The Importance of Estimating Excess Deaths Regionally During the COVID-19 Pandemic.

National or statewide estimates of excess deaths have limited value to understanding the impact of the COVID-19 pandemic regionally. We assessed excess deaths in a 9-county geographically defined population that had low rates of COVID-19 and widescale availability of testing early in the pandemic, well-annotated clinical data, and coverage by 2 medical examiner's offices. We compared mortality rates (MRs) per 100,000 person-years in 2020 and 2021 with those in the 2019 reference period and MR ratios (MRRs). In 2020 and 2021, 177 and 219 deaths, respectively, were attributed to COVID-19 (MR = 52 and 66 per 100,000 person-years, respectively). COVID-19 MRs were highest in males, older persons, those living in rural areas, and those with 7 or more chronic conditions. Compared with 2019, we observed a 10% excess death rate in 2020 (MRR = 1.10 [95% CI, 1.04 to 1.15]), with excess deaths in females, older adults, and those with 7 or more chronic conditions. In contrast, we did not observe excess deaths overall in 2021 compared with 2019 (MRR = 1.04 [95% CI, 0.99 to 1.10]). However, those aged 18 to 39 years (MRR = 1.36 [95% CI, 1.03 to 1.80) and those with 0 or 1 chronic condition (MRR = 1.28 [95% CI, 1.05 to 1.56]) or 7 or more chronic conditions (MRR = 1.09 [95% CI, 1.03 to 1.15]) had increased mortality compared with 2019. This work highlights the value of leveraging regional populations that experienced a similar pandemic wave timeline, mitigation strategies, testing availability, and data quality.

Older Tissue Age Derived From Abdominal Computed Tomography Biomarkers of Muscle, Fat, and Bone Is Associated With Chronic Conditions and Higher Mortality.

OBJECTIVE: To determine whether body composition derived from medical imaging may be useful for assessing biologic age at the tissue level because people of the same chronologic age may vary with respect to their biologic age. METHODS: We identified an age- and sex-stratified cohort of 4900 persons with an abdominal computed tomography scan from January 1, 2010, to December 31, 2020, who were 20 to 89 years old and representative of the general population in Southeast Minnesota and West Central Wisconsin. We constructed a model for estimating tissue age that included 6 body composition biomarkers calculated from abdominal computed tomography using a previously validated deep learning model. RESULTS: Older tissue age associated with intermediate subcutaneous fat area, higher visceral fat area, lower muscle area, lower muscle density, higher bone area, and lower bone density. A tissue age older than chronologic age was associated with chronic conditions that result in reduced physical fitness (including chronic obstructive pulmonary disease, arthritis, cardiovascular disease, and behavioral disorders). Furthermore, a tissue age older than chronologic age was associated with an increased risk of death (hazard ratio, 1.56; 95% CI, 1.33 to 1.84) that was independent of demographic characteristics, county of residency, education, body mass index, and baseline chronic conditions. CONCLUSION: Imaging-based body composition measures may be useful in understanding the biologic processes underlying accelerated aging.

Abdominal Body Composition Reference Ranges and Association With Chronic Conditions in an Age- and Sex-Stratified Representative Sample of a Geographically Defined American Population.

BACKGROUND: Body composition can be accurately quantified from abdominal computed tomography (CT) exams and is a predictor for the development of aging-related conditions and for mortality. However, reference ranges for CT-derived body composition measures of obesity, sarcopenia, and bone loss have yet to be defined in the general population. METHODS: We identified a population-representative sample of 4 900 persons aged 20 to 89 years who underwent an abdominal CT exam from 2010 to 2020. The sample was constructed using propensity score matching an age and sex stratified sample of persons residing in the 27-county region of Southern Minnesota and Western Wisconsin. The matching included race, ethnicity, education level, region of residence, and the presence of 20 chronic conditions. We used a validated deep learning based algorithm to calculate subcutaneous adipose tissue area, visceral adipose tissue area, skeletal muscle area, skeletal muscle density, vertebral bone area, and vertebral bone density from a CT abdominal section. RESULTS: We report CT-based body composition reference ranges on 4 649 persons representative of our geographic region. Older age was associated with a decrease in skeletal muscle area and density, and an increase in visceral adiposity. All chronic conditions were associated with a statistically significant difference in at least one body composition biomarker. The presence of a chronic condition was generally associated with greater subcutaneous and visceral adiposity, and lower muscle density and vertebrae bone density. CONCLUSIONS: We report reference ranges for CT-based body composition biomarkers in a population-representative cohort of 4 649 persons by age, sex, body mass index, and chronic conditions.

