Prevalence and factors associated with depression in the elderly: a cross-sectional study

Este é um artigo publicado em acesso aberto (Open Access) sob a licença Creative Commons Attribution, que permite uso, distribuição e reprodução em qualquer meio, sem restrições, desde que o trabalho original seja corretamente citado. https://doi.org/10.11606/issn.2176-7262.v53i3p205-214 ABSTRACT Introduction: Depression is a psychiatric disease that causes losses in the biopsychosocial aspect of the affected individuals. The prevalence in the elderly population is significant, and identify the factors related to this outcome allows preventive measures and treatment can be early applied. Objective: Assessing the association between depression and sociodemographic and health risk factors in the elderly. Methods: This is a cross-sectional study involving 388 elderly of both genders, aged 65 years and older, urban residents of the city of Cuiabá, state of Mato Grosso (MT), Brazil. A sociodemographic questionnaire, as well as a self-report of chronic diseases and lifestyle, a self-report questionnaire of functional capacity, occurrence of falls, Geriatric Depression Scale, mental state assessment, and anthropometry tests were used. The chi-square test, odds ratio (OR), and multiple logistic regression with 95% confidence interval and p<5% were used in the statistical analysis. Results: There was a predominance of women (64%) who were mulatto/caboclo/brown skin (43%) and married (45%). Depression was significantly associated with: the lowest level of education, <8 years (OR=2.15; p=0.012), partial or total dependence of instrumental activities of daily living (OR=1.85; p=0.003), having five or more diseases (OR=2.93, p=0.002), falls in the last twelve months (OR=1.90; p=0.021), and sleep (OR=2.39; p<0.001) and visual difficulties (OR=2.28; p<0.001). Conclusion: Depression in this group of elderly was associated with modifiable and preventable factors in the health of these people. Thus, the early diagnosis of risk factors associated with depression, the inclusion of social, physical and cognitive activities must be considered for their prevention.


INTRODUCTION
According to the World Health Organization (WHO), around 322 million people live with depression, and women are more affected than men (5.1% and 3.6%, respectively) 1 . In Brazil, 11.1% of the population aged between 60 and 64 years have already been diagnosed with depression 2 . Depression in Brazil is the third leading cause of claiming sick pay from the National Institute of Social Security (INSS), and one of the leading causes of abstention and loss of labor productivity 3 . Between 2016 and 2030, the treatment coverage for depression and anxiety will increase from 7 to 33% and from 28 to 50% in low-income and middle-income countries, respectively 4 . Moreover, these projections are expected to be worsened due to the current COVID-19 pandemic, which is associated with cognitive and emotional impairments, like depression 5 .
The decline in fertility and mortality in the last decades has contributed to the changing age structure of the world population, which is gradually aging. This phenomenon is due to the increase in life expectancy with a decrease in the younger population and an increase in the elderly population 6 . Even the aging process occurring individually, it is influenced by economic, cultural, emotional, genetic, environmental, and life habits 7 .
Neuropsychological and psychological disorders, changes in activities of daily life (ADL), memory oscillation, reasoning speed, sleep disturbances, and mental confusion have also been observed. Thus, these manifestations may be associated with symptoms of dementia 8 or depression in the elderly group 9 .
Depression is a serious mental health problem, that may compromise physical 10 , emotional, cognitive, and psychomotor quality of life, resulting in suicide 11 , in extreme cases. Thus, it affects the professional, academic, and family life of any person 12 . The characteristics of depression include irritable mood and less propensity to pleasure and joy, and may be accompanied by subjective tiredness or fatigue, change in sleep and appetite, general lack of interest, pessimism, slowness, and feelings of failure 13 .
However, there is a difficulty in diagnosing depression by health professionals, the elderly, and their families, who underestimate the symptoms and confuse them with other diseases, classifying them as typical symptoms of aging 14 . Some authors adopt instruments with scales 15,16,17 , visual humor thermometer 18 , and diagnostic criteria of mental disorders 19 in medical semiology. There is also research 20 that found an association of biochemical markers, such as vitamin D, with the increased prevalence of depression. In the meta-analysis 21 , we found an association of depression with the Interleukin-6 in the elderly population.
For establishing health goals and subsidize public policies on depressive disorders, it is necessary to understand the changes in the variables by type of disorder, country, region, age, gender, and year 22 . Therefore, identifying the profile of depressed elderly will allow us to develop strategies for screening and early diagnosis 13 the disease in this population. In this way, it is possible to prevent the progression from healthy adults to dependent elderly, avoiding high financial costs and low quality of life 23 .
Thus, this study aimed to estimate the prevalence of depression and associate it with the physical and social factors of the elderly.

Design and study area
This is a cross-sectional and population-based study carried out with elderly patients aged 65 years and older, of both sexes, living in an urban area, and evaluated between March 2009 to April 2010 using maps provided by the Brazilian Institute for Geography and Statistics (IBGE) 2 .
The number and location of the residences to be visited were determined according to the IBGE data, by the proportion of the elderly from each census tract related to the total of elderly living in the city. Then, the density of elderly was calculated per residence to establish the number of homes to be visited, counted, and drawn in each neighborhood. Thus, we identified 15 census tracts with a density of the elderly representative of the population of Cuiabá (Mato Grosso State, Brazil), and we counted and selected the blocks and streets where the residences to be visited were.

