Clinical outcomes, medical costs, and medication usage patterns of different somatic symptom disorders and functional somatic syndromes: a population-based study in Taiwan.

BACKGROUND: Somatic symptom disorders (SSD) and functional somatic syndromes (FSS) are often regarded as similar diagnostic constructs; however, whether they exhibit similar clinical outcomes, medical costs, and medication usage patterns has not been examined in nationwide data. Therefore, this study focused on analyzing SSD and four types of FSS (fibromyalgia, chronic fatigue syndrome, irritable bowel syndrome, functional dyspepsia). METHODS: This population-based matched cohort study utilized Taiwan's National Health Insurance (NHI) claims database to investigate the impact of SSD/FSS. The study included 2 615 477 newly diagnosed patients with SSD/FSS and matched comparisons from the NHI beneficiary registry. Healthcare utilization, mortality, medical expenditure, and medication usage were assessed as outcome measures. Statistical analysis involved Cox regression models for hazard ratios, generalized linear models for comparing differences, and adjustment for covariates. RESULTS: All SSD/FSS showed significantly higher adjusted hazard ratios for psychiatric hospitalization and all-cause hospitalization compared to the control group. All SSD/FSS exhibited significantly higher adjusted hazard ratios for suicide, and SSD was particularly high. All-cause mortality was significantly higher in all SSD/FSS. Medical costs were significantly higher for all SSD/FSS compared to controls. The usage duration of all psychiatric medications and analgesics was significantly higher in SSD/FSS compared to the control group. CONCLUSION: All SSD/FSS shared similar clinical outcomes and medical costs. The high hazard ratio for suicide in SSD deserves clinical attention.

Patterns, predictors, and patient-reported reasons for antidepressant discontinuation in the WHO World Mental Health Surveys.

BACKGROUND: Despite their documented efficacy, substantial proportions of patients discontinue antidepressant medication (ADM) without a doctor's recommendation. The current report integrates data on patient-reported reasons into an investigation of patterns and predictors of ADM discontinuation. METHODS: Face-to-face interviews with community samples from 13 countries (n = 30 697) in the World Mental Health (WMH) Surveys included n = 1890 respondents who used ADMs within the past 12 months. RESULTS: 10.9% of 12-month ADM users reported discontinuation-based on recommendation of the prescriber while 15.7% discontinued in the absence of prescriber recommendation. The main patient-reported reason for discontinuation was feeling better (46.6%), which was reported by a higher proportion of patients who discontinued within the first 2 weeks of treatment than later. Perceived ineffectiveness (18.5%), predisposing factors (e.g. fear of dependence) (20.0%), and enabling factors (e.g. inability to afford treatment cost) (5.0%) were much less commonly reported reasons. Discontinuation in the absence of prescriber recommendation was associated with low country income level, being employed, and having above average personal income. Age, prior history of psychotropic medication use, and being prescribed treatment from a psychiatrist rather than from a general medical practitioner, in comparison, were associated with a lower probability of this type of discontinuation. However, these predictors varied substantially depending on patient-reported reasons for discontinuation. CONCLUSION: Dropping out early is not necessarily negative with almost half of individuals noting they felt better. The study underscores the diverse reasons given for dropping out and the need to evaluate how and whether dropping out influences short- or long-term functioning.

Examining the role of living alone and loneliness in predicting health-related quality of life: results from the Healthy Aging Longitudinal Study in Taiwan (HALST).

PURPOSE: This study aimed to investigate the distinct yet interconnected aspects of social isolation, namely living alone and loneliness, and their individual and combined effects on predicting health-related quality of life (HRQoL). METHODS: A comprehensive analysis, encompassing both cross-sectional and longitudinal approaches, was conducted using a nationally representative sample of 5644 community-dwelling adults aged 55 and older from the Healthy Aging Longitudinal Study in Taiwan (HALST). RESULTS: Baseline data revealed that 9% of the sample reported living alone, while 10.3% reported experiencing loneliness, with 2.5% reporting both living alone and feeling lonely. Regression analyses consistently demonstrated that loneliness was significantly associated with concurrent and subsequent lower physical (PCS) and mental (MCS) component of HRQoL. Conversely, additional analyses indicated that living alone could indirectly exacerbate the adverse effects of loneliness or contribute to prolonged feelings of loneliness, subsequently predicting lower HRQoL after 3.2 year. CONCLUSION: In terms of practical implications, interventions and policies aiming to enhance HRQoL in older adults should give particular attention to those who report feelings of loneliness, especially individuals living alone.

