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• Published: 29 July 2020

Factors associated with malnutrition in children < 5 years in western Kenya: a hospital-based unmatched case control study

• Edwin Gudu 1 , 2 ,
• Mark Obonyo 2 ,
• Victor Omballa 3 ,
• Elvis Oyugi 2 ,
• Cecilia Kiilu 4 ,
• Jane Githuku 2 ,
• Zeinab Gura 5 &
• James Ransom   ORCID: orcid.org/0000-0001-6528-3994 6  

BMC Nutrition volume  6 , Article number:  33 ( 2020 ) Cite this article

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Globally, under-nutrition accounts for > 3 million deaths annually among children < 5 years, with Kenya having ~ 35,000 deaths. This study aimed to identify factors associated with malnutrition in children aged < 5 years in western Kenya.

We conducted a hospital-based unmatched case-control study between May and June 2017. Cases were defined as children aged 6–59 months with either z-score for weight-for-height ≤ −2SD or ≥ +2SD; weight-for-age ≤ −2SD or ≥ +2SD; or height-for-age ≤ −2SD. Controls were children aged 6–59 months with age-appropriate anthropometric measurements. Cases were consecutively recruited while systematic random sampling was used to select controls. Data from interviews and clinical records were collected and entered into Epi-Info, which was used to run unconditional logistic regression analyses.

A total of 94 cases and 281 controls were recruited. Of the cases, 84% (79/94) were under-nourished. Mother not having attended ante-natal clinic (OR = 7.9; 95% CI: 1.5–41.2), deworming (OR = 0.8; 95% CI: 0.4–1.2), and pre-lacteal feeding (OR = 1.8; 95% CI: 1.1–3.0) were associated with under-nutrition. Delayed developmental milestones (AOR = 13.9; 95% CI: 2.8–68.6); low birth weight (AOR = 3.3; 95% CI: 1.4–7.6), and paternal lack of formal education (AOR = 4.9; 95% CI: 1.3–18.9) were independently associated with under-nutrition.

Proper pre-natal care, child feeding practices and deworming programs should be enhanced to reduce pediatric malnutrition.

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Malnutrition refers to a state of either under-nutrition or over-nutrition. Under-nutrition occurs when the diet a person consumes does not meet their body’s requirement for growth and development whereas over-nutrition occurs when a person consumes too many calories [ 1 ]. Good nutrition and feeding practices are critical to a child’s growth and development especially during the first two years of life [ 2 ]. Under-nutrition impairs a child’s immunity, which can lead to recurrent infections, and impaired physical and cognitive development [ 3 ].

Under-nutrition is a major cause of morbidity and mortality especially, in low-to-middle-income (LMIC) countries. Globally, malnutrition contributes to more than 3 million deaths among children < 5 years annually [ 4 ]. UNICEF estimates that in Kenya, 239,446 children suffer from moderate acute malnutrition (MAM) and 2600 children suffer from severe acute malnutrition (SAM). Under-nutrition also contributes to about 35,000 deaths among children < 5 years each year in Kenya [ 4 ]. Stunting has also been linked to development of non-communicable diseases and lower adult productivity later in life. Children < 5 years who are prone to recurrent infectious diseases such as diarrheal illnesses, respiratory tract infections, tuberculosis and malaria often have under-nutrition as a co-morbidity [ 5 ].

The Kenya Demographic Health Survey 2014 reports that 26% of children < 5 years are stunted, 4% are wasted, and 11% are underweight. Malnutrition remains a public health concern in western Kenya. According to the survey 25.2% of children < 5 years are stunted while 8.2% are severely stunted [ 6 ]. This means that 1 in 4 children suffer from chronic under-nutrition. Therefore, identifying factors associated with malnutrition (especially under-nutrition) is vital in preventing the development of long-term deleterious effects.

This study aimed to identify clinical, demographic, and socio-economic factors associated with malnutrition in children < 5 years for public health action.

The study was carried out at Alupe Sub-County Hospital. The hospital is a level 4 hospital located in Angorom ward, Teso South Sub-County in Busia County serving a catchment population of 34,321 persons (Fig.  1 ) [ 7 ].

Map of Busia County, Western Kenya showing the constituent sub-counties including Teso South sub-county. Map source: Commission on Revenue Allocation-Kenya

Study design

We conducted a facility-based unmatched case control study carried out between May 2017 and June 2017. We chose an unmatched design due to the more limited number of cases and the inconsistency and lack of some documentation of the data available in the records at the hospital. The study population consisted of all children < 5 years attending the child welfare clinic and the outpatient clinic within the hospital during the study period.

Case definitions

Under-nourished child was defined as a child aged 6–59 months attending the hospital as an inpatient or outpatient whose anthropometric measurements were not appropriate for their age with z-scores (weight-for-height [WHZ], weight-for-age [WAZ], height-for-age [HAZ]) of <= − 2 SD. WAZ score from the WHO charts were used to define presence of under-nutrition [ 8 ].

A participant was classified as stunted if HAZ score was <−2SD and severely stunted if HAZ score was <−3SD. Wasting was defined as WHZ score < −2SD while severe wasting was WHZ score < −3SD. Any participant with WAZ score < −2SD was classified underweight.

Mid upper arm circumference (MUAC) calculations

For the MUAC cut-points to determine whether a child was under- or over-nourished, we used the cut-points of any child with MUAC < 126 mm was classified under-nourished [ 8 ].

Definition of controls

Any child aged 6–59 months attending the hospital as an inpatient or outpatient whose anthropometric measurements are appropriate for their age with z-scores between -2SD and + 2SD [ 9 ].

Sample size determination

The sample size was calculated using statistical software Epi Info® version 7.2.0. The study assumed a 95% confidence interval, 80% power, 10% wasting among controls [ 10 ], and the ratio of cases to controls of 1:3. Using these assumptions, the minimum sample size was 375 (94 cases and 282 controls).

