IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i12p6484-d575697.html
   My bibliography  Save this article

Methods to Address Self-Selection and Reverse Causation in Studies of Neighborhood Environments and Brain Health

Author

Listed:
  • Lilah M. Besser

    (Department of Urban and Regional Planning, Institute for Human Health and Disease Intervention (I-HEALTH), Florida Atlantic University, Boca Raton, FL 33431, USA)

  • Willa D. Brenowitz

    (Departments of Psychiatry and Behavioral Sciences and Epidemiology & Biostatistics, University of California San Francisco, San Francisco, CA 94121, USA)

  • Oanh L. Meyer

    (Department of Neurology, University of California Davis, Sacramento, CA 95817, USA)

  • Serena Hoermann

    (Center for Urban and Environmental Solutions (CUES), Department of Urban and Regional Planning, Florida Atlantic University, Boca Raton, FL 33431, USA)

  • John Renne

    (Center for Urban and Environmental Solutions (CUES), Department of Urban and Regional Planning, Florida Atlantic University, Boca Raton, FL 33431, USA)

Abstract

Preliminary evidence suggests that neighborhood environments, such as socioeconomic disadvantage, pedestrian and physical activity infrastructure, and availability of neighborhood destinations (e.g., parks), may be associated with late-life cognitive functioning and risk of Alzheimer’s disease and related disorders (ADRD). The supposition is that these neighborhood characteristics are associated with factors such as mental health, environmental exposures, health behaviors, and social determinants of health that in turn promote or diminish cognitive reserve and resilience in later life. However, observed associations may be biased by self-selection or reverse causation, such as when individuals with better cognition move to denser neighborhoods because they prefer many destinations within walking distance of home, or when individuals with deteriorating health choose residences offering health services in neighborhoods in rural or suburban areas (e.g., assisted living). Research on neighborhood environments and ADRD has typically focused on late-life brain health outcomes, which makes it difficult to disentangle true associations from associations that result from reverse causality. In this paper, we review study designs and methods to help reduce bias due to reverse causality and self-selection, while drawing attention to the unique aspects of these approaches when conducting research on neighborhoods and brain aging.

