Effect of Different Obesity Phenotypes on Cardiovascular Events in Tehran Lipid and Glucose Study (TLGS)




In this community-based study, 6,215 subjects aged ≥30 years (43% men, mean age 47 years) free of cardiovascular disease (CVD) at baseline were followed for a mean of 8.1 years to assess risk for CVD stratified by body mass index and dysmetabolic status. Participants were stratified by body mass index categories (18.5 to 24.9 kg/m 2 = normal, 25 to 29.9 kg/m 2 = overweight, and ≥30 kg/m 2 = obese) and dysmetabolic status. Dysmetabolic status was defined as having metabolic syndrome according to the International Diabetes Federation’s definition or diabetes. First CVD events occurred in 446 subjects. Multivariate-adjusted hazard ratios for CVD events in normal-weight, overweight, and obese subjects without dysmetabolic status were 1.00 (reference), 1.10 (95% confidence interval [CI] 0.76 to 1.61), and 1.07 (95% CI 0.59 to 1.96), respectively, and for normal-weight, overweight and obese subjects with dysmetabolic status were 2.10 (95% CI 1.36 to 3.26), 2.35 (95% CI 1.71 to 3.22), and 2.35 (95% CI 1.71 to 3.22), respectively. There was an interaction between body mass index and metabolic abnormalities in predicting CVD. In conclusion, normal-weight subjects with dysmetabolic status had higher risk for future CVD compared to healthy obese subjects.


Obesity is a well-known risk factor for several causes of death, especially from cardiovascular disease (CVD). There are several metabolic abnormalities due to obesity that lead to increased risk for incident CVD. Interestingly, clustering of CVD risk factors is different across the continuum of body mass index (BMI), leading to phenotype subgroups of obesity. “Metabolically obese but normal weight” (MONW) and “metabolically healthy but obese” are 2 well-known phenotypes of obesity. In United States adults in the National Health and Nutrition Examination Survey (NHANES; 1999 to 2004), 30.1% and 21.1% of normal-weight men and women, respectively, were metabolically abnormal. In urban Iranian adults, the overall prevalence of the metabolic syndrome in normal-weight men and women was 9.9% and 11.0%, respectively. Obesity-related phenotypic characteristics and CVD outcomes have been described in a few studies. In the framework of the Framingham Offspring Study, it has been reported that the increase of CVD events in MONW subjects was twofold compared to metabolically healthy but obese individuals. However, results from NHANES III indicate this association only in women. Moreover, some recent studies have reported upward trends of prevalence of the MONW phenotype. Furthermore, to the best of our knowledge, there is no relevant study on the effect of obesity-related phenotype characteristics on CVD events in the Middle East. Therefore, we followed obesity-related phenotypes for the development of CVD during a mean of 8.1 years in a large cohort of residents of Tehran.


Methods


The Tehran Lipid and Glucose Study (TLGS) is a prospective, population-based study to determine the risk factors for noncommunicable diseases among a representative Tehran urban population. In the TLGS, 15,005 subjects aged ≥3 years were selected by a multistage cluster random sampling method; of these, 8,071 participants aged ≥30 years were evaluated in the cross-sectional phase of the TLGS (February 1999 to August 2001). After the exclusion of those with prevalent CVD (n = 521) and underweight subjects (BMI <18.5 kg/m 2 ; n = 106), 7,444 participants were entered in the study. Data on metabolic syndrome and oral glucose tolerance test results were not available for 486 participants, leaving 6,958 participants with complete data; of these, 6,215 participants were followed until March 2009, with a median of 8.4 years (dropout rate about 11% [743 of 6,958]). The ethics committee of the Research Institute for Endocrine Sciences approved this study. Informed written consent was obtained from all subjects.


At baseline, subjects were interviewed by trained interviewers using pretested questionnaires. Information on age, gender, medical history of CVD, medication use, smoking habit, physical examination results, and family history of premature coronary artery disease (CAD) were collected. Anthropometric measures included weight and waist circumference. Systolic and diastolic blood pressure were measured twice in a seated position after a 15-minute rest period using a standard mercury sphygmomanometer.


A blood sample was taken after a 12- to 14-hour overnight fast. All blood analyses were done at the TLGS research laboratory on the day of blood collection. Standard oral glucose tolerance tests were performed in participants without treated diabetes. Plasma glucose and serum lipids were determined as previously described.


Details of the collection of CVD outcome data have been published elsewhere. Coronary heart disease included cases of definite myocardial infarction (diagnostic electrocardiographic results and biomarkers), probable myocardial infarction (positive electrocardiographic findings plus cardiac symptoms or signs plus missing biomarkers or positive electrocardiographic findings plus equivocal biomarkers), angiographically proved coronary heart disease, and coronary heart disease death. CVD was defined as any coronary heart disease events, stroke (a new neurological deficit that lasted ≥24 hours), or CVD death.


