Might low-protein diet for chronic kidney disease patients be successful? A case study with the application of a random effects ordered probit model

Lara Gitto, Valeria Cernaro, Guido Gembillo, Alfredo Laudani, Daniela Metro and Domenico Santoro

International Journal of Computational Economics and Econometrics, 2024, vol. 14, issue 2, 197-213

Abstract: A low-protein diet (LPD) in chronic kidney disease (CKD) patients delays the natural progression towards end-stage renal disease. The identification of the factors that guarantee patients' adherence to the diet may help physicians to provide a better assistance as well as improving patients' quality of life. Fifty-one patients following a LPD were asked to assess their satisfaction with the diet, difficulties in complying with the nutritional regime and if they felt their health had improved. A random effect ordered probit model, whose dependent variable is patients' perceived health states (better, unchanged, worse) following the diet was estimated. After six months, 49% of patients stated that their conditions improved. Age, gender and number of comorbidities had an impact on the probability to report worse health conditions. The results emphasise the importance of an appropriate nutritional regime for CKD patients and signal the need to design support programs to promote adherence.

Keywords: chronic kidney disease; CKD; low-protein diet; LPD; random effects ordered probit model; promoting adherence. (search for similar items in EconPapers)
Date: 2024
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