State‐Level Estimates of Annual Medical Expenditures Attributable to Obesity*

Objective: To provide state‐level estimates of total, Medicare, and Medicaid obesity‐attributable medical expenditures. Research Methods and Procedures: We developed an econometric model that predicts medical expenditures. We used this model and state‐representative data to quantify obesity‐attributable medical expenditures. Results: Annual U.S. obesity‐attributable medical expenditures are estimated at $75 billion in 2003 dollars, and approximately one‐half of these expenditures are financed by Medicare and Medicaid. State‐level estimates range from $87 million (Wyoming) to $7.7 billion (California). Obesity‐attributable Medicare estimates range from $15 million (Wyoming) to $1.7 billion (California), and Medicaid estimates range from $23 million (Wyoming) to $3.5 billion (New York). Discussion: These estimates of obesity‐attributable medical expenditures present the best available information concerning the economic impact of obesity at the state level. Policy makers should consider these estimates, along with other factors, in determining how best to allocate scarce public health resources. However, because they are associated with large SE, these estimates should not be used to make comparisons across states or among payers within states.     

Age-Dependent Influence of Gender on the Association Between Obesity and a Cluster of Cardiometabolic Risk Factors

BackgroundObesity is a main risk factor in metabolic syndrome. Gender is known to influence the risk of obesity and other cardiovascular risk factors. However, it remains to be determined whether there is a gender-specific difference in the relationship between obesity and accumulation of other cardiometabolic risk factors such as hypertension, dyslipidemia, and diabetes.ObjectiveThe aim of this study was to determine whether the association between obesity and a cluster of other cardiometabolic risk factors is modified by gender.MethodsThe subjects were 17,791 Japanese men and women who were divided into younger (35–40 years) and older (60–70 years) age groups. The relationships between obesity (body mass index [BMI] ≥25 kg/m² or waist-to-height ratio [WHtR] ≥0.5) and multiple cardiometabolic risk factors (≥2 of the risk factors of high blood pressure, dyslipidema, and hyperglycemia) were compared between men and women in each age group.ResultsIn the younger group, the crude odds ratios (ORs) for multiple cardiometabolic risk factors in obese versus nonobese subjects were significantly higher in women than in men (BMI: 6.23 [range, 5.53–7.02] in men vs 16.63 [range, 12.37–22.37] in women, P < 0.01; WHtR: 6.04 [range, 5.36–6.81] in men vs 9.77 [range, 7.14–13.37] in women, P < 0.01), whereas this difference was not found in the older group (BMI: 3.03 [range, 2.69–3.42] in men vs 2.92 [range, 2.33–3.67] in women P = 0.076; WHtR: 3.11 [range, 2.78–3.47] in men vs 2.50 [range, 2.02–3.09] in women, P < 0.05). On multivariate logistic regression analysis, the ORs for multiple cardiometabolic risk factors after adjusting for age, smoking, alcohol consumption, and regular exercise in subjects with versus subjects without a large waist circumference tended to be higher in women than in men in the younger group but not in the older group. The ORs of the interaction term consisting of gender and each adiposity index for multiple cardiometabolic risk factors were significantly higher than a reference level of 1.00 in the younger group (BMI: 2.68 [range, 1.95–3.69], P < 0.01; WHtR: 1.62 [range, 1.16–2.27], P < 0.01) but not in the older group (BMI: 0.95 [range, 0.74–1.23], P = 0.712; WHtR: 0.80 [range, 0.63–1.02], P = 0.066).ConclusionThe results suggest that the association between obesity and a cluster of cardiometabolic risk factors is stronger in women than in men, and this gender-specific difference exists in younger (35–40 years) but not in older (60–70 years) individuals.     

