The burden and correlates of childhood undernutrition in Tanzania according to composite index of anthropometric failure

Determinants of aggregate anthropometric failure among children under-five years in Ethiopia: Application of multilevel mixed-effects negative binomial regression modeling

Undernutrition significantly contributes to failure to thrive in children under five, with those experiencing multiple forms of malnutrition facing the highest risks of morbidity and mortality. Conventional markers such as stunting, wasting, and underweight have received much attention but are insufficient to identify multiple types of malnutrition, prompting the development of the Composite Index of Anthropometric Failure (CIAF) and the Composite Index of Severe Anthropometric Failure (CISAF) as an aggregate indicators. This study aimed to identify factors associated with CIAF and CISAF among Ethiopian children aged 0-59 months using data from the 2019 Ethiopia Mini Demographic and Health Survey. The study included a weighted sample of 5,259 children and used multilevel mixed-effects negative binomial regression modeling to identify determinants of CIAF and CISAF. The result showed higher incidence-rate ratio (IRR) of CIAF in male children (adjusted IRR = 1.27; 95% CI = 1.13-1.42), children aged 12-24 months (aIRR = 2.01, 95%CI: 1.63-2.48), and 24-59 months (aIRR = 2.36, 95%CI: 1.91-2.92), those from households with multiple under-five children (aIRR = 1.16, 95%CI: 1.01-1.33), poorer households (aIRR = 1.48; 95%CI: 1.02-2.15), and those who lived in houses with an earthen floor (aIRR = 1.37, 95%CI: 1.03-1.82). Similarly, the factors positively associated with CISAF among children aged 0-59 months were male children (aIRR = 1.47, 95% CI = 1.21-1.79), age group 6-11 months (aIRR = 2.30, 95%CI: 1.40-3.78), age group 12-24 months (aIRR = 3.76, 95%CI: 2.40-5.88), age group 25-59 months (aIRR = 4.23, 95%CI: 2.79-6.39), children from households living with two and more under-five children (aIRR = 1.27, 95%CI:1.01-1.59), and children from poorer households (aIRR = 1.93, 95% CI = 1.02-3.67). Children were more likely to suffer from multiple anthropometric failures if they were: aged 6-23 months, aged 24-59 months, male sex, living in households with multiple under-five children, and living in households with poor environments. These findings underscore the need to employ a wide range of strategies to effectively intervene in multiple anthropometric failures in under-five children.

The Intersection of a Child's Demographics and Household Socioeconomic Status in the Multimorbidity of Malaria, Anaemia, and Malnutrition among Children Aged 6-59 Months in Nigeria

Multimorbidity of malaria, anemia, and malnutrition (MAMM) is a condition in which an individual has two or more of these health conditions, and is becoming an emergent public health concern in sub-Saharan African countries. The independent associations of a child's demographic variables and household socioeconomic (HSE) disparities with a child's health outcomes have been established in the literature. However, the effects of the intersection of these factors on MAMM, while accounting for other covariates, have not been studied. Therefore, this study aimed to determine how children's sex, age, and household socioeconomic status interact to explain the variations in MAMM among children aged 6-59 months in Nigeria. Data from the 2018 Nigeria Demographic and Health Survey and the 2018 National Human Development Report (NHDR) were used. This study included weighted samples of 10,184 children aged 6-59 months in Nigeria. A three-level multilevel mixed effect ordinal logistic regression model was used, such that individual characteristics at level 1 were nested in communities at level 2 and nested in states at level 3. Subsequently, predictive probability charts and average adjusted probability tables were used to interpret the intersectional effects. Five models were created in this scenario. Model 1 is the interaction between the child's sex and household wealth status; model 2 is the interaction between the child's sex and age; model 3 is the interaction between the child's age and household wealth status; model 4 has the three two-way interactions of the child's sex, age, and household wealth status; and model 5 includes model 4 and the three-way interactions between a child's sex, age, and household wealth quintiles; while accounting for other covariates in each of the models. The prevalence of children with a 'none of the three diseases' outcome was 17.3% (1767/10,184), while 34.4% (3499/10,184) had 'only one of the diseases', and 48.3% (4918/10,184) had 'two or more' MAMMs. However, in the multivariate analyses, model 3 was the best fit compared with other models, so the two-way interaction effects of a child's age and household wealth status are significant predictors in the model. Children aged 36-47 months living in the poorest households had a probability of 0.11, 0.18, and 0.32 of existing with MAMM above the probability of children of the same age who live in the middle class, more prosperous, and richest households, respectively, while all other covariates were held constant. Thus, the variation in the prevalence of MAMM in children of different ages differs depending on the household wealth quintile. In other words, in older children, the variations in MAMM become more evident between the richer and the poorer household quintiles. Therefore, it is recommended that policies that are geared toward economic redistribution will help bridge the disparities observed in the prevalence of multiple diseases among children aged 6-59 months in Nigeria.

