The relationships between objectively measured abdominal and gynoid adipose mass with the prospective risk of myocardial infarction (MI) has been scarcely investigated. We aimed to investigate the associations between fat distribution and the risk of MI.
Total and regional fat mass was measured using dual-energy X-ray absorptiometry (DEXA) in 2336 women and 922 men, of whom 104 subsequently experienced an MI during a mean follow-up time of 7.8 years.
In women, the strongest independent predictor of MI was the ratio of abdominal to gynoid adipose mass (hazard ratio (HR)=2.44, 95% confidence interval (CI) 1.79–3.32 per s.d. increase in adipose mass), after adjustment for age and smoking. This ratio also showed a strong association with hypertension, impaired glucose tolerance and hypertriglyceridemia (P<0.01 for all). In contrast, the ratio of gynoid to total adipose mass was associated with a reduced risk of MI (HR= 0.57, 95% CI 0.43–0.77), and reduced risk of hypertension, impaired glucose tolerance and hypertriglyceridemia (P<0.001 for all). In men, gynoid fat mass was associated with a decreased risk of MI (HR=0.69, 95% CI 0.48–0.98), and abdominal fat mass was associated with hypertriglyceridemia (P for trend 0.02).
In summary, fat distribution was a strong predictor of the risk of MI in women, but not in men. These different results may be explained by the associations found between fat distribution and hypertension, impaired glucose tolerance and hypertriglyceridemia.
The rapidly increasing global prevalence of overweight and obesity is a cause of great concern owing to the wide-ranging pathologic consequences of the condition.1 Thus, considerable effort has been made to understand the pathogenic mechanisms of obesity. The relative contributions of total versus regional adiposity to metabolic and cardiovascular disease (CVD) risk have long been debated.2 Although total adiposity is a risk factor for impaired glucose tolerance, type 2 diabetes and heart disease,3, 4 some obese individuals remain free from cardiovascular disease.5, 6 These observations suggest that adipose distribution, particularly around the viscera, may be the major risk factor for the aforementioned diseases, rather than adipose mass per se.
A variety of pathophysiological processes have been proposed that link visceral obesity with cardiovascular disease. These include low-grade inflammation that inhibits insulin signaling and endothelial function and promotes arterial lipid accumulation and atherosclerosis.7 Atherosclerotic lesions emanate from fatty streaks beneath the endothelium that consist of macrophages, connective tissue elements, lipids, debris, inflammatory cells, immune cells and T cells.8 The resultant emboli can occlude vessels and by consequence restrict blood flow to major organs such as the brain or heart, resulting in stroke or myocardial infarction (MI), respectively.9 In contrast, peripheral obesity, with adipose deposition around the hips and thighs, has been associated with a lower risk of several risk factors for CVD.10, 11, 12 Gynoid adipocytes are insulin sensitive, have high lipoprotein lipase activity,13, 14 and are thus well suited for storing circulating free fatty acids (FFAs). These characteristics may explain why gynoid obesity seems to confer protection against FFA dysmetabolism,15 whereas visceral obesity tends to promote it. In addition, anthropometric measurements, such as waist-to-hip ratio and waist circumference, are more strongly associated with the risk of CVD than total fat mass and body mass index (BMI),16 reflecting a higher correlation with visceral fat mass than BMI.17
Previous cross-sectional and prospective studies have reported the relationships between waist circumference and several CVD risk factor levels and end points.16, 18, 19 However, very few prospective studies exist in which the relationships between objectively measured abdominal adipose mass and cardiovascular end points have been reported.20, 21 A method that is rarely used in studies concerning regional fat mass is dual-energy X-ray absorptiometry (DEXA), although studies have shown it to be just as good or even better in respect to visceral fat mass than anthropometric measurements.22 Furthermore, to our knowledge, no prospective studies have investigated the relationship between gynoid adipose mass and cardiovascular end points. The purpose of this study was to determine the prospective relationships between objectively assessed adipose distribution using DEXA and incident MI in a large sample of initially healthy middle-aged men and women from Northern Sweden.
