Development and External Validation of Models to Predict Need for Nursing Home Level of Care in Community-Dwelling Older Adults With Dementia.

Importance: Most older adults living with dementia ultimately need nursing home level of care (NHLOC). Objective: To develop models to predict need for NHLOC among older adults with probable dementia using self-report and proxy reports to aid patients and family with planning and care management. Design, Setting, and Participants: This prognostic study included data from 1998 to 2016 from the Health and Retirement Study (development cohort) and from 2011 to 2019 from the National Health and Aging Trends Study (validation cohort). Participants were community-dwelling adults 65 years and older with probable dementia. Data analysis was conducted between January 2022 and October 2023. Exposures: Candidate predictors included demographics, behavioral/health factors, functional measures, and chronic conditions. Main Outcomes and Measures: The primary outcome was need for NHLOC defined as (1) 3 or more activities of daily living (ADL) dependencies, (2) 2 or more ADL dependencies and presence of wandering/need for supervision, or (3) needing help with eating. A Weibull survival model incorporating interval censoring and competing risk of death was used. Imputation-stable variable selection was used to develop 2 models: one using proxy responses and another using self-responses. Model performance was assessed by discrimination (integrated area under the receiver operating characteristic curve [iAUC]) and calibration (calibration plots). Results: Of 3327 participants with probable dementia in the Health and Retirement Study, the mean (SD) age was 82.4 (7.4) years and 2301 (survey-weighted 70%) were female. At the end of follow-up, 2107 participants (63.3%) were classified as needing NHLOC. Predictors for both final models included age, baseline ADL and instrumental ADL dependencies, and driving status. The proxy model added body mass index and falls history. The self-respondent model added female sex, incontinence, and date recall. Optimism-corrected iAUC after bootstrap internal validation was 0.72 (95% CI, 0.70-0.75) in the proxy model and 0.64 (95% CI, 0.62-0.66) in the self-respondent model. On external validation in the National Health and Aging Trends Study (n = 1712), iAUC in the proxy and self-respondent models was 0.66 (95% CI, 0.61-0.70) and 0.64 (95% CI, 0.62-0.67), respectively. There was excellent calibration across the range of predicted risk. Conclusions and Relevance: This prognostic study showed that relatively simple models using self-report or proxy responses can predict need for NHLOC in community-dwelling older adults with probable dementia with moderate discrimination and excellent calibration. These estimates may help guide discussions with patients and families in future care planning.

Frequency of Screening for Colorectal Cancer by Predicted Life Expectancy Among Adults 76-85 Years.

This study assesses whether colorectal cancer screening varied by predicted life expectancy in a national sample of Veterans Affairs patients aged 76 to 85 years.

Development and External Validation of a Mortality Prediction Model for Community-Dwelling Older Adults With Dementia.

Importance: Estimating mortality risk in older adults with dementia is important for guiding decisions such as cancer screening, treatment of new and chronic medical conditions, and advance care planning. Objective: To develop and externally validate a mortality prediction model in community-dwelling older adults with dementia. Design, Setting, and Participants: This cohort study included community-dwelling participants (aged ≥65 years) in the Health and Retirement Study (HRS) from 1998 to 2016 (derivation cohort) and National Health and Aging Trends Study (NHATS) from 2011 to 2019 (validation cohort). Exposures: Candidate predictors included demographics, behavioral/health factors, functional measures (eg, activities of daily living [ADL] and instrumental activities of daily living [IADL]), and chronic conditions. Main Outcomes and Measures: The primary outcome was time to all-cause death. We used Cox proportional hazards regression with backward selection and multiple imputation for model development. Model performance was assessed by discrimination (integrated area under the receiver operating characteristic curve [iAUC]) and calibration (plots of predicted and observed mortality). Results: Of 4267 participants with probable dementia in HRS, the mean (SD) age was 82.2 (7.6) years, 2930 (survey-weighted 69.4%) were female, and 785 (survey-weighted 12.1%) identified as Black. Median (IQR) follow-up time was 3.9 (2.0-6.8) years, and 3466 (81.2%) participants died by end of follow-up. The final model included age, sex, body mass index, smoking status, ADL dependency count, IADL difficulty count, difficulty walking several blocks, participation in vigorous physical activity, and chronic conditions (cancer, heart disease, diabetes, lung disease). The optimism-corrected iAUC after bootstrap internal validation was 0.76 (95% CI, 0.75-0.76) with time-specific AUC of 0.73 (95% CI, 0.70-0.75) at 1 year, 0.75 (95% CI, 0.73-0.77) at 5 years, and 0.84 (95% CI, 0.82-0.85) at 10 years. On external validation in NHATS (n = 2404), AUC was 0.73 (95% CI, 0.70-0.76) at 1 year and 0.74 (95% CI, 0.71-0.76) at 5 years. Calibration plots suggested good calibration across the range of predicted risk from 1 to 10 years. Conclusions and Relevance: We developed and externally validated a mortality prediction model in community-dwelling older adults with dementia that showed good discrimination and calibration. The mortality risk estimates may help guide discussions regarding treatment decisions and advance care planning.

