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Background: In developing countries, women are generally vulnerable to undernutrition especially during lactation because of inadequate nutrient intake. The purpose of this study was to assess the prevalence of underweight, associated factors and mean dietary intake of selected nutrients among lactating women in Arba Minch Zuriya districts, Gamo Gofa, Ethiopia. Methods: Multistage cluster sampling technique was used to select 478 exclusively breastfeeding women. Data was collected by using structured questionnaire, and weight and height measurements. Mean intake of calories, calcium, iron, zinc and vitamin A was assessed by using 24-hour recall method on subsample of 73 subjects and compared against the Ethiopian and African food composition tables. Logistic regression analysis was used to evaluate the association between various independent variables and maternal underweight. Results: The prevalence of underweight was 17.4%. Maternal underweight significantly associated with short birth to pregnancy interval, high workload burden, household food insecurity, less access to nutrition information and low level of women educational status. Conclusions: A significant proportion of women suffered from undernutrition and the mean intake of calories, calcium and zinc were below the recommended level for lactating women. Hence, to improve nutritional status of lactating women, strategies should focus on nutrition counseling, improvement in women’s access to labour saving technologies and effective household food security interventions.
Study area: Arba Minch Zuriya is a rural administrative district in the Gamo Gofa zone and is located 505 km away from Addis Ababa. The district has 29 kebeles, with a total estimated population of 200,000. The total number of reproductive age women in the study area was 27,202 of which there were 5140 who were lactating (13). The mean annual daily temperature ranges 15.1 to 25.0 °C. Maize, sorghum, wheat, barley and teff are the primary crops are produced. Moringa stenopetella and kale are among the most consumed staple vegetables; common fruits are banana and mango. According to the woreda office, seven health centers and 29 health posts provide health services for the community. Study design and sample: This was a community-based cross-sectional study with both descriptive and analytic elements, carried out from May to June 2015. The study population comprised women who had given birth within six months prior to data collection and were living in randomly selected kebeles of the study area. Women who had gave birth less than 45 days at the time of recruitment, those who were seriously ill and the ones who could not be found at home after three consecutive visits were excluded. Sample size was determined using single population proportion formula. The inputs were a 95% of confidence level, a 5% of margin of error, a 25% estimated prevalence of maternal underweight (12), a design effect of 1.5 and a 10% of non-response rate. The sample size was found as 478. Sampling procedure: A Multistage cluster sampling procedure was followed. The kebeles in the district were stratified to Woinadega, Kola and Dega agroecology areas. Then, the total sample size was divided to the three strata proportionally to their population size. From each stratum, eight kebeles (4 from Woinadega, 3 from Kola and 1 from Dega) were selected at random and the sample size for each stratum was distributed to the kebeles proportional to their population size. Sampling frame was prepared for each household with lactating women, who were identified with the help of health development army. Study subjects were selected using systematic random sampling. Data collection procedures and quality assurance: The structured questionnaire was derived from different standard questionnaires (14,18). The questionnaire was prepared in English. The final version was translated into Amharic and then re-translated into English. Diploma teachers who were good at Amharic and local languages (Gamogna and Zeisegna) were recruited. The questionnaire included sociodemographic, socio-economic, health and reproductive history and dietary intake/diversity. A food frequency questionnaire listing food groups consumed the previous day was used to calculate dietary diversity score (DDS) of lactating women. DDS was calculated as the number of food groups out of a possible nine were consumed over the past 24 hours. A high dietary diversity was considered if ≥ six food groups, medium if 4 four to five 5 food groups and low if ≤ three or less food groups (15) were consumed in the specified period. A repeated quantitative 24-hour dietary recall was used to collect quantitative data from sub-sample of 73 study participants (15% of total sample size) (16) to assess mean intake of calorie, calcium, zinc, iron and vitamin A. To account for the ‘day of the week effects’ one weekday and one market day were represented. Anthropometric data was collected by measuring weight and height of lactating women using calibrated