Influence Of Romanian Youth Lifestyle On Depressice Disorder / Influenta Stilului de viata al tinerilor din Romania asupra tulburarii depresive - Paul Balanescu, Claudia Zaharia, Raisa Hutuleac, Andreea Ursu, Flavia Haradja

 

 

Paul Balanescu[1], Claudia Zaharia1, Raisa Hutuleac1, Andreea Ursu1, Flavia Haradja 1

 

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            Abstract

            Background: Depression is a severe disorder due to its growing incidence and individual and social impact having a complex therapy and variable accessibility. The determinism is plurifactorial, intrinsic and extrinsic factors being involved.  Lifestyle might play an important role in depressive disorder development.

            Aims: In our study we intended to evaluate the impact that some behaviors of the young urban Romanian population have upon the development of depressive disorder.  Our objective was to identify the behaviors that are at risk for depressive disorder development.

Methods:  We administered a questionnaire to 152 volunteers (75 women and 77 men) from urban areas, 20-40 years of age. We had calculated some scores for the physical activity, social skills, professional stress, family stress and health score.

Results:  The risk factors we found for development of mild depressive disorder in young urban population were feminine gender (OR=3.27, IC95% 1.54-6.99), the existence of financial issues (low income OR=4.39, IC95% 1.25-15.3) and sleep insufficiency (OR=3.09, IC95% 1.48-6.4). We also found that moderate coffee drinking (one cup each day) is a protection factor (OR= 0.59, IC 95% 0.28-0.72).

Conclusion: Lifestyle influences depressive disorder development in Romanian young urban population, identifying on one hand risk factors such as feminine gender, financial issues or insufficient sleep and on the other hand protective factors such as moderate coffee consumption.  We have also found positive correlations between the intensity of the depressive symptomatology and the intensity of stress, body mass index and health problems of the participant. Negative correlations were found between depressive symptomatology and physical activity and sociability. Further studies are needed to deepen the influence of these behaviors on depressive disorder development at this age category.

Keywords: depressive disorder, lifestyle, youth

Rezumat

Introducere: Depresia este o afectiune grava datorita incidentei în continua crestere, repercusiunilor individuale si sociale si datorita complexitatii si variabilitatii terapiei. Determinismul acesteia este plurifactorial, fiind incriminati atât factori intrinseci cât si extrinseci. Stilul de viata poate avea  importanta în aparitia simptomatologiei depresive.

Obiective: În studiul efectuat ne-am propus evaluarea influentei conditiilor de viata asupra aparitiei simptomatologiei depresive în cadrul populatiei tinere, urbane românesti cu intentia decelarii unor posibili factori de risc si protectori în aparitia depresiei.

             Metode: La studiu au participat 152 de participanti (75 de femei si 77 de barbati) cu vârste cuprinse între 20-40 de ani, provenind din mediul urban, carora le-a fost administrat un chestionar. Cu ajutorul acestuia s-au putut determina scorul severitatii depresiei, scorul activitatii fizice, scorul sociabilitatii, scorul stresului acumulat la locul de munca si la domiciliu si scorul imunitatii. 

Rezultate: O proportie statistic semnificativ mai mare a prezentei simptomatologiei depresive s-a întâlnit la participantii de sex feminin (OR=3.27, IC95% 1.54-6.99), la cei care aveau probleme financiare (OR=4.39, IC95% 1.25-15.3) si la cei care si-au considerat somnul insuficient (OR=3.09, IC95% 1.48-6.4). O proportie statistic semnificativ mai mica a prezentei simptomatologiei depresive a fost la  participantii care consumau zilnic o ceasca de cafea (OR= 0.59, IC 95% 0.28-0.72).

Concluzie: Stilul de viata influenteaza aparitia depresiei în cadrul populatiei tinere urbane românesti, identificandu-se atât factori de risc (sexul feminin, existenta problemelor financiare, somnul insuficient) cât si factori protectori (consumul moderat de cafe zilnic).  De asemenea am obtinut corelatii pozitive între intensitatea simptomatologiei depresive si  intensitatea stresului din viata cotidiana, indexul masei corporale si gravitatea problemelor de sanatate ale individului. S-au decelat corelatii inverse între simptomatologia depresiva si  efortul fizic depus de individ sau sociabilitatea acestuia. Studii ulterioare ar trebui sa aprofundeze influenta acestor comportamente asupra aparitiei depresiei la aceasta categorie de vârsta. 

