TY - JOUR
T1 - Do small effects matter more in vulnerable populations? an investigation using Environmental influences on Child Health Outcomes (ECHO) cohorts
AU - on behalf of program collaborators for Environmental Influences on Child Health Outcomes
AU - Peacock, Janet L.
AU - Coto, Susana Diaz
AU - Rees, Judy R.
AU - Sauzet, Odile
AU - Jensen, Elizabeth T.
AU - Fichorova, Raina
AU - Dunlop, Anne L.
AU - Paneth, Nigel
AU - Padula, Amy
AU - Woodruff, Tracey
AU - Morello-Frosch, Rachel
AU - Trowbridge, Jessica
AU - Goin, Dana
AU - Maldonado, Luis E.
AU - Niu, Zhongzheng
AU - Ghassabian, Akhgar
AU - Transande, Leonardo
AU - Ferrara, Assiamira
AU - Croen, Lisa A.
AU - Alexeeff, Stacey
AU - Breton, Carrie
AU - Litonjua, Augusto
AU - O’Connor, Thomas G.
AU - Lyall, Kristen
AU - Volk, Heather
AU - Alshawabkeh, Akram
AU - Manjourides, Justin
AU - Camargo, Carlos A.
AU - Dabelea, Dana
AU - Hockett, Christine W.
AU - Bendixsen, Casper G.
AU - Hertz-Picciotto, Irva
AU - Schmidt, Rebecca J.
AU - Hipwell, Alison E.
AU - Keenan, Kate
AU - Karr, Catherine
AU - LeWinn, Kaja Z.
AU - Lester, Barry
AU - Camerota, Marie
AU - Ganiban, Jody
AU - McEvoy, Cynthia
AU - Elliott, Michael R.
AU - Sathyanarayana, Sheela
AU - Ji, Nan
AU - Braun, Joseph M.
AU - Karagas, Margaret R.
AU - Perera, F.
AU - Swan, S.
AU - Barrett, E.
AU - Herbstman, J.
N1 - Publisher Copyright:
© The Author(s) 2024.
PY - 2024/12
Y1 - 2024/12
N2 - 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.
AB - 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.
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U2 - 10.1186/s12889-024-20075-x
DO - 10.1186/s12889-024-20075-x
M3 - Article
C2 - 39342237
AN - SCOPUS:85205336209
SN - 1471-2458
VL - 24
JO - BMC Public Health
JF - BMC Public Health
IS - 1
M1 - 2655
ER -