1. Associations Between Global Population Health Indicators and Dialysis Variables in the Monitoring Dialysis Outcomes (MONDO) Consortium
- Author
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Gero von Gersdorff, Xiaoqi Xu, Michael Etter, Rasha Hussein, Roberto Pecoits-Filho, Ludimila Guedim de Campos, Danielle Marcelli, Len A. Usvyat, Viviane Calice-Silva, Peter Kotanko, Aileen Grassman, Dalia Yousif, Hanjie Zhang, and Mathias Schaller
- Subjects
Male ,medicine.medical_specialty ,Databases, Factual ,Health Status ,medicine.medical_treatment ,MEDLINE ,World Health Organization ,End stage renal disease ,Global population ,Renal Dialysis ,Prevalence ,medicine ,Humans ,Renal replacement therapy ,Intensive care medicine ,Dialysis ,Aged ,business.industry ,Incidence (epidemiology) ,Hematology ,General Medicine ,Middle Aged ,Health indicator ,Body Fluids ,Socioeconomic Factors ,Nephrology ,Emergency medicine ,Kidney Failure, Chronic ,Female ,Hemodialysis ,business - Abstract
Background: The number of patients receiving renal replacement therapy (RRT) increases annually and worldwide. Differences in the RRT incidence, prevalence, and modality vary between regions and countries for reasons yet to be clarified. Aims: Gain a better understanding of the association between hemodialysis (HD)-related variables and general population global health indicators. Methods: The present study included prevalent HD patients from 27 countries/regions from the monitoring dialysis outcomes (MONDO) database from 2006-2011. Global population health indicators were obtained from the 2014 World Health Organization report and the Human Development Index from the Human Development Report Office 2014. The Spearman rank test was used to assess the correlations between population social economic indicators and HD variables. Results: A total of 84,796 prevalent HD patients were included. Their mean age was 63 (country mean 52-71), and 60% were males (country mean 52-85%). Significant correlations were found between HD demographic clusters and population education, wealth, mortality, and health indicators. The cluster of nutrition and inflammation variables were also highly correlated with population mortality, wealth, and health indicators. Finally, cardiovascular, fluid management, and dialysis adequacy clusters were associated with education, wealth, and health care resource indicators. Conclusion: We identified socioeconomic indicators that were correlated with dialysis variables. This hypothesis-generating study may be helpful in the analysis of how global health indicators may interfere with access to HD, treatment provision, dialytic treatment characteristics, and outcomes.
- Published
- 2015
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