The relationship between Stressful Life Events and Anxiety Symptoms: A cross-sectional survey of with university students in Botswana

doi:10.21203/rs.3.rs-4906332/v1

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The relationship between Stressful Life Events and Anxiety Symptoms: A cross-sectional survey of with university students in Botswana

https://doi.org/10.21203/rs.3.rs-4906332/v1

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Background: Anxiety disorders, particularly in young adults, have a severe influence on the quality of life, career growth, and health. There is a dearth of research on causes and correlates, particularly in areas with limited resources. At a premier higher education institution in Botswana, we set out to determine how stressful life events (SLEs) predict anxiety symptoms in young adults.

Method: In a cross-sectional survey (n = 615, mean age = 21.1, ± 2.1, 59.3% female), the 21-item Beck’s Anxiety Inventory (BAI) and the 26-Item Social Readjustment Rating Scale were used to assess anxiety symptoms and SLEs, respectively. T-tests, analyses of variance (ANOVA) and regression analyses were used to calculate associations, compare SLEs at different levels of anxiety symptoms, and assess whether SLEs predicted anxiety.

Results: Anxiety symptoms were moderate in 16.4% and severe in 11.7% of respondents. Over 50 per cent of respondents reported eight (8) or more SLEs. Higher numbers of SLEs were associated with a gradual increase in anxiety symptoms severity. Respondents at different levels of anxiety differed significantly in reporting SLEs (F _{(3, 612)} = 68.21, p < .001). SLEs significantly predicted reporting anxiety symptoms (β = .56, 95% CI: 0.45, 0.66). When all SLEs were simultaneously included in one model, SLEs related to personal, study and relationship stressors independently predicted anxiety symptoms.

Conclusion: Anxiety in young individuals is highly correlated with reporting SLEs. Practitioners should prioritise initiatives that promote mental health through effective low-cost self-help interventions for easing anxiety symptoms in young adults.

Stressful life events

anxiety symptoms

young adults

university students

Botswana.

Globally, it is estimated that 260 million people are living with anxiety disorders with devastating consequences [1]. These consequences include inter alia, health problems such as increased blood pressure, palpitations, stomach upset, sleep problems, respiratory complications [2, 3], social problems (e.g., social isolation, failure to function in social settings, etc.) [4]. Anxiety disorders are also highly comorbid with substance use disorder, depression, and maybe a precursor to future mental health [4, 5, 6].

Particularly among adolescents and young adults in colleges and universities, anxiety is a common mental health problem and a key public health concern [1]. Particularly among young adults, anxiety is frequently associated with impairment, poor academic outcomes, early school leaving [7], and drug and substance abuse [8]. Furthermore, anxiety disorders may reduce coping and decision-making capacity and predispose young adults to risky behaviours like the risk of self-harm [9, 10]. Consequently, chances of employment and career growth are hindered, which may adversely affect the quality of the labour force and later economic development [11]. Hence, studies on factors associated with anxiety disorders are imperative to aid interventions to identify and treat young adults affected by anxiety disorders.

Literature review

Several factors are known to increase the risk of anxiety among young adults. These factors include genetic background [12, 13], general trauma load based on exposure to adverse childhood experiences [14, 15, 16], low socio-economic background [17], lack of social capital and support [6], and stressful life events [18]. Mainly in young adults, stressful life events are common and are associated with a myriad of mental health problems including anxiety [19] with the majority of mental health problems such as anxiety detected in adulthood originating in childhood or adolescence [20, 21].

Unlike in Europe and North America, only a few studies have been conducted on anxiety among young adults in low- and middle-income countries [22]. Just as previous studies have linked SLEs to depression in the same population [23], SLEs may be associated with anxiety as well as depression because anxiety is known to be comorbid with depression [5, 6, 24]. Moreover, it is imperative to raise awareness, identify risk factors and adduce evidence to intervene and design policies to prevent anxiety and mitigate adverse current and future consequences of anxiety disorder among young adults to inform practice and research. The current study will help to draw attention to and prioritise anxiety disorder as a public health problem, especially among young adults.

