depression and female universities 1 · depression and female universities 3 introduction...

Depression and female universities

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Running head: Depression among female university students

The prevalence of depression among female university students and related factors

1Fernando L. Vázqueza, Ángela Torresb, María Lópeza, Vanessa Blancoa, and Patricia Oteroa

aFaculty of Psychology, bFaculty of Medicine, University of Santiago de Compostela, Spain

1Corresponding author. Universidad de Santiago de Compostela, Facultad de Psicología,

Departamento de Psicología Clínica y Psicobiología, Campus Universitario Sur, 15782 Santiago

de Compostela, Galicia, Spain. E-mail: [email protected]

Vázquez, F.L., Torres, A., López, M., Otero, P. y Blanco, V. (en prensa). The prevalence of

depression among female university students and related factors. En F. Columbus (Ed.), Major

depression in women. Hauppauge, NY: Nova Science Publishers, Inc.


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Abstract

In many countries, university students now constitute a significant proportion of their age

group. As in the general population, depression is relatively frequent in this group, and affects

women more than men. In the study described here we evaluated the prevalence of depression,

depressive symptoms and associated factors among 365 young women sampled randomly, with

stratification by year and discipline, from among the 18,180 female students attending a Spanish

university (65.9% of its total student roll). The prevalence of current major depressive episode

was 10.4% (95% CI 7.5-14.0%). Among students with current depression, the commonest

symptoms were depressed mood (86.5%) and alteration of sleep (78.9%). Some 52.6% of

depressed students had suffered one or more previous depressive episodes (M = 1.2; SD = 1.5),

and 13.2% had attempted suicide, but the existence of previous depressive episodes did not

increase the risk of a current episode. Increased risk was associated with recent problems, which

multiplied the odds of depression by 2.31 (95% CI 1.26-4.26), and with smoking in the past

month, which multiplied the odds of depression by 2.01 (95% CI 1.09-3.89), but not with the

use of alcohol, cannabis or cocaine in the past month. Nor was there any significant association

between depression and declared social class, monthly family income, university course level,

geographical background (urban or rural), persons lived with during term time (family, friends,

etc.), whether all the previous year's exams had been passed, sports activity, or academic

discipline.

Key words: depressive disorder, prevalence, epidemiology, students, cross-sectional study


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Introduction

Depression is one of the commonest psychiatric disorders in the general population, with

an estimated prevalence of around 16% (Kessler et al., 2003). It is currently responsible for some

5% of the all-cause burden of disease (Hyman, Chisholm, Kessler, Patel, & Whiteford, 2006),

which makes it the leading cause of non-fatal burden and the fourth leading cause overall

(Ustün, Ayuso-Mateos, Chatterji, Mathers & Murray, 2004); it is predicted that it will be the

overall leading cause of disability and death by the year 2030 (Mathers & Loncar, 2006). It not

only affects those who suffer it directly, but also causes great suffering to their families and

disrupts everyday activity and productivity; it often complicates the evolution of physical

disorders, and increases the risk of suicide (Wang & Kessler, 2006). Women are about twice as

likely as men to suffer depression (Marcus et al., 2005).

Among adolescents and young adults, the risk of depression is also greater for females

than males: about one in three young women have at some time in their lives suffered

depression, as against one in five young men (Kessler & Walters, 1998). University students,

who in many countries now constitute a considerable proportion of their age-group, share this

general trend: depression is a frequent disorder in this population, especially among women

(Adewuya, Ola, Aloba, Mapayi, & Oginni, 2006; Allgöwer, Wardle, & Steptoe, 2001; Apfel,

2004; Clark, Salazar-Grueso, Grabler, & Fawcett, 1984; Dahlin, Joneborg, & Runeson, 2005;

Eller, Aluoja, Vasar, & Veldi, 2006; Rimmer, Halikas, Schuckit, & McClure, 1978; Schuckit,

1982; Tomoda, Mori, Kimura, Takahashi, & Kitamura, 2000; Vázquez & Blanco, 2006). The

risk of emotional disorders increases under stress, and university students can be put under stress


