Correction: Early Childhood Developmental Status in Low- and Middle-Income Countries: National, Regional, and Global Prevalence Estimates Using Predictive Modelling.
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ABSTRACT:
SUBMITTER: McCoy DC
PROVIDER: S-EPMC5279732 | biostudies-literature | 2017 Jan
REPOSITORIES: biostudies-literature
Publications
Correction: Early Childhood Developmental Status in Low- and Middle-Income Countries: National, Regional, and Global Prevalence Estimates Using Predictive Modelling.
McCoy Dana Charles DC Peet Evan D ED Ezzati Majid M Danaei Goodarz G Black Maureen M MM Sudfeld Christopher R CR Fawzi Wafaie W Fink Günther G
PLoS medicine 20170130 1
[This corrects the article DOI: 10.1371/journal.pmed.1002034.]. ...[more]
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Project description:BackgroundThe development of cognitive and socioemotional skills early in life influences later health and well-being. Existing estimates of unmet developmental potential in low- and middle-income countries (LMICs) are based on either measures of physical growth or proxy measures such as poverty. In this paper we aim to directly estimate the number of children in LMICs who would be reported by their caregivers to show low cognitive and/or socioemotional development.Methods and findingsThe present paper uses Early Childhood Development Index (ECDI) data collected between 2005 and 2015 from 99,222 3- and 4-y-old children living in 35 LMICs as part of the Multiple Indicator Cluster Survey (MICS) and Demographic and Health Surveys (DHS) programs. First, we estimate the prevalence of low cognitive and/or socioemotional ECDI scores within our MICS/DHS sample. Next, we test a series of ordinary least squares regression models predicting low ECDI scores across our MICS/DHS sample countries based on country-level data from the Human Development Index (HDI) and the Nutrition Impact Model Study. We use cross-validation to select the model with the best predictive validity. We then apply this model to all LMICs to generate country-level estimates of the prevalence of low ECDI scores globally, as well as confidence intervals around these estimates. In the pooled MICS and DHS sample, 14.6% of children had low ECDI scores in the cognitive domain, 26.2% had low socioemotional scores, and 36.8% performed poorly in either or both domains. Country-level prevalence of low cognitive and/or socioemotional scores on the ECDI was best represented by a model using the HDI as a predictor. Applying this model to all LMICs, we estimate that 80.8 million children ages 3 and 4 y (95% CI 48.1 million, 113.6 million) in LMICs experienced low cognitive and/or socioemotional development in 2010, with the largest number of affected children in sub-Saharan Africa (29.4.1 million; 43.8% of children ages 3 and 4 y), followed by South Asia (27.7 million; 37.7%) and the East Asia and Pacific region (15.1 million; 25.9%). Positive associations were found between low development scores and stunting, poverty, male sex, rural residence, and lack of cognitive stimulation. Additional research using more detailed developmental assessments across a larger number of LMICs is needed to address the limitations of the present study.ConclusionsThe number of children globally failing to reach their developmental potential remains large. Additional research is needed to identify the specific causes of poor developmental outcomes in diverse settings, as well as potential context-specific interventions that might promote children's early cognitive and socioemotional well-being.
