Prevalence and factors associated with alcohol and substance use among secondary school adolescents in central and Eastern Uganda: a cross-sectional study

Abstract

Background

Alcohol and substance use is a major public health concern in Uganda, with limited evidence focused on school-going adolescents. This study determined the prevalence and factors associated with alcohol and substance use among adolescents in secondary schools in Central and Eastern Uganda.

Methods

This cross-sectional study surveyed 1,833 adolescents aged 10–18 years from eight randomly selected secondary schools in Iganga (Eastern) and Mukono (Central) districts. Schools were stratified by ownership (private or public), and geographic setting (eastern or central). We used the Child and Adolescent Symptom Inventory-5 (CASI-5) to assess the primary outcomes: significant use of alcohol, tobacco, marijuana, and impairment from any substance use. Logistic regression models determined the factors independently associated with significant use of alcohol, tobacco, marijuana and impairment from any substance use. Adjusted odds ratios (AOR) and corresponding 95% confidence intervals (95%CI) were reported.

Results

Among 1,833 school-going adolescents, the mean age was 15.1 years (SD ± 1.6), 60% were female, and 50.7% attended urban schools. The prevalence of significant use was 1.7% (n = 30) for tobacco, 3.0% (n = 54) for alcohol, 2.6% (n = 46) for marijuana, and 6.2% (n = 105) reported significant impairment from any substance use. In adjusted analyses, male adolescents had higher odds of marijuana use than females (AOR 2.21, 95%CI 1.17–4.19, p = 0.015). A history of mental illness was associated with higher odds of marijuana use (AOR 2.87, 95%CI 1.45–5.67, p = 0.002), alcohol use (AOR 2.69, 95%CI 1.42–5.09, p = 0.002), and SUD impairment (AOR 1.91, 95%CI 1.14–3.18, p = 0.014) compared to those with no such history. Urban school attendees had higher odds of SUD impairment than rural attendees (AOR 2.37, 95%CI 1.47–3.81, p < 0.001), and adolescents living in huts had higher odds of tobacco use than those in permanent housing (AOR 5.46, 95%CI 1.12–26.59, p = 0.036).

Conclusions

Targeted school-based interventions addressing sex-specific risks, and urban-rural disparities in mental health may help reduce use of alcohol, substances and SUD impairment among adolescent students in central and eastern Uganda.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-025-25944-7.

Introduction

Substance and alcohol use is a persistent public health problem among adolescents. Globally, the number of people using substances rose from 240 million to 296 million between 2011 and 2021 [1]. This rise disproportionately affects adolescents (individuals aged 10 to 19 years) who are particularly vulnerable to the long-term health and social consequences of early substance use [1]. According to the World Health Organization (WHO) 2024 report, 37 million people aged 13 to 15 years used some form of tobacco [2]. Substances such as marijuana, tobacco, as well as alcohol are associated with reduced learning ability, worsening mental health conditions, school absenteeism and poor academic performance [3, 4]. These negative outcomes also has long term strains on educational systems and national development. Low and middle income countries (LMICs) bear the heaviest burden, accounting for 80% of the world’s 1.3 billion tobacco users [5]. In Sub-Saharan Africa (SSA), which has approximately 250 million adolescents, this rising use of substances and alcohol poses a growing threat to youth development, health systems and national economic growth [6, 7].

In Uganda, the national prevalence of substance use among schooling adolescents remains unknown although estimates suggests that 2.6 million youth aged 10 to 24 years are affected by marijuana use nationally [8]. Studies have also shown that living in impoverished circumstances such as informal settlements in urban Uganda settings is associated with alcohol use among youth [9]. Furthermore, 5.6% of students aged 13 to 17 years in Uganda’s capital city, Kampala, smoke tobacco [10]. The WHO ranks Uganda as the highest alcohol consumer in the Africa region with a per capita alcohol consumption of 12.2 L per persons aged 15 years or more which is twofold the African (6.3 L) and global (6.2 L) averages [7].