Relationships of BMI to Cardiovascular Risk Factors Differ by Ethnicity

The burden of cardiovascular risk associated with obesity disproportionately affects African Americans and little is known about ethnic/racial differences in the relationship of obesity to cardiometabolic risk. This report assesses whether obesity is similarly associated with cardiometabolic risk factors in African Americans and whites of European ancestry. Cross‐sectional observational data from the Jackson Heart Study (JHS) and the Framingham Heart Study (FHS) were compared. This analysis uses participants aged 35–74 years with BMI >18.5 kg/m², and free of prevalent cardiovascular disease (CVD), from the initial JHS clinical examination (2000–2004) and the FHS Offspring (1998–2001) and Third Generation (2002–2005) cohorts. Participants were evaluated for the presence of lipid abnormalities, hypertension, and diabetes. Overall, 4,030 JHS (mean age 54 years, 64% women) and 5,245 FHS (mean age 51 years, 54% women) participants were available for analysis. The prevalence of all risk factors except high triglycerides and low high‐density lipoprotein (HDL) was substantially higher in JHS (all P < 0.001) and BMI was associated with increasing prevalence of most CVD risk factors within each race. For diabetes mellitus, hypertension, and low HDL, steeper relationships to BMI were observed in FHS than in JHS (P values <0.001–0.016). There were larger proportional increases in risk factor prevalence with increasing BMI in whites than in African Americans. The higher prevalence rates of cardiometabolic risk factors at nearly all levels of BMI in African Americans, however, suggest that additional factors contribute to the burden of CVD risk in African Americans.     

Current Estimates of the Economic Cost of Obesity in the United States

This study was undertaken to update and revise the estimate of the economic impact of obesity in the United States. A prevalence-based approach to the cost of illness was used to estimate the economic costs in 1995 dollars attributable toobesity for type 2 diabetes mellitus, coronary heart disease (CHD), hypertension, gallbladder disease, breast, endometrial and colon cancer, and osteoarthritis. Additionally and independently, excess physician visits, work-lost days, restricted activity, and bed-days attributable to obesity were analyzed cross-sectionally using the 1988 and 1994 National Health Interview Survey (NHIS). Direct (personal health care, hospital care, physician services, allied health services, and medications) and indirect costs (lost output as a result of a reduction or cessation of productivity due to morbidity or mortality) are from published reports and inflated to 1995 dollars using the medical component of the consumer price index (CPI) for direct cost and the all-items CPI for indirect cost. Population-attributable risk percents (PAR%) are estimated from large prospective studies. Excess work-lost days, restricted activity, bed-days, and physician visits are estimated from 88,262 U. S. citizens who participated in the 1988 NHIS and 80,261 who participated in the 1994 NHIS. Sample weights have been incorporated into the NHIS analyses, making these data generalizable to the U. S. population. The total cost attributable to obesity amounted to $99. 2 billion dollars in 1995. Approximately $51. 64 billion of those dollars were direct medical costs. Using the 1994 NHIS data, cost of lost productivity attributed to obesity (BMI≥30) was $3. 9 billion and reflected 39. 2 million days of lost work. In addition, 239 million restricted-activity days, 89. 5 million bed-days, and 62. 6 million physician visits were attributable to obesity in 1994. Compared with 1988 NHIS data, in 1994 the number of restricted-activity days (36%), bed-days (28%), and work-lost days (50%) increased substantially. The number of physician visits attributed to obesity increased 88% from 1988 to 1994. The economic and personal health costs of overweight and obesity are enormous and compromise the health of the United States. The direct costs associated with obesity represent 5. 7% of our National Health Expenditure in the United States .     

Racial and Ethnic Cardiometabolic Risk Disparities in the Type 1 Diabetes Exchange Clinic Registry Cohort

ObjectiveTo determine whether individuals from a historically underrepresented racial group have a higher cardiometabolic risk than historically represented individuals with type 1 diabetes (T1D) considering socioeconomic deprivation.MethodsWe used the multivariable logistic and linear regression models to examine socioeconomic deprivation (upper 10th percentile) by race/ethnicity interaction for each cardiometabolic risk factor and cardiometabolic risk burden score, respectively, across 6320 zip code tabulation areas. We also determined the age-adjusted prevalence of low, moderate, and high cardiometabolic risks defined as 0, 1 to 2, and 3 or more risk factors for hypertension, obesity, dyslipidemia, and off-target glycemia for non-Hispanic White (n = 15 746), non-Hispanic Black (n = 1019), Hispanic (n = 1115), and other (n = 887), respectively.ResultsThe sample comprised 18 767 adolescents and adults with T1D. Those identifying as non-Hispanic Black were more likely to have a high cardiometabolic risk profile, including a 4.5-fold increase in the odds of off-target glycemia, a twofold increase in the odds of systolic hypertension, and 0.29 (unadjusted) and 0.46 (adjusted) increases in a higher cardiometabolic risk burden compared with non-Hispanic White individuals (P < .01). Those identifying as Hispanic had a 3.4-fold increase in the odds of off-target glycemia but were less likely to be overweight/obese or have systolic hypertension compared with non-Hispanic White. However, the lower likelihood of overweight/obesity and hypertension did not persist after considering covariates.ConclusionThere is a need to investigate additional determinants of racially/ethnically underrepresented cardiometabolic health, including structural racism and implicit bias in cardiometabolic care for individuals with T1D.     