| S-EPMC4896459 | biostudies-literature
Project description:BackgroundIn the 21st century, increases in immunisation coverage and decreases in under-5 mortality have substantially reduced the global burden of measles mortality. However, the assessment of measles mortality burden is highly dependent on estimates of case-fatality ratios for measles, which can vary according to geography, health systems infrastructure, prevalence of underlying risk factors, and measles endemicity. With imprecise case-fatality ratios, there is continued uncertainty about the burden of measles mortality and the effect of measles vaccination. In this study, we aimed to update the estimations of case-fatality ratios for measles, to develop a prediction model to estimate case-fatality ratios across heterogeneous groupings, and to project future case-fatality ratios for measles up to 2030.MethodsWe did a review of the literature to identify studies examining measles cases and deaths in low-income and middle-income countries in all age groups from 1980 to 2016. We extracted data on case-fatality ratios for measles overall and by age, where possible. We developed and examined several types of generalised linear models and determined the best-fit model according to the Akaike information criterion. We then selected a best-fit model to estimate measles case-fatality ratios from 1990 to 2015 and projected future case-fatality ratios for measles up to 2030.FindingsWe selected 124 peer-reviewed journal articles published between Jan 1, 1980, and Dec 31, 2016, for inclusion in the final review-85 community-based studies and 39 hospital-based studies. We selected a log-linear prediction model, resulting in a mean case-fatality ratio of 2·2% (95% CI 0·7-4·5) in 1990-2015. In community-based settings, the mean case-fatality ratio was 1·5% (0·5-3·1) compared with 2·9% (0·9-6·0) in hospital-based settings. The mean projected case-fatality ratio in 2016-2030 was 1·3% (0·4-3·7).InterpretationCase-fatality ratios for measles have seen substantial declines since the 1990s. Our study provides an updated estimation of case-fatality ratios that could help to refine assessment of the effect on mortality of measles control and elimination programmes.FundingBill & Melinda Gates Foundation.
| S-EPMC6418190 | biostudies-literature
Project description:BackgroundNational estimates for the numbers of babies born small for gestational age and the comorbidity with preterm birth are unavailable. We aimed to estimate the prevalence of term and preterm babies born small for gestational age (term-SGA and preterm-SGA), and the relation to low birthweight (<2500 g), in 138 countries of low and middle income in 2010.MethodsSmall for gestational age was defined as lower than the 10th centile for fetal growth from the 1991 US national reference population. Data from 22 birth cohort studies (14 low-income and middle-income countries) and from the WHO Global Survey on Maternal and Perinatal Health (23 countries) were used to model the prevalence of term-SGA births. Prevalence of preterm-SGA infants was calculated from meta-analyses.FindingsIn 2010, an estimated 32·4 million infants were born small for gestational age in low-income and middle-income countries (27% of livebirths), of whom 10·6 million infants were born at term and low birthweight. The prevalence of term-SGA babies ranged from 5·3% of livebirths in east Asia to 41·5% in south Asia, and the prevalence of preterm-SGA infants ranged from 1·2% in north Africa to 3·0% in southeast Asia. Of 18 million low-birthweight babies, 59% were term-SGA and 41% were preterm-SGA. Two-thirds of small-for-gestational-age infants were born in Asia (17·4 million in south Asia). Preterm-SGA babies totalled 2·8 million births in low-income and middle-income countries. Most small-for-gestational-age infants were born in India, Pakistan, Nigeria, and Bangladesh.InterpretationThe burden of small-for-gestational-age births is very high in countries of low and middle income and is concentrated in south Asia. Implementation of effective interventions for babies born too small or too soon is an urgent priority to increase survival and reduce disability, stunting, and non-communicable diseases.FundingBill & Melinda Gates Foundation by a grant to the US Fund for UNICEF to support the activities of the Child Health Epidemiology Reference Group (CHERG).
| S-EPMC4221634 | biostudies-literature
Project description:Children's blood lead levels have declined worldwide, especially after the removal of lead in gasoline. However, significant exposure remains, particularly in low- and middle-income countries. To date, there have been no global estimates of the costs related to lead exposure in children in developing countries.Our main aim was to estimate the economic costs attributable to childhood lead exposure in low- and middle-income countries.We developed a regression model to estimate mean blood lead levels in our population of interest, represented by each 1-year cohort of children < 5 years of age. We used an environmentally attributable fraction model to estimate lead-attributable economic costs and limited our analysis to the neurodevelopmental impacts of lead, assessed as decrements in IQ points. Our main outcome was lost lifetime economic productivity due to early childhood exposure.We estimated a total cost of $977 billions of international dollars in low- and middle-income countries, with economic losses equal to $134.7 billion in Africa [4.03% of gross domestic product (GDP)], $142.3 billion in Latin America and the Caribbean (2.04% of GDP), and $699.9 billion in Asia (1.88% of GDP). Our sensitivity analysis indicates a total economic loss in the range of $728.6-1162.5 billion.We estimated that, in low- and middle-income countries, the burden associated with childhood lead exposure amounts to 1.20% of world GDP in 2011. For comparison, in the United States and Europe lead-attributable economic costs have been estimated at $50.9 and $55 billion, respectively, suggesting that the largest burden of lead exposure is now borne by low- and middle-income countries.