Anthropometric failures and its predictors among under five children in Ethiopia: multilevel logistic regression model using 2019 Ethiopian demographic and health survey data

BACKGROUND

Composite Index of Anthropometric Failure (CIAF) combines all three forms of anthropometric failures to assess undernutrition status of children. There is no study on CIAF to identify the real and severe form of under nutrition among Ethiopian children that addressed community level factors. So, this study determined CIAF and identified important factors which helps to design appropriate intervention strategies by using multi-level advanced statistical model.

METHODS

The study included 5,530 under five children and utilized a secondary data (EMDHS 2019) which was collected through community-based and cross-sectionally from March 21 to June 28, 2019. Composite index of anthropometric failure among under five children was assessed and a two-stage sampling technique was used to select the study participants. Descriptive summary statistics was computed. A multi-level binary logistic regression model was employed to identify important predictors of CIAF in under five children. Adjusted odds ratio with its 95% CI was estimated and level of significance 0.05 was used to determine significant predictors of CIAF.

RESULTS

The prevalence of composite index of anthropometric failure (CIAF) was 40.69% (95% CI: 39.41, 42.00) in Ethiopia. Both individual and community level predictors were identified for CIAF in under five children. Among individual level predictors being male sex, older age, short birth interval, from mothers who have not formal education, and from poor household wealth quintile were associated with higher odds of CIAF among under five children. Low community women literacy and being from agriculturally based regions were the community level predictors that were associated with higher odds of CIAF in under five children in Ethiopia.

CONCLUSIONS

The burden of composite index of anthropometric failure in under five children was high in Ethiopia. Age of child, sex of child, preceding birth interval, mother's education, household wealth index, community women literacy and administrative regions of Ethiopia were identified as significant predictors of CIAF. Therefore, emphasis should be given for those factors to decrease the prevalence of CIAF in under five children in Ethiopia.

Spatial regression models to assess variations of composite index for anthropometric failure across the administrative zones in Ethiopia

BACKGROUND

There are a number of previous studies that investigated undernutrition and its determinants in Ethiopia. However, the national average in the level of undernutrition conceals large variation across administrative zones of Ethiopia. Hence, this study aimed to determine the geographic distribution of composite index for anthropometric failure (CIAF) and identify the influencing factors it' might be more appropriate.

METHODS

We used the zonal-level undernutrition data for the under-five children in Ethiopia from the Ethiopian Demographic and Health Survey (EDHS) dataset. Different spatial models were applied to explore the spatial distribution of the CIAF and the covariates.

RESULTS

The Univariate Moran's I statistics for CIAF showed spatial heterogeneity of undernutrition in Ethiopian administrative zones. The spatial autocorrelation model (SAC) was the best fit based on the AIC criteria. Results from the SAC model suggested that the CIAF was positively associated with mothers' illiteracy rate (0.61, pvalue 0.001), lower body mass index (0.92, pvalue = 0.023), and maximum temperature (0.2, pvalue = 0.0231) respectively. However, the CIAF was negatively associated with children without any comorbidity (-0.82, pvalue = 0.023), from families with accessibility of improved drinking water (-0.26, pvalue = 0.012), and minimum temperature (-0.16).