Selection of cases and controls

The cases were sampled consecutively due to the low number seen each day for eligible children enrolled for nutritional support in welfare clinic. The sampling occurred via the data entered into the MoH Child Health Logbook, which would have each presenting child’s age, MUAC, and other information indicative of over-, under-, or at-level nutrition. The controls were selected through systematic random sampling from the data in the logbook. The average number of children < 5 years visiting the outpatient section of the child welfare clinic daily was used as a sampling frame. This was determined by obtaining the number of children visiting the out-patient clinic between April and June of three preceding years before the study. The study was conducted during weekdays within the duration of the study period hence the number of controls to be enrolled in the study on any single day was pre-determined. Using the average number of patients seen each day at the clinic and number of controls to be enrolled in the study each day, a sampling interval was determined, and the first control was picked randomly between one and the sampling interval. The sampling interval was then added to enroll the remaining controls. Any eligible participant whose legal parent/guardian did not give oral consent was replaced by the next available participant whose legal parent/guardian consented to the study.

Data collection

Triage was carried out by the hospital staffs as is the norm and all critically and severely ill patients were urgently attended to by the hospital clinicians as per procedures and guidelines of the hospital. The weight was measured using electronic digital weighing scale (Seca®). For height/length, children < 2 years were measured lying down (recumbent length) while those who were > =2 years were measured standing up. For MUAC and head circumference, a non-stretch tape was used.

A pre-tested trans-adapted interviewer-administered questionnaire was used for each study participant to obtain demographic, clinical, nutritional, social and economic information. This questionnaire was adapted from a survey sheet used in Guinea [ 11 ]. (Each patient was de-identified by a unique code to ensure their privacy and maintenance of confidentiality.)

Data management

Data entry, cleaning, validation and analysis was done using Microsoft Excel (Microsoft, Seattle, WA, USA), and Epi info version 7 (CDC, Atlanta, GA, USA). Anthropometric data was analyzed using WHO Anthro® software version 3.2.2 (WHO Anthro®) to assess nutritional indicators like weight-for-length/weight-for-height (wasting), weight-for-age (underweight or overweight), length-for-age/height-for-age (stunting), MUAC-for-age, and HC-for-age. The software then provided the z-scores based on gender, age and the anthropometric measurements. We calculated measures of central tendency and dispersion for the continuous variables and proportions for categorical variables. For univariable analysis, we calculated odds ratios (OR), 95% confidence intervals (CI), chi-square statistics and p -values. Variables with p-value ≤0.05 were statistically significant. We carried out unconditional logistic regression with variables that had p-values of < 0.2 at univariable analysis. A backward elimination stepwise method was used to identify independent factors associated with malnutrition. During model building, any variable that caused an insignificant increase in deviance on removal from the model were left out of the model while the variable that caused a significant increase in deviance on removal were retained in the model. All variables removed from the model when a backward stepwise method was performed and those known to be potential cofounders or factors associated with malnutrition from previous studies were tested for confounding, any of the mentioned variables that had a more than ten percentage change (> 10%) between the crude and adjusted odds ratio was considered as a confounder. The final model after testing for all biologically and statistically plausible interactions had only variables with p -value ≤0.05.

Description of the study participants

There were 375 participants (94 cases and 281 controls), with median age of 16 months (IQR 10, 22), and 51% (191/375) male. Males were 57% (54/94) of cases and 49% (137/281) of controls.

Nutritional status of cases

Of the cases, 84% (79/94) were under-nourished and 16% (15/94) over-nourished. Among those that were under-nourished, by assessing the WHZ score, 20% (16/79) were wasted while 9% (7/79) were severely wasted. Among the same group, using WAZ score, 39% (31/79) were underweight while 29% (23/79) were severely underweight. Using the HAZ score among the under-nourished, 46% (36/79) were stunted while 38% (30/79) were severely stunted.

Univariable and multivariable analysis of factors associated with under-nutrition

On univariable analysis, socio-demographic factors like high birth order of five or more (OR = 2.3; 95% CI: 0.9–6.0), living in urban areas (OR = 1.9; 95% CI: 0.8–4.3), children whose mothers had no formal education (OR = 2.0; 95% CI 0.9–4.4), those whose fathers had no formal education (OR = 4.6; 95% CI: 1.4–15.0) and those who came from large family sizes of more than 6 occupants (OR = 1.8; 95% CI: 1.1–3.0) had higher odds of developing under-nutrition.

Pre-natal maternal factors were also shown to increase odds of developing under-nutrition. These included: participants whose mothers’ did not attend antenatal clinic (ANC) at least once (OR = 7.9; 95% CI: 1.5–41.6), participants whose mothers who did not attend 4 ANC visits as recommended by WHO (OR = 1.6; 95% CI: 0.9–2.7) and those whose mothers had illness during pregnancy (OR = 1.7; 95% CI: 1.0–2.8). The participants who were born preterm (OR = 2.0; 95% CI: 0.6–7.4) and those with low birth weight (OR = 2.8; 95% CI: 1.2–6.2) had higher odds of under-nutrition compared to term babies and those with normal birth weights.

Post-natal factors such as failure to complete or not being up-to-date on immunizations as per the national immunization schedule (OR = 2.2; 95% CI: 0.7–7.2) and human immunodeficiency virus (HIV) sero-exposure (OR = 1.4; 95% CI: 0.6–3.5) and delayed developmental milestones (OR = 18.9; 95% CI: 4.1–87.5) also increased the odds of developing under-nutrition. The participants who were eligible for deworming and had been dewormed at least once were protected from under-nutrition (OR = 0.8; 95% CI: 0.4–1.2). Infant and young child feeding practices also affected nutritional status of the participants. During the study period, 24% (89/375) of the participants were receiving pre-lacteal feeds increased their odds of under-nutrition (OR 1.8; 95% CI: 1.0–3.1). Exclusive breastfeeding for 6 months as recommended by the WHO was also widely practiced with 72% (271/375) of the participant’s parents adhering to this guideline. Forty percent (149/375) of the participant’s parents still used bottle with nipple for feeding, while 31% (116/375) ceased breastfeeding before the recommended 2 years of age. However, during the study period, there was no statistically significant association between duration of exclusive breastfeeding for the first six months of life (OR = 1.1; 95% CI 0.6–2.0), cessation of breastfeeding at less than 2 years (OR = 0.6; 95% CI 0.2–1.7) or bottle with nipple feeding (OR = 0.9; 95% CI 0.5–1.5) and developing under-nutrition.