Multilevel Implementation Strategies for Adolescent Human Papillomavirus Vaccine Uptake: A Cluster Randomized Clinical Trial.

Importance: Despite availability of a safe and effective vaccine, an estimated 36 500 new cancers in the US result from human papillomavirus (HPV) annually. HPV vaccine uptake falls short of national public health goals and lags other adolescent vaccines. Objective: To evaluate the individual and combined impact of 2 evidence-based interventions on HPV vaccination rates among 11- and 12-year-old children. Design, Setting, and Participants: The study team conducted a cluster randomized clinical trial with a stepped-wedge factorial design at 6 primary care practices affiliated with Mayo Clinic in southeastern Minnesota. Using block randomization to ensure balance of patient volumes across interventions, each practice was allocated to a sequence of four 12-month steps with the initial baseline step followed by 2 intermediate steps (none, 1, or both interventions) and a final step wherein all practices implemented both interventions. Each month, all eligible children who turned 11 or 12 years in the 2 months prior were identified and followed until the end of the step. Data were analyzed from April 2018 through March 2019. Participants included children who turned 11 or 12 years old and were due for a dose of the HPV vaccine. Interventions: Parents of eligible patients were mailed reminder/recalls following their child's birthdays. Health care professionals received confidential audit/feedback on their personal in-office success with HPV vaccine uptake via intra-campus mail. These 2 interventions were assessed separately and in combination. Main Outcomes and Measures: Eligible patients' receipt of any valid dose of HPV vaccine during the study step. Results: The cohort was comprised of 9242 11-year-olds (5165 [55.9%]) and 12-year-olds (4077 [44.1%]), and slightly more males (4848 [52.5%]). Parent reminder/recall resulted in 34.6% receiving a dose of HPV vaccine, health care professional audit/feedback, 30.4%, both interventions together resulted in 39.7%-all contrasted to usual care, 21.9%. Compared with usual care, the odds of HPV vaccination were higher for parent reminder/recall (odds ratio [OR], 1.56; 95% CI, 1.23-1.97) and for the combination of parent reminder/recall and health care professional audit/feedback (OR, 2.03; 95% CI, 1.44-2.85). Health care professional audit/feedback alone did not differ significantly from usual care (OR, 1.19; 95% CI, 0.94-1.51). Conclusions and Relevance: In this cluster randomized trial, the combination of parent reminder/recall and health care professional audit/feedback increased the odds of HPV vaccination compared with usual care. These findings underscore the value of simultaneous implementation of evidence-based strategies to improve HPV vaccination.

Exploring social determinants of health and physical activity levels in older adults living with mild cognitive impairment and dementia in the Upper Midwest of the United States.

BACKGROUND: Physical activity can improve physical health for people living with mild cognitive impairment (MCI) and dementia and may have cognitive benefits. Identifying modifiable social factors inhibiting physical activity among this group is needed. We sought to examine the relationship between reported physical activity levels and social determinants of health (SDOH) in a population of older adults living with MCI or dementia. METHODS: This descriptive study included people with a diagnosis of MCI or dementia followed by Community Internal Medicine at Mayo Clinic (Rochester, Minnesota, United States), aged over 55 years, who had a clinic visit between June 1, 2019 and June 30, 2021 and had completed a SDOH questionnaire. We focused on 8 SDOH domains: education, depression, alcohol use, stress, financial resource strain, social connections, food insecurity, and transportation needs. Data were analyzed based on physical activity level (inactive, insufficiently active, sufficiently active). SDOH domains were compared according to physical activity level using the χ2 test and multinomial logistic regression. RESULTS: A total of 3224 persons with MCI (n = 1371) or dementia (n = 1853) who had completed questions on physical activity were included. Of these, 1936 (60%) were characterized as physically inactive and 837 (26%) insufficiently active. Characteristics associated with an increased likelihood of physical inactivity were older age, female sex, obesity, lower education, dementia diagnosis, screening positive for depression and increased social isolation (p < 0.001). CONCLUSIONS: Physical inactivity is common among people living with MCI and dementia. Physical activity levels may be influenced by many factors, highlighting potential areas for intervention.

