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Journal of Affective Disorders 273 (2020) 291–297
Contents lists available at ScienceDirect
Journal of Affective Disorders
journal homepage: www.elsevier.com/locate/jad
Research paper
Depression in the Peruvian population and its associated factors: analysis of
a national health survey
T
⁎
Akram Hernández-Vásquez (MD)a,b, , Rodrigo Vargas-Fernández (MD)c,
Guido Bendezu-Quispe (MD)d, Leandro Nicolás Grendas (MD)e,f
a
Universidad Nacional Mayor de San Marcos. Lima, Peru
Universidad San Ignacio de Loyola, Vicerrectorado de Investigación, Centro de Excelencia en Investigaciones Económicas y Sociales en Salud. Lima, Peru
c
Universidad Científica del Sur. Lima, Peru
d
Universidad San Ignacio de Loyola, Vicerrectorado de Investigación, Unidad de Investigación para la Generación y Síntesis de Evidencias en Salud. Lima, Peru
e
Instituto de Farmacología, Facultad de Medicina. Universidad de Buenos Aires. Buenos Aires, Argentina
f
Hospital General de Agudos "T. Álvarez". Buenos Aires, Argentina
b
A R T I C LE I N FO
A B S T R A C T
Keywords:
Depression
Patient Health Questionnaire
Health Surveys
Cross-Sectional Studies
Peru
Background: : To date, the factors associated with the presence of depression or depressive symptoms in the
Peruvian population have not been described. This study aimed to determine the prevalence of clinically relevant depressive symptoms in the Peruvian population and its associated factors.
Methods: : A cross-sectional analytical study of secondary data from 2018 Demographic and Family Health
Survey was conducted. The survey database includes 31,996 participants over 18 years of age. The dependent
variable of the analysis was the presence of depression during the 14 days before the survey measured by the
Patient Health Questionnaire (PHQ-9). Factors associated with the presence of depression were estimated with a
proportional odds logistic regression model.
Results: : The overall prevalence of clinically relevant depressive symptoms was 6.4% (moderate and severe
symptomatology in 3.9% [95% CI: 3.6–4.3] and 2.5% [95% CI: 2.2–2.7], respectively). Being a woman, belonging to the age groups of 45 to 64 years or 65 or older, living in the Andean region, and having high blood
pressure or diabetes mellitus or some disability increased the probability of having clinically relevant depressive
symptoms.
Limitations: : The use of the PHQ-9 tool to assess depressive symptomatology limits the evaluation to a period of
two weeks before the survey, requiring further study for diagnosis confirmation.
Conclusion: : Six out of 100 Peruvians presented moderate to severe clinically relevant depressive symptoms in
2018. Strategies for depression should contemplate population subgroups , such as women and patients with
chronic diseases and disabilities.
1. Introduction
Major depressive disorder (MDD) is one of the public health problems with the most significant impact on the population, being among
the leading causes of disease burden (GBD 2017 Disease and Injury
Incidence and Prevalence Collaborators, 2018). Globally, more than
300 million people suffer from depression (4.4% of the world's population) (World Health Organization 2017), with an increase of 18.4%
having been reported in the number of people with depression between
2005 and 2015 (Vos et al., 2016). In 2018, depression rose to be the
most significant contributor to disability worldwide (7.5% of all years
lived with disabilities [YLD]) (World Health Organization 2017,
Vos et al., 2016) after having been in third place in 2017 (GBD 2017
Disease and Injury Incidence and Prevalence Collaborators, 2018).
Moreover, depression is the main factor associated with suicide, a
health problem that causes around 800,000 deaths per year
(World Health Organization 2017).
In Peru, neuropsychiatric diseases occupy first place in the burden
of disease (Ministerio de Salud 2018). Among mental health problems,
MDD has the highest burden of disease with 224,535 disability-adjusted
life years (DALYs) (3.9% of the total), which is equivalent to 7.5 years
lost per 1,000 inhabitants (Ministerio de Salud, 2018). Given this
⁎
Corresponding author at: 501 La Fontana Av, La Molina 00012, Lima, Peru.
E-mail addresses: [email protected] (A. Hernández-Vásquez), [email protected] (R. Vargas-Fernández),
[email protected] (G. Bendezu-Quispe), [email protected] (L.N. Grendas).
https://doi.org/10.1016/j.jad.2020.03.100
Received 7 October 2019; Received in revised form 29 January 2020; Accepted 28 March 2020
Available online 12 May 2020
0165-0327/ © 2020 Elsevier B.V. All rights reserved.
Journal of Affective Disorders 273 (2020) 291–297
A. Hernández-Vásquez, et al.
about non-communicable diseases, including information about mental
health. The data used for this study proceeds from the third form.
