Prevalence of MetS and Metabolically Healthy Obesity
In this large-scale collaborative study, we evaluated the prevalence of metabolic syndrome and healthy obesity among obese individuals using the data of 163,517 people from ten European cohort studies from seven different countries. We found considerable variation in the prevalence of both phenotypes suggesting that the distribution of the MetS and MHO across the different populations in general is not equal. However, our analysis did reveal a consistently higher prevalence of the MHO phenotype in women compared to men. Furthermore, the percentage of obese subjects with a favourable risk profile decreases with increasing age in all cohorts.
With the exception of the Italian, Norwegian and UK cohorts, the prevalence of obesity was much higher in the European populations we studied than was reported in the most recent review addressing the distribution of obesity in Europe. Such differences may be due to potential underestimation of the prevalence of obesity in the systematic review because of the inclusion of studies using self-reported BMI. In our study, the data on BMI were obtained through direct measurements made by trained research nurses or study assistants which provides more accurate estimation of obesity prevalence in the participating cohorts. Another explanation for the discrepancy in the prevalence patterns may be related to the difference in the time period when the studies were conducted. While the surveys included in the systematic review were performed between the mid-1980s and 2003, most of the data in our study were collected after 2000, with the earliest data available from 1995 and the most recent data from 2012. The differences in estimations of the obesity prevalence can, therefore, present different phases of an increasing trend. Although our data are obtained from large population-based cohort studies or biobanks, we have to realize that our results cannot always be generalized to the overall prevalence in the specific countries, as some cohorts have only collected data from a specific region of that country (CHRIS/MICROS/HUNT2), or from a specific age group (NCDS). Despite the detected variation, the data confirm the observations that obesity in European countries continued to rise the last decade and has reached epidemic proportions. However, recent publications suggest levelling off of the obesity epidemic, although in subjects with lower socioeconomic status a steady increase in prevalence still is observed.
The Finnish cohorts had the highest prevalence of MetS among obese subjects and the lowest percentage of MHO. In contrast, in the Italian MICROS and the Dutch LifeLines studies we observed a lower prevalence of MetS among obese subjects together with a higher percentage of MHO. Similar patterns in the occurrence of MetS in Europe have been reported previously. MetS is a constellation of metabolic risk factors, associated with an increased risk for the development of atherosclerotic cardiovascular disease as well as type 2 diabetes mellitus. MetS has been shown to be the major risk determinant of heart disease, also when a population generally has low levels of HDL- and LDL-cholesterol. The most frequent MetS component present in obese individuals was elevated blood pressure. In the 10 studies, obesity coincided with hypertension in 60% to 85% cases. In contrast, we observed considerable variations in the prevalence of other components of MetS, especially blood glucose and HDL-cholesterol. A blood pressure exceeding the strict criterion for a high blood pressure can be accounted as a main contributor promoting unhealthy obesity and metabolic syndrome in the Finnish cohorts in this study. Finnish tendency for elevated blood pressure has also been detected earlier, recently by The European Heart Network and The European Society of Cardiology.
Our study extends previous efforts to describe the phenomenon of healthy obesity and to estimate its prevalence in different countries in several important ways, including helping to disentangle whether differences in the prevalence of MHO are due to geographic variation or differences in measurements. Using a large amount of validated information, we applied a rigorous protocol to harmonize data from multiple population-based European studies, and ensure a high level of homogeneity of the MetS definition used to calculate the MHO prevalence. Recently, the lack of a standard approach to use the same sets of criteria and cut-off values to define metabolic abnormalities has been highlighted as the major source of the high variability in the reported MHO prevalence. Yet, our results also demonstrate a significant diversity in the prevalence of MHO across Europe using the harmonized criteria to define MetS. The highest percentage of MHO in men was found in CHRIS and KORA, and in women in NCDS, LifeLines, KORA and CHRIS, whereas the lowest prevalence was found in the Finnish cohorts and in HUNT2. In our study, we have used the established risk factors associated with the metabolic syndrome to identify the MHO phenotype. Our data on MetS components is consistent with the outcome of previously performed studies on the prevalence of the metabolic abnormalities in Europe. As age and sex are important factors in the development of MetS, we have also evaluated the age- and sex-stratified prevalence of MHO per decade. Our results indicate a higher prevalence of the MHO phenotype in women than in men as well as an age-related decline in the percentage of obese subjects with a metabolically healthy phenotype. Collectively, our findings raise additional questions about the underlying factors promoting the variation in the prevalence of MHO across different populations. Such variation in the distribution of metabolic phenotypes can be explained by several factors, including difference in age of the cohort participants, differences in environmental factors such as physical activity level, diet, smoking and alcohol use, and differences in the selection and inclusion of participants. Also the psychosocial profile and genetic factors may play a role. While behavioral factors, i.e. higher levels of physical activity or moderate alcohol intake, have been shown to be associated with the MHO phenotype, there is no evidence yet whether genetic background and divergence between populations does contribute to the metabolically favorable profile in obesity.