Just like in other low- and middle-income countries, Botswana has many factors that may be related to anxiety disorders among young college and university students. Contextual factors such as poverty, high incidence of HIV/AIDS, high academic workloads, alcohol and substance abuse, family dysfunction, and stressful life events (SLEs) such as deaths of family members, financial problems and familial drug and substance abuse are rampant in Botswana and directly affect young people [8, 23, 25, 26, 27]. Although these contextual factors are fertile grounds for anxiety disorders to thrive, no studies have been carried out to assess the relationship between SLEs and anxiety symptoms in Botswana.

In Botswana, most of the studies on mental health in general and anxiety in particular, were related to people living with HIV/AIDS [28] and among the elderly [29] but not among young adults. The results of the studies with HIV/AIDS patients and among the elderly varied extensively. Among HIV/AIDS patients, 41.7% suffered from generalised anxiety disorder compared to 25% in controls while among the elderly, 18.6% suffered from a generalised anxiety disorder [29]. None of these studies assessed the influence of SLEs on anxiety. It is widely recognised that young adults are exposed to numerous life stressors such as high academic demands [18, 26], relationship problems with family members and peers [30], financial problems, and worries about future employment opportunities [31], making them prone to anxiety disorders. Consequently, we hypothesize that exposure to SLEs is associated with increased symptoms of anxiety.

Finally, research on mental health in young adults, particularly in low- and middle-income countries, is scarce yet they are an important sub-population that constitutes the future workforce on whom the future development of the country depends. Young adults are at a stressful developmental stage of transition from adolescence to young adulthood, identity formation, and for some, living independently away from parents, all of which can be stressful. Moreover, when detected early, later mental health burdens can be mitigated by interventions in young adults [15].

Theoretical and conceptual framework

The current study utilised the Social Stress Theory [32, 33] to explain the findings. The Social Stress Theory postulates that exposure to stressful life events such as financial problems, relationship breakups, diseases such as HIV/AIDS, COVID-19, and academic demands, among others, increases the risks of mental health problems such as anxiety disorders [32–34]. Additionally, the theory suggests that people who are vulnerable due to their social status are liable to increased risks of exposure to stress and related mental health problems [34]. Consequently, because of the vulnerable environment they live in, young adults are likely to experience SLEs and related mental health consequences.

Aim and objectives

Previous studies have demonstrated gender variations in reporting SLEs and anxiety symptoms. Women have consistently reported more interpersonal while their male counterparts report more legal work-related life stressors [35] while women regularly report more anxiety symptoms and disorders [36]. Subsequently, we hypothesise that women will report more anxiety symptoms and SLEs than men. In this study, gender differences in reporting anxiety symptoms and SLEs will be assessed. Given the limitations highlighted above, the current study aims to assess the extent to which SLEs predict anxiety symptoms among students at a large premier university in Botswana. The specific objectives of the study were to: a) assess the prevalence of SLEs and anxiety symptoms among young adult students at the University, b) examine the distribution of SLEs at different levels of anxiety, and c) assess the extent to which SLEs predict anxiety symptoms in young adults.

Participants

In a cross-sectional design, respondents were randomly drawn from a population of students registered for different study programmes at a premier university in Botswana. Students from different years of study in different faculties were selected to achieve a representative sample for the study.

Measures

The study instrument comprised three sections: (i) items on the socio-demographic characteristics (e.g., age, year of study, gender, etc.), (ii) items on SLEs, and (iii) items on symptoms of anxiety.

SLEs. To assess exposure to SLEs among the participants, we used the Social Readjustment Rating Scale [37]. The scale consists of 26 items of SLEs that young adults in colleges and universities frequently experience. The items are rated on a 2-point scale with ‘0’ for non-occurrence and ‘1’ for occurrence in the past year [38]. Higher scores are indicative of greater exposure to SLEs and vice versa. After a pilot study with about 20 per cent of the intended sample size, minor adaptations were made to make the scale more relevant to the realities of young adults in Botswana. For instance, 'Chronic car problems' was changed to 'Problems with transport', ‘Change in living conditions’ was adjusted to ‘Change in living conditions/accommodation’, and ‘Minor traffic violations’ was omitted altogether. Lastly, the SLEs comprised family events, relationships with authority figures (e.g., parents, teachers, etc.), study challenges at university, and personal losses. The SLE items are listed in Table 1. The internal consistency of the SLEs measure was assessed using Kuder-Richardson (KR-20) and yielded a coefficient of 𝛂 = .83.

