{"title":"Neighborhood affluence protects against antenatal smoking: Evidence from a spatial multiple membership model","authors":"Jennifer B. Kane, Ehsan Farshchi","doi":"10.1080/08898480.2018.1553399","DOIUrl":null,"url":null,"abstract":"ABSTRACT A spatial multiple membership model formalizes the effect of neighborhood affluence on antenatal smoking. The data are geocoded New Jersey birth certificate records linked to United States census tract-level data from 1999 to 2007. Neighborhood affluence shows significant spatial autocorrelation and local clustering. Better model fit is observed when incorporating the spatial clustering of neighborhood affluence into multivariate analyses. Relative to the spatial multiple membership model, the multilevel model that ignores spatial clustering produced downwardly biased standard errors; the effective sample size of the key parameter of interest (neighborhood affluence) is also lower. Residents of communities located in high-high affluence clusters likely have better access to health-promoting institutions that regulate antenatal smoking behaviors.","PeriodicalId":49859,"journal":{"name":"Mathematical Population Studies","volume":"26 1","pages":"186 - 207"},"PeriodicalIF":1.4000,"publicationDate":"2019-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/08898480.2018.1553399","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mathematical Population Studies","FirstCategoryId":"90","ListUrlMain":"https://doi.org/10.1080/08898480.2018.1553399","RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"DEMOGRAPHY","Score":null,"Total":0}
引用次数: 3
Abstract
ABSTRACT A spatial multiple membership model formalizes the effect of neighborhood affluence on antenatal smoking. The data are geocoded New Jersey birth certificate records linked to United States census tract-level data from 1999 to 2007. Neighborhood affluence shows significant spatial autocorrelation and local clustering. Better model fit is observed when incorporating the spatial clustering of neighborhood affluence into multivariate analyses. Relative to the spatial multiple membership model, the multilevel model that ignores spatial clustering produced downwardly biased standard errors; the effective sample size of the key parameter of interest (neighborhood affluence) is also lower. Residents of communities located in high-high affluence clusters likely have better access to health-promoting institutions that regulate antenatal smoking behaviors.
期刊介绍:
Mathematical Population Studies publishes carefully selected research papers in the mathematical and statistical study of populations. The journal is strongly interdisciplinary and invites contributions by mathematicians, demographers, (bio)statisticians, sociologists, economists, biologists, epidemiologists, actuaries, geographers, and others who are interested in the mathematical formulation of population-related questions.
The scope covers both theoretical and empirical work. Manuscripts should be sent to Manuscript central for review. The editor-in-chief has final say on the suitability for publication.