Given the number of serious health problems associated with obesity including type 2 diabetes, cardiovascular disease, and an increased risk for various types of cancer, the investigation of the healthy obesity phenotype may provide novel insights into the pathophysiology of obesity-related co-morbidities and help to identify at-risk obese individuals. Furthermore, it may help in the development of better interventions for obese patients. There are strong indications that weight loss may not have a beneficial effect on certain metabolic risk factors in MHO individuals and even result in a paradoxical response. Therefore, the one-size-fits-all approach regarding the consequences of obesity should be revisited, and the prevailing concept in the health care system that obesity is always bad should be re-evaluated. Also, a proper classification of the at-risk and metabolically benign obese individuals should be taken into account in medical research to prevent any bias in the interpretation of the results.
The main strengths of this descriptive study are the large sample size and the application of harmonized criteria to evaluate the prevalence of MetS and the degree of the MHO across different European cohort studies. Through our harmonization process, we have shown the possibility for collaborative research based on a careful harmonization process across multiple participating cohort studies. Several important factors may have a bearing on the results. First, we used BMI to define the obesity status. Since BMI is a measure of general obesity and cannot distinguish between fat and lean mass, other measures such as waist circumference (WC) or waist-hip-ratio (WHR) might be better indicators of visceral fat accumulation. Although a few studies reported lower fat accumulation in MHO individuals compared to the obese with metabolic abnormalities, no difference in the prevalence of MHO was found when WC was used instead of BMI to define the MHO phenotype in the NHANES cohort. Second, although our harmonized measures captured the essential information content for the MHO phenotype, there were differences between studies in the way that specific variables such as blood pressure and serum lipid levels were measured. Also, our cut-off values for non-fasting measurements of, for example, blood glucose may underestimate the actual degree of the MHO present in the corresponding studies. Third, although many participating cohort studies included several thousands of participants, their health and lifestyle habits may not always be representative of the general population in this specific country because of bias in participation or differences in recruitment of participants. We also cannot exclude that a potential participation bias could affect the results. As such, higher participation rates from either healthy or unhealthy individuals can influence the outcome, and it cannot be ruled out that the high percentage of MHO in the LifeLines Cohort Study may – at least in part – be explained by a preponderance of healthy individuals willing to participate.
An important factor to discuss is the time period in which the initial screening of each individual cohort was performed. Data in some cohorts were collected in the 1990s, while, for example, the participants in the Dutch LifeLines Cohort Study were recruited between 2007 and 2012, and in the Italian CHRIS study after August 2011. There have been several changes in environmental factors such as health behaviour and smoking pattern over time, which may have a bearing on the prevalence of MetS and on health in general. In many countries higher awareness of the importance of increased physical activity or smoking cessation have been recognized, although it appears that the current epidemic of obesity is still on-going. As an example, cessation of smoking is on one hand associated with weight gain, which may be perceived negatively by individuals, but it also results in improvement of the metabolic profile as smoking cessation is accompanied by an increase of HDL cholesterol and reduction of triglycerides. It is important to note that the major objective of this descriptive study was to evaluate the phenomenon of healthy obesity among the participating European population-based studies. The BioSHaRE-HOP consortium is currently expanding its harmonization efforts, and assessing differences in lifestyle factors such as nutritional habits, physical activity, smoking and general awareness of health between the various participating countries in order to have a better estimate of the characterization and the determinants of (healthy) obesity.
