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High-Prevalence Energy Drink Use among Nigerian University
Students: A Cross-Sectional Analysis of Motivations, Dependency
Indicators, and Self-Reported Adverse Effects
Abdul-Raheem Folorunsho Ahmad, Luqman Adepoju Hassan, Idowu Oluwagbemiga Coker, Kolade
Pelumi Folorunso, Rasheed Tunde Lawal, Foluso Olamide Ojo, Tolulope Adefola Edward, Oluwafemi
Samuel Olaniyi
University of Ilesa, Ilesa, Osun State, Nigeria
DOI: https://dx.doi.org/10.51244/IJRSI.2025.1215PH000201
Received: 07 November 2024; Accepted: 14 November 2024; Published: 26 November 2025
ABSTRACT
Background: Energy drink (ED) consumption is rapidly increasing among university students, with potential
implications for dependency and adverse health outcomes due to high caffeine and sugar content. This study
assessed the prevalence, motivations, dependency indicators, and self-reported adverse effects of ED
consumption among Nigerian university students.
Methods: A descriptive cross-sectional survey was conducted among 542 university students across Nigeria
using a structured, self-administered questionnaire. Data were analyzed using descriptive statistics and chi-
squared tests to explore links between demographic factors, awareness, and consumption.
Results: More than half of respondents (52.8%) currently use energy drinks, mostly to boost energy or
improve performance (61.2%). Although 88.9% were aware of health risks, many showed signs of dependency
such as cravings (38.5%) or a perceived need to drink (37.1%). Males and younger adults consumed more
frequently. Interestingly, non-consumers reported higher rates of some symptoms like headaches and
palpitations, possibly due to self-selection bias.
Conclusion: Energy drink use is highly prevalent among Nigerian university students and largely driven by
academic and performance-related motivations. Despite high awareness of risks, dependency signs persist.
Targeted health education and regulatory measures are needed to reduce potential health risks.
Keywords: Energy drinks; caffeine dependency; awareness; university students; Nigeria; cross-sectional study
INTRODUCTION
Energy drinks (EDs) are non-alcoholic beverages designed with different formulations containing
methylxanthines like caffeine and taurine, carbohydrates, vitamins, herbal extracts and sweeteners (1). They
are commonly taken on the basis of their perceived effects on reducing fatigue, inhibiting sleep, increasing
energy, and improving mental and physical performance (2). The active ingredient primarily is caffeine, which
may be obtained by extracting guarana or yerba mate (3). Caffeine is commonly available in significantly
higher doses in energy drinks than in soft drinks; e.g., cola beverages typically has about 24 mg of caffeine per
serving, whereas energy drinks often range from 50 to 200 mg per serving (4). There is some evidence that
caffeine, alone or combined with glucose, can enhance attention, reaction times, and alertness scales and
alleviate fatigue during cognitively challenging tasks (5). Also, other typical additives, including taurine, are
higher in EDs than other soft drinks, and several of the formulations are high in sugar (21-34 g per 8 ounces)
(6). High consumption of sugar has been associated with the development of glucose intolerance and
dyslipidemia, systemic inflammation, and other metabolic imbalances that can predispose to cardiometabolic
diseases (7).
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The use of EDs has been on the rise globally among young adults, especially university students, who form one
of the highest groups of consumers (8). Research conducted by Adepoju and Ojo (2014) discovered that 74.6
percent of students at the University of Ibadan had tried energy drinks at least once, and 42.4 percent had
consumed no less than one can of energy drinks per week (6). In the same way, Ezemenahi et al. (2024) found
that more than 81.5 percent of medical students enrolled at Nnamdi Azikiwe University Teaching Hospital had
used EDs, and the majority of them had started using them between the ages of 10 and 20 years (9). Some of
the reported reasons why people consume include the use of the substance to boost their energy levels, improve
mental clarity, academic stress, curiosity and peer pressure. Similar results were found in Usmanu Danfodiyo
University, Sokoto, where 55.4% of students said they had ever used EDs and 25.7% were currently using
them, some up to five cans a day (10). The triggers of ED consumption in Nigerian undergraduates include
peer influence, curiosity and promotional marketing (9).
