The impacts of okra consumption on the nutritional status of pregnant women, west Ethiopia.
Efrem Negash KushiTefera BelachewDessalegn TamiruPublished in: Food science & nutrition (2023)
Food-insecurity and poor-quality diets remain a challenge for pregnant women. Consumption of okra has a great impact on improving the nutritional status of pregnant women. Okra plays a critical role in the prevention of malnutrition among pregnant women living in resource-limited settings. The evidence is scarce on the impacts of okra on mid-upper arm circumference (MUAC) measurement of pregnant women. A community-based cross-sectional study was employed among randomly selected 224 pregnant women from June 1 to July 30, 2020. An interviewer-administered questionnaire was used. The MUAC was measured by using an adult MUAC measuring tape. Data were entered into Epi-data version 3.1 and exported to SPSS version 25 for analysis by linear regression. The statistical significance of variables was declared at a p- value of .05, and unstandardized beta ( β ) coefficients along with a 95% confidence interval were computed. The proportion of pregnant women with low MUAC (≤22 cm) was 42.4%. In the multivariable linear regression model, hemoglobin concentration ( β = 0.346, [95% CI: 0.153, 0.539], p = .001), food insecurity ( β = -0.887, (95% CI: -1.441, -0.334), p = .002), daily consumption of okra ( β = 1.269, [95% CI: 0.583, 1.956], p ≤ .001), and women working in NGO ( β = 0.443, [95% CI: 0.256, 0.630], p ≤ .001) were significant variables. The prevalence of malnutrition among pregnant women (MUAC ≤ 22 cm) was 42.4%. Therefore, behavioral change communication interventions to promote okra consumption on regular basis were recommended.
Keyphrases
- pregnant women
- pregnancy outcomes
- psychometric properties
- physical activity
- body mass index
- electronic health record
- risk factors
- polycystic ovary syndrome
- type diabetes
- big data
- weight loss
- magnetic resonance imaging
- magnetic resonance
- quality improvement
- adipose tissue
- cross sectional
- artificial intelligence
- deep learning
- data analysis
- diffusion weighted imaging