However, adjustment for BMI had diverse effects on the associations between WC with HbA1c across sex and ethnic groups. Associations were wholly attenuated for Chinese participants, partly attenuated for Malay participants, and strengthened for Indian men but unaffected for Indian women.

Overall, fully adjusted associations between WC, SBP and lipids tended to be strongest in the Chinese groups and weakest in the Indian groups, whereas this pattern was reversed for HbA1c. Models are presented without and with mutual adjustment for body mass index.

In the largest ethnic comparison of adiposity, body composition and cardiovascular risk factors study to date, we observed distinctly different patterns with CVD risk factors across ethnic groups despite generally small differences in body composition at a given BMI.

BMI and fat mass had similar positive associations with SBP and HbA1c although stronger overall in Malaysian ethnicities than White ; but the associations with lipids were generally stronger for fat mass.

A notable exception was for Indian men and women for whom there was little association of either BMI or fat mass with triglycerides. Contrasting associations across CVD risk factors were observed for appendicular lean mass, with no evidence in men of differences across ethnic groups.

However, among women, associations with appendicular lean mass were particularly strong in Malay and Indian women, with positive associations that were greater than those for fat mass or BMI. Adjustment for BMI did not impact associations between WC and lipids, but it largely attenuated associations with SBP and produced diverse effects on associations with HbA1c across the sex- and ethnic-groups.

Previous research has documented different obesity-related risks across ethnic groups, with South Asians generally at a higher risk for diabetes but a lower risk for CVD than Caucasians at similar levels of BMI [ 2 , 3 , 12 ].

BMI has been criticised as a measure of adiposity since it does not indicate potentially important characteristics of body composition for disease risk, such as the proportion of fat and lean mass, or fat distribution [ 13 , 14 ]. However, this study observed distinctly different patterns of body composition and CVD risk factors across ethnic groups despite generally small differences in body composition at a given BMI.

Other research has also reported that Chinese men had stronger relationships with SBP, fasting glucose and blood lipids than White men for a given BMI, suggesting they were more prone to the metabolic effects of obesity [ 15 ]. Interestingly, the strong relationship between BMI and SBP for the Chinese in this study was still weaker than associations reported from large-scale studies of Chinese adults from mainland China 8.

Even though BMI as a measure of adiposity has been criticised for failing to distinguish between types of tissue mass, ethnic comparisons showed broadly similar patterns for fat mass and BMI although lipids were slightly more strongly associated with fat mass.

Conversely, associations with appendicular lean mass were distinct from those reported with BMI and not consistently beneficial. The positive association between lean mass and SBP has been documented before across White and Non-White ethnicities, but this study reported a novel finding that in Malay and Indian women the deleterious associations of SBP, triglycerides and HbA1c with appendicular lean mass were generally stronger than those with BMI or fat mass [ 18 , 19 ].

Previous research on a Malay population in Malaysia found higher metabolic risks at lower levels of BMI and WC than recommended by international diagnostic criterion, suggesting other elements of body composition were important for metabolic risk [ 20 ].

Current evidence is equivocal regarding the role of lean mass in cardiometabolic health, with large prospective studies reporting both increased and decreased risks of incident CVD with greater lean mass [ 14 , 21 , 22 ]. Theories suggest that muscle tissue is the main depot for glucose uptake and clearance, entailing that greater lean mass should improve insulin sensitivity.

However, meta-analyses of resistance training interventions in participants with diabetes indicated that improvements in glycaemic control were seen alongside improvements in strength, without gains in absolute lean mass [ 21 , 23 ]. This suggests future studies need to look more closely at muscle quality in relation to cardiovascular health, such as fibre typology and fat accumulation, particularly as previous research has reported that south Asians may have higher intermuscular fat than BMI-matched White or Chinese groups [ 21 , 24 ].

Differences in muscle quality may further differ by sex-specific ethnic groups, given the particularly strong associations of lean mass with triglycerides and HbA1c for Malay and Indian women in this study. This could be an important source of heterogeneity for metabolic health that needs to be examined.

Another novel finding from this study was that associations of WC with HbA1c were largely attenuated by adjustment for BMI in Chinese adults, but were less affected in the Malay and were strengthened in Indian men. Few studies have compared associations of general and central adiposity across ethnicities.

