China
| | - Mengsha Yan
- Department of Epidemiology & Biostatistics, School of Public Health, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Zhejiang, China; Department of Respiratory Disease, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Zhejiang, China
| | - Yong Zhou
- Department of Respiratory Disease, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Zhejiang, China
| | - Huiqing Ge
- Department of Respiratory Disease, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Zhejiang, China
| | - Xuhui Zhang
- Hangzhou Center for Disease Control and Prevention, Hangzhou, Zhejiang, China
| | - Yuying Xu
- Department of Epidemiology & Biostatistics, School of Public Health, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Zhejiang, China; Department of Respiratory Disease, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Zhejiang, China
| | - Chengguo Liu
- Putuo District People's Hospital, Zhoushan, Zhejiang, China
| | - Kejing Ying
- Department of Respiratory Disease, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Zhejiang, China
| | - Yimin Zhu
- Department of Epidemiology & Biostatistics, School of Public Health, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Zhejiang, China; Department of Respiratory Disease, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Zhejiang, China; Cancer Center, Zhejiang University, Hangzhou, Zhejiang, China.
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Owodunni OP, Courville EN, Peter-Okaka U, Ricks CB, Schmidt MH, Bowers CA. Multiplicative effect of frailty and obesity on postoperative mortality following spine surgery: a deep dive into the frailty, obesity, and Clavien-Dindo dynamic. Int J Obes (Lond) 2024; 48:360-369. [PMID: 38110501 DOI: 10.1038/s41366-023-01423-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 11/10/2023] [Accepted: 11/22/2023] [Indexed: 12/20/2023]
Abstract
BACKGROUND/OBJECTIVES Obesity is a global health challenge that affects a large proportion of adults worldwide. Obesity and frailty pose considerable health risks due to their potential to interact and amplify one another's negative effects. Therefore, we sought to compare the discriminatory thresholds of the risk analysis index (RAI), 5-factor modified frailty index (m-FI-5) and patient age for the primary endpoint of postoperative mortality. SUBJECTS/METHODS We included spine surgery patients ≥18 years old, from the American College of Surgeons National Quality Improvement program database from 2012-2020, that were classified as obese. We performed receiver operating characteristic curve analysis to compare the discrimination threshold of RAI, mFI-5, and patient age for postoperative mortality. Proportional hazards risk-adjusted regressions were performed, and Hazard ratios and corresponding 95% Confidence intervals (CI) are reported. RESULTS Overall, there were 149 163 patients evaluated, and in the ROC analysis for postoperative mortality, RAI showed superior discrimination C-statistic 0.793 (95%CI: 0.773-0.813), compared to mFI-5 C-statistic 0.671 (95%CI 0.650-0.691), and patient age C-statistic 0.686 (95%CI 0.666-0.707). Risk-adjusted analyses were performed, and the RAI had a stepwise increasing effect size across frailty strata: typical patients HR 2.55 (95%CI 2.03-3.19), frail patients HR 3.48 (95%CI 2.49-4.86), and very frail patients HR 4.90 (95%CI 2.87-8.37). We found increasing postoperative mortality effect sizes within Clavein-Dindo complication strata, consistent across obesity categories, exponentially increasing with frailty, and multiplicatively enhanced within CD, frailty and obesity strata. CONCLUSION In this study of 149 163 patients classified as obese and undergoing spine procedures in an international prospective surgical database, the RAI demonstrated superior discrimination compared to the mFI-5 and patient age in predicting postoperative mortality risk. The deleterious effects of frailty and obesity were synergistic as their combined effect predicted worse outcomes.
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Affiliation(s)
- Oluwafemi P Owodunni
- Department of Emergency Medicine, University of New Mexico Hospital, Albuquerque, NM, USA.
