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Factors associated with dietary diversity among adolescents in Woldia, Northeast Ethiopia

Abstract

Background

Consuming diversified food during the adolescent period is essential to build a healthy and active mind for their later life. Food prices increased in the local market due to fewer production of crops. Thus, exploring the dietary diversity of adolescents in this area is crucial to estimate diet quality. So the aim of the study was to identify determinant factors of dietary diversity.

Methods

An institution-based cross-sectional study was conducted among adolescent students in Woldia town. A total of four hundred eleven students were included in the study. A simple random sampling technique was used to select the participants. The outcome variable was dietary diversity; it was calculated by summing of the number of food group consumed by individuals in the given reference period. Bivariable and multivariable logistic analysis was done. The odds ratio with a 95% confidence interval was computed to measure an association. A variable with a P-value less than 0.05 is considered a significant factor.

Results

The proportion of inadequate dietary diversity was 49.1% (95% CI 44.5–53.8). Being female (AOR =5.53, 95% CI 3.447–8.859), secondary and above mothers’ education level (AOR=0. 27, 95%CI 0.153–0.477), living in a family size five and above (AOR= 2.09, 95CI% 1.31–3.34), and poor knowledge about nutrition (AOR=4.56, 95% CI 2.727–7.639) were significantly associated with inadequate dietary diversity.

Conclusions and recommendations

Inadequate dietary diversity was associated with sex, knowledge of nutrition, maternal education level, and family size. It is better to design a nutrition intervention program that focus on nutrition education to scale up diversified food consumption among adolescents.

Background

Dietary diversity is defined as the simple count of food groups consumed over a given reference period [1]. Individual dietary diversity score is a good predictor for nutrient adequacy [2, 3] and nutritional status [4]. Dietary diversity is an indicator of a balanced diet and normal weight status [5]. Practically dietary diversity can be assessed at an individual or household level, whereas the dietary diversity assessed at the household level is a proxy indicator of food security or insecurity in the family [6].

The adolescent period is a critical age in which nutritional requirement is high due to fast growth and development. Healthy dietary practices during the adolescent period affect the latter life cycle either positively or negatively [7]. Eating habit of adolescents was influenced by multiple factors such as lifestyle, food marketing, media, socioeconomic, and cultural factors [8].

Adolescents who live in the community with low awareness and practice about healthy eating suffered more nutrition-related problems [9]. Besides, adolescents in developing countries do not get enough nutrients due to monotonous dietary dish [10].

In Ethiopia, different scholars intensively identified the determinant factors of dietary diversity among under-five children and pregnant and lactating women, but there is limited research regarding adolescent dietary practices [11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28]. Previous articles conducted in Ethiopia focus on the nutritional status of adolescent either they identify chronic deficiency or overweight/obesity. Dietary diversity was studied as a determinant factor of malnutrition previously in adolescents. But not the factors that influence dietary diversity was not well explored [29,30,31,32,33,34,35,36,37]. Furthermore, the dietary diversity of adolescents was not included and studied in Ethiopia Demographic and Health Survey consecutive reports [38,39,40].

In the majority of the developing countries, assessment of adolescent dietary diversity is not common. Data regarding adolescent nutrition was limited in Ethiopia [10, 41]. North Wollo Zone is part of Ethiopia which is frequently affected by drought; for instance, it was affected by ELINO in 2015/2016. Due to the ELINO drought, food prices were highly increased in Woldia town because of the reduction of crop production in the district around there [42, 43]. The World Health Organization (WHO) and the Food and Agricultural Organization (FAO) recommended dietary diversity assessment during drought season since it is important to know the diet quality of the population clearly [44]. Because of the aforementioned reason, we intend to assess the dietary diversity and its associated factors among adolescents in Woldia Secondary Schools.

Materials and methods

Study design and period

An institution-based cross-sectional study was conducted from February to March 2016 G.c. Woldia is one of the oldest towns in Ethiopia and the center of the North Wollo Zone. It is located 525 km North of Addis Ababa the capital city of Ethiopia and 360 km far from Bahir Dar the capital of Amhara Regional state.

Based on the 2007 National census conducted by the Central Statistical Agency of Ethiopia (CSA), the town has a total population of 46,139, of whom 23,000 are men and 23,139 women. The town has four secondary schools (one preparatory school (grades 11 and 12) and 3 general high schools (grade 9 and 10)). A total of 4298 students attend their education in the 2015/2016 academic year.

Source population and eligibility criteria

All adolescent students who were attending their education in Woldia Secondary Schools in 2015/2016 were considered as source population. Those students who participated in different ceremonies and were ill before a day of the survey were excluded from the study.