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not only by accommodation, finance and social problems, but also by academic difficulties

(demands and deadlines, exams, grades and competition, uncertainty about career and future

success) and by their awareness that they must at this stage make some of the most important

decisions in their lives. Such pressures can trigger the onset of depressive episodes in susceptible

students and, in turn, depression can negatively affect academic performance by altering

memory function and other learning processes (Dyrbye, Thomas, & Shanafelt, 2006;

Hysenbegasi, Hass, & Rowland, 2005; Murphy & Archer, 1996). The university has been

described as a critical context for studying mental health in youth (Weitzman, 2004).

In spite of the evidence of the vulnerability of university students to depression, and the

plausibility of the above reasons, the phenomenology of depression in this population has been

insufficiently investigated, especially as regards any distinctive characteristics of depression

among female university students. In particular, only two studies have been published in which

the object of study has been clearly defined by the use of the DSM-IV criteria of depression: a

study of first-year students in Japan (Tomoda et al., 2000), and a study of Swedish medical

students (Dahlin et al., 2005). There is therefore a need for broader studies of well-defined

depression among university students, especially considering that depressive episodes can not

only disrupt a student’s life during this period that is critical for his or her future, but can also, as

in the case of adolescents (Lewinsohn, Clarke, Seeley, & Rohde, 1994), predispose towards

further episodes (Franko et al., 2005); hopefully, such studies would help orient the design of

preventive strategies.

In view of the apparently greater prevalence of depression among female students, and


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the possibility that depression among female students may have specific characteristics relevant

to the design of preventive strategies, the need for studies of female students is particularly

urgent. The objectives of the present study of a random sample of female university students

stratified by course year and discipline were to determine the prevalence of DSM-IV major

depressive episodes (MDEs) among female university students, to characterize the typical

symptom profile, and to identify associated factors.

Method

From among the 18,180 female students on the roll of the University of Santiago de

Compostela, Spain (65.9% of all students enrolled in this institution), a sample of 368 was

randomly selected, with stratification by course year and discipline. Each student in the sample

was personally contacted and invited to participate in the study; its nature, objectives, risks and

benefits were explained, confidentiality and anonymity were assured, and any questions they

might have about it were answered. Participation was totally voluntary, and no economic,

academic or other kind of incentive was offered. Three of the initial sample declined the

invitation to participate, leaving a final sample of 365 students who gave written consent prior to

participation. The study was reviewed and approved by the Ethics Committee of the University

of Santiago de Compostela.

Data on depressive symptoms, diagnoses of depression, personal relationships, academic

performance and sociodemographic background were obtained from each participant in a 20–

30—minute personal interview with one of three psychologists given specific training for this


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study. During this interview, Muñoz’s Mood Screener (Miller & Muñoz, 2005; Muñoz, 1998)

was administered to determine whether the participant was currently suffering, or had ever

suffered, an MDE; these screening results were subsequently used to estimate the prevalence of

MDE in the sample.

The Mood Screener essentially comprises eighteen items designed to evaluate the nine

positive DSM-IV symptoms of MDE (nine items for current MDE and nine for sometime

MDE), plus two more to assess satisfaction of the DSM-IV requirement that these symptoms

significantly interfere with the subject's life or activities. A positive result for sometime MDE

consists in the subject reporting having experienced, over some two-week period during his or

her life, at least five of the nine symptoms, including one of the first two (depressed mood and

anhedonia), together with satisfaction of the interference requirement. The criterion for current

MDE is the same, except that the items now refer to the 2 weeks preceding completion of the

Screener. The values of kappa for concordance of the Mood Screener with the Primary Care

Evaluation of Mental Disorders scale (PRIME-MD) and with the Structured Clinical Interview

for DSM-IV Axis I Disorders - Clinical Version (SCID-CV) have been reported as respectively

0.75 (Muñoz, McQuaid, González, Dimas, & Rosales, 1999) and 0.758 (Vázquez, Muñoz,

Blanco, & López, in press). The sensitivity and specificity of the Mood Screener for detection

of MDE in a non-clinical population are 0.969 and 0.967, respectively (Vázquez et al., in press).

