ABSTRACT:

Objective:

To analyze the association of major depressive disorder with chronic non-communicable diseases and multimorbidity in Brazilian adults, stratified by gender, as well as examine the interaction between gender and chronic non-communicable diseases in association with major depressive disorder.

Methods:

Based on a sample of 65,803 adults from the 2019 National Health Survey, we estimated the prevalence of major depressive disorder (≥10 points in the Patient Health Questionnaire) according to the presence of chronic non-communicable diseases and multimorbidity (≥2 chronic diseases). Prevalence ratios and their respective confidence intervals were calculated by Poisson regression, and multiplicative interaction terms were used to assess the role of gender in the associations.

Results:

The prevalence of major depressive disorder among Brazilian adults (18–59 years) was 10.9%, with a statistically significant difference between men (6.0%) and women (15.4%) (p<0.001). Individuals with any chronic non-communicable disease and multimorbidity showed a higher prevalence of major depressive disorder, both in the general population and in each gender. However, the association of major depressive disorder with chronic non-communicable diseases tended to be stronger among men. Data also showed an interaction between the male gender and multimorbidity or specific diseases, such as arthritis or rheumatism, heart disease, and chronic kidney disease, in association with major depressive disorder.

Conclusion:

The results reveal a significant association between major depressive disorder and chronic non-communicable diseases in both genders and raise the hypothesis that the effects of multimorbidity and certain diseases may be greater on the mental health of men.

Keywords:
Depressive disorder; Chronic disease; Multimorbidity; Health surveys

INTRODUCTION

In the world population, the proportion of individuals with depression was estimated at 4.4%, representing an increase of 18.4% between 2005 and 2015. This percentage corresponds to more than 300 million individuals¹1. World Health Organization. Depression and other common mental disorders: global health estimates. Geneva: World Health Organization; 2017.. The risk of depression increases with factors such as poverty, unemployment, stressful events, physical illness, and unhealthy behaviors. For almost three decades (1990–2017), depressive disorders remained among the three main causes of non-fatal health loss, measured through years lived with disability (YLD)²2. GBD 2017 Disease and Injury Incidence and Prevalence Collaborators. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: a systematic analysis for the global burden of disease study 2017. Lancet 2018; 392: 10159. https://doi.org/10.1016/S0140-6736(18)32279-7
https://doi.org/10.1016/S0140-6736(18)32... .

Major depressive disorder (MDD) is characterized by broad symptomatology, including depressed mood, loss of interest or pleasure, decreased energy, feelings of guilt, impotence, low self-esteem, sleep or appetite changes, and difficulty concentrating. These symptoms can become chronic or recurrent, interfering with the capacity for self-care and the maintenance of social, work, or domestic activities³3. Marcus M, Yasamy MT, van Ommeren M, Chisholm D, Saxena S. Depression: a global public health concern. World Health Organization: Department of Mental Health and Substance Abuse; 2012.. According to some studies, symptoms may vary between genders. Women with depression usually report depressed mood, anxiety disorder, and appetite, weight, and sleep disorders, while alcohol and drug abuse is more common among depressed men⁴4. Marcus SM, Young EA, Kerber KB, Kornstein S, Farabaugh AH, Mitchell J, et al. Gender differences in depression: Findings from the STAR D study. J Affect Disord 2005; 87 (2-3). https://doi.org/10.1016/j.jad.2004.09.008.
https://doi.org/10.1016/j.jad.2004.09.00... ,⁵5. Marcus SM, Kerber KB, Rush AJ, Wisniewski SR, Nierenberg A, Balasubramani GK, et al. Gender differences in depression symptoms in treatment-seeking adults: STAR D confirmatory analyses. Compr Psychiatry 2008; 49 (3): 238-46. https://doi.org/10.1016/j.comppsych.2007.06.012
https://doi.org/10.1016/j.comppsych.2007... ,⁶6. Cavanagh A, Wilson CJ, Kavanagh DJ, Caputi P. Differences in the expression of symptoms in men versus women with depression: a systematic review and meta-analysis. Harv Rev Psychiatry 2017; 25 (1): 29-38. https://doi.org/10.1097/HRP.0000000000000128
https://doi.org/10.1097/HRP.000000000000... ,⁷7. Vetter JS, Spiller TR, Cathomas F, Robinaugh D, Brühl A, Boeker H, et al. Sex differences in depressive symptoms and their networks in a treatment-seeking population – a cross-sectional study. J Affect Disord 2021; 1 (278): 357-64. https://doi.org/10.1016/j.jad.2020.08.074
https://doi.org/10.1016/j.jad.2020.08.07... .

