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).