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Hu JC, Ding YQ, Pang HY, Yu CQ, Sun DJY, Pei P, Du HD, Chen JS, Chen ZM, Zhu L, Lyu J, Li LM. [Prevalence of urinary incontinence in middle-aged and elderly adults in 10 areas in China]. Zhonghua Liu Xing Bing Xue Za Zhi 2024; 45:11-18. [PMID: 38228519 DOI: 10.3760/cma.j.cn112338-20230910-00144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 01/18/2024]
Abstract
Objective: To describe the population and area distribution differences in the prevalence of urinary incontinence in middle-aged and elderly adults in 10 areas in China. Methods: A total of 24 913 participants aged 45-95 years who completed the third resurvey of China Kadoorie Biobank during 2020-2021 were included. The prevalence of urinary incontinence was assessed by an interviewer-administered questionnaire, and urinary incontinence was classified as only stress urinary incontinence, only urgency urinary incontinence and mixed urinary incontinence. The prevalence of urinary incontinence and its subtypes were reported by sex, age and area, and the severity of urinary incontinence and treatment were described. Results: The average age of the participants was (65.4±9.1) years. According to the seventh national census data in 2020, the age-standardized prevalence rates of urinary incontinence was 25.4% in women and 7.0% in men. The age-standardized prevalence rates of only stress, only urgency and mixed incontinence were 1.7%, 4.2% and 1.2% in men and 13.5%, 5.8% and 6.1% in women, respectively. The prevalence rates of urinary incontinence and all subtypes in men and the prevalence of urinary incontinence and all subtypes except only stress urinary incontinence in women all increased with age (P<0.001). After adjusting for age, the prevalence of urinary incontinence in both men and women were higher in rural area than in urban area (P<0.001). The treatment rates in men and women with urinary incontinence were 15.4% and 8.5%, respectively. Conclusions: The prevalence of urinary incontinence was high in middle-aged and elderly adults in China, and the prevalence rate was higher in women than in men, but the treatment rate of urinary incontinence was low.
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Affiliation(s)
- J C Hu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
| | - Y Q Ding
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
| | - H Y Pang
- Medical Science Research Center, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - C Q Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
| | - D J Y Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
| | - P Pei
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
| | - H D Du
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford OX3 7LF, United Kingdom Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, United Kingdom
| | - J S Chen
- China National Center for Food Safety Risk Assessment, Beijing 100022, China
| | - Z M Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, United Kingdom
| | - L Zhu
- Department of Gynecology and Obstetrics, National Clinical Research Center for Obstetric and Gynecologic Diseases, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - J Lyu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
| | - L M Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
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Yu W, Lan YB, Lyu J, Sun DJY, Pei P, Du HD, Chen JS, Chen ZM, Li LM, Yu CQ. [Epidemiological characteristics of preserved vegetable intake in adults in 10 areas of China]. Zhonghua Liu Xing Bing Xue Za Zhi 2024; 45:19-25. [PMID: 38228520 DOI: 10.3760/cma.j.cn112338-20230613-00370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 01/18/2024]
Abstract
Objective: To describe the epidemiological characteristics of intakes of different types of preserved vegetables in participants from the China Kadoorie Biobank (CKB). Methods: The CKB project conducted baseline survey, the first resurvey, and the second resurvey during 2004-2008, 2008, and 2013-2014, respectively. According to the average intake levels of salted and sour pickled vegetables in the second resurvey, the 10 survey areas were classified as the area where people mainly consumed salted vegetables, the area where people mainly consumed sour pickled vegetables, and the area where people rarely consumed preserved vegetables. For the first two areas, logistic regression model was used to describe the temporal trends and population distribution of preserved vegetable intake and analyze the distribution of other dietary factors. Results: The area where people mainly consumed salted vegetables included Qingdao, Harbin, Suzhou, and Zhejiang (baseline participant number: 204 036), while the area where people mainly consumed sour pickled vegetables included Gansu and Sichuan (baseline participant number: 105 573). In the area where people mainly consumed salted vegetables, the average intake frequencies of preserved vegetables was 3.1, 3.3, and 1.8 days/week in the baseline survey, the first resurvey, and the second resurvey, respectively, showing a declining trend (P<0.001). Similarly, the average intake frequencies of preserved vegetables were 2.8, 2.7, and 1.6 days/week in the baseline survey, the first resurvey and the second resurvey in the area where people mainly consumed sour pickled vegetables (P<0.001). At baseline survey, the married and those had lower education level tended to have more preserved vegetable intakes in both areas (P<0.001). In the area where people mainly consumed salted vegetables, the elderly had higher frequency of preserved vegetable intake (P<0.001), which was converse in the area where people mainly consumed sour pickled vegetables. In the participants with higher frequency of preserved vegetable intake, more people consumed spicy food daily and preferred salty food (P<0.05). Conclusions: The area and population specific differences in the type and frequency of preserved vegetable intake were observed in adults in the CKB project in China. Besides, the average level of preserved vegetable intake showed a declining trend. Preserved vegetable intake might be associated with other dietary habits.
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Affiliation(s)
- W Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Y B Lan
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - J Lyu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education,Beijing 100191, China
| | - D J Y Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education,Beijing 100191, China
| | - P Pei
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
| | - H D Du
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford OX3 7LF, United Kingdom Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, United Kingdom
| | - J S Chen
- China National Center for Food Safety Risk Assessment, Beijing 100022, China
| | - Z M Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, United Kingdom
| | - L M Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education,Beijing 100191, China
| | - C Q Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education,Beijing 100191, China
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Zhao YX, Song MY, Lyu J, Yu CQ, Pei P, Du HD, Chen JS, Chen ZM, Li LM, Sun DJY. [Epidemiological distribution of mosaic loss of chromosome Y in adult men in 10 areas in China and its prospective association with lung cancer]. Zhonghua Liu Xing Bing Xue Za Zhi 2024; 45:56-62. [PMID: 38228525 DOI: 10.3760/cma.j.cn112338-20230412-00228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 01/18/2024]
Abstract
Objective: To detect the prevalence of mosaic loss of chromosome Y in adult men in ten study areas in China, describe the epidemiological distribution of mosaic loss of chromosome Y (mLOY) carriers and assess its prospective association with lung cancer. Methods: Based on the data from baseline survey, genetic analysis and follow-up (as of December 31, 2018) from China Kadoorie Biobank, we used Mosaic Chromosomal Alterations pipeline to detect mLOY carriers in 10 areas in China and described the epidemiological characteristics of mLOY carriers in adult men, including age, area distribution, lifestyle and disease history. We used multivariate logistic regression model to identify the potential relevant factor of mLOY. Cox proportional hazard regression model was fitted to assess the prospective association of mLOY with lung cancer. Stratification analysis were conducted to evaluate the potential modification effects of smoking and age. We also conducted mediation analysis to assess the mediating effect of mLOY in the association between smoking and lung cancer. Results: A total of 42 859 adult men were included in our analysis, in whom 2 458 mLOY carriers were detected (5.7%). The detection rate increased with age (P<0.05). The detection rate was higher in urban area (7.3%±0.2%) than that in rural area (4.7%±0.1%). The results of logistic regression analysis indicated that smoking might be a risk factor for the detection of mLOY (OR=1.49, 95%CI:1.36-1.64). After follow-up for average 11.1 years, 1 041 lung cancer cases were observed. The prospective analysis showed that mLOY carriers had an increased risk for lung cancer by 24% compared with non-mLOY carriers (HR=1.24, 95%CI:1.01-1.52) and expanded mLOY carriers (mLOY cell proportion ≥10%) had an increased risk for lung cancer by 50% (HR=1.50, 95%CI:1.13-2.00). Stratification analysis showed no modification effects of smoking and age in the association between mLOY and lung cancer (interaction P>0.05). Mediation analysis showed that mLOY could be a mediating factor in the association between smoking and lung cancer, the estimated effect was 0.09 (0.01-0.17). Conclusions: There were significant differences in the detection rate of mLOY in adult men with different social-economic characteristics and lifestyles in ten areas in China. Besides, mLOY carriers, especially expanded mLOY carriers, had increased risk for lung cancer and mLOY might be a mediating factor in the association between smoking and lung cancer.
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Affiliation(s)
- Y X Zhao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - M Y Song
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - J Lyu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
| | - C Q Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
| | - P Pei
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
| | - H D Du
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford OX3 7LF, United Kingdom Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, United Kingdom
| | - J S Chen
- China National Center for Food Safety Risk Assessment, Beijing 100022, China
| | - Z M Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, United Kingdom
| | - L M Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
| | - D J Y Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
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Chen YY, Ke YL, Lyu J, Sun DJY, Pan L, Pei P, Du HD, Chen JS, Chen ZM, Li LM, Doherty DOHERTY, Yu CQ. [Progress and practice of objective measurement of physical behaviors in large-scale cohort research]. Zhonghua Liu Xing Bing Xue Za Zhi 2024; 45:35-40. [PMID: 38228522 DOI: 10.3760/cma.j.cn112338-20230724-00036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 01/18/2024]
Abstract
Due to the limited reliability of traditional self-completed questionnaire, the accuracy of measurement of physical behaviors (physical activity, sedentary behavior and sleep) is not high. With the development of technology, wearable devices (e.g. accelerometer) can be used for more accurate measurement of physical behaviors and have great application potential in large-scale research. However, the data of objective measurement of physical behaviors from large-scale cohort research in Asian populations is still limited. Between August 2020 and December 2021, the 3rd resurvey of China Kadoorie Biobank (CKB) project used Axivity AX3 wrist triaxial accelerometer to collect the data of participants' daily activity and sleep status. A total of 20 370 participants from 10 study areas were included in the study, in whom 65.2% were women, and the age was (65.4±9.1) years. The participants' physical activity level varied greatly in different study areas. The objective measurement of participants' physical behaviors in CKB project has provided valuable resources for the description of 24-hour patterns of physical behaviors and evaluation of the health effect of physical activity, sedentary behavior and sleep as well as their association with diseases in the elderly in China.
