REFERENCES

• 1. Story M, Kaphingst KM, Robinson-O'Brien R, Glanz K. Creating healthy food and eating environments: policy and environmental approaches. Annu Rev Public Health 2008; 29: 253-272.ArticlePubMed
• 2. World Health Organization. Global strategy on diet, physical activity, and health [Internet]. cited 2016 Sep 21]. Available from: http://www.who.int/dietphysicalactivity/.
• 3. Institute of Medicine. Health and Behavior: The Interplay of Biological, Behavioral, and Societal Influences. Washington, DC: National Academy Press; 2001.
• 4. Kumanyika S, Jeffery RW, Morabia A, Ritenbaugh C, Antipatis VJ. Obesity prevention: the case for action. Int J Obes Relat Metab Disord 2002; 26(3): 425-436.ArticlePubMedPDF
• 5. Koplan JP, Dietz WH. Caloric imbalance and public health policy. JAMA 1999; 282(16): 1579-1581.ArticlePubMed
• 6. Glanz K, Sallis JF, Saelens BE, Frank LD. Healthy nutrition environments: concepts and measures. Am J Health Promot 2005; 19(5): 330-333.ArticlePubMedPDF
• 7. National Cancer Institute (US). Measures of the food environment [Internet]. National Cancer Institute; 2016; cited 2016 Sep 21]. Available from: http://epi.grants.cancer.gov/mfe./.
• 8. Health Canada. Measuring the Food Environment in Canada [Internet]. Health Canada: 2013; cited 2016 Sep 21]. Available from:http://www.hc-sc.gc.ca/fn-an/nutrition/pol/som-ex-sum-environ-eng.php.
• 9. Charreire H, Casey R, Salze P, Simon C, Chaix B, Banos A, et al. Measuring the food environment using geographical information systems: a methodological review. Public Health Nutr 2010; 13(11): 1773-1785.ArticlePubMed
• 10. Fraser LK, Edwards KL, Cade J, Clarke GP. The geography of fast food outlets: a review. Int J Environ Res Public Health 2010; 7(5): 2290-2308.ArticlePubMedPMC
• 11. Fleischhacker SE, Evenson KR, Rodriguez DA, Ammerman AS. A systematic review of fast food access studies. Obes Rev 2011; 12(5): e460-e471.ArticlePubMed
• 12. McKinnon RA, Reedy J, Morrissette MA, Lytle LA, Yaroch AL. Measures of the food environment: a compilation of the literature, 1990-2007. Am J Prev Med 2009; 36(4): S124-S133.PubMed
• 13. Athens JK, Duncan DT, Elbel B. Proximity to fast-food outlets and supermarkets as predictors of fast-food dining frequency. J Acad Nutr Diet 2016; 116(8): 1266-1275.ArticlePubMedPMC
• 14. Sharkey JR, Johnson CM, Dean WR, Horel SA. Association between proximity to and coverage of traditional fast-food restaurants and non-traditional fast-food outlets and fast-food consumption among rural adults. Int J Health Geogr 2011; 10(1): 37.ArticlePubMedPMC
• 15. Kruger DJ, Greenberg E, Murphy JB, DiFazio LA, Youra KR. Local concentration of fast-food outlets is associated with poor nutrition and obesity. Am J Health Promot 2014; 28(5): 340-343.ArticlePubMedPDF
• 16. Reitzel LR, Regan SD, Nguyen N, Cromley EK, Strong LL, Wetter DW, et al. Density and proximity of fast food restaurants and body mass index among African Americans. Am J Public Health 2014; 104(1): 110-116.ArticlePubMedPMC
• 17. Hollands S, Campbell MK, Gilliland J, Sarma S. Association between neighbourhood fast-food and full-service restaurant density and body mass index: a cross-sectional study of Canadian adults. Can J Public Health 2014; 105(3): e172-e178.ArticlePubMedPMCPDF
• 18. Hollands S, Campbell MK, Gilliland J, Sarma S. A spatial analysis of the association between restaurant density and body mass index in Canadian adults. Prev Med 2013; 57(4): 258-264.ArticlePubMed
• 19. De Vogli R, Kouvonen A, Gimeno D. 'Globesization': ecological evidence on the relationship between fast food outlets and obesity among 26 advanced economies. Crit Public Health 2011; 21(4): 395-402.Article
• 20. Ministry of Health and Welfare, Korea Centers for Disease Control and Prevention. Korea Health Statistics 2014: Korea National Health and Nutrition Examination Survey (KNHANES VI-2). Sejong: Ministry of Health and Welfare; 2015.
• 21. Lee Y, Shim JE, Yoon J. Change of children's meal structure in terms of temporal and spatial dimensions : analysis of the data from the Korea National Health and Nutrition Examination Surveys of 1998 and 2009. Korean J Community Nutr 2012; 17(1): 109-118.Article
• 22. Heo GJ, Nam SY, Lee SK, Chung SJ, Yoon JH. The relationship between high energy/low nutrient food consumption and obesity among Korean children and adolescents. Korean J Community Nutr 2012; 17(2): 226-242.Article