Nevertheless, substance use among adolescents in Uganda has continued to rise which potentially arises from a broader systemic, and infrastructural problems. Due to the increasing burden and use of substances among young people in Uganda, many associated factors have been identified including poverty, mental health conditions, age and peer pressure [11, 12]. In addition, increased access to illicit substances in Uganda, especially in urban areas has had a major impact on substance use in young people. To our knowledge, there are limited mitigation strategies that focus on reducing the exposure and the prevalence of substance use in young people in Uganda. This is, in part, due to the lack of data on factors associated with substance use among young people, especially those in secondary schools in Uganda yet they are important in enacting interventions that target substance use in this population. However, the implementation of mitigation strategies remains crucial as substance use has been associated with inconsistent condom use [13] and carries significant implications that place considerable burden on individuals, families, and society [14].

This paper focused on filling the gap by comprehensively analyzing a sample of school-going adolescents in central and eastern Uganda to gain more insight on the prevalence and risk factors of alcohol, marijuana, tobacco and any substance use. Our study aimed to determine the prevalence and factors associated with alcohol and substance use among adolescents in secondary schools in Central and Eastern Uganda.

Methods

Study design and setting

 Using a cross-sectional study design, we conducted a school-based survey with adolescents aged 10 to 18 years who attended secondary schools in the Eastern and Central region’s districts of Iganga and Mukono respectively. Adolescents comprise approximately 25% of Uganda’s total population, totaling about 12 million individuals [15]. In the Eastern region, Iganga District is predominantly rural, with an estimated population of 426,596 in 2024 [16]. In addition, Mukono District in the Central region is largely urban and has an estimated 932,672 resident population in 2024 [16]. Parents or caretakers provided consent for their children who were below 18 years to participate, and the students gave assent.

Sampling strategy 

These two districts (Iganga and Mukono) were purposively selected from Uganda’s Central and Eastern regions due to their high population density. Iganga district is predominantly rural compared to Mukono district which is more urban. Iganga also has higher poverty levels and lower childhood immunization rates which could indicate poorer access to general and mental health services than Mukono [16, 17]. District Education Officers (DEOs) for both districts were pre-visited in order to obtain updated lists of all registered secondary schools. DEOs implement education policies, laws, and regulations within their jurisdictions. We categorized the schools based on their rural or urban location, and then used purposive, stratified random sampling to select eight schools, namely, four schools from each district. In both Iganga and Mukono, we randomly selected two public and two private schools, to ensure representation from urban and rural settings. We included students aged 12 to 18 years, aligning with the Ugandan education system: seven years of primary education that usually begins at six years of age, followed by four years of lower secondary (ages 13 to 16 years), and two years of upper secondary (ages 17 to 18 years). We included 12-year-olds to account for early school enrollment, often due to limited access to pre-primary education.

Sample size computation

 Kish and Leslie formula for survey studies was used to calculate a total required sample size of 1,960 representing 980 from each region. We assumed a 20% proportion of mental health conditions among adolescents in secondary schools at a 5% margin of error. We selected a total of 245 adolescents from each school through consecutive recruitment, resulting in 980 participants per region and 1,960 across the two regions. We determined the number of participants per region, school, and class proportionately.

Data collection and management 

We pretested the study tools by randomly selecting two schools (one rural, one urban) in central Uganda, which were not part of the main study. We assessed mental health conditions using Child and Adolescent Symptom Inventory-5 (CASI-5). CASI-5 is a behavior rating scale for DSM-5-defined emotional and behavioral disorders in youths between five and 18 years old. The CASI-5 includes all of the items from both the previously published Child Symptom Inventory-4 (CSI-4) and the Adolescent Symptom Inventory-4 (ASI-4) in a single measure. Prior studies adapted the CASI-5 to adolescents living with HIV in central and South-western Uganda [18]. In this study, the CASI-5 was administered to all study participants in English which is the official language of instruction in secondary schools in Uganda.

The survey was a paper-based, interviewer-administered questionnaire conducted in a private classroom provided by school authorities which ensured privacy and confidentiality of the participants during the interview. The research assistants were psychiatric clinical officers (PCOs) who are diploma-level training mental health officers and are familiar with CASI-5 tools and mental health diagnoses. To ensure privacy and minimize peer influence, students were seated with ample space between them. Trained research assistants were present in each classroom to provide instructions, clarify any questions students had about the survey items, and ensure a standardized data collection process. The survey took approximately 30 to 45 min to complete. The data collected using paper-based questionnaires was entered into EpiInfo by trained research assistant. Data were exported into MS Excel for cleaning. Data was exported to and analyzed using StataNow/MP version 19.5. Analyses were conducted by the first and last authors.

