Depressive symptomatology in women and association with socioeconomic, clinical, and behavioral characteristics

Abstract

Objective  To verify the prevalence of depression symptoms in women and their association with socioeconomic, clinical and behavioral characteristics.

Methods  Depressive symptoms were assessed using the Beck Depression Inventory (BDI). Data were analyzed using descriptive statistics, taking unadjusted and relative frequencies along with 95% Confidence Intervals (95%CIs). In bivariate analyses, Pearson’s chi-square test was used. Poisson regression was performed with robust variance using unadjusted and adjusted Prevalence Ratios (PRs) along with 95%CIs. Analyses were performed using Stata 17.

Results  The highest prevalence of depressive symptoms was observed in women with lower education (PR: 1.59; 95%CI: 1.19-2.12), without religion (PR: 1.47; 95%CI: 1.15-1.88), who receive government aid (PR: 1.41; 95%CI: 1.11-1.80), do not practice physical exercise (PR: 1.47; 95%CI: 1.17-1.87), smokers (PR: 1.51; 95%CI: 1.18-1.94) and with a diagnosis of multimorbidity (PR: 1.60; 95%CI: 1.29-1.98).

Conclusion  The data point to the urgency of strengthening and expanding the services offered in psychosocial care networks, as well as public policies to respond to women’s demands and needs, considering their difficulties in accessing services.

Keywords:
Depression; Prevalence; Women’s health; Risk factors

Resumo

Objetivo  Verificar a prevalência de sintomas de depressão em mulheres e sua associação com as características socioeconômicas, clínicas e comportamentais.

Métodos  Os sintomas depressivos foram avaliados pelo instrumento o Beck Depression Inventory (BDI). Os dados foram analisados usando estatística descritiva, tomando as frequências brutas e relativas junto com o intervalo de confiança de 95% (IC95%); nas análises bivariadas foi usado o teste qui-quadrado de Pearson. A regressão de Poisson foi realizada com variância robusta usando as Razões de Prevalência (RPs) bruta e ajustada junto com os intervalos de confiança (IC95%). As análises foram realizadas usando o programa Stata 17.

Resultados  As maiores prevalências de sintomas depressivos foram observadas em mulheres com menor escolaridade (RP: 1,59; IC95%: 1,19-2,12), sem religião (RP: 1,47; IC95%: 1,15-1,88), que recebem auxílio do governo (RP: 1,41; IC95%: 1,11-1,80), não praticam exercício físico (RP: 1,47; IC95%: 1,17-1,87), fumantes, (RP: 1,51; IC95%: 1,18-1,94) e com diagnóstico de multimorbidade (RP: 1,60; IC95%: 1,29-1,98).

Conclusão  Os dados apontam para a urgência em fortalecer e ampliar os serviços oferecidos nas redes de atenção psicossocial bem como as políticas públicas para responder às demandas e necessidades das mulheres, considerando suas dificuldades no acesso aos serviços.

Descritores:
Depressão; Prevalência; Saúde das mulheres; Fatores de risco

Resumen

Objetivo  Verificar la prevalencia de los síntomas de depresión en las mujeres y su relación con las características socioeconómicas, clínicas y conductuales.

Métodos  Los síntomas depresivos se evaluaron mediante el instrumento Beck Depression Inventory (BDI). Los datos se analizaron utilizando estadística descriptiva, tomando las frecuencias brutas y relativas junto con el intervalo de confianza del 95 % (IC95 %). En los análisis bivariados se utilizó la prueba ji cuadrado de Pearson. La regresión de Poisson se realizó con varianza robusta utilizando las razones de prevalencia (RP) brutas y ajustadas junto con los intervalos de confianza (IC95 %). Los análisis se realizaron utilizando el programa Stata 17.

Resultados  La mayor prevalencia de síntomas depresivos se observó en mujeres con menor nivel educativo (RP: 1,59; IC95%: 1,19-2,12), sin religión (RP: 1,47; IC95%: 1,15-1,88), que reciben ayuda del gobierno (RP: 1,41; IC95%: 1,11-1,80), que no practican ejercicio físico (RP: 1,47; IC95%: 1,17-1,87), fumadoras (RP: 1,51; IC95%: 1,18-1,94) y con diagnóstico de multimorbilidad (RP: 1,60; IC95%: 1,29-1,98).