Although consumption is very popular, there is still low awareness about the health risks involved in
consuming energy drinks. Among Nigerian university students, studies have reported such adverse effects as
insomnia, frequent urination, dehydration, anxiety, headaches, palpitations, and gastrointestinal symptoms
(6,10). The findings are consistent with global reports of these adverse effects, like palpitations and sleep
problems among adolescents in Korea (11). The high caffeine levels coupled with the sugar load and common
use during times of academic or social stress pose questions of dependency, overuse and the long-term health
consequences (1).
Since the consumption of energy drinks is growing very fast in Nigeria, and the usage of energy drinks is
becoming the norm among students, there is an urgent need to know the consumption patterns, reasons, and
health consequences, as well as the possibilities of EDs creating a dependency. This research was thus
conducted to help analyze exhaustively the energy drink consumption habits, usage patterns, reasons for use,
satisfaction levels, potential health impacts, and signs of dependency among Nigerian university students aged
10 years and above.
MATERIALS AND METHODOLOGY
2.1 Study Design and Setting
This study adopted a descriptive cross-sectional survey design aimed at evaluating energy drink consumption
patterns, awareness levels, motivations, dependency indicators, and self-reported adverse effects among
Nigerian university students. The research was conducted across selected tertiary institutions within Nigeria’s
six geopolitical zones, with the highest representation from the South-West region, where student accessibility
and participation were greatest during the survey period.
2.2 Study Population and Sampling Technique
The study population comprised university students who were enrolled at the time of data collection. Younger
respondents aged 10–19 years were included because, in Nigeria, 16 years represents the typical minimum age
for university entry through the Joint Admissions and Matriculation Board (JAMB). Including this group
allowed the study to capture early exposure patterns to energy drinks among adolescents transitioning into
university life (12) and a convenience sampling technique was employed to recruit participants who were
available and willing to participate. Inclusion criteria required that respondents be registered students within
recognized tertiary institutions and provide informed consent. Individuals who were not students or who
declined consent were excluded from participation.
2.3 Sample Size Determination
A total of 542 respondents participated in the study, consisting of 188 (34.7%) males and 354 (65.3%) females.
The sample size was derived using Cochran’s formula for cross-sectional studies, assuming a 50% estimated
prevalence of energy drink consumption, a 5% margin of error, and a 95% confidence interval (13). The
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computed sample size was adjusted to account for potential non-response and ensure representativeness across
age groups and regions.
2.4 Data Collection Instrument
Data were gathered using a structured, self-administered questionnaire developed by the researchers after
reviewing relevant literature on energy drink consumption and health outcomes. Questionnaire was set to
standard using the Likert scale while the internal consistency of the survey questions was assessed using the
Cronbach’s alpha. The questionnaire comprised five sections: (i) socio-demographic characteristics; (ii)
awareness and knowledge of energy drinks and their potential side effects; (iii) consumption patterns,
motivations, and preferred brands; (iv) indicators of dependency such as cravings, perceived need, and
difficulty reducing intake; and (v) self-reported adverse effects associated with consumption. The instrument
was pretested among 30 students outside the study sample to assess clarity, reliability, and internal consistency.
Feedback obtained from the pilot testing informed final revisions before deployment.
2.5 Data Collection Procedure
Questionnaires were distributed both physically and electronically to enhance reach and participation. Trained
research assistants supervised the data collection process to ensure accuracy and completeness of responses.
Participation was voluntary, and respondents were informed about the study objectives, confidentiality of
responses, and their right to withdraw at any stage without consequence.
2.6 Data Analysis
All completed questionnaires were coded and entered into Microsoft Excel before being exported to the
Statistical Package for the Social Sciences (SPSS) version 26.0 for analysis. Descriptive statistics such as
frequencies, percentages, and charts were used to summarize categorical variables, while cross-tabulations
were used to compare energy drink consumers and non-consumers. Pearson’s Chi-squared (χ²) tests were
applied to examine associations between socio-demographic variables (age, gender, region, employment status,
and marital status) and key study variables including awareness levels and consumption patterns. Statistical
significance was set at p ≤ 0.05.
