SciELO - Scientific Electronic Library Online

vol.48 número3Incapacidade em atividades instrumentais de vida diária em idosos: diferenças de gênero índice de autoresíndice de assuntospesquisa de artigos
Home Pagelista alfabética de periódicos  

Serviços Personalizados




Links relacionados


Revista de Saúde Pública

versão impressa ISSN 0034-8910

Rev. Saúde Pública vol.48 no.3 São Paulo jun. 2014 

Original Articles

Screening for depressive symptoms in older adults in the Family Health Strategy, Porto Alegre, Brazil

Eduardo Lopes Nogueira I   II  

Leonardo Librelotto Rubin III  

Sara de Souza Giacobbo I  

Irenio Gomes I   IV  

Alfredo Cataldo Neto I   II  

IInstituto de Geriatria e Gerontologia. Pontifícia Universidade Católica do Rio Grande do Sul. Porto Alegre, RS, Brasil

IIDepartamento de Psiquiatria. Pontifícia Universidade Católica do Rio Grande do Sul. Porto Alegre, RS, Brasil

IIIPrograma de Pós-Graduação em Psiquiatria. Pontifícia Universidade Católica do Rio Grande do Sul. Porto Alegre, RS, Brasil

IVDepartamento de Neurologia. Pontifícia Universidade Católica do Rio Grande do Sul. Porto Alegre, RS, Brasil



To analyze the prevalence of depression in older adults and associated factors.


Cross-sectional study using a stratified random sample of 621 individuals aged ≥ 60 from 27 family health teams in Porto Alegre, RS, Southern Brazil, between 2010 and 2012. Community health agents measured depression using the 15-item Geriatric Depression Scale. Scores of ≥ 6 were considered as depression and between 11 and 15 as severe depression. Poisson regression was used to search for independent associations of sociodemographic and self-perceived health with both depression and its severity.


The prevalence of depression was 30.6% and was significantly higher in women (35.9% women versus 20.9% men, p < 0.001). The variables independently associated with depression were: female gender (PR = 1.4, 95%CI 1.1;1.8); low education, especially illiteracy (PR = 1.8, 95%CI 1.2;2 6); regular self-rated health (OR = 2.2, 95%CI 1.6;3.0); and poor/very poor self-rated health (PR = 4.0, 95%CI 2.9;5.5). Except for education, the strength of association of these factors increases significantly in severe depression.


A high prevalence of depression was observed in the evaluations conducted by community health agents, professionals who are not highly specialized. The findings identified using the 15-item Geriatric Depression Scale in this way are similar to those in the literature, with depression more associated with low education, female gender and worse self-rated health. From a primary health care strategic point of view, the findings become still more relevant, indicating that community health agents could play an important role in identifying depression in older adults.

Key words: Aged; Depression, epidemiology; Family Health Strategy; Mental Health Services, Manpower; Cross-Sectional Studies



Analisar a prevalência de depressão em idosos e os fatores associados.


Delineamento transversal com amostra aleatória estratificada de 621 indivíduos ≥ 60 anos provenientes de 27 equipes de saúde da família de Porto Alegre, RS, Brasil, no período entre 2010 e 2012. A depressão foi mensurada por agentes comunitários de saúde utilizando a Escala de Depressão Geriátrica de 15 itens. Escores ≥ 6 foram considerados depressão e entre 11 e 15, depressão severa. A regressão de Poisson foi o método de análise robusta utilizado para busca de associações independentes de variáveis sociodemográficas e autopercepção de saúde com a depressão e sua severidade.


A prevalência de depressão foi de 30,6%, significativamente maior em mulheres (35,9% mulheres versus 20,9% homens; p < 0,001). As seguintes variáveis apresentaram associações independentes com depressão: sexo feminino (RP = 1,4; IC95% 1,1;1,8); baixa escolaridade, sobretudo analfabetismo (RP = 1.8; IC95% 1,2;2,6); e autopercepção de saúde regular (RP = 2,2; IC95% 1,6;3,0) e ruim/péssima (RP = 4,0; IC95% 2,9;5,5). Houve aumento da força de associação desses fatores na depressão severa, exceto para escolaridade.


