This article has Open Peer Review reports available.
Risk factors associated with poor health outcomes for children under the age of 5 with moderate acute malnutrition in rural fagita lekoma district, Awi Zone, Amhara, Ethiopia, 2016
- W/amilak Adamu1,
- Dube Jara2Email author,
- Mulunesh Alemayehu2 and
- Sahai Burrowes3
https://doi.org/10.1186/s40795-017-0208-5
© The Author(s). 2017
Received: 20 June 2017
Accepted: 13 December 2017
Published: 22 December 2017
Abstract
Background
Left untreated, moderate acute malnutrition (MAM) in children can lead to severe acute malnutrition, stunting, developmental delays, and death. Despite recent progress the prevalence of malnutrition remains high throughout Ethiopia. The ability to make accurate prognoses and develop effective treatment strategies for children with MAM is currently limited and, as result, a significant proportion of children with MAM fail to recover even with treatment. We seek to address this limitation by assessing the risk factors for poor outcomes among children under the age of 5 with MAM in a rural area of Ethiopia’s Amhara Region. This region is considered relatively food secure and does not have food supplementation treatment programs.
Methods
We conducted a prospective cohort study of 404 randomly sampled children, 0–59 months old stratified by household food security status. We followed the study children for approximately 2 months, assessing their health status; and used bivariate and multivariate Cox-proportional hazard regression models to identify risk factors for poor health outcomes.
Results
Household food security was significantly associated with low recovery from MAM: 191 (60%) of children in food-insecure and 129 (40%) of children in food-secure households had poor health outcomes. The risk factors found to be significantly associated with poor health outcomes included the duration of exclusive breastfeeding (AHR 1.50, 95%CI: 1.05, 2.15), dietary diversity (AHR 1.74, 95%CI: 1.18, 2.54), and maternal mid-upper arm circumference (AHR=1.36, 95% CI: 1.04, 1.86). Children from pregnancies that were wanted but unplanned had 80% higher incidence of poor health outcomes than others, and children from pregnancies that were both unwanted and unplanned had more than double the incidence of poor health outcomes compared to their counterparts.
Conclusion
We found that without treatment, the majority of children from food insecure households and over a third of children from food secure households did not recover from MAM. Maternal factors particularly the mother’s ability to plan her pregnancy were the main determinants of recovery in this study. Together these findings support arguments for targeting of nutrition support programs to vulnerable households regardless of regional food security status, and for closely integrating robust family planning, and antenatal care services with nutrition interventions.
Keywords
Background
Worldwide, approximately 5% of children under the age of five are affected by moderate acute malnutrition (MAM) [1]. Children with MAM are at increased risk of death and are more likely to suffer delays in their physical and cognitive development than children who have not experienced malnutrition [2, 3]. Recurrent episodes of MAM in children can also lead to later childhood stunting. In turn, stunting can affect the nutritional status of subsequent generations, resulting in “intergenerational growth failure”—a cycle of poor nutrition that perpetuates itself across generations with irreversible effect [4–6]. Moderate wasting is often described as the most important risk factor for childhood illness and mortality globally, and it is directly or indirectly responsible for more than half of all deaths in children under 5 year of age [7, 8].
Worldwide, approximately 165 million children under 5 are stunted—56 million in Africa. Both moderate and acute malnutrition remain a significant and persistent public health problem in Ethiopia [6]. According to the 2016 Demographic and Health Survey, 38% of children under 5 years of age were stunted; 10% had acute malnutrition; and 24% having moderate acute malnutrition. In the Amhara Region, in which this study was conducted, almost half (46%) of children are stunted [9].
Poor health outcomes due to MAM are not inevitable. With early adequate nutritional intervention and the prevention of infectious diseases, children with MAM can catch up their linear growth [5]. Such intervention is especially crucial in the child’s first 1000 days of life, a critical period for child growth and cognitive development [10]. Action to address MAM during this window of opportunity, particularly during the complementary feeding period (between 6 to 24 months), is crucial for preventing stunting and later cognitive and developmental delays [10, 11]. However, there is still debate about the proper strategies for addressing MAM at the national-level in a cost-effective manner.
A 2016 study [12] notes that the current Ethiopian strategy for managing MAM nationally is to restrict supplementary feeding programs (SFPs) for treatment to districts (woredas) that are chronically food-insecure. In areas not considered chronically food-insecure, there are no public SFPs; instead, providers rely on existing infant and child health interventions such as vitamin A supplementation, de-worming, water treatment, improved sanitation, and nutrition counseling. Researchers have noted that while this policy is logical in terms of efficiency, it may be failing to adequately address the problem of widespread malnutrition, because aggregate, average food security at the woreda level is may mask severe food insecurity at the household level [7, 12, 13]. Household food security has been shown to be associated with developing MAM and a failure to recover from MAM [14, 15]. Children with MAM need food of sufficient energy and nutrient density in order to recover from MAM and access to such food may be limited in food-insecure households [16]. There is, therefore, concern that the current policy may be inadequate to meet this pressing health threat.