Outcome variables: The dietary diversity score was an outcome variable. It was coded as “1” inadequate dietary diversity and “0” as adequate dietary diversity. The dichotomization was based on mean dietary diversity score. That is inadequate DDS (≤4.75) and adequate DDS (>4.75).

Independent variables: sociodemographic characteristics and socioeconomic and behavioral factors.

Sample size determination and sampling technique

Single population proportion formula was done to estimate sample size with the following assumptions N= Zα/22p (1 − p)/d2= (1.96)2*0.5*0.5/0.0025= 384.The assumption is Z = level of confidence (1.96), p = proportion of inadequate dietary diversity was taken as 50%, d=s margin of error (5%), N= sample size, and thorough consideration of 10% non-response rate the final sample size was 422. In Woldia town, there are four secondary schools namely, Selama, Millennium, Woldia General, and Woldia Preparatory Schools which were included as source population. In the four schools, 4298 students attend their education of which 4095 students were adolescents. Then, the student list was collected from the respective school directors and aggregated to one data set. Then the combined student data set list contains information about grade level, school name, section, and students’ identity number. Finally, through a simple random sampling technique, 422 students were selected through openepi random number computer generator.

Data collection tools and procedures

Dietary Diversity Score (DDS) was computed using Food and Agriculture Organizations (FAO) 1-day individual dietary diversity questionnaire. Due to the lack of local food, dietary guidelines in Ethiopia food items were identified through market observation and by collecting hotel meal menus. Around fifty food items were identified and aggregated with the FAO food grouping system. Ten food groups were formed; the formed food groups were cereals, vitamin A-rich vegetables, white roots and tubers, dark green leafy vegetables, other vegetables and fruits, organ and flesh meat, eggs, legumes and seeds, milk and milk products, oils, and fats. To collect the necessary data, semi-structured interview was used. Food item eaten by an individual a day before the interview was recorded in a food group table .Finally, DDS was constructed by counting food groups consumed by adolescents over 24 h [45]. Additionally, sixteen nutritional knowledge questions were adapted from FAO guidelines to measure nutrition-related knowledge, attitudes, and practices [46]. Individuals who responded less than nine nutrition knowledge questions were considered as having poor nutrition knowledge and those who answered ≥9 questions were categorized as having good knowledge. The content of nutritional knowledge question was composed of the cause and prevention mechanism of (iodine deficiency, vitamin A deficiency, iron deficiency anemia, and protein energy malnutrition).

Five Bachelor of Science (BSc.) Nursing students were recruited for data collection. The principal investigator had taken written consent from their parents and was granted their consent for those students whose ages were below 18 years. The list of randomly selected students’ identity number was given to the data collectors. Data collectors introduce themselves and explain the purpose of the study to each study participant. At the end, the data were collected after taking verbal assent from each participant. Nutrition counseling was given for the students to practice diversified dietary habits.

Data quality control

A pretest was performed before the actual data collection in Mersa Town. A 1-day training was given to the data collectors how they can conduct an interview. The questionnaire was initially prepared in English and translated to Amharic version. Double-entry of the data was done by two independent personnel.

Data management and analysis

The data were entered into the Epi-Data version 3.1, cleaned manually, and exported to SPSS (Statistical Package for Social Science) version 20 for analysis. Descriptive statistics were presented using mean, median, standard deviations, interquartile range, and frequency table. Wealth index was analyzed through the principal component analysis (PCA) method and classified as (low, middle, and high).The bivariable and multivariable logistic regression analyses were performed. Finally, adjusted odds ratio with 95% CI was computed and variables having P-value less than 0.05 were considered as significant. The model was fitted with Hosmer and Lemeshow P-value of 0.89.

Results

Socio-demographic characteristics

A total of 411 adolescents were interviewed with a response rate of 97.3%. From 422 randomly selected participants, 11 students were excluded due to the following reasons: 4 students were refusing to participate in the study and 7 students were experiencing illness one day before the interview, which affect usual eating habit.

The median age of the students was 17 years (interquartile range 2) and 279 (67.2%) adolescents were aged 17–19 years. More than two thirds, 296 (72.0%), were Orthodox and 104 (25.3%) were Muslims in religion. Concerning the occupation of the parents, 251 (61.1%) of adolescents’ mothers were housewives and 272 (66.2%) of adolescent’s fathers were private workers.

Regarding the participants’ source of food, 304 (74.0%) got from the market. Fifty percent of adolescents live in a family size of five and above (Table 1).