Symptoms of anxiety. Symptoms of anxiety were measured by the 21-item Becks Anxiety Inventory (BAI) developed by Beck and colleagues [39]. BAI is a self-report measure of the extent to which a person is bothered by anxiety symptoms (e.g., “unable to relax”, “nervous”, “difficulty breathing”, “scared”, etc.). The anxiety symptoms are rated on a 4-point Likert-type scale ranging from 0 (not at all) to 3 (severely). The scores ranged from 0 – 63 and are classified as follows: 0–7 (minimal level of anxiety), 8–15 (mild level of anxiety), 16–25 (moderate level of anxiety), and 26–63 (severe level of anxiety) [39]. The internal consistency of the BAI as measured by Cronbach alpha in previous studies yielded coefficients ranging from α= .92 to α= .94 for adults and test-retest (one-week interval) reliability of α=.75 [40]. The higher the scores the higher the number of anxiety symptoms. The internal consistency coefficient (Cronbach alpha) of the BAI scale in the current study was acceptable at α=.94.

Procedure

Permission to collect data from different faculties was obtained from registrars, who, in turn, got permission from lecturers to collect data from students during their class hours. Before the lecturers were contacted, classes were randomly drawn based on teaching schedules for the different departments. Before data collection, the students were made aware of the purpose of the study, their rights, confidentiality and anonymity about data collection, usage, and participation in data collection. Thereafter, a signed informed consent was obtained from each participant before data collection. Data collection lasted between 15 – 20 minutes in the presence of research assistants who ensured that any queries from participants were clarified. Overall, 657 students registered for various courses of study in different faculties were invited to participate in this study. Eleven students who were over the age of 25 were excluded and 31 others with incomplete data were excluded. In the end, data from 615 students (59,3% female, n = 365) were included in the analyses.

Ethical considerations

Permission to conduct this study was granted by the Institutional Review Board of the University of Botswana. After data collection, the students were given contacts of two psychological services (the Student Centre and the Psychology Clinic at the Department of Psychology) both situated at the university campus in case they were affected by their participation in the study.

Data analysis

General socio-demographic characteristics of the study participants were computed using descriptive statistics (e.g., mean, SD, and range) and the results were tabulated. Next, descriptive statistics and t-tests were run to assess the prevalence of SLEs and anxiety symptoms among the students. The distribution of SLEs at different levels of anxiety symptoms was assessed by a one-way analysis of variance (ANOVA). The total number of SLEs was used as the independent variable with different levels of anxiety symptoms as the dependent variable. Tukey HSD test for multiple comparisons was used to examine significant differences between levels of severity of anxiety symptoms. The effect sizes of each of the SLEs on anxiety symptoms in both univariable and multivariable analyses were computed using Eta squared (η2). Finally, both univariable and multivariable linear regression models were fitted to examine whether SLEs individually and simultaneously predicted the total number of anxiety symptoms. The multivariable regression model was fitted to assess whether the SLEs that significantly predicted anxiety symptoms in the univariate models uniquely and independently predicted the total number of anxiety symptoms. Due to the correlation between the SLE items, it was possible that the assumption of multicollinearity could have been violated. Thus, we computed multi-collinearity as a variance inflation factor (VIF) [41]. Generally, a VIF value greater than 10 indicates a serious violation of the assumption of multi-collinearity while VIF values of less than 4.0 may be a reason for concern [41]. All statistical analyses were performed using IBM SPSS Statistics (version 27) predictive analytic software. Associations with a p-value <.05 were considered statistically significant.

Socio-demographic characteristics

The characteristics of the study participants are presented in Table 1. A total of 615 students provided data (female 365, 59.3%) with an average age of 21.1 (SD = 2.1, range: 18–25) years. Also indicated in Table 1 are scores on the independent (total score on SLEs) and dependent (total score and different levels of anxiety symptoms) variables.

Prevalence of anxiety symptoms

More than one in four students reported moderate (16.4%) to severe (11.7%) symptoms of anxiety (Table 1). There was a significant gender difference in reporting anxiety symptoms (t ₍₆₁₄₎ = -6.72, p < .001) with female students (M = 28.09, SD = 13.93, range=00-63) reporting more anxiety symptoms than their male peers (M = 17.69, SD = 13.08, range=00-63).

