v25id19987

ORIGINAL RESEARCH

 

Association between depression and quality of life in older adults: primary health care

 

Sônia Maria SoaresI; Patrícia Aparecida Barbosa SilvaII; Joseph Fabiano Guimarães SantosIII; Líliam Barbosa SilvaIV

I Nurse. Ph.D. in Public Health. Professor at the Nursing School of the Federal University of Minas Gerais. Belo Horizonte, Minas Gerais, Brazil. E-mail: smsoares.bhz@terra.com.br
II Nurse. Ph.D. in Nursing and Health, Nursing School of the Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil. E-mail: patygemeasbalp2016@gmail.com
III Physician. Ph.D. in Clinical Epidemiology, Governador Israel Pinheiro Hospital. Belo Horizonte, Minas Gerais, Brazil. E-mail: josephfgsantos@yahoo.com.br
IV Nurse. Ph.D. student of the Nursing School of the Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil. E-mail: ligemeasbh@yahoo.com.br
V Thanks go to the Foundation for Research Support of the state of Minas Gerais for funding (# APQ-00570-09 and APQ-03626-10).

DOI: http://dx.doi.org/10.12957/reuerj.2017.19987

 

 


ABSTRACT

Objective: to evaluate the association between depression and quality of life in older adults. Method: in this cross-sectional study involving 593 primary care users from Belo Horizonte, Minas Gerais, data were obtained using a structured questionnaire, from October 2010 to June 2012, after approval by the research ethics committees of the institutions involved (Opinions Nos. 0043.0.410.203-10 and 0043.0.410.203-10A). Data analysis was based on descriptive techniques and forward logistic regression. Results: the prevalence of depression was 15.5%. After controlling for confounding factors, the variables that continued to be significantly associated with the outcome were overall quality-of-life score lower than 60, self-reported depression, female sex, positive Alcohol Use Disorders Identification Test-Consumption and family income of less than three minimum wages. Conclusion: it was concluded that it is necessary to invest in mental health and well-being policies for older age groups and in training health personnel in early screening for depression.

Keywords: Depression; quality of life; aged; primary health care.


 

 

INTRODUCTION

Depression is the most prevalent mental disorder, and is the second leading cause of disability in the world after low back pain. It is associated with worsening of the general health status, loss of disability-adjusted life years, decreased productivity and it is a risk factor for early mortality and suicide 1. There is also a greater use of health services and operational costs 2.

A population-based study involving 17 countries identified the prevalence of depression ranging from 2.2% in Japan to 10.4% in Brazil. Thus, Brazil ranked first in the depression index compared to the other countries with its prevalence being higher among the younger age groups (10.9% vs. 3.9%; χ 2 = 36.1; p-value <0.001)3.

In a meta-analysis involving 74 studies conducted between 1955 and 2005, the prevalence of depressive symptoms in the geriatric population (≥60 years) was 10.3% (interquartile range 4.7% -16%) 4.

Authors warn that this variability in the prevalence of depression around the world is attributed to the combination of genetic vulnerability and environmental risk factors as well as cultural differences and psychometric features of depression detection instruments. Moreover, the quality of the methodology used to design studies should be taken into account 5.

Many risk factors for depression have been reported in the literature, such as being female6,7, race (Asian, mulatto or indigenous), low economic status, retired, history of heart problems, incapacity to perform basic and instrumental activities of daily living6, low schooling7, worse self-perception of health and dissatisfaction of life in general6,7, high body mass index and smoking 8. Depressive symptomatology is associated with increased risk of dementia 9, hospitalization, greater number of readmissions, and longer hospital stay in elderly men 10 as well as all-cause mortality 11. Studies have also shown an inverse correlation between quality of life (QoL) and depression as well as self-perceived health, which acts as a vulnerability factor for low QoL scores in the elderly 12-14.

These results reinforce the importance of depression in the geriatric population. However, although it is relevant in public health to investigate the prevalence of depression and associated factors, it is also necessary to analyze the impact on QoL. There is a greater investment in research involving institutionalized and hospitalized elderly and few studies in primary health care (PHC). Moreover, studies, where depression is evidenced only by the participant's self-report, are less consistent. Few studies have been concerned with categorizing participants clinically in different depression groups, or using scales with specific cutoff points that are indicative of categories of clinical diagnoses 14.

Hence, the objective of this investigation was to evaluate the association between depression and QoL in the elderly attended in PHC.

 

LITERATURE REVIEW

The term QoL has several concepts and reflects both macrossocial and sociodemographic influences; it is also subjective, dependent on the interpretations and perceptions of each individual 15.