• 23. Statistics Korea. 1994-2014 Census on Establishments [Internet]. Statistics Korea; 2016; cited 2016 Sep 21]. Available from: https://mdis.kostat.go.kr.
• 24. Kweon S, Kim Y, Jang MJ, Kim Y, Kim K, Choi S, et al. Data resource profile: the Korea National Health and Nutrition Examination Survey (KNHANES). Int J Epidemiol 2014; 43(1): 69-77.ArticlePubMedPMC
• 25. Macintyre S, McKay L, Cummins S, Burns C. Out-of-home food outlets and area deprivation: case study in Glasgow, UK. Int J Behav Nutr Phys Act 2005; 2(1): 16.ArticlePubMedPMCPDF
• 26. Macintyre S, Macdonald L, Ellaway A. Do poorer people have poorer access to local resources and facilities? The distribution of local resources by area deprivation in Glasgow, Scotland. Soc Sci Med 2008; 67(6): 900-914.ArticlePubMedPMC
• 27. Thornton LE, Crawford DA, Ball K. Neighbourhood-socioeconomic variation in women's diet: The role of nutrition environments. Eur J Clin Nutr 2010; 64(12): 1423-1432.ArticlePubMedPDF
• 28. Block JP, Scribner RA, DeSalvo KB. Fast food, race/ethnicity, and income: a geographic analysis. Am J Prev Med 2004; 27(3): 211-217.ArticlePubMed
• 29. Cummins SC, McKay L, MacIntyre S. McDonald″s restaurants and neighborhood deprivation in Scotland and England. Am J Prev Med 2005; 29(4): 308-310.ArticlePubMed
• 30. Lewis LB, Sloane DC, Nascimento LM, Diamant AL, Guinyard JJ, Yancey AK, et al. African Americans″ access to healthy food options in south Los Angeles restaurants. Am J Public Health 2005; 95(4): 668-673.ArticlePubMedPMC
• 31. Macdonald L, Cummins S, Macintyre S. Neighbourhood fast food environment and area deprivation substitution or concentration? Appetite 2007; 49(1): 251-254.ArticlePubMed
• 32. Pearce J, Blakely T, Witten K, Bartie P. Neighborhood deprivation and access to fast-food retailing: a national study. Am J Prev Med 2007; 32(5): 375-382.PubMed
• 33. Hemphill E, Raine K, Spence JC, Smoyer-Tomic KE. Exploring obesogenic food environments in Edmonton, Canada: the association between socioeconomic factors and fast-food outlet access. Am J Health Promot 2008; 22(6): 426-432.ArticlePubMedPDF
• 34. Smoyer-Tomic KE, Spence JC, Raine KD, Amrhein C, Cameron N, Yasenovskiy V, et al. The association between neighborhood socioeconomic status and exposure to supermarkets and fast food outlets. Health Place 2008; 14(4): 740-754.ArticlePubMed
• 35. Kim SA, Choe JS, Joung H, Jang MJ, Kim Y, Lee SE. Comparison of the distribution and accessibility of restaurants in urban area and rural area. J Nutr Health 2014; 47(6): 475-483.Article
• 36. Joo S, Ju S, Chang H. Comparison of fast food consumption and dietary guideline practices for children and adolescents by clustering of fast food outlets around schools in the Gyeonggi area of Korea. Asia Pac J Clin Nutr 2015; 24(2): 299-307.PubMed
• 37. Chung SJ, Kang SH, Song SM, Ryu SH, Yoon J. Nutritional quality of Korean adults' consumption of lunch prepared at home, commercial places, and institutions: analysis of the data from the 2001 National Health and Nutrition Survey. Korean J Nutr 2006; 39(8): 841-849.
• 38. Suh Y, Kang J, Kim H, Chung YJ. Comparison of nutritional status of the Daejeon metropolitan citizens by frequency of eating out. Korean J Nutr 2010; 43(2): 171-180.Article
• 39. Lee HS. Studies on salt intake through eat-out foods in Andong area. Korean J Soc Food Sci 1997; 13(3): 314-318.
• 40. Polsky JY, Moineddin R, Dunn JR, Glazier RH, Booth GL. Absolute and relative densities of fast-food versus other restaurants in relation to weight status: Does restaurant mix matter? Prev Med 2016; 82: 28-34.ArticlePubMed
• 41. Thornton LE, Lamb KE, Ball K. Employment status, residential and workplace food environments: associations with women's eating behaviours. Health Place 2013; 24: 80-89.ArticlePubMed
• 42. Burgoine T, Forouhi NG, Griffin SJ, Wareham NJ, Monsivais P. Associations between exposure to takeaway food outlets, takeaway food consumption, and body weight in Cambridgeshire, UK: Population based, cross-sectional study. BMJ 2014; 348: g1464.ArticlePubMedPMC
• 43. Rundle A, Neckerman KM, Freeman L, Lovasi GS, Purciel M, Quinn J, et al. Neighborhood food environment and walkability predict obesity in New York City. Environ Health Perspect 2009; 117(3): 442-447.ArticlePubMed

