https://orcid.org/0000-0002-9293-9693
ABSTRACT
We examined the prevalence and evaluated the associated risk and protective factors of adolescent school truancy through sex-stratified models by analysing 7562 adolescent data from the Global School-based Student Health Survey (GSHS) of three South Asian countries: Afghanistan, Bangladesh, and Pakistan. The prevalence of school truancy was 26.6%. The highest truancy was found in Bangladesh (37%), followed by Pakistan (24.7%) and Afghanistan (14.7%). Male adolescents had a 2.05 times higher relative risk ratio (RRR) [95% CI: 1.29, 3.28] of having truancy of ≥ 3 days (last month) than the female respondents. Respondents of older age, bullied, and injured had significantly higher RRR of truancy of ≥ 3 days than their counterparts. Household food insecurity also significantly increased male and female students’ RRR of school truancy. However, peer and high parental support significantly reduced the RRR of 1–2 days and ≥ 3 days of truancy of male and female students.
Introduction
School truancy occurs when students detach themselves from school (Epstein & Sheldon, Citation2002). Broadly, school truancy refers to the behavioral or habitual practice of unexcused absence from school by students, which has become a significant concern for most stakeholders involved in education (Zhang et al., Citation2010). Additionally, scholars like Van Breda (Citation2006) defined school truancy in multidimensional ways resulting from various psychological, social, and institutional factors (Van Breda, Citation2006). However, a recent study reviewed the definition of school attendance problems and defined truancy using three concepts, such as (i) skipping classes, (ii) intentional absence from school or missing classes, and (iii) school non-attendance (Heyne et al., Citation2019; Gentle-Genitty et al., Citation2015).
Several studies reported that school truancy in childhood has detrimental consequences in later life course phases (Attwood & Croll, Citation2006; Ramberg et al., Citation2019). For example, truancy, particularly chronic truancy, has a significant negative association with school completion, academic achievement, post-school outcomes, social adjustments, and other socioeconomic outcomes (e.g. truants have a higher risk of living in poverty, lower employment opportunities and salary, and highly depended on social benefits compared to those who did not miss school) (Baker et al., Citation2001; Huizinga et al., Citation2000; Mueller & Stoddard, Citation2006). Moreover, truancy, accompanied by school failure, is a significant predictor of adolescent multiple health risk behaviours; for example, illicit drug use, cigarette smoking, alcohol consumption, and risky sexual practices (Best et al., Citation2006; Chou et al., Citation2006; Kokkevi et al., Citation2007; White et al., Citation2007). In addition, delinquent behaviours, such as burglary, vandalism, gang activity, auto theft, and adult criminal activity are also linked to truancy (Balfanz et al., Citation2003; Dryfoos, Citation1991; Siziya et al., Citation2007). Therefore, truancy is significantly associated with harmful social and health outcomes as well as poor academic performance, which has become a salient public and social concern and needs to be monitored in all countries (Siziya et al., Citation2007; Yoep et al., Citation2016).
Recent studies on truancy and its predictors have been conducted in the field of public health and psychology from high-income and developed countries, and reported a lower prevalence of truancy in high-income countries in comparison with low- and middle-income countries (Muula et al., Citation2012; Seidu et al., Citation2021). For instance, the prevalence of truancy was 31% in Ghana (Seidu et al., Citation2019), and 30.8% in Malaysia (Yoep et al., Citation2016) using the data from the same GSHS 2012, as well as the prevalence of truancy in Mozambique was 36.6% (Seidu, Citation2019), and in Tanzania was 25.7% (Seidu et al., Citation2021) using the GSHS 2015 data. In opposition, studies using nationally representative data, the National Survey on Drug Use and Health (NSDUH) in the United States reported 10.8% truancy among adolescent in 2002 and 11% truancy in 2009 and 2014 (Maynard et al., Citation2017; Vaughn et al., Citation2013). Moreover, in the low and middle-income countries in the Asian region, the prevalence of truancy (past month) was 24.8% in six countries of Southeast Asia, according to GSHS 2014-15 (Pengpid & Peltzer, Citation2017), while 40.7% in Laos (Pengpid & Peltzer, Citation2019). Hence, the prevalence of truancy in low- and middle-income countries is higher because students from socio-economically disadvantaged schools had a higher likelihood to miss school compared to students in advantaged schools (OECD, Citation2019; Sosu et al., Citation2021).
