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Obesity, high-molecular-weight (HMW) adiponectin, and metabolic risk factors: prevalence and gender-specific associations in Estonia.

ABSTRACT: BACKGROUND: The metabolic consequences of obesity are associated with an imbalance of adipocytokines, e.g. adiponectin. However, some obese subjects remain metabolically healthy and have adiponectin levels similar to normal body weight subjects. Current estimates of the prevalence of obesity in Estonia have relied only on self-report data. OBJECTIVES: To estimate the prevalence of obesity in Estonia, to test for associations between HMW adiponectin and metabolic risk factors and to test if HMW adiponectin levels differentiate metabolically healthy and metabolically unhealthy subjects. METHODS: We conducted a population-based cross-sectional multicentre study to gather history, examination and blood test results for 495 subjects aged 20-74. Metabolically healthy subjects were free from hypertension, dyslipidaemia, impaired glucose regulation and insulin resistance. Metabolically unhealthy subjects had at least one of these four metabolic abnormalities. RESULTS: The prevalence of obesity was 29% in men and 34% in women. HMW adiponectin was positively correlated with HDL cholesterol and negatively correlated with triglycerides, obesity, insulin resistance and blood glucose. This effect was driven by metabolically unhealthy subjects in men, but by both metabolically healthy and metabolically unhealthy subjects in women. Metabolically healthy women had higher HMW adiponectin levels than metabolically unhealthy women. 12% of all obese subjects were metabolically healthy, and their HMW adiponectin levels were similar to normal weight subjects. CONCLUSIONS: Obesity is more prevalent in Estonian adults than previously thought. HMW adiponectin levels were associated with various metabolic risk factors in metabolically healthy women but not in metabolically healthy men. For both genders, HMW adiponectin differentiates metabolically healthy obese subjects from metabolically unhealthy obese subjects.

SUBMITTER: Eglit T

PROVIDER: S-EPMC3767784 | biostudies-other | 2013

REPOSITORIES: biostudies-other

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Project description:BackgroundCardiometabolic disorders are frequently observed among those who have obesity as measured by body mass index (BMI). However, there is limited data available on the cardiometabolic profile of those who are non-obese by BMI but with a high body fat percentage (BFP), a phenotype frequently observed in the Indian population. We examined the prevalence of individuals with normal weight obesity (NWO) and the cardiometabolic profile of NWO individuals at high risk for type 2 diabetes(T2D) in a south Asian population.Material and methodsIn the Kerala Diabetes Prevention Program, individuals aged between 30 to 60 years were screened using the Indian Diabetes Risk Score(IDRS) in 60 rural communities in the Indian state of Kerala. We used data from the baseline survey of this trial for this analysis which included 1147 eligible high diabetes risk individuals(IDRS >60). NWO was defined as BMI within the normal range and a high BFP (as per Asia-pacific ethnicity based cut-off); Non-obese (NO) as normal BMI and BFP and overtly obese (OB) as BMI ≥25 kg/m2 irrespective of the BFP. Data on demographic, clinical and biochemical characteristics were collected using standardized questionnaires and protocols. Body fat percentage was assessed using TANITA body composition analyser (model SC330), based on bioelectrical impedance.ResultsThe mean age of participants was 47.3 ± 7.5 years and 46% were women. The proportion with NWO was 32% (n = 364; 95% CI: 29.1 to 34.5%), NO was 17% (n = 200) and OB was 51% (n = 583). Among those with NWO, 19.7% had T2D, compared to 18.7% of those who were OB (p value = 0.45) and 8% with NO (p value = 0.003). Among those with NWO, mean systolic and diastolic blood pressure were 129 ± 20; 78 ± 12 mmHg, compared to 127 ± 17; 78±11 mmHg among those with OB (p value = 0.12;0.94) and 120 ± 16; 71±10 mmHg among with NO (p value<0.001; 0.001), respectively. A similar pattern of association was observed for LDL cholesterol and triglycerides. After adjusting for other risk factors, the odds of having diabetes (OR:2.72[95% CI:1.46-5.08]) and dyslipidemia (2.37[1.55-3.64]) was significantly more in individuals with NWO as compared to non-obese individuals.ConclusionsAlmost one-third of this South Asian population, at high risk for T2D, had normal weight obesity. The significantly higher cardiometabolic risk associated with increased adiposity even in lower BMI individuals has important implications for recognition in clinical practice.

