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Wang X, Peng Y, Liu F, Wang P, Si C, Gong J, Zhou H, Zhang M, Song F. Joint association of biological aging and lifestyle with risks of cancer incidence and mortality: A cohort study in the UK Biobank. Prev Med 2024; 182:107928. [PMID: 38471624 DOI: 10.1016/j.ypmed.2024.107928] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 03/06/2024] [Accepted: 03/08/2024] [Indexed: 03/14/2024]
Abstract
BACKGROUND Aging is a risk factor for cancer incidence and mortality. Biological aging can reflect the aging degree of the body better than chronological age and can be aggravated by unhealthy lifestyle factors. We aimed to assess the joint effect of biological aging and lifestyle with risks of cancer incidence and mortality. METHODS This study included a total of 281,889 participants aged 37 to 73 from the UK Biobank database. Biological age was derived from chronological age and 9 clinical blood indicators, and lifestyle score was constructed by body mass index, smoking status, alcohol consumption, physical activity, and diet. Multivariate Cox hazard proportional regression model was used to analyze the independent and joint association of biological aging and lifestyle with risks of cancer incidence and mortality, respectively. RESULTS Over a median follow-up period of 12.3 years, we found that older biological age was associated with increased risks of overall cancer, digestive system cancers, lung, breast and renal cancers incidence and mortality (HRs: 1.12-2.25). In the joint analysis of biological aging and lifestyle with risks of cancer incidence and mortality, compared with unhealthy lifestyle and younger biological age, individuals with healthy lifestyle and older biological age had decreased risks of incidence (8% ∼ 60%) and mortality (20% ∼ 63%) for overall, esophageal, colorectal, pancreatic and lung cancers. CONCLUSIONS Biological aging may be an important risk factor for cancer morbidity and mortality. A healthier lifestyle is more likely to mitigate the adverse effects of biological aging on overall cancer and some site-specific cancers.
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Affiliation(s)
- Xixuan Wang
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Major Diseases in the Population, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China
| | - Yu Peng
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Major Diseases in the Population, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China
| | - Fubin Liu
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Major Diseases in the Population, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China
| | - Peng Wang
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Major Diseases in the Population, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China
| | - Changyu Si
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Major Diseases in the Population, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China
| | - Jianxiao Gong
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Major Diseases in the Population, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China
| | - Huijun Zhou
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Major Diseases in the Population, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China
| | - Ming Zhang
- Comprehensive Management Department of Occupational Health, Shenzhen Prevention and Treatment Center for Occupational Diseases, Shenzhen 518020, China
| | - Fangfang Song
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Major Diseases in the Population, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China.
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Yu L, Guo Z, Long Q, Zhao X, Liu Y, Cao X, Zhang Y, Yan W, Qian QQ, Chen J, Teng Z, Zeng Y. Modifiable Lifestyle, Sedentary Behaviors and the Risk of Frailty: A Univariate and Multivariate Mendelian Randomization Study. Adv Biol (Weinh) 2024; 8:e2400052. [PMID: 38532244 DOI: 10.1002/adbi.202400052] [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: 01/29/2024] [Revised: 03/11/2024] [Indexed: 03/28/2024]
Abstract
This research conducted a two-sample univariate and multivariate Mendelian Randomization (MR) analysis to explore the causal link between different types of leisure sedentary behavior (LSB) and frailty. Independent instrumental variables significantly associated with sedentary behaviors (p < 5 × 10-8) are obtained from a genome-wide association study (GWAS) of 422,218 individuals, and Frailty Index (FI) are derived from the latest GWAS dataset of 175,226 individuals. MR analysis is conducted using inverse variance weighting, MR-Egger, weighted median, simple mode, and weighted mode, supplemented by MRAPSS. Univariate MR revealed that sedentary behaviors such as watching television increased the risk of frailty (OR, 1.271; 95% CI: 1.202-1.345; p = 6.952 × 10-17), as sedentary driving behaviors are done (OR, 1.436; 95% CI: 1.026-2.011; p = 0.035). Further validation through APSS, taking into account cryptic relatedness, stratification, and sample overlap, maintained the association between television viewing and increased frailty risk (OR, 1.394; 95% CI: 1.266-1.534; p = 1.143 × 10-11), while the association with driving dissipated. In multivariate inverse variance weighted (IVW) analysis, after adjusting for C-reactive protein (CRP) levels, television Sedentary behavior (SB) inversely affected frailty (OR, 0.782; 95% CI: 0.724-0.845; p = 4.820 × 10-10). This study indicates that televisio SB significantly increases the risk of frailty, suggesting potential biological heterogeneity behind specific sedentary activities. This process may interact with inflammation, influencing the development of frailty.
