Selected article for: "log likelihood and logistic regression analysis"
Author: Selvaraj, Siddharthan; Naing, Nyi Nyi; Wan-Arfah, Nadiah; de Abreu, Mauro Henrique Nogueira Guimarães
Title: Demographic and Habitual Factors of Periodontal Disease among South Indian Adults
  • Cord-id: 4vthfanx
  • Document date: 2021_7_26
    • ID: 4vthfanx
    Snippet: The aim of this study was to evaluate the performance of a set of sociodemographic and habits measures on estimating periodontal disease among south Indian adults. This cross-sectional study was carried out among 288 individuals above 18 years old in Tamil Nadu, India. The outcome of the study was periodontal disease, measured by WHO criteria. The covariates were age, ethnicity, smoking and alcohol habit. The assessment of factors predicting periodontal disease was carried out by multiple logist
    Document: The aim of this study was to evaluate the performance of a set of sociodemographic and habits measures on estimating periodontal disease among south Indian adults. This cross-sectional study was carried out among 288 individuals above 18 years old in Tamil Nadu, India. The outcome of the study was periodontal disease, measured by WHO criteria. The covariates were age, ethnicity, smoking and alcohol habit. The assessment of factors predicting periodontal disease was carried out by multiple logistic regression analysis using R version 3.6.1. The demographic factors like age group (AOR = 3.56; 95% CI 1.69–7.85), ethnicity (AOR = 6.07; 95% CI 2.27–18.37), non-alcoholic (AOR = 0.31; 95% CI 0.13–0.64) and non-smoking (AOR = 0.33; 95% CI 0.15–0.67) were found to be associated with the outcome. The maximum log likelihood estimate value was −30.5 and AIC was 385 for the final model, respectively. Receiver operating characteristic (ROC) curve for the periodontal disease was 0.737. We can conclude that sociodemographic factors and habits were useful for predicting periodontal diseases.

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