| S-EPMC3764081 | biostudies-other
Project description:BACKGROUND:Numerous studies have reported the economic burden of childhood diarrhea in low- and middle-income countries (LMICs). Yet, empirical data on the cost of diarrheal illness is sparse, particularly in LMICs. In this study we review the existing literature on the cost of childhood diarrhea in LMICs and generate comparable estimates of cost of diarrhea across 137 LMICs. METHODS:The systematic literature review included all articles reporting cost estimates of diarrhea illness and treatment from LMICs published between January 2006 and July 2018. To generate country-specific costs, we used service delivery unit costs from the World Health Organization's Choosing Interventions that are Cost-Effective (WHO-CHOICE database). Non-medical costs were calculated using the ratio between direct medical and direct non-medical costs, derived from the literature review. Indirect costs (lost wages to caregivers) were calculated by multiplying the average GDP per capita per day by the average number of days lost to illness identified from the literature. All cost estimates are reported in 2015 USD. We also generated estimates using the IHME's service delivery unit costs to explore input sensitivity on modelled cost estimates. RESULTS:We identified 25 articles with 64 data points on either direct or indirect cost of diarrhoeal illness in children aged <?5?years in 20 LMICs. Of the 64 data points, 17 were on the cost of outpatient care, 28 were on the cost of inpatient care, and 19 were unspecified. The average cost of illness was US$36.56 (median $15.73; range $4.30 - $145.47) per outpatient episode and $159.90 (median $85.85; range $41.01 - $538.33) per inpatient episode. Direct medical costs accounted for 79% (83% for inpatient and 74% for outpatient) of the total direct costs. Our modelled estimates, across all 137 countries, averaged (weighted) $52.16 (median $47.56; range $8.81 - $201.91) per outpatient episode and $216.36 (median $177.20; range $23.77 -$1225.36) per inpatient episode. In the 12 countries with primary data, there was reasonable agreement between our modelled estimates and the reported data (Pearson's correlation coefficient?=?.75). CONCLUSION:Our modelled estimates generally correspond to estimates observed in the literature, with a few exceptions. These estimates can serve as useful inputs for planning and prioritizing appropriate health interventions for childhood diarrheal diseases in LMICs in the absence of empirical data.
| S-EPMC7201538 | biostudies-literature
Project description:OBJECTIVE:To investigate the association between maternal employment and childhood overweight in low- and middle-income countries (LMIC). Design/Setting We utilized cross-sectional data from forty-five Demographic and Health Surveys from 2010 to 2016 (n 268 763). Mothers were categorized as formally employed, informally employed or non-employed. We used country-specific logistic regression models to investigate the association between maternal employment and childhood overweight (BMI Z-score>2) and assessed heterogeneity in the association by maternal education with the inclusion of an interaction term. We used meta-analysis to pool the associations across countries. Sensitivity analyses included modelling BMI Z-score and normal weight (weight-for-age Z-score?-2 to <2) as outcomes. SUBJECTS:Participants included children 0-5 years old and their mothers (aged 18-49 years). RESULTS:In most countries, neither formal nor informal employment was associated with childhood overweight. However, children of employed mothers, compared with children of non-employed mothers, had higher BMI Z-score and higher odds of normal weight. In countries where the association varied by education, children of formally employed women with high education, compared with children of non-employed women with high education, had higher odds of overweight (pooled OR=1·2; 95 % CI 1·0, 1·4). CONCLUSIONS:We find no clear association between employment and child overweight. However, maternal employment is associated with a modestly higher BMI Z-score and normal weight, suggesting that employment is currently associated with beneficial effects on children's weight status in most LMIC.