Subjects and methods
The bone mineral density and fat mass database
Since 1991, DEXA has been used to measure adipose mass and accumulation at the Sports Medicine Unit, Umeå University, Sweden. By the end of 2006, DEXA scans had been performed on 4333 women and 2320 men. The 64 prevalent MI cases within this cohort were excluded. Because of the nature of the involved databases, reliable follow-up data could only be obtained for those still living within the county of Västerbotten at the end of the study (1 August 2006). We were able to trace 2537 women and 958 men using regional and national disease registers. After excluding individuals >75 years of age, 2336 women and 922 men remained. These individuals comprise the present cohort study. The reasons for admission for a DEXA scan were recorded for all subjects aged ⩾30 years during 2005 (n=790). The reasons for admission included a previous fracture (34.2%), a general suspicion of osteoporosis (19.6%), or previous or current oral corticoid steroid therapy (19.4%). Approximately 9% of the subjects were not admitted for medical reasons and underwent DEXA scans as part of research projects at the University.
Measurements of adipose mass
Total adipose mass was assessed using DEXA (GE Lunar, Madison, WI, USA). The ‘region of interest’ program was used to manually determine abdominal and gynoid adipose masses. The inferior part of the abdominal adipose mass region was defined by the upper parts of the pelvis with the upper margin 96 mm superior to the lower part of this region. The lateral part of this region was defined by the lateral part of the thorax.23 The upper part of the gynoid adipose mass region was defined by the superior part of trochanter major, with the lower margin 96 mm inferior to the upper part of the trochanter major. The lateral part of this region was defined by the subcutaneous tissue on the hip that can be visualized using the Image Values option. Two investigators (PW and FT) performed all the analyses. The inter-operator reproducibility was determined by having both investigators estimate abdominal fat mass in 15 subjects. The correlation coefficient was estimated to be 0.997, with a mean difference between the estimates of 2.4%. DEXA has been validated previously in children, adults and the elderly, and has been found to be a reliable and valid method for measuring adipose mass.17, 22, 24 The coefficient of variation (that is, s.d./mean × 100) was evaluated in our laboratory by scanning one person (male, 30 years of age, 30% body adipose, with normal weight and height) seven times in the same day, with repositioning between each scan. For this individual, the coefficient of variation was 2% for abdominal adipose mass and total adipose mass. The equipment was calibrated each day using a standardized phantom to detect drifts in measurements, and equipment servicing was performed regularly. Concerning bone mineral density, the scanners were also scanned regularly during the 15 years of measurements using a spine phantom without detecting any drifts in the measurements. Two different machines were used for the measurements: from 1991 to 1998, a Lunar DPX-L was used, and from 1998 to 2006, a Lunar-IQ was used. These machines were cross-calibrated by scanning one male subject with a mean fat percent of 17 and one female subject with a mean fat percent of 32 on the same day on both machines. Before the measurement the subjects’ weight and height were measured in light clothing using standardized equipment. BMI was calculated as weight (kg)/height (m)2.
Verification of MI events
To identify subjects who experienced an MI, the bone mineral density and fat mass database was merged with the Northern Sweden MONICA myocardial infarction database. MONICA is an international research project started by the World Health Organization in 1985. Its purpose is to identify time trends concerning the risk factors and incidence of cardiovascular events. With these premises, all MIs occurring in people <65 years before 2000, and <75 years of age thereafter, in the Northern Swedish counties of Västerbotten and Norrbotten have been registered and validated. To identify subjects between 65 and 75 years of age who sustained an MI before 2000, the bone mineral density and adipose mass database was merged with the hospital register at the University Hospital of Northern Sweden in Umeå. The hospital records of the patients with an MI diagnosis were then registered and validated according to the MONICA criteria.25 Altogether, 104 first ever MIs were identified within the cohort and included in the present study. Only MIs before the study end date were included in this report.