For the World Health Organization, the definition of QoL refers to individual perception of one's own QoL, which is influenced by a range of factors, whether physical, psychological, social or environmental 16.

However, there are many threats to the QoL of elderly people, such as chronic non-communicable diseases, including depression. Prevention should be widely implemented employing an interdisciplinary and intersectoral approach to care that can contribute to the improvement of the health status and QoL of this population 17.

It is known that geriatric depression can go unnoticed by health professionals and family members and is probably under-treated. Its debilitating symptoms have a negative impact on the course of life and are associated with a decline in the general health status 18.

The unpreparedness of professionals to diagnose depression in the elderly contributes to the low recognition rate of depressive symptoms, such as anxiety, low self-esteem, loneliness, insomnia, helplessness and anhedonia and the consequent delay in establishing an effective therapy to solve the problem in the context of PHC 19.

Given the growing body of scientific evidence 2,7,20, depression is taking on a prominent role in as a comorbidity related to old age. In view of the above, it is recommended that all the elderly should be evaluated for mental health in order to diagnose depression, due to its significant repercussions.

In this setting, the performance of nurses in PHC is important, as nursing consultations can identify depressive symptoms, causal factors and health problems related to this morbidity 21.

 

METHODS

A cross-sectional study was made of 593 older adults registered in the 20 primary health care units of the Northwestern Sanitary District of Belo Horizonte, Minas Gerais from October 2010 to June 2012.

The study sample was non-probabilistic, as it depended on spontaneous demand and consultations programmed by the health teams during the data collection period. Calculation of the sample size, estimated using the Lwanga & Lemeshow formula 22, was based on the prevalence of depression in the elderly attended at the primary health care units (30.6%) 7, with a significance level of 5% and an absolute precision of 4%. The calculated sample size was 504 elderly. The final sample totaled 605 elderly, considering 20% of possible losses and represented 1.35% of the elderly population of the sanitary district.

The inclusion criteria were subjects of both genders, aged 60 or over, having used primary health care services in the district and agreed to participate in the research which included an interview. Elderly with severe cognitive impairment [Mini-Mental State Examination - MMSE ≤ 9] were excluded from the study because of the impossibility to complete the questionnaire 23.

Among the 605 elderly interviewed, 12 were excluded from the present study: three because they only completed the identification form, four because they did not answer more than 20% of the questions of the World Health Organization Quality of Life (WHOQOL-bref) questionnaire and five were <60 years, totaling 593 valid questionnaires (98% of the calculated sample).

Data collection was carried out by a previously trained team composed of three nurses and three scientific initiation students. Eligible elderly were approached in the primary health care units while waiting for medical care or other services in the morning or afternoon according to the availability of each interviewer.

Depressive symptoms were evaluated using the Patient Health Questionnaire-2 (PHQ-2), an abbreviated version of The Patient Health Questionnaire Depression Module (PHQ-9), a self-assessment scale with the total score ranging from 0 to 6 points; the higher the score, the greater the severity of depressive symptoms. Depression was characterized by a score ≥ 3 (sensitivity: 83% and specificity: 92%) suggesting a probable depressive state, according to a previous study 24. Some authors advocate the use of the PHQ-2 instead of PHQ-9, arguing that the high performance of the first instrument and its ease of application make its use feasible in PHC services, where the demand for tracking different clinical conditions is high and the time of attending people is short 25. The abbreviated version of the World Health Organization Quality of Life (WHOQOL-bref) in Portuguese was used to evaluate the individual's subjective perception of QoL. This instrument is a good measure of QoL in the elderly 13,26,27 and has been translated and validated in Brazil 28. The WHOQOL-bref has 26 items; the first two items assess the self-perception of QoL (here referred to as WHOQOL-1) and satisfaction with health (WHOQOL-2). The remaining 24 items are categorized into four domains: physical (seven items), psychological (six items), social relationships (three items) and environment (eight items) 29. Each of the 26 items are assigned a score ranging from 1 to 5. The score for each domain is transformed into a linear scale from 0 to 100 according to the syntax proposed by the WHOQOL group 30 reflecting worse or better evaluation of the QoL.