Table 1 Socio-demographic characteristics of adolescents in Woldia Secondary Schools, Northeast Ethiopia, 2016 (N=411)

Behavioral-related characteristics of adolescents

Among 411 participants, 282 (68.6%) had good knowledge of nutrition and 281 (68.4%) of them did not eat outside home in the last week. Moreover, more than half of them were satisfied with their current body weight and 283 (68.9%) ate their meals with their family members (Table 2).

Table 2 Behavioral-related characteristics of the adolescent in Woldia Secondary Schools, Northeast Ethiopia, 2016 (N=411)

The magnitude of inadequate dietary diversity

The mean dietary diversity score was 4.73 (SD±1. 186) that ranged from 2 to 10 food groups. The proportion of inadequate dietary diversity among adolescents in Woldia Secondary Schools was 49.1% (95% CI 44.5–53.8).

Majority of the participants, 166 (40.4%), consumed four and 125 (30.4%) consumed five food groups computed from the total food category. More than 50% of the adolescent ate cereals, other vegetables and fruits, legumes, oils, and fat food groups. However, vitamin A-rich foods, milk, and eggs were consumed in a small proportion of the adolescents. Animal source food consumed by minor adolescents; 94 (22.9%) took flesh and organ meat, 41 (10.0 %) ate eggs, and 32 (7.8%) consumed milk and its products. Specifically eggs, milk, white root and tubers, green leafy vegetables, and vitamin A source fruits were almost not consumed by adolescents who had inadequate dietary diversity (Table 3).

Table 3 The proportion of food group consumption tabulated with dietary diversity among adolescents in Woldia Secondary Schools, Northeast Ethiopia, 2016 (N=411)

Factors associated with dietary diversity

All variables were entered into multivariable logistic regression model, and out of these, four variables had a significant association with inadequate dietary diversity.

Thus, age, residence, occupations of mother, religion, occupation of father, paternal education, source of food, wealth index, and current body weight satisfaction, eating out practice, and eating companions had no significant association with dietary diversity.

On the contrary, being female, the education level of adolescents’ mother, poor knowledge on nutrition, and living in five and above family size had a significant association with inadequate dietary diversity.

The odds of having inadequate dietary diversity among female was 5.526 times higher than male (AOR=5.53, 95% CI 3.447–8.859).The practice of inadequate dietary diversity was decreased by 73% among adolescents whose mother education level was secondary and above (AOR=0.27, 95% CI 0.153–0.477). The odds of having inadequate dietary diversity among adolescents living in a family size of five and above were 2.09 times higher than adolescents who lived in a family size less than five (AOR=2.092, 95 CI% 1.31–3.34).The odds of inadequate dietary diversity among adolescents who had poor knowledge of nutrition increased by 4.56 times than the adolescents who had good knowledge of nutrition (AOR=4.564, 95% CI 2.727–7.639) (Table 4).

Table 4 Multivariable logistic regression analysis of factors associated with inadequate dietary diversity among adolescents in Woldia Secondary Schools, Northeast Ethiopia, 2016 (N=411)

Discussion

The overall mean dietary diversity score was 4.73 (SD ±1. 186) which ranged from 2 to 10 food groups. The proportion of inadequate dietary diversity among adolescents in Woldia Secondary Schools was 49.1 % (95% CI 44.5–53.8).

The proportion of inadequate dietary diversity among adolescents was 49.1% which is similar to the study carried out in the Amhara region among female adolescents [4], but it is smaller than a study conducted in Jimma 80.5% [47]. Thus, the variation might occur because of the reference period difference to calculate DDS, the number of food groups included in the score, and the study setting.

The current study is higher than a study conducted in Iran among female adolescents 21.3% [48]. The disparity might happen due to socio-economic differences and the presence of food-based dietary guidelines in Iran which promote diversified food consumption.

Meanwhile, the mean DDS of the current study was consistent with a study done in India 5.75 [49], Amhara Region among female adolescents 5.6 [4], Tigray region among female adolescents 3.5 [50], and Bangladesh among adult females 4.28 [51].

On the contrary, the mean DDS of this study was lower than a study conducted in Ahvaz 6.81 [48] and Tehran 6.25 [2]. Possibly the difference could be due to the variation of food groups included and socioeconomic differences among study participants.

In this study, cereals were consumed by all participants; this is similarly reported in a study done in Mozambique [52], Ghana [53], and India [54]. Mostly cereals were produced in the majority area and highly accessible in the market.