Additionally, women tend to mention more depressive symptoms and with higher frequency than men in different populations⁸8. Lim GY, Tam WW, Lu Y, Ho CS, Zhang MW, Ho RC. Prevalence of Depression in the Community from 30 Countries between 1994 and 2014. Sci Rep 2018; 8 (1). https://doi.org/10.1038/s41598-018-21243-x
https://doi.org/10.1038/s41598-018-21243... . The estimate of MDD in women is generally twice that observed among men, and these differences remain throughout life, despite the variation in magnitude, reaching their peak in adolescence and stability in adulthood. Nonetheless, this does not mean that depression in men should be considered less important. A possible negative consequence of emphasizing the prevalence of women with depression is stereotyping the disease, leading to overdiagnosis of women and underdiagnosis of men⁹9. Salk RH, Hyde JS, Abramson LY. Gender differences in depression in representative national samples: Meta-analyses of diagnoses and symptoms. Psychol Bull 2017; 143 (8): 783-822. https://doi.org/10.1037/bul0000102
https://doi.org/10.1037/bul0000102... .

Several factors may explain sex or gender disparities in the incidence and prevalence of MDD. Aspects such as social role overload, greater exposure to stressful life events, financial difficulties, in addition to genetic and biological differences, make women more vulnerable to depression¹⁰10. Piccinelli M, Wilkinson G. Gender differences in depression. Critical review. Br J Psychiatry 2000; 177 (6): 486-92. https://doi.org/10.1192/bjp.177.6.486
https://doi.org/10.1192/bjp.177.6.486... ,¹¹11. Labaka A, Goñi-Balentziaga O, Lebeña A, Pérez-Tejada J. Biological sex differences in depression: a systematic review. Biol Res Nurs 2018; 20 (4). https://doi.org/10.1177/1099800418776082
https://doi.org/10.1177/1099800418776082... ,¹²12. Stegenga BT, King M, Grobbee DE, Torres-González F, Švab I, Maaroos HI, et al. Differential impact of risk factors for women and men on the risk of major depressive disorder. Ann Epidemiol 2012; 22 (6): 388-96. https://doi.org/10.1016/j.annepidem.2012.04.011
https://doi.org/10.1016/j.annepidem.2012... , while factors such as informal work and living alone can increase the risk of depression in men¹²12. Stegenga BT, King M, Grobbee DE, Torres-González F, Švab I, Maaroos HI, et al. Differential impact of risk factors for women and men on the risk of major depressive disorder. Ann Epidemiol 2012; 22 (6): 388-96. https://doi.org/10.1016/j.annepidem.2012.04.011
https://doi.org/10.1016/j.annepidem.2012... . Social support, in turn, can be considered a protective factor against depression for both genders¹³13. Tibubos AN, Brähler E, Ernst M, Baumgarten C, Wiltink J, Burghardt J, et al. Course of depressive symptoms in men and women: differential effects of social, psychological, behavioral and somatic predictors. Sci Rep 2019; 9 (18929). https://doi.org/10.1038/s41598-019-55342-0
https://doi.org/10.1038/s41598-019-55342... .

Another important risk factor for depression is the presence of chronic non-communicable diseases (NCDs), but, despite the evidence of this association in the general population¹⁴14. Hasan SS, Mamun AA, Clavarino AM, Kairuz T. Incidence and risk of depression associated with diabetes in adults: evidence from longitudinal studies. Community Ment Health J 2015; 51 (2): 204-10. https://doi.org/10.1007/s10597-014-9744-5
https://doi.org/10.1007/s10597-014-9744-... –¹⁶16. Wium-Andersen MK, Wium-Andersen IK, Prescott EIB, Overvad K, Jørgensen MB, Osler M. An attempt to explain the bidirectional association between ischaemic heart disease, stroke and depression: a cohort and meta-analytic approach. Br J Psychiatry 2020; 217 (2): 434-41. https://doi.org/10.1192/bjp.2019.130
https://doi.org/10.1192/bjp.2019.130... , the effect of gender on this relationship remains unclear. The literature review identified two studies that analyzed the interaction between gender and psychological factors in the development of heart diseases¹⁷17. Smaardijk VR, Lodder P, Kop WJ, van Gennep B, Maas AHEM, Mommersteeg PMC. Sex- and gender-stratified risks of psychological factors for incident ischemic heart disease: systematic review and meta-analysis. J Am Heart Assoc 2019; 8 (9): e010859. https://doi.org/10.1161/JAHA.118.010859
https://doi.org/10.1161/JAHA.118.010859... ,¹⁸18. Smaardijk VR, Maas AHEM, Lodder P, Kop WJ, Mommersteeg PMC. Sex and gender-stratified risks of psychological factors for adverse clinical outcomes in patients with ischemic heart disease: a systematic review and meta-analysis. Int J Cardiol 2020; 302:21-9. https://doi.org/10.1016/j.ijcard.2019.12.014
https://doi.org/10.1016/j.ijcard.2019.12... . However, no work was found in the opposite direction, with analyses of possible differential effects of the interaction between gender and NCDs on the incidence or prevalence of depression.