CONCLUSION

The CIAF across the administrative zones of Ethiopia is spatially clustered. Improving women's education, improving drinking water, and improving child breast feeding can reduce the prevalence of undernutrition (CIAF) across Ethiopian administrative zones. Moreover, targeted intervention in the geographical hotspots of CIAF can reduce the burden of CIAF across the administrative zones.

Socio-economic, demographic, and contextual predictors of malnutrition among children aged 6-59 months in Nigeria

Malnutrition has remained a global public health issue, particularly in low- and middle-income countries (LMICs). Researchers have committed to studying malnutrition (especially in children under the age of five) to address the nine malnutrition targets, set by the WHO to be achieved by 2025. This study seeks to evaluate the prevalence, the individual and contextual predictors of malnutrition among children aged 6-59 months across Nigeria and its states. Two separates, independently collected, nationally representative cross-sectional surveys, the National Human Development Report (NHDR 2018) and the 2018 Nigeria Demographic and Health Survey (2018 NDHS) were linked for this study. Spatial map was used to describe the prevalence of malnutrition, a 3-level multivariate multilevel logistic regression models were fitted where children/individuals (at level 1) were nested in communities/clusters (at level 2) and nested in states (at level 3). A weighted sample of 7,770 children 6-59 months were considered in this study. The results showed that an estimated 43.6% of children aged 6-59 months are poorly nourished in Nigeria. The proportions of poorly nourished children were generally highest in the Northern Nigeria. Child's gender, age, birth size, preceding birth order, anaemia status, maternal education, work status, body weight, household wealth status, number of bedrooms were among individual/household predictors of malnutrition. On the community level, being from community with high wealth index, distance to nearest health facilities is no big problem. Regional variations and gender inequality index were the state level predictors of malnutrition among children in Nigeria. This study has shown that two-third of children aged 6-59 months in Nigeria were poorly nourished, an indication of a growing concern of double burden of malnutrition in Nigeria.

Epidemiological profile of malnutrition status and spatial distribution of children and adolescents living with HIV/AIDS in Tanzania

OBJECTIVES

To determine the prevalence of malnutrition status, analyse the association between malnutrition status and individual-level factors, and explore the spatial variation among children and adolescents living with HIV/AIDS in Tanzania.

METHODS

The study is based on large-scale baseline routine data from the National AIDS Control Programme on people living with HIV from January 2016 to December 2021 in mainland Tanzania. 70,102 children and adolescents aged 5-19 years receiving active antiretroviral therapy were included in the analysis. Nutritional status of participants was assessed by anthropometric measurement. Pearson's Chi-square test was used to describe the association between individual-level factors with all malnutrition outcomes and spatial analysis was used to investigate spatial distribution of malnutrition. The excess risk of malnutrition for each region was calculated while Anselin Local Moran's I and Getis-Ord statistical tools were used to identify significant hot spots regions of malnutrition.

RESULTS

The mean age of participants was 11.1 (SD 4.7) years, with 71.7% in the 5-14-year age group and 58.4% being girls. 39.2% were attending care and treatment clinics services at hospital level with public ownership. 53.4% started using ARV at age 5-14 years and 55.5% had already switched to second- or third-line ARV with 61.1% using ARV for less than 3 years. 51.2% were in WHO HIV clinical stage III or IV. The prevalence of malnutrition was 36.0% for stunting, 28.9% for underweight, 13.0% for wasting, and 48.0% for anthropometric failure. Individual-level factors which accounted for a higher proportion of malnutrition based on anthropometric failure were male sex (56.3%), age 5-14 years (50.0%), being unmarried (52.9%), being on second- or third-line ARV treatment (51.4%), ART initiation at age 5-14 years (55.7%), ARV for more than 3 years (49.4%), and stage IV of WHO HIV clinical status (57.8%). There were regional hot spots (p < 0.05): the prevalence rate and excess risk of malnutrition for stunting and anthropometric failure were highest in the southern highlands regions, for underweight in the central regions, and for wasting in the northern regions.