Conclusión  Los datos apuntan a la urgencia de fortalecer y ampliar los servicios ofrecidos en las redes de atención psicosocial, así como las políticas públicas para responder a las demandas y necesidades de las mujeres, teniendo en cuenta sus dificultades para acceder a los servicios.

Descriptores:
Depresión; Prevalencia; Salud de la mujer; Fatores de riesgo

Introduction

Depression is one of the psychiatric disorders that most affects the global population, considered the most common disorder along with anxiety disorders. Approximately 300 million people suffer from depression worldwide, and an approximate 25% increase occurred during the first year of the coronavirus-19 pandemic.(¹)

Brazil is considered the country with the highest number of cases of depression in South America, with 11,548,577 (5.8%) cases registered in the Brazilian population.(²) According to data from the Global Burden of Disease (GBD) in Brazil (2017), depressive disorders were among the main causes of disability experienced for years, especially among women.(³) Women have a prevalence of depression twice as high as men due to sociocultural and environmental factors permeated by historically transmitted gender inequality.(⁴,⁵)

Regarding clinical manifestations, depressive symptoms are primarily characterized by a sad mood and loss of interest or satisfaction. They significantly affect the ability to perform daily activities, impacting work performance, relationships, and quality of life.(¹) Symptoms include: sadness, discouragement, fatigue, sluggishness, isolation, and rumination; loss of interest, desire, sense of humor, and ability to enjoy; irregular sleep, lack of energy, difficulty performing activities, eating, and personal hygiene; catastrophic perception, rigid beliefs, guilt feelings, and reduced concentration.(⁶,⁷) Symptoms may be interrelated, presenting feedback and progressive worsening in most cases.(⁸,⁹)

In this scenario, it is important to consider the Brazilian National Mental Health Policy,(¹⁰) which represents a robust legal framework to tackle psychiatric illnesses, as well as the creation of Psychosocial Care Centers.(¹¹) In this regard, Ordinance 2436/2017 included the area of mental health in the Family Health Strategy.(¹²) These administrative procedures contribute to a broader, multidisciplinary, and holistic approach to improving services provided, moving away from the hospital-centric model.(¹³)

Furthermore, it is worth reflecting on the importance of knowledge about mental health. Training is crucial because when professionals receive training, they are better prepared to provide care. Furthermore, it is crucial that training goes beyond providing specific mental health knowledge, contributing to interprofessional care, prioritizing the dialogue between knowledge and responsibilities, and promoting comprehensive care.(¹⁴)The relevance of this research is highlighted, considering the above and the fact that studies on the prevalence of depressive symptoms in women are few. This is the first cross-sectional, population-based study to explore depressive symptoms and associated factors in women living in the city of Vitória (Espírito Santo, Espírito Santo, Brazil), contributing to knowledge in the areas of women’s mental and comprehensive health. Therefore, this study aimed to determine the prevalence of depressive symptoms and their association with socioeconomic, clinical, and behavioral characteristics in women.

Methods

A cross-sectional epidemiological study was conducted from January to May 2022 in the city of Vitória (Espírito Santo, Espírito Santo State) with 1,086 women aged ≥18 years. The inclusion criterion was having an intimate partner currently or in the last 24 months. Women who were unable to understand or communicate due to an intellectual or sensory deficit, which prevented them from completing the survey, were excluded.

Sampling was carried out by consulting the census sectors in the city of Vitória according to the 2010 census conducted by the Brazilian Institute of Geography and Statistics (In Portuguese, Instituto Brasileiro de Geografia e Estatística - IBGE).(¹⁵) The total number of households in the urban area of Vitória, Espírito Santo, in 2010 (108,515) was divided by 100 (the number of sectors to be visited) to calculate the systematic skip (1,085). The list of households was ordered by socioeconomic status, and a random selection was performed using the R statistical program until the appropriate number for each sector was obtained. Proportionality regarding the number of households and women in each sector was respected.(¹⁶) After selecting census tracts, households were randomly selected from the list provided by the IBGE on its online platform. To estimate the sample size, a prevalence of 50% was considered to maximize the sample size (95% confidence level; acceptable error: 5%). To study the association of risk factors, a 95% confidence level, 80% power, and an exposed/unexposed ratio of 1:1 were considered. To this value, 10% for possible losses and 30% for confounding factors were added, resulting in a final sample size of 1,100 women.(¹⁶)

