Download Report

RESEARCH ARTICLE
Clinical and sociodemographic factors in a sample of older
subjects experiencing depressive symptoms
Ricardo Barcelos-Ferreira1, Marcos A. Lopes2, Eduardo Yoshio Nakano3, David C. Steffens4
and Cássio M. C. Bottino1
1
Old Age Research Group (Proter), Institute of Psychiatry, University of Sao Paulo Medical School, Brazil
Department of Internal Medicine, Federal University of Santa Catarina, Brazil
3
Department of Statistics, University of Brasilia, Brazil
4
Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, USA
Correspondence to: Dr. R. Barcelos-Ferreira, E-mail: barcelosfr@usp.br
2
Objectives: This study aims to determine the frequency of clinically signiﬁcant depressive symptoms (CSDS)
in a community sample of older Brazilians and to examine their relationship with sociodemographic
factors, cognitive and functional impairment (CFI), and medical illness.
Methods: A total of 1145 subjects aged 60 years or older living in the City of Ribeirao Preto, State of
Sao Paulo, Brazil, were interviewed. The following instruments were used: a 10-item scale for screening
of depressive symptoms in older people, the mini mental state examination, the Fuld Object Memory
Evaluation, the Informant Questionnaire on Cognitive Decline in the Elderly, the Bayer Activities of
Daily Living Scale, and a sociodemographic and clinical questionnaire.
Results: The frequency of CSDS was 15.7%. Logistic regression analysis indicated that being previously
depressed, having CFI, having lower level of education, using psychotropics, and not engaging in physical
exercise were related to CSDS. On the other hand, being a woman, older, medically ill, employed, or
married was not associated with CSDS.
Conclusions: Consistent with previous reports, lower education, lack of physical activity, and CFI were
signiﬁcantly associated with higher frequencies of CSDS. Further investigations are necessary to clarify
the occurrence of depression and possible modiﬁable factors in developing countries such as Brazil.
Copyright # 2011 John Wiley & Sons, Ltd.
Key words: epidemiology; prevalence; depressive symptoms; elderly; cognitive and functional impairment; Alzheimer’s disease
History: Received 6 June 2011; Accepted 31 August 2011; Published online 12 October 2011 in Wiley Online Library
(wileyonlinelibrary.com).
DOI: 10.1002/gps.2803
Introduction
Previous studies have reported that among older people,
the presence of signiﬁcant depressive symptoms that do
not meet the diagnostic criteria for minor depression
or dysthymia according to DSM-IV (APA, 1994) may
nevertheless adversely impact the quality of life (Penninx
et al., 2007; Barcelos-Ferreira et al., 2009). Such
subsyndromal symptoms are more frequent in the
older population and are associated with an increased
risk for major depression, physical disability, clinical
disease, and high rates of use of health services.
A review of prevalence studies of depressive symptoms in older people has shown values ranging from
13.5% to 16% among community-dwelling population
Copyright # 2011 John Wiley & Sons, Ltd.
and hospitalized patients, respectively (Beekman et al.,
1999; Katon, 2003). In addition, a recent longitudinal
study carried on by Dozeman et al. (2010) found that
after 18 months, the incidence rate of all clinically relevant symptoms of depression was a surprisingly high
48% and that such clinically signiﬁcant depressive
symptoms (CSDS) decreased the quality of life and
were associated with excess morbidity and mortality
in older adults. Others have found that CSDS also
confer a higher risk of developing a major depressive
disorder and dysthymia (Cuijpers and Smit, 2004;
Cuijpers et al., 2006; Lyness, 2008). The objective of
this study was to present the frequency of CSDS in a
community sample of older people (≥60 years), living
in the city of Ribeirao Preto, in the southeast region
Int J Geriatr Psychiatry 2012; 27: 924–930.
Older subjects experiencing depressive symptoms
of Brazil, and to investigate possible associated factors
such as cognitive and functional impairment (CFI),
history of clinical diseases, and sociodemographic
variables. Consistent with a prior meta-analysis of
depressive morbidity in older community-dwelling
adults in Brazil (Barcelos-Ferreira et al., 2010), we
hypothesized that the female gender, the presence of
cardiovascular disease, and the lack of physical exercise
would be associated with higher prevalence of CSDS.
