10 research outputs found

    Influential periods in longitudinal clinical cardiovascular health scores

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    The prevalence of ideal cardiovascular health (CVH) among adults in the United States is low and decreases with age. Our objective was to identify specific age windows when the loss of CVH accelerates, to ascertain preventive opportunities for intervention. Data were pooled from 5 longitudinal cohorts (Project Heartbeat!, Cardiovascular Risk in Young Finns Study, The Bogalusa Heart Study, Coronary Artery Risk Development in Young Adults, Special Turku Coronary Risk Factor Intervention Project) from the United States and Finland from 1973 to 2012. Individuals with clinical CVH factors (i.e., body mass index, blood pressure, cholesterol, blood glucose) measured from ages 8 to 55 years were included. These factors were categorized and summed into a clinical CVH score ranging from 0 (worst) to 8 (best). Adjusted, segmented, linear mixed models were used to estimate the change in CVH over time. Among the 18,343 participants, 9,461 (52%) were female and 12,346 (67%) were White. The baseline mean (standard deviation) clinical CVH score was 6.9 (1.2) at an average age of 17.6 (8.1) years. Two inflection points were estimated: at 16.9 years (95% confidence interval: 16.4, 17.4) and at 37.2 years (95% confidence interval: 32.4, 41.9). Late adolescence and early middle age appear to be influential periods during which the loss of CVH accelerates

    Association of body mass index in midlife with morbidity burden in older adulthood and longevity

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    Importance: Abundant evidence links obesity with adverse health consequences. However, controversies persist regarding whether overweight status compared with normal body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) is associated with longer survival and whether this occurs at the expense of greater long-term morbidity and health care expenditures. Objective: To examine the association of BMI in midlife with morbidity burden, longevity, and health care expenditures in adults 65 years and older. Design, Setting, and Participants: Prospective cohort study at the Chicago Heart Association Detection Project in Industry, with baseline in-person examination between November 1967 and January 1973 linked with Medicare follow-up between January 1985 and December 2015. Participants included 29 621 adults who were at least age 65 years in follow-up and enrolled in Medicare. Data were analyzed from January 2020 to December 2021. Exposures: Standard BMI categories. Main Outcomes and Measures: (1) Morbidity burden at 65 years and older assessed with the Gagne combined comorbidity score (ranging from -2 to 26, with higher score associated with higher mortality), which is a well-validated index based on International Classification of Diseases, Ninth Revision codes for use in administrative data sets; (2) longevity (age at death); and (3) health care costs based on Medicare linkage in older adulthood (aged ≥65 years). Results: Among 29 621 participants, mean (SD) age was 40 (12) years, 57.1% were men, and 9.1% were Black; 46.0% had normal BMI, 39.6% were overweight, and 11.9% had classes I and II obesity at baseline. Higher cumulative morbidity burden in older adulthood was observed among those who were overweight (7.22 morbidity-years) and those with classes I and II obesity (9.80) compared with those with a normal BMI (6.10) in midlife (P \u3c .001). Mean age at death was similar between those who were overweight (82.1 years [95% CI, 81.9-82.2 years]) and those who had normal BMI (82.3 years [95% CI, 82.1-82.5 years]) but shorter in those who with classes I and II obesity (80.8 years [95% CI, 80.5-81.1 years]). The proportion (SE) of life-years lived in older adulthood with Gagne score of at least 1 was 0.38% (0.00%) in those with a normal BMI, 0.41% (0.00%) in those with overweight, and 0.43% (0.01%) in those with classes I and II obesity. Cumulative median per-person health care costs in older adulthood were significantly higher among overweight participants (12 390[9512 390 [95% CI, 10 427 to 14 354])andthosewithclassesIandIIobesity(14 354]) and those with classes I and II obesity (23 396 [95% CI, 18 474to18 474 to 28 319]) participants compared with those with a normal BMI (P \u3c .001). Conclusions and Relevance: In this cohort study, overweight in midlife, compared with normal BMI, was associated with higher cumulative burden of morbidity and greater proportion of life lived with morbidity in the context of similar longevity. These findings translated to higher total health care expenditures in older adulthood for those who were overweight in midlife