- Bowers Neurosurgical Frailty and Outcomes Data Science Lab, Albuquerque, NM, USA.
| | - Evan N Courville
- Bowers Neurosurgical Frailty and Outcomes Data Science Lab, Albuquerque, NM, USA
- Department of Neurosurgery, University of New Mexico Hospital, Albuquerque, NM, USA
| | - Uchenna Peter-Okaka
- Bowers Neurosurgical Frailty and Outcomes Data Science Lab, Albuquerque, NM, USA
| | - Christian B Ricks
- Department of Neurosurgery, University of New Mexico Hospital, Albuquerque, NM, USA
| | - Meic H Schmidt
- Department of Neurosurgery, University of New Mexico Hospital, Albuquerque, NM, USA
| | - Christian A Bowers
- Bowers Neurosurgical Frailty and Outcomes Data Science Lab, Albuquerque, NM, USA
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Sun B, Wang J, Wang Y, Xiao W, Liu Y, Wang Y, Chen Y, Lu W. Associations of Dynapenic Abdominal Obesity and Frailty Progression: Evidence from Two Nationwide Cohorts. Nutrients 2024; 16:518. [PMID: 38398843 PMCID: PMC10892768 DOI: 10.3390/nu16040518] [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: 01/03/2024] [Revised: 01/31/2024] [Accepted: 02/01/2024] [Indexed: 02/25/2024] Open
Abstract
The associations of dynapenic abdominal obesity and transitions with frailty progression remain unclear among middle-aged and older adults. We included 6937 participants from the China Health and Retirement Longitudinal Study (CHARLS) and 3735 from the English Longitudinal Study of Aging (ELSA). Participants were divided into non-dynapenia and non-abdominal obesity (ND/NAO), abdominal obesity alone (AO), dynapenia alone (D), and dynapenic abdominal obesity (D/AO). Frailty status was assessed by the frailty index (FI), and a linear mixed-effect model was employed to analyze the associations of D, AO, D/AO, and transitions with frailty progression. Participants with AO, D, and D/AO had increased FI progression compared with ND/NAO in both cohorts. D/AO possessed the greatest additional annual FI increase of 0.383 (95% CI: 0.152 to 0.614), followed by D and AO in the CHARLS. Participants with D in the ELSA had the greatest magnitude of accelerated FI progression. Participants who transitioned from ND/NAO to D and from AO to D/AO presented accelerated FI progression in the CHARLS and ELSA. In conclusion, dynapenic abdominal obesity, especially for D/AO and D, presented accelerated frailty progression. Our findings highlighted the essential intervention targets of dynapenia and abdominal obesity for the prevention of frailty progression.
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Affiliation(s)
| | | | | | | | | | | | | | - Wenli Lu
- Department of Epidemiology and Statistics, School of Public Health, Tianjin Medical University, Tianjin 300070, China; (B.S.); (J.W.); (Y.W.); (W.X.); (Y.L.); (Y.W.); (Y.C.)
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Sang N, Liu RC, Zhang MH, Lu ZX, Wu ZG, Zhang MY, Li BH, Wei M, Pan HF, Wu GC. Changes in frailty and depressive symptoms among middle-aged and older Chinese people: a nationwide cohort study. BMC Public Health 2024; 24:301. [PMID: 38273230 PMCID: PMC10811919 DOI: 10.1186/s12889-024-17824-3] [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: 07/31/2023] [Accepted: 01/19/2024] [Indexed: 01/27/2024] Open
Abstract
BACKGROUND AND AIMS The older people bears a severe burden of disease due to frailty and depressive symptoms, however, the results of association between the two in the older Chinese people have been conflicting. Therefore, this study aimed to investigate the developmental trajectories and interactions of frailty and depressive symptoms in the Chinese middle-aged and older adults. METHODS The study used four waves of data from 2011, 2013, 2015 and 2018 in the China Health and Retirement Longitudinal Study (CHARLS) database, focused on middle-aged and older people ≥ 45 years of age, and analyzed using latent growth models and cross-lagged models. RESULTS The parallel latent growth model showed that the initial level of depressive symptoms had a significant positive predictive effect on the initial level of frailty. The rate of change in depressive symptoms significantly positively predicted the rate of change in frailty. The initial level of frailty had a significant positive predictive effect on the initial level of depressive symptoms, but a significant negative predictive effect on the rate of change in depressive symptoms. The rate of change in frailty had a significant positive predictive effect on the rate of change in depressive symptoms. The results of the cross-lagged analysis indicated a bidirectional causal association between frailty and depressive symptoms in the total sample population. Results for the total sample population grouped by age and gender were consistent with the total sample. CONCLUSIONS This study recommends advancing the age of concern for frailty and depressive symptoms to middle-aged adults. Both men and women need early screening and intervention for frailty and depressive symptoms to promote healthy aging.