Alta prevalência de depressão foi observada na avaliação realizada por agentes comunitários de saúde, profissionais sem alta especialização. Esse modelo de aplicação da Escala de Depressão Geriátrica de 15 itens identificou achados similares aos encontrados na literatura, em que a depressão associou-se à baixa escolaridade, ao sexo feminino e à pior autopercepção de saúde. Do ponto de vista estratégico no âmbito da atenção básica, os achados são ainda mais relevantes, pois apontam que agentes comunitários de saúde podem ter um papel importante na detecção da depressão em idosos.

Palavras-Chave: Idoso; Depressão, epidemiologia; Estratégia Saúde da Família; Serviços de Saúde Mental, recursos humanos; Estudos Transversais


The ageing population is a global phenomenon. It is occurring at an unprecedented rate in developing countries such as Brazil, due to improvements in health indicators, such as increased life expectancy at birth and progressive falls in the fertility rate.a In Brazil, in 2011,b the estimated number of older adults was 23.5 million (12.1% of the population) according to estimates from the Brazilian Institute of Geography and Statistics (IBGE). Porto Alegre, RS, Southern Brazil, has one of the highest concentrations of older adults in the country (211,896 individuals).

Depression4 is one of the most common pathologies in older adults.6 Now understood as a chronic disease, it is a mental disorder, the main criteria of which are depressed mood and loss of interest or enjoyment. Complementary criteria include feelings of guilt or worthlessness, sleep and appetite disturbances, weight loss, lack of energy, poor concentration and suicidal thoughts. The prevalence of depression in the general population varies between 3.0% and 11.0% and is twice as high in females as in males. This proportion varies between 15.0% and 30.0% in older adults, depending on location, socioeconomic conditions and the instrument used to measure it.16 Depression is seen as a significant public health problem, with worrying perspectives for the future. The World Health Organization estimates that the disorder will be the pathology with the heaviest global disease load by 2030, being more intense in low and middle income countries due to lack of diagnosis and treatment.c

Internationally, rates of recognition for mood disorders in primary care are poor or inaccurate. Under diagnosis or late diagnosis in more severe depressive episodes,15 not detecting bipolar disorder in patients suffering from episodes of depression21 and under diagnosis in patients with chronic illness20 have been well documented. Diagnosing depression in older adults may be challenging due to varied or atypical phenomenology, differing from classic forms and combining depressed mood or persistent sadness with anhedonia. Loss of pleasure can be prominent in severe depression and sadness may go unnoticed or be denied. Depression is the psychological disease most commonly leading to suicide. Older adults in primary care (PC) with mood disorders may be at higher risk of suicide.9 Suicidal behavior in this age group tends to be more lethal – ratio of around 1:1 suicides/attempts by older adults, whereas in adolescents this figure is 1:100.d

The Geriatric Depression Scale (GDS-15)2 – instrument recommended by the Brazilian Ministry of Health – has been shown to be of great value in detecting geriatric depression in different clinical contexts and is of growing important in PC.d The short version of the GDS-15 plays a well-established role in screening and national studies have validated it in samples in both psychiatric2 and general outpatient contexts.18 Studies validating the GDS-15 show it to be accurate in identifying depressive disorders with a 5/6 cut-off point. The GDS-15 is an instrument made up of 15 questions, with each positive response associated with depression scoring 1 point, giving a score of 0 to 15.

There have been few studies of geriatric depression in PC using robust methodology, despite its relevance. Studies validating the GDS-15 in this environment are more recent and the scale was applied by trained medical students, doctors or research collaborators, even when the studies were of methodological quality.8,17 The GDS-15 was considered more appropriate for use in primary care than the GDS with 5, 10 or 30 items, both nationally and internationally.8,17

PC is responsible for promoting and maintaining health, preventing health problems, diagnosis, treatment and rehabilitation. For elderly users, it is the main access to the Unified Health System (SUS). Studies in realistic situations with SUS professionals may encourage the implementation of more effective and pro-active strategic actions.

The aim of this study was to analyze the prevalence of depression and associated factors in older adults.


This was a cross-sectional study of 621 older adults registered with the Estratégia Saúde da Família (ESF – Family Health Strategy), in Porto Alegre, RS, between 2011 and 2012. The original project was developed in order to discover the target population’s health problems. The sample was of 900 older adults for different prevalence with a margin of error varying between 1.0% (very low or very high prevalence) and 10.0% (prevalence approaching 50.0%). We selected 30.0% of family health care strategy teams for each of the eight administrative districts of Porto Alegre; 36 older adults were selected for each team, corresponding to the team’s maximum care capacity. All of the data pertaining to the older adults between March 2011 and August 2012 were analyzed.

