School Absenteeism Among Children and its Correlates: A Predictive Model for Identifying Absentees.

ABSTRACT

Objectives: To determine the magnitude of absenteeism and its correlates and to develop a model to predict absenteeism in school children. Design: A cross-sectional study. Setting: Three government schools in Delhi. Participants: 704 students, aged 10 to15 years. Methods: Students were registered and interviewed using a pre-designed questionnaire. The frequency and causes of school absenteeism were ascertained by school records, leave applications and one month’s recall. The factors were subjected to univariate analysis and a stepwise multiple logistic regression analysis and a predictive model was developed. Results: The average absenteeism of a student over 6 months was 14.3±10.2 days (95% CI 13.5-15.0). 48% children absented themselves for more than two days per month on an average. The main factors associated with school absenteeism were younger age, male sex, increasing birth order, lower levels of parental education and income, school truancy, school phobia and family reasons. The discriminating ability of the predictive model developed was 92.4%. Conclusions: It is possible to identify potential absentees in school children.