The process of obtaining informed parental consent was initiated through introductory letters to the parents of students sampled that described the study. Letters with study information in English, Luganda or Lusoga languages were sent home with students from the selected schools. These letters invited parents to schedule school meetings where the research team was available to explain the study in detail, answer questions, and address concerns. Parents who did not attend these meetings, follow-up telephone calls were made by the research team to provide additional information and offer another opportunity for consent. Only adolescents who provided both parental consent and their own assent were enrolled in the study.

Study measures

 We computed four categorical outcome variables, namely: alcohol use, tobacco use, marijuana use, and impairment from any substance use using the SUD section of the CASI-5, which measured current or recent behavioral frequency on a 4-point Likert scale (Never, Sometimes, Often, Very often). Participants were asked whether they engaged in behaviors using items such as: “I smoke tobacco cigarettes” (tobacco use), “I drink alcoholic beverages (beer, wine, spirits, liquor)” (alcohol use), and “I smoke marijuana” (marijuana use). Significant use for each outcome was defined as a response of; sometimes, often, or very often. Binary variables were created to indicate significant use of tobacco cigarettes, alcoholic beverages, and marijuana. A binary variable for significant impairment was also created based on the question, “How often do the behaviors in the “Category P” interfere with your ability to do schoolwork or get along with others?”, with a response of sometimes or more frequent indicating clinically significant functional impairment. Impairment on any of the substance use items or on related substance-related problems, including “I get into trouble because of alcohol use” and “I get into trouble because of illegal drug use,” which were also rated on the same Likert scale. The fourth outcome, any substance use disorder (SUD), was defined as significant use of one or more substances occurring with significant self-reported impairment.

To ensure clarity and consistency in participant responses, all questionnaires were administered by PCOs trained in ethical conduct of human subjects’ research who provided standardized explanations for potentially ambiguous terms during the interviews. Covariates were defined as follows: age in years collected as a continuous variable; sex (self-reported as female or male) and history of mental illness was operationalized as a previously diagnosed condition such as depression, severe anxiety, psychosis, or epilepsy were binary (no or yes), age categorized to 10–14 years and 15–18 years, education level referred to the student’s current class level [Ordinary (O’) or Advanced (A’) level]; orphanhood status defined as those whose mother, father, or both had died or not (no or yes); and exposure to domestic violence asked whether the participant witnessed any physical, verbal, and/or psychological abuse in their home (no or yes). School-level covariates included school type i.e. whether day, boarding, or both, school ownership (private or public), and location (rural or urban). To minimize participant misinterpretation, examples were provided. For example, housing type, a proxy indicator socio-economic status described whether their home structures comprised of brisk or mud and wattle walls, and roofing of iron sheets or grass thatched. Participants were encouraged to seek clarification to ensure that they understood the questions in order to enhance the reliability of the data collected.

Statistical analysis

 Descriptive statistics for all study variables were reported using frequencies and their corresponding percentages for categorical variables, means and their standard deviations (SD) for continuous variables. Unadjusted and multivariable logistic regression models were fitted to estimate odds ratios (OR) with 95% confidence intervals (95%CI). Variables with p < 0.25 in the unadjusted analyses were entered into the logistic regression, and backward elimination conducted by sequentially removing non-significant variables (p > 0.05) while assessing for confounding. We fitted the final adjusted logistic regression model with variables that have p < 0.25 in unadjusted models and those identified as potential confounders. Age and sex variables were included appropriately. Statistical significance was considered for variables with p < 0.05.

Results

Among 1,833 study participants, mean age was 15.1 (SD ± 1.6) years, and 60.0% (n = 1,100) were female, and 50.7% (n = 930) were attending urban secondary schools. 15.9% (n = 283) self-reported having a history of mental illness and 14.2% (n = 250) reported witnessing domestic violence. Prevalence of significant use was 1.7% (n = 30) for tobacco, 3.0% (n = 54) for alcohol, 2.6% for marijuana (n = 46), and 6.2% (n = 105) reported significant impairment from substance use (Table 1, Supplementary Table 1).

Table 1.