Further information on the objectives, collection, and processing of
ENDES data is described at https:///bit.ly/2lOgEaB.
scenario, the Ministry of Health of Peru has proposed the inclusion of
mental health as a research priority in the country over the period from
2019 to 2023. This proposal includes promoting and supporting studies
aimed at assessing the state of mental health in the Peruvian population
as well as the factors associated with various mental health problems,
including depression (Ministerio de Salud, 2019).
The biomedical literature has described several factors associated
with the development of MDD, including sex and socioeconomic factors
(Lorant et al., 2007, Cole and Dendukuri, 2003). However, studies are
required at a local level because each area can have specific sociodemographic factors that have an impact on the prevalence of mental
illness (Ferrari et al., 2013, Weissman et al., 1996). Demographic
Health Surveys (DHS) are useful to study the state of diseases in the
population.
Since 1986, the National Institute of Statistics and Informatics (INEI
by its acronym in Spanish) in Peru has carried out the Demographic and
Family Health Survey (ENDES by its acronym in Spanish), allowing the
study of various health problems in the Peruvian population (Instituto
Nacional de Estadística e Informática, 2019; Instituto Nacional de
Estadística e Informática, 2019). ENDES has been collecting data to
assess the mental health status of the Peruvian population since 2014,
and while depression is reported to be at the top of disease load, the
factors associated with the presence of depression or depressive
symptoms in the Peruvian population have not been described. Some
symptoms scales such as the PHQ-9 questionnaire are used for
screening and severity assessment of depressive symptoms
(Calderón et al., 2012, Villarreal-Zegarra et al., 2019). ENDES survey
measures PHQ-9 questionnaire to evaluate the presence of clinically
relevant depressive symptoms in the Peruvian population.
2.2. Variables and measurements
The dependent variable of the analysis was the presence of clinically
relevant depressive symptoms during the 14 days before the survey,
measured by the Patient Health Questionnaire (PHQ-9). PHQ-9 is a
screening instrument for depression that has been validated in many
countries, including Peru through expert judgment (Calderón et al.,
2012). PHQ-9 was also been validated for reliable comparisons according sociodemographic characteristics in Peruvian population
(Villarreal-Zegarra et al., 2019). The usefulness of this instrument is not
only based on the diagnosis of depression but also on the evaluation of
the severity of the condition, which facilitates patient monitoring.
Symptoms scales such as the PHQ-9 questionnaire have shown acceptable validity and reliability for both screening and severity assessment of depressive symptoms, and have high internal consistency
and satisfactory convergent validity with other diagnostic tools such as
the BDI-II scale (Urtasun et al., 2019). PHQ-9 contains nine questions
that assess the presence of depressive symptoms. The PHQ-9 scale was
validated for use in the general population (Kocalevent et al., 2013).
The responses measure severity, ranging from 0 (not at all) to 3 (nearly
every day) with a total score of 0 to 27 points. This score is classified
into five categories: minimum (0-4), mild (5-9), moderate (10-14),
moderately severe (15-19), and severe (20-27). For this study, three
categories were used to categorize the dependent variable based on the
score of the instrument: 0-9, 10-14, and 15 or more considering a cut
point of 10 points to determine the presence of clinically relevant depressive symptoms. It should be noted that this cut point maximizes the
sensitivity and specificity of the instrument reported for Latin American
countries (Urtasun et al., 2019; Munhoz et al., 2016) and the rest of the
world (Manea et al., 2017).
The independent variables of the study were: sex (male / female),
age groups (18-24 / 25-44 / 45-64 / 65 or more), civil status (unmarried / married or cohabiting / widower, divorced or separated),
level of education (no formal schooling or initial level / primary /
secondary / upper), economic welfare quintile (I / II / III / IV / V; from
lowest to highest quintile), geographical domain (Metropolitan Lima /
Rest of Coast / Andean / Amazon), health insurance (yes / no), current
smoker, defined as a person who has smoked cigarettes in the last 30
days to the present (yes / no), binge drinking, defined as having five or
more alcoholic drinks for males or four or more alcoholic drinks for
females on the same occasion on at least one day in the past month.
High blood pressure, defined as the average systolic blood pressure
(two readings) 140 mmHg or diastolic blood pressure 90 mmHg (yes /
no), history of diabetes, defined by self-reporting of having diabetes
(diagnosed by a doctor) or defined by automated diagnosis of diabetes
mellitus by a doctor (yes / no), obesity was defined as a body mass
index of 30 kg/m2 (yes / no), presence of limitations (without limitations / with one or more limitations), area of residence (rural / urban),
and consumption of five or more portions of fruits and vegetables per
day (yes / no). According to previous literature, all of these variables
are factors associated with the presence of depression or clinically relevant depressive symptoms (Ferrari et al., 2013; Boden and
Fergusson, 2011; Bruce et al., 2003, da Silva et al., 2011; Foulds et al.,
2015; Alexopoulos, 2005; Saghafian et al., 2018; Wolniczak et al.,
2017; Anderson et al., 2001; Borges et al., 2019; Stagnaro et al., 2018).