Biomarkers of cellular senescence and risk of death in humans.

A robust and heterogenous secretory phenotype is a core feature of most senescent cells. In addition to mediators of age-related pathology, components of the senescence associated secretory phenotype (SASP) have been studied as biomarkers of senescent cell burden and, in turn, biological age. Therefore, we hypothesized that circulating concentrations of candidate senescence biomarkers, including chemokines, cytokines, matrix remodeling proteins, and growth factors, could predict mortality in older adults. We assessed associations between plasma levels of 28 SASP proteins and risk of mortality over a median follow-up of 6.3 years in 1923 patients 65 years of age or older with zero or one chronic condition at baseline. Overall, the five senescence biomarkers most strongly associated with an increased risk of death were GDF15, RAGE, VEGFA, PARC, and MMP2, after adjusting for age, sex, race, and the presence of one chronic condition. The combination of biomarkers and clinical and demographic covariates exhibited a significantly higher c-statistic for risk of death (0.79, 95% confidence interval (CI): 0.76-0.82) than the covariates alone (0.70, CI: 0.67-0.74) (p < 0.001). Collectively, these findings lend further support to biomarkers of cellular senescence as informative predictors of clinically important health outcomes in older adults, including death.

Association Between Fluctuations in Blood Lipid Levels Over Time With Incident Alzheimer Disease and Alzheimer Disease-Related Dementias.

BACKGROUND AND OBJECTIVES: Prevention strategies for Alzheimer disease and Alzheimer disease-related dementias (AD/ADRDs) are urgently needed. Lipid variability, or fluctuations in blood lipid levels at different points in time, has not been examined extensively and may contribute to the risk of AD/ADRD. Lipid panels are a part of routine screening in clinical practice and routinely available in electronic health records (EHR). Thus, in a large geographically defined population-based cohort, we investigated the variation of multiple lipid types and their association to the development of AD/ADRD. METHODS: All residents living in Olmsted County, Minnesota on the index date January 1, 2006, aged 60 years or older without an AD/ADRD diagnosis were identified. Persons with ≥3 lipid measurements including total cholesterol, triglycerides, low-density lipoprotein cholesterol (LDL-C), or high-density lipoprotein cholesterol (HDL-C) in the 5 years before index date were included. Lipid variation was defined as any change in individual's lipid levels over time regardless of direction and was measured using variability independent of the mean (VIM). Associations between lipid variation quintiles and incident AD/ADRD were assessed using Cox proportional hazards regression. Participants were followed through 2018 for incident AD/ADRD. RESULTS: The final analysis included 11,571 participants (mean age 71 years; 54% female). Median follow-up was 12.9 years with 2,473 incident AD/ADRD cases. After adjustment for confounding variables including sex, race, baseline lipid measurements, education, BMI, and lipid-lowering treatment, participants in the highest quintile of total cholesterol variability had a 19% increased risk of incident AD/ADRD, and those in highest quintile of triglycerides, variability had a 23% increased risk. DISCUSSION: In a large EHR derived cohort, those in the highest quintile of variability for total cholesterol and triglyceride levels had an increased risk of incident AD/ADRD. Further studies to identify the mechanisms behind this association are needed.

Health Care Utilization and Death in Patients With Heart Failure During the COVID-19 Pandemic.