Methods
Sample selection
Participants lived in Ribeirao Preto, an urban city located
in southeast Brazil, in one of the most developed
regions of the country, with a population of 583,842
people (FIBGE, 2010), of whom 54,633 (9.3%) were
60 years old or older. A cluster sampling of a population of individuals aged 60 years and older from three
different socioeconomic classes (upper, middle, and
low) was carried out. This strategy was an attempt to
ensure that the population sample would be representative of the city’s different socioeconomic classes. To
that end, “Fundacao Instituto Brasileiro de Geograﬁa
e Estatística” (FIBGE, 2000) data were used (FIBGE,
1991, 1996). The population’s sample size was calculated
by Epi-Info-5.1 software (Dean, 1990) and resulted in
1110 older individuals. The original parameters were
estimated for a dementia prevalence study and have
previously been reported by our group (Lopes et al.,
2007). These parameters were based on a previous
Brazilian study on dementia: 7% rate, sampling accuracy
or error (d) of 1.5%, and 95% conﬁdence interval
(Herrera et al., 2002).
Assessment
The following instruments were used in this study: the
mini mental state examination (Folstein et al., 1975;
Brucki et al., 2003) and the Fuld Object Memory Evaluation (Fuld et al., 1990) were administered to the older
subjects; the Informant Questionnaire on Cognitive
Decline in the Elderly (Perroco et al., 2009) and the
Bayer Activities of Daily Living scale (Folquitto et al.,
2007) were administered to the informants. On the
basis of a previous study (Bottino et al., 2009), these
instruments were combined to classify subjects with CFI.
The following tools were also administered: sociodemographic questionnaire; clinical inventory; inventory
of previous personal history and habits; inventory of
previous family information; survey on the use of health
Copyright # 2011 John Wiley & Sons, Ltd.
925
care services; inventory of instrumental and physical
activities; and socioeconomic classiﬁcation scale (including ﬁve decreasing levels of classiﬁcation from A to E),
using the questionnaire of the Brazilian Association
of Institutes of Market Research (ABIPEME, 2000).
A 10-item instrument, the D-10, with scores from 0
to 10, was administered for the evaluation of depressive symptoms in the older patients. Questions were
related to the presence of symptoms most of the
time during the past 2 weeks, and the participants
chose YES or NO as an answer. Six of the items were
based on items from the Geriatric Depression Scale
(GDS-30; satisfaction with life, boredom, hopelessness, worthlessness, preference to stay at home, and
excessive concerns); and one item was obtained from
the Center for Epidemiologic Studies Depression Scale
(concerning sleep disorders) (Batistoni et al., 2007).
Three additional items were assigned through a consensus of the study team composed of psychiatrists and neurologists with clinical experience caring for depressed
older Brazilians. They chose three symptoms (feeling little enjoyment, weight loss, and irritability) that their clients also frequently complained of. Furthermore, the
D-10 scale was validated in a sample of 62 depressed
older Brazilian outpatients diagnosed according to
DSM-IV criteria, with a mean score of 7 points. The scale
showed internal consistency measured by a Cronbach’s
alpha of 0.82 and high agreement with the GDS-5 in
the community sample (rs_0.85, p _ 0.001). Considering
the DSM-IV as a gold standard, and 7 points as a cutoff
score, this new scale had sensitivity of 72.7%, speciﬁcity
of 100%, positive predictive value of 100%, a negative
predictive value of 75.7%, and an accuracy of 85.2%
(Barczak, 2010). Data were collected by interviewers
trained to apply the protocol described. The investigation was approved by the local ethics committee, and
all the subjects and their relatives agreed to participate
in the study by providing signed informed consent.
Statistical analysis
The statistical analysis was performed using the Complex Samples module of Statistical Package for Social
Sciences (Field, 2000) for Windows, version 14.0. To
address the nonresponse effect, we calculated a probability by dividing the number of older subjects interviewed in each sector by the number of older subjects
selected in each sector. The inverse of this probability
was the weight to account for the nonresponse effect.
The global weight was calculated by multiplying the
weight for the nonresponse by the weight for the cluster
sampling.
Int J Geriatr Psychiatry 2012; 27: 924–930.
