Kidney International Supplements (2019) 9, e1-e81 e53 Chapter 6. Prevalence, incidence, and characteristics of dialysis patients e57 Chapter 7. Clinical measurement and treatment among dialysis patients e60 Chapter 8. Vascular access e62 Chapter 9. Cardiovascular diseases and diabetes among dialysis patients e63 Chapter 10. Hospitalization e66 Chapter 11. Medical expenditures for dialysis patients e68 Chapter 12. Kidney transplant waiting list e74 Chapter 13. Discussion e75 References e76 Appendices: Definitions of ICD coding e76 Appendix 1 | Coding of various CKD etiologies e77 Appendix 2 | Coding of CKD stages e78 Appendix 3 | Coding of diabetes mellitus e78 Appendix 4 | Coding of hypertension e78 Appendix 5 | Coding of CVD e80 Appendix 6 | Coding of CVD operations e81 Appendix 7 | Coding of AKI www.kisupplements.org d e t a i l e d c o n t e n t s
Kidney International Supplements (2019) 9, e1-e81 e53 Chapter 6. Prevalence, incidence, and characteristics of dialysis patients e57 Chapter 7. Clinical measurement and treatment among dialysis patients e60 Chapter 8. Vascular access e62 Chapter 9. Cardiovascular diseases and diabetes among dialysis patients e63 Chapter 10. Hospitalization e66 Chapter 11. Medical expenditures for dialysis patients e68 Chapter 12. Kidney transplant waiting list e74 Chapter 13. Discussion e75 References e76 Appendices: Definitions of ICD coding e76 Appendix 1 | Coding of various CKD etiologies e77 Appendix 2 | Coding of CKD stages e78 Appendix 3 | Coding of diabetes mellitus e78 Appendix 4 | Coding of hypertension e78 Appendix 5 | Coding of CVD e80 Appendix 6 | Coding of CVD operations e81 Appendix 7 | Coding of AKI www.kisupplements.org d e t a i l e d c o n t e n t s
BackgroundPrevious studies indicated that lifestyle-related cardiovascular risk factors tend to be clustered in certain individuals. However, population-based studies, especially from developing countries with substantial economic heterogeneity, are extremely limited. Our study provides updated data on the clustering of cardiovascular risk factors, as well as the impact of lifestyle on those factors in China.MethodsA representative sample of adult population in China was obtained using a multistage, stratified sampling method. We investigated the clustering of four cardiovascular disease (CVD) risk factors (defined as two or more of the following: hypertension, diabetes, dyslipidemia and overweight) and their association with unhealthy lifestyles (habitual drinking, physical inactivity, chronic use of non-steroidal anti-inflammatory drugs (NSAIDs) and a low modified Dietary Approaches to Stop Hypertension (DASH) score).ResultsAmong the 46,683 participants enrolled in this study, only 31.1% were free of any pre-defined CVD risk factor. A total of 20,292 subjects had clustering of CVD risk factors, and 83.5% of them were younger than 65 years old. The adjusted prevalence of CVD risk factor clustering was 36.2%, and the prevalence was higher among males than among females (37.9% vs. 34.5%). Habitual drinking, physical inactivity, and chronic use of NSAIDs were positively associated with the clustering of CVD risk factors, with ORs of 1.60 (95% confidence interval [CI] 1.40 to1.85), 1.20 (95%CI 1.11 to 1.30) and 2.17 (95%CI 1.84 to 2.55), respectively. The modified DASH score was inversely associated with the clustering of CVD risk factors, with an OR of 0.73 (95%CI 0.67 to 0.78) for those with modified DASH scores in the top tertile. The lifestyle risk factors were more prominent among participants with low socioeconomic status.ConclusionClustering of CVD risk factors was common in China. Lifestyle modification might be an effective strategy to control CVD risk factors.
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