| S-EPMC7059352 | biostudies-literature
Project description:Vaccines may reduce the burden of antimicrobial resistance, in part by preventing infections for which treatment often includes the use of antibiotics1-4. However, the effects of vaccination on antibiotic consumption remain poorly understood-especially in low- and middle-income countries (LMICs), where the burden of antimicrobial resistance is greatest5. Here we show that vaccines that have recently been implemented in the World Health Organization's Expanded Programme on Immunization reduce antibiotic consumption substantially among children under five years of age in LMICs. By analysing data from large-scale studies of households, we estimate that pneumococcal conjugate vaccines and live attenuated rotavirus vaccines confer 19.7% (95% confidence interval, 3.4-43.4%) and 11.4% (4.0-18.6%) protection against antibiotic-treated episodes of acute respiratory infection and diarrhoea, respectively, in age groups that experience the greatest disease burden attributable to the vaccine-targeted pathogens6,7. Under current coverage levels, pneumococcal and rotavirus vaccines prevent 23.8 million and 13.6 million episodes of antibiotic-treated illness, respectively, among children under five years of age in LMICs each year. Direct protection resulting from the achievement of universal coverage targets for these vaccines could prevent an additional 40.0 million episodes of antibiotic-treated illness. This evidence supports the prioritization of vaccines within the global strategy to combat antimicrobial resistance8.
| S-EPMC7332418 | biostudies-literature
Project description:BackgroundWhile the COVID-19 pandemic will increase mortality due to the virus, it is also likely to increase mortality indirectly. In this study, we estimate the additional maternal and under-5 child deaths resulting from the potential disruption of health systems and decreased access to food.MethodsWe modelled three scenarios in which the coverage of essential maternal and child health interventions is reduced by 9·8-51·9% and the prevalence of wasting is increased by 10-50%. Although our scenarios are hypothetical, we sought to reflect real-world possibilities, given emerging reports of the supply-side and demand-side effects of the pandemic. We used the Lives Saved Tool to estimate the additional maternal and under-5 child deaths under each scenario, in 118 low-income and middle-income countries. We estimated additional deaths for a single month and extrapolated for 3 months, 6 months, and 12 months.FindingsOur least severe scenario (coverage reductions of 9·8-18·5% and wasting increase of 10%) over 6 months would result in 253 500 additional child deaths and 12 200 additional maternal deaths. Our most severe scenario (coverage reductions of 39·3-51·9% and wasting increase of 50%) over 6 months would result in 1 157 000 additional child deaths and 56 700 additional maternal deaths. These additional deaths would represent an increase of 9·8-44·7% in under-5 child deaths per month, and an 8·3-38·6% increase in maternal deaths per month, across the 118 countries. Across our three scenarios, the reduced coverage of four childbirth interventions (parenteral administration of uterotonics, antibiotics, and anticonvulsants, and clean birth environments) would account for approximately 60% of additional maternal deaths. The increase in wasting prevalence would account for 18-23% of additional child deaths and reduced coverage of antibiotics for pneumonia and neonatal sepsis and of oral rehydration solution for diarrhoea would together account for around 41% of additional child deaths.InterpretationOur estimates are based on tentative assumptions and represent a wide range of outcomes. Nonetheless, they show that, if routine health care is disrupted and access to food is decreased (as a result of unavoidable shocks, health system collapse, or intentional choices made in responding to the pandemic), the increase in child and maternal deaths will be devastating. We hope these numbers add context as policy makers establish guidelines and allocate resources in the days and months to come.FundingBill & Melinda Gates Foundation, Global Affairs Canada.
