Weight-adjusted Waist Index and Cardiovascular Disease: a Population-based Study in Ravansar, Iran

Overview

Journal Arch Public Health

Publisher Biomed Central

Date 2024 Nov 20

PMID 39568057

Authors

Sepehr Sadafi

Ali Azizi

Ebrahim Shakiba

Yahya Pasdar

Affiliations

Soon will be listed here.

Abstract

Background: The weight-adjusted-waist index (WWI) is a relatively new index to obesity. This study aimed to explore the reationship between WWI and cardiovascular disease (CVD).

Methods: This cross-sectional study included 8,899 participants aged 35 to 65 from the Ravansar non-communicable diseases (RaNCD) cohort study in Ravansar, Iran. The WWI was calculated by dividing waist circumference (WC) by the square root of weight. The receiver operating characteristic (ROC) curve was utilized to assess the predictive performance of WWI in relation to CVD. The study applied multiple logistic regression to assess the association between WWI and CVD.

Results: Participants had an average age of 47.52 ± 8.29 years, with 45.30% being men and 41.13% residing in rural areas. The prevalence of CVD was found to be 17.36%. A positive correlation between WWI and CVD was obseved, with individuals in the highest WWI quartile having a 36% (OR = 1.36, 95%CI: 1.11, 1.78) greater odds of CVD compared to those in the lowest quartile (OR = 1.03, 95%CI: 0.79, 1.33) (ptrend = 0.010). Subgroup analyses indicated stronger links between WWI and CVD among participants over 50, males, urban residents, those of high socioeconomic status (SES), and passive smokers (p < 0.001). The ROC analysis revealed that WWI is a greater ability in predicting CVD (AUC: 0.64, 95%CI: 0.61, 0.64) compared to body mass index (BMI) (AUC: 0.60, 95%CI: 0.58, 0.61) and WC (AUC: 0.61, 95%CI: 0.59, 0.62).

Conclusion: The increase in WWI elevates the odds of CVD, making the management of WWI crucial for CVD prevention.

Citing Articles

The relationship between weight-adjusted waist index and peripheral artery disease.

Wu Z, Liu Y, Wang B Front Nutr. 2025; 12:1504896.

PMID: 40013161 PMC: 11860073. DOI: 10.3389/fnut.2025.1504896.

References

Kim J, Choi J, Vella C, Criqui M, Allison M, Kim N . Associations between Weight-Adjusted Waist Index and Abdominal Fat and Muscle Mass: Multi-Ethnic Study of Atherosclerosis. Diabetes Metab J. 2022; 46(5):747-755. PMC: 9532169. DOI: 10.4093/dmj.2021.0294. View

Flegal K, Kit B, Orpana H, Graubard B . Association of all-cause mortality with overweight and obesity using standard body mass index categories: a systematic review and meta-analysis. JAMA. 2013; 309(1):71-82. PMC: 4855514. DOI: 10.1001/jama.2012.113905. View

Najafi F, Rezaei S, Hajizadeh M, Soofi M, Salimi Y, Kazemi Karyani A . Decomposing socioeconomic inequality in dental caries in Iran: cross-sectional results from the PERSIAN cohort study. Arch Public Health. 2020; 78:75. PMC: 7436972. DOI: 10.1186/s13690-020-00457-4. View

Hamjane N, Benyahya F, Ghailani Nourouti N, Bennani Mechita M, Barakat A . Cardiovascular diseases and metabolic abnormalities associated with obesity: What is the role of inflammatory responses? A systematic review. Microvasc Res. 2020; 131:104023. DOI: 10.1016/j.mvr.2020.104023. View

Zbikowski S, Jack L, McClure J, Deprey M, Javitz H, McAfee T . Utilization of services in a randomized trial testing phone- and web-based interventions for smoking cessation. Nicotine Tob Res. 2011; 13(5):319-27. PMC: 3082503. DOI: 10.1093/ntr/ntq257. View

Li X, Wang L, Zhou H, Xu H . Association between weight-adjusted-waist index and chronic kidney disease: a cross-sectional study. BMC Nephrol. 2023; 24(1):266. PMC: 10494374. DOI: 10.1186/s12882-023-03316-w. View

Eghtesad S, Hekmatdoost A, Faramarzi E, Homayounfar R, Sharafkhah M, Hakimi H . Validity and reproducibility of a food frequency questionnaire assessing food group intake in the PERSIAN Cohort Study. Front Nutr. 2023; 10:1059870. PMC: 10436288. DOI: 10.3389/fnut.2023.1059870. View