Discussion
In this large-scale collaborative study, we evaluated the prevalence of metabolic syndrome and healthy obesity among obese individuals using the data of 163,517 people from ten European cohort studies from seven different countries. We found considerable variation in the prevalence of both phenotypes suggesting that the distribution of the MetS and MHO across the different populations in general is not equal. However, our analysis did reveal a consistently higher prevalence of the MHO phenotype in women compared to men. Furthermore, the percentage of obese subjects with a favourable risk profile decreases with increasing age in all cohorts.
With the exception of the Italian, Norwegian and UK cohorts, the prevalence of obesity was much higher in the European populations we studied than was reported in the most recent review addressing the distribution of obesity in Europe. Such differences may be due to potential underestimation of the prevalence of obesity in the systematic review because of the inclusion of studies using self-reported BMI. In our study, the data on BMI were obtained through direct measurements made by trained research nurses or study assistants which provides more accurate estimation of obesity prevalence in the participating cohorts. Another explanation for the discrepancy in the prevalence patterns may be related to the difference in the time period when the studies were conducted. While the surveys included in the systematic review were performed between the mid-1980s and 2003, most of the data in our study were collected after 2000, with the earliest data available from 1995 and the most recent data from 2012. The differences in estimations of the obesity prevalence can, therefore, present different phases of an increasing trend. Although our data are obtained from large population-based cohort studies or biobanks, we have to realize that our results cannot always be generalized to the overall prevalence in the specific countries, as some cohorts have only collected data from a specific region of that country (CHRIS/MICROS/HUNT2), or from a specific age group (NCDS). Despite the detected variation, the data confirm the observations that obesity in European countries continued to rise the last decade and has reached epidemic proportions. However, recent publications suggest levelling off of the obesity epidemic, although in subjects with lower socioeconomic status a steady increase in prevalence still is observed.
The Finnish cohorts had the highest prevalence of MetS among obese subjects and the lowest percentage of MHO. In contrast, in the Italian MICROS and the Dutch LifeLines studies we observed a lower prevalence of MetS among obese subjects together with a higher percentage of MHO. Similar patterns in the occurrence of MetS in Europe have been reported previously. MetS is a constellation of metabolic risk factors, associated with an increased risk for the development of atherosclerotic cardiovascular disease as well as type 2 diabetes mellitus. MetS has been shown to be the major risk determinant of heart disease, also when a population generally has low levels of HDL- and LDL-cholesterol. The most frequent MetS component present in obese individuals was elevated blood pressure. In the 10 studies, obesity coincided with hypertension in 60% to 85% cases. In contrast, we observed considerable variations in the prevalence of other components of MetS, especially blood glucose and HDL-cholesterol. A blood pressure exceeding the strict criterion for a high blood pressure can be accounted as a main contributor promoting unhealthy obesity and metabolic syndrome in the Finnish cohorts in this study. Finnish tendency for elevated blood pressure has also been detected earlier, recently by The European Heart Network and The European Society of Cardiology.
Our study extends previous efforts to describe the phenomenon of healthy obesity and to estimate its prevalence in different countries in several important ways, including helping to disentangle whether differences in the prevalence of MHO are due to geographic variation or differences in measurements. Using a large amount of validated information, we applied a rigorous protocol to harmonize data from multiple population-based European studies, and ensure a high level of homogeneity of the MetS definition used to calculate the MHO prevalence. Recently, the lack of a standard approach to use the same sets of criteria and cut-off values to define metabolic abnormalities has been highlighted as the major source of the high variability in the reported MHO prevalence. Yet, our results also demonstrate a significant diversity in the prevalence of MHO across Europe using the harmonized criteria to define MetS. The highest percentage of MHO in men was found in CHRIS and KORA, and in women in NCDS, LifeLines, KORA and CHRIS, whereas the lowest prevalence was found in the Finnish cohorts and in HUNT2. In our study, we have used the established risk factors associated with the metabolic syndrome to identify the MHO phenotype. Our data on MetS components is consistent with the outcome of previously performed studies on the prevalence of the metabolic abnormalities in Europe. As age and sex are important factors in the development of MetS, we have also evaluated the age- and sex-stratified prevalence of MHO per decade. Our results indicate a higher prevalence of the MHO phenotype in women than in men as well as an age-related decline in the percentage of obese subjects with a metabolically healthy phenotype. Collectively, our findings raise additional questions about the underlying factors promoting the variation in the prevalence of MHO across different populations. Such variation in the distribution of metabolic phenotypes can be explained by several factors, including difference in age of the cohort participants, differences in environmental factors such as physical activity level, diet, smoking and alcohol use, and differences in the selection and inclusion of participants. Also the psychosocial profile and genetic factors may play a role. While behavioral factors, i.e. higher levels of physical activity or moderate alcohol intake, have been shown to be associated with the MHO phenotype, there is no evidence yet whether genetic background and divergence between populations does contribute to the metabolically favorable profile in obesity.