Economic factors of the families also affected the nutritional status of the participants. Those whose mothers were unemployed had higher chances of under-nutrition (OR = 1.8; 95% CI 1.0–3.1) whereas those families with an average monthly income of above 5000 Kenya shillings (KES) were protective of under-nutrition (OR 0.7; 95% CI 0.4–1.2) (Table  1 ).

On multivariable analysis, delayed developmental milestones (AOR = 13.9; 95% CI: 2.8–68.6); low birth weight (AOR = 3.3; 95% CI: 1.4–7.6) and paternal lack of formal education (AOR = 4.9; 95% CI: 1.3–18.9) were found to be independently associated with under-nutrition.

The study identified various factors affecting nutritional status among children < 5 years which need to be adequately addressed. This included both pre-natal and post-natal factors as well as infant and young child feeding practices. Therefore, consistent follow-up of pregnant mothers from the antenatal period and post-natal care of the children < 5 years needs to be enhanced.

Among the undernourished, we found that stunting was the most common form of malnutrition, followed by children who were underweight and wasting being the least common among the study population. Stunting was common among cases of under-nutrition and over-nutrition alike. Stunting is a chronic form of malnutrition that results from prolonged non-adherence to proper dietary requirements to meet the body’s physiological needs. These findings were similar to those of a demographic and health survey carried out in the Western Kenya in 2014 [ 6 ]. Other studies carried out in Burundi and Uganda also had similar findings [ 12 , 13 ].

Deworming of children > 1 year of age was also found to be protective of under-nutrition. This finding was in line with another study done in India among pre-school children which showed substantial weight gain among children who were dewormed [ 14 ]. This is because intestinal nematodes affect absorption of both micro and macronutrients which are vital for a child’s growth. However, current systematic reviews show little benefit is derived from mass deworming. They show that children found to be worm infested are the ones that gain weight more significantly compared to non-worm infested children [ 15 , 16 ].

Proper breastfeeding practices for children are advocated for by WHO [ 17 ]. Children that are breastfed up to 2 years of age show quicker linear growth than those breastfed for shorter durations [ 2 ]. Feeding practices such as bottle with nipple feeding, breastfeeding within thirty minutes of delivery, exclusive breast feeding for 6 months and cessation of breastfeeding at 2 years were also assessed during the study. However, they were not statistically significantly associated with under-nutrition. In contrast, the giving of pre-lacteal feeds adversely affected nutritional status and predisposed the children to under-nutrition. This has also been shown by other studies [ 18 , 19 , 20 ]. This could be because pre-lacteal feeding affects the quality and quantity of breastfeeding which in turn affects the nutritional intake by the child. As such, proper education on feeding practices during post-natal period should be enhanced.

Children with under-nutrition were also shown to be more likely to have delayed developmental milestones. This finding was consistent with other studies [ 21 , 22 , 23 ]. This could be because they lack the macro and micronutrients necessary for normal growth and development. Children with prematurity and low birth weight also had higher odds of under-nutrition. These findings were similar from a review done in several countries [ 24 ]. This could be because they require more nutrients for catch-up growth which if not provided in adequate quantities leave them vulnerable to develop under-nutrition. These children should therefore be followed up more closely.

We also found that lack of parental formal education was linked to development of under-nutrition with paternal illiteracy being shown to have a greater influence. This finding concurred with other studies [ 20 , 25 ]. This could be because the community being a patriarchal society, the fathers control the family’s resources. As such, lack of formal education could mean no formal employment and by extension no regular source of income to provide for their families.

Our study also showed that the cases of over-nutrition were also high, compared to findings of other studies in Kenya, despite the hospital serving a population of predominantly low socio-economic status [ 26 ]. This clearly points to the double burden of malnutrition that is supported by other literature based on a critical review done in other lower middle income countries [ 27 ]. This is a new development over the last couple of decades that needs to be further explored to halt and decrease the burden of cases of over-nutrition.

During the study period, children aged less than 12 months were more likely to be over-nourished. This finding was similar to another study carried out in Kenya in 2009 [ 28 ]. This could be because younger children are more likely to receive more attention and feeding effort from their parents as compared to older children. Male gender was also positively associated with over-nutrition. A study carried out in Kenya in 2016 had similar findings [ 29 ]. This could probably be due to the value and cultural preferences placed on the male child. As such, they are likely to be better fed as compared to the girl child. This has also been shown in other Sub-Saharan African countries [ 30 ].

Children who came from households in urban areas and those who came from families with higher average monthly income had higher odds of over-nutrition. This finding was similar to other studies [ 28 ]. This could be due to the higher levels of income which increase their ability to provide more than enough nutrition for their growing children.

Maternal lack of formal education also increased the chances of developing over-nutrition. This finding was contrary with other studies carried out in Sub-Saharan Africa [ 30 ]. High birth weight was also linked to increased chances of over-nutrition. This has also been shown by other studies [ 30 , 31 ]. However, the exact mechanism of this link has not yet been clearly described.

We conducted a hospital-based case-control study and as such, its findings cannot be generalized to the entire population of under-five children in Western Kenya. The data collected on some of the variables could be susceptible to recall bias more so if the child was brought in by a guardian. Another limitation of the study was that the study relied on participants’ self-reported data, which was prone to recall bias and social desirability bias and interviewer bias due to the retrospective tracking of information beyond the advantages of case control study. The other limitation was that since it was a case–control study, which means it cannot establish the relationship between exposure and disease. Anthropometric measures and their technical errors are another limitation because it can result in misclassification of children’s nutritional status. However, we gave strict attention to the study procedures, including the process of training the research team and workers at the hospital, standardization of anthropometric measurements, and close and supportive supervision throughout the field activities to minimize biases.