Factors of depression in the elderly
All participants were informed about the purpose of the research and signed an informed consent form. The study was approved (No. 632/09; Resolution 466/12 of the National Health Council) by the Research Ethics Committee of Julio Muller University Hospital of the Federal University of Mato Grosso (UFMT). The sample size (n) was first determined through the simple random sampling method, corresponding to a 5% error 24 .

Participants and instruments
Non-participation criteria were: being a wheelchair user or bed-ridden even if transiently; having sequel of cerebrovascular accidents, decreased strength that could affect performance on tests, advanced Parkinson's disease, terminal state of cancer and other chronic diseases, and significant cognitive deficit -Mini-Mental State Examination ≤ 14. Data collection was performed in two stages. The first one was by a semi-structured interview at the elderly's home, and in the second phase, the physical-functional data were collected by trained evaluators in public schools, community centers, and health centers of the city.
In this subproject, the following variables were used: age, gender, marital status, living alone, schooling (individuals who report less than eight years of school attendance were considered with low education, those with eight years of school or more were considered to have a middle/high level of education), body mass [determined using a platform scale of the type Filizola® electronics ID 1500 (SP, Brazil) with a capacity of 200 kg and an accuracy of 0.1 kg]. The height was measured by a professional portable Sanny® stadiometer (SP, Brazil), with 0.1 cm accuracy. The body mass index was calculated using the weight ratio in kilograms by height in meters squared (kg/m²). The reference values adopted for the body mass index were those suggested and suitable for the elderly who categorizes in: <22.0 kg/m² = underweight, 22.0 kg/ m² to 27.0 kg/m² = normal weight, and> 27.0 kg/m² = overweight 25 . Self-reported sleep changes, falls in the last year, hearing and visual deficits, self-reported diseases (heart disease, arterial hypertension, stroke, diabetes, depression, cancer, lung problems, osteoporosis, urinary and/ or fecal incontinence), and the functional performance were evaluated using Lawton Instrumental Activities of Daily Living Scale (IADL) 26 and Basic Activities of Daily Living (BADL), Falls Efficacy Scale-International (FES-I) 26 , cognitive function by Mini-Mental State Examination (MMSE) 15 , and depression symptoms by the Geriatric Depression Scale (GDS-15) 27 , 28 . The Five-Step test and Short Physical Performance Battery (SPPB) 26 were used for physical-functional evaluation.

Statistical analysis
Statistical analysis was performed using the SPSS ® (Statistical Package for the Social Sciences), version 20.0 for Windows, considering the effect of study design and the sample weights. A descriptive analysis was performed by simple frequency and measures of central tendency. The Chi-square test was used to compare the groups with mild depression, moderate depression, and no depression.
The Geriatric Depression Scale in a reduced version of Yesavage (GDS-15) was used to detect depressive symptoms, which were classified according to severity, in which the elderly with less than 5 points were considered to have no depressive symptoms, with 5 or more points were considered with moderate depression, and with a score equal to or greater than 11 characterized with severe symptoms of depression.
The logistic regression analysis was performed by calculating the gross odds ratio (OR) to analyze the probability of association between depressed people and covariables (sociodemographic, body mass index, cognitive deficit, referred morbidity, reports of falls, low functional performance, and sleep, hearing, and visual problems). For all the variables, it was used 95% as a confidence interval and p<0.05.

RESULTS
Five hundred and thirteen elderly were interviewed, 125 of them were excluded according to the criteria above-mentioned or because of absences/losses in the second stage of the physical tests. The final sample consisted of 388 elderly, aged 65 years and older, of both sexes, living in the city of Cuiabá.
The mean age was 72±6 years, with a mean of 4±4 years of school attendance and a family income of 3±4 minimum wages. Women were predominant in the sample, and as for the marital status, the highest frequency of those married and widowed stood out (Table 1).
About 17% of the elderly with depression symptoms were between 65 and 69 years old. The sample comprised a prevalence of mild/moderate depression of 38.4% and severe depression of 3.1%. There was a greater percentage of depression in women, and those with mild/moderate or severe depression had lower schooling. Depression was significantly associated with years of school, BADL, and IADL, number of diseases, cardiovascular diseases, hypertension, diabetes mellitus, arthritis, osteoporosis, and urinary infection, low physical performance, falls in the last year, and sleep and visual difficulties (Tables 2 and 3).
The gross analysis of multiple logistic regression showed that older adults with low schooling were twice as likely to be depressed than those with medium or high schooling levels. By analyzing the functionality of the elderly, both in the BADL and IADL, those with partial or total dependence were approximately four times and two times, respectively, more likely to have depression. Older people who reported having five or more diseases were almost three times as likely to be depressed. Of the diseases reported, hypertension, diabetes mellitus, arthritis, osteoporosis, and urinary incontinence were associated with depression. Moreover, the elderly with urinary incontinence or sleep or visual problems are twice as likely to have depression. Finally, the older adults who had low performance or reported having suffered falls in the previous year are almost twice as likely to have depression (Table 4). Table 1 Sociodemographic characterization of a sample of urban elderly residents in the sampled community (n=388)