Changing national strategies to prevent and treat MAM requires a solid understanding of the factors that are related to poor health outcomes for children with MAM, particularly children not receiving treatment. Such information facilitates the development of comprehensive programs containing complementary services and allows policy makers to better assess the tradeoffs involved in not providing SFPs for children with MAM. Unfortunately, the factors related to failure to recover from MAM, particularly for children not receiving treatment, are poorly understood. There is relatively strong evidence that household food insecurity, unhealthy environmental conditions, maternal under-nutrition and inadequate care and feeding practices contribute to the development of MAM [10]. Household wealth, maternal fertility, vitamin A supplementation, good hygiene practices, safe water source, having nutritional counseling, and the child’s Mid-Upper Arm Circumference (MUAC) at enrollment, have been found to be negatively associated with recovery in some studies [12, 17]. In others, the child’s age, gender, initial level of malnutrition and breastfeeding status were the important factors [18]. Household food insecurity and maternal workload have been found to be drivers of health outcomes in some studies but not in others [12]. This study wants to contribute to a better understanding of the risk factors for failure of children to recover from MAM in Ethiopia.
Methods
Study Setting
The study was conducted from February 2, 2016 to April 4, 2016 (the post-harvest, dry season) in the Fagita Lekoma woreda. Fagita Lekoma is one of 12 woredas in the Awi Zone, which is located in the Amhara Regional State. It is a rural woreda (20 of its 22 kebeles are rural) located 450 kms from Ethiopia’s capital, Addis Ababa [11]. We selected Fagita Lekoma because there are no SFPs in the woreda. The woreda has 6 health centers, only one of which provides outpatient care for severe acute malnutrition (SAM). The estimated population for the woreda is 156,671; with 36,435 households, and 21,213 children under the age of five. The five kebeles in this study had a total population of 22,682 [19].
Study design and population
This community-based prospective cohort study was conducted among children with MAM aged 0–59 months. Children 59 months of age or younger with MAM that lived in the randomly sampled kebeles were eligible for recruitment. We excluded children older than 59 months; whose age was not known; without MAM; with no present mother or whose mother was unable to communicate with the study team; children who had health problems or disabilities that made it difficult to collect anthropometric measurements; and children with MAM who were receiving medical treatment.
Sample size and sampling techniques
Because food security has been shown to be an important factor for predicting poor health outcomes in children with MAM we selected it as an “exposure” variable for sample size calculation and for the stratification of our Kaplan-Meier survival plots [12]. Households were categorized as food-secure and food-insecure based on Household Food Insecurity Access Scale (HFIAS) results that were from previous study [12]. We calculated our sample size using the double population proportion formula. Our assumptions were as follows: 37.78% children with MAM in food-secure households would have poor health outcomes [12] for an adjusted hazard ratio (AHR) of 1.39 for poor health outcome among food-secure compared to food insecure households [12]. We assumed a 95% two-sided confidence interval (CI), a statistical power of 80%, and a one-to-one allocation ratio of food-secure to food-insecure. Based on these assumptions, using EPI INFO 7 [20], we calculated a sample size 384. Allowing for an additional 5% non-response rate, the total sample size was 404 (202 for food-secure households and 202 for food-insecure households).
We randomly selected 5 kebeles from Fagita Lekoma’s 20 rural kebeles (25%) using a simple random sample lottery method. We then visited all households in the selected kebeles and screened all children aged 0–59 months (n = 2995) for their nutritional status. We used the conventional definition of MAM: having a weight-for-height (WFH) below the WHO median child growth standards (the child growth with Z-scores between -3SD to -2SD).
All children were assessed for WFH using WHO Anthro version 3.2.2 software and those with MAM were identified and registered. At this time we also categorized households as food insecure and food secure. We found 414 children with MAM (202 from food-secure and 212 from food insecure households). We retained all 202 children from food-secure households. We randomly selected 202 children from the remaining 212 food-insecure households using a lottery method. When there was more than one child with MAM in a household, we selected one of them using lottery method. The selected children were enrolled in the study and followed for two months.
Study variables and measurement
Our outcome variable was whether, by the two-month follow up visit, a child had progressed to severe acute malnutrition (SAM); had not recovered from MAM, or had died. Children with any of these outcomes were categorized as having “poor health outcomes”.
We categorize children as having MAM, if at the second follow up visit, they had a weight-for-height/length (WFH/L) between -3 and - 2 Z-scores (-3SD to -2SD of the WHO median value), or WFH/L at 70–80% of the National Center for Health Statistics (NCHS), or had a MUAC measurement that was > = 11.5 cm <12.5 cm, without edema. Children whose MAM status did not change by the 2-month follow up period were categorized as not recovering. We categorized children as having SAM if, at the first or second follow-up visit, they had WFH/L below −3 SD of the WHO median value and/or (WFH/L) below 70% of the NCHS median value and/or MUAC <11.5 cm, with or without edema. Children were categorized as recovering if, at first and/or second follow up visit, they had WFH/L Z-scores > = -2SD of the WHO median value and/or WFH/L > =80% of the NCHS, and/or MUAC > = 12.5 cm) with no edema.
Data collection methods
We collected data using a cross-sectional, structured, interviewer-administered questionnaire containing closed-ended questions and by taking anthropometric measurements of children and their mothers during home visits.
Our study began with the development of a project survey and the recruitment of project staff. Our survey was developed from standard, validated, English-language instruments that were translated to into Amharic. We recruited 2 health officers to supervise data collection, and 10 health extension workers and 3 nurses to act as data collectors. All spoke Amharic, the local language. We then conducted one-day training on how to collect the data for the data collectors and supervisors and then pre-tested the questionnaire in a kebele that was adjacent to our study kebeles, with 20 households (5% of our sample size).
