Journal of Nutrition and Metabolism

Journal of Nutrition and Metabolism / 2020 / Article

Research Article | Open Access

Volume 2020 |Article ID 6702036 | https://doi.org/10.1155/2020/6702036

Getahun Fentaw Mulaw, Fentaw Wassie Feleke, Seteamlak Adane Masresha, "Maternal Characteristics Are Associated with Child Dietary Diversity Score, in Golina District, Northeast Ethiopia: A Community-Based Cross-Sectional Study", Journal of Nutrition and Metabolism, vol. 2020, Article ID 6702036, 7 pages, 2020. https://doi.org/10.1155/2020/6702036

Maternal Characteristics Are Associated with Child Dietary Diversity Score, in Golina District, Northeast Ethiopia: A Community-Based Cross-Sectional Study

Academic Editor: Jos Mar a Huerta
Received13 Mar 2020
Revised12 Aug 2020
Accepted13 Sep 2020
Published22 Sep 2020

Abstract

Background. Dietary diversity is part of the set of indicators developed to assess infant and young child feeding practices. In developing countries, only a quarter of children met the required minimum dietary diversity. In Ethiopia, only 14% of children aged 6–23 months met the minimum dietary diversity score, with regional variation. Therefore, this study aimed to assess dietary diversity score and associated factors among children aged 6–23 months in Golina district, Afar region, Ethiopia. Method. A community-based cross-sectional study was conducted among 345 study participants from February 15 to March 30, 2017, in Golina district, Afar, Northeast Ethiopia. The study kebeles were selected randomly and the study subjects were selected using a cluster sampling technique. The child dietary diversity score was determined by the WHO child dietary diversity score scale, using a 24-hour dietary recall method, and data were collected using an interviewer-administered questionnaire. Multivariable logistic regression was used to identify predictor variables, and the level of significance was determined at value <0.05. Result. This study revealed that children who met the required minimum dietary diversity score were 35.1% (95% CI, (30%–40%)). Children whose mothers have not attended formal education were 3.042 times (AOR = 3.042 95% CI: (1.312–7.052)) less likely to meet the minimum dietary diversity score than children whose mothers have attended secondary and above. Children whose mothers had normal BMI were 51.2% (AOR = 0.488, 95% CI: (0.259–918)) and 68.1% (AOR = 0.319, 95% CI: (0.119–0.855)) more likely to meet the minimum dietary diversity score than children whose mothers’ BMI was underweight and overweight, respectively. Conclusion. Maternal characteristics (educational status and nutrition status) were found to be associated with their child's dietary diversity score. This study also revealed that children who met the minimum dietary diversity score were few. Therefore, the increased emphasis on the importance of the education of girls (future mothers) and nutrition counseling for girls/women who currently have received little education on ways to improve the family and child dietary feeding practice is needed.

1. Introduction

Proper infant and young child feeding practice within the first two years of life is crucial for optimal child growth, development, better health, and preventing chronic degenerative disease [1]. According to the World Health Organization (WHO), introducing optimal complementary foods exactly at six months of age is vital to fulfilling children’s nutritional requirements [2, 3].

Optimal complementary food is explained by fulfilling minimum dietary diversity, meal frequency, and an acceptable diet. Minimum dietary diversity refers to the proportion of children aged 6–23 months who received, on a preceding day, at least four or more varieties of foods from the seven standard food groups recommended by the WHO, without imposing a minimum intake restriction [2, 46].

Greater than two-thirds of malnutrition-related child deaths are associated with inadequate dietary feeding practices during the first two years of life. In developing countries, only a quarter of children met the required minimum dietary diversity [7, 8]. Inappropriate child feeding practices contribute to poor physical growth, including irreversible outcomes of stunting, poor cognitive development, increased risk of infectious diseases, and mortality [2, 9, 10].

Globally, there are efforts to improve the nutritional status of children by implementing different programs like the zero hunger draft [11], scaling up nutrition (SUN) movement [1214], and sustainable development goals (SDGs) [15]. The World Health Assembly has a target for reducing stunted children by 40% in 2025 [9]. At least 12 of the 17 SDGs are highly related to nutrition [16, 17].