Objective: To compare the 1-year health care utilization and mortality in persons living with heart failure (HF) before and during the coronavirus disease 2019 (COVID-19) pandemic. Patients and Methods: Residents of a 9-county area in southeastern Minnesota aged 18 years or older with a HF diagnosis on January 1, 2019; January 1, 2020; and January 1, 2021, were identified and followed up for 1-year for vital status, emergency department (ED) visits, and hospitalizations. Results: We identified 5631 patients with HF (mean age, 76 years; 53% men) on January 1, 2019, 5996 patients (mean age, 76 years; 52% men) on January 1, 2020, and 6162 patients (mean age, 75 years; 54% men) on January 1, 2021. After adjustment for comorbidities and risk factors, patients with HF in 2020 and patients with HF in 2021 experienced similar risks of mortality compared with those in 2019. After adjustment, patients with HF in 2020 and 2021 were less likely to experience all-cause hospitalizations (2020: rate ratio [RR], 0.88; 95% CI, 0.81-0.95; 2021: RR, 0.90; 95% CI, 0.83-0.97) compared with patients in 2019. Patients with HF in 2020 were also less likely to experience ED visits (RR, 0.85; 95% CI, 0.80-0.92). Conclusion: In this large population-based study in southeastern Minnesota, we observed an approximately 10% decrease in hospitalizations among patients with HF in 2020 and 2021 and a 15% decrease in ED visits in 2020 compared with those in 2019. Despite the change in health care utilization, we found no difference in the 1-year mortality between patients with HF in 2020 and those in 2021 compared with those in 2019. It is unknown whether any longer-term consequences will be observed.

Cohort study examining associations between ceramide levels and risk of multimorbidity among persons participating in the Mayo Clinic Biobank.

OBJECTIVE: Ceramides have been associated with several ageing-related conditions but have not been studied as a general biomarker of multimorbidity (MM). Therefore, we determined whether ceramide levels are associated with the rapid development of MM. DESIGN: Retrospective cohort study. SETTING: Mayo Clinic Biobank. PARTICIPANTS: 1809 persons in the Mayo Clinic Biobank ≥65 years without MM at the time of enrolment, and with ceramide levels assayed from stored plasma. PRIMARY OUTCOME MEASURE: Persons were followed for a median of 5.7 years through their medical records to identify new diagnoses of 20 chronic conditions. The number of new conditions was divided by the person-years of follow-up to calculate the rate of accumulation of new chronic conditions. RESULTS: Higher levels of C18:0 and C20:0 were associated with a more rapid rate of accumulation of chronic conditions (C18:0 z score RR: 1.30, 95% CI: 1.10 to 1.53; C20:0 z score RR: 1.26, 95% CI: 1.07 to 1.49). Higher C18:0 and C20:0 levels were also associated with an increased risk of hypertension and coronary artery disease. CONCLUSIONS: C18:0 and C20:0 were associated with an increased risk of cardiometabolic conditions. When combined with biomarkers specific to other diseases of ageing, these ceramides may be a useful component of a biomarker panel for predicting accelerated ageing.

Variability in Lipid Levels and Risk for Cardiovascular Disease: An Electronic Health Record-Based Population Cohort Study.

Background Larger within-patient variability of lipid levels has been associated with increased risk of cardiovascular disease (CVD); however, measures of lipid variability require ≥3 measurements and are not currently used clinically. We investigated the feasibility of calculating lipid variability within a large electronic health record-based population cohort and assessed associations with incident CVD. Methods and Results We identified all individuals ≥40 years of age who resided in Olmsted County, MN, on January 1, 2006 (index date), without prior CVD, defined as myocardial infarction, coronary artery bypass graft surgery, percutaneous coronary intervention, or CVD death. Patients with ≥3 measurements of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, or triglycerides during the 5 years before the index date were retained. Lipid variability was calculated using variability independent of the mean. Patients were followed through December 31, 2020 for incident CVD. We identified 19 652 individuals (mean age 61 years; 55% female), who were CVD-free and had variability independent of the mean calculated for at least 1 lipid type. After adjustment, those with highest total cholesterol variability had a 20% increased risk of CVD (Q5 versus Q1 hazard ratio, 1.20 [95% CI, 1.06-1.37]). Results were similar for low-density lipoprotein cholesterol and high-density lipoprotein cholesterol. Conclusions In a large electronic health record-based population cohort, high variability in total cholesterol, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol was associated with an increased risk of CVD, independent of traditional risk factors, suggesting it may be a possible risk marker and target for intervention. Lipid variability can be calculated in the electronic health record environment, but more research is needed to determine its clinical utility.

