Study area, study design and study period

The design of the community cross-sectional study with group discussion (FGD) was carried out in the district of Konso from December 1, 2018 to January 31, 2019. The district of Konso is located 595 kilometers from Addis Ababa (capital of the city of Konso). ‘Ethiopia) and 365 km from Hawassa. (the capital of the southern region). Based on the administrative population profile of Konso district, the district has a total population of 270,837 inhabitants, of which 132,710 are men and 138,127 women. The district has 50 health posts, 11 health centers, 1 primary hospital and 25 private clinics that provide health services to the community.

Population

The source population for this study consisted of all pregnant women in Konso district. The study population consisted of all pregnant women from the selected Kebeles (small administrative unit in Ethiopia) of Konso district. All pregnant women who had resided in Konso district for at least 6 months or more were included in the study, while seriously ill pregnant women, those with hand deformity were excluded.

Sample size determination and sampling technique

The sample size was calculated using a single population proportion formula; given 95% confidence level, 5% margin of error, 1.5 design effect, hypothetical 31.8% prevalence of undernutrition in women speakers from a study in Ethiopia’s Central Rift Valley [15] and adding a 5% non-response rate, the final sample size for this study was 527. Multi-stage stratified sampling followed by a systematic sampling technique was applied to reach each participant in study. The kebeles in the district have been stratified into rural and urban. One urban kebele and eight rural kebeles were selected using the lottery method out of a total of forty-one kebeles in Konso district. Then, using the housing record of the health extension workers, the total number of households with pregnant women (2277) was consulted and the sampling interval was calculated. Finally, households with eligible pregnant women were selected using a systematic random sampling technique. For households with more than one pregnant woman, a pregnant woman was selected using the lottery method. Data collectors visited the house the next day when pregnant women were not available at home and pregnant women who were not available on the second visit were recorded as non-response, then the household nearby has been taken into account.

Qualitative sampling procedure

Two FGDs were conducted with 12 subjects in each group who were chosen on purpose. A situational analysis was performed prior to conducting the Target Group Discussion (FGD) in order to minimize errors in the selection of participants. The key informants were a maternal health case team leader and a supervisor assigned to each Kebele and agricultural expert (responsible for agriculture and natural resources). In each focus group, pregnant women, their husbands and health extension workers participated. To minimize possible bias in a selection of study participants, we made sure to emphasize that we want a group of people who can express a range of views, to be able to have an appropriate discussion. A fluid discussion environment was created and we tried to encourage communication and interaction during the focus group discussion in every way possible. Group discussions took place in a neutral setting that encouraged participants to freely express their views. We made sure there was no disturbance, adequate lighting and ventilation as it was the hottest season during the data collection period, and there were also cold drinks including the water. The materials needed to conduct the target group discussion (FGD) were prepared before a discussion, such as the FGD guideline, voice recorders, notebooks, a pen and pencils. To create a suitable space for discussion, the chairs were arranged in a circle.

Study variables

The dependent variable in this study was undernutrition in pregnant women. The independent variables were: Socio-demographic factors: – age, marital status, education of the husband, education of the mother, size of the family, polygamy. Maternal factor: – parity, use of family planning before current pregnancy, interval of births, iron supplementation, follow-up of antenatal care, satisfaction with antenatal care, nutritional knowledge, illness, history of abortion, history of stillbirth, food diversification (24-hour reminder), frequency of meals, socio-cultural factors: -dietary taboo and food restriction during pregnancy, decision-making on household goods, stable family food. Economic factors: -Source of family food, ownership of agricultural land, employment status (employment of mother and husband), household income, wealth index. Hygiene and sanitation factors: access to water and sanitation facilities, such as availability and use of latrines, household water source, distance to get water . Food security factors – accessibility and availability of food.

Data collection tool and procedure

A structured questionnaire administered by an interviewer was used to collect data for the quantitative part of the study and qualitative data was collected using two focus groups (FGDs). The tool included: Sociodemographic factors adapted from the Ethiopian demographic and health survey (EDHS 2016) [36], Maternity-related factors, Socio-cultural factors, Economic factors, Hygiene and sanitation factors, and Food security factors.

To determine the nutritional status of pregnant women, MUAC (arm circumference) was used. The upper arm circumference of the left arm was measured in triplicate using a standard non-stretch MUAC tape to the nearest 0.1 cm without any clothing on the arm. The average of the triplicate measurements was taken. PB value less than 23 cm was considered undernourished and PB 23 cm was considered normal nutritional status [34, 37].

Dietary diversity information from individual respondents was collected using the 24-hour recall method and female dietary diversity score model questionnaires from nine food groups with a method of listing foods in. which the list of foods replaced by foods common in the local context included in the questioner [38].

Household food security was measured by the Household Food Insecurity Access Scale (HFIAS) which is an approach taken to estimate the prevalence of food insecurity in the United States (United States) and a was used to estimate food insecurity among study participants. [39]. The HFIAS prevalence indicator classifies households into four levels of food security: food security, light, moderate and severe food insecurity [25]. The HFIAS yes or no questions were used to collect information on the state of household food security followed by the occurrence of the situation if the answer is yes [39]. For the occurrence of once or twice, it was recorded as rarely if the occurrence is 3 to 10 times, it was classified as sometimes and if the occurrence was more than ten times in the last 4 weeks , it was classified as often [26, 40].

Purposely selected subjects participated in the two focus group discussions for qualitative data. The composition of the participants in the group discussions was made up of pregnant women, the elderly or young mothers, and their husbands, health extension workers participated in the discussion separately to facilitate the expression of opinions without fear and a key informant interview took place with health workers. head of service and agricultural expert (head of agriculture and natural resources). The discussion took place in community meeting places and information was gathered using open-ended questions. Note taking and tape recording were used to document appropriate information and detect redundant responses. The redundant responses identified were considered saturated and removed each evening after triangulation of daytime work during the preliminary analysis.

Data quality assurance

To ensure data quality, training was provided to data collectors and supervisors prior to data collection. The data collection tool was pre-tested in 5% of the sample size. The pretest was performed on individuals with characteristics similar to those of the Kebele study which was not selected in this study. After the pre-test, the instrument was modified accordingly. Supervisors supervised the data collection process and checked the completeness of the questionnaire on a daily basis. In addition, the principal investigators carefully cleaned the data and entered the collected data into computer software.

Data processing and analysis

Epi-data version 3.1 statistical software was used for data entry and exported to SPSS version 21 for analysis. Descriptive statistics such as mean, standard deviation, frequencies and percentages were calculated. Bivariate and multivariate logistic regression was used to determine the degree of association between the independent and dependent variables. All variables with a p-value less than 0.2 in the bivariate analysis were entered into a multivariate logistic regression. The presence of an association between dependent and independent variables was verified with an odds ratio adjusted with 95% confidence intervals. Then the statistical significance was declared to a p-value less than 0.05 and adjusted odds ratio interval that excluded one. Logistic regression assumption such that; meaningful coding, multicollinearity, and outlier checking were performed prior to logistic regression model analysis. Multicollinearity was also checked using variance inflation factors and the tolerance test. Hosmer-Lemeshow tests were checked to assess the fit model and it was a good fit (p-value> 0.05). The wealth index of individual families of respondents was also analyzed using principal component analysis.



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