Prevalence of stunting and its associated factors among children 6-59 months of age in Libo-Kemekem district, Northwest Ethiopia; A community based cross sectional study
Prevalence of stunting and its associated factors among children 6-59 months of age in Libo-Kemekem district, Northwest Ethiopia; A community based cross sectional study
Selamawit Bekele Geberselassie 0 1 2
Solomon Mekonnen Abebe 0 2
Yayehirad Alemu Melsew 0 2
Shadrack Mulinge Mutuku 0 2
Molla Mesele Wassie 0 2
0 Abbreviations: AOR , Adjusted Odds Ratio; ARI, Acute respiratory infection; CBN, Community
1 Program Development Division, World Vision Ethiopia , Addis Abeba , Ethiopia , 2 Department of Human Nutrition, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia, 3 Department of Epidemiology and Biostatistics, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia, 4 Adelaide Medical School, Faculty of Health and Medical Sciences, University of Adelaide , Adelaide , Australia
2 Editor: Michelle Louise Gatton, Quensland University of Technology , AUSTRALIA
Children in developing countries are highly vulnerable to impaired physical growth because of poor dietary intake, lack of appropriate care, and repeated infections. This study aimed at assessing the prevalence of stunting and associated factors among children 6±59 months of age in Libo-kemekem district, northwest Ethiopia.
Data Availability Statement: All data underlying
the study are within the paper and its Supporting
Funding: The thesis is supported by University of
Competing interests: The authors have declared
that no competing interests exist.
A community based cross sectional study was conducted in Libo-Kemekem from October
15 to December 15, 2015. The multistage sampling technique was employed to select 1,320
children aged 6-59months. Data were collected by trained community health extension
workers under regular supervision. Data were entered into EPI-Info version 3.5.1, and
height for age was converted to Z-score with ENA-SMART software. Data were then
exported to SPSS version 20 for descriptive and binary logistic regression analysees. The
significance of associations was determined at p<0.05.
Out of 1287 children included in the analysis, 49.4% (95% CI: 46.7%±52.3%) were found to
be stunted. In the multivariate analysis, increased child age [AOR = 6.31, 95%CI: (3.65,
10.91)], family size of six and above [AOR = 1.77, 95%CI: (1.35, 2.32)] were positively
associated with stunting, while, fathers with secondary school education [AOR = 0.50, 95%CI:
(0.30, 0.81)], farmers as household heads [AOR = 0.56, 95%CI: (0.38, 0.84)] and
selfemployed parents as household head [AOR = 0.45, 95% CI: (0.28, 0.72)] were found to be
Based Nutrition; CI, Confidence Interval; CSA,
Central Statistics Agency; COR, Crude Odds Ratio;
ENA, Emergency Nutrition Assessment; EDHS,
Ethiopian Demographic Health Data; SD, Standard
deviation; SMART, Standardize Monitoring and
assessment of Relief and Transition; SPSS,
Statistical Package for Social Science; WHO, World
The prevalence of stunting was high in the study area. We found that stunting was
significantly correlated with child age, occupational status of household head, family size, and
fathers' education. Therefore, intervention focusing on supporting housewives, family
planning, and education on child feeding and nutrition should be implemented.
