Contextual Correlates of Physical Activity among Older Adults: A Neighborhood Environment-Wide Association Study (NE-WAS).
Background:Few older adults achieve recommended physical activity levels. We conducted a "neighborhood environment-wide association study (NE-WAS)" of neighborhood influences on physical activity among older adults, analogous, in a genetic context, to a genome-wide association study.Methods:Physical Activity Scale for the Elderly (PASE) and sociodemographic data were collected via telephone survey of 3,497 residents of New York City aged 65 to 75 years. Using Geographic Information Systems, we created 337 variables describing each participant's residential neighborhood's built, social, and economic context. We used survey-weighted regression models adjusting for individual-level covariates to test for associations between each neighborhood variable and (i) total PASE score, (ii) gardening activity, (iii) walking, and (iv) housework (as a negative control). We also applied two "Big Data" analytic techniques, LASSO regression, and Random Forests, to algorithmically select neighborhood variables predictive of these four physical activity measures.Results:Of all 337 measures, proportion of residents living in extreme poverty was most strongly associated with total physical activity [-0.85; (95% confidence interval, -1.14 to -0.56) PASE units per 1% increase in proportion of residents living with household incomes less than half the federal poverty line]. Only neighborhood socioeconomic status and disorder measures were associated with total activity and gardening, whereas a broader range of measures was associated with walking. As expected, no neighborhood meaZsures were associated with housework after accounting for multiple comparisons.Conclusions:This systematic approach revealed patterns in the domains of neighborhood measures associated with physical activity.Impact:The NE-WAS approach appears to be a promising exploratory technique.Cancer Epidemiol Biomarkers Prev; 26(4); 495-504. ©2017 AACRSee all the articles in thisCEBP Focussection, "Geospatial Approaches to Cancer Control and Population Sciences."
Harborview Injury Prevention & Research Center, University of Washington, Seattle, Washington. sjm2186@u.washington.edu.
Stephen J
SJ
Mooney
Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, Minnesota.
Spruha
S
Joshi
Department of Emergency Medicine, University of California, Davis, Davis, California.
Magdalena
M
Cerdá
Albert Einstein College of Medicine, New York, New York.
Gary J
GJ
Kennedy
Department of Ageing and Life Course, World Health Organization, Geneva, Switzerland.
John R
JR
Beard
Department of Epidemiology, Mailman School of Public Health, New York, New York.
Andrew G
AG
Rundle
D000368:Aged; D003430:Cross-Sectional Studies; D004777:Environment; D015444:Exercise; D005260:Female; D051639:Gardening / Q000706:statistics & numerical data; D006801:Humans; D008297:Male; D009519:New York City; D011203:Poverty; D012044:Regression Analysis; D012111:Residence Characteristics; D057566:Self Report; D012959:Socioeconomic Factors; D014505:Urban Population; D016138:Walking / Q000706:statistics & numerical data