Missingness of Height Data from the Demographic and Health Surveys in Africa between 1991 and 2016 Was Not Random but Is Unlikely to Have Major Implications for Biases in Estimating Stunting Prevalence or the Determinants of Child Height

Finaret, Amelia B.; Hutchinson, Matthew

doi:10.1093/jn/nxy037

Cited by 13 publications

(11 citation statements)

References 16 publications

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“…Children with missing values for height or for age were excluded from the stunting analyses, as were those with extreme Z-score values, as recommended by WHO ( WHO, 2006 ). Published multicountry analyses of missing anthropometric data in national surveys has shown that missingness is unlikely to bias the study of associations with postulated risk factors ( Finaret & Hutchinson, 2018 ).…”

Section: Methodsmentioning

confidence: 99%

Are children in female-headed households at a disadvantage? An analysis of immunization coverage and stunting prevalence: in 95 low- and middle-income countries

Wendt¹,

Hellwig²,

Saad³

et al. 2021

SSM - Population Health

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Studies of inequalities in child health have given limited attention to household structure and headship. The few existing reports on child outcomes in male and female-headed households have produced inconsistent results. The aim of our analyses was to provide a global view of the influence of sex of the household head on child health in cross-sectional surveys from up to 95 LMICs. Studied outcomes were full immunization coverage in children aged 12–23 months and stunting prevalence in under-five children. We analyzed the most recent nationally-representative surveys for each country (since 2010) with available data. After initial exploratory analyses, we focused on three types of households: a) male-headed household (MHH) comprised 73.1% of all households in the pooled analyses; b) female Headed Household (FHH) with at least one adult male represented 9.8% of households; and c) FHH without an adult male accounted for 15.0% of households. Our analyses also included the following covariates: wealth index, education of the child’s mother and urban/rural residence. Meta-analytic approaches were used to calculate pooled effects across the countries with MHH as the reference category. Regarding full immunization, the pooled prevalence ratio for FHH (any male) was 0.99 (0.97; 1.01) and that for FHH (no male) was 0.99 (0.97; 1.02). For stunting prevalence, the pooled prevalence ratio for FHH (any male) was 1.00 (0.98; 1.02) and for FHH (no male) was 1.00 (0.98; 1.02). Adjustment for covariates did not lead to any noteworthy change in the results. No particular patterns were found among different world regions. A few countries presented significant inequalities with different directions of association, indicating the diversity of FHH and how complex the meaning and measurement of household headship may be. Further research is warranted to understand context, examine mediating factors, and exploring alternative definitions of household headship in countries with some association.

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Section: Methodsmentioning

confidence: 99%

Are children in female-headed households at a disadvantage? An analysis of immunization coverage and stunting prevalence: in 95 low- and middle-income countries

Wendt¹,

Hellwig²,

Saad³

et al. 2021

SSM - Population Health

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“…While these are currently the only sources of representative and comparable data, they contain multiple potential biases, such as recall and reporting bias, interviewer effects on responses, and refusal bias. 69 , 70 , 71 , 72 In addition, there were data gaps in some locations ( appendix p 4 ) that affected the robustness of our estimates, and increased uncertainty. Our resampling method increased the uncertainty intervals in our analysis.…”

Section: Discussionmentioning

confidence: 99%

Mapping local variation in household overcrowding across Africa from 2000 to 2018: a modelling study

Chipeta

Kumaran

Browne

et al. 2022

The Lancet Planetary Health

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“…Anthropometric data quality may be affected by survey design (e.g., sampling strategy, questionnaire design, and measurement tools), implementation (e.g., nonresponse rate, management of field operations, staff training in data collection and anthropometry measurement, and method of data entry), and data processing procedures ( 6 , 8 , 9 ). Several indicators have been used to assess anthropometric data quality including the pattern of age heaping ( 10 ), missingness of data on child height ( 11 ), proportion of biologically implausible values ( 6 ), misreporting of month of birth (MOB) for age estimation ( 12 ), and effect of random error ( 7 ). Whereas examining several individual indicators is informative for assessing various dimensions of quality within a single survey, for multisurvey analyses, a single aggregate measure of relative anthropometric data quality, which combines several data quality indicators, would better enable researchers to account for heterogeneity in the quality of anthropometric data collected across countries and over time.…”

Section: Introductionmentioning

confidence: 99%

Anthropometric data quality assessment in multisurvey studies of child growth

Perumal

Namasté

Qamar

et al. 2020

The American Journal of Clinical Nutrition

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Background Population-based surveys collect crucial data on anthropometric measures to track trends in stunting [height-for-age z score (HAZ) < −2SD] and wasting [weight-for-height z score (WHZ) < −2SD] prevalence among young children globally. However, the quality of the anthropometric data varies between surveys, which may affect population-based estimates of malnutrition. Objectives We aimed to develop composite indices of anthropometric data quality for use in multisurvey analysis of child health and nutritional status. Methods We used anthropometric data for children 0–59 mo of age from all publicly available Demographic and Health Surveys (DHSs) from 2000 onwards. We derived 6 recommended indicators of anthropometric data quality at the survey level, including 1) date of birth completeness, 2) anthropometric measure completeness, 3) digit preference for height and age, 4) difference in mean HAZ by month of birth, 5) proportion of biologically implausible values, and 6) dispersion of HAZ and WHZ distribution. Principal component factor analysis was used to generate a composite score of anthropometric data quality for HAZ and WHZ separately. Surveys were ranked from the highest (best) to the lowest (worst) index values in anthropometric quality across countries and over time. Results Of the 145 DHSs included, the majority (83 of 145; 57%) were conducted in Sub-Saharan Africa. Surveys were ranked from highest to lowest anthropometric data quality relative to other surveys using the composite index for HAZ. Although slightly higher values in recent DHSs suggest potential improvements in anthropometric data quality over time, there continues to be substantial heterogeneity in the quality of anthropometric data across surveys. Results were similar for the WHZ data quality index. Conclusions A composite score of anthropometric data quality using a parsimonious set of individual indicators can effectively discriminate among surveys with excellent and poor data quality. This score can be used to account for variations in anthropometric data quality in multisurvey epidemiologic analyses of child health.

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Missingness of Height Data from the Demographic and Health Surveys in Africa between 1991 and 2016 Was Not Random but Is Unlikely to Have Major Implications for Biases in Estimating Stunting Prevalence or the Determinants of Child Height

Cited by 13 publications

References 16 publications

Are children in female-headed households at a disadvantage? An analysis of immunization coverage and stunting prevalence: in 95 low- and middle-income countries

Are children in female-headed households at a disadvantage? An analysis of immunization coverage and stunting prevalence: in 95 low- and middle-income countries

Mapping local variation in household overcrowding across Africa from 2000 to 2018: a modelling study

Anthropometric data quality assessment in multisurvey studies of child growth

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