Suggested Citation

  • Lilah M. Besser & Willa D. Brenowitz & Oanh L. Meyer & Serena Hoermann & John Renne, 2021. "Methods to Address Self-Selection and Reverse Causation in Studies of Neighborhood Environments and Brain Health," IJERPH, MDPI, vol. 18(12), pages 1-19, June.
  • Handle: RePEc:gam:jijerp:v:18:y:2021:i:12:p:6484-:d:575697
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/12/6484/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/18/12/6484/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Scott C. Brown & Tatiana Perrino & Joanna Lombard & Kefeng Wang & Matthew Toro & Tatjana Rundek & Carolina Marinovic Gutierrez & Chuanhui Dong & Elizabeth Plater-Zyberk & Maria I. Nardi & Jack Kardys , 2018. "Health Disparities in the Relationship of Neighborhood Greenness to Mental Health Outcomes in 249,405 U.S. Medicare Beneficiaries," IJERPH, MDPI, vol. 15(3), pages 1-11, March.
    2. Nuala A Sheehan & Vanessa Didelez & Paul R Burton & Martin D Tobin, 2008. "Mendelian Randomisation and Causal Inference in Observational Epidemiology," PLOS Medicine, Public Library of Science, vol. 5(8), pages 1-6, August.
    3. Grafova, Irina B. & Freedman, Vicki A. & Lurie, Nicole & Kumar, Rizie & Rogowski, Jeannette, 2014. "The difference-in-difference method: Assessing the selection bias in the effects of neighborhood environment on health," Economics & Human Biology, Elsevier, vol. 13(C), pages 20-33.
    4. Imbens, Guido W. & Lemieux, Thomas, 2008. "Regression discontinuity designs: A guide to practice," Journal of Econometrics, Elsevier, vol. 142(2), pages 615-635, February.
    5. Frank, Lawrence Douglas & Saelens, Brian E. & Powell, Ken E. & Chapman, James E., 2007. "Stepping towards causation: Do built environments or neighborhood and travel preferences explain physical activity, driving, and obesity?," Social Science & Medicine, Elsevier, vol. 65(9), pages 1898-1914, November.
    6. Cao, Xinyu, 2006. "The Causal Relationship between the Built Environment and Personal Travel Choice: Evidence from Northern California," University of California Transportation Center, Working Papers qt07q5p340, University of California Transportation Center.
    7. Besser, Lilah M. & Rodriguez, Daniel A. & McDonald, Noreen & Kukull, Walter A. & Fitzpatrick, Annette L. & Rapp, Stephen R. & Seeman, Teresa, 2018. "Neighborhood built environment and cognition in non-demented older adults: The Multi-Ethnic Study of Atherosclerosis," Social Science & Medicine, Elsevier, vol. 200(C), pages 27-35.
    8. Kristen Cooksey-Stowers & Marlene B. Schwartz & Kelly D. Brownell, 2017. "Food Swamps Predict Obesity Rates Better Than Food Deserts in the United States," IJERPH, MDPI, vol. 14(11), pages 1-20, November.
    9. Dunn, Richard A. & Sharkey, Joseph R. & Horel, Scott, 2012. "The effect of fast-food availability on fast-food consumption and obesity among rural residents: An analysis by race/ethnicity," Economics & Human Biology, Elsevier, vol. 10(1), pages 1-13.
    10. Vicki A. Freedman & Brenda C. Spillman, 2014. "The Residential Continuum From Home to Nursing Home: Size, Characteristics and Unmet Needs of Older Adults," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 69(Suppl_1), pages 42-50.
    11. Leventhal, T. & Brooks-Gunn, J., 2003. "Moving to Oppurtunity: An Experimental Study of Neighborhood Effects on Mental Health," American Journal of Public Health, American Public Health Association, vol. 93(9), pages 1576-1582.
    12. Hirsch, J.A. & Roux, A.V.D. & Moore, K.A. & Evenson, K.R. & Rodriguez, D.A., 2014. "Change in walking and body mass index following residential relocation: The multi-ethnic study of atherosclerosis," American Journal of Public Health, American Public Health Association, vol. 104(3), pages 49-56.
    13. Mark P.C. Cherrie & Niamh K. Shortt & Catharine Ward Thompson & Ian J. Deary & Jamie R. Pearce, 2019. "Association Between the Activity Space Exposure to Parks in Childhood and Adolescence and Cognitive Aging in Later Life," IJERPH, MDPI, vol. 16(4), pages 1-13, February.
    Full references (including those not matched with items on IDEAS)

