IDEAS home Printed from https://ideas.repec.org/a/eee/socmed/v67y2008i12p1951-1958.html
   My bibliography  Save this article

Personal and neighborhood socioeconomic status and indices of neighborhood walk-ability predict body mass index in New York City

Author

Listed:
  • Rundle, Andrew
  • Field, Sam
  • Park, Yoosun
  • Freeman, Lance
  • Weiss, Christopher C.
  • Neckerman, Kathryn

Abstract

Past research has observed inverse associations between neighborhood and personal level measures of socioeconomic status and body mass index (BMI), but has not assessed how personal and neighborhood-level measures might interact together to predict BMI. Using a sample of 13,102 adult residents of New York City who participated in a health survey, cross-sectional multi-level analyses assessed whether personal income, education and Zip code-level poverty rates were associated with BMI. Demographic, income, education and objectively measured height and weight data were collected in the survey and poverty rates and the proportion of Black and Hispanic residents in the subject's Zip code were retrieved from the 2000 Census. Zip code-level population density and land use mix, indices of neighborhood walk-ability which are often higher in lower income neighborhoods and are associated with lower BMI, were also measured. After controlling for individual and Zip code-level demographic characteristics, increasing income was associated with lower BMI in women but not in men, and college and graduate level education was associated with lower BMI in both men and women. After control for income and individual and Zip code-level demographic characteristics, higher Zip code poverty rate was unassociated with BMI. However, as expected, indices of neighborhood walk-ability acted as substantial inverse confounders in the relationship between Zip code poverty rate and BMI. After further adjustment for indices of neighborhood walk-ability, Zip code poverty rate became significantly, and positively associated with BMI in women. Among women, the inverse association between income and BMI was significantly stronger in richer compared to poorer Zip codes. In men and women, the association between college and graduate education and lower BMI was significantly stronger in richer versus poorer Zip codes. These analyses suggest that neighborhood socioeconomic context influences how personal socioeconomic status interact in predicting boby size.

