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Stephanie B. Jilcott Pitts, Michael B. Edwards, Justin B. Moore, Kindal A. Shores, Katrina Drowatzky DuBose and David McGranahan

Background:

Little is known about the associations between natural amenities, recreation facility density, and obesity, at a national level. Therefore, the purpose of this paper was to examine associations between county-level natural amenities, density of recreation facilities, and obesity prevalence among United States counties.

Methods:

Data were obtained from a compilation of sources within the United States Department of Agriculture Economic Research Service Food Environment Atlas. Independent variables of interest were the natural amenities scale and recreation facilities per capita. The dependent variable was county-level obesity prevalence. Potential covariates included a measure of county-level percent Black residents, percent Hispanic residents, median age, and median household income. All models were stratified by population loss, persistent poverty, and metro status. Multilevel linear regression models were used to examine the association between obesity and natural amenities and recreation facilities, with “state” as a random effects second level variable.

Results:

There were statistically significant negative associations between percent obesity and 1) natural amenities and 2) recreation facilities per capita.

Conclusions:

Future research should examine environmental and policy changes to increase recreation facilities and enhance accessible natural amenities to decrease obesity rates.

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Bronagh McGrane, Danielle Powell, Sarahjane Belton and Johann Issartel

, and physical self-confidence was log transformed due to skewness. Independent sample t-tests were conducted to assess sex differences in actual FMS, perceived FMS and MVPA. Multi-level modelling analyses was used for each FMS subtest to examine: (i) actual FMS as the predictor and perceived FMS as the

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Jorge Mota, Rute Santos, Manuel João Coelho-e-Silva, Armando M. Raimundo and Luís B. Sardinha

Região Alentejo– Relatório . évora, Portugal : Núcleo Regional do Alentejo da Plataforma contra a Obesidade da ARSA ; 2012 . 7. Gomes TN , Dos Santos FK , Garganta RM , Kenny DA , Katzmarzyk PT , Maia JA . Multi-level modelling of physical activity in nuclear families . Ann Hum Biol

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Christine M. Habeeb, Robert C. Eklund and Pete Coffee

.-C. , & Perreault , S. ( 2010 ). Multi-level modeling of dyadic data in sport sciences: Conceptual, statistical, and practical issues . Measurement in Physical Education and Exercise Science, 14 ( 1 ), 29 – 50 . doi:10.1080/10913670903455017 10.1080/10913670903455017 Gully , S.M. , Incalcaterra , K

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Christine M. Habeeb, Robert C. Eklund and Pete Coffee

doi:10.1037/0003-066X.48.6.621 10.1037/0003-066X.48.6.621 Gaudreau , P. , Fecteau , M.-C. , & Perreault , S. ( 2010 ). Multi-level modeling of dyadic data in sport sciences: Conceptual, statistical, and practical issues . Measurement in Physical Education and Exercise Science, 14 ( 1 ), 29

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Alison Doherty and Graham Cuskelly

. Sport Management Review, 17, 23 – 34 . doi: 10.1016/j.smr.2013.03.005 Wicker , P. , & Breuer , C. ( 2015 ). How the economic and financial situation of the community affects clubs’ resources: Evidence from multi-level models . International Journal of Financial Studies, 3, 31 – 48 . doi

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Heather Kennedy, Bradley J. Baker, Jeremy S. Jordan and Daniel C. Funk

. , Hallmann , K. , & Breuer , C. ( 2013 ). Analyzing the impact of sport infrastructure on sport participation using geo-coded data: Evidence from multi-level models . Sport Management Review, 16 ( 1 ), 54 – 67 . doi:10.1016/j.smr.2012.05.001 10.1016/j.smr.2012.05.001 Yin , R.K. ( 2003 ). Case