Considering this gap in the literature, the present study aimed to investigate the association of MDD with NCDs and multimorbidity in Brazilian adults, stratified by gender. Specifically, we examined the interaction between gender and determined NCDs or multimorbidity in association with MDD.

METHOD

This population-based cross-sectional study used the database from the Brazilian National Health Survey (Pesquisa Nacional de Saúde — PNS), conducted by the Brazilian Institute of Geography and Statistics (Instituto Brasileiro de Geografia e Estatística — IBGE) together with the Ministry of Health. PNS data were collected in 2019, in a probabilistic sample of the Brazilian population, selected through a three-stage cluster sampling process, with stratification of primary sampling units (PSU). The first stage selected census tracts or sets of tracts that constituted the PSU; the second consisted of choosing the households; the third selected a resident aged 15 years or older to answer the specific questionnaire. In each stage, the draw was made by simple random sampling. As part of IBGE’s Integrated Household Research System (Sistema Integrado de Pesquisas Domiciliares — SIPD), PNS used the master sample to select primary units. PNS administered three questionnaires: one concerning household characteristics, another related to the household residents, and the third with information about the selected resident¹⁹19. Stopa SR, Szwarcwald CL, Oliveira MM, Gouveia LCDP, Vieira MLFP, Freitas MPS, et al. Pesquisa Nacional de Saúde 2019: histórico, métodos e perspectivas. Epidemiol Serv Saúde 2020; 29 (5): e2020315. https://doi.org/10.1590/s1679-49742020000500004
https://doi.org/10.1590/s1679-4974202000... .

The households visited amounted to 94,114. A total of 90,846 selected residents were interviewed on their health status, lifestyle, and chronic diseases. This study only analyzed data from selected residents aged 18 to 59 years, comprising a sample of 65,803 individuals. Another publication¹⁹19. Stopa SR, Szwarcwald CL, Oliveira MM, Gouveia LCDP, Vieira MLFP, Freitas MPS, et al. Pesquisa Nacional de Saúde 2019: histórico, métodos e perspectivas. Epidemiol Serv Saúde 2020; 29 (5): e2020315. https://doi.org/10.1590/s1679-49742020000500004
https://doi.org/10.1590/s1679-4974202000... provides further details on the sampling process, the weighting, and other methodological aspects.

MDD was identified through the Patient Health Questionnaire-9 (PHQ-9), an instrument validated in Brazil²⁰20. Santos IS, Tavares BF, Munhoz TN, Almeida LSP, Silva NTB, Tams BD et al. Sensibilidade e especificidade do Patient Health Questionnaire-9 (PHQ-9) entre adultos da população geral. Cad Saude Publica 2013; 29 (8): 1533-43. https://doi.org/10.1590/0102-311x00144612
https://doi.org/10.1590/0102-311x0014461... , composed of nine questions that assess the frequency of depressive symptoms in the previous two weeks. Symptoms consist of sleep problems, fatigue or lack of energy, loss of interest or pleasure in doing things, concentration problems, food issues (poor appetite or overeating), slowness or restlessness to move or speak, depressive mood (feeling down or hopeless), feelings of failure or of having disappointed the family, and suicidal thoughts. The frequency of symptoms in the reference period was evaluated for each question, ranging from zero (not at all) to three (nearly every day) points. The maximum score is 27 points, and individuals with ten points or more were considered the most likely to have MDD. This is the score that maximizes the sensitivity and specificity of the test²¹21. Levis B, Benedetti A, Thombs BD. Accuracy of Patient Health Questionnaire-9 (PHQ-9) for screening to detect major depression: individual participant data meta-analysis. BMJ 2019; 9 (365): 1476. http://doi.org/10.1136/bmj.l1476
http://doi.org/10.1136/bmj.l1476... .