The study had three data collection points: we collected baseline survey and anthropometric data during community-based nutritional screening for all children 0–59 months of age in our 5 sampled kebeles. We used the HFIAS to measure food security for stratifying the sample [21]. This tool is the current standard for assessing household-level food security and has been validated for use in Ethiopia [22]. Households that were enrolled in the study were visited once monthly for 2 months, during which mothers were asked follow up survey questions and anthropometric measurements of the study children were taken.
The survey contained questions on socio-economic factors, demographic risk factors, child characteristics, child-care practices, maternal characteristics, and environmental risk factors. We recorded the child’s vaccination status by reviewing immunization cards when these were available, or by using the mother’s recall. We checked bacille Calmette-Guerin vaccination by observing whether there was scar on the child’s arm.
We used procedures stipulated by the WHO to take anthropometric measurements [23]. Before measuring children we established their age, using a local event to establish the child’s birth period. Mothers were asked whether the child was born before or after certain major events until a fairly accurate age was pinpointed. If we were not able to determine the child’s age accurately, the next child in the household was recruited. We measured body length of children age up to 23 months (or those who were older but too ill to stand) in the recumbent position, without shoes, reading the length to the nearest 0.1 cm or 1 mm using a horizontal wooden length measuring board/sliding board. We measured MUAC for both the study children and their mothers. MUAC was measured on left mid upper arm half way between the olecranon process and acromion process using a non-stretchable strap, to the nearest 1 mm.
Quality control measures
We checked the calibration of the measurement scale by weighing a 2-kg stone after each child measurement and after moving the scale from one household to another. Then the scale indicators were checked against a zero reading before and after weighing every child and mother. Only one observer was used for each subject. Mothers and children were required to wear only light clothing in order not to skew the weight results. The project principal investigator reviewed collected data on a daily basis, and returned records with possible errors to the data collectors for correction.
Data processing and analysis
The collected data were checked for completeness, consistency and entered using EPI-data software; then the data were exported to SPSS version 20 for analysis [24]. Descriptive analysis such as Kaplan-Meier survival curves and log-rank test statistics were used to describe important variables of the study and compare the outcome variables. A Cox-regression model was fitted to identify risk factors for poor health outcomes of MAM. All predictors that were associated with the outcome variable in bivariate analysis at p-values of 0.20 or lower were included in our multivariate Cox-regression models. Crude and adjusted hazard risks with their corresponding 95% confidence intervals were computed. Variables with p-values <0.05 were considered statistically significant risk factors in this study.
Results
A total of 202 children with MAM in food-secure and 202 in food-insecure households were enrolled in the study with no loss to follow-up, for an overall response rate of 100%.
Socio-demographic and economic characteristics
Socio-demographic and economic household characteristics in Fagita District, Awi Zone, Amhara, Ethiopia, 2016
Variables | Description | Moderate Acute Malnutrition | |||
|---|---|---|---|---|---|
Food-Secure Households | Food-Insecure Households | ||||
Sex HH head | Female | 20 | 9.90% | 22 | 10.89% |
Male | 182 | 90.0% | 180 | 89.1% | |
Age of male HH head | 15-39 | 27 | 13.36% | 27 | 13.36% |
30-39 | 72 | 35.64% | 64 | 31.68% | |
40-49 | 75 | 37.12% | 82 | 40.59% | |
50andabove | 8 | 3.90% | 7 | 3.46% | |
Marital Status of HH Head | Married | 182 | 90.09% | 180 | 89.1% |
Divorced | 12 | 5.94% | 16 | 7.92% | |
Widowed | 8 | 3.96% | 6 | 2.97% | |
No. of person in household | <5 | 72 | 35.64% | 64 | 31.68% |
5 and above | 130 | 64.35% | 138 | 68.31% | |
Father’s Educational Status | Can't Read &write | 91 | 45.04% | 80 | 39.6% |
Can Read &Write and above | 91 | 45.04% | 100 | 49.5% | |
Maternal Educational Status | Can't read &write | 137 | 67.8% | 121 | 59.9% |
Can Read &Write and above | 65 | 32.17% | 81 | 40.09% | |
Maternal Occupational Status | Farmer | 200 | 99% | 201 | 99.5% |
Who Decides Money Use | Mainly spouse | 20 | 9.9% | 24 | 11.880% |
Mainly husband | 94 | 46.53% | 98 | 48.53% | |
Both | 66 | 32.67% | 56 | 27.72% | |
Only husbanded | 22 | 10.89% | 24 | 11.88% | |
Monthly Income | <750 | 192 | 95.05% | 195 | 96.50% |
750+ | 10 | 4.95% | 7 | 3.50% | |
Child characteristics
Child characteristics in Rural Fagita District, Awi Zone, Amhara, Ethiopia, 2016
Variables | Description | Moderate acute malnutrition | |||
|---|---|---|---|---|---|
Food-Insecure Households | Food-Insecure Households | ||||
Child’s sex | Female | 101 | 50.0% | 111 | 54.95% |
Male | 101 | 50.0% | 91 | 45.04% | |
Child’s age | 0-11 | 29 | 14.35% | 31 | 15.34% |
12-23 | 99 | 49.00% | 102 | 50.45% | |
24-35 | 50 | 24.75% | 44 | 21.78% | |
36-47 | 18 | 8.90% | 18 | 8.90% | |
48-59 | 6 | 2.90% | 7 | 3.40% | |
Birth interval | 0-23 months | 95 | 47.02% | 85 | 42.07% |
24+ months | 107 | 52.97% | 117 | 57.92% | |
Gestational age | <9month | 28 | 13.86% | 46 | 22.77% |
9+ month | 174 | 86.13% | 156 | 77.22% | |
Illness in the last 2 weeks | 149 | 73.76% | 147 | 72.77% | |
53 | 26.23% | 55 | 27.22% | ||
Frequency of health problems | Fever | 9 | 16.98% | 5 | 9.00% |
Cough | 6 | 11.32% | 5 | 9.00% | |
Fever & cough | 13 | 24.52% | 25 | 45.45% | |
Vomiting &diarrhea | 25 | 47.16% | 20 | 36.36% | |
Child care characteristics
We found high rates of exclusive breastfeeding in children from food-insecure households (83.47%) but more modest rates in among households with higher food security (57.14%). Roughly 80% had been given breast milk immediately after birth. More than half of the children (55.44% and 59.9% in food-secure and insecure households respectively) were being breastfed at the time of data collection.