equipment and standardized techniques (16,17). Weight was measured to the nearest 0.1 kg using a digital scale. Height was measured to the nearest 0.1 cm with a fixed stadiometer with vertical backboard and movable headboard. Measurements were taken with the women standing erect with feet parallel and buttocks, shoulders and back of head touching the wall. Body Mass Index (BMI) was calculated as weight (kg) divided by height squared (m2). Subjects were classified as underweight if BMI < 18.5 (17). The Food and Nutrition Technical Assistance (FANTA) household food insecurity access scale (HFIAS) was used to assess household food security (18). The tool had nine questions each having four answer options in a recall period of 30 days. The precoded options were never (0 points), rarely (once or twice in the past 4 weeks; 1 point), sometimes (three to ten times in the past 4 weeks; 2 points), and often (more than ten times in the past 4 weeks; 3 points). Scores for answers to these questions were summed (0–27) and households classified as four level of household food insecurity. The higher the score, the more food insecurity a household experienced. Food security was defined as follows. Households who experienced none of the food insecurity conditions were categorized as “food secure”, but household worries about not having enough food sometimes or often in the last four weeks were “mildly food insecure”. A “moderately food insecure” household sacrificed quality more frequently, by eating monotonous diet or undesirable foods sometimes or often, but did not experience any of the severe conditions (running out of food, going to bed hungry, or going a whole day and night without eating) which are characteristic of “severely food insecure” households. To assure data quality, training was given to data collectors and supervisors on all procedures. Pretest was carried out on 5% of the study sample on kebeles not included in this study. Data collectors' accuracy of anthropometric measurements was standardized prior to the study. The principal investigator supervised all data collection. Filled copies of the questionnaire were checked for their completeness every day after data collection. Ethical clearance was obtained from the Institutional Review Board of Hawassa University, College of Medicine and Health Sciences. Further permission was obtained from Arba Minch Zuriya Woreda Health Office, and explanation about the purpose of the survey and the benefits was provided to study participants in order to obtain their verbal or written consent. Confidentiality of the data was maintained. The independent variables were socioeconomic factors, household food insecurity, family size, housing condition, work load, parity, birth to pregnancy interval, frequency of breast feeding, meal frequency, dietary diversity, antenatal care, place of delivery and access to nutrition information during pregnancy or postpartum. The dependent variables were work load, parity, birth to pregnancy interval, frequency of breast feeding, meal frequency, dietary diversity, antenatal care, place of delivery and access to nutrition information (12,19). Data analysis: Tolerance test <2 was used to check the absence of multi-co-linearity. Variables were checked for normality using Kolmogorov-Smirnove test (20). Descriptive summaries, frequencies and proportions were found. Logistic regression was employed to assess the association between dependent and independent variables. Odds ratio (OR) with 95% CI was used to assess strength of association, and p-value <0.05 was statistical significance. The amount of consumed foods and drinks obtained from repeated 24 hr recall data was converted to grams. Nutrients values were computed using Ethiopian (21) and African (22) food composition tables. Since the data was not normally distributed, median energy and nutrient intake values were computed and compared with the recommended dietary intake (RDA) for lactating women (23,24). Wealth index was computed using principal component analysis (PCA) as a composite indicator of living standard, initially based on 19 variables related to ownership of valuable assets, livestock, size of agricultural land and materials used for house construction (13). A score of “1” was given for each of 14 binary variables; for the remaining five variables, different scoring systems were used. Variables (sources of water, sanitary facility and ownership of kerosene) were removed from analysis as they had low communality score. Five categories (poorest, poorer, middle, richer and richest) were generated as approximately equal quintiles. In order to identify factors associated with maternal underweight, logistic regression analysis was used. Two models were developed separately for proximal and distal independent variables. Variables at binary logistic analysis with a p-value of less than 0.25 were subsequently included in the multivariate analysis. The adequacy of the model was checked by using Hosmer and Lemeshow goodness of fit test (20).
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