One study on adults from different ethnicities in the London SABRE study found that central adiposity, particularly visceral adipose tissue, was a stronger risk factor for diabetes in south Asian than European men [ 25 ]. Likewise, Indian men and women in this study had the strongest associations between WC and HbA1c of any ethnic group.

Such differences may be due to adipocyte morphology, with suggestions that south Asians may have a lower capacity to store fat in subcutaneous fat depots, so excess fat more readily overflows into ectopic compartments that increase metabolic impairment [ 26 ].

However, this theory contradicts the markedly weaker relationships between adiposity and triglycerides for Indian men and women in this study, as an increase in liver fat accumulation is often accompanied by elevated triglycerides [ 27 ].

Such weak associations are also interesting as elevated triglycerides are generally associated with insulin resistance and diabetes, with Indian adults reporting elevated risks of both compared to other ethnicities [ 28 , 29 ].

In the future, incorporation of genetic data would help elucidate the independent relevance of different anthropometric and body composition measures across ethnic groups.

For example, a previous sub-study in TMC suggested there was a gradient in genetic risk scores for type II diabetes across ordered strata of BMI, with the genetic risk score having progressively larger effects across decreasing levels of BMI.

However, that study was too small to detect differences across ethnic groups and genetic evidence in multi-ethnic populations for other measures of body composition like ectopic fat is currently lacking [ 30 , 31 ]. A clear strength of this research is that it is the largest study to date with global multi-ethnic comparisons of detailed measures of body composition and cardiovascular risk factors, so chance findings due to small sample sizes between ethnic- and sex- specific groups is less likely.

Furthermore, the Malaysian and UK studies began recruitment around the same time, and had harmonised measurements on many covariates. TMC collected fasting blood samples from their participants, whereas UK Biobank did not, which limits the comparisons of lipids between the two studies, although it still allows for comparisons within TMC.

Additionally, while both studies assessed body composition using BIA, this was done using two different models, each with their own algorithms for estimating fat and lean mass.

However, since the two different BIA models were not able to be calibrated to a gold standard measure in this study, any inferences on body composition should be limited to within-cohort comparisons. Furthermore, neither study was able to adjust the associations with BIA for hydration status, a key factor that can impact the measurements [ 32 ].

Future research should investigate if more detailed measurements of body composition across ethnicities, such as those from DXA, would produce similar associations. The data used in this study was cross-sectional, so temporality and causality cannot be inferred.

Even though a comprehensive list of prevalent diseases were excluded in both datasets to limit reverse causality, there is still the possibility that prevalent subclinical disease could be influencing both CVD risk factors and body composition when measurements were taken.

Residual confounding is also possible due to both unmeasured confounders and to errors within measured confounders e. In particular, dietary intake was not adjusted for, but since sequential adjustment for other lifestyle factors had little impact on the associations data not shown , it is unlikely that adjustment for dietary intake would have made a substantive impact.

Different relationships with body composition could also be due to environmental differences between and within countries for ethnic groups. Overall, this study observed distinctly different patterns of adiposity and body composition with CVD risk factors across ethnic groups despite generally small differences in body composition at a given BMI.

Chinese men and women had a smaller BMI and less fat mass, but the strongest associations with many risk factors. Meanwhile, Indian participants reported the strongest relationships between WC and HbA1c, particularly after adjustment for BMI, but notably weak associations between adiposity and triglycerides.

There were consistently weak associations with appendicular lean mass across male ethnic groups, but positive relationships between lean mass and several risk factors were stronger in Malay and Indian women than for BMI.

Despite these distinct patterns across ethnic groups, it is still not clear why marked differences in the risks for diabetes or CVD for a given BMI have been observed in different ethnic groups.

The limitations of BIA and the as-yet unclear mechanisms linking aspects of body composition to cardiovascular disease suggest that more detailed measurements of regional fat and lean mass across ethnicities needs to be undertaken.

Only once the mechanisms linking adiposity and body composition with disease aetiology are better understood can we start to engage with more targeted prevention strategies to help attenuate the increasing global burden of obesity-associated diseases. The global burden of obesity-related disease has been increasing over the last three decades, but the metabolic risks associated with adiposity differ between populations and are not completely understood.