Do functional status and Medicare claims data improve the predictive accuracy of an electronic health record mortality index? Findings from a national Veterans Affairs cohort.

BACKGROUND: Electronic health record (EHR) prediction models may be easier to use in busy clinical settings since EHR data can be auto-populated into models. This study assessed whether adding functional status and/or Medicare claims data (which are often not available in EHRs) improves the accuracy of a previously developed Veterans Affairs (VA) EHR-based mortality index. METHODS: This was a retrospective cohort study of veterans aged 75 years and older enrolled in VA primary care clinics followed from January 2014 to April 2020 (n = 62,014). We randomly split participants into development (n = 49,612) and validation (n = 12,402) cohorts. The primary outcome was all-cause mortality. We performed logistic regression with backward stepwise selection to develop a 100-predictor base model using 854 EHR candidate variables, including demographics, laboratory values, medications, healthcare utilization, diagnosis codes, and vitals. We incorporated functional measures in a base + function model by adding activities of daily living (range 0-5) and instrumental activities of daily living (range 0-7) scores. Medicare data, including healthcare utilization (e.g., emergency department visits, hospitalizations) and diagnosis codes, were incorporated in a base + Medicare model. A base + function + Medicare model included all data elements. We assessed model performance with the c-statistic, reclassification metrics, fraction of new information provided, and calibration plots. RESULTS: In the overall cohort, mean age was 82.6 years and 98.6% were male. At the end of follow-up, 30,263 participants (48.8%) had died. The base model c-statistic was 0.809 (95% CI 0.805-0.812) in the development cohort and 0.804 (95% CI 0.796-0.812) in the validation cohort. Validation cohort c-statistics for the base + function, base + Medicare, and base + function + Medicare models were 0.809 (95% CI 0.801-0.816), 0.811 (95% CI 0.803-0.818), and 0.814 (95% CI 0.807-0.822), respectively. Adding functional status and Medicare data resulted in similarly small improvements among other model performance measures. All models showed excellent calibration. CONCLUSIONS: Incorporation of functional status and Medicare data into a VA EHR-based mortality index led to small but likely clinically insignificant improvements in model performance.

Venous thromboembolism (VTE) prevention and diagnosis in COVID-19: Practice patterns and outcomes at 33 hospitals.