Table 1

Distribution of tertile groups according to the count of unhealthy food outlets

Table 2

Characteristics of tertile groups according to the count of unhealthy food outlets

Data are expressed as unweighted frequency and weighted percentage or mean.

p-value was obtained from the Rao-Scott χ² test for categorical variables and Bonferroni correction of multiple comparison for continuous variables.

Table 3

Daily nutrient intake across tertile groups according to the count of unhealthy food outlets

1) The p-values for differences across groups were calculated according to Bonferroni correction of multiple comparisons at alpha=0.05 using PROC SURVEYREG (^*: p<0.05; ^**: p<0.01).

2) The p for trend obtained to trend as the levels of the predictor variable increase.

3) The means of daily nutrient intake were analyzed after adjusting for gender (male, female), age (19 − 39, 40 − 59, ≥60), education level (less than elementary school, middle school, high school, university or above), employment status (non-manual, manual, service, not working), household monthly income (quartile), BMI (<18.5, 18.5 − 24.9, ≥25), current diet control (yes, no), urban-rural status (urban, rural).

Table 4

Insufficient or excessive nutrient intakes across tertile groups according to the count of unhealthy food outlets

1) The p-values for differences across groups were calculated according to Bonferroni correction of multiple comparisons at alpha=0.05 using PROC SURVEYREG (^*: p<0.05; ^**: p<0.01).

2) The p for trend obtained to trend as the levels of the predictor variable increase.

3) The percentage were analyzed after adjusting for gender (male, female), age (19 − 39, 40 − 59, ≥60), education level (less than elementary school, middle school, high school, university or above), employment status (non-manual, manual, service, not working), household monthly income (quartile), BMI (<18.5, 18.5 − 24.9, ≥25), current diet control (yes, no), urban-rural status (urban, rural).

Table 5

Weekly food consumption frequency across tertile groups according to the count of unhealthy food outlets

1) The p-values for differences across groups were calculated according to Bonferroni correction of multiple comparisons at alpha=0.05 using PROC SURVEYREG (^*: p<0.05; ^**: p<0.01; ^***: p<0.001).

2) The p for trend obtained to trend as the levels of the predictor variable increase.

3) The means of food consumption frequency were analyzed after adjusting for gender (male, female), age (19 − 39, 40 − 59, ≥60), education level (less than elementary school, middle school, high school, university or above), employment status (non-manual, manual, service, not working), household monthly income (quartile), BMI (<18.5, 18.5 −24.9, ≥25), current diet control (yes, no), urban-rural status (urban, rural).