2.7 Ethical Considerations
Ethical approval for the study was obtained from the ethical committee, Faculty of Basic Medical Science,
University of Ilesa. Additional permissions were secured from the relevant departments and university
authorities before data collection. Written informed consent was obtained from all participants, and anonymity
and confidentiality were strictly maintained.
RESULTS
3.1 Participant Socio-Demographic Characteristics
A total of five hundred and forty-two (542) respondents consisting of 188 (34.7%) males and 354 (65.3%)
females participated in the study. It reveals that more females partook in the study with 65.3% responses as
against 34.7% responses from their male counterparts. This, however, does not suggest that there is more
female population than male at all levels; the gender distribution of the respondents in the study area is based
on their accessibility and availability during the period this survey was carried out. The study cohort was
characterized by a high proportion of young adults and adolescents, with 47.0% of participants (n=255) aged
20-29 years and 35.4% (n=192) aged 10-19 years. Geographically, participants were primarily from Nigeria's
South-west geopolitical zone (82.7%, n=448) as presented in Table 1.
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Table 1: Socio-demographic characteristics of the study cohort (N=542).
Characteristic
Category
Frequency (n=542)
Percentage (%)
Age
10-19 Years
20-29 Years
30-39 Years
40-49 Years
50-59 Years
60 Years and above
Total
192
255
67
16
10
2
542
35.4
47.0
12.4
3.0
1.8
0.4
100.0
Gender
Male
Female
Total
188
354
542
34.7
65.3
100.0
Origin by Geo-Political Zones
South-west
South-South
South-East
North-West
North-East
North-Central
Total
448
25
11
0
6
52
542
82.7
4.6
2.0
0.0
1.1
9.6
100.0
Employment Status
Employed
Jo Seeker
Self-employed
Student
Retired
Total
103
21
3
32
383
542
19.0
3.9
0.6
5.9
70.7
100.0
Marital Status
Divorced/Widowed
Married
Single
Total
6
86
450
542
1.1
15.9
83.0
100.0
Figures 1: Bar Chart of Respondents’ State of Origin
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3.2 Awareness of Energy Drinks and Potential Side Effects
A high degree of awareness regarding energy drinks was observed across the cohort. The vast majority of
participants (93.0%, n=504) reported being familiar with energy drinks. Furthermore, knowledge of potential
adverse health effects was similarly widespread, with 88.9% (n=482) of all respondents affirming their
awareness of such risks (Table 2).
To synthesize these findings, a composite awareness score was generated. Based on this, the majority of
participants (89.1%, n=483) were categorized as having 'high awareness' regarding energy drinks and their
potential effects. In contrast, 9.1% (n=49) were categorized as having 'moderate awareness' and 1.8% (n=10) as
having 'low awareness' (Figure 2).
Table 2: Respondent Awareness of Energy Drinks and Their Potential Side Effects (N=542).
Frequency (n=542)
Percentage (%)
504
24
14
542
93.0
4.4
2.6
100.0
482
39
21
542
88.9
7.2
3.9
100.0
Figure 2: Pie-chart of High/Moderate/Low Awareness percentages
3.3 Consumption Motivations, Patterns, and Dependency Indicators
Analysis of the energy drink consumer cohort (n=286) revealed that consumption is primarily driven by
functional and performance-related motives. The leading motivation for use was "to boost energy or
INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)
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performance" (61.2%, n=175), a finding consistent with consumption occasions linked to academic or
highpressure environments, such as "during stressful situation" (19.2%) and "while studying or working"
(18.2%).
Consumption frequency was largely moderate, with a majority of users (68.2%, n=195) consuming fewer than
five cans per month. This consumption appears reinforced by high perceived efficacy; a combined 85.7% of
users reported that they "partially" (29.4%) or fully "yes" (56.3%) achieve the intended benefits after
consumption.
