Abstract
Objective:
We sought to identify the general health of college students.
Participants:
A total of 4402 university freshmen and sophomores were recruited to report their general health through an online questionnaire.
Methods:
Responses from the DePaul Symptom Questionnaire were analyzed. We then conducted latent class analyses to evaluate 54 different symptoms among participants.
Results:
A four class solution was identified, consisting of a group of asymptomatic students (35.65%), a second group of students reporting mild fatigue and sleep symptoms (38.87%), a third group reporting moderate sleep and fatigue symptoms (20.36%), and a group reporting moderate and severe complaints on the majority of symptoms (5.11%). Female students had 2.07 times the relative risk of the severe symptom class of men. Indigenous students have 2.88 times the relative risk of occupying the severe symptom class than non-indigenous students.
Conclusions:
The results suggest that about 5% of college students have varied symptoms of a moderate to severe degree. Future research is needed to better assess whether there are biological associations with these self-report findings, as well as to determine longer-term implications of these symptoms.
Keywords: General Health, Latent Class Analysis, College Student
Introduction
College student health has been studied since the 19th century1,2. Issues of concern include high risk behavior, sexual health, mental health, and sleep dysregulation3, many of which are amenable to counseling and therapy.4–6 For example, college health guidelines from the Center for Disease Control and Prevention (CDC) focus on dietary behaviors, sexually transmitted diseases, sleep hygiene, vaccinations, substance abuse, violence, and mental health.7 Another study examined about 10,000 Minnesotan students and their current healthcare status/needs, and focused on health insurance and health care utilization, mental health, alcohol and drug use, tobacco use, nutrition, physical activity, and sexual health.8
In addition, physical symptoms present in college populations are also of importance. For example, the American College Health Association National College Health Assessment9 gathers information on disease, injury, and general symptoms of college students. The most recent report concluded that the predominant health issues among college students were allergies (19.3%), back pain (12.9%), and sinus infection (15.5%).9 However, these data only reflected physician diagnoses. Therefore students who may be experiencing symptoms, but do not visit the campus health services or a primary care clinician due to lack of motivation, time, cost, or unwillingness to disclose substance abuse or high risk behaviors were excluded.10–12 Underutilization of health services among college students is also supported by data in which female students report a greater annual usage of campus health services or visiting a clinician for an annual checkup than male students.13.14 Increased risk and marginalization among nonbinary and transgender college students, along with the lack of longitudinal data regarding health services visits, indicate that such students may be more distrustful of campus health services and therefore may not seek them out.15 Additionally, Native American/ Alaskan Native college students have been reported to be the most at risk student population for severe symptoms, but health services usage is reported to be lower for them than for other groups.13,16 Thus, evaluating student symptoms based solely on those who make an appointment with a physician is not reflective of the general health of college students. Additionally, while the aforementioned report listed the most common illness diagnoses of students, it did not identify whether or not these illnesses were comorbid or how seriously the illnesses affected the lives of students.
One statistical process which can be used to identify clusters of symptoms is latent class analysis (LCA). The process of LCA creates a number of “solutions”, each containing subgroups that categorize the data; for example, a two-class solution would contain two subgroups of students. LCA identifies groups based on shared variability of continuous or categorical variables.17 The difference between LCA and other modeling techniques, such as factor analysis, is that LCA is a person-centered approach, allowing for the classification of individuals into meaningful groups based on shared characteristics.17 Applying LCA to a large sample of university students allows for a greater understanding of reported general complaints by identifying subgroups categorized by multiple symptoms.
The current study sought to overcome limitations of previous college health surveys by sampling students using a validated questionnaire that provides a standardized method for assessing the severity of various complaints without the necessity of a physician visit. LCA was then used to categorize the data.
Method
A total of 4,402 freshman and sophomore students at Northwestern University were recruited to participate in a prospective study of student health. Participants completed an online questionnaire following online consent. Participants were then compensated. This study was approved by all relevant Institutional Review Boards.
