MedicalResearch.com Interview with:
Ching-Ti Liu, PhD
Department of Biostatistics
Boston University School of Public Health
MedicalResearch.com: What is the background for this study? What are the main findings?
Response: Being overweight and obese are increasing worldwide and this obesity epidemic threatens to reverse the gains in life expectancy achieved over the past century. However, many investigators have observed, paradoxically, that overweight individuals are associated with a lower mortality risk. These results may suffer from a potential confounding due to illness or reverse causality in which preexisting conditions may alter both body weight and the risk of death. Recently published studies have tried to mitigate this reverse causal bias by implementing sample exclusion and they came to a different conclusion: between BMI and all-cause mortality there is an increased risk of death for the entire range of weights that are in the overweight and obesity ranges.
However, the elimination strategies may lead to the loss of generalizability or precision due to over-adjustment. In addition, the traditional investigations have only utilized a subject’s weight at a single point in time, which makes it difficult to adequately address bias associated with reverse causality.
Currently, the idea incorporating a subject’s weight history has been proposed to deal with the concern of reverse causality, but the existing works had been based on a subject’s recall or self-reported data, which may lead to misclassification and, therefore, result in overestimating the risk of mortality.
To help assess the relevance of being overweight or obese to the risk of death in the general population, we conducted a prospective study, using an individuals’ maximum BMI before the beginning of survival follow-up instead of their weight status at a single point in time, using data from the Framingham Heart Study (FHS).
We observed increasing risk of mortality across various BMI categories (overweight < obese I < obese II) relative to normal weight using maximum BMI over 24 years of weight history.