Integrating Environmental Data with Medical Data in a Records-Linkage System to Explore Groundwater Nitrogen Levels and Child Health Outcomes.

Background: The Rochester Epidemiology Project (REP) medical records-linkage system offers a unique opportunity to integrate medical and residency data with existing environmental data, to estimate individual-level exposures. Our primary aim was to provide an archetype of this integration. Our secondary aim was to explore the association between groundwater inorganic nitrogen concentration and adverse child and adolescent health outcomes. Methods: We conducted a nested case-control study in children, aged seven to eighteen, from six counties of southeastern Minnesota. Groundwater inorganic nitrogen concentration data were interpolated, to estimate exposure across our study region. Residency data were then overlaid, to estimate individual-level exposure for our entire study population (n = 29,270). Clinical classification software sets of diagnostic codes were used to determine the presence of 21 clinical conditions. Regression models were adjusted for age, sex, race, and rurality. Results: The analyses support further investigation of associations between nitrogen concentration and chronic obstructive pulmonary disease and bronchiectasis (OR: 2.38, CI: 1.64-3.46) among boys and girls, thyroid disorders (OR: 1.44, CI: 1.05-1.99) and suicide and intentional self-inflicted injury (OR: 1.37, CI: >1.00-1.87) among girls, and attention deficit conduct and disruptive behavior disorders (OR: 1.34, CI: 1.24-1.46) among boys. Conclusions: Investigators with environmental health research questions should leverage the well-enumerated population and residency data in the REP.

Synergistic interactions of obesity with sex, education, and smoking and accumulation of multi-morbidity (MM) across the lifespan.

Objectives: Obesity is a potentially modifiable risk factor that has been consistently associated with the development and progression of multi-morbidity (MM). However, obesity may be more problematic for some persons compared to others because of interactions with other risk factors. Therefore, we studied the effect of interactions between patient characteristics and overweight and obesity on the rate of accumulation of MM. Methods: We studied 4 cohorts of persons ages 20-, 40-, 60-, and 80-years residing in Olmsted County, Minnesota between 2005 and 2014 using the Rochester Epidemiology Project (REP) medical records-linkage system. Body mass index, sex, race, ethnicity, education, and smoking status were extracted from REP indices. The rate of accumulation of MM was calculated as the number of new chronic conditions accumulated per 10 person years through 2017. Poisson rate regression models were used to identify associations between characteristics and rate of MM accumulation. Additive interactions were summarized using relative excess risk due to interaction, attributable proportion of disease, and the synergy index. Results: Greater than additive synergistic associations were observed between female sex and obesity in the 20- and 40-year cohorts, between low education and obesity in the 20-year cohort (both sexes), and between smoking and obesity in the 40-year cohort (both sexes). Conclusions: Interventions targeted at women, persons with lower education, and smokers who also have obesity may result in the greatest reduction in the rate of MM accumulation. However, interventions may need to focus on persons prior to mid-life to have the greatest effect.

Predictors of Metformin Failure: Repurposing Electronic Health Record Data to Identify High-Risk Patients.