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Affiliation(s)
- Y Y Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191,China
| | - Y L Ke
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191,China
| | - J Lyu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191,China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191,China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191,China
| | - D J Y Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191,China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191,China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191,China
| | - L Pan
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191,China
| | - P Pei
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191,China
| | - H D Du
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford OX3 7LF, United Kingdom Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, United Kingdom
| | - J S Chen
- China National Center for Food Safety Risk Assessment, Beijing 100022, China
| | - Z M Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, United Kingdom
| | - L M Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191,China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191,China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191,China
| | - D O H E R T Y Doherty
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, United Kingdom Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, United Kingdom
| | - C Q Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191,China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191,China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191,China
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Yang HM, Zhao YX, Lyu J, Yu CQ, Guo Y, Pei P, Du HD, Chen JS, Chen ZM, Sun DJY, Li LM. [Study on the associations of meeting intensive systolic blood pressure control goals with risk for incident cardiovascular and cerebrovascular diseases among the adult hypertensive patients in China]. Zhonghua Liu Xing Bing Xue Za Zhi 2023; 44:1175-1182. [PMID: 37661606 DOI: 10.3760/cma.j.cn112338-20230317-00156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
Objective: To evaluate the associations of meeting intensive systolic blood pressure (SBP) control goals with risk for incident cardiovascular and cerebrovascular diseases among the adult hypertensive patients in China. Methods: We used data from adult hypertensive patients from the China Kadoorie Biobank. logistic regression models evaluated the influencing factors of meeting intensive and standard SBP control goals. Cox proportional hazard models evaluated the associations between meeting intensive vs. standard SBP control goals and risk for incident cardiovascular and cerebrovascular diseases. Results: A total of 3 628 hypertensive patients who reported continuous medication use were included in this study, of which 5.0% of the participants met the goals of intensive SBP control (≤130 mmHg). Participants with higher educational attainment (OR=2.36,95%CI: 1.32-4.04), healthier diet (OR=2.09,95%CI: 1.45-2.96), daily intake of fresh fruit (OR=1.67,95%CI: 1.17-2.36) and combination treatment (OR=1.82,95%CI: 1.03-3.09) were more likely to meet intensive SBP control goal after adjustment of age, sex and urban/rural areas. During an average follow-up of (10.0±3.7) years, 1 278 cases of composite cardiovascular outcome were recorded. This study did not find a statistical correlation between achieving the goal of enhanced SBP control and the occurrence of composite cardiovascular and cerebrovascular outcomes (HR=0.89, 95%CI: 0.63-1.25). For major adverse cardiovascular events (MACE), cerebrovascular diseases, stroke, and ischemic stroke, we observed a trend of decrease in risk of outcomes with more intensive SBP control (trend test P<0.05). Conclusions: We observed decreased risk for MACE and cerebrovascular diseases with more intensive SBP control. However, there was no significant risk reduction for cardiovascular and cerebrovascular diseases when meeting the intensive SBP control goal, compared to the standard SBP control goal.
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Affiliation(s)
- H M Yang
- Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Y X Zhao
- Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - J Lyu
- Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
| | - C Q Yu
- Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
| | - Y Guo
- Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing 100037, China
| | - P Pei
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
| | - H D Du
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford OX3 7LF, United Kingdom Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, United Kingdom
| | - J S Chen
- China National Center for Food Safety Risk Assessment, Beijing 100022, China
| | - Z M Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, United Kingdom
| | - D J Y Sun
- Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
| | - L M Li
- Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
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Song MY, Zhao YX, Han YT, Lyu J, Yu CQ, Pei P, Du HD, Chen JS, Chen ZM, Sun DJY, Li LM. [Epidemiological distribution characteristics of peripheral blood mosaic chromosomal alteration in adults from 10 regions of China]. Zhonghua Liu Xing Bing Xue Za Zhi 2023; 44:1021-1026. [PMID: 37482702 DOI: 10.3760/cma.j.cn112338-20230306-00129] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 07/25/2023]
Abstract
Objective: To describe the epidemiological distribution characteristics of peripheral blood mosaic chromosomal alteration (mCA) in community adults aged 30-79 years in 10 regions of China. Methods: A total of 100 297 participants with complete baseline information (demographic characteristics, lifestyle, physical examination, etc.) and genotyping data of blood-derived DNA in ten regions of the China Kadoorie Biobank study were included. The mCAs were detected with the Mosaic Chromosomal Alterations pipeline, and logistic regression models were used to compare the differences in the detection rate of mCAs in different regions and populations. Results: A total of 5 810 mCA carriers were detected, with the detection rate of 5.8%. The standardized detection rate was 5.1%. The baseline detection rate of mCA increased with age, which were 3.4%, 5.0%, and 9.4% in those aged 30-, 51-, and >60 years, respectively (trend test P<0.001). A more significant proportion of mCAs were found in men (8.0%) than women (4.0%), as well as in urban areas (6.4%) than in rural areas (5.3%), the difference was significant (P<0.001). After adjusting for age and gender, the detection rate of mCA was higher in current smokers or people quitting smoking due to illness and people with low physical activity level, and the mCA detection rate was lower in obesy people (5.3%) than that in people with normal body weight (5.9%) (P=0.006). Conclusions: The detection rate of mCAs varied with region and population in community adults aged 30-79 years in 10 regions of China. The study results might contribute to the molecular identification of aging populations and guide precision prevention of age-related diseases such as cancers.
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Affiliation(s)
- M Y Song
- Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Y X Zhao
- Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Y T Han
- Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - J Lyu
- Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
| | - C Q Yu
- Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
| | - P Pei
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
| | - H D Du
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford OX3 7LF, United Kingdom Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, United Kingdom
| | - J S Chen
- China National Center for Food Safety Risk Assessment, Beijing 100022, China
| | - Z M Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, United Kingdom
| | - D J Y Sun
- Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
| | - L M Li
- Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
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Wang X, Shi KX, Yu CQ, Lyu J, Guo Y, Pei P, Xia QM, Du HD, Chen JS, Chen ZM, Li LM. [Prevalence of chronic kidney disease and its association with lifestyle factors in adults from 10 regions of China]. Zhonghua Liu Xing Bing Xue Za Zhi 2023; 44:386-392. [PMID: 36942332 DOI: 10.3760/cma.j.cn112338-20220801-00680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 03/23/2023]
Abstract
Objective: To investigate the distribution of chronic kidney disease (CKD) in participants from the China Kadoorie Biobank (CKB) study and evaluate the association between lifestyle risk factors and CKD. Methods: Based on the baseline survey data and follow-up data (as of December 31, 2018) of the CKB study, the differences in CKD cases' area and population distributions were described. Cox proportional hazards regression model was used to estimate the association between lifestyle risk factors and the risk of CKD. Results: A total of 505 147 participants, 4 920 cases of CKD were recorded in 11.26 year follow up with a incidence rate of 83.43/100 000 person-years. Glomerulonephropathy was the most common type. The incidence of CKD was higher in the urban area, men, and the elderly aged 60 years and above (87.83/100 000 person-years, 86.37/100 000 person-years, and 132.06/100 000 person-years). Current male smokers had an increased risk for CKD compared with non-smokers or occasional smokers (HR=1.18, 95%CI: 1.05-1.31). The non-obese population was used as a control group, both general obesity determined by BMI (HR=1.19, 95%CI: 1.10-1.29) and central obesity determined by waist circumference (HR=1.27, 95%CI: 1.19-1.35) were associated with higher risk for CKD. Conclusion: The risks for CKD varied with area and population in the CKB cohort study, and the risk was influenced by multiple lifestyle factors.