Unlocking the Secrets Behind Advanced Artificial Intelligence Language Models in Deidentifying Chinese-English Mixed Clinical Text: Development and Validation Study.

BACKGROUND: The widespread use of electronic health records in the clinical and biomedical fields makes the removal of protected health information (PHI) essential to maintain privacy. However, a significant portion of information is recorded in unstructured textual forms, posing a challenge for deidentification. In multilingual countries, medical records could be written in a mixture of more than one language, referred to as code mixing. Most current clinical natural language processing techniques are designed for monolingual text, and there is a need to address the deidentification of code-mixed text. OBJECTIVE: The aim of this study was to investigate the effectiveness and underlying mechanism of fine-tuned pretrained language models (PLMs) in identifying PHI in the code-mixed context. Additionally, we aimed to evaluate the potential of prompting large language models (LLMs) for recognizing PHI in a zero-shot manner. METHODS: We compiled the first clinical code-mixed deidentification data set consisting of text written in Chinese and English. We explored the effectiveness of fine-tuned PLMs for recognizing PHI in code-mixed content, with a focus on whether PLMs exploit naming regularity and mention coverage to achieve superior performance, by probing the developed models' outputs to examine their decision-making process. Furthermore, we investigated the potential of prompt-based in-context learning of LLMs for recognizing PHI in code-mixed text. RESULTS: The developed methods were evaluated on a code-mixed deidentification corpus of 1700 discharge summaries. We observed that different PHI types had preferences in their occurrences within the different types of language-mixed sentences, and PLMs could effectively recognize PHI by exploiting the learned name regularity. However, the models may exhibit suboptimal results when regularity is weak or mentions contain unknown words that the representations cannot generate well. We also found that the availability of code-mixed training instances is essential for the model's performance. Furthermore, the LLM-based deidentification method was a feasible and appealing approach that can be controlled and enhanced through natural language prompts. CONCLUSIONS: The study contributes to understanding the underlying mechanism of PLMs in addressing the deidentification process in the code-mixed context and highlights the significance of incorporating code-mixed training instances into the model training phase. To support the advancement of research, we created a manipulated subset of the resynthesized data set available for research purposes. Based on the compiled data set, we found that the LLM-based deidentification method is a feasible approach, but carefully crafted prompts are essential to avoid unwanted output. However, the use of such methods in the hospital setting requires careful consideration of data security and privacy concerns. Further research could explore the augmentation of PLMs and LLMs with external knowledge to improve their strength in recognizing rare PHI.

Psychiatrist density and risk of suicide: a multilevel case-control study based on a national sample in Taiwan.

AIM: No previous studies, to our knowledge, have investigated the association between psychiatrist density and suicide, accounting for individual- and area-level characteristics. METHODS: We investigated all suicide cases in 2007-2017 identified from the national cause-of-death data files, with each suicide case matched to 10 controls by age and sex and each suicide case/control assigned to one of the 355 townships across Taiwan. Our primary outcome was the odds ratio (OR) of suicide and its 95% confidence interval (CI) estimated via multilevel models, which included both individual- and area-level characteristics. Townships with no psychiatrists were compared with the quartiles of townships with psychiatrists (density per 100,000 population): quartile 1 (Q1) (0.01-3.02); quartile 2 (Q2) (3.02-7.20); quartile 3 (Q3) (7.20-13.82); and quartile 4 (Q4) (>13.82). RESULTS: A total of 40,930 suicide cases and 409,300 age- and sex-matched controls were included. We found that increased psychiatrist density was associated with decreased suicide risk (Q1: adjusted OR [aOR], 0.95 [95% CI, 0.90-1.01]; Q2: aOR, 0.90 [95% CI, 0.85-0.96]; Q3: aOR, 0.89 [95% CI, 0.83-0.94]; Q4: aOR, 0.89 [95% CI, 0.83-0.95]) after adjusting for individual-level characteristics (employment state, monthly income, physical comorbidities, and the diagnosis of psychiatric disorders) and area socioeconomic characteristics. CONCLUSIONS: The psychiatrist density-suicide association suggests an effect of increased availability of psychiatric services on preventing suicide. Suicide prevention strategies could usefully focus on enhancing local access to psychiatric services.