Table 6

Associations between unhealthy food outlets and obesity (n=8,912)

1) Model 2: Adjusted for individual level variable; Model 3: Adjusted for Model 2+local level variable

2) OR; Odds Ratio, 95%

3) CI; 95% Confidence Interval

^*: p<0.05, ^**: p<0.01, ^***: p<0.001

Figure & Data

Table 1

Distribution of tertile groups according to the count of unhealthy food outlets

Table 2

Characteristics of tertile groups according to the count of unhealthy food outlets

Data are expressed as unweighted frequency and weighted percentage or mean.

p-value was obtained from the Rao-Scott χ² test for categorical variables and Bonferroni correction of multiple comparison for continuous variables.

Table 3

Daily nutrient intake across tertile groups according to the count of unhealthy food outlets

1) The p-values for differences across groups were calculated according to Bonferroni correction of multiple comparisons at alpha=0.05 using PROC SURVEYREG (^*: p<0.05; ^**: p<0.01).

2) The p for trend obtained to trend as the levels of the predictor variable increase.

3) The means of daily nutrient intake were analyzed after adjusting for gender (male, female), age (19 − 39, 40 − 59, ≥60), education level (less than elementary school, middle school, high school, university or above), employment status (non-manual, manual, service, not working), household monthly income (quartile), BMI (<18.5, 18.5 − 24.9, ≥25), current diet control (yes, no), urban-rural status (urban, rural).

Table 4

Insufficient or excessive nutrient intakes across tertile groups according to the count of unhealthy food outlets

1) The p-values for differences across groups were calculated according to Bonferroni correction of multiple comparisons at alpha=0.05 using PROC SURVEYREG (^*: p<0.05; ^**: p<0.01).

2) The p for trend obtained to trend as the levels of the predictor variable increase.

3) The percentage were analyzed after adjusting for gender (male, female), age (19 − 39, 40 − 59, ≥60), education level (less than elementary school, middle school, high school, university or above), employment status (non-manual, manual, service, not working), household monthly income (quartile), BMI (<18.5, 18.5 − 24.9, ≥25), current diet control (yes, no), urban-rural status (urban, rural).

Table 5

Weekly food consumption frequency across tertile groups according to the count of unhealthy food outlets

1) The p-values for differences across groups were calculated according to Bonferroni correction of multiple comparisons at alpha=0.05 using PROC SURVEYREG (^*: p<0.05; ^**: p<0.01; ^***: p<0.001).

2) The p for trend obtained to trend as the levels of the predictor variable increase.

3) The means of food consumption frequency were analyzed after adjusting for gender (male, female), age (19 − 39, 40 − 59, ≥60), education level (less than elementary school, middle school, high school, university or above), employment status (non-manual, manual, service, not working), household monthly income (quartile), BMI (<18.5, 18.5 −24.9, ≥25), current diet control (yes, no), urban-rural status (urban, rural).

Table 6

Associations between unhealthy food outlets and obesity (n=8,912)

1) Model 2: Adjusted for individual level variable; Model 3: Adjusted for Model 2+local level variable