Cuvinte cheie: depresie, stil de viata, tinerete

 

[1] 5th year students at University of Medicine and Pharmacy “Carol Davila” Bucharest, 37 Dionisie Lupu Street,  Bucharest, Romania

*Corresponding author Paul Balanescu, 46 Popa Soare Street, Bucharest, Romania, telephone/fax +402132734703.

E-mail: plbalanescu@gmail.com

 

 

 

BACKGROUND

           

Today depression is considered to be an important public health problem due to its social and individual consequences (subject’s incapability to accomplish daily responsibilities, work absenteeism, chronic fatigue syndrome and suicidal intentions). World Health Organization estimates that 121 million inhabitants are suffering from depression disorders all over the world but only about 25% of patients beneficiate from appropriate treatment due to socio-economical  reasons (marginalization, stigmatization, lack of material resources) (1).

            Diagnosing depression is difficult and frequently belated due to its various and subtle presentation forms.  This is why some countries (such as United States) implemented in their public health programs untimely diagnosis methods like questionnaire administration. Subsequently these questionnaires can direct the patients towards the psychologist or psychiatrist.  DSM-IV (Diagnostic and Statistical Manual of Mental Disorders) presents diagnosis criteria for depressive disorders. According to these, a person is considered having a depressive disorder if in the past 2 weeks  is frequently having suggestive symptoms excluding patients known with bipolar disorders, those with schizophrenic disorder or those who consumed drugs that could induce depressive symptoms (2).

            Actual research is focusing upon studying factors that could induce the development of depressive disorders and the relationship between these factors and other mental disorders. Lifestyle is one of the factors that could induce depressive disorder. Lifestyle is reflecting virtues and attitudes of each person through its dependence of multiple extrinsic factors. An example would be  the financial status of the person that is in the same manner dependent of the person’s workplace and of the financial status of the social group the person belongs. Lifestyle is expressed by a multitude of behaviors such as availability for physical activity, stress management, social activities,  social and familial obligations, diet, leisure, relaxation methods (3).

            In our study we intended to evaluate the impact that some behaviors of the young Romanian, urban population has upon the development of depressive disorder.  Our objective was to identify the behaviors that are at risk for depressive disorder development.    

 

MATERIALS AND METHODS

After obtaining their written consent, we administered the questionnaire to 152 volunteers of urban provenance (77 men and 75 women) having the age between 20-40 years.  The data confidentiality was assured.

The questionnaire was structured in 3 distinct parts.  In the first part the goals of the study were presented along with some instructions and the participant was asked to fill in some personal data such as age, sex and their relationship status.  The second part comprised the evaluation of the degree of depression by calculation of SDS (severity depression score) using an adaptation after Zung’s questionnaire (4). A SDS less than 49 was considered without depression, SDS between 50-59 mild depression, SDS between 60-69 moderate depression and SDS above 70 severe depression. The third part had the aim to assess the lifestyle of the participants using a questionnaire having 36 questions (4 had open-ended and 32 closed questions). With these questions we were able to develop 7 scores. The questions aimed the degree of physical activity, vicious habits (such as smoking, drinking alcohol, drinking coffee), social skills, financial status, stress, feeding habits (sweets and “fast-food”), sleeping disorders and  health.

The physical activity score was deduced from the points that the participants had obtained after completing 4 items concerning the weekly frequency of their physical activity, long walks, jogging and practicing a team sport. The sociability score was calculated from 3 questions concerning the satisfaction of their relationship with their friends, with their family, the weekly frequency of socializing with their friends.  The professional stress score and the school stress score were each calculated from 3 questions regarding the participant’s satisfaction with his job, the presence and frequency of tense situations with the colleagues or chief and the degree of responsibility. The residence stress score was determined using 4 questions concerning the responsibility the participant assumed at their home residence, the presence of tensions in the family, the satisfaction with his neighborhood and with the home atmosphere. The total stress score was deduced by adding the 3 scores (if the participant did not attend school or did not have a job the school stress respectively the work stress was quantified as 0). The health score was determined with 3 questions regarding auto evaluation of the participant’s resistance to infection, the yearly frequency of  seasonal  viral disease (seasonal flu)  and the enumeration of chronic conditions. The response set for each frequency item was never, sometimes or often.