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Affiliation(s)
- Ni Sang
- School of Nursing, Anhui Medical University, 15 Feicui Road, Hefei, Anhui, 230032, China
| | - Rong-Chao Liu
- School of Nursing, Anhui Medical University, 15 Feicui Road, Hefei, Anhui, 230032, China
| | - Ming-Hui Zhang
- School of Nursing, Anhui Medical University, 15 Feicui Road, Hefei, Anhui, 230032, China
| | - Zong-Xiao Lu
- School of Nursing, Anhui Medical University, 15 Feicui Road, Hefei, Anhui, 230032, China
| | - Zhen-Gang Wu
- School of Nursing, Anhui Medical University, 15 Feicui Road, Hefei, Anhui, 230032, China
| | - Meng-Yao Zhang
- School of Nursing, Anhui Medical University, 15 Feicui Road, Hefei, Anhui, 230032, China
| | - Bo-Han Li
- School of Nursing, Anhui Medical University, 15 Feicui Road, Hefei, Anhui, 230032, China
| | - Meng Wei
- School of Nursing, Anhui Medical University, 15 Feicui Road, Hefei, Anhui, 230032, China
| | - Hai-Feng Pan
- Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, 81 Meishan Road, Hefei, Anhui, China.
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China.
| | - Guo Cui Wu
- School of Nursing, Anhui Medical University, 15 Feicui Road, Hefei, Anhui, 230032, China.
- Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, 81 Meishan Road, Hefei, Anhui, China.
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He D, Wang Z, Li J, Yu K, He Y, He X, Liu Y, Li Y, Fu R, Zhou D, Zhu Y. Changes in frailty and incident cardiovascular disease in three prospective cohorts. Eur Heart J 2024:ehad885. [PMID: 38241094 DOI: 10.1093/eurheartj/ehad885] [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: 04/19/2023] [Revised: 11/20/2023] [Accepted: 12/21/2023] [Indexed: 01/21/2024] Open
Abstract
BACKGROUND AND AIMS Previous studies found that frailty was an important risk factor for cardiovascular disease (CVD). However, previous studies only focused on baseline frailty status, not taking into consideration the changes in frailty status during follow-up. The aim of this study was to investigate the associations of changes in frailty status with incident CVD. METHODS This study used data of three prospective cohorts: China Health and Retirement Longitudinal Study (CHARLS), English Longitudinal Study of Ageing (ELSA), and Health and Retirement Study (HRS). Frailty status was evaluated by the Rockwood frailty index and classified as robust, pre-frail, or frail. Changes in frailty status were assessed by frailty status at baseline and the second survey which was two years after the baseline. Cardiovascular disease was ascertained by self-reported physician-diagnosed heart disease (including angina, heart attack, congestive heart failure, and other heart problems) or stroke. Cox proportional hazard models were used to calculate the hazard ratio (HR) and 95% confidence interval (95% CI) after adjusting for potential confounders. RESULTS A total of 7116 participants from CHARLS (female: 48.6%, mean age: 57.4 years), 5303 from ELSA (female: 57.7%, mean age: 63.7 years), and 7266 from HRS (female: 64.9%, mean age: 65.1 years) were included according to inclusion and exclusion criteria. The median follow-up periods were 5.0 years in the CHARLS, 10.7 years in the ELSA, and 9.5 years in the HRS. Compared with stable robust participants, robust participants who progressed to pre-frail or frail status had increased risks of incident CVD (CHARLS, HR = 1.84, 95% CI: 1.54-2.21; ELSA, HR = 1.53, 95% CI: 1.25-1.86; HRS, HR = 1.59, 95% CI: 1.31-1.92). In contrast, frail participants who recovered to robust or pre-frail status presented decreased risks of incident CVD (CHARLS, HR = 0.62, 95% CI: 0.47-0.81; ELSA, HR = 0.49, 95% CI: 0.34-0.69; HRS, HR = 0.70, 95% CI: 0.55-0.89) when compared with stable frail participants. These decreased risks of incident CVD were also observed in pre-frail participants who recovered to robust status (CHARLS, HR = 0.66, 95% CI: 0.52-0.83; ELSA, HR = 0.65, 95% CI: 0.49-0.85; HRS, HR = 0.71, 95% CI: 0.56-0.91) when compared with stable pre-frail participants. CONCLUSIONS Different changes in frailty status are associated with different risks of incident CVD. Progression of frailty status increases incident CVD risks, while recovery of frailty status decreases incident CVD risks.