CONTEXT: Metformin is the first-line drug for treating diabetes but has a high failure rate. OBJECTIVE: To identify demographic and clinical factors available in the electronic health record (EHR) that predict metformin failure. METHODS: A cohort of patients with at least 1 abnormal diabetes screening test that initiated metformin was identified at 3 sites (Arizona, Mississippi, and Minnesota). We identified 22 047 metformin initiators (48% female, mean age of 57 ± 14 years) including 2141 African Americans, 440 Asians, 962 Other/Multiracial, 1539 Hispanics, and 16 764 non-Hispanic White people. We defined metformin failure as either the lack of a target glycated hemoglobin (HbA1c) (<7%) within 18 months of index or the start of dual therapy. We used tree-based extreme gradient boosting (XGBoost) models to assess overall risk prediction performance and relative contribution of individual factors when using EHR data for risk of metformin failure. RESULTS: In this large diverse population, we observed a high rate of metformin failure (43%). The XGBoost model that included baseline HbA1c, age, sex, and race/ethnicity corresponded to high discrimination performance (C-index of 0.731; 95% CI 0.722, 0.740) for risk of metformin failure. Baseline HbA1c corresponded to the largest feature performance with higher levels associated with metformin failure. The addition of other clinical factors improved model performance (0.745; 95% CI 0.737, 0.754, P < .0001). CONCLUSION: Baseline HbA1c was the strongest predictor of metformin failure and additional factors substantially improved performance suggesting that routinely available clinical data could be used to identify patients at high risk of metformin failure who might benefit from closer monitoring and earlier treatment intensification.

Convergence of four measures of multi-morbidity.

Objectives: To compare the agreement between percentile ranks from 4 multi-morbidity scores. Design: Population-based descriptive study. Setting: Olmsted County, Minnesota (USA). Participants: We used the medical records-linkage system of the Rochester Epidemiology Project (REP; http://www.rochesterproject.org) to identify all residents of Olmsted County, Minnesota who reached one or more birthdays between 1 January 2005 and 31 December 2014 (10 years). Methods: For each person, we calculated 4 multi-morbidity scores using readily available diagnostic code lists from the US Department of Health and Human Services, the Clinical Classifications Software, and the Elixhauser Comorbidity Index. We calculated scores using diagnostic codes received in the 5 years before the index birthday and fit quantile regression models across age and separately by sex to transform unweighted, simple counts of conditions into percentile ranks as compared to peers of same age and of same sex. We compared the percentile ranks of the 4 multi-morbidity scores using intra-class correlation coefficients (ICCs). Results: We assessed agreement in 181,553 persons who reached a total of 1,075,433 birthdays at ages 18 years through 85 years during the study period. In general, the percentile ranks of the 4 multi-morbidity scores exhibited high levels of agreement in 6 score-to-score pairwise comparisons. The agreement increased with older age for all pairwise comparisons, and ICCs were consistently greater than 0.65 at ages 50 years and older. Conclusions: The assignment of percentile ranks may be a simple and intuitive way to assess the underlying trait of multi-morbidity across studies that use different measures.

Multi-morbidity and patient-reported functional limitations: a population-based cohort study.

Background: Persons who accumulate chronic conditions at a rate faster than their peers may experience accelerated aging and poor health outcomes, including functional limitations. Methods: Adults aged ≥40 years who resided in Olmsted County, Minnesota on 1 January 2006 were identified. The prevalence of 21 chronic conditions was ascertained, and age-specific quartiles of the number of chronic conditions was estimated within 4 age groups: 40-54, 55-64, 65-74, and ≥75 years. Difficulty with nine patient-reported functional limitations (including basic and instrumental activities of daily living and mobility activities) were ascertained through 31 October 2018. Cox regression was used to model associations of chronic condition quartiles with new-onset functional limitations considered separately. We estimated absolute risk differences and hazard ratios stratified by age group, and adjusted for sex, race, ethnicity, marital status, education, and the residual effect of age. Results: Among 39,624 persons (44.5% men, 93.2% white), the most common reported new functional limitations were difficulty with climbing stairs, walking, and housekeeping. For all functional limitations, the absolute risk differences were largest among the oldest age group (≥75 years). Approximately twofold increased hazard ratios were observed among those in the highest vs. lowest quartile for the three oldest age groups, and approximately threefold or higher hazard ratios were observed for persons aged 40-54 years. Conclusion: Persons with increased accumulation of chronic conditions experience increased risks of developing functional limitations compared to their peers. These findings underscore the importance of assessing health status and of employing interventions to prevent and effectively manage multi-morbidity at all ages.

