Background Adolescent girls have a greater nutrient demand and their poor dietary intake is associated with micronutrient deficiencies and poor maternal outcomes. Having information on micronutrient intake inadequacy in adolescent girls is critical for promoting healthy behavior and breaking the cycle of intergenerational malnutrition. Thus, this study assessed overall micronutrient intake inadequacy and associated factors among school adolescent girls in Meshenti town of Bahir Dar City Administration, North West Ethiopia. Methods A school-based cross-sectional study was conducted among 401 adolescent girls from February 7 to 23, 2020. A Simple random sampling technique was used to select study participants. A multiple-pass 24-hour dietary recall with portion size estimation method and recommended dietary allowance cut-off point were used to assess micronutrient intake inadequacy. Overall micronutrient intake inadequacy was measured using the mean adequacy ratio. Nutrient databases were developed by ESHA FOOD PROCESSOR version 8.1 software. Data were entered into Epi-data version 3.1 and exported to SPSS version 23 for analysis. Multivariable logistic regression was performed to identify determinants of overall micronutrient intake inadequacy and an adjusted odds ratio at a p-value of less than 0.05 was used to see the strength of statistical association. Results The prevalence of overall micronutrient intake inadequacy was 44.4% (95% CI: 39.7%-49.6%). Early adolescent age (AOR: 2.75, 95% CI: 1.71–4.42), food-insecure household (1.74, 95%CI: 1.087–2.784), low dietary diversity score (AOR = 2.83, 95% CI: 1.35–5.92), and high peer pressure on eating and body concern (AOR = 1.853, 95% CI: 1.201–2.857) were significantly associated factors with overall micronutrient intake inadequacy. Conclusion Findings of this study revealed that micronutrient intake inadequacy among adolescent girls was a high public health problem in the study area. Therefore, attention should be given to adolescent girls of the study area, especially the ones in the early adolescent age. Interventions should also focus on nutrition-sensitive activities to address food insecurity, a less diversified diet, and the negative impact of peer influence.
A school-based cross-sectional study was conducted in February 2020 among school adolescent girls (10–19 years) of Meshenti town. Meshenti town is one of the rural towns of Bahir Dar City Administration. It is located around 12km in the Southern direction from Bahir Dar town, Center of Amhara region. There are two governmental schools (one primary, from grade 1 up to 8 and one secondary, from grade 9 up to 12) in the town. A total of 1430 adolescent girls attended the town schools (831 girls at primary school (starting from grade four) and 599 girls at secondary school) during the study period. The students attending these schools come from both rural and urban areas. The major economic activities of the inhabitants in Meshenti town and its surrounding villages are agriculture in the rural area and trade in the urban area. In agriculture maize, millet, teff, barley, grass pea, and coffee are commonly produced. Also, fruits like Mango, Avocado, Guava, Orange, and Banana are produced along with Khat by using groundwater and spring water. All adolescent girls in Meshenti town schools were the source population, whereas adolescent girls attending their education in Meshenti town schools during the study period were the study population. The sample size was determined by using a single population proportion by taking into account the following assumptions: expected prevalence of overall micronutrient intake inadequacy as 50% (since there was no prior study in the study area), 95% level of confidence, 5% margin of error. In addition, a 10% non-response rate was considered to obtain the final sample size of 422. First, lists of students from primary and secondary schools of the town were obtained from each school registrar’s office with their names, age, respective grade, and address. Then adolescent girls were traced from this list. There were 1430 (831 from primary and 559 from secondary) adolescent girls from that list and those were arranged by their identification number which was used as a sampling frame. After that, the required sample of adolescent girls (422) was proportionally allocated based on the number of adolescent girls found in each school. Finally, 245 and 177 adolescent girls were selected from primary and secondary schools respectively using simple random sampling by considering the distribution of estimated sample size in each school. Data were collected by interviewer-administered questionnaires. The questionnaire used is developed by the researchers after reviewing the related literature and it included sociodemographic/economic variables, dietary related variables, intrahousehold food allocation, knowledge on nutrients, media exposure and peer pressure on eating and body concern, body image perception, and medical conditions [4, 21, 26–30]. After study participants were selected from the schools, their household addresses were traced in schools record. Then data collectors went to the girl’s house for the interview. In each interview written consent was taken from adolescent girls and verbal consent was taken from caregivers after explaining the purpose of the study. Assent was taken from caregivers for adolescent girls below age 18. Data were collected from mothers (caregivers) and adolescent girls by six public health nutrition masters students. The household food security and food allocation status were assessed using the responses of mothers, whereas knowledge on nutrients, media exposure, body image