Stunting is defined as a height that is more than two standard deviations below the World
Health Organization (WHO) child growth standard median [1, 2]. Stunting is considered as a
severe public health problem in the community when its prevalence in children is greater than
40% . It is a largely irreversible outcome of inadequate nutrition and repeated bouts of
infection during the first 1000 days of the child's life [
]. It has long term effects on
individuals and societies, including diminished cognitive and physical development, reduced
productive capacity, and poor health, and increased risk of degenerative diseases such as diabetes [[
]. Furthermore, stunted children experienced rapid weight gain after 2 years have an
increased risk of becoming overweight or obese later in life [
Globally 161 million children under five were stunted in 2013 [
]. In 2015, Africa has the
highest prevalence of stunting at 37.6%, followed by Asia at 22.9% [
] According to the
Ethiopian mini Demographic and Health Survey (EDHS) report 2014, stunting among children
under five years of age is at 40%. In the Amhara National Regional State of Ethiopia stunting,
wasting, and underweight is reported to be 40%, 10% and 33%, respectively [
Stunting can be caused by various factors such as parental, socio-demographic, and
economic status, as well as cultural practices and environmental and other health related variables
]. For instance, poverty, low parental education, lack of sanitation, low food intake, poor
feeding practices, inadequate breastfeeding, repeated infections, family size and birth interval
are regarded as key determinants of stunting [9±11]. Another study reported that family
socioeconomic status was the most important factor associated with stunting [
]. Similarly, other
studies are in agreement that stunting is influenced by child age [
], age of the mother, child
sex, family size, wealth index [
], maternal/paternal education, marital status of mother, and
number of livestock of the family [10, 14±19]. Moreover, availability and utilization of health
services and the care provided to the child were found to be other determinants of stunting
The Ethiopian government recognizes stunting as a major public health problem and
obstacle to its economic goals. Since stunting is greatly dependent on the local geo-cultural factors
such as tradition and community livelihood, investigating its prevalence and causative factors
within this context is important to prioritize development interventions to mitigate the
problem. Therefore, the aim of this study was to determine the magnitude of stunting and identify
its determinants among children aged less than five years in Libo-kemkem district, northwest
Study design and setting
A community based cross sectional study was conducted in Libo-Kemkem district from
October 15 to December 15, 2015, to determine the level of stunting among children 6±59 months
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of age. The district has an area of 1,560 km2 and is located at 11Ê57'46.6'-12Ê25'32.6N latitude
and 37Ê34'48.9±38Ê3'30.9º E longitude. It comprises 34 villages of which 5 are urban. The
district is located on black cotton clay soil and flat plain with relatively high temperature and high
rainfall, with a mean of 1173mm rain per annum. Agricultural activities are restricted to a
single rain season (from June to September). Maize, barley and millet are the main food crops,
while rice, vetch, and chickpeas are the main cash crops. The total population of the district in
2010 was 198,951 of which 100,951 were males and 97,423 females. The district has a
population density of 1948 per square km [
Ethical clearance was obtained from the Ethical Review Committee of the Institute of Public
Health, College of Medicine and Health Sciences, the University of Gondar. Letters of
permission were also obtained from the North Gondar Zonal Health Office and the Libo-kemekem
District Administration. Informed consent obtained from each parent/care giver after the
purpose of the study was explained. Confidentiality was ensured by using code numbers rather
Study population and sampling
The study population included children aged 6±59 months in the 12 randomly selected villages
of the district, three urban and nine rural villages. Children who were seriously ill during the
whole data collection season and children with spinal curvature (Kiphosis, scoliosis and
kiphoscoliosis) were excluded. Out of 34 villages in the district, 12 were selected randomly. The total
sample size (n = 1320) was distributed to each village proportionally based on the number of
households in the village, using probability proportionate to size method. The number of
households in each village was obtained from the respective health posts. Sampling interval (K) was
calculated for each village, and the first household in each village was identified using a random
number from k number of households. Then, systematic random sampling technique was used
to select study participants from selected households for measurements. For households which
had more than one eligible children, lottery method was used to select one child for the study.
Mothers or care givers were interviewed on socio-demographic, economic, child health related
characteristics and environmental conditions with a pre-tested structured questionnaire. Child
morbidity status was asked in the previous 6 months as diagnosed by a health professional.
Data collection and analysis
Data were collected by trained community health extension workers from October 15 to
December 15, 2016. Mothers or care givers were interviewed and anthropometry
measurement (height and weight) was taken on children.
Height of infants aged six months to 23 months was measured in a recumbent position to
the nearest 0.1 cm, using a board with an upright wooden base and movable headpieces.