The cutoff score adopted to classify the QoL and satisfaction with health was 60 points (sensitivity: 95% and specificity: 54.4%). This cutoff point suggestive of worse QoL and health dissatisfaction (score <60) was proposed by the authors, the methodology for which is described in another publication 27. In brief, this method is based on the rationalization of the analysis by defining two extreme and simultaneous groups in relation to the perception of QoL and satisfaction with health. These groups were good QoL/satisfied (those who stated they had a good or very good QoL and felt satisfied or very satisfied with their health) and poor QoL/dissatisfied (those who stated they had poor or very poor QoL and felt dissatisfied or very dissatisfied with their health) 27.

Four groups were first created to define the QoL/satisfaction groups: G1 - Perception that the quality of life is good or very good = 381 individuals; G2 - Perception that the quality of life is poor or very poor = 35 individuals; G3 - Satisfied or very satisfied with their health = 371 individuals; G4 - Unsatisfied or very dissatisfied with their health = 103 individuals 27.

Subsequently, good QoL/satisfied and poor QoL/dissatisfied were defined: G5 - Good or very good quality of life and satisfied or very satisfied with their health (characteristics of G1 and G3: n = 289; 48.7%) and G6 - poor or very poor quality of life and dissatisfied or very dissatisfied with their health (characteristics of G2 and G4: n = 22; 3.7%) 27.

The dependent variable was depression, represented by individuals who obtained scores greater than or equal to three in the PHQ-2 instrument. This measure was dichotomized as PHQ ≥3 (1 = probable depression, 0 = otherwise) 24.

Independent variables included sociodemographic characteristics, clinical conditions, lifestyle and QoL. The sociodemographic variables were gender, age group (60-69, 70-79, 80 or more years), marital status (presence of spouse was defined as married or in a stable union), schooling (none; 4 or more years) and monthly family income (<3 or ≥3 minimum wages). The clinical conditions were number of comorbidities, self-reported comorbidities, cognitive level, habits (alcoholism, smoking, physical activity) and QoL [general quality of life score (GQoL): Physical, Psychological, Social Relationships and Environment; GQoL <60 points; QoL/satisfaction groups - G5 and G6].

The MMSE was used to assess the cognitive level; illiterate individuals with a score <13 were categorized as altered, as were those with up to eight years of schooling and a score <18, and those with more than eight years of schooling and a score <26 23.

Behavioral variables were categorized as follows: smoker (currently smokes or quit smoking within the previous 12 months), non-smoker (never smoked), ex-smoker (quit smoking more than 12 months previously). The Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) was used to evaluate alcohol consumption. Based on a previous validation study, a score ≥ 4 for men and ≥ 3 for women suggests alcohol abuse and this was adopted as a criterion in this study 31. Physical activity was considered for those who performed physical exercises on a regular basis at least three times per week for at least 30 minutes each session.

In the data analysis, frequencies and proportions were reported for the categorical variables and medians and interquartile range for continuous variables. The Kolmogorov-Smirnov test was used to analyze the normality of continuous variables. Percentages were compared using the chi-square test. The Mann-Whitney U test was applied to compare the medians between groups.

In the univariate analysis, a critical level for p-value ≤0.20 value was adopted for inclusion in the multivariate model. The logistic regression model employed the forward method to evaluate the direction and magnitude of associations for each independent variable with the response variable (PHQ ≥3). In this analysis, a p-value <0.05 was considered statistically significant. The values obtained are expressed as odds ratios with their respective 95% confidence intervals. The fit of the final model was evaluated by the goodness-of-fit test. Receiver-operating characteristic (ROC) curve analysis was performed to evaluate the discriminatory power of the score of 60 and the area under the curve (AUC) in predicting good QoL/satisfied or poor QoL/unsatisfied of the study sample. The diagnostic test considering the cutoff point of 60 was applied to groups G5 (good QoL/satisfied) and G6 (poor QoL/unsatisfied). The SPSS program (version 22.0) was used for all analyses.

Participation in this research was voluntary on signing an informed consent form. The study was approved by the Research Ethics Committee of the Federal University of Minas Gerais (# 0043.0.410.203-10) and by the Ethics Committee of the Municipal Health Department of Belo Horizonte (# 0043.0.410.203-10A) respecting all ethical precepts 32.

 

RESULTS

Characteristics of the sample

The median age of participants was 70 [interquartile range: 65-75 years]. Overall, 92 (15.5%) of the subjects had a diagnosis suggestive of depression (PHQ ≥3). Among the potentially depressed, 40 (43.5%) had scores of six points, indicating a more severe condition. It was observed that the group with depressive symptoms (PHQ ≥3) presented statistically lower scores (p-value <0.001) for all components of the WHOQOL-bref. In contrast, more than half of the sample (58.5%) scored zero in the PHQ-2 questionnaire. These individuals were four times more likely (OR: 4.01; 95% CI: 2.87-5.93) to obtain a QoL score >60 than the others (data not shown). Further details of the study sample are shown in Table 1.