Data collection was conducted individually and privately at home. All interviewers were female and adequately trained and supervised. Data were collected using tablets and managed by the Research Electronic Data Capture (REDCap) electronic data capture tool. The pilot study took place in December 2021 (34 interviews), the data of which were not included in the final research sample. The dependent variable of this study is related to depressive symptoms assessed by the Beck Depression Inventory (BDI), developed by Aaron Beck et al. (1961).(¹⁷) The questionnaire assessed items such as: sadness; pessimism; self-criticism; crying; irritability; indecision; self-esteem; worry; tiredness or fatigue; suicidal thoughts; loss of energy; loss of satisfaction and/or interest; failure and/or guilt and/or punishment and/or disappointment feelings; and changes in appetite and/or sleep and/or weight and/or sexual interest.(¹⁷)

The Beck Depression Inventory is a 21-item Likert-type scale that can be self-administered. According to the instrument’s validity, the presence of depressive symptoms is classified as minimal (0-11), mild (12-19), moderate (20-35), and severe (36-63).(¹⁸) In the present study, the items and their respective intensity ratings (mild, moderate and severe) were initially described and then dichotomized, classifying those who scored 0-11 as the absence of depressive symptoms and those with a score ≥12 as having depressive symptoms.

The independent variables of this study were as follows: age group (18-29, 30-39, 40-49, 50-59 and ≥60 years); race or skin color (white, black, yellow, brown and indigenous); woman’s education level (0-8, 9-11 and ≥12 years of study); family income by tertile (first, lowest tertile, second and third, highest tertile) and socioeconomic class (assessed by the Brazil Criterion, Brazilian Association of Companies and Research, ABEP, which stratifies socioeconomic classes) A1, B1, B2, C1, D and E. In the present study, the classifications (A, B, C and D/E)(¹⁹) were grouped into marital status (with and without partner); religion (no, yes); paid work (no, yes); number of people in the household (0-2, 3-5 and ≥6 people); own home (no, yes) and government assistance (no, yes). Excess weight was classified by calculating the Body Mass Index (BMI) in which weight and height were self-reported, considering people with a BMI ≥25 kg as being overweight (no, yes), smoking (never smoked, smoked but stopped smoking), alcohol consumption (no, yes) and self-reported physical activity (walking, weight training, gymnastics, Pilates and/or other types of activity), being dichotomized (no, yes). The multimorbidity variable was measured based on the self-report of two or more disease conditions, such as hypertension, dyslipidemia, diabetes, coronary heart disease (acute myocardial infarction and/or angina), stroke, lung problems (asthma, bronchitis, emphysema, and/or chronic obstructive pulmonary disease (COPD), chronic liver disease (hepatitis, cirrhosis, and/or others), arthritis and/or osteoarthritis, vision problems (glaucoma and/or cataracts), thyroid problems (hypothyroidism and/or hyperthyroidism), cancer, epilepsy, Alzheimer’s disease, Parkinson’s disease, osteoporosis, loss of renal function, or depression. The multimorbidity variable was dichotomized as yes/no.

The data were initially analyzed by BDI items and symptomatic classifications using descriptive statistics for absolute and relative frequencies and their 95% Confidence Intervals (CI). Comparative analysis of symptomatic classifications was then performed dichotomously using Pearson’s chi-squared (χ2) test (significance level: 5%), and the association between variables was assessed using Poisson Regression with robust variance by unadjusted and adjusted Prevalence Ratios (PRs), as well as their respective 95%CIs. Values of p<0.20 were considered for entry into the adjusted analysis, and p<0.05 for retention. Adjusted analysis occurred by entering the model from two levels: sociodemographic data were included in the first level; and data from the first model added to behavioral and clinical data were included in the second. A significance level of 5% (p<0.05) was adopted for retention in the final model. Statistical analysis was performed using the Stata program (v. 17.0).

This study was part of the research “Violência contra a mulher em Vitória, Espírito Santo: um estudo de base populacional”, approved by the Universidade Federal do Espírito Santo Research Ethics Committee (REC/UFES; Opinion 4.974.080) and registered with the Certificate of Presentation for Ethical Consideration (CAAE 41628820.6.0000.5060).