The interviewers were trained for this study by a psychologist with 14 years’ experience

of clinical evaluation who had himself been trained in the use of the Mood Screener by its

author. Training consisted of two 90-minute “theoretical” sessions, followed by practice sessions


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in which the interviewers applied the instrument to subjects similar to those taking part in the

main study, but who did not themselves actually participate in the main study. The theoretical

sessions involved explanation of the instrument, role play, and practice in the diagnosis of

depressive disorders by consideration of 10 cases. Videotapes of the practical sessions were used

by the instructor to evaluate deviation from the interview protocol, and to correct the

interviewers accordingly until performance was satisfactory; in all, 18 subjects took part in these

practice sessions.

Statistical analyses were performed using SPSS software (version 14.0). Data are

presented as percentages for categorical variables, and as means, standard deviations and

medians for continuous variables. The relationship between current MDE and other variables

was evaluated using logistic regression (both with and without adjustment for age), for which

purpose two age groups were defined (< 20 years and ≥ 20 years) and “number of friends” was

split in three groups (0-2, 3-9 and > 9). Since weighting did not significantly influence the

estimated odds ratios (ORs), only the results of unweighted analyses are presented. Confidence

intervals (CIs) for the values of parameters in the population from which the sample was drawn

were estimated by calculation of exact binomial probabilities.

Results

Mean student age was 21.9 years (SD = 2.4 years) (see Table 1). Some 99.3% of the

sample were single, 40.3% were from families with a monthly income of 960-1,920 €, 74.5%

described themselves as middle-class, and 67.9% came from urban localities. 67.4% were


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studying social sciences, law or humanities, and 66.3% were in the third or subsequent years of

their undergraduate course. 47.0% lived with their parents during term time, 58.7% had failed

one or more of the subjects taken the previous year, and 57.8% did not take part in regular sports

activity. The mean number of friends declared was 8.2 (SD = 10.2). 61.4% of participants had

not recently had personal, social or other problems. In the 30 days preceding the interview, the

legal psychoactive substance most commonly consumed was alcohol (76.2%), and the illegal

substance most commonly consumed was cannabis (19.7%) (see Table 2).

The prevalence of current MDE was 10.4% (95% CI 7.5-14.0%). Among students with

current depression, the commonest symptoms were depressed mood (86.5%) and alteration of

sleep (78.9%) (see Table 3). Some 52.6% of depressed students had suffered one or more

previous depressive episodes (M = 1.2; SD = 1.5), and 13.2% had attempted suicide, but the

existence of previous depressive episodes did not increase the risk of a current episode.

Reported age at occurrence of the first episode was on average 17.3 years (SD = 3.4 years);

50.7% of students with current MDE had had their first episode at age 17 years or younger,

and the average number of years that had elapsed since the first episode was 4.6 (SD = 3.4).

Increased risk was associated with recent problems, which multiplied the odds of

depression by 2.31 (95% CI 1.26-4.26), and with smoking in the past month, which multiplied

the odds of depression by 2.01 (95% CI 1.09-3.89), but not with the use of alcohol, cannabis

or cocaine in the past month. Nor was there any significant association between depression

and declared social class, monthly family income, university course level, geographical

background (urban or rural), persons lived with during term time (family, friends, etc.),


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whether all the previous year's exams had been passed, sports activity, or academic discipline.