The distribution of SLEs in different levels of anxiety symptoms is presented in Figure 1. Generally, higher exposure to SLEs was gradually related to more severe levels of anxiety symptoms with a steeper gradient observed for moderate and severe levels of anxiety symptoms (Figure 1).

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Table 1 about here

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Figure 1 about here

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Prevalence and distributions of SLEs

Participants' reports of SLEs are included in Table 2. Generally, students reported an average of 9 SLEs (M = 8.87, SD = 4.47, range =00-26). Most of the students reported SLEs associated with their studies (e.g., problems with assignments, tests, and exams, not getting the desired grades), personal situations (e.g., financial situations, change in living conditions), and relationship difficulties (e.g., an argument with parents, serious arguments with friends). Although there was no overall gender difference in reporting the total number of SLEs, particular SLEs were reported differently between male and female participants. For example, male participants reported more SLEs related to aggression and alcohol and drug use such as “serious argument with a lecturer”, "trouble with the police", and "problems with alcohol or drugs" than their female peers. On the other hand, female students reported more SLEs related to relationships and family such as “change in acceptance by peers”, "death of a relative/friend", and “excessive alcohol use by parents” than their male counterparts (see Table 2).

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Table 2 about here

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The influence of different SLEs on anxiety symptoms

Overall, most of the SLEs were significantly associated with anxiety symptoms (based on a continuous scale) in univariable regression analyses (Table 3). Initial analyses demonstrated that the VIFs were all less than 2.0, indicating that multi-collinearity was not an issue of concern [41]. Some of the SLEs that did not significantly predict anxiety symptoms included “failing a course”, “retaking a course”, “unplanned pregnancy”, etc., predicting anxiety symptoms (Table 3). The total number of SLEs experienced significantly predicted the total number of anxiety symptoms in this sample (β = .56, 95% confidence interval [CI]: [.45, .66]). The regression model yielded a significant fit (R² = .31, F (_{2, 615)} = 89.84, p < .001). Adding gender to the regression analysis did not materially improve the model fit. The regression coefficients denote the SD change in anxiety symptoms as a result of the change of the independent variable. For instance, the regression of anxiety symptoms on the number of SLEs indicates a change of 1SD associated with a .56 SD change in anxiety symptoms.

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Table 3 about here

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The unique influence of particular types of SLEs on anxiety symptoms

The result of the multivariable regression analysis to assess the unique and independent effects of individual SLEs on the total continuous measure of anxiety symptoms is presented in Table 4. The following SLEs uniquely and independently predicted anxiety symptoms: “personal injury”, “problems with assignments, tests, or exams”, “financial problems”, and “change in acceptance by peers”, among others (Table 4).

Finally, a one-way between-subjects ANOVA was conducted to compare subjects with minimal, mild, moderate, and severe levels of anxiety symptoms on reporting SLEs. Subjects at different levels of anxiety symptoms significantly varied in reporting SLEs (F _{(3, 612)} = 68.21, p < .001). Post hoc comparisons using the Tukey HSD test indicated that the mean score for the minimal level of anxiety symptoms (M = 4.90, SD = 3.49) significantly differed from the mild (M = 7.56, SD = 3.71), moderate (M = 8.84, SD = 4.09), and severe anxiety symptoms (M = 10.38, SD = 4.42). Conversely, only mild and moderate levels of anxiety symptoms did not significantly differ.

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Table 4 about here

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To our knowledge, only a few studies have assessed the influence of SLEs on anxiety symptoms. The results of this study are a useful addition to the literature on anxiety symptoms and their correlates in low- and middle-income countries. The results of this study indicated the widespread prevalence of SLEs and anxiety symptoms among young adults in universities and colleges. On average, the students reported about nine (9) SLEs and about 28% (n = 173) experienced moderate (16.4%) or severe (11.7%) anxiety symptoms. Altogether, the results show that increased exposure to SLEs is associated with a higher number of anxiety symptoms, particularly SLEs related to personal, educational, and relationship problems.

The results of this study are in line with the social stress theory which posits that exposure to SLEs increases the risks of mental health problems such as anxiety symptoms [32–34]. The theory also suggests that people who are made vulnerable as a result of their social statuses or personal circumstances are liable to increased risks of exposure to stress and related mental health problems such as anxiety disorders [34]. This resonates with the situation in Botswana as well. Even though Botswana is an upper-middle-income country, the majority of the population remains in poverty. Equally, there has been a marked change in the family configuration in Botswana with about 70 per cent of children coming from one-parent households, often single mothers [42]. Generally, families headed by single mothers are known to be poorer than families headed by fathers [42]. Likewise, children brought up by single mothers are known to be poorly adjusted with poor learning outcomes and mental health [43, 44].

