Nationally representative household survey data for studying the interaction between district-level development and individual-level socioeconomic gradients of cardiovascular disease risk factors in India

• Verfasst von: Jung, Lara [VerfasserIn]
• Verfasst von: De Neve, Jan-Walter [VerfasserIn]
• Verfasst von: Chen, Simiao [VerfasserIn]
• Verfasst von: Manne-Goehler, Jennifer [VerfasserIn]
• Verfasst von: Jaacks, Lindsay M. [VerfasserIn]
• Verfasst von: Corsi, Daniel J. [VerfasserIn]
• Verfasst von: Awasthi, Ashish [VerfasserIn]
• Verfasst von: Subramanian, S. V. [VerfasserIn]
• Verfasst von: Vollmer, Sebastian [VerfasserIn]
• Verfasst von: Bärnighausen, Till [VerfasserIn]
• Verfasst von: Geldsetzer, Pascal [VerfasserIn]
• Titel: Nationally representative household survey data for studying the interaction between district-level development and individual-level socioeconomic gradients of cardiovascular disease risk factors in India
• Verf.angabe: Lara Jung, Jan-Walter De Neve, Simiao Chen, Jennifer Manne-Goehler, Lindsay M. Jaacks, Daniel J. Corsi, Ashish Awasthi, S. V. Subramanian, Sebastian Vollmer, Till Bärnighausen, Pascal Geldsetzer
• E-Jahr: 2019
• Jahr: 13 September 2019
• Umfang: 75 S.
• Fussnoten: Gesehen am 10.07.2020
• Titel Quelle: Enthalten in: Data in Brief
• Ort Quelle: Amsterdam [u.a.] : Elsevier, 2014
• Jahr Quelle: 2019
• Band/Heft Quelle: 27(2019), Seite 104486
• ISSN Quelle: 2352-3409
• DOI: doi:10.1016/j.dib.2019.104486
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Cardiovascular disease
• Sach-SW: Diabetes mellitus
• Sach-SW: Education
• Sach-SW: Household wealth
• Sach-SW: Hypertension
• Sach-SW: India
• Sach-SW: Multi-level modelling
• Sach-SW: Obesity
• Sach-SW: Smoking
• K10plus-PPN: 172425880X

Abstract

In this article, we describe the dataset used in our study entitled “The interaction between district-level development and individual-level socioeconomic gradients of cardiovascular disease risk factors in India: A cross-sectional study of 2.4 million adults”, recently published in Social Science & Medicine, and present supplementary analyses. We used data from three different household surveys in India, which are representative at the district level. Specifically, we analyzed pooled data from the District-Level Household Survey 4 (DLHS-4) and the second update of the Annual Health Survey (AHS), and separately analyzed data from the National Family Health Survey (NFHS-4). The DLHS-4 and AHS sampled adults aged 18 years or older between 2012 and 2014, while the NFHS-4 sampled women aged 15-49 years and - in a subsample of 15% of households - men aged 15-54 years in 2015 and 2016. The measures of individual-level socio-economic status that we used in both datasets were educational attainment and household wealth quintiles. The measures of district-level development, which we calculated from these data, were i) the percentage of participants living in an urban area, ii) female literacy rate, and iii) the district-level median of the continuous household wealth index. An additional measure of district-level development that we used was Gross Domestic Product per capita, which we obtained from the Planning Commission of the Government of India for 2004/2005. Our outcome variables were diabetes, hypertension, obesity, and current smoking. The data were analyzed using both district-level regressions and multilevel modelling.