Proper pre-natal care, child feeding practices and deworming programs should be enhanced. As such, we recommend that close monitoring especially of children more likely to be malnourished should be enhanced. This can be done by providing job aids to providers to help them talk to parents about adherence to key recommended practices such as appropriate feeding, continuous auditing of patient outcomes, and better use of data for improved decision-making should be implemented at these facilities.

Proper infant and young child feeding practices and deworming should be emphasized. Provider advocacy and better health education to parents should be intensified in the region for better outcomes. The hospital in conjunction with Busia County Government should organize for regular outreach to the community targeting pregnant and lactating mothers, strengthen deworming programs for children > 1 year and all children with delayed developmental milestones. It should also organize for health advocacy camps targeting the parents with children < 5 years to educate them on the proper infant and young child feeding practices.

Availability of data and materials

All data generated or analyzed during this study are available upon request to the corresponding author.

Abbreviations

Moderate Acute Malnutrition

Mid Upper Arm Circumference

Weight for Height Z-score

Weight for Age Z-score

Height for Age Z-score

Standard Deviation

Adjusted Odds Ratio

Confidence Interval

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Acknowledgements

We would like to appreciate the participants whose data were used in this study. We also acknowledge Alupe Sub-County Hospital and Busia County Government.

This study was fully funded by Kenya Field Epidemiology and Laboratory Training Program. The funding body of this study did not participate in the design or conclusion of the study.

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Ministry of Health, Moi Teaching and Referral Hospital, Eldoret, Kenya

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Edwin Gudu, Mark Obonyo, Elvis Oyugi & Jane Githuku

Center for Global Health Research, Kenya Medical Research Institute, Nairobi, Kenya

Victor Omballa

West Pokot County Health Department, Kapenguria, West Pokot, Kenya

Cecilia Kiilu

Ministry of Health, Division for Human Resource for Health Development, Nairobi, Kenya

Zeinab Gura

Piret Partners Consulting, 611 Pennsylvania Avenue SE, Unit 358, Washington, DC, 20003, USA

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Contributions

EG, MO, JG, EO, and JR conceived the study, EG collected data, EG, VO, EO, CK, JG, ZG, and MO analyzed the data and drafted the manuscript. All authors helped with the interpretation of the results, read, critically reviewed and approved the final manuscript.

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Correspondence to James Ransom .

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Ethics approval and consent to participate.

Ethical clearance was sought from Institutional Review Ethics Committee Moi University/Moi teaching and Referral Hospital under reference FAN: IREC 1870. Permission for the study was also sought from the County health department and the hospital administration. During the interviews informed oral consent was obtained from parents/legal guardians of all study participants after explaining the objectives of the study. The authors used oral consent to accommodate the low literacy rates in the populations served by this hospital in Alupe. Measures were taken to assure confidentiality of the information provided during these interviews and codes were used to de-classify personal identifying information of study participants. Measures were taken to assure collected data were properly stored and secured and only accessible to the investigators.

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This study was based on patient records, thus consent for publication was not applicable.

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The authors declare that they have no personal or financial competing interests that may bias publication of this manuscript.

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Gudu, E., Obonyo, M., Omballa, V. et al. Factors associated with malnutrition in children < 5 years in western Kenya: a hospital-based unmatched case control study. BMC Nutr 6 , 33 (2020). https://doi.org/10.1186/s40795-020-00357-4

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Received : 09 July 2019

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Published : 29 July 2020

DOI : https://doi.org/10.1186/s40795-020-00357-4

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Malnutrition shows a decline in health due to the disproportion of nutrients and energy in the body. Malnutrition is one of the main risk factors related to children's morbidity and mortality. It is estimated that about 52.50% of child mortality is linked to malnutrition and its associated diseases. 1 Malnutrition is a crucial medical problem in approximately every region of the globe and particularly in Southern Asia and Sub-Saharan Africa. In several developing nations, stunting, underweight, and micronutrient deficiencies among children are common due to insufficient nutrition and ABSTRACT Background: Malnutrition is one of the main health issues among children. Malnutrition is more prevalent in developing countries. Malnutrition among children is affected by many factors. These factors are studied in many parts of the world but they are understudied in most the areas of Pakistan. This study aimed to assess the incidence of malnutrition and its associated factors among children in Murree, Rawalpindi, Pakistan. Methods: This descriptive cross-sectional study was carried out among children of Murree, Rawalpindi for about 6 months from August 2021 to January 2022. Simple random sampling along with an established inclusion and exclusion criteria was applied to enroll 316 participants. A self-adapted questionnaire was applied to take data after taking ethical approval from the institutional research board and informed consent from the participants. Results: The incidence of underweight, normal weight, overweight and obesity among school children of study population was 22.80%, 35.40%, 26.90%, and 14.90% respectively. The association between malnutrition and gender (p=0.001), birth weight (p=0.01), supplementation intake (p=0.03), filtered water use (p=0.02), hygiene (p=0.01), vaccination status (p=0.04), recurrent infection history (p=0.02), socioeconomic status (p=0.04), mother education (p=0.04), mother occupation (p=0.03), awareness of parents about balanced diet (p=0.02), and family size (p=0.04) was statistically significant, whereas association between nutritional status and age group (p=0.05) was insignificant. Conclusions: The incidence of underweight, overweight, and obesity was remarkable among children. Many factors such as gender, birth weight, supplementation intake, filtered water use, hygiene, vaccination status, recurrent infection, socioeconomic status, mother education, mother occupation, parental awareness about a balanced diet, and family size were found to associate with malnutrition among children.