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Affiliation(s)
- X Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191,China
| | - K X Shi
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191,China
| | - C Q Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191,China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191,China
| | - J Lyu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191,China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191,China
| | - Y Guo
- Fuwai Hospital, Chinese Academy of Medical Sciences, National Center for Cardiovascular Diseases, Beijing 100037, China
| | - P Pei
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Q M Xia
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - H D Du
- Nuffield Department of Population Health, Center for Clinical and Epidemiological Studies, University of Oxford, Oxford OX3 7LF, UK
| | - J S Chen
- China National Center for Food Safety Risk Assessment, Beijing 100022, China
| | - Z M Chen
- Nuffield Department of Population Health, Center for Clinical and Epidemiological Studies, University of Oxford, Oxford OX3 7LF, UK
| | - L M Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191,China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191,China
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Wen QR, Zhu YQ, Lyu J, Guo Y, Pei P, Yang L, Du HD, Chen YP, Chen JS, Yu CQ, Chen LM, Li L. [Characteristics of daytime napping and its correlation with chronic diseases in Chinese adults]. Zhonghua Liu Xing Bing Xue Za Zhi 2022; 43:1869-1874. [PMID: 36572456 DOI: 10.3760/cma.j.cn112338-20220108-00016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Objective: To describe the prevalence of daytime nap habit in participants of the China Kadoorie Biobank (CKB) study, across 10 study regions and explore its correlation with prevalence of major chronic diseases. Methods: Participants with a self-reported pre-diagnosis of any cancer at baseline survey were excluded. Logistic regression models were used to analyze the differences in study regions and age distribution of the prevalence daytime nap habit, and its correlation with the prevalence of diabetes, hypertension, coronary heart disease (CHD), stroke, chronic obstructive pulmonary disease (COPD), and chronic liver diseases. Results: Among 510 145 participants, 39.9% had daytime nap habit in summer and 20.8% had daytime nap habit all the year round. Urban-rural differences were observed in the prevalence of summer nap habit and perennial nap habit. Daytime nap in summer was common in rural areas and Suzhou, with prevalence ranged from 32.9% to 73.3%. Haikou and Liuzhou had higher prevalence of perennial nap (60.4% and 63.3%). The proportion of people with daytime nap habit all the year round increased with age (P for trend <0.001), the proportion was highest in those aged 70- years (31.9%). Daytime nap habit in summer was positively correlated with the prevalence of diabetes, hypertension, CHD and chronic liver disease with OR of 1.10 (95%CI: 1.07-1.14), 1.03 (95%CI:1.02-1.05), 1.07 (95%CI: 1.02-1.12) and 1.07 (95%CI:1.00-1.14), respectively. Daytime nap habit all the year round was positively correlated with the prevalence of diabetes, hypertension, CHD, stroke, COPD and chronic liver disease with OR of 1.33 (95%CI: 1.29-1.37), 1.11 (95%CI: 1.09-1.13), 1.39 (95%CI: 1.33-1.45), 1.33 (95%CI: 1.26-1.41), 1.12 (95%CI: 1.08-1.16) and 1.27 (95%CI:1.18-1.37) respectively. Conclusion: There were regional and age differences in prevalence of daytime nap habit among CKB participants. Daytime nap habit, especially daytime nap habit all the year round, was positively correlated with the prevalence of major chronic diseases.
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Affiliation(s)
- Q R Wen
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Y Q Zhu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - J Lyu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
| | - Y Guo
- Fuwai Hospital, Chinese Academy of Medical Sciences, National Center for Cardiovascular Diseases, Beijing 100037, China
| | - P Pei
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
| | - L Yang
- Nuffield Department of Population Health, Center for Clinical and Epidemiological Studies, University of Oxford, Oxford OX3 7LF, UK Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - H D Du
- Nuffield Department of Population Health, Center for Clinical and Epidemiological Studies, University of Oxford, Oxford OX3 7LF, UK Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Y P Chen
- Nuffield Department of Population Health, Center for Clinical and Epidemiological Studies, University of Oxford, Oxford OX3 7LF, UK Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - J S Chen
- China National Center for Food Safety Risk Assessment, Beijing 100022, China
| | - C Q Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
| | - L M Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
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Zhu YQ, Fan JN, Yu CQ, Lyu J, Guo Y, Pei P, Xia QM, Du HD, Chen YP, Chen JS, Chen ZM, Li LM. [Correlation between sleep status and frailty in adults aged 30-79 years in China]. Zhonghua Liu Xing Bing Xue Za Zhi 2022; 43:1349-1356. [PMID: 36117338 DOI: 10.3760/cma.j.cn112338-20220110-00018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Objective: To explore the correlation between sleep status and frailty in adults aged 30-79 years in China, and explore the potential effect modification of general and central obesity. Methods: Based on the baseline data of the China Kadoorie Biobank, we used multinomial logistic regression to analyze the correlation between long and short sleep duration, insomnia disorder, snoring, and unhealthy sleep score with risks of pre-frailty and frailty. Both overall and obesity-stratified analyses were performed. Result: Among the 512 724 participants, 2.3% had frailty and 40.1% had pre-frailty. There was a U-shaped relationship between sleep duration and frailty score. Short (OR=1.21, 95%CI: 1.19-1.23) or long sleep duration (OR=1.19, 95%CI: 1.17-1.21), insomnia disorder (OR=2.09, 95%CI: 2.02-2.17), and snoring (OR=1.61, 95%CI: 1.59-1.63) were all positively correlated with pre-frailty, and dose-response relationships were observed between unhealthy sleep score and pre-frailty (P for trend<0.001), with OR values of 1.46 (1.44-1.48), 1.97 (1.93-2.00) and 3.43 (3.21-3.67) respectively for those having unhealthy sleep score of 1 to 3. These sleep problems were also positively correlated with frailty. Compared with the overweight or obesity group, stronger relationships were observed between short sleep duration and frailty or pre-frailty and between insomnia disorder and pre-frailty, while the relationships between snoring and frailty and pre-frailty were weaker in the participants with normal weight (P for interaction <0.007 for all). We also observed similar effect modification by central obesity. Conclusion: Long or short sleep duration, insomnia disorder, snoring and higher unhealthy sleep scores were positively correlated with pre-frailty or frailty, general and central obesity status could modify the relationships.
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Affiliation(s)
- Y Q Zhu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - J N Fan
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - C Q Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
| | - J Lyu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
| | - Y Guo
- Fuwai Hospital, Chinese Academy of Medical Sciences, National Center for Cardiovascular Diseases, Beijing 100037, China
| | - P Pei
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Q M Xia
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - H D Du
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford OX3 7LF, UK Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Y P Chen
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford OX3 7LF, UK Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - J S Chen
- China National Center for Food Safety Risk Assessment, Beijing 100022, China
| | - Z M Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - L M Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
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Wang WX, Huang NH, Lyu J, Yu CQ, Guo Y, Pei P, Du HD, Chen JS, Chen ZM, Huang T, Li L. [Association between genetic predisposition to childhood obesity and the risk of adult ischemic heart disease in China]. Zhonghua Liu Xing Bing Xue Za Zhi 2022; 43:445-451. [PMID: 35443296 DOI: 10.3760/cma.j.cn112338-20210413-00309] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Objective: To examine the associations of childhood obesity, assessed by genetic variations of childhood body mass index (BMI), with the risk of adult ischemic heart disease (IHD) and major coronary event (MCE). Methods: More than 69 000 participants from the China Kadoorie Biobank were genotyped. After excluding those with coronary heart disease, stroke, or cancer at baseline, a total of 64 454 participants were included in this study. Based on genome-wide significant single nucleotide polymorphisms (SNPs), childhood BMI genetic risk score were constructed for every participant and divided into quintiles, with the lowest quintile as the low genetic risk group and the highest quintile as the high genetic risk group. Cox proportional hazards regression models were used to estimate the association between genetic predisposition to childhood obesity and the risk of ischemic heart disease. Results: During a median of 10.7 years of follow-up, 7 073 incident cases of IHD and 1 845 cases of MCE were documented. After adjusting for sex, age, region, and the first ten genetic principal components, the HRs (95%CIs) for IHD and MCE in the high genetic risk group were 1.10 (1.02-1.18) and 1.10 (0.95-1.27), compared with the low genetic risk group. IHD risk increased by 4% (2%-6%) for each one standard deviation increase in genetic risk score (trend P=0.001). After further adjustment for baseline BMI, the differences between genetic risk groups were not statistically significant, but there was still a linear trend between genetic risk score and IHD risk (trend P=0.019). Conclusions: IHD risk increased with genetic predisposition to childhood obesity, suggesting that childhood obesity is an important risk factor for the development of IHD in China. As an easily identifiable feature, changes of childhood BMI should be monitored regularly to realize early intervention of IHD in adults.
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Affiliation(s)
- W X Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Beijing 100191, China
| | - N H Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Beijing 100191, China
| | - J Lyu
- Department of Epidemiology and Biostatistics, School of Public Health, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China Key Laboratory of Molecular Cardiovascular Sciences, Ministry of Education, Beijing 100191, China
| | - C Q Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
| | - Y Guo
- Fuwai Hospital Chinese Academy of Medical Sciences, National Center for Cardiovascular Diseases, Beijing 100037, China
| | - P Pei
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - H D Du
- Medical Research Council Population Health Research Unit/Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - J S Chen
- China National Center for Food Safety Risk Assessment, Beijing 100022, China
| | - Z M Chen
- Medical Research Council Population Health Research Unit/Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - T Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Beijing 100191, China
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
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11
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Pan L, Wu M, Wen QR, Lyu J, Guo Y, Pei P, Du HD, Chen JS, Yu CQ, Chen LM, Li L. [The correlation of physical activity and sedentary leisure time with low muscle mass, strength, and quality in Chinese adults]. Zhonghua Liu Xing Bing Xue Za Zhi 2022; 43:162-168. [PMID: 35184479 DOI: 10.3760/cma.j.cn112338-20210402-00273] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Objective: To explore the relationship of physical activity and sedentary leisure time with muscle mass, strength, and quality in Chinese adults. Methods: Based on the second resurvey of China Kadoorie Biobank (CKB) in 2013-2014, logistic regression models were used to analyze the correlation of physical activity and sedentary leisure time with low muscle mass, grip strength, and muscle quality. Results: A total of 24 245 participants were included in the analysis. The average daily physical activity level was (18.3±13.8) MET-h/d, and the sedentary leisure time was (4.4±1.9) hours. We took the lowest physical activity quartile as the reference and found that the participants' physical activity was negatively correlated to low muscle mass, strength, and quality. The ORs (95%CIs) of low appendicular skeletal muscle mass index (ASMI), low total skeletal muscle mass index (TSMI), low grip strength and low arm muscle quality (AMQ) were 0.68 (0.60-0.77), 0.66 (0.58-0.75), 0.82 (0.72-0.94) and 0.84 (0.74-0.95), respectively. The subtypes of physical activity, including those related to work, transportation, housework, and leisure, also showed negative correlations with low muscle mass, strength, and quality to varying degrees. Compared with participants with the shortest sedentary leisure time, those who had the longest were more likely to have low TSMI (OR=1.13, 95%CI: 0.99-1.30). Conclusions: Physical activity was negatively correlated with a lower risk of low muscle mass and strength, while longer sedentary leisure time positively correlated with low muscle mass.