Currently, the Ethiopian government also set targets to improve the nutritional status of children through the National Nutrition Program (NNP-II) [18], Health Sector Transformation Plan (HSTP) [19], and Health Extension Program (HEP) [20]. Ethiopia also declared to end child malnutrition by 2030 [21, 22]. Despite the above efforts, currently, 38% of children are stunted, 10% are wasted, and 24% are underweight. In Ethiopia, 14%, 45%, and 7% of children aged 6–23 months have met the minimum dietary diversity, minimum meal frequency, and minimum acceptable diet, respectively [23].

There are no documented studies on the dietary diversity feeding and associated factors among children aged 6–23 months in Northeast Ethiopia. Therefore, this study aimed to assess child dietary diversity score and associated factors among children aged 6–23 months in Golina district, Northeast Ethiopia.

2. Methods and Materials

2.1. Study Design, Setting, and Participants

A community-based cross-sectional study was conducted in Golina district from February 15 to March 30, 2017. The district is found in the pastoralist region of Afar regional state, located 691 km northeast of Addis Ababa, the capital city of Ethiopia, and 220 km northwest of Samara, the capital city of the region. According to the projection of the 2007 census, the total population of the district was estimated to be 56,929; of which 5,727 were under-five children [24]. In the district, there were 1 general hospital, 2 health centers, and 10 health posts. Participants from the randomly selected kebeles were considered as the study population. Those who gave recently up-to-date information about their index children aged 6–23 months were the study unit.

2.2. Sample Size and Sampling Technique

The minimum sample size for each specific objective was separately calculated using a single population proportion formula (Table 1) and double population proportion formula using EPI Info 7.1 (Table 2).


Percentage of minimum child dietary diversity score (%)Reference no.Minimum final sample size

10.6[25]153
68.4[26]347
18.8[27]247
12.6[28]177
30.4[29]342


VariablesCI (%)Power (%)Ratio (unexposed to exposed)Outcome in the unexposed group (%)Outcome in the exposed group (%)No response obtained (%)Sample size

Maternal education [28]95804.568.425.65268

Index child age [28]95801.156.818.35307

Finally, the required size was taken as 347, since this was found as the largest from all calculated sample sizes (Tables 1 and 2). Four kebeles were selected randomly from a total of eight kebeles in Golina district. The sample size was allocated proportionally for each selected kebele, based on the number of children less than two years of age. Then study units were selected using a simple random sampling method.

2.3. Data Collection Tools and Instruments

Data were collected using a semistructured questionnaire via face-to-face interviews with mothers of children aged 6–23 months. The questionnaire was prepared in English and translated into the local language and retranslated back to English to check the consistency. The Food and Agriculture Organization (FAO) meal frequency questionnaire was used to determine the weekly food group consumption of the children [2].

Pretesting was done on 10% of the calculated sample size in nonselected kebeles, and then the necessary modification was done. Anthropometric measurements, such as the mother’s height and weight, were performed following WHO standard procedures. The mother’s weight was measured using UNICEF electronic weighing scales. The weighing scales were calibrated and standardized using a 5 kg standard weight, every morning before the actual measurements. The children’s age was determined using written official documents like vaccination cards. For those who had no written evidence of birthdate, a preprepared local calendar was used by cross-checking with the other family members. The children’s vaccination status was assessed by card, BCG scar, and mother recalled.

Four data collectors and two supervisors, who were fluent in the local language, were employed. Two days of training, on the study tool and anthropometric measurement procedures, were given for data collectors and supervisors. When households found having two or more eligible children, one of them was selected randomly via the lottery method.

