Association between consumption of ultra-processed foods and all cause mortality: SUN prospective cohort study

The prospective cohort study by Rico-Campà et al addresses an important question on the risk of ultra processed foods (UPF) and all cause mortality1. The authors correctly state that the study could be subject to residual confounding as a number of confounders could not be controlled for. However, another important limitation of the study with respect to confounding is lack of control for time varying confounders which can affect previous exposure2,3.

In this study body mass index (BMI) was only measured at baseline but in reality a subject’s BMI can change over time which can affect that subject’s use of UPFs. For example, intake of UPFs can lead to a high BMI but later if that subject’s BMI is lowered (secondary to a weight loss diet) it can affect UPF use (the person might stop UPFs or take a smaller amount). Here BMI acts as a classic case of a time varying confounder affected by previous exposure3. Proper assessment of time varying confounders requires use of nuanced methods in causal inference that can account for the time varying nature of these variables2,3,4. We hope that future studies that examine the effect of certain diets and their relation to morbidity or mortality can appropriately control for time varying confounders.

References:
1. Rico-Campà A, Martínez-González MA, Alvarez-Alvarez I, Mendonça RD, de la Fuente-Arrillaga C, Gómez-Donoso C, Bes-Rastrollo M. Association between consumption of ultra-processed foods and all cause mortality: SUN prospective cohort study. BMJ. 2019;365:l1949.

2. Mansournia MA, Altman DG. Inverse probability weighting BMJ 2016; 352:i189.

3. Mansournia MA, Etminan M, Danaei G, et al. Handling time varying confounding in observational research. BMJ 2017;359:j4587.

4. Mansournia MA, Naimi AI, Greenland S. The implications of using lagged and baseline exposure terms in the longitudinal-causal and regression models. Am J Epidemiol 2019 1;188(4):753-759.