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Affiliation(s)
- Ling Yu
- Department of Psychiatry, the Second Affiliated Hospital of Kunming Medical University, Kunming, Yunnan Province, 650101, China
| | - Zeyi Guo
- Department of Psychiatry, the Second Affiliated Hospital of Kunming Medical University, Kunming, Yunnan Province, 650101, China
| | - Qing Long
- Department of Psychiatry, the Second Affiliated Hospital of Kunming Medical University, Kunming, Yunnan Province, 650101, China
| | - Xinling Zhao
- Department of Psychiatry, the Second Affiliated Hospital of Kunming Medical University, Kunming, Yunnan Province, 650101, China
| | - Yilin Liu
- Department of Psychiatry, the Second Affiliated Hospital of Kunming Medical University, Kunming, Yunnan Province, 650101, China
| | - Xiang Cao
- Department of Psychiatry, the Second Affiliated Hospital of Kunming Medical University, Kunming, Yunnan Province, 650101, China
| | - Yunqiao Zhang
- Department of Psychiatry, the Second Affiliated Hospital of Kunming Medical University, Kunming, Yunnan Province, 650101, China
| | - Weimin Yan
- Department of Psychiatry, the Second Affiliated Hospital of Kunming Medical University, Kunming, Yunnan Province, 650101, China
| | - Qing Qing Qian
- Department of Psychiatry, the Second Affiliated Hospital of Kunming Medical University, Kunming, Yunnan Province, 650101, China
| | - Jian Chen
- Department of Gastroenterology, Nanchong Central Hospital, Nanchong, Sichuan Province, 637000, China
| | - Zhaowei Teng
- Department of Psychiatry, the Second Affiliated Hospital of Kunming Medical University, Kunming, Yunnan Province, 650101, China
| | - Yong Zeng
- Department of Psychiatry, the Second Affiliated Hospital of Kunming Medical University, Kunming, Yunnan Province, 650101, China
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Yang G, Cao X, Yu J, Li X, Zhang L, Zhang J, Ma C, Zhang N, Lu Q, Wu C, Chen X, Hoogendijk EO, Gill TM, Liu Z. Association of Childhood Adversity With Frailty and the Mediating Role of Unhealthy Lifestyle: A Lifespan Analysis. Am J Geriatr Psychiatry 2024; 32:71-82. [PMID: 37770350 PMCID: PMC11078585 DOI: 10.1016/j.jagp.2023.08.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 08/10/2023] [Accepted: 08/23/2023] [Indexed: 09/30/2023]
Abstract
OBJECTIVES Childhood adversity and lifestyle have been associated with frailty in later life, but not much is known about factors that may explain these associations. Therefore, this study aims to investigate the association of childhood adversity with frailty, and the mediating role of unhealthy lifestyle in the association. METHODS This lifespan analysis included 152,914 adults aged 40-69 years old from the UK Biobank. We measured childhood adversity with five items: physical neglect, emotional neglect, sexual abuse, physical abuse, and emotional abuse through online mental health survey. Frailty was measured by the frailty index; an unhealthy lifestyle score (range: 0-5) was calculated based on unhealthy body mass index, smoking, alcohol consumption, physical inactivity, and unhealthy diet at the baseline survey. Multiple logistic regression and mediation analysis were performed. RESULTS A total of 10,078 participants (6.6%) were defined as having frailty. Participants with any childhood adversity had higher odds of frailty. For example, in the fully adjusted model, with a one-point increase in cumulative score of childhood adversity, the odds of frailty increased by 38% (odds ratio: 1.38; 95% Confidence Interval: 1.36, 1.40). Unhealthy lifestyle partially mediated the associations of childhood adversity with frailty (mediation proportion: 4.4%-7.0%). The mediation proportions were largest for physical (8.2%) and sexual (8.1%) abuse. CONCLUSIONS Childhood adversity was positively associated with frailty, and unhealthy lifestyle partially mediated the association. This newly identified pathway highlights the potential of lifestyle intervention strategies among those who experienced childhood adversity (in particular, physical, and sexual abuse) to promote healthy aging.