Several socio-demographic, externalizing behaviour, internalizing symptoms, and protective indicators were linked to truancy among school adolescents (Pengpid & Peltzer, Citation2019). For example, socio-demographic factors comprise being male, having poor socioeconomic status, and older age (15 years and older) (Muula et al., Citation2012; Siziya et al., Citation2007; Uppal et al., Citation2010, Citation2010). In addition, a recent cross-sectional study argued that adolescents living in residential care are more likely to be truant and have grade retention (Santos et al., Citation2023). Externalizing factors for school truancy may comprise injury, bullying, physical fighting, substance use, soft drinks consumptions, and low academic performance (Bailey et al., Citation2015; Holtes et al., Citation2015; Kholasezadeh et al., Citation2013; Muula et al., Citation2012; Shah et al., Citation2012; Siziya et al., Citation2007). Moreover, internalizing factors, like anxiety or depressive symptoms, were significantly associated with adolescents truancy (Finning et al., Citation2019; Lehmkuhl & Lehmkuhl, Citation2004). Additionally, protective factors, including communication problems with peers, poor peer support, weak parental support, or complications with parents, were associated with adolescents truancy (Lehmkuhl & Lehmkuhl, Citation2004; Muula et al., Citation2012; Siziya et al., Citation2007; Vaughn et al., Citation2013).
While the prevalence and predictors linked to truancy in developed countries have been fairly reported, the situation in low- and middle-income countries still needs to be documented. Although a few studies have been conducted on truancy in some Asian countries (i.e. Southeast Asian countries), limited studies have focused on South Asian countries like Afghanistan, Bangladesh, and Pakistan. For example, a recent study from the Sylhet division in Bangladesh acknowledged truancy as the reason for poor academic achievements, early dropouts, and hindered lifetime income (Bakth & Hasanuzzaman, Citation2023). Another study using Pakistan GSHS 2009 reported that truant adolescents were more likely to engage in physical fights (Shaikh et al., Citation2020). Similarly, a cross-sectional study using Afghanistan GSHS 2014 claimed that Afghan truant adolescents showed multiple psychological distress (Pengpid & Peltzer, Citation2020b). Moreover, to tackle the challenges of educational sectors, Bangladesh has adopted National Education Policy 2010 (MOE, Citation2010), along with the recent Education Sector Plan (ESP) fiscal years 2020/21–2024/25 (MOE, Citation2020); Pakistan drafted their National Education Policy for 2017–2025 (Ministry of Federal Education and Professional Training, Citation2017), and Afghanistan implemented National Education Strategic Plan 2017–21 (Ministry of Education, Citation2016).
The pre-adult age groups shared a good percentage of the total population and worked as a catalyst for socioeconomic development and the future well-being of any society; therefore, the Sustainable Development Goals (SDGs) 2030 will not be obtained without minimizing the prevalence of school truancy (Alegana et al., Citation2021; UNESCO, Citation2015). Therefore, our study aimed to fill this gap in the literature by estimating the prevalence of truancy with its associated factors among adolescents from three South Asian countries. We used cross-sectional GSHS data to examine the prevalence and associated risk and protective factors of school truancy among adolescents in three South Asian countries: Afghanistan, Bangladesh, and Pakistan. In addition, we also presented the sex differences in the prevalence of truancy and its predictors. The findings of this study aim to support designing interventions that could diminish the negative consequences of truancy in these three countries.
Methods
Study design
We used the latest Global School-based Student Health Survey (GSHS) datasets of three South Asian countries: Afghanistan, Bangladesh, and Pakistan, conducted in 2014, 2014, and 2009 respectively (World Bank, Citation2023). The GSHS is a nationally representative school-based cross-sectional survey collecting a wide set of variables, such as demographics, physical activity, tobacco use, violence, schooling, and mental health among school-going adolescents aged 13–17 years. The World Health Organization (WHO) initially developed GSHS in 2003 in participation with UNESCO, UNICEF, and UNAIDS with the technical support of the Centre for Disease Control and Prevention (CDC) (Owusu et al., Citation2022).