2) OR; Odds Ratio, 95%

3) CI; 95% Confidence Interval

^*: p<0.05, ^**: p<0.01, ^***: p<0.001

REFERENCES

• 1. Story M, Kaphingst KM, Robinson-O'Brien R, Glanz K. Creating healthy food and eating environments: policy and environmental approaches. Annu Rev Public Health 2008; 29: 253-272.ArticlePubMed
• 2. World Health Organization. Global strategy on diet, physical activity, and health [Internet]. cited 2016 Sep 21]. Available from: http://www.who.int/dietphysicalactivity/.
• 3. Institute of Medicine. Health and Behavior: The Interplay of Biological, Behavioral, and Societal Influences. Washington, DC: National Academy Press; 2001.
• 4. Kumanyika S, Jeffery RW, Morabia A, Ritenbaugh C, Antipatis VJ. Obesity prevention: the case for action. Int J Obes Relat Metab Disord 2002; 26(3): 425-436.ArticlePubMedPDF
• 5. Koplan JP, Dietz WH. Caloric imbalance and public health policy. JAMA 1999; 282(16): 1579-1581.ArticlePubMed
• 6. Glanz K, Sallis JF, Saelens BE, Frank LD. Healthy nutrition environments: concepts and measures. Am J Health Promot 2005; 19(5): 330-333.ArticlePubMedPDF
• 7. National Cancer Institute (US). Measures of the food environment [Internet]. National Cancer Institute; 2016; cited 2016 Sep 21]. Available from: http://epi.grants.cancer.gov/mfe./.
• 8. Health Canada. Measuring the Food Environment in Canada [Internet]. Health Canada: 2013; cited 2016 Sep 21]. Available from:http://www.hc-sc.gc.ca/fn-an/nutrition/pol/som-ex-sum-environ-eng.php.
• 9. Charreire H, Casey R, Salze P, Simon C, Chaix B, Banos A, et al. Measuring the food environment using geographical information systems: a methodological review. Public Health Nutr 2010; 13(11): 1773-1785.ArticlePubMed
• 10. Fraser LK, Edwards KL, Cade J, Clarke GP. The geography of fast food outlets: a review. Int J Environ Res Public Health 2010; 7(5): 2290-2308.ArticlePubMedPMC
• 11. Fleischhacker SE, Evenson KR, Rodriguez DA, Ammerman AS. A systematic review of fast food access studies. Obes Rev 2011; 12(5): e460-e471.ArticlePubMed
• 12. McKinnon RA, Reedy J, Morrissette MA, Lytle LA, Yaroch AL. Measures of the food environment: a compilation of the literature, 1990-2007. Am J Prev Med 2009; 36(4): S124-S133.PubMed
• 13. Athens JK, Duncan DT, Elbel B. Proximity to fast-food outlets and supermarkets as predictors of fast-food dining frequency. J Acad Nutr Diet 2016; 116(8): 1266-1275.ArticlePubMedPMC
• 14. Sharkey JR, Johnson CM, Dean WR, Horel SA. Association between proximity to and coverage of traditional fast-food restaurants and non-traditional fast-food outlets and fast-food consumption among rural adults. Int J Health Geogr 2011; 10(1): 37.ArticlePubMedPMC
• 15. Kruger DJ, Greenberg E, Murphy JB, DiFazio LA, Youra KR. Local concentration of fast-food outlets is associated with poor nutrition and obesity. Am J Health Promot 2014; 28(5): 340-343.ArticlePubMedPDF
• 16. Reitzel LR, Regan SD, Nguyen N, Cromley EK, Strong LL, Wetter DW, et al. Density and proximity of fast food restaurants and body mass index among African Americans. Am J Public Health 2014; 104(1): 110-116.ArticlePubMedPMC
• 17. Hollands S, Campbell MK, Gilliland J, Sarma S. Association between neighbourhood fast-food and full-service restaurant density and body mass index: a cross-sectional study of Canadian adults. Can J Public Health 2014; 105(3): e172-e178.ArticlePubMedPMCPDF
• 18. Hollands S, Campbell MK, Gilliland J, Sarma S. A spatial analysis of the association between restaurant density and body mass index in Canadian adults. Prev Med 2013; 57(4): 258-264.ArticlePubMed
• 19. De Vogli R, Kouvonen A, Gimeno D. 'Globesization': ecological evidence on the relationship between fast food outlets and obesity among 26 advanced economies. Crit Public Health 2011; 21(4): 395-402.Article
• 20. Ministry of Health and Welfare, Korea Centers for Disease Control and Prevention. Korea Health Statistics 2014: Korea National Health and Nutrition Examination Survey (KNHANES VI-2). Sejong: Ministry of Health and Welfare; 2015.
• 21. Lee Y, Shim JE, Yoon J. Change of children's meal structure in terms of temporal and spatial dimensions : analysis of the data from the Korea National Health and Nutrition Examination Surveys of 1998 and 2009. Korean J Community Nutr 2012; 17(1): 109-118.Article
• 22. Heo GJ, Nam SY, Lee SK, Chung SJ, Yoon JH. The relationship between high energy/low nutrient food consumption and obesity among Korean children and adolescents. Korean J Community Nutr 2012; 17(2): 226-242.Article
