Antonio Fernando Boing; Guilherme Rocha Melo; Alexandra Crispim Boing; Rodrigo Otávio Moretti-Pires; Karen Glazer Peres; Marco Aurélio Peres
Programa de Pós-graduação em Saúde Coletiva. Centro de Ciências da Saúde. Universidade Federal de Santa Catarina. Florianópolis, SC, Brasil
OBJECTIVE: To assess the association between depression and chronic diseases in adults.
METHODS: Population-based cross-sectional study with a sample of 1,720 adults aged 20 to 59 years conducted in the city of Florianópolis, southern Brazil, in 2009. Multistage sampling was used and census tracts were the primary sample unit. Subjects were interviewed at home, and reported being diagnosed with depression (outcome) and 11 other chronic diseases (exploratory variable) by a health provider. They were grouped into those with no chronic disease, one, and two or more diseases. Gender, age, marital status, income, physical activity, hospitalization and medical visits were confounders. Poisson regression analysis was used to estimate prevalence ratios and related 95% confidence intervals.
RESULTS: The prevalence os depression was 16.2% (95%CI 14.3;18.2). It was higher in women, older individuals, widowed or divorced, and poor ones. Those who reported no leisure-time physical activity and medical visits in the last two weeks, and who were hospitalized in the last year also showed higher prevalence of depression and chronic diseases. Even after adjustment for confounders the prevalence of depression was 1.44 (95%CI 1.09;1.92) times higher among those reporting one chronic disease and 2.25 times higher among those reporting two or more diseases than among those with no diseases.
CONCLUSIONS: The prevalence of depression is much higher among people with higher burden of chronic diseases. Health professionals, health services, and policy makers must target specific strategies to this group.
Descriptors: Depression, epidemiology. Chronic Disease, epidemiology. Comorbidity. Cross-Sectional Studies.
The high and increasing prevalence of depression in populations of all continents and the serious impacts that it produces make the disease be one of the most serious public health problems of the beginning of the 21st century. It is estimated that depression was the third main cause of years of life lost due to disability (disability-adjusted life year - DALY) in the whole world (4.3%) in 2004 and it ranked first among the causes of years lived with disability, affecting more women (13.4%) than men (8.3%).25
People with depression present higher health expenditures,20 work disability,20 lower adherence to prescribed medical treatments9 and higher risk of mortality after heart surgery.4 The economic impacts of depression on the society are also considered to be serious, reaching 118 billion Euros in Europe in 2004 (equivalent to 1% of the continent's economy).21
The prevalence of depression is unequally distributed in the population: it is more common among women,22 younger individuals,3 those who have poorer economic conditions10 and those who live without a partner.22 It is associated with the existence of chronic diseases: people with depression can present biological alterations that can increase the risks of developing them. In addition, people with chronic diseases can present limitations in their daily life that increase their odds of having depression.13
Despite the important relationship between depression and chronic diseases, there are no Brazilian population-based studies that aimed to test the association between these factors. A search in databases with the descriptors "depression", "chronic diseases" and "Brazil" found only studies with hospitalized patients or with specific diseases.
The present study aimed to analyze the association between depression and chronic diseases in adults.
Population-based cross-sectional study carried out with 2,016 adults aged 20 to 59 years in the city of Florianópolis (Southern Brazil), in 2009. This study was part of a research called EpiFloripa 2009, which aimed to analyze different health conditions and the exposure to risk factors of the urban adult population of the municipality. The reference population was composed of 249,530 people.
The formula to determine prevalence in the program EpiInfo 6.04 was used to calculate sample size. The parameters used were 95% confidence level and sample error of 3.5 percentage points. As diverse outcomes were investigated in the large research, an expected prevalence of the phenomenon of 50% was used to obtain the largest sample size. A design effect (deff) of 2 was considered. A total of 10% was added considering estimated losses and 15% to control for confounders, resulting in a sample of 1,979 people. The largest sample calculated in the broad inquiry that analyzed diverse health outcomes was considered (n = 2,016). It was possible to calculate a posteriori the sample's statistical power. The sample enabled to identify a minimum relative risk of 1.47, considering power of 80%, alpha error of 5%, non-exposed:exposed ratio of 2:3 (chronic disease distribution) and prevalence in the non-exposed of 9.9%.
