Skip to main content
Advertisement
  • Loading metrics

Diversified dietary intake and associated factors among pregnant mothers attending antenatal care follow-up in public health facilities of Dire Dawa, Eastern Ethiopia

  • Efrata Nigussie,

    Roles Conceptualization, Formal analysis, Methodology, Validation, Writing – original draft, Writing – review & editing

    Affiliation Public Health Expert at Ohio State Global One Health initiative, Dire Dawa City Administration, Dire Dawa, Ethiopia

  • Abebe Ferede,

    Roles Supervision, Validation, Writing – review & editing

    Affiliation Department of Public Health, School of Health Science, Arsi University, Asella, Ethiopia

  • Melese Markos

    Roles Conceptualization, Formal analysis, Supervision, Validation, Writing – original draft, Writing – review & editing

    melesemarkos@gmail.com

    Affiliation Department of Public Health, College of Health and Medical Science, Wachemo University Durame Campus, Durame, Ethiopia

Abstract

Poor diversity dietary intake has great significance to women, pregnancy outcome and on her fetus or the growing and development of their baby collectively. Uncertainty of studies to examine whether pregnant women have been utilizing diversity dietary in their frequent intake and this has changed nutritional status. Therefore, this study aims to assess diversified dietary intake and associated factors among pregnant mothers attending antenatal care follow-up in public health facilities of Dire Dawa, Eastern Ethiopia. A facility-based cross-sectional study was conducted among 453 pregnant mothers randomly selected from the antenatal care unit at public health facilities from November 1-30/2020. Study subjects were selected with a systematic random sampling method from randomly selected antenatal care unity of health facilities in Dire Dawa Administration. A structured questionnaire and anthropometric measurements were used to collect data. Data were entered with kobo software and exported to Statistical Package for Social Science statistical software version 20 for analysis. Binary and multiple logistic regression models were used to declare the significance of independent variables at P<0.05. This study shows 55% (95% CI = (50–59.5) were inadequate diversified dietary intake. Having lower monthly income (Adjusted Odds Raito [AOR] = 4.4, Confident interval [95%CI] = 1.3–14.6), elementary educational status of mothers (AOR = 3.8, 95%CI = 1.5–9.9), consumption of two meals per day (AOR = 16.6, 95% CI = 2.04–135.8), didn’t get antenatal care counseling (AOR = 2.2, 95% CI = 1.1–2.8) were significantly associated with diversified dietary. The result revealed that around 55% of respondents had inadequate dietary diversity. low household income, had less maternal education level and, consuming two meals per day, and no information about dietary diversity has contributed to inadequate dietary diversity. Accordingly, go forward in the right side of those variables were the core recommendation of this study.

Background

Dietary Diversity is the feeding of an adequate variety of food groups. Sufficient maternal nutrition throughout the “first 1,000 days” window is mostly critical throughout a woman’s pregnancy through to the child’s second birthday. Improving the nutritional status of the woman before and during pregnancy can reduce the risk of adverse birth outcomes, such as low birth weight and pre-term birth [13].

A Diversified Dietary is one of the greatest strategies extremely suggested among pregnant women, which is associated with enriched diet competence through improved food groups in daily diet. Dietary diversity takes been defined as the number of diverse food groups that are consumed over a definite reference period [46]. Good maternal nutrition is significant to health and growth. Nutrition throughout pregnancy is different from the non-pregnant state; sufficient dietary feeding during pregnancy is needed to suitable birth outcomes and good health for the mother [710].

Pregnancy requests a good diet that contains a sufficient intake of energy, protein, vitamins, and minerals to meet maternal and fetal desires. In Poor countries in sub-Saharan Africa, south-central, and Southeast Asia, maternal undernutrition is highly prevalent and has poor perinatal outcomes [11].

A pregnant woman with advanced dietary diversity makes definite the adequacy of dietary diversity for their children and families. Inadequate dietary diversity at the individual, household, and community levels, or any combination of these, may be influence factors to poor nutrition status which is an intergenerational cycle of malnutrition [12]. Day-to-day calorie consumption among pregnant women is made-up to be about 1,800 calories per day during the first trimester, 2,200 calories per day during the second trimester, and 2,400 calories per day during the third trimester [13].

Globally, around 2 billion people, most women and young children, are affected, by micronutrient deficiencies, with even higher rates during pregnancy [14]. Nearly all (99%) of maternal deaths annually occur in developing countries [15].