Measures
DePaul Symptom Questionnaire (DSQ) The DSQ is a 54-item self-report measure of symptomatology and illness history18 that provides a standardized method for assessing the dimensions of illness symptom complexes including fatigue, post exertional malaise, sleep, pain, neurocognitive, autonomic, neuroendocrine, and immune functioning. Participants rate each symptom’s frequency over the past six months on a 5-point Likert scale: 0=none of the time, 1=a little of the time, 2=about half the time, 3=most of the time, and 4=all of the time. Likewise, participants rate each symptom’s severity over the past six months on a similar 5-point Likert scale: 0=symptom not present, 1=mild, 2=moderate, 3=severe, 4=very severe. Frequency and severity scores are multiplied by 25 to create 100-point scales. The 100-point frequency and severity scores for each symptom are averaged to create one composite score per symptom. Average scores below 25 are considered to be very low as participants would report the symptoms as either not occurring, or occurring with no negative effects. Scores from 25 to 50 are considered to be mild to moderate. In contrast, average scores of 75 or greater are considered to be more serious (occurring with a severe to very severe intensity, most or all of the time).19 The DSQ has evidenced good test-retest reliability among both patient and control groups,19 and is available in the shared library of Research Electronic Data Capture (REDCap).20
Sociodemographics Sociodemographic items collected included gender, year of study, and race/ethnicity.
Statistical analysis
Mplus version 7.321 was used to conduct the LCA, a computational technique that evaluates which students shared similar symptomatology. In order to identify the best-fit solution, six different class solutions were examined, each containing a different number of groups. This is consistent with previous literature which suggests that 6–8 solutions be examined to determine which best fits the data.22 The 54 DSQ symptom averages were included in the analysis as continuous variables. Parameter estimates were determined in an iterative manner using maximum likelihood estimation with robust standard errors (MLR). As MLR can over-fit the data if too few computations are executed, 300 random sets of start values were used in the first step of the optimization. Then, the 40 sets with the largest log likelihood values were selected for the second step of the optimization process, a standard process for LCA.21
Comparative assessment of best-fit was conducted using Bayesian Information Criterion (BIC), Akaike Information Criterion (AIC), Entropy, log likelihood, and Lo-Mendell-Rubin Test (LMRT).22 The principle of LCA relies on multiple best-fit assessments and not one single criterion. Therefore, all of the described criteria were used to estimate the quality of the 6 solutions, and the best one was then selected.
Results
Of the 4,402 students, 57.7% (n = 2540) were female, 41.9% (n = 1847) were male, and 0.3% (n = 15) reported themselves as nonbinary or preferred not to disclose. Of the total sample, 60.6% reported themselves as White/Caucasian, 25.9% reported themselves as Asian/Pacific Islander, 10.6% reported themselves as Black/African American, 1.2% reported themselves as Alaskan Native/ Native American, 4.5% reported themselves as multiracial, 2.1% preferred to not respond; 14.4% reported themselves as Latinx; students could indicate more than one response. LCAs were used to examine the best-fit structure for student symptoms. Table 1 shows the fit statistics of each of the six class solutions. All solutions met the recommended lower bound for entropy25; however, only class solutions 2 through 4 had a significant LMRT. This LMRT result indicated the four-class solution better explained the data than the three- or five-class solutions. Among latent class solutions 1 through 4, the four-class solution had the lowest AIC and BIC. Therefore, the four-class model was considered the best-fit, and the students were grouped accordingly by symptoms and symptom severity into 4 classes.
Table 1.