Considering current literature,2,8,18 the outcome, depression, was measured using the GDS-15,2 with scores of ≥ 6 signifying depression and classified as mild to moderate depression (MMD) (scores between 6 and 10); severe depression (SD) (score of 11). Community health agents (CHA) from the selected family health care strategy teams were trained to apply the instrument. It contained questions concerning current depressive symptoms, avoiding somatic complaints. It is a scale of easily understood questions, with objective responses (yes; no) which can be applied by health care professionals who are not mental health specialists, after a brief training period.18

Home visits, part of the ESF pro-active model, were conducted to obtain various types of data, including that concerning health. Each CHA received a list of selected individuals, inhabitants in their health micro region. If the older adult was not at home, the CHA was instructed to attempt contact various times (at least twice) at different times of day and on different days. Of the 972 older adults selected, 809 were located (alive and residing at the registered address). The response rate was 76.7%. In total, 621 older adults were evaluated and complete data were obtained for 585 of them, who were therefore included in this analysis.

Absolute and relative frequencies were used in the descriptive analysis. Pearson’s Chi-square test was used to compare the frequency of the variables (classification shown in Tables 1 and 2) between groups with and without alteration in the GDS-15 and between groups with mild to severe alteration in the GDS-15. The variables associated with the outcome with significance ≤ 0.20 were included in the Poisson regression analysis with robust variance and a 95% confidence interval (CI). The Statistical Package for the Social Sciences (SPSS), version 17.0, was used.

Table 1 Sociodemographic data and frequency of alteration on the Geriatric Depression Scale. Porto Alegre, RS, Southern Brazil, 2012. 

Variable na Geriatric Depression Scale ≥ 6 pb
n %
Sex < 0.001c
 Female 379 136 35.9
 Male 206 43 20.9
Age (years) 0.798
 60 to 69 332 98 29.5
 70 to 79 192 62 32.3
 ≥ 80 61 19 31.3
Schooling (years) 0.004
 < 1 127 46 36.2
 1 to 3 231 68 29.4
 4 to 7 130 49 37.7
 ≥ 8 94 17.0b
Income (Brazilian minimum wage) 0.115
 < 2 514 165 32.1
 ≥ 2 38 7 18.4
Household income (Brazilian minimum wage) 0.220
 ≤ 3 451 144 31.9
 > 3 53 12 22.6
Retired 0.217
 Yes 363 102 28.1
 No 197 66 33.5
Race/Ethnicity 0.636
 White 378 113 29.9
 Non-white 202 65 32.2
Religion 0.287
 Catholic 382 108 28.3
 Evangelic 109 39 38.5
 Other 86 28 32.6
Marital status 0.939
 Single 104 32 30.8
 Married 207 60 29.0
 Widowed 182 58 31.9
 Separated/Divorced 90 28 31.1
Living alone 0.079
 Yes 104 40 38.5
 No 471 137 29.1
Practicing religion 0.312
 Yes 381 111 29.1
 No 187 63 33.7
Self-perceived health < 0.001c
 Very good/Good 194 26 13.4d
 Regular 323 109 33.7
 Poor/Very poor 59 41 69.5e
Total 585 179 30.6

a Values may not total 585 due to data losses

b based on the Chi-square test.

c p ≤ 0,05

d Frequencies of residues lower than expected (residue ≤ -1.96).

e Frequencies of residues higher than expected (residue ≥ 1.96).

Table 2 Sociodemographic data and intensity of the Geriatric Depression Scale. Porto Alegre, RS, Southern Brazil, 2012. 

