Abstract:Child undernutrition is a major public health problem throughout the world, particularly in developing countries. The main objective of this study was to identify the risk factors for acute undernutrition among under-5 children in Bangladesh. Data were taken from the nationally representative Bangladesh Demographic Health and Survey conducted in 2014. The study sample comprised 7131 under-5 children. Of these, 4.6% were found to be severely wasted (Z-score < −3.0), 11.1% moderately wasted (−3.0≤Z-score <… Show more
“…In contrast, CISAF uses conventional nutritional indicators' aggregate values to estimate the overall burden of severe malnutrition, thus provide a more convincing estimation of the proportion of malnourished children in the population [10]. Our nding of a higher prevalence of severe under-5 malnutrition in rural areas concurs with previous research [20,21,22,23]. Several studies have also reported a higher prevalence of severe under-5 malnutrition in urban areas in Bangladesh with limited geographical coverage [24,25,26].…”
IntroductionSevere under-5 child malnutrition (i.e., severe stunting, severe wasting and severe underweight) is high in Bangladesh. The interplay between risk factors needs to be understood to address this complex public health issues. We aim to explore the prevalence and risk factors for severe under-5 child malnutrition in Bangladesh's rural and urban areas using the Composite Index of Severe Anthropometric Failure (CISAF).MethodsWe analysed data from Bangladesh Demographic Health Surveys (BDHSs), 2017-18. Severe malnutrition was defined using the CISAF, and conventional nutritional indicators were aggregated to estimate malnutrition's overall burden. The proportional differences of variables between non-severe malnutrition and severe malnutrition group were assessed using Chi-square test. Risk factors for malnutrition were analysed using regression models to assess the odds ratio (OR) and 95% confidence interval (CI).ResultsThe overall prevalence of severe under-5 child malnutrition was 11% with 12% in rural areas and 10% in urban areas. The key risk factors in rural areas were children born with small birth weight (OR: 2.4, 95% CI: 1.5–3.8), socio-economically poorest households (OR: 2.3, 95% CI: 1.4–3.7) and children aged 36-47 months (OR: 2.1, 95% CI: 1.6–2.8). The key risk factors in urban areas were children born with small birth weight (OR: 5.0, 95% CI: 2.9–8.6), children of mothers with no formal education (OR: 2.0, 95% CI: 1.2–3.6) and children's birth order ≥4 (OR: 1.8, 95% CI: 1.2–2.8). 52% lower risk difference of parents with formal education vs no formal education, and 71% higher risk difference of most affluent vs poorest household for being severely malnourished were estimated in rural areas than in urban areas.ConclusionOne in ten children living in both rural and urban areas experience severe malnutrition. Children of parents with no formal education, children of underweight mothers, those living in socio-economically poorest households and children of small birth weight experienced severe malnutrition regardless of setting. Educational attainments and access to health and nutritional care may not be enough to reduce the burden of severe malnutrition in rural settings. Our study provides helpful guidelines for context-specific interventions to reduce under-5 severe malnutrition.
“…In contrast, CISAF uses conventional nutritional indicators' aggregate values to estimate the overall burden of severe malnutrition, thus provide a more convincing estimation of the proportion of malnourished children in the population [10]. Our nding of a higher prevalence of severe under-5 malnutrition in rural areas concurs with previous research [20,21,22,23]. Several studies have also reported a higher prevalence of severe under-5 malnutrition in urban areas in Bangladesh with limited geographical coverage [24,25,26].…”
IntroductionSevere under-5 child malnutrition (i.e., severe stunting, severe wasting and severe underweight) is high in Bangladesh. The interplay between risk factors needs to be understood to address this complex public health issues. We aim to explore the prevalence and risk factors for severe under-5 child malnutrition in Bangladesh's rural and urban areas using the Composite Index of Severe Anthropometric Failure (CISAF).MethodsWe analysed data from Bangladesh Demographic Health Surveys (BDHSs), 2017-18. Severe malnutrition was defined using the CISAF, and conventional nutritional indicators were aggregated to estimate malnutrition's overall burden. The proportional differences of variables between non-severe malnutrition and severe malnutrition group were assessed using Chi-square test. Risk factors for malnutrition were analysed using regression models to assess the odds ratio (OR) and 95% confidence interval (CI).ResultsThe overall prevalence of severe under-5 child malnutrition was 11% with 12% in rural areas and 10% in urban areas. The key risk factors in rural areas were children born with small birth weight (OR: 2.4, 95% CI: 1.5–3.8), socio-economically poorest households (OR: 2.3, 95% CI: 1.4–3.7) and children aged 36-47 months (OR: 2.1, 95% CI: 1.6–2.8). The key risk factors in urban areas were children born with small birth weight (OR: 5.0, 95% CI: 2.9–8.6), children of mothers with no formal education (OR: 2.0, 95% CI: 1.2–3.6) and children's birth order ≥4 (OR: 1.8, 95% CI: 1.2–2.8). 52% lower risk difference of parents with formal education vs no formal education, and 71% higher risk difference of most affluent vs poorest household for being severely malnourished were estimated in rural areas than in urban areas.ConclusionOne in ten children living in both rural and urban areas experience severe malnutrition. Children of parents with no formal education, children of underweight mothers, those living in socio-economically poorest households and children of small birth weight experienced severe malnutrition regardless of setting. Educational attainments and access to health and nutritional care may not be enough to reduce the burden of severe malnutrition in rural settings. Our study provides helpful guidelines for context-specific interventions to reduce under-5 severe malnutrition.