Fit Statistics for Latent Class Solutions
| Latent Class Solutions | Log Likelihood | BIC | AIC | LMRT p-value | Entropy |
|---|---|---|---|---|---|
| 1 Class Solution | 507094 | 2029282 | 2028592 | ||
| 2 Class Solution | 497652 | 1992776 | 1991735 | <.001 | 0.96 |
| 3 Class Solution | 494985 | 1981767 | 1980374 | <.001 | 0.94 |
| 4 Class Solution | 493859 | 1977726 | 1975981 | .01 | 0.90 |
| 5 Class Solution | 493188 | 1975502 | 1973406 | .07 | 0.90 |
| 6 Class Solution | 493188 | 1974093 | 1971646 | .43 | 0.90 |
Table 2 shows the symptom means and standard errors for the four-class solution. Class 1 accounted for 35.65% of the student sample (n = 1570), class 2 accounted for 38.87% of the sample (n = 1712), class 3 accounted for 20.37% of the sample (n = 897), and class 4 accounted for 5.11% (n = 225) of the sample. Symptoms of fatigue and sleep occurred in multiple classes, suggesting the four classes were not generally clustered with regards to different symptom groupings, but were clustered mainly due to differences in frequency and severity of similarly occurring symptoms.
Table 2.
Four class model of student symptomatology
| Symptom | Class 1 Mean(Standard Error) | Class 2 Mean (Standard Error) | Class 3 Mean (Standard Error) | Class 4 Mean (Standard Error) |
|---|---|---|---|---|
| Unrefreshing Sleep | 24.15 (0.65) | 41.08(0.74) | 53.45(0.83) | 66.60(1.72) |
| Needing to Nap | 16.33 (0.63) | 29.39(0.68) | 40.87(1.05) | 55.00(2.49) |
| Trouble Falling Asleep | 15.45 (0.58) | 27.22(0.73) | 37.68(1.06) | 51.93(2.35) |
| Trouble Staying Asleep | 6.76 (0.41) | 15.38(0.66) | 25.28(1.06) | 40.74(2.19) |
| Waking up Early | 6.19 (0.37) | 11.96(0.51) | 19.08(0.90) | 34.87(2.40) |
| Dead Heavy Feeling after starting to exercise | 4.65(0.30) | 11.71(0.61) | 21.02(0.74) | 39.30(2.66) |
| Next-Day Soreness after everyday activities | 4.88(0.34) | 12.65(0.55) | 22.24(0.82) | 37.27(1.96) |
| Mentally tired after the slightest effort | 5.73(0.38) | 17.52(0.73) | 31.97(1.13) | 52.60(2.01) |
| Minimum exercise makes you physically tired | 5.30(0.34) | 15.45(0.63) | 25.51(0.79) | 39.45(2.51) |
| Physically drained after mild exercise | 2.48(0.22) | 9.09(0.34) | 20.13(0.81) | 37.50(2.26) |
| Problems remembering things | 6.01(0.37) | 16.65(0.80) | 33.54(1.18) | 49.49(2.30) |
| Difficulty paying attention for a long period of time | 12.09(0.57) | 28.56(0.91) | 46.70(1.15) | 62.21(2.51) |
| Difficulty finding the right word to say or expressing thoughts | 9.11(0.48) | 24.59(0.87) | 38.50(1.05) | 55.03(2.41) |
| Difficulty understanding things | 4.81(0.34) | 16.31(0.75) | 30.50(0.99) | 44.40(2.04) |
| Unable to focus vision | 7.42(0.45) | 19.29(0.75) | 33.74(0.91) | 48.88(2.84) |
| Slowness of thought | 2.34(0.23) | 10.87(0.60) | 24.46(1.09) | 43.88(2.22) |
| Absent-mindedness | 8.83(0.48) | 21.65(0.73) | 36.33(1.04) | 54.60(2.44) |
| Sore throat | 17.13(0.52) | 25.64(0.50) | 31.51(0.88) | 39.87(1.59) |
| Sore lymph nodes | 4.70(0.29) | 9.31(0.48) | 15.30(0.93) | 28.09(1.92) |