Conclusion

In this study a substantial proportion of female university students, more than 10%, were

currently suffering an MDE. This rate is somewhat higher than the 1-month prevalence among

US women (5.8%) (Ohayon, 2007), the average for European women (7.9%) (Ayuso-Mateos et

al., 2001), and the 12-month prevalence among young women in a representative nationwide

sample of adolescent and young adult Finns (8.1%) (Haarasilta, Marttunen, Kaprio, & Aro,

2001). It is much higher than the average among Spanish women in general (1.8%) (Ayuso-

Mateos et al., 2001). However, it is lower than depression prevalences reported in other studies

of university students: 11.9% among female Nigerian university students (Adewuya et al., 2006)

(although this figure included minor depressive disorder); 12.9% among Swedish female

medical students (Dahlin et al., 2005); and 28.4% among first-year female students in Japan

(Tomoda et al., 2000). It therefore seems unlikely to be an overestimated, especially since only

14.2% of the sample were in their first year (when students are probably most vulnerable) and all

interviews were carried out at a time of year when there were no exams to cause stress.

Furthermore, a positive Mood Screener result requires a positive answer to the question on

interference with life or activity; failure to evaluate this or other indications of clinical

significance has been pointed to as a significant cause of overestimation by other instruments

(Narrow, Rae, Robins, & Regier, 2002).

It is well known that women are more prone to depression than men, regardless of


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whether the criterion employed is the level of depressive symptoms or a diagnosis of unipolar

depressive disorder (Kessler et al., 2003; Mazure, Keita, & Blehar, 2002). The prevalence

observed in the present study is twice that observed among male students at the same university

(Vázquez & Blanco, in press). Similar differences between men and women have been observed

in other studies of depression among university students (Adewuya et al., 2006; Dahlin et al.,

2005; Tomoda et al., 2000).

The typical symptom profile observed in this study among participants who screened

positive for MDE was similar to that reported by Haarasilta et al. (2001) for young adult women

in that, in both studies, depressed mood and impaired concentration are among the three most

prevalent symptoms, and thoughts of death are among the least. Anhedonia, thoughts of death,

and weight loss or altered appetite were all more prevalent in Haarasilta et al.’s study, and

alteration of sleep in ours, but both studies suggest that physical symptoms of depression

(fatigue, alteration of sleep, alteration of appetite) are common in major depressive episodes.

A considerable proportion of the participants with current MDE in this study, 52.6%, had

suffered previous episodes. This finding is in keeping with those of longitudinal studies in which

the peak of first episodes has occurred soon after puberty (Lewinsohn et al., 1994; Newman et

al., 1996: Oldenhinkel, Wittchen, & Schuster, 1999). However, the average number of previous

episodes, 1.2, was fewer than the figure of about 10 observed in the U.S. National Comorbidity

Survey (Kessler, Zhao, Blazer, & Swartz, 1997); average age at the time of the first episode,

17.3 years, was younger than figures in the 20s observed in studies of the general female

population (Andrade et al., 2003; Marcus et al., 2005; Weissman et al., 1996); and the time


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elapsed since the first episode was shorter than the 15.5 years reported in one of these latter

studies (Marcus et al., 2005). All these differences are of course probably attributable to the

youth of our sample. Furthermore, this characteristic of our sample – or, more specifically, the

consequent low value of the number of episodes suffered by anyone with sometime MDE (1.3) -

also probably explains why we did not find that past MDE significantly increased the probability

of current MDE, since the risk of MDE is known to increase with the number of previous

episodes (Depression Guideline Panel, 1993).

It is striking that five of the 38 participants who screened positive for current MDE,

13.2%, had attempted suicide. This is a very large proportion in comparison with the 2.7%

reported by Dahlin et al. (2005) for Swedish medical students of both sexes, but is compatible

with reports of 6-13% among adolescents (Garland & Zigler, 1993; Ruangkanchanasetr,

Plitponkarnpim, Hetrakul, & Kongsakon, 2005) and less than the 19.7% observed by Marcus et

al. (2005) among adult outpatients with depression.

Personal problems in the previous 6 months significantly increased the risk of current

MDE in this study. This is in keeping with the results of studies that clearly show the relevance

of serious adverse personal experiences to the commencement of depression (see, for example,

Kendler, Neale, Kessler, Heath, & Eaves, 1993; and Mazure, Bruce, Maciejewski, & Jacobs,

2000). Maciejewski, Prigerson, & Mazure (2001) reported that women are three times more

likely than men to suffer depression in response to stressful events.