DISCUSSION
The most significant finding of this study is that depression was associated with a loss of independence, poor sleep quality, and self-reported comorbidities. In this study, it was observed a higher prevalence of depression in the elderly when compared to the national 2 average, which was also found in other studies 29,30 .
Women accounted for 64% of the sample and had a higher prevalence of depression. This relationship was found in many different studies, regardless of age 29,30,31,32 . Factors related to female physiological and hormonal differences, low educational level, low income, socio-cultural issues, and the different ways of dealing with stressful situations have been analyzed in an attempt to justify this higher prevalence in women 31,33 .
Although our sample does not include institutionalized elderly, the risk factor female sex was also predominant in studies with elderly in these scenarios, however, these elderly end to manifest depressive symptoms at older ages, while in our sample the age group with greater depressive impairment was between 65 and 69 years old, emphasizing that care must be comprehensive for this population regardless of the living environment 34,35,36 .
The low schooling level and female gender had a strong association with depression, similar to other study 30 . Wu et al. 37 justify that low schooling is a precursor to memory difficulty because of the lack of brain stimulation during daily activities and they believe that mental exercise and the maintenance of social relationships with friends and family can maintain the stimulus and increase Table 4 Gross analysis of multiple logistic regression between depression and sociodemographic variables, functionality, body mass index, cognitive deficit, referred morbidities, reports of falls, low functional performance, sleep, hearing, and visual problems in a sample of urban elderly residents in the sampled community (n=388)

Variables
Gross  38 identified risk factors similar to these and believed that social and economic support is essential for the elderly, and that good schooling increases their chances of having better financial security and thus, participate in social activities successfully. The preservation of functional capacity, i.e., the ability to perform basic and instrumental activities daily, such as eating, bathing, shopping, and taking medicine, has a great influence on the quality of life for the elderly. It also ensures that these people interact with society independently, for a longer period 39 . Our data corroborate these results, showing the elderly with partial or total dependence on the IADLs were more likely to be depressive. Hoffman et al. 40 characterize the relationship between depressive symptoms and functional decline as bidirectional, cause and effect, and they also add sleep difficulty as a factor associated with depression symptoms. Thus, in this study 41 , there was an association between sleep quality in elderly patients with osteoporosis and depression.
In the analysis of the elderly senses (vision and hearing), only self-report of any visual impairment proved to be relevant for the development of depression. This relationship was already expected given the impact of this deficit on the performance of daily activities, affecting their functional capacity. In a study on the elderly in Belgium 42 , it was found a strong relationship between depression and visual problems, emphasizing that the higher prevalence of depression in the aging population increases the chances of these two events occurring, thus requiring more effective prevention and treatment strategies.
Although senescence does not mean getting sick, this process favors the development of diseases 43 , especially the chronic ones due to the increased exposure to stressors, such as long periods of pain 41 , nutritional impairment 44 , reduced autonomy, and physical mobility in response to physical illness. In this study, the chance the elderly develop depressive symptoms was three times higher when they had five or more diseases, such as cardiovascular diseases, diabetes mellitus, arthritis, osteoporosis, and urinary incontinence. Corroborating these results, other authors also found a strong association among depression, cardiovascular and cerebrovascular diseases 45 , and diabetes mellitus 46 , and they also indicated the importance of early diagnosis of depression.
Our results showed that the elderly who had sleep difficulty were twice as likely to have depression. In this reasoning, Becker et al. 47 observed that sleep quality is a mediating factor for the development of depression among the elderly, and they reinforce the importance of maintaining a good quality of sleep, especially in old age.
The occurrence of falls in the elderly in the previous year was also associated with depression in our study. This relationship has been analyzed in different places, and this has been repeatedly confirmed 29 . A study 48 assessed 149,876 elderly in the United States and showed that depression is an important risk factor for falls, as well as its recurrence. In a study 49 that analyzed the association of occurrence of previous falls with depression, it was found no significant results for this relationship in the male elderly.
From this analysis, some risk factors, such as reduced functional capacity, falls, and sleep difficulties can be alleviated with the adoption of new lifestyle habits. Reichert et al. 50 observed an inversely proportional relationship between depression and level of physical activity in the elderly, in which the more active ones demonstrated a lower prevalence of depression symptoms. Corroborating this finding, another study 51 found that reduced exercise increases the chances of developing depression and cognitive problems.
As a limiting factor is that the data analyzed in this study came from a cross-sectional survey and, therefore, no causal inferences can be made from our associations.

CONCLUSION
Depression in this group of elderly was mostly associated, at least in part, with modifiable factors. It indicates that depression in the elderly can be positively influenced by changes in habits and preventive interventions of these identified factors. Socialization, regular physical activity, and education should be strategies adopted to prevent depression in the elderly population.