Screening Depression Among Elderly in a City of Southeast Asia

Prevalence and risk factors of depression among elderly people in nursing homes from 2012 to 2022: a systematic review and meta-analysis

OBJECTIVES

To determine a pooled prevalence of depression and its influencing factors among nursing home residents.

METHOD

PsycINFO, PubMed, Embase, and Web of Science were searched for studies investigating the prevalence and risk factors of late-life depression among nursing home residents between January 2012 and November 2022. Two reviewers independently completed the literature screening, data extraction and quality assessment. A random-effects model was utilized to pool the prevalence of depression and summarize the influencing factors.

RESULTS

This meta-analysis included 48 studies involving 28,501 participants. The pooled prevalence of depressive mood and major depressive disorder was 53% and 27%, respectively. The rate of depressive mood is higher in lower-middle-income countries (60.0%), compared with high- (53.0%) and upper-middle-income countries (44.0%). The rate of depressive mood (35.0%) is higher among females than male (19.0%). Depression was influenced by factors, including male (OR = 0.28), insufficient income (OR = 3.53), comorbidities (OR = 2.66), pain (OR = 2.67; r = 0.31), functional disability (r = 0.33), loneliness (r = 0.43), number of chronic health problems (r = 0.18), social support (r = -0.28), activities of daily living (r = -0.43), subjective health (r = -0.28), autonomy (r = -0.41), environment (r = -0.50) and physical (r = -0.57) and psychological health (r = -0.65).

CONCLUSION

The prevalence of depressive mood is high among nursing home residents, especially in lower-middle-income countries. It is influenced by factors including gender, income, social support, daily activities, environment, physical and psychological health and autonomy. Understanding those factors can provide evidence-based recommendations for improved awareness, prevention and better management of late-life depression.

Screening of Depression in Elderly Population Using a Geriatric Depression Scale in the Field Practice Area of Urban Health Training Centre Attached to SMS Medical College, Jaipur

BACKGROUND AND OBJECTIVE

Depression is one of the most common illnesses worldwide, with more than 264 million people affected. Various studies in the elderly population have estimated the prevalence of depression across India, with results ranging from 6% to 62%. The objectives of this study were to estimate the prevalence of depression among the elderly population using a Geriatric Depression Scale (GDS) and to find out the association between various sociodemographic parameters and depression among elderly people.

MATERIALS AND METHODS

This cross-sectional study was conducted in the field practice area of Urban Health Training Centre (UHTC), attached to Sawai Man Singh (SMS) Medical College, Jaipur from September 2019 to July 2020 among elderly people. Some 250 participants were interviewed.

RESULTS

Depression was present in 41.6% of the study participants. Age group, gender, marital status, educational qualification, type of family, financial dependence, socioeconomic status, and presence of morbidity were significantly associated with the presence of depression among study participants (p<0.05).

CONCLUSION

The prevalence of depression in the urban elderly population was high (41.6%). By identifying risk factors for depression among the elderly population and screening them on time, we can reduce the severity and burden of the disease to a greater extent.

Prevalence of depression amongst the Elderly population in old age homes of Mangalore city

Context:

Depression is a silent killer. The people living in the old age homes (OAHs) appear to be overtly neglected by the community and depression is easily overlooked in such individuals especially in elderly people with comorbidities. Its early detection and treatment are imperative to improve quality of life.

Aim:

To find the prevalence of depression and the socio-demographic factors associated with depression among the elderly of OAHs.

Materials and Methods:

A Cross-sectional study in geriatric population of OAHs around Mangalore city was conducted over a duration of 5 months. About 142 elderly above the age of 60 years participated in the study. The study tools used were Geriatric Depression Scale-15 (GDS-15), Activities of Daily Living Scale (Katz index) and socio-demographic questionnaire.

Statistical Analysis Used:

The results were expressed in percentages and proportions. Univariate logistic regression analysis was done to find out the associated sociodemographic factors. Means and standard deviation of the GDS-15 and KATZ index scores were calculated and correlation was assessed between both the scores.

Results:

The overall prevalence of depression was 47.8% by using the GDS. The GDS score and Katz score were found to have a significant negative correlation. (r = -0.245 P = 0.003). Less social interaction amongst the peers was found to be associated with depression.

Conclusions:

The prevalence of depression in this study population was moderately high. Spending time with other residents was protective and functionally able people were less likely to have depression.

Comparison of the extent and prevalence of prescription of potentially inappropriate medications prescribed to geriatric age group residing in old-age homes versus those receiving care from tertiary care hospital using Beers criteria

Context:

Certain medications have higher chances of causing adverse effects in geriatric age group. Evidence is against prescribing these medications to the elderly. A list of such medications is called Beers criteria, which was revised by the American Geriatrics Society in 2015.

Aims:

Using the Beer's list as reference, the researchers intend to find the extent and prevalence of potentially inappropriate medication (PIM) in geriatric population residing in different settings.

Settings and Design:

The researchers analyzed prescription pattern of 200 individuals with age ≥65 years, 100 individuals from old-age homes (OAHs) and 100 individuals from a tertiary care hospital. After collecting data, the researchers tallied each prescription with list of drugs in Beers criteria to find all the possible PIMs in both the groups.