Overall, the results of this study echo the results of previous studies that found an association with SLEs [19] particularly illnesses [29]. Most of the SLEs assessed in this study predicted anxiety symptoms in univariable regression models while a few SLEs related to personal, educational, and relationship independently and uniquely predicted anxiety symptoms. The results demonstrate that anxiety symptoms are not only highly prevalent among young adults and a public health problem in universities but may be related to particular SLEs. Consequently, interventions to alleviate personal problems, support study problems, and counselling for relationship challenges should be prioritised on university campuses.

In the univariable regression analyses, stressors related to personal (e.g., personal injury, financial problems), relationship (e.g., change in acceptance by peers, an argument with parents), and study problems (problems with assignments, tests, and exams), were highly endorsed by participants (Table 3). Similar trends were observed in the multivariable analyses (Table 4). Preventive strategies and intervention programmes to mitigate mental health problems such as anxiety disorders should prioritise personal, relationship and study problems among students. For example, on-campus student centres where counselling and study support is provided may be important strategies to reduce anxiety symptoms among students. Furthermore, self-help interventions are cheap, effective, and efficient in reducing anxiety symptoms among young adults [45]. Likewise, past studies have also shown that social support may be helpful to those suffering from stress and is known to be a mediator of the associations between life stressors and mental health problems [46].

Relationship problems have been recognised as very stressful among young adults in universities [47]. This could be due to the developmental stage (18–25 years of age) that is characterised by an increase in physical growth, sexual activities, break-ups, and conflicts with peers and parents. Moreover, young adulthood is also characterised by an increase in roles and responsibilities such as self-supervision, financial management, juggling academic demands and social life, and wading through a web of social environments, all of which, may predispose young adults to a high density of stressors leading to mental health problems including anxiety disorders [47].

Another pathway through which SLEs may lead to anxiety symptoms is through the physical body’s persistent stress system stimulation as a result of exposure to numerous SLEs [48]. In turn, the persistent stress system stimulation may lead to an elevated and sustained production of the stress hormone, cortisol [14, 49]. The protracted stress condition may result in other compensatory deregulatory feedback interactions such as the hypo-activation of the hypothalamic-pituitary-adrenal axis (HPA axis) [14, 49]. Consequently, stress system stimulation, the continued production of stress hormones and down-regulatory mechanisms such as hypo-activation of the HPA-axis, keep on in a state of flux, thus vulnerable to anxiety symptoms.

Interpretation of the results of this study is constrained by several limitations. First, there may be biases arising from the cross-sectional nature of the study and self-report measures. Second, the sample of university students may not be representative of young adults out of school, thus, it may be difficult to extrapolate the results to other samples of young adults outside school. Third, the source of information for both the SLEs and anxiety symptoms is the same. This might have led to inflated coefficients as a result of biases arising from the same source variance. Fourth, general trauma, exposure to childhood adversity, low socioeconomic background, lack of social capital and support, depressive symptoms, and worries related to the ongoing COVID-19 pandemic were not assessed and controlled. These factors might have inflated the anxiety symptoms. Finally, the associations between individual SLEs and anxiety symptoms yielded small effect sizes although the effects of the aggregate number of SLEs were moderate. Consequently, interventions to reduce the adverse effects of SLEs on anxiety effects may only have a small effect.

Anxiety symptoms are widespread and significantly related to reporting SLEs in young adult students. Increased exposure to SLEs amplified anxiety symptoms, particularly, personal, study, and relationship problems uniquely and independently predicted anxiety symptoms. Further research with longitudinal designs and a larger and more diverse representative sample is required to illuminate the path from different types of SLEs to anxiety symptoms in young adults. Future research should aim at mental health literacy and intervention studies to reduce the number of SLEs and to ease the negative effects of anxiety symptoms on young adults. University administrators and policymakers should prioritise mental health literacy, study support, and counselling services in universities and colleges. Particularly, programmes to alleviate anxiety symptoms should target personal, study, and relationship stressors among young adults as self-help interventions are known to be cheap, effective, and efficient in alleviating symptoms of anxiety symptoms. Moreover, self-help interventions involve less staff time, can be computer-adapted, and are more suitable in settings short of healthcare workers.