“…This findings are consistent with findings from Tanzania by Mshida et al [22], and from Onitsa South eastern Nigeria by Ndukwu et al [23]. The pathophysiology of undernutrition due to prolong influence of unhygienic environmental factors via environmental enteropathy (EE) or Environmental Enteric Dysfunction (EED) and which triggers mal-absorption has been adequately described [12,[24][25][26]. This aptly explains the association between underweight and the WASH factors.…”
Section: Underweight (Malnutrition) and Wash Factorssupporting
The state of the environment in which we live and certain hygienic practices we indulge in has been known to affect our nutritional status. This study was aimed at examining the association between malnutrition and some selected water, sanitation and hygiene (WASH) practices among school children in Gombe State Nigeria. A cross sectional survey was conducted between March and June, 2019. A total of 745 pupils were selected from 12 public and 6 private schools across 6 LGAs in Gombe state, using multi-stage sampling technique. Anthropometric measurements of heights and weights of the study participants were done using standard instruments and procedures. Other relevant data (age, sex, some environmental variables etc) were collected using a structured template. Data analysis was done using IBM SPSS version 21 and key variables were presented using descriptive statistics, while associations were tested using Chi square. Odd ratio (OR) was used to estimate risks of malnutrition among the subjects and p-value was set at 0.05. The pupils had a mean age of 9.96±2.26 years, 50.9% of whom were males the rest being females. Though 84.6% of them had toilets in their residences not all of them (98.6%) put them to use. A good proportion (79.1%) dispose their refuse by dumping and slightly more than half of them (51.7%) have access to pipe borne water. And though only two (method of refuse disposal and source of drinking water) out of the eight WASH variables studied were found to be associated with underweight (Composite indicator of malnutrition), all the eight variables were found to be associated with stunting (chronic malnutrition). Overall, 20.8% and 22.4% of the subjects were underweight and stunted, respectively. The foregoing raises a germane concern about the role of WASH in malnutrition among school children and the need for a comprehensive and sustainable school feeding programme in the state and country at large. There should also be an integration of a WASH component in all nutrition intervention programmes.
“…However, the possibility of the shift towards more wasting in urban settings of low and middle-income countries was predicted in the UNICEF publication Innocenti Digest number 10 in 2002 [79]. Under five children living in informal settlements in large cities are often exposed to very precarious conditions that can lead to poor health status, including poor nutrition status [79,80]. The presence of such informal settlements should be a trigger for including urban setting in all strategies to tackle undernutrition.…”
Childhood wasting is among the most prevalent forms of undernutrition globally. The Southeast Asia region is home to many wasted children, but wasting is not recognized as a public health problem and its epidemiology is yet to be fully examined. This analysis aimed to determine the burden of wasting, its predictors, and the level of wasting and stunting concurrence. Datasets from Demographic and Health Surveys and Multiple Indicator Cluster Surveys in six countries in the region were analyzed. The pooled weighted prevalence for wasting and concurrent wasting and stunting among children 0–59 months in the six countries was 8.9%, 95% CI (8.0–9.9) and 1.6%, 95% CI (1.5–1.8), respectively. This prevalence is approximately 12-fold higher than the 0.7% prevalence of high-income countries; and translated into an absolute number of 1,088,747 children affected by wasting and 272,563 concurrent wasting and stunting. Wasting prevalence was 50 percent higher in the 0–23-month age group. Predictors for wasting included source of drinking water, wealth index, urban residence, child’s age and history of illness and mother’s body mass index. In conclusion, our analysis showed that wasting is a serious public health problem in the region that should be addressed urgently using both preventive and curative approaches.
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