Trends in Metabolic Phenotypes According to Body Mass Index Among US Adults, 1999-2018

County-level socio-environmental factors and obesity prevalence in the United States

AIMS

To investigate high-risk sociodemographic and environmental determinants of health (SEDH) potentially associated with adult obesity in counties in the United States using machine-learning techniques.

MATERIALS AND METHODS

We performed a cross-sectional analysis of county-level adult obesity prevalence (body mass index ≥30 kg/m2) in the United States using data from the Diabetes Surveillance System 2017. We harvested 49 county-level SEDH factors that were used in a classification and regression trees (CART) model to identify county-level clusters. The CART model was validated using a 'hold-out' set of counties and variable importance was evaluated using Random Forest.

RESULTS

Overall, we analysed 2752 counties in the United States, identifying a national median (interquartile range) obesity prevalence of 34.1% (30.2%, 37.7%). The CART method identified 11 clusters with a 60.8% relative increase in prevalence across the spectrum. Additionally, seven key SEDH variables were identified by CART to guide the categorization of clusters, including Physically Inactive (%), Diabetes (%), Severe Housing Problems (%), Food Insecurity (%), Uninsured (%), Population over 65 years (%) and Non-Hispanic Black (%).

CONCLUSION

There is significant county-level geographical variation in obesity prevalence in the United States, which can in part be explained by complex SEDH factors. The use of machine-learning techniques to analyse these factors can provide valuable insights into the importance of these upstream determinants of obesity and, therefore, aid in the development of geo-specific strategic interventions and optimize resource allocation to help battle the obesity pandemic.

Prevalence and correlates of metabolic syndrome among adults in freetown, Sierra Leone: A comparative analysis of NCEP ATP III, IDF and harmonized ATP III criteria

Background

Metabolic syndrome (MetS) is a global health concern, especially for low and middle-income countries with limited resources and information. The study's objective was to assess the prevalence of MetS in Freetown, Sierra Leone, using the National Cholesterol Education Program (NCEP) Adult Treatment Panel III (ATP III), International Diabetes Federation (IDF) and Harmonize ATP III. Additionally, we aimed to establish the concordance between these three different criteria used.

Methods

This community-based health screening survey was conducted from October 2019 to October 2022. A multistage stratified random design was used to select adults aged 20 years and above. Mean, interquartile range (IQR), and logistic regression were used for statistical analysis. The kappa coefficient statistics resolved the agreement between these defined criteria.

Results

The prevalence for NCEP ATP III, Harmonize ATP III and IDF criteria was 11.8 % (95 % CI: 9.0-15.15), 14.3 % (95 % CI: 11.3-18.0), and 8.5 % (95 % CI: 6.2-11.2), respectively for the 2394 selected adults. The kappa coefficient (κ) agreement between the MetS is: Harmonized ATP III and IDF criteria = [(208 (60.8 %); (κ = 0.62)]; Harmonized ATP III and NCEP ATP III = [(201 (58.7 %); (κ = 0.71)]; while IDF and NCEP ATP III was [(132 (38.6 %); (κ = 0.52)]. In the multivariable regression analysis, waist circumference correlated with all three MetS criteria: ATP III [AOR = 0.85; C.I 95 %: (0.40-1.78), p = 0.032], Harmonized ATP III [AOR = 1.14; C.I 95 %: (0.62-2.11), p = 0.024], IDF [AOR = 1.06; C.I 95 % (0.52-2.16), p = 0.018].

Conclusion

We reported a high prevalence of MetS in Freetown, Sierra Leone and identified waist circumference as a major risk factor for MetS. This underscores the crucial role of health education and effective management of MetS in Sierra Leone.