Settings and sampling procedure
During the survey, Afghanistan, Bangladesh, and Pakistan – three South Asian countries – had a population of 32.72 million, 156 million, and 190.1 million, respectively. Afghanistan and Pakistan are neighbouring countries, and Bangladesh became independent from Pakistan in 1971. The sample size in the latest GSHS survey in Afghanistan was 2579, 2989 in Bangladesh, and 5192 in Pakistan. After dropping 3198 cases due to missing values in the outcome variable, we included 7562 students as the final analytical sample in our study.
The GSHS used a two-stage cluster sampling method to generate a representative sample of students (13–17 years). At first, schools were selected with a probability proportional approach to enrolment size, and then classes were selected randomly. All students in a class were requested to participate and complete questionnaires in the classroom. The GSHS survey was authorized in each country by their respective national government administration and institutional review board or ethics committee. All participants in the survey required written or verbal consent (Guan et al., Citation2022; Pengpid & Peltzer, Citation2019). The data sets are freely downloaded from https://extranet.who.int/ncdsmicrodata/index.php/catalog/GSHS.
Measures and definitions
The description of variables, questions, and coding of the variables used in the GSHS questionnaire and for this study is listed in the Appendix, .
Outcome variable
Truancy was the outcome variable of the study, measured from the question: ‘During the past 30 days, on how many days did you miss classes or school without permission?’ The responses were 1 = 0 days, 2 = 1 or 2 days, 3 = 3 to 5 days, 4 = 6 to 9 days, and 5 = 10 days or more. The responses were then coded as 0 = 0, indicating no truancy; 1 = 1–2 days, and 2 = 3 or more days, indicating truancy.
Explanatory variables
Sixteen variables under four domains: socio-demographic factors (i.e. age, sex, and being hungry as a proxy for socioeconomic status), externalizing behaviour (i.e. current tobacco use, soft drinks intake, in physical fight, being bullied, physically attacked, and being injured), internalizing behaviour (i.e. having no close friends, anxiety, loneliness, suicide ideation and suicide plan), and protective factors (i.e. peer support, parental supervision, parental connectedness, parental bonding and parental support) were included in this study (see Appendix, ). These variables were included in the analysis due to their association with truancy founded in previous studies (Attwood & Croll, Citation2006; Kholasezadeh et al., Citation2013; Muula et al., Citation2012; Pengpid & Peltzer, Citation2017, Citation2019; Seidu et al., Citation2019; Siziya et al., Citation2007; Vaughn et al., Citation2013; Yoep et al., Citation2016).
Data analysis
Data analysis was conducted using STATA version 14 software for MS Windows (Stata Corporation, Texas, U.S.A.). We used descriptive statistics to explore the general characteristics of the study population with sex-stratified samples as male and female disproportionately reported school truancy and we applied Pearson’s chi-square values to report the differences in the outcome variable (truancy) against the sub-categories of explanatory variables (). We also used multinominal regression analyses to examine the associations between explanatory variables and the outcome variables for the total population as well as sex-stratified data (). The results from multinominal regression analyses were reported as unadjusted relative risk ratio (URRR), adjusted relative risk ratio (ARRR), and 95% confidence interval (CI), represented in . The statistical significance level was set at p ≤0.05.
Table 1. Respondents’ characteristics and prevalence of school truancy of school-going adolescents in three countries of South Asia (n = 7562).
Table 2. Male respondents’ characteristics and prevalence of school truancy of school-going adolescents in three countries of South Asia (n = 4543).
Table 3. Female respondents’ characteristics and prevalence of school truancy of school-going adolescents in three countries of South Asia (n = 3019).
Table 4. Associations of independent variables with 1–2 days and ≥3 days of school truancy (with 0 days as a reference category) in three countries of South Asia (n = 7562).
Table 5. Sex differences in the associations of independent variables with 1–2 days and ≥3 days of school truancy (with 0 days of school truancy as reference category) in three countries of South Asia.
Results
Respondents’ characteristics
Among the total sample (N = 7562), about 60% were male, and 40% were female. About 57% of respondents were 13–14 years old, and 33% were 15 years. Six percent of respondents were current tobacco users, 7% had no friends, 35% had experienced bullying, and 49% had low parental support. In this study, one-tenth of in-school adolescents came from food-insecure households ().