Pathophysiologic Mechanisms Linking Adipose Tissue and Cardiometabolic Risk

ObjectiveTo describe the contribution of adipocytes and adipose tissue to increased cardiometabolic risk as well as the mechanisms by which adipose tissue and obesity contribute to dysglycemia, dyslipidemia, hypertension, and a prothrombotic, inflammatory state favoring atherogenesis.MethodsA review was undertaken of the relevant available reports, compiled by means of a search(PubMed) of the English-language literature published between 1994 and 2010.ResultsCoronary risk factors cause susceptibility to development of atherosclerosis. Traditional coronary risk factors are obesity, smoking, hypertension, diabetes, elevated serum cholesterol levels, male sex, advancing age, and a family history of early coronary events. The currently preferred term of cardiometabolic risk encompasses both the traditional coronary risk factors and the additional contributing factors of insulin resistance, atherogenic dyslipidemia, physical inactivity, unhealthful eating, inflammation, and hypercoagulation. The accumulation of adipose tissue (adiposity) and dysfunctional adipose tissue (adiposopathy) contribute to most, if not all, of the cardiometabolic risk factors. Adipose tissue promotes atherosclerosis through several different pathologic mechanisms, which are reviewed in this report. The treatment of obesity should focus on reducing fat mass and minimizing adipocyte dysfunction.ConclusionAdipose tissue contributes to the development of insulin resistance, hyperglycemia, atherogenic dyslipidemia, and arterial hypertension and favors a prothrombotic and proinflammatory state. Adipose tissue dysfunction increases cardiometabolic risk through a variety of mechanisms. (Endocr Pract. 2010;16:692-698)     

Epidemiology and factor analysis of obesity, type II diabetes, hypertension, and dyslipidemia (syndrome X) on the Island of Kosrae, Federated States of Micronesia

OBJECTIVES: Obesity, type II diabetes, hypertension, and dyslipidemia are major causes of morbidity and mortality throughout the world. Though these disorders often cluster in individuals and families and are collectively known as syndrome X, the basis for this aggregation is not well understood. To further understand the pathogenesis of syndrome X, a comprehensive epidemiological study was undertaken on the Pacific Island of Kosrae, Federated States of Micronesia (FSM). METHODS: The entire adult (>20 years of age) population of Kosrae underwent a clinical evaluation that included a questionnaire that noted the participants' sex, family data including listing of biological parents, siblings, and children, smoking status, village of residence, age and health status. The medical evaluation included: anthropometric measures (weight, height, waist, hip), serum chemistries (leptin, fasting blood sugar (FBS), insulin, total cholesterol (TC), triglycerides (TG), and apolipoproteins B and A-I (apo B and apo A-I) and blood pressure (BP) measurements. RESULTS: Obesity (BMI >/=35) was found in 24%, diabetes (FBS >/=126 or 2-hour oral glucose tolerance test >/=200) in 12%, hypertension (SBP >/=140 or DBP >/=90) in 17%, and dyslipidemia (TC >/=240 or TG >/=200 or apo B >/=120 or apo A-I 相似文献   

Mifepristone Reduces Weight Gain and Improves Metabolic Abnormalities Associated With Risperidone Treatment in Normal Men