Crucially, and in line with the study's objectives, a substantial subset of consumers reported key indicators of
dependency. Despite the moderate consumption frequency, over one-third of users (a combined 37.1%)
reported a perceived functional need to consume energy drinks, either "sometimes" (30.8%, n=88) or "always"
(6.3%, n=18). This was mirrored by the prevalence of cravings, with a combined 38.5% of consumers
experiencing them "Periodically" (30.1%, n=86) or "frequently" (8.4%, n=24). Furthermore, of the consumers
who had attempted to reduce their intake (n=107), a notable proportion found it "manageable" (31.1% of all
consumers) or "very difficult" (6.3% of all consumers).
These data (detailed in Table 3) characterize a user profile where consumption is motivated by performance
demands, reinforced by perceived efficacy, and associated with a significant prevalence of dependency
indicators.
Table 3. Energy Drink Consumption Patterns, Motivations, and Dependency Indicators Among
Consumers (n=286).
Variable
Response Category
Frequency (n)
Percentage (%)
Brand Consumed
Fearless
Lucozade Boost
Predator
Monster
Bullet
Total
116
64
42
33
31
286
40.6
22.4
14.7
11.5
10.8
100.0
Primary Motivation
To boost energy or performance
For enjoyment or taste
Habit or social influence
Total
175
94 17
286
61.2
32.9
5.9
100.0
Consumption Occasion
Anytime, no specific occasion
During stressful situation
While studying or working
At social gatherings or parties
During physical exercise or sports
After physical exertion
Total
92 55
52
46
32
9
286
32.2
19.2
18.2
16.1
11.2
3.1
100.0
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Monthly Frequency
Less than 5 cans
5–10 cans
11–20 cans
More than 20 cans
Total
195
59
21
11
286
68.2
20.6
7.3
3.8
100.0
Perceived Efficacy
Yes
Partially
Not sure
No
Total
161
84
24
17
286
56.3
29.4
8.4
5.9
100.0
Perceived Need
No, not at all
Yes, sometimes
Yes, always
Total
182
88
18
286
63.6
30.8
6.3
100.0
Cravings
No, never
Yes, Periodically
Yes, frequently
Total
176
86
24
286
61.5
30.1
8.4
100.0
Difficulty Quitting
No, I have not tried
Yes, it was manageable
Yes, and it was very difficult
Total
179
89
18
286
62.6
31.1
6.3
100.0
3.4 Comparative Prevalence of Self-Reported Adverse Effects
To identify potential associations between energy drink consumption and adverse health phenomena, a detailed
comparative analysis of symptom prevalence was conducted between consumers (n=286) and non-consumers
(n=256). The full frequency distributions for nine separate adverse effects are detailed in Table 4 and 5.
The analysis revealed the unexpected finding that non-consumers reported a statistically significant higher
prevalence of several key adverse symptoms. This was most pronounced for headaches, which were reported at
least periodically by 47.3% of non-consumers compared to 31.5% of consumers (x
2
test, p < 0.001). Similarly,
non-consumers reported a significantly higher incidence of rapid heartbeat or palpitations (28.1% vs. 19.2%, x
2
test, p = 0.015) and high blood pressure (12.1% vs. 5.2%, x
2
test, p = 0.004).
For all other physiological and psychological symptoms measured—including difficulty sleeping, anxiety,
fatigue, and irritability—the prevalence rates were comparable between the two groups, with no statistically
significant differences observed (p > 0.05 for all). For instance, 30.4% of consumers reported experiencing
anxiety or nervousness at least periodically, a rate nearly identical to the 30.9% observed in the non-consumer
cohort.