Pasdar Y, Najafi F, Moradinazar M, Shakiba E, Karim H, Hamzeh B . Cohort Profile: Ravansar Non-Communicable Disease cohort study: the first cohort study in a Kurdish population. Int J Epidemiol. 2019; 48(3):682-683f. DOI: 10.1093/ije/dyy296. View

Gholamalizadeh M, Doaei S, Akbari M, Rezaei S, Mosavi Jarrahi A . Influence of Fat Mass- and Obesity-Associated Genotype, Body Mass Index, and Dietary Intake on Effects of Iroquois-related Homeobox 3 Gene on Body Weight. Chin Med J (Engl). 2018; 131(17):2112-2113. PMC: 6111688. DOI: 10.4103/0366-6999.239309. View

10.

Cai S, Zhou L, Zhang Y, Cheng B, Zhang A, Sun J . Association of the Weight-Adjusted-Waist Index With Risk of All-Cause Mortality: A 10-Year Follow-Up Study. Front Nutr. 2022; 9:894686. PMC: 9174751. DOI: 10.3389/fnut.2022.894686. View

11.

Yao F, Ma J, Cui Y, Huang C, Lu R, Hu F . Dietary intake of total vegetable, fruit, cereal, soluble and insoluble fiber and risk of all-cause, cardiovascular, and cancer mortality: systematic review and dose-response meta-analysis of prospective cohort studies. Front Nutr. 2023; 10:1153165. PMC: 10579821. DOI: 10.3389/fnut.2023.1153165. View

12.

Teo P, van Dam R, Whitton C, Tan L, Forde C . Consumption of Foods With Higher Energy Intake Rates is Associated With Greater Energy Intake, Adiposity, and Cardiovascular Risk Factors in Adults. J Nutr. 2020; 151(2):370-378. DOI: 10.1093/jn/nxaa344. View

13.

Cao S, Hu X, Shao Y, Wang Y, Tang Y, Ren S . Relationship between weight-adjusted-waist index and erectile dysfunction in the United State: results from NHANES 2001-2004. Front Endocrinol (Lausanne). 2023; 14:1128076. PMC: 10167952. DOI: 10.3389/fendo.2023.1128076. View

14.

Fang H, Xie F, Li K, Li M, Wu Y . Association between weight-adjusted-waist index and risk of cardiovascular diseases in United States adults: a cross-sectional study. BMC Cardiovasc Disord. 2023; 23(1):435. PMC: 10474739. DOI: 10.1186/s12872-023-03452-z. View

15.

colak E, Pap D . The role of oxidative stress in the development of obesity and obesity-related metabolic disorders. J Med Biochem. 2021; 40(1):1-9. PMC: 7857849. DOI: 10.5937/jomb0-24652. View

16.

Vusirikala A, Thomas T, Bhala N, Tahrani A, Thomas G, Nirantharakumar K . Impact of obesity and metabolic health status in the development of non-alcoholic fatty liver disease (NAFLD): A United Kingdom population-based cohort study using the health improvement network (THIN). BMC Endocr Disord. 2020; 20(1):96. PMC: 7325099. DOI: 10.1186/s12902-020-00582-9. View

17.

Wiklund P, Toss F, Weinehall L, Hallmans G, Franks P, Nordstrom A . Abdominal and gynoid fat mass are associated with cardiovascular risk factors in men and women. J Clin Endocrinol Metab. 2008; 93(11):4360-6. DOI: 10.1210/jc.2008-0804. View

18.

Freisling H, Arnold M, Soerjomataram I, ODoherty M, Ordonez-Mena J, Bamia C . Comparison of general obesity and measures of body fat distribution in older adults in relation to cancer risk: meta-analysis of individual participant data of seven prospective cohorts in Europe. Br J Cancer. 2017; 116(11):1486-1497. PMC: 5520086. DOI: 10.1038/bjc.2017.106. View

19.

Emamian M, Hashemi H, Fotouhi A . Predicted 10-year risk of cardiovascular disease in the Islamic Republic of Iran and the body mass index paradox. East Mediterr Health J. 2020; 26(12):1465-1472. DOI: 10.26719/emhj.20.012. View

20.

Yarahmadi S, Etemad K, Hazaveh A, Azhang N . Urbanization and non-communicable risk factors in the capital city of 6 big provinces of iran. Iran J Public Health. 2013; 42(Supple1):113-8. PMC: 3712588. View