Influential periods in longitudinal clinical cardiovascular health scores

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

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 [95$10 427 to $14 354]) and those with classes I and II obesity ($23 396 [95% CI, $18 474 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

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

Abstract MP70: Pre-pregnancy Beta Cell Compensation for Insulin Resistance Associated With Subsequent Gestational Diabetes Mellitus: The CARDIA Study

Hypothesis: Gestational diabetes mellitus (GDM) is a disorder of glucose metabolism during pregnancy characterized by pancreatic beta cell dysfunction and greater insulin resistance, but it is unclear whether dysfunction exists before pregnancy. The disposition index (DI) is a physiologic measure of beta cell compensation for insulin resistance strongly predictive of future diabetes. This prospective study evaluates whether a clinical approximation of DI before pregnancy is associated with risk of GDM. Methods: This analysis included 696 women (45% black, 55% white) enrolled in the CARDIA Study, a U.S. multi-center prospective cohort of young adults aged 18-30 at baseline (1985-86) who gave birth at least once during 30 years of follow up, reported GDM status and had fasting glucose and insulin measured before one or more post-baseline births. DI was defined as HOMA-B divided by HOMA-IR using standard formulas. Multinomial logistic regression models estimated odds ratios (OR) and 95%CI for GDM among pre-pregnancy DI tertiles (low, moderate, high) and fully adjusted for time to birth, race, age, parity, BMI, lifestyle behaviors and family history of diabetes, and also stratified by pre-pregnancy BMI. Results: 9% of women reported GDM (64/696) for 794 births. 55% of GDM and 30% of non-GDM were categorized as low DI. Low pre-pregnancy DI compared to moderate DI was associated with higher fully adjusted odds of GDM (OR=2.71, 95%CI:1.37-5.35) in the entire sample. In models stratified by pre-pregnancy BMI, low DI was associated with 4-fold higher odds of GDM among Overweight/Obese (OR=4.22, 95%CI: 1.35-13.91) and somewhat attenuated higher odds of GDM among Normal BMI (OR=1.94, 95%CI: 0.78–4.86); Table 1. Only family history of diabetes was strongly associated with GDM independent of DI. Conclusions: Inadequate beta cell compensation is present before pregnancy and discriminates greatest risk of GDM among high BMI, and may identify higher risk among women of normal BMI. </jats:p

Decision Tree-Based Classification for Maintaining Normal Blood Pressure Throughout Early Adulthood and Middle Age: Findings From the Coronary Artery Risk Development in Young Adults (CARDIA) Study

Abstract Background For most individuals, blood pressure (BP) is related to multiple risk factors. By utilizing the decision tree analysis technique, this study aimed to identify the best discriminative risk factors and interactions that are associated with maintaining normal BP over 30 years and to reveal segments of a population with a high probability of maintaining normal BP. Methods Participants from the Coronary Artery Risk Development in Young Adults study aged 18–30 years with normal BP level at baseline visit (Y0, 1985–1986) were included in this study. Results Of 3,156 participants, 1,132 (35.9%) maintained normal BP during the follow-up period and 2,024 (64.1%) developed higher BP. Systolic BP (SBP) within the normal range, race, and body mass index (BMI) were the most discriminative factors between participants who maintained normal BP throughout midlife and those who developed higher BP. Participants with a baseline SBP level ≤92 mm Hg and White women with baseline BMI &amp;lt; 23 kg/m2 were the two segments of the population with the highest probability for maintaining normal BP throughout midlife (69.2% and 59.9%, respectively). Among Black participants aged &amp;gt;26.5 years with BMI &amp;gt; 27 kg/m2, only 5.4% of participants maintained normal BP throughout midlife. Conclusions This study emphasizes the importance of early life factors to later life SBP and support efforts to maintain ideal levels of risk factors for hypertension at young ages. Whether policies to maintain lower BMI and SBP well below the clinical thresholds throughout young adulthood and middle age can reduce later age hypertension should be examined in future studies. </jats:sec

A County-Level Susceptibility Index and Coronavirus Disease 2019 Mortality in the United States: A Socioecological Study