About 870 million people are probable to be underweight around the world. Out of these, 852 million were in developing countries [16]. In further, 3.5 million women and children aged under five in developing countries die each year due to the underlying cause of undernutrition. Around 800 pregnant women die every day during pregnancy and childbirth and 8,000 newborn babes die within the first month of life in developing countries [12]. Inadequate dietary intake may lead to low birth weight, stillbirth, the premature rupture of membrane, intrauterine growth restriction, intrauterine fetal death, and congenital anomalies and affect later on sudden infant death syndrome, developmental impairment, malnutrition, and threat for chronic disease [1719]. Universally, mortality and morbidity due to undernourishment have not meaningfully changed over the last 30 years, to advance it, the dietary diversification status of pregnant women needs to sustainably improve through addressing evidence and reduction of obstacles of obedience [20].

Poor diversified dietary consumption during pregnancy is an important contributor to international maternal malnutrition in less developed countries. A previous review showed that pregnant women in developing countries suffer from energy insufficiencies due to relatively insufficient energy intake. Besides, 42% of pregnant mothers globally and more than 50% of pregnant mothers in developing countries are anemic, mainly due to iron deficiency [21, 22].

In Africa alone, 20% of women are underweight, Even however dietary diversification is significant for the health of the mother and the fetus in Ethiopia, 22% of women are thin due to inadequate diet diversity (vegetables and fruits), and fluctuating regimes [23]. Still, a high problem of maternal malnutrition due to diversified diets are mostly based on starchy foods with slight or no animal products and few fresh fruits and vegetables [24]. Studies were done in different parts of the Africa region, Kenya and Ghana shows that 43.9% and 74.5% of women get minimum dietary diversity score (MDDS) respectively, and also mean dietary iron intake from 3.8 to 97.8 mg/d and 34–100% of the women’s reproductive age (WRA) in Kenya, Nigeria, and South Africa had inadequate intakes) [2527].

In Ethiopia, Iron consumption is described to be high (47–97.8 mg/d) and only 8–12% of the women’s reproductive age (WRA) had inadequate intake. Mean dietary vitamin A intake reached from 71 to 2477 μg/d, and 3–100% had inadequate intake. Mean dietary zinc intake from 3.8–16.2 mg/d and 23–96% had inadequate intake in Ethiopia [27]. Organs are being designed, and the fetus develops at an enormously rapid rate, this all leads to improved nutrient needs that want the pregnant women to grow both the diversity and the total of foods consumed [28]. Ethiopia’s administration launched the National Nutrition Program and prioritized interventions like, Stimulate maternal nutrition containing adequate intake of diversified foods to develop the nutritional status of women. The application of the above strategy, thinness, and different micronutrient deficiencies are common problems during pregnancy [23, 29].

A cross-sectional study was done in Dire Dawa 2017, Dietary diversity and nutritional status of pregnant women attending a public hospital, high undernourished and low diversified dietary of pregnant women were found [30]. However, there is little known about the relationship between dietary diversity and associated factors among pregnant mothers in Eastern Ethiopia, particularly this study assesses the impact of health service utilization, maternal illness, and meal frequency on diversified dietary intake of pregnant mothers. Therefore, this study aims to assess dietary diversity and associated factors among pregnant mothers both in urban and rural public health facilities in Dire Dawa.

Methods and materials

Study setting, design, and population

The facility-based cross-sectional study design was conducted in Dire Dawa city administration from November 1-30/2020. Dire Dawa is one the administrative city, which is 515 km far from Addis Ababa, a capital city. Dire Dawa’s 2020 population is now estimated at 408,096 and the annual growth of the population was 4.37%. There are two governmental hospitals, four private hospitals, five higher clinics, twelve medium clinics (Private), fifteen health centers, and thirty-four health posts with 100% health service coverage. All public health facilities give Antenatal care. The total number of pregnant mothers come to public health on ANC Follow up in a single month 1256.

The population of the study

All pregnant mothers attending antenatal care at public health facilities of Dire Dawa from 12 weeks gestational age, were the source population and those pregnant mothers who were selected among Antenatal care follow-up from selected public health facilities during the data collection time were the study population.

All pregnant mothers attending antenatal care at the selected facility were included in this study.

During the collecting time, the pregnant mother’s ill and/or difficulty communicating was excluded.

Sample size determination

The required sample size was determined by using a single population proportion formula with the following assumptions: With a 95% confidence interval (CI) reported prevalence from a similar study had been conducted in the study area 57%) (31) With 5% precision and 10% non-response rate was used. The final sample size for the study was the final sample size with a single population proportion formula is 453. For factors associated with diversified dietary intake the sample size using Epi-info software imperial statistics like odd ration, the proportion of exposed and unexposed with diversified dietary intake and power of 80%, with the ratio of exposed to unexposed 1:1 and 5% level of significance. Finally, the sample size for the second objective, which is calculated for the associated factors For Diversified Dietary intake, is less than the first objective. Therefore, the sample size of the first objective is taken as the final sample size, which is 453.