Abdul Tauqeer

Eng Abdirahman

Abstract Background: Malnutrition is a severe problem that affects a child’s cognitive and physical development. An adequate, balanced nutrition is crucial for a proper physical, emotional, and mental development. Malnutrition remains one of the most common causes of morbidity and mortality among children under 5 children throughout the World. It is the most important risk factor for the burden of disease causing about 300, 000 deaths per year directly and indirectly responsible for more than half of all deaths in children. Child malnutrition is one of the most serious public health problems in the developing world. Objective: To assess prevalence of malnutrition and associated factors among children aged 5 years at Lasanod district, Sool region, October 2014. Methods: An institution based cross sectional study was done among MCHs under five children found in Lasanod town on October 2014. The sample size of the study was 113. A pretested structured questionnaire and interview guide were employed to obtain the necessary information for this study. The structured questionnaire were originally prepared in English language and then translated into the Somali language and then back to English. The collected data was analyzing using SPSS Version 20.0 and triangulated. Bivariate and multivariate logistic regressions were carried out. Result: The analysis this study revealed that, 57.5%, 25.6.9% and 33.7% of children were underweight ,wasted, and stunted respectively and also revealed that 3.5%, 10.6% and 13.3% of children were severe underweight , severe wasted and severe stunted. The main associated factors of malnutrition were found to be mother’s age at first birth, place of delivery and duration of breastfeeding. Conclusion and recommendation: - This study revealed that, prevalence of malnutrition was high and it was the top list among the health problems in Lasanod district. In Somalia where most mothers do not know nutritional status and nutrient foods, a lot should be done by different sectors. We suggest that under nutrition prevention programs and strategies in the region as well as other regions should target Nutritional status among mothers and their children in extensive way to bring further positive changes related to diet.

Journal of Nutritional Science and Vitaminology

Francis Nkrumah

American Journal of Public Health Research

Irene Sumbele

International Journal Foundation

This is cross-sectional community based study conducted in Angola area in Khartoum State of Sudan during period of 2015-2017. The aim of the study was to assess nutritional status of under five years old children and its associated risk factors using anthropometric measurements, interview of childcare givers, and observation on nutrition status indicators and socioeconomic profile of families. 282 children and their caregivers were selected and investigated using cluster sampling techniques and predesigned questionnaires and checklist. The results revealed that 19.1 of the studied children were severely malnourished, and 4.7 were moderately malnourished with children in age of one to two years were mostly affective with P value of < 0.05. Family size and parent education level also were reported among the major risk factors of malnutrition with P value of < 0.05. 96.6% of the children had episode of diarrhea at least once, and 81.1% had respiratory tract infection at least once. Few were exposed to frequently to those infectious diseases. The study concluded that severe and moderate malnutrition affect almost quarter of the children in the area especially in the age group of one to two years. Poor education and awareness on how to maintain children health generally is the main risk factor especially knowledge and skills on the causes of malnutrition, proper young children food and feeding practices, breastfeeding, and utilization of available health services. The study recommended extensive health education program along with family support through provision of nutrients high density food. Study Area: The area has a total population of the area 56,534 with 10,386 under five year old children according to the area popular committees. Household with children aged 6 to 59 months were selected for the study along with their mothers. Diarrheal diseases, malaria and acute respiratory infections were the major health problem among young children in the areas. There are five health centers providing PHC services and 5 private clinics. Diarrheal diseases, malaria and acute respiratory infections were the major health problem among young children in the areas. There are five health centers providing PHC services and 5 private clinics. Sample size: 282 children and their mother were selected using the following formula and based on prevalence rate of nutritional deficiency diseases in Khartoum State of which was estimated to be 10% according Khartoum State Ministry of Health, 2009 n = z 2 pq* design defect (d) 2 Where: n = sample size, Z = 1.96, P = prevalence rate of nutritional deficiency diseases= (10%), q = 1-p, d = 0.05, Design defect=2 n =(1.96) 2 X 0.9 X0.X 2 = 138.2976 X 2 = 276.59 (0.05) 2 (14) The number was rounded to 282 children taken into account the refusal which was estimated to be 9%. Cluster sampling techniques was used by dividing the area into 6 clusters, in each 47 children's and their mothers/caretakers were selected randomly (15). Data were collected in predesigned questionnaire and check list through interview with mothers and measuring weight and high of their children. Indicators used during this study were: height –for –age (for chronic malnutrition), weight for weight (for acute malnutrition) and edema (16,17). Weight: The Staler 25kg hanging spring scale marked out in steps 0.1 kg, was used instrument was adjusted to zero before used, the child freed from heavy clothing (16,17). Height: Children up to 2years (23 months 85 cm length) of age were measured on horizontal measuring board. Children over two years of age (or over 85cm) were measured standing on horizontal surface against vertical measuring device. The height was read out as before, to nearest 0.1cm (29) Age: The birth data was entered on the recording form from birth certificates where this document was not available we used date of birth given by mothers Edema: Presence of edema also was recording after examination of children using finger press on the abdomen and legs.

Geleta Asebe

Abdul-Rasheed L Sulaiman , Ahmed Olusi

The road to good health is through good food which depends on the socioeconomic condition of the giver of the food. Numerous studies had been conducted on the causes of child malnutrition among children less than 5 years, that of children between 8 and 16 years with keen interest on the socioeconomic context of the giver has not been well documented. This lacuna is what this paper filled. Cross-sectional household survey was used for the study. 322 respondents were selected using a multi stage cluster sampling design. A well-structured pretested questionnaire was used to elicit the socio-demographic data from the respondents, while the respondents' nutritional status was calculated using the Body Mass Index (B.M.I) method. Chi-square and bivariate logistics regression were used to test the hypotheses. The study discovered that parental education and parental income were the fundamental factors affecting child malnutrition in the study location. Hence, government should ensure that education is made compulsory and affordable to everyone. Also, the menace of poverty should be adequately addressed.

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Impact of malnutrition on the academic performance of school children in Ethiopia: A systematic review and meta-analysis

Aregash abebayehu zerga.

1 Department of Nutrition, School of Public Health, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

Sisay Eshete Tadesse

Fanos yeshanew ayele, segenet zewdie ayele.

2 Department of Pharmacy, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

This study aimed to identify the impact of malnutrition on the academic performance of children in Ethiopia.