Among the male respondents, 55% were ≤14 years old, 9% came from food-insecure households, 41% experienced physical fights, 40% experienced bullying, 6% had no close friends, 7.5% had anxiety, 12% had loneliness, and 53% had low parental support (). On the other hand, among the female respondents, 59% were ≤14 years old, 11% came from food-insecure households, 18% experienced physical fights, 28% experienced bullying, 10% had no close friends, 12% had anxiety, 17% had loneliness, and 40% had low parental support during the survey ().
Prevalence of truancy
The prevalence rate of truancy was 26.6% among the total respondents, while the rate was 20.4% among females and 30.8% among male respondents. Bangladesh had the highest rate of truancy (37%), followed by Pakistan (24.7%) and Afghanistan (14.7%). In addition, school-going respondents aged 15 years had the highest truancy rate (30.2%), followed by the age group 13–14 (25.5%) ().
Among the male respondents, 24% had 1–2 days of school truancy, and 6.4% had school truancy of ≥3 days. In addition, male respondents of current tobacco use (57.3%), Bangladeshi (43,7%), bullied (34.5%), physically attacked (29%), suicide planners (34.5%), and low parental support (36.6%) had a higher truancy rate (). On the other hand, among all female respondents, 17% had 1–2 days of school truancy, and 3% had school truancy of ≥3 days. Besides, among the female respondents, the rate of school truancy was higher among 15 years old (24.8%), Bangladeshi (32%), current tobacco users (29%), experienced bullying (19%), physically attacked (19.5%), and had low parental support (31%) ().
Factors associated with truancy
We performed multinominal regression analysis on the total in-school respondents and sex-stratified samples to examine the associations of the exploratory variables with the outcome variable: truancy (1–2 days and ≥3 days, with 0 days as a reference category). In the total sample model, male respondents had a 2.05 times higher relative risk ratio (RRR) of having truancy of 3 and more days than the RRR of truancy of female respondents in the adjusted analysis [ARRR = 2.05, 95% CI: 1.29, 3.28] (). In addition, students coming from food insecure (mostly/always) households had 2.2 times higher RRR of having truancy of 3 and more days than the RRR of truancy of respondents coming from families having food security in the adjusted analysis [ARRR = 2.2, 95% CI: 1.20, 4.01]. Moreover, Bangladeshi respondents had a 2.13 times higher RRR of having truancy of 3 and more days than the RRR of truancy of Afghan respondents in the adjusted analysis [ARRR = 2.13, 95% CI: 1.10, 4.13]. We also found that respondents who experienced bullying [ARRR = 1.74, 95% CI: 1.15, 2.62], and were injured [ARRR = 1.59, 95% CI: 1.11, 2.27] had a significantly higher RRR of having truancy of 3 and more days than their counterparts. In addition, respondents who were tobacco users [ARRR = 2.57, 95% CI: 1.60, 4.15] and carbonated soft drinks takers (≥2 times/day) [ARRR = 2.36, 95% CI: 1.54, 3.62] had a significantly higher relative risk ratio (RRR) of having truancy of 1–2 days than the respondents of non-tobacco users and limited carbonated soft drinkers, respectively ().
According to sex-stratified analyses, male respondents of 15 years old [ARRR = 1.13, 95% CI: 1.03, 1.64], were bullied [ARRR = 1.58, 95% CI: 1.21, 2.06] and heavy carbonated soft drinkers (≥2 times/day) [ARRR = 2.94, 95% CI: 2.30, 3.74] had a significantly higher RRR of having truancy of 1–2 days than their counterparts. In addition, both Bangladeshi [ARRR = 8.20, 95% CI: 5.26, 12.79] and Pakistani [ARRR = 2.58, 95% CI: 1.64, 4.06] male respondents had a higher RRR of having truancy of 1–2 days than the male respondents of Afghanistan ().
On the other hand, female respondents from food insecure households, were tobacco users, and experienced bullying had a significantly higher RRR of truancy of 1–2 days and ≥3 days than their counterparts. In addition, female in-school respondents from Bangladesh [ARRR = 3.23, 95% CI: 2.34, 4.47] and Pakistan [ARRR = 1.74, 95% CI: 1.28, 2.34] had a significantly higher RRR of having truancy of 1–2 days than the female respondents in Afghanistan; however, these relationships were non-significant in case of the RRR of having truancy of ≥3 days ().