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Affiliation(s)
- L Pan
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Preparedness and Response/Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education,Beijing 100191, China
| | - M Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Preparedness and Response/Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education,Beijing 100191, China
| | - Q R Wen
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Preparedness and Response/Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education,Beijing 100191, China
| | - J Lyu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Preparedness and Response/Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education,Beijing 100191, China
| | - Y Guo
- Fuwai Hospital Chinese Academy of Medical Sciences, National Center for Cardiovascular Diseases, Beijing 100037, China
| | - P Pei
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - H D Du
- Nuffield Department of Population Health, Center for Clinical and Epidemiological Studies/Population Health Research Unit, Medical Research Council, University of Oxford, Oxford OX3 7LF, UK
| | - J S Chen
- China National Center for Food Safety Risk Assessment, Beijing 100022, China
| | - C Q Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Preparedness and Response/Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education,Beijing 100191, China
| | - L M Chen
- Nuffield Department of Population Health, Center for Clinical and Epidemiological Studies/Population Health Research Unit, Medical Research Council, University of Oxford, Oxford OX3 7LF, UK
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Preparedness and Response/Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education,Beijing 100191, China
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12
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Wen QR, Liu Q, Lyu J, Guo Y, Pei P, Yang L, Du HD, Chen YP, Chen JS, Yu CQ, Chen LM, Li L. [Spicy food consumption and risk of lip, oral cavity and pharynx cancers: a prospective cohort study of Chinese adults]. Zhonghua Liu Xing Bing Xue Za Zhi 2022; 43:169-174. [PMID: 35184480 DOI: 10.3760/cma.j.cn112338-20210616-00475] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Objective: To explore the association of spicy food consumption and risk of lip, oral cavity, and pharynx cancers (LOCPs) in Chinese adults. Methods: Based on the baseline survey and long-term follow-up of the China Kadoorie Biobank (CKB) study, Cox proportional hazard regression models were used to estimate hazard ratios (HR) and 95% confidence intervals (95%CI) for associations between spicy food consumption and LOCPs incidence. Results: Of the 510 145 participants included at baseline, 30.1% reported daily spicy food consumption. During a mean follow-up of 10.8 (2.0) years, we documented 767 LOCPs cases. Multivariate adjusted analyses showed that the risk of LOCPs incidence decreased with the frequency of spicy food intake (trend P=0.003), with HR of 0.69 (95%CI:0.54-0.88) for daily spicy food consumers, compared with never or occasional consumers. Participants who preferred moderate pungency degrees had the lowest risk of LOCPs, with a 33%[0.67(95%CI:0.52-0.87)] reduced risk compared to those who consumed spicy food less than once per week. The later the starting age, the lower the risk (trend P=0.004). Those who started eating spicy food after 18 years old had the lowest risk of LOCPs incidence, with adjusted HR (95%CI) of 0.70(0.54-0.92). Conclusions: Spicy food intake might be associated with a decreased risk of LOCPs incidence. Such association was independent of healthy lifestyles. Advocating moderate-pungency spicy food consumption and healthy lifestyles might help prevent LOCPs.
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Affiliation(s)
- Q R Wen
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Preparedness and Response/Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education,Beijing 100191, China
| | - Q Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Preparedness and Response/Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education,Beijing 100191, China
| | - J Lyu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Preparedness and Response/Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education,Beijing 100191, China
| | - Y Guo
- Fuwai Hospital Chinese Academy of Medical Sciences, National Center for Cardiovascular Diseases, Beijing 100037, China
| | - P Pei
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - L Yang
- Nuffield Department of Population Health, Center for Clinical and Epidemiological Studies/Population Health Research Unit, Medical Research Council, University of Oxford, Oxford OX3 7LF, UK
| | - H D Du
- Nuffield Department of Population Health, Center for Clinical and Epidemiological Studies/Population Health Research Unit, Medical Research Council, University of Oxford, Oxford OX3 7LF, UK
| | - Y P Chen
- Nuffield Department of Population Health, Center for Clinical and Epidemiological Studies/Population Health Research Unit, Medical Research Council, University of Oxford, Oxford OX3 7LF, UK
| | - J S Chen
- China National Center for Food Safety Risk Assessment, Beijing 100022, China
| | - C Q Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Preparedness and Response/Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education,Beijing 100191, China
| | - L M Chen
- Nuffield Department of Population Health, Center for Clinical and Epidemiological Studies/Population Health Research Unit, Medical Research Council, University of Oxford, Oxford OX3 7LF, UK
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Preparedness and Response/Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education,Beijing 100191, China
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13
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Wen QR, Wu M, Pan L, Lyu J, Guo Y, Pei P, Du HD, Chen JS, Yu CQ, Chen LM, Li L. [The correlation of sleep duration and insomnia with low muscle mass, strength and quality in Chinese adults]. Zhonghua Liu Xing Bing Xue Za Zhi 2022; 43:175-182. [PMID: 35184481 DOI: 10.3760/cma.j.cn112338-20201020-01252] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Objective: To explore the relationship of sleep duration and insomnia with muscle mass, strength, and quality in Chinese adults. Methods: Based on the second resurvey of China Kadoorie Biobank (CKB) in 2013-2014, logistic regression models were used to analyze the correlation of sleep duration, insomnia, and its duration with low muscle mass, handgrip strength, and muscle quality. Results: The average sleep duration of the study population was (7.4±1.5) hours. Morbidities of short sleep duration (<6 hours), long sleep duration (≥9 hours), and insomnia were 9.3%,17.4%,and 29.9%,respectively. Compared with those who slept for 7- hours, those who slept for ≥9 hours were more likely to have low muscle mass, low handgrip strength,and low arm muscle quality (AMQ), and the OR (95%CI) of low appendicular skeletal muscle mass index (ASMI), low total skeletal muscle mass index (TSMI), low grip strength and low AMQ were 1.32 (1.18-1.48),1.26 (1.13-1.41), 1.33 (1.18-1.49) and 1.16 (1.03-1.30), respectively. Compared with participants without insomnia, insomnia patients were more likely to have low muscle mass,and the longer the duration of insomnia,the higher the risk (P for trend <0.001). Participants who reported <6 hours sleep duration and insomnia had a higher proportion of low ASMI and low TSMI,compared with those who slept for 7- hours and without insomnia, the OR (95%CI) were 1.26 (1.08-1.47) and 1.25 (1.07-1.46), respectively. Conclusions: Participants who reported ≥9 hours sleep duration were more likely to have low muscle mass,low handgrip strength,and low AMQ. Participants with insomnia had lower muscle mass, and the longer the duration of insomnia, the higher the proportion of low ASMI and low TSMI.
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Affiliation(s)
- Q R Wen
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Preparedness and Response/Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education, Beijing 100191, China
| | - M Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Preparedness and Response/Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education, Beijing 100191, China
| | - L Pan
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Preparedness and Response/Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education, Beijing 100191, China
| | - J Lyu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Preparedness and Response/Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education, Beijing 100191, China
| | - Y Guo
- Fuwai Hospital Chinese Academy of Medical Sciences, National Center for Cardiovascular Diseases, Beijing 100037,China
| | - P Pei
- Chinese Academy of Medical Sciences,Beijing 100730,China
| | - H D Du
- Nuffield Department of Population Health, Center for Clinical and Epidemiological Studies/Population Health Research Unit, Medical Research Council, University of Oxford, Oxford OX3 7LF, UK
| | - J S Chen
- China National Center for Food Safety Risk Assessment, Beijing 100022, China
| | - C Q Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Preparedness and Response/Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education, Beijing 100191, China
| | - L M Chen
- Nuffield Department of Population Health, Center for Clinical and Epidemiological Studies/Population Health Research Unit, Medical Research Council, University of Oxford, Oxford OX3 7LF, UK
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Preparedness and Response/Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education, Beijing 100191, China
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14
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Wen QR, Wu M, Liu Q, Lyu J, Guo Y, Bian Z, Pei P, Du HD, Chen JS, Yu CQ, Chen ZM, Li LM. [Correlation between chronic diseases and low muscle mass, strength and quality in adults in China]. Zhonghua Liu Xing Bing Xue Za Zhi 2021; 42:1948-1954. [PMID: 34818839 DOI: 10.3760/cma.j.cn112338-20200910-01146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Objective: To explore the correlation between chronic diseases and muscle mass, strength and quality in adults in China. Methods: Based on the second resurvey of China Kadoorie Biobank (CKB) in 2013-2014, logistic regression models were used to analyze the correlation of different types, number and duration of chronic diseases with low muscle mass, handgrip strength and muscle quality. Results: The prevalence rate of diabetes, coronary heart disease (CHD), stroke and chronic obstructive pulmonary disease (COPD) were 9.6%, 5.8%, 3.2% and 26.8%, respectively, and 38.8% of the participants had at least one disease, and they were more likely to have low handgrip strength and low arm muscle quality (AMQ), and the longer the chronic diseases duration, the higher the risk. The ORs (95%CIs) for low handgrip strength and low AMQ in patients with 1 chronic disease for more than 10 years was 1.64 (1.42-1.90) and 1.83 (1.60-2.10), respectively. The ORs (95%CIs) for low handgrip strength were 1.26 (1.17-1.37), 1.42 (1.23-1.64) and 2.27 (1.55-3.32) and the ORs (95%CIs) for low AMQ were 1.28 (1.18-1.38), 1.67 (1.46-1.92) and 2.41(1.69-3.45), respectively, in patients with 1, 2, ≥3 chronic diseases, the correlation showed a linear trend (P for trend <0.001). Diabetes, CHD and stroke were positively correlated with low handgrip strength and low AMQ. Compared with participants without COPD, COPD patients were more likely to have low appendicular skeletal muscle mass index (ASMI), low total skeletal muscle mass index (TSMI) and low handgrip strength, and the risk was positively correlated with disease duration. Conclusions: Patients with chronic diseases were more likely to have lower muscle strength and muscle quality, especially the patients with multi diseases and longer disease duration. The proportion of low handgrip strength and low AMQ was higher in patients who reported multi-prevalence and longer duration of chronic diseases.