The protocol of this study is registered in PROSPERO with a registration number CRD42021242269. A comprehensive search of studies from HINARY, MEDLINE (via PubMed), EMBASE, Cochrane Library, SCOPUS, Google Scholar, and Google was conducted. All published and unpublished studies conducted about the effect of any forms of malnutrition on academic performance of elementary school children in Ethiopia using the English language were included. Quality of the articles was assessed using the Joanna Briggs Institute critical appraisal tool. The pooled log odds ratio with 95% confidence interval was determined to identify the effect of malnutrition on academic performance. I-square statistics was applied to check the degree of heterogeneity between studies. The presence of publication or small study bias had been assessed by Funnel plots, Egger’s weighted regression test, and Begg’s rank correlation test.

A total of 10 studies were included in this study. The pooled prevalence of good academic performance among elementary school students in Ethiopia was 58% (95% confidence interval: 48%, 69%). Stunting (odds ratio = 0.48; 95% confidence interval: 0.30, 0.79), underweight (odds ratio = 0.38; 95% confidence interval: 0.27, 0.53), and iodine deficiency (odds ratio = 0.49; 95% confidence interval: 0.31, 0.78) had a significant association with the academic performance. Rural residence (odds ratio = 0.61; 95% confidence interval: 0.44, 0.83), being female (odds ratio = 0.53; 95% confidence interval: 0.37, 0.77), and uneducated parent (odds ratio = 0.51; 95% confidence interval: 0.44, 0.58) were also factors associated with good academic performance of primary school children in Ethiopia.

Conclusion:

This study concluded that malnutrition in the form of stunting, underweight, and iodine deficiency affected the academic performance of elementary school children in Ethiopia. So, the Ministry of Health worked better to strengthen the nutrition intervention at the critical periods of brain development.

Introduction

Malnutrition refers to deficiency, excess, or an impaired utilization of one or more essential nutrients. 1 It consists of both under and over-nutrition. 2 Undernutrition includes wasting, stunting, underweight, and micronutrient deficiencies. 3 Malnutrition in any of its forms is a significant public health problem. 4 Globally, 29.8% of school-age children have insufficient iodine intake. 5 In India, 54% of school children were under-nourished. 6 In Africa, the prevalence of iodine deficiency among school-age children was 39.3%. 7 In Ethiopia, the prevalence of wasting, underweight, and stunting among primary school children were 17.7%, 18.2%, and 21.3%, respectively. 8 Malnutrition has substantial effects on the neurological development and behavioral capacity of children. 9 Thus, malnourished children may never reach their full scholastic potential. Malnutrition among school age can result in impaired cognitive and motor development, which may undesirably upset academic performance through reduced learning capacity and poor school attendance. 10 , 11

Concurrent with malnutrition, quality of education is a big challenge in Ethiopia. 12 One of the sustainable development goals agenda is inclusive, equitable, and quality education. 13 Ethiopia is doing well in terms of enrollment and coverage of universal primary education. But the total score of grade 8 students has consecutively decreased from 41.1% in 2000 to 35.3% in 2010. 14 The dropout rate, grade repetition, and completion rate of elementary school student was 13.9%, 5%, and 71%, respectively. 15 A qualitative study reported that teachers have complained about their students’ poor academic performance in school. 12 Hence, poor academic achievement has been the main concern for teachers, parents, and students.

Academic performance can be affected by gender, age, residence, study hours, absenteeism, socio-economic status, illness, medium of instruction, and malnutrition. 16 – 18 Malnutrition is the main factor for poor academic performance and contributed to the development of other factors. 19 , 20 Studies showed that malnutrition among school-age children is a risk factor for high absenteeism, early dropouts, low school enrollment, and unsatisfactory classroom performance. 21 , 22

Efforts such as School Feeding Program have been made to improve the nutritional status, enrollment, attendance, retention, and completion rate of students. 23 – 25 However, still many school children suffer from poor nutrition and academic achievement. 22 In Ethiopia, studies investigated the effect of malnutrition on the academic performance of primary school children, but there is an inconsistency between their findings. For instance, a study from Dera District and southern Ethiopia reported that stunting was not a factor for academic performance. 26 , 27 Whereas studies from northwest Ethiopia and Lalibela stated that stunting and being underweight were factors for poor academic performance. 28 , 29 There is no nationally representative information on the effect of malnutrition on the academic performance of primary school children. The evidence generated by this study design would be stronger than individual studies to influence policymakers. 30 , 31 Therefore, this study aimed to determine the impact of malnutrition on the academic performance of primary school children in Ethiopia. “Does malnutrition affect the academic performance of elementary school children in Ethiopia?” was the research question of this study.

Materials and methods

Study design, search strategy, and protocol registration.

Systematic review and meta-analysis (SRMA) study design was applied for this study. The Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guideline was applied to report this SRMA. 32 An extensive search of studies from HINARY, MEDLINE (via PubMed), EMBASE, Cochrane Library, SCOPUS, Google Scholar, and Google was done. “Nutritional status” OR “malnutrition” OR “under-nutrition” OR “stunting” OR “wasting” OR “underweight” OR “height-for-age z score” OR “weight-for-age z score” OR “weight-for-height z score” OR “iron deficiency” OR “iodine deficiency” AND “academic performance” OR “school performance” OR “school achievement” OR “academic achievement” OR “educational performance” AND “primary school children” OR “elementary school children” OR “student” AND “Ethiopia” were used as key terms. The search was undertaken from 1 February to 23 March 2021. This SRMA was registered in PROSPERO with a registration number CRD42021242269.

Inclusion criteria

All published and unpublished observational studies about the effect of malnutrition on the academic performance of elementary school children in Ethiopia were included. Under-nutrition among primary school children were the exposure variable. Normal nutrition among primary school children was the comparison variable/group for this study. Studies assessed academic performance of primary school children using at least two-semester average scores as a primary outcome were included. To get a more comprehensive result, no restriction was made by the year of publication (studies published until 23 March 2021 were included).

Exclusion criteria

Review articles, conferences, abstracts, editorials, and descriptive studies were excluded from this study. We also excluded studies that did not report the outcome of interest and at least one form of malnutrition.

