Citations

Abstract Background Climate-related stressors such as heat, wildfires, and extreme weather are increasingly recognized as determinants of cardiovascular and oncologic health. However, their joint impact on overlapping cancer–cardiovascular disease (CVD) burdens remains unknown. We developed a Cardio-Oncology Burden Index (COBI) to quantify the co-prevalence of cancer and CVD at the community level and examined its association with climate vulnerability across U.S. census tracts. Methods We conducted a cross-sectional ecological analysis of 82,679 census tracts (328,683,841 residents) using the CDC PLACES database. COBI was derived using principal component analysis of age-adjusted prevalence of cancer, coronary artery disease, and stroke. The Climate Burden Index (CBI, 0–1 percentile) integrates multiple climate-related exposures, including extreme temperature, wildfire frequency, and severe weather events. Population-weighted mixed-effects regression models with county-level random effects estimated associations between CBI and COBI, adjusting for region, rurality, and environmental justice indicators. β coefficients represent percentage-point differences in COBI per unit (or category) increase in climate burden. Exposure–response relationships were examined using restricted cubic splines (RCS). Robustness was assessed via geographically matched (<50 km) and fully matched (region, rural–urban commuting area, and environmental justice) analyses. Results Marked spatial heterogeneity was observed in both CBI and COBI across the U.S. (Fig. A–B). Higher climate burden was consistently associated with greater cardio-oncology burden (Fig. C), demonstrating a dose–response relationship: second vs lowest quartile β=0.92 (95% CI, 0.61–1.24); third vs lowest quartile β=1.61 (95% CI, 1.30–1.92); highest vs lowest quartile β=3.44 (95% CI, 3.11–3.76). The RCS model revealed a significant non-linear association (p_non-linear<0.001), with a plateau at moderate exposures and a steep rise at the highest CBI levels (Fig. D). Results remained robust in sensitivity analyses (β=4.17 [95% CI, 3.62–4.71] for geographically matched; β=4.39 [95% CI, 4.10–4.69] for fully matched tracts; Table). Conclusions Greater climate burden is independently associated with higher cardio-oncology burden across U.S. communities, with disproportionate effects in the most climate-vulnerable areas. This novel, population-level linkage between climate stress and onco-cardiovascular disease burden, highlights an emerging syndemic at the intersection of environment, cancer, and CVD. Targeted mitigation and prevention strategies integrating environmental resilience into chronic disease prevention are urgently needed.For image description, please refer to the figure legend and surrounding text.

AbstractBackgroundEvidence suggests that select hippocampal subfields are implicated in the initial stages of Alzheimer’s disease (AD) and are selectively involved in objective memory. Less is known whether subfields are associated with informant-reported memory difficulties of individuals with a diagnosis of mild cognitive impairment (MCI).MethodData from 56 participants with a diagnosis of amnestic MCI were included in the present study. To test whether FreeSurfer derived hippocampal subfields (CA1–4, subiculum, presubiculum, and dentate gyrus) were associated with objective (learning and delayed recall) and informant-reports of memory difficulties, we used multiple linear regression analysis. Subfields were adjusted for total intracranial volume, and age, sex, and years of education were included as covariates in all models.ResultsLarger presubiculum, subiculum, and CA4/dentate gyrus volumes were associated with higher delayed recall scores, and larger subiculum and CA4/dentate gyrus volumes were associated with fewer informant-reports of memory difficulties. There were no statistically significant associations between subfields and learning scores.DiscussionFindings from the present study support the idea that difficulties with memory-dependent everyday tasks in older adults with MCI may signal a neurodegenerative process while increasing understanding of subfields correlates of these memory-specific functional difficulties. Continued investigations into identifying patterns of subfield atrophy in AD may aid early identification of those at higher risk of dementia conversion while advancing precision medicine.

Background: In Alzheimer’s disease and related disorders (ADRD) research, common outcome measures include cognitive and functional impairment, as well as persons with mild cognitive impairment (pwMCI) and care partner self-reported mood and quality of life. Studies commonly analyze these measures separately, which potentially leads to issues of multiple comparisons and/or multicollinearity among measures while ignoring the latent constructs they may be measuring. Objective: This study sought to examine the latent factor structure of a battery of 12-13 measures of domains mentioned above, used in a multicomponent behavioral intervention (The HABIT® program) for pwMCI and their partners. Methods: Exploratory factor analysis (EFA) involved 214 pwMCI-partner pairs. Subsequent Confirmatory factor analyses (CFA) used 730 pairs in both pre- and post-intervention conditions. Results: EFA generated a three-factor model. Factors could be characterized as partner adjustment (29.9%), pwMCI adjustment (18.1%), and pwMCI impairment (12.8%). The subsequent CFA confirmed our findings, and the goodness-of-fit for this model was adequate in both the pre- (CFI = 0.937; RMSEA = 0.057, p = 0.089) and post-intervention (CFI = 0.942; RMSEA = 0.051, p = 0.430) groups. Conclusion: Results demonstrated a stable factor structure across cohorts and intervention conditions suggesting that three broad factors may provide a straightforward and meaningful model to assess intervention outcome, at least during the MCI phase of ADRD.

ObjectivesWe adapted a self‐efficacy measure for managing chronic illness to be specific to persons with mild cognitive impairment (pwMCI). The aim of this study was to investigate the psychometric properties of the scale, the self‐efficacy for managing MCI scale, for use in research.MethodsAnalyses involved data from pwMCI enrolled in a behavioral intervention study that completed the measure five times from intervention enrollment to 18‐month post‐intervention. Factor structure, construct validity, internal consistency, and test‐retest reliability were analyzed.ResultsFactor analysis identified two factors, related to self‐efficacy for daily activities and managing MCI, which corresponded with domains from the original chronic illness self‐efficacy scale. Consistent with prior research, construct validity analysis suggested an association between memory‐loss self‐efficacy and psychosocial distress, but not cognitive or functional ability. Further analyses supported the scale's internal and test‐retest reliability.ConclusionsCurrently, no “gold standard” scale of memory‐loss self‐efficacy for pwMCI exists, despite the positive impact self‐efficacy may have on modifiable health behaviors. Overall, results supported the notion that the scale is a valid and reliable measure of memory‐loss self‐efficacy for pwMCI.