na %  Geriatric Depression Scale
Variable 6-10  11   pb
n % n %
Sex < 0.001c
 Female 136 35.9 103 27.2 33 8.7
 Male 43 20.9 35 17.0 8 3.9
Age (years) 0.967
 60 to 69 98 29.5 76 22.9 22 6.6
 70 to 79 62 32.3 47 24.5 15 7.8
 ≥ 80 19 31.3 15 24.6 4 6.6
Schooling (years) 0.021
 < 1 46 36.2 33 26.0 13 10.2
 1 to 3 68 29.4 53 22.9 15 6.5
 4 to 7 49 37.7 40 30.8 9 6.9
 ≥ 8 16b 17.0 12 12.8 4 4.3
Income (Brazilian minimum wage) 0.115
 < 2 165 32.1 124 24.1 41 8.0
 ≥ 2 7 18.4 7 18.4 0 0.0
Household income (Brazilian minimum wage) 0,107
 ≤ 3 144 31.9 109 24.2 35 7.8
 > 3 12 22.6 11 20.8 1 1.9
Retired 0.211
 Yes 102 28.1 77 21.2 25 6.9
 No 66 33.5 52 26.4 14 7.1
Race/Ethnicity 0.851
 White 113 29.9 87 23.0 26 6.9
 Non-white 65 32.2 50 24.8 15 7.4
Religion 0.006
 Catholic 108 28.3 75b 16.9 33a 8.6
 Evangelic 39 38.5 36a 33.0 3 2.8
 Other 28 32.6 25 29.1 3 3.5
Marital status 0.982
 Single 32 30.8 25 24.0 7 6.7
 Married 60 29.0 49 23.7 11 5.3
Widowed 58 31.9 43 23.6 15 8.2
 Separated/Divorced 28 31.1 20 22.2 8 8.9
Living alone 0.153
 Yes 40 38.5 32 30.8 8 7.7
 No 137 29.1 105 22.3 32 6.8
Practicing religion 0.198
 Yes 111 29.1 91 23.9 20 5.2
 No 63 33.7 46 24.6 17 9.1
Self-perceived health < 0.001c
 Very good/Good 26d 13.4 21 10.8 5 2.6
 Regular 109 33.7 88 27.2 21 6.5
 Poor/Very poor 41e 69.5 27 45.8 14 23.7
Total 179 30.6

a Values may not total 621 due to data losses

b based on the Chi-square test.

c p ≤ 0,05.

d Frequencies of residues lower than expected (residue ≤ -1.96).

e Frequencies of residues higher than expected (residue ≥ 1.96).

g Drucker C. Religiosidade, crenças e atitudes em idosos deprimidos em um serviço de saúde mental de São Paulo, Brasil [dissertation]. Campinas: Faculdade de Educação da Universidade Estadual de Campinas; 2005.

This research was approved by the Research Ethics Committee of the Municipal Health Secretariat (Record 499 – Process 001.021434.10.7/2009) and of the Pontifícia Universidade Católica do Rio Grande do Sul (Protocol 11/05663). All individuals signed an informed consent form.


The prevalence of depression was 30.6% (95%CI 26.9 to 34.3%). Women predominated (63.8%) and the mean age was 69.4 (SD = 7.31 years), with decreasing frequency of depression between ages 60 and 69 (56.4%), 70 and 79 (33.2%) and 80 and over (10.5%). With regards to schooling, 21.8% were illiterate (including functional illiterates), 40.2% had between one and three years of schooling, 21.7%, between four and seven years and 16.3%, > eight years of schooling. Low income (< 2 minimum wages – MW) was the case for 89.5% of the older adults. The majority of the older adults reported that they were white (64.9%), followed by black (19.9%) and mixed race (12.1%). The majority (64.8%) were retired. Most were married (36.1%) or widowed (30.6%). The majority reported practicing some religion (67.7%) and being Catholic (66.6%). Regular self-perceived health was reported in 55.7% of the older adults, while 10.0% reported their health as poor or very poor (Table 1).

The non-controlled analysis showed in detail the frequency of distribution of the sociodemographic and self-perceived health data in relation to the outcomes: cases of depression versus not cases (Table 1) and two groups regarding severity of symptoms (Table 2).

Higher prevalence of detecting depression were seen in the Poisson regression: women, with PR:.4 (95%CI 1.1;1.8) for detecting depression, PR: 1.6 (95%CI 1.2;2.3) for MMD and PR: 2.9 (95%CI 1.2;6.8) for SD; illiterates, with PR: 1.8 (95%CI 1.2;2.6) and with four to seven years of schooling, PR: 1.5 (95%CI 1.0;2.2) for detecting depression, with four to seven years of schooling PR: 2.0 (95%CI 1.1;3.5) for MMD; and in individuals with regular or poor/very poor self-perceived health, highlighting the relationship between more severe depression and worse reported health, reaching PR: 23.6 (95%CI 7.2;77.4) for SD and poor/very poor self-perceived health (Table 3).

Table 3 Composition of Poisson Regression with robust variance, Porto Alegre, RS, Southern Brazil, 2012. 