ABSTRACTAs of June 2020, the United States (US) has experienced the highest number of deaths related to coronavirus disease 2019 (Covid-19) in the world, but significant geographic heterogeneity exists at the county-level. Therefore, we sought to classify counties in the United States across multiple domains utilizing a socioecological framework and examine the association between these county-level groups and Covid-19 mortality. We harmonized and linked county-level sociodemographic, health, and environmental metrics associated with increased susceptibility for Covid-19 mortality. Latent class analysis defined a county-level susceptibility index (CSI) based on these metrics (n=2701 counties). Next, we used linear regression models to estimate the associations of the CSI and Covid-19 deaths per capita and initial mortality doubling time (as of 6/2/20), adjusted for days since first Covid-19 case. We identified 4 groups classified by the CSI with distinct sociodemographic, health, and environmental profiles and widespread geographic dispersion. Covid-19 deaths per capita were significantly higher in the group consisting of rural, vulnerable counties (55.8 [95% CI 50.3-61.2] deaths per 100,000) compared with the group with diverse, urban counties (32.2 [27.3-37.0]) at similar points in the outbreak (76 days since first case). Our findings can inform equitable resource allocation for Covid-19 to allow targeted public health preparedness and response in vulnerable counties.</jats:p

Association between county-level risk groups and COVID-19 outcomes in the United States: a socioecological study

Abstract Background Geographic heterogeneity in COVID-19 outcomes in the United States is well-documented and has been linked with factors at the county level, including sociodemographic and health factors. Whether an integrated measure of place-based risk can classify counties at high risk for COVID-19 outcomes is not known. Methods We conducted an ecological nationwide analysis of 2,701 US counties from 1/21/20 to 2/17/21. County-level characteristics across multiple domains, including demographic, socioeconomic, healthcare access, physical environment, and health factor prevalence were harmonized and linked from a variety of sources. We performed latent class analysis to identify distinct groups of counties based on multiple sociodemographic, health, and environmental domains and examined the association with COVID-19 cases and deaths per 100,000 population. Results Analysis of 25.9 million COVID-19 cases and 481,238 COVID-19 deaths revealed large between-county differences with widespread geographic dispersion, with the gap in cumulative cases and death rates between counties in the 90th and 10th percentile of 6,581 and 291 per 100,000, respectively. Counties from rural areas tended to cluster together compared with urban areas and were further stratified by social determinants of health factors that reflected high and low social vulnerability. Highest rates of cumulative COVID-19 cases (9,557 [2,520]) and deaths (210 [97]) per 100,000 occurred in the cluster comprised of rural disadvantaged counties. Conclusions County-level COVID-19 cases and deaths had substantial disparities with heterogeneous geographic spread across the US. The approach to county-level risk characterization used in this study has the potential to provide novel insights into communicable disease patterns and disparities at the local level. </jats:sec

Coronary Artery Calcium Progression Among the US and Japanese Men.

Background The risk of coronary heart disease remains low in Japan, although distributions of several coronary risk factors have become comparable with those in the United States. We prospectively compared coronary atherosclerosis burden, measured with coronary artery calcium (CAC) progression, between men in the 2 countries. Methods In 2 population-based samples of 1712 US White, Black, Hispanic, Chinese men (baseline, 2000-2002) and 697 Japanese men in Japan (2006-2008) aged 45-74 years without clinical cardiovascular disease, we quantified CAC progression by serial computed tomography with medians of 3.4 and 5.2 years between scans, respectively. Results Among White, Black, Hispanic, Chinese, and Japanese men free of baseline CAC, CAC incidence was observed in 35.2%, 26.9%, 29.2%, 18.9%, and 29.2%, respectively. After adjustment for times between scans, demographics, behaviors, coronary risk factors, and their changes between scans, White men had significantly higher CAC incidence than Japanese men (relative risk, 1.68; 95% CI, 1.13-2.50). Among those with detectable baseline CAC, after similar adjustments, all the US race/ethnic groups had significantly greater annual changes in CAC score (mean [95% CI]: 39.4 [35.2-43.6] for White, 26.9 [21.4-32.4] for Black, 30.6 [24.7-36.5] for Hispanic, and 30.2 [22.6-37.8] for Chinese men) than Japanese men (15.9 [10.1-21.8]). Conclusions We found a higher CAC incidence among US White men and greater increases in existing CAC among all the US race/ethnic groups than among Japanese men in Japan. These differences persisted despite adjustment for differences in coronary risk factors