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Affiliation(s)
- Gan Yang
- Second Affiliated Hospital, and School of Public Health (GY, XC, JY, XL, LZ, JZ, ZL), The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Xingqi Cao
- Second Affiliated Hospital, and School of Public Health (GY, XC, JY, XL, LZ, JZ, ZL), The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Jie Yu
- Second Affiliated Hospital, and School of Public Health (GY, XC, JY, XL, LZ, JZ, ZL), The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Xueqin Li
- Second Affiliated Hospital, and School of Public Health (GY, XC, JY, XL, LZ, JZ, ZL), The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Liming Zhang
- Second Affiliated Hospital, and School of Public Health (GY, XC, JY, XL, LZ, JZ, ZL), The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Jingyun Zhang
- Second Affiliated Hospital, and School of Public Health (GY, XC, JY, XL, LZ, JZ, ZL), The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Chao Ma
- School of Economics and Management (CM), Southeast University, Nanjing, Jiangsu, China
| | - Ning Zhang
- Department of Social Medicine School of Public Health and Center for Clinical Big Data and Analytics Second Affiliated Hospital (NZ), Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Qingyun Lu
- School of Public Health (QL), Nantong University, Nantong, JiangSu, China
| | - Chenkai Wu
- Global Health Research Center (CW), Duke Kunshan University, Kunshan, Jiangsu, China
| | - Xi Chen
- Department of Health Policy and Management (XC), Yale School of Public Health, New Haven, CT, USA; Department of Economics (XC), Yale University, New Haven, CT, USA
| | - Emiel O Hoogendijk
- Department of Epidemiology & Data Science (EOH), Amsterdam Public Health research institute, Amsterdam UMC-Location VU University Medical Center, Amsterdam, The Netherlands
| | - Thomas M Gill
- Department of Internal Medicine (TMG), Yale School of Medicine, New Haven, CT, USA
| | - Zuyun Liu
- Second Affiliated Hospital, and School of Public Health (GY, XC, JY, XL, LZ, JZ, ZL), The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
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Qi Y, Zhang Z, Fu X, Han P, Xu W, Cao L, Guo Q. Adherence to a healthy lifestyle and its association with cognitive impairment in community-dwelling older adults in Shanghai. Front Public Health 2023; 11:1291458. [PMID: 38179562 PMCID: PMC10765578 DOI: 10.3389/fpubh.2023.1291458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 11/28/2023] [Indexed: 01/06/2024] Open
Abstract
Introduction There is a growing body of recent literature linking the association of specific or multiple lifestyles with cognitive impairment, but most of these studies have been conducted in Western populations, and it is necessary to study multiple lifestyles and cognitive abilities in different populations, with the primary population of this study being a select group of community-dwelling older adults in Shanghai, China. Methods The sample included 2,390 community-dwelling Chinese participants. Their cognitive function was assessed using the Mini-Mental State Examination (MMSE). We defined a healthy lifestyle score on the basis of being non-smoking, performing ≥210 min/wk moderate/vigorous-intensity physical activity, having light to moderate alcohol consumption, eating vegetables and fruits daily, having a body mass index (BMI) of 18.5-23.9 kg/m2, and having a waist-to-hip ratio (WHR) <0.90 for men and <0.85 for women, for an overall score ranging from 0 to 6. Results Compared with participants with ≤2 healthy lifestyle factors, the adjusted odds ratio (OR) and 95% confidence interval (CI) for participants with 4, 5, and 6 healthy lifestyle factors were 0.53 (95% CI, 0.29-0.98), 0.40 (95% CI, 0.21-0.75), and 0.36 (95% CI, 0.16-0.79), respectively. Only WHR (OR = 0.54, 95% CI = 0.37-0.78) and physical activity (OR = 0.69, 95% CI = 0.51-0.92) were associated with cognitive impairment. A healthy lifestyle correlated with overall cognition (β = 0.066, orientation (β = 0.049), language ability (β = 0.060), delayed recall (β = 0.045) and executive function (β = 0.044) (P all < 0.05). Conclusion The study provides evidence on an inverse association between healthy lifestyles and cognitive impairment. We investigated whether healthy lifestyle was related to specific cognitive functions to provide a theoretical basis for accurate clinical prescription.