Results

Regarding data on depressive symptoms in women living in the city of Vitória (ES, Brazil), 22.8% of interviewees reported feelings of sadness and 21.2% of them felt discouraged about the future. It was observed that 12.5% of them felt they had failed more than the average person. About 3 in 10 women no longer felt satisfaction in things as before, sometimes feeling guilty (25.1%), disappointed in themselves (21.3%), and that they could be punished (6.9%). They reported feeling more irritable than usual (~27%) and less interested in people (~24%). Concerning self-esteem, they reported feeling that their appearance was worse than usual (16.4%), changes in sleep (~26%), and more tired or fatigued than usual (~41%). Furthermore, they reported feeling more worried (25%) and having had suicidal thoughts (~5%) (Table 1).

Table 1
Responses from women living in the city of Vitória (urban area; ES, Brazil) about the intensity of depression symptoms (n=1086)

Variables	n(%)	95%CI
Sadness
I do not feel sad	786(72.4)	69.6-74.9
I feel sad	248(22.8)	20.4-25.4
I am sad all the time and I can’t snap out of it.	38(3.5)	2.6-4.8
I am so sad and unhappy that I can’t stand it.	14(1.3)	0.7-2.2
Pessimism
I am not particularly discouraged about the future.	782(72.0)	69.2-74.6
I feel discouraged about the future.	230(21.2)	18.8-23.7
I feel I have nothing to look forward to.	45(4.1)	3.1-5.5
I feel the future is hopeless and that things cannot improve.	29(2.7)	1.8-3.8
Sense of failure
I do not feel like a failure.	919(84.6)	82.3-86.6
I feel I have failed more than the average person.	135(12.5)	10.6-14.5
As I look back on my life, all I can see is a lot of failures.	20(1.8)	1.2-2.8
I feel I am a complete failure as a person.	12(1.1)	0.6-1.9
Loss of satisfaction
I get as much satisfaction out of things as I used to.	713(65.6)	62.8-68.4
I don’t enjoy things the way I used to.	320(29.5)	26.8-32.3
I don’t get real satisfaction out of anything anymore.	24(2.2)	1.4-3.3
I am dissatisfied or bored with everything.	29(2.7)	1.9-3.8
Guilt feelings
I don’t feel particularly guilty	761(70.1)	67.3-72.7
I feel guilty a good part of the time.	273(25.1)	22.6-27.8
I feel quite guilty most of the time.	38(3.5)	2.6-4.8
I feel guilty all of the time.	14(1.3)	0.8-2.2
Punishment feelings
I don’t feel I am being punished.	942(86.7)	84.5-88.6
I feel I may be punished.	75(6.9)	5.5-8.6
I expect to be punished.	13(1.2)	0.7-2.0
I feel I am being punished.	56(5.2)	0.4-6.6
Disappointment feelings
I don’t feel disappointed in myself.	843(77.6)	75.0-80.0
I am disappointed in myself.	231(21.3)	18.9-23.8
I am disgusted with myself.	10(0.9)	0.5-1.7
I hate myself.	2(0.2)	0.0-0.7
Self-criticism
I don’t feel I am any worse than anybody else.	809(74.5)	71.8-77.0
I am critical of myself for my weaknesses or mistakes.	210(19.3)	17.1-21.8
I blame myself all the time for my faults.	56(5.2)	4.0-6.6
I blame myself for everything bad that happens.	11(1.0)	0.6-1.8
Suicidal thoughts
I don’t have any thoughts of killing myself.	1035(95.3)	93.9-96.4
I have thoughts of killing myself, but I would not carry them out.	40(3.7)	2.7-4.9
I would like to kill myself.	6(0.6)	0.2-1.2
I would kill myself if I had the chance.	5(0.5)	0.2-1.1
Crying
I don’t cry any more than usual.	812(74.7)	72.1-77.3
