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Conteúdo (article):

DEPRESSIVE SYMPTOMS AMONG BRAZILIAN OLDER ADULTS: A STUDY BASED ON THE 2019 NATIONAL HEALTH SURVEY

Authors:
Vinicius dos Santos Sguerri (SGUERRI, V.S.) I
e-mail: vinicius_ssguerri@hotmail.com
ORCID: https://orcid.org/0000-0002-3239-2825
Érico de Castro Costa (CASTRO-COSTA, E.) II
e-mail: ericocastrocosta@gmail.com
ORCID: http://orcid.org/0000-0003-0792-5439
Antônio Ignácio de Loyola Filho (LOYOLA FILHO, A.I) II,III
e-mail: antonio.filho@fiocruz.br
ORCID: https://orcid.org/0000-0002-7317-3477

I – Programa de Pós-Graduação em Saúde Pública – Instituto René Rachou/FIOCRUZ Minas
II – Núcleo de Estudos em Saúde Pública e Envelhecimento (NESPE)/Instituto René Rachou/FIOCRUZ MINAS
III – Departamento de Gestão de Serviços de Saúde – Universidade Federal de Minas Greais (UFMG)
 
RESUMO
Introdução — A depressão é um transtorno mental comum, que gera limitações para o funcionamento psicossocial e prejudica a qualidade de vida. Objetivo — Investigar a prevalência e identificar os fatores sociodemográficos e condições de saúde associados a sintomas depressivos na população idosa brasileira. Metodologia — Foram utilizados dados coletados junto a 21.965 participantes da Pesquisa Nacional de Saúde – 2019, com 60 anos ou mais. O Patient Health Questionnaire-9 (PHQ-9) foi utilizado para rastreamento de sintomas depressivos, considerando o ponto de corte ≥9. O modelo de regressão de Poisson foi utilizado para detecção dos fatores associados, ao nível de significância de p<0,05. Resultados — A prevalência de sintomas depressivos foi de 13,2%. Após o ajustamento, mostraram-se positivamente associados à presença de sintomas depressivos o sexo feminino, autoavaliação negativa da saúde (regular ou ruim/muito ruim) e ter duas ou mais doenças crônicas. Associações negativas foram detectadas para idade entre 70 e 79 anos e residência em zona rural e nas regiões Nordeste e Norte. Conclusão — Tendo em vista a frequência com que os sintomas depressivos ocorrem entre pessoas idosas, e as consequências para a qualidade de vida desse segmento populacional, os serviços de saúde devem organizar-se para monitorá-los, identificá-los e fornecer ou referenciar o cuidado adequado.

Palavras-Chave: sintomas depressivos; pessoa idosa; Envelhecimento; PHQ-9; Inquéritos de Saúde

 
ABSTRACT
Background — Depression is a common mental disorder that leads to limitations in psychosocial functioning and impairs quality of life. Objective — To investigate the prevalence and identify the sociodemographic factors and health conditions associated with depressive symptoms among Brazilian older adults. Methodology — Data were collected from 21,965 participants aged 60 or older in the 2019 National Health Survey. The Patient Health Questionnaire-9 (PHQ-9) was used to screen for depressive symptoms, with a cut-off score of ≥9. Poisson regression analysis was employed to identify associated factors, with a significance level of p<0.05. Results — The prevalence of depressive symptoms was 13.2%. After adjustment, depressive symptoms were positively associated with the female sex, negative self-rated health (fair or poor/very poor) and having two or more chronic diseases. Negative associations were found for the group age between 70 and 79 years, residing in rural areas, and in the Northeast and North regions. Conclusion — Given the frequency of depressive symptoms among older adults and their impact on the quality of life in this population segment, health services should be organized to monitor, identify, and provide or refer appropriate care.

Keywords: Depressive symptoms; older adults; aging; PHQ-9; health surveys

 
INTRODUCTION
Population aging, characterized by the proportional increase of the older adult segment within the population, is a global phenomenon, though it has occurred or is occurring at different rates across countries1. In Brazil, population aging began in the 1970s, completely transforming the country\'s demographic profile. At that time, the population was still relatively young, with older adults representing 4.3% of the total population. By 2010, this percentage had risen to 10.8%2. According to the latest census conducted in 2022, the older adult population in Brazil now exceeds 32 million, accounting for 15.8% of the total population3.