Antipsychotic medications are associated with significant weight gain, type 2 diabetes mellitus, dyslipidemia, and increased cardiovascular risk. The objective of this study was to determine whether mifepristone, a glucocorticoid receptor antagonist, could prevent risperidone‐induced weight gain. Using a 2:2:1 randomization scheme, 76 lean, healthy men (BMI 18–23 kg/m²) age 18–40 years were randomized to risperidone (n = 30), risperidone plus mifepristone (n = 30) or mifepristone (n = 16) daily for 28 days in an institutional setting. Subjects were provided food ad libitum. Body weight was measured daily. Metabolic measures were taken at study onset, midpoint, and end. Analyses of covariance indicated that the group receiving risperidone plus placebo gained significantly more weight (P < 0.001) and exhibited a significantly greater increase in waist circumference (P < 0.05) than the group receiving risperidone plus mifepristone. Significant differences were also observed for metabolic measures including fasting insulin (P < 0.001) and triglyceride levels (P < 0.05). Mifepristone attenuated increases in weight and reduced the metabolic changes induced by risperidone use, replicating results from a prior study of olanzapine‐induced weight gain. These findings suggest mechanistic involvement of the hypothalamic‐pituitary‐adrenal axis in the weight and cardiometabolic side effects of antipsychotic medications. Future research should continue to test the potential of glucocorticoid antagonists to alleviate the deleterious side effects associated with use of antipsychotic medications.     

Body size phenotypes and inflammation in the Women's Health Initiative Observational Study

Individuals with "metabolically benign" obesity (obesity unaccompanied by hypertension, dyslipidemia, and diabetes) are not at elevated 10-year risk of cardiovascular disease (CVD) compared to normal weight individuals. It remains unclear whether these obese individuals or normal weight individuals with clustering of cardiometabolic factors display heightened immune activity. Therefore, we characterized levels of acute-phase reactants (C-reactive protein (CRP), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), white blood cell (WBC) count), adhesion molecules (E-selectin, vascular cell adhesion molecule-1), and coagulation products (fibrinogen, plasminogen activator inhibitor-1 (PAI-1)) among four body size phenotypes (normal weight with 0/1 vs. ≥2 metabolic syndrome components/diabetes and overweight/obesity with 0/1 vs. ≥2 metabolic syndrome components/diabetes) in cross-sectional analyses of 1,889 postmenopausal women from the Women's Health Initiative Observational Study (WHI-OS) nested case-control stroke study. Higher levels of all three inflammatory marker categories were found among women with overweight/obesity or ≥2 metabolic syndrome components or diabetes. Compared to normal weight women with 0 or 1 metabolic syndrome components, normal weight women with ≥2 metabolic syndrome components or diabetes were more likely to have ≥3 inflammatory markers in the top quartile (multivariate odds ratio (OR) 2.0, 95% confidence interval (CI): 1.3-3.0), as were overweight/obese women with 0 or 1 metabolic syndrome components (OR 2.3; 95% CI: 1.5-3.5). Overweight/obese women with ≥2 metabolic syndrome components or diabetes had the highest OR (OR 4.2; 95% CI: 2.9-5.9). Despite findings that metabolically benign obese individuals are not at increased 10-year risk of CVD compared to normal weight individuals, the current results suggest that overweight/obese women without clustering of cardiometabolic risk factors still possess abnormal levels of inflammatory markers.     

Obesity and cardiovascular risk factors among men and women aged 40 years and older in a rural area of Japan

Obesity is one of the most common health problems, and is recognized worldwide as an "escalating epidemic." For the establishment of an obesity-prevention strategy in Japan, it is important to assess the association between obesity and cardiovascular risk factors. Therefore, we conducted anthropometric measures of obesity and investigated the association of obesity with cardiovascular risk factors such as hypertension, diabetes, and dyslipidemia among community-dwelling men (N=85) and women (N=173) aged 40 years and older. Height, weight, and waist circumference (WC) were measured, and body mass index (BMI) was calculated. Subjects with a BMI> or =25 kg/m(2) were considered obese (BMI obesity), while men with a WC> or =85 cm and women with a WC> or =90 cm were classified as obese (WC obesity). In the present study, we defined 'obesity' as a BMI> or =25 kg/m(2) or a WC> or =85 cm for men, and a BMI> or =25 kg/m(2) or a WC> or =90 cm for women. The results of an age- and sex-adjusted logistic regression analysis indicated that BMI obesity was associated with dyslipidemia (p=0.04), WC obesity was associated with dyslipidemia (p=0.07), and 'obesity' was associated with diabetes (p=0.06) and dyslipidemia (p=0.01). These results emphasize the importance of preventing obesity in Japan. Therefore, healthcare professionals should measure BMI and WC in order to enhance their assessment of cardiovascular risk.     

