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An Original Stepwise Multilevel Logistic Regression Analysis of Discriminatory Accuracy: The Case of Neighbourhoods and Health

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  • Juan Merlo
  • Philippe Wagner
  • Nermin Ghith
  • George Leckie

Abstract

Background and Aim: Many multilevel logistic regression analyses of “neighbourhood and health” focus on interpreting measures of associations (e.g., odds ratio, OR). In contrast, multilevel analysis of variance is rarely considered. We propose an original stepwise analytical approach that distinguishes between “specific” (measures of association) and “general” (measures of variance) contextual effects. Performing two empirical examples we illustrate the methodology, interpret the results and discuss the implications of this kind of analysis in public health. Methods: We analyse 43,291 individuals residing in 218 neighbourhoods in the city of Malmö, Sweden in 2006. We study two individual outcomes (psychotropic drug use and choice of private vs. public general practitioner, GP) for which the relative importance of neighbourhood as a source of individual variation differs substantially. In Step 1 of the analysis, we evaluate the OR and the area under the receiver operating characteristic (AUC) curve for individual-level covariates (i.e., age, sex and individual low income). In Step 2, we assess general contextual effects using the AUC. Finally, in Step 3 the OR for a specific neighbourhood characteristic (i.e., neighbourhood income) is interpreted jointly with the proportional change in variance (i.e., PCV) and the proportion of ORs in the opposite direction (POOR) statistics. Results: For both outcomes, information on individual characteristics (Step 1) provide a low discriminatory accuracy (AUC = 0.616 for psychotropic drugs; = 0.600 for choosing a private GP). Accounting for neighbourhood of residence (Step 2) only improved the AUC for choosing a private GP (+0.295 units). High neighbourhood income (Step 3) was strongly associated to choosing a private GP (OR = 3.50) but the PCV was only 11% and the POOR 33%. Conclusion: Applying an innovative stepwise multilevel analysis, we observed that, in Malmö, the neighbourhood context per se had a negligible influence on individual use of psychotropic drugs, but appears to strongly condition individual choice of a private GP. However, the latter was only modestly explained by the socioeconomic circumstances of the neighbourhoods. Our analyses are based on real data and provide useful information for understanding neighbourhood level influences in general and on individual use of psychotropic drugs and choice of GP in particular. However, our primary aim is to illustrate how to perform and interpret a multilevel analysis of individual heterogeneity in social epidemiology and public health. Our study shows that neighbourhood “effects” are not properly quantified by reporting differences between neighbourhood averages but rather by measuring the share of the individual heterogeneity that exists at the neighbourhood level.

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  • Juan Merlo & Philippe Wagner & Nermin Ghith & George Leckie, 2016. "An Original Stepwise Multilevel Logistic Regression Analysis of Discriminatory Accuracy: The Case of Neighbourhoods and Health," PLOS ONE, Public Library of Science, vol. 11(4), pages 1-31, April.
  • Handle: RePEc:plo:pone00:0153778
    DOI: 10.1371/journal.pone.0153778
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    References listed on IDEAS

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    1. Jon Rasbash & George Leckie & Rebecca Pillinger & Jennifer Jenkins, 2010. "Children's educational progress: partitioning family, school and area effects," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(3), pages 657-682, July.
    2. Alastair H. Leyland & Øyvind Næss, 2009. "The effect of area of residence over the life course on subsequent mortality," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(3), pages 555-578, June.
    3. Klaus Larsen & Jørgen Holm Petersen & Esben Budtz-Jørgensen & Lars Endahl, 2000. "Interpreting Parameters in the Logistic Regression Model with Random Effects," Biometrics, The International Biometric Society, vol. 56(3), pages 909-914, September.
    4. Duncan, Craig & Jones, Kelvyn & Moon, Graham, 1998. "Context, composition and heterogeneity: Using multilevel models in health research," Social Science & Medicine, Elsevier, vol. 46(1), pages 97-117, January.
    5. Anders Skrondal & Sophia Rabe‐Hesketh, 2009. "Prediction in multilevel generalized linear models," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(3), pages 659-687, June.
    6. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    7. George Leckie & Harvey Goldstein, 2009. "The limitations of using school league tables to inform school choice," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(4), pages 835-851, October.
    8. Margaret Pepe & Holly Janes & Gary Longton & Wendy Leisenring & Polly Newcomb, 2004. "Limitations of the Odds Ratio in Gauging the Performance of a Diagnostic or Prognostic Marker," UW Biostatistics Working Paper Series 1035, Berkeley Electronic Press.
    9. Oakes, J. Michael, 2004. "The (mis)estimation of neighborhood effects: causal inference for a practicable social epidemiology," Social Science & Medicine, Elsevier, vol. 58(10), pages 1929-1952, May.
    10. W. J. Browne & S. V. Subramanian & K. Jones & H. Goldstein, 2005. "Variance partitioning in multilevel logistic models that exhibit overdispersion," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(3), pages 599-613, July.
    11. George Leckie & Harvey Goldstein, 2011. "Understanding Uncertainty in School League Tables," Fiscal Studies, Institute for Fiscal Studies, vol. 32(2), pages 207-224, June.
    12. Shai Mulinari & Sol Pia Juárez & Philippe Wagner & Juan Merlo, 2015. "Does Maternal Country of Birth Matter for Understanding Offspring’s Birthweight? A Multilevel Analysis of Individual Heterogeneity in Sweden," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-19, May.
    13. Merlo, Juan & Ohlsson, Henrik & Chaix, Basile & Lichtenstein, Paul & Kawachi, Ichiro & Subramanian, S.V., 2013. "Revisiting causal neighborhood effects on individual ischemic heart disease risk: A quasi-experimental multilevel analysis among Swedish siblings," Social Science & Medicine, Elsevier, vol. 76(C), pages 39-46.
    14. Duncan, Craig & Jones, Kelvyn & Moon, Graham, 1993. "Do places matter? A multi-level analysis of regional variations in health-related behaviour in Britain," Social Science & Medicine, Elsevier, vol. 37(6), pages 725-733, September.
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    3. Garikayi Bernard Chemhaka & Clifford Odimegwu, 2020. "Individual and community factors associated with lifetime fertility in Eswatini: an application of the Easterlin–Crimmins model," Journal of Population Research, Springer, vol. 37(3), pages 291-322, September.
    4. Lobo, Mariana F & Azzone, Vanessa & Lopes, Fernando & Freitas, Alberto & Costa-Pereira, Altamiro & Normand, Sharon-Lise & Teixeira-Pinto, Armando, 2020. "Understanding the large heterogeneity in hospital readmissions and mortality for acute myocardial infarction," Health Policy, Elsevier, vol. 124(7), pages 684-694.

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