1.1. Aims of the study
The aim of this study was to determine the prevalence of clinically
relevant depressive symptoms in the Peruvian population and its associated factors. The results will help to develop health strategies to
reduce the mental health burden in our country.
2. Materials and methods
2.1. Design and study population
We performed a secondary analysis of the ENDES survey 2018,
carried out by the INEI. ENDES is an annual survey conducted at a
national level, which provides information on fertility, mortality,
health, maternal and child health indicators and non-communicable
and communicable diseases in Peru. This survey involved a balanced,
two-stage, probabilistic, stratified, and independent sampling at the
departmental level and by urban and rural areas (Instituto Nacional de
Estadística e Informática, 2019; Instituto Nacional de Estadística e
Informática, 2019). This sampling method allows obtaining samples
with estimates of totals approximately equal to the characteristics of the
target population of the survey. It replicates the population structure
within the selected sample considering the age groups, sex, and other
variables.
The Peruvian territory is divided into 25 administrative regions and
into three natural regions, including the Coast (which borders the
Pacific Ocean), the Andes (which borders the Andes Mountains), and
the Amazonian (part of the Peruvian Amazon rainforest). The results
obtained from analysis of the annual ENDES data gives representative
estimates at the following levels: national (total Peruvian population),
urban and rural, natural region, and administrative regions (25 regions)
(Instituto Nacional de Estadística e Informática, 2019). In the ENDES
survey, there are three questionnaires i) a home questionnaire (for
homes and their members), ii) an individual woman questionnaire (for
all women of childbearing age), and iii) a health questionnaire (applied
to persons from 15 years of age or more), that collects information
2.3. Statistic analysis
Data analyses were performed using the statistical program Stata®
v14.2 (Stata Corporation, College Station, Texas, USA). For all statistical tests, a value of p<0.05 was considered as statistically significant.
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Journal of Affective Disorders 273 (2020) 291–297
A. Hernández-Vásquez, et al.
The sociodemographic characteristics of the study population were
described using absolute frequencies and weighted proportions. The
Chi-square test was used for the bivariate analysis among the variables
of interest.
Due to the ordinal nature of the dependent variable, an ordinal logistic model of proportional probabilities was estimated to determine
the factors associated with the presence of clinically relevant depressive
symptoms. Odds ratios were estimated along with their 95% confidence
intervals (95% CI). Before the application of an ordinal logistic model,
the assumption of parallelism must be met. For this purpose, the Brant
test was used, the results of which confirmed that the assumption of
proportional probabilities was not violated since it had a p value higher
than 0.05 in each of the variables.
On the other hand, all variables with a p value < 0.20 in the bivariate analysis were included in the generalized ordinal logistic model.
To assess collinearity, variance inflation factors (VIF) were used.
Multicollinearity among the variables was considered if the inflation
factor of the variance exceeded the value of 10.
of habits, 11.8% were current smokers, and 22.6% were binge drinkers.
Regarding their medical history, 21.3% had high blood pressure, 3.8%
had a history of diabetes, 25.9% were obese, and 2.2% had some disability. In terms of feeding patterns, 10.9% consumed five or more
fruits or vegetables daily (Table 1).
2.4. Ethical considerations
The ordinal logistic regression model found that factors such as
being female (OR=2.25, 95% CI: 1.93-2.63) and individuals belonging
to the age groups of 45-64 years (OR=1.76, 95% CI: 1.36-2.27) and 65
and older (OR=1.91, 95% CI: 1.34-2.72), living in the Andean region
(OR= 1.75, 95% CI: 1.46-2.09), having high blood pressure (OR=1.35,
95% CI: 1.14-1.60), a history of diabetes mellitus (OR=2.06, 95% CI:
1.49-2.84%), and a history of disability (OR=2.40, 95% CI: 1.65-3.49),
were more likely to have clinically relevant depressive symptoms. On
the other hand, being married/cohabiting (OR = 0.76, 95% CI: 0.600.96), having a secondary (OR = 0.72, 95% CI: 0.52-0.99) or a high
level of education (OR = 0.44, 95% CI: 0.31-0.63), belonging to good
economic welfare (quintile 3-5) and the consumption of 5 or more fruits
or vegetables (OR = 0.64, 95% CI: 0.47-0.87) were associated with a
lower probability of presenting clinically relevant depressive symptoms
(Table 3).
