scholarly journals New estimations of child marriage: Evidence from 98 low- and middle-income countries

PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0258378
Author(s):  
Mengjia Liang ◽  
Sandile Simelane ◽  
Satvika Chalasani ◽  
Rachel Snow
Keyword(s):  
Survival Analysis ◽  
Child Marriage ◽  
Demographic And Health Surveys ◽  
Hazard Rates ◽  
Middle Income ◽  
The Sustainable Development ◽  
Marriage Rates ◽  
Middle Income Countries ◽  
Nationally Representative ◽  
Low And Middle Income

The Sustainable Development Goals include a target on eliminating child marriage, a human rights abuse. Yet, the indicator used in the SDG framework is a summary statistic and does not provide a full picture of the incidence of marriage at different ages. This paper aims to address this limitation by providing an alternative method of measuring child marriage. The paper reviews recent data on nuptiality and captures evidence of changes in the proportion married and in the age at marriage, in 98 low- and middle-income countries (LMICs). Using data collected from nationally representative Demographic and Health Surveys and Multiple Indicator Cluster Surveys, survival analysis is applied to estimate (a) age-specific marriage hazard rates among girls before age 18; and (b) the number of girls that were married before age 18 in 2020. Results show that the vast majority of girls remain unmarried until age 10. Child marriage rates increase gradually until age 14 and accelerate significantly thereafter at ages 15–17. By accounting for both single-year-age-specific child marriage hazard rates and the age structure of the population with a survival analysis approach, lower estimates in countries with a rapid decrease in child marriage and higher estimates in countries with constant or slightly rising child marriage rates relative to the direct approach are obtained.

scholarly journals Age patterns in overweight and wasting prevalence of under 5-year-old children from low- and middle-income countries

2021 ◽  
Author(s):  
Luiza I. C. Ricardo ◽  
Giovanna Gatica-Domínguez ◽  
Inácio Crochemore-Silva ◽  
Paulo A. R. Neves ◽  
Juliana dos Santos Vaz ◽  
...  
Keyword(s):  
Low Income ◽  
Age Groups ◽  
Demographic And Health Surveys ◽  
Older Children ◽  
Middle Income ◽  
Middle Income Countries ◽  
Multiple Indicator ◽  
Standard Deviations ◽  
Nationally Representative ◽  
Low And Middle Income

Abstract Objectives To describe how overweight and wasting prevalence varies with age among children under 5 years in low- and middle-income countries (LMICs). Methods We used data from nationally representative Demographic and Health Surveys and Multiple Indicator Cluster Surveys. Overweight and wasting prevalence were defined as the proportions of children presenting mean weight for length/height (WHZ) more than 2 standard deviations above or below 2 standard deviations from the median value of the 2006 WHO standards, respectively. Descriptive analyses include national estimates of child overweight and wasting prevalence, mean, and standard deviations of WHZ stratified by age in years. National results were pooled using the population of children aged under 5 years in each country as weight. Fractional polynomials were used to compare mean WHZ with both overweight and wasting prevalence. Results Ninety national surveys from LMICs carried out between 2010 and 2019 were included. The overall prevalence of overweight declined with age from 6.3% for infants (aged 0–11 months) to 3.0% in 4 years olds (p = 0.03). In all age groups, lower prevalence was observed in low-income compared to upper-middle-income countries. Wasting was also more frequent among infants, with a slight decrease between the first and second year of life, and little variation thereafter. Lower-middle-income countries showed the highest wasting prevalence in all age groups. On the other hand, mean WHZ was stable over the first 5 years of life, but the median standard deviation for WHZ decreased from 1.39 in infants to 1.09 in 4-year-old children (p < 0.001). For any given value of WHZ, both overweight and wasting prevalence were higher in infants than in older children. Conclusion The higher values of WHZ standard deviations in infants suggest that declining prevalence in overweight and wasting by age may be possibly due to measurement error or rapid crossing of growth channels by infants.

scholarly journals Prevalence and trends in the childhood dual burden of malnutrition in low- and middle-income countries, 1990–2012

