Latest study reveals increased cancer risk linked to higher BMI in adults with cardiovascular diseases

It’s unclear whether the danger of cancer related to a better body mass index (BMI) varies across individuals with and without type 2 diabetes (T2D) and cardiovascular diseases (CVD).

A recent BMC Medicine study analyzed the joint and individual correlations of CVD/T2D and BMI with cancer risk. 

Study: Body mass index and cancer risk amongst adults with and without cardiometabolic diseases: evidence from the EPIC and UK Biobank prospective cohort studies. Image Credit: urbans/Shutterstock.com

Background

The issue of being chubby and obese has risen sharply globally in recent a long time. This has increased the probabilities of non-communicable diseases (NCDs), equivalent to T2D, CVD, and cancer. The BMI is a commonly accepted measure of body fatness, which raises the danger of several sorts of cancer.  

Recent research has shown that CVD could independently drive certain cancers despite accounting for shared risk aspects, equivalent to BMI. Cancer, CVD, and T2D biological pathways, e.g., oxidative stress and inflammation, are common.

Taken together, it might be hypothesized that cardio-metabolic diseases (CMDs) could worsen the adversarial effects of obesity and being chubby in the event of cancer. Nevertheless, it should be highlighted that this linkage isn’t completely clear. 

Prior studies gave little attention to CMD and solely focussed on the cancer-BMI correlation in the overall population. Moreover, joint associations between CMD and chubby/obesity with cancer haven’t been widely studied.

Concerning the study

The current study is a meta-analysis of two cohort studies. These are the European Prospective Investigation into Cancer and Nutrition (EPIC) and the UK Biobank (UKB). The sample comprised 577,343 adults freed from CVD, T2D, and cancer on the time of recruitment. 

Cox proportional hazard regressions were used to estimate multivariable-adjusted hazard ratios (HRs). HRs and 95% CIs for joint and separate correlations between chubby/obesity and CMD status were also estimated.

The relative excess risk as a consequence of interaction (RERI) was used to quantify an additive interaction. As a secondary consequence, total cancer or all cancers combined was also studied. 

Key findings

It was noted that the sum of separate associations of obesity and CVD with cancer risk was lower than their joint association. Overall, this finding was consistent across the EPIC and UKB for all sorts of cancer.

Nevertheless, this association is held only within the UKB for obesity-related cancer risk. This result implies that reducing obesity could lead on to a discount in cancer risk amongst individuals with CVD. 

The variability in cancer risk amongst patients with CMD isn’t well understood. Targeting this information gap, it was shown that prime BMI and cancer risk were equally associated in individuals with and without CMDs. It must be noted that no association between cancer risk and BMI was noted within the population group with T2D only. 

This study provided recent evidence of an additive interaction between CVD and obesity/chubby, with respect to obesity-related and overall cancers. It’s imperative to know why certain diseases cluster and the way the clustering affects the disease burdens in numerous groups of people. 

A typical risk factor for CMD and cancer is excessive body weight. This could possibly be one reason why these diseases are likely to cluster. Mechanisms underlying the fat-cancer link could possibly be increased insulin levels, altered sex hormone metabolism, and adipokine pathophysiology.

These mechanisms could also potentially explain the T2D-cancer link. Quite the opposite, the CVD-cancer link is less well-understood. 

Conclusions

In sum, this study showed that higher BMI was related to a greater risk of cancer, regardless of the CMD status. The outcomes indicate that prevention of obesity could lead on to a better reduction in cancer risk in individuals with CVD in comparison with the overall population.

The important thing strength of the study is its use of two large prospective cohorts across multiple European countries and validated assessments of T2D, cancer, and CVD. The time-varying modeling of associations and sensitivity analyses to scale back biases also strengthen the evaluation. 

One limitation of the study was around the lack to think about changes in modifiable habits on the follow-up stage. Metformin, used to treat T2D, can result in weight reduction and reduce obesity.

The usage of metformin couldn’t be accounted for within the EPIC data. The outcomes could even have been influenced by selection bias, owing to including only participants without CMD. A key limitation of the UKB must also be highlighted here regarding its very low response rate. 

The generalizability of the findings is also a cause for concern since the UKB sample was less socioeconomically deprived, showed a lower presence of long-term conditions, and fewer risk aspects in comparison with the overall UK population.

Moreover, BMI might not be a really perfect measure of fat since it neither captures fat distribution nor distinguishes between fat and lean mass. Future studies should improve upon this through the use of detailed body composition assessments.