Suggested Citation

  • Rundle, Andrew & Field, Sam & Park, Yoosun & Freeman, Lance & Weiss, Christopher C. & Neckerman, Kathryn, 2008. "Personal and neighborhood socioeconomic status and indices of neighborhood walk-ability predict body mass index in New York City," Social Science & Medicine, Elsevier, vol. 67(12), pages 1951-1958, December.
    • Handle: RePEc:eee:socmed:v:67:y:2008:i:12:p:1951-1958
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0277-9536(08)00487-5
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Robert, Stephanie A. & Reither, Eric N., 2004. "A multilevel analysis of race, community disadvantage, and body mass index among adults in the US," Social Science & Medicine, Elsevier, vol. 59(12), pages 2421-2434, December.
    2. Lopez, R., 2004. "Urban sprawl and risk for being overweight or obese," American Journal of Public Health, American Public Health Association, vol. 94(9), pages 1574-1579.
    3. Ball, Kylie & Crawford, David, 2005. "Socioeconomic status and weight change in adults: a review," Social Science & Medicine, Elsevier, vol. 60(9), pages 1987-2010, May.
    4. Moore, L.V. & Diez Roux, A.V., 2006. "Associations of neighborhood characteristics with the location and type of food stores," American Journal of Public Health, American Public Health Association, vol. 96(2), pages 325-331.
    5. Krieger, N. & Chen, J.T. & Waterman, P.D. & Rehkopf, D.H. & Subramanian, S.V., 2003. "Race/Ethnicity, Gender, and Monitoring Socioeconomic Gradients in Health: Comparison of Area-Based Socioeconomic Measures - The Public Health Disparities Geocoding Project," American Journal of Public Health, American Public Health Association, vol. 93(10), pages 1655-1671.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Akresh, Ilana Redstone & Do, D. Phuong & Frank, Reanne, 2016. "Segmented assimilation, neighborhood disadvantage, and Hispanic immigrant health," Social Science & Medicine, Elsevier, vol. 149(C), pages 114-121.
    2. Sund, Erik Reidar & Jones, Andy & Midthjell, Kristian, 2010. "Individual, family, and area predictors of BMI and BMI change in an adult Norwegian population: Findings from the HUNT study," Social Science & Medicine, Elsevier, vol. 70(8), pages 1194-1202, April.
    3. Qian Wang & Guie Li & Min Weng, 2024. "Unraveling the Dynamic Relationship between Neighborhood Deprivation and Walkability over Time: A Machine Learning Approach," Land, MDPI, vol. 13(5), pages 1-19, May.
    4. Robinovich, Jossiana & Bosma, Hans & Borne, Bart van der & Ossa, Ximena & Muñoz, Sergio & Krumeich, Anja, 2021. "Is a ‘culture of plus-size women’ the independent effect of neighborhood disadvantage on female BMI? A cross-sectional study in two Chilean Municipalities," Social Science & Medicine, Elsevier, vol. 280(C).
    5. Wen, Ming & Maloney, Thomas N., 2014. "Neighborhood socioeconomic status and BMI differences by immigrant and legal status: Evidence from Utah," Economics & Human Biology, Elsevier, vol. 12(C), pages 120-131.
    6. Park, Yoosun & Quinn, James & Florez, Karen & Jacobson, Judith & Neckerman, Kathryn & Rundle, Andrew, 2011. "Hispanic immigrant women's perspective on healthy foods and the New York City retail food environment: A mixed-method study," Social Science & Medicine, Elsevier, vol. 73(1), pages 13-21, July.
    7. Pengxiang Zhao & Mei-Po Kwan & Suhong Zhou, 2018. "The Uncertain Geographic Context Problem in the Analysis of the Relationships between Obesity and the Built Environment in Guangzhou," IJERPH, MDPI, vol. 15(2), pages 1-20, February.
    8. Boylan, Jennifer Morozink & Robert, Stephanie A., 2017. "Neighborhood SES is particularly important to the cardiovascular health of low SES individuals," Social Science & Medicine, Elsevier, vol. 188(C), pages 60-68.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chen, Duan-Rung & Wen, Tzai-Hung, 2010. "Socio-spatial patterns of neighborhood effects on adult obesity in Taiwan: A multi-level model," Social Science & Medicine, Elsevier, vol. 70(6), pages 823-833, March.
    2. Wen, Ming & Maloney, Thomas N., 2014. "Neighborhood socioeconomic status and BMI differences by immigrant and legal status: Evidence from Utah," Economics & Human Biology, Elsevier, vol. 12(C), pages 120-131.
    3. Dustin T. Duncan & Jared Aldstadt & John Whalen & Kellee White & Márcia C. Castro & David R. Williams, 2012. "Space, race, and poverty: Spatial inequalities in walkable neighborhood amenities?," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 26(17), pages 409-448.
    4. Anura Amarasinghe & Gerard D'Souza & Cheryl Brown & Tatiana Borisova, 2006. "A Spatial Analysis of Obesity in West Virginia," Working Papers Working Paper 2006-13, Regional Research Institute, West Virginia University.
    5. Chang, Virginia W., 2006. "Racial residential segregation and weight status among US adults," Social Science & Medicine, Elsevier, vol. 63(5), pages 1289-1303, September.
    6. Hamdi Lemamsha & Chris Papadopoulos & Gurch Randhawa, 2018. "Perceived Environmental Factors Associated with Obesity in Libyan Men and Women," IJERPH, MDPI, vol. 15(2), pages 1-16, February.
    7. Brunello, Giorgio & D'Hombres, Beatrice, 2007. "Does body weight affect wages?: Evidence from Europe," Economics & Human Biology, Elsevier, vol. 5(1), pages 1-19, March.
    8. Umberson, Debra & Liu, Hui & Mirowsky, John & Reczek, Corinne, 2011. "Parenthood and trajectories of change in body weight over the life course," Social Science & Medicine, Elsevier, vol. 73(9), pages 1323-1331.
    9. repec:rri:wpaper:200613 is not listed on IDEAS
    10. Boncinelli, Fabio & Riccioli, Francesco & Marone, Enrico, 2015. "Do forests help to keep my body mass index low?," Forest Policy and Economics, Elsevier, vol. 54(C), pages 11-17.
    11. Baum II, Charles L. & Ruhm, Christopher J., 2009. "Age, socioeconomic status and obesity growth," Journal of Health Economics, Elsevier, vol. 28(3), pages 635-648, May.
    12. Butler, Danielle C. & Thurecht, Linc & Brown, Laurie & Konings, Paul, 2013. "Social exclusion, deprivation and child health: a spatial analysis of ambulatory care sensitive conditions in children aged 0–4 years in Victoria, Australia," Social Science & Medicine, Elsevier, vol. 94(C), pages 9-16.
    13. Ivan Parise & Penelope Abbott & Steven Trankle, 2021. "Drivers to Obesity—A Study of the Association between Time Spent Commuting Daily and Obesity in the Nepean Blue Mountains Area," IJERPH, MDPI, vol. 19(1), pages 1-14, December.
    14. Brueckner, Jan K. & Largey, Ann G., 2008. "Social interaction and urban sprawl," Journal of Urban Economics, Elsevier, vol. 64(1), pages 18-34, July.
    15. Brett Theodos & Christina Stacy & Daniel Teles & Chris Davis & Ananya Hariharan, 2022. "Place‐based investment and neighborhood change: The impacts of New Markets Tax Credits on jobs, poverty, and neighborhood composition," Journal of Regional Science, Wiley Blackwell, vol. 62(4), pages 1092-1121, September.
    16. Philip B Mason & Frank M. Howell & Jeremy R. Porter, 2014. "Examining Rural-Urban Obesity Trends among Youth in the U.S.: Testing the Socioeconomic Gradient Hypothesis," International Journal of Business and Social Research, MIR Center for Socio-Economic Research, vol. 4(12), pages 27-42, December.
    17. Kristína Bilková & František Križan, 2015. "Mapping of Grocery Stores in Slovak Countryside in Context of Food Deserts," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 63(5), pages 1633-1638.
    18. Chen, Susan E. & Liu, Jing & Binkley, James K., 2012. "An Exploration of the Relationship Between Income and Eating Behavior," Agricultural and Resource Economics Review, Cambridge University Press, vol. 41(1), pages 82-91, April.
    19. David Gálvez Ruiz & Pilar Diaz Cuevas & Olta Braçe & Marco Garrido-Cumbrera, 2018. "Developing an Index to Measure Sub-municipal Level Urban Sprawl," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 140(3), pages 929-952, December.
    20. Philip B Mason & Frank M. Howell & Jeremy R. Porter, 2014. "Examining Rural-Urban Obesity Trends among Youth in the U.S.: Testing the Socioeconomic Gradient Hypothesis," International Journal of Business and Social Research, LAR Center Press, vol. 4(12), pages 27-42, December.
    21. Stephanie A. Prince & Elizabeth A. Kristjansson & Katherine Russell & Jean-Michel Billette & Michael Sawada & Amira Ali & Mark S. Tremblay & Denis Prud’homme, 2011. "A Multilevel Analysis of Neighbourhood Built and Social Environments and Adult Self-Reported Physical Activity and Body Mass Index in Ottawa, Canada," IJERPH, MDPI, vol. 8(10), pages 1-26, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:socmed:v:67:y:2008:i:12:p:1951-1958. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/315/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.