Acknowledgements

The authors want to thank every student who completed the survey forms for volunteering their time and the lecturers for allowing data collection during their lecture hours.

Authors’ Contributions

The first author was responsible for the research idea, literature review, data collection, data analysis and writing of the article. The second author supervised the study and contributed to the project design, literature review, data analysis and writing of the report.

Funding: no funding for this research.

Data Availability: Data available upon reasonable request from the corresponding author.

Ethical Statement

All the respondents gave their informed consent. The study complies with the 1964 Declaration of Helsinki and its later addenda, and the survey on which our study is based was approved by the Ethical Review Board of the University of Botswana, Gaborone, Botswana. This original contribution has never been published before, nor has been sent to any other journals for consideration. I confirm that all co-authors have reviewed and approved the final version of the manuscript that I am submitting and have agreed to the listing-order for authors. The corresponding author is affirming these details on behalf of all authors.

Conflict of interest: We have no known conflict of interest to disclose.

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Table 1

		Total		Male		Female
		Mean or number	(SD or %)	Mean or number	(SD or %)	Mean or number	(SD or %)	t-test
1	Participants	N=615	100%	n=250	40.7%	n=365	59.3%
2	Age	21.1	SD = 2.1	21.41	SD 2.26	21.00	SD 1.99	ns
3	Stressful life events	8.87	SD = 4.47	8.93	SD 5.03	8.84	SD 4.23	ns
4	Anxiety	25.05	SD = 14.46	17.69	SD 13.08	28.09	SD 13.93	-6.72, p < .001
	Minimal	n=279	45.4%	n=120	48.0%	n=159	43.6%
	Mild	n=163	26.5%	n=79	31.6%	n=86	23.6%
	Moderate	n=101	16.4%	n=32	12.8%	n=69	18.9%
	Severe	n=72	11.7%	n=21	8.4%	n=51	14.0%

Note: Socio-demographic characteristics of the study participants

Key: N/n=number, SD=standard deviation

Table 2

		Total (N=615)		Male (n=250)		Female (n=365)
	Stressful life events	*Yes*	%	*Yes*	%	*Yes*	%	t test
1	Problem with assignments, tests, and or exams	538	87.5	216	86.4	322	88.2	ns
2	Not getting the desired grades	533	86.7	217	86.8	316	86.6	ns
3	Financial problems (debts, lack of pocket money)	365	59.4	144	57.6	221	60.5	ns
4	Change in living conditions/ accommodation	327	53.2	133	53.3	194	53.2	ns
5	Arguments with parents (dressing, curfew, etc.)	314	51.1	110	44.0	204	56.2	ns
6	Illness in the family ( e.g. cancer, diabetes)	281	45.7	100	41.9	181	49.5	ns
7	Personal injury or illness	268	43.6	103	41.2	165	45.2	ns
8	Failing a course	257	41.8	133	53.2	124	34.4	2.41, p < 0.05
9	Serious argument with a close friend	237	38.6	95	38.0	142	38.9	ns
10	Troubles with registration (e.g. timetable clashes, system failure, etc.)	232	37.8	99	39.6	133	36.4	ns
11	Death of a family member ( e.g. parent, sibling)	226	36.7	86	34.4	140	38.4	ns
12	Change in acceptance by peers	226	36.7	63	25.2	163	44.7	3.84, p < 0.05
13	Troubles with transport	222	36.1	87	34.8	135	36.9	ns
14	Death of a relative or close friend	222	36.1	72	28.8	150	41.1	-2.65, p < 0.05
15	Breaking up with a boy/girlfriend	205	33.4	84	33.6	121	33.2	ns
16	Trouble with parents	191	31.1	75	30.0	116	31.8	ns
17	Entering a new relationship (e.g. new boyfriend/girlfriend)	190	30.9	80	32.0	110	30.1	ns
18	Loss of a cell phone, tablet, or laptop computer	190	30.9	83	33.2	107	29.3	ns
19	Having to retake or write a supplementary exam	169	27.5	74	29.6	95	26.0	ns
20	Problems with alcohol or drugs	60	9.8	37	13.3	23	6.3	2.11, p < 0.05
21	Serious argument with a lecturer	55	8.9	35	14.0	20	5.4	3.19, p < 0.05
22	Excessive alcohol use by parents	48	7.8	31	12.3	17	3.3	2.98, p < 0.05
23	Unplanned pregnancy	38	6.1	11	4.4	27	7.4	ns
24	Trouble with the police	27	4.4	22	7.4	5	1.4	2.37, p < 0.05
25	Getting married	22	3.6	5	2.5	17	4.7	ns
26	Trouble with law enforcement (e.g. fraud, parents in jail etc.)	17	2.8	10	4.0	7	1.9	ns
27	Total number of stressful life events (Means/SD)	-	8.87	-	8.93	-	8.84	ns