Cross-Sectional Assessment of Nut Consumption and Obesity,Metabolic Syndrome and Other Cardiometabolic Risk Factors: The PREDIMED Study

Introduction

Prospective studies have consistently suggested that nut consumption is inversely related to fatal and non-fatal coronary heart disease. Limited data are available on the epidemiological associations between nut intake and cardiometabolic risk factors.

Objective

To evaluate associations between frequency of nut consumption and prevalence of cardiometabolic risk factors [obesity, metabolic syndrome (MetS), type-2 diabetes, hypertension, and dyslipidemia] in a Mediterranean population at high cardiovascular risk.

Materials and Methods

Cross-sectional study of 7,210 men and women (mean age, 67 y) recruited into the PREDIMED study. MetS was defined by the harmonized ATPIII and IDF criteria. Diabetes and hypertension were assessed by clinical diagnosis and dyslipidemia (high triglycerides, low HDL-cholesterol, and hypercholesterolemia) by lipid analyses. Nut consumption was assessed using a validated food frequency questionnaire and categorized as <1, 1–3, and >3 servings/wk. Control of confounding was done with multivariate logistic regression.

Results

Compared to participants consuming <1 serving/wk of nuts, those consuming >3 servings/wk had lower adjusted odds ratios (OR) for obesity (0.61, 95% confidence interval 0.54 to 0.68; P-trend <0.001), MetS (0.74, 0.65 to 0.85; P-trend<0.001), and diabetes (0.87, 0.78 to 0.99; P-trend = 0.043). Higher nut consumption was also associated with lower risk of the abdominal obesity MetS criterion (OR 0.68, 0.60 to 0.79; P-trend<0.001). No significant associations were observed for the MetS components high blood pressure, dyslipidemia, or elevated fasting glucose.

Conclusions

Nut consumption was inversely associated with the prevalence of general obesity, central obesity, MetS, and diabetes in subjects at high cardiovascular risk.     

Leptin Predicts a Worsening of the Features of the Metabolic Syndrome Independently of Obesity

Objective: The term metabolic syndrome (MS) describes a cluster of cardiovascular risk factors including dyslipidemia, glucose intolerance, insulin resistance, and hypertension. Obesity increases the risk of MS, but as obesity is neither necessary nor sufficient to cause the syndrome, there is considerable interest in identifying obesity‐independent pathways. One such pathway may involve the actions of the adipokine leptin, which is associated cross‐sectionally with MS and prospectively with coronary heart disease and stroke, independently of obesity. Our goal was to test the hypothesis that leptin predicts the development of the features of MS independently of obesity. Research Methods and Procedures: This study used a prospective population‐based cohort of 748 middle‐aged whites in whom baseline measures of leptin and repeated measurement of the subcomponents of the MS at 5 and 10 years were available. The features of the MS were characterized as five factors (obesity, dyslipidemia, elevated blood pressure, glucose intolerance, and insulin resistance), which were combined to create an MS summary score. Results: Baseline leptin significantly predicted the development of obesity (p = 0.001) and, after adjustment for BMI, development of glucose intolerance (p = 0.016) and insulin resistance (p < 0.0001). Leptin levels did not independently predict a change in lipids or blood pressure. Leptin levels significantly predicted the development of the MS (p = 0.036), independently of baseline BMI. Discussion: Leptin predicts the development of the MS independently of baseline obesity. This association is specifically related to the development of glucose intolerance and insulin resistance. The extent to which these relationships are explained through residual confounding by obesity remains to be determined.     