Variable No depression versus GDS ≥ 6 No depression versus GDS 6-10 No depression versus GDS ≥ 11  

PRraw 95%CI PRajusted 95%CI p PRraw 95%CI PRajusted 95%CI p PRraw 95%CI PRajusted 95%CI p
 Male 1 1 1 1 1 1
 Female 1.4 1.1;1.8 1.4 1.1;1.8 0.002 1.7 1.2;2.4 1.6 1.2;2.3 0.004 2.6 1.2;5.4 2.9 1.2;6.8 0.016
Age (age)
 > 80 1 1 1 1 1 1
 70 to 79 1.2 0.8;1.8 1.2 0.8;1.8 0.393 1.0 0.6;1.7 1.0 0.6;1.6 0.95 1.2 0.4;3.4 0.9 0.3;3.2 0.921
 60 to 69 1.3 0.9;1.9 1.3 0.9;1.9 0.221 0.9 0.6;1.5 0.9 0.6;1.5 0.697 1.0 0.4;2.7 0.8 0.2;2.7 0.719
Schooling (years)
 ≥ 8 1 1 1 1 1 1
 4 to 7 2.1 2.4;3.2 1.5 1.0;2.2 0.041 2.5 1.4;4.4 2.0 1.1;3.5 0.02 2.1 0.7;6.4 1.4 0.4;4.7 0.548
 1 to 3 1.7 1.1;1.5 1.3 0.9;1.9 0.115 1.8 1.0;3.3 1.3 0.7;2.3 0.334 1.7 0.6;5.0 1.2 0.4;3.2 0.761
 < 1 2.1 1.4;3.1 1.8 1.2;2.6 0.003 2.2 1.2;4.0 1.4 0.8;2.6 0.259 2.8 1.0;8.4 1.2 0.4;3.5 0.693
Income (Brazilian minimum wage)
 ≥ 2 1 1
 < 2 1.8 1.0;3.2 1.4 0.7;2.8
Living alone
 No 1 1 1 1 1 1
 Yes 1.1 0.9;1.4 1.0 0.8;1.3 0.764 1.4 1.0;1.9 1.3 1.0;1.8 0.101 1.3 0.6;2.6 0.9 0.4;2.0 0.852
Practicing religion
 No 1 1 1 1 1 1
 Yes 0.9 0.7;1.1 0.9 0.8;1.1 0.514 0.9 0.7;1.3 1.0 0.7;1.3 0.919 0.6 0.3;1.1 0.7 0.4;1.3 0.276
Self-perceived health
 Very good/Good 1 1 1 1 1 1
 Regular 2.3 1.7;3.1 2.2 1.6;3.0 < 0.001a 2.6 1.7;4.1 2.5 1.6;3.9 < 0.001a 3.1 1.2;8.0 4.5 1.4;15.1 0.014
 Bad/Very bad 4.1 3.1;5.6 4.0 2.9;5.5 < 0.001a 5.4 3.4;8.6 5.3 3.3;8.5 < 0.001a 15.1 5.9;39.1 23.6 7.2;77.4 < 0.001a

a Personal income excluded as there were no individuals in the sample with GDS ≥ 11 and income > 2 Brazilian minimum wage.


The prevalence of depression (30.6%) is comparable to the higher levels found in studies whose samples were from primary care. Meta-analysis evaluating 17 publications which used the GDS-15 or -30 in primary care showed that overall prevalence of depression in older adults was 17.1% of a sample of 4,869 older adults.17 Brazilian population-based research indicates a prevalence of depression between 1.0% and 3.0% in the community, between 10.0% and 12.0% in individuals in outpatient care and 15.0% in hospitalized patients. The prevalence of depressive symptoms is around 15.0%, climbing to 20.0% in patients in primary care and 25.0% of hospitalized patients.e A meta-analysis examining geriatric depression in national studies using non-clinical samples found a prevalence of depression varying between 13.0% and 38.5%.5 The frequencies in other national studies were not uniform when studies conducted in different places were compared: 14.3% in Sao Paulo, SP,4 22.8% in Itajaí, SC,f and 35.3% in Rio de Janeiro, RJ.e A study evaluated more than 7 thousand older adults living in the community, both urban and rural, in Rio Grande do Sul. It used the Short Psychiatric Evaluation Schedule and showed a 22.7% prevalence of depressive symptoms.6 Such variations may be explained by the use of different screening instruments, as well as the small sample size and the different age group profiles (ages included and mean ages) of the studies.