perception, and peer pressure on eating and body concern were assessed using the responses of girls. Initially, the English version questionnaire was translated into Amharic and then translated back into English to maintain its consistency. The data collection was supervised by two supervisors (public health professionals having a degree). Two days of training was given for data collectors regarding the aim of the study, data collection procedure, photographs of utensils for portion size estimation, and the way of approaching the study participants. Reliability of all the questioners including Body image perception, An Inventory of peer influence on children’s eating and body concern(IPIEC), Household Food Insecurity Access Scale(HFIAS) were checked from previous literature in which these were adapted, and these were reliable with Cronbach’s alpha greater than 0.7 [4, 21, 26–30]. To check the validity of the questionnaire, a pretest of the questionnaire was conducted on 5% (21) of girls who were not included in the final study in the study area. Then the understanding of girls was compared with the primary aim of the questions, and when there was a difference between what they understood and what we were looking for, consulting and discussion with experts was done on how that question could best be framed to make it clearer and contextually appropriate. Lastly, the questions were adapted through modification of wordings and rephrasing. The food portion weighting scale was calibrated at zero after each measurement to ensure validity. Overall micronutrient intake inadequacy (Yes/No) was considered as a dependent variable. Sociodemographic/economic variables, dietary related variables, medical condition, environmental influence (media exposure, peer pressure on eating and body concern, intra-household food distribution,), and personal characteristics (knowledge on nutrients, body image perception, meal skipping habit, and food dislike habit) of adolescent girls were independent variables. An interactive, multiple-pass 24-hour dietary recall questionnaire adapted and validated for use in developing countries [29] was used for portion size estimation and to assess nutrient intakes from foods or beverages consumed by adolescent girls. Repeated interactive 24-h dietary recall was conducted in sub-sample using the multiple-pass technique. The dietary data collection was repeated in 20% (84) of adolescents in non-consecutive day from the first interview. The recall was repeated to take in to account for the day-to-day variation in nutrient consumption of adolescent girls. The dietary data collection was not conducted on holidays or fasting days. Single day recall was conducted for the remaining study participants since, there was no significant difference in micro-nutrient intake between the first and second day dietary recall (P-value was > 0.05 in paired sample T-test for all micronutrients). Before actual data collection inspection of the market and surveillance of twenty-one households in the study area were done to collect data on common foods eaten, cooking methods, and utensils used in the area. Photographs of equipment and food portions usually eaten at one meal were taken during surveillance. These utensils were purchased at the market. After that, each utensil and portion were taken photograph and assigned a code. Those utensils used for food serving were standardized with food portions and water using a measuring cylinder and digital food portion weighing scale. The results were expressed in terms of milliliters and grams and 100 milliliters was considered as 100 grams for beverages. Photographs of household utensils (spoons, ladles, cups, and glasses) and food portions were used to assist the participant to recall and for the determination of portion sizes of the consumed items. Furthermore, foods commonly consumed (staple foods) in the study area during the study period were listed and the lists were read for the participant after completing dietary recall to help the participant recall any food that they forgot at first pass. Quantities of food consumed were estimated in household measures, local estimations (like Efign (by two hands of an average adult), Lat (one hand of an average adult), Coffee breakfast…), in number (orange, banana, lemon, mango, Guava, boiled potato, and boiled egg) and pieces). Foods expressed in number were collected as large, medium, and small. The respondents were asked which utensil they used from the photographic atlas and the portion at the average by the equipment. For purchased foods like pasta, Biscuits, and beverages (soft drinks) the brand name was recorded together with the number of items consumed, and these foods were bought from the market to see the nutrient concentration from their label. For mixed dishes, the nutrient content was obtained from their recipes. Inadequate intakes of micronutrients were estimated by the proportion of the adolescent girls with intakes that fall below the RDA (RDA cut-point method) of a particular nutrient. The inadequacy of a particular nutrient was measured using nutrient adequacy ratio (NAR) whereas, the overall micronutrient intake inadequacy (nutritional inadequacy in terms of micronutrient) was measured using mean adequacy ratio (MAR) for ten micronutrients namely vitamin A, vitamin B1, vitamin B2, vitamin B3, vitamin C, Vitamin B12, folate, calcium, iron, and zinc. In addition to assessing nutrient intake, the 24-hour recall data were used to determine the dietary diversity score for the adolescents. The dietary diversity was assessed using a standard tool suggested by Food and Agricultural Organization to measure women’s dietary diversity. The food