Sampling techniques

From seventeen public health facilities in the Dire Dawa administration stratified by urban and rural strata, by using simple random technique 8 public health facilities (i.e. 4 from urban and 4 from rural) were selected.

The calculated sample size (453) is proportionally allocated to the selected public health facility based on their average number of client flows (client load). Participants in each facility were selected by using a systematic sampling technique after calculating the sampling interval (K) for each facility. To determine whom to be included in our sample we use systematic random sampling then calculate for constant ‘K’ by dividing the total client flow of required public health facilities in 15 days by our required sample size in that facility and the first sample was selected by lottery method between 1 and K, then every K interval value was selected to get required sample size from each public health facility during the required period.

Data collection tools, techniques, and personnel

Data were collected by interview administered methods using a Structured and pre-tested questionnaires and anthropometric measurement. The quantitative data collection questionnaire has four components: socio-demographic characteristics, Health service factors, and maternal factors. Parts of the questionnaire on the Individual Dietary Diversity Scale (IDDS) were assessed by using a standard questioner developed by Food and Nutrition Technical Assistant (FANTA) [2]. Eight clinical nurses experienced in data collection were recruited as data collectors. The training was given by (PI) to data collectors and supervisors for three days about the objective and methodology of the research on basic skills of anthropometric, interview techniques, data recording, ways of obtaining consent, and on how to maintain confidentiality of information.

Precautions made to limit exposer to COVID-19 during data collocation

The data collectors were a trend and updated on the current situation of COVID-19 along with precautions that must be implemented during the data collection. The data collectors were provided with personal protective tools (face mask, glove, and sanitizer hand rub) and a proper time and calendar were developed to limit crowding during data collection with other data collectors at the site.

Variables

Dependent variable.

Diversified Dietary intake

Independent variable.

Sociodemographic; residence, family size, monthly income, husband educational level, husband occupation. Health service factors; the number of ANC visits, Counseling in this facility. Maternal factors; experience of illness. Dietary Factor; meal frequency

Operational definitions and measurements

Dietary diversity.

Number of individual food groups consumed over 24 hours, inadequate dietary diversity:—When individuals consume less than five food groups, Adequate dietary diversity:—When individuals consume greater than five food groups [2].

Meal frequency.

Pregnant mothers eating a meal more than 3times per day had adequate meal frequency and less than 3 times inadequate meal frequency [31].

Maternal nutritional status.

MUAC categorized as undernutrition (MUAC < 23) and normal (MUAC ≥ 23) [32].

Data processing and data analysis

Data were cleaned and checked by Kobo tool data and it was exported to SPSS version 20 for analysis. Frequency distribution and percentages were computed to describe socio-demographic and other characteristics of respondents and presented in tables and figures. To identify factors associated with Diversified Dietary Intake, binary logistic regression analysis was carried out at two levels, first bivariate logistic regression was performed on each independent variable with the outcome variable, and those variables with a p-value < 0.25 were included in the final model (multivariate analysis). The strength of association was measured using the odds ratio, and 95% confidence intervals. Statistical significance was declared at P-value <0.05. Hosmer and Lemeshow goodness of fit (p-value above) was used to show model fitness in stepwise backward regression analysis. For qualitative data, the narrative data was interpreted and described.

In this analysis, dietary diversity scores were calculated by summing up the number of food groups consumed over 24 hours by the women. The scores greater than or equal to 5 were coded as adequate dietary diversity scores and inadequate dietary diversity otherwise (FHI/FAO/FANTA, 2016) [2]. The women with Mid Upper Arm Circumference (MUAC) less than 23cm were categorized as wasted, based on previous studies.

Data quality assurance

To maintain consistency, the questionnaire was first translated from English to the local language (Afan-Oromo, somaligna, and Amharic) the native language of the study area, and was back-translated to the English language by professional translators. To evaluate the acceptability and applicability of the procedures and tools a pre-test was administered on 5% of the sample in Gende Gerada health center. Finally, unclear questions were modified before the data collection. To keep completeness and consistency, data collectors were closely supervised before and during the data collection process by the supervisor.

Ethical considerations

Ethical clearance was obtained from Research Ethical Review Committee of Dire Dawa University, college of medicine and health science. Then, to get the required support, a formal letter was written from the college of medicine and health science to the Dire Dawa administrative health bureau. An informed voluntary, written, and signed consent was obtained from all subjects for their participation after the nature of the study is fully explained to them in their local languages. A thumbprint or signature was used on the consent form. Those who are signed written consent were only participants in the study and confidentiality of response was maintained throughout the research process by giving code for the participant. The entire study participants were informed that data was kept private and confidential and used only for research purposes. The participants were also assured that they have the right to refuse or withdraw if they are not comfortable at any time. Personal privacy and cultural norms were respected.