2.4. Operational Definitions

(i)Minimum child dietary diversity (MCDD): when a child gets at least 4 from the 7 WHO recommended food groups, regardless of the portion size and meal frequency [2].(ii)Minimum meal frequency (MMF): calculated by grouping child age into two (6–8 months and 9–23 months). The acceptable MMF of children aged 6–8 months is considered as two or more times per 24 hours while for children aged 9–23 months it is three or more times [2].(iii)Minimum acceptable diet (MAD): the percentage of breastfed children 6–23 months of age who had at least the minimum dietary diversity and the minimum meal frequency during the previous day, and nonbreastfed children 6–23 months of age who received at least two milk feedings and had at least the minimum dietary diversity not including milk feeds and the minimum meal frequency during the previous day [2].

2.5. Data Processing and Analysis

Data were edited, cleaned, coded, and entered into EPI Data 4.2 and exported to SPSS version 22 for analysis. Characteristics of study participants were summarized using descriptive statistics. Multivariable logistic regression was used to identify independent predictors of childhood dietary diversity. The strength of association was measured through the odds ratio at a 95% confidence interval. Predictor variables with the value <0.25 at bivariable analysis were included in the multivariable logistic regression model and analyzed using the backward logistic regression model. Statistical significance was declared at a value <0.05.

Multicollinearity was checked using standard error as a cutoff of 2, but no variables were found. The percentage of the model accurately classified was 70.7%, with Hosmer and Lemeshow goodness-of-fit test value = 0.857, indicating the model fits well.

3. Result

3.1. Sociodemographic Characteristics of Study Participants

A total of 345 study participants were included, with a 97% response rate. Nearly 264 (76.5%) were lived in rural areas, and 284 (82.3%) were of Afar ethnicity. Almost quarters (254 (73.6%)) of mothers had not attended formal education. More than half (180 (52.2%)) of children were female (Table 3).


VariableCategoryTotal, n (%)Minimum child dietary diversity score (MCDDS) value
Meet, n (%)Not meet, n (%)

Maternal religionMuslim315 (91.3)106 (87.6)209 (93.3)0.073
Others30 (8.7)15 (12.4)15 (6.7)

Maternal ethnicityAfar284 (82.3)92 (76)192 (85.7)0.024
Others61 (17.7)26 (24)32 (14.3)

Maternal age15–2495 (27.5)39 (32.2)56 (25.0)0.338
25–34195 (56.5)65 (53.7)130 (58.0)
≥3555 (16)17 (14.1)38 (17.0)

Maternal education statusNo formal education254 (73.6)74 (62.2)180 (80.4)<0.0001
Primary35 (10.1)16 (13.2)19 (8.5)
Secondary and above56 (16.3)31 (25.6)25 (11.1)

Maternal occupationGovernment employee41 (11.9)24 (19.8)17 (7.6)<0.0001
Pastoralist216 (62.6)65 (53.7)151 (67.4)
Housewife62 (18)17 (14.0)45 (20.1)
Others26 (7.5)15 (12.3)11 (4.9)

Maternal residenceUrban81 (23.5)52 (23.2)29 (24)0.875
Rural264 (76.5)172 (76.8)92 (76)

Index child sexMale165 (47.8)48 (39.7)117 (52.2)0.026
Female180 (52.2)73 (60.3)107 (47.8)

Index child age6–8 months53 (15.4)26 (21.5)27 (12.1)0.025
9–11 months77 (22.3)20 (16.5)57 (25.4)
12–23 months215 (62.3)75 (62.0)140 (62.5)
Maternal age (in completed years)Mean ± SD27.97 ± 5.43
Family sizeMean ± SD5.81 ± 2.13
Index child age (in completed month)Mean ± SD13.76 ± 4.57

Orthodox, Protestant, and Catholic. Amhara and Oromo. Student, merchant, and daily laborer.
3.2. Maternal Health and Nutritional Status Characteristics

More than half (202 (58.5%)) of mothers were not attended ANC, and 267 (76.8%) of them were given birth at home (Table 4).


