Week 5

Week 5

by Luis Rodriguez -
Number of replies: 2

Assignment: For a specific exposure-outcome combination of interest to you, specify which lifecourse model is likely most appropriate and why you think this is the case. Describe the regression models you could use to test your hypothesis. Are there any possible data sets in which this test could be conducted, and if so, what concerns would you have about interpreting your proposed test of the lifecourse model?

I am interested in evaluating the effect of maternal and child dietary composition (refined carbohydrates and added sugars) on the development of non-alcoholic fatty liver disease during adolescence and early adulthood (<30 years). Some studies would favor the hypothesis of prenatal preprogramming in which the fetal environment (in this case maternal diet) interacts with fetal genetics and epigenetics to alter risk of chronic diseases. This hypothesis would favor the Critical Period Model in which exposure to high amounts of refined carbohydrates and sugars determines an individual’s risk of developing fatty liver later in life during adolescence and adulthood. However, multiple studies have shown that dietary modification during adolescence or early adulthood can reverse fatty liver, thus the accumulation model is likely most appropriate to test the causal effect of carbs and sugars on fatty liver.     

I could use a linear regression model with a lifetime diet score that takes the value between 0 and 5. Where 0 is always diet low in refined carbs and sugars, and 5 is always a diet high in refined carbs and sugars.

0 = maternal diet before pregnancy

1 = maternal diet during fetal development

2 = maternal diet during breastfeeding period, or presence of sucrose in infant formula

3 = diet during infancy

4 = diet during adolescence

5 = diet during adulthood

 E(Y) = alpha + B(Sum of Sj

B =change in the score; for every unit increase in this score, the change in mean liver fat attenuation is expected to be constant and equal to the change in lifetime accumulation.

 We could potentially use the Project Viva cohort out of Harvard. Project Viva enrolled 2,670 women during pregnancy and is following them and their children over time. The project was established to examine prenatal diet and other factors in relation to maternal and child health (Oken et al. International Journal of Epi, 2015). Diet exposures were ascertained and included pre-pregnancy, during pregnancy, and after birth. Even though liver fat attenuation was likely not measured in infancy, it could be measured during adolescence and early adulthood since data on teenagers are currently being collected.   

Concerns in interpreting my proposed test would include potentially lacking heterogeneity in the exposure due to having a high education sample with health insurance within the Boston area, and who were primarily white. Also, temporal changes of decreased sugar consumption from the year 2000 to 2010 may have brought down consumption of sugars to within tolerable levels to be able to measure cumulative effects on fatty liver attenuation. This exposure-outcome relationship is also susceptible to confounding, including the fact that a diet high in refined carbohydrates and sugars may be a marker of a general poor diet or a sedentary lifestyle. 

In reply to Luis Rodriguez

Re: Week 5

by Amy -

Hi Luis.

It makes sense to me that given the potential for changes in diet in adolescence and early childhood to modify the effects of prenatal programming on young adult fatty liver. However, based on the Mishra article, I would have expected that you would have used nested models that take into account both the critical period and effect modification hypotheses, rather than a lifetime score that sums a series of binary indicators over time. Maybe I'm just not understanding the model you propose?

 

Amy  

In reply to Luis Rodriguez

Re: Week 5

by Maria Glymour -

Interesting example Luis.  I agree with Amy's point though - given how you've proposed to code it, is there any value of beta that will tell you "this is an accumulation model" or "only adolescent exposures matter, infancy is not important", or "only infancy matters, adolescence is not important".  The exposure coding imposes a strong assumption about how the effects of each exposure category relate to one another. Do you really think such an assumption is justified a priori?