Population aging is accompanied by a shift in patterns of morbidity, mortality, and functionality, with a progressive increase in the prevalence of chronic non-communicable diseases (NCDs). These diseases are non-infectious and result from a combination of genetic, physiological, behavioral, and environmental factors. They tend to have a prolonged course, require long-term treatment, and include conditions such as cardiovascular diseases, chronic respiratory diseases, cancers, and diabetes mellitus (DM), among others4. The predominance of NCDs in the morbidity and mortality profile of aging populations underscores the importance of addressing mental health issues, as many of these diseases are associated with depressive disorders. This association may result from specific diseases or the presence of multimorbidity5,6,7.
Depressive disorders are characterized by symptoms such as sadness, loss of interest or pleasure, feelings of guilt or reduced self-esteem, sleep or appetite disturbances, fatigue, and difficulty concentrating. They can manifest as major depressive disorder, depressive episodes (which can be mild, moderate, or severe), or dysthymia (a chronic form of mild depressive disorder, similar to a depressive episode but less intense and more enduring)8. In large epidemiological studies, various sets of questions are used to detect clinically relevant symptoms of depressive disorders, known as screening scales9. This approach is preferred because using psychiatric interviews for diagnosing depressive disorders in such studies is extremely challenging due to their high cost and the time required for administration10.
The determinants of depressive disorders encompass a broad spectrum of factors, ranging genetic predisposition to NCDs (as previously mentioned), as well as sociodemographic and psychosocial factors11,12,13. In addition to their impact on physical health, depressive disorders impose a significant social cost by impairing work, domestic, and social activities. They lead to recurrent work absences, prolonged periods away from work, decreased productivity, increased social exclusion, and earlier retirement due to health issues14. Among older adults, depressive disorders contribute to a diminished quality of life, as economic and emotional losses are compounded by health-related issues such as comorbidities, functional impairment, and dementia15.
Depressive disorder is the most commonly observed mental disorder. In 2015, 322 million people (4.4% of the global population) were affected by depressive disorders, with prevalence increasing by 18.4% from 2005 to 20158. In Brazil, the 2019 National Health Survey revealed that one in ten (10.9%) Brazilian adults aged 18-59 suffered from major depressive disorder6. Among older adults, the 2013 National Health Survey reported a prevalence of depressive disorders of 5.0% in the 60-79 age group and 6.8% in those aged 80 and older16.
The National Health Survey is a comprehensive health assessment that continues the work of the Health Supplement of the National Household Sample Survey (Suplemento Saúde da Pesquisa Nacional por Amostra de Domicílio—PNAD), with similar objectives, focus, and periodicity. It provides results for a situational diagnosis of the health of the Brazilian population, identifying at-risk subgroups and detailing access to and use of health services. The survey offers a detailed overview of health across different population levels, including regional, state, and capital city levels, to guide public health policies. In its two most recent editions (2013 and 2019), it includes a screening tool for depressive symptoms, allowing for a robust assessment of the prevalence of this issue in the Brazilian population17. However, we were unable to find any studies in major electronic bibliographic databases that specifically investigated the prevalence and associated factors of depressive symptoms among a representative sample of the Brazilian older adult population.
In this regard, the present study used data from the 2019 National Health Survey to investigate the prevalence of depressive symptoms and identify the sociodemographic characteristics and health conditions associated with these symptoms in the Brazilian older adult population (aged 60 and older).
METHODOLOGY
Study design, context, and population
This cross-sectional study utilized data from the 2019 National Health Survey. The survey aimed to understand the determinants, conditions, and health needs of Brazilians to support the development of public policies and enhance the effectiveness of the Brazilian health system through targeted health interventions17.
The National Health Survey was conducted with a representative sample of the Brazilian population across all age groups, totaling 279,382 individuals. The sampling design used in the survey included cluster sampling in three stages: (1) census sectors or sets of census sectors formed the primary sampling units, (2) households were selected as the units of the second stage, and (3) adult residents defined the units of the third stage. Census sectors and households were chosen through simple random sampling, and participants (household residents) were selected with equal probability. Questionnaires were completed by residents aged 18 and older17. For the present study, all participants aged 60 years or older (n=22,728) who responded to the selected resident\'s questions in the 2019 National Health Survey were eligible.
Variables and data collection
Data were collected through household interviews using a structured questionnaire. All data collectors, supervisors, and coordinators involved in the National Health Survey were trained and qualified. The interviews were conducted using Personal Digital Assistants (PDAs)—handheld computers programmed for the process of criticizing variables17.