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Affiliation(s)
- Yiqiong Qi
- Department of Rehabilitation Medicine, Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Shanghai, China
- Department of Sport Rehabilitation, Shanghai University of Sport, Shanghai, China
- Department of Rehabilitation Medicine, Shanghai University of Medicine and Health Sciences, Shanghai, China
| | | | - Xiya Fu
- Department of Rehabilitation Medicine, Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Shanghai, China
- Department of Sport Rehabilitation, Shanghai University of Sport, Shanghai, China
- Department of Rehabilitation Medicine, Shanghai University of Medicine and Health Sciences, Shanghai, China
| | - Peipei Han
- Department of Rehabilitation Medicine, Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Shanghai, China
- Department of Rehabilitation Medicine, Shanghai University of Medicine and Health Sciences, Shanghai, China
| | - Weixin Xu
- Department of Laboratory Medicine of Central Hospital of Jiading District Shanghai Affiliated to Shanghai University of Medicine and Health Sciences, Shanghai, China
| | - Liou Cao
- Department of Nephrology, Molecular Cell Lab for Kidney Disease, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qi Guo
- Department of Rehabilitation Medicine, Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Shanghai, China
- Department of Rehabilitation Medicine, School of Health, Fujian Medical University, Fuzhou, China
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Wang J, Chen C, Zhou J, Ye L, Li Y, Xu L, Xu Z, Li X, Wei Y, Liu J, Lv Y, Shi X. Healthy lifestyle in late-life, longevity genes, and life expectancy among older adults: a 20-year, population-based, prospective cohort study. THE LANCET. HEALTHY LONGEVITY 2023; 4:e535-e543. [PMID: 37804845 DOI: 10.1016/s2666-7568(23)00140-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 07/17/2023] [Accepted: 07/17/2023] [Indexed: 10/09/2023] Open
Abstract
BACKGROUND Lifestyle and longevity genes have different and important roles in the human lifespan; however, the association between a healthy lifestyle in late-life and life expectancy mediated by genetic risk is yet to be elucidated. We aimed to investigate the associations of healthy lifestyle in late-life and genetic risk with life expectancy among older adults. METHODS A weighted healthy lifestyle score was constructed from the following variables: current non-smoking, non-harmful alcohol consumption, regular physical activity, and a healthy diet. Participants were recruited from the Chinese Longitudinal Healthy Longevity Survey, a prospective community-based cohort study that took place between 1998 and 2018. Eligible participants were aged 65 years and older with available information on lifestyle factors at baseline, and then were categorised into unhealthy (bottom tertile of the weighted healthy lifestyle score), intermediate (middle tertile), and healthy (top tertile) lifestyle groups. A genetic risk score was constructed based on 11 lifespan loci among 9633 participants, divided by the median and classified into low and high genetic risk groups. Stratified Cox proportional hazard regression was used to estimate the interaction between genetic and lifestyle factors on all-cause mortality risk. FINDINGS Between Jan 13, 1998, and Dec 31, 2018, 36 164 adults aged 65 years and older were recruited, among whom a total of 27 462 deaths were documented during a median follow-up of 3·12 years (IQR 1·62-5·94) and included in the lifestyle association analysis. Compared with the unhealthy lifestyle category, participants in the healthy lifestyle group had a lower all-cause mortality risk (hazard ratio [HR] 0·56 [95% CI 0·54-0·57]; p<0·0001). The highest mortality risk was observed in individuals in the high genetic risk and unhealthy lifestyle group (HR 1·80 [95% CI 1·63-1·98]; p<0·0001). The absolute risk reduction was greater for participants in the high genetic risk group. A healthy lifestyle was associated with a gain of 3·84 years (95% CI 3·05-4·64) at the age of 65 years in the low genetic risk group, and 4·35 years (3·70-5·06) in the high genetic risk group. INTERPRETATION A healthy lifestyle, even in late-life, was associated with lower mortality risk and longer life expectancy among Chinese older adults, highlighting the importance of a healthy lifestyle in extending the lifespan, especially for individuals with high genetic risk. FUNDING National Natural Science Foundation of China. TRANSLATION For the Mandarin translation of the abstract see Supplementary Materials section.
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Affiliation(s)
- Jun Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, 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, Beijing, China
| | - Jinhui Zhou
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Lihong Ye
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yang Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Lanjing Xu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Department of Big Data in Health Science, School of Public Health, Zhejiang University, Hangzhou, China
| | - Zinan Xu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, China
| | - Xinwei Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China
| | - Yuan Wei
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Department of Hygienic Inspection, School of Public Health, Jilin University, Changchun, China
| | - Junxin Liu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yuebin Lv
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China.
| | - Xiaoming Shi
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.
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Rafati F, Pourshahrokhi N, Bahador RS, Dastyar N, Mehralizadeh A. The effect of mobile app-based self-care training on the quality of marital relations and the severity of menopausal symptoms in postmenopausal women: a clinical trial study in Iran. BMC Womens Health 2023; 23:306. [PMID: 37308866 DOI: 10.1186/s12905-023-02463-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Accepted: 06/07/2023] [Indexed: 06/14/2023] Open
Abstract
BACKGROUND Educational interventions for self-care are a necessary solution to help postmenopausal women properly deal with menopausal problems. The present study aimed to investigate the effect of self-care training using an application on the quality of marital relations and the severity of menopausal symptoms in postmenopausal women in Iran. METHODS In this study, 60 postmenopausal women selected using the convenience sampling method were divided into two groups, intervention and control, using simple random allocation (lottery). The intervention group used the menopause self-care application for eight weeks in addition to routine care, but the control group only received the routine care. The Menopause Rating Scale (MRS) and the Perceived Relationship Quality Components (PRQC) questionnaire were completed in two stages, before and immediately after eight weeks, in both groups. Data were analyzed using SPSS software (version 16), descriptive (mean and standard deviation), and inferential (ANCOVA and Bonferroni post hoc) statistics. RESULTS The ANCOVA results showed that the use of the menopause self-care application decreased the severity of the participants' menopause symptoms (P = 0.001) and improved the quality of their marital relations (P = 0.001). CONCLUSION Implementation of a self-care training program through the application helped improve the quality of marital relations and reduce the severity of postmenopausal women's symptoms, so it can be used as an effective method to prevent the unpleasant consequences of menopause. TRIAL REGISTRATION The present study was registered at https://fa.irct.ir/ on 2021-05-28 (registration number: IRCT20201226049833N1).