R. Barcelos-Ferreira et al.
926
The statistical analysis was based on frequencies
of CSDS and the odds ratio estimated by univariate
and multivariate logistic regression. In the univariate
analysis, the factors associated with the presence
of CSDS (D-10 ≥ 7) were analyzed individually.
The initial multivariate model included all variables
in the study, and persons with low average score for
the depression scale were taken as the reference
category. In the ﬁnal model, only the variables that
maintained an association with this syndrome at a level
of 0.10 or less were retained, and we considered here
the Wald’s Backward criterion of variable selection.
The association between these symptoms and the
variables gender, age, skin color, or apparent ethnicity
(according to the interviewer’s observation, following
the classiﬁcation of the Brazilian Institute of Geography
and Statistics [IBGE, 2000]), marital status, educational
level, social class, occupation, employment, smoking,
alcohol problems, diabetes mellitus, hypertension,
use of psychotropics (any kind of psychotropics,
including antidepressants, mood stabilizers, antipsychotics, benzodiazepines, and hypnotics), physical
exercise, CFI, previous depressive episode (PDE),
stroke, and acute myocardial infarction were assessed.
Results
A sample of 1828 subjects was approached, of which
1145 agreed to participate (refusal rate: 37.3%). Those
who refused were more likely to be women, age
80 years or older, white, engaged in household chores
as an occupation, have 1 to 4 years of schooling. They
were also more likely to report on clinical comorbidities,
have CFI, and lack CSDS. The instruments for the
detection of CFI were applied to older individuals
distributed in three socioeconomic levels in the following fashion: upper class: 369 subjects (32.2% of the total
sample); middle class: 439 subjects (38.3%); lower class:
332 subjects (29%); data lacked for ﬁve subjects.
The sample showed a mean age of 70.9 years (60–100;
SD = 7.7) and was mostly composed of women and
married individuals who had attended school up to
4 years (Table 1).
The weighted frequency of CSDS was 15.7% (95%
CI; 13.5–18.1%). An examination of isolated symptoms
showed that the most frequent symptom was “Has
been worried most of the time lately?” and the least frequent symptom was “feeling hopeless”. Five depressive
symptoms presented frequencies higher than 35%.
The univariate and multivariate analyses were
accomplished, and the missing data ranged from
0.02% to 0.3%. The presence of CSDS (D 10 ≥ 7)
was deﬁned as a dependent variable, and the
Copyright # 2011 John Wiley & Sons, Ltd.
Table 1 Total sample and its distribution in relation to sociodemographic
characteristics
Variables
Age range
60–64
65–69
70–74
75–79
80–84
85–89
≥90
Missing
Sex
Male
Female
Marital status
Single
Married
Separated
Widowed
Missing
Education
0 (illiterate)
1–4
5–8
≥9
Missing
Social class (ABIPEME†)
A
B
C
D
E
Missing
†
N = 1145
%
269
272
251
170
102
40
21
23.7
23.8
21.9
14.8
8.9
3.5
1.8
0.5
419
726
36.6
63.4
90
660
64
315
11
7.9
57.6
5.6
27.5
1.0
116
489
108
415
10.1
42.7
9.4
36.2
0.5
123
383
346
203
72
13
10.7
33.4
30.2
17.7
6.3
1.1
ABIPEME: Brazilian Association of Market Research.
associated factors were considered as independent
variables. The mini mental state examination mean
score of the sample (N = 1145) was 25.3 (SD = 5.0).
To simplify the cognitive and functional evaluation,
we included only the CFI construct in the analyses.
First, we performed a univariate analysis with
weighted data that showed a higher frequency of CSDS
for female gender, occupation, PDE, stroke, use of
psychotropics, presence of CFI, and absence of physical
exercise. Patients with 1–4 and 5–8 years of schooling
and with no formal education presented higher
frequencies of CSDS when compared with those
reporting more than 12 years of schooling. Concerning
social class, only patients belonging to Classes C, D,
and E had higher frequencies of CSDS when compared
with those belonging to Class A. Skin color or apparent
ethnicity was not associated with CSDS (Table 2).
Among occupational categories, only “Household
chores” had higher frequencies of CSDS when compared
with the “Qualiﬁed work” category. Age, skin color, employment, and marital status were not associated with
CSDS. After the univariate analysis, the ﬁnal regression
model showed that PDE, 1–4 years of schooling and
Int J Geriatr Psychiatry 2012; 27: 924–930.