Result

Socio-demographic characteristics

Out of 453 pregnant mothers, 448 of them provided a complete response to the questionnaire marking the response rate of 98.9%. The mean age with a standard deviation of study participants was 27.7 ± 5.01SD and above half of them, 282 (62.9%) were within the age group of 20–29 years. The majority of the participant were urban 289 (64.5%) and educational status, most respondents 124(27.7%) had High and preparatory school. Concerning the respondent’s occupation, 273(60.9%) were housewives. Of the total, 150(33.5%) of husbands education had college and above. Out of the total, 178(39.7%) pregnant mothers monthly income had greater than 3000ETB, 145(32.4%) between 2100-3000ETB (Table 1).

thumbnail
Table 1. Socio-demographic characteristics of pregnant mothers attending antenatal care at public health facilities in Dire Dawa, Eastern Ethiopia, 2020.

https://doi.org/10.1371/journal.pgph.0000002.t001

Maternal and health service factors

Out of 448 participants three fourth 346 (77.2%) of them were no illness in the past four weeks, 160 (35.7%) of respondents there is no counseling about diversified dietary intake, and a majority of 259 (57.8%) of participants reported that they consumed three times meals per day (Table 2).

thumbnail
Table 2. Maternal and health service factors of a pregnant mother attending antenatal care at public health facilities in Dire Dawa, Eastern Ethiopia, 2020.

https://doi.org/10.1371/journal.pgph.0000002.t002

While concerning antenatal care practice, 51(11.4%) of a pregnant mother had one ANC visit, 162 (36.2%) had two visits, 175(39.1%) had three visits and 60 (13.4%) of pregnant women had four visit. (Fig 1)

thumbnail
Fig 1. Number of ANC Visit illness for dietary y diversity among pregnant mother attending antenatal care in public health facilities in Dire Dawa, 2020.

https://doi.org/10.1371/journal.pgph.0000002.g001

Nutritional status among pregnant mothers

The mean and standard deviation MUAC of the respondent was 25.4cm ±3.5SD cm. Out of the pregnant mothers, 133(29.7%) of them were under nutritional and 315(70.3%) were having normal nutritional status.

Dietary intake among pregnant mother

In this study about 245 (55%); 95%CI: (50, 59.6) pregnant mothers had Inadequate Dietary Diversity and 203(45%); 95%CI: (40.4, 50) pregnant mothers had Adequate Dietary Diversity practice which is recommended by FAO 2016 (> = five food groups) (Fig 2). The most commonly consumed food groups were other vegetables 440(98%) followed by grains 381(85%) and dark green leafy vegetables 222(50%) (Fig 3).

thumbnail
Fig 2. Diversified dietary score of pregnant mother in public health facilities in Dire Dawa, 2020.

https://doi.org/10.1371/journal.pgph.0000002.g002

thumbnail
Fig 3. Food groups consumption patterns of pregnant mother in public health facilities in Dire Dawa, 2020.

https://doi.org/10.1371/journal.pgph.0000002.g003

Factors associated with diversified dietary intake pregnant mother

The association of outcome variable (Diversified Dietary Intake) and independent variables was assessed using both bivariate and multivariate logistic regression. Accordingly; bivariate analysis revealed that out of fourteen explanatory variables only nine variables such as- educational status, maternal occupation, husband education and occupation, family size, monthly income, meal frequency, information about dietary diversity and MUAC had a statistical association with pregnant mother diversified dietary intake (P-value <0.25) whereas residence, religion, age, past illness of mothers and ANC visit were not significantly associated and excluded from further analysis (Table 3).

thumbnail
Table 3. Bivariate analysis of factors associated with diversified dietary intake of a pregnant mother attending antenatal care in public health facilities in Dire Dawa, Eastern Ethiopia, 2020.

https://doi.org/10.1371/journal.pgph.0000002.t003

After bivariate analysis; those variables showing significant association were entered into multivariate logistic regression in order to rule out the effect of confounding variables. As a result four of contributing factors such as, Household monthly income, maternal education, information about dietary diversity, and meal frequency were the variables that were significantly associated with diversified dietary intake (P-value <0.05).

In this study, pregnant Mothers who had elementary education were almost 3.8 times more likely to have inadequate dietary diversity as compared to those who had college and above education (AOR = 3.8, 95% CI:1.5, 9.9). Concerning family monthly income; those who had an estimated monthly income of less than 1000ETB had 4.4 times more likely an increase the chance of inadequate dietary diversity as compared to those who had an estimated monthly income of greater than 3000ETB (AOR = 4.4, 95% CI: 1.3, 14.6) and also those who had an estimated monthly income of 1100-2000ETTB increase the likelihood of attaining inadequate dietary diversity by 2.7 times as compared to those who had an estimated monthly income greater than 3000ETB (AOR = 2.7, 95% CI:1.3, 5.5).