Prospective Impacts of Social Participation Activities on Cognitive and Psychopathological Statuses in Community-Dwelling Older Adults.

OBJECTIVES: This study investigated the impact of social activities on cognitive functioning and psychopathological symptoms. METHODS: Participants aged 55 or older were enrolled through communities. Initial measures assessed demographic data, neuropsychological functioning, psychopathological state, and happiness. Social activities were evaluated using a modified 12-item tool, with 3-4 activities as the cutoff. Follow-up after 6-9 months included Mini-Mental State Examination (MMSE), Beck Depression Inventory - II (BDI-II), Beck Anxiety Inventory (BAI), Health Assessment Questionnaire (HAQ), and Patient Health Questionnaire-15 (PHQ-15) measurements. Predictive models for psychiatric and cognitive statuses were built using multiple linear regression, adjusting for baseline conditions. RESULTS: Initially, 516 older individuals enrolled, with 403 undergoing follow-up. During follow-up, the low participation group reported lower MMSE scores, higher BAI scores, and increased PHQ-15 risk. Negative correlations between social activity numbers and PHQ-15 results were found. Engagement in social clubs correlated positively with higher MMSE scores, while regular interactions with one's adult child(ren) were linked to decreased BAI scores. CONCLUSIONS: The quantity of social activities was associated with lower somatic distress. Social club engagement positively influenced cognition, and regular interactions with one's adult child(ren) mitigated anxiety among older individuals. CLINICAL IMPLICATIONS: Enough types of social activities, participating in social clubs, and adequate interactions with children protected against psychopathologies.

Population-attributable risk of psychiatric disorders for suicide among adolescents and young adults in Taiwan.

BACKGROUND: Youth suicide rates have increased markedly in some countries. This study aimed to estimate the population-attributable risk of psychiatric disorders associated with suicide among Taiwanese youth aged 10-24 years. METHODS: Data were obtained from the National Death Registry and National Health Insurance (NHI) claims database between 2007 and 2019. Youth who died by suicide were included, and comparisons, 1:10 matched by age and sex, were randomly selected from the Registry for NHI beneficiaries. We used multivariable logistic regression to estimate suicide odds ratios for psychiatric disorders. The population-attributable fractions (PAF) were calculated for each psychiatric disorder. RESULTS: A total of 2345 youth suicide and 23 450 comparisons were included. Overall, 44.8% of suicides had a psychiatric disorder, while only 7.9% of the comparisons had a psychiatric disorder. The combined PAF for all psychiatric disorders was 55.9%. The top three psychiatric conditions of the largest PAFs were major depressive disorder, dysthymia, and sleep disorder. In the analysis stratified by sex, the combined PAF was 45.5% for males and 69.2% for females. The PAF among young adults aged 20-24 years (57.0%) was higher than among adolescents aged 10-19 years (48.0%). CONCLUSIONS: Our findings of high PAF from major depressive disorder, dysthymia, and sleep disorder to youth suicides suggest that youth suicide prevention that focuses on detecting and treating mental illness may usefully target these disorders.

Antidepressant use in low- middle- and high-income countries: a World Mental Health Surveys report.

BACKGROUND: The most common treatment for major depressive disorder (MDD) is antidepressant medication (ADM). Results are reported on frequency of ADM use, reasons for use, and perceived effectiveness of use in general population surveys across 20 countries. METHODS: Face-to-face interviews with community samples totaling n = 49 919 respondents in the World Health Organization (WHO) World Mental Health (WMH) Surveys asked about ADM use anytime in the prior 12 months in conjunction with validated fully structured diagnostic interviews. Treatment questions were administered independently of diagnoses and asked of all respondents. RESULTS: 3.1% of respondents reported ADM use within the past 12 months. In high-income countries (HICs), depression (49.2%) and anxiety (36.4%) were the most common reasons for use. In low- and middle-income countries (LMICs), depression (38.4%) and sleep problems (31.9%) were the most common reasons for use. Prevalence of use was 2-4 times as high in HICs as LMICs across all examined diagnoses. Newer ADMs were proportionally used more often in HICs than LMICs. Across all conditions, ADMs were reported as very effective by 58.8% of users and somewhat effective by an additional 28.3% of users, with both proportions higher in LMICs than HICs. Neither ADM class nor reason for use was a significant predictor of perceived effectiveness. CONCLUSION: ADMs are in widespread use and for a variety of conditions including but going beyond depression and anxiety. In a general population sample from multiple LMICs and HICs, ADMs were widely perceived to be either very or somewhat effective by the people who use them.