Abstract MP08: Using Electronic Health Record Data To Link Families: The Pythonic Relationship Inference From The Electronic Health Record Algorithm

Introduction: Intergenerational patterns are an important part of understanding disease, but much of the family-based research can be costly or biased. Emergency contacts in electronic health records (EHR) can be used to link family members using a population that is more representative of a community than traditional family cohort studies. Hypothesis: Creating family trees using emergency contacts will result in robust data that can be used in intergenerational research. Methods: We revised a published algorithm: relationship inference from the electronic health record (RIFTEHR). Our version, pythonic RIFTEHR (P-RIFTEHR) was run on 8/5/21 in the Northwestern Medicine Electronic Data Warehouse (NMEDW) on approximately 3.7 million individuals and was validated using the existing link between children born at NM hospitals and their mothers as the gold-standard. As proof-of-concept, we modeled the association between parent and child obesity using logistic regression. Results: The P-RIFTEHR algorithm matched 1,427,622 individuals in 500,408 families. The median family size is 2, the largest family is approximately 300 persons, and 115 families span four generations or more. Of the EDW-linked mother-child pairs, all matching pairs in P-RIFTEHR were correctly identified as mother-child, resulting in 100% sensitivity. Children are two times more likely to be obese if a parent is obese (OR: 2.01; 95% CI: 1.94, 2.09). This association persists after adjustment (OR: 2.19; 95% CI: 2.10, 2.28) and in mixed models nesting children within parents (OR: 2.70; 95% CI: 2.56, 2.85). Conclusions: P-RIFTEHR works well in a large, diverse population in an integrated health system. Our obesity results are consistent with the literature, including a 2017 meta-analysis by Wang, et al, showing a strong parent-child obesity association (pooled OR: 2.22; 95% CI: 2.09, 2.36). While the information used in the EHR can be completely deidentified, privacy concerns will be addressed before these data are more widely available for research. </jats:p

Coronary Artery Calcium Progression Among the US and Japanese Men.

Background The risk of coronary heart disease remains low in Japan, although distributions of several coronary risk factors have become comparable with those in the United States. We prospectively compared coronary atherosclerosis burden, measured with coronary artery calcium (CAC) progression, between men in the 2 countries. Methods In 2 population-based samples of 1712 US White, Black, Hispanic, Chinese men (baseline, 2000-2002) and 697 Japanese men in Japan (2006-2008) aged 45-74 years without clinical cardiovascular disease, we quantified CAC progression by serial computed tomography with medians of 3.4 and 5.2 years between scans, respectively. Results Among White, Black, Hispanic, Chinese, and Japanese men free of baseline CAC, CAC incidence was observed in 35.2%, 26.9%, 29.2%, 18.9%, and 29.2%, respectively. After adjustment for times between scans, demographics, behaviors, coronary risk factors, and their changes between scans, White men had significantly higher CAC incidence than Japanese men (relative risk, 1.68; 95% CI, 1.13-2.50). Among those with detectable baseline CAC, after similar adjustments, all the US race/ethnic groups had significantly greater annual changes in CAC score (mean [95% CI]: 39.4 [35.2-43.6] for White, 26.9 [21.4-32.4] for Black, 30.6 [24.7-36.5] for Hispanic, and 30.2 [22.6-37.8] for Chinese men) than Japanese men (15.9 [10.1-21.8]). Conclusions We found a higher CAC incidence among US White men and greater increases in existing CAC among all the US race/ethnic groups than among Japanese men in Japan. These differences persisted despite adjustment for differences in coronary risk factors