Identifying the Smoking and Smokeless Tobacco-Related Predictors on Frequencies of Heavy Vehicle Traffic Accidents in Bangladesh: Linear and Binary Logistic Regression-Based Approach

Table 1

Elaboration of the response and different predictors for RTAs.

Ser. No.	Response/predictors	Elaboration	Value range
1	AccidentFreq	Frequency of accidents
2	AvgCigPerDay	The average number of cigarettes smoked each day	Natural numbers
3	NosmokePerDrivHr	Number of smoking per hour of driving	Natural numbers
4	SmokeDurDrive	Status of whether a driver smokes while he is driving	Yes, no
5	Foursmokemore	Status of smoking four or more cigarettes per day	Yes, no
6	Age	Age of each driver	Natural numbers
7	DrivingHour	Number of hours taken to drive	Natural numbers
8	CigUseYr	Number of days per year that people smoke cigarettes	Natural numbers
9	NoSmokeDurDrive	Number of smoking while driving	Natural numbers
10	SmokeorTobaccoStatus	Status of smoking (yes or no)	Yes, no
11	SmokeDaily	Status of whether a driver smokes every day	Yes, no
12	TypeofSmoke	Number of the type of smoking a driver uses	Natural numbers
13	TypofSmklessTobc	Type of tobacco-free smoking	Gul, Jarda, Khoini, White-pata, no consumption
14	SmkLessTobDailyStat	Status of a driver’s less-than-daily tobacco use	No consumption, daily, sometimes