Paternal age and 13 psychiatric disorders in the offspring: a population-based cohort study of 7 million children in Taiwan.

Although paternal age has been linked to certain psychiatric disorders, the nature of any causal relationship remains elusive. Here, we aimed to comprehensively assess the magnitude of a wide range of offspring's psychiatric risk conferred by paternal age, leveraging a pedigree inferred from covered-insurance relationship (accuracy >98%) in Taiwan's single-payer compulsory insurance program. We also examined whether there is an independent role of paternal age and explored the potential effect of parental age difference. A total cohort of 7,264,788 individuals born between 1980 and 2018 were included; 5,572,232 with sibling(s) were selected for sibling-comparison analyses and 1,368,942 and 1,044,420 children with information of paternal-grandparents and maternal-grandparents, respectively, were selected for multi-generation analyses. Using inpatient/outpatient claims data (1997-2018), we identified schizophrenia, autism, bipolar disorder (BPD), attention deficit-hyperactivity disorder (ADHD), major depressive disorder (MDD), eating disorder (ED), substance use disorder (SUD), mental retardation (MR), tic disorder, obsessive-compulsive disorder (OCD), anxiety, and somatoform disorder. We identified suicides using death certificates. Logistic regression analysis was used to estimate the paternal/maternal/grand-paternal age association with psychiatric risk in the offspring. The total cohort and sibling-comparison cohort resulted in similar estimates. Paternal age had a U-shaped relationship with offspring's MDD, ED, SUD, and anxiety. A very young maternal age (<20 years) was associated with markedly higher risk in offspring's SUD, MR, and suicide. Older paternal age (>25 years) was linearly associated with offspring's schizophrenia, autism, BPD, ADHD, MDD, ED, SUD, MR, OCD, anxiety, and suicide. Older grand-paternal age was linearly associated with offspring's schizophrenia, autism, ADHD, and MR. Dissimilar parental age was positively associated with offspring's ADHD, MDD, SUD, MR, anxiety, and suicide, and negatively associated with offspring's OCD. This comprehensive assessment provides solid evidence for the independent role of paternal age in psychiatric risk in the offspring and clarifies the significance of both early parenthood and delayed paternity.

Neurodevelopmental model of schizophrenia revisited: similarity in individual deviation and idiosyncrasy from the normative model of whole-brain white matter tracts and shared brain-cognition covariation with ADHD and ASD.

The neurodevelopmental model of schizophrenia is supported by multi-level impairments shared among schizophrenia and neurodevelopmental disorders. Despite schizophrenia and typical neurodevelopmental disorders, i.e., autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD), as disorders of brain dysconnectivity, no study has ever elucidated whether whole-brain white matter (WM) tracts integrity alterations overlap or diverge between these three disorders. Moreover, whether the linked dimensions of cognition and brain metrics per the Research Domain Criteria framework cut across diagnostic boundaries remains unknown. We aimed to map deviations from normative ranges of whole-brain major WM tracts for individual patients to investigate the similarity and differences among schizophrenia (281 patients subgrouped into the first-episode, subchronic and chronic phases), ASD (175 patients), and ADHD (279 patients). Sex-specific WM tract normative development was modeled from diffusion spectrum imaging of 626 typically developing controls (5-40 years). There were three significant findings. First, the patterns of deviation and idiosyncrasy of WM tracts were similar between schizophrenia and ADHD alongside ASD, particularly at the earlier stages of schizophrenia relative to chronic stages. Second, using the WM deviation patterns as features, schizophrenia cannot be separated from neurodevelopmental disorders in the unsupervised machine learning algorithm. Lastly, the canonical correlation analysis showed schizophrenia, ADHD, and ASD shared linked cognitive dimensions driven by WM deviations. Together, our results provide new insights into the neurodevelopmental facet of schizophrenia and its brain basis. Individual's WM deviations may contribute to diverse arrays of cognitive function along a continuum with phenotypic expressions from typical neurodevelopmental disorders to schizophrenia.

