Exploring Spatial Variations and Determinants of Dietary Diversity Among Children in Ethiopia: Spatial and Multilevel Analysis Using EDHS (2011-2016)

Spatial variation of zero fruits/vegetables consumption and associated factors among children aged 6-23 months in Ethiopia: geographical weighted regression analysis

Background

After 6 months, nutrient-dense, varied diets containing fruits and vegetables are crucial to supplement breastfeeding. Like many other low-income countries, Ethiopia has very low FV consumption. Zero vegetable or fruit (ZVF) consumption has been shown to significantly raise the risk of non-communicable diseases and has been ranked among the top 10 risk factors for mortality. And it is associated with poor health, an increased risk of obesity, and a higher risk of non-communicable diseases. Thus, this study's goal was to investigate the spatial distribution of ZVF consumption and its spatial determinants among children aged 6-23 months in Ethiopia.

Methods

A cross-sectional study design was employed. A total of 1,489 weighted samples were included from kids' datasets from the 2019 Ethiopian mini-demographic and health survey. STATA version 16, ArcGIS version 10.8, Kuldorff's SaTScan version 9.6, and MGWR version 2.0 software were used for analysis. Spatial regression analyses (geographical weighted regression and ordinary least squares analysis) were conducted. Models were compared using AICc and adjusted R2. A p-value of less than 0.05 was used to declare statistically significant spatial predictors, and the corresponding local coefficients were mapped.

Results

The spatial distribution of ZVF consumption among children aged 6-23 months was non-random in Ethiopia. Spatial scan analysis revealed a total of 120 significant clusters. Maternal education, wealth status, age of the child, place of delivery, number of under-five children in the house, and current pregnancy status were significant predictors of the spatial variation of ZVF consumption.

Conclusion

Significant geographic variation in ZVF consumption was found in this study throughout Ethiopia's regions. Significant predictors of the spatial variation in ZVF consumption were maternal education, wealth status, child age, place of delivery, number of under-five children in the home, and status as a pregnant woman at the time of birth. Therefore, in order to improve children's adequate consumption of fruit and vegetables, area-based interventions that can consider these significant factors into account are needed.

The prevalence and multilevel analysis of minimum dietary diversity intake and its determinants among 6-23 months old infants in The Gambia: further analysis of the Gambian demographic and health survey data

BACKGROUND

Poor infant and young child feeding (IYCF) practices are a significant issue both globally and in developing nations, and they have a significant role in undernutrition, healthy growth, and development, particularly in the first 2 years of life. Improving children's general health and wellbeing requires recognizing and decreasing preventable drivers of malnutrition. Hence, this study aimed to assess the prevalence and possible determinants of minimum dietary diversity among 6-23 months old babies in the Gambia.

METHODS

Data from the 2019-2020 Gambia demographic and health survey were used. The study included a total of 2100 weighted 6-23 months old children. To identify characteristics significantly linked with minimum dietary diversity among infants, a multilevel fixed-effect analysis approach was used. After adjusting other confounding variables, variables with a p value of 0.25 were incorporated into a multivariable multilevel regression analysis to determine associated variables. An adjusted odds ratio with a 95% confidence interval was then applied.

RESULTS

Only 22.22% (95% CI 18.55, 21.99) of infants had received the minimum dietary diversity. Mothers, who had mass media exposure (aOR = 2.71, CI = (1.02, 6.21), wealthier (aOR = 1.70, CI = 1.02, 2.85), child age of (aOR = 4.14, CI = 2.98, 5.76), and (aOR = 4.97, CI = 3.54, 6.98), have shown a positive statistical association with the outcome variable, respectively. Regarding regions mothers who came from Kanifing (aOR = 0.49, CI = 0.25, 0.94), Janjanbureh (aOR = 0.38, CI = 0.18, 0.82), and Basse (aOR = 0.51, CI = 0.26, 0.99) had showed less likelihood odds to provide the minimum dietary diversity (MDD) for their babies compared to Banjul local government area, respectively.

