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?
Exposure: air pollution
Outcome: small for gestational age and preterm birth à chronic disease later in life
Lifecourse model: Critical period
Babies exposed to air pollution in utero are more likely to be born pre-term and be small for gestational size. This irreversible intermediate outcome predisposes them to chronic disease later in life, most closely aligned to the critical period hypothesis (Mishra). This model assumes Y111 = Y101 = Y110= Y100= Y1**, and Y011= Y001= Y010 = Y000= Y0**; corresponding to an average change over this critical period time = Y1** - Y0**. A linear regression model corresponding to the early critical period is: E(Y) = a + B1S1.
I am not aware of any datasets that include air pollution exposure during gestation and later life outcomes (probably ethical issues). I think we can probably conduct natural experiments in heavily polluted cities or areas that experienced periods of heavy/reduction of pollution. I think the biggest obstacle in my ‘dataset’ is exposure assessment.