Children aged 24 to 59 months were measured in a standing up position to the nearest of 0.1 cm.
Additionally, child weight was measured by an electronic digital weight scale for children who
were comfortable to be measured alone, and also for children who were uncomfortable to be
measured alone, we used the combined mother and child weight and the mother's individual
weight to calculate the child's weight .Respondent economic status was accounted for
through the occupational variables. The Categories of morbidity status were based on the types
of diseases that the child encountered in the previous six months. For instance, if the child had
one type of disease it will be categorized as one disease. Distance of water source from
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household was categorized as near if it takes less than 30 minutes while far if it takes 30
minutes on foot.
The collected data underwent cleaning and entered using the EPI-INFO 3.5.1 software.
Data on sex, age, height, and weight was transferred with participants' identification number
to ENA for SMART software to convert nutritional data into Z scores of the indices HAZ
using the WHO standard. The anthropometry measurement of height for age (HAZ) was
calculated through ENA SMART software, and children less than -2 SD were classified as stunted.
Those children with HFA indices between -2 and -3 SD were classideid as moderate stunting
while < -3 SD were classified as severe stunting. Data was also exported to SPSS version 20 for
further analysis and identification of factors associated with stunting by the binary logistic
regression model. Variables with a p-value less than 0.2 in the bivariate analysis were included
in the multivariate logistic regression model. The strength of association was determined by
the Adjusted Odds Ratio (AOR) at a 95% confidence interval, and p-value <0.05 was used to
show the association between independent variables and the presence of stunting. Variables
having p-value, of < 0.05 were considered as statistically significant.
Demographic and socio-economic characteristics
In this study a total of 1287 children aged 6-59months were included, with a response rate of
97.5%. The majority 1149 (86.9%) of the mothers were married, and 788 (61.2%) were within
the age group of 26±35 years. With regard to parents educational status, 61.2% of the mothers
and 47.6% of the father were illiterate. Out of the total households included, 649 (53.9%) family
heads were farmers. (Table 1)
The children varied in terms of sex and age in that 665 (51.7%) were females, while 367
(28.5%) and 356 (27.7%) were 13±25, and 25±36 months old, respectively. Regarding child
morbidity status, most of the children 948 (73.7%) had infectious diseases such as diarrhea
caused by infectious agents for in the previous six months. (Table 2)
Environmental health condition
The majority (71.3%) of the households used public tap water for drinking. Almost all, 1170
(90%), of the households had access to a nearby water source, whereas 117 (9.1%) are required
to travel more than 30 minutes on foot to fetch water.
With regard to the availability of toilet, 745 (57.9%) households had toilettes; traditional pit
latrines were most commonly used, whilst 529(41.1%) households used open field defecation.
Prevalence of stunting
The overall prevalence of stunting in the study population was 49.4% [95% CI: 46.7±52.3]. The
prevalence of stunting was 52.3% among female children and 47.7% among males. The
prevalence of moderate and severe stunting was 37.5% and 13.1%, respectively. Stunting was most
prevalent in the 49±59 months age group at 65.5%, while the 6±12 months age group had the
least. (Fig 1)
Factor associated with stunting
Child age, family size, fathers educational status, occupational status of household head, child
morbidity status, and marital status of parents were entered into the multivariate binary
logistic regression model. The output of the multivariate binary logistic regression showed that,
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36 and above
Divorced, Widow and separated
Cannot read & write
Cannot read & write
child age, family size, fathers educational, and occupational status were significantly associated
with stunting. (Table 4)
Age of a child was directly correlated with stunting. Accordingly, compared to children
aged 6-12months, children of age13-24 months were 2.07 times more likely to be stunted
[AOR = 2.07, 95% CI: (1.34, 3.18)]. Similarly, children aged 25±36 months had 3.86 times
more odds of being stunted than children aged 6-12months [AOR = 3.86, 95%CI: (2.50, 5.97)].