The observed relationship between smoking and depression in this study was not

unexpected. It is well known that nicotine is one of the substances related to depression, and


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similar associations have been observed in a number of other studies of university students and

other young people (Adewuya et al., 2006; Allgöwer et al., 2001; Haarasilta et al., 2001). The

relationship is two-way: smoking can increase the risk of depression, and vice versa (Choi,

Patten, Gillin, Kaplan, & Pierce, 1997; Rao, Daley, & Hammen, 2000).

It may be pointed out that because the target population of this study consisted of

university students, comparison of its results with those of similar studies carried out in other

societies may possibly be more meaningful than for studies of the general population: it has been

suggested that cross-cultural comparison of results on depression is more transparent when they

concern undergraduate students than when it is necessary to control for confounding factors such

as type of job, job-related stress, and marital stress (Iwata & Buka, 2002).

The findings of this study suggest that therapeutic resources and preventive measures

should target female university students as a population at relatively high risk of major

depression, a disorder with possible life-long consequences. Teachers, educational authorities

and students themselves should be made more aware of the threat of depression, and measures

should be taken to minimize this threat, including measures to promote awareness of

depression as a disorder and not a stigma.


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Acknowledgments

This study was supported by grant PGIDT05PXIA21101PR from the Directorate General for

Research and Development (Counsellery of Innovation, Industry and Trade) of the Xunta de

Galicia (Spain).


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Nervous and Mental Disease, 192, 269-277.


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Table 1. Sociodemographic and academic profile of the final sample (N = 365) ______________________________________________________________________ Characteristic n % ________________________________________________________________________ Age (years) M 21.9 SD 2.4 Declared social class Upper 52 14.2 Middle 272 74.5 Lower 34 9.3 NR/NS* 7 1.9 Monthly family income < 960 € 35 9.6 960-1920 € 147 40.3 > 1920 € 98 26.8 NR/NS* 85 23.3 Geographical background Rural 117 32.1 Urban 248 67.9 University course level Years 1-2 123 33.7 3rd and subsequent years 242 66.3 Kind of discipline Social sciences and humanities 216 67.4 Health sciences 63 17.3 Natural sciences and mathematics 56 15.3 Passed all previous year’s subjects Yes 145 39.7 No 214 58.7 NR/NS* 6 1.6 Persons lived with during term Parents 171 47.0 Friends 142 38.7 Others 52 14.3 Sports activity Yes 145 39.7 No 211 57.8 NR/NS* 9 2.5 Number of friends M 8.2 SD 10.2 Recent problems? Yes 136 37.3 No 224 61.4 NR/NS* 5 1.3 ________________________________________________________________________ Note. (*) No response or not sure.


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Table 2. Substance use in the past 30 days. ________________________________________________________________________ Substance n % ________________________________________________________________________ Tobacco Yes 202 55.3 No 162 44.4 NR/NS* 1 0.3 Alcohol Yes 278 76.2 No 86 23.6 NR/NS* 1 0.2 Cannabis Yes 72 19.7 No 291 79.7 NR/NS* 2 0.6 Cocaine Yes 6 1.6 No 359 98.4 __________________________________________________________________________ Note. (*) No response or not sure.


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Table 3. Frequencies of DSM-IV diagnostic symptoms among the 38 female students who screened positive for MDE. __________________________________________________________________________

n % ___________________________________________________________________

Depressed mood 33 86.5 Anhedonia 20 52.6 Weight loss or altered appetite 20 52.6 Alteration of sleep 30 78.9 Psychomotor agitation or retardation 20 52.6 Fatigue or loss of energy 22 57.9 Feelings of worthlessness or of excessive or inappropriate guilt 15 39.5 Impaired concentration 23 60.5 Thoughts of death 8 21.1 _________________________________________________________________________

depression and female universities 1 · depression and female universities 3 introduction...

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