PubMed was searched for all papers up to July containing words related to 1 adiposity or body composition e. Studies were excluded if they studied children, adolescents, or elderly populations; and if they focused on weight maintenance, weight management or weight reduction. No large-scale studies compared relative associations between ethnicities regarding anthropometry and body composition and cardiovascular disease CVD risk factors.

In the largest comparison to date of global multi-ethnic populations; with harmonised data on over 30, Malay, 25, Chinese, 10, Indian and , White Europeans; unique insights into metabolic health were observed. Chinese participants had lower absolute levels of adiposity but generally stronger deleterious relationships to CVD risk factors than Malay, Indian or White participants.

Those of Indian descent had markedly weaker relationships between adiposity and triglycerides, but the strongest relationship between waist circumference and HbA1c. Associations with appendicular lean mass were not consistently beneficial, particularly for Malay and Indian women, among whom there were positive relationships with systolic blood pressure, triglycerides and HbA1c that were stronger than those for BMI.

There were distinct patterns in adiposity and body composition and CVD risk factors across sex and ethnic groups that do not explain observed variation in CVD rates across populations.

The unclear mechanisms linking body composition to cardiovascular disease risk suggest that more detailed measurements of regional fat and lean mass across ethnicities needs to be undertaken.

Only once the mechanisms underlying associations of adiposity and body composition with CVD are better understood can we start to engage with appropriately targeted prevention strategies to attenuate the increasing global burden of disease from obesity.

All results from this analysis are returned to UK Biobank within 6 months of publication, at which point they can be made available to other researchers upon reasonable request. Data analysis in TMC is done by staff at Universiti Kebangsaan Malaysia but relevant tables and analytic code can be shared with researchers upon reasonable request.

The statistical analysis plan and analytic code are available upon request to the corresponding author. The GBD Obesity Collaborators. Health effects of overweight and obesity in Countries over 25 Years. N Engl J Med.

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Download references. BL acknowledges support from UK Biobank, which is funded largely by the UK Medical Research Council and Wellcome. We would like to thank Naomi Allen for the role of scientific advisor and in setting up the collaboration between TMC and UK Biobank.

Clinical Trial Service Unit and Epidemiological Studies, Nuffield Department of Population Health, University of Oxford, Richard Doll Building, Old Road Campus, Oxford, OX3 7LF, UK. Jennifer L. UKM Medical Molecular Biology Institute UMBI , Jalan Yaacob Latiff, Cheras, Kuala Lumpur, Malaysia.

Medical Research Council, Population Health Research Unit, University of Oxford, Oxford, UK. Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Headington, OX3 7LE, UK.

Department of Medicine, Faculty of Medicine, University Kebangsaan Malaysia, Cheras, Kuala Lumpur, Malaysia. You can also search for this author in PubMed Google Scholar. All authors contributed to the design of the study and the statistical analysis plan. NA, FB, HT, PS, and JC conducted the analyses.

All authors contributed to the interpretation of the analyses and the presentation of the results. The distance from the start-line to the back of the heel nearest to the starting point was measured.

During the test, the child ran as fast as possible between two parallel lines 10 m apart. Systolic and diastolic blood pressure were measured in millimeter of mercury mmHg with an electric sphygmomanometer WelchAllyn, ProBP series, NY, USA. The participants were sitting in an upright resting position and had to rest at least five minutes before the measurement.

Two readings of blood pressure were done; if the readings differed by more than 10 mmHg, a third measurement was carried out. The mean value of two or three measures of blood pressure was calculated and used in the analyses. Children provided fasting venous blood samples which were analyzed for glucose, insulin, total cholesterol, high density lipoprotein cholesterol HDL cholesterol and triglycerides as described previously Due to the skewed distribution of HOMA-IR, values were transformed with the natural logarithm ln in the statistical analyses.

A continuous cardiovascular risk score based on the most used definition of the metabolic syndrome MetS was used in accordance with previous studies 7 , Since body composition was an independent variable in the analysis, waist circumference was not included in the score.

Linear regression was utilized in the statistical analyses. Additionally, models with fat mass index and fat-free mass index as the independent variable were mutually adjusted for each other. Thus, the latter model provides estimates that are mutually adjusted for body composition and cardiorespiratory fitness.