This study also showed that pregnant mothers who had not exposure of dietary diversity information were 2.2 times more likely having inadequate dietary diversity as compared to those who were the exposure of dietary diversity information (AOR = 2.2, 95% CI:1.1, 2.8). Furthermore; those pregnant mothers who had two meals per day were 16.6 times more likely to have inadequate dietary diversity as compared to those who had greater than four meals per day (AOR = 16.6, 95% CI:2.04,135.8) (Table 4).

thumbnail
Table 4. Multivariate analysis of factors associated with diversified dietary intake of a pregnant mother attending antenatal care in public health facilities in Dire Dawa, Eastern Ethiopia, 2020.

https://doi.org/10.1371/journal.pgph.0000002.t004

Discussion

This study found that about 55% of a pregnant mothers were inadequate dietary diversity (< 5 food groups) while 45% of them were adequate dietary diversity (> = 5 food groups). The finding of this study was lower as compared to the inadequate dietary diversity in which pregnant mothers should consume 57% study done in Dire Dawa 2016, [30], 59.6% in Gambela [33], 73% in Mekele [34], and 56.4% in Axum Northern Ethiopia [35]. And also this finding was higher as compared to inadequate dietary diversity in which pregnant mothers should consume study conducted in Pakistan 2014, 11% [22], 25.6% in Nepal 2016 [36], 37% in Bangladesh 2015 [37], 22.7% in Malaysia 2015 [38], 39% in Laikipia, Kenya 2016 [39], 25.4% in Shashemene 2017 [40] and 38.8% in Alamata 2017 [31]. The possible reason for this great discrepancy may be due to differences with respect to socio-demographic, socio-economic health characteristics of the population, and sample size variation. Many studies also used the nine or fourteen food groups, and those consumed four or more food groups of the fourteen food groups were considered as they achieved diversified dietary intake which result from high proportion of diet diversity.

When comparing individual food group consumption patterns, grain, other vegetables, and dark green leafy vegetables are the commonest consumption in the study area due to being easily available and cheapest for other food groups. In the particular conception of the animal sources of food such as dairy products, egg, meat, and fish were observed among some number of participants. This is also because of seasonal variability since a dairy products like milk and milk products are accessible in the study area and the practice of eating meat and fish was mostly oriented towards the celebration of religious holidays, marriage ceremony and other social welfares.

Maternal education, Monthly income, Meal frequency, and information about dietary diversity are significantly associated with dietary diversity intake.

Pregnant mothers who had elementary education were almost 4 times more likely to have inadequate dietary diversity as compared to those who had college and above education. This is in line with a study done in rural Bangladesh 2015 [37], southwest Bangladesh 2016 [41], Bangladesh 2013 [42], Kenya 2016 [39], Alamata [31], and Hossana, Ethiopia, [43], Tigray Ethiopia [44]. The reason behind here is because the most educated pregnant mother had good food choices due to knowledge about the importance of food and were more likely to understand educational messages transfer through different media channels and also a pregnant mothers who had education have greater awareness about how to utilize available resources for the improvement of their diet quality.

Family income was significantly associated with pregnant mother dietary diversity. As a result, the study revealed those who had a monthly income of less than 1000ETB had 4.4 times more likely an increase in the chance of inadequate dietary diversity as compared to those who had a monthly income of greater than 3000 ETB. This result is supported by different studies conducted in India [45], Ahvaz-Iran [7], Shashemene 2017 [40]. As income levels decreased, the chance of pregnant mothers being inadequate in dietary diversity was high [46]. The possible reason behind here is income and the prices of foods determine food access. Mothers with higher income have the purchase power to afford foods from the market even not available at home.

In this study, pregnant mothers who had two meals per day was 16.6 times more likely to have inadequate dietary diversity as compared to those who had greater than four meals per day. This finding is in line with the other studies conducted in Hossana [43], Alamata [31], and Bale, Ethiopia, [47]. This might be related to their opportunity of having greater than two meals may have the chance of consuming different categories of food group.

This study also showed that pregnant mothers who had not the exposure of dietary diversity information were 2.2 times more likely to have inadequate dietary diversity as compared to those who were the exposure to dietary diversity information. This finding is in line with studies carried out Hossana town south Ethiopia [48], in Jijiga town [49], in Guto Gida Woreda, East Wollega, and Central Gonder [50, 51]. This is since those who had exposure to dietary diversity have better knowledge about the importance of a diversified diets to maintain proper health and pregnancy outcomes.