Background variables and clinical measurements
Background data concerning diabetes, prescription medication usage and smoking habits were collected for all who sustained an MI within the MONICA registers, MONICA screening project26 and the Västerbotten Intervention Programme.27 For those who sustained an MI, information was also collected from medical journal records. In total, background data were collected for 1523 subjects including all who sustained an MI for some of the variables. Systolic and diastolic blood pressures, serum levels of triglycerides, fasting plasma glucose and results of a 2-h glucose tolerance test were collected for 1346 subjects including 34 who sustained an MI through Västerbotten Intervention Programme. Hypertension was defined as diastolic blood pressure >90 mm Hg and/or systolic blood pressure >140 mm Hg or using drugs prescribed for hypertension. Impaired glucose tolerance, 2 h after 75 g oral glucose load, was defined as fasting plasma glucose <7 mmol l–1, and 2-h plasma glucose between 8.9 and 12.1 mmol l–1. Diabetes was defined as a fasting plasma glucose of at least 7 mmol l–1, a 2-h plasma glucose of >12.1 mmol l–1 or using drugs prescribed for diabetes. Hypertriglyceridemia was defined as a triglyceride concentration >2 mmol l–1, or using drugs for hyperlipidemia. When comparing those subjects with and without background data, there was no significant difference (P>0.05) in total fat mass (mean 25.1 vs 24.5 kg), BMI (mean 25.8 vs 25.6 kg m–2) or sex (27 vs 30% men). However, those with no background data were significantly older (mean 51.5 vs 54.7 years, P<0.001).
Data are presented as the mean (±s.d. or 95% confidence interval (CI)) unless otherwise indicated. Differences between two groups were tested using Student's t-test for independent samples. The relationships between the different estimates of adipose distribution and MI events were determined using Cox proportional hazards models. The proportional hazard assumption was checked graphically for quartiles of the adiposity estimates using Kaplan–Meier curves. Interaction terms were fitted to the Cox models to test whether these effects differed by sex. Individual data points were censored at the event date (for those who sustained an MI), date of death or at the end of the study (1 August 2006), whichever came first. The area under the receiver operator characteristic curves (ROCAUC) was compared for different measures of adipose mass in relation to the risk of MI. The incremental (likelihood ratio) χ2 values were also compared. Logistic regression was used to investigate the relationship between quartiles of the different adipose mass estimates and the different risk factors for CVD, that is, hypertension, impaired glucose tolerance or diabetes and hypertriglyceridemia. All statistical tests were two sided. A P-value of <0.05 was considered statistically significant. SPSS for the PC (version 15.0; SPSS Inc., Chicago, IL, USA) or SAS (version 9, SAS Institute Inc., Cary, NC, USA) were used for statistical analyses.
We followed 3258 men and women (baseline mean age of 53.3 years) for a mean of 7.8±3.8 years. During follow-up, 104 MI events occurred on average 5.1±3.2 years after the baseline examination. The baseline physical characteristics, adipose distribution, prevalent disease, smoking habits and usage of medications prescribed to treat CVDs are shown in Table 1.
Women who suffered an MI during follow-up were at baseline shorter, had more abdominal adipose mass, a lower ratio of gynoid to total adipose mass and were more likely to have diabetes or hypertension or hypertriglyceridemia than women who remained event free (P<0.05). Men who suffered an MI during follow-up were more likely to have diabetes and/or hypertension than men who remained event free (P<0.05).
Statistically significant interactions (P<0.05) were observed for sex and the different adipose measures both in models investigating the association with the different risk factors for MI, that is, hypertension, impaired glucose tolerance and hypertriglyceridemia (Table 2), and in models assessing future risk of MI (Table 3). Regression models are therefore presented for men and women separately.
The associations between quartiles of the different adipose estimates and hypertension, impaired glucose tolerance and hypertriglyceridemia are presented in Table 2 after adjustment for age and smoking. In women, the different estimates of abdominal fat mass were the best predictors of all three risk factors (P<0.01 for all), although all other adiposity estimates also showed evidence for a significant positive dose-dependent relationship, with one exception. Thus, the ratio of gynoid to total fat mass showed a negative significant association with all risk factors (P for trend <0.001 for all). In the male cohort, abdominal fat mass was associated with hypertriglyceridemia (odds ratio 3.01, 95% CI 1.29–7.05).