Furthermore, we observed no violations against the assumptions of the regression models The statistical analyses were conducted using SPSS Statistics IMB SPSS statistics, version 26, IBM Corp. Ethical permission for all studies in this manuscript was approved by the ethics committees in Linköping ref no.

All parents provided informed written consent before any measurements were conducted. Table 1 describes the children girls and boys who participated in this study. They were on average 9. Of the children, Maternal age was on average The majority of mothers had a university degree Table 2 displays the associations of body composition with physical fitness.

Fat mass index and fat-free mass index had joint but opposite associations with physical fitness for the weight-bearing fitness tests in the adjusted models. Associations of body composition with cardiovascular risk factors are presented in Table 3.

Table 4 presents the associations of physical fitness with cardiovascular risk factors. Although data collection at the 9-year follow-up, which is the focus of this paper, was carefully standardized, children were originally from three previous studies.

Hence, we re-analyzed the associations of body composition and physical fitness with the MetS score only using data from MINISTOP 25 , which is the largest individual study Tables S1 and S2.

We also re-analyzed the data using only data from the two birth cohort studies Tables S1 and S2. As shown in the tables, associations were generally very comparable in terms of direction and magnitude when analyzing all participants or participants from MINISTOP or the birth cohorts separately.

Furthermore, since it has been suggested that normalizing body mass and composition i. As shown in Table S3 , this adjustment had minor influence on the estimates, and results remained virtually the same. Finally, we also examined the influence of expressing cardiorespiratory fitness in estimated VO 2 -max using the equation by Léger et al.

However, estimates were very comparable to our main analysis, i. This study comprehensively examined associations of body composition and physical fitness with CVD risk factors in 9-year-old children and reports several findings of interest.

First, body composition and physical fitness were strongly associated, which highlight the need of mutual adjustments when examining the independent associations of body composition and physical fitness with CVD risk factors.

Second, accurately measured fat mass and fat mass index were strongly and positively associated with CVD risk factors also after adjustments for covariates including physical fitness. Third, accurately measured fat-free mass index had generally weak associations with CVD risk factors that were attenuated after adjustments.

Finally, greater cardiorespiratory fitness and motor fitness were associated with lower HOMA-IR and MetS score, although associations were strongly attenuated by the adjustments for other covariates including body composition fat mass index and fat-free mass index.

We found that body composition was strongly associated with physical fitness which extends our previous findings in preschool aged children 19 and previous studies in children that have not examined the combined association of fat mass and fat-free mass on physical fitness.

Previous studies have consistently reported that greater fat mass is strongly associated with CVD risk factors such as higher blood pressure, LDL cholesterol, triglycerides and insulin values as well as lower HDL cholesterol 12 , 13 , 14 , There are many mechanisms by which obesity may increase the prevalence of CVD risk factors or actual CVD events 35 , For instance, impaired adipogenesis, altered fat deposition, inflammatory and adipokine dysregulation, adipose tissue hypoxia, increased circulating free fatty acids, oxidative stress and lipotoxicity have been suggested as relevant pathways Furthermore, excess body fatness is closely connected with insulin resistance which in turn is related with dyslipidemia i.

Finally, obesity induce adaptations in the cardiac system including increased cardiac output and systemic vascular resistance which elevate the blood pressure Relatively few studies have examined associations between fat-free mass with CVD risk factors in children.

Grijalva-Eternod et al. Interestingly, associations were attenuated and not statistically significant after accounting for physical fitness i. Another study reported no associations with fat-free mass and insulin resistance in 7—9-year-old children although a positive association was observed in girls only after the age of 10 15 which may be reconciled with our findings.

Thus, based on our and the previous studies 15 , 38 , 39 , fat-free mass appears not to have any beneficial association with CVD risk factors.

Greater cardiorespiratory fitness and motor fitness in our unadjusted analyses were associated with lower HOMA-IR and MetS score which generally agrees well with previous studies of fitness and CVD risk factors 40 , 41 , 42 , 43 , 44 , 45 , However, previous studies have generally shown that the associations of cardiorespiratory fitness with CVD risk factors are strongly attenuated by adjustments for BMI or body fatness, both in studies that have used laboratory 47 , 48 or field measures 44 , 45 , 46 of cardiorespiratory fitness.