    Influential Periods in Longitudinal Clinical Cardiovascular Health Scores

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    The prevalence of ideal cardiovascular health (CVH) among adults in the United States is low and decreases with age. Our objective was to identify specific age windows when the loss of CVH accelerates, to ascertain preventive opportunities for intervention. Data were pooled from 5 longitudinal cohorts (Project Heartbeat!, Cardiovascular Risk in Young Finns Study, The Bogalusa Heart Study, Coronary Artery Risk Development in Young Adults, Special Turku Coronary Risk Factor Intervention Project) from the United States and Finland from 1973 to 2012. Individuals with clinical CVH factors (i.e., body mass index, blood pressure, cholesterol, blood glucose) measured from ages 8 to 55 years were included. These factors were categorized and summed into a clinical CVH score ranging from 0 (worst) to 8 (best). Adjusted, segmented, linear mixed models were used to estimate the change in CVH over time. Among the 18,343 participants, 9,461 (52%) were female and 12,346 (67%) were White. The baseline mean (standard deviation) clinical CVH score was 6.9 (1.2) at an average age of 17.6 (8.1) years. Two inflection points were estimated: at 16.9 years (95% confidence interval: 16.4, 17.4) and at 37.2 years (95% confidence interval: 32.4, 41.9). Late adolescence and early middle age appear to be influential periods during which the loss of CVH accelerates. </p

    Influential Periods in Longitudinal Clinical Cardiovascular Health Scores

    Get PDF
    The prevalence of ideal cardiovascular health (CVH) among adults in the United States is low and decreases with age. Our objective was to identify specific age windows when the loss of CVH accelerates, to ascertain preventive opportunities for intervention. Data were pooled from 5 longitudinal cohorts (Project Heartbeat!, Cardiovascular Risk in Young Finns Study, The Bogalusa Heart Study, Coronary Artery Risk Development in Young Adults, Special Turku Coronary Risk Factor Intervention Project) from the United States and Finland from 1973 to 2012. Individuals with clinical CVH factors (i.e., body mass index, blood pressure, cholesterol, blood glucose) measured from ages 8 to 55 years were included. These factors were categorized and summed into a clinical CVH score ranging from 0 (worst) to 8 (best). Adjusted, segmented, linear mixed models were used to estimate the change in CVH over time. Among the 18,343 participants, 9,461 (52%) were female and 12,346 (67%) were White. The baseline mean (standard deviation) clinical CVH score was 6.9 (1.2) at an average age of 17.6 (8.1) years. Two inflection points were estimated: at 16.9 years (95% confidence interval: 16.4, 17.4) and at 37.2 years (95% confidence interval: 32.4, 41.9). Late adolescence and early middle age appear to be influential periods during which the loss of CVH accelerates.publishedVersionPeer reviewe

    Moderate and Vigorous Intensity Exercise During Pregnancy and Gestational Weight Gain in Women with Gestational Diabetes

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    Objectives To estimate the associations of moderate and vigorous intensity exercise during pregnancy with the rate of gestational weight gain (GWG) from gestational diabetes (GDM) diagnosis to delivery, overall and stratified by prepregnancy overweight/obesity. Methods Prospective cohort study with physical activity reported shortly after the GDM diagnosis and prepregnancy weight and post-diagnosis GWG obtained from electronic health records (n&nbsp;=&nbsp;1055). Multinomial logistic regression models in the full cohort and stratified by prepregnancy overweight/obesity estimated associations of moderate and vigorous intensity exercise with GWG below and above the Institute of Medicine's (IOM) prepregnancy BMI-specific recommended ranges for weekly rate of GWG in the second and third trimesters. Results In the full cohort, any participation in vigorous intensity exercise was associated with decreased odds of GWG above recommended ranges as compared to no participation [odds ratio (95&nbsp;% confidence interval): 0.63 (0.40, 0.99)], with a significant trend for decreasing odds of excess GWG with increasing level of vigorous intensity exercise. Upon stratification by prepregnancy overweight/obesity, significant associations were only observed for BMI&nbsp;≥&nbsp;25.0&nbsp;kg/m(2): any vigorous intensity exercise, as compared to none, was associated with 54&nbsp;% decreased odds of excess GWG [0.46 (0.27, 0.79)] and significant trends were detected for decreasing odds of GWG both below and above the IOM's recommended ranges with increasing level of vigorous exercise (both P&nbsp;≤&nbsp;0.03). No associations were observed for moderate intensity exercise. Conclusions&nbsp;for Practice In women with GDM, particularly overweight and obese women, vigorous intensity exercise during pregnancy may reduce the odds of excess GWG

