Citation

Miranda JJ, Carrillo-Larco RM, Gilman RH, Avilez JL, Smeeth L, Checkley W, Bernabe-Ortiz A. J. Phys. Act. Health 2016; 13(6): 654-662.

Affiliation

CRONICAS Center of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru.

Copyright

(Copyright © 2016, Human Kinetics Publishers)

DOI

10.1123/jpah.2015-0424

PMID

26800569

Abstract

BACKGROUND: Physical inactivity and sedentary behaviors have been linked with impaired health outcomes. Establishing the physical inactivity profiles of a given population is needed to establish program targets and to contribute to international monitoring efforts. We report the prevalence of, and explore socio-demographical and built environment factors associated with physical inactivity in four resource-limited settings in Peru: rural Puno, urban Puno, Pampas de San Juan de Miraflores (urban), and Tumbes (semi-urban).

METHODS: Cross-sectional analysis of the CRONICAS Cohort Study's baseline assessment. Outcomes of interest were physical inactivity of leisure time (<600 MET-min/week) and transport-related physical activity (not reporting walking or cycling trips) domains of the IPAQ, as well as watching TV, as a proxy of sedentarism (≥2 hours per day). Exposures included demographic factors and perceptions about neighborhood's safety. Associations were explored using Poisson regression models with robust standard errors. Prevalence ratios (PR) and 95% confidence intervals (95% CI) are presented.

RESULTS: Data from 3593 individuals were included: 48.5% males, mean age 55.1 (SD: 12.7) years. Physical inactivity was present at rates of 93.7% (95% CI 93.0%-94.5%) and 9.3% (95% CI 8.3%-10.2%) within the leisure time and transport domains, respectively. In addition, 41.7% (95%CI 40.1%-43.3%) of participants reported watching TV for more than two hours per day. Rates varied according to study settings (p<0.001). In multivariable analysis, being from rural settings was associated with 3% higher prevalence of leisure time physical inactivity relative to highly urban Lima. The pattern was different for transport-related physical inactivity: both Puno sites had around 75% to 50% lower prevalence of physical inactivity. Too much traffic was associated with higher levels of transport-related physical inactivity (PR=1.24; 95%CI 1.01-1.54).

CONCLUSION: Our study showed high levels of inactivity and marked contrasting patterns by rural/urban sites. These findings highlight the need to generate synergies to expand nationwide physical activity surveillance systems.

Language: en