The risk of incident MI per s.d. increase in each measure of adipose mass, after adjustment for age and smoking, is shown in Table 3. For women, the ratio of abdominal to gynoid adipose mass conferred the greatest risk of MI (hazard ratio (HR) 2.44, 95% CI 1.79–3.32). Moreover, abdominal adipose mass was significantly associated with an increased risk of MI (HR=1.53, 95% CI 1.10–2.12). In contrast, the ratio of gynoid to total adipose mass was associated with a reduced MI risk (HR= 0.57, 95% CI 0.43–0.77). In men, gynoid adipose mass was associated with a decreased risk of MI (HR=0.69, 95% CI 0.48–0.98).
Information concerning all background variables was available for 1014 women and 378 men, including 43 women and 35 men who experienced an MI. The ratio of abdominal to gynoid adipose mass was found to be independently associated with the risk of MI in women, after adjustment for all background variables (HR=1.91, 95% CI 1.37–2.68 per s.d. increase). Other independent predictors included age, diabetes and hypertension in all models (P<0.05). In men, total fat mass (HR=0.63, 95% CI 0.42–0.92) and gynoid fat mass (HR=0.62, 95% CI 0.42–0.92) were associated with a decreased risk of MI. Other independent predictors included age and diabetes in all models (P<0.05).
ROCAUCs for each of the models were compared for the total cohort of women (n=2336, events=56). The comparison of χ2 distributions for the respective models indicated that the ROCAUC for the ratio of abdominal to gynoid adipose mass and age (0.733; P<0.0001) was significantly larger than the ROCAUCs for BMI and age (0.599), total adipose mass and age (0.593) and gynoid adipose mass and age (0.593). When adding the ratio of abdominal to gynoid adipose mass to BMI and age, the ROCAUC increased significantly to 0.737 (P<0.001). This ROC area was, however, not significantly greater than for the ratio of abdominal to gynoid adipose mass and age alone (P>0.05). We did not undertake comparisons of ROCAUCs in the male cohort, as only gynoid fat mass was significantly associated with MI.
In this study we investigated the relationship between regional adiposity and incident MI. Our findings show that abdominal adipose mass is associated with an increased risk of MI in women. Estimates of abdominal fat mass were also most strongly associated with the different cardiovascular risk factors. In contrast, estimates of gynoid adipose mass were associated with a decreased risk of MI, hypertension, impaired glucose tolerance and hypertriglyceridemia. These findings are novel and reinforce the findings of previous studies using anthropometric methods,16 suggesting that the distribution of adipose tissue, using the waist to hip ratio, is more relevant when predicting MI than a general obesity measure such as BMI.
In men, the different adiposity measures were not related to an increased risk of MI, and only abdominal fat mass showed a positive association with one of the cardiovascular risk factors. These results are interesting as BMI and anthropometric estimates of abdominal adipose mass have generally been shown to increase the risk of both CVD morbidity and mortality in men in large multicenter studies.16, 28, 29 To our knowledge, only two previous studies have investigated the prospective relationship between objectively measured visceral adipose mass and the risk of CVD. Nicklas et al.21 assessed the association of visceral adipose mass measured by computed tomography and incident MI in 2503 men and women aged ⩾70 years. They found that in women, visceral adipose mass was the only variable that was significantly associated with an increased risk of MI events, whereas in men, no associations were found. Elsewhere, Fujimoto et al.20 investigated the relationship between visceral adipose mass measured by computed tomography and coronary heart disease (MI, angina and coronary angioplasty) in 175 Japanese-American men with a mean age of 61 years, of whom 50 went on to develop coronary heart disease. Among the adipose variables, only visceral adipose mass was a significant predictor of coronary heart disease. There could be several explanations for the different results of studies using anthropometric methods to approximate fat distribution and those where fat mass was objectively measured. First, anthropometric measures such as the waist-to-hip ratio are influenced not only by fat mass, but also by lean body mass and skeletal structure, which might affect the association with cardiovascular outcomes.30 Second, the design of the different studies may also influence the associations found with the outcome variables. For example, in retrospective studies the cases may have concurrent co-morbidities and the reporting of health-related behaviors may be biased owing to disease labeling,16 the factors that are considerably less common in prospective case–control studies. Interestingly, other large population-based studies have also found stronger associations between anthropometric measures of adipose distribution and CVD in women than in men.16, 29
