Prioritizing population-based nutrition-related interventions to prevent and control hypertension in Iran: a multi-criteria decision-making approach.

BACKGROUND: Numerous nutrition-related policy options and strategies have been proposed to tackle hypertension and other risk factors of non-communicable diseases (NCDs). In this study, we developed a comparative analysis using a multi-criteria decision-making (MCDM) model for prioritizing population-based nutrition-related interventions to prevent and control hypertension in Iran. METHODS: We employed a combination of Delphi technique and Analytic Hierarchy Process (AHP) method as the methodological tool to prioritize decision alternatives using multiple criteria. The prominent assessment criteria and intervention strategies were derived using a literature review, focus group discussion (n = 11), and a 2-round modified Delphi technique with specialists and experts involved in different stages of health policy-making (round 1: n = 50, round 2: n = 46). Then, the AHP was used to determine the weightage of the selected interventions and develop the decision-making model. The sensitivity analysis was performed to test the stability of the priority ranking. RESULTS: Nine alternative interventions were included in the final ranking based on eight assessment criteria. According to the results, the most priority interventions to prevent and control hypertension included reformulation of food products to contain less salt and changing the target levels of salt in foods and meals, providing low-sodium salt substitutes, and reducing salt intake through the implementation of front-of-package labeling (FOPL). The results of the sensitivity analysis and a comparison analysis suggested that the assessment model performed in this study had an appropriate level of robustness in selecting the best option among the proposed alternatives. CONCLUSION: MCDM techniques offer a potentially valuable approach to rationally structuring the problem, along with the opportunity to make explicit the judgments used as part of the decision-making model. The findings of this study provide a preliminary evidence base to guide future decisions and reforms aiming to improve appropriate population-based interventions for tackling hypertension and other risk factors of NCDs.

Predictors of Childhood High Blood Pressure among Overweight and Obese Children and Adolescents according to the Lifestyle-Scoring Algorithm Using Data from Iranian Health Care Reform Plan.

In this study, the association between dietary pattern and lifestyle in predicting hypertension (HTN) among 425 overweight and obese children and adolescents aged 6 to 18 years was evaluated. In the current cross-sectional study, the lifestyle-scoring algorithm was developed considering the Iranian Health Reform Plan (HRP) criterion. HTN was defined according to standard protocols. Hierarchical linear regression models were used for the analysis. The prevalence of overweight/obesity was 5.82%. The results showed that systolic and diastolic blood pressure (SBP, DBP) had significant positive correlation with age (p < 0.001 and p < 0.001) and body mass index (BMI) (p < 0.005 and p < 0.007), respectively. Moreover, DBP had a significant correlation with fruit consumption of less than 2 servings per day versus no consumption (p = 0.014, B = 0.444), fruit consumption of more than 2 servings per day versus no consumption (p = 0.014, B = 0.480), and vegetable consumption less than 3 servings per day versus no consumption (p = 0.045, B = -0.374). Moreover, DBP had a significant correlation with fast foods/junk foods consumption of 1-2 items per week versus almost daily consumption (p = 0.047, B = -0.177). The final model could predict 32.1% of HTN by SBP and DBP (R2 = 0.32). According to our findings, lower intake of vegetables and fruits, higher amounts of fast foods, higher age and BMI could be potent predictors of high blood pressure among Iranian children and adolescents.