items consumed within 24 hours were categorized into ten food groups based on their nutrients: those include grains (white roots, tubers, and plantains), pulses (beans, peas, and lentils), nuts and seeds, dairy, meat (poultry and fish), eggs, dark green leafy vegetables, vitamin A-rich fruits and vegetables, other vegetables, and fruits. Finally, Dietary Diversity Scores (DDS) were created as a summary measure of dietary diversity [4]. Wealth index of the households was determined using the Principal Component Analysis (PCA) by considering latrine, water source, household assets, livestock, agricultural land ownership, and crop production adopted from EDHS 2016 [26]. A total of seven knowledge assessing choice questions on the source of nutrients, the benefit of nutrients, and nutrient needs of adolescent girls were prepared [21, 31]. An Inventory peer influence on children’s eating and body concern (I-PIEC), a self-reported measurement tool developed by Oliver & Thelen [32] was used to assess peer influence of adolescent girls on their eating and indirectly on nutrient intake. The tool consists of three constructs called messages (the frequency that girls’ experienced negative messages about their bodies or eating habit), interactions (the frequency that adolescent girls interacted (talked, exercised, or compared their bodies) with others regarding eating habits and body issues), and likability (the degree to which girls believed changing body weight or shape would increase their likability by their peers or friends or boys). The items in each construct had a five-point Likert scale which instructs the individual to answer as 1 = ‘‘never (null),”2 = ‘‘almost never (1–2 day),” 3 = ‘‘not very often (3–4 day),”4 = ‘‘sometimes (5–6 day),” and 5 = ‘‘a lot (every day)” within a week. A total of 8 items measuring message, interaction, and likability were prepared. Then the scores were added for analysis. The possible range of scores was from 8–40 points. Finally, the mean of scores was computed [33]. Body image perception was assessed using a five-point Likert scale that was adapted from the study on body image perception in university students [27]. Adolescent girls were asked: “In your opinion are you…” with five response options (“Far too thin”, “A little too thin”, “Just right”, “A little overweight”, “and Very overweight” and are you happy in your current body weight or shape (yes/no). For the analysis, the five options were re-coded into three categories (“Too thin”, “Just right”, and “Too fat”). Food insecurity was measured by the Household Food Insecurity Access Scale (HFIAS) which has a nine-item scale consisting of an occurrence question followed by a frequency of occurrence question during the previous month which is a structured, standardized, and validated tool developed by the USAID funded FANTA project. The participants’ response indicated a frequency of occurrence of never, rarely (1to 2 times), sometimes (3 to 10 times), and often (>10 times) for each of the questions, over the previous 4 weeks [28]. The average daily dietary intake level that is sufficient to meet the nutrient requirement of nearly all (97 to 98%) healthy individuals in a particular life-stage and gender group. It is the goal for usual intake by an individual [34]. The ratio of subject’s nutrient intake to the requirement (RDA). Is the sum of NARs for nutrients divided by the number of nutrients evaluated [35]. When an individual’s intake mean adequacy ratio(MAR) for ten (vitamin A, B1, B2, B3, B12, vitamin C, folate, iron, calcium, and zinc) micronutrients was less than 1(100%). When daily intake value of a particular nutrient (vitamin B1, B2, B3, B12, A, C, folate, calcium, zinc, and iron) was less than its RDA or when NAR for a nutrient was less than 1, otherwise considered as adequate intake [35]. Adolescent girls who consumed five and above food groups from ten food groups were considered as having a high dietary diversity score and those who consumed less than five food groups were considered as having a low dietary diversity score [4]. People hate any food items like porridge, milk, Avocado, etc. either due to taste, odor, color, religious restriction, or feeling sick while eating that food item. The frequency of meal was obtained by asking the participants to identify the meals they usually had as breakfast, lunch, dinner, and snacks (morning, afternoon, or evening) within a day. Thus, number of meals they had on a recall day were counted and classified as = 3 meals per day. Individuals skipped at least one of their usual meals were considered as meal skipper. Household experiences none of the food insecurity (access) conditions, or just experiences worry, but rarely were considered as secured, otherwise considered as food in-secured [28]. If girls answer knowledge assessing questions correctly above the mean of the total score they were considered as having sufficient knowledge otherwise considered as having insufficient knowledge [31]. Respondents were asked how often they read a newspaper, listened to the radio, or watched television. Those who responded at least once a week were considered to be exposed to that form of media [26]. “one’s subjective attitude toward one’s own physical appearance. It can include both one’s own mental images of his or her body as well as the feelings one has toward his or her body” or “the way one sees his/herself, what he/she believe about his/her appearance and not how others sees her/him” [36] When the peer pressure score of adolescent girls was greater than the mean score, they were considered as having high peer pressure influence whereas, peer pressure score less than or equal to the mean score was considered