Participants were classified into 3 categories according to BMI: normal weight (<25 kg/m 2 ), overweight (25 to 29.9 kg/m 2 ), and obese (>30 kg/m 2 ). Diabetes was defined as fasting plasma glucose ≥126 mg/dl or 2-hour post–glucose challenge ≥200 mg/dl or current therapy for a definite diagnosis of diabetes. Metabolic syndrome was defined according to the new International Diabetes Federation definition, with the ethnic-specific cutoff point for waist circumference in the eastern Mediterranean region as waist circumference ≥89 cm for men and ≥91 cm for women plus any 2 or more of the following: (1) fasting plasma glucose ≥100 mg/dl or 2-hour post–glucose challenge ≥140 mg/dl; (2) fasting triglycerides ≥150 mg/dl; (3) fasting high-density lipoprotein cholesterol <40 mg/dl in men or <50 mg/dl in women; and (4) increased blood pressure, defined as blood pressure ≥140/85 mm Hg or the us of any antihypertensive drugs. Family history of premature CAD was defined as previous diagnoses of CAD in first-degree female relatives aged <65 years or first-degree male relatives aged <55 years. Smoking status defined as never, ex-smoker, and smoker (current or occasionally), and high total cholesterol was defined as total cholesterol ≥240 mg/dl. Data on physical activity, which have been reported previously, were obtained using the Lipid Research Clinic questionnaire.


Dysmetabolic status was defined as having metabolic syndrome or diabetes, resulting in 6 subgroups: (1) normal weight and normal metabolic status, (2) normal weight and dysmetabolic status, (3) overweight and normal metabolic status, (4) overweight and dysmetabolic status, (5) obese and normal metabolic status, and (6) obese and dysmetabolic status.


All continuous data are expressed as mean ± SD, and categorical variables are expressed as percentages. Logarithmic transformation was performed to normalize the distribution of triglyceride levels. Serum triglyceride levels are presented as geometric mean ± SD. Differences of continuous variables between groups were analyzed using analysis of variance (Tukey’s post hoc test). Participants free of CVD at baseline were followed until the occurrence of a new ischemic cardiovascular event (the exact date of which was considered as the date of the end point event) or to death or loss to follow-up, in which case the date of the last patient visit or the date of death due to a non-CVD event were considered as censoring. In the regression model, subjects were stratified into 6 categories according to BMI and dysmetabolic status, considering the group with normal weight and normal metabolic status as the reference category. We calculated incidence rates and adjusted hazard ratios of CVD events according to BMI groups in the presence or the absence of dysmetabolic status. The person-time for each participant was calculated from the beginning of the study to the date of CVD event or the end of the study, whichever came first. Incidence rates of CVD were obtained by dividing the number of cases by person-years in subgroup of obesity-related phenotypes. Using Cox proportional-hazards models, relative risks were computed as the incidence rate in subgroup of obesity-related phenotypic divided by the incidence rate in the reference category. The initial model was adjusted for age (years) and gender. In the second multivariate model, we further adjusted for exercise (light, moderate, and heavy), smoking (never, ex-smoker, and smoker), family history of premature CAD (yes or no), and high total cholesterol (≥240 mg/dl). Stata version 10 was used for data analysis, and p values ≤0.05 were considered statistically significant.




Results


A total of 6,215 subjects fulfilled the study criteria at baseline and had ≥1 follow-up assessment and were included in the analysis involving development of CVD. The mean age of participants was 47.4 ± 12.3 years, and 56.9% were women. Normal weight, overweight, and obesity were present in 28.6%, 44%, and 27.4% of our population, respectively. Overall, the prevalence of diabetes was 13.7% (n = 851). In diabetes group, 297 subjects (34.9%) were known to have diabetes, and 554 subjects (65.1%) were newly diagnosed, of whom 40.4% (n = 224) had isolated postchallenge hyperglycemia (2-h post–glucose challenge ≥200 mg/dl and fasting plasma glucose <126 mg/dl). After excluding those who had diabetes (n = 851), in the remaining 5,364 participants, metabolic syndrome was present in 36.4% (n = 1,954); hence, 45% (n = 2,805) had dysmetabolic status (with metabolic syndrome or diabetes). The prevalence of dysmetabolic status in normal-weight, overweight, and obese participants was 12.5%, 47.1%, and 76%, respectively. Overall, of 6,215 subjects, 3.5% had normal weight with dysmetabolic status (resembling the MONW phenotype), and 6.5% were obese without dysmetabolic status (resembling the metabolically healthy but obese phenotype). Characteristics of the study population, stratified by BMI and dysmetabolic categories, are listed in Table 1 . Almost all cardiovascular risk factors increased with increasing BMI in those participants with and without dysmetabolic status. Moreover, BMI and waist circumference in normal-weight subjects with dysmetabolic status were higher compared to subjects without dysmetabolic status (23.1 vs 22.7 kg/m 2 and 86.4 vs 78.9 cm, respectively, p <0.01).