Birth weight correlates differently with cardiovascular risk factors in youth

Objective: Childhood obesity has become prevalent, resulting in a greater risk of hypertension, diabetes, and dyslipidemia. However, the relationship between these comorbid conditions and birth weight remains uncertain. We conducted this study to evaluate the relationship between birth weight and cardiovascular risk factors in children and adolescents. Research Methods and Procedures: In a nationwide survey conducted between 1992 and 2000, all schoolchildren 6 to 18 years old with glucosuria, proteinuria, or microscopic hematuria in repeated urine samples were included and received a physical examination and blood test. Those with gestational age <37 weeks were excluded. We enrolled 81,538 children (51,111 girls and 30,427 boys) and obtained their birth weights from the Taiwan Birth Registry. Obesity and hypertension were defined by age‐ and sex‐specific cut‐offs. Diabetes was diagnosed if the fasting glucose was >7 mM. Results: The risk of obesity was higher for those with birth weights ≥4000 grams [odds ratio (OR), 1.65] and 3543 to 3999 grams (OR, 1.28) and lower for those with birth weights 2601 to 2999 grams (OR, 0.90), using 3000 to 3542 grams as the reference group. An increased risk of diabetes was associated with both higher and lower birth weights, indicating a U‐shaped relationship (OR, <2600 grams, 1.607; 2601 to 2999 grams, 1.119; 3543 to 3999 grams, 1.112; ≥4000 grams, 1.661). In the 10‐ to 12‐year‐old age group, the risk of hypertension was higher in those with birth weights <2600 grams (OR, 1.20). Discussion: Low birth weight was associated with childhood diabetes. High birth weight was correlated with childhood obesity and diabetes. Our data indicate different relationships between birth weight and the development of obesity, hypertension, and diabetes in childhood.     

Left Ventricular Hypertrophy Is Associated With Obesity,Male Gender,and Symptoms in Healthy Adolescents

Obesity has been found to be associated with left ventricular (LV) hypertrophy (LVH). However, the occurrence of LVH in obese teenagers who are involved in sport programs has not been studied. The objective of this study was to evaluate the prevalence of LVH and its correlation with obesity, gender, and symptoms in teenage athletes. We used echocardiographic database of 1,500 adolescences between the ages of 12 and 20 years who were actively involved in school sport programs. We evaluated associations between obesity and LVH (defined as LV wall thickness (LVWT)) >12 mm, or LV mass (LVM) >215 g or relative wall thickness (RWT) >0.43) and physical symptoms. Using univariate and multivariate analysis, male gender was associated with increased LVWT (multivariate odds ratio (OR) 4.87, confidence interval (CI) 2.41–9.82). Obesity was associated with parameters of LVH using univariate and multivariate analysis. (LVM > 215 g) occurred in 10.32% of obese athletes vs. 0.2% (1/445) of controls, (OR 51.33, CI 6.05–433.8), P < 0.001, LVWT >12 mm occurred in 16.5% of obese students vs. 3.6% of controls (OR 5.2, CI 2.7–10.1, P < 0.001), RWT >0.43 occurred in 41.4% of obese students vs. 15.7% of controls (OR 3.78, CI 2.11–6.76, P < 0.001). After adjusting for age and gender, reported history of shortness of breath (SOB), fatigue and leg edema were also significantly more prevalent in obese students and in students with LVH. In conclusion obesity is associated with LVH in a population of healthy teenagers actively involved in sport programs. Furthermore, the presence of LVH was independently associated with many physical symptoms suggesting negative effect of LVH on myocardial function.     

Clinical Profile and Management of Patients With Hypertension and Chronic Ischemic Heart Disease According to BMI

