Background

Whether timeliness of follow-up after abnormal mammography differs at facilities serving vulnerable populations, such as women with limited education or income, in rural areas, and racial/ethnic minorities is unknown.

Methods

We examined receipt of diagnostic evaluation after abnormal mammography using 1998-2006 Breast Cancer Surveillance Consortium-linked Medicare claims. We compared whether time to recommended breast imaging or biopsy depended on whether women attended facilities serving vulnerable populations. We characterized a facility by the proportion of mammograms performed on women with limited education or income, in rural areas, or racial/ethnic minorities.

Results

We analyzed 30,874 abnormal screening examinations recommended for follow-up imaging across 142 facilities and 10,049 abnormal diagnostic examinations recommended for biopsy across 114 facilities. Women at facilities serving populations with less education or more racial/ethnic minorities had lower rates of follow-up imaging (4%-5% difference, P<0.05), and women at facilities serving more rural and low-income populations had lower rates of biopsy (4%-5% difference, P<0.05). Women undergoing biopsy at facilities serving vulnerable populations had longer times until biopsy than those at facilities serving nonvulnerable populations (21.6 vs. 15.6 d; 95% confidence interval for mean difference 4.1-7.7). The proportion of women receiving recommended imaging within 11 months and biopsy within 3 months varied across facilities (interquartile range, 85.5%-96.5% for imaging and 79.4%-87.3% for biopsy).

Conclusions

Among Medicare recipients, follow-up rates were slightly lower at facilities serving vulnerable populations, and among those women who returned for diagnostic evaluation, time to follow-up was slightly longer at facilities that served vulnerable population. Interventions should target variability in follow-up rates across facilities, and evaluate effectiveness particularly at facilities serving vulnerable populations.

Though it is known that most older adults do not meet the recommended physical activity (PA) guidelines, little is known regarding their participation in balance activities or the full guidelines. Therefore, we sought to describe PA patterns among 1,352 community-dwelling older adult participants of the Adult Changes in Thought study, a longitudinal cohort study exploring dementia-related risk factors. We used a modified version of the Community Healthy Activities Model Program for Seniors questionnaire to explore PA performed and classify participants as meeting or not meeting the full guidelines or any component of the guidelines. Logistic regression was used to identify factors associated with meeting PA guidelines. Despite performing 10 hr of weekly PA, only 11% of participants met the full guidelines. Older age, greater body mass index, needing assistance with instrumental daily activities, and heart disease were associated with decreased odds of meeting PA guidelines. These results can guide interventions that address PA among older adults.

Objectives

Early recognition of dementia would allow patients and their families to receive care earlier in the disease process, potentially improving care management and patient outcomes, yet nearly half of patients with dementia are undiagnosed. Our aim was to develop and validate an electronic health record (EHR)-based tool to help detect patients with unrecognized dementia (EHR Risk of Alzheimer's and Dementia Assessment Rule [eRADAR]).

Design

Retrospective cohort study.

Setting

Kaiser Permanente Washington (KPWA), an integrated healthcare delivery system.

Participants

A total of 16 665 visits among 4330 participants in the Adult Changes in Thought (ACT) study, who undergo a comprehensive process to detect and diagnose dementia every 2 years and have linked KPWA EHR data, divided into development (70%) and validation (30%) samples.

Measurements

EHR predictors included demographics, medical diagnoses, vital signs, healthcare utilization, and medications within the previous 2 years. Unrecognized dementia was defined as detection in ACT before documentation in the KPWA EHR (ie, lack of dementia or memory loss diagnosis codes or dementia medication fills).

Results

Overall, 1015 ACT visits resulted in a diagnosis of incident dementia, of which 498 (49%) were unrecognized in the KPWA EHR. The final 31-predictor model included markers of dementia-related symptoms (eg, psychosis diagnoses, antidepressant fills), healthcare utilization pattern (eg, emergency department visits), and dementia risk factors (eg, cerebrovascular disease, diabetes). Discrimination was good in the development (C statistic = .78; 95% confidence interval [CI] = .76-.81) and validation (C statistic = .81; 95% CI = .78-.84) samples, and calibration was good based on plots of predicted vs observed risk. If patients with scores in the top 5% were flagged for additional evaluation, we estimate that 1 in 6 would have dementia.

Conclusion

The eRADAR tool uses existing EHR data to detect patients with good accuracy who may have unrecognized dementia. J Am Geriatr Soc 68:103-111, 2019.

Neighborhood walkability has been associated with self-reported sedentary behavior (SB) and self-reported and objective physical activity. However, self-reported measures of SB are inaccurate and can lead to biased estimates, and few studies have examined how associations differ by gender and age. The authors examined the relationships between perceived neighborhood walkability measured with the Physical Activity Neighborhood Environment Scale (scored 1.0-4.0) and device-based SB and physical activity in a cohort of community-dwelling older adults (N = 1,077). The authors fit linear regression models adjusting for device wear time, demographics, self-rated health, and accounting for probability of participation. The Higher Physical Activity Neighborhood Environment Scale was associated with higher steps (+676 steps/point on the Physical Activity Neighborhood Environment Scale, p = .001) and sit-to-stand transitions (+2.4 transitions/point, p = .018). Though not statistically significant, stratified analyses suggest an attenuation of effect for those aged 85 years and older and for women. Consistent with previous literature, neighborhood walkability was associated with more steps, though not with physical activity time. The neighborhood environment may also influence SB.