VariablesCategoryTotal, n (%)MCDDS value
Meet, n (%)Not meet, n (%)

Maternal ANC follow-upYes143 (41.5)43 (35.5)100 (44.6)0.101
No202 (58.5)78 (64.5)124 (55.4)

Birth placeHome267 (76.8)93 (76.9)174 (77.7)0.862
Health institution78 (23.2)28 (23.1)50 (22.3)

Nutrition counseling and health educationYes82 (23.8)34 (28.1)48 (21.4)0.165
No263 (76.2)87 (71.9)176 (78.6)

Maternal BMI (kg/m2)<18.573 (21.2)19 (15.7)54 (24.1)0.012
18.5–24.932 (9.3)6 (5.0)26 (11.6)
≥25240 (69.5)96 (79.3)144 (64.3)

Mother of the index child making ANC follow-up at least once.Getting counseling and education regarding maternal feeding practice (during pregnancy and lactation) and on child feeding practice.
3.3. Child Healthcare and Feeding Practice

Nearly two-thirds (115 (33.3%)) of children were not exclusively breastfed for the first six months of age. About 67 (19.4%) of children have met the minimum acceptable diet (Table 5).


VariablesCategoryTotal, n (%)MCDDS value
Meet, n (%)Not meet, n (%)

Exclusive breastfeeding for the first six monthsYes115 (33.3)50 (41.3)65 (29)0.021
No230 (66.7)71 (58.7)159 (71)

Food taboo for childrenYes14 (4.1)2 (1.7)12 (5.4)0.096
No331 (95.9)119 (98.3)212 (94.6)

Minimum meal frequency (MMF)Meet185 (53.6)67 (55.4)118 (52.7)0.632
Not meet160 (46.4)54 (44.6)106 (47.3)

Minimum acceptable diet (MAD)Meet67 (19.4)67 (55.4)0 (0)<0.0001
Not meet278 (80.6)54 (44.6)224 (100)

Immunization status of the child (at least one type)Yes170 (49.3)62 (51.3)108 (48.2)0.592
No175 (50.7)59 (47.7)116 (51.8)

Birth order of the child≤3174 (50.4)71 (58.7)103 (46)0.047
4–593 (22.6)24 (19.8)69 (30.8)
≥678 (27)26 (21.5)52 (23.2)

Any type of food which is strictly prohibited for children either culturally or religiously. The order of the index childbirth from all successive births.
3.4. Percentage of Weekly Food Groups’ Consumption

All of the children consumed cereals for one week before the survey. But only 35.9% of them consumed flesh foods. Children meeting the dietary diversity score was 35.1% (Figure 1).

3.5. Infant and Young Child Feeding Practice

Among all children, only 19.4% of them met the minimum acceptable diet (Figure 2).

3.6. Factors Associated with Minimum Child Dietary Diversity Score of Children

Child dietary diversity score had no significant association with place of delivery, birth order, maternal residence, child immunization status, and food taboo (Table 6). Children whose mothers attended formal education were 3.042 times (AOR = 3.042 (1.312–7.052)) more likely to meet the minimum optimal dietary diversity score than children whose mothers not attended secondary and above educational status. Children whose mothers were underweight and/or overweight were 51.2% (AOR = 0.488, 95% CI, (0.259–0.918)) and 68.10% (AOR = 0.319, 95% CI, (0.119–0.855)) less likely to meet the optimum minimum dietary diversity score than children whose mothers were with normal BMI, respectively.


Variables/CategoryMinimum CDDSCOR (95% CI)AOR (95% CI)
Meet (≥4)Not Meet (≤3)

Maternal education status
No formal education74 (61.16)180 (80.36)11
Attended primary16 (13.22)19 (8.48)2.048 (0.999–4.200)1.877 (0.807–4.370)
Secondary and above31 (25.62)25 (11.16)3.016 (1.668–5.454)3.042 (1.312–7.052)

Maternal BMI in (kg/m2) status
Normal19 (15.7)54 (24.11)11
Underweight6 (4.96)26 (11.61)0.528 (0.295–0.946)0.488 (0.259–0.918)
Overweight96 (79.34)144 (64.28)0.346 (0.137–0. 873)0.319 (0.119–0.855)

The variables entered into the model was maternal educational status, maternal marital status, maternal BMI status, number of under-five children at the household, nutrition counseling during antenatal care follow-up, household decision making power, livestock, index child sex, maternal ethnicity, family size, maternal age, child age, and religion.