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Affiliation(s)
- Q R Wen
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - M Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Q Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - J Lyu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Y Guo
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Z Bian
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - P Pei
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - H D Du
- Nuffield Department of Population Health, Center for Clinical and Epidemiological Studies, University of Oxford, Oxford OX3 7LF, UK
| | - J S Chen
- China National Center for Food Safety Risk Assessment, Beijing 100022, China
| | - C Q Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Z M Chen
- Nuffield Department of Population Health, Center for Clinical and Epidemiological Studies, University of Oxford, Oxford OX3 7LF, UK
| | - L M Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
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Fan JN, Sun ZJ, Yu CQ, Guo Y, Sun DJY, Pei P, Du HD, Chen JS, Chen ZM, Lyu J, Li LM. [Comparison of Fried phenotype and frailty index and their associations with risk of mortality]. Zhonghua Liu Xing Bing Xue Za Zhi 2021; 42:1179-1187. [PMID: 34814528 DOI: 10.3760/cma.j.cn112338-20210310-00192] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Objective: To compare the consistency of frailty status measured by Fried phenotype and frailty index composed of different numbers of deficits, and their prospective associations with risk of mortality. Methods: Data of 23 615 participants from the second resurvey of the China Kadoore Biobank (CKB) was used. Fried phenotype was constructed using five phenotypes, and frailty indexes (FI) were constructed using 28 and 40 deficits, respectively. We calculated the Weighted Kappa coefficient to compare the consistency of three measures in the classification of frailty status. Cox regression was performed to analyze the association of frailty status with risk of mortality. Results: The frailty prevalence calculated by Fried phenotype, FI-28, and FI-40 were 5.4%, 7.9%, and 4.0%, respectively. The Kappa coefficients of Fried phenotype with FI-28 and FI-40 were 0.357 and 0.408, respectively. The Kappa coefficients of FI-28 and FI-40 was 0.712. During an average of (3.9±0.5) years of follow-up, 755 participants died. When Fried phenotype was used, compared with the robust participants, the prefrail and frail participants had increased risk of mortality, the multivariable-adjusted HRs were 1.60 (95%CI: 1.32-1.94) and 2.90 (95%CI: 2.25-3.73), respectively. When FI-28 was used, the corresponding HRs were 1.71 (95%CI: 1.39-2.11) and 2.52 (95%CI:1.95-3.27) for prefrail and frail participants, and when FI-40 was used, the corresponding HRs were 1.98 (95%CI:1.60-2.44) and 3.71 (95%CI: 2.80-4.91). The association of frailty status with mortality differed in different age groups, with the association stronger in younger adults than in older adults. Conclusion: Fried phenotype and frailty index constituted with different numbers of deficits showed good consistency; which can be used to well predict the risk of mortality.
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Affiliation(s)
- J N Fan
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Preparedness & Response/Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education, Beijing 100191, China
| | - Z J Sun
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Preparedness & Response/Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education, Beijing 100191, China
| | - C Q Yu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Preparedness & Response/Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education, Beijing 100191, China
| | - Y Guo
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - D J Y Sun
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Preparedness & Response/Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education, Beijing 100191, China
| | - P Pei
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - H D Du
- Medical Research Council Population Health Research Unit at the University of Oxford/Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - J S Chen
- China National Center for Food Safety Risk Assessment, Beijing 100022, China
| | - Z M Chen
- Medical Research Council Population Health Research Unit at the University of Oxford/Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - J Lyu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Preparedness & Response/Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education, Beijing 100191, China
| | - L M Li
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Preparedness & Response/Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education, Beijing 100191, China
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16
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Yang RT, Han YT, Lyu J, Yu CQ, Guo Y, Bian Z, Pei P, Du HD, Chen JS, Chen ZM, Huang T, Li LM. [Prevalence of heart failure and its association with smoking behavior in adults from 10 regions of China]. Zhonghua Liu Xing Bing Xue Za Zhi 2021; 42:787-793. [PMID: 34814468 DOI: 10.3760/cma.j.cn112338-20200703-00916] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Objective: To describe the prevalence of heart failure in China and to explore the prospective association between smoking behavior and the risk of incident heart failure. Methods: The subjects were from the China Kadoorie Biobank (CKB) and the baseline survey was conducted from June 2004 to July 2008. A total of 487 197 subjects were included in this study, after excluding those with missing BMI information, lost follow-up immediately after baseline investigation, and self-reported coronary heart disease, stroke, or malignant tumor at baseline. This study included data from baseline and follow-up until December 31, 2016. Cox proportional hazards regression models were used to estimate the association between smoking behavior and the risk of heart failure. Results: The median follow-up time was 10.15 years, during which a total of 4 208 new cases of heart failure occurred, with a crude incidence rate of 0.87/1 000 person-years and a cumulative incidence rate of 0.86%. The higher the age at baseline, the higher the incidence of heart failure. The incidence of heart failure in high age group, rural area and male was higher than that in low age group, urban area and female population respectively. Compared with non-smokers, there was no significant difference in the risk of heart failure in occasional smokers (HR=1.05; 95%CI: 0.91-1.22), while former smokers (HR=1.48; 95%CI:1.31-1.67) and current smokers (HR=1.34;95%CI:1.22-1.49) increased risk. Former smokers (HR=1.33;95%CI:1.21-1.46) and current smokers (HR=1.46; 95%CI:1.31-1.64) had higher risk of heart failure than non-smokers or occasional smokers. No dose-response relationship was observed between the number of cigarettes smoked per day and the risk of heart failure in current and former smokers (for trend P=0.347 and 0.066). Compared with non-smokers or occasional smokers, the hazard ratios of <5, 5-, 10- and ≥20 years since quit smoking were 1.61 (95%CI: 1.36-1.92), 1.55 (95%CI: 1.27-1.90), 1.24 (95%CI: 1.02-1.51) and 1.35 (95%CI: 1.08-1.68), respectively (for trend P=0.091). The hazard ratios of quitting smoking due to disease and other reasons were 1.62 (95%CI:1.41-1.86) and 1.23 (95%CI: 1.04-1.45). Healthy smoking behaviors had a significant protective effect on heart failure compared with non-healthy smoking behaviors (HR=0.75, 95%CI:0.69-0.81). Area and family history of coronary heart disease, and the smoking behaviors interacted with the risk of heart failure (for all interactions were P<0.05). Conclusions: The incidence of heart failure in China is higher in males than females, higher in rural areas than in urban areas, and increases with age. Both former smokers and current smokers had a higher risk of heart failure than nonsmokers or occasional smokers, regardless of the frequency, amount, duration, and reason for quitting. Smoking is an important risk factor for heart failure and comprehensive anti-smoking measures should be maintained.