3.2. Prevalence and severity of clinically relevant depressive symptoms
The overall prevalence of clinically relevant depressive symptoms
was 6.4% (95% CI: 6.0-6.9). The prevalence of moderate clinically relevant depressive symptoms was 3.9% (95% CI: 3.6-4.3) and severe
clinically relevant depressive symptoms 2.5% (95% CI: 2.2-2.7).
Bivariate analysis showed an association among the depressive symptoms scores measured with the PHQ-9 and all the independent variables
included in the study except health insurance (p-value > 0.2), which
was not included in the regression model (Table 2).
3.3. Factors associated with clinically relevant depressive symptoms
This study did not require the approval of an ethics committee as it
was an analysis of secondary data that is in the public domain and does
not allow the identification of the participants evaluated. ENDES data
does not have any information to identify individuals that respond to
the survey. Hence, the confidentiality of the information of a person
participating in the survey is assured. The databases can be freely
downloaded on the INEI website (http://iinei.inei.gob.pe/microdatos/
).
3. Results
3.1. General characteristics of the sample
A total of 31,996 people were included (Fig. 1). The weighted
proportion of women was 51.3%. The mean age was 42.7 years (SD
0.17), ranging from 25-44 in 42.6% of the study population; 65.8%
were married or lived with their partner, and 34.7% had higher education. As for the area of residence, 37.8% lived in Metropolitan Lima,
80.7% lived in urban areas, and 72.6% had health insurance. In terms
4. Discussion
This study aimed to determine the prevalence of clinically relevant
depressive symptoms and its associated factors in the Peruvian population during 2018. Six out of every 100 Peruvians were found to have
Fig. 1. Flowchart of the selection of adults included in the study. ENDES2018.
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Journal of Affective Disorders 273 (2020) 291–297
A. Hernández-Vásquez, et al.
There are few studies on depression in the Latin American region
(Ferrari et al., 2013). Our findings on the prevalence of clinically relevant depressive symptoms in Peruvian population were slightly
higher than those reported in other countries of the region, such as
Argentina (3.8%) (Stagnaro et al., 2018) and Brazil (4.1%)
(Munhoz et al., 2016). However, it is not adequate to make conclusive
comparisons due to methodological differences between the studies and
because symptom scales, such as the one used in this study, estimate
higher values of depression prevalence compared to clinical structural
interviews (Ferrari et al., 2013). Hence, the slightly higher prevalence
found in this study may be related to the different instruments used to
measure depression. Data from the Global Burden of Diseases 2017
report indicate that depressive disorders rank third in the world
(Institute for Health Metrics and Evaluation (IHME) 2018) and seventh
in Peru (Institute for Health Metrics and Evaluation (IHME) 2020) as a
cause of disability. Similarly, the burden of disease caused by depression is of interest worldwide due to the loss of productivity generated
by the involvement of a significant proportion of the labor force
(Boden and Fergusson, 2011; Bruce et al., 2003). Considering that only
one third of patients with mental disorders in the region receive optimal
treatment for their medical condition (Borges et al., 2019), the impact
of these repeated findings on depression in the region makes it necessary to develop strategies to address the problem of depression and
reduce its burden. In this sense, both Peru and Latin America need to
improve access to the health system and the approach to primary
mental health care, as well as develop occupational health policies for
the population affected by this problem (World Health Organization,
2001).
Regarding sociodemographic variables, women were more likely to
have depression, with a ratio of 2:1, which is in accordance with previous studies (Markkula et al., 2015; Calvó-Perxas et al., 2015). This
result is in line with the global trend, and while mental health problems
affect and have shown an increase in both sexes, depression is more
prevalent in women (5.1%) than in men (3.6%) (World Health
Organization, 2017). From 1990 to 2007, the number of YLD attributable to depressive disorders increased by 32.2% in women, being the
third cause of YLD in 2007. During the period 2007-2017, the YLD
increased 14.1%, indicating that depression continues to be a significant problem for women (GBD 2017 Disease and Injury Incidence
and Prevalence Collaborators, 2018).
In terms of the distribution of depressive symptoms by age group,
the older the population, the more likely to have clinically relevant
depressive symptoms in Peru. Similarly, this result is in line with the
global picture, in which older adults have an increased prevalence of
depression compared to younger populations (World Health
Organization, 2017). It has been reported that the higher prevalence of
depression among the older adult population is associated with loneliness, being female, and the presence of comorbidities in this population (Cole and Dendukuri, 2003; Alexopoulos, 2005). Thus, women and
older adults are priority groups for the evaluation and development of
strategies against depression.