    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. Peter James & Jaime E. Hart & Mariana C. Arcaya & Diane Feskanich & Francine Laden & S.V. Subramanian, 2015. "Neighborhood Self-Selection: The Role of Pre-Move Health Factors on the Built and Socioeconomic Environment," IJERPH, MDPI, vol. 12(10), pages 1-16, October.
    2. Kajosaari, Anna & Hasanzadeh, Kamyar & Kyttä, Marketta, 2019. "Residential dissonance and walking for transport," Journal of Transport Geography, Elsevier, vol. 74(C), pages 134-144.
    3. Xinyu Cao & Patricia L. Mokhtarian, 2012. "The connections among accessibility, self- selection and walking behaviour: a case study of Northern California residents," Chapters, in: Karst T. Geurs & Kevin J. Krizek & Aura Reggiani (ed.), Accessibility Analysis and Transport Planning, chapter 5, pages 73-95, Edward Elgar Publishing.
    4. Finlay, Jessica & Esposito, Michael & Langa, Kenneth M. & Judd, Suzanne & Clarke, Philippa, 2022. "Cognability: An Ecological Theory of neighborhoods and cognitive aging," Social Science & Medicine, Elsevier, vol. 309(C).
    5. Winters, Meghan & Voss, Christine & Ashe, Maureen C. & Gutteridge, Kaitlyn & McKay, Heather & Sims-Gould, Joanie, 2015. "Where do they go and how do they get there? Older adults' travel behaviour in a highly walkable environment," Social Science & Medicine, Elsevier, vol. 133(C), pages 304-312.
    6. Sun, Bindong & Yan, Hong & Zhang, Tinglin, 2017. "Built environmental impacts on individual mode choice and BMI: Evidence from China," Journal of Transport Geography, Elsevier, vol. 63(C), pages 11-21.
    7. Wolday, Fitwi & Cao, Jason & Næss, Petter, 2018. "Examining factors that keep residents with high transit preference away from transit-rich zones and associated behavior outcomes," Journal of Transport Geography, Elsevier, vol. 66(C), pages 224-234.
    8. Yi Lu & Long Chen & Yiyang Yang & Zhonghua Gou, 2018. "The Association of Built Environment and Physical Activity in Older Adults: Using a Citywide Public Housing Scheme to Reduce Residential Self-Selection Bias," IJERPH, MDPI, vol. 15(9), pages 1-13, September.
    9. Jonas De Vos & Long Cheng & Frank Witlox, 2021. "Do changes in the residential location lead to changes in travel attitudes? A structural equation modeling approach," Transportation, Springer, vol. 48(4), pages 2011-2034, August.
    10. Chenyang Wang & Zhiping Zhen & Nan Zhao & Chenlin Zhao, 2021. "Associations between Fast-Food Restaurants Surrounding Kindergartens and Childhood Obesity: Evidence from China," IJERPH, MDPI, vol. 18(17), pages 1-15, September.
    11. Zhao, Chunli & Nielsen, Thomas Alexander Sick & Olafsson, Anton Stahl & Carstensen, Trine Agervig & Meng, Xiaoying, 2018. "Urban form, demographic and socio-economic correlates of walking, cycling, and e-biking: Evidence from eight neighborhoods in Beijing," Transport Policy, Elsevier, vol. 64(C), pages 102-112.
    12. Marlon G. Boarnet & Kenneth Joh & Walter Siembab & William Fulton & Mai Thi Nguyen, 2011. "Retrofitting the Suburbs to Increase Walking: Evidence from a Land-use-Travel Study," Urban Studies, Urban Studies Journal Limited, vol. 48(1), pages 129-159, January.
    13. Li, Jingjing & Auchincloss, Amy H. & Yang, Yong & Rodriguez, Daniel A. & Sánchez, Brisa N., 2020. "Neighborhood characteristics and transport walking: Exploring multiple pathways of influence using a structural equation modeling approach," Journal of Transport Geography, Elsevier, vol. 85(C).
    14. Kristen Cooksey-Stowers & Marlene B. Schwartz & Kelly D. Brownell, 2017. "Food Swamps Predict Obesity Rates Better Than Food Deserts in the United States," IJERPH, MDPI, vol. 14(11), pages 1-20, November.
    15. Yi Lu, 2018. "The Association of Urban Greenness and Walking Behavior: Using Google Street View and Deep Learning Techniques to Estimate Residents’ Exposure to Urban Greenness," IJERPH, MDPI, vol. 15(8), pages 1-15, July.
    16. Lilah M. Besser & Marcia Pescador Jimenez & Cameron J. Reimer & Oanh L. Meyer & Diana Mitsova & Kristen M. George & Paris B. Adkins-Jackson & James E. Galvin, 2023. "Diversity of Studies on Neighborhood Greenspace and Brain Health by Racialized/Ethnic Group and Geographic Region: A Rapid Review," IJERPH, MDPI, vol. 20(9), pages 1-22, April.
    17. Persson, Petra & Qiu, Xinyao & Rossin-Slater, Maya, 2021. "Family Spillover Effects of Marginal Diagnoses: The Case of ADHD," IZA Discussion Papers 14020, Institute of Labor Economics (IZA).
    18. KAMKOUM, Arnaud Cedric, 2023. "The Federal Reserve’s Response to the Global Financial Crisis and its Effects: An Interrupted Time-Series Analysis of the Impact of its Quantitative Easing Programs," Thesis Commons d7pvg, Center for Open Science.
    19. Francesca Carta & Lucia Rizzica, 2015. "Female employment and pre-kindergarten: on the uninteded effects of an Italian reform," Temi di discussione (Economic working papers) 1030, Bank of Italy, Economic Research and International Relations Area.
    20. Dong, Yingying, 2010. "Jumpy or Kinky? Regression Discontinuity without the Discontinuity," MPRA Paper 25461, University Library of Munich, Germany.

    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:gam:jijerp:v:18:y:2021:i:12:p:6484-:d:575697. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.