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Affiliation(s)
- R T Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Preparedness & Response/Peking University Key Laboratory of Molecular Cardiovascular Sciences, Ministry of Education, Peking University, Beijing 100191, China
| | - Y T Han
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Preparedness & Response/Peking University Key Laboratory of Molecular Cardiovascular Sciences, Ministry of Education, Peking University, Beijing 100191, China
| | - J Lyu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Preparedness & Response/Peking University Key Laboratory of Molecular Cardiovascular Sciences, Ministry of Education, Peking University, Beijing 100191, China
| | - C Q Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Preparedness & Response/Peking University Key Laboratory of Molecular Cardiovascular Sciences, Ministry of Education, Peking University, Beijing 100191, China
| | - Y Guo
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Z Bian
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - P Pei
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - H D Du
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health/Medical Research Council Population Health Research Unit, University of Oxford, Oxford OX3 7LF, UK
| | - J S Chen
- China National Center for Food Safety Risk Assessment, Beijing 100022, China
| | - Z M Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health/Medical Research Council Population Health Research Unit, University of Oxford, Oxford OX3 7LF, UK
| | - T Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Preparedness & Response/Peking University Key Laboratory of Molecular Cardiovascular Sciences, Ministry of Education, Peking University, Beijing 100191, China
| | - L M Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Preparedness & Response/Peking University Key Laboratory of Molecular Cardiovascular Sciences, Ministry of Education, Peking University, Beijing 100191, China
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17
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Sun ZJ, Fan JN, Yu CQ, Guo Y, Bian Z, Pei P, Du HD, Chen JS, Chen ZM, Lyu J, Li LM. [Prevalence, patterns and long-term changes of multimorbidity in adults from 10 regions of China]. Zhonghua Liu Xing Bing Xue Za Zhi 2021; 42:755-762. [PMID: 34814464 DOI: 10.3760/cma.j.cn112338-20200305-00259] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Objective: To describe the prevalence of multimorbidity and its secular trend, and to explore the common patterns of multimorbidity in Chinese adults. Methods: A total of 25 033 participants who attended the second resurvey of China Kadoorie Biobank (CKB) were included in the study. We used data collected both at baseline (2004-2008) and at resurvey (2013-2014). A total of 13 chronic conditions were included, defined by self-reported, physical examination, and blood sample testing. Multimorbidity was defined as co-existence of two or more chronic conditions. Patterns of multimorbidity were explored using hierarchical cluster analysis. Results: The mean age of participants was (51.5±10.1) years at baseline and (59.5±10.2) years at second resurvey. The prevalence of multimorbidity increased from 33.5% to 58.1% over (8.0±0.8) years of follow-up. The average number of chronic conditions per person increased from 1.15 to 1.82 and all participants increased 0.42 conditions per 5 years on average. Participants who were older, less educated or lived in urban areas had a higher prevalence of multimorbidity and a higher increase in the number of chronic conditions. The increase in the number of chronic conditions was also higher among smokers and heavy alcohol drinkers. The most common multimorbidity pattern in the present population consisted of obesity, hypertension, diabetes, stroke, and heart disease. Conclusions: The prevalence of multimorbidity in Chinese adults is increasing rapidly due to ageing population. Populations of different sociodemographic background and lifestyle habits may have different prevalence of multimorbidity and changes in rates over time.
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Affiliation(s)
- Z J Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Preparedness & Response/Peking University Key Laboratory of Molecular Cardiovascular Sciences, Ministry of Education, Beijing 100191, China
| | - J N Fan
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Preparedness & Response/Peking University Key Laboratory of Molecular Cardiovascular Sciences, Ministry of Education, Beijing 100191, China
| | - C Q Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Preparedness & Response/Peking University Key Laboratory of Molecular Cardiovascular Sciences, Ministry of Education, Beijing 100191, China
| | - Y Guo
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Z Bian
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - P Pei
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - H D Du
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health/Medical Research Council Population Health Research Unit, University of Oxford, Oxford OX3 7LF, UK
| | - J S Chen
- China National Center for Food Safety Risk Assessment, Beijing 100022, China
| | - Z M Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health/Medical Research Council Population Health Research Unit, University of Oxford, Oxford OX3 7LF, UK
| | - J Lyu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Preparedness & Response/Peking University Key Laboratory of Molecular Cardiovascular Sciences, Ministry of Education, Beijing 100191, China
| | - L M Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Preparedness & Response/Peking University Key Laboratory of Molecular Cardiovascular Sciences, Ministry of Education, Beijing 100191, China
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18
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Liu Q, Wu M, Wen QR, Du HD, Lyu J, Guo Y, Bian Z, Pei P, Chen JS, Yu CQ, Chen ZM, Li LM. [The correlation of dietary patterns with low muscle mass, strength and quality in adults from 10 regions of China]. Zhonghua Liu Xing Bing Xue Za Zhi 2021; 42:780-786. [PMID: 34814467 DOI: 10.3760/cma.j.cn112338-20200618-00855] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Objective: To evaluate the correlation of dietary patterns with low muscle mass, strength and quality in Chinese adults. Methods: Based on the second resurvey of China Kadoorie Biobank, factor analysis was conducted to derive dietary patterns from 20 food groups. Low muscle mass, strength, and quality were defined as the sex-specific lowest quintile of appendicular skeletal muscle mass index (ASMI), total skeletal muscle mass index (TSMI), handgrip strength and arm muscle quality (AMQ) according to Asian Working Group for Sarcopenia recommendations. Logistic regression models were used to evaluate the correlation of dietary patterns with low muscle mass, strength, and quality. Results: Two major dietary patterns were extracted. The balanced dietary pattern was characterized by the intake of a variety of foods, whereas the rice-meat dietary pattern was characterized by high intakes of rice, meat, poultry and fish. Individuals who had the highest quintile score of the balanced dietary pattern were less likely to have low TSMI, handgrip strength or AMQ(OR=0.83, 95%CI: 0.74-0.95 for low TSMI; OR=0.64, 95%CI: 0.56-0.74 for low handgrip strength; OR=0.82, 95%CI: 0.72-0.93 for low AMQ; for trend P<0.05). And those who scored higher on the rice-meat dietary pattern had lower risk of low muscle mass and strength (OR=0.67, 95%CI: 0.55-0.82 for low ASMI; OR=0.69, 95%CI: 0.56-0.85 for low TSMI; OR=0.74, 95%CI: 0.60-0.91 for low handgrip strength; for trend P<0.05). Conclusion: Individuals followed the balanced dietary pattern, as well as those who followed the rice-meat dietary pattern, had better levels of skeletal muscle mass, strength and quality.
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Affiliation(s)
- Q Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Pre[aredmess amd Response/Peking University Key Laboratory of Molecular Cardiovascular Sciences, Ministry of Education, Beijing 100191, China
| | - M Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Pre[aredmess amd Response/Peking University Key Laboratory of Molecular Cardiovascular Sciences, Ministry of Education, Beijing 100191, China
| | - Q R Wen
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Pre[aredmess amd Response/Peking University Key Laboratory of Molecular Cardiovascular Sciences, Ministry of Education, Beijing 100191, China
| | - H D Du
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health/Medical Research Council Population Health Research Unit, University of Oxford, Oxford OX3 7LF, UK
| | - J Lyu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Pre[aredmess amd Response/Peking University Key Laboratory of Molecular Cardiovascular Sciences, Ministry of Education, Beijing 100191, China
| | - Y Guo
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Z Bian
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - P Pei
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - J S Chen
- China National Center for Food Safety Risk Assessment, Beijing 100022, China
| | - C Q Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Pre[aredmess amd Response/Peking University Key Laboratory of Molecular Cardiovascular Sciences, Ministry of Education, Beijing 100191, China
| | - Z M Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health/Medical Research Council Population Health Research Unit, University of Oxford, Oxford OX3 7LF, UK
| | - L M Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University/Peking University Center for Public Health and Epidemic Pre[aredmess amd Response/Peking University Key Laboratory of Molecular Cardiovascular Sciences, Ministry of Education, Beijing 100191, China
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Liu Q, Li JC, Du HD, Cao WH, Lyu J, Guo Y, Bian Z, Long ZP, Pei P, Chen JS, Yu CQ, Chen ZM, Li LM. [Regional and demographic differences on passive smoking among non-smokers aged 30-79 years in 10 regions of China]. Zhonghua Liu Xing Bing Xue Za Zhi 2020; 41:1668-1673. [PMID: 33297624 DOI: 10.3760/cma.j.cn112338-20191016-00737] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: To describe the regional and demographic differences on passive non-smokers from 10 regions involved in the China Kadoorie Biobank (CKB) study. Methods: Detailed information regarding passive smoking behaviors related to 317 486 non-smokers who were 30-79 years old from the 10 study regions were gathered and analyzed. Results: Following the standardization of the 2010 China national population, the prevalence rate of passive smoking was 56.7%, and the prevalence rate of living with smokers was 66.5% among the Chinese adults. Both of the aforementioned rates were higher in rural than in urban areas. Meanwhile, the regional distribution of weekly passive smoking frequency and cumulative duration of passive smoking per week and cumulative duration of passive smoking per day were significantly different. The cumulative passive smoking duration per week increased along with the weekly frequency in people living in urban areas. Among women, the weekly passive smoking frequency was the highest, and the cumulative durations per week and per day appeared the lowest in Hunan, opposite to the situation in Henan. The prevalence of passive smoking among participants living with smokers was 2.27 times (95%CI: 2.24-2.29) of those who were not and the association appeared stronger in women (OR=2.61, 95%CI: 2.58-2.64) but not in men (OR=1.01, 95%CI: 0.95-1.06). Almost all the indicators seemed higher in women than those in men, except for the cumulative duration per day. Furthermore, these indicators appeared higher among those who were at younger age or with less education. The prevalence rates of passive smoking and living with smokers were lower but the cumulative duration per day was higher among those with lower household income. And the two rates were higher in married women and lower in married men, as compared to their counterparts. Conclusion: Regional and demographic differences in passive smoking were noticed among study population of CKB in the 10 regions.