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Affiliation(s)
- Foozieh Rafati
- School of Nursing and Midwifery, Jiroft University of Medical Sciences, Jiroft, Iran
| | | | - Raziyeh Sadat Bahador
- School of Nursing and Midwifery, Jiroft University of Medical Sciences, Jiroft, Iran
| | - Neda Dastyar
- Department of Midwifery, School of Nursing and Midwifery, Jiroft University of Medical Sciences, Jiroft, Iran.
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Haapanen M, Mikkola T, Kortelainen L, Jylhävä J, Wasenius N, Kajantie E, Eriksson J, von Bonsdorff M. Body Composition in Late Midlife as a Predictor of Accelerated Age-associated Deficit-accumulation From Late Midlife into Old Age: A Longitudinal Birth Cohort Study. J Gerontol A Biol Sci Med Sci 2023; 78:980-987. [PMID: 36434783 PMCID: PMC10235203 DOI: 10.1093/gerona/glac233] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Indexed: 09/26/2023] Open
Abstract
BACKGROUND Body mass index (BMI) may not be an optimal predictor of frailty as its constituents, lean and fat mass, may have opposite associations with frailty. METHODS A linear mixed model analysis was performed in the Helsinki Birth Cohort Study (n = 2 000) spanning from 57 to 84 years. A 39-item frailty index (FI) was calculated on three occasions over 17 years. Body composition in late midlife included BMI, percent body fat (%BF), waist-to-hip ratio (WHR), lean mass index (LMI), and fat mass index (FMI). RESULTS Mean FI levels increased by 0.28%/year among men and by 0.34%/year among women. Among women, per each kg/m2 higher BMI and each unit higher %BF the increases in FI levels per year were 0.013 percentage points (PP) steeper (95% CI = 0.004, 0.023) and 0.009 PP steeper (95% CI = 0.002, 0.016) from late midlife into old age. Among men, per each 0.1-unit greater WHR the increase in FI levels was 0.074 PP steeper per year (95% CI = -0.0004, 0.148). Cross-sectionally, greater FMI and LMI in late midlife were associated with higher FI levels but the direction of the association regarding LMI changed after adjustment for FMI. The categories "high FMI and high LMI" and "high FMI and low LMI" showed the highest FI levels relative to the category "low FMI and low LMI". CONCLUSIONS In late midlife, greater adiposity (%BF) among women and abdominal obesity (WHR) among men may predispose to higher levels of frailty from late midlife into old age. Greater lean mass alone may be protective of frailty, but not in the presence of high fat mass.
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Affiliation(s)
- Markus J Haapanen
- Folkhälsan Research Center, Helsinki, Finland
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Tuija M Mikkola
- Folkhälsan Research Center, Helsinki, Finland
- Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Lauri Kortelainen
- Folkhälsan Research Center, Helsinki, Finland
- Department of Health and Social Management, University of Eastern Finland, Kuopio, Finland
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Faculty of Social Sciences (Health Sciences) and Gerontology Research Center, Tampere University, Tampere, Finland
| | - Niko S Wasenius
- Folkhälsan Research Center, Helsinki, Finland
- Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland
| | - Eero Kajantie
- Department of Public Health and Welfare, Population Health Unit, Finnish Institute for Health and Welfare, Helsinki, Finland
- PEDEGO Research Unit, Medical Research Center Oulu, Oulu University Hospital, University of Oulu, Oulu, Finland
| | - Johan G Eriksson
- Folkhälsan Research Center, Helsinki, Finland
- Department of Obstetrics and Gynecology and Human Potential Translational Research Programme, Yong Loo Lin School of Medicine, National University Singapore, Singapore
| | - Mikaela B von Bonsdorff
- Folkhälsan Research Center, Helsinki, Finland
- Gerontology Research Center and Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
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Yang G, Cao X, Yu J, Li X, Zhang L, Zhang J, Ma C, Zhang N, Lu Q, Wu C, Chen X, Hoogendijk EO, Gill TM, Liu Z. Association of childhood adversity with frailty and the mediating role of unhealthy lifestyle: Findings from the UK biobank. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.02.08.23285634. [PMID: 36798168 PMCID: PMC9934802 DOI: 10.1101/2023.02.08.23285634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
Abstract
Background Childhood adversity and lifestyle have been associated with frailty in later life, but not much is known about factors that may explain these associations. An unhealthy lifestyle may play an important role in the pathway from childhood adversity to frailty. Therefore, this study aims to investigate the association of childhood adversity with frailty, and the mediating role of unhealthy lifestyle in the association. Methods This lifespan analysis included 152914 adults aged 40-69 years old from the UK Biobank. We measured childhood adversity with five items: physical neglect, emotional neglect, sexual abuse, physical abuse, and emotional abuse through online mental health survey. Frailty was measured by the frailty index; an unhealthy lifestyle score (range: 0-5) was calculated based on unhealthy body mass index, smoking, drinking, physical