Being married/living together was found to be a protective factor
for the presence of clinically relevant depressive symptoms. This result
is consistent with previous studies in the region (Daray et al., 2017) and
the remaining western countries (Andrade et al., 2003). It was found
that belonging to good economic welfare (quintile 3-5) and having a
higher level of education are protective factors for depressive symptoms. These findings are in accordance with published data on factors
associated with socially disadvantaged populations, which are positively associated with depression (Fryers et al., 2003). Indeed, the
presence of depressive symptoms is influenced by regional socioeconomic determinants.
Regarding the place of residence, living in the Andean region was
associated with clinically relevant depressive symptoms. An epidemiological study carried out by the National Institute of Mental Health
reported that in 2008 depression was one of the most prevalent mental
Table 1
Description of the sample (n=31,996).
Characteristics
n
Weighted %%†
Sample size
Sex
Male
Female
Age groups, years
18–24
25–44
45–64
65 or more
Marital status
Never married
Married/Cohabiting
Separated/Divorced/Widowed
Education level
No formal schooling
Primary
Secondary
Higher
Wealth Index
Poorest
Poorer
Middle
Richer
Richest
Natural regions
Amazon
Andean
Rest of the Coast
Lima Metropolitan
Health insurance
No
Yes
Current smoker‡
No
Yes
Binge Drinking*
No
Yes
High blood pressure⁎⁎
No
Yes
Diabetes history
No
Yes
Obesity⁎⁎⁎
No
Yes
Impairment
None
1 or more
Area
Rural
Urban
Five or more fruits and vegetables
No
Yes
31,996
100
13,712
18,284
48.7 (47.8-49.5)
51.3 (50.5-52.2)
4,558
16,753
7,248
3,437
16.3
42.6
28.2
13.0
4,389
22,485
5,122
17.4 (16.7-18.2)
65.8 (64.9-66.6)
16.8 (16.2-17.5)
1,720
8,048
12,795
9,433
4.2 (3.9-4.5)
20.7 (20.0-21.3)
40.5 (39.6-41.3)
34.7 (33.8-35.5)
10,159
7,856
5,936
4,609
3,436
18.3
20.3
20.8
20.6
19.9
(17.8-18.9)
(19.6-21.1)
(20.1-21.6)
(19.8-21.4)
(19.1-20.8)
7,293
11,713
9,135
3,855
11.9
24.9
25.3
37.8
(11.4-12.6)
(24.0-25.9)
(24.5-26.2)
(36.9-38.7)
7,672
24,324
27.4 (26.6-28.3)
72.6 (71.7-73.4)
28,687
3,309
88.2 (87.6-88.8)
11.8 (11.2-12.4)
25,225
6,771
77.4 (76.7-78.2)
22.6 (21.8-23.3)
26,270
5,726
78.7 (77.9-79.4)
21.3 (20.6-22.1)
31,073
923
96.2 (95.8-96.5)
3.8 (3.5-4.2)
24,453
7,543
74.1 (73.3-75.0)
25.9 (25.0-26.7)
31,347
649
97.8 (97.5-98.1)
2.2 (1.9-2.5)
10,994
21,002
19.3 (18.8-19.8)
80.7 (80.2-81.2)
29,060
2,936
89.1 (88.5-89.6)
10.9 (10.4-11.5)
(15.6-17.0)
(41.7-43.4)
(27.3-29.1)
(12.4-13.6)
†
Estimates included weights and ENDES sample specifications.
If had smoked cigarettes in the last 30 days.
⁎
Five or more alcoholic drinks for males or four or more alcoholic drinks for
females on the same occasion on at least one day in the past month.
⁎⁎
Average systolic blood pressure (two readings) was ≥140 mmHg or the
diastolic blood pressure was ≥90 mmHg or if you had a previous diagnosis by a
doctor.
⁎⁎⁎
A body mass index ≥30 kg/m2.
‡
moderate to severe clinically relevant depressive symptoms (PHQ≥10)
within 14 days before the ENDES survey. Factors such as being a
woman, belonging to the age groups of 45 and 65 years old and older,
living in the Andean region, having high blood pressure, a history of
diabetes mellitus or some disability were associated with an increased
likelihood of clinically relevant depressive symptoms.
294
Journal of Affective Disorders 273 (2020) 291–297
A. Hernández-Vásquez, et al.
Table 2
Sample distribution of individuals according to PHQ-9 score, ENDES 2018.