Interactions of Insomnia and Sedative-Hypnotic Drug Use Associated with Frailty Over Time Among Older Adults.

BACKGROUND: Insomnia and frailty are prevalent in older adults. This study aimed to elucidate the impact of insomnia and sedative-hypnotic use on the frailty rate over time. METHODS: We used data from community-dwelling older adults (mean ± SD age = 69.4 ± 8.2 years) from the Healthy Aging Longitudinal Study in Taiwan (HALST). A total of 4,744 participants were included in the study and were followed up for an average of 3.2 years. Frailty was assessed using the Fried criteria. Self-reported sleep problems, sedative-hypnotic use, and claims records from the National Health Insurance database were used. The generalized equation estimation (GEE) approach was applied to account for correlations between repeated measures. The average impact of insomnia and drug use on frailty over time was estimated by adjusting for potential confounding factors using the logic link in the GEE approach. RESULTS: The adjusted odds ratio (OR) of frailty was 1.41 (95% CI: [1.16, 1.72], Z-test statistics Z = 3.39, p <0.001) for insomnia and 1.52 ([1.16, 2.00], Z = 3.00, p = 0.0027) for sedative-hypnotic use. Interactions between insomnia and sedative-hypnotic use with frailty were not statistically significant. Long sleep duration > 8 hours, daytime sleepiness, and sleep apnea was also associated with an increased likelihood of developing frailty. Notably, a dose-response relationship between sedative-hypnotic drug use and frailty was observed. CONCLUSIONS: Insomnia and sedative-hypnotic use were independently associated with increased frailty. The implementation of nonpharmacological treatments to attenuate insomnia may reduce frailty rates.

Association between neighborhood availability of physical activity facilities and cognitive performance in older adults.

The existing evidence on the contextual influence of the availability of local facilities for physical activity on the cognitive health of elderly residents is sparse. This study examined the association between neighborhood physical activity facilities and cognitive health in older individuals. A cohort study of community-dwelling older adults was performed using baseline data and follow-up data from the Taiwan Biobank. Cognitive health was measured in 32,396 individuals aged 60-70 years using the Mini-Mental State Examination (MMSE) with follow-up information on 8025 participants. The district was used as the proxy for local neighborhood. To determine neighborhood physical activity facilities, school campuses, parks, activity centers, gyms, swimming pools, and stadiums were included. Multilevel linear regression models were applied to examine the associations of neighborhood physical activity facilities with baseline MMSE and MMSE decline during follow-up, with adjustment for individual factors and neighborhood socioeconomic characteristics. Multilevel analyses revealed that there was a neighborhood-level effect on cognitive health among older adults. After adjusting for compositional and neighborhood socioeconomic characteristics, baseline MMSE was higher in individuals living in the middle- (beta = 0.12, p-value = 0.140) and high-density facility (beta = 0.22, p-value = 0.025) groups than in the low-density group (p-value for trend-test = 0.031). MMSE decline during follow-up was slower in the middle- (beta = 0.15, p-value = 0.114) and high-density facility (beta = 0.27, p-value = 0.052) groups than in the low-density group (p-value for trend-test = 0.032). Greater neighborhood availability of physical activity facilities was associated with better cognitive health among older residents. These findings have implications for designing communities and developing strategies to support cognitive health of an aging population.

Evaluation of the optimal cutoff number of types of social participation activities in older people.

