Dietary Practice and Nutritional Status Among Pregnant Women

Alkalash, Safa H; Hegazy, Nagwa N; ELnady, Rasha Tawakal; Khalil, Nazeha A.

doi:10.21608/ejhm.2021.160053

Cited by 6 publications

(5 citation statements)

References 22 publications

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“…The current study also revealed that women whose partners’ education level of high school and above had higher appropriate dietary practice, which is consistent with the former studies done in Wachamo [ 36 ], and Shashamane [ 11 ]. This might be because literate partners have a better understanding of the importance of consuming a quality diet in pregnancy, and they may positively influence their wives to have appropriate dietary practices.…”

Section: Discussionsupporting

confidence: 92%

Prevalence and determinants of dietary practices among pregnant women in eastern Ethiopia

et al. 2022

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Introduction Appropriate dietary practices in pregnancy are critical to meet the increased metabolic and physiological demands; however, information about dietary practices among pregnant women, particularly rural residents, is limited. The study aimed to assess the level of appropriate dietary practices and associated determinants among pregnant women in Haramaya District, eastern Ethiopia, 2021. Methods A community-based cross-sectional study was conducted among 448 pregnant women in Haramaya District, Eastern Ethiopia. Data was collected through face-to-face interviews by trained research assistants, using a validated frequency questionnaire. The pregnant women were labeled as “appropriate dietary practice” when they consumed at least four meals daily, had a good food variety score, high dietary diversity score, and high consumption of animal source foods during the reference period. Otherwise, they were defined as “inappropriate.” A Poisson regression model with robust variance estimation was used to investigate the association of the independent variables with the dietary practice. An adjusted prevalence ratio with a 95% confidence interval was reported to show an association using a p-value < 0.05. Results The appropriate dietary practice among the study participants was 15.2% (95% CI = 12–18%). Of the respondents, 29.46, 37.5, and 24.7% had a high dietary diversity, high food variety score, and high consumption of animal source foods. The appropriate dietary practice was more prevalent among merchant women (APR = 2.07; 95% CI 1.07–4.02) and those whose husbands have at least a high school educational level (APR = 1.96; 95% CI 1.06–3.46). However, the prevalence of appropriate dietary practice was significantly lower among those who chewed khat (APR = 0.58; 95% CI 0.37–0.90) and among respondents who reported restriction of the intake of some foods (APR = 0.36; 95% CI 0.20–0.65). Conclusion We found sup-optimal appropriate dietary practice among pregnant women in this predominantly rural setting. Additionally, the lower appropriate dietary practice was observed among women who reported chewing khat and experienced restriction of dietary consumption during pregnancy. Therefore, nutrition policy programs and interventions aimed at encouraging maternal nutritional guidance and counseling are recommended.

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Section: Discussionsupporting

confidence: 92%

Prevalence and determinants of dietary practices among pregnant women in eastern Ethiopia

et al. 2022

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“…So, pregnant women should have educational sessions about the importance of breakfast. This is consistent with the results of Alkalash, Hegazy, ELnady& Khalil (2021)who stated that about two-thirty of the studied women ate three times per day. Also, near to half of them didn't delete the dinner meal.…”

Section: Discussionsupporting

confidence: 93%

Daily Dietary habits and Nutrition Attitude of Pregnant Women in Port-said city

Osman

Shalaby

El-Shabory

et al. 2022

Egyptian Journal of Health Care

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Background: Nutrition during pregnancy has a significant impact on pregnancy outcomes and is seen as a critical component of a healthy and successful pregnancy, as well as the offspring's long-term health. Aim: This study aimed to explore daily dietary habits of women regarding healthy nutrients during pregnancy. Subjects and Methods: A descriptive study was used to apply the research in prenatal clinics at six health centers in Port Said, with a total of 270 women receiving antenatal care. The tools used for data collection consisted of; a structured interviewing form, Food Frequency Questionnaire (FFQ), and the nutritional attitude scale. Results: The current study revealed that more than three quarter of the studied women had unsatisfactory level of knowledge related to nutrition during pregnancy. Most of them had positive attitude related to nutrition during pregnancy in Port-said city. A statistically significant relationship was found between total knowledge level and total attitude level of the pregnant women related to nutrition during pregnancy whereby p-value ≤ 0.05. Conclusion: Most of the studied women reported low level of knowledge regarding healthy nutrients during pregnancy. Moreover, more than half of the studied women didn't change their diet habits during pregnancy, because they were convinced that their nutrition is actually healthy. Recommendations: Applying nutrition counseling to all pregnant women to improve their practices.

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“…Respondent age is a vital indicator of the nutritional status of pregnant women. Some previous studies revealed that respondent age during the third trimester of pregnancy is a risk factor for developing malnutrition [52,53]. The husband's age is also an important feature in the nutritional status of pregnant women.…”

Section: Plos Onementioning

confidence: 99%

Machine learning prediction of nutritional status among pregnant women in Bangladesh: Evidence from Bangladesh demographic and health survey 2017–18

Begum,

Rahman,

Omar Faruk

2024

PLoS ONE

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Aim Malnutrition in pregnant women significantly affects both mother and child health. This research aims to identify the best machine learning (ML) techniques for predicting the nutritional status of pregnant women in Bangladesh and detect the most essential features based on the best-performed algorithm. Methods This study used retrospective cross-sectional data from the Bangladeshi Demographic and Health Survey 2017–18. Different feature transformations and machine learning classifiers were applied to find the best transformation and classification model. Results This investigation found that robust scaling outperformed all feature transformation methods. The result shows that the Random Forest algorithm with robust scaling outperforms all other machine learning algorithms with 74.75% accuracy, 57.91% kappa statistics, 73.36% precision, 73.08% recall, and 73.09% f1 score. In addition, the Random Forest algorithm had the highest precision (76.76%) and f1 score (71.71%) for predicting the underweight class, as well as an expected precision of 82.01% and f1 score of 83.78% for the overweight/obese class when compared to other algorithms with a robust scaling method. The respondent’s age, wealth index, region, husband’s education level, husband’s age, and occupation were crucial features for predicting the nutritional status of pregnant women in Bangladesh. Conclusion The proposed classifier could help predict the expected outcome and reduce the burden of malnutrition among pregnant women in Bangladesh.

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Dietary Practice and Nutritional Status Among Pregnant Women

Cited by 6 publications

References 22 publications

Prevalence and determinants of dietary practices among pregnant women in eastern Ethiopia

Prevalence and determinants of dietary practices among pregnant women in eastern Ethiopia

Daily Dietary habits and Nutrition Attitude of Pregnant Women in Port-said city

Machine learning prediction of nutritional status among pregnant women in Bangladesh: Evidence from Bangladesh demographic and health survey 2017–18

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