S-EPMC6404455 - Body Mass Index From Early-, Mid-, and Older-Adulthood and Risk of Heart Failure and Atherosclerotic Cardiovascular Disease: MESA. - OmicsDI

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Body Mass Index From Early-, Mid-, and Older-Adulthood and Risk of Heart Failure and Atherosclerotic Cardiovascular Disease: MESA.

ABSTRACT: Background Obesity contributes significantly to risk of atherosclerotic cardiovascular disease (ASCVD) and especially for heart failure (HF). An elevated body mass index (BMI) in older adults might not carry the same risk as in younger adults, but measured weights at other lifetime points are often not available. We determined the associations of self-reported weights from early- and mid-adulthood, after accounting for measured weight at older age, with incident HF/ASCVD risk. Methods and Results We studied 6437 MESA (Multi-Ethnic Study of Atherosclerosis) participants (aged 45-84, free of baseline HF/ASCVD) with self-reported weights at ages 20 and 40 years (by questionnaire), measured weights at up to 5 in-person examinations (2000-2012), and follow-up for adjudicated HF/ASCVD events. Participant mean±SD age at the baseline examination was 62.2±10.2 years. Over median follow-up of 13 years, 290 HF and 828 ASCVD events occurred. After adjustment for cardiovascular risk factors and baseline BMI, higher self-reported weights at ages 20 and 40 years were independently associated with increased risk of incident HF with hazard ratios (95% confidence interval) of 1.27 (1.07-1.50) and 1.36 (1.18-1.57), respectively, per 5-kg/m² higher BMI. For incident ASCVD, only higher BMI at age 20 years was associated after accounting for current BMI (1.13 [1.01-1.26] per 5 kg/m²). Obesity during follow-up examinations was also associated with incident HF (1.72 [1.21-2.45]) but not ASCVD. Conclusions Self-reported lifetime weight is a low-tech tool easily utilized in any clinical encounter. Although subject to recall bias, self-reported weights may provide prognostic information about future HF risk, incremental to current BMI, in a multiethnic cohort of middle-aged to older adults. Clinical Trial Registration URL: http://www.clinicaltrials.gov . Unique identifier: NCT00005487.

SUBMITTER: Fliotsos M

PROVIDER: S-EPMC6404455 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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Body Mass Index From Early-, Mid-, and Older-Adulthood and Risk of Heart Failure and Atherosclerotic Cardiovascular Disease: MESA.

Fliotsos Michael M Zhao Di D Rao Vishal N VN Ndumele Chiadi E CE Guallar Eliseo E Burke Gregory L GL Vaidya Dhanajay D Delaney Joseph Chris A JCA Michos Erin D ED

Journal of the American Heart Association 20181101 22

Background Obesity contributes significantly to risk of atherosclerotic cardiovascular disease (ASCVD) and especially for heart failure (HF). An elevated body mass index (BMI) in older adults might not carry the same risk as in younger adults, but measured weights at other lifetime points are often not available. We determined the associations of self-reported weights from early- and mid-adulthood, after accounting for measured weight at older age, with incident HF/ASCVD risk. Methods and Result ...[more]

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Project description:BackgroundUnderstanding lifecourse trajectories of body-mass index (BMI) is important for identifying groups at high risk of poor health and potential target points for intervention. This study aimed to describe BMI trajectories from childhood to mid-adulthood in four population-based cohorts established in the 1970s and 1980s and to identify childhood sociodemographic factors related to trajectory membership.MethodsBetween Dec 17, 1970 and Dec 15, 1994, data were collected at the first visit from 9830 participants from the International Childhood Cardiovascular Cohort (i3C) Consortium, which includes participants from Australia (1985), Finland (1980) and the USA (1970-1994). Participants had at least three measures of height and weight, including one in childhood (6-18 years) and one in adulthood (>18 years), and were aged 30-49 years at last measurement. Latent Class Growth Mixture Modelling was used to identify lifecourse BMI trajectory groups and log multinomial regression models were fit to identify their childhood sociodemographic predictors.FindingsFive consistent BMI trajectory groups were identified amongst the four cohorts: persistently low (35.9-58.6%), improving from high (0.7-4.8%), progressing to moderate (9.3-43.7%), progressing to high (1.1-6.0%), and progressing to very high (0.7-1.3%). An additional three BMI trajectory groups were identified in some, but not all, cohorts: adult onset high (three cohorts; 1.8-20.7%), progressing to moderate-high (two cohorts; 5.2-13.8%), and relapsing yo-yoers (alternating upward and downward; one cohort; 1.3%). In pooled analyses, each predictor variable in childhood, including age, gender, parental education and race, was associated with increased likelihood of belonging to the most (e.g., improving from high) and least (e.g., progressing to very high) favourable BMI trajectory groups, suggesting a U-shaped (or inverse U-shaped) pattern of association.InterpretationFive consistent BMI trajectory groups were identified across four cohorts from Australia, Finland, and the USA, mainly across two eras of birth. While most participants remained on a persistently low trajectory (50%), many demonstrated worsening BMI trajectories (47%), with only few demonstrating improving trajectories (<5%). Age, gender, parental education, and race appear to be important predictors of BMI trajectory group membership and need consideration in preventive and management strategies.FundingThis study was supported by funding from the National Institutes of Health, National Heart, Lung and Blood Institute (grant number R01 HL121230).