Protective factors associated with truancy
We examined the role of protective factors: peer support, and parental support on truancy and found that higher peer support of the students significantly lowered the RRR of having truancy of ≥3 days [ARRR = 0.63, 95% CI: 0.41, 0.97] than the respondents had no or low peer support; however, these relationships were non-significant in case of the RRR of having truancy of 1–2 days. Moreover, medium [ARRR = 0.58, 95% CI: 0.41, 0.84] and high parental support [ARRR = 0.60, 95% CI: 0.36, 0.98] of the respondents also significantly lowered the RRR of having truancy of 1–2 days than those with low parental support ().
For sex-specific analysis, we found that higher peer support of female students significantly lowered the RRR of having truancy of ≥3 days [URRR = 0.75, 95% CI: 0.59, 0.96] than females with lower or no peer support in the unadjusted model; however, this association was no longer significant in the adjusted model. Interestingly, higher peer support for male students significantly increased the RRR of truancy of 1–2 days [ARRR = 1.42, 95% CI: 1.12, 1.80] than male students with no or low peer support. In addition, higher parental support significantly lowered the RRR of 1–2 days and ≥3 days of truancy for male and female school-going respondents than their counterparts with low parental support ().
Discussion
The study examined the prevalence and factors linked to school truancy through sex-stratified models using a large representative sample of school-going adolescents from three South Asian countries.
Prevalence of truancy
In our study, the prevalence of school truancy in three countries (past month) was about 21% (1–2 days) and more than 5% (3 or more days). In terms of countries, the prevalence of truancy (past 30 days) was higher in Bangladesh (37%) compared to Pakistan (24.7%) and Afghanistan (15%). However, the findings were similar to previous empirical studies among adolescents from low- and middle-income countries in Southeast Asia as well as Africa and these studies measured truancy in the same way using the GSHS data (Muula et al., Citation2012; Pengpid & Peltzer, Citation2017; Shah et al., Citation2012; Siziya et al., Citation2007). Moreover, the prevalence of truancy in Bangladesh and Pakistan was higher than in Vietnam, Thailand (Pengpid & Peltzer, Citation2017), Malaysia (Yoep et al., Citation2016), and the U.S.A. (Vaughn et al., Citation2013). The credible logic for the higher rate of truancy in the three countries of this study is that adolescents from poor socioeconomic conditions could miss school for joining earning activities or household chores (Muula et al., Citation2012).
There are other possible explanations for why the prevalence of truancy is higher in these three countries, particularly in Bangladesh. Adolescents from disaster-affected regions with low levels of parental education and poorer household have a greater level of truancy in Bangladesh (Bakth & Hasanuzzaman, Citation2023; Farah et al., Citation2017; Kumar & Saqib, Citation2017). For example, during disasters, nearly 30% of schools in Bangladesh are used as shelter centres, while many schools went waterlogged and damaged during monsoons, resulting in truancy. Accordingly, environmental shocks (i.e. floods) are essential factors for temporary migration and force adolescents to be involved in alternative earning sources causing adolescent’s truancy and dropouts (Amin et al., Citation2004; Bakth & Hasanuzzaman, Citation2023; Joarder & Miller, Citation2013). Kumar & Saqib reported that one-fourth of children (aged 7–14 years) in rural Bangladesh missed classes at least a day/week (Kumar & Saqib, Citation2017), and nearly 4.3% of children (5–14 years) in Bangladesh engaged in the labour market as full-time workers and 6.8% worked as part-time along with their school enrolment (ILO Bangladesh, Citation2015). Moreover, teenage marriage is another reason for truancy and dropout among poor adolescents in Bangladesh (Uddin, Citation2021). Studies conducted in Karak District, Pakistan, and Kabul City, Afghanistan, also acknowledged the above-mentioned reasons for adolescents truancy in Pakistan and Afghanistan (Suleman et al., Citation2017; Totakhail, Citation2015).
Furthermore, the sex-stratified analysis suggested that the prevalence of school truancy was greater among male students than females. This pattern is the same for all three South Asian countries in this study. Similarly, most of the previous studies using the GSHS survey from ASEAN member states (six Southeast Asian countries) (Pengpid & Peltzer, Citation2017), Ghana (Seidu et al., Citation2019), Mozambique (Seidu, Citation2019) and Timor-Leste (Owusu et al., Citation2022) reported the higher prevalence of school truancy among male adolescents. Although some studies from Tanzania and Kuwait showed a higher prevalence among female adolescents (Pengpid & Peltzer, Citation2020a; Seidu et al., Citation2021). Therefore, the current findings of this study are a matter of concern and demand urgent intervention programmes highlighting sex dynamics in society due to cultural expectations towards males and females (Siziya et al., Citation2007).