A study conducted in Fortaleza, CE, with older adults in primary care found a 17.2% prevalence in detecting depression.d However, this study only investigated individuals who spontaneously sought health care services. A large study of around 2,000 older adults conducted in Sao Paulo, SP, detected depression in 27.1%.c The samples from the two studies shared more characteristics with this study as the subjects were on low income and from primary care. However, trained health care specialists conducted the screening in these cases. This makes it more difficult to approach the reality of PC and the aim of brief evaluations and screening for depression conducted by lay professionals.

This study found a higher frequency of depression in women (35.9% versus 20.9%), as in the literature. In the regression analysis, there were 1.4 times more cases of depression in women. Being female is a recognized risk factor, described in the literature.5,f In a study of older adults on low income in Sao Paulo, depressive symptoms in women were practically double those in men (34.5% versus 18.0%). Sociocultural factors associated with greater vulnerability to stressor events3 may contribute to this difference between genders. Another possible explanation may lie in cultural aspects, as women tend to seek more help for health problems and to express their feelings more openly.

Frequency of depression was similar in the age groups, even in the Poisson analysis, although some studies show that depressive symptoms dominate in the younger age groups.3,14 Other studies indicate that being aged > 75 is a risk factor in depression.14,19 The uniformity found is worth noting, as depression is a highly prevalent condition throughout the life cycle. The pro-active form of collecting data (home visits) may have contributed to reduced chances of losing individuals who are organically more affected and may have been more effective in healthy older adults and those in lower age groups who, although registered in the health district, are not patients. Some sub-types of depression may be more common in older adults, such as late-onset depression and secondary symptoms with organic causes, something which this study did not examine in-depth.

Illiteracy and low levels of schooling were associated with detecting greater levels of depression, as in the literature,3,a,f although this independent association was not clear when we examined the two groups of severity of symptoms (MMD and SD). In our sample, 17.0% of the older adults with > 8 years of schooling had depressive symptoms. Crepaldi reports a 50.0% reduction in the prevalence of depressive symptoms in older adults with ≥ 8 years of schooling compared with those with no schooling, a statistically significant difference.c

There was an association between detecting depression and income < 2 minimum wages, as described in the literature, which indicates low income and poverty as risk factors for depression.a Household income was tested in the Poisson analysis, the contribution was lower and it was not maintained in the analysis. Being on a low income may deprive older adults of appropriate health care and make it more difficult to buy medication and follow treatments, interfering with autonomy and recovering and remaining healthy.13,16

There was no significant difference in prevalence between the different religions or practicing religion in this sample. Drucker investigated religiosity in depressed older adults in the city of Campinas, SP, and stated that reading religious literature was the religious practice most predictive of depressive symptoms, which may indicate better mental health, compared with prayer, which was negatively related to depressive symptoms.a,g The main motive for increased religiosity was experiencing stressor events and it was identified as a resource for dealing with or alleviating symptoms of depression.g A study with 6,961 older adults living in the community in Rio Grande do Sul showed that the majority of the population were Catholic, followed by Evangelical. Subjects who were illiterate or had never been to school, those on low income, women, those who were separated or divorced and the Evangelicals reported becoming more religious with age and were at lower risk of developing mental disorders over time. Older adults who were Spiritists or Evangelical were at higher risk of psychological disease compared with other religious groups.6

The relationship between depression and self-perceived health is consistent. The more severe the depression, the worse the self-perceived health. The strongest association was found between SD and poor/very poor health (PR: 23.6, 95%CI 7.2;77.4). Pereira showed that 78.0% of those who perceived their own health to be poor/very poor had depressive symptoms, with likelihood ration of 4.56 in binary logistic regression.f A study of 310 older adults in primary care in Santa Cruz, RN, showed a likelihood ratio of depression 6.15 times higher (95%CI 3.09;13.71) in those with poor or very poor self-perceived health.16 According to the study, although this is a subjective aspect, the form in which the individual reports their overall status is closely associated with depression. Worse organic health also increases the chance of depression and this increase is directly related to the number of chronic diseases.7 The bi-directional relationship between depression and organic diseases appears well-established, although care should be taken when making this generalization. Some clinical situations appear to be more associated with depression, such as the pre-motor stage or diagnosis period in Parkinson’s disease,1 and late-onset depression may be more closely related to mild cognitive decline or dementia.12 This study is limited to self-related health and does not examine organic pathology in-depth.

