Our current understanding of obesity and cancer is largely limited to studies that have used body mass index (BMI) as the sole measure of excess adiposity. However, fat mass and lean body mass, which cannot be distinguished by BMI, may have distinct effect on cancer. Hence, failure to assess the independent role of fat mass and lean body mass may dilute or even distort the true relationship between obesity and cancer endpoints, as exemplified by the `obesity paradox'. Attempts to examine the effect of body composition have been hampered by infeasibility in using expensive technologies in large scale. We offer a novel approach to overcome this limitation and explore the association between lean body mass and fat mass and the risk of major cancers, including lung, pancreatic, colorectal, breast, and prostate cancers. We propose to use anthropometric prediction models, which were developed in the National Health and Nutrition Examination Survey and validated using obesity-related biomarkers. The predicted lean body mass and fat mass were further tested in relation to mortality in the Health Professional Follow-up Study (HPFS) and Nurses' Health Study (NHS) to ensure the significance and feasibility of the proposed aims.
Aim 1 will further build on existing evidence on the harmful effect of adiposity on cancer development by examining the association between fat mass and cancer endpoints that is independent of lean body mass. Compared to prior literature using BMI, a stronger and more linear association may be detected with predicted fat mass.
Aim 2 will be the first analysis to test whether the emerging evidence suggesting beneficial effect of lean body mass on chronic diseases holds true for the risk of major cancers. If lean body mass, independent of fat mass, has inverse association with cancer endpoints, then future studies and interventions should emphasize the role of lean body mass, and not just body weight per se.
For Aims 1 and 2, we will leverage the repeated measures over three decades of follow-up in the HPFS and NHS to explore the latency periods and change in body composition that can uncover important biological mechanisms underlying cancer development.
Aim 3 will perform stratified analyses by age and smoking status to better understand heterogeneous cancer etiologies. Given that body composition changes unfavorably with aging, decomposing the effect of lean body mass and fat mass may be particularly relevant for the older population. Moreover, stratification by smoking can appropriately address confounding and capture the changes in body composition resulting from smoking. In summary, the proposed study has great potentials to provide novel insights into the role of lean body mass and fat mass in cancer incidence that are distinctive from prior studies that have used BMI measure. This study will serve as a promising step towards development of a clinically feasible method to better characterize future cancer risk, facilitate research directed to assessing the effect of specific body compartments, and generate new evidence to inform weight and lifestyle guidelines for cancer prevention.
Despite the accumulating evidence suggesting independent effect of lean body mass and fat mass on cancer endpoints, no comprehensive investigation exists on this association due to difficulty in measuring body composition in large scale epidemiological studies. We propose to examine the risk of major cancers in relation to lean body mass and fat mass derived directly from anthropometric prediction equations that were developed, systematically validated, and further tested in two large prospective cohorts (i.e., Health Professional Follow-up Study and Nurses' Health Study). This innovative proposal addresses a critical limitation of current cancer research that relies on the measure of body mass index that fails to discriminate different body compartments, and provides a unique opportunity to further our understanding of cancer etiology in relation to lean body mass and fat mass separately, and thereby possess important scientific and public health significance.