Study selection and data extraction

The article searches and screening activity was performed by two reviewers (AAZ and SET). Articles were exported and managed using Endnote X8 software. Duplicates were identified and removed from the citation manager. Then the remaining articles were assessed for eligibility by title, abstract, and full-text level. Studies conducted out of Ethiopia and with unrelated topics were excluded. Then the abstract and full document of remaining articles was examined. Those studies that were not eligible based on the full-text assessment were excluded and reasons were described. 32 Studies that passed through this selection process were included in the review.

A data extraction sheet was developed using Microsoft Excel worksheet 2013 and the following variables were extracted from each eligible article:

• Study characteristics: name of first author, year of publication, region, study area, study design, and sample size.
• Outcome (number of children with good academic performance) and independent variables (count data with 2 × 2 table, and odds ratio (OR) with 95% confidence interval (CI; where count data not available)).

Quality assessment

The Joanna Briggs Institute (JBI) 33 critical appraisal tool was used to assess the quality of each paper. The tool has Yes, No, Unclear, and “not applicable” answers. A value was given 1 for “Yes” and 0 for “No” and “Unclear” responses. Three investigators (AAZ, FYA, and SZA) independently performed the quality assessment using the JBI criteria. Scores of each item were summed and converted into percentages. The quality scores of the three reviewers were averaged. Disagreement between investigators was solved by discussion and consensus. Agreement between the investigators were determined and there was substantial agreement (kappa = 0.77). 34 Finally, studies with higher scores (> 50%) were included in this SRMA.

Outcome assessment

The main objective of this study was to identify the effect of malnutrition (stunting, underweight, wasting, and micronutrient deficiency) on academic performance in log OR form. In addition to malnutrition, socio-demographic variables such as place of residence, educational status of the family (no-formal education versus formal education), student sex (male versus female), family size (⩾ 5 versus < 5), and income (low versus high) were extracted.

Statistical analysis

The extracted data were exported to STATA version 14.0 for the meta-analysis. The pooled prevalence was calculated to estimate the prevalence of good academic performance. The pooled log OR and its 95% CI was determined to identify the effect of malnutrition on the academic performance of primary school children. Heterogeneity was checked by Higgins’s I-square statistics in which I-square value of > 75%, 50% to 75%, and < 50% was reported as high, moderate, and low heterogeneity, respectively. 35 A random effect model with 95% CI was used to report heterogeneous findings. Meta-regression, subgroup analysis, and sensitivity analysis were conducted to identify the possible sources of heterogeneity. Publication bias was visually identified by funnel plots. The funnel plot asymmetry was statistically checked using Egger’s and Begg’s test. The visual asymmetry of the funnel plot and p-value < 0.05 of the Egger’s and Begg’s test was suggestive of publication bias. 35 , 36 Then, trims and fills analysis was conducted to deal with publication bias. Finally, data were presented in tables and figures.

Study selection and characteristics

A total of 1906 articles were retrieved by literature search. Of these, 398 were excluded because of duplication, 1490 did not have relation with the aim of the study, and 8 did not meet the eligibility criteria due to differences in outcome classification, 37 outcome measurement, 26 target population 38 , 39 and we cannot get the 2 × 2 table and the OR. 40 , 41 Finally, 10 articles were included in this SRMA ( Figure 1 ). All included articles were full text and done using a cross-sectional study design with one prospective cohort. 42 A total of 5626 students participated in the study with a minimum of 273 43 and a maximum of 1254 44 sample population. Studies were obtained from three regions of Ethiopia; Amhara, Oromia, and Southern Nations, Nationalities, and People (SNNP) region that published or posted from 2013 to 2021 ( Table 1 ).

PRISMA flow diagram of included studies in systematic review and meta-analysis of the impact of malnutrition on academic performance of primary school children in Ethiopia from 2013 to 2021.

Characteristics of studies included in this systematic review and meta-analysis about the impact of malnutrition on the academic performance of primary school children in Ethiopia from 2013 to 2021.

SNNP: Southern Nations, Nationalities, and People.

Pooled prevalence of good academic performance

The pooled estimate indicated that 58% (95% CI: 48%, 69%) of elementary school students have good academic performance in Ethiopia. The true heterogeneity among studies other than chance was 98.6% (I 2  = 98.6%, p-value < 0.001). The highest frequency was reported from Lalibela, Amhara region 85% (95% CI: 82%, 88%) and the lowest was from Meskan, SNNP region 32% (95% CI: 27%, 37%; Figure 2 ).

Forest plot for pooled prevalence of good academic performance among elementary school children in Ethiopia, 2013–2021.

Subgroup analysis

Based on the subgroup analysis, the academic performance was highest in Oromia 69% (95% CI: 59%, 78%) followed by Amhara 62% (95% CI: 42, 83%) and then SNNP 42% (95% CI: 32%, 52%). However, the I-square value was still high in each region. Hence, region is not the source of heterogeneity ( Figure 3 ).

Subgroup analysis by region for the pooled good academic performance of elementary school children in Ethiopia, 2013–2021.

Meta-regression and sensitivity analysis

Meta-regression was conducted by including sample size and publication year. But all of these variables were not the sources of heterogeneity (p > 0.05). Sensitivity analysis indicated that there was no study that influences the pooled effect ( Figure 4 ).

Sensitivity analysis for the academic performance of elementary school children in Ethiopia, 2013–2021

Test for publication bias

Visual observation of the funnel plot indicated the presence of some publication bias ( Figure 5 ). However, it was statistically disproved by the Egger’s (p = 0.96) and Begg’s test (p = 0.72).

Funnel plot to detect the presence of publication bias regarding the pooled prevalence of good academic performance among elementary school children in Ethiopia, 2013–2021.