BACKGROUND: Early reports of increased thrombosis risk with SARS-CoV-2 infection led to changes in venous thromboembolism (VTE) management. Real-world data on the prevalence, efficacy and harms of these changes informs best practices. OBJECTIVE: Define practice patterns and clinical outcomes related to VTE diagnosis, prevention, and management in hospitalized patients with coronavirus disease-19 (COVID-19) using a multi-hospital US sample. METHODS: In this retrospective cross-sectional study of 1121 patients admitted to 33 hospitals, exposure was dose of anticoagulant prescribed for VTE prophylaxis (standard, intensified, therapeutic), and primary outcome was VTE (pulmonary embolism [PE] and deep vein thrombosis [DVT]); secondary outcomes were PE, DVT, arterial thromboembolism (ATE), and bleeding events. Multivariable logistic regression models accounting for clustering by site and adjusted for risk factors were used to estimate odds ratios (ORs). Inverse probability weighting was used to account for confounding by indication. RESULTS: 1121 patients (mean age 60 ± 18, 47% female) admitted with COVID-19 between February 2, 2020 and December 31, 2020 to 33 US hospitals were included. Pharmacologic VTE prophylaxis was prescribed in 86%. Forty-seven patients (4.2%) had PE, 51 (4.6%) had DVT, and 23 (2.1%) had ATE. Forty-six patients (4.1%) had major bleeding and 46 (4.1%) had clinically relevant non-major bleeding. Compared to standard prophylaxis, adjusted odds of VTE were 0.67 (95% CI 0.21-2.1) with no prophylaxis, 1.0 (95% CI 0.06-17) with intensified, and 3.0 (95% CI 0.89-10) with therapeutic. Adjusted odds of bleeding with no prophylaxis were 5.6 (95% CI 3.0-11) and 5.3 (95% CI 3.0-10) with therapeutic (no events on intensified dosing). CONCLUSIONS: Therapeutic anticoagulation was associated with a 3-fold increased odds of VTE and 5-fold increased odds of bleeding. While higher bleeding rates with high-intensity prophylaxis were likely due to full-dose anticoagulation, we conclude that high thrombosis rates were due to clinical concern for thrombosis before formal diagnosis.

Long-term functional outcomes and mortality after hospitalization for extracranial hemorrhage.

BACKGROUND: The effects of extracranial hemorrhage (ECH), or bleeding outside the brain, are often considered transient. Yet, there are few data on the long-term and functional consequences of ECH. OBJECTIVE: Define the association of ECH hospitalization with functional independence and survival in a nationally representative cohort of older adults. DESIGN: Longitudinal cohort study. SETTINGS AND PARTICIPANTS: Data from the Health and Retirement Study from 1995 to 2016, a nationally representative, biennial survey of older adults. Adults aged 66 and above with Medicare linkage and at least 12 months of continuous Medicare Part A and B enrollment. INTERVENTION: Hospitalization for ECH. MAIN OUTCOMES AND MEASURES: Adjusted odds ratios and predicted likelihood of independence in all activities of daily living (ADLs), independence in all instrumental activities of daily living (IADLs) and extended nursing home stay. Adjusted hazard ratio and predicted likelihood for survival. RESULTS: In a cohort of 6719 subjects (mean age 77, 59% women) with average follow-up time of 8.3 years (55,767 person-years), 736 (11%) were hospitalized for ECH. ECH was associated with a 15% increase in ADL disability, 15% increase in IADL disability, 8% increase in nursing home stays, and 4% increase in mortality. After ECH, subjects became disabled and died at the same annual rate as pre-ECH but never recovered to pre-ECH levels of function. In conclusion, hospitalization for ECH was associated with significant and durable declines in independence and survival. Clinical and research efforts should incorporate the long-term harms of ECH into decision-making and strategies to mitigate these effects.

Predicting Life Expectancy to Target Cancer Screening Using Electronic Health Record Clinical Data.