This study may have certain limitations like due to the cross-sectional design this study cannot make the cause and effect relationship between different factors with the outcome variable. Besides, this study might not give the exact figure of the dietary diversity practice due to recall bias so the 24-hour dietary recall may not truly represent the usual intake and is also unable to generalize to the population because of the health-facility nature of this study.

Conclusions

This study suggested that around 55% of respondents had inadequate dietary diversity mainly defined by the inclusion of ten food groups. The study showed that pregnant mothers’ educational status, family income, meal frequency, and information about dietary diversity have contributed to low diversified dietary intake. There is a need for enhancing dietary diversity or food groups and promotion of awareness on nutritional benefits especially consumption of at least five food groups for pregnant women. Increase meal frequency and health service utilization. And also support health facilities to train their health professionals especially, health extension workers should provide regular advice to women about the nutritional value of consuming different food groups.

Supporting information

S1 Text. Questionnaire used to assess diversified dietary intake and associated factors among pregnant mothers.

https://doi.org/10.1371/journal.pgph.0000002.s001

(DOCX)

S1 Data. Raw data used in the analysis of diversified dietary intake and associated factors among pregnant mothers.

https://doi.org/10.1371/journal.pgph.0000002.s002

(SAV)

Acknowledgments

We would like to thank Dire Dawa University. Furthermore, I would like to thank the Administrative bodies of Dire Dawa Health bureau for giving information and their full cooperation, and, the study participants for their commitment to respond to questions by Sacrificing their time, data collectors, translators, and data supervisors for their commuted activities.

