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Updated: Mar 18, 2026

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
Published on: July 27, 2018
Cluster analytical approach to Lifestyle characteristics: A population based study in Shiraz, Iran
Veda Vakili1, Pardis Shojaei2, Zahra Abbasi Shaye2
1MD, Assistant Professor, Department of Community Medicine, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Introduction:
A limited number of risky behaviors cause most morbidity and mortality. The aim of this study was to determine the possible clustering of lifestyle behaviors, including transportation behaviors, diet, physical activity, and smoking in Shiraz, Iran.
Methods:
There were 776 representative Shirazi adults who participated in this cross-sectional study. The questionnaires were completed via person-to-person interviews. The datasets were searched for any clustering patterns. Cluster analysis was used for statistical analysis, and the data were analyzed using SPSS version 11.5.
Results:
Three distinct clusters were identified. Cluster 1 was named "Healthy," and it included non-smokers, safe drivers, appropriate or acceptable fruit, vegetable, and fast-food consumers, and physically-active people. Cluster 2, "Moderately Healthy," was relatively risky drivers who had appropriate behaviors on the rest of the health-related behaviors. Cluster 3, "Unhealthy," was smokers, risky drivers, inappropriate or unacceptable fruit, vegetable & fast-food consumers, and a sedentary lifestyle.
Conclusions:
It was obvious that health-related behaviors were clustered together and unhealthy behaviors were not established in isolation.
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