Thus older children had a stronger association with stunting. Children aged 37±48 months
were 4.73 times [AOR = 4.73, 95%CI: (3.00, 10.91)] more stunted while children aged 49±59
months were 6.31 times more likely to be stunted compared to children aged 6-12months
[AOR = 6.31, 95%CI: (3.65, 10.91)].
The categories of morbidity status were based on the types of diseases that the child encountered in the previous six months.
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Family size had also shown a positive significant association with stunting. Children in a
family of at least six members were 1.77 times at higher odds of stunting than children in a
family of five and less [AOR = 1.77, 95%CI: (1.35, 2.32)].
Reduction in the odds of stunting was observed among children who lived with their fathers
and whose parents were farmers and self-employed. Children whose fathers completed
secondary school education had shown 50% reduced odds of being stunted compared to children
with illiterate fathers [AOR = 0.50, 95%CI: (0.30, 0.81)]. Similarly, farmers and self-employed
household heads reduced the odds of their children compared to housewife heads. As a result
children of farmer household heads had 44% lower odds of being stunted [AOR = 0.56, 95%
CI: (0.38, 0.84)] than children of housewives. Similarly, children from self-employed
household heads had 55% lower odds of stunting than housewives [AOR = 0.45, 95% CI: (0.28,
This study has explored the prevalence of stunting and its associated factors among children
aged 6±59 months at Libo-kemekem district, North West Ethiopia. The prevalence of stunting
was 49.4%, of this 47.3% in males and 50.3% in females. This finding was the highest compared
Fig 1. Prevalence of stunting by age (in months) among children aged 6±59 months at Libo-kemekem district,
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to the regional, national and WHO cut off point of 40% set for stunting [
]. The current
magnitude was also higher compared to that of Kenyan study which was 39% [
] and other
study conducted in eastern Ethiopia which showed prevalence of 34.4% [
]. Similarly, it
was higher than those of studies conducted in southwest Ethiopia, which was 35.4% . A
studies in Libo-kemkem and Fogera districts of northwest Ethiopia, and Haramaya district of
eastern Ethiopia reported a higher prevalence of 42.7% [
] and 45.8% [
] stunting among
school age children, respectively.
Our findings might vary in part from previous ones due to differences in geographic
characteristics of the study area [23±25], study period, age difference of the study participants [
(i.e. 0±59 and 6±59 months) and other socio-economic characteristics of the participants.
Higher prevalence of infectious diseases like malaria and Visceral leishmaniosis and
micronutrient deficiencies in Libo-kemkem district with inadequate health care may contribute higher
occurrences of child stunting in our study subjects [29, 30]. However, the magnitude of
stunting in the study area is much higher compared to the national recommendations and efforts to
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alleviate the problem. For example, the prevalence is consistent with the 2005 national report
; however, there have been improvements over that time as reported in 2014 [
Also this study showed that the prevalence of stunting increases with the age of the child.
This association was supported by other studies in north and northwest Ethiopia [
might be due to the nutritional status of the mother since stunting has a chronic and cyclic
nature, poor dietary practice, weaning, lower and inappropriate breast and complementary
feeding practices. The other possible explanation for increased risk of stunting in older
children may be due to unhygienic preparation of complementary foods which exposes children
to recurrent infections. Limited access to safe drinking water in the study area also exposes
these children to varied types of infections and diarrheal diseases which further increase the
risk of chronic malnutrition.
Our results shows that, education is the key resource that enabled women and men to
provide appropriate childcare with regard to health, child feeding and child education.