References

  1. 1. Black R, Victora C, Walker S, Bhutta Z, Christian P, De Onis M, et al. Maternal and child undernutrition and overweight in low-income and middle-income countries. The lancet. 2013;382(9890):427–51. https://pubmed.ncbi.nlm.nih.gov/23746772/ pmid:23746772
  2. 2. FAO; Minimum Dietary Diversity for Women: A Guide for Measurement. Rome 2016. http://www.fao.org/3/i5486e/i5486e.pdf
  3. 3. Haddad L, Achadi E, Bendech M, Ahuja A, Bhatia K, Bhutta Z, et al. The Global Nutrition Report 2014: actions and accountability to accelerate the world’s progress on nutrition. The Journal of nutrition. 2015;145(4):663–71. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5129664/ pmid:25740908
  4. 4. Lee S, Talegawkar S, Merialdi M, Caulfield L. Dietary intakes of women during pregnancy in low-and middle-income countries. Public health nutrition. 2013;16(8):1340–53. pmid:23046556
  5. 5. WHO recommendations on antenatal care for a positive pregnancy experience: World Health Organization; 2016. pmid:28079998.
  6. 6. Luckett B, DeClerck F, Fanzo J, Mundorf A, Rose D. Application of the nutrition functional diversity indicator to assess food system contributions to dietary diversity and sustainable diets of Malawian households. Public Health Nutrition. 2015;18(13):2479–87. pmid:26027595
  7. 7. Vakili M, Abedi P, Sharifi M, Hosseini M. Dietary diversity and its related factors among adolescents: a survey in Ahvaz-Iran. Global journal of health science. 2013;5(2):181. pmid:23445707
  8. 8. Arzoaquoi S, Essuman E, Gbagbo F, Tenkorang E, Soyiri I, Laar A. Motivations for food prohibitions during pregnancy and their enforcement mechanisms in a rural Ghanaian district. Journal of ethnobiology and ethnomedicine. 2015;11(1):59.
  9. 9. Ekwochi U, Osuorah C, Ndu I, Ifediora C, Asinobi I, Eke C. Food taboos and myths in South Eastern Nigeria: The belief and practice of mothers in the region. Journal of ethnobiology and ethnomedicine. 2016;12(1):7. pmid:26818243
  10. 10. UNICEF. A Survival and Development Priority. Tracking Progress on Child and Maternal Nutrition:. New York: UNICEF; 2009.
  11. 11. Tang A, Chung M, Dong K, Terrin N, Edmonds A, Assefa N, et al. Determining a global mid-upper arm circumference cutoff to assess malnutrition in pregnant women. Food and Nutrition Technical Assistance. 2016.
  12. 12. WHO. Good Maternal Nutrition. The Best Start in Life. Europe Copenhagen (Denmark): UN City;: WHO Regional Office for 2016; (2016). https://www.euro.who.int/__data/assets/pdf_file/0008/313667/Good-maternal-nutrition-The-best-start-in-life.pdf
  13. 13. medlineplus. Eating right during pregnancy 2018 [Available from: Eating right during pregnancy: MedlinePlus Medical Encyclopedia https://medlineplus.gov/ency/patientinstructions/000584.htm.
  14. 14. IGNR. Actions and accountability to accelerate the World’s progress on Nutrition. Washington, DC, USA,: International Food Policy Research Institute:; 2014.
  15. 15. organization wh. Women’s health, Available from: https://www.who.int/topics/womens_health/en/.WHO; 2019.
  16. 16. Saaka M. Maternal dietary diversity and infant outcome of pregnant women in Northern Ghana. International Journal of Child Health and Nutrition. 2013;1(2):148–56.
  17. 17. Parets S, Bedient C, Menon R, Smith A. Preterm birth and its long-term effects: methylation to mechanisms. Biology. 2014;3(3):498–513. pmid:25256426
  18. 18. Muthayya S. Maternal nutrition & low birth weight-what is really important. Indian J Med Res. 2009;130(5):600–8. pmid:20090114.
  19. 19. Haider B, Bhutta Z. Multiple‐micronutrient supplementation for women during pregnancy. Cochrane Database of Systematic Reviews. 2017(4). pmid:28407219; PMCID: PMC6478115.
  20. 20. International Food Policy Research Institute. 2016. Global Nutrition Report 2016: From Promise to impact: Ending Malnutrition by 2030. Washington, D.C. http://dx.doi.org/10.2499/9780896295841
  21. 21. World Health Organization. (2016). Guideline: Daily iron supplementation in adult women and adolescent girls. World Health Organization. https://apps.who.int/iris/handle/10665/204761
  22. 22. Ali F, Thaver I, Khan S. Assessment of dietary diversity and nutritional status of pregnant women in Islamabad, Pakistan. Journal of Ayub Medical College Abbottabad. 2014;26(4):506–9. pmid:25672175
  23. 23. CSACaI. Ethiopia Demographic and Health Survey 2016.CSA and ICF;. Addis Abab; 2016. https://dhsprogram.com/pubs/pdf/FR328/FR328.pdf
  24. 24. Ruel M. Operationalizing dietary diversity: a review of measurement issues and research priorities. The Journal of nutrition. 2003;133(11):3911S–26S. pmid:14672290.
  25. 25. Kemunto M. Dietary Diversity and Nutritional Status of Pregnant Women Aged 15–49 Years Attending Kapenguria District Hospital West Pokot County. 2013. https://ir-library.ku.ac.ke/bitstream/handle/123456789/7486/Marita%20Lillian%20Kemunto.pdf?sequence=3
  26. 26. Workicho A, Belachew T, Feyissa G, Wondafrash B, Lachat C, Verstraeten R, et al. Household dietary diversity and Animal Source Food consumption in Ethiopia: evidence from the 2011 Welfare Monitoring Survey. BMC Public Health. 2016;16(1):1192. pmid:27884138
  27. 27. Harika R, Faber M, Samuel F, Kimiywe J, Mulugeta A, Eilander A. Micronutrient status and dietary intake of iron, vitamin A, iodine, folate and zinc in women of reproductive age and pregnant women in Ethiopia, Kenya, Nigeria and South Africa: a systematic review of data from 2005 to 2015. Nutrients. 2017;9(10):1096.
  28. 28. Nnam N. Improving maternal nutrition for better pregnancy outcomes. Proceedings of the Nutrition Society. 2015;74(4):454–9. pmid:26264457.