Table 1: Baseline characteristics - crude and adjusted analysis of the scores of the Patient Health Questionnaire-2 (PHQ-2). Belo Horizonte, Minas Gerais, 2010 to 2012. (n = 593)

AUDIT-C: Alcohol Use Disorders Identification Test-Consumption; CI: Confidence interval; OR: Odds Ratio; PHQ-2: The Patient Health Questionnaire-2; GQoL: General quality of life; ref.: reference.
a Variations in total n due to missing data.
b Minimum wage during study period: R$510,00 in 2010, R$540,00 and R$545,00 in 2011, R$622,00 in 2012.
c Audit-C scores ≥ 4 for men and ≥ 3 for women suggest probably alcohol abuse. † p-value ≤ 0.05; ₸ p-value <0.001.

Quality of life of the elderly according to the WHOQOL-bref

Approximately 64.3% of the elderly perceived their QoL as good or very good and 5.9% as bad or very bad. Furthermore, 62.6% felt satisfied or very satisfied with their health, while 17.4% felt dissatisfied or very dissatisfied. Of the 381 elderly people with good or very good QoL, 75.9% were satisfied or very satisfied with their health (Group G5 - good QoL/satisfied). There were 35 elderly people with poor or very poor QoL; of these, 62.9% reported dissatisfaction or greatly dissatisfied with their health (Group G6 - poor QoL/unsatisfied). See Table 2.

Table 2: Frequency for the WHOQOL-1 and WHOQOL-2 variables by group of quality of life/satisfaction with health. Northwest Sanitary District, Belo Horizonte, Minas Gerais, 2010 to 2012. (n = 593)

WHOQOL: World Health Organization Quality of Life
a G6 – Poor quality of life/unsatisfied with health (n = 22).
b G5 - Good quality of life/satisfied with health (n = 289).
c Not defined (n = 282).
(a) Very unsatisfied; (b) unsatisfied; (c) not satisfied/not unsatisfied; (d) satisfied; (e) very satisfied.
[a] very poor; [b] poor; [c] not poor not good; [d] good; [e] very good.

The analysis of the ROC curve indicated the critical value 60 as the best cutoff point for the evaluation for perceived QoL and satisfaction with health. The area under the curve was 0.764 (95% CI: 0.726-0.802; p-value: <0.001) with a sensitivity of 80.62% and specificity of 57.57% for GQoL ≥60 in the elderly of Group G5 and sensitivity of 86.36% and specificity of 62.87% for GQoL <60 in elderly in Group G6 (Figure 1).


Figure 1: ROC curve demonstrating the sensitivity and specificity of cutoff points to predict good quality of life/satisfied with health or poor quality of life/unsatisfied with health corresponding to groups G5 and G6, respectively. Northwestern Sanitary District, Belo Horizonte, Minas Gerais, 2010 to 2012.

Factors associated with quality of life in the study sample

In the univariate analysis, the variables directly associated with the PHQ scores were being female (OR: 2.9; p-value = 0.001), monthly family income less than three minimum wages (OR: 2.3; p-value = 0.004), number of comorbidities (OR: 8.6; p-value = 0.004 for 3 or more comorbidities), arterial hypertension (OR: 2.3; p-value ≤0.005), diabetes mellitus (OR: 1.7; p-value = 0.040), osteomuscular diseases (OR: 1.9; p-value = 0.012), self-reported depression (OR: 5.4; p-value <0.001) and GQoL score <60 (OR: 7.7; p-value <0.001). On the other hand, alcohol consumption (OR: 0.3; p-value = 0.049) and physical activity (OR: 0.4; p-value = 0.012 for frequency 4 to 7 times a week) were inversely associated with depression (Table 1).

After adjusting for the confounding variables by means of multivariate logistic regression according to Table 1, the variables GQoL score <60 (OR: 8.6; p-value <0.001), self-reported depression (OR: 4.7; p-value <0.001), being female (OR: 3.2; p-value = 0.001), positive AUDIT-C (OR: 0.2; p-value = 0.015) and monthly family income less than three minimum wages (OR: 2.2; p-value = 0.012) maintained significant associations with the outcome (PHQ ≥3). The independent variables explained 25.28% (Pseudo R2 = 0.2528) of the variability of the odds of the dependent variable. The results of the adjustment tests of the multiple logistic regression models (Hosmer and Lemeshow) showed a good fit in the final model (Prob. Chi-square = 0.5549).

