Background: In adults, short periods of weight loss followed by weight gain, known as body mass index(BMI) variability, has been linked to adverse cardiovascular outcomes. However, the impact of long-term BMI variability from childhood on midlife dyslipidemia is unclear. We identified this effect in a cohort of Black and White midlife adults living in a rural community. Methods: We studied 1,268 midlife participants of the Bogalusa Heart Study (age at baseline 9.5 ± 3.5 years, age at midlife 48.2 ± 5.2 years, 59.5% women, 34.4% black) with ≥4 measurements of BMI and other traditional cardiovascular risk factors (CVRF) from childhood. Long-term BMI variability was computed as deviation from age-predicted values (DEV). The associations between long-term BMI variability and dyslipidemia and dyslipidemia subtypes were assessed by logistic regression, adjusting for age, sex, race, CVRF, depression, alcohol use, education, and employment status. Interactions between race, sex and long-term BMI variability were assessed. Results: Prevalence of midlife dyslipidemia were 88.01%(n=1116). DEV was positively significantly associated with having midlife dyslipidemia. Stratified analyses showed that men had higher odds of having midlife dyslipidemia, HDL-C<60 mg/dL, and triglycerides ≥150 mg/dL with 1 unit increase in DEV, compared to those of women. White participants had higher odds of having triglycerides ≥150 mg/dL with 1 unit increase in DEV compared to Black participants. (see Table 1) Conclusions: We identified associations between long-term BMI variability from childhood and midlife dyslipidemia. Race and sex were found to modify the associations of long-term BMI variability on having midlife dyslipidemia and dyslipidemia subtypes. Further studies are needed to determine the role of long-term BMI variability as a predictor for increased risk of midlife dyslipidemia.
Background: Short periods of weight loss followed by weight gain (BMI variability) has been linked to adverse cardiovascular outcomes in adults. However, less is known about the effect of long-term BMI variability from childhood on midlife class II and class III obesity. We identified this effect in a cohort of Black and White midlife adults living in a rural community. Methods: We studied 1,268 midlife participants of the Bogalusa Heart Study (age at baseline 9.5 ± 3.5 years, age at midlife 48.2 ± 5.2 years, 59.5% women, 34.4% Black) with ≥4 measurements of BMI and other traditional cardiovascular risk factors (CVRF) from childhood. Long-term BMI variability was computed as deviation from age-predicted values (DEV). Logistic regression, adjusting for age, sex, race, CVRF, depression, alcohol use, education, and employment status, was conducted to assess associations between long-term BMI variability and midlife obesity (class II and III, BMI ≥35kg/m 2 and ≥40kg/m 2 , respectively). Interactions between race, sex and long-term BMI variability were assessed. Results: Prevalence of midlife class II and class III obesity were 26.81%(n=340) and 12.7%(n=161), respectively. DEV was positively significantly associated with having midlife class II and class III obesity. For class II obesity, no significant interactions between DEV and race or sex were observed. For class III obesity, interactions of DEV with race and sex were significant; the odds of having class III midlife obesity per unit increase in DEV were greater in White participants and in men compared with Black participants and women(see Table 1). Conclusions: We identified associations between long-term BMI variability from childhood and midlife obesity. Race and sex were observed to modify the effect of BMI variability on having midlife obesity. Further studies are needed to elucidate the role of long-term BMI variability as a predictor for increased risk of midlife obesity.
Background: Multiple chronic conditions, primarily of cardiovascular origins, are a major cause of disability, death, and health care spending. Cardiovascular multimorbidity is also associated with multiplicative risk of morality and substantially lower life expectancy, which may exacerbate health disparities. However, its impact in a rural and low socioeconomic community with a high proportion of minorities is understudied. We aimed to describe multimorbidity prevalence and patterns by race, sex, and socioeconomic status in a middle-aged, community-based cohort. Methods: We examined 1,298 Black (35%) and White (65%) individuals (mean age 48.17 ± SD 5.27 years; 59% female) from the Bogalusa Heart Study, a rural, community-based, longitudinal cohort in Bogalusa, Louisiana, between 2013 and 2016. Eight chronic conditions (CCs) selected based on CMS (Centers for Medicare & Medicaid Services) guidance were defined using data from self-reported medical history, medication use, and physiological or laboratory measures. We defined multimorbidity as the coexistence of two or more of these conditions. The prevalence of cardiovascular multimorbidity and the most commonly occurring dyads and triads were assessed by race, sex, and socioeconomic factors using chi-square tests. Results: We found that 70% of the 1,298 participants had ≥2 CCs, while 31% had ≥3 CCs. The most prevalent conditions were dyslipidemia (87.9%, n=1,141), hypertension (66.6%, n=864), and diabetes (19.7%, n=255). The prevalence of multimorbidity was higher in Black than in White (76.8%, n=344 vs. 66.5%, n=565; p<0.01) participants and higher in men than in women (73.6%, n=393 vs. 67.5%, n=516; p<0.02). Hypertension and dyslipidemia made up the most prevalent dyad (33.0%, n=413), while hypertension, dyslipidemia, and diabetes made up the most prevalent triad (9.4%, n=116). Multimorbidity prevalence was significantly higher among participants with government issued insurance compared to private insurance (80.7%, n=267 vs. 64%, n=427; p<0.001), and more common among lower income compared to higher income (74.6%, n=390 vs 65.4%, n=397; p<0.01), respectively. Conclusion: Cardiovascular multimorbidity is highly prevalent in midlife among participants of the Bogalusa cohort compared to national and even state-wide levels. These findings have critical public health ramifications and support the need to better study multiple CCs in rural, underserved populations to create tailored interventions that are effective among adults in their most productive years of life despite geographic and income barriers.
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