Given the number of serious health problems associated with obesity including type 2 diabetes, cardiovascular disease, and an increased risk for various types of cancer, the investigation of the healthy obesity phenotype may provide novel insights into the pathophysiology of obesity-related co-morbidities and help to identify at-risk obese individuals. Furthermore, it may help in the development of better interventions for obese patients. There are strong indications that weight loss may not have a beneficial effect on certain metabolic risk factors in MHO individuals and even result in a paradoxical response. Therefore, the one-size-fits-all approach regarding the consequences of obesity should be revisited, and the prevailing concept in the health care system that obesity is always bad should be re-evaluated. Also, a proper classification of the at-risk and metabolically benign obese individuals should be taken into account in medical research to prevent any bias in the interpretation of the results.
The main strengths of this descriptive study are the large sample size and the application of harmonized criteria to evaluate the prevalence of MetS and the degree of the MHO across different European cohort studies. Through our harmonization process, we have shown the possibility for collaborative research based on a careful harmonization process across multiple participating cohort studies. Several important factors may have a bearing on the results. First, we used BMI to define the obesity status. Since BMI is a measure of general obesity and cannot distinguish between fat and lean mass, other measures such as waist circumference (WC) or waist-hip-ratio (WHR) might be better indicators of visceral fat accumulation. Although a few studies reported lower fat accumulation in MHO individuals compared to the obese with metabolic abnormalities, no difference in the prevalence of MHO was found when WC was used instead of BMI to define the MHO phenotype in the NHANES cohort. Second, although our harmonized measures captured the essential information content for the MHO phenotype, there were differences between studies in the way that specific variables such as blood pressure and serum lipid levels were measured. Also, our cut-off values for non-fasting measurements of, for example, blood glucose may underestimate the actual degree of the MHO present in the corresponding studies. Third, although many participating cohort studies included several thousands of participants, their health and lifestyle habits may not always be representative of the general population in this specific country because of bias in participation or differences in recruitment of participants. We also cannot exclude that a potential participation bias could affect the results. As such, higher participation rates from either healthy or unhealthy individuals can influence the outcome, and it cannot be ruled out that the high percentage of MHO in the LifeLines Cohort Study may – at least in part – be explained by a preponderance of healthy individuals willing to participate.
An important factor to discuss is the time period in which the initial screening of each individual cohort was performed. Data in some cohorts were collected in the 1990s, while, for example, the participants in the Dutch LifeLines Cohort Study were recruited between 2007 and 2012, and in the Italian CHRIS study after August 2011. There have been several changes in environmental factors such as health behaviour and smoking pattern over time, which may have a bearing on the prevalence of MetS and on health in general. In many countries higher awareness of the importance of increased physical activity or smoking cessation have been recognized, although it appears that the current epidemic of obesity is still on-going. As an example, cessation of smoking is on one hand associated with weight gain, which may be perceived negatively by individuals, but it also results in improvement of the metabolic profile as smoking cessation is accompanied by an increase of HDL cholesterol and reduction of triglycerides. It is important to note that the major objective of this descriptive study was to evaluate the phenomenon of healthy obesity among the participating European population-based studies. The BioSHaRE-HOP consortium is currently expanding its harmonization efforts, and assessing differences in lifestyle factors such as nutritional habits, physical activity, smoking and general awareness of health between the various participating countries in order to have a better estimate of the characterization and the determinants of (healthy) obesity.
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