ArticleIranian journal of public health2022
Patterns of Lifestyle Behaviors and Relevant Metabolic Profiles in Chinese Adults: Latent Class Analysis from Two Independent Surveys in Urban and Rural Populations.
Article in Iranian journal of public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed, 3 citations in OpenAlex.
- Lifestyle Subgroups and its Relationship with the Incidence of Hypertension in the Population of Azar Cohort: A Latent Class Analysis.Health promotion perspectives · 2026Article
- Metabotype Risk Clustering Based on Metabolic Disease Biomarkers and Its Association with Metabolic Syndrome in Korean Adults: Findings from the 2016-2023 Korea National Health and Nutrition Examination Survey (KNHANES).Diseases (Basel, Switzerland) · 2025Article
- Patterns of Health Behaviors and Trajectories of Stress among People with Disabilities in Korea.Iranian journal of public health · 2024Article
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: This study was determined to describe the patterns of lifestyle behaviors and their associations with metabolic profiles among Chinese urban and rural adults. Methods: This was a cross-sectional study set in the Nanjing (5,824) and Hefei (20,269) Community Cardiovascular Risk Surveys from 2011-2013, using random cluster sampling. Questionnaires were completed via face-to-face interview, and data on lifestyle behaviors including daily night sleep duration, nap duration (if any) and sitting time, and weekly physical activity (measured using the International Physical Activity Questionnaire, in metabolic equivalents of task × minutes, and separated into walking and moderate-to-vigorous physical activity (MOVPA) according to intensity) was collected. The patterns of physical activity in Chinese urban and rural populations and the metabolic profile in each pattern were identified by the latent class analysis. Results: Six distinct clusters were determined, with the sizes ranging from 45% to 5% of the total population. For example, the most common cluster was associated with a sufficient night and nap sleep duration, a long sitting time, and above WHO recommended physical activities for both walking and MOVPA, and the smallest cluster was featured by its huge amount of MOVPA and limited amount of walking activity. Difference in proportion of each cluster was observed between the two survey sites. No obvious abnormal blood measures were seen in any cluster. Conclusion: Common lifestyle behavior clusters were described, leading to a better understanding of people's routine activities.
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