2016 ◽  
Vol 19 (8) ◽  
pp. 1375-1388 ◽  
Author(s):  
Emma Tzioumis ◽  
Melissa C Kay ◽  
Margaret E Bentley ◽  
Linda S Adair
Keyword(s):  
Demographic And Health Surveys ◽  
Cross Sectional ◽  
Middle Income ◽  
Individual Level ◽  
Middle Income Countries ◽  
Country Level ◽  
Before And After ◽  
Dual Burden ◽  
Nationally Representative ◽  
Low And Middle Income

AbstractObjectiveTo describe trends in country- and individual-level dual burden of malnutrition in children <5 years, and age-stratified (<2 years, ≥2 years) country-level trends, in thirty-six low- and middle-income countries (LMIC).DesignUsing repeated cross-sectional nationally representative data, we calculated the prevalence of malnutrition (stunting, wasting, overweight) at each survey wave, annualized rates of prevalence change for each country over time, and trends before and after 2000, for all children <5 years and separately for those </≥2 years. We examined country- (ratio of stunting to overweight) and individual-level (coexistence of stunting and overweight) dual burden in children <5 years.SettingDemographic and Health Surveys from thirty-six LMIC between 1990 and 2012.SubjectsChildren <5 years.ResultsOverall malnutrition prevalence decreased in children <5 years, driven by stunting decreases. Stunting rates decreased in 78 % of countries, wasting rates decreased in 58 % of countries and overweight rates increased in 36 % of countries. Rates of change differed for children </≥2 years, with children <2 years experiencing decreases in stunting in fewer countries yet increases in overweight in more countries. Countries with nearly equal prevalences of stunting and overweight in children <5 years increased from 2000 to the final year. Within a country, 0·3–10·9 % of children <5 years were stunted and overweight, and 0·6–37·8 % of stunted children <5 years were overweight.ConclusionsThe dual burden exists in children <5 years on both country and individual levels, indicating a shift is needed in policies and programmes to address both sides of malnutrition. Children <2 years should be identified as a high-risk demographic.

scholarly journals Finding Children with High Risk of Non-Vaccination in 92 Low- and Middle-Income Countries: A Decision Tree Approach

Vaccines ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 646
Author(s):  
Thiago M. Santos ◽  
Bianca O. Cata-Preta ◽  
Cesar G. Victora ◽  
Aluisio J. D. Barros
Keyword(s):  
High Risk ◽  
Decision Tree ◽  
Immunization Coverage ◽  
Risk Groups ◽  
Demographic And Health Surveys ◽  
Middle Income ◽  
Agenda 2030 ◽  
Middle Income Countries ◽  
Tree Approach ◽  
Low And Middle Income

Reducing vaccination inequalities is a key goal of the Immunization Agenda 2030. Our main objective was to identify high-risk groups of children who received no vaccines (zero-dose children). A decision tree approach was used for 92 low- and middle-income countries using data from Demographic and Health Surveys and Multiple Indicator Cluster Surveys, allowing the identification of groups of children aged 12–23 months at high risk of being zero dose (no doses of the four basic vaccines—BCG, polio, DPT and measles). Three high-risk groups were identified in the analysis combining all countries. The group with the highest zero-dose prevalence (42%) included 4% of all children, but almost one in every four zero-dose children in the sample. It included children whose mothers did not receive the tetanus vaccine during and before the pregnancy, who had no antenatal care visits and who did not deliver in a health facility. Separate analyses by country presented similar results. Children who have been missed by vaccination services were also left out by other primary health care interventions, especially those related to antenatal and delivery care. There is an opportunity for better integration among services in order to achieve high and equitable immunization coverage.

scholarly journals Toward Model-Generated Household Listing in Low- and Middle-Income Countries Using Deep Learning

2018 ◽  
Vol 7 (11) ◽  
pp. 448 ◽  
Author(s):  
Robert Chew ◽  
Kasey Jones ◽  
Jennifer Unangst ◽  
James Cajka ◽  
Justine Allpress ◽  
...  
Keyword(s):  
Sustainable Development ◽  
Object Detection ◽  
Household Surveys ◽  
Building Structures ◽  
Middle Income ◽  
The Sustainable Development ◽  
Detection Model ◽  
Middle Income Countries ◽  
Development Goals ◽  
Low And Middle Income