Project description:AimsThere are limited data examining whether body mass index (BMI) influences the association between cardiovascular biomarkers and incident heart failure (HF).Methods and resultsThirteen biomarkers representing key HF domains were measured: N-terminal pro-B-type natriuretic peptide (NT-proBNP), mid-regional pro-A-type natriuretic peptide (MR-proANP), cardiac troponin T (cTnT), C-reactive protein, procalcitonin, galectin-3, C-terminal pro-endothelin-1 (CT-proET-1), mid-regional pro-adrenomedullin, plasminogen activator inhibitor-1, copeptin, renin, aldosterone, and cystatin-C. Associations of biomarkers with BMI were examined using linear regression models, and with incident HF using Cox regression models. We selected biomarkers significantly associated with incident HF, and evaluated whether BMI modified these associations. Among 8202 individuals, 41% were overweight (BMI 25-30 kg/m2 ), and 16% were obese (BMI ≥30 kg/m2 ). Mean age of the cohort was 49 years (range 28-75), and 50% were women. All biomarkers except renin were associated with BMI: inverse associations were observed with NT-proBNP, MR-proANP, CT-proET-1 and aldosterone whereas positive associations were observed with the remaining biomarkers (all P ≤ 0.001). During 11.3 ± 3.1 years of follow-up, 357 HF events were recorded. Only NT-proBNP, MR-proANP and cTnT remained associated with incident HF (P < 0.001), and a significant biomarker*BMI interaction was not observed (interaction P > 0.1). Combined NT-proBNP and cTnT measurements modestly improved performance metrics of the clinical HF model in overweight (ΔC-statistic = 0.024; likelihood ratio χ2 = 38; P < 0.001) and obese (ΔC-statistic = 0.020; likelihood ratio χ2 = 32; P < 0.001) individuals.ConclusionsPlasma concentrations of several cardiovascular biomarkers are influenced by obesity. Only NT-proBNP, MR-proANP and cTnT were associated with incident HF, and BMI did not modify these associations. A combination of NT-proBNP and cTnT improves HF risk prediction in overweight and obese individuals.

Project description:ImportanceAbundant 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.ObjectiveTo examine the association of BMI in midlife with morbidity burden, longevity, and health care expenditures in adults 65 years and older.Design, setting, and participantsProspective 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.ExposuresStandard 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).ResultsAmong 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 < .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% CI, $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 < .001).Conclusions and relevanceIn 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.