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Table 4: Participants' Self-Reported Adverse Effects in Consumers vs. Non-Consumers
Advers
e effect
Energy drink consumers
Energy drink non-consumers
Never
Rarel
y
Periodi
cally
Often
Alw
ays
Tota
l
Never
Rarel
y
Periodi
cally
Often
Alw
ays
Tota
l
Difficul ty
sleepin
g /
Insomn
ia
107
(37.4
1%)
97
(33.9
2%)
37
(12.94
%)
31
(10.8
4%)
14
(4.90
%)
286
(100
%)
94
(36.7
2%)
76
(29.6
9%)
47
(18.36
%)
30
(11.7
2%)
9
(3.52
%)
256
(100
%)
Headac
hes
123
(43.0
1%)
73
(25.5
2%)
52
(18.18
%)
28
(9.79
%)
10
(3.50
%)
286
(100
%)
51
(19.9
2%)
84
(32.8
1%)
69
(26.95
%)
46
(17.9
7%)
6
(2.34
%)
256
(100
%)
Rapid
heartbe
at /
Palpitat ions
145
(50.7
0%)
86
(30.0
7%)
33
(11.54
%)
19
(6.64
%)
3
(1.05
%)
286
(100
%)
116
(45.3
1%)
68
(26.5
6%)
42
(16.41
%)
28
(10.9
4%)
2
(0.78
%)
256
(100
%)
Increas ed
thirst
91
(31.8
2%)
111
(38.8
1%)
43
(15.03
%)
32
(11.1
9%)
9
(3.15
%)
286
(100
%)
75
(29.3
0%)
97
(37.8
9%)
50
(19.53
%)
27
(10.5
5%)
7
(2.73
%)
256
(100
%)
High blood
pressur
e
241
(84.2
7%)
30
(10.4
9%)
6
(2.10%
)
9
(3.15
%)
0
(0.00
%)
286
(100
%)
188
(73.4
4%)
37
(14.4
5%)
14
(5.47%
)
15
(5.86
%)
2
(0.78
%)
256
(100
%)
Anxiety or
nervous ness
129
(45.1
0%)
70
(24.4
8%)
53
(18.53
%)
30
(10.4
9%)
4
(1.40
%)
286
(100
%)
108
(42.1
9%)
69
(26.9
5%)
49
(19.14
%)
20
(7.81
%)
10
(3.91
%)
256
(100
%)
Muscle
tremors or
cramps
136
(47.5
5%)
75
(26.2
2%)
45
(15.73
%)
22
(7.69
%)
8
(2.80
%)
286
(100
%)
111
(43.3
6%)
73
(28.5
2%)
44
(17.19
%)
25
(9.77
%)
3
(1.17
%)
256
(100
%)
Fatigue or
energy
crashes
125
(43.7
1%)
72
(25.1
7%)
60
(20.98
%)
23
(8.04
%)
6
(2.10
%)
286
(100
%)
105
(41.0
2%)
74
(28.9
1%)
45
(17.58
%)
27
(10.5
5%)
5
(1.95
%)
256
(100
%)
Feeling
s of irritabil
ity or
restless ness
121
(42.3
1%)
87
(30.4
2%)
41
(14.34
%)
27
(9.44
%)
10
(3.50
%)
286
(100
%)
101
(39.4
5%)
74
(28.9
1%)
48
(18.75
%)
28
(10.9
4%)
5
(1.95
%)
256
(100
%)
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Table 5: Comparative Prevalence of Self-Reported Adverse Effects in Consumers vs. Non-Consumers.
Adverse Effect
Consumers (n=286) reporting
'Periodically,' 'Often,' or
'Always'
n (%)
Non-Consumers
(n=256) reporting
'Periodically,' 'Often,'
or 'Always' n (%)
p-value
Difficulty sleeping /
Insomnia
82 (28.67%)
89 (34.77%)
0.1523
Headaches
90 (31.47%)
121 (47.27%)
0.0002*
Rapid heartbeat /
Palpitations
55 (19.23%)
72 (28.12%)
0.0147
Increased thirst
84 (29.37%)
84 (32.81%)
0.3870
High blood pressure
15 (5.24%)
31 (12.11%)
0.0042*
Anxiety or nervousness
87 (30.42%)
79 (30.86%)
0.9117
Muscle tremors or
cramps
75 (26.22%)
72 (28.12%)
0.6192
Fatigue or energy
crashes
89 (31.12%)
77 (30.08%)
0.7930
Feelings of irritability
or restlessness
78 (27.27%)
81 (31.64%)
0.2648
* P value ≤ 0.05, hence significant
3.6 Demographic Correlates of Awareness and Consumption Patterns
To identify demographic predictors of awareness and consumption, Pearson Chi-squared (x
2
) tests were
performed to assess associations between demographic characteristics and the composite 'Awareness Level'
and 'Consumption Pattern' scores.