PHQ-9 score†
Characteristics
Sample size
Sex
Male
Female
Age groups, years
18–24
25–44
45–64
65 or more
Marital status
Never married
Married/Cohabiting
Separated/Divorced/Widowed
Education level
No formal schooling
Primary
Secondary
Higher
Wealth Index
Poorest
Poorer
Middle
Richer
Richest
Natural regions
Amazon
Andean
Rest of the Coast
Lima Metropolitan
Health insurance
No
Yes
Current smoker*
No
Yes
Binge drinking⁎⁎¶
No
Yes
High blood pressure⁎⁎⁎
No
Yes
Diabetes history
No
Yes
Obesity⁎⁎⁎⁎
No
Yes
Impairment
None
1 or more
Area
Rural
Urban
Five or more fruits and vegetables
No
Yes
0-9
Weighted % (95% CI)
10-14
Weighted % (95% CI)
15-27
Weighted % (95% CI)
93.6 (93.2-94.0)
3.9 (3.6-4.3)
2.5 (2.2-2.7)
96.1 (95.6-96.6)
91.2 (90.5-91.9)
2.7 (2.3-3.1)
5.1 (4.6-5.7)
1.2 (1.0-1.5)
3.7 (3.2-4.1)
<0.001
96.2
95.9
91.8
86.8
2.4
2.7
5.1
7.2
1.4
1.4
3.1
6.0
(0.9-2.0)
(1.1-1.6)
(2.6-3.7)
(4.9-7.3)
<0.001
(95.3-96.9)
(95.5-96.3)
(90.8-92.6)
(84.7-88.7)
(1.9-3.1)
(2.4-3.1)
(4.4-5.9)
(5.8-8.9)
P value‡
95.4 (94.4-96.2)
94.8 (94.4-95.3)
87.0 (85.4-88.4)
3.2 (2.6-4.1)
3.2 (2.9-3.6)
7.4 (6.3-8.7)
1.4 (1.0-2.0)
2.0 (1.7-2.2)
5.6 (4.7-6.7)
<0.001
80.7
89.7
94.1
96.9
(77.5-83.6)
(88.5-90.9)
(93.4-94.8)
(96.4-97.3)
10.0 (7.8-12.7)
5.8 (5.0-6.7)
3.9 (3.4-4.5)
2.1 (1.7-2.5)
9.3
4.5
1.9
1.1
(7.4-11.6)
(3.8-5.2)
(1.6-2.3)
(0.8-1.4)
<0.001
90.3
92.6
94.1
94.7
96.0
(89.4-91.2)
(91.6-93.5)
(93.0-95.0)
(93.6-95.6)
(94.9-96.9)
5.4
4.7
3.5
3.5
2.7
(4.8-6.1)
(3.9-5.6)
(2.8-4.2)
(2.8-4.4)
(2.1-3.6)
4.2
2.7
2.5
1.8
1.3
(3.7-4.8)
(2.2-3.3)
(1.9-3.2)
(1.3-2.5)
(0.8-1.9)
<0.001
94.4
90.6
94.4
94.8
(93.7-95.1)
(89.8-91.4)
(93.7-95.0)
(93.7-95.7)
3.5
5.4
3.5
3.4
(3.0-4.1)
(4.8-6.0)
(3.0-4.0)
(2.7-4.2)
2.0
4.0
2.1
1.8
(1.6-2.5)
(3.5-4.5)
(1.8-2.6)
(1.3-2.4)
<0.001
94.1 (93.1-94.9)
93.4 (92.9-93.9)
3.8 (3.2-4.7)
4.0 (3.6-4.4)
2.1 (1.7-2.6)
2.6 (2.3-2.9)
0.211
93.4 (92.9-93.9)
95.3 (94.0-96.3)
4.0 (3.7-4.4)
3.3 (2.4-4.4)
2.6 (2.3-2.9)
1.5 (1.0-2.2)
0.012
93.0 (92.5-93.5)
95.6 (94.8-96.2)
4.3 (3.9-4.7)
2.8 (2.3-3.4)
2.7 (2.4-3.0)
1.6 (1.3-2.1)
<0.001
94.7 (94.2-95.1)
89.8 (88.4-91.0)
3.4 (3.0-3.7)
6.0 (5.1-7.1)
2.0 (1.8-2.2)
4.2 (3.5-5.1)
<0.001
93.9 (93.5-94.4)
85.1 (81.3-88.2)
3.8 (3.5-4.1)
7.6 (5.5-10.5)
2.3 (2.0-2.5)
7.3 (5.0-10.4)
<0.001
93.9 (93.4-94.3)
92.9 (91.9-93.8)
3.8 (3.5-4.2)
4.3 (3.6-5.0)
2.3 (2.1-2.6)
2.8 (2.3-3.5)
0.140
93.9 (93.5-94.4)
78.8 (72.8-83.7)
3.8 (3.5-4.1)
10.5 (7.0-15.5)
2.3 (2.0-2.5)
10.7 (7.4-15.2)
<0.001
91.0 (90.1-91.8)
94.2 (93.7-94.7)
5.1 (4.5-5.7)
3.7 (3.3-4.1)
3.9 (3.5-4.5)
2.1 (1.8-2.4)
<0.001
93.3 (92.8-93.7)
96.3 (95.1-97.3)
4.1 (3.8-4.5)
2.4 (1.6-3.5)
2.6 (2.3-2.9)
1.3 (0.8-1.9)
<0.001
†
P value was obtained using x2 test statistics.