  29. 29. Ethiopia FDRO. National nutrition program. 2016–2020. https://extranet.who.int/nutrition/gina/sites/default/filesstore/ETH%202016%20National%20Nutrition%20Programme%20II.pdf
  30. 30. Shenka A, Damena M, Abdo M, Roba K. Dietary Diversity and Nutritional Status of Pregnant Women Attending Public Hospitals in Dire Dawa City Administration, Eastern Ethiopia. East African Journal of Health and Biomedical Sciences. 2018;2(1):10–7.
  31. 31. Jemal K, Awol M. Minimum Dietary Diversity Score and Associated Factors among Pregnant Women at Alamata General Hospital, Raya Azebo Zone, Tigray Region, Ethiopia. Journal of nutrition and metabolism. 2019;2019. pmid:31192011
  32. 32. Bye A SJ, Stephenson J, Bick D, Brima N, Micali N., Differences in pre-conception and pregnancy healthy lifestyle advice by maternal BMI: Findings from a cross sectional survey. Midwifery. pmid:27744203. 2016;.
  33. 33. Nigatu M, Gebrehiwot T, Gemeda D. Household food insecurity, low dietary diversity, and early marriage were predictors for Undernutrition among pregnant women residing in Gambella, Ethiopia. Advances in Public Health. 2018.
  34. 34. Tela F, Bezabih A, Adhanu A. Effect of pregnancy weight gain on infant birth weight among mothers attending antenatal care from private clinics in Mekelle City, Northern Ethiopia: A facility based follow-up study. PloS one. 2019;14(3). pmid:30856197
  35. 35. Weldehaweria N, Misgina K, Weldu M, Gebregiorgis Y, Gebrezgi B, Zewdie S, et al. Dietary diversity and related factors among lactating women visiting public health facilities in Aksum town, Tigray, Northern Ethiopia. BMC Nutrition. 2016;2(1):38.
  36. 36. Bhandari S, Sayami J, Thapa P, Sayami M, Kandel B, Banjara M. Dietary intake patterns and nutritional status of women of reproductive age in Nepal: findings from a health survey. Archives of public health. 2016;74(1):1–11. pmid:26823976
  37. 37. Harris-Fry H, Azad K, Kuddus A, Shaha S, Nahar B, Hossen M, et al. Socio-economic determinants of household food security and women’s dietary diversity in rural Bangladesh: a cross-sectional study. Journal of Health, Population and Nutrition. 2015;33(1):1–12. pmid:26825273
  38. 38. Mirsanjari M, Muda W, Ahmad A, Othman MS, Mirsanjari M, editors. Diversity of nutrient intake in pregnant women with different nutritional behaviors. International conference on nutrition and food sciences; 2012.
  39. 39. Kiboi W, Kimiywe J, Chege P. Dietary diversity, nutrient intake and nutritional status among pregnant women in Laikipia County, Kenya. International Journal of Health Sciences & Research. 2016: 6(4); 378–85.
  40. 40. Desta M, Akibu M, Tadese M, Tesfaye M. Dietary Diversity and Associated Factors among Pregnant Women Attending Antenatal Clinic in Shashemane, Oromia, Central Ethiopia: A Cross-Sectional Study. Journal of nutrition and metabolism. 2019. pmid:30993019
  41. 41. Shamim A, Mashreky S, Ferdous T, Tegenfeldt K, Roy S, Rahman A, et al. Pregnant women diet quality and its sociodemographic determinants in southwestern Bangladesh. Food and nutrition bulletin. 2016;37(1):14–26. pmid:27004969.
  42. 42. Nguyen P, Avula R, Ruel M, Saha K, Ali D, Tran L, et al. Maternal and child dietary diversity are associated in Bangladesh, Vietnam, and Ethiopia. The Journal of nutrition. 2013;143(7):1176–83. pmid:23658424.
  43. 43. Degefa Helamo Kobiro R, Beakal Zinab. Determinants of Dietary Diversity among Pregnant Women Attending Public Health Facilities in Hossana town,South Ethiopia. BMC Nutrition. 2018.
  44. 44. Fetene Nega. Assessment on the Outcomes of Promotion of Nutrition Education on Dietary Diversity Among Women’s of Reproductive Age (15–49 Years) and Children Aged 6–36 Month in Tigray Regional State Selected Rural Kebeles: Addis Ababa University; 2018. http://213.55.95.56/handle/123456789/30/browse?type=subject&value=Nutrition+Education
  45. 45. Rammohan A, Goli S, Singh D, Ganguly D, Singh U. Maternal dietary diversity and odds of low birth weight: Empirical findings from India. Women & health. 2019;59(4):375–90. pmid:29920173
  46. 46. Pieters H, Guariso A, Vandeplas A. Conceptual framework for the analysis of the determinants of food and nutrition security. 2013. https://www.wecr.wur.nl/WECRGeneral/FoodSecurePublications/13_Pieters_Guariso_Vandeplas_ConceptualFramework.pdf
  47. 47. Hailu S, Woldemichael B. Dietary diversity and associated factors among pregnant women attending antenatal care at public health facilities in Bale Zone, Southeast Ethiopia. Nutrition and Dietary Supplements. 2019;11:1. DOI https://doi.org/10.2147/NDS.S179265
  48. 48. Delil R, Tamiru D, Zinab B. Dietary Diversity and Its Association with Anemia among Pregnant Women Attending Public Health Facilities in South Ethiopia. Ethiopian journal of health sciences. 2018;28(5). 625–634. pmid:30607078
  49. 49. Ali A. Dietary Diversity and Nutritional Status of Pregnant Women Aged 15–49 Years Attending at Antenatal Care in Karamara Hospital Jigjiga Town, Ethiopia. International Journal of Advanced Scientific Research & Development (IJASRD). 2019;6(08).
  50. 50. Gemeda Daba F, Wondu Garoma and Habtamu Fekadu. Assessment of Nutritional Practices of Pregnant Mothers on Maternal Nutrition and Associated Factors in Guto Gida Woreda, East Wollega Zone, Ethiopia. Science, Technology and Arts Research Journal. 2013.
  51. 51. Mekonen h. Dietary diversity and associated factors among pregnant women in east belessa district, central gondar, ethiopia: community based cross-sectional study 2020.