2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association

BACKGROUND

The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Relevance of body composition in phenotyping the obesities

Obesity is the most extended metabolic alteration worldwide increasing the risk for the development of cardiometabolic alterations such as type 2 diabetes, hypertension, and dyslipidemia. Body mass index (BMI) remains the most frequently used tool for classifying patients with obesity, but it does not accurately reflect body adiposity. In this document we review classical and new classification systems for phenotyping the obesities. Greater accuracy of and accessibility to body composition techniques at the same time as increased knowledge and use of cardiometabolic risk factors is leading to a more refined phenotyping of patients with obesity. It is time to incorporate these advances into routine clinical practice to better diagnose overweight and obesity, and to optimize the treatment of patients living with obesity.

Cardiovascular Disease Risk Factors and Outcomes of Acute Myocardial Infarction in Young Adults: Evidence From 2 Nationwide Cohorts in the United States a Decade Apart

The purpose of this study was to evaluate 2 national in-patient cohorts of young adults (18-44 years) hospitalized with acute myocardial infarction (AMI) a decade apart to highlight its prevalence, associated comorbidities, and in-hospital outcomes. We identified hospitalizations for AMI in young adults in 2007 and 2017 using the weighted data from the National Inpatient Sample. We compared admission rates, sociodemographic characteristics, in-hospital morbidity, complications, mortality, rate of coronary interventions, and healthcare utilization between the 2 cohorts. We found that the admission rate of AMI increased among young adults in 2017 vs 2007. The overall admission rate was higher in males, although with a decline (77.1% vs 66.1%), whereas it rose from 28.9% to 33.9% in females. Hypertension (47.8% vs 60.7%), smoking (49.7% vs 55.8%), obesity (14.8% vs 26.8%), and diabetes mellitus (22.0% vs 25.6%) increased in the 2017 cohort. Post-AMI complications: cardiogenic shock (aOR = 1.16 [1.06-1.27]) and fatal arrhythmias heightened with comparable all-cause mortality (aOR = 1.01 [0.93-1.10], P = 0.749). Reperfusion interventions, percutaneous coronary intervention (PCI) and coronary artery bypass grafting (CABG) decreased in the 2017 cohort (PCI; aOR = 0.95 [0.91-0.98], CABG; aOR = 0.66 [0.61-0.71], P < 0.001). Our study highlights the rise in AMI hospitalizations, plateauing of mortality, sex-based and racial disparities, the surge in post-MI complications, and a reassuring decline in the requirement of reperfusion interventions in young AMI patients over the decade.

Adherence to the DASH, MeDi, and MIND diet scores and the incidence of metabolically unhealthy phenotypes

BACKGROUND

A metabolically unhealthy phenotype is associated with the risk of cardiometabolic events and can be prevented by adherence to healthy dietary patterns. The present study was designed to investigate the association between high adherence to the Dietary Approaches to Stop Hypertension (DASH), Mediterranean (MeDi), and Mediterranean-DASH intervention for neurodegenerative delay (MIND) diet scores and the incidence of metabolically unhealthy phenotypes in adults across body mass index (BMI) categories.

METHODS

In this cohort study, 512 subjects with metabolically healthy normal weight (MHNW) at baseline and 787 subjects with metabolically healthy overweight/obesity (MHOW/MHO) at baseline were included. Dietary intake was collected by a validated food frequency questionnaire, and DASH, MeDi, and MIND scores were calculated. The Joint Interim Statement (JIS) criteria were used to define a metabolically unhealthy status.

RESULTS

A total of 137 and 388 subjects with metabolically unhealthy normal weight (MUNW) and metabolically unhealthy overweight/obesity (MUOW/MUO) phenotypes, respectively, were observed, over a mean of 5.91 years of follow-up. The Cox proportional hazard regression indicated participants in the third tertile of the DASH score had a lower risk of the MUNW phenotype (HR: 0.59; 95% CI: 0.37-0.92) than those in the lowest tertile. Similarly, the highest adherence to the MeDi and MIND scores was also linked to a 46% (HR: 0.54; 95% CI: 0.36-0.81) and 47% (HR: 0.53; 95% CI: 0.34-0.83) lower risk of the MUNW phenotype, respectively. As well, there was an inverse relationship between the highest adherence to the DASH (HR: 0.66; 95% CI: 0.50-0.86), MeDi (HR: 0.74; 95% CI: 0.58-0.93), and MIND (HR: 0.57; 95% CI: 0.43-0.74) scores and the risk of MUOW/MUO. There was no interaction between age and the three dietary patterns in relation to a metabolically unhealthy phenotype.