Socio-demographic characteristics of study participants, N = 1,833

Characteristic	Freq. n (%)
Sex (n = 1,833)
Male	733 (40.0)
Female	1,100 (60.0)
Age, years (n = 1,833) Mean ± SD	15.1 ± 1.6
Age category, years (n = 1,833)
10–14	675 (36.8)
15–18	1,158 (63.2)
Education level (n = 1,794)
A’ level	142 (7.9)
O’ level	1,652 (92.1)
School location (n = 1,833)
Urban	930 (50.7)
Rural	903 (49.3)
History of mental illness (n = 1,785)
No	1,502 (84.2)
Yes	283 (15.9)
Housing type (n = 1,777)
Permanent House	1,477 (83.1)
Semi-permanent House	278 (15.6)
Hut	22 (1.2)
Witnessed domestic violence (n = 1,760)
No	1,510 (85.8)
Yes	250 (14.2)
School type (n = 1,833)
Day	134 (7.3)
Boarding	200 (10.9)
Both (day and boarding)	1,499 (81.8)
Orphan status (n = 1,822)
No	1,522 (83.5)
Yes	300 (16.5)
Tobacco use (n = 1,795)
No	1,765 (98.3)
Yes	30 (1.7)
Marijuana use (n = 1,786)
No	1,740 (97.4)
Yes	46 (2.6)
Alcohol use (n = 1,788)
No	1,734 (97.0)
Yes	54 (3.0)
SUD impairment (n = 1,688)
No	1,583 (93.8)
Yes	105 (6.2)

Findings from Table 2 revealed that males had significantly higher marijuana use compared to females (3.8% vs. 1.8%, p = 0.008) while students in urban schools had higher marijuana use (3.4% vs. 1.7%, p = 0.022) and SUD impairment (8.8% vs. 3.5%, p < 0.001) compared to their rural counterparts. Higher prevalence of alcohol use (6.2% vs. 2.4%, p = 0.001) and marijuana use (5.5% vs. 2.1%, p = 0.001) were observed in students with self-reported history of mental illness than those without such history. Regarding housing type, there was higher prevalence of tobacco use among hut dwellers compared to students living in semi-permanent and permanent houses (9.1% vs. 1.1% vs. 1.6%, p = 0.016) respectively. The prevalence of tobacco use was higher among students who witnessed domestic violence compared to those who did not (3.3% vs. 1.4%, p = 0.032). None of the students in boarding schools had SUD impairment when compared to students in day schools and both (day and boarding schools) respectively (0% vs. 7.7% vs. 6.9%, p = 0.001).

Table 2.

Bivariate comparison between participant characteristics, significant use of alcohol, substances and SUD impairment