4. Discussion

In this study, children who met the minimum dietary diversity score were 35.1%, (95% CI: (30%–40%)). This figure is higher than that reported in studies done in Ethiopia such as Arsi Negele district (18.8%) [27], Gorche district (10.6%) [25], and Dangila town (12.6%) [28]. It is also higher than that reported in African countries such as Tanzania (32.58%) and Uganda (29.5%) [30]. But it was lower than those reported in other studies done in Ghana (51.4%) [31], China (63.2%) [32], Indonesia (68.4%) [26], and Kenya (39.06%) [30]. The reason might be due to the difference in the data collection time, awareness creation by health policy systems, media exposure, and community child feeding practice.

This study revealed that maternal nutritional status (BMI) was associated with meeting the minimum dietary diversity score of children. This finding could be explained by the good nutritional status of the mother which might be due to her improved feeding practice, which could be a proxy for her child’s good feeding practice. This might be also influenced by decision making and media exposure [28]. This might be also due to wealth index, place of delivery, maternal age, and maternal employment [30].

Maternal education was found to be associated with meeting the child’s minimum dietary diversity score. This is in line with studies done in Ethiopia such as Dangilla [28] and African countries (Nigeria [33], Kenya, Uganda, and Tanzania [30]), and Asian country, Nepal [34]. This might be explained by the fact that as the mother’s educational level increases, her knowledge, attitude, and practice towards dietary feeding practice might be improved. Also, in addition, as the mother’s educational level increases, she might have antenatal care follow-up and media exposure, by which she could get nutritional counseling and improve her child feeding practice [28, 30].

In conclusion, maternal nutrition status and maternal education status were associated with child dietary diversity scores. This study revealed that children who met the minimum dietary diversity score were few. Therefore, increased emphasis on the importance of the education of girls (future mothers) and nutrition counseling for girls/women who received little education on ways to improve the family and child dietary feeding practice is needed.

Abbreviations

AOR:Adjusted odds ratio
BCG:Bacillus Calmette–Guerin
BMI:Body mass index
CI:Confidence interval
CDDS:Child dietary diversity score
EDHS:Ethiopian Demographic and Health Survey
FAO:Food and Agriculture Organization
MDDS:Minimum dietary diversity score
MMF:Minimum meal frequency
MUAC:Mid-upper arm circumference
SPSS:Statistical Package for Social Science
UNICEF:United Nations Children’s Fund
WHO:World Health Organization.

Data Availability

The datasets analyzed during the current study are available from the corresponding author upon reasonable request.

Ethical Approval

Ethical approval was obtained from the Institutional Review Board of the College of Health Sciences, Mekelle University (protocol approval: ERC-0936/2007). An official letter of support was obtained from Afar Regional Health Bureau, Golina district Health and Administrative Offices. The study objective was explained to parents. Privacy and confidentiality were ensured at all levels. Interview and anthropometric measurements were conducted in a private area and their name was not requested and recorded.

Informed written consent was obtained from study participants. Counseling and linkage to appropriate healthcare and support were given.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

Authors’ Contributions

GFM conceived and designed the study, performed analysis, interpreted the data, and drafted the manuscript. FWF and SA were involved in the analysis and interpretation of the data and critically reviewed the manuscript. All authors read and approved the final manuscript.

Acknowledgments

The authors would like to express their deepest gratitude to Samara University for facilitating this study. Our appreciation also goes to supervisors, data collectors, and study participants.