| Fever | 5.66(0.36) | 11.64(0.48) | 14.83(0.85) | 22.75(1.62) |
| Flu-like symptoms | 8.65(0.42) | 16.45(0.58) | 23.53(0.86) | 34.66(1.80) |
| Cold limbs | 6.09(0.41) | 12.99(0.58) | 22.30(1.15) | 40.26(2.52) |
| Feeling chills or shivers | 3.58(0.30) | 11.08(0.49) | 19.23(0.85) | 34.79(2.06) |
| Feeling hot or cold for no reason | 3.20(0.30) | 10.11(0.47) | 19.32(1.09) | 37.67(1.93) |
| Feeling like you have a low temperature | 0.99(0.14) | 2.52(0.23) | 6.38(0.66) | 16.29(1.78) |
| Muscle pain | 10.34(0.48) | 20.90(0.57) | 29.77(0.80) | 43.10(1.65) |
| Joint pain | 3.64(0.28) | 9.65(0.53) | 19.60(1.02) | 34.84(2.00) |
| Bloating | 8.24(0.44) | 18.12(0.62) | 25.86(0.90) | 38.67(2.11) |
| Stomach pain | 6.48(0.43) | 16.66(0.62) | 26.76(1.04) | 40.19(1.71) |
| Irritable bowel problems | 3.34(0.29) | 8.31(0.49) | 15.02(1.24) | 30.96(2.39) |
| Chest pain | 1.88(0.19) | 5.67(0.40) | 12.69(0.74) | 23.27(1.62) |
| Feeling unsteady on your feet | 1.38(0.16) | 4.61(0.35) | 12.17(0.79) | 29.04(2.22) |
| Shortness of breath | 2.18(0.20) | 7.35(0.52) | 16.42(0.71) | 35.76(2.74) |
| Dizziness or fainting | 2.00(0.21) | 5.88(0.38) | 13.28(0.90) | 31.70(1.94) |
| Irregular heart beats | 0.97(0.15) | 2.52(0.25) | 5.86(0.51) | 16.73(2.11) |
| Asleep all day/awake all night | 3.49(0.26) | 8.49(0.46) | 15.81(0.82) | 28.84(2.29) |
| Sensitivity to noise | 2.18(0.23) | 7.14(0.47) | 16.78(0.99) | 31.46(2.21) |
| Sensitivity to lights | 2.41(0.23) | 7.11(0.42) | 16.82(1.02) | 31.82(2.07) |
| Losing or gaining weight without trying | 4.81(0.32) | 11.10(0.58) | 18.44(0.97) | 36.52(2.47) |
| Alcohol intolerance | 2.17(0.23) | 4.32(0.32) | 7.80(0.65) | 18.09(1.99) |
| Feeling like you have a high temperature | 3.84(0.31) | 10.40(0.45) | 16.65(0.98) | 31.73(1.75) |
| Nausea | 4.26(0.34) | 12.23(0.54) | 19.95(1.07) | 35.56(1.74) |
| Night sweats | 5.29(0.34) | 11.64(0.50) | 20.27(1.03) | 37.72(2.12) |
| Sweating hands | 6.16(0.37) | 10.81(0.53) | 17.18(0.96) | 27.41(2.16) |
| Muscles twitches | 4.62(0.28) | 9.69(0.42) | 16.39(0.77) | 30.23(1.89) |
| Eye pain | 3.38(0.25) | 7.83(0.40) | 16.18(1.10) | 26.00(1.85) |
| Sensitivity to smells, foods, or chemicals | 2.97(0.24) | 8.28(0.47) | 17.03(0.97) | 30.63(1.86) |
| Headaches | 14.62(0.56) | 25.86(0.53) | 35.51(1.04) | 49.61(1.75) |
| Appetite loss | 4.82(0.29) | 10.64(0.57) | 19.03(0.86) | 35.47(1.79) |
| Bladder problems | 1.56(0.19) | 4.66(0.35) | 9.33(0.81) | 21.17(2.04) |
| Only able to focus on one thing at a time | 3.07(0.25) | 12.27(0.70) | 28.02(1.16) | 47.18(2.27) |
| Loss of depth perception | 0.57(0.10) | 1.61(0.18) | 6.82(0.67) | 22.24(2.29) |
| Fatigue | 16.07(0.58) | 30.46(0.63) | 41.24(0.81) | 57.26(1.58) |
| Muscle weakness | 1.64(0.18) | 5.81(0.43) | 15.70(0.75) | 33.52(2.44) |
Note. A boldfaced score indicates a symptom score over 25, an underlined score indicates symptom score over 50. Class 1 contained 0 symptoms with scores over 25. Class 2 contained 6 symptoms with scores over 25, class 3 contained 17 symptoms with scores over 25 and class 4 contained 48 symptoms with scores over 25.