The analysis of awareness (summarized in Table 5) identified Age as the sole significant demographic
predictor. A statistically significant association was found between the participants’ age group and their
designated awareness level (x
2
= 25.091, df = 10, p = 0.005). No significant associations were observed
between awareness level and gender, geopolitical origin, employment status, or marital status (p > 0.05 for all).
The analysis of consumption patterns (summarized in Table 6) identified Gender as the only significant
demographic correlate. A statistically significant relationship was found between gender and the 'Good,' 'Fair,'
or 'Poor' consumption pattern categories (x
2
= 7.779, df = 2, p = 0.020). No other demographic variables
showed a significant association with consumption patterns (p > 0.05 for all).
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Table 5: Relationship between socio-demographic and awareness of energy drinks
Awareness of Energy Drinks
Total
x2
d.f
High
Awareness
Moderate
Awareness
Low
Awareness
pvalue
Age:
10-19 Years
20-29 Years
30-39 Years
40-49 Years
50-59 Years
60 Years and
above Total
166(30.6%)
232(42.8%)
63(11.6%)
14(2.6%)
7(1.3%)
1(0.2%)
483(89.1%)
25(4.6%)
14(2.6%)
4(0.7%)
2(0.4%)
2(0.4%)
1(0.2%)
49(9.0%)
1(0.2%)
9(1.7%)
0(0.0%)
0(0.0%)
0(0.0%)
0(0.0%)
10(1.8%)
192 (35.4)
255 (47.0%)
67 (12.4%)
2 (0.4%)
16 (3.0%)
10 (1.8%)
542(100.0%)
25.091
10
0.005*
Gender:
Female
Male
Total
312(57.6%)
171(31.5%)
483(89.1%)
36(6.6%)
13(2.4%)
49(9.0%)
6(1.1%)
4(0.7%)
10(1.8%)
354 (65.3%)
188 (34.7%)
542 (100.0%)
1.673
2
0.433
Origin:
South West
South-South
South East
North West
North East
North Central
Total
395(72.9%)
23(4.2%)
10(1.8%)
0(0.0%)
6(1.1%)
49(9.0%)
483(89.1%)
43(7.9%)
2(0.4%)
1(0.2%)
0(0.0%)
0(0.0%)
3(0.6%)
49(9.0%)
10(1.8%)
0(0.0%)
0(0.0%)
0(0.0%)
0(0.0%)
0(0.0%)
10(1.8%)
448 (82.7%)
25 (4.6%)
11 (2.0%)
0 (0.0%) 6
(1.1%)
52 (9.6%)
542 (100.0%)
3.745
8
0.879
Employment
Status:
Employed
Jo Seeker
Self-employed
Student
Retired
Total
94(17.3%)
18(3.3%)
27(5.0%)
341(62.9%)
3(0.6%)
483(89.1%)
9(1.7%)
2(0.4%)
5(0.9%)
33(6.1%)
0(0.0%)
49(9.0%)
0(0.0%)
1(0.2%)
0(0.0%)
9(1.7%)
0 (0.0%)
10(1.8%)
103 (19.0%)
21 (3.9%)
32(5.9%)
383 (70.7%)
3 (0.6%)
542 (100.0%)
6.143
8
0.631
Marital Status:
Divorced/Widowed
Married
Single
Total
4(0.7%)
77(14.2%)
402(74.2%)
483(89.1%)
2(0.4%)
8(1.5%)
39(7.2%)
49(9.0%)
0(0.0%)
1(0.2%)
9(1.7%)
10(1.8%)
6 (11.0%)
86 (15.9%)
450 (83.0%)
542 (100.0%)
4.722
4
0.317
INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)
ISSN No. 2321-2705 | DOI: 10.51244/IJRSI | Volume XII Issue XV October 2025 | Special Issue on Public Health