The main independent variable of interest was the presence of NCDs. Adults were asked whether a doctor had ever diagnosed them with the following diseases: hypertension, diabetes, heart disease, cerebrovascular accident (CVA), asthma or asthmatic bronchitis, arthritis or rheumatism, chronic back pain, work-related musculoskeletal disorder (WMSD), chronic lung disease, cancer, or chronic kidney disease. Each question had two possible answers (yes or no). The interviewees were also asked to what extent these diseases or their complications limited their routine activities (such as working, doing household chores, etc.), with the following response options: no limitation, slightly, moderately, severely, and very severely. Additionally, the number of chronic diseases reported by the interviewees was calculated and categorized as: zero, one, two, three, and four or more. Multimorbidity was defined as the presence of two or more NCDs²²22. Willadsen TG, Bebe A, Køster-Rasmussen R, Jarbøl DE, Guassora AD, Waldorff FB, et al. The role of diseases, risk factors and symptoms in the definition of multimorbidity – a systematic review. Scand J Prim Health Care 2016; 34 (2): 112-21. http://doi.org/10.3109/02813432.2016.1153242
http://doi.org/10.3109/02813432.2016.115... . Gender and age were used as control variables. Also, in order to evaluate the interactions, variables were built by the multiplication of each chronic disease (reference category: without NCDs) or multimorbidity and gender (reference categories: without multimorbidity and female gender, respectively).

Prevalence, prevalence ratios (PR), and 95% confidence intervals (95%CI) of MDD were estimated according to the presence or absence of each NCD and to the number of diseases and multimorbidity for the total population and by gender. The association between MDD and chronic diseases was also calculated based on the degree of limitation of NCDs. PR was obtained through multiple Poisson regression with adjustments for gender and age. Multiplicative interaction terms were used to evaluate the role of gender in the association between MDD and specific chronic diseases, as well as concerning the number of NCDs and multimorbidity. The analyses were adjusted for age, and the results were considered statistically significant when their p-values were less than 0.05. We conducted the analyses in the Stata 14.0 statistical software, taking into account the effect of the sampling plan, non-response rates, and post-stratification weights.

The National Research Ethics Committee (Comissão Nacional de Ética em Pesquisa — CONEP)/National Health Council (Conselho Nacional de Saúde — CNS) approved PNS, under the opinion no. 3,529,376, issued on August 23, 2019.

RESULTS

Data from 65,803 individuals were analyzed; their mean age was 38.1 years (95%CI 37.9–38.2), with a predominance of females (52.2%). Approximately 40% (95%CI 39.5–41.0) of adults (18–59 years) reported at least one NCD, and 14.1% (95%CI 13.6–14.6) had multimorbidity. The most prevalent diseases were chronic back pain (19%; 95%CI 18.4–19.6), hypertension (17%; 95%CI 16.4–17.5), and asthma or asthmatic bronchitis (5.5%; 95%CI 5.1–5.8). The remaining diseases were reported by less than 5% of the adult population.

Based on the PHQ-9 instrument, the prevalence of MDD among Brazilian adults was 10.9% (95%CI 10.4–11.3), with a statistically significant difference between genders: 15.4% (95%CI 14.6–16.1) in women and 6.0% (95%CI 5.5–6.5) in men. Among the adults identified with MDD by the PHQ-9, 37.0% (95%CI 34.9–39.1) reported having received a clinical diagnosis of this disease at some point in their lives.

The prevalence of MDD was higher among individuals who reported any studied NCD compared to those who had no such diseases. The most significant differences in the prevalence of MDD were detected among adults who declared being diagnosed with chronic lung disease (PR=2.82; 95%CI 2.30–3.47), CVA (PR=2.78; 95%CI 2.25–3.44), chronic back pain (PR=2.40; 95%CI 2.22–2.59), and heart disease (PR=2.33; 95%CI 2.03–2.66) in relation to those who did not present these morbidities. In addition, we identified that the prevalence of MDD increased with the number of chronic diseases, resulting in a PR=6.84 (95%CI 5.92–7.91) among interviewees with four or more chronic diseases compared to those without morbidities. The findings of this study also revealed a strong association between multimorbidity and MDD (Table 1).

Table 2 shows the prevalence ratios of MDD according to the degree of limitation of the diseases. The data demonstrated that groups reporting a greater degree of limitation in the performance of the routine activities due to chronic diseases also presented higher prevalence rates of MDD compared to those without disease.

Tables3 and 4 describe the data stratified by prevalent gender and PR of MDD according to the presence and number of chronic diseases. We found that the prevalence of MDD was higher among women who reported chronic diseases than among men in the same condition (compared to their respective groups without the disease). However, for almost all diseases, age-adjusted PR values were higher among men, except for chronic lung disease. A statistically significant interaction was identified between males and the following chronic diseases: heart disease (PR=1.53; 95%CI 1.08–2.15); arthritis or rheumatism (PR=1.69; 95%CI 1.23–2.33), and chronic kidney disease (PR=1.79; 1.10–2.89). Both genders showed a positive gradient between the prevalence of MDD and the number of chronic diseases, as well as a strong association between multimorbidity and MDD. Likewise, PRs were higher among men. We also detected a statistically significant interaction between males and multimorbidity, with PR=1.42 (95%CI 1.17–1.73). Interaction data were not shown in the tables.