Factors associated with truancy
In line with previous studies, our study found socio-demographic factors, such as being male, being older (16 or more years), and having hunger experience (proxy of poor socioeconomic status) were significantly associated with adolescent truancy (Muula et al., Citation2012; Pengpid & Peltzer, Citation2017; Siziya et al., Citation2007; Uppal et al., Citation2010). Male adolescents were more likely to be truant due to cultural expectations and involvement with income-generating activities, as truancy in male adolescents may be more accepted than in girls (Muula et al., Citation2012; Siziya et al., Citation2007). In contrast, previous studies reported that the prevalence of school truancy was greater among female adolescents than male adolescents (Maynard et al., Citation2017; Pengpid & Peltzer, Citation2017). Additionally, older school adolescents were more likely to be truant because of reduced parental influences (Pengpid & Peltzer, Citation2020a). Moreover, adolescents who experienced hunger were expected to be truant; because school-going adolescents from poor households had a greater risk of hunger and may miss school to engage in income-source activities (Muula et al., Citation2012; Seidu et al., Citation2019). Further investigation is required to understand the dynamics of sociocultural factors and school truancy.
In terms of externalizing symptoms, current tobacco use, frequent soft drink intake, being in a physical fight, being bullied, being physically attacked, and being injured increased the likelihood of being truant. These similar findings were reported among adolescents in Kuwait (Pengpid & Peltzer, Citation2020a), Malaysia (Shah et al., Citation2012), Ghana (Seidu et al., Citation2019), and seven Southeast Asian countries (Pengpid & Peltzer, Citation2017). In order to avoid bullying victimization and physical violence, adolescents may miss school and involve them more likely in tobacco use if there is poor control from school and parents. Some studies argued that frequent soft drink consumption increased adolescents’ risk of violent behaviours and made them vulnerable to being truant (Solnick & Hemenway, Citation2012). In addition, students who engage in physical attacks or fights might suffer from injuries requiring medical care and absence from school (Seidu et al., Citation2019). Therefore, the school authority may monitor and take effective prevention strategies regarding fighting among school adolescents.
Furthermore, in agreement with previous studies, our analysis documented that some internalizing symptoms (anxiety and loneliness) were associated with adolescent truancy, which called for attention to address these multiple conditions in combined interventions (Lehmkuhl & Lehmkuhl, Citation2004). For example, lonely adolescents were more likely to be truant in Tanzania (Seidu et al., Citation2021). Previous studies also showed that adolescents with their delinquent friends were more likely to be truant, as truant adolescents with a truant peer might be involved with similar behaviours being kind and supportive to them (Henry & Huizinga, Citation2007; Siziya et al., Citation2011). Moreover, this study did not find a statistically significant association of suicidal behavior with truancy, while some previous research reported suicidal attempts as a significant internalizing symptom of school truancy (Lehmkuhl & Lehmkuhl, Citation2004; Pengpid & Peltzer, Citation2020a).
Protective factors associated with truancy
Similar to previous studies, our analysis found that peer and parental support had a significant protective role against school truancy (Lehmkuhl & Lehmkuhl, Citation2004; Muula et al., Citation2012; Pengpid & Peltzer, Citation2020a; Siziya et al., Citation2007; Vaughn et al., Citation2013). In addition, these studies argue that peer and parental support might encourage adolescents to attend school regularly. Hence, social interventions to strengthen peer and parental support are valuable for reducing adolescent school truancy in these three South Asian countries.