Vitamin A-rich fruits and vegetable consumption was 18% which is in line with a study done in Iran 19.98% [48]. Surely, those adolescents with low vitamin A consumption were at risk of other micronutrient deficiency [2]. On the other hand, vitamin A consumption among adolescent girls in this study was lower than a study conducted in Tigray 31.9% [50]. This difference could be variation in the study design and the presence of drought in the current study area which deteriorate cultivation of fruit and vegetables.

In the present study, milk consumption was 7.7% which is lower than the study conducted in India 37.25% [54], 79.2% in Iran [48], and 26.5% in Tigray Region [50]. This variation would be the socio-economic difference between the study participants and lack of animal source foods and water in the study area due to seasonal ELINO drought.

Being female was associated with inadequate dietary diversity. This finding is in line with a study done in Jimma [47] and contradicted to the study done in Iran [2] and Malaysia [55]. Females in Ethiopia are investing their times in food cooking; the smelling of the food might decrease the appetite. Practically women in Ethiopia spent more than 14 h in indoor and outdoor activity, which hampers their normal physiological need specifically daily dietary consumption [56]. Additionally females’ appetites are influenced by hormone secretion and female felt more satisfied easily.

The occurrence of inadequate dietary diversity decreased as the education of the mother increased; it was similarly reported in a study conducted in Nigeria [57] and South Africa [58]. It is true that the educational status of parents influences the dietary habit, food choice, and meal pattern of adolescents [17]. In fact, as the educational status of mothers increased, they have a chance to get information on healthy dietary habit. As a result, they formulate the dietary habit of the adolescent to be diversified [59]. Moreover, as mother’s educational level increases their income will grow and gives a chance to fulfill basic needs properly [56]. Generally, educated mothers can easily change nutrition knowledge to practice in food preparation because home activities and food preparation were covered by females most of the time in the Ethiopia context.

In this study, adolescents having poor knowledge of nutrition were positively associated with inadequate dietary diversity. The current study is supported by studies conducted in Luxembourg [60] and Jimma [47]. This is evidenced that as adolescents’ knowledge about disease increases, they start to take more diversified food [53]. Similarly, an evidence from Greece study revealed that having essential knowledge about food was important to maintain good health [61].

Inadequate dietary diversity among adolescents who live in family size of five and more was 2.05 times higher than adolescents living in family size less than five. The current finding is consistent with study conducted in South Africa [62] and Ethiopia [19]. It is a basic truth that as the number of family members increased, they face the economical insufficiency to meet their family needs. Because of this, they put their time to fulfill the daily needs, rather on diet quality.

Even though the study has several strengths, they had some little limitations. The limitation of this study was it did not address portion size estimation of food eaten by participants because of financial and time constraints. The data was collected through a 24-h dietary recall method which may be prone to recall and social desirability bias.

Conclusion and recommendations

The proportion of inadequate dietary diversity was a significant figure which needs policy attention. Family size, sex, knowledge on nutrition, and education level of the mother were affecting the dietary diversity of adolescents. Animal source foods and fruit/vegetables were the least consumed food groups. In order to break intergenerational cycle of malnutrition, promoting diversified food consumption is a good opportunity, since today adolescents are tomorrow mothers Developing a nutrition education program and establishing a nutrition club in the school will be a better approach to reduce the problem. Moreover, formulating special nutrition education programs for mothers who have low educational status will improve the practice of diversified food consumption.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author based on reasonable request.

References

  1. 1.

    Ruel MT. Is dietary diversity an indicator of food security or dietary quality? a review of measurement issues and research needs. Washington: International Food Policy Research Institute; 2002.

    Google Scholar 

  2. 2.

    Mirmiran P, Azadbakht L, Esmaillzadeh A, Azizi F. Dietary diversity score in adolescents - a good indicator of the nutritional adequacy of diets: Tehran lipid and glucose study. Asia Pac J Clin Nutr. 2004;13(1):56–60.

    CAS  PubMed  Google Scholar 

  3. 3.

    Gina K, Fanou N, Seghieri C, Inge BD. Dietary diversity as a measure of the micronutrient adequacy of women’s diets: results from Bamako. Washington DC: Mali Site; 2009.

    Google Scholar 

  4. 4.

    Wassie MM, Gete AA, Yesuf ME, et al. Predictors of nutritional status of Ethiopian adolescent girls: a community based cross sectional study. BMC Nutr. 2015;1:20. https://doi.org/10.1186/s40795-015-0015-9.

  5. 5.

