Purpose: The population-based National Health Insurance database was used to investigate the trends, correlates, and disease patterns for elderly people in Taiwan who use antidepressants.
Methods: The National Health Research Institute provided a database of 1000,000 random subjects for study. We created a sample of subjects who were older than 65 years from 1997 to 2005. Trends, prevalence, and associated factors of antidepressant use were detected. We also examined the proportion of antidepressant use for psychiatric and medical disorders.
Results: The one-year prevalence of antidepressant use in elderly persons increased from 5.8 % in 1997 to 9.8 % in 2005. The one-year prevalence rates of tricyclic antidepressant (TCA), selective serotonin reuptake inhibitor (SSRI), serotonin-norepinephrine reuptake inhibitor (SNRI), serotonin modulator, and other antidepressant use in 2005 were 5.3, 2.6, 0.4, 2.9, and 0.6 %, respectively. Overall antidepressant use was higher for those in the 75- to 84-year-old age group, females, and those with higher Charlson Comorbidity Index scores. Among subjects using TCAs, 77.6 % users did not have a psychiatric diagnosis. Psychiatric disorders were commonly found in most SSRI and SNRI users (85.1 and 90.1 %, respectively). Subjects using SSRIs and SNRIs had higher proportions of psychiatric disorders such as neurotic depression, major depression, senile and presenile organic psychotic conditions, and anxiety.
Conclusion: The prevalence of antidepressant use among elderly persons increased greatly from 1997 to 2005. SSRIs, SNRIs, and other antidepressants were used mostly by subjects with psychiatric disorders, whereas TCAs were used mostly by subjects with nonpsychiatric disorders.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1007/s00127-015-1052-z | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Few Patients Are Treated for Both Obesity and Depression.
South Med J
February 2025
From the Center for Value-Based Care Research, Cleveland Clinic.
Objectives: Understanding the epidemiology of treatment for patients with co-occurring depression and obesity can inform care quality. The objective of the study was to identify how patients with obesity and newly diagnosed depression are treated and whether treatment is associated with body mass index change.
Methods: This cohort study included adults with obesity and newly diagnosed depression who had ≥2 primary care visits between 2015 and 2020 at a large integrated health system.
Article Synopsis
- Smoking is a significant public health issue in Tamil Nadu, causing preventable diseases and increasing healthcare costs, necessitating effective smoking cessation strategies in primary health care (PHC) settings.
- The study aims to evaluate the cost-effectiveness of three proposed smoking cessation strategies against the current standard strategy, focusing on various combinations of counseling, nicotine replacement therapy, and medications for smokers aged 15 and older.
- Results indicated that the current cessation strategy was more expensive than the proposed strategies, with two of them (PS1 and PS3) being more cost-effective, potentially leading to better resource allocation for smoking cessation efforts.
A network-based analysis anticipates time to recovery from major depression revealing a plasticity by context interplay.
Transl Psychiatry
January 2025
Center for Behavioral Sciences and Mental Health, Istituto Superiore di Sanità, Rome, Italy.
Predicting disease trajectories in patients with major depressive disorder (MDD) can allow designing personalized therapeutic strategies. In this study, we aimed to show that measuring patients' plasticity - that is the susceptibility to modify the mental state - identifies at baseline who will recover, anticipating the time to transition to wellbeing. We conducted a secondary analysis in two randomized clinical trials, STAR*D and CO-MED.
View Article and Find Full Text PDFInsights into prescribing patterns for antidepressants: an evidence-based analysis.
BMC Med Inform Decis Mak
January 2025
Department of Health Administration and Policy, College of Public Health, George Mason University, 4400 University Dr, Fairfax, VA, 22030, USA.
Background: Antidepressants are a primary treatment for depression, yet prescribing them poses significant challenges due to the absence of clear guidelines for selecting the most suitable option for individual patients. This study aimed to analyze prescribing patterns for antidepressants across healthcare providers, including physicians, physician assistants, nurse practitioners, and pharmacists, to better understand the complex factors influencing these patterns in the management of depression.
Methods: Least Absolute Shrinkage and Selection Operator (LASSO) regression was employed to identify variables that explained the variation in the prescribed antidepressants, utilizing a large number of claims.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!