Results:

It was found that the average age of residents of OAHs was significantly higher (P < 0.002) than the corresponding group from a tertiary care hospital. The residents of OAHs were also a receiving significantly higher (P < 0.0001) number of PIM than their counterparts from the tertiary care hospital. The average number of PIMs prescribed to females in OAHs was also significantly higher than those in the other group. About 55% of residents of OAHs received at least one PIM, compared to just 26% in the other group. At least 27% of individuals of OAHs received two or more PIMs, compared to just 2% in a tertiary care hospital. Lorazepam was the most commonly prescribed PIM in OAHs, whereas ranitidine was the most common PIM in a tertiary care hospital. Ibuprofen was the second most common PIM, with 15% of OAHs residents receiving this drug, while none of the patients from a tertiary care hospital received ibuprofen.

Conclusion:

All the results point toward a poor prescription pattern in the residents of OAHs compared to those receiving care from a tertiary care hospital.

Adding life to years: Role of gender and social and family engagement in geriatric depression in rural areas of Northern India

Background:

Depression among elderly population is a major public health issue affecting nearly 5% to 7% of the world's elderly. In the coming years, a major share will be contributed by developing countries like India. In the rural areas of Allahabad district of Uttar Pradesh, there is scarce data on the depression.

Methodology:

A community-based cross-sectional study was conducted in rural Allahabad. A total of 411 elderly persons were selected from 2 blocks—Jasra and Bahadurpur—through multistage random sampling method. Short form of geriatric depression scale (GDS) was used to assess depression.

Results:

The prevalence of depression among elderly was 19.7%. On binary logistic regression, depression had significant association with female sex [aOR = 2.4, 95% CI 1.1–5.1], having less-than-good relationship with family members [aOR = 2.7, 95% CI 1.2–6.0], not being cared for during illness by family members [aOR = 3.9, 95% CI 1.2-12.9], not being involved in leisure time activities [aOR = 2.5, 95% CI 1.3–4.9], and not regularly meeting relatives and friends [aOR = 4.7, 95% CI 1.9–11.6].

Conclusions:

The prevalence of depression in elderly was high in rural areas of Allahabad. Female sex and social and family engagement are the important predictors of depression among them.

Prevalence of depression among the elderly (60 years and above) population in India, 1997-2016: a systematic review and meta-analysis

BACKGROUND

There is lack of information on the magnitude of depression among elderly population in India. This systematic review and meta-analysis aimed to estimate the prevalence of depression among elderly population in India.

METHODS

PubMed, Scopus, Web of Science, Embase, PsycINFO, IndMed, and Google Scholar were searched to identify articles reported community-based prevalence of depression among elderly population using screening tools. This study included the articles published during the years 1997 to 2016. Studies conducted in the special population groups, hospitals, reported only a subcategory of depression, and not specified the screening tool were excluded. Data were extracted from published reports and any missing information was requested from authors. Estimates were pooled using random-effects meta-analyses. Subgroup and sensitivity analysis were performed. The publication bias was evaluated by using Egger's test and visual inspection of the symmetry in funnel plots.

RESULTS

Fifty-one studies from 16 States of India were included as 56 datasets, which estimated the prevalence of depression among Indian elderly population as 34.4% (95% CI: 29.3-39.7). In sub-group analysis, the pooled prevalence was higher among females, rural populations, and in the eastern part of the country. Studies using non-probability sampling, and GDS and CES-D screening tool showed higher prevalence. Exclusion of the studies with sample size less than 100 and low-quality studies (score < 5/8) had no effect on the estimate of the prevalence. The studies that excluded dementia before assessment of depression had lower prevalence.

CONCLUSION

About one third elderly population of India suffered from depression with female preponderance. The estimates varied with type of study tool, geographic region, sampling methods, and presence of dementia. The pooled estimate should be interpreted with caution as the studies included in this review had varied methodological approach and screening tools.

Elder abuse: Screening in Iranian families

Background: The rate of elder abuse has been increasing worldwide. This study aimed at identifying the group of elders susceptible to abuse and determining the influential factors of elder abuse. Methods: A total of 683 elders, living in rural and urban areas of Qazvin (Iran), participated in this cross- sectional study that was conducted during September to December 2015. They were selected by stratified multistage random sampling method and filled in a standard questionnaire (H-S/EAST). Multiple logistic regression models were used for data analysis in Microsoft SPSS v.18. Type 1 error was considered equal to 0.05. Results: The average age of participants was 68.5±7.6. Also, the prevalence of elder abuse in this study was 38.5 (95% CI: 3.34- 42.3). After eliminating the confounders and applying multiple regression analysis, we found a significant association between elder abuse and factors such as education level (OR= 2.003, 95% CI: 1.177-3.409), residence (OR= 3.53, 95% CI: 1.969-6.324), and age (OR= 0.963, 95% CI: 0.931-0.995). Conclusion: The results of this study indicated a high prevalence of elder abuse in the studied population. By identifying high-risk individuals for elder abuse and planning to improve their quality of life, we will be able to successfully overcome this issue.