DISCUSSION

This study revealed that adults (18–59 years) with a self-reported diagnosis of any NCD had a higher prevalence of MDD than individuals without these diseases. The prevalence of MDD also increased with the number of NCDs and the degree of limitation caused by the diseases in the performance of routine activities, both in the general population and in each gender. For almost all diseases evaluated, the prevalence of MDD was significantly higher in women; nevertheless, the relationship between depression and NCDs, expressed by adjusted PRs, tended to be stronger in men. Men also showed an increase of 42% in the association between MDD and multimorbidity, as well as a higher association between MDD and specific morbidities, such as heart disease, arthritis or rheumatism, and chronic kidney disease (53, 69, and 79%, respectively). Such interactions reflect a differential effect on MDD from the relationship between the male gender and NCDs.

Despite the methodological differences of the studies regarding instruments and criteria for identifying the presence of depression, the age group assessed, the follow-up duration, the disease severity, and controlled covariates, among other aspects, there is strong evidence of the association between depression and NCDs, with temporal bidirectionality. Namely, the previous history of chronic diseases has been associated with a higher probability of depression¹⁴14. Hasan SS, Mamun AA, Clavarino AM, Kairuz T. Incidence and risk of depression associated with diabetes in adults: evidence from longitudinal studies. Community Ment Health J 2015; 51 (2): 204-10. https://doi.org/10.1007/s10597-014-9744-5
https://doi.org/10.1007/s10597-014-9744-... –¹⁶16. Wium-Andersen MK, Wium-Andersen IK, Prescott EIB, Overvad K, Jørgensen MB, Osler M. An attempt to explain the bidirectional association between ischaemic heart disease, stroke and depression: a cohort and meta-analytic approach. Br J Psychiatry 2020; 217 (2): 434-41. https://doi.org/10.1192/bjp.2019.130
https://doi.org/10.1192/bjp.2019.130... , in the same way that depression has been associated with the incidence of several NCDs²³23. Clarke DM, Currie KC. Depression, anxiety and their relationship with chronic diseases: a review of the epidemiology, risk and treatment evidence. Med J Aust 2009; 6;190 (S7): S54-60. https://doi.org/10.5694/j.1326-5377.2009.tb02471.x
https://doi.org/10.5694/j.1326-5377.2009... –²⁹29. Wu Q, Kling JM. Depression and the risk of myocardial infarction and coronary death: a meta-analysis of prospective cohort studies. Medicine (Baltimore) 2016; 95 (6): e2815. https://doi.org/10.1097/MD.0000000000002815
https://doi.org/10.1097/MD.0000000000002... .

In the temporal direction in which depression was posterior to the presence of diseases, studies such as those by Hasan et al.¹⁴14. Hasan SS, Mamun AA, Clavarino AM, Kairuz T. Incidence and risk of depression associated with diabetes in adults: evidence from longitudinal studies. Community Ment Health J 2015; 51 (2): 204-10. https://doi.org/10.1007/s10597-014-9744-5
https://doi.org/10.1007/s10597-014-9744-... and Chireh et al.³⁰30. Chireh B, Li M, D’Arcy C. Diabetes increases the risk of depression: A systematic review, meta-analysis and estimates of population attributable fractions based on prospective studies. Prev Med Rep 2019; 14: 100822. https://doi.org/10.1016/j.pmedr.2019.100822
https://doi.org/10.1016/j.pmedr.2019.100... revealed a significantly higher risk of individuals with diabetes developing depression (relative risk — RR=1.27; odds ratio — OR 1.33; respectively). In a study based on ten cohorts, ischemic heart disease (IHD) was associated with a higher risk of developing depression, with a hazard ratio (HR) of 1.79 (95%CI 1.43–2.23). The study also estimated the mean time between being diagnosed with IHD and subsequently developing depression in 4.7 years¹⁶16. Wium-Andersen MK, Wium-Andersen IK, Prescott EIB, Overvad K, Jørgensen MB, Osler M. An attempt to explain the bidirectional association between ischaemic heart disease, stroke and depression: a cohort and meta-analytic approach. Br J Psychiatry 2020; 217 (2): 434-41. https://doi.org/10.1192/bjp.2019.130
https://doi.org/10.1192/bjp.2019.130... . In a meta-analysis carried out by Xue et al.¹⁵15. Xue Q, Pan A, Gong J, Wen Y, Peng X, Pan J, et al. Association between arthritis and depression risk: a prospective study and meta-analysis. J Affect Disord 2020; 273: 493-9. https://doi.org/10.1016/j.jad.2020.04.038
https://doi.org/10.1016/j.jad.2020.04.03... , patients with arthritis were 1.42 times more likely to develop incident depression (95%CI 1.34–1.52) than those without the disease.