Older subjects experiencing depressive symptoms
927
Table 2 Univariate-weighted analysis of the association between (the
presence of) clinically signiﬁcant depressive symptoms (Dep ≥ 7) with
sociodemographic and clinical characteristics
Dep ≥ 7
Age group
60–64
42.2 (15.4%)
65–69
39.4 (15.1%)
70–74
29.4 (12.1%)
75–79
28.6 (15.9%)
≥ 80
35.7 (22.3%)
Gender
Male
39.1 (9.4%)
Female
137.1 (19.3%)
Skin color
White
134.6 (15.4%)
Brown
37.3 (18.7%)
Black
3.4 (8.3%)
Asian
0.9 (12.6%)
Occupation
Qualified work
69.1 (12.5%)
Manual work
28.9 (15.1%)
Household
75.7 (20.7%)
chores
Never had a job
1.5 (13.7%)
Educational level
Illiterate
34.6 (26.7%)
1–4
96.6 (18.9%)
5–8
14.3 (14.5%)
9–11
20.1 (10.2%)
≥12
10.5 (5.7%)
Social class
A
7.8 (7.4%)
B
42.9 (12.1%)
C
58.0 (16.5%)
D
51.2 (23.7%)
E
16.2 (17.9%)
Marital status
Married
88.7 (13.9%)
Separated
9.0 (14.2%)
Widowed
57.6 (18.0%)
Single
20.9 (21.8%)
Employment
No
81.0 (16.8%)
Yes
89.1 (14.3%)
CFI
No
115,8 (12,7%)
Yes
60,4 (28,5%)
Stroke
No
163.4 (15.3%)
Yes
12.8 (25.9%)
Acute myocardial infarction
No
164.1 (15.4%)
Yes
10.7 (20.5%)
Smoking
No
150.4 (15.3%)
Yes
25.7 (18.4%)
PDE
No
91.5 (10.9%)
Yes
79.8 (30.4%)
Psychotropic
No
92.5 (11.5%)
Yes
80.3 (26.1%)
Physical exercise
No
111.4 (21.1%)
Yes
64.7 (10.9%)
OR (95%CI)
p
1.000
0.97 (0.58–1.62)
0.75 (0.44–1.27)
1.04 (0.59–1.81)
1.57 (0.91–2.70)
0.912
0.290
0.901
0.102
1.000
2.30 (1.53–3.47)
0.000
1.000
1.27 (0.80–1.99)
0.50 (0.17–1.46)
0.79 (0.09–6.68)
0.307
0.202
0.831
1.000
1.25 (0.74–2.11)
1.84 (1.26–2.68)
0.404
0.002
1.11 (0.22–5.55)
0.895
6.05 (2.86–12.82)
3.88 (2.05–7.37)
2.82 (1.25–6.36)
1.89 (0.89–4.00)
1.000
0.000
0.000
0.013
0.095
1.000
1.74 (0.82–3.68)
2.48 (1.17–5.27)
3.90 (1.81–8.40)
2.73 (1.05–7.15)
0.150
0.018
0.001
0.040
1.000
1.03 (0.48–2.21)
1.36 (0.92–2.02)
1.73 (0.99–3.03)
0.948
0.126
0.055
1.000
0.82 (0.58–1.17)
0.280
1.000
2.75 (1.87–4.04)
0.000
1.000
1.93 (1.00–3.74)
0.050
1.000
1.42 (0.71–2.83)
0.326
1.000
1.24 (0.74–2.09)
0.412
1.000
3.58 (2.49–5.14)
0.000
1.000
2.72 (1.90–3.88)
0.000
1.000
0.45 (0.32–0.65)
0.000
(Continues)
Copyright # 2011 John Wiley & Sons, Ltd.
