Assessing differences in hours worked between male and female dentists: an analysis of cross-sectional national survey data from 1979 through 1999.
BACKGROUND
Women are increasingly entering the dental work force. This study examines the impact of sex, age and other demographic characteristics on dentists' work force participation and on hours worked from 1979 through 1999.


METHODS
The study drew on cross-sectional data on dentists (4,209 men and 354 women) from national population surveys conducted by the U.S. Bureau of Labor Statistics from 1979 through 1999. The authors used descriptive statistics and regression analyses to examine sex differences in work force participation and in hours worked across age, as well as other factors.


RESULTS
Work force participation was high for both men and women. Men worked more hours and worked part time less frequently; they worked more than 42 hours per week more frequently. Older dentists worked fewer hours, with a larger impact of age seen among men. Having children had a significantly greater effect on the number of hours worked per week among female dentists than among male dentists.


CONCLUSIONS
There were significant differences in dentists' hours worked by sex and by age. The consistency of the results with past studies suggests these differences will hold in the near future.


CONCLUSIONS
Women's entry into the dental work force has been significant and has helped maintain the supply of dentists. Sex differences in the work force should be considered in evaluating the supply of dentists and related work force policy.
Walton
Surrey M
SM
University of Illinois at Chicago, College of Pharmacy, Department of Pharmacy Administration, 60612-7231, USA. Walton@uic.edu
Byck
Gayle R
GR
Cooksey
Judith A
JA
Kaste
Linda M
LM
D000328:Adult; D003430:Cross-Sectional Studies; D003815:Dentists / Q000706:statistics & numerical data*; D003816:Dentists, Women / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D008297:Male; D017533:Marital Status; D008875:Middle Aged; D015999:Multivariate Analysis; D010298:Parity; D010561:Personnel Staffing and Scheduling / Q000706:statistics & numerical data*; D012044:Regression Analysis; D014481:United States; D016526:Workload / Q000706:statistics & numerical data*