| S-EPMC7217645 | biostudies-literature
Project description:BackgroundBirth weight (BW) is a strong predictor of neonatal outcomes. The purpose of this study was to compare BWs between global regions (south Asia, sub-Saharan Africa, Central America) prospectively and to determine if trends exist in BW over time using the population-based maternal and newborn registry (MNHR) of the Global Network for Women'sand Children's Health Research (Global Network).MethodsThe MNHR is a prospective observational population-based registryof six research sites participating in the Global Network (2013-2018), within five low- and middle-income countries (Kenya, Zambia, India, Pakistan, and Guatemala) in threeglobal regions (sub-Saharan Af rica, south Asia, Central America). The birth weights were obtained for all infants born during the study period. This was done either by abstracting from the infants' health facility records or from direct measurement by the registry staff for infants born at home. After controlling for demographic characteristics, mixed-effect regression models were utilized to examine regional differences in birth weights over time.ResultsThe overall BW meanswere higher for the African sites (Zambia and Kenya), 3186 g (SD 463 g) in 2013 and 3149 g (SD 449 g) in 2018, ascompared to Asian sites (Belagavi and Nagpur, India and Pakistan), 2717 g (SD450 g) in 2013 and 2713 g (SD 452 g) in 2018. The Central American site (Guatemala) had a mean BW intermediate between the African and south Asian sites, 2928 g (SD 452) in 2013, and 2874 g (SD 448) in 2018. The low birth weight (LBW) incidence was highest in the south Asian sites (India and Pakistan) and lowest in the African sites (Kenya and Zambia). The size of regional differences varied somewhat over time with slight decreases in the gap in birth weights between the African and Asian sites and slight increases in the gap between the African and Central American sites.ConclusionsOverall, BWmeans by global region did not change significantly over the 5-year study period. From 2013 to 2018, infants enrolled at the African sites demonstrated the highest BW means overall across the entire study period, particularly as compared to Asian sites. The incidence of LBW was highest in the Asian sites (India and Pakistan) compared to the African and Central American sites. Trial registration The study is registered at clinicaltrials.gov. ClinicalTrial.gov Trial Registration: NCT01073475.
| S-EPMC7745347 | biostudies-literature
Project description:BACKGROUND:The aim of this study was to assess the relationship between early childhood caries (ECC) in 3-5-year-old children, seven indicators of poverty and the indicator of monetary poverty in low- and middle-income countries (LICs, MICs). METHODS:This ecologic study utilized 2007 to 2017 country-level data for LICs and MICs. Explanatory variables were seven indicators of poverty namely food, water, sanitation, health, shelter, access to information, education; and monetary poverty. The outcome variable was the percentage of 3-5-year-old children with ECC. A series of univariate general linear regression models were used to assess the relationship between the percentage of 3-5?year-old children with ECC and each of the seven indicators of poverty, and monetary poverty. This was followed by multivariable regression models to determined the combined effect of the seven indicators of poverty, as well as the combined effect of the seven indicators of poverty and monetary poverty. Adjusted R2 measured models' ability to explain the variation among LICs and MICs in the percentage of 3-5-year-old children with ECC. RESULTS:Significantly more people had food, sanitation, shelter, access to information, education and monetary poverty in LICs than in MICs. There was no difference in the prevalence of ECC in 3-5-year-old children between LICs and MICs. The combination of the seven indicators of poverty explained 15% of the variation in the percentage of 3-5-year-old children with ECC compared to 1% explained by monetary poverty. When the seven indicators of poverty and the indicator for monetary poverty were combined, the amount of variation explained by them was 10%. Only two of the poverty indicators had a direct relationship with the percentage of children with ECC; there was a higher percentage of ECC in countries with higher percentage of population living in slums (B?=?0.35) and in those countries with higher percentage of the population living below poverty lines (B?=?0.19). The other indicators had an inverse relationship. CONCLUSION:The use of multiple indicators to measures of poverty explained greater amount of variation in the percentage of 3-5-year-olds with ECC in LICs and MICs than using only the indicator for monetary poverty.
| S-EPMC6945445 | biostudies-literature