BACKGROUND: Guidelines recommend breast and colorectal cancer screening for older adults with a life expectancy >10 years. Most mortality indexes require clinician data entry, presenting a barrier for routine use in care. Electronic health records (EHR) are a rich clinical data source that could be used to create individualized life expectancy predictions to identify patients for cancer screening without data entry. OBJECTIVE: To develop and internally validate a life expectancy calculator from structured EHR data. DESIGN: Retrospective cohort study using national Veteran's Affairs (VA) EHR databases. PATIENTS: Veterans aged 50+ with a primary care visit during 2005. MAIN MEASURES: We assessed demographics, diseases, medications, laboratory results, healthcare utilization, and vital signs 1 year prior to the index visit. Mortality follow-up was complete through 2017. Using the development cohort (80% sample), we used LASSO Cox regression to select ~100 predictors from 913 EHR data elements. In the validation cohort (remaining 20% sample), we calculated the integrated area under the curve (iAUC) and evaluated calibration. KEY RESULTS: In 3,705,122 patients, the mean age was 68 years and the majority were male (97%) and white (85%); nearly half (49%) died. The life expectancy calculator included 93 predictors; age and gender most strongly contributed to discrimination; diseases also contributed significantly while vital signs were negligible. The iAUC was 0.816 (95% confidence interval, 0.815, 0.817) with good calibration. CONCLUSIONS: We developed a life expectancy calculator using VA EHR data with excellent discrimination and calibration. Automated life expectancy prediction using EHR data may improve guideline-concordant breast and colorectal cancer screening by identifying patients with a life expectancy >10 years.

Long-term individual and population functional outcomes in older adults with atrial fibrillation.

BACKGROUND: Older adults with atrial fibrillation (AF) have multiple risk factors for disablement. Long-term function and the contribution of strokes to disability have not been previously characterized. Our objective was to determine long-term function among older adults with AF and the relative contribution of stroke. METHODS: We used data from the nationally representative Health and Retirement Study (1992-2014) with participants ≥65 years with incident AF. We examined the association of incident stroke with three outcomes: independence with activities of daily living (ADL), instrumental activities of daily living (IADL), and residence outside a nursing home (community-dwelling). We fit logistic regression models with repeated measures adjusting for comorbidities and demographics to estimate the effect of stroke on function. We estimated the contribution of strokes to the overall population burden of disability using the method of recycled predictions. RESULTS: Among 3530 participants (median age 79 years, 53% women), 262 had a stroke over 17,396 person-years. Independent of stroke and accounting for comorbidities, annually, ADL independence decreased by 4.4%, IADL independence decreased by 3.9%, and community dwelling decreased by 1.2% (p < 0.05 for all). Accounting for comorbidities, of those who experienced a stroke, 31.9% developed new ADL dependence, 26.5% developed new IADL dependence, and 8.6% newly moved to a nursing home (p < 0.05 for all). Considering all causes of function loss, 1.7% of ADL disability-years, 1.2% of IADL disability-years, and 7.3% of nursing home years could be attributed to stroke over 7.4 years. CONCLUSION: Older adults lose substantial function over time following AF diagnosis, independent of stroke. Stroke was associated with a significant functional decline and increase in the likelihood of nursing home move, but stroke did not accelerate subsequent disability accrual. Because of the high background rate of disability, stroke was not the dominant determinant of population-level disability in older adults with AF.

Geriatric Syndromes and Atrial Fibrillation: Prevalence and Association with Anticoagulant Use in a National Cohort of Older Americans.

BACKGROUND: Although guidelines recommend focusing primarily on stroke risk to recommend anticoagulants in atrial fibrillation (AF), physicians report that geriatric syndromes (e.g., falls and disability) are important when considering anticoagulants. Little is known about the prevalence of geriatric syndromes in older adults with AF or the association with anticoagulant use. METHODS: We performed a cross-sectional analysis of the 2014 Health and Retirement Study, a nationally representative study of older Americans. Participants were asked questions to assess domains of aging, including function, cognition, and medical conditions. We included participants 65 years and older with 2 years of continuous Medicare enrollment who met AF diagnosis criteria by claims codes. We examined five geriatric syndromes: one or more falls within the last 2 years, receiving help with activities of daily living (ADLs) or instrumental ADLs (IADL), experienced incontinence, and cognitive impairment. We determined the prevalence of geriatric syndromes and their association with anticoagulant use, adjusting for ischemic stroke risk (i.e., CHA2 DS2 -VASc score [congestive heart failure, hypertension, age, diabetes mellitus, stroke, vascular disease, and sex]). RESULTS: In this study of 779 participants with AF (median age = 80 years; median CHA2 DS2 -VASc score = 4), 82% had one or more geriatric syndromes. Geriatric syndromes were common: 49% reported falls, 38% had ADL impairments, 42% had IADL impairments, 37% had cognitive impairments, and 43% reported incontinence. Overall, 65% reported anticoagulant use; guidelines recommend anticoagulant use for 97% of participants. Anticoagulant use rate decreased for each additional geriatric syndrome (average marginal effect = -3.7%; 95% confidence interval = -1.4% to -5.9%). Lower rates of anticoagulant use were reported in participants with ADL dependency, IADL dependency, and dementia. CONCLUSION: Most older adults with AF had at least one geriatric syndrome, and geriatric syndromes were associated with reduced anticoagulant use. The high prevalence of geriatric syndromes may explain the lower than expected anticoagulant use in older adults.