Obesity is associated with numerous risk factors and comorbidities such as hypertension, metabolic syndrome, type 2 diabetes, and cardiovascular diseases. However, numerous studies have reported an obesity paradox; the overweight and obese patients with established cardiovascular disease have better prognosis than those with a BMI <25 kg/m². This study was designed to assess potential differences in the clinical profile and management of hypertensive outpatients with chronic ischemic heart disease in obese and lean patients that could explain these two apparently contradictory points. Overweight and obesity were defined as a BMI 25–29.9 kg/m² and ≥30 kg/m², respectively. Cardiovascular risk factors goals were considered according to European Society of Hypertension‐European Society of Cardiology 2003, National Cholesterol Education Program Adult Treatment Panel III and American Diabetes Association 2005 guidelines. A sample of 2,024 patients (66.8 ± 10.1 years; 31.7% women) was included. Of these, 0.1% had a BMI <20 kg/m²; 17.1% BMI 20–24.9 kg/m²; 53.7% BMI 25–29.9 kg/m²; 23.7% BMI 30–34.9 kg/m²; 4.3% BMI 35–39.9 kg/m²; and 1.1% BMI ≥40 kg/m². The subgroup of patients with BMI ≥30 kg/m² had a higher proportion of women, diastolic dysfunction, diabetes, dyslipidemia, left ventricular hypertrophy, and heart failure. There was an inverse relationship between risk factors control rates and BMI (all comparisons BMI 20–24.9 kg/m² vs. 25–29.9 kg/m² vs. ≥30 kg/m²): blood pressure (BP) control (51.7% vs. 42.4% vs. 29.2%, P < 0.001); low‐density lipoprotein cholesterol (LDL‐C) control (35.2% vs. 30.5% vs. 27.9%, P = 0.03) and diabetes control (38.6% vs. 27.6% vs. 22.2%, P = 0.023). In conclusion, in patients with hypertension and chronic ischemic heart disease, as BMI increases, the clinical profile worsens as well as risk factors control rates.     

Impact of cardiometabolic risk factor clusters on health-related quality of life in the U.S

Objective: Research has shown that risk factors for cardiovascular disease often cluster together, most notably overweight/obesity, diabetes, hyperlipidemia, and hypertension. The impact of cardiometabolic risk factor clusters on health‐related quality of life (HRQL) is not well understood. The purpose of this study was to examine and quantify the impact of cardiometabolic risk factor clusters on HRQL as measured by the SF (Short Form)‐12 Mental Component Scale (MCS‐12), SF‐12 Physical Component Scale (PCS‐12), EQ‐5D index (a generic quality of life index), and Visual Analogue Scale. Research Methods and Procedures: The Medical Expenditure Panel Survey is a nationally representative survey of the U.S. population. From 2000 to 2002, detailed information on sociodemographic characteristics and health conditions were collected for 36,697 adults with complete responses. Controlling for comorbidity and sociodemographic characteristics, this study estimated the marginal impact of cardiometabolic risk factor clusters on MCS‐12, PCS‐12, EQ‐5D index, and Visual Analogue Scale scores. Cardiometabolic risk factor clusters were defined as the presence of BMI ≥25 kg/m² and at least two of the following: diabetes, hyperlipidemia, and hypertension. Using BMI ≥30 kg/m² as the cut‐off was also examined. Results: The marginal impact of cardiometabolic risk factor clusters was highly statistically significant across all four HRQL measures and seemed to be clinically significant for all but the MCS‐12. The PCS‐12 showed a greater decrease in HRQL associated with physical function compared with mental function‐related domains of the MCS‐12. Discussion: Common cardiometabolic risk factor clusters such as overweight/obesity, diabetes, hypertension, and hyperlipidemia have a significant and negative impact on HRQL in the United States.     

Prevalence of Obesity and Associated Risk Factors in a Turkish Population (Trabzon City,Turkey)

Objective: To estimate the prevalence of overweight and obesity (general and central) in the Trabzon Region and its associations with demographic factors (age, sex, marital status, reproductive history in women, and level of education), socioeconomic factors (household income and occupation), family history of selected medical conditions (diabetes, hypertension, and obesity), lifestyle factors (smoking habits, physical activity, and alcohol consumption), and hypertension in the adult population. Research Methods and Procedures: A sample of households was systematically selected from the central province of Trabzon and its five towns, namely, Sürmene, Vakfikebir, Maçka, Hayrat, and Tonya. A total of 5016 subjects (2728 women and 2288 men) were included in the study. Individuals more than 20 years old were selected from their family health cards. Demographic factors, socioeconomic factors, family history of selected medical conditions, and lifestyle factors were obtained for all participants. Systolic blood pressure and diastolic blood pressure levels were measured for all subjects. Study procedures were carried out in the local health centers in each town over an 8‐month period. Obesity was defined as BMI ≥ 30 kg/m² and overweight as BMI = 25.0 to 29.9 kg/m². Results: The prevalence of obesity was 23.5%: 29.4% in women and 16.5% in men. The combined prevalence of both overweight and obesity was 60.3%. The prevalence of abdominal obesity was 29.4%: 38.9% among women and 18.1% among men. The prevalence of obesity increased with age, being highest in the 60‐ to 69‐year‐old age group (40.8%) but lower again in the 70+ age group. Obesity was associated positively with marital status, parity, cessation of cigarette smoking, alcohol consumption, and household income and inversely with level of education, cigarette use, and physical activity. Also, obesity was associated positively with hypertension. Discussion: In the Trabzon Region, 60.3% of the adult population presents with some excess weight. Obesity is a major public health problem that requires generalized interventions to prevent it among the adult population.     