Estimates included weights and ENDES sample specifications.
⁎
If had smoked cigarettes in the last 30 days.
⁎⁎
Five or more alcoholic drinks for males or four or more alcoholic drinks for females on the same occasion on at least one day in the past month.
⁎⁎⁎
Average systolic blood pressure (two readings) was ≥140 mmHg or the diastolic blood pressure was ≥90 mmHg or if you had a previous diagnosis by a doctor.
⁎⁎⁎⁎
A body mass index ≥30 kg/m2
PHQ-9: Patient Health Questionnaire.
‡
political violence (present in Peru from the 1980s to 2000) which have
been described as being associated with mental health problems in the
population of Latin America (Borges et al., 2019) and the Andean region of Peru (Zevallos-Bustamante, 2016; Mendoza-Amaya and
Saavedra-Castillo, 2012). Moreover, in recent years, depression has
health problems in the population of the Peruvian rural highlands.
Moreover, 20% of the population living in this area did not consider
depression to be a health problem (Instituto Nacional de Salud Mental,
2009). This might be explained by factors such as difficult accessibility
to treatment, rurality, language barriers and experiences or history of
295
Journal of Affective Disorders 273 (2020) 291–297
A. Hernández-Vásquez, et al.
clinically relevant depressive symptoms was found in individuals with a
history of diabetes, in accordance with what has been reported in
previous studies (Cannon et al., 2018). Diabetes and depression are
widely distributed diseases throughout the world, and the presence of
diabetes doubles the probability of developing depression compared to
subjects without diabetes (Wolniczak et al., 2017). Previous studies in
Peru have described a higher frequency of depression in people with
diabetes (Urrutia-Aliano and Segura, 2016). People with disabilities
were also more likely to have depression. Individuals with chronic
diseases and physical disabilities have a higher prevalence of depression than their peers without these health problems. It is also of note
that this association is higher in elderly patients, who usually present
some
physical
limitations
and
comorbidities
(Cole
and
Dendukuri, 2003; Bruce et al., 2003; da Silva et al., 2011; Arnow et al.,
2006), which could also explain a higher prevalence of depressive
symptoms in this population subgroup in our study.
Binge drinking was not found to be associated with a higher prevalence of clinically relevant depressive symptoms in the Peruvian
population. It has been reported that the association between alcohol
consumption and depression depends on the intensity of consumption,
and is mediated by alcohol abuse in young populations. However, this
relation was not found in this study. There are possible differences in
this association according to sex (Boden and Fergusson, 2011;
Caldwell et al., 2002). Since the association between these comorbidities is conditioned by the intensity of consumption, it has been reported that treatment for depression is effective independent of the
comorbidity (Foulds et al., 2015). In Peru, alcohol is more frequently
consumed by men, although there has been an increase in the consumption of alcohol by women with the changes taking place in cultural
conceptions (Ministerio de Salud, 2020). Since women have a higher
risk of developing depression, it is necessary to study the impact of this
factor on the development of depression in this population group.
Regarding the consumption of fruits and vegetables, an inversely
proportional association was found between this practice and depressive symptoms. This result is in line with various observational studies
that indicate that the consumption of fruits and vegetables decreases
the likelihood of developing depression, acting as a protective factor
(Saghafian et al., 2018). Previously, a study in Peru described that less
than 5% of Peruvians consumed five or more portions of fruit or vegetables daily, finding an inverse relationship between fruit consumption and the presence of depressive symptoms (Saghafian et al., 2018).
Thus, further studies are needed to determine the possibilities and
benefits of promoting the consumption of fruits and vegetables in the
Peruvian population and its impact on the development of depression.