    Incorporating longitudinal history of risk factors into atherosclerotic cardiovascular disease risk prediction using deep learning

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    Abstract It is increasingly clear that longitudinal risk factor levels and trajectories are related to risk for atherosclerotic cardiovascular disease (ASCVD) above and beyond single measures. Currently used in clinical care, the Pooled Cohort Equations (PCE) are based on regression methods that predict ASCVD risk based on cross-sectional risk factor levels. Deep learning (DL) models have been developed to incorporate longitudinal data for risk prediction but its benefit for ASCVD risk prediction relative to the traditional Pooled Cohort Equations (PCE) remain unknown. Our study included 15,565 participants from four cardiovascular disease cohorts free of baseline ASCVD who were followed for adjudicated ASCVD. Ten-year ASCVD risk was calculated in the training set using our benchmark, the PCE, and a longitudinal DL model, Dynamic-DeepHit. Predictors included those incorporated in the PCE: sex, race, age, total cholesterol, high density lipid cholesterol, systolic and diastolic blood pressure, diabetes, hypertension treatment and smoking. The discrimination and calibration performance of the two models were evaluated in an overall hold-out testing dataset. Of the 15,565 participants in our dataset, 2170 (13.9%) developed ASCVD. The performance of the longitudinal DL model that incorporated 8 years of longitudinal risk factor data improved upon that of the PCE [AUROC: 0.815 (CI 0.782–0.844) vs 0.792 (CI 0.760–0.825)] and the net reclassification index was 0.385. The brier score for the DL model was 0.0514 compared with 0.0542 in the PCE. Incorporating longitudinal risk factors in ASCVD risk prediction using DL can improve model discrimination and calibration

    Rationale and design for Healthy Hearts for Michigan (HH4M): A pragmatic single-arm hybrid effectiveness-implementation study

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    Background: The burden of cardiovascular disease (CVD) is particularly high in several US states, which include the state of Michigan. Hypertension and smoking are two major risk factors for mortality due to CVD. Rural Michigan is disproportionally affected by CVD and by primary care shortages. The Healthy Hearts for Michigan (HH4M) study aims to promote hypertension management and smoking cessation through practice facilitation and quality improvement efforts and is part of the multi-state EvidenceNOW: Building State Capacity initiative to provide external support to primary care practices to improve care delivery. Methods: Primary care practices in rural and underserved areas of Michigan were recruited to join HH4M, a pragmatic, single-arm hybrid Type 2 effectiveness-implementation study during which practice facilitation was delivered at the practice level for 12 months, followed by a 3-month maintenance period. Results: Fifty-four practices were enrolled over a 12-month recruitment period. At baseline, the mean proportion (standard deviation) of patients at the practice level meeting the clinical quality measures were: blood pressure, 0.72 (0.12); tobacco screening, 0.80 (0.30); tobacco cessation intervention, 0.57 (0.28); tobacco screening and cessation intervention: 0.78 (0.26). Conclusion: This three-year research program will evaluate the ability of rural and medically underserved primary care practices to implement the quality improvement model by identifying drivers of and barriers to sustainable implementation, and test whether the model improves (a) blood pressure control and (b) tobacco use screening and cessation
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