BACKGROUND: Research supports that moderate-to-vigorous intensity physical activity (MVPA) is key to prolonged health and function. Among older adults, substantial changes to MVPA may be infeasible, thus a growing literature suggests a shift in focus to whole-day activity patterns. METHODS: With data from 795 older adults aged 65-100 in the Adult Changes in Thought Activity Monitoring study, we used linear regression to estimate associations between ActiGraph and activPAL measured activity patterns - including light intensity physical activity, steps, standing, and sedentary behaviors - and physical function as measured by a short Performance-based Physical Function (sPPF) score (range 0-12), a composite score based on three standardized physical performance tasks: gait speed, timed chair stands, and grip strength. We examined whether relationships persisted when controlling for MVPA or differed across age, gender, or quartiles of MVPA. RESULTS: In models unadjusted for MVPA, a 1-standard deviation (SD) increment of daily sitting (1.9 h more), mean sitting bout duration (8 min longer average), or time spent in sedentary activity (1.6 h more) was associated with ~ 0.3-0.4 points lower mean sPPF score (all p < 0.05). A 1-SD increment in daily steps (~ 3500 more steps) was associated with ~ 0.5 points higher mean sPPF score (95% CI: 0.22 to 0.73). MVPA adjustment attenuated all relationships. The association between physical function and steps was strongest among adults aged 75+; associations of worse function with greater sedentary behavior were more pronounced in participants with the lowest levels of MVPA. CONCLUSIONS: We found associations between function and activity metrics other than MVPA in key subgroups, findings that support research on broader activity patterns and may offer ideas regarding practical intervention opportunities for improving function in older adults.

Background

Few studies characterize older adult physical activity and sitting patterns using accurate accelerometer and concurrent posture measures. In this descriptive paper, we report accelerometer data collection protocols, consent rates, and physical behavior measures from a population-based cohort study (Adult Changes in Thought, ACT).

Methods

The ACT study holds enrollment steady at approximately 2000 members of Kaiser Permanente Washington aged 65+ without dementia undergoing detailed biennial assessments. In 2016 the ACT-Activity Monitor (ACT-AM) sub-study was initiated to obtain data from wearing activPAL and ActiGraph devices for 7 days following regular biennial visits. We describe the methods protocol of ACT-AM and present characteristics of people who did and did not consent to wear devices. We compute inverse probability of response weights and incorporate these weights in linear regression models to estimate means and 95% confidence intervals (CI) of device-based pattern metrics, adjusted for wear time and demographic factors, and weighted to account for potential selection bias due to device-wear consent.

Results

Among 1885 eligible ACT participants, 56% agreed to wear both devices (mean age 77 years, 56% female, 89% non-Hispanic white, 91% with post-secondary education). On average, those who agreed to wear devices were younger and healthier. Estimated mean (95% CI) activPAL-derived sitting, standing, and stepping times were 10.2 h/day (603-618 min/day), 3.9 h/day (226-239 min/day), and 1.4 h/day (79-84 min/day), respectively. Estimated mean ActiGraph derived sedentary (Vector Magnitude [VM] < =18 counts/15 s), light intensity (VM 19-518 counts/15 s), and moderate-to-vigorous intensity (VM > 518 counts/15 s) physical activity durations were 9.5 h/day (565-577 min/day), 4.5 h/day (267-276 min/day), and 1.0 h/day (59-64 min/day). Participants who were older, had chronic conditions, and were unable to walk a half-mile had higher sedentary time and less physical activity.

Conclusions

Our recruitment rate demonstrates the feasibility of cohort participants to wear two devices that measure sedentary time and physical activity. Data indicate high levels of sitting time in older adults but also high levels of physical activity using cut-points developed for older adults. These data will help researchers test hypotheses related to physical behavior and health in older adults in the future.

Objective

Type 2 diabetes confers a greater excess risk of cardiovascular disease in women than in men. Diabetes is also a risk factor for dementia, but whether the association is similar in women and men remains unknown. We performed a meta-analysis of unpublished data to estimate the sex-specific relationship between women and men with diabetes with incident dementia.

Research design and methods

A systematic search identified studies published prior to November 2014 that had reported on the prospective association between diabetes and dementia. Study authors contributed unpublished sex-specific relative risks (RRs) and 95% CIs on the association between diabetes and all dementia and its subtypes. Sex-specific RRs and the women-to-men ratio of RRs (RRRs) were pooled using random-effects meta-analyses.

Results

Study-level data from 14 studies, 2,310,330 individuals, and 102,174 dementia case patients were included. In multiple-adjusted analyses, diabetes was associated with a 60% increased risk of any dementia in both sexes (women: pooled RR 1.62 [95% CI 1.45-1.80]; men: pooled RR 1.58 [95% CI 1.38-1.81]). The diabetes-associated RRs for vascular dementia were 2.34 (95% CI 1.86-2.94) in women and 1.73 (95% CI 1.61-1.85) in men, and for nonvascular dementia, the RRs were 1.53 (95% CI 1.35-1.73) in women and 1.49 (95% CI 1.31-1.69) in men. Overall, women with diabetes had a 19% greater risk for the development of vascular dementia than men (multiple-adjusted RRR 1.19 [95% CI 1.08-1.30]; P < 0.001).

Conclusions

Individuals with type 2 diabetes are at ∼60% greater risk for the development of dementia compared with those without diabetes. For vascular dementia, but not for nonvascular dementia, the additional risk is greater in women.