    Zhao W, Yu K, Tan S, Zheng Y, Zhao A, Wang P, et al. Dietary diversity scores: an indicator of micronutrient inadequacy instead of obesity for Chinese children. BMC Public Health. 2017;17(1):440. https://doi.org/10.1186/s12889-017-4381-x.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  6. 6.

    Hoddinott J, Yisehac Y. Dietary diversity as a food security indicator, FCND discussion papers 136, International Food Policy Research Institute (IFPRI). 2002.

  7. 7.

    Ochola S, Masibo PK. Dietary intake of schoolchildren and adolescents in developing countries. Ann Nutr Metab. 2014;64(Suppl 2):24–40. https://doi.org/10.1159/000365125.

    CAS  Article  PubMed  Google Scholar 

  8. 8.

    World Health Organization. Nutrition in adolescence –issues and challenges for the health sector. Switzerland: WHO; 2005. Contract No.: 92 4 159366 0

    Google Scholar 

  9. 9.

    The Federal Democratic Republic of Ethiopia. National School Health And Nutrition Strategy. Addis Ababa: FDRE; 2012.

    Google Scholar 

  10. 10.

    Ochola S, Masibo PK. Dietary intake of school children and adolescents in developing countries. Ann Nutr Metab. 2014;64(12):24–40. https://doi.org/10.1159/000365125.

    CAS  Article  PubMed  Google Scholar 

  11. 11.

    Kuche D, Moss C, Eshetu S, Ayana G, Salasibew M, Dangour AD, et al. Factors associated with dietary diversity and length-for-age z-score in rural Ethiopian children aged 6-23 months: a novel approach to the analysis of baseline data from the Sustainable Undernutrition Reduction in Ethiopia evaluation. Matern Child Nutr. 2020;16(1):e12852. https://doi.org/10.1111/mcn.12852.

    Article  PubMed  Google Scholar 

  12. 12.

    Aemro M, Mesele M, Birhanu Z, Atenafu A. Dietary diversity and meal frequency practices among infant and young children aged 6-23 months in Ethiopia: a secondary analysis of Ethiopian Demographic and Health Survey 2011. J Nutr Metab. 2013;2013:782931.

    Article  Google Scholar 

  13. 13.

    Ali D, Saha KK, Nguyen PH, Diressie MT, Ruel MT, Menon P, et al. Household food insecurity is associated with higher child undernutrition in Bangladesh, Ethiopia, and Vietnam, but the effect is not mediated by child dietary diversity. J Nutr. 2013;143(12):2015–21. https://doi.org/10.3945/jn.113.175182.

    CAS  Article  PubMed  Google Scholar 

  14. 14.

    Nguyen PH, Avula R, Ruel MT, Saha KK, Ali D, Tran LM, et al. Maternal and child dietary diversity are associated in Bangladesh, Vietnam, and Ethiopia. J Nutr. 2013;143(7):1176–83. https://doi.org/10.3945/jn.112.172247.

    CAS  Article  PubMed  Google Scholar 

  15. 15.

    Beyene M, Worku AG, Wassie MM. Dietary diversity, meal frequency and associated factors among infant and young children in Northwest Ethiopia: a cross- sectional study. BMC Public Health. 2015;15(1):1007. https://doi.org/10.1186/s12889-015-2333-x.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  16. 16.

    Herrador Z, Perez-Formigo J, Sordo L, Gadisa E, Moreno J, Benito A, et al. Low dietary diversity and intake of animal source foods among school aged children in Libo Kemkem and Fogera Districts, Ethiopia. PLoS One. 2015;10(7):):e0133435. https://doi.org/10.1371/journal.pone.0133435.

    CAS  Article  Google Scholar 

  17. 17.

    Bilal SM, Dinant G, Blanco R, Crutzen R, Mulugeta A, Spigt M. The influence of father's child feeding knowledge and practices on children’s dietary diversity: a study in urban and rural districts of Northern Ethiopia, 2013. Matern Child Nutr. 2016;12(3):473–83. https://doi.org/10.1111/mcn.12157.

    Article  PubMed  Google Scholar 

  18. 18.

    Wondafrash M, Huybregts L, Lachat C, Bouckaert KP, Kolsteren P. Dietary diversity predicts dietary quality regardless of season in 6-12-month-old infants in south-west Ethiopia. Public Health Nutr. 2016;19(14):2485–94. https://doi.org/10.1017/S1368980016000525.

    Article  PubMed  Google Scholar 

  19. 19.

    Workicho A, Belachew T, Feyissa GT, 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. https://doi.org/10.1186/s12889-016-3861-8.

