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      The prevalence of metabolically healthy obesity: a systematic review and critical evaluation of the definitions used : Prevalence of metabolically healthy obesity

      1 , 1 , 2 , 3 , 4 , 1
      Obesity Reviews
      Wiley

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          Abstract

          We performed a systematic review of the prevalence of metabolically healthy obesity (MHO). Medline, Web of Science and EMBASE were searched for original articles from inception to November 2013. Only prospective and cross-sectional studies were included. After screening 478 titles, we selected 55 publications, of which 27 were population-based studies and were used in the narrative synthesis. From the 27 studies, we identified 30 definitions of metabolic health, mainly based on four criteria: blood pressure, high-density lipoprotein cholesterol, triglycerides and plasma glucose. Body mass index ≥30 kg m(-2) was the main indicator used to define obesity (74% of the studies). Overall, MHO prevalence ranged between 6% and 75%. In the studies that stratified the analysis by sex, prevalence was higher in women (seven out of nine studies) and in younger ages (all four studies). One-third of the studies (n = 9) reported the response rate. Of these, four reported a response rate of ≥70% and they showed MHO prevalence estimates between 10% and 51%. The heterogeneity of MHO prevalence estimates described in this paper strengthens calls for the urgent need for a commonly established metabolic health definition. © 2014 The Authors. obesity reviews © 2014 World Obesity.

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          Body-mass index and cause-specific mortality in 900 000 adults: collaborative analyses of 57 prospective studies

          Summary Background The main associations of body-mass index (BMI) with overall and cause-specific mortality can best be assessed by long-term prospective follow-up of large numbers of people. The Prospective Studies Collaboration aimed to investigate these associations by sharing data from many studies. Methods Collaborative analyses were undertaken of baseline BMI versus mortality in 57 prospective studies with 894 576 participants, mostly in western Europe and North America (61% [n=541 452] male, mean recruitment age 46 [SD 11] years, median recruitment year 1979 [IQR 1975–85], mean BMI 25 [SD 4] kg/m2). The analyses were adjusted for age, sex, smoking status, and study. To limit reverse causality, the first 5 years of follow-up were excluded, leaving 66 552 deaths of known cause during a mean of 8 (SD 6) further years of follow-up (mean age at death 67 [SD 10] years): 30 416 vascular; 2070 diabetic, renal or hepatic; 22 592 neoplastic; 3770 respiratory; 7704 other. Findings In both sexes, mortality was lowest at about 22·5–25 kg/m2. Above this range, positive associations were recorded for several specific causes and inverse associations for none, the absolute excess risks for higher BMI and smoking were roughly additive, and each 5 kg/m2 higher BMI was on average associated with about 30% higher overall mortality (hazard ratio per 5 kg/m2 [HR] 1·29 [95% CI 1·27–1·32]): 40% for vascular mortality (HR 1·41 [1·37–1·45]); 60–120% for diabetic, renal, and hepatic mortality (HRs 2·16 [1·89–2·46], 1·59 [1·27–1·99], and 1·82 [1·59–2·09], respectively); 10% for neoplastic mortality (HR 1·10 [1·06–1·15]); and 20% for respiratory and for all other mortality (HRs 1·20 [1·07–1·34] and 1·20 [1·16–1·25], respectively). Below the range 22·5–25 kg/m2, BMI was associated inversely with overall mortality, mainly because of strong inverse associations with respiratory disease and lung cancer. These inverse associations were much stronger for smokers than for non-smokers, despite cigarette consumption per smoker varying little with BMI. Interpretation Although other anthropometric measures (eg, waist circumference, waist-to-hip ratio) could well add extra information to BMI, and BMI to them, BMI is in itself a strong predictor of overall mortality both above and below the apparent optimum of about 22·5–25 kg/m2. The progressive excess mortality above this range is due mainly to vascular disease and is probably largely causal. At 30–35 kg/m2, median survival is reduced by 2–4 years; at 40–45 kg/m2, it is reduced by 8–10 years (which is comparable with the effects of smoking). The definite excess mortality below 22·5 kg/m2 is due mainly to smoking-related diseases, and is not fully explained. Funding UK Medical Research Council, British Heart Foundation, Cancer Research UK, EU BIOMED programme, US National Institute on Aging, and Clinical Trial Service Unit (Oxford, UK).
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            Pathophysiology of human visceral obesity: an update.