Child caring characteristics in Rural Fagita District, Awi Zone, Amhara, Ethiopia, 2016
Variables | Description | Moderate Acute Malnutrition | |||
|---|---|---|---|---|---|
Food-Secure Households | Food-Insecure Households | ||||
Breast fed | No | 90 | 44.55% | 81 | 40.09% |
Yes | 112 | 55.44% | 121 | 59.9% | |
Time to initiate breast feeding | Immediately | 92 | 82.14% | 97 | 80.16% |
>=1Hr of Delivery | 20 | 17.85% | 24 | 19.83% | |
Frequency of breast feed in 24hrs | <8 time/day | 21 | 18.75% | 23 | 19.00% |
8-12 time/day & above | 91 | 81.25% | 98 | 80.99% | |
Exclusively breast feed | < 6 month | 48 | 42.85% | 20 | 16.52% |
>=6 month | 64 | 57.14 | 101 | 83.47% | |
Pre-lactation food/fluid | No | 174 | 86.13% | 167 | 82.67% |
Yes | 28 | 13.86% | 35 | 17.32% | |
Material used to feed the child | Cup | 27 | 96.42% | 30 | 85.74% |
Bottle | 1 | 3.57% | 5 | 14.28% | |
Who is in charge of the baby’s Feeding | Mother | 199 | 98.51% | 198 | 98.01% |
Sister | 3 | 1.48% | 3 | 1.48% | |
Sickness in the last 2weeks | No | 191 | 94.55% | 190 | 94.05% |
Yes | 11 | 5.44% | 12 | 5.94% | |
Breast feeding until 1 year(6-23 month) | No | 1 | 0.78% | 1 | 0.78% |
Yes | 126 | 99.2% | 127 | 99.21% | |
Time to start complementary feeding(6-23month) | 1-5months | 24 | 19.04% | 29 | 22.83% |
6months | 89 | 68.99% | 84 | 66.14% | |
7-12months | 14 | 11.11% | 14 | 11.02% | |
Took soft thick (semi solid) porridge (6-8 months) | No | 42 | 10.4% | 51 | 12.6% |
Yes | 8 | 2.0% | 9 | 2.2% | |
Frequency the child take semi-solid porridge(6-8 month) | 1-2 time/day | 3 | 37.5% | 4 | 44.44% |
2-3 time/day | 4 | 50.00% | 4 | 44.44% | |
3-4 time/day | 1 | 12.5% | 1 | 11.11% | |
Took soft thick (semi solid) porridge (9-11 months) | No | 41 | 75.92% | 52 | 81.25% |
Yes | 13 | 24.07% | 12 | 18.75% | |
Family food consumption | No | 39 | 34.51% | 39 | 33.33% |
Yes | 74 | 65.48% | 78 | 66.66% | |
Frequency of family food | 1-2 time/day | 8 | 10.81% | 4 | 51.28% |
2-3 time/day | 64 | 86.48% | 71 | 91% | |
3-4 time/day | 2 | 2.70% | 3 | 3.84% | |
The number of MDD intake | Legumes & Nut | 4 | 3.10% | 6 | 4.68% |
Diary Products | 79 | 62.20% | 86 | 67.18% | |
Grain, rut, tuber, diary product, Legume & Nuts | 38 | 29.92% | 26 | 20.31% | |
<4 food groups | 111 | 88.09% | 101 | 79.52% | |
4+ food groups | 15 | 11.91% | 31 | 20.48% | |
MDD in 24 hours stop breast milk | No | 113 | 88.97% | 118 | 92.18% |
Yes | 14 | 11.02% | 10 | 7.81% | |
Immunized | No | 0 | 0% | 1 | 0.79% |
Yes | 127 | 100% | 127 | 99.21% | |
Vitamin A supplementation | No | 26 | 20.47% | 26 | 20.31% |
Yes | 101 | 79.52% | 102 | 79.69% | |
Vaccines received | Only Penta1 and 2 K | 3 | 2.3% | 4 | 3.12% |
Fully | 107 | 84.25% | 110 | 85.93% | |
BCG, penta1-penta3 | 12 | 11.81% | 6 | 4.68% | |
Not Sure | 5 | 3.90% | 4 | 3.12% | |
Maternal characteristics
Maternal characteristics in Rural Fagita District, Awi Zone, Amhara, Ethiopia, 2016
Variables | Description | Moderate Acute Malnutrition | |||
|---|---|---|---|---|---|
Food-Secure Households | Food-Insecure Households | ||||
Mother’s age | 15-29 | 50 | 24.75% | 45 | 22.27% |
30-39 | 120 | 59.40% | 120 | 59.40% | |
40-49 | 32 | 15.84% | 37 | 18.31% | |
BMIin kg/m2 | <18.5kg/m2(CED) | 60 | 29.70% | 87 | 43.06% |
18.5+kg/m2(NM) | 142 | 70.29% | 115 | 56.93% | |
MUAC in centimeter | <23cm | 99 | 49.00% | 141 | 69.8% |
>=23cm | 103 | 51.00% | 61 | 30.2% | |
Gravidity | 1 | 28 | 13.86% | 25 | 12.37% |
2-5 | 136 | 67.32% | 138 | 68.31% | |
>5 | 38 | 18.81% | 39 | 19.30% | |
Parity | 1 | 28 | 13.86% | 25 | 12.37% |
2-5 | 137 | 67.82% | 139 | 68.81% | |
>5 | 37 | 18.31% | 38 | 18.81% | |
Extra meal during pregnancy | No | 129 | 63.86% | 138 | 68.31% |
Yes | 73 | 36.13% | 64 | 31.68% | |
Number of extra meals during pregnancy | <2 time/day | 44 | 60.27% | 41 | 64.06% |
>= 2 time/day | 29 | 39.72% | 23 | 35.93% | |
Extra meals during lactation | No | 137 | 67.82% | 145 | 71.78% |
Yes | 65 | 32.17% | 57 | 28.21% | |
Number of extra meals during pregnancy | <2 time/day | 45 | 69.23% | 35 | 61.4% |
>= 2 time/day | 20 | 30.76% | 22 | 38.59% | |
Pregnancy type | Wanted & planned | 148 | 73.26% | 113 | 55.94% |
Wanted & unplanned | 33 | 16.33% | 61 | 30.19% | |
Unwanted & unplanned | 21 | 10.39% | 28 | 13.86% | |
Health Outcomes
Kaplan-meier hazard estimation of moderate acute malnutrition children by duration of exclusive breastfeeding, in Fagita District, Awi Zone, Amhara, Ethiopia, 2016