CONCLUSIONS

Children and adolescents living with HIV/AIDS in Tanzania suffer from poor nutritional status. Malnutrition does not occur arbitrarily, and the regions identified as hot spots should be given priority for nutritional intervention. Effective nutritional interventions for children living with HIV/AIDS should incorporate multiple approaches by considering unique geographical factors.

Space-time dynamics regression models to assess variations of composite index for anthropometric failure across the administrative zones in Ethiopia

BACKGROUND

A single anthropometric index such as stunting, wasting, or underweight does not show the holistic picture of under-five children's undernutrition status. To alleviate this problem, we adopted a multifaceted single index known as the composite index for anthropometric failure (CIAF). Using this undernutrition index, we investigated the disparities of Ethiopian under-five children's undernutrition status in space and time.

METHODS

Data for analysis were extracted from the Ethiopian Demographic and Health Surveys (EDHSs). The space-time dynamics models were formulated to explore the effects of different covariates on undernutrition among children under five in 72 administrative zones in Ethiopia.

RESULTS

The general nested spatial-temporal dynamic model with spatial and temporal lags autoregressive components was found to be the most adequate (AIC = -409.33, R2 = 96.01) model. According to the model results, the increase in the percentage of breastfeeding mothers in the zone decreases the CIAF rates of children in the zone. Similarly, the increase in the percentages of parental education, and mothers' nutritional status in the zones decreases the CIAF rate in the zone. On the hand, increased percentages of households with unimproved water access, unimproved sanitation facilities, deprivation of women's autonomy, unemployment of women, and lower wealth index contributed to the increased CIAF rate in the zone.

CONCLUSION

The CIAF risk factors are spatially and temporally correlated across 72 administrative zones in Ethiopia. There exist geographical differences in CIAF among the zones, which are influenced by spatial neighborhoods of the zone and temporal lags within the zone. Hence these findings emphasize the need to take the spatial neighborhood and historical/temporal contexts into account when planning CIAF prevention.

Incidence of Asymptomatic Shigella Infection and Association with the Composite Index of Anthropometric Failure among Children Aged 1–24 Months in Low-Resource Settings

Asymptomatic or subclinical infection by diarrheal enteropathogens during childhood has been linked to poor health and nutritional outcomes. In this study, we aimed to assess the impact of asymptomatic Shigella infection on different forms of childhood malnutrition including the composite index of anthropometric failure (CIAF). We used data from 1715 children enrolled in the multi-country birth cohort study, MAL-ED, from November 2009 to February 2012. Monthly non-diarrheal stools were collected and assessed using TaqMan Array Cards (TAC). Poisson regression was used to calculate incidence rates of asymptomatic Shigella infection. Generalized estimating equations (GEE) were used to assess the association between asymptomatic Shigella infection and nutritional indicators after adjusting for relevant covariates. Incidence rates per 100 child-months were higher in Tanzania, Bangladesh and Peru. Overall, after adjusting for relevant covariates, asymptomatic Shigella infection was significantly associated with stunting (aOR 1.60; 95% CI: 1.50, 1.70), wasting (aOR 1.26; 95% CI: 1.09, 1.46), underweight (aOR 1.45; 95% CI: 1.35, 1.56), and CIAF (aOR 1.55; 95% CI: 1.46, 1.65) in all the study sites except for Brazil. The high incidence rates of asymptomatic Shigella infection underscore the immediate need for Shigella vaccines to avert the long-term sequelae involving childhood growth.

Anthropometric failures and its associated factors among preschool-aged children in a rural community in southwest Ethiopia

Background

In 2019, 144 million under-five-year-old children were stunted, and 47 million were wasted globally. In Ethiopia, approximately 350,000 children are estimated to die each year. Preschool aged children need focused attention because this age group not only has special needs, but also forms the platform for growth and development of all children. Under nutrition among preschool children is the result of a complex interplay of diverse elements, such as birth weight, household access to food, availability and use of drinking water. This study aimed at determining the anthropometric failures and associated factors using composite indictors.