            Excess intra-abdominal adipose tissue accumulation, often termed visceral obesity, is part of a phenotype including dysfunctional subcutaneous adipose tissue expansion and ectopic triglyceride storage closely related to clustering cardiometabolic risk factors. Hypertriglyceridemia; increased free fatty acid availability; adipose tissue release of proinflammatory cytokines; liver insulin resistance and inflammation; increased liver VLDL synthesis and secretion; reduced clearance of triglyceride-rich lipoproteins; presence of small, dense LDL particles; and reduced HDL cholesterol levels are among the many metabolic alterations closely related to this condition. Age, gender, genetics, and ethnicity are broad etiological factors contributing to variation in visceral adipose tissue accumulation. Specific mechanisms responsible for proportionally increased visceral fat storage when facing positive energy balance and weight gain may involve sex hormones, local cortisol production in abdominal adipose tissues, endocannabinoids, growth hormone, and dietary fructose. Physiological characteristics of abdominal adipose tissues such as adipocyte size and number, lipolytic responsiveness, lipid storage capacity, and inflammatory cytokine production are significant correlates and even possible determinants of the increased cardiometabolic risk associated with visceral obesity. Thiazolidinediones, estrogen replacement in postmenopausal women, and testosterone replacement in androgen-deficient men have been shown to favorably modulate body fat distribution and cardiometabolic risk to various degrees. However, some of these therapies must now be considered in the context of their serious side effects. Lifestyle interventions leading to weight loss generally induce preferential mobilization of visceral fat. In clinical practice, measuring waist circumference in addition to the body mass index could be helpful for the identification and management of a subgroup of overweight or obese patients at high cardiometabolic risk.
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              National, regional, and global trends in body-mass index since 1980: systematic analysis of health examination surveys and epidemiological studies with 960 country-years and 9·1 million participants.

              Excess bodyweight is a major public health concern. However, few worldwide comparative analyses of long-term trends of body-mass index (BMI) have been done, and none have used recent national health examination surveys. We estimated worldwide trends in population mean BMI. We estimated trends and their uncertainties of mean BMI for adults 20 years and older in 199 countries and territories. We obtained data from published and unpublished health examination surveys and epidemiological studies (960 country-years and 9·1 million participants). For each sex, we used a Bayesian hierarchical model to estimate mean BMI by age, country, and year, accounting for whether a study was nationally representative. Between 1980 and 2008, mean BMI worldwide increased by 0·4 kg/m(2) per decade (95% uncertainty interval 0·2-0·6, posterior probability of being a true increase >0·999) for men and 0·5 kg/m(2) per decade (0·3-0·7, posterior probability >0·999) for women. National BMI change for women ranged from non-significant decreases in 19 countries to increases of more than 2·0 kg/m(2) per decade (posterior probabilities >0·99) in nine countries in Oceania. Male BMI increased in all but eight countries, by more than 2 kg/m(2) per decade in Nauru and Cook Islands (posterior probabilities >0·999). Male and female BMIs in 2008 were highest in some Oceania countries, reaching 33·9 kg/m(2) (32·8-35·0) for men and 35·0 kg/m(2) (33·6-36·3) for women in Nauru. Female BMI was lowest in Bangladesh (20·5 kg/m(2), 19·8-21·3) and male BMI in Democratic Republic of the Congo 19·9 kg/m(2) (18·2-21·5), with BMI less than 21·5 kg/m(2) for both sexes in a few countries in sub-Saharan Africa, and east, south, and southeast Asia. The USA had the highest BMI of high-income countries. In 2008, an estimated 1·46 billion adults (1·41-1·51 billion) worldwide had BMI of 25 kg/m(2) or greater, of these 205 million men (193-217 million) and 297 million women (280-315 million) were obese. Globally, mean BMI has increased since 1980. The trends since 1980, and mean population BMI in 2008, varied substantially between nations. Interventions and policies that can curb or reverse the increase, and mitigate the health effects of high BMI by targeting its metabolic mediators, are needed in most countries. Bill & Melinda Gates Foundation and WHO. Copyright © 2011 Elsevier Ltd. All rights reserved.
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                Author and article information

                Journal
                Obesity Reviews
                Obes Rev
                Wiley
                14677881
                October 2014
                October 2014
                July 16 2014
                : 15
                : 10
                : 781-790
                Affiliations
                [1 ]Departamento de Medicina Preventiva; Faculdade de Medicina da Universidade de São Paulo; São Paulo Brasil
                [2 ]Centro de Estudos do Laboratório de Aptidão Física de São Caetano do Sul (CELAFISCS); São Paulo Brasil
                [3 ]Departamento de Salud Pública; Historia de la Ciencia y Ginecología; Facultad de Medícina; Universidad Miguel Hernández de Elche; Elche España
                [4 ]CIBER en Epidemiología y Salud Pública (CIBERESP); Madrid España
                Article
                10.1111/obr.12198
                25040597
                0afdf21b-f099-4c3b-b1c4-625e5580f385
                © 2014

                http://doi.wiley.com/10.1002/tdm_license_1.1

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