Data Analysis:
Data were coded and analyzed using SPSS 26. The socio-demographic variables of the respondents were presented using descriptive statistics. Descriptive statistics (frequency, percentage and mean) was used to determine the level of quality of life of the quarry workers. The score on the quality of life were computed and converted to scale 100 as per scoring guideline. Simple logistic regression was used to screen the independent variables. The independent variables with significance value less than 0.25 were selected for multiple logistic regression. Backward and forward variable selection approach was used in the multiple logistic analysis. The final multiple logistic regression model included those independent variables with significant value of less than 0.05. Model fitness was then assessed based on Hosmer and Lemershow test, classification table and receiver operating characteristics (ROC).