    Article  PubMed  PubMed Central  Google Scholar 

  20. 20.

    Zerfu TA, Umeta M, Baye K. Dietary diversity during pregnancy is associated with reduced risk of maternal anemia, preterm delivery, and low birth weight in a prospective cohort study in rural Ethiopia. Am J Clin Nutr. 2016;103(6):1482–8. https://doi.org/10.3945/ajcn.115.116798.

    CAS  Article  PubMed  Google Scholar 

  21. 21.

    Dangura D, Gebremedhin S. Dietary diversity and associated factors among children 6-23 months of age in Gorche district, Southern Ethiopia: Cross-sectional study. BMC Pediatr. 2017;17(1):6. https://doi.org/10.1186/s12887-016-0764-x.

    Article  PubMed  PubMed Central  Google Scholar 

  22. 22.

    Gebremedhin S, Baye K, Bekele T, Tharaney M, Asrat Y, Abebe Y, et al. Predictors of dietary diversity in children ages 6 to 23 mo in largely food-insecure area of South Wollo, Ethiopia. Nutrition. 2017;33:163–8. https://doi.org/10.1016/j.nut.2016.06.002.

    Article  PubMed  Google Scholar 

  23. 23.

    Mekonnen TC, Workie SB, Yimer TM, Mersha WF. Meal frequency and dietary diversity feeding practices among children 6-23 months of age in Wolaita Sodo town, Southern Ethiopia. J Health Popul Nutr. 2017;36(1):18. https://doi.org/10.1186/s41043-017-0097-x.

    Article  PubMed  PubMed Central  Google Scholar 

  24. 24.

    Solomon D, Aderaw Z, Tegegne TK. Minimum dietary diversity and associated factors among children aged 6-23 months in Addis Ababa, Ethiopia. Int J Equity Health. 2017;16(1):181. https://doi.org/10.1186/s12939-017-0680-1.

    Article  PubMed  PubMed Central  Google Scholar 

  25. 25.

    Tegegne M, Sileshi S, Benti T, Teshome M, Woldie H. Factors associated with minimal meal frequency and dietary diversity practices among infants and young children in the predominantly agrarian society of Bale zone, Southeast Ethiopia: a community based cross sectional study. Arch Public Health. 2017;75:53.

    Article  Google Scholar 

  26. 26.

    Boke MM, Geremew AB. Low dietary diversity and associated factors among lactating mothers in Angecha districts, Southern Ethiopia: community based cross-sectional study. BMC Res Notes. 2018;11(1):892. https://doi.org/10.1186/s13104-018-4001-6.

    Article  PubMed  PubMed Central  Google Scholar 

  27. 27.

    Aliwo S, Fentie M, Awoke T, Gizaw Z. Dietary diversity practice and associated factors among pregnant women in North East Ethiopia. BMC Res Notes. 2019;12(1):123. https://doi.org/10.1186/s13104-019-4159-6.

    Article  PubMed  PubMed Central  Google Scholar 

  28. 28.

    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. J Nutr Metab. 2019;2019:3916864.

    Article  Google Scholar 

  29. 29.

    Hadley C, Belachew T, Lindstrom D, Tessema F. The shape of things to come? household dependency ratio and adolescent nutritional status in rural and urban Ethiopia. Am J Phys Anthropol. 2011;144(4):643–52. https://doi.org/10.1002/ajpa.21463.

    Article  PubMed  PubMed Central  Google Scholar 

  30. 30.

    Teji K, Dessie Y, Assebe T, Abdo M. Anaemia and nutritional status of adolescent girls in Babile District, Eastern Ethiopia. Pan Afr Med J. 2016;24:62.

    PubMed  PubMed Central  Google Scholar 

  31. 31.

    Arage G, Assefa M, Worku T. Socio-demographic and economic factors are associated with nutritional status of adolescent school girls in Lay Guyint Woreda, Northwest Ethiopia. SAGE Open Med. 2019;7:2050312119844679.

    PubMed  PubMed Central  Google Scholar 

  32. 32.

    Kahssay M, Mohamed L, Gebre A. Nutritional status of school going adolescent girls in Awash Town, Afar Region, Ethiopia. J Environ Public Health. 2020;2020:7367139.

    Article  Google Scholar 

  33. 33.

    Berheto TM, Mikitie WK, Argaw A. Urban-rural disparities in the nutritional status of school adolescent girls in the Mizan district, south-western Ethiopia. Rural Remote Health. 2015;15(3):3012.

    PubMed  Google Scholar 

  34. 34.