The cross-sectional design meant that causal relationships between organic and mental pathologies were not able to be examined. The phenomenological examination of depressive symptoms is limited in discerning melancholic depression or intense apathy, characteristics more closely related to organic alterations.

The high prevalence of depression in older adults requires special attention due to its direct and indirect impact on worsening the individual’s health. Improvements in the rate of diagnosis, in identifying cases early and better approaches to depression in PC are down to systematic screening. Using standardized instruments minimizes the influence of subjective factors which may result in differences in data collection by the interviewees.d Although the GDS-15 is recommended by the Brazilian Ministry of Health for use in PC, it is only used routinely in local initiatives. Including this screening in pre-consultation may lead to earlier and more accurate diagnosis and intervention, as well as lowering costs for the health care system.

This study may contribute to greater diffusion of systematic screening and detecting depression in older adults in primary care. CHA, the health care professionals closest to the interface between health care and the community, are able to make this assessment, which is essential at this level.


1.  Aarsland D, Pahlhagem S, Ballard CG, Ehrt U, Svenningsson P. Depression in Parkinson disease: epidemiology, mechanisms and management. Nat Rev Neurol. 2011;8(1):35-47. DOI:10.1038/nrneurol.2011.189 [ Links ]

2.  Almeida OP, Almeida SA. Confiabilidade da versão brasileira da Escala de Depressão Geriátrica (GDS) versão reduzida. Arq Neuropsiquiatr. 1999;57(2B):421-6. DOI:10.1590/S0004-282X1999000300013 [ Links ]

3.  Bandeira CB. Perfil dos idosos com depressão em comunidade do município de Fortaleza. Rev Bras Med Fam Com. 2008;4(15):189-204. [ Links ]

4.  Barcelos-Ferreira R, Pinto Jr JA, Nakano EY, Steffens DC, Litvoc J, Bottino CMC. Clinically significant depressive symptoms and associated factors in community elderly subjects from Sao Paulo, Brazil. Am J Geriatr Psychiatry. 2009;17(7):582-90. DOI:10.1097/JGP.0b013e3181a76ddc [ Links ]

5.  Barcelos-Ferreira R, Izbicki R, Steffens DC, Bottino CM. Depressive morbidity and gender in community-dwelling Brazilian elderly: systematic review and meta-analysis. Int Psychogeriatr. 2010;22(5):712-26. DOI:10.1017/S1041610210000463 [ Links ]

6.  Blay SL, Andreoli SB, Fillenbaum GG, Gastal FL. Depression morbidity in later life: prevalence and correlates in a developing country. Am J Geriatr Psychiatry. 2007;15(9):790-9. DOI:10.1097/JGP.0b013e3180654179 [ Links ]

7.  Boing AF, Melo GR, Boing AC, Moretti-Pires RO, Peres KG, Peres MA. Associação entre depressão e doenças crônicas: um estudo populacional. Rev Saude Publica. 2012;46(4):617-23. DOI:10.1590/S0034-89102012005000044 [ Links ]

8.  Castelo MS, Coelho-Filho JM, Carvalho AF, Lima JWO, Noleto JCS, Ribeiro KG, et al. Validity of the Brazilian version of the Geriatric Depression Scale (GDS) among primary care patients. Int Psychogeriatr. 2010;22(1):109-13. DOI:10.1017/S1041610209991219 [ Links ]

9.  Ciulla L, Nogueira EL, Silva Filho IG, Tres GL, Engroff P, Ciulla V, et al. Suicide risk in the elderly: data from Brazilian public health care program. J Affect Disord. 2014;152-154:513-6. DOI:10.1016/j.jad.2013.05.090 [ Links ]

10.  Diniz BS, Butters MA, Albert SM, Dew MA, Reynolds 3rd CF. Late-life depression and risk of vascular dementia and Alzheimer’s disease: systematic review and meta-analysis of community-based cohort studies. Br J Psychiatry. 2013;202(5):329-35. DOI:10.1192/bjp.bp.112.118307 [ Links ]

11.  Ferrari JF, Dalacorte RR. Uso da Escada de Depressão Geriátrica de Yesavage para avaliar a prevalência de depressão em idosos hospitalizados. Sci Med (Porto Alegre). 2007;17(1):3-8. [ Links ]