I cry more now than I used to.	170(15.7)	13.6-17.9
I cry all the time now.	44(4.1)	3.0-5.4
I used to be able to cry, but now I can’t cry even though I want to.	60(5.5)	4.3-7.0
Irritability
I am no more irritated by things than I ever was.	652(60.0)	57.1-62.9
I am slightly more irritated now than usual.	288(26.5)	23.9-29.2
I am quite annoyed or irritated a good deal of the time.	87(8.0)	6.5-9.7
I feel irritated all the time.	59(5.5)	4.2-6.9
Loss of Interest.
I have not lost interest in other people.	752(69.2)	66.4-71.9
I am less interested in other people than I used to be.	257(23.7)	21.2-26.3
I have lost most of my interest in other people.	53(4.9)	3.7-6.3
I have lost all of my interest in other people.	24(2.2)	1.5-3.3
Indecision
I make decisions about as well as I ever could.	795(73.2)	70.5-75.8
I put off making decisions more than I used to.	157(14.5)	12.5-16.7
I have greater difficulty in making decisions more than I used to.	109(10.0)	8.4-11.9
I can’t make decisions at all anymore.	25(2.3)	1.6-3.4
Self-esteem
I don’t feel that I look any worse than I used to.	762(70.2)	67.4-72.8
I am worried that I am looking old or unattractive.	178(16.4)	14.3-18.7
I feel there are permanent changes in my appearance that make me look unattractive.	91(8.3)	6.9-10.2
I believe that I look ugly.	55(5.1)	3.9-6.5
Loss of energy
I can work about as well as before.	753(69.3)	66.5-72.0
It takes an extra effort to get started at doing something.	251(23.1)	20.6-25.7
I have to push myself very hard to do anything.	64(5.9)	4.6-7.4
I can’t do any work at all.	18(1.7)	1.0-2.6
Changes in sleep
I can sleep as well as usual.	627(57.7)	54.8-60.6
I don’t sleep as well as I used to.	280(25.8)	23.3-28.5
I wake up 1-2 hours earlier than usual and find it hard to get back to sleep.	106(9.8)	8.1-11.7
I wake up several hours earlier than I used to and cannot get back to sleep.	73(6.7)	5.4-8.4
Tiredness or fatigue
I don’t get more tired than usual.	555(51.1)	48.1-54.1
I get tired more easily than I used to.	443(40.8)	37.9-43.7
I get tired from doing almost anything.	63(5.8)	4.6-7.4
I am too tired to do anything.	25(2.3)	1.6-3.4
Changes in appetite
My appetite is no worse than usual.	875(80.6)	78.1-82.8
My appetite is not as good as it used to be.	133(12.2)	10.4-14.3
My appetite is much worse now.	61(5.6)	4.3-7.1
I have no appetite at all anymore.	17(1.6)	0.9-2.5
Changes in weight
I haven’t lost much weight, if any, lately.	896(82.5)	80.1-84.7
I have lost more than five pounds.	115(10.6)	8.9-12.6
I have lost more than ten pounds.	39(3.6)	2.6-4.8
I have lost more than fifteen pounds.	36(3.3)	2.4-4.6
Concerns
I am no more worried about my health than usual.	718(66.1)	63.2-68.9
I am worried about physical problems like aches, pains, upset stomach, or constipation.	268(24.7)	22.2-27.3
I am very worried about physical problems and it’s hard to think of much else.	80(7.4)	5.9-9.0
I am so worried about my physical problems that I cannot think of anything else.	20(1.8)	1.2-2.8
Changes in sexual interest
I have not noticed any recent change in my interest in sex.	643(59.2)	56.2-62.1
I am less interested in sex than I used to be.	223(20.5)	18.2-23.0
I have almost no interest in sex.	139(12.8)	10.9-14.9
I have lost interest in sex completely.	81(7.5)	6.0-9.2