INTRODUCTION: Social participation activities have a close association with health aging. However, the clinical significance of numbers of social participation activities and its cutoff value has not been defined. METHODS: We recruited 516 people aged ≥55 years. Twelve social participation behaviors modified according to Taiwanese culture were investigated, and the adequacy of cutoff number was determined by the area under the receiver operating characteristic curve (AUC) according to the results of cluster analysis of individual activities and scores of the Brief Symptom Rating Scale-5 (BSRS-5) and the Chinese Happiness Inventory (CHI). Demographic, BSRS-5 and CHI data were then compared according to the candidate cutoff numbers. RESULTS: The distribution of the numbers of social activities suggested that the highest partition of numbers of social activities was 3 in women and 4 in men. The AUC regarding the cluster of activity types was 0.917, with the highest Youden's J value located between 3 and 4. The AUC regarding the cluster of activity types and scores of the BSRS-5 and the CHI was 0.929, with similar cutoffs. If 3 and 4 were used as cutoffs, the between-group differences of both the CHI and the BSRS-5 were significant. More types of social activities had a different engaging frequency with the 3 and 4 cutoffs. CONCLUSION: Our findings found an adequate cutoff with better differential power in the psychopathology and happiness of older people that provided a basis for application in intervention and policy formation.

Can peripheral biomarkers reflect the psychological condition in geriatric populations? The influence of cardiovascular comorbidities.

BACKGROUND: Although previous studies indicated the association between peripheral biomarkers and psychological conditions, a higher prevalence of cardiovascular diseases (CVD) among geriatric populations may hinder the applicability of the biomarkers. The objective of this study was to assess the adequacy of the application of biomarkers to evaluate psychological conditions among geriatric populations. METHOD: We collected information on the demographics and history of CVD in all participants. All participants completed the Brief Symptom Rating Scale (BSRS-5) and the Chinese Happiness Inventory (CHI), which are the measurement of negative and positive psychological conditions, respectively. Four indicators of the peripheral biomarkers, including the standard deviation of normal to normal RR intervals (SDNN), finger temperature, skin conductance, and electromyogram were collected for each participant during a 5-min resting state. Multiple linear regression models were conducted to evaluate the association between the biomarkers and the psychological measurements (BSRS-5, CHI) with and without the inclusion of the participants with CVD. RESULTS: A total of 233 participants without CVD (non-CVD group) and 283 participants with CVD (CVD group) were included. The CVD group was older and with higher body mass index compared to the non-CVD group. In the multiple linear regression model with all participants, only BSRS-5 scores had a positive association with electromyogram. After the exclusion of the CVD group, the association between the BSRS-5 scores and electromyogram was more relevant, while CHI scores became positively associated with SDNN. CONCLUSIONS: A single measurement of the peripheral biomarker may be insufficient to depict psychological conditions among geriatric populations.

Familial aggregation and shared genetic loading for major psychiatric disorders and type 2 diabetes.

AIMS/HYPOTHESIS: Psychiatric disorders, such as schizophrenia (SCZ), major depressive disorder (MDD) and bipolar disorder (BPD), are highly comorbid with type 2 diabetes. However, the mechanisms underlying such comorbidity are understudied. This study explored the familial aggregation of common psychiatric disorders and type 2 diabetes by testing family history association, and investigated the shared genetic loading between them by testing the polygenic risk score (PRS) association. METHODS: A total of 105,184 participants were recruited from the Taiwan Biobank, and genome-wide genotyping data were available for 95,238 participants. The Psychiatric Genomics Consortium-derived PRS for SCZ, MDD and BPD was calculated. Logistic regression was used to estimate the OR with CIs between a family history of SCZ/MDD/BPD and a family history of type 2 diabetes, and between the PRS and the risk of type 2 diabetes. RESULTS: A family history of type 2 diabetes was associated with a family history of SCZ (OR 1.23, 95% CI 1.08, 1.40), MDD (OR 1.19, 95% CI 1.13, 1.26) and BPD (OR 1.26, 95% CI 1.15, 1.39). Compared with paternal type 2 diabetes, maternal type 2 diabetes was associated with a higher risk of a family history of SCZ. SCZ PRS was negatively associated with type 2 diabetes in women (OR 0.92, 95% CI 0.88, 0.97), but not in men; the effect of SCZ PRS reduced after adjusting for BMI. MDD PRS was positively associated with type 2 diabetes (OR 1.04, 95% CI 1.00, 1.07); the effect of MDD PRS reduced after adjusting for BMI or smoking. BPD PRS was not associated with type 2 diabetes. CONCLUSIONS/INTERPRETATION: The comorbidity of type 2 diabetes with psychiatric disorders may be explained by shared familial factors. The shared polygenic loading between MDD and type 2 diabetes implies not only pleiotropy but also a shared genetic aetiology for the mechanism behind the comorbidity. The negative correlation between polygenic loading for SCZ and type 2 diabetes implies the role of environmental factors.