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Affiliation(s)
- Q Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - J C Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - H D Du
- Nuffield Department of Population Health, Center for Clinical and Epidemiological Studies, University of Oxford, Oxford OX3 7LF, UK
| | - W H Cao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - J Lyu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Y Guo
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Z Bian
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Z P Long
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - P Pei
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - J S Chen
- China National Center for Food Safety Risk Assessment, Beijing 100022, China
| | - C Q Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Z M Chen
- Nuffield Department of Population Health, Center for Clinical and Epidemiological Studies, University of Oxford, Oxford OX3 7LF, UK
| | - L M Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
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20
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Shen ZW, Sun ZJ, Yu CQ, Guo Y, Bian Z, Pei P, Du HD, Chen JS, Chen ZM, Lyu J, Li LM. [Association between height loss and calcaneus bone mineral density in Chinese adults]. Zhonghua Liu Xing Bing Xue Za Zhi 2020; 41:813-818. [PMID: 32564541 DOI: 10.3760/cma.j.cn112338-20191005-00716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: To examine the association between height loss and calcaneus bone mineral density (BMD) through data gathered from the China Kadoorie Biobank (CKB). Methods: The present study included 24 231 participants who attended the CKB resurvey during 2013-2014, in which calcaneus BMD was measured by quantitative ultrasound method for the first time. Height loss was calculated according to the differences appeared in height measurement between baseline and resurvey. We used linear regression models to estimate the association between height loss and BMD measures. Results: The mean interval between baseline and resurvey was (8.0±0.8 ) years. 33.0% of the participants showed a height loss of ≥1.0 cm, and another 3.7% were with height loss of ≥3.0 cm. After adjustment for potential confounders, there was a linear correlation seen between height loss and BMD (P for all linear trend were <0.001). The βs (95%CIs) for each 1.0 cm of height loss were -0.79 (-0.95--0.63) for broadband ultrasound attenuation (BUA), -2.74 (-3.35--2.13) for speed of sound (SOS), and -1.29 (-1.54--1.04) for stiffness index (SI). Compared with participants with stable height, the multivariate-adjusted βs (95%CIs) for those with height loss of ≥3.0 cm were -3.29 (-4.08--2.50) for BUA, -10.70 (-13.66--7.73) for SOS, and -5.16 (-6.36--3.96) for SI, respectively. According to the subgroup analyses, the association of height loss with BMD measures seemed to be more apparent among females, in those aged ≥55 years, and those being less physically active. Conclusions: BMD became lower with the increase of height loss. Regular height measurement may contribute to the early diagnosis and prevention of osteoporosis.
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Affiliation(s)
- Z W Shen
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Z J Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - C Q Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Y Guo
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Z Bian
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - P Pei
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - H D Du
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - J S Chen
- China National Center for Food Safety Risk Assessment, Beijing 100022, China
| | - Z M Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - J Lyu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; Key Laboratory of Molecular Cardiovascular Sciences, Ministry of Education, Peking University, Beijing 100191, China
| | - L M Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
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Gao M, Wei YX, Lyu J, Yu CQ, Guo Y, Bian Z, Pei P, Du HD, Chen JS, Chen ZM, Huang T, Li LM. [The cut-off points of body mass index and waist circumference for predicting metabolic risk factors in Chinese adults]. Zhonghua Liu Xing Bing Xue Za Zhi 2020; 40:1533-1540. [PMID: 32062911 DOI: 10.3760/cma.j.issn.0254-6450.2019.12.006] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: To assess the association of BMI and waist circumference (WC) with metabolic risk factors, and confirm the appropriate cut-off points of BMI and WC among Chinese adults. Methods: After excluding participants with missing or extreme measurement values, as well as individuals with self-reported histories of cancer, a total of 501 201 adults in baseline and 19 201 adults in the second re-survey from the China Kadoorie Biobank were included. The associations of BMI and WC with metabolic risk factors were estimated. Receiver operating characteristic (ROC) analyses were conducted to assess the appropriate cut-off values of BMI and WC to predict the risk of hypertension, diabetes, dyslipidemia and clustering of risk factors. Results: The prevalence of hypertension, diabetes, dyslipidemia and clustering of risk factors all presented ascending trends with the increasing levels of BMI or WC. Defined as the points on the ROC curve where Youden's index reached the highest, the appropriate overweight cut-off points of BMI were around 24.0 kg/m(2) both in men and women, and the points of WC were around 85 cm in men and 80 to 85 cm in women. With specificity 90% for identification of risk factors, the appropriate obese cut-off points of BMI were around 28.0 kg/m(2) both in men and women, with the range of 27.0 to 28.9 kg/m(2). Conclusions: The cut-off points for overweight and obesity recommended by Coorperative Meta-analysis Group of China Obesity Task Force was verified in the large sample survey conducted more recently. The cut-off points of BMI were 24.0 and 28.0 kg/m(2) for overweight and obesity, and the cut-off point of WC was 85 cm in men and 80 to 85 cm in women for central obesity.
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Affiliation(s)
- M Gao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Y X Wei
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - J Lyu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; Key Laboratory of Molecular Cardiovascular Sciences, Ministry of Education, Peking University, Beijing 100191, China
| | - C Q Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Y Guo
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Z Bian
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - P Pei
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - H D Du
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK; Medical Research Council Population Health Research Unit at the University of Oxford, Oxford OX3 7LF, UK
| | - J S Chen
- China National Center for Food Safety Risk Assessment, Beijing 100022, China
| | - Z M Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - T Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - L M Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
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22
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Li JC, Lyu J, Gao M, Yu CQ, Guo Y, Bian Z, Pei P, Du HD, Chen JS, Chen ZM, Li LM. [Association of body mass index and waist circumference with major chronic diseases in Chinese adults]. Zhonghua Liu Xing Bing Xue Za Zhi 2020; 40:1541-1547. [PMID: 32062912 DOI: 10.3760/cma.j.issn.0254-6450.2019.12.007] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: To examine the association of BMI with major chronic diseases morbidity and all-cause mortality in Chinese adults. Methods: This study is based on China Kadoorie Biobank. Anthropometric indexes were objectively measured at the baseline survey during 2004-2008. After excluding participants with heart disease, stroke, cancer, COPD and diabetes, 428 113 participants aged 30 to 79 years were included in the analysis. Cox regression models were used to investigate the associations of BMI and waist circumference with incidence of major chronic diseases (including cardiovascular disease, cancer, COPD, and type 2 diabetes) and all-cause mortality. Results: Over an average of 10 years, 131 454 participants developed any one of major chronic diseases. A total of 26 892 all-cause deaths were reported. The risk of major chronic diseases increased with BMI. Compared with normal BMI (18.5-24.0 kg/m(2)), the HR (95%CI) of overweight (BMI 24.0-28.0 kg/m(2)) and obesity (BMI≥28.0 kg/m(2)) were 1.26 (95%CI: 1.24-1.27) and 1.59 (95%CI: 1.57-1.62) respectively. Underweight and obesity were both associated with risk of all-cause mortality. Waist circumference was positively associated with risk of major chronic diseases and all-cause mortality. According to recommended cut-off points of BMI and waist circumference for Chinese adults, maintaining a healthy body weight would prevent 12% incident cases of major chronic diseases. Conclusion: General and central obesity were risk factors for major chronic disease among Chinese adults.
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Affiliation(s)
- J C Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - J Lyu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; Key Laboratory of Molecular Cardiovascular Sciences, Ministry of Education, Peking University, Beijing 100191, China
| | - M Gao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - C Q Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Y Guo
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Z Bian
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - P Pei
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - H D Du
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK; Medical Research Council Population Health Research Unit at the University of Oxford, Oxford OX3 7LF, UK
| | - J S Chen
- China National Center for Food Safety Risk Assessment, Beijing 100022, China
| | - Z M Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - L M Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
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23
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Wei YX, Shen ZW, Yu CQ, Du HD, Lyu J, Guo Y, Bian Z, Pei P, Chen JS, Chen ZM, Li LM. [Epidemiological characteristics and correlated factors of habitual snoring among Chinese aged 30 to 79 year-old]. Zhonghua Liu Xing Bing Xue Za Zhi 2019; 40:917-923. [PMID: 31484254 DOI: 10.3760/cma.j.issn.0254-6450.2019.08.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: To describe the characteristics of habitual snoring among adults from 10 regions engaged in the China Kadoorie Biobank (CKB) study. Methods: The baseline survey of CKB was conducted from 2004 to 2008. Data was collected regarding the information on socio- demographic characteristics, lifestyle, sleeping habits, and results from the physical examination of the participants. Logistic regression models were used to compare the regional differences and to estimate the associations of other baseline characteristics on snoring habit. Results: A total of 512 713 participants were included in this study. The overall prevalence of habitual snoring was 21.2%, higher among men, in south regions and urban areas, but no difference observed among people with different socioeconomic status after adjusting for age, regions, BMI, waist circumference or lifestyle factors. Results showed that the prevalence of habitual snoring under the multivariable adjusted model increased among current and ever smokers, also among current and ever alcohol consumers. The risk of habitual snoring was increased by 19% per 1 kg/m(2) and 6% per 1 cm increment in BMI or waist circumference, respectively. Among participants with similar BMI, central obese individuals were more likely to be habitual snorers. For individuals with similar waist circumference, the prevalence of habitual snoring was higher among those with higher BMI. Conclusion: The prevalence of habitual snoring varied across regions. Substantial differences in habitual snoring were also seen among people with different lifestyles and body sizes.