References

  1. World Health Organization, Global Strategy for Infant and Young Child Feeding, World Health Organization, Geneva, Switzerland, 2003.
  2. World Health Organization, Indicators for Assessing Infant and Young Child Feeding Practices: Part 1: Definitions: Conclusions of a Consensus Meeting Held 6-8 November 2007, World Health Organization, Washington, DC, USA, 2008.
  3. World Health Organization, Indicators for Assessing Infant and Young Child Feeding Practices: Part 2: Measurement, World Health Organization, Geneva, Switzerland, 2010.
  4. G. L. Kennedy, Evaluation of Dietary Diversity Scores for Assessment of Micronutrient Intake and Food Security in Developing Countries, Wageningen University, Wageningen, Netherlands, 2009.
  5. CARE, Young Child Feeding Practices: Collecting and Using Data: A Step-by-Step Guide: Cooperative for Assistance and Relief Everywhere, Inc[CARE], Waltham, MA, USA, 2010.
  6. N. Steyn, J. Nel, G. Nantel, G. Kennedy, and D. Labadarios, “Food variety and dietary diversity scores in children: are they good indicators of dietary adequacy?” Public Health Nutrition, vol. 9, no. 5, pp. 644–650, 2006. View at: Publisher Site | Google Scholar
  7. C. G. Victora, L. Adair, C. Fall et al., “Maternal and child undernutrition: consequences for adult health and human capital,” The Lancet, vol. 371, no. 9609, pp. 340–357, 2008. View at: Publisher Site | Google Scholar
  8. R. E. Black, L. H. Allen, Z. A. Bhutta et al., “Maternal and child undernutrition: global and regional exposures and health consequences,” The Lancet, vol. 371, no. 9608, pp. 243–260, 2008. View at: Publisher Site | Google Scholar
  9. World Health Organization, Global Nutrition Targets 2025: Stunting Policy Brief, World Health Organization, Geneva, Switzerland, 2014.
  10. L. H. Allen and S. R. Gillespie, What Works? A Review of the Efficacy and Effectiveness of Nutrition Interventions, Asian Development Bank, Mandaluyong, Philippines, 2001.
  11. K. Von Grebmer, J. Bernstein, D. Nabarro et al., Global Hunger Index: Getting to Zero Hunger, International Food Policy Research Institute, Washington, DC, USA, 2016.
  12. S. Horton, M. Shekar, and M. Ajay, Scaling up Nutrition: What Will it Cost? The World Bank, Washington, DC, USA, 2009.
  13. World Health Organization, “Accelerating nutrition improvements (ani): mapping of stakeholders and nutrition actions,” in Three Scaling-Up Countries in Sub-saharan Africa: Report of a Meeting, pp. 27-28, World Health Organization, Addis Ababa, Ethiopia, 2014. View at: Google Scholar
  14. R. Shrimpton, L. M. du Plessis, H. Delisle et al., “Public health nutrition capacity: assuring the quality of workforce preparation for scaling up nutrition programmes,” Public Health Nutrition, vol. 19, no. 11, pp. 2090–2100, 2016. View at: Publisher Site | Google Scholar
  15. K. W. Robert, T. M. Parris, and A. A. Leiserowitz, “What is sustainable development? Goals, indicators, values, and practice,” Environment: Science and Policy for Sustainable Development, vol. 47, no. 3, pp. 8–21, 2005. View at: Publisher Site | Google Scholar
  16. S. S. Lim, K. Allen, Z. A. Bhutta et al., “Measuring the health-related sustainable development goals in 188 countries: a baseline analysis from the global burden of disease study 2015,” The Lancet, vol. 388, no. 10053, pp. 1813–1850, 2016. View at: Google Scholar
  17. D. Griggs, M. Stafford-Smith, O. Gaffney et al., “Sustainable development goals for people and planet,” Nature, vol. 495, no. 7441, pp. 305–307, 2013. View at: Publisher Site | Google Scholar
  18. Central Statistical Agency, National Nutrition Program 2016–2020, Federal Democratic Republic of Ethiopia, Ethiopia, 2015.
  19. Federal Democratic Republic of Ethiopia, Ministry of Health. Health Sector Transformation Plan (2015/16–2019/20), Federal Democratic Republic of Ethiopia, Ethiopia, 2015.