    Melaku YA, Zello GA, Gill TK, Adams RJ, Shi Z. Prevalence and factors associated with stunting and thinness among adolescent students in Northern Ethiopia: a comparison to World Health Organization standards. Arch Public Health. 2015;73(1):44. https://doi.org/10.1186/s13690-015-0093-9.

    Article  PubMed  PubMed Central  Google Scholar 

  35. 35.

    Schott W, Aurino E, Penny ME, Behrman JR. Adolescent mothers’ anthropometrics and grandmothers’ schooling predict infant anthropometrics in Ethiopia, India, Peru, and Vietnam. Ann N Y Acad Sci. 2017.

  36. 36.

    Birru SM, Tariku A, Belew AK. Improved dietary diversity of school adolescent girls in the context of urban Northwest Ethiopia: 2017. Ital J Pediatr. 2018;44(1):48. https://doi.org/10.1186/s13052-018-0490-0.

    Article  PubMed  PubMed Central  Google Scholar 

  37. 37.

    Gebregyorgis T, Tadesse T, Atenafu A. Prevalence of thinness and stunting and associated factors among adolescent school girls in Adwa Town, North Ethiopia. Int J Food Sci. 2016;2016:8323982.

    Article  Google Scholar 

  38. 38.

    Central Statistical Agency (CSA) [Ethiopia], ICF International. Ethiopia Demographic and Health Survey 2011. In: Central Statistical Agency , ICF International, editors. Addis Ababa, Ethiopia Calverton, Maryland, 2012

  39. 39.

    Yisma E, Smithers LG, Lynch JW, Mol BW. Cesarean section in Ethiopia: prevalence and sociodemographic characteristics. J Matern Fetal Neonatal Med. 2019;32(7):1130–5. https://doi.org/10.1080/14767058.2017.1401606.

    Article  PubMed  Google Scholar 

  40. 40.

    EDHS Ethiopia Demographic and Health Survey 2016. Addis Ababa, Ethiopia, and Rockville, Maryland, USA: CSA and ICF. 2016. Report No.: 1471-2458 Contract No.: 1.

  41. 41.

    Save the Children. adolescent nutrition Policy and programming in SUN+ countries. London; 2015.

  42. 42.

    Famine early warning system, Ethiopia food security outlook. October 2015 to March 2016.

  43. 43.

    Watson C, Regassa G, Kassie A. Rapid assessment of organizational capacity for the application of LEGS and the ‘National Guidelines for Livestock Relief Interventions in Pastoralist Areas of Ethiopia’ to inform the El Niño response; March, 2016 Cathy Watson, Genene Regassa and Amanuel Kassie Disclaimer The views expressed in this report are those of the Consultants and do not necessarily reflect the view of USAID or the United States Government.

  44. 44.

    Kennedy G, Ballard T, Claude DM. Guidelines for measuring household and individual dietary diversity. In: Division NaCP, editor. Rome: Food and Agriculture Organization of the United Nations; 2010 p. 9789251067499.

  45. 45.

    Kennedy G, Ballard T, Dop MC. In: Division N, editor. Guidelines for measuring household and individual dietary diversity. Rome: FAO; 2011.

    Google Scholar 

  46. 46.

    Marías YF, Glasauer P. Guidelines for assessing nutrition-related knowledge, attitudes and practices. Rome: Food and Agriculture Organization of the United Nations (FAO); 2014. vi + 180 pp. p.

  47. 47.

    Belachew T, Lindstrom D, Gebremariam A, Hogan D, Lachat C, Huybregts L, et al. Food insecurity, food based coping strategies and suboptimal dietary practices of adolescents in Jimma Zone Southwest Ethiopia. J pone. 2013;8(3):e57643.

    CAS  Google Scholar 

  48. 48.

    Vakili M, Abedi P, Sharifi M, Hosseini M. Dietary diversity and its related factors among adolescents: a survey in Ahvaz-Iran. Global J Health Sci. 2013;5(2):181–6.

    Article  Google Scholar 

  49. 49.

    Mehlawat U. Dietary Diversity Score of college going students (17-21 years) and its association with family income in India. Indian J Nutr Diet. 2015;52(3).

  50. 50.

    Mulugeta A, Tessema M, Sellasie KH, Seid O, Kidane G, Kebede A. Examining means of reaching adolescent girls for iron supplementation in Tigray, Northern Ethiopia. Nutrients. 2015;7(11):9033–45. https://doi.org/10.3390/nu7115449.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  51. 51.