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* P value ≤ 0.05, hence significant
Table 7: Relationship between socio-demographic and consumption patterns of energy drinks
Respondents’ Consumption Patterns
Total
x2
d.f
pvalue
Good
Consumption
Patterns
Fair
Consumption
Patterns
Poor
Consumption
Patterns
Age:
10-19 Years
20-29 Years
30-39 Years
40-49 Years
50-59 Years
Total
46(16.1%)
50(17.5%)
10(3.5%)
2(0.7%)
1(0.3%)
109(38.1%)
19(6.6%)
26(9.1%)
3(1.0%)
2(0.7%)
0(0.0%)
50(17.5%)
45(15.7%)
61(21.3%)
16(5.6%)
2(0.7%)
3(1.0%)
127(44.4%)
110 (38.5)
137 (47.9%)
29 (10.1%)
6 (2.1%)
4 (1.4%)
286(100.0%)
5.461
8
0.707
Gender:
Female
Male
Total
60(21.0%)
49(17.1%)
109(38.1%)
36(13.6%)
11(3.8%)
50(17.5%)
76(26.6%)
51(17.8%)
127(44.4%)
175 (61.2%)
111 (38.8%)
286(100.0%)
7.779
2
0.020
Origin:
South West
South-South
South East
North West
North East
North Central
Total
96(33.6%)
2(0.7%)
2(0.7%)
0(0.0%)
1(0.3%)
8(2.8%)
109(38.1%)
46(16.1%)
3(1.0%)
1(0.3%)
0(0.0%)
0(0.0%)
0(0.0%)
50(17.5%)
101(35.3%)
8(2.8%)
2(0.7%)
0(0.0%)
3(1.0%)
13(4.5%)
127(44.4%)
243 (85.0%)
13 (4.5%)
5 (1.7%)
0(0.0%)
4 (1.4%)
21 (7.3%)
286(100.0%)
10.598
8
0.226
Employment
Status:
Employed
Jo Seeker
Self-employed
Student
Retired
Total
15(5.2%)
1(0.3%)
5(1.7%)
88(30.8%)
0(0.0%)
109(38.1%)
5(1.7%)
2(0.7%)
1(0.3%)
42(14.7%)
0(0.0%)
50(17.5%)
26(9.1%)
7(2.4%)
5(1.7%)
87(30.4%)
2(0.7%)
127(44.4%)
46 (16.1%)
10 (3.5%)
11(3.8%)
217 (75.9%)
2(0.7%)
286(100.0%)
11.411
8
0.179
INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)
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Marital Status:
Divorced/Widowed
Married
Single
Total
0(0.0%)
11(3.8%)
98(34.3%)
109(38.1%)
1(0.3%)
4(1.4%)
45(15.7%)
50(17.5%)
1(0.3%)
19(6.6%)
107(37.4%)
127(44.4%)
2 (0.7%)
34 (11.9%)
250 (87.3%)
286(100.0%)
4.187
4
0.381
* P value ≤ 0.05, hence significant
DISCUSSION
This study highlights a high prevalence (52.8%) of energy drink use among Nigerian university students,
driven mainly by academic and performance-related motives. This observed 52.8% consumption prevalence is
substantially similar to, or higher than, average documented rates in university populations across diverse
geographical contexts, including Jordan (42.0%-50%) (14,15) and Poland (49%) (16).Within the African
context, these findings are particularly salient, as systematic reviews report prevalence rates up to 58% among
South African university students (17). This elevated prevalence likely reflects a synergy between the high
academic pressure characteristic of Nigerian tertiary institutions (18).
