Neighborhood affluence protects against antenatal smoking: Evidence from a spatial multiple membership model

IF 1.4 3区 社会学 Q3 DEMOGRAPHY
Jennifer B. Kane, Ehsan Farshchi
{"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.
社区富裕可以防止产前吸烟:来自空间多成员模型的证据
一个空间多成员模型形式化了社区富裕程度对产前吸烟的影响。这些数据是经过地理编码的新泽西州出生证明记录,与1999年至2007年的美国人口普查数据相关联。邻里富裕表现出显著的空间自相关和局部聚类。当将邻里富裕的空间聚类纳入多变量分析时,可以观察到更好的模型拟合。相对于空间多重隶属度模型,忽略空间聚类的多层模型产生了向下偏的标准误差;感兴趣的关键参数(邻里富裕程度)的有效样本量也较低。位于高-高富裕集群的社区居民可能有更好的机会进入规范产前吸烟行为的健康促进机构。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Mathematical Population Studies
Mathematical Population Studies 数学-数学跨学科应用
CiteScore
3.20
自引率
11.10%
发文量
7
审稿时长
>12 weeks
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.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信