The dependent variable was the presence of depressive symptoms, screened using the Patient Health Questionnaire-9 (PHQ-9)18, which has been validated in Brazil12. This screening tool consists of nine questions that assess depressive symptoms as outlined in the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders19. It evaluates the following symptoms: depressed mood, fatigue or lack of energy, anhedonia, difficulty sleeping, changes in appetite or weight, feelings of guilt or worthlessness, difficulty concentrating, restlessness or lethargy, and suicidal thoughts.
For each question, the frequency of symptoms experienced in the past two weeks was assessed. The instrument assigns points based on the frequency of symptoms, ranging from zero (not at all) to three (nearly every day). The scores for each question are summed to obtain a final score with a maximum possible value of 27 points. Clinically relevant depressive symptoms were identified in participants who scored nine or more points, a threshold that maximizes the sensitivity and specificity of the test as validated in Brazil12.
Sociodemographic variables and health condition descriptors were considered in the investigation of associated factors. The sociodemographic variables included sex (male; female), age (60-69 years, 70-79 years, and 80 years or older), education level (no formal education; primary education; secondary education; higher education), marital status (married; divorced; widowed; single), per capita household income in national minimum wages (NMW) (up to 1 NMW; between >1 and 2 NMW; between >2 and 5 NMW; and >5 NMW), area of residence (urban; rural), and geographic region of residence (Southeast, South, Northeast, Central-West, North).
The health condition variables included the number of chronic diseases and self-rated health (very good/good; fair; poor/very poor). The first category corresponded to a positive health assessment, while the other categories indicated a negative one. The "number of chronic conditions" variable considered the sum of reported medical diagnoses for the following NCDs: hypertension (HTN), DM, heart disease, stroke, asthma, arthritis, chronic obstructive pulmonary disease (COPD), cancer, and chronic kidney disease (CKD). These variables were dichotomous (no; yes), and positive responses (yes) for each disease were summed to assign a numerical value to the variable, which was later categorized (none; 1; 2 or more NCDs) for analytical procedures.
Data analysis
The characterization of the study population based on explanatory variables was based on absolute and relative frequencies. The prevalence of depressive symptoms (overall and by explanatory variables) was calculated proportionally by relating the number of participants with depressive symptoms (score ≥ 9) to the total number of study participants. Confidence intervals (95% CI) were also calculated for the prevalence estimates.
Regarding explanatory variables, the comparison between participants with and without depressive symptoms was conducted using univariate analyses based on Pearson\'s chi-square test with Rao-Scott correction. This adjustment was made to account for the effects of the complex sampling design.
Univariate and multivariate analyses were based on the Poisson regression model, which provides estimates of prevalence ratios and their corresponding 95% confidence intervals. All variables were included in the initial multivariate model (full model), regardless of the results from the univariate analyses. Selective deletion of variables (backward elimination) was then performed for those not associated with depressive symptoms in the presence of other variables. Variables independently associated with the outcome were retained in the final model. A significance level of p<0.05 was adopted for both the selective deletion of variables in the intermediate models and for identifying variables independently associated with the outcome in the final model.
The analyses in this study were conducted using STATAⓇ statistical software, version 14.0, with the survey module, which is suitable for handling data from population surveys with complex samples.
Ethical aspects
In compliance with Resolution 196/96 of the National Health Council, the 2019 National Health Survey received approval from the National Research Ethics Commission (Comissão Nacional de Ética em Pesquisa—CONEP) in August 2019, under number 3.529.376. The study ensured participants\' voluntary participation, anonymity, and the right to withdraw from the study at any time.
RESULTS
The study included 21,965 older adults with complete data for all analyzed variables (response rate = 96.6%), excluding those with missing information on any variable. The losses (n = 763, or 3.4%) were not significantly different with respect to the event under investigation (p = 0.268).
The study population was predominantly female (57.2%), aged between 60 and 69 years (56.4%), with education equivalent to elementary school (53.4%), and with a per capita household income of up to 2 NMW (73.3%). Most were married (50.8%) and resided in urban areas (86.0%), with nearly half (46.9%) living in the Southeast region. Regarding health conditions, 11.3% rated their health as poor or very poor, and 37.7% reported a medical diagnosis of two or more chronic diseases. Table 1 provides a complete description of the study population.