Median recovery times
Median recovery time for children with moderate acute malnutrition in Rural Fagita District, Awi Zone, Amhara, Ethiopia, 2016
Food security Status | Mean | Std. Error | 95% CI | Median | Std. Error | 95% CI |
|---|---|---|---|---|---|---|
Food secure | 62.29 | 0.097 | (62.10, 62.48) | 62.0 | 0.178 | (61.65, 62.35) |
Food insecure | 61.67 | 0.432 | (60.82, 62.51) | 63.0 | 0.111 | (62.78, 63.22) |
Overall | 61.98 | 0.225 | (61.54, 62.42) | 63.0 | 0.087 | (62.83, 63.17) |
Median recovery time for children with moderate acute malnutrition by Maternal MUAC in Rural Fagita District, Awi Zone, Amhara, Ethiopia, 2016
MUAC in centimeter | Food security Status | Mean | Std. Error | 95% CI | Median | Std. Error | 95% CI |
|---|---|---|---|---|---|---|---|
<23cm | Food secure | 62.78 | 0.114 | (62.56, 63.00) | 63.0 | 0.130 | (62.75, 63.26) |
Food insecure | 61.24 | 0.661 | (59.95, 62.54) | 63.0 | 0.119 | (62.77, 63.23) | |
Overall | 61.90 | 0.384 | (61.15, 62.65) | 63.0 | 0.088 | (62.83, 63.17) | |
>= 23cm | Food secure | 61.78 | 0.141 | (61.50, 62.06) | 61.0 | 0.181 | (60.65, 61.35) |
Food insecure | 62.45 | 0.167 | (62.12, 62.77) | 63.0 | 0.285 | (62.44, 63.56) | |
Overall | 62.08 | 0.111 | (61.86, 62.30) | 62.0 | 0.194 | (61.62, 62.38) |
Risk factors for poor health outcomes due to MAM
Risk factors for poor health outcomes of moderate acute malnutrition in multivariate cox regression in Rural Fagita District, Awi Zone, Amhara, Ethiopia, 2016
Variable | Moderate Acute Malnutrition | CHR at 95% CI | AHR at 95% CI | p-Value | |
|---|---|---|---|---|---|
Food-Secure Households | Food-Insecure Households | ||||
Exclusive breast feeding | |||||
<6 month | 48 (42.85%) | 20 (16.52%) | 1.89 (1.36,2.62) | 1.50 (1.05, 2.15) | 0.027 |
>=6 month | 64 (57.14%) | 101 (83.47) | 1 | 1 | |
Dietary diversity | |||||
<4 food groups | 111 (88.09%) | 101 (75.59%) | 1.67 (1.19,2.37) | 1.74 (1.184,2.54) | 0.005 |
>=4 food groups | 15 (11.90%) | 31 (24.40%) | 1 | 1 | |
Maternal MUAC | |||||
<23cm | 99(49.00%) | 141 (69.8%) | 1.45 (1.14, 1.82) | 1.36 (1.05,1.86) | 0.044 |
>=23cm | 103 (51%) | 61(30.19%) | 1 | 1 | |
Pregnancy type | |||||
Wanted & planned | 148 (73.26%) | 11 3(55.94%) | 1 | 1 | |
Wanted & unplanned | 33 (16.33%) | 61 (30.19%) | 1.49 (1.16,1.92) | 1.80 (1.27,2.26) | 0.001 |
Unwanted & unplanned | 21 (10.39%) | 28 (13.86%) | 1.66 (1.21,2.28) | 2.19 (1.44,3.31) | 0.001 |
The risk of having poor health outcomes among children who had been exclusively breastfed for less than 6 months were 50% times higher than among children who had exclusively breastfed for 6 months or more (AHR = 1.50, 95% CI: 1.05, 2.15). Children with MAM had 74% higher risk of having poor health outcomes if they had eaten less than 4 food groups in the last 24 h compared with children whose diet was more diverse (AHR = 1.74, 95% CI: 1.184, 2.54). Maternal nutritional status was significantly associated with poor health outcomes. Children whose mothers had MUAC measurements less than 23 cm had 36% higher risk of having poor health outcomes than children whose mothers had measurement that were > = 23 cm (AHR = 1.36, 95% CI: 1.04,1.86). We also found a surprisingly strong association between whether a pregnancy was planned and/or wanted and the risk of poor health outcomes. Poor health outcomes were 80% higher among children born of unplanned pregnancies that were wanted compared children from wanted and planned pregnancies (AHR = 1.80, 95% CI: 1.27, 2.26). And the risk of poor health outcomes was 119% higher among children born of pregnancies that were both unwanted and unplanned (AHR = 2.19, 95% CI: 1.44, 3.31).
Discussion
This study set out to explore the risk factors associated with poor health outcomes in children with MAM in a food-secure region of Ethiopia with little access to supplemental feeding programs. We found that without treatment, the vast majority of children (79%) did not recover from MAM and that the proportion of children who failed to recover was significant even in food-secure households (approximately 40%). This high level of non-recovery is concerning particularly because most of the children in our study were in the critical, first 1000 days of life. Studies have found that children in this vulnerable age range (0–23 months) are relatively more prone to moderate wasting, which is often exacerbated by bouts of diarrhea and respiratory illness, deteriorating into more severe illness [10].
