Abstract

Background: The availability of food varies seasonally in the most rural areas of developing nations, especially in areas affected by drought and climate change. It may have an impact on food intake, household food security, and the nutritional status of household residents. One of the most vulnerable groups might be women. Therefore, the purpose of this study was to evaluate the association between food intake and nutritional status among women of reproductive age over the course of four seasons in a year.

Method: From June 2021 to March 2022, a cohort study of women aged 15–49 was carried out in two woredas of Sidama National Regional State, with follow-up visits of every three months. A multistage sampling technique was employed to select 910 households. Weight, height, and MUAC measures were recorded along with interviews. The outcome variable was thinness, which was defined as a BMI of less than 18.5kg/m2 for women who weren't pregnant, a BMI of less than 2 standard deviations for adolescent girls between the ages of 15 and 19, and a MUAC of less than 230 mm for women who were pregnant. The Household Food Insecurity Access Scale developed by FANTA was used to measure household food insecurity. A 24-hour dietary recall was used to evaluate the dietary diversity of households, and consumption patterns were determined using a food frequency questionnaire. Descriptive statistics and mixed multilevel linear regression analysis were done by using STATA version 16.1.

Result: There were 1,292 women at the outset of the study. They were monitored for an additional nine months. Sixty percent (2,979/4,922 observations) came from homes with severe food insecurity. Fruits, egg, milk, and sweets intake showed seasonal variation. Women had a BMI of 20.5 kg/m2 on average. Based on mixed multilevel linear regression, woman's occupation was an individual-level predictor. BMI increased by 0.74 (95% CI 0.2-0.3) among women who were engaged in business activities compared to housewives. Additionally, students had a BMI that was 0.4 higher than housewives (95% CI: 0.06-0.73). A household-level predictor of BMI was the household dietary diversity score. There was an improvement in BMI of 0.04 for each unit increase in the household dietary diversity score (95% CI 0.0005-0.07). The average BMI in September was the lowest, indicated by an increment of BMI of 0.35 (95% CI 0.24-0.45) in December and 0.44 (95% CI 0.3-0.5) in March. The household dietary diversity score and the average BMI were lowest at the end of the food scarcity season.

In conclusion, our study showed a scarce seasonal variation in household food insecurity, indicating increased vulnerability to weather and climatic patterns. Household food consumption had an impact on the BMI of women. Food consumption and BMI also displayed significant seasonal variations.