Nutritional Status of Postpartum Mothers and Associated Risk Factors in Shey-Bench District, Bench-Sheko Zone, Southwest Ethiopia: A Community Based Cross-Sectional Study

Background: Malnutrition affects millions of people in developing countries and contributes to poor health outcomes and nutritional status among women in the postpartum period. Lactation increases high nutritional demands and marks a significant life transition that can impact diet quality and subsequently predispose woman to high risk of overweight and undernutrition. Although, studies have been conducted on the nutritional status of lactating women, there is a gap especially on women’s nutritional status during the postpartum period. Therefore, this study aimed to assess the nutritional status of postpartum women and associated factors in Shey-Bench District, Bench-Sheko Zone, Southwest Ethiopia, 2020. Method: A community-based cross-sectional study was conducted in Shey-Bench District from March 1 to 30/2020 among 359 postpartum mothers. Bivariate analysis was employed to select candidate variables at P-value <.25 as a cut-off point. Multiple multinomial logistic regression analysis was used to identify variables significantly associated with nutritional status of the mother at P <.05 with 95% CI. Results: The study revealed that 10.3% of women were underweight and 16.7% were overweight. Employed mothers (AOR = 4.467, 95% CI [1.05-19.04]), employed husband (AOR = 0.087, 95% CI [0.021-0.370]), farmer husband (AOR = 0.084, 95% CI [0.024-0.293]), trader husband (AOR = 0.19, 95% CI [0.0614-0.616]), married mother (AOR = 0.222, 95% CI [0.088-0.560]), dietary diversity (AOR = 0.181, 95% CI [0.075-0.436]) were significantly associated with underweight and while being overweight was associated with dietary diversity, maternal age of between 15 to 24 and 25 to 34, exclusive breastfeeding, and frequency of breastfeeding. Conclusion: This study found a lower prevalence of underweight compared with overweight in the study area. Occupational status, marital status, age of the mother, dietary diversity, exclusive and frequency of breastfeeding were significantly associated factors with nutritional status of postpartum mother. We recommend strengthening the provision of nutrition education on modifiable factors with collaboration of other sectors. A community-based cross-sectional survey was conducted in Shey-Bench District, southwest Ethiopia, from March 1 to 30, 2020. The district is located 595 km from Addis Ababa, the capital city of Ethiopia, and 870 km from Hawassa, the central city of South, Nation, Nationality and People Region (SNNPR). It consists of 20 kebeles (the smallest administrative unit of Ethiopia) and has a total population of 160 618 of whom 81 112 are women. According to the Shey-Bench district reports, there were a total population of 500 postpartum mothers during the data collection period. Six health centers and 20 health posts offer health services to this community. All postpartum mothers who had lived in the Shey-Bench District for at least 6 months were the source population. Postpartum mothers resident in the selected kebeles (the smallest administrative unit in Ethiopia) were study populations. All selected postpartum mothers who fulfilled the inclusion criteria were study units. The required sample size was determined using the single-population proportion formula considering 50% malnutrition among postpartum mothers, 95% confidence interval (CI), and 5% margin of error. The obtained sample size was adjusted by finite population correction formula and multiplied by a 1.5 design effect. After a 10% non-response rate was considered, the final sample size was 359. Out of 20 kebeles, 6 were randomly selected by using the lottery method. A unique identification number was assigned to each participating household with postpartum mothers, with the assistance of health extension workers during a preliminary survey. Proportional allocation was carried out. A sampling frame was prepared using the identification number of households with postpartum mothers. A simple random sampling technique was employed to select the postpartum mothers to include in the study. A semi-structured interviewer-administered questionnaire was developed after reviewing related literature. The tool included questions related to socio-demographic variables, household wealth index, obstetric history, nutritional and morbidity related questions, 24 hours women dietary diversity recall of 10 food groups, Household Food Insecurity Access Scale (HFIAS). Bodyweight: The weight of the women was measured using a portable battery-operated Seca digital scale (Seca Germany). The weighing scale was checked for zero reading before the mother was asked to calibrate. In addition, the proper performance of each scale was checked regularly by measuring known weights before measuring the women’s weight. During the procedure, the subjects wore light clothes and removed their shoes. The weight was recorded to the nearest 0.1 kg. Height: The height of the mother was measured using a portable stadiometer (Seca Germany). All respondents were have been measured against the wall in an upright position, without shoes and with heels together and their heads positioned and eyes looking straight ahead (Frankfurt plane). The height was measured and recorded to the nearest 0.1 cm. When it was difficult to measure height due to inability to erect in Frankfurt plane position height was intended to estimate from arm span or demi span or knee height position. The respondent’s weight and height were measured at least twice and the average value of each measurement was taken for further analysis. Six Diploma nurses and 2 degreed nurse supervisors, who were not employed in health facilities in the actual research area and were fluent in the local language and Amharic, were recruited to collect data. A structured questionnaire was pretested among 18 (5%) postpartum women out of the study area. Relative Technical Error of Measurement (TEM) was calculated to minimize a random anthropometric measurement error. The data collectors’ accuracy of the measurements was standardized with their trainer during training and pretesting. A respondent’s weight and height were measured at least twice and when the difference between the 2 weight measures was greater than 0.1 kg and when the difference between the 2 height measures was greater than 0.1 cm, the average value was taken. In addition to providing materials, the supervisor also verified the completeness and consistency of the questionnaire responses. The lead researcher conducted a comprehensive and in-depth follow-up of the data collection. After coding and checking by the principal investigator the data were entered and cleaned using Epi data version 3.1 before being exported to Statistical package for social science (SPSS) version 22.0 for analysis. The women-dietary diversity score was calculated by minimum dietary diversity (MDD-W) which was adapted from the Food and Agriculture Organization of the United Nations (FAO) 2016. The dietary diversity questionnaire had 10 different food groups: (1) grains (white roots, tubers, and plantains), (2) pulses (beans, peas, and lentils), (3) nuts and seeds, (4) dairy, (5) meat and fish (poultry and fish), (6) eggs, (7) dark green leafy vegetables, (8) vitamin A-rich fruits and vegetables, (9) others 146 vegetables, and (10) others fruits. It was assessed by using 24-hour dietary recall methods; 1 point was given to each food group consumed over the past 24 hours before the survey period. The participants were asked about all foods and beverages consumed during the past 24 hours and the interviewer probed for any food types that might have been forgotten by participants. 21 By considering the locally available household assets and using Principal Component Analysis (PCA) the families’ wealth index was constructed after assumptions were checked. The HIFAS was calculated for each household by summing the code for each frequency of occurrence question. The maximum score for a household was 27 if the households response to all 9 frequencies of occurrence questions was “three” (3). The minimum score was 0, which represented the household response of “no” to all occurrence questions. The Household Food Insecurity Access Scale scores were categorized as a food secured, mildly food insecure, moderately food insecure, and severely food insecure based on the indicator guideline.22,23 Based on the coefficient output the presence of multicollinearity was cheeked and the maximum Variance Inflation Factor (VIF) was 2 indicating no collinearity. The minimum number of cases per independent variable ratio of 10:1 was satisfied, in this study with a ratio of 13:1. The model fitting information was seen on the likelihood ratio test showed P < .001, Goodness of fit test with Pearson chi-square P = .83, and deviance P = 1, P > .05 for best model fitness. The outcome variable was categorized as underweight, normal, overweight. In the bivariate multinomial logistic regression model independent variables at P < .25 were considered for further multiple multinomial logistic regression analysis. In multiple multinomial logistic regression adjusted odds ratios (AOR), along with 95% CI were presented to indicate the association i between the risk factors associated with the outcome variable at the level of statistical significance P < .05. The reference sub-population for nutritional status of postpartum mothers used in the multiple multinomial logistic regression model was “Normal weight” which was compared with the sub-populations “underweight” and “overweight” for each of the identified risks factors. Postpartum period: period between births to 6 weeks Body mass index (BMI): Weight in kilogram/height in meter squared Underweight: BMI <18.5 kg/m2 Normal weight: BMI from 18.5 to 24.9 kg/m2 Overweight: BMI from 25 to 29.9 kg/m2 24 Optimum meal frequency: Meal taken ⩾4 meals/day Sub-optimum meal frequency: Meal taken <4 meals/day Instrumental delivery: SVD assisted delivery Food insecurities categories: Categorized as Food secure (<2), mildly secured (2-10), moderately (11-17), and while severely (>17) food insecured based on HFIAS 25 Dietary diversity: is a measure of the number of food groups consumed over a reference period, 24 hours before the time of data collection. High women dietary diversity score: postpartum mothers who consumed ⩾5 food groups intake out of 10. Low women dietary diversity score: postpartum mothers who consumed <5 food groups intake out of 10. 21