Two of the risk factors found in our study were consistent with those found previously, namely, maternal nutritional status and the diversity of the child’s diet [12]. However, several of our findings were unusual. Many of the factors found to be associated with the development of, or the recovery from, moderate acute malnutrition in other studies were not found to be significant factors in risk of non-recovery in our study. These include the child’s age, household wealth [25], maternal education [11], household income [11], drinking water source, sanitation (e.g., hand washing practices, appropriate waste disposal and latrine availability), household size [12], having received vitamin A supplementation or de-worming interventions [26] . This discrepancy may be due to the fact that our study took place during the post-harvest season when relative abundance of food might have mitigated or washed out the impact of other factors. The positive impact of high rates of exclusive breastfeeding that we observed in this study may have also played a similar role.
However, the rates of poor health outcomes for children with MAM observed in this study were quite high, and indeed much higher than that observed in previous Ethiopian research. For example, a similar study, recently conducted in Jimma found that roughly 62% of children with MAM either deteriorated or remained with MAM compared to our 79% rate [12]. Their lower rates may be due to differences between our sample in the age ranges of children (our sample was considerably younger than these previous studies) and the fact that the follow up period in the Jimma study was longer than ours, which gave children a more time to recover. There may have also been differences in our samples the duration of exclusive breastfeeding and the proportion of pregnancies that were wanted and planned. .
Indeed, the strength of association between poor health outcomes and whether a pregnancy was planned and/or wanted was one of the surprising findings of this study. While associations between fertility and overall rates of childhood malnutrition have been observed in numerous studies [27, 28] there has been less evidence of a relationship between the ability to plan pregnancy and women’s ability to effectively care for children with MAM.
Conclusions and Recommendations
This study finds that, without intervention, the majority of children with MAM fail to recover. After a 2-month period, most either remain moderately malnourished or their condition deteriorates. Those from food-insecure households were more likely to have poor health outcomes than those from food secure households. These poor health outcomes are negatively associated with the duration of exclusive breastfeeding, minimum dietary diversity, maternal MUAC and whether pregnancies were planned and/or wanted. Based on the finding of the study the following recommendations were forwarded.
The high level of non-recovery found in our study suggests the need for ongoing, intensive, community-based nutrition education programs and nutritional surveillance to tackle the problem. It also suggests that children with MAM should be managed by targeted supplemental feeding programs, regardless of the food security status of the woreda. This would require the additional investment of scare resources. It could also be an important preventative measure that reduces the future outlay of resources for more expensive interventions to treat severe acute malnutrition and its co-morbidities. Our findings also suggest that it will be crucial to link these additional nutritional interventions for children with programs that provide intensive, high quality, prenatal and antenatal care for women. Our findings suggest that these programs should provide maternal nutritional support, counseling support for exclusive breastfeeding and diversifying childhood diets, and, most importantly, family planning counseling and provision of contraception, (particularly long-acting contraception), and safe abortion services when needed. This, in turn will require closer collaboration between stakeholders in reproductive health services, and those working in infant and young child feeding programs.