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Affiliation(s)
- Di He
- Department of Epidemiology and Biostatistics, and Department of Respiratory Disease, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 866 Yuhangtang Rd, Hangzhou 310058, Zhejiang, China
| | - Zhaoping Wang
- Department of Epidemiology and Biostatistics, and Department of Respiratory Disease, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 866 Yuhangtang Rd, Hangzhou 310058, Zhejiang, China
| | - Jun Li
- Department of Epidemiology and Biostatistics, and Department of Respiratory Disease, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 866 Yuhangtang Rd, Hangzhou 310058, Zhejiang, China
| | - Kaixin Yu
- Department of Epidemiology and Biostatistics, and Department of Respiratory Disease, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 866 Yuhangtang Rd, Hangzhou 310058, Zhejiang, China
| | - Yusa He
- Department of Epidemiology and Biostatistics, and Department of Respiratory Disease, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 866 Yuhangtang Rd, Hangzhou 310058, Zhejiang, China
| | - Xinyue He
- Department of Epidemiology and Biostatistics, and Department of Respiratory Disease, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 866 Yuhangtang Rd, Hangzhou 310058, Zhejiang, China
| | - Yuanjiao Liu
- Department of Epidemiology and Biostatistics, and Department of Respiratory Disease, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 866 Yuhangtang Rd, Hangzhou 310058, Zhejiang, China
| | - Yuhao Li
- Department of Epidemiology and Biostatistics, and Department of Respiratory Disease, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 866 Yuhangtang Rd, Hangzhou 310058, Zhejiang, China
| | - Ruiyi Fu
- Department of Epidemiology and Biostatistics, and Department of Respiratory Disease, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 866 Yuhangtang Rd, Hangzhou 310058, Zhejiang, China
| | - Dan Zhou
- Department of Big Data in Health Science, School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, 866 Yuhangtang Rd, Hangzhou 310058, Zhejiang, China
- Center of Clinical Big Data and Analytics of the Second Affiliated Hospital, Zhejiang University School of Medicine, 866 Yuhangtang Rd, Hangzhou 310058, Zhejiang, China
| | - Yimin Zhu
- Department of Epidemiology and Biostatistics, and Department of Respiratory Disease, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 866 Yuhangtang Rd, Hangzhou 310058, Zhejiang, China
- Cancer Center, Zhejiang University, 866 Yuhangtang Rd, Hangzhou 310058, Zhejiang, China
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Li X, Wang Q, Guo L, Xue Y, Dang Y, Liu W, Yin T, Zhang Y, Zhao Y. Associations between Low-Carbohydrate Diets and Low-Fat Diets with Frailty in Community-Dwelling Aging Chinese Adults. Nutrients 2023; 15:3084. [PMID: 37513502 PMCID: PMC10383029 DOI: 10.3390/nu15143084] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 06/28/2023] [Accepted: 06/30/2023] [Indexed: 07/30/2023] Open
Abstract
Frailty is a major health issue associated with aging. Diet affects frailty status; however, studies on the associations between the low-carbohydrate diet (LCD) score, low-fat diet (LFD) score and frailty in older Chinese adults are scarce. This study aimed to examine the associations between the LCD score, LFD score and risk of frailty in older Chinese adults. We analyzed data from 6414 participants aged ≥ 60 years from the China Northwest Natural Population Cohort: Ningxia Project. Frailty was measured using the frailty index (FI), calculated from 28 items comprising diseases, behavioral disorders and blood biochemistry and classified as robust, pre-frail and frail. LCD and LFD scores were calculated using a validated food frequency questionnaire (FFQ). Multiple logistic regression models were used to evaluate associations between LCD, LFD scores and frail or pre-frail status after adjusting for confounders. Participants' mean age was 66.60 ± 4.15 years, and 47.8% were male. After adjusting for age, sex, educational level, drinking, smoking, BMI, physical activity and total energy, compared to the lowest quartile (Q1: reference), the odds ratios (ORs) for pre-frail and frail status in the highest quartile (Q4) of LCD score were 0.73 (95% confidence intervals: 0.61-0.88; p for trend = 0.017) and 0.73 (95%CI: 0.55-0.95; p for trend = 0.035), respectively. No significant associations were observed between LFD score and either pre-frail or frail status. Our data support that lower-carbohydrate diets were associated with lower pre-frail or frail status, particularly in females, while diets lower in fat were not significantly associated with the risk of either pre-frail or frail status in older Chinese adults. Further intervention studies are needed to confirm these results.