• n: absolute frequency; %: relative frequency; 95%CI: 95% Confidence Interval.

Women had no depressive symptoms (~76%; 95%CI: 73.4-78.5), mild (15.1%; 95%CI: 13.1-17.4), moderate (7.9%; 95%CI: 6.4-9.7), and severe (~1%; 95%CI: 0.5-1.7) symptoms (Table 2).

Table 2
Intensity of depressive symptoms among women living in the city of Vitória (ES, Brazil; 2022) (n=1,086)

Variables	n(%)	95%CI
No symptoms	826(76.1)	73.4-78.5
Mild symptoms	164(15.1)	13.1-17.4
Moderate symptoms	86(7.9)	6.4-9.7
Severe symptoms	10(0.9)	0.5-1.7

• n: absolute frequency; %: relative frequency; 95%CI: 95% Confidence Interval.

Regarding bivariate analysis, Table 3 shows that depressive symptoms were related to the variables of women’s education level, family income (by tertile) and/or income (ABEP classification), marital status, religion, and government aid (p<0.05). Concerning behavioral and clinical characteristics, depressive symptoms were related to smoking, physical activity, and multimorbidity (p<0.05).

Table 3
Distribution of depressive symptoms among women living in the city of Vitória (ES, Brazil; 2022) according to sociodemographic, economic, behavioral, and clinical characteristics (n=1,086)

	n(%)	95%CI	p-value*
Sociodemographic and economic characteristics
Age range (years)			0.170
18-29	61(30.2)	24.3-36.9
30-39	48(23.5)	18.2-29.8
40-49	53(23.9)	18.7-29.9
50-59	39(19.9)	14.9-26.1
≥60	59(22.5)	17.8-27.9
Race and/or skin color			0.586
White	102(23.4)	19.6-27.6
Black	54(27.6)	21.7-34.2
Yellow	2(12.5)	3.1-38.6
Brown	100(23.2)	19.5-27.4
Indigenous	2(28.6)	7.2-6.7
Women’s education (years of study)			<0.001
0-8	61(30.1)	24.1-36.7
9-11	101(28.7)	24.2-33.6
≥12	98(18.5)	15.4-22.0
Family income by tertile			<0.001
First (lowest)	127(30.7)	26.4-35.3
Second	76(21.8)	17.8-26.4
Third (highest)	57(17.6)	13.9-22.2
ABEP**			0.031
A	17(17.2)	10.9-25.9
B	104(21.7)	18.2-25.6
C	108(26.1)	22.1-30.6
D/E	31(32.6)	23.9-42.7
Marital status			0.003
With a partner	196(22.1)	19.5-25.0
Without a partner	64(32.0)	25.9-38.8
Religion (n=1,086)			0.002
No	60(33.0)	26.5-40.1
Yes	200(22.1)	19.5-24.9
Paid work			0.207
No	152(25.4)	22.0-29.0
Yes	108(22.1)	18.6-26.0
Number of people in the household			0.613
0-2	92(22.3)	18.6-26.6
3-5	155(24.8)	21.6-28.4
≥6 or more	13(26.0)	15.7-39.8
Own home			0.082
No	87(27.4)	22.8-32.6
Yes	173(22.5)	19.7-22.6
Government aid			<0.001
No	193(21.6)	18.9-24.4
Yes	67(35.1)	28.6-42.1
Behavioral and clinical characteristics
Overweight (N=1,075)			0.311
No	107(22.4)	18.9-26.4
Yes	150(25.1)	21.8-28.7
Smoking			<0.001
Never smoked	171(21.3)	18.6-24.2
Yes	56(40.9)	32.9-49.3
Smoked, but quit smoking	33(22.8)	16.6-30.3
Alcohol use (N=1,080)			0.470
No	137(25.0)	21.5-28.8
Yes	123(23.1)	19.7-26.9
Physical activity			<0.001
No	172(29.2)	25.7-33.0
Yes	88(17.7)	14.6-21.3
Multimorbidity			<0.001
No	111(18.6)	15.6-21.9
Yes	149(30.5)	26.6-34.8

• n: absolute frequency; %: relative frequency; 95%CI: 95% Confidence Interval; *Pearson’s chi-square test; **ABEP: Brazilian Association of Research Companies.

Adjusted analysis showed that women with lower levels of education had almost 60% more depressive symptoms (PR: 1.59; 95%CI: 1.19-2.12) compared to those with higher levels of education. Women without a partner had a 42% higher prevalence of depressive symptoms (PR: 1.42; 95%CI: 1.12-1.80) compared to those with a partner. Furthermore, not having any religion led to a 1.47-fold higher prevalence of depressive symptoms (PR: 1.47; 95%CI: 1.15-1.88), and women receiving government assistance had a 41% higher prevalence of depressive symptoms (PR: 1.41; 95%CI: 1.11-1.80) (Table 4). As for women who smoked, they had a 51% higher prevalence of depressive symptoms than non-smokers, and those who did not practice physical activity also had a higher prevalence of this condition (PR: 1.47; 95%CI: 1.17-1.87). The presence of a diagnosis of multimorbidity showed a 60% higher prevalence of depressive symptoms compared to those women without a diagnosis of multimorbidity.