In order to inform the development of these programs, further study on the management of MAM should be conducted to explore risk factors not measured in the present study and to in particular, to address two of the main limitations on this study, its limited geographic scope, and its short time frame which did not include the pre-harvest and harvest seasons.
Abbreviations
- AHR:
-
Adjusted Hazard Rate
- BMI:
-
Body Mass Index
- CI:
-
Confidence interval
- CMAM:
-
Comprehensive Moderate Acute Malnutrition
- EBF:
-
Exclusive breastfeeding
- HEWs:
-
Health Extension Workers
- HFIAS:
-
Household Food Insecurity Access Scale
- MAM:
-
Moderate Acute Malnutrition
- MDD:
-
Minimum Dietary Diversity
- MUAC:
-
Mid Upper-arm Circumference
- NCHS:
-
National Center for Health Statistics
- SAM:
-
Severe acute malnutrition
- SD:
-
Standard Deviation
- SPSS:
-
Statistical Package for Social Sciences
- WFH:
-
Weight for height
- WFL:
-
Weight for length
- WHO:
-
World Health Organization
Declarations
Acknowledgments
The authors would like to thank the Debre Markos University, College of Medicine and Health Sciences for reviewing this paper. We also thank the Dangila Primary Hospital for their support in providing materials used in the project; the Fagita District for their help in printing materials; and the Fagita Health Center Director and staff for their support in survey development and data collection. The author’s deep gratitude goes to the HEWs, participants, data collectors, and supervisors for their careful work in gathering information and collecting data for the study.
Funding
This was a self-funded research project. There were no external organizations that funded this research.
Availability of data and materials
The datasets analyzed during the current study are available from the corresponding author upon reasonable request.
Authors’ contributions
WA conceived and designed the study, performed analysis, and interpreted the data. DJ and MA assisted with the design, conception, analysis and interpretation of data. DJ also prepared and drafted the manuscript. SB assisted in drafting the manuscript. All authors read and approved the final manuscript.
Ethics approval and consent to participate
Ethical clearance was obtained from Ethical Review Committee of Debre Markos University’s College of Medicine and Health Sciences. Letters of permission were also obtained from the Amhara Regional Health Bureau, the Awi Zonal Health Department, the Health Office of Fagita Lekoma District and its Kebele Administration Units. Verbal informed ascent was obtained from the parents of the child study subjects. The objectives of the study were explained to the parents who were assured that their names and the names of their children would be kept private. Privacy and confidentiality of collected information was ensured at all level. During the community-based nutritional screening phase of the study, we referred 5 children with severe acute malnutrition and 8 sick children referred to nearest health facilities. Health and nutritional education was given to all parents in the study.
Consent for publication
This manuscript does not report personal data such individual details, images or videos; therefore, consent for publication is not necessary.
Competing interests
The authors declare that they have no competing interests.
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Authors’ Affiliations
References
- Black RE, Victora CG, Walker SP, Bhutta ZA, Christian P, de Onis M, et al. Maternal and child undernutrition and overweight in low-income and middle-income countries. Lancet Lond Engl. 2013;382(9890):427–51.View ArticleGoogle Scholar
- Olofin I, McDonald CM, Ezzati M, Flaxman S, Black RE, Fawzi WW, et al. Associations of suboptimal growth with all-cause and cause-specific mortality in children under five years: a pooled analysis of ten prospective studies. PLoS One. 2013;8(5):e64636.View ArticlePubMedPubMed CentralGoogle Scholar
- Nassar MF, Shaaban SY, Nassar JF, Younis NT, Abdel-Mobdy AE. Language skills and intelligence quotient of protein energy malnutrition survivors. J Trop Pediatr. 2012;58(3):226–30.View ArticlePubMedGoogle Scholar
- Ruel MT, Alderman H. Nutrition-sensitive interventions and programmes: how can they help to accelerate progress in improving maternal and child nutrition? Lancet. 2013;382(9891):536–51.View ArticlePubMedGoogle Scholar
- Richard SA, Black RE, Gilman RH, Guerrant RL, Kang G, Lanata CF, et al. Wasting is associated with stunting in early childhood. J Nutr. 2012;142(7):1291–6.View ArticlePubMedPubMed CentralGoogle Scholar
- WHO, UNICEF, The World Bank: Joint child malnutrition estimates - Levels and trends [Internet]. [cited 2017 Aug 29]. Accessed http://www.who.int/nutgrowthdb/estimates/en/
- Rayhan MI, Khan MSH. Factors causing malnutrition among under five children in Bangladesh. Pak J Nutr. 2006;5(6):558–62.View ArticleGoogle Scholar