There were no symptoms which students in class 1 reported having at a frequency or severity score 25 or greater, meaning class 1 can be considered healthy. Students in class 2 were likely to report 6 symptoms having a score between 25 and 50, including unrefreshing sleep, needing to nap, difficulty paying attention, sore throat, headaches, and fatigue. Students in class 3 were likely to report a score between 25 and 50 for the same symptoms as those reported by the students of class 2, with the exception of unrefreshing sleep, that was often reported at a score between 50 and 75, meaning that it was at least of “moderate” severity and present at least half of the time. Students in class 3 also reported 11 additional symptoms with a score between 25 and 50. Finally, students in class 4 reported 8 symptoms with a score between 50 and 75: unrefreshing sleep, needing to nap, trouble falling asleep, waking up early, mentally tired after the slightest effort, difficulty paying attention, difficulty finding the right word, absent mindedness, and fatigue, as well as an additional 40 symptoms with a score between 25 and 50.
A series of Chi-Square and Fisher’s exact tests were conducted to evaluate class membership by gender and race. The data were analyzed by collapsing the latent class memberships into two categories: the most severely symptomatic class (Class 4) compared against the milder symptom classes (Class 1, Class 2, and Class 3). There was a significant difference in class membership by gender (Fisher’s Exact = 29.51, p <.001). Of the 2540 women who responded to the survey, 6.2% were likely members of the most severe symptoms class (Class 4). This is 2.07 times the relative risk of the severe symptom class of men, of which 3.0% were likely members of the most severe symptom class. However, of the participants who reported their gender as “nonbinary or prefer not to answer” (n = 15), 20% were classified as members of the most severe symptoms class. Nonbinary or prefer not to answer participants had 3.23 times the relative risk of women to be members of the most severe symptoms class, and 6.67 times the relative risk of men to be members of the most severe symptoms class.
There were no differences in predicted severe symptoms class among participants who reported themselves as Asian/Pacific Islander, Black/African American, Latinx, or Multiracial. However, participants who reported themselves as Alaskan Native/Native American (n = 58) had 2.88 times the relative risk of being a member of the severe symptoms latent class (13.8%) than participants who did not report themselves as Alaskan Native/Native American (4.8%). Additionally, participants who reported themselves as White/Caucasian (n = 2745) had 0.7 times the relative risk of being a member of the severe symptoms latent class (4.2%) than participants who did not report themselves as White/Caucasian (6.0%).
Discussion
LCA of the health complaints of college students led to a different outcome than is usually seen. Often LCA solutions yield groups with different symptoms from one another; however, in our four-class solution, groups were not clustered via similar or dissimilar symptoms. Rather, the four-class solution identified one asymptomatic class and three symptomatic classes reporting similar core symptoms of fatigue and sleep, with differing degrees of severity as well as additional symptoms.