Table 2. (Continued)
Hypertension
No
Yes
Diabetes
No
Yes
Dep ≥ 7
OR (95%CI)
p
87.6 (14.5%)
86.4 (16.9%)
1.000
1.20 (0.85–1.70)
0.297
133.6 (14.6%)
38.3 (19.7%)
1.000
1.43 (0.94–2.18)
0.097
CFI, cognitive and functional impairment; PDE, previous depressive
episode. OR (95%CI): odds ratio estimated by univariate logistic
regression, comparing the weighted frequencies in each variable. In each
variable, the category with OR = 1.000 indicates the reference category.
no formal education, use of psychotropics, absence of
physical exercise, and presence of CFI were associated
with higher odds of CSDS. The variable Diabetes was
not signiﬁcant. The variables age, gender, skin color, occupation, social class, marital status, employment, stroke,
acute myocardial infarction, smoking, and hypertension
were not associated with the presence of CSDS (Table 3).
Discussion
The present data were obtained from a populationbased cross-sectional epidemiologic study performed
with older subjects (≥60 years), who lived in the city
of Ribeirao Preto, in southeast Brazil. The weighted
frequency of CSDS was 15.7%, and there was a significant association of the CSDS with CFI, psychotropic
use, educational level, physical exercise, and history
of previous depression. On the other hand, we found
that gender, ethnic differences, cardiovascular disease,
and diabetes were not associated with depressive
symptoms. The percentage of losses and refusals to
participate was signiﬁcant (37%) but similar to that
found in the literature in studies that assessed population samples of older subjects (Veras and Coutinho,
1991; Barcelos-Ferreira et al., 2009; Barcelos-Ferreira
et al., 2010). The sociodemographic and clinical characteristics of the subjects who refused to participate
were not signiﬁcantly different compared with the
subjects who participated in the study.
A recent meta-analysis developed by our group
(Barcelos-Ferreira et al., 2010) found prevalence of
CSDS varying between 13% and 39%, with a combined
prevalence of 26%. We believe that the lower frequencies of CSDS found in our study and in the Sao
Paulo’s study could be inﬂuenced by the use of same
depression screening instrument. The cutoff point of
the D-10 used seemed to provide a more speciﬁc
and less sensitive diagnostic screening, leading to a
lower prevalence of CSDS. In addition, methodological similarities between the studies of Sao Paulo and
Int J Geriatr Psychiatry 2012; 27: 924–930.
R. Barcelos-Ferreira et al.
928
Table 3 Final results of the multivariate weighted analysis of
sociodemographic and clinical characteristics associated to (the presence
of) depressive symptoms (Dep ≥ 7)
Educational level
Illiterate
1–4
5–8
9–11
≥12
CFI
No
Yes
PDE
No
Sim
Psychotropic
No
Yes
Physical exercise
No
Yes
Diabetes
No
Yes
OR (95%CI)
p
4.37 (1.94–9.87)
3.01 (1.54–5.85)
2.13 (0.89–5.05)
1.42 (0.65–3.12)
1.000
0.000
0.001
0.087
0.378
1.000
1.99 (1.28–3.09)
0.002
1.000
2.86 (1.89–4.31)
0.000
1.000
2.15 (1.42–3.24)
0.000
1.000
0.61 (0.41–0.90)
0.013
1.000
1.48 (0.94–2.36)
0.094
CFI, cognitive and functional impairment; PDE, previous depressive
episode. OR (95%CI): odds ratio estimated by multivariate logistic
regression. In each variable, the category with OR = 1.000 indicates
the reference category. Beyond these, the initial multivariate model
included age group, gender, skin color, occupation, social class, marital status, employment, Stroke, acute myocardial infarction, smoking, and hypertension.
Ribeirao Preto, such as sample size, sociodemographic
characteristics, and recalling instruments, could have
played a role to explain lower frequencies of CSDS.
We compared two of our group’s recent studies that
used the same methodology to evaluate CSDS and
associated factors in older community subjects (BarcelosFerreira et al., 2009; Barcelos-Ferreira et al., submitted);
and we found that in both of them, CFI, PDE,
and “psychotropic use” were associated with higher
prevalence of CSDS, whereas physical exercise seemed
to be a protective factor against depression. Results
from multivariate models differed by study, with gender
remaining signiﬁcant in the Sao Paulo study, and
education remaining signiﬁcant in the Ribeirao Preto
study. Many studies have suggested that schooling is a
possible protective factor against depressive symptoms
in the general population (Almeida et al., 1997; Gazalle
et al., 2004; Blay et al., 2007). Among the individual items
from the D-10 scale, we found that Has been worried
most of the time lately had high prevalence in Ribeirao
Preto (56.7%) and in Sao Paulo (62%). These results
reinforce the clinical importance of investigating anxiety
and other psychological symptoms in older patients, as
they are frequently comorbid with depressive symptoms
Copyright # 2011 John Wiley & Sons, Ltd.