Table 4
Unadjusted and adjusted analysis of depressive symptoms using Poisson Regression with robust variance among women living in the city of Vitória (ES, Brazil; 2022) according to sociodemographic, economic, behavioral, and clinical characteristics

Variables	PR*	95%CI	p-value	aPR**	95%CI	p-value
Age group (years)			0.159			0.516
18-29	1.34	0.99-1.82		1.13	0.81-1.59
30-39	1.04	0.75-1.46		0.99	0.70-1.42
40-49	1.06	0.77-1.47		1.07	0.77-1.49
50-59	0.88	0.62-1.27		0.82	0.58-1.17
≥60	Ref.			Ref.
Race and/or skin color			0.608			-
White	Ref.			-	-
Black	1.18	0.89-1.56		-	-
Yellow	0.53	0.14-1.98		-	-
Brown	0.99	0.78-1.26		-	-
Indigenous	1.22	0.34-3.99		-	-
Education (years of study)			0.001			0.001
0-8	1.63	1.24-2.15		1.59	1.19-2.12
9-11	1.55	1.22-1.98		1.50	1.18-1.91
≥12	Ref.			Ref.
Household income by tertile			<0.001			0.291
First (lowest)	1.74	1.32-2.29		1.27	0.92-1.17
Second	1.23	0.91-1.68		1.09	0.78-1.50
Third (highest)	Ref.			Ref.
ABEP#			0.030			0.640
A	Ref.			Ref.
B	1.26	0.79-2.01		1.04	0.64-1.69
C	1.52	0.96-2.42		0.88	0.51-1.50
D/E	1.90	1.13-3.20		0.85	0.46-1.59
Marital status			0.002			0.004
With partner	Ref.			Ref.
No partner	1.45	1.14-1.83		1.42	1.12-1.80
Religion			0.001			0.002
No	1.49	1.17-1.90		1.47	1.15-1.88
Yes	Ref.			Ref.
Paid work			0.218			-
No	1.15	0.93-1.43		-	-
Yes	Ref.
Number of people in the household			0.615			-
0-2	Ref.
3-5	1.11	0.89-1.40		-	-
≥6	1.16	0.71-1.92		-	-
Own home			0.079			0.288
No	1.22	0.98-1.52		1.13	0.90-1.41
Yes	Ref.			Ref.
Government aid			<0.001			0.005
No	Ref.			Ref.
Yes	1.63	1.29-2.05		1.41	1.11-1.80
Overweight			0.312			-
No	Ref.			-	-
Yes	1.12	0.90-1.39		-	-
Smoking			<0.001			0.003
Never smoked	Ref.			Ref.
Yes	1.92	1.50-2.45		1.51	1.18-1.94
Smoked, but quit	1.07	0.77-1.49		0.97	0.70-1.34
Alcohol use			0.470			-
No	Ref.			-	-
Yes	0.92	0.75-1.14		-	-
Physical activity			<0.001			0.001
No	1.65	1.31-2.07		1.47	1.17-1.85
Yes	Ref.			Ref.
Multimorbidity			<0.001			<0.001
No	Ref.			Ref.
Yes	1.64	1.32-2.04		1.60	1.29-1.98

• *PR: Prevalence Ratio; **aPR: Adjusted Prevalence Ratio; 95%CI: 95% Confidence Interval; #ABEP: Brazilian Association of Research Companies.

Discussion

The findings of this study showed that the women interviewed had mild (15.1%), moderate (7.9%), and severe (0.9%) depressive symptoms, with highlights including reduced satisfaction in performing activities, irritability, lack of interest in people, guilt feelings, tiredness, fatigue, worry, and sleep disturbances. The above findings are similar to those of a study conducted with women assisted by the Family Health Strategy (FHS) in a city in Minas Gerais, indicating that they had symptoms of depression according to the BDI (~18%), and their symptoms were mild (5.0%) and moderate (8.2%).(²⁰)

Symptoms of depression in women highlight the vulnerability of the population, as they are more susceptible to this condition due to genetic factors, hormonal changes, and overload from performing multiple tasks and social issues.(²¹)These findings are worrying because depressive symptoms cause psychological distress that can interfere with women’s functional and social capacities, well-being, and quality of life.(¹)

Regarding the socioeconomic variables studied, women with less education had a higher prevalence of depressive symptoms (~60%). A recent study showed that education level is a social risk indicator for depression.(²²)Likewise, another study conducted in Minas Gerais (Brazil) involving 1,958 women highlighted that having low education and a history of mental illness are factors associated with depression.(²³)The data indicate that lower education levels are often associated with fewer job opportunities, resulting in precarious economic conditions that can lead to depressive symptoms.(²⁴,²⁰)

