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Lifestyle patterns in the Iranian population: Self- organizing map application

BACKGROUND: The present study evaluated the lifestyle behavior patterns and its associations with demographic factors in the Iranian population. METHODS: A total of 8244 people aged 25-70 years who participated in a national survey in 2011 were included in the study. Factors related to lifestyle (su...

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Detalles Bibliográficos
Autores principales: Akbarpour, Samaneh, Khalili, Davood, Zeraati, Hojjat, Mansournia, Mohammad Ali, Ramezankhanim, Azra, Fotouhi, Akbar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Babol University of Medical Sciences 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6121339/
https://www.ncbi.nlm.nih.gov/pubmed/30197772
http://dx.doi.org/10.22088/cjim.9.3.268
Descripción
Sumario:BACKGROUND: The present study evaluated the lifestyle behavior patterns and its associations with demographic factors in the Iranian population. METHODS: A total of 8244 people aged 25-70 years who participated in a national survey in 2011 were included in the study. Factors related to lifestyle (such as diet, physical activity, and tobacco use) have been collected using a questionnaire. A self-organizing map was used for cluster analysis and a multinomial logistic model was used for assessment of associations. RESULTS: Seven clusters were identified as the following: cluster 1 (15.84%): healthiest lifestyle; cluster 2 (12.45%): excessive consumption of sweet tasting soft drinks, salt, and fast food; cluster 3 (33.73%): no recreational physical activity; cluster 4 (6.86%) alcohol consumption, smoking, and consumption of sweet tasting soft drinks; cluster 5 (14.18%): less salt and oil intake and lack of physical activity; cluster 6 (7.85%): no use of dairy products; cluster 7 (9.08%): the most unhealthy lifestyles; excessive work-related physical activity and smoking and unhealthy diet. Male gender was associated with higher odds of being in clusters 4 and 7. Individuals who were in unhealthy lifestyle clusters were mostly less educated and more self-employed or laborers. CONCLUSIONS: A very small percentage of individuals was in the healthy lifestyle cluster yet they had poor nutrition. Health policy-makers should pay more attention to low recreational physical activity among elder people and in middle-aged and housekeepers, and also to high work-related physical activities that have a strong tendency to be in a cluster with smoking among workers and less educated men.