Spatial variations and associated factors of food insecurity and child under nutrition in east Gojjam zone, Ethiopia: a multilevel mixed effects model.
Creators: name: Aderaw, Zewdie
Publisher: name: National Academic Digital Repository of Ethiopia
Year: 2018

description: Background: - Child undernutrition remains a major public health challenge. The magnitude of the problem varies based on geographical location. In Ethiopia, spatial analysis studies were done based on coarse spatial resolutions. To be more efficient in targeting interventions geographically, spatial analysis using micro level spatial resolution is recommended. Accordingly, different studies were done to identify factors associated with food insecurity and child undernutrition, but most of them ignore either the individual or community level factors. Hence, identification of spatial variations and individual and contextual level determinant factors of food insecurity and child undernutrition in XVI | P a g e relation to the agroecosystem is essential to deliver targeted, efficient and sustainable solutions to the problems. Objectives: - This study determined spatial variations of food insecurity and child undernutrition. The study also identified the role of individual and community level factors of food insecurity and child undernutrition using multilevel mixed effects regression analysis in East Gojjam Zone, Ethiopia. Methods: - An agroecosystem linked to community based comparative cross sectional survey was conducted among 3108 households with children aged 6-59 months. Multistage cluster random sampling technique was used to select study participants. Data were collected on household geographical location, socio-demographic characteristics, child and maternal anthropometry and on potential individual and community level determinant factors. Collected data were entered using Epi info version 3.5 and exported to World Health Organization (WHO) Anthro to determine child nutritional status. SaTScan software was used to determine spatial variations of food insecurity and child undernutrition using SaTScan Bernoulli model. To identify the most likely clusters using SaTScan software, the Log Likelihood Ratio (LLR) at 95% Confidence Interval (CI) and P value less than 0.05 as the level of significance were considered. To identify determinant factors of food insecurity and child undernutrition, multilevel mixed effects ordinal regression and multilevel mixed effects linear regression analyses were used, respectively. The results of fixed effects were shown as an adjusted odd ratio (AORs) for the multilevel mixed effects ordinal regression and regression coefficients for the multilevel mixed effects linear regression. The results of random effects were presented as variance and the intra-class correlation coefficient (ICC) was calculated to estimate unexplained variance attributable to cluster level. Results: - The overall prevalence of household food insecurity was 65.3% (95% CI: 63.5, 67.00). The highest prevalence of food insecurity was observed from the lowlands of the Abay Valley (70.6%, 95% CI: 66.9, 74.2). Followed by the hilly and mountainous highland areas of Choke Mountain (69.8%, 95% CI: 65.9, 73.3). Similarly, sample clusters taken from hilly and mountainous highland areas (LLR: 11.64; P&lt;0.01) and low lands of the Abay Valley (LLR: 8.23; P&lt;0.05) were identified as the most likely primary and secondary clusters, respectively. XVII | P a g e The prevalence of stunting 39.0% (95% CI: 37.32, 40.75), 18.7% (95% CI: 17.32, 20.0) underweight, and 12.22% (95% CI: 11.12, 13.42) wasting were observed in the study area. The highest prevalence of wasting (15.9%; 95% CI: 13.5, 18.8) was observed from hilly and mountainous highlands. The highest prevalence of child stunting (42.4%; 95% CI: 38.5, 46. 6) and underweight (22.9%; 95% CI: 19.7, 26.3)) were observed from the lowlands of Abay Valley. SaTScan spatial analysis indicated that sample clusters taken from the hilly and mountainous highlands were the most likely primary cluster for child wasting (LLR: 13.0, p &lt; 0.01) and underweight (LLR: 23.16, p &lt; 0.001). Also, primary cluster for child stunting was identified from lowlands of Abay Valley (LLR: 10.78, p&lt;0.05). After adjusting for both individual and community level determinant factors, 1.5% (p&lt;0.001) of the variance of food insecurity was attributable to the cluster level. Similarly, after adjusting for all potential determinant factors, 2.4% (p&lt;0.001) of the child weight for height Z score and 1.4% (p&lt;0.001) of the child height for age Z score variance were due to cluster level. From level one factors, in the final model, household head being male, marital status being in union, higher parental education, women's participation in household decision making, having additional income sources, better crop production in the survey year and application of chemical fertilizer have a positive influence in mitigating household food insecurity. From community level determinant factors, households being from hilly and mountainous highlands and lowlands of the Abay Valley were more severely household food insecure compared to midland plain areas. Households with better farmland size showed less severe household food insecurity in the study area. In the study, from level one factors, the number of under five children, antenatal (ANC) follow up, breast feeding initiation time, household dietary diversity, mother nutritional status, household food insecurity and diarrheal morbidity were associated with weight for height Z score. From level two factors, agroecosystem characteristics, proper household refuse disposal practice, agroecosystem characteristics and proper latrine utilization were significantly associated with child weight for height Z score. From level one factors, child age in months, child gender, the number of under-five children in the household, child immunization status, breastfeeding initiation time, mother nutritional status, child diarrheal morbidity, household level water treatment practice and household dietary diversity showed a statistical significant association with child height for age Z score. From level two factors, agroecosystem characteristics, proper household refuse disposal practice and proper latrine utilization were significantly associated with child height-for-age Z score. XVIII | P a g e Conclusions: - The prevalence of food insecurity and child undernutrition were public health concerns in the study area. Spatial variations of household food insecurity and child undernutrition were observed across the agroecosystems. Households from the lowlands of Abay Valley and hilly and mountainous highland areas were more vulnerable to food insecurity and child undernutrition compared to midland areas. The SaTScan cluster level spatial analysis identified statistical significant hotspot clusters for food insecurity, childhood stunting, underweight and wasting. The multilevel mixed effects analysis indicated that the heterogeneity of food insecurity, childhood stunting and wasting were observed after adjusting to potential individual and community level determinant factors. Both individual and community level factors played a significant role in determining food insecurity and child undernutrition (stunting and wasting). An agroecosystem characteristic was one of the community level factors affecting household food insecurity and child undernutrition. Recommendations: - The spatial variation of food insecurity and child undernutrition based on agroecosystem characteristics should be fully understood by program implementers and policy makers during planning, resource allocation and community mobilization in the study area. Water, sanitation and hygiene interventions are important in the study area. Further study on spatiotemporal variations of food insecurity and child undernutrition at different time is recommended. Also, food insecurity and child undernutrition intervention strategies and plans designed using aggregated or macro level evidence may not indicate the true picture of spatial distribution of the problem at lower government administrative units. So, program level planning may take into account agroecosystem based micro level variations to allocate resources. Policy and intervention strategies aiming at mitigating food insecurity and child undernutrition should address the effects of lower and community level determinant factors using the integration of individual/household level and geographical targeting.