inactivity, and unhealthy diet at the baseline survey. Multiple logistic regression and mediation analysis were performed. Results A total of 10078 participants (6.6%) were defined as having frailty. Participants with any childhood adversity had higher odds of frailty. For example, in the fully adjusted model, with a one-point increase in cumulative score of childhood adversity, the odds of frailty increased by 41% (Odds Ratio: 1.41; 95% Confidence Interval: 1.39, 1.44). Unhealthy lifestyle partially mediated the associations of childhood adversity with frailty (mediation proportion: 4.4%-7.0%). The mediation proportions were largest for physical (8.2%) and sexual (8.1%) abuse. Conclusions Among this large sample, childhood adversity was positively associated with frailty, and unhealthy lifestyle partially mediated the association. This newly identified pathway highlights the potential of lifestyle intervention strategies among those who experienced childhood adversity (in particular, physical and sexual abuse) to promote healthy aging.
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Affiliation(s)
- Gan Yang
- School of Public Health and Second Affiliated Hospital, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Xingqi Cao
- School of Public Health and Second Affiliated Hospital, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Jie Yu
- School of Public Health and Second Affiliated Hospital, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Xueqin Li
- School of Public Health and Second Affiliated Hospital, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Liming Zhang
- School of Public Health and Second Affiliated Hospital, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Jingyun Zhang
- School of Public Health and Second Affiliated Hospital, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Chao Ma
- School of Economics and Management, Southeast University, Nanjing 211189, Jiangsu, China
| | - Ning Zhang
- Department of Social Medicine School of Public Health and Center for Clinical Big Data and Analytics Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Qingyun Lu
- School of Public Health, Nantong University, Nantong 226007, JiangSu, China
| | - Chenkai Wu
- Duke Global Health Institute, Duke University, Durham, NC, USA
| | - Xi Chen
- Department of Health Policy and Management, Yale School of Public Health, New Haven, CT 06520, United States of America
- Department of Economics, Yale University, New Haven, CT 06520, United States of America
| | - Emiel O. Hoogendijk
- Department of Epidemiology & Data Science, Amsterdam Public Health research institute, Amsterdam UMC – location VU University medical center, Amsterdam, the Netherlands
| | - Thomas M. Gill
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT 06520, United States of America
| | - Zuyun Liu
- School of Public Health and Second Affiliated Hospital, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
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Li H, Ge M, Pei Z, He J, Wang C. Associations of environmental factors with total cholesterol level of middle-aged and elderly people in China. BMC Public Health 2022; 22:2423. [PMID: 36564736 PMCID: PMC9783789 DOI: 10.1186/s12889-022-14922-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 12/21/2022] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Dyslipidemia is a key factor causing cardio cerebrovascular diseases, and the total cholesterol (TC) is an important lipid indicator among them. Studies have shown that environmental factors have a strong association with TC levels. Previous studies only focused on the seasonal variation of TC level and the short-term effects of some environmental factors on TC level over time, and few studies explored the geographical distribution of TC level and quantified the impact of environmental factors in space. METHODS Based on blood test data which was from China Health and Retirement Longitudinal Study (Charls) database, this study selected the TC level test data of middle-aged and elderly people in China in 2011 and 2015, and collected data from 665 meteorological stations and 1496 air pollutant monitoring stations in China. After pretreatment, the spatial distribution map of TC level was prepared and the regional statistics were made. GeoDetector and geographically weighted regression (GWR) were used to measure the relationship between environmental factors and TC level. RESULTS The TC level of middle-aged and elderly in China was higher in females than in males, and higher in urban areas than in rural areas, showing a clustered distribution. The high values were mainly in South China, Southwest China and North China. Temperature, humidity, PM10 and PM2.5 were significant environmental factors affecting TC level of middle-aged and elderly people. The impact of pollutants was more severe in northern China, and TC level in southern China was mainly affected by meteorological factors. CONCLUSIONS There were gender and urban-rural differences in TC levels among the middle-aged and elderly population in China, showing aggregation in geographical distribution. Meteorological factors and air pollutants may be very important control factors, and their influencing mechanism needs further study.
