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Configural path of obesity

Linkage of physical activity and lifestyle based on fuzzy-set qualitative comparative analysis

Bibliographic Data

ID22077883
AuthorsYi Wang (0000-0003-2228-7009, Sichuan University), Fengshan Yue (Northwestern Polytechnical University), Wei Li (0000-0002-3581-849X, Sichuan University), Lixu Tang (0000-0002-8146-9999, Wuhan Sports University, corresponding author)
Year2025
Volume13
Pages1533311-1533311
Publication date2025-03-28
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2025.1533311
PMID40226321
OpenAlexW4408929358
LanguageEN
References cited44

Obesity plays a significant role in the burden of various health conditions, it is not only a global health issue but challenges the national public health system. Some regions of China still face a high prevalence of obesity, and it is broadly recognized that physical activities interact with lifestyle in different pathways would affect obesity. We aim to capture different configurational paths that lead to obesity, using the fuzzy set Qualitative Comparative Analysis. Eight obesity-related variables were involved, and data were collected between January 1, 2021, and January 31, 2022. The study shows six configurational paths result in obesity, in which the necessary condition is “educational status,” and core conditions of “the time of exercise” and “weekly sitting time*sleeping time less than 6 h*second hand smoking exposure on average of 4–6 days per week *keep excising on average of 4 times per week* exercise intensity on the shortness of breath, markedly increased heart rate, heavy sweating” play an important role in the obesity outcome, and the solution exhibits acceptable consistency is 0.50. The six configurational paths solution consistency is 0.76, and the solution coverage is 0.31. Besides the necessary condition and core factors that play(s) an important role in the development of obesity, we have to consider the multiple factors of physical activity and lifestyle have a cross-cutting effect on obesity. This can offer a better understanding of the mechanisms that cause obesity by identifying and characterizing the regional population, which would help develop an effective protective measure for obesity

Biology · Fuzzy logic · Fuzzy set · Machine learning · Obesity · Physical activity · Physical medicine and rehabilitation · Qualitative comparative analysis · Computer Science · Medicine · Qualitative Comparative Analysis Research · Artificial Intelligence · Endocrinology · Genetics

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