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Affiliation(s)
- Xiaoxia Li
- School of Public Health, Ningxia Medical University, Yinchuan 750004, China; (X.L.)
- NHC Key Laboratory of Metabolic Cardiovascular Diseases Research, Ningxia Medical University, Yinchuan 750004, China
- Key Laboratory of Environmental Factors and Chronic Disease Control, Ningxia Medical University, Yinchuan 750004, China
| | - Qingan Wang
- School of Public Health, Ningxia Medical University, Yinchuan 750004, China; (X.L.)
- NHC Key Laboratory of Metabolic Cardiovascular Diseases Research, Ningxia Medical University, Yinchuan 750004, China
- Key Laboratory of Environmental Factors and Chronic Disease Control, Ningxia Medical University, Yinchuan 750004, China
| | - Linfeng Guo
- School of Public Health, Ningxia Medical University, Yinchuan 750004, China; (X.L.)
- Key Laboratory of Environmental Factors and Chronic Disease Control, Ningxia Medical University, Yinchuan 750004, China
| | - Yixuan Xue
- School of Public Health, Ningxia Medical University, Yinchuan 750004, China; (X.L.)
- Key Laboratory of Environmental Factors and Chronic Disease Control, Ningxia Medical University, Yinchuan 750004, China
| | - Yuanyuan Dang
- School of Public Health, Ningxia Medical University, Yinchuan 750004, China; (X.L.)
- Key Laboratory of Environmental Factors and Chronic Disease Control, Ningxia Medical University, Yinchuan 750004, China
| | - Wanlu Liu
- School of Public Health, Ningxia Medical University, Yinchuan 750004, China; (X.L.)
- Key Laboratory of Environmental Factors and Chronic Disease Control, Ningxia Medical University, Yinchuan 750004, China
| | - Ting Yin
- School of Public Health, Ningxia Medical University, Yinchuan 750004, China; (X.L.)
- NHC Key Laboratory of Metabolic Cardiovascular Diseases Research, Ningxia Medical University, Yinchuan 750004, China
- Key Laboratory of Environmental Factors and Chronic Disease Control, Ningxia Medical University, Yinchuan 750004, China
| | - Yuhong Zhang
- School of Public Health, Ningxia Medical University, Yinchuan 750004, China; (X.L.)
- NHC Key Laboratory of Metabolic Cardiovascular Diseases Research, Ningxia Medical University, Yinchuan 750004, China
- Key Laboratory of Environmental Factors and Chronic Disease Control, Ningxia Medical University, Yinchuan 750004, China
| | - Yi Zhao
- School of Public Health, Ningxia Medical University, Yinchuan 750004, China; (X.L.)
- NHC Key Laboratory of Metabolic Cardiovascular Diseases Research, Ningxia Medical University, Yinchuan 750004, China
- Key Laboratory of Environmental Factors and Chronic Disease Control, Ningxia Medical University, Yinchuan 750004, China
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