Project description:BACKGROUND:Despite the important role of adiponectin in regulating general metabolic homeostasis, analysis of genetic determinants of adiponectin and the related cardio-metabolic traits in African American population has been limited and inconsistent. Considering the high genetic admixture of African Americans and thus the important population stratification that may confound the genetic-trait associations, the objective of this work was to perform a comprehensive analysis of the associations between ADIPOQ variants and adiponectin levels and obesity phenotypes in a large African American population from the Jackson Heart Study (JHS) cohort. METHODS:Genotype data was available for 2968 JHS participants (1131men; 1837women). Single Nucleotide Polymorphisms (SNPs) were selected by a Tag-SNP Approach and literature review. The genotype imputation was performed using IMPUTE2 software and reference phased data from the 1000G project. PLINK software was used for the genetic analysis. Plasma specimens were analyzed by ELISA for adiponectin levels. All analyses were controlled for population stratification assessed by Individual Proportions of European Ancestry (PEA) estimates calculated in HAPMIX using ancestry informative markers (AIMs). RESULTS:We found a gender-dependent association of some ADIPOQ variants and adiponectin levels. In women four of the studied polymorphisms (rs6444174, rs16861205, rs1403697, rs7641507) were associated with adiponectin levels after Bonferroni correction and controlling for the percentage of PEA, age, annual household income and smoking. These results were consistent with the haplotype analysis. The association between the rs12495941 variant and obesity is modulated by the PEA, so that the relationship between the G allele and a higher incidence of obesity was present in those individuals within the lower PEA group. In addition we found an effect modification of obesity on the association between the ADIPOQ rs6444174 SNP and BMI so that the presence of the T allele was negatively and significantly associated with BMI only in participants with a normal weight. CONCLUSIONS:In this large African American cohort, ADIPOQ variants were associated with adiponectin levels in a gender-dependent manner and the relationship of some of these variants with obesity and BMI was modulated by the PEA and obesity status respectively. This suggests that the effects of these polymorphisms on adiponectin and obesity phenotypes are subject to a strong interaction with genetic and environmental factors in African American population.

Project description:BackgroundMany studies have identified early-life risk factors for childhood overweight/obesity (OwOb), but few have evaluated how they combine to influence later cardiometabolic health.ObjectivesWe aimed to examine the association of risk factors in the first 1000 d with adiposity and cardiometabolic risk in early adolescence.MethodsWe studied 1038 mother-child pairs in Project Viva. We chose 6 modifiable early-life risk factors previously associated with child adiposity or metabolic health in the cohort: smoking during pregnancy (yes compared with no); gestational weight gain (excessive compared with nonexcessive); sugar-sweetened beverage consumption during pregnancy (≥0.5 compared with <0.5 servings/d); breastfeeding duration (<12 compared with ≥12 mo); timing of complementary food introduction (<4 compared with ≥4 mo); and infant sleep duration (<12 compared with ≥12 h/d). We computed risk factor scores by calculating the cumulative number of risk factors for each child. In early adolescence (median: 13.1 y) we measured indicators of adiposity [BMI, fat mass index (FMI), trunk fat mass index (TFMI)]. We also calculated OwOb prevalence and metabolic syndrome (MetS) risk z score of adolescents.ResultsAmong 1038 adolescents, 71% had >1 early-life risk factor. In covariate-adjusted models, we observed positive monotonic increases in BMI, FMI, TFMI, and MetS z scores with increasing risk factor score. Children with 5‒6 risk factors (compared with 0-1 risk factors) had the highest risk of OwOb [risk ratio (RR): 2.53; 95% CI: 1.63, 3.91] and being in the highest MetS quartile (RR: 2.46; 95% CI: 1.43, 4.21). The predicted probability of OwOb in adolescence varied from 9.4% (favorable levels for all factors) to 63.6% (adverse levels for all factors), and for being in the highest MetS quartile from 9.6% to 56.6%.ConclusionsEarly-life risk factors in the first 1000 d cumulatively predicted higher adiposity and cardiometabolic risk in early adolescence. Intervention strategies to prevent later obesity and cardiometabolic risk may be more effective if they concurrently target multiple modifiable factors.

Project description:ObjectivesThe purpose of this study is to assess the prevalence of overweight/obesity, abdominal obesity and obesity-related risk factors in southern China.MethodsA cross-sectional survey of 15,364 participants aged 15 years and older was conducted from November 2013 to August 2014 in Jiangxi Province, China, using questionnaire forms and physical measurements. The physical measurements included body height, weight, waist circumference (WC), body fat percentage (BFP) and visceral adipose index (VAI). Multivariate logistic regression analysis was performed to evaluate the risk factors for overweight/obesity and abdominal obesity.ResultsThe prevalence of overweight was 25.8% (25.9% in males and 25.7% in females), while that of obesity was 7.9% (8.4% in males and 7.6% in females). The prevalence of abdominal obesity was 10.2% (8.6% in males and 11.3% in females). The prevalence of overweight/obesity was 37.1% in urban residents and 30.2% in rural residents, and this difference was significant (P < 0.001). Urban residents had a significantly higher prevalence of abdominal obesity than rural residents (11.6% vs 8.7%, P < 0.001). Among the participants with an underweight/normal body mass index (BMI), 1.3% still had abdominal obesity, 16.1% had a high BFP and 1.0% had a high VAI. Moreover, among obese participants, 9.7% had a low /normal WC, 0.8% had a normal BFP and 15.9% had a normal VAI. Meanwhile, the partial correlation analysis indicated that the correlation coefficients between VAI and BMI, VAI and WC, and BMI and WC were 0.700, 0.666, and 0.721, respectively. A multivariate logistic regression analysis indicated that being female and having a high BFP and a high VAI were significantly associated with an increased risk of overweight/obesity and abdominal obesity. In addition, living in an urban area and older age correlated with overweight/obesity.ConclusionThis study revealed that obesity and abdominal obesity, which differed by gender and age, are epidemic in southern China. Moreover, there was a very high, significant, positive correlation between WC, BMI and VAI. However, further studies are needed to explore which indicator of body fat could be used as the best marker to indirectly reflect cardiometabolic risk.

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Obesity, high-molecular-weight (HMW) adiponectin, and metabolic risk factors: prevalence and gender-specific associations in Estonia.

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