Completion of secondary education of the father was observed to ameliorate the prevalence of
stunting among the study participants. These associations were not observed in those
completed primary education and may be due to the fact that life science courses are not integrated
with nutrition education and communication. Similar associations were seen in studies
conducted in Bangladesh and the Philippines [
]. This is because in the study area fathers
who are educated better than their wife's as, household heads have control over family
expenditures. Thus, they have a leading role in providing quality health care and optimal feeding for
their children. Therefore, if the father is educated, he is more knowledgeable in childcare as
well as optimal child feeding recommendations and can advise the mother on children's
On the other hand, this study identified that as family size increases, so to do the odds of
being stunted. Children from families with six and more members had a higher odds of being
stunted compared to children from five or less family members. This finding is supported by
another study conducted in southeast Ethiopia which stated that children whose mothers gave
birth to more than four children were more likely to be stunted compared to children from
mothers who gave birth to one child[
]. This could be due to the fact that, families with more
children are more stretched economically and cannot feed themselves well and face difficulty
in providing the daily nutrition requirements for proper child physical development. This
means, as the size of a family increases there is a scarcity of resources for household
consumption, especially food, and healthcare which ultimately leads to stunted growth. Furthermore,
parents with more children generally lack adequate time to pay proper attention to the need of
The occupational status of the household head also has a significant role in a child's
stunting. Households headed by farmers and self-employed parents reduced the odds of stunting
among their children compared to households led by housewives. This is because the income
earned by a single parent (a mothers) is always often less than what couples can procure.
The study has the following limitations. We cannot declare a temporal relationship between
stunting and other independent variables due to the cross sectional design of the study.
Standard procedures were used for the measurement of height/length but measurement errors are
inevitable especially within assessors. Moreover, there may be a recall bias in reporting age of
children in a rural villages.
Our findings demonstrate a higher prevalence of stunting in Libo-kemkem district and thus
represents an important public health concern. This study also revealed that a child's age,
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occupational status of the household head, family size, and fathers' education were
significantly associated factors for stunting. Therefore, a strong nutrition specific and sensitive
intervention should be implemented in the study area with a special focus on supporting
housewives, promoting family planning, and education on child feeding and nutrition.
S1 Dataset. Metadata.
We would like to thank the Institute of Public Health, the University of Gondar,
Libo-kemekem District Health Office for their support. We are also grateful to the study participants.
Conceptualization: Selamawit Bekele Geberselassie, Solomon Mekonnen Abebe, Molla
Data curation: Selamawit Bekele Geberselassie.
Formal analysis: Selamawit Bekele Geberselassie, Solomon Mekonnen Abebe.
Investigation: Selamawit Bekele Geberselassie, Molla Mesele Wassie.
Methodology: Selamawit Bekele Geberselassie, Solomon Mekonnen Abebe, Yayehirad Alemu
Melsew, Molla Mesele Wassie.
Project administration: Selamawit Bekele Geberselassie, Molla Mesele Wassie.
Resources: Molla Mesele Wassie.
Software: Yayehirad Alemu Melsew, Molla Mesele Wassie.
Supervision: Solomon Mekonnen Abebe, Molla Mesele Wassie.
Validation: Solomon Mekonnen Abebe, Shadrack Mulinge Mutuku.
Writing ± original draft: Molla Mesele Wassie.
Writing ± review & editing: Solomon Mekonnen Abebe, Yayehirad Alemu Melsew, Shadrack
Mulinge Mutuku, Molla Mesele Wassie.
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WHO. Global nutrition report 2015; actions and accountability to advance nutrition & sustainable
10 / 11
World Health Organization. Child Growth Standards: Length/height-for-age, weight-for-age, weight-forlength, weight-for-height and body mass index-for-age: Methods and development . Geneva WHO , 2006 .
World Health Organization: Child growth standards Anthro and macro : WHO; 2011 .
World Health Organization. Physical status: The use and interpretation of anthropometry: report of a WHO expert committee Geneva WHO; 1995 .