CONCLUSION

The World Health Organization dietary evaluation tool suggests that the MDD value be extremely low, even though it might be slightly higher than the numbers for some nations. The country may need to take drastic measures to tackle child malnutrition.

Minimum Dietary Diversity Among Children Aged 6-59 Months in East Africa Countries: A Multilevel Analysis

Objective: To find out the determinants of minimum dietary diversity (MDD) among under-five children in East Africa based on the 2017 revised indicator. Methods: Secondary data from the demographic and health survey (DHS) of eight countries in East Africa were combined. A total of 27,223 weighted samples of children aged 6-59 months were included. Multi-level logistic regression analysis was employed to identify the determinants of dietary diversity. Results: The magnitude of adequate MDD in East Africa was found to be 10.47% with 95% CI (10.12-10.84) with the lowest and highest magnitude in Ethiopia and Rwanda respectively. Having a mother in the age group of 35-49, having a mother with higher educational attainment, and having a post-natal check-up within 2 months were significant factors in determining adequate MDD. Conclusion: The magnitude of adequate MDD intake among children aged 6-59 months in East Africa is relatively low. Therefore, strengthening interventions focused on improving the economic status of households, the educational status of mothers, and diversified food consumption of children aged 6-59 months should get priority to improve the recommended feeding practice of children.

Understanding Child Wasting in Ethiopia: Cross-sectional Analysis of 2019 Ethiopian Demographic and Health Survey Data Using Generalized Linear Latent and Mixed Models

BACKGROUND

Wasting is an immediate, visible, and life-threatening form of undernutrition in children aged <5 years. Within a short time, wasting causes recurrent sickness, delayed physical and mental growth, impatience, poor feeding, and low body weight. The long-term consequences of wasting and undernutrition are stunting, inability to learn, poor health status, and poor work performance. Wasting remains a public health problem in Ethiopia. According to the World Health Organization, countries have to reduce undernutrition including child wasting to below 5% by 2025. Ethiopia is attempting to attain national and international targets of undernutrition while struggling with many problems.

OBJECTIVE

This study aimed to identify the prevalence and associated factors of wasting to provide information for further renewing policy commitments.

METHODS

We used community-based, cross-sectional data from the Ethiopian Mini Demographic and Health Survey. The survey was conducted in 9 regions and 2 city administrations. Two-stage cluster sampling was used to recruit study participants. In the first stage, enumerations areas were selected, and 28-35 households per enumeration area were selected in the second stage. Our analysis included 2016 women with children aged <5 years from the 2019 EMDHS data set. We dropped incomplete records and included all women who fulfilled the eligibility criteria. We used multilevel ordinal regression using Generalized Linear Latent and Mixed Models (GLLAMM) and predicted probability with log-likelihood ratio tests. Fulfilling the proportional odds model's assumption during the application of multilevel ordinary logistic regression was a cumbersome task. GLLAMM enabled us to perform the multilevel proportional odds model using an alternative method.

RESULTS

In our analysis, wasting was 7.68% (95% CI 6.56%-8.93%). Around 26.82% of mothers never used antenatal care for their current child. Most mothers (52.2%) did not have formal education, and 86.8% did not have postnatal care for their children. Additionally, half (50.93%) of the mothers have ≥6 household members. Wasting was associated with feeding diverse foods (coefficient 4.90, 95% CI 4.90-4.98), female sex of the household head (-40.40, 95% CI -40.41 to -40.32), home delivery (-35.51, 95% CI -35.55 to -35.47), first (16.66, 95% CI, 16.60-16.72) and second (16.65, 95% CI 16.60-16.70) birth order, female child (-12.65, 95% CI -12.69 to -12.62), and household size of 1 to 3 (10.86, 95% CI 10.80-10.92).

CONCLUSIONS

According to the target set by World Health Organization for reducing undernutrition in children aged <5 years to below 5% by 2025, child wasting of 7.68% in Ethiopia should spark an immediate reaction from the government and stakeholders. Informed policy decisions, technology-based child-feeding education, and food self-sufficiency support could improve the current challenges. Additional effort is important to improve low maternal education, family planning, awareness of sex preferences, women empowerment, and maternal health services.