While governments, researchers, and NGOs are exploring ways to leverage big data sources for sustainable development, household surveys are still a critical source of information for dozens of the 232 indicators for the Sustainable Development Goals (SDGs) in low- and middle-income countries (LMICs). Though some countries’ statistical agencies maintain databases of persons or households for sampling, conducting household surveys in LMICs is complicated due to incomplete, outdated, or inaccurate sampling frames. As a means to develop or update household listings in LMICs, this paper explores the use of machine learning models to detect and enumerate building structures directly from satellite imagery in the Kaduna state of Nigeria. Specifically, an object detection model was used to identify and locate buildings in satellite images. In the test set, the model attained a mean average precision (mAP) of 0.48 for detecting structures, with relatively higher values in areas with lower building density (mAP = 0.65). Furthermore, when model predictions were compared against recent household listings from fieldwork in Nigeria, the predictions showed high correlation with household coverage (Pearson = 0.70; Spearman = 0.81). With the need to produce comparable, scalable SDG indicators, this case study explores the feasibility and challenges of using object detection models to help develop timely enumerated household lists in LMICs.

scholarly journals Co-morbid anaemia and stunting among children of pre-school age in low- and middle-income countries: a syndemic

2018 ◽  
Vol 22 (1) ◽  
pp. 35-43 ◽  
Author(s):  
Thach Duc Tran ◽  
Beverley-Ann Biggs ◽  
Sara Holton ◽  
Hau Thi Minh Nguyen ◽  
Sarah Hanieh ◽  
...  
Keyword(s):  
Rural Areas ◽  
Secondary Analysis ◽  
Logistic Models ◽  
Demographic And Health Surveys ◽  
Healthy Children ◽  
Middle Income ◽  
Disadvantaged Children ◽  
Middle Income Countries ◽  
Co Morbidity ◽  
Low And Middle Income

AbstractObjectiveTo determine the prevalence of co-morbidity of two important global health challenges, anaemia and stunting, among children aged 6–59 months in low- and middle-income countries.DesignSecondary analysis of data from Demographic and Health Surveys (DHS) conducted 2005–2015. Child stunting and anaemia were defined using current WHO classifications. Sociodemographic characteristics of children with anaemia, stunting and co-morbidity of these conditions were compared with those of ‘healthy’ children in the sample (children who were not stunted and not anaemic) using multiple logistic models.SettingLow- and middle-income countries.SubjectsChildren aged 6–59 months.ResultsData from 193 065 children from forty-three countries were included. The pooled proportion of co-morbid anaemia and stunting was 21·5 (95 % CI 21·2, 21·9) %, ranging from the lowest in Albania (2·6 %; 95 % CI 1·8, 3·7 %) to the highest in Yemen (43·3; 95 % CI 40·6, 46·1 %). Compared with the healthy group, children with co-morbidity were more likely to be living in rural areas, have mothers or main carers with lower educational levels and to live in poorer households. Inequality in children who had both anaemia and stunting was apparent in all countries.ConclusionsCo-morbid anaemia and stunting among young children is highly prevalent in low- and middle-income countries, especially among more disadvantaged children. It is suggested that they be considered under a syndemic framework, the Childhood Anaemia and Stunting (CHAS) Syndemic, which acknowledges the interacting nature of these diseases and the social and environmental factors that promote their negative interaction.

Socioeconomic inequalities in unhealthy lifestyles in low- and middle-income countries

2020 ◽  
Author(s):  
Charlotte Dieteren ◽  
Igna Bonfrer
Keyword(s):  
Alcohol Use ◽  
Tobacco Use ◽  
Socioeconomic Inequalities ◽  
Individual Characteristics ◽  
Middle Income ◽  
The Sustainable Development ◽  
Middle Income Countries ◽  
The Poor ◽  
Harmful Alcohol ◽  
Low And Middle Income