Factors associated with academic performance

Stunting (OR = 0.48; 95% CI: 0.30, 0.79), underweight (OR = 0.38; 95% CI: 0.27, 0.53), and iodine deficiency (OR = 0.49; 95% CI: 0.31, 0.78) had significant negative association with good academic performance. Similarly rural residence (OR = 0.61; 95% CI: 0.44, 0.83), being female (OR = 0.53; 95% CI: 0.37, 0.77), and non-formal educated parent (OR = 0.51; 95% CI: 0.44, 0.58) had significant negative association with good academic performance of Ethiopian primary school children ( Table 2 ).

Factors associated with academic performance among elementary school children in Ethiopia, 2013–2021.

OR: odds ratio; CI: confidence interval.

This SRMA aimed to generate pooled evidence on the impact of different forms of malnutrition on the academic performance of elementary school children in Ethiopia. This study reported that the odds of good academic performance were 57% lower among stunted children than not stunted children. It is similar to studies from Burkina Faso, Vietnam, Benin, and a multi-country cohort study. 49 – 53 This is because stunting is often occurred within the first 1000 days of a child’s life (from conception up to the first 2 years of life) which is a period of children’s rapid brain development takes place. 54 , 55 Once occurred, stunting causes tissue damage, impaired differentiation, delayed myelination, and limited overall development of the brain. 56 , 57 Then it results in aberration of the temporal sequences of brain maturation and the foundation of neuronal circuits. 9 As a result, the brain’s cognitive process, motor and language development will be limited and causes a long-term permanent impact on academic performance of children. 58 This study reported that being underweight reduces the academic performance of children by 68%. However, a study from Bennin reported that underweight cannot affect the cognitive development of children. 51 Since most researchers focus on the effect of stunting on the academic performance, there is no adequate review to compare and set conclusion about underweight.

In this study, good academic performance was 50% lower among iodine-deficient children than in iodine-sufficient children. Similarly, most reviews reported that iodine deficiency is a risk factor for academic performance. 59 – 61 Iodine is an essential micronutrient needed for production of thyroid hormones. 62 Thyroid hormone is necessary for many body processes such as thermal and metabolic regulation, organ and neurological development, and function of the central nervous system by regulating the genetic expression and cell differentiation of the brain. 63 – 65 Therefore, iodine deficiency significantly lowers cognitive capacities ranging from mental retardation to impaired development of intelligence and academic performance. 59 Although iodine deficiency at early age poses irreversible damage, studies conducted among school-age children showed that iodine supplementation can still improve cognitive abilities. 66 , 67 So, iodine fortification should be strengthened to improve the academic performance of primary school children in Ethiopia. 66

In this review, students from rural residences had a lower academic performance than those from urban areas. This finding is in agreement with a policy-brief report of Ethiopia. 68 In contrast to this study finding, a review conducted on rural and urban areas reported that rural students had a better academic performance than urban students. 69 Then again, a study from Benin showed that place of residence had no association with academic performance. 51 This discrepancy might be due to the sociocultural difference between countries.

In this review, the odds of good academic performance were lower among girls than boys. This might be because better preferences had been given to boys and girls are often faced with the burden of household tasks, which hinders their ability to perform successfully at school. However, a review from the global north and south reported that girls were better in academic performance. 69 In addition, a systematic review in Trinidad and Tobago stated that females had better performance than males. 70

In this study, parents’ educational level had a significant association with the academic performance of primary school children. Students from non-educated parents were less likely to have good academic performance than students from formally educated parents. This finding was in agreement with a study from Benin. 51 This might be because children from uneducated parents get less support on doing assignments, project work, homework, class work, and other academic and social issues. Conversely, children from highly educated parents may consider their parents as role models for their academic success. 71

Limitation of the study

This study had the following limitations; first, this meta-analysis represented only studies reported from three regions of Ethiopia. Second, it was limited to articles written in the English language only. Third, the result was highly heterogeneous. Fourth, almost all of the included studies were cross-sectional, which may not show the cause–effect relationships. Fifth, due to the shortage of individual studies, this study cannot assess the effect of iron deficiency on academic performance.

Strength of the study

This review tried to include both published and unpublished studies.

This SRMA concluded that stunting, underweight, and inadequate iodine intake had a significant impact on the academic performance of children. Also being female, rural residents, and from uneducated parents had a negative association with academic performance of children in Ethiopia. So, the Ministry of Health worked better to strengthen the nutrition intervention at the critical periods of brain development. In addition, to improve the nutritional status and the related academic performance of elementary school children, the Ministry of Education enhanced the coverage of school feeding programs by emphasizing rural children, girls, and uneducated parents. Further research is recommended on the effect of iron deficiency/iron deficiency anemia on the academic performance of school children in Ethiopia.

Acknowledgments

We would like to acknowledge Wollo University, College of Medicine and health sciences, School of public health for providing us with basic training on SRMA.

Author contributions: All authors contributed to data analysis, drafting, and revising the article, gave final approval of the version to be published, and agreed to be responsible for all aspects of the work.

Data availability: All the required data are included in the manuscript.

Declaration of conflicting interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethical approval: Ethical approval for this study was obtained from Wollo University, College of Medicine and Health Sciences Ethical Review Committee (CMHS 857/13/13).

Funding: The author(s) received no financial support for the research, authorship, and/or publication of this article.

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Title: megalodon: efficient llm pretraining and inference with unlimited context length.

Abstract: The quadratic complexity and weak length extrapolation of Transformers limits their ability to scale to long sequences, and while sub-quadratic solutions like linear attention and state space models exist, they empirically underperform Transformers in pretraining efficiency and downstream task accuracy. We introduce Megalodon, a neural architecture for efficient sequence modeling with unlimited context length. Megalodon inherits the architecture of Mega (exponential moving average with gated attention), and further introduces multiple technical components to improve its capability and stability, including complex exponential moving average (CEMA), timestep normalization layer, normalized attention mechanism and pre-norm with two-hop residual configuration. In a controlled head-to-head comparison with Llama2, Megalodon achieves better efficiency than Transformer in the scale of 7 billion parameters and 2 trillion training tokens. Megalodon reaches a training loss of 1.70, landing mid-way between Llama2-7B (1.75) and 13B (1.67). Code: this https URL

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