Fingerstick Glucose Monitoring in Veterans Affairs Nursing Home Residents with Diabetes Mellitus.

BACKGROUND/OBJECTIVE: Guidelines recommend less intensive glycemic treatment and less frequent glucose monitoring for nursing home (NH) residents. However, little is known about the frequency of fingerstick (FS) glucose monitoring in this population. Our objective was to examine the frequency of FS glucose monitoring in Veterans Affairs (VA) NH residents with diabetes mellitus, type II (T2DM). DESIGN AND SETTING: National retrospective cohort study in 140 VA NHs. PARTICIPANTS: NH residents with T2DM and older than 65 years admitted to VA NHs between 2013 and 2015 following discharge from a VA hospital. MEASUREMENTS: NH residents were classified into five groups based on their highest hypoglycemia risk glucose-lowering medication (GLM) each day: no GLMs; metformin only; sulfonylureas; long-acting insulin; and any short-acting insulin. Our outcome was a daily count of FS measurements. RESULTS: Among 17,474 VA NH residents, mean age was 76 (standard deviation (SD) = 8) years and mean hemoglobin A1c was 7.6% (SD = 1.5%). On day 1 after NH admission, 49% of NH residents were on short-acting insulin, decreasing slightly to 43% at day 90. Overall, NH residents had an average of 1.9 (95% confidence interval (CI) = 1.8-1.9) FS measurements on NH day 1, decreasing to 1.4 (95% CI = 1.3-1.4) by day 90. NH residents on short-acting insulin had the most frequent FS measurements, with 3.0 measurements (95% CI = 2.9-3.0) on day 1, decreasing to 2.6 measurements (95% CI = 2.5-2.7) by day 90. Less frequent FS measurements were seen for NH residents receiving long-acting insulin (2.1 (95% CI = 2.0-2.2) on day 1) and sulfonylureas (1.7 (95% CI = 1.5-1.8) on day 1). Even NH residents on metformin monotherapy had 1.1 (95% CI = 1.1-1.2) measurements on day 1, decreasing to 0.5 (95% CI = 0.4-0.6) measurements on day 90. CONCLUSION: Although guidelines recommend less frequent glucose monitoring for NH residents, we found that many VA NH residents receive frequent FS monitoring. Given the uncertain benefits and potential for substantial patient burdens and harms, our results suggest decreasing FS monitoring may be warranted for many low hypoglycemia risk NH residents.

Long-term individual and population functional outcomes in older adults with atrial fibrillation.