CONCLUSION

High compliance with the DASH, MeDi, and MIND scores was associated with a lower risk of MUNW. An inverse relationship between these three dietary patterns and the incidence of the metabolically unhealthy phenotype was also observed in individuals who had MHOW/MHO at baseline.

Trends in the Prevalence of Metabolically Healthy Obesity Among US Adults, 1999-2018

IMPORTANCE

Improved understanding of trends in the proportion of individuals with metabolically healthy obesity (MHO) may facilitate stratification and management of obesity and inform policy efforts.

OBJECTIVES

To characterize trends in the prevalence of MHO among US adults with obesity, overall and by sociodemographic subgroups.

DESIGN, SETTING, AND PARTICIPANTS

This survey study included 20 430 adult participants from 10 National Health and Nutrition Examination Survey (NHANES) cycles between 1999-2000 and 2017-2018. The NHANES is a series of cross-sectional and nationally representative surveys of the US population conducted continuously in 2-year cycles. Data were analyzed from November 2021 to August 2022.

EXPOSURES

National Health and Nutrition Examination Survey cycles from 1999-2000 to 2017-2018.

MAIN OUTCOMES AND MEASURES

Metabolically healthy obesity was defined as a body mass index of 30.0 (calculated as weight in kilograms divided by height in meters squared) without any metabolic disorders in blood pressure, fasting plasma glucose (FPG), high-density lipoprotein cholesterol (HDL-C), or triglycerides based on established cutoffs. Trends in the age-standardized prevalence of MHO were estimated using logistic regression analysis.

RESULTS

This study included 20 430 participants. Their weighted mean (SE) age was 47.1 (0.2) years; 50.8% were women, and 68.8% self-reported their race and ethnicity as non-Hispanic White. The age-standardized prevalence (95% CI) of MHO increased from 3.2% (2.6%-3.8%) in the 1999-2002 cycles to 6.6% (5.3%-7.9%) in the 2015-2018 cycles (P < .001 for trend). There were 7386 adults with obesity. Their weighted mean (SE) age was 48.0 (0.3) years, and 53.5% were women. The age-standardized proportion (95% CI) of MHO among these 7386 adults increased from 10.6% (8.8%-12.5%) in the 1999-2002 cycles to 15.0% (12.4%-17.6%) in the 2015-2018 cycles (P = .02 for trend). Substantial increases in the proportion of MHO were observed for adults aged 60 years or older, men, non-Hispanic White individuals, and those with higher income, private insurance, or class I obesity. In addition, there were significant decreases in the age-standardized prevalence (95% CI) of elevated triglycerides (from 44.9% [40.9%-48.9%] to 29.0% [25.7%-32.4%]; P < .001 for trend) and reduced HDL-C (from 51.1% [47.6%-54.6%] to 39.6% [36.3%-43.0%]; P = .006 for trend). There was also a significant increase in elevated FPG (from 49.7% [95% CI, 46.3%-53.0%] to 58.0% [54.8%-61.3%]; P < .001 for trend) but no significant change in elevated blood pressure (from 57.3% [53.9%-60.7%] to 54.0% [50.9%-57.1%]; P = .28 for trend).

CONCLUSIONS AND RELEVANCE

The findings of this cross-sectional study suggest that the age-standardized proportion of MHO increased among US adults from 1999 to 2018, but differences in trends existed across sociodemographic subgroups. Effective strategies are needed to improve metabolic health status and prevent obesity-related complications in adults with obesity.