Methods

A community-based cross-sectional study design was used among randomly selected 588 caregivers with pre-school aged children. Under-nutrition of pre-school aged children was computed by using the composite index of anthropometric failure. A multi-stage sampling technique followed by a systematic random sampling technique was used to select study participants. Structured questionnaires were used to collect data. WHO Anthro software was used to calculate height for age, weight for age and weight for height. The overall prevalence of anthropometric failure (CIAF). Both bivariable and multivariable binary logistic regressions were used to identify factors associated with under-nutrition.

Results

The overall prevalence of under-nutrition among pre-school children was 50.8%, which was significantly associated with being a female (AOR = 1.51, CI: 1.076, 2.12), being from a large family (AOR = 1.78, CI: 1.19, 2.663), having acute respiratory infection (AOR = 1.767, CI: 1.216, 2.566), lack of improved source of drinking water (AOR = 1.484 CI: 1.056, 2.085) and poor dietary diversity score (AOR = 1.5, CI: 1.066, 2.112).

Conclusions

The study area has a high prevalence of CIAF in pre-school aged children. The CIAF was found to be significantly associated with the sex of the child, family size, ARI within the last two weeks, and dietary diversity score. To promote the use of family planning and the prevention of infectious diseases, health education is required. The government should adapt CIAF as a metric for assessing children’s nutritional status.

Spatial data analysis of malnutrition among children under-five years in Ethiopia

Background

Childhood malnutrition is a major cause of child mortality under the age of 5 in the sub-Saharan Africa region. This study sought to identify the risk factors and spatial distribution of the composite index of anthropometric failure (CIAF).

Methods

Secondary data from 2000, 2005, 2011, and 2016 Ethiopian Health and Demographic Survey (EDHS) were used. The generalized geo-additive mixed model was adopted via the Integrated Nested Laplace Approximation (INLA) with a binomial family and logit link function.

Results

The CIAF status of children was found to be positively associated with the male gender, the potency of contracting a disease, and multiple births. However, it was negatively associated with family wealth quartiles, parental level of education, place of residence, unemployment status of mothers, improved sanitation, media exposure, and survey years. Moreover, the study revealed significant spatial variations on the level of CIAF among administrative zones.

Conclusions

The generalized geo-additive mixed-effects model results identified gender of the child, presence of comorbidity, size of child at birth, dietary diversity, birth type, place of residence, age of the child, parental level of education, wealth index, sanitation facilities, and media exposure as main drivers of CIAF. The results would help decision-makers to develop and carry out target-oriented programs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-021-01391-x.

Effects of dairy intake on anthropometric failure in children ages 6 to 23 mo consuming vegetarian diets and fulfilling minimum dietary diversity in India

OBJECTIVES

In India, although nutritional conditions have improved, a high prevalence of anthropometric failure is still reported in children. Unfortunately, there are knowledge gaps surrounding nutrient and anthropometric shortcomings as well as dietary patterns. More than half of children are consuming a vegetarian diet. This study aimed to evaluate the effects of dietary adequacy levels on anthropometric failure in 5772 vegetarian children (ages 6-23 mo) satisfying minimum dietary diversity.

METHODS

Data were collected from the National Family Health Survey 2015-16. We created three food combinations: maximum adequacy (dairy and four food groups), medium adequacy (dairy and three food groups), and minimum adequacy (four food groups excluding dairy). We calculated odds ratios (ORs) for the association between dietary adequacy levels and anthropometric failures with 95% confidence intervals (CIs) using logistic regression models. The modification effect of breastfeeding status was also explored.