The differences among groups were determined using Fischer exact test.  Spearman’s rank correlation test was used to assess the correlations between variables.  The risk statistics was assessed using odds ratio. Statistical analysis was performed using the statistical package for the Social Sciences (SPSS) statistical software for Windows, Version 14.0. Probability values (p)<0.05 were considered as significant. 

 

RESULTS AND DISCUSSION

 

            The SDS had a range between 23 and 59 (median was 44). The prevalence of depression symptoms was 28.28%. No participant had neither moderate nor severe depression (SDS above 60).  The socio demographic and descriptive data of the participants are presented in table 1 and table 2.

Category

N

 Gender

 

   Men

77

   Women

75

Age

 

    20-24

114

    25-29

  18

    30-34

8

    35-40

12

  Relationship status 

 

      Committed

108

       Single

44

Table 1. Socio demographic data

 

Score category and range

Range obtained

Median

SDS  (20-80)

   23-59

   44

Physical activity (0-8)

0-8

4

Sociability (0-7)

2-7

6

Professional stress (0-5)

0-4

1

Residence stress (0-5)

 0-4

1

School stress (0-5)

      0-5

     2

Total stress (0-15)

0-13

3

Health

0-2

1

Table 2. Descriptive data

           

Figure 1: Percent of female and male with depression (unadjusted OR= 3.27, p<0.001)

The proportion of the women (40%) having mild depression was statistically significant from the proportion of the men (16.9%) having mild depression (figure 1, p<0.001). The risk of developing depressive symptoms was greater in women (unadjusted OR=3.27, CI 95% 1.54-6.99). These results are consistent with another report where female adolescents in France had higher depression scores than male adolescents, female gender being more exposed (5). The reasons for the gender disparity in rates of depression are not completely understood. There is growing evidence that estrogens have powerful effects beyond their role in reproduction that they play a critical role in mood disorders in women. Fluctuations in estrogen occur naturally throughout the reproductive years and can be associated with disruptions in mood (6). These observations point out the fact that link between female hormones and depression deserves better research in the future.

            We did not find any statistically significant relation between the presence of mild depression and unhealthy behaviors like smoking or alcohol drinking, even after stratification of the data by sex and age, although there is increasing evidence that substance use disorders such as alcohol and illicit drug abuse are positively correlated with severe depression.  Nearly one-third of patients with major depressive disorder also have substance-use disorders (7). However in our study none of the subjects had major depressive disorder since the SDS was always under 60.

In our study moderate coffee consumption (1 cup each morning) appears to be a protection factor for the development of the depressive symptoms (unadjusted OR=0.58, CI95%-0.28-0.72).  Inconsistently, coffee consumption is leading to both rising up the mood and depression. The mood rising is due to the caffeine that in moderate amounts is acting as a competitive antagonist for the adenosine receptors in the brain, having stimulatory effect on the brain activity (8). Recent studies have demonstrated additional stimulatory effect of coffee due to a yet unknown chemical agent that stimulates the production of cortisone and adrenalin (9). On the other hand, excessive coffee consumption can be damaging.  A 10 year prospective study over a cohort of 86.626 nurses in United States has shown a greater suicidal rate in the women who drank four or more cups of coffee a day, compared to the ones who consumed no more than three cups a day (10).

A population based cohort study in a low income population in India, on women aged 18 – 50, identified baseline factors as low income and having difficulty making ends meet, as being independently associated with common mental disorders (11). The Canadian national population health survey investigated the risk of major depression by socioeconomic status: financial strain was associated with an increased risk of a major depressive event in participants who worked in the past 12 months and it was not associated with major depressive events in participants who did not work. Working men who reported low household income (12.9%) and participants who did not work and reported low personal income (5.4%) had a higher incidence of major depressive events than others (12). There is an increase in the number of publications in psychiatric research concerning determinants of common mental disorders in low and middle income countries. Their findings include a study among women with young infants (mean age 24.4 years) in rural Malawi which states that both minor and major depressive disorder was significantly associated with lower socioeconomic status and HIV infection (13). Another population group studied to establish the nature of the relationship between depressive symptoms and low income was an older adults group screened for late-life depression. They proved that the number of unmet needs was significantly positively associated with these older adults' depressive symptoms (14). Our study showed that there is a positive association between low income and the risk for depressive disorders (unadjusted OR=4.39, CI95% 1.25-15.34 in both men and women, aged 20-40 years, figure 2).