(Blazer, 2003). As some factors, such as cardiovascular
diseases, neurologic diseases, and psychiatric disturbances,
are commonly associated with both mood disorders and
dementia, we expect that that could be a possible moderator of the relationship between cognitive decline and
depression in older people (Bottino et al., 2010).
Although the higher frequency of depression in
women is a common ﬁnding in Brazilian (BarcelosFerreira et al., 2010) and international (Cole and
Dendukuri, 2003) literature, in our sample, the association between CSDS and gender was not sustained
after the ﬁnal regression model. The consistent lack
of association between ethnic differences and depression prevalence found in previous studies with older
Brazilian community residents (Gazalle et al., 2004;
Blay et al., 2007; Barcelos-Ferreira et al., 2010) could
be explained by the country’s historical miscegenation
among several ethnic groups. Traditionally, people of
minority status tend to be lower socioeconomically
and are more likely to have CSDS. Others have shown
that socioeconomic status may inﬂuence the impact of
race on mental disease in older Brazilian population
(Blay et al., 2007). Regarding clinical general health,
depression has been associated with a decline in health
status and may increase the risk of cardiovascular
disease (Tsay and Chao, 2002; Yu et al., 2004; Bottino
et al., 2010; Park and Lee, 2011). In spite of this, in our
study, we found no signiﬁcant relationship between
cardiovascular disease and CSDS. Duarte and Rego
(2007), evaluating a sample of geriatric outpatients,
found that the amount of chronic diseases could be
a better predictor of depressive symptoms when
compared with the presence of cardiovascular diseases.
In addition, Oldehinkel et al. (2003) considered the
hypothesis that possible interactions between vascular
factors and stress life events could modify the occurrence of depression in older people.
There are several limitations of the study that
deserve comment. The psychiatric assessment was based
on a screening questionnaire rather than on a comprehensive psychiatric diagnostic interview. Although this
scale was validated in a sample of older Brazilian
subjects, it is entirely unknown how the D-10 performs
in those with cognitive impairment, as opposed to
those cognitively intact. Therefore, it is possible that
the instrument is not reliable in cognitively impaired
subjects. Another limitation is that our sample was
restricted only to community residents, deliberately
excluding persons in hospitals or nursing homes,
where the prevalence of CSDS or depression morbidity
and the associated factors are likely to be higher and
have worse consequences. Moreover, the widely differing cultural and socioeconomic backgrounds present
Int J Geriatr Psychiatry 2012; 27: 924–930.
Older subjects experiencing depressive symptoms
among Brazilians may not have been fully represented.
Thus, the ﬁndings in the study cannot be generalized
beyond the study population. Finally, given the crosssectional design of our study, some caution is
warranted regarding the interpretation of the associations. We cannot establish deﬁnitive temporal
relationships between the factors we examined and
our main outcomes.
In conclusion, our data come from a large sample
of community residents aged 60 years and older from
Ribeirao Preto, Sao Paulo, Brazil, which was evaluated
using standardized procedures. In agreement with the
literature, our controlled analysis indicated that older
community residents with CSDS were more likely to
use psychotropic medication, have greater cognitive
and functional disability, have PDE, do not practice
physical exercise, and have lower level of education.
On the other hand, being a woman, clinically sick,
older, employed, or married was not associated with
CSDS in our sample. As some factors associated
with depression are potentially modiﬁable, perhaps,
at minimally higher costs, strategies leading to the
reduction of depressive symptoms should reduce
the levels of morbidity in older subjects. Further
investigations, including additional cross-national
comparison studies that will examine the role of gender, socioeconomic class, lifestyle, and employment,
are needed.
Key points
•
•
The prevalence of CSDS in this communitybased sample was 15.7%.
Previous depressive episode, 1–4 years of
schooling and no formal education, use of
psychotropics, absence of physical exercise,
and presence of CFI were associated with
higher odds of CSDS.
Conﬂict of interest
None declared.