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Affiliation(s)
- Hao Li
- grid.412498.20000 0004 1759 8395Institute of Healthy Geography, School of Geography and Tourism, Shaanxi Normal University, 620 West Chang’an Street, Chang’an District, Xi’an, 710119 China
| | - Miao Ge
- grid.412498.20000 0004 1759 8395Institute of Healthy Geography, School of Geography and Tourism, Shaanxi Normal University, 620 West Chang’an Street, Chang’an District, Xi’an, 710119 China
| | - Zehua Pei
- grid.412498.20000 0004 1759 8395Institute of Healthy Geography, School of Geography and Tourism, Shaanxi Normal University, 620 West Chang’an Street, Chang’an District, Xi’an, 710119 China
| | - Jinwei He
- grid.440747.40000 0001 0473 0092Medical School, Yan’an University, 580 Shengdi Road, Yan’an, 716000 China
| | - Congxia Wang
- grid.43169.390000 0001 0599 1243Department of Cardiology, the Second Affiliated Hospital of Medical College, Xi’an Jiaotong University, No. 157, Xiwu Road, Xi’an, 710004 China
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Zhu Y, Fan J, Lv J, Guo Y, Pei P, Yang L, Chen Y, Du H, Li F, Yang X, Avery D, Chen J, Chen Z, Yu C, Li L. Maintaining healthy sleep patterns and frailty transitions: a prospective Chinese study. BMC Med 2022; 20:354. [PMID: 36266610 PMCID: PMC9585775 DOI: 10.1186/s12916-022-02557-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2022] [Accepted: 09/08/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Little is known about the effects of maintaining healthy sleep patterns on frailty transitions. METHODS Based on 23,847 Chinese adults aged 30-79 in a prospective cohort study, we examined the associations between sleep patterns and frailty transitions. Healthy sleep patterns included sleep duration at 7 or 8 h/d, without insomnia disorder, and no snoring. Participants who persisted with a healthy sleep pattern in both surveys were defined as maintaining a healthy sleep pattern and scored one point. We used 27 phenotypes to construct a frailty index and defined three statuses: robust, prefrail, and frail. Frailty transitions were defined as the change of frailty status between the 2 surveys: improved, worsened, and remained. Log-binomial regression was used to calculate the prevalence ratio (PR) to assess the effect of sleep patterns on frailty transitions. RESULTS During a median follow-up of 8.0 years among 23,847 adults, 45.5% of robust participants, and 10.8% of prefrail participants worsened their frailty status, while 18.6% of prefrail participants improved. Among robust participants at baseline, individuals who maintained sleep duration of 7 or 8 h/ds, without insomnia disorder, and no-snoring were less likely to worsen their frailty status; the corresponding PRs (95% CIs) were 0.92 (0.89-0.96), 0.76 (0.74-0.77), and 0.85 (0.82-0.88), respectively. Similar results were observed among prefrail participants maintaining healthy sleep patterns. Maintaining healthy sleep duration and without snoring, also raised the probability of improving the frailty status; the corresponding PRs were 1.09 (1.00-1.18) and 1.42 (1.31-1.54), respectively. Besides, a dose-response relationship was observed between constantly healthy sleep scores and the risk of frailty transitions (P for trend < 0.001). CONCLUSIONS Maintaining a comprehensive healthy sleep pattern was positively associated with a lower risk of worsening frailty status and a higher probability of improving frailty status among Chinese adults.
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Affiliation(s)
- Yunqing Zhu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, 100191, Beijing, China
| | - Junning Fan
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, 100191, Beijing, China
| | - Jun Lv
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, 100191, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China
| | - Yu Guo
- Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing, 100037, China
| | - Pei Pei
- Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Ling Yang
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, OX3 7LF, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
| | - Yiping Chen
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, OX3 7LF, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
| | - Huaidong Du
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, OX3 7LF, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
| | - Feifei Li
- NCDs Prevention and Control Department, Qingdao CDC, Qingdao, 266033, Shandong, China
| | - Xiaoming Yang
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
| | - Daniel Avery
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
| | - Junshi Chen
- China National Center for Food Safety Risk Assessment, Beijing, 100022, China
| | - Zhengming Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
| | - Canqing Yu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, 100191, Beijing, China.
