Obesity as a predictive factor for chronic kidney disease in adults: systematic review and meta-analysis

Abstract

Chronic kidney disease (CKD) is one of the main chronic diseases affecting the world population due to its high prevalence and increasing morbidity. Similarly, obesity gained the interest of the scientific community as it directly or indirectly increases mortality from cardiovascular causes, and its prevalence characterizes a pandemic. The objective of this study was to investigate obesity measured by body mass index as a predictor for end-stage renal disease in the general adult population. A systematic review and meta-analysis was carried out by searching 10 databases for prospective or retrospective cohort studies, with no restrictions on the language of publication, including adults with obesity without previous renal disease and who evolved to CKD (diagnosed by estimated glomerular filtration rate below 60 mL&mac_middot;min-1&mac_middot;(1.73 m2)-1 over the follow-up period. The R software and Meta package were used for data analysis. After removing duplicates, 5431 studies were submitted to the steps of the systematic review, and 21 articles were included in the data analysis. In total, 3,504,303 patients, 521,216 with obesity, and an average follow-up time of 9.86 years were included. The relative risk of obese people for developing CKD in the random effects model was 1.81 (95%CI: 1.52-2.16). The evidence found in this meta-analysis confirmed that obese people are at higher risk of developing CKD that the non-obese population (1.81 times higher), with obesity being a priority risk factor in preventive actions.

Figure 1. Flowchart of study selection by systematic review. CKD: chronic kidney disease.

Figure 2. Forest plot of chronic kidney disease cases in obese and non-obese patients.

Figure 3. Forest plot for sensitivity analysis according to years of follow-up.

Figure 4. Forest plot for sensitivity analysis according to study design.

Figure 5. Forest plot for sensitivity analysis according to mean age range.

Figure 6. Forest plot for complementary sensitivity analysis excluding articles with kidney transplantation, dialysis, and estimated glomerular filtration rate below 15 mL&mac_middot;min^-1&mac_middot;(1.73 m²)^-1 outcomes.