References
ABIPEME. 2000. Criterio de Classiﬁcacao Economica Brasil [ABEP Website]. Dados
do Levantamento Socio Economico, IBOPE. Available at: http://www.abep.org/
codigosguias/ABEP_CCEB.pdf.
Almeida OP, Forlenza OV, Lima NK, et al. 1997. Psychiatric morbidity among the
elderly in a primary care setting: report from a survey in Sao Paulo, Brazil. Int J
Geriatr Psychiatry 12: 728–736.
American Psychiatric Association. 1994. Diagnostic and Statistical Manual of Mental
Disorders (4th ed. APA: Washington, DC.
Copyright # 2011 John Wiley & Sons, Ltd.
929
Barcelos-Ferreira R, Izbicki R, Steffens DC, Bottino CMC. 2010. Depressive
morbidity and gender in community-dwelling Brazilian elderly: systematic review
and meta-analysis. Int Psychogeriatr 22(5): 712–726.
Barcelos-Ferreira R, Junior JAP, Nakano EY, et al. 2009. Clinically signiﬁcant
depressive symptoms and associated factors in community elderly subjects from
Sao Paulo, Brazil. Am J Geriatr Psychiatry 17: 582–590.
Barczak DS. Validação de Escala para rastreamento de depressão em idosos:
importância de um teste de aplicação rápida. Banca de Qualiﬁcação do Mestrado
IPq/HC-FMUSP. São Paulo Nov 2010.
Batistoni SST, Neri AL, Cupertino APFBretas. 2007. Validade da escala de depressão
do Center for Epidemiological Studies entre idosos brasileiros. Rev. Saúde
Pública 41(4): 598–605. Available at: http://www.scielo.br/scielo.php?script=
sci_arttext&pid=S0034-89102007000400014&lng=pt. http://dx.doi.org/10.
1590/S0034-89102007000400014
Beekman AT, Copeland JR, Prince MJ. 1999. Review of community prevalence of
depression in later life. Br J Psychiatry 174: 307–311.
Blay S, Andreoli S, Fillenbaum G, et al. 2007. Depression morbidity in later life:
prevalence and correlates in a developing country. Am J Geriatr Psychiatry
15: 790–799.
Blazer DG. 2003. Depression in late life: review and commentary. J Gerontol A Biol Sci
Med Sci 58: 249–265.
Bottino CMC, Barcelos-Ferreira R, Ribeiz S, Alves TCTF, Busatto Filho G. 2010.
Aging-related depression: epidemiology, treatment and brain correlates. In
Neurociências Aplicada à Prática Clínica - SPPC Série da Pesquisa à Prática Clínica.
1ª ed. Busatto-Filho G (eds.). Atheneu: Sao Paulo; 177–190.
Bottino CM, Zevallos-Bustamante SE, Lopes MA, et al. 2009. Combined instruments
for the screening of dementia in older people with low education. Arq Neuropsiquiatr
67(2A): 185–190.
Brucki SMD, Nitrini R, Caramelli P, et al. 2003. Sugestoes para o uso do mini-exame
do estado mental no Brasil. Arq Neuro-Psiquiatr 61(3B): 777–781.
Cole MG, Dendukuri N. 2003. Risk factors for depression among elderly
community subjects: a systematic review and meta-analysis. Am J Psychiatry
160(6): 1147–1156.
Cuijpers P, Beekman A, Smit F, Deeg D. 2006. Predicting the onset of major
depressive disorder and dysthymia in older adults with subthreshold depression:
a community based study. Int J Geriatr Psychiatry 21(9): 811–818.
Cuijpers P, Smit F. 2004. Subthreshold depression as a risk indicator for major
depressive disorder: a systematic review of prospective studies. Acta Psychiatr Scand
109(5): 325–331.
Dean PJ. 1990. Using standards to improve performance. Aust J Educ Tech,
6(2): 75–91.
Dozeman E, van Marwijk HWJ, van Schaik DJF, et al. 2010. High incidence of
clinically relevant depressive symptoms in vulnerable persons of 75 years or older
living in the community, Aging Ment Health 14(7): 828–833.
Duarte MB, Rego MAV. 2007. Depression and clinical illness: comorbidity in a
geriatric outpatient clinic. Cad Saude Publica 23(3): 691–700.