as having low peer pressure influence [33]. Nutrient values per 100 gram of each food item were primarily obtained from the Ethiopian food composition tables [37, 38]. Nutrient content of certain food items that are not part of the Ethiopian food composition tables particularly for folate and vitamin B12 were supplemented from African (Tanzanian and West African) food composition tables [39, 40]. To obtain the weight and nutrient values of purchased foods their nutrient label were used to analyze their nutrient composition. These values were fed to ESHA FOOD PROCESSOR software version 8.1 to create a nutrient database. Then, the food items in portion size obtained from the 24-hour recall were converted into their corresponding weight (into gram) manually. After that, the calculated daily intakes in grams were fed to the created nutrient database. Hence, the software calculated nutrient values for consumed portions of each food item for every individual. Results were copied to excel and exported to SPSS for analysis. The average intake of first and second day consumption was taken for repeated recalls. Paired sample T-test was conducted to know the significant difference in micronutrient intakes between the first and the second day dietary recall in repeated recall among sub-sample. P-value greater than 0.05 was considered as there was no significant difference. Micronutrients (vitamin A, vitamin B1, vitamin B2, vitamin B3, vitamin C, Vitamin B12, folate, calcium, iron, and zinc) which remain issues globally and are highly required by adolescent girls were analyzed in this specific study [15]. Finally, nutrient intakes were compared with RDA set by WHO/FAO joint expert consultation report 2004 for identifying the prevalence of inadequate intake [5]. Inadequate intakes of micronutrients were estimated by the proportion of the adolescent girls with intakes that fall below the RDA (RDA cut-point method) of a particular nutrient. The inadequacy of a particular micronutrient was measured using nutrient adequacy ratio (NAR) whereas, the overall micronutrient intake inadequacy (quality of diet in terms of micronutrient) was measured using mean adequacy ratio (MAR) for ten micronutrients namely vitamin A, vitamin B1, vitamin B2, vitamin B3, vitamin C, Vitamin B12, folate, calcium, iron, and zinc. The collected data from other sections of the questionnaire (independent variables) were coded and entered into Epi data version 3.1 and exported into SPSS version 23. The data were sorted, cleaned, and analyzed using SPSS version 23. To determine the nutrient knowledge of participants, first adolescent girls who answered the knowledge assessing questions correctly were given a score 1 and for those who did not correctly answer the question score 0 were given. After that total score of the correct answers and mean values of the knowledge score were calculated. Principal component analysis (PCA) was used to determine the wealth status of respondents. The responses of all variables were classified into two scores. The highest score was coded as 1 and the lower score was given code 0. Assumptions of PCA were checked to carry out the wealth index score. In PCA to determine the number of components that would retain, eigenvalue-one criterion was used and those variables having a commonality value of greater than 0.5 were used to produce factor scores. Then, the score for each household on the first principal component was retained to create the wealth score. Finally, tercials of the wealth score were created to categorize households as poor, medium, and rich. Descriptive statistics like frequency and percentage for categorical variables, mean/median, and standard deviation /interquartile range were carried out for continuous variables. For continuous variables normality was checked by using histograms, and then normally distributed data were presented as mean (SD) and non-normally distributed data were presented as median (IQR). Bivariable logistic regression analysis was used to know the crude association between each independent variable and the outcome variable (overall micronutrient intake inadequacy) and crude odds ratio was obtained. Then, to control for possible confounding effects and to identify factors that are independently associated with overall micronutrient intake inadequacy among adolescent girls, the variables in the bivariable analysis with a p-value less than 0.25 were included in multivariable logistic regression analysis with a backward approach. The Hosmer–Lemeshow test was performed for model fitness in the final model (P = 0.945). Having a p-value less than 0.05 in multivariable logistic regression analysis was used to conclude the presence of a statistically significant association between predictor variables with the response variable. The strength of statistical association was measured by an adjusted odds ratio at a 95% confidence level. Finally, the results were presented in terms of text, frequency tables, and graphs. Ethical approval was obtained from the Institutional Review Board (IRB) of College of Medicine and Health Science at Bahir Dar University with protocol number (0017/2020 and assigned number 002. An official letter of permission was obtained from Bahir Dar City Administration Health Department and Meshenti kebele administration office. Finally, oral permission was obtained from school directors. Before the interview, informed written and verbal consent was obtained from adolescent girls and caregivers respectively. For those aged below 18 years old assent was taken along with permission from caregivers. The confidentiality of study participants was kept anonymous in any process of the study.
DIMA AI Care