Among the limitations of the study, it should be noted that the use
of secondary data poses challenges for the analysis of health problems
in the absence of some characteristics of the population that could
allow better characterization of the population, including the absence
of some data about mental health determinants. In addition, the use of
the PHQ-9 tool to assess clinically relevant depressive symptoms only
allows the mental health status of the population to be characterized
within a two week time before the interview as part of the survey data
collection, being unable to evaluate depressive symptoms in the population over a more extended period. Furthermore, it is possible the
non-precision of the data due to recall bias or inadequate understanding
of some survey questions. Despite this, the use of a database of national
representativeness facilitated the identification of factors associated
with the presence of depressive symptoms. These findings are useful
from the Peruvian and global perspective in order to promote the study
of depression and its related factors.
In conclusion, it was found that in 2018 the prevalence of moderate
to severe depressive symptoms in the Peruvian population was 6%. The
likelihood of developing clinically relevant depressive symptoms was
higher in females and individuals greater than 45 years of age, living in
the Andean region, having high blood pressure, having a history of
diabetes mellitus, and having a disability. The identification of factors
Table 3
Ordered logit model to examine the PHQ-9 score among Peruvian adults,
ENDES 2018.
Depression
Variable
Sex
Male
Female
Age groups, years
18–24
25–44
45–64
65 or more
Marital status
Never married
Married/Cohabiting
Separated/Divorced/Widowed
Education level
No formal schooling
Primary
Secondary
Higher
Wealth Index
Poorest
Poorer
Middle
Richer
Richest
Natural regions
Amazon
Andean
Rest of the Coast
Lima Metropolitan
Current smoker‡
No
Yes
Binge drinking*
No
Yes
High blood pressure⁎⁎
No
Yes
Diabetes history
No
Yes
Obesity⁎⁎⁎
No
Yes
Impairment
None
1 or more
Area
Rural
Urban
Five or more fruits and vegetables
No
Yes
OR
(95% CI)†
P value†
Ref.
2.25
(1.93-2.63)
<0.001
Ref.
1.12
1.76
1.91
(0.88-1.42)
(1.36-2.27)
(1.34-2.72)
0.352
<0.001
<0.001
Ref.
0.76
1.28
(0.60-0.96)
(0.99-1.65)
0.019
0.062
Ref.
0.84
0.72
0.44
(0.65-1.08)
(0.52-0.99)
(0.31-0.63)
0.169
0.042
<0.001
Ref.
0.89
0.73
0.66
0.55
(0.73-1.09)
(0.56-0.96)
(0.49-0.91)
(0.38-0.78)
0.265
0.027
0.010
0.001
Ref.
1.75
1.16
1.23
(1.46-2.09)
(0.94-1.43)
(0.94-1.62)
<0.001
0.173
0.136
Ref.
1.18
(0.90-1.54)
0.228
Ref.
1.03
(0.85-1.24)
0.762
Ref.
1.35
(1.14-1.60)
<0.001
Ref.
2.06
(1.49-2.84)
<0.001
Ref.
1.08
(0.91-1.29)
0.390
Ref.
2.40
(1.65-3.49)
<0.001
Ref.
1.15
(0.95-1.39)
0.158
Ref.
0.64
(0.47-0.87)
0.004
†
Estimates included weights and ENDES sample specifications.
If had smoked cigarettes in the last 30 days.
⁎
Five or more alcoholic drinks for males or four or more alcoholic drinks for
females on the same occasion on at least one day in the past month.
⁎⁎
Average systolic blood pressure (two readings) was ≥140 mmHg or the
diastolic blood pressure was ≥90 mmHg or if you had a previous diagnosis by a
doctor.
⁎⁎⁎
A body mass index ≥30 kg/m2
PHQ-9: Patient Health Questionnaire.
‡
been linked to living at high altitudes (Kious et al., 2018;
Ishikawa et al., 2016). Since people living in the Andean region are
exposed to prolonged hypoxia due to high altitude, it is possible that
this factor could be related to depression among this population.
However, it is necessary to further study this possible association in the
Andean population.
Regarding clinical variables, a greater probability of presenting
296
Journal of Affective Disorders 273 (2020) 291–297
A. Hernández-Vásquez, et al.
associated with the presence of depressive symptoms makes it possible
to determine the subgroups of the population who may be prioritized
for the implementation of strategies to address this important health
problem in Peru.
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Authors' contributions
AHV and RVF analyzed the data. GBQ and LNG were major contributors in writing the manuscript. All authors interpreted the results,
read and approved the final manuscript.
Funding
This research received no specific grant from any funding agency in
the public, commercial, or not-for-profit sectors.
Data availability
The databases used in this study are freely accessible and can be
downloaded from the website of the Instituto Nacional de Estadística e
Informática (http://iinei.inei.gob.pe/microdatos/).
Declaration of Competing interests
The authors declare that they have no competing interests.
Acknowledgments
To the National Institute of Statistics and Informatics (INEI) for the
publicly available data set used in this work.
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