SAIF, RIYADH

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.

Abstract Aims Obesity, particularly visceral adiposity, is a key driver of cardiovascular mortality (CVM), yet conventional measures such as body mass index (BMI) inadequately capture fat distribution. The Body Roundness Index (BRI) is a novel anthropometric measure integrating waist circumference and height to better reflect body shape and visceral fat. This study examined the association between BRI and CVM in U.S. adults and across sociodemographic subgroups. Methods and results We analysed data from 31 351 adults (median age 43 yrs, 50% females) aged ≥20 years in NHANES 1999–2018, excluding those with prior cardiovascular disease or cancer. BRI was computed using a validated equation and categorized into quintiles (Q3 as reference). The primary outcome was CVM; secondary outcomes included all-cause, heart disease, and cerebrovascular mortality. Weighted Cox proportional hazards and restricted cubic spline (RCS) models evaluated associations after adjustment for demographic, behavioural, and clinical factors. Subgroup and sensitivity analyses tested consistency and effect modification. During a median follow-up of 10.1 years (IQR: 5.3–14.9 years), 883 cardiovascular deaths occurred. In fully adjusted models, participants in the highest BRI quintile had a 54% higher risk of CVM (HR, 1.54; 95% CI, 1.13–2.08; P = 0.006) vs. Q3. This risk remained high even among those with normal BMI. RCS analysis indicated a modest U-shaped association. Stronger effects were observed among middle-aged adults (45–64 years) and those with higher educational attainment. Conclusion Higher BRI is independently associated with increased cardiovascular mortality, particularly among middle aged adults and those with normal BMI, underscoring its potential as a practical, noninvasive tool for cardiovascular risk stratification. Incorporating BRI into clinical and public health assessment may improve identification of individuals at elevated risk.