Cluster sampling was used and the census tracts were the primary sample unit. The municipality's territorial network was formed by 420 urban census tracts, which were stratified in deciles in ascending order, according to the income of the head of the family (R$ 192.80 to R$ 13,209.50). Sixty of these tracts were systematically drawn (sampling fraction equal to seven, six tracts selected in each income decile).
The units of the second stage were the households. The number of inhabited and permanent private units in each drawn tract initially varied from 61 to 810. Such variation, caused by the temporal distance in relation to the last census conducted in Brazil, led to the division of the largest tracts and to the grouping of the smallest ones (respecting their contiguity and income deciles). This procedure led to the formation of 63 tracts, which resulted in a coefficient of variation in the number of households in the tracts of 32%. Thirty-two households were systematically drawn in each one of the 63 tracts, totaling 1,134 selected units. All the adults aged between 20 and 59 years at the moment of the interview and residing in these households were potential participants in the study. The individuals who did not have physical or psychological conditions to answer the questionnaire were excluded.
Losses were considered the households that were visited at least four times, including weekends and the evening period, without the interviewer being able to locate the person. Refusal was considered when the research subject decided not to participate in the study.
Data collection was performed between September/2009 and January/2010 by 35 interviewers appropriately trained to use personal digital assistants. The interviews were individually conducted at the homes of the drawn individuals. A pre-test (n = 30) and a pilot-study were carried out in two census tracts that were not included in the study.
Approximately 15% of the subjects (n = 248) were interviewed for the second time by telephone and answered the reduced questionnaire with ten questions. Concordance was high, with the lowest kappa value equaling 0.56 (use of dental prosthesis). Concordance was 97.6% for self-reported diabetes.
The dependent variable was self-reported depression at some moment of the subject's life. The question that was used had been employed in the health supplements of the Pesquisa Nacional por Amostra de Domicíliosª (PNAD - National Household Sample Survey) of 2003 and 2008: "Has some doctor or health professional ever told you that you have depression?" The independent variable of main interest was the number of chronic diseases. The structure of the questions about the existence of the chronic disease was the same one that was used for depression, substituting the disease in question. Data were obtained about the existence of problem in the spine or on the back, arthritis or rheumatism, cancer, diabetes, bronchitis or asthma, hypertension, heart disease, chronic renal failure, tuberculosis, tendinitis or tenosynovitis and cirrhosis. The variable was categorized as (1) inexistence of any chronic disease, (2) existence of only one chronic disease and (3) presence of two or more chronic diseases.
The following variables were utilized for control: sex, age, marital status, per capita family income in reais (in tertiles), alcohol abuse (score > 7 points in the Alcohol Use Disorder Identification Test [AUDIT]),2 leisure-time physical activity in the last three months, hospitalization in the last 12 months and medical consultation in the last two weeks.
Poisson's multiple regression analysis was carried out in the statistical program Stata 9, and the prevalence ratios (PR) and their respective 95%CI were obtained as association measures. The design effect and the individual weights were incorporated into the analysis in all the estimates. The crude analysis of the outcome (depression) was performed with each one of the independent variables. Those that presented p-value < 0.20 were included in the multiple model according to the stepwise forward method, when the association between depression and chronic diseases was adjusted by all the independent variables. Those with p < 0.20 or that adjusted the measures obtained from another investigated dimension remained in the analysis.
The project was approved by the Ethics Committee of Research with Human Beings of Universidade Federal de Santa Catarina (Process nº 351/08).
A total of 1,720 people were interviewed (85.3% of the estimated sample of 2,016). The participants were mostly women (55.6%), adults aged between 20 and 39 years (55.6%), married or with a partner (60.1%). Approximately 60.0% reported at least one chronic disease and the major part did not practice leisure-time physical activity (53.1%). The prevalence of depression was 16.2% (95%CI 14.3%;18.2%) in the general population. The highest point values were observed among women (22.2%), older individuals (22.7%), widowed or separated individuals (30.7%), poor individuals (18.1%), among those with two or more chronic diseases (29.1%), those who did not practice leisure-time physical activity (19.2%), those who consulted a doctor in the last two weeks (23.2%), and those who were hospitalized in the last year (32.7%) (Table 1). The most prevalent chronic disease was problem in the spine or on the back (31.0%), followed by tendinitis/tenosynovitis (18.0%), hypertension (14.3%) and bronchitis/asthma (13.8%).