On the other hand, studies assessing depression as a risk factor for the incidence of NCDs also provide consistent findings. A meta-analysis based on 11 prospective studies revealed a relative risk of developing hypertension of 1.42 (95%CI 1.09–1.86) among people with depression compared to those without depression²⁴24. Meng L, Chen D, Yang Y, Zheng Y, Hui R. Depression increases the risk of hypertension incidence: a meta-analysis of prospective cohort studies. J Hypertens 2012; 30 (5): 842-51. https://doi.org/10.1097/HJH.0b013e32835080b7
https://doi.org/10.1097/HJH.0b013e328350... . Other investigations also point to depression as a marker of prospective risk for heart disease²⁵25. Charlson FJ, Moran AE, Freedman G, Norman RE, Stapelberg NJ, Baxter AJ, et al. The contribution of major depression to the global burden of ischemic heart disease: a comparative risk assessment. BMC Med 2013; 11 (250). https://doi.org/10.1186/1741-7015-11-250
https://doi.org/10.1186/1741-7015-11-250... ,²⁷27. Gan Y, Gong Y, Tong X, Sun H, Cong Y, Dong X, et al. Depression and the risk of coronary heart disease: a meta-analysis of prospective cohort studies. BMC Psychiatry 2014; 14 (371). https://doi.org/10.1186/s12888-014-0371-z
https://doi.org/10.1186/s12888-014-0371-... ,²⁹29. Wu Q, Kling JM. Depression and the risk of myocardial infarction and coronary death: a meta-analysis of prospective cohort studies. Medicine (Baltimore) 2016; 95 (6): e2815. https://doi.org/10.1097/MD.0000000000002815
https://doi.org/10.1097/MD.0000000000002... . The meta-analysis conducted by Dong et al.³¹31. Dong JY, Zhang YH, Tong J, Qin LQ. Depression and risk of stroke: a meta-analysis of prospective studies. Stroke 2012; 43 (1): 32-7. https://doi.org/10.1161/STROKEAHA.111.630871
https://doi.org/10.1161/STROKEAHA.111.63... showed that people with depression had an increase of 34% (95%CI 17–54) in the risk of developing CVA compared to those without depression, while in the study by Wium-Andersen et al.¹⁶16. Wium-Andersen MK, Wium-Andersen IK, Prescott EIB, Overvad K, Jørgensen MB, Osler M. An attempt to explain the bidirectional association between ischaemic heart disease, stroke and depression: a cohort and meta-analytic approach. Br J Psychiatry 2020; 217 (2): 434-41. https://doi.org/10.1192/bjp.2019.130
https://doi.org/10.1192/bjp.2019.130... , the diagnosis of depression was associated with a higher risk of IHD (HR=1.63; 95%CI 1.36–1.95). Depressed individuals also presented an increased risk of having asthma at the beginning of adulthood (RR=1.43; 95%CI 1.28–1.61)³²32. Gao YH, Zhao HS, Zhang FR, Gao Y, Shen P, Chen RC, et al. The relationship between depression and asthma: a meta-analysis of prospective studies. PLoS One 2015; 10 (7): e0132424. https://doi.org/10.1371/journal.pone.0132424
https://doi.org/10.1371/journal.pone.013... and of developing type 2 diabetes, ranging from 32% in the study by Yu et al.²⁸28. Yu M, Zhang X, Lu F, Fang L. Depression and risk for diabetes: a meta-analysis. Can J Diabetes 2015; 39 (4): 266-72. https://doi.org/10.1016/j.jcjd.2014.11.006
https://doi.org/10.1016/j.jcjd.2014.11.0... to 38% in the research by Rotella and Mannucci²⁶26. Rotella F, Mannucci E. Depression as a risk factor for diabetes: a meta-analysis of longitudinal studies. J Clin Psychiatry 2013; 74 (1): 31-7. https://doi.org/10.4088/JCP.12r07922
https://doi.org/10.4088/JCP.12r07922... . Less significantly, another meta-analysis suggested a relationship between depression and the general risk of having cancer (RR=1.15; 95%CI 1.09–1.22), with variation in risk according to the type of cancer³³33. Jia Y, Li F, Liu YF, Zhao JP, Leng MM, Chen L. Depression and cancer risk: a systematic review and meta-analysis. Public Health 2017; 149: 138-48. https://doi.org/10.1016/j.puhe.2017.04.026
https://doi.org/10.1016/j.puhe.2017.04.0... .