Causality of abdominal obesity on cognition: a trans-ethnic Mendelian randomization study.

BACKGROUND: Obesity has been associated with cognition in observational studies; however, whether its effect is confounding or a reverse causality remains inconclusive. This study aimed to investigate the causal relationships of overall obesity, measured by body mass index (BMI), and abdominal adiposity, measured by waist-hip ratio adjusted for BMI (WHRadjBMI), and cognition across European and Asian populations using Mendelian randomization (MR) analysis. METHODS: We used publicly available genome-wide association study (GWAS) summary data of European ancestry, including BMI (n = 322,154) and WHRadjBMI (n = 210,088) from the GIANT consortium, and cognition performance (n = 257,828) from the UK Biobank and COGENT consortium. Data for individuals of Asian ancestry were retrieved from Taiwan Biobank to perform GWAS for BMI (n = 65,689), WHRadjBMI (n = 65,683), and Mini-Mental State Examination (MMSE, n = 21,273). MR analysis was carried out using the inverse-variance weighted method for the main results. Further, we examined the overall pleiotropy by MR-Egger intercept, and detected and adjusted for possible outliers using MR PRESSO. RESULTS: No causal effect of BMI on cognition performance (beta [95% CI] = 0.00 [-0.07, 0.07], p value = 0.91) was found for Europeans; however, a 1-SD increase in WHRadjBMI was associated with a 0.07 standardized score decrease in cognition performance (beta [95% CI] = -0.07 [-0.12, -0.02], p value = 0.006). Further, no causal effect of BMI on MMSE (beta [95% CI] = 0.01 [-0.08, 0.10], p = 0.91) was found for Asians; however, a 1-SD increase in WHRadjBMI was associated with a 0.17 standardized score decrease in MMSE (beta [95% CI] = -0.17 [-0.30, -0.03], p = 0.02). In both populations, overall pleiotropy was not detected, and outliers did not affect the robustness of the main findings. CONCLUSIONS: This trans-ethnic MR study reveals that abdominal adiposity, as measured by WHR adjusted for BMI, impairs cognition, whereas weak evidence suggests that BMI impairs cognition.

Assessment of incident frailty hazard associated with depressive symptoms in a Taiwanese longitudinal study.

OBJECTIVES: To estimate the risks of depressive symptoms for developing frailty, accounting for baseline robust or pre-frailty status. DESIGN: An incident cohort study design. SETTING: Community dwellers aged 55 years and above from urban and rural areas in seven regions in Taiwan. PARTICIPANTS: A total of 2,717 participants from the Healthy Aging Longitudinal Study in Taiwan (HALST) were included. Subjects with frailty at baseline were excluded. The average follow-up period was 5.9 years. MEASUREMENTS: Depressive symptoms were measured by the 20-item Center for Epidemiological Studies Depression (CES-D) Scale. Frailty was assessed using the Fried frailty measurement. Participants were stratified by baseline robust or pre-frailty status to reduce the confounding effects of the shared criteria between depressive symptoms and frailty. Overall and stratified survival analyses were conducted to assess risks of developing frailty as a result of baseline depressive symptoms. RESULTS: One hundred individuals (3.7%) had depressive symptoms at baseline. Twenty-seven individuals (27.0%) with depressive symptoms developed frailty, whereas only 305 out of the 2,617 participants (11.7%) without depressive symptoms developed frailty during the follow-up period. After adjusting for covariates, depressive symptoms were associated with a 2.6-fold (95% CI 1.6, 4.2) increased hazard of incident frailty. The patterns of increased hazard were also observed when further stratified by baseline robust or pre-frailty status. CONCLUSIONS: Depressive symptoms increased the risk of developing frailty among the older Asian population. The impact of late-life depressive symptoms on physical health was notable. These findings also replicated results from Western populations. Future policies on geriatric public health need to focus more on treatment and intervention against geriatric depressive symptoms to prevent incident frailty among older population.

Ten-year trends in depression care in Taiwan.