Project description:ImportanceObesity is a global health challenge and a risk factor for atherosclerotic cardiovascular disease (ASVCD). Performance of the pooled cohort equations (PCE) for ASCVD risk by body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) is unknown.ObjectiveTo assess performance of the PCE across clinical BMI categories.Design, setting, and participantsThis cohort study used pooled individual-level data from 8 community-based, prospective, longitudinal cohort studies with 10-year ASCVD event follow-up from 1996 to 2016. We included all adults ages 40 to 79 years without baseline ASCVD or statin use, resulting in a sample size of 37 311 participants. Data were analyzed from August 2017 to July 2020.ExposuresParticipant BMI category: underweight (<18.5), normal weight (18.5 to <25), overweight (25 to <30), mild obesity (30 to <35), and moderate to severe obesity (≥35).Main outcomes and measuresDiscrimination (Harrell C statistic) and calibration (Nam-D'Agostino χ2 goodness-of-fit test) of the PCE across BMI categories. Improvement in discrimination and net reclassification with addition of BMI, waist circumference, and high-sensitivity C-reactive protein (hsCRP) to the PCE.ResultsAmong 37 311 participants (mean [SD] age, 58.6 [11.8] years; 21 897 [58.7%] women), 380 604 person-years of follow-up were conducted. Mean (SD) baseline BMI was 29.0 (6.2), and 360 individuals (1.0%) were in the underweight category, 9937 individuals (26.6%) were in the normal weight category, 13 601 individuals (36.4%) were in the overweight category, 7783 individuals (20.9%) were in the mild obesity category, and 5630 individuals (15.1%) were in the moderate to severe obesity category. Median (interquartile range [IQR]) 10-year estimated ASCVD risk was 7.1% (2.5%-15.4%), and 3709 individuals (9.9%) developed ASCVD over a median (IQR) 10.8 [8.5-12.6] years. The PCE overestimated ASCVD risk in the overall cohort (estimated/observed [E/O] risk ratio, 1.22; 95% CI, 1.18-1.26) and across all BMI categories except the underweight category. Calibration was better near the clinical decision threshold in all BMI groups but worse among individuals with moderate or severe obesity (E/O risk ratio, 1.36; 95% CI, 1.25-1.47) and among those with the highest estimated ASCVD risk ≥20%. The PCE C statistic overall was 0.760 (95% CI, 0.753-0.767), with lower discrimination in the moderate or severe obesity group (C statistic, 0.742; 95% CI, 0.721-0.763) compared with the normal-range BMI group (C statistic, 0.785; 95% CI, 0.772-0.798). Waist circumference (hazard ratio, 1.07 per 1-SD increase; 95% CI, 1.03-1.11) and hsCRP (hazard ratio, 1.07 per 1-SD increase; 95% CI, 1.05-1.09), but not BMI, were associated with increased ASCVD risk when added to the PCE. However, these factors did not improve model performance (C statistic, 0.760; 95% CI, 0.753-0.767) with or without added metrics.Conclusions and relevanceThese findings suggest that the PCE had acceptable model discrimination and were well calibrated at clinical decision thresholds but overestimated risk of ASCVD for individuals in overweight and obese categories, particularly individuals with high estimated risk. Incorporation of the usual clinical measures of obesity did not improve risk estimation of the PCE. Future research is needed to determine whether incorporation of alternative high-risk obesity markers (eg, weight trajectory or measures of visceral or ectopic fat) into the PCE may improve risk prediction.

Project description:BackgroundChildren with overweight or obesity are at greatly increased risk of experiencing obesity in adulthood but for reasons generally unknown some attain a healthier adult weight. This qualitative study investigated individual, social and environmental factors that might explain diverging body mass index (BMI) trajectories. This knowledge could underpin interventions to promote healthy weight.MethodsThis 2016 study included participants from three adult follow-ups of children who (when 7-15 years) participated in the 1985 Australian Schools Health and Fitness Survey and provided BMI data at each time point. Trajectory-based group modelling identified five BMI trajectories: stable below average, stable average, increasing from average, increasing from very high and decreasing from very high. Between six and 12 participants (38-46 years) from each BMI trajectory group were interviewed (n = 50; 60% women). Thematic analysis guided by a social-ecological framework explored individual, social and environmental influences on diet and physical activity within the work setting.ResultsA distinct approach to healthy behaviour was principally identified in the stable and decreasing BMI groups - we term this approach "health identity" (exemplified by "I love having a healthy lifestyle"). This concept was predominant in the stable or decreasing BMI groups when participants explained why work colleagues seemingly did not influence their health behaviour. Participants in the stable and decreasing BMI groups also more commonly reported, bringing home-prepared lunches to work, working or being educated in a health-related field, having a physically active job or situating physical activity within and around work - the latter three factors were common among those who appeared to have a more distinct "health identity". Alcohol, workplace food culture (e.g. morning teas), and work-related stress appeared to influence weight-related behaviours, but generally these factors were similarly discussed across all trajectory groups.ConclusionWork-related factors may influence weight or weight-related behaviours, irrespective of BMI trajectory, but the concept of an individual's "health identity" may help to explain divergent BMI trajectories. "Health identity" and its influence on health behaviour warrants further exploratory work.