Results of the present study as to the association between MDD and the number of NCDs or multimorbidity are also consistent with the evidence found in the literature. A meta-analysis demonstrated an expressive relationship between multimorbidity and depression — individuals with this condition had almost three times the risk of depressive disorder compared to those without NCDs (RR=2.97; 95%CI 2.06–4.27). The study also showed that, with each additional chronic disease, the risk of having a depressive disorder increased by 45% in relation to those without diseases³⁴34. Read JR, Sharpe L, Modini M, Dear BF. Multimorbidity and depression: a systematic review and meta-analysis. J Affect Disord 2017; 221: 36-46. https://doi.org/10.1016/j.jad.2017.06.009
https://doi.org/10.1016/j.jad.2017.06.00... . From another temporal perspective, a meta-analysis of population-based cross-sectional studies (n=190,593 individuals from 43 low- and middle-income countries, recruited by the World Health Survey) revealed that the chance of multimorbidity was higher among people with depressive episodes (OR 3.44; p<0.0001) compared to those without depression³⁵35. Stubbs B, Vancampfort D, Veronese N, Kahl KG, Mitchell AJ, Lin PY, et al. Depression and physical health multimorbidity: primary data and country-wide meta-analysis of population data from 190 593 people across 43 low- and middle-income countries. Psychol Med 2017; 47 (12): 2107-17. https://doi.org/10.1017/S0033291717000551
https://doi.org/10.1017/S003329171700055... . These studies reveal the robust relationship between multimorbidity and depressive disorder, as the associations were significant in all age groups, cultures, and scenarios. Besides, regardless of how depression was measured³⁴34. Read JR, Sharpe L, Modini M, Dear BF. Multimorbidity and depression: a systematic review and meta-analysis. J Affect Disord 2017; 221: 36-46. https://doi.org/10.1016/j.jad.2017.06.009
https://doi.org/10.1016/j.jad.2017.06.00... and the level of depression³⁵35. Stubbs B, Vancampfort D, Veronese N, Kahl KG, Mitchell AJ, Lin PY, et al. Depression and physical health multimorbidity: primary data and country-wide meta-analysis of population data from 190 593 people across 43 low- and middle-income countries. Psychol Med 2017; 47 (12): 2107-17. https://doi.org/10.1017/S0033291717000551
https://doi.org/10.1017/S003329171700055... , the relationships remained significant. However, this association is so complex that its simple linearity should not be presumed³⁴34. Read JR, Sharpe L, Modini M, Dear BF. Multimorbidity and depression: a systematic review and meta-analysis. J Affect Disord 2017; 221: 36-46. https://doi.org/10.1016/j.jad.2017.06.009
https://doi.org/10.1016/j.jad.2017.06.00... . The current study evidenced, for example, that the degree of limitation in the performance of routine activities caused by diseases is a factor that interferes with the strength of association with MDD. Also, the possibility of other factors influencing this relationship cannot be dismissed, including the severity and complications of diseases and the different combinations between them, which result in higher health care demands²²22. Willadsen TG, Bebe A, Køster-Rasmussen R, Jarbøl DE, Guassora AD, Waldorff FB, et al. The role of diseases, risk factors and symptoms in the definition of multimorbidity – a systematic review. Scand J Prim Health Care 2016; 34 (2): 112-21. http://doi.org/10.3109/02813432.2016.1153242
http://doi.org/10.3109/02813432.2016.115... .