In the present study, the ratio of gynoid to total fat mass was associated with a decreased risk of MI in women, and an inverse dose-dependent relationship with all cardiovascular risk factors investigated. Gynoid fat mass was also associated with a decreased risk of MI in the male cohort. Although we are unaware of other studies that have assessed the relationship between gynoid adiposity and subsequent coronary heart disease events, two small computed tomography studies reported inverse relationships between gynoid adipose mass and CVD risk factors.11, 12 For example, Caprio et al.11 measured regional adipose mass in 14 obese adolescent women and 10 non-obese controls and showed that femoral adipose tissue was associated with lower triglyceride and low-density lipoprotein cholesterol levels. In a second study, Pouliot et al.12 measured visceral adiposity in 58 obese and 29 lean males. They found that visceral adiposity was associated with lower levels of high-density lipoprotein cholesterol levels and with higher fasting plasma triglyceride and insulin levels. The same researchers showed in 29 pre-menopausal women that femoral adipose tissue lipoprotein lipase activity showed a positive association with high-density lipoprotein 2 cholesterol, whereas abdominal adipose tissue lipoprotein lipase activity tended to be negatively correlated.31
There are some possible mechanisms through which regional adiposity might influence MI risk. One is the post-prandial model of insulin resistance;15 FFAs are primarily meal derived and when insulin-resistant visceral adipocytes release FFAs from chylomicrons, they are prone to enter the circulation instead of being re-esterified for storage. On the other hand, gynoid adipocytes are insulin sensitive and thus metabolize FFAs more efficiently.13, 32 Another plausible explanation is that gynoid obesity signifies a generally healthy adipose deposition, either genetically or through lifestyle, in which a general subcutaneous deposition is preferred over visceral locations. Hence, gynoid fat could work as a healthy metabolic sink, decreasing ectopic fat accumulation.
There are some limitations to this study that should be highlighted. The cohort was not population based, but consisted primarily of people with a suspicion of osteoporosis, which might cause a degree of selection bias. However, in a recent study, we observed comparable genotype distributions to those reported in other northern European populations for a range of bona fide obesity risk loci.33 Furthermore, a variant in the FTO (fat mass and obesity associated) gene, which is the strongest known genetic predictor of polygenic obesity,34 was comparably associated with adiposity traits in our cohort to those studied elsewhere. These factors suggest that, insofar as genetic architecture is concerned, our cohort is representative of the background populations of northern Europe. In this study the number of MIs was also rather small and no background data were available for some subjects, which might explain the lack of significant associations for several predictor variables in the male cohort. Nevertheless, the interaction term for sex was significant for most adiposity traits, suggesting adequate statistical power. It is also important to point out that DEXA cannot selectively measure visceral fat. This would, if anything decreases the regression coefficients for measures of abdominal fat. However, in the female cohort, the ratio of abdominal to gynoid fat was a significantly stronger predictor of MI than general measures of adiposity, for example, total fat mass and BMI.
In summary, in this cohort of people from Northern Sweden, fat distribution was a significantly stronger predictor of the risk of MI than general obesity. These findings may be at least partly mediated by effects on blood pressure, glucose metabolism and lipid metabolism. In men, the associations between fat distribution, cardiovascular risk factors and the risk of MI were generally weaker than in women.
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This study was supported by grants from Umeå University and Västerbottens läns landsting.
The authors declare no conflict of interest.
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Wiklund, P., Toss, F., Jansson, J. et al. Abdominal and gynoid adipose distribution and incident myocardial infarction in women and men. Int J Obes 34, 1752–1758 (2010). https://doi.org/10.1038/ijo.2010.102
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