Data from this and previous studies 19 , 20 , 22 have shown that performance in the 20 m shuttle run is strongly and inversely associated with body fatness in children.

Given the close relationship between cardiorespiratory fitness and body fatness, it is possible that the unadjusted and statistically significant associations of cardiorespiratory and motor fitness with lower HOMA-IR and MetS are due to differences in body composition and especially a higher fat mass.

This would explain why these estimates are no longer statistically significant in the models that accounted for fat mass and fat-free mass and highlight the importance of considering body composition when examining associations of physical fitness and health outcomes.

Although cardiorespiratory and motor fitness are regarded as markers of health 49 , 50 , it is important to consider that associations between fitness and health outcomes may, at least partly, be due to other factors such as body fatness.

We observed that upper body strength and lower body strength in some cases had opposite associations with the measured CVD risk factors. For instance, greater upper body strength was associated with higher systolic blood pressure and MetS score, whereas greater lower body strength was associated with lower HOMA-IR and MetS score.

These results may be reconciled with previous studies of muscular strength and CVD risk factors in youth. Such studies have generally reported positive or null associations with handgrip strength 46 , 51 , 52 and inverse or null associations with standing long jump 46 , 51 , 52 in analyses that did not account for body composition or fatness.

As shown in Table 2 , associations between fat mass and upper body and lower body strength differed, which may be due to the nature of the fitness tests weight bearing or not. Although greater fat-free mass was associated with better performance in both tests, greater fat mass was associated with better performance in the handgrip strength non-weight bearing , but with poorer performance in the standing long jump weight bearing.

Considering the strong associations of fat mass with CVD risk factors, this difference may at least partly account for the difference in associations between strength and CVD risk factors. Indeed, when additionally adjusting for fat mass and fat-free mass, associations were generally strongly attenuated, although handgrip strength remained positively associated with systolic blood pressure and lower body strength inversely associated with HOMA-IR.

Thus, future studies should consider adjustments for body composition to elucidate the independent associations of physical fitness with CVD risk factors.

Furthermore, we were able to analyze the joint associations of body composition fat mass and fat-free mass and physical fitness with CVD risk factors. Another strength is that children were measured at 9. The current study also has some limitations that needs to be considered.

First, the cross-sectional study design limits interferences regarding the casualty of the examined associations. Moreover, the high proportion of mothers with a university degree may influence generalizability of the results. However, maternal educational attainment was accounted for in the analyses and had little influence on the estimates.

Furthermore, we lacked data regarding pubertal status in the analyses which is a limitation. Thus, we consider it likely that the effects of puberty have limited influence on our estimates, although further studies should consider accounting for pubertal status in the analysis.

The findings of our study have some implications that may be of importance for the promotion of cardiovascular health in children. First, our findings showed that fat mass index and fat-free mass index have generally independent but opposite associations with physical fitness, which indicate that analyses that include both body composition and physical fitness variables should be mutually adjusted for each other.

Second, BMI was generally as strongly associated to CVD risk factors as accurately measured fat mass, which indicate that more advanced body composition measurements e. Third, fat-free mass had no beneficial associations with CVD risk factors which provides support that cardiovascular health promotion in childhood should focus on the maintenance of a healthy fat mass.

Finally, higher cardiorespiratory fitness and motor fitness were associated with lower HOMA-IR and MetS score. However, associations were strongly attenuated by accounting for body composition fat mass and fat-free mass. Nevertheless, evidence from longitudinal studies in childhood and adolescence suggest that greater cardiorespiratory fitness, independent of BMI, is associated with better cardiovascular outcomes later in life 2 , 6 , 18 , Thus, further studies are needed to elucidate the independent influence of physical fitness on cardiovascular health in childhood and adolescence.

In conclusion, greater BMI and fat mass was associated with CVD risk factors even after adjustments for covariates and physical fitness. Importantly, associations with BMI were generally as strong as with accurately measured fat mass which may have implication given the easy measurement of BMI in children.

However, fat-free mass did not have any beneficial associations with CVD risk factors which support the notion that the focus for cardiovascular health promotion during childhood could be on excess fat mass and not on the fat-free mass.

Finally, higher cardiorespiratory and motor fitness were associated with lower HOMA-IR and MetS score although associations were strongly attenuated by adjusting the estimates for body composition fat mass and fat-free mass.

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