Literature DB >> 23148108

Demographic and health surveys: a profile.

Daniel J Corsi1, Melissa Neuman, Jocelyn E Finlay, S V Subramanian.   

Abstract

Demographic and Health Surveys (DHS) are comparable nationally representative household surveys that have been conducted in more than 85 countries worldwide since 1984. The DHS were initially designed to expand on demographic, fertility and family planning data collected in the World Fertility Surveys and Contraceptive Prevalence Surveys, and continue to provide an important resource for the monitoring of vital statistics and population health indicators in low- and middle-income countries. The DHS collect a wide range of objective and self-reported data with a strong focus on indicators of fertility, reproductive health, maternal and child health, mortality, nutrition and self-reported health behaviours among adults. Key advantages of the DHS include high response rates, national coverage, high quality interviewer training, standardized data collection procedures across countries and consistent content over time, allowing comparability across populations cross-sectionally and over time. Data from DHS facilitate epidemiological research focused on monitoring of prevalence, trends and inequalities. A variety of robust observational data analysis methods have been used, including cross-sectional designs, repeated cross-sectional designs, spatial and multilevel analyses, intra-household designs and cross-comparative analyses. In this profile, we present an overview of the DHS along with an introduction to the potential scope for these data in contributing to the field of micro- and macro-epidemiology. DHS datasets are available for researchers through MEASURE DHS at www.measuredhs.com.

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Year:  2012        PMID: 23148108     DOI: 10.1093/ije/dys184

Source DB:  PubMed          Journal:  Int J Epidemiol        ISSN: 0300-5771            Impact factor:   7.196


  280 in total

1.  On the assumption of bivariate normality in selection models: a Copula approach applied to estimating HIV prevalence.

Authors:  Mark E McGovern; Till Bärnighausen; Giampiero Marra; Rosalba Radice
Journal:  Epidemiology       Date:  2015-03       Impact factor: 4.822

2.  Prevalence and trends in the childhood dual burden of malnutrition in low- and middle-income countries, 1990-2012.

Authors:  Emma Tzioumis; Melissa C Kay; Margaret E Bentley; Linda S Adair
Journal:  Public Health Nutr       Date:  2016-02-24       Impact factor: 4.022

3.  Impact of International Monetary Fund programs on child health.

Authors:  Adel Daoud; Elias Nosrati; Bernhard Reinsberg; Alexander E Kentikelenis; Thomas H Stubbs; Lawrence P King
Journal:  Proc Natl Acad Sci U S A       Date:  2017-05-15       Impact factor: 11.205

4.  Impact of measles supplementary immunization activities on reaching children missed by routine programs.

Authors:  Allison Portnoy; Mark Jit; Stéphane Helleringer; Stéphane Verguet
Journal:  Vaccine       Date:  2017-11-23       Impact factor: 3.641

5.  Patterning of individual heterogeneity in body mass index: evidence from 57 low- and middle-income countries.

Authors:  Rockli Kim; Ichiro Kawachi; Brent Andrew Coull; Sankaran Venkata Subramanian
Journal:  Eur J Epidemiol       Date:  2018-01-22       Impact factor: 8.082

6.  Comment: Getting into Space with a Weight Problem.

Authors:  Jon Wakefield; Daniel Simpson; Jessica Godwin
Journal:  J Am Stat Assoc       Date:  2016-10-18       Impact factor: 5.033

7.  Child Gender and Parental Reporting of Illness Symptoms in Sub-Saharan Africa.

Authors:  Peter C Rockers; Margaret McConnell
Journal:  Am J Trop Med Hyg       Date:  2017-01-30       Impact factor: 2.345

8.  Why Are Orphaned Adolescents More Likely to Be HIV Positive? Distinguishing Between Maternal and Sexual HIV Transmission Using 17 Nationally Representative Data Sets in Africa.

Authors:  Rachel Kidman; Philip Anglewicz
Journal:  J Adolesc Health       Date:  2017-03-28       Impact factor: 5.012

9.  Are adolescent orphans more likely to be HIV-positive? A pooled data analyses across 19 countries in sub-Saharan Africa.

Authors:  Rachel Kidman; Philip Anglewicz
Journal:  J Epidemiol Community Health       Date:  2016-02-10       Impact factor: 3.710

10.  Anthropometric data quality assessment in multisurvey studies of child growth.

Authors:  Nandita Perumal; Sorrel Namaste; Huma Qamar; Ashley Aimone; Diego G Bassani; Daniel E Roth
Journal:  Am J Clin Nutr       Date:  2020-09-14       Impact factor: 7.045

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