Assessment of the Prevalence of Kidney Stone Disease: A  Structural Equation Model

Authors

Structural equation modeling (SEM), Confirmatory factor analysis (CFA), Patients with Kidney stone disease, Stone size and Demographic variables.

Background : This study entitled “Assessment of the Prevalence of Kidney Stone Disease: A Structural

Equation Model” deals with the Kidney stones are of many types and have many causes, treatment depends

on the size, nature and cause of the stone. Calcium and Oxalate stones are the most common varieties.

Changes in the daily intake of Sodium, Protein, Calcium, Oxalate and fluid will slow stone formation.

Dietary restrictions slow but do not cure kidney stones.

Materials and Method : A retrospective cross-sectional study design was conducted. In this study, we have

discussed the detection of kidney stones using structural equation modeling (SEM).

Results : In general, structural equation models with scores for these measures of 0.9 or above are considered

to have acceptable model fit and RMSEA is also a very popular measures this value is 0.19. This value

indicates a not good model fit.

Conclusion : There is strong evidence that there is no association between stone size, age, sex, height, BMI,

and hydronephrosis.

K. Lokesh1 , K. Alagirisamy2 , P. Manigandan1 , D. Pachiyappan1

1 Research Scholar, 2Assistant Professor, Department of Statistics, Periyar University, Salem-11, Tamilnadu, India