	Alcohol use			Tobacco use				Marijuana use			SUD impairment
	N = 1,788			N = 1,795				N = 1,786			N = 1,833
Characteristic	Yes	No	p-value	Yes	No	p-value	Yes	No	p-value	Yes	No	p-value
	n (%)	n (%)		n (%)	n (%)		n (%)	n (%)		n (%)	n (%)
Sex
Male	26(3.7)	683(96.3)	0.195	17(2.4)	696(97.6)	0.056	27(3.8)	682(96.2)	0.008	46(6.8)	629(93.2)	0.409
Female	28(2.6)	1,051(97.4)		13(1.2)	1,069(98.8)		19(1.8)	1,058(98.2)		59(5.8)	954(94.2)
Age category, years
10–14	14(2.1)	642(97.9)	0.096	10(1.5)	648(98.5)	0.703	15(2.3)	641(97.7)	0.557	29(4.7)	586(95.3)	0.053
15–18	40(3.5)	1,092(96.5)		20(1.8)	1,117(98.2)		31(2.7)	1,099(97.3)		76(7.1)	997(92.9)
Education level
A’ level	8(5.8)	131(94.2)	0.058	2(1.4)	138(98.6)	0.79	7(5.0)	133(95.0)	0.068	14(10.4)	120(89.6)	0.039
O’ level	46(2.9)	1,564(97.1)		28(1.7)	1,588(98.3)		39(2.4)	1,568(97.6)		90(5.9)	1,428(94.1)
School location
Urban	34(3.7)	874(96.3)	0.069	17(1.9)	897(98.1)	0.525	31(3.4)	874(96.6)	0.022	76(8.8)	783(91.2)	< 0.001
Rural	20(2.3)	860(97.7)		13(1.5)	868(98.5)		15(1.7)	866(98.3)		29(3.5)	800(96.5)
History of mental illness
No	35(2.4)	1,433(97.6)	0.001	22(1.5)	1,451(98.5)	0.099	31(2.1)	1,437(97.9)	0.001	77(5.5)	1,317(94.5)	0.016
Yes	17(6.2)	258(93.8)		8(2.9)	268(97.1)		15(5.5)	259(94.5)		24(9.4)	230(90.6)
Housing Type
Permanent	45(3.1)	1,396(96.9)	0.126	23(1.6)	1,424(98.4)	0.016	37(2.6)	1,401(97.4)	0.075	79(5.8)	1,283(94.2)	0.031
Semi-permanent	5(1.8)	267(98.2)		3(1.1)	270(98.9)		4(1.5)	269(98.5)		19(7.4)	237(92.6)
Hut	2(9.1)	20(90.9)		2(9.1)	20(90.9)		2(9.1)	20(90.9)		4(19.0)	17(81.0)
Witnessed domestic violence
No	43(2.9)	1,436(97.1)	0.465	21(1.4)	1,463(98.6)	0.032	36(2.4)	1,441(97.6)	0.409	83(5.9)	1,316(94.1)	0.472
Yes	9(3.8)	229(96.2)		8(3.3)	232(96.7)		8(3.4)	231(96.6)		16(7.2)	207(92.8)
School type
Day	3(2.3)	128(97.7)	0.071	2(1.5)	130(98.5)	0.144	2(1.5)	130(98.5)	0.031	10(7.7)	120(92.3)	0.001
Boarding	1(0.5)	196(99.5)		0(0.0)	197(100.0)		0(0.0)	197(100.0)		0(0.0)	191(100.0)
Both	50(3.4)	1,410(96.6)		28(1.9)	1,438(98.1)		44(3.0)	1,413(97.0)		95(6.9)	1,272(93.1)
Orphan status
Yes	8(2.7)	284(97.3)	0.79	5(1.7)	289(98.3)	0.911	6(2.1)	286(97.9)	0.568	87(6.2)	1,319(93.8)	0.8
No	45(3.0)	1,440(97.0)		24(1.6)	1,466(98.4)		39(2.6)	1,444(97.4)		18(6.6)	255(93.4)

From the unadjusted logistic regression analyses (Table 3), male adolescents had significantly higher odds than female adolescents for marijuana use (odds ratio [OR] 2.20, 95%CI 1.22–4.00.22.00, p = 0.009) and SUD impairment (OR 1.68, 95%CI 1.11–2.53, p = 0.014). Urban residence was associated with higher odds of both marijuana use (OR 2.05, 95%CI: 1.10–3.82, p = 0.024) and SUD impairment (OR 1.66, 95%CI 1.09–2.54, p = 0.019). Adolescents with a history of mental illness had nearly three times higher odds of alcohol use (OR 2.70, 95%CI: 1.49–4.89, p = 0.001) and marijuana use (OR 2.68, 95%CI: 1.43–5.04, p = 0.002), and more than twice the odds of SUD impairment (OR 2.52, 95%CI: 1.60–3.99, p < 0.001) compared to those without such history. Those living in huts had six times higher odds of tobacco use (OR 6.19, 95%CI: 1.37–28.05, p = 0.018) and four times higher odds of SUD impairment (OR 4.10, 95%CI: 1.35–12.40, p = 0.013) than those in permanent housing. Witnessing domestic violence was associated with twice the odds of tobacco use (OR 2.40, 95%CI: 1.05–5.49, p = 0.038) and SUD impairment (OR 2.12, 95%CI: 1.29–3.46, p = 0.003) when compared to those with no history of witnessing domestic violence.

Table 3.

