@article {8976, title = {Diabetes Status Modifies the Association Between Different Measures of Obesity and Heart Failure Risk Among Older Adults: A Pooled Analysis of Community-Based NHLBI Cohorts.}, journal = {Circulation}, volume = {145}, year = {2022}, month = {2022 01 25}, pages = {268-278}, abstract = {

BACKGROUND: Obesity and diabetes are associated with a higher risk of heart failure (HF). The interrelationships between different measures of adiposity-overall obesity, central obesity, fat mass (FM)-and diabetes status for HF risk are not well-established.

METHODS: Participant-level data from the ARIC study (Atherosclerosis Risk in Communities; visit 5) and the CHS (Cardiovascular Health Study; visit 1) cohorts were obtained from the National Heart, Lung, and Blood Institute Biologic Specimen and Data Repository Information Coordinating Center, harmonized, and pooled for the present analysis, excluding individuals with prevalent HF. FM was estimated in all participants using established anthropometric prediction equations additionally validated using the bioelectrical impedance-based FM in the ARIC subgroup. Incident HF events on follow-up were captured across both cohorts using similar adjudication methods. Multivariable-adjusted Fine-Gray models were created to evaluate the associations of body mass index (BMI), waist circumference (WC), and FM with risk of HF in the overall cohort as well as among those with versus without diabetes at baseline. The population attributable risk of overall obesity (BMI>=30 kg/m), abdominal obesity (WC>88 and 102 cm in women and men, respectively), and high FM (above sex-specific median) for incident HF was evaluated among participants with and without diabetes.

RESULTS: The study included 10 387 participants (52.9\% ARIC; 25.1\% diabetes; median age, 74 years). The correlation between predicted and bioelectrical impedance-based FM was high (=0.90; n=5038). During a 5-year follow-up, 447 participants developed HF (4.3\%). Higher levels of each adiposity measure were significantly associated with higher HF risk (hazard ratio [95\% CI] per 1 SD higher BMI=1.15 [1.05, 1.27], WC=1.22 [1.10, 1.36]; FM=1.13 [1.02, 1.25]). A significant interaction was noted between diabetes status and measures of BMI ( interaction=0.04) and WC ( interaction=0.004) for the risk of HF. In stratified analysis, higher measures of each adiposity parameter were significantly associated with higher HF risk in individuals with diabetes (hazard ratio [95\% CI] per 1 SD higher BMI=1.29 [1.14-1.47]; WC=1.48 [1.29-1.70]; FM=1.25 [1.09-1.43]) but not those without diabetes, including participants with prediabetes and euglycemia. The population attributable risk percentage of overall obesity, abdominal obesity, and high FM for incident HF was higher among participants with diabetes (12.8\%, 29.9\%, and 13.7\%, respectively) versus those without diabetes (<=1\% for each).

CONCLUSIONS: Higher BMI, WC, and FM are strongly associated with greater risk of HF among older adults, particularly among those with prevalent diabetes.

}, keywords = {Aged, Cohort Studies, Diabetes Mellitus, Female, Heart Failure, Humans, Male, National Heart, Lung, and Blood Institute (U.S.), Obesity, Risk Factors, United States}, issn = {1524-4539}, doi = {10.1161/CIRCULATIONAHA.121.055830}, author = {Patel, Kershaw V and Segar, Matthew W and Lavie, Carl J and Kondamudi, Nitin and Neeland, Ian J and Almandoz, Jaime P and Martin, Corby K and Carbone, Salvatore and Butler, Javed and Powell-Wiley, Tiffany M and Pandey, Ambarish} } @article {9637, title = {Development and Validation of the American Heart Association{\textquoteright}s PREVENT Equations.}, journal = {Circulation}, volume = {149}, year = {2024}, month = {2024 Feb 06}, pages = {430-449}, abstract = {

BACKGROUND: Multivariable equations are recommended by primary prevention guidelines to assess absolute risk of cardiovascular disease (CVD). However, current equations have several limitations. Therefore, we developed and validated the American Heart Association Predicting Risk of CVD EVENTs (PREVENT) equations among US adults 30 to 79 years of age without known CVD.

METHODS: The derivation sample included individual-level participant data from 25 data sets (N=3 281 919) between 1992 and 2017. The primary outcome was CVD (atherosclerotic CVD and heart failure). Predictors included traditional risk factors (smoking status, systolic blood pressure, cholesterol, antihypertensive or statin use, and diabetes) and estimated glomerular filtration rate. Models were sex-specific, race-free, developed on the age scale, and adjusted for competing risk of non-CVD death. Analyses were conducted in each data set and meta-analyzed. Discrimination was assessed using the Harrell C-statistic. Calibration was calculated as the slope of the observed versus predicted risk by decile. Additional equations to predict each CVD subtype (atherosclerotic CVD and heart failure) and include optional predictors (urine albumin-to-creatinine ratio and hemoglobin A1c), and social deprivation index were also developed. External validation was performed in 3 330 085 participants from 21 additional data sets.

RESULTS: Among 6 612 004 adults included, mean{\textpm}SD age was 53{\textpm}12 years, and 56\% were women. Over a mean{\textpm}SD follow-up of 4.8{\textpm}3.1 years, there were 211 515 incident total CVD events. The median C-statistics in external validation for CVD were 0.794 (interquartile interval, 0.763-0.809) in female and 0.757 (0.727-0.778) in male participants. The calibration slopes were 1.03 (interquartile interval, 0.81-1.16) and 0.94 (0.81-1.13) among female and male participants, respectively. Similar estimates for discrimination and calibration were observed for atherosclerotic CVD- and heart failure-specific models. The improvement in discrimination was small but statistically significant when urine albumin-to-creatinine ratio, hemoglobin A1c, and social deprivation index were added together to the base model to total CVD (ΔC-statistic [interquartile interval] 0.004 [0.004-0.005] and 0.005 [0.004-0.007] among female and male participants, respectively). Calibration improved significantly when the urine albumin-to-creatinine ratio was added to the base model among those with marked albuminuria (>300 mg/g; 1.05 [0.84-1.20] versus 1.39 [1.14-1.65]; =0.01).

CONCLUSIONS: PREVENT equations accurately and precisely predicted risk for incident CVD and CVD subtypes in a large, diverse, and contemporary sample of US adults by using routinely available clinical variables.

}, keywords = {Adult, Aged, Albumins, American Heart Association, Atherosclerosis, Cardiovascular Diseases, Creatinine, Female, Glycated Hemoglobin, Heart Failure, Humans, Male, Middle Aged, Risk Assessment, Risk Factors}, issn = {1524-4539}, doi = {10.1161/CIRCULATIONAHA.123.067626}, author = {Khan, Sadiya S and Matsushita, Kunihiro and Sang, Yingying and Ballew, Shoshana H and Grams, Morgan E and Surapaneni, Aditya and Blaha, Michael J and Carson, April P and Chang, Alexander R and Ciemins, Elizabeth and Go, Alan S and Gutierrez, Orlando M and Hwang, Shih-Jen and Jassal, Simerjot K and Kovesdy, Csaba P and Lloyd-Jones, Donald M and Shlipak, Michael G and Palaniappan, Latha P and Sperling, Laurence and Virani, Salim S and Tuttle, Katherine and Neeland, Ian J and Chow, Sheryl L and Rangaswami, Janani and Pencina, Michael J and Ndumele, Chiadi E and Coresh, Josef} }