FIBGE Censo Demograﬁco. 1991. Fundacao Instituto Brasileiro de Geograﬁa e Estatística. Available at: http://www.ibge.gov.br/home/estatistica/populacao/censodem/
default_censo1991.shtm.
FIBGE Censo Demograﬁco. 1996. Fundacao Instituto Brasileiro de Geograﬁa e Estatística.
Available at: http://www.ibge.gov.br/home/estatistica/populacao/contagem/default_
censo1996.shtm.
FIBGE Censo Demograﬁco. 2000. Fundacao Instituto Brasileiro de Geograﬁa e Estatística.
Available at: http://www.ibge.gov.br/home/estatistica/populacao/perﬁlidoso/
tabela1_2.s.
FIBGE Censo Demograﬁco. 2010. Fundacao Instituto Brasileiro de Geograﬁa e Estatística.
Available at: Available at: http://www.ibge.gov.br/home/estatistica/populacao/
censo2010/default.shtm.
Field A. 2000. Advanced techniques for the beginner: exploring data. In Discovering
Statistics using SPSS for Windows, Daniel BW (ed.). Sage Publications: University
of Sussex, London; 37–69.
Folquitto JC, Bustamante SE, Barros SB, et al. 2007. The Bayer: Activities of Daily
Living Scale (B-ADL) in the differentiation between mild to moderate dementia
and normal aging. Rev Bras Psiquiatr 29(4): 350–353.
Folstein MF, Folstein SE, Mchugh PR. 1975. Mini mental state: a practical
method for grading the cognitive state of patients for the clinician. J Psychiatr
Res 12: 189–198.
Fuld PA, Masur DM, Blau AD, et al. 1990. Object-memory evaluation for prospective
detection of dementia in normal functioning elderly: predictive and normative
data. J Clin Exp Neuropsychol 12: 520–528.
Gazalle FK, de Lima MS, Tavares BF, et al. 2004. Depressive symptoms and
associated factors in an elderly population in southern Brazil. Rev Saude
Publica 38: 365–371.
Katon WJ. 2003. Clinical and health services relationships between major
depression, depressive symptoms, and general medical illness. Biol Psychiatry
54: 216–226.
Lopes MA, Hototian SR, Bustamante SEZ, et al. 2007. Prevalence of cognitive
and functional impairment in a community sample in Ribeirao Preto, Brazil. Int
J Geriatr Psychiatry 22: 770–776.
Int J Geriatr Psychiatry 2012; 27: 924–930.
930
Lyness JM. 2008. Naturalistic outcomes of minor and subsyndromal depression in
older primary care patients. Int J Geriatr Psychiatry 23(8): 773–781.
Oldehinkel AJ, Ormel J, Brilman EI, van den Berg MD. 2003. Psychosocial and vascular
risk factors of depression in later life. J Affect Disord 74(3): 237–246.
Park JE, Lee JE. 2011. Cardiovascular disease risk factors and depression in Korean
women: results from the fourth Korean National Health and Nutrition Examination Survey. Psychiatry Res (in press, 2011). doi: 10.1016/j.psychres.2011.05.040
Penninx BW, Beekman AT, Bandinelli S, et al. 2007. Late-life depressive symptoms are
associated with both hyperactivity and hypoactivity of the hypothalamo-pituitaryadrenal axis. Am J Geriatr Psychiatry 15: 522–529.
Copyright # 2011 John Wiley & Sons, Ltd.
R. Barcelos-Ferreira et al.
Perroco TR, Bustamante SE, Moreno Mdel P, et al. 2009. Performance of Brazilian
long and short IQCODE on the screening of dementia in elderly people with
low education. Int Psychogeriatr 21(3): 531–538.
Tsay SL, Chao YF. 2002. Effects of perceived self-efﬁcacy and functional status on
depression in patients with chronic heart failure. J Nurs Res 10: 271–278.
Veras RP, Coutinho ESF. 1991. Prevalence of depression and organic cerebral
syndrome in the elderly population (Brazil). Rev Saude Publica 25: 209–217.
Yu DS, Lee DT, Woo J, Thompson DR. 2004. Correlates of psychological distress in elderly patients with congestive heart failure. J Psychosom Res 57:
573–581.
Int J Geriatr Psychiatry 2012; 27: 924–930.