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Development of a Cvd Mortality Risk Score Using Nutritional Predictors: A Risk Prediction Model in the Golestan Cohort Study Publisher Pubmed



Jabbari M1 ; Barati M2 ; Kalhori A3 ; Einizinab H1 ; Zayeri F4 ; Poustchi H5 ; Pourshams A6 ; Hekmatdoost A7 ; Malekzadeh R6
Authors
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Authors Affiliations
  1. 1. Department of Community Nutrition, Faculty of Nutrition and Food Technology, National Nutrition and Food Technology Research Institute, Shahid Beheshti University of Medical Sciences, Tehran, Iran
  2. 2. Department of Cellular and Molecular Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran
  3. 3. Department of Food Science and Technology, Nutritional Science, The Ohio State University, Columbus, OH, United States
  4. 4. Proteomics Research Center and Department of Biostatistics, Faculty of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
  5. 5. Liver and Pancreaticobiliary Disease Research Center, Digestive Diseases Research Institute, Shariati Hospital, Tehran University of Medical Sciences, Tehran, 14117-13135, Iran
  6. 6. Digestive Oncology Research Center, Digestive Diseases Research Institute, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran
  7. 7. Department of Clinical Nutrition and Dietetics, Faculty of Nutrition and Food Technology, National Nutrition and Food Technology Research Institute, Shahid Beheshti University of Medical Sciences, Tehran, Iran

Source: Nutrition, Metabolism and Cardiovascular Diseases Published:2025


Abstract

Background and aim: We aimed to develop a dietary score using prediction model method for evaluating the risk of cardiovascular disease (CVD) mortality and suggesting a simple and practical scoring system within the healthcare context. Method and results: A total of 43878 adult participants (aged 37–80 years) from the Golestan Cohort Study (GCS) were included in analysis. A random split of the subjects into the derivation (n = 28930) and the validation sets (n = 14948) was done. The Cox proportional hazard model was used to develop prediction model for the 8-year risk of CVD mortality. The model's discrimination and calibration were assessed by C-statistic and calibration plot, respectively. To enhance clinical utility, we devised a point-based scoring system derived from our model. This prediction model was developed by nine predictors including age, physical activity level (MET minutes/week), waist-to-hip ratio, tea intake (cup/day), vegetable intake (gr/1000 kcal/day), white meat intake (gr/1000 kcal/day), salt intake (gr/1000 kcal/day), dairy intake (Cup/1000 kcal/day), and percentage of protein intake. The model had an acceptable discrimination in both derivation (C-statistic: 0.76, p < 0.001) and validation (C- statistic: 0.77, p < 0.001) samples. Also, the calibration of model in both derivation and validation datasets was 0.81. Conclusion: This is the first attempt to develop a risk prediction model of CVD mortality and the risk scoring system by the majority of nutritional predictors in a large cohort study. This nutritional risk assessment tool is suitable for motivating at-risk individuals to make lifestyle and dietary pattern changes to reduce future risk to prevent health problems. © 2024 The Italian Diabetes Society, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition and the Department of Clinical Medicine and Surgery, Federico II University
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