Differences in the prevalences of depression were statistically significant between at least two categories in the analyzed variables, except in the variable income (p = 0.059) and alcohol abuse (p = 0.340) in the crude analysis (Figure). The most expressive ratio differences in the prevalence of depression were between those who reported two or more chronic diseases and those without diseases (PR = 3.09; 95%CI 2.42;3.95), between widowed/separated individuals and married/in a stable union (PR = 2.88; 95%CI 2.00;4.14), between people aged 50 to 59 years and people aged 20 to 29 years (PR = 2.52; 95%CI 1.81;3.50), and between women (PR = 2.53; 95%CI 1.99;3.22) and men.
People with one chronic disease presented a prevalence of depression that was 1.58 times higher compared to those without diseases in the unadjusted model (Table 2). In the subsequent models, with the adjustments of the demographic, socioeconomic, behavioral and health services use variables, the magnitude of the PR decreased, but the prevalence was 44% higher in the group exposed to at least one chronic disease (p = 0.025). The increase in the number of diseases also increased the prevalence of depression. In comparison with people without any chronic diseases, the adults with two or more diseases presented a prevalence of depression that was 209% higher in the unadjusted analysis. The prevalence ratio decreased in the model when all the control variables had been introduced, but people with two or more chronic diseases present a prevalence of depression that is 125% higher compared to that of the people who did not report any chronic diseases (p < 0.001).
Individuals with one or more chronic diseases presented higher prevalence of depression, even after adjustment by the demographic, socioeconomic and health services use variables. This result is consistent with the literature. Moussavi et al16 analyzed data concerning people older than 18 years in 60 countries from all continents and observed that the prevalence of depression in the whole sample was 3.2%, but it reached 9.3% among those who reported diabetes, 10.7% among those who had arthritis and 18.1% among asthmatic individuals. There is evidence that patients with chronic respiratory18 and cardiovascular5 diseases present higher prevalence of depression, but many studies have not adjusted the association by possible confounders.
Depression can be associated with hormonal and physiological changes in the organism that increase the odds of developing certain chronic diseases, i.e. depression would be a risk exposure for the development of other chronic diseases. The relationship between depressive episodes and a decrease in the heart rate variability has already been reported,7 and also the relationship to high levels of cortisol,6 not to mention that it has an impact on the autonomic nervous system, on metabolic factors and on the hypothalamic-pituitary axis.13 Depression can also modulate behaviors, as it can lead to insomnia and to shorter sleep duration, which would act as modulators of the occurrence of hypertension.11 For biological reasons, populations with less experience in depressive events can present lower odds of developing chronic diseases.
The relationship between depression and chronic diseases can be bidirectional. People who suffer from chronic diseases report worse self-rated health, as shown by Alves & Rodrigues1 through a population-based study conducted in São Paulo. Having four or more chronic diseases has been associated with odds that are ten times higher of negative self-perception of health among men. Quality of life is also directly associated with the presence of chronic diseases, being lower among those with more chronic diseases, in a clear dose-response effect.24 However, diseases like lumbar pain, knee osteoarthritis and cancer seem to present a larger impact on quality of life than diabetes and hypertension.24 People with chronic diseases can present limitations, like those concerning mobility, eating, physical activity and limitations in the performance of the daily activities of personal life, social life or at work. The problems and implications that are inherent in these restrictions can lead to mood disorders and depression.
Independently of the direction in which the association between depression and chronic diseases occurs, the combination of the two implies worse handling of the diseases and worse outcome. A meta-analysis carried out by De Groot et al8 showed that depression is associated with complications in patients with diabetes, like retinopathy, neuropathy, nephropathy, sexual dysfunction and macrovascular complications. Depression has also been associated with lower adherence to drug therapy, special diets and health expenses.15
The self-report of a previous diagnosis of the analyzed diseases may be a limitation of the study. The prevalences may be underestimated due to absence of recent symptoms in the cases in which the disease does not express clinical manifestation, when the health services are not used for the diagnosis or due to memory bias. On the other hand, the presence of symptoms in a period close to the interview may lead the person to refer the disease, even without the professional diagnosis. However, studies have indicated the validity of self-reported depression19 and other chronic diseases12 in different contexts, a practicable and reliable way of obtaining data about the prevalence of morbidities in epidemiological studies.
