Background: Gestational diabetes mellitus (GDM) is currently the most common medical complication of pregnancy. Evidence suggests that by lifestyle modifications, especially nutritional behaviors, GDM may be preventable. This study aimed to investigate the Health Action Process Approach in predicting behavior and nutrition style in diabetic pregnant mothers referred to health centers under Abadan University of Medical Sciences (southern Iran). Method: This descriptive cross-sectional study on 82 pregnant women with diabetes referred to an urban health center. The samples were selected using simple random sampling. Data were analyzed using SPSS 25 software through descriptive tests, regression, analysis of variance, and correlation. Results: Most pregnant mothers (41.5 %) were in the 21-30 age group. 4 3.9% of the subjects were at the moderate economic level. Linear regression test showed among demographic variables, the strongest predictor of HAPA model was income (p<0.01, R=19.9, β=-0.299).The result also showed that none of the model constructs alone predicted nutritional behavior in pregnant women. The HAPA model was able to predict 21% of the variance of the nutritional behavior (p<0.001, r=0.210, β=0.458). Conclusion: Positive or negative outcomes, pregnant women's behavioral intent, and planning for healthy eating behaviors are effective in educating pregnant women about the prevention and control of diabetes.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.