BACKGROUND: Older adults with atrial fibrillation (AF) have multiple risk factors for disablement. Long-term function and the contribution of strokes to disability has not been previously characterized. METHODS: We performed a longitudinal, observational study in the nationally representative Health and Retirement Study (1992-2014). We included participants ≥65 years with Medicare claims who met incident AF diagnosis claims criteria. We examined the association of incident stroke with three functional outcomes: independence with activities of daily living (ADL) and instrumental activities of daily living (IADL) and community-dwelling. We fit separate logistic regression models with repeated measures adjusting for comorbidities and demographics to estimate the effect of stroke on function. We estimate the contribution of strokes to the overall population burden of functional impairment using the method of recycled predictions. RESULTS: Among 3530 participants (median age 79 years, 53% women, median CHA 2 DS 2 -VASc 5), 262 had a stroke over 17,396 person-years. Independent of stroke and accounting for population comorbidities, annually, ADL dependence increased by 4.4%, IADL dependence increased by 3.9%, and nursing home residence increased by 1.2% (p<0.05 for all). Accounting for comorbidities, of those who experienced a stroke, 31.9% developed new ADL dependence, 26.5% developed new IADL dependence, and 8.6% newly moved to a nursing home (p<0.05 for all). Considering all causes of function loss, 1.7% of ADL disability-years, 1.2% of IADL disability-years, and 7.3% of nursing home years could be attributed to stroke over 7.4years. CONCLUSION: Older adults lose substantial function over time following AF diagnosis, independent of stroke. Stroke was associated with a significant decline in function and an increase in the likelihood of nursing home move, but stroke did not accelerate subsequent disability accrual. Because of the high background rate of functional loss, stroke was not the dominant determinant of population-level disability in older adults with AF. IMPACT STATEMENT: We certify that this work is novel. Little is known about long-term function (ADL, IADL, community-dwelling) among older adults with AF and the association with stroke. This nationally representative study finds a high rate of function loss independent of stroke, and among those who suffer a stroke, a dramatic and immediate decline in function. Because of the high rate of function loss independent of stroke and the relatively low rate of stroke, on a population level, stroke is not the dominant determinant of disability in older adults with AF.

Long-term individual and population functional outcomes in older adults with atrial fibrillation.

BACKGROUND: Older adults with atrial fibrillation (AF) have multiple risk factors for disablement. Long-term function and the contribution of strokes to disability has not been previously characterized. METHODS: We performed a longitudinal, observational study in the nationally representative Health and Retirement Study (1992-2014). We included participants ≥65 years with Medicare claims who met incident AF diagnosis claims criteria. We examined the association of incident stroke with three functional outcomes: independence with activities of daily living (ADL) and instrumental activities of daily living (IADL) and community-dwelling. We fit separate logistic regression models with repeated measures adjusting for comorbidities and demographics to estimate the effect of stroke on function. We estimate the contribution of strokes to the overall population burden of functional impairment using the method of recycled predictions. RESULTS: Among 3530 participants (median age 79 years, 53% women, median CHA2DS2-VASc 5), 262 had a stroke over 17,396 person-years. Independent of stroke and accounting for population comorbidities, annually, ADL dependence increased by 4.4%, IADL dependence increased by 3.9%, and nursing home residence increased by 1.2% (p<0.05 for all). Accounting for comorbidities, of those who experienced a stroke, 31.9% developed new ADL dependence, 26.5% developed new IADL dependence, and 8.6% newly moved to a nursing home (p<0.05 for all). Considering all causes of function loss, 1.7% of ADL disability-years, 1.2% of IADL disability-years, and 7.3% of nursing home years could be attributed to stroke over 7.4years. CONCLUSION: Older adults lose substantial function over time following AF diagnosis, independent of stroke. Stroke was associated with a significant decline in function and an increase in the likelihood of nursing home move, but stroke did not accelerate subsequent disability accrual. Because of the high background rate of functional loss, stroke was not the dominant determinant of population-level disability in older adults with AF. IMPACT STATEMENT: We certify that this work is novel. Little is known about long-term function (ADL, IADL, community-dwelling) among older adults with AF and the association with stroke. This nationally representative study finds a high rate of function loss independent of stroke, and among those who suffer a stroke, a dramatic and immediate decline in function. Because of the high rate of function loss independent of stroke and the relatively low rate of stroke, on a population level, stroke is not the dominant determinant of disability in older adults with AF.

Clinical Outcomes and Costs Following Unplanned Excisions of Soft Tissue Sarcomas in the Elderly.

