Leading Determinants for Disease-Free Status in Community-Dwelling Middle-Aged Men and Women: A 9-Year Follow-Up Cohort Study
Background: Identifying leading determinants for disease-free status may provide evidence for action priorities, which is imperative for public health with an expanding aged population worldwide. This study aimed to identify leading determinants, especially modifiable factors for disease-free status...
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Frontiers Media S.A.
2019-11-01
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| Series: | Frontiers in Public Health |
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| Online Access: | https://www.frontiersin.org/article/10.3389/fpubh.2019.00320/full |
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| author | Xianwen Shang Xianwen Shang Xianwen Shang Wei Wang Stuart Keel Jinrong Wu Mingguang He Mingguang He Lei Zhang Lei Zhang Lei Zhang Lei Zhang Lei Zhang |
| author_facet | Xianwen Shang Xianwen Shang Xianwen Shang Wei Wang Stuart Keel Jinrong Wu Mingguang He Mingguang He Lei Zhang Lei Zhang Lei Zhang Lei Zhang Lei Zhang |
| author_sort | Xianwen Shang |
| collection | DOAJ |
| description | Background: Identifying leading determinants for disease-free status may provide evidence for action priorities, which is imperative for public health with an expanding aged population worldwide. This study aimed to identify leading determinants, especially modifiable factors for disease-free status using machine learning methods.Methods: We included 52,036 participants aged 45–64 years from the 45 and Up Study who were free of 13 predefined chronic conditions at baseline (2006–2009). Disease-free status was defined as participants aging from 45–64 years at baseline to 55–75 years at the end of the follow-up (December 31, 2016) without developing any of the 13 chronic conditions. We used machine learning methods to evaluate the importance of 40 potential predictors and analyzed the association between the number of leading modifiable healthy factors and disease-free status.Results: Disease-free status was found in about half of both men and women during a mean 9-year follow-up. The five most common leading predictors were body mass index (6.4–9.5% of total variance), self-rated health (5.2–8.2%), self-rated quality of life (4.1–6.8%), red meat intake (4.5–6.5%), and chicken intake (4.5–5.9%) in both genders. Modifiable behavioral factors including body mass index, diets, smoking, alcohol consumption, and physical activity, contributed to 37.2–40.3% of total variance. Participants having six or more modifiable health factors were 1.63–8.76 times more likely to remain disease-free status and had 0.60–2.49 more disease-free years (out of 9-year follow-up) than those having two or fewer. Non-behavioral factors including low levels of education and income and high relative socioeconomic disadvantage, were leading risk factors for disease-free status.Conclusions: Body mass index, diets, smoking, alcohol consumption, and physical activity are key factors for disease-free status promotion. Individuals with low socioeconomic status are more in need of care. |
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| id | doaj.art-23b9d38c62c74006b4a084d516cb4a7a |
| institution | Directory Open Access Journal |
| issn | 2296-2565 |
| language | English |
| last_indexed | 2024-12-12T20:22:29Z |
| publishDate | 2019-11-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Public Health |
| spelling | doaj.art-23b9d38c62c74006b4a084d516cb4a7a2022-12-22T00:13:13ZengFrontiers Media S.A.Frontiers in Public Health2296-25652019-11-01710.3389/fpubh.2019.00320465133Leading Determinants for Disease-Free Status in Community-Dwelling Middle-Aged Men and Women: A 9-Year Follow-Up Cohort StudyXianwen Shang0Xianwen Shang1Xianwen Shang2Wei Wang3Stuart Keel4Jinrong Wu5Mingguang He6Mingguang He7Lei Zhang8Lei Zhang9Lei Zhang10Lei Zhang11Lei Zhang12Department of Surgery, Centre for Eye Research Australia, Ophthalmology, University of Melbourne, Melbourne, VIC, AustraliaSchool of Behavioural and Health Sciences, Australian Catholic University, Melbourne, VIC, AustraliaDepartment of Medicine-Royal Melbourne Hospital, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, Melbourne, VIC, AustraliaState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, ChinaDepartment of Surgery, Centre for Eye Research Australia, Ophthalmology, University of Melbourne, Melbourne, VIC, AustraliaDepartment of Surgery, Centre