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China.
| | - Liming Li
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, 100191, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China
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Li H, Ge M, Pei Z, He J, Wang C. Nonlinear associations between environmental factors and lipid levels in middle-aged and elderly population in China: A national cross-sectional study. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 838:155962. [PMID: 35588809 DOI: 10.1016/j.scitotenv.2022.155962] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 05/04/2022] [Accepted: 05/11/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Blood lipid is an important factor affecting cardiovascular disease in middle-aged and elderly people. At present, the associations between environmental factors and blood lipid level in elderly people has been controversial, and the nonlinear effect of their relationship is lack of research. METHODS This study used data from a national cross-sectional survey of blood lipid levels in 13,354 subjects and data from environmental monitoring sites. Logistic regression was used to measure the relationship between the basic characteristics of the study population and blood lipid levels. After controlling the confounding factors, the nonlinear associations between environmental factors and blood lipid levels of middle-aged and elderly people in different geographical regions were studied by random forest model. RESULTS The risk of dyslipidemia is significantly higher in middle-aged women, obese people, elderly people, and urban people. Smoking and alcohol consumption increase the risk. The associations between environmental factors and lipid levels of middle-aged and elderly people are nonlinear, the correlation effect between air pollutants and blood lipid level is mainly shown in northern China, and the correlation between meteorological factors and blood lipid level is more obvious in southern China. CONCLUSIONS This study shows that the associations between environmental factors and lipid levels in middle-aged and elderly population are nonlinear and have regional differences. Therefore it should be considered in optimizing the allocation of public health resources and preventing and controlling environmental exposure of middle-aged and elderly population.
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Affiliation(s)
- Hao Li
- Institute of Healthy Geography, School of Geography and Tourism, Shaanxi Normal University, 620 West Chang'an Street, Chang'an District, Xi'an 710119, China
| | - Miao Ge
- Institute of Healthy Geography, School of Geography and Tourism, Shaanxi Normal University, 620 West Chang'an Street, Chang'an District, Xi'an 710119, China.
| | - Zehua Pei
- Institute of Healthy Geography, School of Geography and Tourism, Shaanxi Normal University, 620 West Chang'an Street, Chang'an District, Xi'an 710119, China
| | - Jinwei He
- Medical School, Yan'an University, 580 Shengdi Road, Yan'an 716000, China
| | - Congxia Wang
- Department of Cardiology, the Second Affiliated Hospital of Medical College, Xi'an Jiaotong University, No. 157, Xiwu Road, Xi'an 710004, China
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Karimi L, Mokhtari Seghaleh M, Khalili R, Vahedian-Azimi A. The effect of self-care education program on the severity of menopause symptoms and marital satisfaction in postmenopausal women: a randomized controlled clinical trial. BMC Womens Health 2022; 22:71. [PMID: 35287681 PMCID: PMC8919913 DOI: 10.1186/s12905-022-01653-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 03/07/2022] [Indexed: 12/03/2022] Open
Abstract
Background Physiological and psychological changes during menopause can affect the quality of marital satisfaction. The aim of this study was to evaluate the effect of self-care education program on the severity of menopause symptoms and marital satisfaction in postmenopausal women.
Methods In this randomized controlled clinical trial, 70 postmenopausal women who referred to the gynecology clinic of Baqiyatallah and 502 Artesh hospitals in Tehran, Iran, and met the all inclusion criteria were randomly allocated into two equal groups (intervention and control groups) using block randomization. The intervention group received self-care training program in physical, psychological, social and sexual dimensions in 5 sessions during a week. The control group also had 5 sessions exactly the same as the intervention group, except that they received only routine care and training. Data were collected pre- and post-intervention using Menopause Symptoms' Severity Inventory (MSSI-38) questionnaire and the Revised Dyadic Adjustment Scale (RDAS) questionnaire. Results In the control and intervention groups before the intervention, socio-demographic characteristics (P > 0.05), the mean scores of MSSI-38 (P = 0.388) and RADS (P = 0.476) were not statistically significant. However, in the intervention group the mean scores of MSSI-38 (49.88 ± 3.3 vs. 39.33 ± 3.7, P < 0.001) and RADS (35.15 ± 4.3 vs. 49.48 ± 3.2, P < 0.001) after the intervention changed significantly and this change were statistically significant compared to the control group. Significant inverse correlation between severity of menopausal symptoms and marital satisfaction was observed with r = -0.461, P < 0.001. Conclusion Our findings indicate that self-care training has a positive effect on the severity of menopause symptoms and also improves marital satisfaction in postmenopausal women. Therefore, we recommend that more attention be paid to providing self-care educational content to improve the marital satisfaction in postmenopausal women. Clinical trial registration Iranian Registry of Clinical Trials; https://www.irct.ir/trial/49225 (IRCT20200624047910N1), registered (10/11/2020). Supplementary Information The online version contains supplementary material available at 10.1186/s12905-022-01653-w.
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Affiliation(s)
- Leila Karimi
- Behavioral Sciences Research Center, Life Style Institute, Nursing Faculty, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Maliheh Mokhtari Seghaleh
- Behavioral Sciences Research Center, Life Style Institute, Nursing Faculty, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Robabeh Khalili
- Behavioral Sciences Research Center, Life Style Institute, Nursing Faculty, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Amir Vahedian-Azimi
- Trauma Research Center, Nursing Faculty, Baqiyatallah University of Medical Sciences, Tehran, Iran.
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