Unadjusted logistic regression models for factors associated with use of alcohol, substances, and SUD impairment

Characteristic	Tobacco Use OR (95% CI)	p-value	Marijuana Use OR (95% CI)	p-value	Alcohol Use OR (95% CI)	p-value	SUD Impairment OR (95% CI)	p-value
Sex
Female	Ref		Ref		Ref		Ref
Male	2.01 (0.97–4.16)	0.061	2.20 (1.22–4.00.22.00)	0.009	1.43 (0.83–2.46)	0.197	1.68 (1.11–2.53)	0.014
Age category
10–14	Ref		Ref		Ref		Ref
15–18	1.16 (0.54–2.49)	0.703	1.21 (0.65–2.25)	0.558	1.68 (0.91–3.11)	0.099	1.44 (0.92–2.26)	0.112
Education level
O level	Ref		Ref		Ref		Ref
A level	0.82 (0.19–3.49)	0.79	2.12 (0.93–4.82)	0.075	2.08 (0.96–4.49)	0.064	2.12 (1.17–3.85)	0.013
Location
Rural	Ref		Ref		Ref		Ref
Urban	1.27 (0.61–2.62)	0.525	2.05 (1.10–3.82)	0.024	1.67 (0.96–2.93)	0.072	1.66 (1.09–2.54)	0.019
Mental illness history
No	Ref		Ref		Ref		Ref
Yes	1.97 (0.87–4.47)	0.105	2.68 (1.43–5.04)	0.002	2.70 (1.49–4.89)	0.001	2.52 (1.60–3.99)	< 0.001
Housing type
Permanent	Ref		Ref		Ref		Ref
Semi-permanent	0.69 (0.21–2.31)	0.545	0.56 (0.20–1.59)	0.279	0.58 (0.23–1.48)	0.254	0.90 (0.49–1.65)	0.744
Hut	6.19 (1.37–28.05)	0.018	3.79 (0.85–16.80)	0.08	3.10 (0.70–13.68.70.68)	0.135	4.10 (1.35–12.40)	0.013
Witnessed domestic violence
No	Ref		Ref		Ref		Ref
Yes	2.40 (1.05–5.49)	0.038	1.39 (0.64–3.02)	0.411	1.31 (0.63–2.73)	0.467	2.12 (1.29–3.46)	0.003
School type
Day	Ref		Ref		Ref		Ref
Boarding	Omitted		Omitted		0.22 (0.02–2.12)	0.189	0.13 (0.01–1.12)	0.064
Both	1.27 (0.30–5.37)	0.749	2.02 (0.49–8.44)	0.334	1.51 (0.47–4.92)	0.491	1.65 (0.66–4.13)	0.286
Orphan status
No	Ref		Ref		Ref		Ref
Yes	1.06 (0.40–2.79)	0.912	0.78 (0.33–1.85)	0.569	0.90 (0.42–1.93)	0.79	0.95 (0.54–1.67)	0.855

In adjusted analyses shown in Table 4, male adolescent students had significantly higher odds of marijuana use compared to females (AOR: 2.21, 95%CI 1.17–4.19, p = 0.015) after controlling for potential confounding. Having a history of mental illness was significantly associated with higher odds of marijuana use (AOR 2.87, 95%CI 1.45–5.67, p = 0.002), alcohol use (AOR 2.69, 95%CI 1.42–5.09, p = 0.002), and SUD impairment (AOR 1.91, 95%CI 1.14–3.18, p = 0.014) when compared to those with no history of mental illness. Respondents in urban schools had significantly higher odds of SUD impairment (AOR 2.37, 95%CI 1.47–3.81, p < 0.001) when compared to respondents attending rural schools after adjusting for potential confounders. Adolescent students who self-reported living in huts had more than five-fold higher odds for tobacco use compared to those dwelling in permanent housing (AOR 5.46, 95%CI 1.12–26.59, p = 0.036) after controlling for potential confounders.

Table 4.

Factors independently associated with use of alcohol, substances and SUD impairment among secondary school adolescents

Outcome	Independent Variable	Adjusted OR (95% CI)	p-value
Model 1. Tobacco use	Housing type
	Permanent	Ref
	Semi-permanent	0.62 (0.18–2.12)	0.451
	Hut	5.46 (1.12–26.59)	0.036
Model 2. Marijuana use	Sex
	Female	Ref
	Male	2.21 (1.17–4.19)	0.015
	History of mental illness
	No	Ref
	Yes	2.87 (1.45–5.67)	0.002
Model 3. Alcohol use	History of mental illness
	No	Ref
	Yes	2.69 (1.42–5.09)	0.002
Model 4. SUD impairment	School location
	Rural	Ref
	Urban	2.37 (1.47–3.81)	< 0.001
	History of mental illness
	No	Ref
	Yes	1.91 (1.14–3.18)	0.014