Abstract Background: The heavy and ever rising burden of non-communicable diseases (NCDs) in low- and middle-income countries (LMICs) warrants interventions to reduce unhealthy lifestyles. To effectively target these interventions, it is important to know how unhealthy lifestyles vary with socioeconomic characteristics. This study quantifies prevalence and socioeconomic inequalities in unhealthy lifestyles in LMICs, to identify policy priorities conducive to the Sustainable Development Goal of a one third reduction in deaths from NCDs by 2030.Methods: Data from 1,278,624 adult respondents to Demographic & Health Surveys across 22 LMICs between 2013 and 2018 are used to estimate crude prevalence rates and socioeconomic inequalities in tobacco use, overweight, harmful alcohol use and the clustering of these three in a household. Inequalities are measured by a concentration index and correlated with the percentage of GDP spent on health. We estimate a multilevel model to examine associations of individual characteristics with different unhealthy lifestyles.Results: The prevalence of tobacco use among men ranges from 59.6% (Armenia) to 6.6% (Nigeria). The highest level of overweight among women is 83.7% (Egypt) while this is less than 12% in Burundi, Chad and Timor-Leste. 82.5% of women in Burundi report that their partner is “often or sometimes drunk” compared to 1.3% in Gambia. Tobacco use is concentrated among the poor, except for the low share of men smoking in Nigeria. Overweight, however, is concentrated among the better off, especially in Tanzania and Zimbabwe (Erreygers Index (EI) 0.227 and 0.232). Harmful alcohol use is more concentrated among the better off in Nigeria (EI 0.127), while Chad, Rwanda and Togo show an unequal pro-poor distribution (EI respectively -0.147, -0.210, -0.266). Cambodia exhibits the largest socioeconomic inequality in unhealthy household behaviour (EI -0.253). The multilevel analyses confirm that in LMICs, tobacco and alcohol use are largely concentrated among the poor, while overweight is concentrated among the better-off.Conclusions: This study emphasizes the importance of unhealthy lifestyles in LMICs and the socioeconomic variation therein. Given the different socioeconomic patterns in unhealthy lifestyles - overweight patters in LMICs differ considerably from those in high income countries- tailored interventions towards specific high-risk populations are warranted.

Shifting disease burden in low and middle-income countries: a 14-year survival analysis of childhood mortality in Bangladesh

2017 ◽  
Vol 71 (9) ◽  
pp. 882-888 ◽  
Author(s):  
Olakunle Alonge ◽  
Siran He ◽  
Dewan Emdadul Hoque ◽  
Shumona Sharmin Salam ◽  
Irteja Islam ◽  
...  
Keyword(s):  
Survival Analysis ◽  
Disease Burden ◽  
Childhood Mortality ◽  
Middle Income ◽  
Middle Income Countries ◽  
Low And Middle Income

scholarly journals Microestimates of wealth for all low- and middle-income countries

2022 ◽  
Vol 119 (3) ◽  
pp. e2113658119
Author(s):  
Guanghua Chi ◽  
Han Fang ◽  
Sourav Chatterjee ◽  
Joshua E. Blumenstock
Keyword(s):  
Survey Data ◽  
Household Survey ◽  
Heterogeneous Data ◽  
Machine Learning Algorithms ◽  
Middle Income ◽  
Middle Income Countries ◽  
Economic Development And Growth ◽  
Household Survey Data ◽  
Nationally Representative ◽  
Low And Middle Income

Many critical policy decisions, from strategic investments to the allocation of humanitarian aid, rely on data about the geographic distribution of wealth and poverty. Yet many poverty maps are out of date or exist only at very coarse levels of granularity. Here we develop microestimates of the relative wealth and poverty of the populated surface of all 135 low- and middle-income countries (LMICs) at 2.4 km resolution. The estimates are built by applying machine-learning algorithms to vast and heterogeneous data from satellites, mobile phone networks, and topographic maps, as well as aggregated and deidentified connectivity data from Facebook. We train and calibrate the estimates using nationally representative household survey data from 56 LMICs and then validate their accuracy using four independent sources of household survey data from 18 countries. We also provide confidence intervals for each microestimate to facilitate responsible downstream use. These estimates are provided free for public use in the hope that they enable targeted policy response to the COVID-19 pandemic, provide the foundation for insights into the causes and consequences of economic development and growth, and promote responsible policymaking in support of sustainable development.

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