Despite widespread awareness of health risks (88.9%), many users showed dependency indicators such as
cravings (38.5%) and perceived functional need (37.1%), suggesting behavioral reinforcement rather than lack
of knowledge as the main driver.These patterns align disturbingly well with emerging literature on Caffeine
Use Disorder (19). While this study did not employ formal diagnostic criteria, the observed patterns—
particularly difficulty reducing consumption despite risk awareness—suggest a meaningful subset may meet
criteria for problematic use as conceptualized in DSM-5.
Gender and age were significant predictors of consumption and awareness, respectively, consistent with other
reports that younger males are more likely to use energy drinks. Interestingly, non-consumers reported higher
rates of headaches, palpitations, and high blood pressure. This counterintuitive finding likely reflects
selfselection bias, where individuals with preexisting health concerns avoid energy drinks, rather than a
protective effect of consumption. This interpretation is supported by research identifying pre-existing health
concerns as a primary reason for non-consumption (20-22). It is also plausible that the consumer and non-
consumer groups differ systematically in unmeasured variables, leading to confounding. Baseline stress levels,
sleep patterns, or dietary habits (20,22) could be potent confounders, especially given that psychological stress
is robustly associated with both headache frequency and cardiovascular symptoms (23).
Overall, the study underscores a gap between awareness and behavior. High knowledge of risks does not
appear to stop use,This aligns with established health behavior frameworks, such as the Health Belief Model,
which posits that behavior change requires not only risk knowledge but also perceived personal susceptibility,
severity, and the absence of significant barriers (24) implying that educational interventions alone may be
insufficient. Instead, addressing underlying stress, sleep deprivation, and academic pressure may be more
effective in reducing reliance on energy drinks.
Limitations
This study's findings should be interpreted considering several limitations. The cross-sectional design
precludes causal inference and cannot rule out reverse causation, particularly relevant to the adverse effects
findings. Reliance on self-report introduces potential recall and social desirability biases affecting consumption
and symptom reporting. The convenience sample, primarily from South-West Nigeria, limits generalizability.
Furthermore, the study did not employ validated dependency scales or control for key confounders like
baseline mental health, total caffeine intake, or concurrent substance use, which could influence the observed
associations.
INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)
ISSN No. 2321-2705 | DOI: 10.51244/IJRSI | Volume XII Issue XV October 2025 | Special Issue on Public Health
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Page 2671
CONCLUSION
Energy drink use is widespread among Nigerian university students and is largely driven by academic and
performance pressures rather than ignorance of risks. Although consumption frequency is generally moderate,
signs of dependency are present in a notable subset of users. The findings do not establish causal relationships
between energy drink use and health outcomes but highlight associations that warrant further exploration.
Implications
Despite limitations, this study offers actionable implications:
1. Policy: The high prevalence (52.8%) and awareness-behavior gap (88.9% aware vs. 52.8% consuming)
highlight the insufficiency of awareness-only campaigns. Regulatory focus on age restrictions, accurate
caffeine labeling for local brands, and marketing controls targeting youth are warranted.
2. University Interventions: Given the academic drivers, universities should implement stress
management programs, promote healthy fatigue alternatives, and consider regulating on-campus
sales/marketing. Screening for problematic ED use may identify students under significant academic
distress.
3. Clinical Practice: Clinicians serving students should inquire about ED use as a potential indicator of
underlying stress, sleep issues, or nascent Caffeine Use Disorder, while interpreting reported symptoms
cautiously due to potential self-selection biases.
4. Future Research: To strengthen causal inferences, longitudinal studies are essential. Additionally,
qualitative investigations should explore the socio-cultural factors driving and impeding behavioral
change. Key priorities include analyzing ingredients in local brands and evaluating interventions
tailored to the Nigerian setting. Biochemical assays to validate caffeine consumption levels, coupled
with histopathological assessments of multi-organ caffeine toxicity in preclinical models featuring
diverse local brands, would be highly impactful. These efforts would foster critical synergies between
field-based global health research and laboratory-based studies.
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