• 23. Statistics Korea. 1994-2014 Census on Establishments [Internet]. Statistics Korea; 2016; cited 2016 Sep 21]. Available from: https://mdis.kostat.go.kr.
• 24. Kweon S, Kim Y, Jang MJ, Kim Y, Kim K, Choi S, et al. Data resource profile: the Korea National Health and Nutrition Examination Survey (KNHANES). Int J Epidemiol 2014; 43(1): 69-77.ArticlePubMedPMC
• 25. Macintyre S, McKay L, Cummins S, Burns C. Out-of-home food outlets and area deprivation: case study in Glasgow, UK. Int J Behav Nutr Phys Act 2005; 2(1): 16.ArticlePubMedPMCPDF
• 26. Macintyre S, Macdonald L, Ellaway A. Do poorer people have poorer access to local resources and facilities? The distribution of local resources by area deprivation in Glasgow, Scotland. Soc Sci Med 2008; 67(6): 900-914.ArticlePubMedPMC
• 27. Thornton LE, Crawford DA, Ball K. Neighbourhood-socioeconomic variation in women's diet: The role of nutrition environments. Eur J Clin Nutr 2010; 64(12): 1423-1432.ArticlePubMedPDF
• 28. Block JP, Scribner RA, DeSalvo KB. Fast food, race/ethnicity, and income: a geographic analysis. Am J Prev Med 2004; 27(3): 211-217.ArticlePubMed
• 29. Cummins SC, McKay L, MacIntyre S. McDonald″s restaurants and neighborhood deprivation in Scotland and England. Am J Prev Med 2005; 29(4): 308-310.ArticlePubMed
• 30. Lewis LB, Sloane DC, Nascimento LM, Diamant AL, Guinyard JJ, Yancey AK, et al. African Americans″ access to healthy food options in south Los Angeles restaurants. Am J Public Health 2005; 95(4): 668-673.ArticlePubMedPMC
• 31. Macdonald L, Cummins S, Macintyre S. Neighbourhood fast food environment and area deprivation substitution or concentration? Appetite 2007; 49(1): 251-254.ArticlePubMed
• 32. Pearce J, Blakely T, Witten K, Bartie P. Neighborhood deprivation and access to fast-food retailing: a national study. Am J Prev Med 2007; 32(5): 375-382.PubMed
• 33. Hemphill E, Raine K, Spence JC, Smoyer-Tomic KE. Exploring obesogenic food environments in Edmonton, Canada: the association between socioeconomic factors and fast-food outlet access. Am J Health Promot 2008; 22(6): 426-432.ArticlePubMedPDF
• 34. Smoyer-Tomic KE, Spence JC, Raine KD, Amrhein C, Cameron N, Yasenovskiy V, et al. The association between neighborhood socioeconomic status and exposure to supermarkets and fast food outlets. Health Place 2008; 14(4): 740-754.ArticlePubMed
• 35. Kim SA, Choe JS, Joung H, Jang MJ, Kim Y, Lee SE. Comparison of the distribution and accessibility of restaurants in urban area and rural area. J Nutr Health 2014; 47(6): 475-483.Article
• 36. Joo S, Ju S, Chang H. Comparison of fast food consumption and dietary guideline practices for children and adolescents by clustering of fast food outlets around schools in the Gyeonggi area of Korea. Asia Pac J Clin Nutr 2015; 24(2): 299-307.PubMed
• 37. Chung SJ, Kang SH, Song SM, Ryu SH, Yoon J. Nutritional quality of Korean adults' consumption of lunch prepared at home, commercial places, and institutions: analysis of the data from the 2001 National Health and Nutrition Survey. Korean J Nutr 2006; 39(8): 841-849.
• 38. Suh Y, Kang J, Kim H, Chung YJ. Comparison of nutritional status of the Daejeon metropolitan citizens by frequency of eating out. Korean J Nutr 2010; 43(2): 171-180.Article
• 39. Lee HS. Studies on salt intake through eat-out foods in Andong area. Korean J Soc Food Sci 1997; 13(3): 314-318.
• 40. Polsky JY, Moineddin R, Dunn JR, Glazier RH, Booth GL. Absolute and relative densities of fast-food versus other restaurants in relation to weight status: Does restaurant mix matter? Prev Med 2016; 82: 28-34.ArticlePubMed
• 41. Thornton LE, Lamb KE, Ball K. Employment status, residential and workplace food environments: associations with women's eating behaviours. Health Place 2013; 24: 80-89.ArticlePubMed
• 42. Burgoine T, Forouhi NG, Griffin SJ, Wareham NJ, Monsivais P. Associations between exposure to takeaway food outlets, takeaway food consumption, and body weight in Cambridgeshire, UK: Population based, cross-sectional study. BMJ 2014; 348: g1464.ArticlePubMedPMC
• 43. Rundle A, Neckerman KM, Freeman L, Lovasi GS, Purciel M, Quinn J, et al. Neighborhood food environment and walkability predict obesity in New York City. Environ Health Perspect 2009; 117(3): 442-447.ArticlePubMed

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