All models adjusted for sex, age, education, location, mental illness history, housing type, witnessing domestic violence, and school type

Discussion

This study aimed to determine the prevalence and factors associated with use of alcohol, substance use and SUD impairment among adolescents attending secondary schools in central and eastern Uganda. We revealed two key findings. First, we revealed the prevalence of significant use of tobacco (1.7%), marijuana (2.6%), and alcohol (3.0%) and 6.2% had impairment from SUD among adolescents attending secondary schools in central and eastern Uganda. Prior studies among Ugandan high school students revealed slightly higher proportions of cigarette use, with 5.9% of rural students having ever smoked[19], 5.3% of rural residents currently smoking[20], and 5.6% of urban students currently smoking [10]. However, the proportion of tobacco smoking among in-school adolescents was comparable to national estimates for 15 to 19 year olds (both in and out of school), any type tobacco use (1.1%) and cigarette smoking (1.0%)[6]. Although current tobacco use was reported by 1.7% of secondary school students in the study area, this finding highlights the importance of implementing early cessation and prevention interventions before adulthood.

Conversely, prior research has documented a markedly higher proportion of ever using tobacco products (approximately twentyfold higher) among rural high school students[21], indicating that tobacco use persists as a significant public health issue among schooling adolescence. This concern is compounded by the absence of recent, nationally representative estimates specific to this adolescent population, as the most reliable estimates are nearly a decade old and not disaggregated by schooling status [6]. However, the low prevalence of tobacco use does offer support that anti-smoking initiatives have been effective. In the current study, male students had higher odds of using marijuana, tobacco, and alcohol, with a significant association observed for any substance use. Male students also demonstrated higher odds of meeting criteria for alcohol use disorder, aligning with findings from previous studies [22]. Furthermore, a prior study reported higher odds of past-year marijuana and khat use among adolescents aged 15 to 19 years [23] compared to the current study, possibly due to regional variation in marijuana use or differences in sample size.

Prior studies from Uganda highlights cheap price, social norms, and use of tobacco as a replacement for alcohol as risk factors for tobacco use [24]. Although we did not assess these specific factors, we found that adolescents living in huts had higher odds of using tobacco compared to those in permanent houses, suggesting that housing conditions which is a proxy for socio-economic status may influence tobacco use. Although adolescents reporting hut residence had higher odds of tobacco use and borderline higher odds of any SUD, this subgroup was very small (n = 22) and results should be interpreted with caution. Given that most hut residents were in urban rather than rural settings, this category likely reflects informal or transitional housing and serves as a proxy for socioeconomic vulnerability rather than a direct causal factor. Future studies should use standard or validated housing classifications to better capture housing type and urban informal settlements in Uganda. We also found that male students had higher odds of marijuana use than female students, supporting existing research that shows substance use is more prevalent among Ugandan male students [9]. Interestingly, we found that having a family history of mental illness were more likely to use marijuana. This relationship, which has not been thoroughly explored in the current literature especially among school-going adolescents in Uganda offers an interesting insight and highlights the need for future research aimed at further understanding and mitigating marijuana use among adolescent students in Uganda. We found a consistent association between alcohol use and having a family history of mental illness, supporting existing literature.

The relationship between residing in urban areas and alcohol use was not statistically significant which differed from prior research showing that adolescents living in urban Kampala were more likely to participate in high-risk drinking behavior [9]. These patterns offer important insights into contextual risk factors to inform targeted school interventions. Conversely, in the Ugandan context, the studies surveyed students in districts that do not provide a clear rural-urban delineation. Although previous research linked higher education levels (secondary/advanced lev)[22], and early exposure to alcohol use[25], our analyses did not find education level to be a significant factor for alcohol, tobacco, marijuana or use of any substances. Our study shows higher alcohol use levels among male secondary students contrary to previous studies. This could be potentially due to our study solely focusing on adolescents in school. This difference highlights the need for broader research to assess how education influences substance use in Ugandan adolescents.

