Search

Abstract Satellite Radar altimetry has emerged as a powerful tool for monitoring inland water bodies including rivers, lakes, and coastal regions. However, challenges persist regarding its accuracy, particularly over complex terrains. This study addresses these challenges by enhancing water level estimation accuracy in complex environments. Although the scope of our study may appear limited in terms of temporal and spatial scales, it aims to contribute additional validation results for a comprehensive water-level database utilizing satellite radar altimetry data. In this paper, we applied two pulse filter criteria on Sentinel-3A radar data—Pulse Peakiness (PP) and Misfit (Mf)—to enhance the selection of altimetry waveforms. After applying the filters, the estimated water levels show improved accuracy when validated against in-situ observations. Pulses from non-water surfaces were excluded using riverbank boundaries to ensure higher-quality pulses. A total of six scenarios were considered where the PP and Mf criteria were used to optimize water level estimates. The results indicate that Mf 0.3 yields even better outcomes (RMSE = 0.28 m, R = 0.95). These findings underscore the significance and efficacy of filtering in enhancing the accuracy of water level estimation. The dataset correlation (R) increased substantially, from 0.088 to 0.935–0.953, with the implementation of filters. Additionally, the RMSE significantly improved, reducing from 4.2 m to 0.26–0.27 m with filter parameters. As anticipated, filters removed data points but vastly improved results. Integrating multi-mission satellite data can compensate for data loss and augment overall quantity and quality.

Background Cardiovascular disease (CVD) is a leading cause of morbidity and mortality in American Indian people. In 2022, the American Heart Association developed the Life's Essential 8 goals to promote cardiovascular health (CVH) for Americans, composed of diet, physical activity, nicotine exposure, sleep, body mass index, blood lipids, blood pressure, and blood glucose. We examined whether achievement of Life's Essential 8 goals was associated with incident CVD among SHFS (Strong Heart Family Study) participants. Methods and Results A total of 2139 SHFS participants without CVD at baseline were included in analyses. We created a composite CVH score based on achievement of Life's Essential 8 goals, excluding sleep. Scores of 0 to 49 represented low CVH, 50 to 69 represented moderate CVH, and 70 to 100 represented high CVH. Incident CVD was defined as incident myocardial infarction, coronary heart disease, congestive heart failure, or stroke. Cox proportional hazard models were used to examine the relationship of CVH and incident CVD. The incidence rate of CVD at the 20‐year follow‐up was 7.43 per 1000 person‐years. Compared with participants with low CVH, participants with moderate and high CVH had a lower risk of incident CVD; the hazard ratios and 95% CIs for incident CVD for moderate and high CVH were 0.52 (95% CI, 0.40–0.68) and 0.25 (95% CI, 0.14–0.44), respectively, after adjustment for age, sex, education, and study site. Conclusions Better CVH was associated with lower CVD risk which highlights the need for comprehensive public health interventions targeting CVH promotion to reduce CVD risk in American Indian communities.

Background Although many studies on the association between dyslipidemia and cardiovascular disease (CVD) exist in older adults, data on the association among adolescents and young adults living with disproportionate burden of cardiometabolic disorders are scarce. Methods and Results The SHFS (Strong Heart Family Study) is a multicenter, family‐based, prospective cohort study of CVD in an American Indian populations, including 12 communities in central Arizona, southwestern Oklahoma, and the Dakotas. We evaluated SHFS participants, who were 15 to 39 years old at the baseline examination in 2001 to 2003 (n=1440). Lipids were measured after a 12‐hour fast. We used carotid ultrasounds to detect plaque at baseline and follow‐up in 2006 to 2009 (median follow‐up=5.5 years). We identified incident CVD events through 2020 with a median follow‐up of 18.5 years. We used shared frailty proportional hazards models to assess the association between dyslipidemia and subclinical or clinical CVD, while controlling for covariates. Baseline dyslipidemia prevalence was 55.2%, 73.6%, and 78.0% for participants 15 to 19, 20 to 29, and 30 to 39 years old, respectively. Approximately 2.8% had low‐density lipoprotein cholesterol ≥160 mg/dL, which is higher than the recommended threshold for lifestyle or medical interventions in young adults of 20 to 39 years old. During follow‐up, 9.9% had incident plaque (109/1104 plaque‐free participants with baseline and follow‐up ultrasounds), 11.0% had plaque progression (128/1165 with both baseline and follow‐up ultrasounds), and 9% had incident CVD (127/1416 CVD‐free participants at baseline). Plaque incidence and progression were higher in participants with total cholesterol ≥200 mg/dL, low‐density lipoprotein cholesterol ≥160 mg/dL, or non–high‐density lipoprotein cholesterol ≥130 mg/dL, while controlling for covariates. CVD risk was independently associated with low‐density lipoprotein cholesterol ≥160 mg/dL. Conclusions Dyslipidemia is a modifiable risk factor that is associated with both subclinical and clinical CVD, even among the younger American Indian population who have unexpectedly high rates of significant CVD events. Therefore, this population is likely to benefit from a variety of evidence‐based interventions including screening, educational, lifestyle, and guideline‐directed medical therapy at an early age.