BACKGROUND: Surgical guidelines for soft tissue sarcoma (STS) emphasize pretreatment evaluation and reports of the perils of unplanned excision exist. Given the paucity of population-based data on this topic, our objective was to analyze clinical outcomes and costs of planned versus unplanned STS excisions in the Medicare population. METHODS: We analyzed 3913 surgical patients with STS ≥66 y old from 1992 to 2011 using the Surveillance, Epidemiology, and End Results-Medicare datafiles. Planned excisions were classified based on preoperative MRI and/or biopsy, whereas unplanned excisions were classified by excision as the first procedure. Inverse probability of treatment weighting with propensity scores was used to adjust for clinicopathologic differences. Re-excisions, complications, and Medicare payments were compared with multivariate models. Overall survival and disease-specific survival were analyzed using Cox proportional hazards and competing risk models. RESULTS: Before the first excision, 24.3% had an MRI and biopsy, 27.3% had an MRI, 11.4% had a biopsy, and 36.9% were unplanned. Re-excision rates were highest for unplanned excisions: 46.3% compared to 18.1%, 36.4%, and 29.7% for other groups (P < 0.0001). There was no difference in disease-specific survival or overall survival between groups (P > 0.05). Planned excisions were associated with increased Medicare costs (P < 0.05), with the first resection contributing to the majority of costs. Subgroup analyses by histologic grade and tumor size revealed similar results. CONCLUSIONS: Survival was comparable with greater health care costs in elderly patients undergoing planned STS excision. Although unplanned excisions remain a quality of care issue with high re-excision rates, these data have important implications for the surgical management of STS in the elderly.

A population-based analysis of increasing rates of suicide mortality in Japan and South Korea, 1985-2010.

BACKGROUND: In the past two decades, rates of suicide mortality have declined among most OECD member states. Two notable exceptions are Japan and South Korea, where suicide mortality has increased by 20 % and 280 %, respectively. METHODS: Population and suicide mortality data were collected through national statistics organizations in Japan and South Korea for the period 1985 to 2010. Age, period of observation, and birth cohort membership were divided into five-year increments. We fitted a series of intrinsic estimator age-period-cohort models to estimate the effects of age-related processes, secular changes, and birth cohort dynamics on the rising rates of suicide mortality in the two neighboring countries. RESULTS: In Japan, elevated suicide rates are primarily driven by period effects, initiated during the Asian financial crisis of the late 1990s. In South Korea, multiple factors appear to be responsible for the stark increase in suicide mortality, including recent secular changes, elevated suicide risks at older ages in the context of an aging society, and strong cohort effects for those born between the Great Depression and the aftermath of the Korean War. CONCLUSION: In spite of cultural, demographic and geographic similarities in Japan and South Korea, the underlying causes of increased suicide mortality differ across these societies-suggesting that public health responses should be tailored to fit each country's unique situation.

Clarifying hierarchical age-period-cohort models: A rejoinder to Bell and Jones.

Previously, Reither et al. (2015) demonstrated that hierarchical age-period-cohort (HAPC) models perform well when basic assumptions are satisfied. To contest this finding, Bell and Jones (2015) invent a data generating process (DGP) that borrows age, period and cohort effects from different equations in Reither et al. (2015). When HAPC models applied to data simulated from this DGP fail to recover the patterning of APC effects, B&J reiterate their view that these models provide "misleading evidence dressed up as science." Despite such strong words, B&J show no curiosity about their own simulated data--and therefore once again misapply HAPC models to data that violate important assumptions. In this response, we illustrate how a careful analyst could have used simple descriptive plots and model selection statistics to verify that (a) period effects are not present in these data, and (b) age and cohort effects are conflated. By accounting for the characteristics of B&J's artificial data structure, we successfully recover the "true" DGP through an appropriately specified model. We conclude that B&Js main contribution to science is to remind analysts that APC models will fail in the presence of exact algebraic effects (i.e., effects with no random/stochastic components), and when collinear temporal dimensions are included without taking special care in the modeling process. The expanded list of coauthors on this commentary represents an emerging consensus among APC scholars that B&J's essential strategy--testing HAPC models with data simulated from contrived DGPs that violate important assumptions--is not a productive way to advance the discussion about innovative APC methods in epidemiology and the social sciences.