Class 1 is the healthiest, asymptomatic, subgroup constituting 35.65% of the student sample. The three symptomatic classes generally shared similar symptom groupings, centered on sleep dysregulation, fatigue, paying attention/neurocognitive symptoms, sore throat, and headaches. The largest of these classes was class 2, the mildly symptomatic group, at 38.87% of the student sample. This student group has some complaints of fatigue and unrefreshing sleep, along with sore throats, needing to nap, and difficulty paying attention. This is not surprising as it has been well-documented that many university students, in some cases as much as 87%, have some trouble with sleep, fatigue, and related issues.5,24
Class 3 (20.37%) reported the same sleep and fatigue difficulties as class 2, but to a greater degree. Additionally, students in class 3 also complained of abdominal pain, myalgia, headaches, and various neurocognitive symptoms. This too is not unexpected as previous literature has demonstrated that digestive disorders, along with other associated symptoms, affects between 6.3% and 37% of college students, possibly related to university-induced stress.25 The severity differences between class 2 and class 3 may be due to individual differences in sleep hygiene and stressed-based coping mechanisms.
The most symptomatic group, class 4, made up a small portion of the sample (5.11%), but reported the symptoms found in class 2 and class 3 (unrefreshing sleep, needing to nap, trouble falling asleep, difficulty paying attention, difficulty finding the right word, absent-mindedness, and fatigue) as moderate to severe. In total, class 4 reported some degree of difficulty with 48 of the 54 symptoms. Class 4 represents a small proportion of college students who reported major difficulties in many symptom areas.
Based on survey data alone, it is not clear why these particular students are highly symptomatic. One possibility is these students suffer from a chronic illness; recent reporting indicates the rate of college students living with a chronic illness is 6.1%9, similar to the proportion of students represented by class 4. Female students were twice as likely as male students to develop symptoms severe enough to place them in latent class 4. Nonbinary students/students who did not wish to disclose their gender were between 4 and 7 times as likely to develop symptoms severe enough to place them in class 4. Previous studies have found that 85% of nonbinary students and transgender students on college campus experience mental health challenges and extreme stressors in addition to the typical stressors of college life.15,26 These additional stressors may be responsible for nonbinary students’ physical symptoms, and explain why so many are in Class 4, although the numbers are quite small. Finally, 13.8% students who reported themselves as Alaskan Native/Native American were also categorized in class 4. Previous studies have shown that although Native American students comprise a small segment of the student body, they often report the poorest health outcomes.13,15 Taken together, these findings suggest that perhaps additional campus resources should be dedicated to nonbinary students and Indigenous/Peoples clinical and mental health, as well as social outreach.
This study has limitations. One limitation was that it relied solely on survey data, without requiring medical corroboration. How many of these students’ complaints could be successfully diagnosed and treated is unknown. Similarly, we do not know whether many of these complaints are related to mental health, sleep disorders, unhealthful behaviors, or medical conditions that cause fatigue (e.g., anemia or hypothyroidism). However, assessing student symptomatology through self-reported questionnaires does identify students who may have been unwilling or unable to report to health services or be diagnosed by a physician. Finally, while the overall sample size was large, students in the categories of nonbinary gender (n = 15) and Alaskan Native/Native American (n = 58) were relatively small, creating unequal variances among the groups; we therefore relied on Fisher’s exact tests to evaluate meaningful differences, indicating a need for further study to evaluate the exact degree of relative risk. Finally, students were not asked about pre-existing medical conditions, which may explain some severe symptoms among the student population.
Our results suggest the health complaints of college students are complex, varied, and disproportionate with regards to gender and ethnicity. At least 5% of sampled students reported complaints of moderate intensity occurring at least half of the time, with a greater proportion of nonbinary and indigenous students reporting severe symptoms. Many more experience a multitude of symptoms with milder degrees of severity. Future studies of university students should examine longitudinal health data integrated with a medical evaluation.
Acknowledgments
Funding was provided by the National Institute of Allergy and Infectious Diseases (grant number AI105781).
Footnotes
Declaration of Interest: No potential conflict of interest was reported by the authors
Contributor Information
Joseph Cotler, DePaul University.
Ben Z. Katz, Northwestern University Feinberg School of Medicine.
Chelsea Torres, DePaul University.
Leonard A. Jason, DePaul University.
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