Association of Depression and Anxiety With the Accumulation of Chronic Conditions.

Importance: Longitudinal associations between comorbid depression and anxiety with the accumulation of chronic illnesses are unclear, and questions remain about the contributions associated with each condition in the increasing prevalence of multimorbidity. Objective: To compare the risk and rate of accumulating chronic conditions in people with depression, anxiety, and comorbid depression and anxiety vs individuals with neither depression nor anxiety. Design, Setting, and Participants: This cohort study used the Rochester Epidemiology Project medical records-linkage system to identify residents of Olmsted County, Minnesota, from January 1, 2005, to December 31, 2014, with follow-up ending December 31, 2017. The sample was divided into cohorts anchored at birthday ages of 20, 40, and 60 years. Individuals were classified at anchoring birthday age as having depression alone, anxiety alone, comorbid depression and anxiety, or neither depression nor anxiety (reference group), using electronically extracted diagnosis codes from the International Classification of Diseases, Ninth Revision (ICD-9) in the 5 years before each anchoring birthday. Data were analyzed from August 2020 through November 2021. Exposures: Depression alone, anxiety alone, comorbid depression and anxiety, or neither depression nor anxiety (reference group). Main Outcomes and Measures: The main outcome was sex-specific risk, calculated as hazard ratios (HRs) and rates of accumulation, calculated as mean annual incidence rates per 100 person-years, of 15 common chronic conditions within each birthday age cohort through the end of study. Results: Among the 40 360 individuals included across all 3 age cohorts, 21 516 (53.3%) were women. After balancing cohorts on race, Hispanic ethnicity, education level, body mass index, smoking status, and calendar year at index birthday, the risk of accumulating chronic conditions was significantly increased among women with depression alone (cohort aged 20 years: HR, 1.20 [95% CI, 1.02-1.42]; cohort aged 40 years: HR, 1.20 [95% CI, 1.10-1.31]; cohort aged 60 years: HR, 1.09 [95% CI, 1.02-1.16]) and women with comorbid depression and anxiety (cohort aged 20 years: HR, 1.60 [95% CI, 1.28-1.99]; cohort aged 40 years: HR, 1.41 [95% CI, 1.21-1.65]; cohort aged 60 years: HR, 1.29 [95% CI, 1.15-1.44]) compared with referent women in the same birthday cohorts and in men with comorbid depression and anxiety compared with referent men in the cohort aged 20 years (HR, 1.77 [95% CI, 1.08-2.91]). For women, the rates of accumulation of conditions were significantly higher across birthday cohorts in the comorbid depression and anxiety group compared with the depression alone group (eg, cohort aged 20 years: difference, 1.2 [95% CI, 0.2-2.1] per 100 person-years) and reference group (eg, cohort aged 20 years: difference, 1.7 [95% CI, 0.9-2.6] per 100 person-years). For men, compared with the reference group, the rates of accumulation of conditions were significantly higher in men with comorbid depression and anxiety in the cohort aged 20 years (difference, 1.4 [95% CI, 0.1-2.6] per 100 person-years) and in men with depression in the cohort aged 40 years (difference, 2.0 [95% CI, 0.8-3.2] per 100 person-years). Conclusions and Relevance: In this cohort study, the risk of accumulating chronic conditions was increased with depression and comorbid depression and anxiety in women across the age span and in younger men with comorbid depression and anxiety. Compared with women without depression or anxiety, there was a more rapid rate of accumulation of chronic conditions in women with depression and anxiety individually and an even higher rate when depression and anxiety cooccurred.

Longitudinal trajectories of treatment burden: A prospective survey study of adults living with multiple chronic conditions in the midwestern United States.