The prevalence of depressive symptoms was 13.2% (95% CI: 12.4%-14.0%) according to PHQ-9≥9. Table 1 also shows the distribution of depressive symptoms by explanatory variables. The prevalence was significantly (p<0.05) higher among females and individuals aged 80 or older and lower among those who were married. Depressive symptoms decreased with increasing education and per capita household income and were higher among urban residents. No significant differences were observed with respect to geographic region.
Depressive symptoms were more frequent among participants in poorer health conditions, both subjectively and objectively. The prevalence of depressive symptoms was 43.6% among those who rated their health as poor or very poor, compared to 4.3% among those who rated their health as good or very good. Approximately one-fifth (20.9%) of respondents with two or more chronic diseases reported depressive symptoms, compared to 6.8% among those with none of the assessed conditions (Table 1).
Table 2 presents the results of univariate and multivariate analyses of factors associated with depressive symptoms using the Poisson regression model. In the univariate analysis, all variables were associated with depressive symptoms (p<0.05). After adjusting in the multivariate model, the factors independently associated with higher probabilities of depressive symptoms were female sex (PR=1.70; 95% CI: 1.50-1.92), self-rated health as fair (PR=3.25; 95% CI: 2.69-3.93) and poor/very poor (PR=8.65; 95% CI: 7.06-10.61), and having two or more chronic diseases (PR=1.64; 95% CI: 1.37-1.97). Factors associated with lower probabilities of depressive symptoms included being in the age group of 70-79 years (PR=0.83; 95% CI: 0.74-0.94), living in a rural area (PR=0.82; 95% CI: 0.71-0.94), and residing in the Northeast (PR=0.79; 95% CI: 0.69-0.90) and North (PR=0.68; 95% CI: 0.57-0.82) regions.
DISCUSSION
The present investigation revealed that approximately 13% of the older adult Brazilian population had a PHQ-9 score ≥9, compatible with the presence of clinically relevant depressive symptoms. It also showed that depressive symptoms were more common among older women and less frequent among those aged 70-79, residing in rural areas, and living in the Northeast and North regions. Additionally, the prevalence of depressive symptoms was significantly higher among participants in poorer health conditions (negative self-assessment of health and with two or more NCDs). All these differences remained as independent associations after multivariate analysis.
The prevalence of depressive symptoms detected in the present study was lower than the average prevalence (28.4%) found in a systematic review and meta-analysis based on 48 studies involving approximately 73,000 older adults from various continents, predominantly Asian20. It was nearly the same (13.3%) as that observed in another meta-analysis aggregating 18,953 older adults from countries across all continents15. It was also lower than the prevalences observed among Canadians aged 50 or older (27.0%)21 and among older adults in India (29,0%)22, Chile (28.3%)23, and China (15,9%)24— all of which were national studies.
Regarding studies conducted in Brazil, our results fall within the range of prevalence values for depressive symptoms (between 7.1% and 39.6%, mean=21.0%), as estimated in a systematic review and meta-analysis encompassing 33 articles (n=39,431 older adults), nearly all of which were published between 2000 and 2017. Several studies conducted in Brazilian cities of varying population sizes (Caeté-MG26, São Paulo-SP27, Pelotas-RS28, and Florianópolis-SC29) found prevalences between 14.2% and 25.6%, which are higher than the estimate from our study.
Explaining the variation in prevalence rates of depressive symptoms among different populations is challenging. These variations can arise from a variety of factors, primarily related to the characteristics of the population and socio-environmental context. Methodological issues, especially concerning the screening instruments used, also play a significant role.
Regarding population and contextual characteristics, depressive symptoms are more prevalent in populations experiencing worse health conditions, particularly those with debilitating illnesses30. Studies that exclude individuals with severe illnesses or disabilities often report lower prevalence estimates31. Similarly, populations facing greater socioeconomic deprivation and/or stigma related to depression tend to have higher prevalences of depressive symptoms, as they are more frequently exposed to stressful events and may be less likely to seek health services for treatment. Conversely, governments in regions with higher socioeconomic and human development can implement health policies that provide greater support and mental health benefits, resulting in lower prevalence rates20. In Brazil, municipalities with higher Human Development Index (HDI) scores have exhibited lower frequencies of depressive symptoms25.