12.  Gao Y, Huang C, Zhao K, Ma L, Qiu X, Zhang L, et al. Depression as a risk factor for dementia and mild cognitive impairment: a meta-analysis of longitudinal studies. Int J Geriatr Psychiatry. 2013;28(5):441-9. DOI:10.1002/gps.3845 [ Links ]

13.  Gazalle FK, Hallal PC, Lima MS. Depressão na população idosa: os médicos estão investigando? Rev Bras Psiquiatr. 2004;26(3):145-9. DOI:10.1590/S1516-44462004000300003 [ Links ]

14.  Grinberg LP. Depressão em idosos: desafios no diagnóstico e tratamento. RBM Rev Bras Med. 2006;63(7):317-30. [ Links ]

15.  Huerta-Ramírez R, Bertsch J, Cabello M, Roca M, Haro JM, Ayuso-Mateos JL. Diagnosis delay in first episodes of major depression: a study of primary care patients in Spain. J Affect Disord. 2013;150(3):1247-50. DOI:10.1016/j.jad.2013.06.009 [ Links ]

16.  Maciel ACC, Guerra RO. Prevalência e fatores associados à sintomatologia depressiva em idosos residentes no Nordeste do Brasil. J Bras Psiquiatr. 2006;55(1):26-33. DOI:10.1590/S0047-20852006000100004 [ Links ]

17.  Mitchell AJ, Bird V, Rizzo M, Meader N. Diagnostic validity and added value of the Geriatric Depression Scale for depression in primary care: a meta-analysis of GDS30 and GDS15. J Affect Disord. 2010;125(1-3):10-7. DOI:10.1016/j.jad.2009.08.019 [ Links ]

18.  Paradela EMP, Lourenço RA, Veras RP. Validação da escala de depressão geriátrica em um ambulatório geral. Rev Saude Publica. 2005;39(6):918-23. DOI:10.1590/S0034-89102005000600008 [ Links ]

19.  Park M, Unützer J. Geriatric depression in primary care. Psychiatr Clin North Am. 2011;34(2):469-87. DOI:10.1016/j.psc.2011.02.009 [ Links ]

20.  Salazar A, Dueñas M, Mico JA, Ojeda B, Agüera-Ortiz L, Cervilla JA, et al. Undiagnosed mood disorders and sleep disturbances in primary care patients with chronic musculoskeletal pain. Pain Med. 2013;14(9):1416-25. DOI:10.1111/pme.12165 [ Links ]

21.  Smith DJ, Griffiths E, Kelly M, Hood K, Craddock N, Simpson SA. Unrecognised bipolar disorder in primary care patients with depression. Br J Psychiatry. 2011;199(1):49-56. DOI:10.1192/bjp.bp.110.083840 [ Links ]

a Ministério da Saúde, Secretaria de Atenção à Saúde, Departamento de Atenção Básica. Envelhecimento e saúde da pessoa idosa. Brasília (DF); 2006. (Cadernos de Atenção Básica, 19) (Série A. Normas e Manuais Técnicos).

b Secretaria de Direitos Humanos: Coordenação Geral dos Direitos do Idoso. Dados sobre o envelhecimento no Brasil. (2011). Available from:

c World Health Organization. Global burden of mental disorders and the need for a comprehensive, coordinated response from health and social sectors at the country level: report by the Secretariat. Geneva; 2011 [cited 2013 Nov 2]. Available from:

d Castelo MS. Validade da Escala de Depressão Geriátrica em unidades primárias de saúde na cidade de Fortaleza, Ceará [dissertation]. Fortaleza: Faculdade de Medicina da Universidade Federal do Ceará; 2004.

e Carvalho JMA. Prevalência de sintomas depressivos em uma população de idosos usuários de serviços públicos de saúde [dissertation]. Rio de Janeiro: Instituto de Medicina Social da Universidade do Estado do Rio de Janeiro; 2010.

f Pereira SP. Prevalência de depressão na população idosa de Itajaí (SC): relação com variáveis biopsicossociais [end of course project]. Itajaí: Curso de Psicologia da Universidade do Vale do Itajaí; 2005.

Received: November 27, 2012; Accepted: January 21, 2014

Correspondence: Eduardo Lopes Nogueira Hospital São Lucas Ambulatório de Psiquiatria - PUCRS Av. Ipiranga, 6690 Prédio 60 3o andar Sala 309 90610-000 Porto Alegre, RS, Brasil E-mail:

The authors declare that there is no conflict of interest.

Creative Commons License This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.