Similarly, a higher prevalence of depressive symptoms was observed among women receiving government assistance, indicating that they had a higher prevalence of depressive symptoms (41%) compared to women who did not receive assistance. This is consistent with a study that found a prevalence of depression in illiterate, unemployed, and widowed and/or separated women, as well as in people from ethnic minority groups and smaller families (1-4 members).(²⁵) It has been confirmed that socioeconomic factors such as poverty, economic hardship and unemployment can increase the risk of developing depressive symptoms.(²⁶)

A higher prevalence of signs and symptoms of depression was confirmed in women without partners, who also had a higher prevalence of depressive symptoms (42%). This may be explained by the fact that the absence of a family and emotional support network can lead to greater psychological vulnerability, as well as a disproportionate burden of domestic responsibilities, social commitments, and economic burdens for women without spousal support.(²⁷,²⁸) Furthermore, it is important to highlight the gender disparity and inequality that make women more vulnerable to social stress, in addition to the feminization of poverty that leads women to work double or triple shifts.(⁶,²⁹)

Another finding in this study was that the prevalence of symptoms of depression was higher among women who reported having no religion. This led to a higher prevalence of depressive symptoms (47%) because religion facilitates the search for meaning in life. Spirituality is considered an important part of overall health and a form of support for coping with difficulties and problems.(³⁰,³¹)

Concerning the behavioral variables in this study, a higher prevalence of depressive symptoms was found among female smokers, who had a higher frequency of depressive symptoms compared to non-smokers (51%). This is consistent with a study that showed that smoking is one of the causes of health deterioration, altering brain function and predisposing to neuropsychiatric diseases.(³²)Thus, a higher prevalence of depressive symptoms was observed among women who do not engage in physical activity. An increase in the prevalence of depression found in Brazil between 2013 and 2019 was associated with smoking and sedentary lifestyles.(³³)Different studies have shown that there are risk factors related to unhealthy behaviors, habits and lifestyles, poor diet, physical inactivity and a sedentary lifestyle, as well as the consumption and abuse of psychoactive substances such as alcohol, cigarettes, and drugs.(³⁴,³⁵)

As for the association with the presence of multimorbidity (i.e., a diagnosis of two or more health problems), the findings indicated a 1.6-fold higher prevalence of depressive symptoms among women who reported having two or more chronic diseases. This result is similar to that found in the literature, which confirmed that people with illnesses are more likely to experience the most severe manifestation of depression.(³⁶)

Mental health is a challenging public health issue that requires the reconstruction of health policy in Brazil, allowing for the provision of adequate care to monitor the determinants of mental illness.(³⁷)New care strategies must be implemented to improve patients’ quality of life, involving continuous interprofessional care encompassing all levels of care with qualified listening.(¹⁴)

Regarding the study’s limitations, we highlighted the research design, as cross-sectional studies should consider the possibility of reverse causation between depressive symptoms and the socioeconomic, clinical, and behavioral variables studied. On the other hand, our findings are consistent with other studies. Furthermore, we recommended future population-based research in different cities to obtain different parameters for comparison, as well as qualitative studies in women with depressive symptoms to complement the information and strengthen mental health policies.

Conclusion

The prevalence of mild depressive symptoms and a higher prevalence of depressive symptoms are associated with women with lower education, no religion, those receiving government assistance, sedentary lifestyles, smokers, and those with multimorbidity. Public policies are needed to address gender inequalities, the burden of domestic work alongside caregiving activities, vulnerabilities, and social determinants that affect women’s mental health in healthcare services. It is urgent to strengthen and expand the services offered in psychosocial care networks to respond to women’s demands and needs, facilitate access to mental healthcare services in Brazil, and the diagnosis and treatment of depression symptoms in women.

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• Data availability:
  The survey data are available in the article.

Edited by

• Associate Editor:
  Thiago da Silva Domingos (https://orcid.org/0000-0002-1421-7468) Escola Paulista de Enfermagem, Universidade Federal de São Paulo, São Paulo, SP, Brasil

Data availability

The survey data are available in the article.

Publication Dates

• Publication in this collection
  20 Apr 2026
• Date of issue
  2026

History

• Received
  12 Mar 2025
• Accepted
  31 Aug 2025