Prevalence estimates can also be influenced by the tests used to identify depressive symptoms. Tests with higher sensitivity tend to yield higher prevalence rates, while those with higher specificity may result in lower estimates. Among Brazilians, the Geriatric Depression Scale (GDS-15) has shown greater sensitivity compared to specificity32. In the validation study of the PHQ-9 with the Brazilian adult population, the cut-off point of ≥9 provided greater specificity (86.7%) than sensitivity (77.5%)12. Consequently, the PHQ-9 showed lower sensitivity compared to the GDS-15. Studies conducted in Brazil that reported higher prevalence rates than ours used the GDS-15 for screening depressive symptoms.
Similarly, lower cut-off points confer greater sensitivity to the test, while higher cut-off points increase specificity. For instance, a trend study based on data from the National Health Survey 2019 found prevalence rates of 10.5% and 11.1% for the age groups 60-69 years and 70 years or older, respectively33. These prevalences are lower than those detected in our study, which used the same database. The likely reason for this difference is the discrepancy in the cut-off point adopted for detecting depressive symptoms: Lopes et al. (2022)33 used a cut-off of ≥10, which is more specific than the cut-off of ≥9 used in our study.
Among the sociodemographic characteristics, depressive symptoms were positively associated with the female sex and negatively associated with the intermediate age group (60-79 years), as well as residents in the North and Northeast regions and rural areas. The association between female sex and depression is well-documented in both international and national scientific literature. In various countries21,24,31,34, older women experience more depressive symptoms than their male counterparts, a pattern also observed among older adults in Brazil16,27,28,35.
The higher frequency of depressive symptoms among older women may stem from both biological and socioeconomic factors. Biologically, the pathophysiology of depression differs between men and women, with variations in the behavior of biomarkers related to neurotransmission, neuroplasticity, and the immune system. These mechanisms are intricately linked with sex hormones, making women more susceptible to depressive symptoms15,36. Socioeconomically, women may experience depression due to greater exposure to stressors related to sexual discrimination, their roles within family and society, and economic dependence on their partners34,35.
Scientific literature is not unanimous regarding the influence of age on the occurrence of depressive symptoms among older adults. Several studies from various countries show a positive association between age and depressive symptoms11,15,24,34,36, while others indicate no such association27,31,35. We observed a lower frequency of depressive symptoms with increasing age, (restricted to the 70-79 age group, which aligns with findings from older adults of Chile23,38 and Southern Brazil29.
The increase in depression with advancing age may be linked to chronic diseases, memory and vision impairments, functional disability, and other events common in later life, which contribute to dependency and a decline in quality of life27,34. Therefore, the negative association between age and depressive symptoms observed in our study might seem counterintuitive. In older Chileans, this association was attributed to the exclusion of the oldest individuals with cognitive problems or dementia from the study population23. In our study, however, physical or cognitive dysfunction was not an exclusion criterion, and data losses due to missing information were not differentiated by health conditions (results not shown). Another plausible explanation could be psychological immunity, a term referring to greater resilience to adverse life events due to repeated exposure, which might make older adults less susceptible to depression39.
Similar to the present study, a lower prevalence of depressive symptoms among older adults living in rural areas and the North and Northeast macro-regions was also detected in the 2013 National Health Survey in studies involving the general population (18 years or older)16,33. Specifically regarding residence area, the results in other countries are controversial and may vary depending on the socioeconomic context. Some studies have associated depression with urban residence24,40, while others have found no such association41,42.
The environment can be a risk factor for developing depressive symptoms. In urban areas, higher population density, excessive noise, frequent sleep disturbances, insecurity, and fear can permeate daily life. Social inequality is often more pronounced, all contributing to a lower quality of life and increasing the risk of depression for those living in such environments35.
In turn, the lower prevalence of depressive symptoms among older adults in the North and Northeast regions, compared to those in the Southeast, could be attributed to differences in the distribution of determinants of depressive symptoms across these population strata and the intensity of the relationship between exposures and the outcome. For instance, the likelihood of living in rural areas was higher in both the North and Northeast regions, whereas the frequency of having two or more chronic diseases was lower in the North. In our study population, living in rural areas was negatively associated with depressive symptoms, while the presence of two or more chronic diseases was positively associated with depressive symptoms, supporting this explanatory hypothesis. However, this pattern was not observed for other variables associated with depressive symptoms, such as sex, which did not differ by macro-geographic region. Additionally, similar to the general population, older adults in the North and Northeast regions rated their own health worse, contradicting the speculated explanation.
Among Brazilian older adults, poorer health conditions, such as the presence of chronic disease and a negative self-assessment of health, were associated with depressive symptoms. The association between worse self-perceived health and depressive symptoms has been documented in various older populations5,27,28,30,35,38.