 

Figure 2: Relationship between low income and depressive disorder (unadjusted OR=4.39, p=0.01)

We found that sleeping insufficiency is a possible risk factor for the apparition of  mild depressive disorder  (unadjusted OR=3.09, CI95% 1.48-6.45, figure 3). This is concordant to some studies that showed that older adolescents living in urban areas and having depression associated subjective sleep and daytime distress (15). Another study focused upon the impact of sleep disturbance and major depression development concluding that poor sleep quality associates with severe depressive disorder (16). Children with severe depressive disorder have insomnia or hypersomnia (17).

Figure 3:  Relationship between sleeping disorder and depression (unadjusted OR=3.09, p=0.04)

              In our study the SDS used to quantify depressive symptoms is positively correlated to higher body mass index-BMI (r=0.25, p=0.05). This result is concordant with the majority of the anterior conducted studies.  There are multiple referrals in literature to the association between depressive disorder and higher body mass index/obesity but even if the results of different studies have varied, there are still no studies among urban Romanian population groups aged 20-40. This study was designed to document such associations and to examine the nature of the relationship between BMI and depressive disorder. The literature reviewed suggests that men and women (mean age 47 in one study) with depressive disorder have significant higher BMI than controls, with a greater proportion of the cases in the obese range, rather than overweight (18). The association between obesity and mental disorders becomes stronger with age (19) and according to the HUNT study blood pressure, total cholesterol and BMI are associated with increased mortality in patients with depressive disorders (20). A study among bariatric surgery candidates found that 66% of the participants had a lifetime history of mental disorders, particularly depressive disorder (21). The HUNT-2 study showed the existence of an association between obesity and depressive disorder, however it was strongly attenuated by abdominal fat distribution (waist hip ratio), while a high BMI was not independently associated with depression. These findings are consistent with a hypothesis that links obesity and depression via metabolic disturbances involving the hypothalamic–pituitary–adrenocortical axis. In contrast to the findings afore mentioned, a study conducted in the Czech population did not show any differences in the depressive disorder group, metabolic syndrome group and controls in age and BMI (22)

We found that the severity depression score correlated positively with professional stress score(r=0.36,  p<0.001, school stress score (r=0.41, p<0.001), residence stress score (r=0.35, p<0.001) and cumulated stress score (r=0.40, p<0.001), suggesting a strong association between stress and depressive disorders in young people.  One recent study shows that chronic stress may lead to chronically elevated levels of glucocorticoids, which in turn may reduce cell functioning, via the interaction between Bcl-2 in the mitochondria. The decrease in proper neuronal cell function may be the start point for certain physical and mental disorders such as depression (23). Another recent study revealed that stress plays a role in triggering or worsening depression and cardiovascular disease and in speeding the progression of HIV/AIDS and participants with a high pattern of stress had a greater risk to develop depression and other organic diseases (24). Molecular genetic studies demonstrated that there might be a molecular link between stress and depressive disorders (25). A specific polymorphism in the 5-HTT (5-hydroxytryptamine transporter)  gene could moderate the influence of stressful life events on depression. Individuals with one or two copies of the short allele of the 5-HTT promoter polymorphism exhibited more depressive symptoms and greater suicidal rates in relation to stressful life events than individuals homozygous for the long allele. So, the genetic background may explain the perception upon the different aspects related to material problems or insufficient sleep.