4. Black RE , Allen LH , Bhutta ZA , Caulfield LE , de Onis M , Ezzati M , et al. Maternal and child undernutrition 1ÐMaternal and child undernutrition: global and regional exposures and health consequences . Lancet . 2008 ; 371 ( 9608 ): 243 ± 60 . doi: 10 .1016/S0140- 6736 ( 07 ) 61690 - 0 . WOS:000252471900028. PMID: 18207566
5. Dewey K , Begum K. Long-term consequences of stunting in early life . Maternal & child nutrition . 2011 ; 7 ( s3 ): 5 ± 18 .
6. de Onis M , Branca F. Childhood stunting: a global perspective . Matern Child Nutr . 2016 ; 12 Suppl 1 : 12 ± 26 . https://doi.org/10.1111/mcn.12231 PMID: 27187907; PubMed Central PMCID : PMC5084763 .
7. de Onis M , Blossner M , Borghi E . Prevalence and trends of stunting among pre-school children , 1990± 2020. Public Health Nutr . 2012 ; 15 ( 1 ): 142 ±8. https://doi.org/10.1017/S1368980011001315 PMID: 21752311 .
8. CSA. Ethiopia Mini Demographic and Health Survey 2014 . Central Statistical Agency Addis Ababa , Ethiopia. 2014 .
9. UNICEF. Focus on nutrition: The state of the world's children Oxford and Nework: UNICEF , 1998 .
10. Mengistu K , Alemu K , Destaw B . Prevalence of Malnutrition and Associated Factors Among Children Aged 6 ±59 Months at Hidabu Abote District, North Shewa, Oromia Regional State. Nutritional Disorders & Therapy 2013 .
11. Gelano T , Birhan N , Mekonnen M. Prevalence of under nutrition and its associated factors among under five children in Gondar city, Northwest Ethiopia . Journal Of Harmonized Research in Medical & Health Sci 2015 ; 2 ( 4 ): 163 ± 74 .
12. Ruwali D. Nutritional Status of Children Under Five Years of Age and Factors Associated in Padampur VDC, Chitwan . Health Prospect. 2011 ; 10 ( 14 ±8).
13. Derso T , Tariku A , Biks GA , Wassie MM . Stunting, wasting and associated factors among children aged 6±24 months in Dabat health and demographic surveillance system site: A community based cross-sectional study in Ethiopia . BMC Pediatr . 2017 ; 17 ( 1 ): 96 . https://doi.org/10.1186/s12887-017- 0848-2 PMID: 28376746; PubMed Central PMCID : PMC5379504 .
14. 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 ; 15 : 41 . https://doi.org/10.1186/s12889-015-1370-9 PMID: 25636688; PubMed Central PMCID : PMC4314803 .
15. Megabiaw B , Rahman A . Prevalence and Determinants of Chronic Malnutrition Among Under-5 Children in Ethiopia . International Journal of Child Health and Nutrition . 2013 ; 2 ( 3 ): 230 ± 6 .
16. Rajalakshmi J , Endazenaw G . Assesment of Nutritional Status among Under-Five Children in Bishoftutown, Oromiya Region , Ethiopia. International Journal of Nursing Didactics . 2015 ;; 15 ( 11 ): 10 ± 2 .
17. Yalew B . Prevalence of Malnutrition and Associated Factors among Children Age 6 ±59 Months at Lalibela Town Administration, North WolloZone, Anrs, Northern Ethiopia . J Nutr Disorders Ther 2014 ; 4 : 132 .
18. Ali W , Ayub A , Hussain H. Prevalance and associated risk factors of under nutrition among children aged 6 to 59 months in Iinternally displaced persons of JalazoiI camp, district Nowshera, Khyber Pakhtunkhwa . JOURNAL OF AYUB MEDICAL COLLEGE, ABBOTTABAD . 2015 ; 27 ( 3 ): 556 ±9. https://www. ncbi.nlm.nih.gov/pubmed/26721006. PMID: 26721006
19. Kadima YE . Factors influencing malnutrition among children under age of five age in Kweneng West District of Botswana: University of South Africa; 2012 .