    Nazrul Islam M, Akther F, Sultana S, Nahar Q. Assessment of micro nutritional malnutrition in an urban area of Bangladesh among the adult population onthe basis of individual Dietary Diversity Score (IDDS). Nutr Food Sci. 2015;5(3). https://doi.org/10.4172/2155-9600.1000362.

  52. 52.

    Korkalo L. Hidden hunger in adolescent Mozambican girls: dietary assessment, micronutrient status, and associations between dietary diversity and selected biomarkers. finland: University of Helsinki; 2016.

    Google Scholar 

  53. 53.

    Nti Christina A, Brown A, Danquah A. Adolescents’ knowledge of diet-related chronic diseases and dietary practices in Ghana. Food Nutr Sci. 2012;3:3(1527–1532).

  54. 54.

    Krishna J, Mishra CP, Singh GP Dietary diversity of urban adolescent girls in varanasi. Indian J Prev Soc Med. 2012;43(0301-1216).

  55. 55.

    Rezali FW, Chin YS, Shariff ZM, Yusof BNM, Sanker K, Woon FC. Evaluation of diet quality and its associated factors among adolescents in Kuala Lumpur, Malaysia. Nutr Res Pract. 2015;9(5):511–6. https://doi.org/10.4162/nrp.2015.9.5.511.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  56. 56.

    Tefera B, Pereznieto P, Emirie DG. Transforming the lives of girls and young women Case study: Ethiopia Working paper. 2013. http://www.odi.org/sites/odi.org.uk/files/odi-assets/publications-opinion-files/8820.pdf.

  57. 57.

    Akerele D, Odeiyi K. Demand for diverse diets: evidence from Nigeria, No 204210, 89th Annual Conference, April 13-15, 2015. Coventry: Warwick University, Agricultural Economics Society; 2015.

  58. 58.

    Taruvinga A, Muchenje V, Mushunje A. Determinants-of-rural-household-dietary-diversity-Amatole-and-Nyandeni-districts-South-Africa. Int J Dev Sustain. 2013;2(4).

  59. 59.

    Ambrosini GL, Oddy WH, Robinson M, O'Sullivan TA, Hands BP, de Klerk NH, et al. Adolescent dietary patterns are associated with lifestyle family psycho-social factors. Health Sciences Papers and Journal Articles. 2009;12(10):1807–15.

    Google Scholar 

  60. 60.

    Alkerwi A, Sauvageot N, Malan L, Shivappa N, Hebert JR. Association between nutritional awareness and diet quality: evidence from the observation of cardiovascular risk factors in Luxembourg (ORISCAV-LUX) study. Nutrients. 2015;7(4):2823–38. https://doi.org/10.3390/nu7042823.

    Article  PubMed  PubMed Central  Google Scholar 

  61. 61.

    Bargiota A, Delizona M, Tsitouras A, Georgios KN. Eating habits and factors affecting food choice of adolescents living in rural areas. HORMONES. 2013;12(2):246–53. https://doi.org/10.14310/horm.2002.1408.

    Article  PubMed  Google Scholar 

  62. 62.

    Wynand Grobler CJ Socio economic determinants of household dietary diversity in a low income neighbourhood in South Africa. Proceedings of 30th International Business Research Conference; 20 - 22 April Dubai2015.

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Acknowledgements

First of all, we would like to thank the University of Gondar for providing this chance and the opportunity to carry out this research. We also thank the Woldia education office, school head teachers, and study participants. Lastly, we acknowledge our friends for their continuous emotional and material support.

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Authors

Contributions

MLE designed research proposal, supervised the data collection, analyzed the data, and wrote, edited, and approved the manuscript. GA, BM and BLE participated in the design of the study, performed statistical analysis, and reviewed, edited, and approved the proposal and manuscript.

Corresponding author

Correspondence to Melese Linger Endalifer.

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Ethics approval and consent to participate

The study was conducted as per the Helsinki Declaration for biomedical research. Ethical approval and clearance were obtained from the University of Gondar Institute of public Health Research Ethical Review committee with a reference number of IPH/2849/02/2016. An ethical clearance letter was submitted to the Woldia Education office and a permission letter was obtained. Informed written consent was taken from each student and informed written consent was taken from their parents for those students whose age less than 18.

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Not applicable

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The authors declare that they have no competing interests.

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Endalifer, M.L., Andargie, G., Mohammed, B. et al. Factors associated with dietary diversity among adolescents in Woldia, Northeast Ethiopia. BMC Nutr 7, 27 (2021). https://doi.org/10.1186/s40795-021-00430-6

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Keywords

  • Adolescent
  • Dietary diversity
  • Woldia