Spatial distribution of vitamin A rich foods intake and associated factors among children aged 6-23 months in Ethiopia: spatial and multilevel analysis of 2019 Ethiopian mini demographic and health survey

Background

Inadequate micronutrients in the diet and vitamin A deficiency are worldwide public health problems. In developing regions, many preschool children are undernourished, become blind every year and died before the age of 23 months. This study was aimed to explore the spatial distribution of vitamin A rich foods intake among children aged 6–23 months and identify associated factors in Ethiopia.

Methods

Ethiopian Mini Demographic and Health Survey 2019 dataset with a total 1407 children aged 6–23 months was used. Data management and processing were done using STATA version 15 software and Microsoft Office Excel. ArcMap version 10.7 software was used for mapping and spatial visualization of the distribution. Spatial scan statistics was performed using SaTScan version 9.5 software for Bernoulli-based model. Multilevel mixed effect logistic regression model was employed to identify associated factors.

Results

Overall, 38.99% (95% CI: 36.46–41.62) of children aged 6– 23 months took vitamin A rich foods. Poor intake of vitamin A rich foods was significantly clustered Dire Dawa city, Somali and Harari regions of Ethiopia. Children aged 6–23 months lived in the primary cluster were 70% (RR = 1.70, P-value < 0.001) more likely to intake vitamin A rich foods than children lived outside the window. In the multilevel mixed effect logistic regression analysis, Primary educational status (AOR:1.42, 95% CI: 1.05, 1.93) and higher educational status (AOR:3.0, 95% CI: 1.59, 5.65) of mother, Dire Dawa (AOR:0.49, 95% CI: 0.22, 1.12) city, Afar (AOR: 0.16, 95% CI: 0.07, 0.36), Amhara (AOR: 0.37, 95% CI: 0.19, 0.71) and Somali (AOR: 0.02, 95% CI: 0.003, 0.08) regions of Ethiopia, children aged 13–23 months (AOR: 1.80, 95% CI: 1.28, 2.36), Mothers’ exposure to media (AOR: 1.41, 95% CI: 1.04, 1.92) were statistically significant factors for vitamin A rich foods intake among children aged 6–23 months.

Conclusions

Only 4 out of ten children took vitamin A rich foods which is too low compared to the national target and significantly clustered in Ethiopia. Mother’s educational status, Region, Child age and Mother’s media exposure are significant factors vitamin A rich foods intake. Stakeholders should strengthen mothers’ education status, creating awareness for mothers on child feeding and using locally available natural resource to produce vitamin A rich foods.

Stunting and Associated Factors Among 6-23 Months Age Children in Ethiopia: Application of Generalized Linear Latent and Mixed Modeling

Low height/length-for-age (stunting) is a public health problem in Ethiopia. Efforts that have been made to evaluate factors affecting national and international strategies related to the problem are very limited and poorly achieved. The present study aimed to evaluate low length/height-for-age (stunting) and its associated factors among children 6 to 23 months of age in Ethiopia. We used cross-sectional data collected for 2019 EMDHS. We cleaned, processed, and analyzed in Stata v.15. Socio-demographic, socio-economic parameters, and nutritional (wasting, diet frequency, breast milk, and animal milk) factors were used in the analysis. We fitted Generalized Linear Latent and Mixed Model (GLLAMM) to examine the associations. We analyzed the data of 2,037 children aged 6-23 months and found stunting of 933.07(45.80%). Some factors such as home delivery [coef. = -4.58, 95% CI:-7.81,-1.34] and household size of ≥6 [coef. = -5.53, 95% CI:-10.36,-7.10] were positively associated. No current breastfeeding [coef. = 10.70, 95% CI: 2.16, 19.23] and still breastfeed [coef. = 10.68, 95% CI: 2.62, 18.74] were negatively associated with stunting. Stunting among 6-23 months aged children in Ethiopia is very high above all the national, regional, and international targets. Feeding practice, socio-economic, and psychosocial-support for mothers need revised commitment for pragmatic solution.