for Eye Research Australia, Ophthalmology, University of Melbourne, Melbourne, VIC, AustraliaDepartment of Surgery, Centre for Eye Research Australia, Ophthalmology, University of Melbourne, Melbourne, VIC, AustraliaState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, ChinaDepartment of Surgery, Centre for Eye Research Australia, Ophthalmology, University of Melbourne, Melbourne, VIC, AustraliaMelbourne Sexual Health Centre, Alfred Health, Melbourne, VIC, AustraliaFaculty of Medicine, Central Clinical School, Monash University, Melbourne, VIC, AustraliaDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, ChinaChina-Australia Joint Research Centre for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, ChinaBackground: Identifying leading determinants for disease-free status may provide evidence for action priorities, which is imperative for public health with an expanding aged population worldwide. This study aimed to identify leading determinants, especially modifiable factors for disease-free status using machine learning methods.Methods: We included 52,036 participants aged 45–64 years from the 45 and Up Study who were free of 13 predefined chronic conditions at baseline (2006–2009). Disease-free status was defined as participants aging from 45–64 years at baseline to 55–75 years at the end of the follow-up (December 31, 2016) without developing any of the 13 chronic conditions. We used machine learning methods to evaluate the importance of 40 potential predictors and analyzed the association between the number of leading modifiable healthy factors and disease-free status.Results: Disease-free status was found in about half of both men and women during a mean 9-year follow-up. The five most common leading predictors were body mass index (6.4–9.5% of total variance), self-rated health (5.2–8.2%), self-rated quality of life (4.1–6.8%), red meat intake (4.5–6.5%), and chicken intake (4.5–5.9%) in both genders. Modifiable behavioral factors including body mass index, diets, smoking, alcohol consumption, and physical activity, contributed to 37.2–40.3% of total variance. Participants having six or more modifiable health factors were 1.63–8.76 times more likely to remain disease-free status and had 0.60–2.49 more disease-free years (out of 9-year follow-up) than those having two or fewer. Non-behavioral factors including low levels of education and income and high relative socioeconomic disadvantage, were leading risk factors for disease-free status.Conclusions: Body mass index, diets, smoking, alcohol consumption, and physical activity are key factors for disease-free status promotion. Individuals with low socioeconomic status are more in need of care.https://www.frontiersin.org/article/10.3389/fpubh.2019.00320/fulldisease-free statusleading predictorshealthy modifiable factorsfamily history of chronic diseasesocioeconomic statuspsychological factors |
| spellingShingle | Xianwen Shang Xianwen Shang Xianwen Shang Wei Wang Stuart Keel Jinrong Wu Mingguang He Mingguang He Lei Zhang Lei Zhang Lei Zhang Lei Zhang Lei Zhang Leading Determinants for Disease-Free Status in Community-Dwelling Middle-Aged Men and Women: A 9-Year Follow-Up Cohort Study Frontiers in Public Health disease-free status leading predictors healthy modifiable factors family history of chronic disease socioeconomic status psychological factors |
| title | Leading Determinants for Disease-Free Status in Community-Dwelling Middle-Aged Men and Women: A 9-Year Follow-Up Cohort Study |
| title_full | Leading Determinants for Disease-Free Status in Community-Dwelling Middle-Aged Men and Women: A 9-Year Follow-Up Cohort Study |
| title_fullStr | Leading Determinants for Disease-Free Status in Community-Dwelling Middle-Aged Men and Women: A 9-Year Follow-Up Cohort Study |
| title_full_unstemmed | Leading Determinants for Disease-Free Status in Community-Dwelling Middle-Aged Men and Women: A 9-Year Follow-Up Cohort Study |
| title_short | Leading Determinants for Disease-Free Status in Community-Dwelling Middle-Aged Men and Women: A 9-Year Follow-Up Cohort Study |
| title_sort | leading determinants for disease free status in community dwelling middle aged men and women a 9 year follow up cohort study |
| topic | disease-free status leading predictors healthy modifiable factors family history of chronic disease socioeconomic status psychological factors |
| url | https://www.frontiersin.org/article/10.3389/fpubh.2019.00320/full |
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