- Semba RD. Nutrition and Development: A Historical Perspective. In: Nutrition and Health in Developing Countries [Internet]. Humana Press; 2008 [cited 2017 Aug 31]. p. 1–31. (Nutrition and Health Series). Accessed: https://link.springer.com/chapter/10.1007/978-1-59745-464-3_1
- Central Statistical Agency-Ethiopia, ICF. Ethiopia Demographic and Health Sruvey 2016. Addis Ababa: CSA and ICF; 2017. [cited 2017 Aug 29]. Accessed: http://dhsprogram.com/publications/publication-FR328-DHS-Final-Reports.cfm Google Scholar
- Mucha N. Preventing Moderate Acute Malnutrition (MAM) through nutrition-sensitive interventions [Internet]. CMAM; 2014 [cited 2017 Aug 31]. (CMAM Forum Technical Brief). Accessed: http://files.ennonline.net/attachments/2291/Nutrition-Sensitive-MAM-Prevention-CMAM-Forum-Dec-2014.pdf
- Dewey KG, Mayers DR. Early child growth: how do nutrition and infection interact? Matern Child Nutr. 2011;7(Suppl 3):129–42.View ArticlePubMedGoogle Scholar
- James P, Sadler K, Wondafrash M, Argaw A, Luo H, Geleta B, et al. Children with moderate acute malnutrition with no access to supplementary feeding Programmes experience high rates of deterioration and no improvement: results from a prospective cohort study in rural Ethiopia. PLoS One. 2016;11(4):e0153530.View ArticlePubMedPubMed CentralGoogle Scholar
- Teshome B, Kogi-Makau W, Getahun Z, Taye G. Magnitude and determinants of stunting in children underfive years of age in food surplus region of Ethiopia: The case of West Gojam Zone. Ethiop J Health Dev. 2009;23:–2. [cited 2017 Aug 29] Available from: https://www.ajol.info/index.php/ejhd/article/view/53223
- Mutisya M, Kandala N, Ngware MW, Kabiru CW. Household food (in)security and nutritional status of urban poor children aged 6 to 23 months in Kenya. BMC Public Health. 2015;15:1052.View ArticlePubMedPubMed CentralGoogle Scholar
- Psaki S, Bhutta ZA, Ahmed T, Ahmed S, Bessong P, Islam M, et al. Household food access and child malnutrition: results from the eight-country MAL-ED study. Popul Health Metr. 2012;10:24.View ArticlePubMedPubMed CentralGoogle Scholar
- Golden MH. Proposed Recommended Nutrient Densities for Moderately Malnourished Children. Food Nutr Bull. 2009;30(3_suppl3):S267–342.View ArticlePubMedGoogle Scholar
- Larrea C, Kawachi I. Does economic inequality affect child malnutrition? The case of Ecuador. Soc Sci Med. 2005;60(1):165–78.View ArticlePubMedGoogle Scholar
- Trehan I, Banerjee S, Murray E, Ryan KN, Thakwalakwa C, Maleta KM, et al. Extending supplementary feeding for children under five with moderate acute malnutrition leads to lower relapse rates. J Pediatr Gastroenterol Nutr. 2015;60(4):544–9.View ArticlePubMedPubMed CentralGoogle Scholar
- Fagita Lekoma District Health Office. Annual report of Fagita Lekoma District health office. Addis Kidam: Fagita Lekoma District health Office; 2013.Google Scholar
- Dean A, Arner T, Sunki G, Friedman R, Lantinga M, Sangam S, et al. Epi Info™, a database and statistics program for public health professionals: CDC, Atlanta; 2011. [cited 2017 Aug 31]. Available from: https://wwwn.cdc.gov/epiinfo/user-guide/getting-started/Acknowledgements.html
- Swindale A, Bilinsky P. Development of a universally applicable household food insecurity measurement tool: process, current status, and outstanding issues. J Nutr. 2006;136(5):1449S–52S.PubMedGoogle Scholar
- Gebreyesus SH, Lunde T, Mariam DH, Woldehanna T, Lindtjørn B. Is the adapted household food insecurity access scale (HFIAS) developed internationally to measure food insecurity valid in urban and rural households of Ethiopia? BMC Nutr. 2015;1:2.View ArticleGoogle Scholar
- WHO Multicentre Gwrowth. Reference study group. WHO child growth standards based on length/height, weight and age. Acta Paediatr Suppl. 2006;450:76–85.Google Scholar
- IBM Corp. IBM SPSS statistics for windows, version 20.0. IBM Corp: Armonk; 2011.Google Scholar
- Eshete H, Abebe Y, Loha E, Gebru T, Tesheme T. Nutritional status and effect of maternal employment among children aged 6–59 months in Wolayta Sodo town, southern Ethiopia: a cross-sectional study. Ethiop J Health Sci. 2017;27(2):155–62.View ArticlePubMedPubMed CentralGoogle Scholar
- FAO, IFAD, WFP. The state of food insecurity in the world 2013. Rome: FAO; 2013. [cited 2017 Aug 29]. Accessed: http://www.fao.org/docrep/018/i3434e/i3434e00.htm Google Scholar
- Asfaw M, Wondaferash M, Taha M, Dube L. Prevalence of undernutrition and associated factors among children aged between six to fifty nine months in Bule Hora district, South Ethiopia. BMC Public Health. 2015;31:15. [cited 2017 Aug 26]Accessed: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4314803/ Google Scholar
- Lalou R, Mbacke C. The micro-consequences of high fertility on child malnutrition in Mali. In: Fertility, family size, and structure: consequences for families and children, vol. 232. New York: Population Council; 1993. p. 193. (Proceedings of a Population Council Seminar). Accessed: https://www.popline.org/node/336714.Google Scholar