BACKGROUND/PURPOSE: The number of psychiatrists working in community clinics in Taiwan has increased dramatically in the recent decade. This study aimed to investigate the trend of prevalence and incidence of depressive disorders and assess the quality of depression care between 2007 and 2016 in Taiwan. METHODS: We used the claims database derived from Taiwan's National Health Insurance (NHI) program, in which approximately 23.0 million individuals were enrolled, translating to a coverage rate of 99%. Patients with depressive disorders were identified based on International Classification of Diseases codes. The process indicators of depression care quality included visit, duration, and dose adequacy. The outcome indicators included the rate of psychiatric hospitalisation, emergency visit, self-harm hospitalisation, and suicide. RESULTS: The prevalence of treated depressive disorders increased from 1.61% in 2007 to 1.92% in 2016, i.e., a 25% increase, whereas the incidence of first-ever or recurrent depressive disorder did not change significantly. The number of patients treated by psychiatrists and in community clinics also increased. The quality of depression care improved, the proportion of patients receiving minimum psychiatric clinic follow-up and adequate medication increased, and the rate of emergency visits, psychiatric hospitalisation, and self-harm hospitalisation declined. CONCLUSION: The community-based psychiatric services increased and the quality indicators of depression care in Taiwan improved during 2007-2016. The causality warrants further investigations.

Toward measuring effective treatment coverage: critical bottlenecks in quality- and user-adjusted coverage for major depressive disorder.

BACKGROUND: Major depressive disorder (MDD) is a leading cause of morbidity and mortality. Shortfalls in treatment quantity and quality are well-established, but the specific gaps in pharmacotherapy and psychotherapy are poorly understood. This paper analyzes the gap in treatment coverage for MDD and identifies critical bottlenecks. METHODS: Seventeen surveys were conducted across 15 countries by the World Health Organization-World Mental Health Surveys Initiative. Of 35 012 respondents, 3341 met DSM-IV criteria for 12-month MDD. The following components of effective treatment coverage were analyzed: (a) any mental health service utilization; (b) adequate pharmacotherapy; (c) adequate psychotherapy; and (d) adequate severity-specific combination of both. RESULTS: MDD prevalence was 4.8% (s.e., 0.2). A total of 41.8% (s.e., 1.1) received any mental health services, 23.2% (s.e., 1.5) of which was deemed effective. This 90% gap in effective treatment is due to lack of utilization (58%) and inadequate quality or adherence (32%). Critical bottlenecks are underutilization of psychotherapy (26 percentage-points reduction in coverage), underutilization of psychopharmacology (13-point reduction), inadequate physician monitoring (13-point reduction), and inadequate drug-type (10-point reduction). High-income countries double low-income countries in any mental health service utilization, adequate pharmacotherapy, adequate psychotherapy, and adequate combination of both. Severe cases are more likely than mild-moderate cases to receive either adequate pharmacotherapy or psychotherapy, but less likely to receive an adequate combination. CONCLUSIONS: Decision-makers need to increase the utilization and quality of pharmacotherapy and psychotherapy. Innovations such as telehealth for training and supervision plus non-specialist or community resources to deliver pharmacotherapy and psychotherapy could address these bottlenecks.

Cohort selection for clinical trials using multiple instance learning.

Identifying patients eligible for clinical trials using electronic health records (EHRs) is a challenging task usually requiring a comprehensive analysis of information stored in multiple EHRs of a patient. The goal of this study is to investigate different methods and their effectiveness in identifying patients that meet specific eligibility selection criteria based on patients' longitudinal records. An unstructured dataset released by the n2c2 cohort selection for clinical trials track was used, each of which included 2-5 records manually annotated to thirteen pre-defined selection criteria. Unlike the other studies, we formulated the problem as a multiple instance learning (MIL) task and compared the performance with that of the rule-based and the single instance-based classifiers. Our official best run achieved an average micro-F score of 0.8765 which was ranked as one of the top ten results in the track. Further experiments demonstrated that the performance of the MIL-based classifiers consistently yield better performance than their single-instance counterparts in the criteria that require the overall comprehension of the information distributed among all of the patient's EHRs. Rule-based and single instance learning approaches exhibited better performance in criteria that don't require a consideration of several factors across records. This study demonstrated that cohort selection using longitudinal patient records can be formulated as a MIL problem. Our results exhibit that the MIL-based classifiers supplement the rule-based methods and provide better results in comparison to the single instance learning approaches.