Relationship between Serum Ferritin Levels and Dyslipidemia in Korean Adolescents

BackgroundFerritin is associated with various cardiometabolic risk factors such as dyslipidemia, hypertension, obesity, and insulin resistance in adults. We aimed to study the association between serum ferritin levels and dyslipidemia in adolescents, because dyslipidemia is considered an important modifiable cardiovascular risk factor in the young.MethodsWe analyzed 1,879 subjects (1,026 boys and 853 girls) from the 2009–2010 Korean National Health and Nutrition Examination Survey IV. Subjects were categorized into quartiles according to their lipid parameters, which were classified according to age and gender. Those in the highest quartile groups for total cholesterol, low-density lipoprotein cholesterol (LDL-C), and triglyceride concentrations were diagnosed as having dyslipidemia. Those in the lowest quartile for high-density lipoprotein cholesterol (HDL-C) values were diagnosed with abnormal levels.ResultsIn boys, total cholesterol, LDL-C, and triglyceride concentrations were significantly correlated with serum ferritin levels. In both boys and girls, serum ferritin levels were negatively associated with HDL-C values, even after adjusting for all covariates. Furthermore, there was no significant correlation between serum ferritin levels and total cholesterol, LDL, and triglyceride concentrations in girls.ConclusionSerum ferritin levels were significantly associated with major dyslipidemia parameters, more prominently in boys than in girls, and this association represents a cardiometabolic risk factor.     

Prevalence,Pharmacological Treatment,and Control of Cardiometabolic Risk Factors among Older People in Central Stockholm: A Population-Based Study

Background

Cardiometabolic risk factors and related cardiovascular diseases represent major threats to healthy aging.

Objective

We aimed to estimate distribution, pharmacological treatment, and control of main cardiometabolic risk factors among older people.

Methods

This population-based study included 3363 participants (age≥60 years, 64.9% women) in the Swedish National study on Aging and Care in Kungsholmen, in central Stockholm, Sweden (2001-2004). Data on demographics, cardiometabolic risk factors (hypertension, obesity, diabetes, and high cholesterol), and medication use were collected through face-to-face interviews, clinical examinations, laboratory tests, and the inpatient register. Cardiometabolic risk factors were defined following the most commonly used criteria. Prevalence was standardized using local census data.

Results

The age- and sex-standardized prevalence of diabetes, obesity, high cholesterol, and hypertension was 9.5%, 12.8%, 49.7%, and 74.9%, respectively. The prevalence of hypertension and diabetes increased with age, whereas the prevalence of obesity and high cholesterol decreased with age. Forty-nine percent of older adults had two or more cardiometabolic risk factors; 9.8% had three or more. Overall, 55.5% of people with hypertension, 50.3% with diabetes, and 25.0% with high cholesterol received pharmacological treatment. Of those treated pharmacologically, 49.4%, 38.1%, and 85.5% reached therapeutic goals for hypertension (blood pressure<150/90 mmHg), diabetes (glycated haemoglobin<7%), and high cholesterol (total cholesterol<6.22 mmol/l), respectively.

Conclusions

Hypertension, high cholesterol, and clustering of cardiometabolic risk factors were common among older people in Stockholm, but pharmacological treatment and control of these major factors can be improved. Appropriate management of cardiometabolic profiles among older people may help improve cardiovascular health and achieve healthy aging.