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Affiliation(s)
- Y X Wei
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Z W Shen
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - C Q Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - H D Du
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - J Lyu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; Key Laboratory of Molecular Cardiovascular Sciences, Ministry of Education, Peking University, Beijing 100191, China
| | - Y Guo
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Z Bian
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - P Pei
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - J S Chen
- China National Center for Food Safety Risk Assessment, Beijing 100022, China
| | - Z M Chen
- China National Center for Food Safety Risk Assessment, Beijing 100022, China
| | - L M Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
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24
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Wu M, Wei YX, Yu CQ, Du HD, Lyu J, Guo Y, Bian Z, Tan YL, Pei P, Chen JS, Chen ZM, Li LM. [Levels of skeletal muscle mass and handgrip strength in adults from 10 regions of China]. Zhonghua Liu Xing Bing Xue Za Zhi 2019; 40:376-381. [PMID: 31006194 DOI: 10.3760/cma.j.issn.0254-6450.2019.04.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: To describe the regional and population-related differences in skeletal muscle mass and handgrip strength across the 10 regions of China. Methods: 24 533 participants aged 38-88 years from the second resurvey of China Kadoorie Biobank were included in our analyses. Appendicular and trunk skeletal muscle mass were assessed using the bioelectrical impedance analysis (TANITA). Handgrip strength was measured using Jamar hand-held dynamometer. Low muscle mass and low muscle strength were defined as the lowest quintile of height-adjusted appendicular muscle mass or handgrip strength according to the Consensus Report of the Asian Working Group for Sarcopenia. We analyzed the mean value of absolute muscle mass, height-adjusted muscle mass, weight-adjusted muscle mass and handgrip strength. We also reported the prevalence of low muscle mass and low muscle strength. Results: The average appendicular and total skeletal muscle mass were (22.0±0.02) kg and (49.7±0.05) kg in men, which were higher than in women [(15.9±0.02) kg and (37.2±0.04) kg, respectively]. The handgrip strength was (32.6±0.06) kg in men, which was higher than (19.9±0.05) kg in women. The absolute muscle mass was higher in north area and urban region (P<0.001). The weight-adjusted muscle mass showed reverse patterns of regional difference compared with height-adjusted muscle mass. Both muscle mass and handgrip strength decreased by age (trend P<0.001), with a larger decline observed in handgrip strength. According to AWGS criteria, the proportions of low muscle mass and strength increased by age. Among participants over 80 years old, the prevalence of low muscle mass and strength were 56.2% and 74.5% in men, and 35.7% and 66.0% in women. Conclusions: Levels of skeletal muscle mass and strength varied greatly among people from 10 regions and among participants with different demographic characteristics. The prevalence of low muscle mass and strength was extremely high in elderly.
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Affiliation(s)
- M Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Y X Wei
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - C Q Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - H D Du
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - J Lyu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; Key Laboratory of Molecular Cardiovascular Sciences, Ministry of Education, Peking University, Beijing 100191, China
| | - Y Guo
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Z Bian
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Y L Tan
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - P Pei
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - J S Chen
- China National Center for Food Safety Risk Assessment, Beijing 100022, China
| | - Z M Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - L M Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
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25
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Wang H, Du HD, Hu RY, Qian YJ, Wang CM, Xie KX, Chen LL, Pan DX, Bian Z, Guo Y, Yu M, Li LM, Chen ZM. [Association between tea drinking and stroke in adults in Zhejiang province: a prospective study]. Zhonghua Liu Xing Bing Xue Za Zhi 2019; 39:1200-1205. [PMID: 30293310 DOI: 10.3760/cma.j.issn.0254-6450.2018.09.011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: To prospectively explore the association between tea drinking and incidence of stroke of adults of Zhejiang province. Methods: After excluding participants with heart disease, stroke, cancer and diabetes at baseline study, 53 916 participants aged 30-79 years in the China Kadoorie Biobank (CKB) study from Tongxiang were included for final analysis. Cox regression model was used to estimate the hazard ratio (HR) for the association of tea drinking with incident stroke. Results: The main type of drinking tea was black tea (79.78%), followed by green tea (20.08%). Of the 53 916 participants, the proportion of participants who drank tea at least once per week was 31.27%. The corresponding proportions for men and women were 60.24% and 10.30%, respectively. Among 391 512 person-years of the follow-up program (median 7.26 years), a total of 1 487 men and 1 769 women were diagnosed with stroke. After adjusting for socio-demographic status, lifestyle, BMI, waist circumference, and systolic blood pressure, HR for incident stroke decreased with the increase of daily average tea consumption amount (P=0.000 6). Compared with participants who did not drink tea weekly, the HRs for incident stroke in those consuming tea 0.1-, 3.0- and ≥5.0 g/d were 0.93 (95%CI: 0.85-1.00), 0.88 (95%CI: 0.77-0.99) and 0.79 (95%CI: 0.69-0.89), respectively. The HRs for incident stroke in smokers and non-smokers who consumed tea ≥5.0 g/d were 0.71 (95%CI: 0.59-0.86) and 0.97 (95%CI: 0.77-1.21), respectively, compared with current smokers and non-smokers who did not drink tea weekly (P=0.040 0). The corresponding HRs for alcohol drinkers and non-drinkers were 0.96 (95%CI: 0.76-1.22) and 0.70 (95%CI: 0.58-0.84), respectively (P=0.040 0). The corresponding HRs for central obese persons and non-central obese persons were 0.60 (95%CI: 0.44-0.81) and 0.86 (95%CI: 0.73-1.01), respectively (P=0.040 0). Conclusion: Tea drinking had an effect on reducing the possibility of incident stroke, especially among those who were current smokers, non-alcohol drinkers and central obese.
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Affiliation(s)
- H Wang
- Department of Chronic and Non-communicable Disease Prevention and Control, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China
| | - H D Du
- Clinical Trial Service and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, United Kingdom
| | - R Y Hu
- Department of Chronic and Non-communicable Disease Prevention and Control, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China
| | - Y J Qian
- Department of Chronic and Non- communicable Disease Prevention and Control, Tongxiang County Center for Disease Control and Prevention, Tongxiang 314500, China
| | - C M Wang
- Department of Chronic and Non- communicable Disease Prevention and Control, Tongxiang County Center for Disease Control and Prevention, Tongxiang 314500, China
| | - K X Xie
- Department of Chronic and Non- communicable Disease Prevention and Control, Tongxiang County Center for Disease Control and Prevention, Tongxiang 314500, China
| | - L L Chen
- Department of Chronic and Non- communicable Disease Prevention and Control, Tongxiang County Center for Disease Control and Prevention, Tongxiang 314500, China
| | - D X Pan
- Department of Chronic and Non- communicable Disease Prevention and Control, Tongxiang County Center for Disease Control and Prevention, Tongxiang 314500, China
| | - Z Bian
- Department of China Kadoorie Biobank, Chinese Academy of Medical Sciences, Beijing 102308, China
| | - Y Guo
- Department of China Kadoorie Biobank, Chinese Academy of Medical Sciences, Beijing 102308, China
| | - M Yu
- Department of Chronic and Non-communicable Disease Prevention and Control, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China
| | - L M Li
- School of Public Health, Peking University, Beijing 100191, China
| | - Z M Chen
- Clinical Trial Service and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, United Kingdom
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26
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Tan YL, Shen ZW, Yu CQ, Guo Y, Bian Z, Pei P, Du HD, Chen JS, Chen ZM, Lyu J, Li LM. [Relationship between educational level and long-term changes of body weight and waist circumference in adults in China]. Zhonghua Liu Xing Bing Xue Za Zhi 2019; 40:26-32. [PMID: 30669727 DOI: 10.3760/cma.j.issn.0254-6450.2019.01.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: To evaluate the association of educational level with anthropometric measurements at different adult stages and their long-term changes in adults who participated in the second re-survey of China Kadoorie Biobank (CKB). Methods: The present study excluded participants who were aged >65 years, with incomplete or extreme measurement values, or with major chronic diseases at baseline survey or re-survey. The weight at age 25 years was self-reported. Body height, body weight and waist circumference at baseline survey (2004-2008) and re-survey (2013-2014) were analyzed. Results: The present study included 3 427 men and 6 320 women. Both body weight and waist circumference (WC) increased with age. From age 25 years to baseline survey (mean age 45.2±6.5), the mean weight change per 5-year was (1.70±2.63) kg for men and (1.27±2.10) kg for women. From baseline survey to re-survey (53.2±6.5), the mean changes per 5-year for body weight were (1.12±2.61) kg for men and (0.90±2.54) kg for women; and that for WC was (3.20±3.79) cm for men and (3.83±3.85) cm for women. Among women, low educational level was consistently associated with higher body mass index (BMI) and WC at age 25 years, baseline survey and re-survey. Among men, low educational level was associated with higher BMI at age 25 years. At baseline survey and re-survey, the educational level in men was not statistically associated with BMI; but men who completed junior or senior high school showed slight higher WC and increase of WC from baseline survey to re-survey than other male participants. Conclusions: Body weight and WC increased with age for both men and women. The associations of educational level with BMI and WC were different between men and women.
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Affiliation(s)
- Y L Tan
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Z W Shen
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - C Q Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Y Guo
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Z Bian
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - P Pei
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - H D Du
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - J S Chen
- China National Center for Food Safety Risk Assessment, Beijing 100021, China
| | - Z M Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - J Lyu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - L M Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
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