 

DISCUSSION

The prevalence of depression was high among the elderly (15.5%), however, lower than the rates reported by other Brazilian studies at the level of primary health care, with variations ranging from 26.1% to 30.6% 7,25,33.

A recent study in New York City, USA, involving primary care users, identified depression by screening using the PHQ instrument to be cost-effective with a gain of $1,726 per quality-adjusted life year. It is known that the underdiagnosis and under-treatment of depression increases disease burden and financial cost34.

Among the predictors of association with depression, the QoL score <60 was the independent variable with greatest power to explain the outcome; the elderly with a QoL score <60 were 8.6 times more likely to have depression compared to higher scores. Other studies also showed an inverse correlation between depression and QoL, as well as self-perception of health, which acts as a vulnerability factor for low QoL scores in the elderly 12-14.

In addition, there was evidence of an association between depression measured by the PHQ-2 instrument and self-reported depression. It is worth noting that among the 92 elderly people who presented scores suggestive of depression, 60 (65.2%) did not recognize this situation either because they were unaware of the diagnosis or because of their resistance to having this disease. It is known that the elderly are more susceptible to negating mental illnesses due to their experience of a period when mental disorders was highly stigmatized, considered a shameful state or a sign of mental weakness 35. Another possible explanation is the tendency of the elderly to consider depressive symptoms characteristic of the aging process 36. Geriatric depression may go unnoticed by health professionals and family members and is probably underdiagnosed. This is of great concern as delayed diagnosis implies a worse prognosis, and, consequently, it negatively affects the QoL of these individuals and their families.

An association was also found between being female and depressive symptoms with a 3.2 times greater risk compared to males; this corroborates other studies 6,14,37. One possible explanation for higher depression scores in elderly women may be attributed to a greater chance of admitting and complaining of depressive feelings than older men, who habitually hide their feelings more. Women achieve greater longevity, but are accompanied by a higher incidence of chronic diseases including depression and seek health services more often than men do.

Furthermore, there was an inverse relationship between depression and alcohol consumption. Older people with a positive screening for alcoholism measured by the AUDIT-C were 80 times less likely to have depression than those who did not drink alcohol, thus contradicting the literature 37. Moreover, the English Longitudinal Study of Aging (ELSA) showed that, for both genders, the consumption of moderate levels of alcohol was associated with better cognitive health, subjective well-being and less depressive symptoms than if they were abstinent 38.

Consistent with previous studies, depression in the elderly was also associated with low incomes 6,39. A study carried out in Turkey indicated that poverty became the main social determinant for loneliness in the elderly who, consequently, evolved with depression 39. Thus, a satisfactory financial situation enables people to engage in socio-cultural activities, increase purchasing power, and allows them to meet the needs of health care, autonomy and survival.

It is worth noting that there were questions related to the adoption of a cutoff point in the assessment of QoL using the WHOQOL-bref questionnaire 27. The test with a GQoL cutoff point of 60 had optimal sensitivity and negative predictive value for screening elderly patients with poor QoL/dissatisfied. The negative likelihood ratio showed that the effect on the posttest probability for negative results is large and serves as a good marker to track individuals with poor QoL/dissatisfied when the GQoL is less than 60; the sensitivity was 86.36% and negative predictive value was 99.17%.

Finally, some limitations of this investigation must be considered. First the cross-sectional nature of the study makes it impossible to determine causal relationships of the outcome and variables of interest. Second, non-probabilistic intentional sampling makes it impossible to reproduce this data in populations from other areas. Thirdly, there are few national studies of elderly populations on the subject for comparison purposes.

 

CONCLUSION

The underdiagnosis of depression in the elderly is of great concern. Of the predictors of depression, a worse perception of QoL and dissatisfaction of health status had a greater power of explanation of the outcome. It is necessary to invest in public policies aimed at mental health and well-being in the most advanced age groups and in training of health professionals for the early detection of depression.

Systematic efforts should be made to improve the living conditions and health of the elderly, both in the context of collective and individual care. The maintenance of the QoL is now a preponderant factor in the context of the development of public policies related to elderly care. Perhaps the failure of well-meaning plans are the result of disregarding the category within a multidimensional system that suffers and all the deprivations and limitations are reflected in its QoL.

Thus, it is hoped that this study will contribute to arouse the interest of health professionals, especially in the context of PHC, in respect to the early detection of depression, which can be achieved using specific tests and the clinical evaluation.

 

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