RESULTS

Approximately 35% of children had stunted growth. ORs showed a significant increase in the risk of anthropometric failure, notably wasting, and underweight in children with minimum-adequacy diets (OR, 1.46; 95% CI, 1.15-1.86) compared with children with maximum-adequacy diets. Those associations were more pronounced among children who were not breastfed (OR, 2.44; 95% CI, 1.19-5.00) than among children who were (OR, 1.35; 95% CI, 1.04-1.74; P value for the interaction = 0.07). Similar associations were observed for wasting among children who were not breastfed (OR, 2.82; 95% CI, 1.34-5.95) and who were breastfed(OR, 1.12; 95% CI, 0.85-1.5; P value for the interaction = 0.03).

CONCLUSIONS

Dairy is an essential source of nutrients that are required for healthy growth and development in children younger than 2 y, even if they satisfy minimum dietary diversity conditions in India.

Disparities in childhood composite index of anthropometric failure prevalence and determinants across Ethiopian administrative zones

BACKGROUND

The prevalence of under-five children's undernutrition in Ethiopia is among the highest in the world. This study aimed at exploring the prevalence and risk factors of the composite index for anthropometric failure (CIAF) of under-five children in Ethiopia by incorporating the zonal (district) effects.

METHODS

The data was drawn from Ethiopian Demographic and Health Surveys (EDHSs), a population-based cross-sectional study of 29,599 under-five year children from 72 Zones in the years 2000, 2005, 2011, and 2016. Fixed effect variables related to child and maternal-household were included in the model. We adopted a generalized mixed model with CIAF as outcome variable and Zones as random effects.

RESULTS

The prevalence of CIAF in Ethiopia was 53.78% with the highest prevalence of 61.30% in 2000 and the lowest prevalence of 46.58% in 2016. The model result revealed that being a female child, absence of comorbidity, singleton births, and the first order of birth showed significantly lower CIAF prevalence than their counterparts. Among the household characteristics, children from mothers of underweight body mass index, uneducated parents, poor household sanitation, and rural residents were more likely to be undernourished than their counterparts. Based on the best linear unbiased prediction for the zonal-level random effect, significant variations of CIAF among zones were observed.

CONCLUSION

The generalized linear mixed-effects model results identified gender of the child, size of child at birth, dietary diversity, birth type, place of residence, age of the child, parental level of education, wealth index, sanitation facilities, and media exposure as main drivers of CIAF. Disparities of CIAF were observed between and within the Ethiopian administrative Zones over time.

Tracking progress in anthropometric failure among under-five children in Ethiopia: a geospatial and multilevel analysis

Background

Undernutrition is a major public health concern among under-five children in many developing countries. This work evaluated the overall prevalence of under-nutrition by using a composite index of anthropometric failure (CIAF), which helps in the detection of children with multiple anthropometric failures. This research also includes the Spatio-temporal distribution of childhood anthropometric failures across time.

Methods

Secondary data was obtained from the Ethiopian Demographic and Health Survey for the survey 2005, 2011, and 2016 years. Data included 23,864 samples of children between the ages of 0–59 months, which is a nationally representative sample in Ethiopia. Other than descriptive statistics, the multivariate multilevel logistic regression was used to identify associated factors, and Getis-Ord spatial statistical tools were employed to identify high and low hotspots areas of anthropometric failures.

Result

The prevalence obtained with CIAF in 2005, 2011, and 2016 was, 53.5 %, 51 %, and 46.2 % of children were suffering from under-nutrition respectively. The spatial analysis revealed areas that are at a higher risk of anthropometric failures consistently were found in northern parts of the country, largely in the Amhara, Tigray, and Afar regions. Multilevel logistic regression analysis showed that the risk of anthropometric failure was higher among older children, had low birth weight, had a mother with low BMI, was in a rural area, had mothers and fathers without formal education.

Conclusions

In addition to identifying wasted, stunted, and underweight children, CIAF also identified children with multiple conditions, which are often overlooked in nutritional surveys. As revealed by this composite index, the prevalence of anthropometric failure remains considerably high and its spatial distribution also significantly varied across the regions in the country. The established socio-demographic characteristics and districts with a higher risk of anthropometric failure can be used to develop localized intervention and prevention strategies to improve Ethiopian children’s nutritional status and healthcare.