Self-assessment of health is a widely used variable in epidemiological studies due to its robustness and comprehensiveness in explaining health events and ease of implementation, as it relies on a single question. This measure offers valuable insights into the individual\'s health and life context, capturing symptoms of undiagnosed illnesses and reflecting their perceived progression. Its measurement power stems from its ability to assess both physical and psychological factors that threaten an individual\'s health, incorporating biological and psychological aspects of well-being43.
In addition to reflecting the individual\'s judgment of their own health, this variable can signal internal motivations, the social resources available for coping with illness, and their propensity for managing it44,45. Given the extensive and comprehensive information it encompasses, a poorer self-perception of health undoubtedly affects an individual\'s well-being and mental health, potentially contributing to the occurrence of depression. Consequently, healthcare professionals should be attentive to their patient\'s health perceptions, as a simple question during a consultation can reveal not only the presence of depressive symptoms but also the individual\'s readiness to address them. The bidirectional nature of this association43,46 does not invalidate this approach.
The association between chronic diseases and depression is well-established in the literature. Some studies have investigated specific diseases, linking depression to conditions such as heart disease, arthritis, and rheumatism5; HTN and DM16; stroke; COPD; asthma; and chronic spine problems6,47. Others, like our study, have addressed chronic diseases collectively, without individualizing them, and associated depression with the number of chronic conditions present6,24,34,35,38,48.
From a broader perspective, the presence of pain and inflammatory processes links NCDs to depression. The biological connections between these diseases include vascular changes (such as endothelial dysfunction), neurochemical alterations, and disruptions in nervous system metabolism. NCDs cause discomfort due to their symptom burden and persistent complications, leading to functional decline and dependency. Additionally, the psychological impact of losing control over important life activities, coupled with the negative feelings associated with NCDs—stemming from the unpredictability of their course and past experiences—contributes to a decline in quality of life and acts as a trigger for the development of depression7,47,49.
Similar to the case with self-rated health, it is important to highlight the bidirectional nature of the association between NCDs and depression7. Depression can impact adherence to treatment for NCDs and promote the adoption of health-damaging behaviors (such as smoking, physical inactivity, and poor diet), which are risk factors for NCDs50. This mutual determination should receive special attention from healthcare services and professionals due to its implications for the therapeutic management of these diseases.
The main limitation of this study arises from its cross-sectional design. Cross-sectional studies cannot establish causal relationships between exposure and outcome, as they do not allow for temporal separation of measures. Thus, the presence of reverse causation bias cannot be ruled out, especially regarding associations with variables describing health conditions. Another limitation pertains to the measurement process of the investigated event. While screening instruments can identify clinically relevant depressive symptoms, they are insufficient for diagnosing depression. However, they are valuable for identifying segments of the population at risk of developing depressive symptoms, who should undergo further evaluation by healthcare services.
On the other hand, the strength of our work lies in the size of the sample (study population) used and its representativeness across different levels of aggregation (national, macro-regions, federal states, and their capitals). This aspect allows for the full potential of statistical analyses, producing robust and reliable results that can be generalized to the older adult population in Brazil. Finally, the choice of the PHQ-9 as a screening tool maximizes sensitivity and specificity for detecting clinically relevant depressive symptoms. The PHQ-9 is particularly suitable for the older adult population and has been validated in Brazil.
In summary, the present investigation revealed that depressive symptoms among older adults in Brazil are associated with sociodemographic characteristics and health conditions, corroborating findings from other population-based epidemiological studies. It also demonstrated that, within this population, both objectively and subjectively measured health conditions —particularly the latter—were the factors most strongly associated with depressive symptoms. Given the frequency of depressive symptoms among older adults and their impact on the quality of life of this population segment, healthcare services should be organized to monitor, identify, and provide appropriate care for these symptoms.
In light of the connections between NCDs and depression and the frequent use of healthcare services, medical consultations represent a valuable opportunity to investigate depression among older adults, even in non-specialized settings. This can be achieved through depression screening tests or by incorporating selected questions from these instruments during routine medical consultations, aiming to refer patients for specialized care when necessary. Additionally, considering that depressive symptoms in older adults are potentially modifiable and preventable, our findings support the implementation of early multidisciplinary intervention strategies. These strategies should involve healthcare professionals beyond specialists and include guidance and psychoeducation for family members to promote better self-assessment of the older adult\'s health.

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