The SDS did positively correlate with the health score (r=0.41, p=0.01), that is the more the immune system is affected by infectious or inflammation conditions the more the depressive disorder is likely to develop.   New data indicate that activated inflammatory processes can influence multiple aspects of central nervous system function leading to behavioral changes in humans causing depression. Individuals who suffer from depression have been shown to display reductions in measures of cellular immune competence as well as elevated markers of systemic inflammation (26, 27). Furthermore, adolescents with major depressive disorder had significantly elevated plasma IFN-γ levels and IFN-γ/IL-4 ratio, findings that remained evident when medicated subjects were excluded. This study concluded that immune system deregulation may be associated with adolescent major depressive disorder (28).

We found that the physical activity score inversely correlated with the SDS         (r=-0.35, p=0.01).  Physical activity raises the cerebral endorphin concentration, which together with other neurotransmitters in the brain, causes an euphorically state of being (29).  It also determines a decrease in the cortisone level, a hormone that secreted excessively in stress situations can determine psychical changes, including depression (30). This beneficial effect of physical activity was confirmed by numerous studies.  Suit et al. after 10 years of follow-up concluded that higher physical activity is associated with lower risk of incident depressive symptoms independent from other clinical risk predictors (31).

The sociability score inversely correlated with the severity depression score        (r=-0.35, p=0.01).  Studies concerning the sociability and depressive disorders in humans are scarce. Animal models suggested that low sociability is associated with the decrease of serotonin in the frontal cortex, thus associated with depression (32). Further studies are required to assess the connection between sociability and depressive disorder. 

Table 3 summarizes the risk and protection factors we found for depression disorder development.

 

Exposure (risk factor)

% depression disorder in exposed group

% depression disorder in non-exposed group

Odds Ratio and 95% CI

 χ2 value

p-value

 

 

 

 

 

 

Gender (woman)

40%

16.9%

3.27

 (1.54, 6.99)

10.08

<0.001

Moderate coffee consumption

14%

34%

0.58

(0.28-0.72)

2.146

0.05

Low income

32.8%

10%

4.39

 (1.25-15.3)

6.16

0.01

Sleeping insufficiency

40.6%

18.1%

3.09

 (1.48-6.4)

9.40

0.04

Table 3: Associations between risk factors and depression disorder determined by the SDS 

POTENTIAL BIAS

There was selection bias since the study population was not randomly recruited thus not representative of the general population.  There were measurements biases since assessment of important variables were based on respondent’s answer to the questionnaire.  No outside, professional assessments were conducted.

 

CONCLUSIONS

          In our study we proved some risk and protection factors for the development of depression disorder in Romanian young urban population and the existence of some statistically significant correlations between lifestyle behaviors and the intensity of the depressive symptoms.  Young people avoiding sedentary life, socializing, drinking one cup of coffee a day, having a sleep discipline, developing appropriate strategies in order to avoid stress, being satisfied with their life and career are less exposed in developing a depressive disorder. However it is obvious the fact that we need prospective randomized studies to accurately assess the risk factors involved in this disorder and to extrapolate the results to the general population.  Nowadays, in order to interfere with prophylactic strategies it is very interesting, intriguing and important to discover correlations and a pathway through fashionable lifestyle is influencing our behavior.

 

REFERENCES

 

World Health Organization webpage: http://www.who.int/en/

Diagnostic and Statistical Manual of Mental Disorders DSM-IV-TR Fourth Edition. Washington D.C, United States:  American Psychiatry Association,  2005.

Mol J,  Sonnenfeld D. Ecological modernization around the world: Perspective and critical debates. London: Roultedge, 2001.

Zung WW.  A self-rating depression scale. Archives of General Psychiatry  1965; 12: 63-70.

Chabrol H, Montovany A, Chouicha K, Duconge E. Study of the CES-D on a sample of 1,953 adolescent students. Encephale  2002; 28(5 pt 1):429-32.

Lasiuk GC, Hegadoren M. The Effects of Estradiol on Central Serotonergic Systems and Its Relationship to Mood in Women. Biological research for nursing 2007; 9(2):147-160.

Davis L, Uezato A, Newell JM,  Frazer E. Major depression and comorbid substance use disorders. Curr Opin Psychiatry 2008; 21(1):14-18.

 Fisone, G; Borgkvist A, Usiello A. Caffeine as a psychomotor stimulant: mechanism of action.  Cell Mol Life Sci 2004;  61 (7–8): 857–72.

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