As for gender differences, the current investigation found that women with NCDs or multimorbidity had a higher prevalence of MDD than men with the same conditions. Nonetheless, the data also revealed that, although associations between NCDs and MDD were significant in both genders, they were stronger among men. In addition, we detected a differential effect on MDD due to the relationship between males and specific diseases (heart disease, arthritis or rheumatism, and chronic kidney disease), as well as between males and multimorbidity. The literature also confirms the greater susceptibility of women to depression⁸8. Lim GY, Tam WW, Lu Y, Ho CS, Zhang MW, Ho RC. Prevalence of Depression in the Community from 30 Countries between 1994 and 2014. Sci Rep 2018; 8 (1). https://doi.org/10.1038/s41598-018-21243-x
https://doi.org/10.1038/s41598-018-21243... ,⁹9. Salk RH, Hyde JS, Abramson LY. Gender differences in depression in representative national samples: Meta-analyses of diagnoses and symptoms. Psychol Bull 2017; 143 (8): 783-822. https://doi.org/10.1037/bul0000102
https://doi.org/10.1037/bul0000102... ; however, no studies have been found with analyses stratified by gender on the effects resulting from the interaction between gender and NCDs on mental health. What we observed was research that sought to understand how the interaction between gender and psychological factors impacted the incidence of NCDs or correlated markers¹⁷17. Smaardijk VR, Lodder P, Kop WJ, van Gennep B, Maas AHEM, Mommersteeg PMC. Sex- and gender-stratified risks of psychological factors for incident ischemic heart disease: systematic review and meta-analysis. J Am Heart Assoc 2019; 8 (9): e010859. https://doi.org/10.1161/JAHA.118.010859
https://doi.org/10.1161/JAHA.118.010859... ,¹⁸18. Smaardijk VR, Maas AHEM, Lodder P, Kop WJ, Mommersteeg PMC. Sex and gender-stratified risks of psychological factors for adverse clinical outcomes in patients with ischemic heart disease: a systematic review and meta-analysis. Int J Cardiol 2020; 302:21-9. https://doi.org/10.1016/j.ijcard.2019.12.014
https://doi.org/10.1016/j.ijcard.2019.12... . From this perspective, Smaardijk et al.¹⁷17. Smaardijk VR, Lodder P, Kop WJ, van Gennep B, Maas AHEM, Mommersteeg PMC. Sex- and gender-stratified risks of psychological factors for incident ischemic heart disease: systematic review and meta-analysis. J Am Heart Assoc 2019; 8 (9): e010859. https://doi.org/10.1161/JAHA.118.010859
https://doi.org/10.1161/JAHA.118.010859... , in a systematic review and meta-analysis, found that psychological factors were associated with IHD in women (HR=1.22; 95%CI 1.14–1.30) and men (HR=1.25; 95%CI 1.19–1.31), but with no difference between genders (p=0.547). Another meta-analysis showed that, in individuals with IHD, depression was associated with a higher risk of major adverse cardiovascular events (MACE), both in women (HR=1.20; 95%CI 1.10–1.32) and men (HR=1.48; 95%CI 1.32–1.65), with a statistical difference (p=0.005)¹⁸18. Smaardijk VR, Maas AHEM, Lodder P, Kop WJ, Mommersteeg PMC. Sex and gender-stratified risks of psychological factors for adverse clinical outcomes in patients with ischemic heart disease: a systematic review and meta-analysis. Int J Cardiol 2020; 302:21-9. https://doi.org/10.1016/j.ijcard.2019.12.014
https://doi.org/10.1016/j.ijcard.2019.12... . Thus, further studies are necessary to clarify the effect of the interaction between gender and NCDs on the association with depression.

Regarding preventive measures, a 2013 PNS study with 60,022 Brazilian adults, using PHQ-9, also identified an association between depression and multimorbidity. Nevertheless, men who practiced the recommended level of physical activity (150 minutes per week) had an attenuation in the association of heart diseases, cancer, and chronic obstructive pulmonary disease (COPD) with depressive symptoms, which reinforces the importance of recommending healthy habits and lifestyles to cope with these conditions⁴⁰40. Andrade-Lima A, Werneck AO, Szwarcwald CL, Schuch FB, Stubbs B, Bastos AA, et al. The role of physical activity in the association between multimorbidity and depressive symptoms: data from 60,202 adults from the Brazilian National Health Survey. J Psychosom Res 2020; 134: 110122. https://doi.org/10.1016/j.jpsychores.2020.110122
https://doi.org/10.1016/j.jpsychores.202... .

A limitation of this study is its cross-sectional design, which does not allow us to establish causality relationships. The possibility of information bias is another limitation since data were obtained through interviews, and information on the diagnosis of chronic diseases was self-reported. In addition, comparisons with results from other studies were hindered by the use of different sample compositions, instruments, and analysis strategies. However, in order to minimize the effects of such differences, we took the precaution of comparing the results, whenever possible, with systematic reviews and meta-analyses, which identify and summarize the best scientific evidence. We underline that, in all of them, the adult population was included in the analyses.

On the other hand, this study analyzed a representative sample of the Brazilian adult population, which allowed investigating rarer events, and data were collected in a standardized and supervised manner, adopting a validated and widely used instrument to identify the presence of MDD (PHQ-9). This research filled a gap by analyzing the association of MDD with NCDs and multimorbidity, examining the modifying role of gender in these associations. Results of the present investigation raise the hypothesis that the effect of multimorbidity and certain NCDs may be greater on the mental health of men and instigate new studies on the subject.

Acknowledgments

The authors thank the National Council for Scientific and Technological Development (Conselho Nacional de Desenvolvimento Científico e Tecnológico — CNPq) for funding the productivity grants to M.B.A. Barros, C.L. Szwarcwald, and D.C. Malta and the São Paulo Research Foundation (Fundação de Amparo à Pesquisa do Estado de São Paulo — FAPESP) for the postdoctoral fellowship to L.P.B. Medina.

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