Spatial variation and determinates of dietary diversity among children aged 6-23 months in Ethiopia: spatial and multilevel analysis using Ethiopian Demography Health Survey (EDHS) 2019

BACKGROUND

Minimum dietary diversity is the consumption of five or more food groups from the eight World Health Organization recommended food groups. Adequately diversified diet, in terms of amount and composition, is critical for optimal growth, development, and long-term health outcomes in the first 2 years. Understanding the regional variation of dietary diversity and the underlying factors is crucial for developing and implementing interventions. However, the use of spatial approaches in dietary studies has not been widely established. Therefore, this study aimed to explore the spatial patterns and determinates of minimum dietary diversity practice among 6-23 months children in Ethiopia.

METHODS

Secondary data analysis was conducted based on the Demographic and Health Surveys data conducted in Ethiopia. A total weighted sample of 1578 children aged 6-23 months was included for this study. The Global Moran's I was estimated to look into the regional variation of dietary diversity and hotspot and cold spot areas. Further, multivariable multilevel logistic regression was used for factor analyses. Adjusted Odds Ratio with 95% CI was used to declare the strength and significance of the association.

RESULTS

Overall, 87.4% (95% CI: 85.7 to 88.9%) of children in 2019 had inadequate Minimum dietary diversity. We identified statistically significant clusters of high inadequate dietary diversity (hotspots) notably observed in Somali, Afar, Eastern and western Amhara, western Tigray, Benishangul, and Northeastern and western parts of the southern nations, nationality and peoples' regions. Inadequate dietary diversity was significantly higher among young children, uneducated mother, married women, younger mother, no postnatal check, community with higher level of poverty and community level uneducated woman.

CONCLUSION

According to the findings of this study inadequate Minimum dietary diversity for children as measured by World Health Organization dietary assessment shows high. Children's dietary diversity was distributed non-randomly in different districts across Ethiopia's regions. The findings of the study provided critical evidence about dietary diversity and associated factors. Hence, policy should focused on improve education status of Mother, boosting economic status of the community, increased maternal continuum of care and focused on young children nutrition may advance dietary diversity.

Associations Between Obesity, Physical Inactivity, Healthcare Capacity, and the Built Environment: Geographic Information System Analysis

Background

Obesity is one of the major critical health conditions affecting many people across the world. One of the major causes of obesity is identified to be sedentary lifestyles and physical inactivity, which may be associated with environmental factors.

Objective

The study analyzes variations in obesity and physical inactivity in the State of South Carolina, US, and their association with healthcare capacity and the built environment.

Methods

Data were obtained from different secondary sources and surveys, 2012, and then linked on the county-level using ArcGIS. Global Moran's I was used to examine the spatial distribution at the state level, and Anselin's local Moran's I was used to detect any significant clusters at the county level. Ordinary least squares regression models were calculated for obesity and physical inactivity separately.

Results

More than 70% of SC counties had high levels of obesity and physical inactivity. Spatial analysis showed statistical clusters of high obesity, high physical inactivity, and low access to exercise opportunities in rural areas compared to urban areas. Conversely, clusters of high density of health-care facilities appeared in urban areas. Through the regression models, the density of primary care physicians (p = 0.025) and access to exercise opportunities (p = 0.075) were negatively associated with obesity, while the low perception of own health (p = 0.001) and obesity rate (0.011) were positively associated with physical inactivity.

Conclusion

GIS was useful to illustrate and identify significant geographic variations and high clusters of obesity and physical inactivity in rural areas, compared with high clusters of access to exercise opportunities and health-care facilities in urban areas. The international health community is encouraged to utilize spatial information systems to examine variations and recommend evidence-based recommendations to redistribute equitable public health efforts. The development of strategies and initiatives toward reducing variation in health and sustainable development is key to promote the population wellbeing.