21. CSA. Population and Housing Census Report at National Level. Addis Ababa , Ethiopia. 2010 . www. csa.gov.et/newcsaweb/images/documents/pdf_files/regional/report.pdf.
World Health Organization. Global Nutrition Targets 2025 Stunting Policy Brief (WHO/NMH/NHD/14.3).
Geneva: WHO , 2014 .
23. Mutua N , Onyango D , Wakoli A , Mueni H . Factors associated with increase in undernutrition among children aged 6±59 months in kamoriongo village, nandi county, kenya . International Journal of Academic Research and Reflection 2015 ; 3 ( 2 ).
24. Demissie S , Worku A . Magnitude and factors associated with malnutrition in children 6±59 months of age in pastoral community of Dollo Ado district, Somali region , Ethiopia. Science Journal of Public Health 2013 ; 1 ( 4 ): 175 ± 83 .
25. Sisay Z. Magnitude and factors associated with malnutrition of children under five years of age in rural Kebeles of Haramaya, Ethiopia . Harar Bull Health Sci Extracts . 2012 ; 4 .
26. Ayalew E. The prevalence of stunting and associated factors among children age 6±59 months at Mizan-Aman Town, Bench Maji zone , SNNPR region, Ethiopia. Addis Abeba University 2015.
27. Herrador Z , Sordo L , Gadisa E , Moreno J , Nieto J , Benito A , et al. Cross-sectional study of malnutrition and associated factors among school aged children in rural and urban settings of Fogera and Libo Kemkem districts , Ethiopia. PLoS One . 2014 ; 9 ( 9 ):e105880. https://doi.org/10.1371/journal.pone.0105880 PMID: 25265481; PubMed Central PMCID : PMC4179248 .
28. Yisak H , Gobena T , Mesfin F . Prevalence and risk factors for under nutrition among children under five at Haramaya district, Eastern Ethiopia . BMC Pediatr . 2015 ; 15 : 212 . https://doi.org/10.1186/s12887- 015-0535-0 PMID: 26675579; PubMed Central PMCID : PMC4682239 .
Herrador Z , Sordo L , Gadisa E , Buno A , Gomez-Rioja R , Iturzaeta JM , et al. Micronutrient deficiencies and related factors in school-aged children in Ethiopia: a cross-sectional study in Libo Kemkem and Fogera districts, Amhara Regional State . PLoS One . 2014 ; 9 ( 12 ):e112858. https://doi.org/10.1371/ journal.pone.0112858 PMID: 25546056; PubMed Central PMCID : PMC4278675 .
Lopez-Perea N , Sordo L , Gadisa E , Cruz I , Hailu T , Moreno J , et al. Knowledge, attitudes and practices related to visceral leishmaniasis in rural communities of Amhara State: a longitudinal study in northwest Ethiopia . PLoS Negl Trop Dis . 2014 ; 8 ( 4 ):e2799. https://doi.org/10.1371/journal.pntd.0002799 PMID: 24743328; PubMed Central PMCID : PMC3990515 .
CSA. Ethiopia Demographic and Health Survey Calverton, Maryland, USA Central Statistical Agency, Addis Ababa, Ethiopia 2005 .
33. Jamro B , Junejo A , Lal S , Bouk G , Jamro S . Risk factors for severe acute malnutrition in children under the age of five year in Sukkur . Pakistan Journal of Medical Research . 2012 ; 51 ( 4 ): 111 .
34. Islam MM , Alam M , Tariquzaman M , Kabir MA , Pervin R , Begum M , et al. Predictors of the number of under-five malnourished children in Bangladesh: application of the generalized poisson regression model . BMC Public Health . 2013 ; 13 ( 11 ): 11 . https://doi.org/10.1186/ 1471 -2458-13-11 PMID: 23297699; PubMed Central PMCID : PMC3599578 .