Objectives: Determine whether there are different longitudinal patterns of treatment burden in people living with multiple chronic conditions (MCC) and, if so, explore predictors that might reveal potential routes of intervention. Methods: We analyzed data from a prospective mailed survey study of 396 adults living with MCC in southeastern Minnesota, USA. Participants completed a measure of treatment burden, the Patient Experience with Treatment and Self-management (PETS), and valid measures of health-related and psycho-social concepts at baseline, 6, 12, and 24 months. Latent class growth mixture modeling (LCGM) determined trajectories of treatment burden in two summary index scores of the PETS: Workload and Impact. Multivariable logistic regressions were used to identify independent predictors of the trajectories. Results: LCGM supported a 2-class model for PETS Workload, including a group of consistently high workload (N = 69) and a group of consistently low workload (N = 311) over time. A 3-class model was supported for PETS Impact, including groups of consistently high impact (N = 62), consistently low impact (N = 278), and increasing impact (N = 51) over time. Logistic regression analyses showed that the following factors were associated with patterns of consistently high or increasing treatment burden over time: lower health literacy, lower self-efficacy, more interpersonal challenges with others, and worse subjective reports of physical and mental health (all p < .05). Conclusions: Different longitudinal patterns of treatment burden exist among people with MCC. Raising health literacy, enhancing self-efficacy, and lessening the effects of negative social interactions might help reduce treatment burden.

Prevalence of co-occurring serious illness diagnoses and association with health care utilization at the end of life.

INTRODUCTION: End-of-life care differs by serious illness diagnosis. Cancer and dementia are serious illnesses that have been associated with less intensive end-of-life health care use. It is not known how health care utilization varies in the presence of >1 serious illness. METHODS: We used the Rochester Epidemiology Project to identify persons living in a midwestern area who died on July 1, 2017-June 30, 2018 at age ≥65 years, and were seriously ill. We examined the number of emergency department (ED), hospital, and intensive care unit (ICU) stays in the last 6 months and the last 30 days of life. We used Poisson regression to determine the incidence rate ratio for ED, hospital, and ICU stay in the last 6 months and 30 days of life by number of serious illness diagnoses. For cancer and dementia, we examined the effect of an additional serious illness. RESULTS: We included a population of 1372 adults who were, on average, 84 years, 52% female, and 96% white. Approximately 41% had multiple serious illnesses. Compared to older adults with 1 serious illness diagnosis, rates of hospitalization, and ICU stay for adults with 2 or ≥3 serious illness diagnoses were at least 1.5 times higher in the last 6 months and the last 30 days of life. Rates of ED visits were significantly higher for older adults with 2 or ≥3 serious illness diagnoses in the last 6 months of life, but only higher for those with ≥3 versus 1 serious illness diagnosis in the last 30 days of life. For both cancer and dementia, rates of ED visits, hospitalization and ICU stay were lower for the condition alone than when an additional serious illness diagnosis was present. CONCLUSION: Having multiple serious illnesses increases the risk of health care utilization at the end of life.

Implementation of preemptive DNA sequence-based pharmacogenomics testing across a large academic medical center: The Mayo-Baylor RIGHT 10K Study.

PURPOSE: The Mayo-Baylor RIGHT 10K Study enabled preemptive, sequence-based pharmacogenomics (PGx)-driven drug prescribing practices in routine clinical care within a large cohort. We also generated the tools and resources necessary for clinical PGx implementation and identified challenges that need to be overcome. Furthermore, we measured the frequency of both common genetic variation for which clinical guidelines already exist and rare variation that could be detected by DNA sequencing, rather than genotyping. METHODS: Targeted oligonucleotide-capture sequencing of 77 pharmacogenes was performed using DNA from 10,077 consented Mayo Clinic Biobank volunteers. The resulting predicted drug response-related phenotypes for 13 genes, including CYP2D6 and HLA, affecting 21 drug-gene pairs, were deposited preemptively in the Mayo electronic health record. RESULTS: For the 13 pharmacogenes of interest, the genomes of 79% of participants carried clinically actionable variants in 3 or more genes, and DNA sequencing identified an average of 3.3 additional conservatively predicted deleterious variants that would not have been evident using genotyping. CONCLUSION: Implementation of preemptive rather than reactive and sequence-based rather than genotype-based PGx prescribing revealed nearly universal patient applicability and required integrated institution-wide resources to fully realize individualized drug therapy and to show more efficient use of health care resources.