People who use more the health services are more likely to receive a diagnosis of some chronic disease. In the present study, this factor was controlled through adjusting the analysis by the prevalence of medical consultations in the last two weeks and hospitalization in the last 12 months. However, some residual confounding may have happened, as in any association. Nevertheless, the magnitude of the association of interest was quite expressive. As it is a cross-sectional study, it is also not possible to establish the chronology of the events, i.e., whether people with depression have higher odds of developing chronic diseases or whether people, because they have a greater amount of diseases, present higher prevalence of depression.
Despite the limitations, the study had a high response rate and similar distribution among the income deciles of the primary sample units. Furthermore, the age and sex composition observed in the sample was similar to the one estimated by the IBGE to the municipality in 2009.
In light of the epidemiological scenario that was verified - strong association between depression and chronic diseases and the evidence that people with depression present worse outcomes for these diseases - it is essential that professionals and health services structure specific policies and actions for this population. Interventions like telephonic counseling targeted at these patients,17 patients' proper follow-up by primary care professionals23 or drug administration when indicated14 seem to present positive results in the handling of chronic diseases.
We thank Dr. Nilza Nunes da Silva, Department of Epidemiology, School of Public Health of Universidade de São Paulo, São Paulo, Brazil, for her advice on sample procedures. We would like to thank the Brazilian Institute of Geography and Statistics (IBGE) and the Florianópolis Health Authority staff for their useful help with the practical aspects of the study.
1. Alves LC, Rodrigues RN. Determinantes da autopercepção de saúde entre idosos do Município de São Paulo, Brasil. Rev Panam Salud Publica. 2005;17(5-6):333-41. DOI:10.1590/S1020-49892005000500005
2. Babor TF, Higgins-Biddle JC, Saunders JB, Monteiro MG. AUDIT: The Alcohol Use Disorders Identification Test: guidelines for use in primary care. 2.ed. Geneva: WHO; 2001
3. Blazer DG, Kessler RC, McGonagle KA, Swartz MS. The prevalence and distribution of major depression in a national community sample: the National Comorbidity Survey. Am J Psychiatry. 1994;151(7):979-86.
4. Blumenthal JA, Lett HS, Babyack MA, White W, Smith PK, Mark DB, et al. Depression as a risk factor for mortality after coronary artery bypass surgery. Lancet. 2003;362(9384):604-9. DOI:10.1016/S0140-6736(03)14190-6
5. Bremmer MA, Hoogendijk WJ, Deeg DJ, Schoevers RA, Schalk BW, Beekman AT. Depression in older age is a risk factor for first ischemic cardiac events. Am J Geriatr Psychiatry. 2006;14(6):523-30. DOI:10.1097/01.JGP.0000216172.31735.d5
6. Brown ES, Varghese FP, McEwen BS. Association of depression with medical illness: does cortisol play a role? Biol Psychiatry. 2004;55(1):1-9. DOI:10.1016/S0006-3223(03)00473-6
7. Carney RM, Blumenthal JA, Freedland KE, Stein PK, Howells WB, Berkman LF, et al. Low heart rate variability and the effect of depression on post-myocardial infarction mortality. Arch Intern Med. 2005;165(13):1486-91. DOI:10.1001/archinte.165.13.1486
8. De Groot M, Anderson R, Freedland KE, Clouse RE, Lustman PJ. Association of depression and diabetes complications: a meta-analysis. Psychosom Med. 2001;63(4):619-30.
9. DiMatteo MR, Lepper HS, Croghan TW. Depression is a risk factor for noncompliance with medical treatment: meta-analysis of the effects of anxiety and depression on patient adherence. Arch Int Med. 2000;160(14):2101-7.
10. Everson SA, Maty SC, Lynch JW, Kaplan GA. Epidemiologic evidence for the relation between socioeconomic status and depression, obesity and diabetes. J Psychosom Res. 2002;53(4):891-5.