Table 1

Baseline characteristics of 6,215 study participants classified by body mass index and dysmetabolic status










































































































































































































































































Variable Overall (n = 6,215) Without Dysmetabolic Status With Dysmetabolic Status
BMI 18.5–24.9 kg/m 2 BMI 25–29.9 kg/m 2 BMI ≥30 kg/m 2 BMI 18.5–24.9 kg/m 2 BMI 25–29.9 kg/m 2 BMI ≥30 kg/m 2
(n = 1,555) (n = 1,447) (n = 408) (n = 223) (n = 1,288) (n = 1,294)
Age (years) 47.4 ± 0.2 44.6 ± 0.3 43.8 ± 0.3 44.6 ± 0.5 57.1 ± 0.8 51.8 ± 0.3 49.4 ± 0.3
Men 43.1% 56.8% 39.3% 20.3% 47.1% 53.3% 27.1%
Smoking
Never 77.9% 70.1% 79.9% 90.4% 75.3% 74.5% 84.8%
Ex-smoker 7.9% 8.5% 6.5% 2.9% 9.4% 11.1% 6.7%
Smoker 14.2% 21.4% 13.6% 6.6% 15.2% 14.4% 8.5%
Physical activity
Heavy 24.3% 23.4% 26.6% 29.4% 28.2% 24.0% 20.6%
Moderate 13.3% 14.3% 14.8% 10.6% 15.0% 13.1% 11.1%
Light 62.5% 62.3% 58.5% 60.0% 56.8% 63.0% 68.3%
Family history of premature CAD § 16.5% 13.6% 14.7% 17.6% 17.9% 17.7% 20.2%
Weight (kg) 72.0 ± 0.2 61.1 ± 0.2 70.2 ± 0.2 81.0 ± 0.5 60.6 ± 0.6 73.8 ± 0.2 84.2 ± 0.3
BMI (kg/m 2 ) 27.6 ± 0.05 22.7 ± 0.04 27.0 ± 0.04 32.7 ± 0.1 23.1 ± 0.1 27.7 ± 0.04 33.4 ± 0.08
Waist circumference (cm) 90.7 ± 0.1 78.9 ± 0.2 86.8 ± 0.2 97.2 ± 0.5 86.4 ± 0.5 95.3 ± 0.1 103.0 ± 0.2
Abdominal obesity 54.0% 3.0% 27.6% 77.0% 42.2% 93.9% 99.6%
Fasting plasma glucose (mg/dl) 101.0 ± 0.4 88.8 ± 0.2 89.6 ± 0.2 87.8 ± 0.4 152.5 ± 4.8 113.6 ± 1.3 111.0 ± 1.1
2-hour post–glucose challenge 123.0 ± 0.8 100.5 ± 0.7 107.0 ± 0.7 110.0 ± 1.3 198.0 ± 10.1 148.4 ± 2.4 146.6 ± 2.0
HDL cholesterol (mg/dl) 41.8 ± 0.1 43.5 ± 0.3 43.3 ± 0.3 48.4 ± 0.6 41.2 ± 0.8 38.0 ± 0.3 c 39.7 ± 0.3
HDL cholesterol <40/50 mg/dl for men/women 71.6% 59.0% 65.6% 49.5% 74.8% 84.4% 84.7%
LDL cholesterol (mg/dl) 139.2 ± 0.5 129.9 ± 0.9 136.4 ± 0.9 138.7 ± 1.6 145.5 ± 2.8 144.3 ± 1.2 148.3 ± 1.1
Total cholesterol (mg/dl) 217.1 ± 0.6 200.9 ± 1.0 210.5 ± 1.1 212.9 ± 1.9 225.9 ± 3.2 227.7 ± 1.3 233.4 ± 2.0
Total cholesterol ≥240 mg/dl, 27.8% 16.5% 22.2% 21.8% 34.2% 36.2% 40.0%
Triglycerides (mg/dl) 159.0 ± 0.1 120.0 ± 1.0 136.7 ± 1.0 118.5 ± 1.0 180.7 ± 1.0 214.2 ± 1.0 210.6 ± 1.0
Triglycerides ≥150 mg/dl 54.6% 31.8% 38.4% 19.1% 66.7% 81.0% 83.0%
SBP (mm Hg) 122.2 ± 0.2 114.2 ± 0.4 116.4 ± 0.4 118.1 ± 0.8 130.0 ± 1.4 129.6 ± 0.6 130.9 ± 0.6
DBP (mm Hg) 79.3 ± 0.1 74.5 ± 0.2 76.8 ± 0.2 78.6 ± 0.4 78.9 ± 0.7 82.3 ± 0.3 85.1 ± 0.3
Hypertension (SBP ≥135 mm Hg and/or DBP ≥80 mm Hg and/or medication use) 40.2% 22.6% 23.7% 24.3% 57.0% 58.0% 63.4%

Data are expressed as mean ± SE or as percentages.

DBP = diastolic blood pressure; HDL = high-density lipoprotein; SBP = systolic blood pressure.

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Dec 22, 2016 | Posted by in CARDIOLOGY | Comments Off on Effect of Different Obesity Phenotypes on Cardiovascular Events in Tehran Lipid and Glucose Study (TLGS)

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