- Peacock, Janet L;
- Coto, Susana Diaz;
- Rees, Judy R;
- Sauzet, Odile;
- Jensen, Elizabeth T;
- Fichorova, Raina;
- Dunlop, Anne L;
- Paneth, Nigel;
- Padula, Amy;
- Woodruff, Tracey;
- Morello-Frosch, Rachel;
- Trowbridge, Jessica;
- Goin, Dana;
- Maldonado, Luis E;
- Niu, Zhongzheng;
- Ghassabian, Akhgar;
- Transande, Leonardo;
- Ferrara, Assiamira;
- Croen, Lisa A;
- Alexeeff, Stacey;
- Breton, Carrie;
- Litonjua, Augusto;
- O’Connor, Thomas G;
- Lyall, Kristen;
- Volk, Heather;
- Alshawabkeh, Akram;
- Manjourides, Justin;
- Camargo, Carlos A;
- Dabelea, Dana;
- Hockett, Christine W;
- Bendixsen, Casper G;
- Hertz-Picciotto, Irva;
- Schmidt, Rebecca J;
- Hipwell, Alison E;
- Keenan, Kate;
- Karr, Catherine;
- LeWinn, Kaja Z;
- Lester, Barry;
- Camerota, Marie;
- Ganiban, Jody;
- McEvoy, Cynthia;
- Elliott, Michael R;
- Sathyanarayana, Sheela;
- Ji, Nan;
- Braun, Joseph M;
- Karagas, Margaret R
Background
A major challenge in epidemiology is knowing when an exposure effect is large enough to be clinically important, in particular how to interpret a difference in mean outcome in unexposed/exposed groups. Where it can be calculated, the proportion/percentage beyond a suitable cut-point is useful in defining individuals at high risk to give a more meaningful outcome. In this simulation study we compute differences in outcome means and proportions that arise from hypothetical small effects in vulnerable sub-populations.Methods
Data from over 28,000 mother/child pairs belonging to the Environmental influences on Child Health Outcomes Program were used to examine the impact of hypothetical environmental exposures on mean birthweight, and low birthweight (LBW) (birthweight < 2500g). We computed mean birthweight in unexposed/exposed groups by sociodemographic categories (maternal education, health insurance, race, ethnicity) using a range of hypothetical exposure effect sizes. We compared the difference in mean birthweight and the percentage LBW, calculated using a distributional approach.Results
When the hypothetical mean exposure effect was fixed (at 50, 125, 167 or 250g), the absolute difference in % LBW (risk difference) was not constant but varied by socioeconomic categories. The risk differences were greater in sub-populations with the highest baseline percentages LBW: ranging from 3.1-5.3 percentage points for exposure effect of 125g. Similar patterns were seen for other mean exposure sizes simulated.Conclusions
Vulnerable sub-populations with greater baseline percentages at high risk fare worse when exposed to a small insult compared to the general population. This illustrates another facet of health disparity in vulnerable individuals.