Note: Endorsements of Stressful Life Events

Key: N=total sample; n=sub-sample = number, ns = not significant, SD=Standard Deviation. All significant associations are in bold

Table 3

	Stressful life events	β	(95% CI)	η²
1	Personal injury or illness	0.31	0.21, 0.41	.10
2	Change in acceptance by peers	0.30	0.20, 0.40	.09
3	Problem with assignments, tests, and or exams	0.28	0.18, 0.38	.10
4	Arguments with parents (dressing, curfew, etc.)	0.25	0.15, 0.35	.06
5	Financial problems (debts, lack of pocket money)	0.24	0.14, 0.34	.07
6	Change in living conditions/ accommodation	0.24	0.14, 0.24	.07
7	Trouble with parents	0.21	0.11, 0.31	.06
8	Death of a relative or close friend	0.19	0.09, 0.29	.05
9	Trouble with law enforcement (e.g. fraud, parents in jail etc.)	0.19	0.08, 0.29	.05
10	Serious argument with a close friend	0.18	0.08, 0.28	.04
11	Breaking up with a boy/girlfriend	0.18	0.08, 0.29	.04
12	Loss of a cell phone, tablet, or laptop computer	0.18	0.02, 0.19	.01
13	Illness in the family ( e.g. cancer, diabetes)	0.16	0.06, 0.26	.03
14	Getting married	0.16	0.06, 0.26	.02
15	Troubles with transport	0.15	0.05, 0.26	.03
16	Problems with alcohol or drugs	0.15	0.05, 0.26	.02
17	Troubles with registration (e.g. timetable clashes, system failure, etc.)	0.15	0.05, 0.25	.03
18	Not getting the desired grades	0.13	0.03 – 0.24	.02
19	Serious argument with a lecturer	0.13	0.03, 0.23	.02
20	Death of a family member ( e.g. parent, sibling)	0.12	0.01, 0.22	.02
21	Excessive alcohol use by parents	0.10	-0.02, 0.20	.02
22	Trouble with the police	0.10	-0.01, 0.20	.01
23	Unplanned pregnancy	0.08	-0.01, 0.20	.01
24	Failing a course	0.07	-0.03, 0.18	.01
25	Entering a new relationship (e.g. new boyfriend/girlfriend)	0.06	-0.02, 0.17	.01
26	Having to retake or write a supplementary exam	0.05	-0.06, 0.15	.00

Note: Univariable regression models of the influence of individual and total number of stressful life events on depression (based on a continuous scale)

β: standardized beta; CI: confidence interval, η²: eta squared, a measure of effect size. All significant associations are in bold.

Table 4

Stressful life events		β	(95% CI)	η²
1	Personal injury	0.20	0.10, 0.31	.31
2	Problem with assignments, tests, and or exams	0.17	0.06, 0.27
3	Financial problems (debts, lack of pocket money)	0.15	0.05, 0.26
4	Change in acceptance by peers	0.14	0.04, 0.25
5	Change in living conditions/accommodation	0.13	0.04, 0.23
6	Death of a relative or close friend	0.13	0.01, 0.25
7	Loss of a cell phone, tablet, or laptop computer	0.11	0.01, 0.22

Note: Multivariable regression model of the unique influence of individual of stressful life events on depression based on a continuous scale.

β: standardized beta; CI: confidence interval; η²: eta squared, a measure of effect size.

All significant associations are in bold.

No competing interests reported.

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The relationship between Stressful Life Events and Anxiety Symptoms: A cross-sectional survey of with university students in Botswana

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