Adolescents living in huts or mixed housing had higher odds of substance use disorder compared to those in permanent homes. Comparatively, we identified higher odds of marijuana use in adolescents residing in huts. Although our study did not assess socioeconomic factors such parental education or household income level, these findings may reflect underlying differences in socioeconomic status and availability of substances in the community. It is plausible that living in huts or mixed housing may be associated with lower socioeconomic status and potentially, adolescents may have increased access to substances. Nevertheless, these results showcase a potential relationship between housing situation which is a potential proxy for socioeconomic status and substance use. Limited research has explored this association, making housing a potentially important but underexamined factor. Our findings also highlight male sex and family history of mental illness as key risk factors for substance use disorder in school-going adolescents. This supports existing evidence linking mental health and substance use[26], and underscores the need for targeted, evidence-based interventions in school settings.

Substance use remains a public health concern among Ugandan adolescents in secondary schools. Substance abuse prevention programs should leverage parental education workshops and community dialogues to de-stigmatize adolescent smoking and discuss associated risks. Effective interventions should combine school-based programs with community education initiatives, particularly in high-prevalence areas, to ensure consistent messaging and support across both environments where adolescents spend their time. Targeting high-risk groups, such as male students, may improve the impact of substance abuse prevention initiatives in Uganda especially in school-based programs [27]. From a policy perspective, it is imperative to strengthen enforcement of tobacco control initiatives, increasing taxes on tobacco and alcohol sales, advertising (media and street), and use of alcohol and tobacco in adolescents in Uganda. Although adolescents with limited parental supervision were more likely to use tobacco and illicit drugs[23], there is a dearth of literature on this topic. Future interventions should involve parents to help address this gap.

Our study had some limitations. The cross-sectional design limits casual inferences in the current study. Although stratified random sampling was used, the current study sample is not nationally representative. Therefore, our study findings are generalizable to similar school settings in central and eastern Uganda. We also acknowledge that social desirability bias could have led to underreporting of sensitive behavior such as substance use[28], and personal history of mental health conditions among others. Furthermore, categorical variables like “housing type” should be interpreted as proxies for broader socioeconomic conditions rather than precise measurements, as these classifications may carry subjective interpretations across different contexts. Although our study assessed witnessing domestic violence, it did not comprehensively assess other forms of trauma including post-traumatic stress disorder, which is a major risk factor for substance use [29]. Our finding that witnessing domestic violence was associated with substance use in unadjusted analyses, but not in the adjusted models, suggests that potential trauma experienced through witnessing domestic violence might influence substance use though intermediary factors like mental health disorders. Future research should conduct validated trauma assessments to better understand its role in substance use among Ugandan adolescents. Future studies should examine the broader range of psychosocial factors, such as social support, interpersonal stress, peer influence, and their impact on functional impairment [30–34] which were not assessed in the current study but are critical to understanding substance use risks in adolescent students.

Our study strengths included the large sample size adequate to generalize our findings to similar study populations in this study setting. Our proposed next steps for this study include the designing of school-based interventions to mitigate the increasing prevalence of substance use in adolescents. Further research should explore the accessibility and availability of existing substance prevention programs to school going adolescents in Uganda. Deliberate efforts by key stakeholders should be initiated to identify what factors contribute to sex differences in substance use.

Conclusions

This study identified key factors associated with significant use of alcohol, marijuana, tobacco and SUD impairment among school-going adolescents in central and eastern Uganda. Targeted school-based interventions addressing sex differences, mental health evaluations, housing conditions, and urban-rural disparities may help reduce use of alcohol, substances and SUD impairment among adolescents in central and eastern Uganda.

Authors’ contributions

WB and RA primarily drafted the manuscript and interpreted all data. CA, JDG, RK, AK, and FO edited the manuscript. LD, AS, SK, KK and MB formalized the data for usage.

Funding

This study was supported by a grant awarded to CA from the Swedish International Development Cooperation Agency (SIDA/SAREC; Grant No. 51180060). The funder had no involvement in the study’s design, data collection, analysis, publication decision, or manuscript preparation.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics and consent to participate

The study received ethical clearance from the School of Medicine Research Ethics Committee (SOMREC) and approval from the Uganda National Council for Science and Technology (UNCST). Informed consent was obtained from all participants, with parental or guardian consent secured for those under 18 years of age. This study was conducted in accordance with the Declaration of Helsinki.

Consent for publication

Not Applicable.

Competing interests

The authors declare no competing interests.