The biggest strength of this study was to analyse nationally large-scale representative data from lower-income three neighbouring countries in South Asia. However, the study acknowledged some limitations. First, as the GSHS was a cross-sectional data, it was impossible to estimate any causality. Second, as the GSHS collected information using a self-completed questionnaire, it may provide desirable information. Besides, there was a chance of misreporting the number of days they missed school for recall bias. Third, the survey considered only adolescents who attended on the survey day, which might influence the estimation of truancy prevalence, particularly students who were excluded from the study. Fourth, the responses to the predictors of school truancy were categorical. We further re-coded them as dummy variables for our analysis, which might have affected the statistical power of the analysis. Fifth, some variables, i.e. anxiety and loneliness, in the GSHS survey, were measured using a single item of questions; future studies should use comprehensive items of measurements and scale. Lastly, we used datasets from the last GSHS surveys of each country, which were done a couple of years ago. However, as the survey was country-representative with a large sample of in-school adolescents, it is still useful as a baseline study on school truancy.
Conclusion
This study was unique and contributed to filling the gap in the scientific literature on truancy in the context of South Asian low-income countries using nationally representative data and sex-specific analysis that documented a relatively higher prevalence of school truancy among school adolescents. Socio-demographic factors (i.e. age, sex, and poor socioeconomic status), externalizing factors (soft drink intake, tobacco use, in a physical fight and attacked, being bullied), internalizing symptoms (anxiety and loneliness) and socio-familial protective factors (peer and parental support) were reported to be significant predictors of truancy among school going adolescent in Bangladesh, Pakistan, and Afghanistan. To address school truancy, all stakeholders in education and parents combined with a whole school approach are needed to draft preventive interventions for school truancy as well as promote health and well-being of adolescents (Simões et al., Citation2021). Moreover, accessible and free educational programmes and behaviour change communication interventions about health risk behaviours during adolescence are also required to reduce the negative consequences of school truancy and attain the educational targets of the Sustainable Development Goals with quality education.
CRediT Author Contribution Statement
Md. Khalid Hasan: Conceptualization, Methodology, Investigation, Formal Analysis, Writing – Original Draft, Writing – Review & Editing, Supervision. Helal Uddin: Conceptualization, Writing – Original Draft, Writing – Review & Editing. Tahmina Bintay Younos: Conceptualization, Methodology, Formal Analysis, Writing – Review & Editing. Nur A Habiba Mukta: Conceptualization, Methodology, Formal Analysis, Writing – Review & Editing. Dilara Zahid: Conceptualization, Writing – Review & Editing.
Ethics statement
Ethical approval for the survey was granted by the World Health Organization’s Ethical Committee. In addition, the GSHS survey was authorized in each country by their respective national government administration and institutional review board. The data sets are freely downloaded from https://extranet.who.int/ncdsmicrodata/index.php/catalog/GSHS
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability statement
Data associated with this study has been deposited at WHO and can be downloaded from https://extranet.who.int/ncdsmicrodata/index.php/catalog/GSHS.
Correction Statement
This article has been corrected with minor changes. These changes do not impact the academic content of the article.
Additional information
Funding
Notes on contributors
Md. Khalid Hasan
Md. Khalid Hasan is an Associate Professor at the Institute of Disaster Management and Vulnerability Studies, University of Dhaka. His research has focused on public health, disaster preparedness, disaster management, climate change impact and adaptation, adolescent health and wellbeing, and health in disasters and emergencies.
Helal Uddin
Helal Uddin is a Senior Lecturer in the Sociology Department at East West University, Bangladesh. Currently, He is pursuing his Erasmus Mundus Master’s in Public Health in Disasters conducted by the University of Oviedo, Spain, and Karolinska Institute, Sweden. His research interests focus on social determinants of health, childhood adversity, and child and adult health.
Tahmina Bintay Younos
Tahmina Bintay Younos is a graduate student of the Department of Geosciences at Texas Tech University. She completed her Bachelor's and Master's degrees in Disaster Management from the Institute of Disaster Management and Vulnerability Studies, University of Dhaka. Her research interests are disaster preparedness and management, public health and wellbeing, GIS and RS applications in disasters and emergencies, and climate change adaptations.
Nur A Habiba Mukta
Nur A Habiba Mukta graduated in Sociology from East West University, Bangladesh. Right now, she works as an independent researcher. Her area of interest includes maternal and child health and sociology of health and illness.
Dilara Zahid
Dilara Zahid is an Associate Professor and Director of the Institute of Disaster Management and Vulnerability Studies, University of Dhaka. Her current research focuses on child protection, education in emergency, disaster preparedness, disaster governance, and youth volunteerism.
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Appendix
Table A1. Description of the variables used in the study.