  20. H. Wang, R. Tesfaye, G. NV Ramana, and C. T. Chekagn, Ethiopia Health Extension Program: An Institutionalized Community Approach for Universal Health Coverage, The World Bank, Washington, DC, USA, 2016.
  21. Ethiopian Public Health Institute, An Evidence Informed Policy Brief; Reducing Stunting in Ethiopia: “From Promise to Impact”, Ethiopian Public Health Institute, Addis Ababa, Ethiopia, 2019.
  22. Ethiopian Ministory of Health, Seqota Declaration Implementation Plan (2016–2030): Summary Program Approach Document, Ethiopian Ministory of Health, Ethiopia, 2016.
  23. Central Statistical Agency, Ethiopian Demographic and Health Survey, Federal Democratic Republic of Ethiopia, Ethiopia, 2016.
  24. Federal Democratic Republic of Ethiopia, Population Census Commission. Summary and Statistical Report of the 2007 Population and Housing Census, Central Statistics Agency, Addis Ababa, Ethiopia, 2008.
  25. D. Dangura and S. Gebremedhin, “Dietary diversity and associated factors among children 6–23 months of age in Gorche district, Southern Ethiopia: cross-sectional study,” BMC Pediatrics, vol. 17, no. 1, p. 6, 2017. View at: Publisher Site | Google Scholar
  26. C. S. Ng, M. J. Dibley, and K. E. Agho, “Complementary feeding indicators and determinants of poor feeding practices in Indonesia: a secondary analysis of 2007 demographic and health survey data,” Public Health Nutrition, vol. 15, no. 5, pp. 827–839, 2012. View at: Publisher Site | Google Scholar
  27. T. Kassa, B. Meshesha, Y. Haji, and J. Ebrahim, “Appropriate complementary feeding practices and associated factors among mothers of children age 6–23 months in Southern Ethiopia,” BMC Pediatrics, vol. 16, no. 1, p. 31, 2016. View at: Publisher Site | Google Scholar
  28. M. Beyene, A. G. Worku, and M. M. Wassie, “Dietary diversity, meal frequency and associated factors among infant and young children in Northwest Ethiopia: a cross- sectional study,” BMC Public Health, vol. 15, no. 1, p. 1007, 2015. View at: Publisher Site | Google Scholar
  29. V. Khanal, K. Sauer, and Y. Zhao, “Determinants of complementary feeding practices among Nepalese children aged 6–23 months: findings from Demographic and Health Survey 2011,” BMC Pediatrics, vol. 13, no. 1, p. 31, 2013. View at: Publisher Site | Google Scholar
  30. C. A. Gewa and T. F. Leslie, “Distribution and determinants of young child feeding practices in the East African region: demographic health survey data analysis from 2008–2011,” Journal of Health, Population, and Nutrition, vol. 34, no. 1, p. 6, 2015. View at: Publisher Site | Google Scholar
  31. A. I. Issaka, K. E. Agho, P. Burns, A. Page, and M. J. Dibley, “Determinants of inadequate complementary feeding practices among children aged 6–23 months in Ghana,” Public Health Nutrition, vol. 18, no. 4, pp. 669–678, 2015. View at: Publisher Site | Google Scholar
  32. D. B. Hipgrave, X. Fu, H. Zhou et al., “Poor complementary feeding practices and high anaemia prevalence among infants and young children in rural central and western China,” European Journal of Clinical Nutrition, vol. 68, no. 8, pp. 916–924, 2014. View at: Publisher Site | Google Scholar
  33. F. A. Ogbo, P. Ogeleka, and A. O. Awosemo, “Trends and determinants of complementary feeding practices in Tanzania, 2004–2016,” Tropical Medicine and Health, vol. 46, p. 40, 2018. View at: Publisher Site | Google Scholar
  34. K. P. Gautam, M. Adhikari, R. B. Khatri, and M. D. Devkota, “Determinants of infant and young child feeding practices in Rupandehi, Nepal,” BMC Research Notes, vol. 9, no. 1, p. 35, 2016. View at: Publisher Site | Google Scholar

Copyright © 2020 Getahun Fentaw Mulaw et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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