11. Gangwisch JE, Malaspina D, Posner K, Babiss LA, Heymsfield SB, Turner JB, et al. Insomnia and sleep duration as mediators of the relationship between depression and hypertension incidence. Am J Hypertens. 2010;23(1):62-9. DOI:10.1038/ajh.2009.202
12. Haapanen N, Miilunpalo S, Pasanen M, Oja P, Vuori I. Agreement between questionnaire data and medical records of chronic diseases in middle-aged and elderly Finnish men and women. Am J Epidemiol. 1997;145(8):762-9.
13. Katon WJ. Epidemiology and treatment of depression in patients with chronic medical illness. Dialogues Clin Neurosci. 2011;13(1):7-23.
14. Lespérance F, Frasure-Smith N, Koszycki D, Laliberté MA, van Zyl LT, Baker B, et al. Effects of citalopram and interpersonal psychotherapy on depression in patients with coronary artery disease: the Canadian Cardiac Randomized Evaluation of Antidepressant and Psychotherapy Efficacy (CREATE) trial. JAMA. 2007;297(4):367-79. DOI:10.1001/jama.297.4.367
15. Lustman PJ, Clouse RE. Depression in diabetic patients: the relationship between mood and glycemic control. J Diabetes Complications. 2005;19(2):113-22. DOI:10.1016/j.jdiacomp.2004.01.002
16. Moussavi S, Chatterji S, Verdes E, Tandon A, Patel V, Ustun B. Depression, chronic diseases, and decrements in health: results from the World Health Surveys. Lancet. 2007;370(9590):851-8. DOI:10.1016/S0140-6736(07)61415-9
17. Piette JD, Richardson C, Himle J, Duffy S, Torres T, Vogel M. A randomized trial of telephonic counseling plus walking for depressed diabetes patients. Med Care. 2011;49(7):641-8. DOI:10.1097/MLR.0b013e318215d0c9
18. Ryu YJ, Chun EM, Lee JH, Chang JH. Prevalence of depression and anxiety in outpatients with chronic airway lung disease. Korean J Intern Med. 2010;25(1):51-7. DOI:10.3904/kjim.2010.25.1.51
19. Sanchez-Villegas A, Schlatter J, Ortuno F, Lahortiga F, Pla J, Benito S, et al. Validity of a self-reported diagnosis of depression among participants in a cohort study using the Structured Clinical Interview for DSM-IV (SCID-I). BMC Psychiatry. 2008;8:43. DOI:10.1186/1471-244X-8-43
20. Simon GE. Social and economic burden of mood disorders. Biol Psychiatry. 2003;54(3):208-15. DOI:10.1016/S0006-3223(03)00420-7
21. Sobocki P, Jönsson B, Angst J, Rehnberg C. Cost of depression in Europe. J Ment Health Policy Econ. 2006;9(2):87-98.
22. Van de Velde S, Bracke P, Levecque K. Gender differences in depression in 23 European countries: cross sectional variation in the gender gap in depression. Soc Sci Med. 2010;71(2):305-13. DOI:10.1016/j.socscimed.2010.03.035
23. Vergouwen AC, Bakker A, Burger H, Verheij TJ, Koerselman F. A cluster randomized trial comparing two interventions to improve treatment of major depression in primary care. Psychol Med. 2005;35(1):25-33.
24. Wang HM, Beyer M, Gensichen J, Gerlach FM. Health-related quality of life among general practice patients with differing chronic diseases in Germany: cross sectional survey. BMC Public Health. 2008;8:246. DOI:10.1186/1471-2458-8-246
25. World Health Organization. Global burden of disease: 2004 update. Geneva: WHO; 2008. Correspondence: Received: 4/30/2011 The authors declare no conflicts of interest.
Antonio Fernando Boing
Universidade Federal de Santa Catarina Campus Universitário
Trindade Departamento de Saúde Pública
88040-970 Florianópolis, SC, Brasil
Research financed by Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq - Process nº 485327/2007-4).
a Instituto Brasileiro de Geografia e Estatística. Pesquisa Nacional por Amostra de Domicílios - Suplementos. Rio de Janeiro: 2011 [cited 2011 Feb 21]. Available from: http://www.ibge.gov.br/home/xml/suplemento_pnad.shtm
The authors declare no conflicts of interest.