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阿维基因组计划中社会经济地位的计算

Computation of Socio-Economic Status in the AWI-Gen Project.

作者信息

Hazelhurst Scott, Boua Palwendé, Choudhury Ananyo, Madala Siyanda, Sengupta Dhriti, Tluway Furahini, Ramsay Michèle

机构信息

Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg.

School of Electrical & Information Engineering, University of the Witwatersrand, Johannesburg, South Africa.

出版信息

medRxiv. 2024 Aug 22:2024.08.22.24312411. doi: 10.1101/2024.08.22.24312411.

DOI:10.1101/2024.08.22.24312411
PMID:39228720
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11370514/
Abstract

Socio-economic status of participants in many public health, epidemiological, and genome-wide association studies is an important trait of interest. It is often used in these studies as a measure of direct interest or as a covariate. The Africa Wits INDEPTH Partnership for Genomic and Environmental Research (AWI-Gen) explores genomic and environmental factors in non-communicable diseases, particularly cardio-metabolic disease. In Phase I of AWI-Gen, approximately 12,000 participants were recruited at six sites in four African countries. Participants were asked questions about asset ownership. This technical note describes how AWI-Gen computed socio-economic status from the asset register.

摘要

许多公共卫生、流行病学和全基因组关联研究中参与者的社会经济地位是一个重要的研究特征。在这些研究中，它经常被用作直接研究的指标或协变量。非洲维特沃特斯兰德大学深入基因组与环境研究合作组织（AWI-Gen）探索非传染性疾病，特别是心血管代谢疾病中的基因组和环境因素。在AWI-Gen的第一阶段，在四个非洲国家的六个地点招募了约12000名参与者。参与者被问及有关资产拥有情况的问题。本技术说明描述了AWI-Gen如何根据资产登记册计算社会经济地位。

相似文献

1
Computation of Socio-Economic Status in the AWI-Gen Project.阿维基因组计划中社会经济地位的计算
medRxiv. 2024 Aug 22:2024.08.22.24312411. doi: 10.1101/2024.08.22.24312411.
2
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Glob Health Epidemiol Genom. 2016 Nov 22;1:e20. doi: 10.1017/gheg.2016.17. eCollection 2016.
3
Kidney damage and associated risk factors in rural and urban sub-Saharan Africa (AWI-Gen): a cross-sectional population study.农村和城市撒哈拉以南非洲地区（AWI-Gen）的肾脏损伤及相关风险因素：一项横断面人群研究。
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Genomic and environmental risk factors for cardiometabolic diseases in Africa: methods used for Phase 1 of the AWI-Gen population cross-sectional study.非洲心脏代谢疾病的基因组和环境风险因素：AWI-Gen 人群横断面研究第一阶段使用的方法。
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Autozygosity influences cardiometabolic disease-associated traits in the AWI-Gen sub-Saharan African study.自交导致 AWI-Gen 撒哈拉以南非洲研究中与心血管代谢疾病相关的特征。
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本文引用的文献

1
Genomic and environmental risk factors for cardiometabolic diseases in Africa: methods used for Phase 1 of the AWI-Gen population cross-sectional study.非洲心脏代谢疾病的基因组和环境风险因素：AWI-Gen 人群横断面研究第一阶段使用的方法。
Glob Health Action. 2018;11(sup2):1507133. doi: 10.1080/16549716.2018.1507133.
2
H3Africa AWI-Gen Collaborative Centre: a resource to study the interplay between genomic and environmental risk factors for cardiometabolic diseases in four sub-Saharan African countries.H3Africa AWI-Gen合作中心：一个用于研究撒哈拉以南非洲四个国家心脏代谢疾病的基因组与环境风险因素之间相互作用的资源。
Glob Health Epidemiol Genom. 2016 Nov 22;1:e20. doi: 10.1017/gheg.2016.17. eCollection 2016.
3
Using Principal Component Analysis to Identify Priority Neighbourhoods for Health Services Delivery by Ranking Socioeconomic Status.
利用主成分分析通过对社会经济地位进行排名来确定卫生服务提供的优先社区。
Online J Public Health Inform. 2016 Sep 15;8(2):e192. doi: 10.5210/ojphi.v8i2.6733. eCollection 2016.
4
Measuring socio-economic position for epidemiological studies in low- and middle-income countries: a methods of measurement in epidemiology paper.测量中低收入国家流行病学研究中的社会经济地位：流行病学方法测量论文。
Int J Epidemiol. 2012 Jun;41(3):871-86. doi: 10.1093/ije/dys037. Epub 2012 Mar 21.
5
Constructing socio-economic status indices: how to use principal components analysis.构建社会经济地位指数：如何使用主成分分析
Health Policy Plan. 2006 Nov;21(6):459-68. doi: 10.1093/heapol/czl029. Epub 2006 Oct 9.