Do small effects matter more in vulnerable populations? an investigation using Environmental influences on Child Health Outcomes (ECHO) cohorts

doi:10.1186/s12889-024-20075-x

. 2024 Sep 28;24(1):2655.

doi: 10.1186/s12889-024-20075-x.

Do small effects matter more in vulnerable populations? an investigation using Environmental influences on Child Health Outcomes (ECHO) cohorts

Janet L Peacock¹, Susana Diaz Coto², Judy R Rees², Odile Sauzet³, Elizabeth T Jensen⁴, Raina Fichorova⁵, Anne L Dunlop⁶, Nigel Paneth⁷, Amy Padula⁸, Tracey Woodruff⁸, Rachel Morello-Frosch⁹, Jessica Trowbridge⁸, Dana Goin¹⁰, Luis E Maldonado¹¹, Zhongzheng Niu¹¹, Akhgar Ghassabian¹², Leonardo Transande¹³, Assiamira Ferrara¹⁴, Lisa A Croen¹⁴, Stacey Alexeeff¹⁴, Carrie Breton¹¹, Augusto Litonjua¹⁵, Thomas G O'Connor¹⁵, Kristen Lyall¹⁶, Heather Volk¹⁷, Akram Alshawabkeh¹⁸, Justin Manjourides¹⁸, Carlos A Camargo Jr¹⁹, Dana Dabelea²⁰, Christine W Hockett^{21

22}, Casper G Bendixsen²³, Irva Hertz-Picciotto²⁴, Rebecca J Schmidt²⁴, Alison E Hipwell²⁵, Kate Keenan²⁶, Catherine Karr²⁷, Kaja Z LeWinn²⁸, Barry Lester²⁹, Marie Camerota²⁹, Jody Ganiban³⁰, Cynthia McEvoy³¹, Michael R Elliott³², Sheela Sathyanarayana^{33

34

35}, Nan Ji¹¹, Joseph M Braun³⁶, Margaret R Karagas²; Program Collaborators for Environmental influences on Child Health Outcomes

Collaborators, Affiliations

Collaborators

Program Collaborators for Environmental influences on Child Health Outcomes:
P B Smith, L K Newby, L P Jacobson, D J Catellier, R Gershon, D Cella, J Cordero, J Meeker, L Gatzke-Kopp, M Swingler, J M Mansbach, J M Spergel, M E Samuels-Kalow, M D Stevenson, C S Bauer, D Koinis Mitchell, S Deoni, V D 'Sa, C S Duarte, C Monk, J Posner, G Canino, A J Elliott, J Gern, R Miller, E Zoratti, C Seroogy, D Jackson, L Bacharier, M Kattan, R Wood, K Rivera-Spoljaric, G Hershey, T Hartert, C Johnson, D Ownby, A Singh, T Bastain, S Farzan, R Habre, F Tylavsky, A Mason, Q Zhao, N Bush, K Z LeWinn, B Carter, S Pastyrnak, C Neal, L Smith, J Helderman, L Leve, J Neiderhiser, S T Weiss, G O Connor, R Zeiger, R Tepper, R Landa, S Ozonoff, S Dager, R Schultz, J Piven, H Simhan, C Buss, P Wadhwa, K Huff, R K Miller, E Oken, J M Kerver, C Barone, C Fussman, M Elliott, D Ruden, J Herbstman, S Schantz, J Stanford, C Porucznik, A Giardino, R J Wright, M Bosquet-Enlow, K Huddleston, R Nguyen, E Barrett, S Swan, F Perera

Affiliations

¹ Department of Epidemiology, Geisel School of Medicine at Dartmouth, Dartmouth College, Hanover, NH, 03756, USA. janet.l.peacock@dartmouth.edu.
² Department of Epidemiology, Geisel School of Medicine at Dartmouth, Dartmouth College, Hanover, NH, 03756, USA.
³ Bielefeld School of Public Health and Department of Economy and Business Administration, Bielefeld University, Bielefeld, Germany.
⁴ Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC, USA.
⁵ Department of Gynecology and Reproductive Biology, Brigham and Women's Hospital, Boston, MA, USA.
⁶ Emory University School of Medicine, Atlanta, GA, USA.
⁷ Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, MI, USA.
⁸ Department of Reproductive Sciences, School of Medicine, University of California San Francisco, San Francisco, CA, USA.
⁹ Department of Environmental Health Sciences, University of California, Berkeley, CA, USA.
¹⁰ Children's Environmental Health Center, University of Illinois, Urbana, IL, USA.
¹¹ Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
¹² Harvard TH Chan School of Public Health, Harvard University, Boston, MA, USA.
¹³ Department of Pediatrics, NYU Grossman School of Medicine, New York, NY, USA.
¹⁴ Kaiser Permanente Northern California Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA.
¹⁵ University of Rochester Medical Center, Rochester, NY, USA.
¹⁶ AJ Drexel Autism Institute, Drexel University, Philadelphia, PA, USA.
¹⁷ Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
¹⁸ Department of Civil and Environmental Engineering, Northeastern University, Boston, MA, USA.
¹⁹ Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA, USA.
²⁰ Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
²¹ Avera Research Institute, Sioux Falls, SD, USA.
²² Department of Pediatrics, University of South Dakota School of Medicine, Sioux Falls, SD, USA.
²³ National Farm Medicine Center, Marshfield Clinic Research Institute, Marshfield, WI, USA.
²⁴ Department of Public Health Sciences, School of Medicine, The MIND Institute, University of California Davis, Davis, CA, USA.
²⁵ Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.
²⁶ University of Chicago, Chicago, IL, USA.
²⁷ Department of Pediatrics, University of Washington, Seatle, WA, USA.
²⁸ Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA.
²⁹ Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, Brown University, Providence, RI, USA.
³⁰ George Washington University, Washington, DC, USA.
³¹ Department of Pediatrics, School of Medicine, Oregan Health and Science University, Portland, OR, USA.
³² University of Michigan School of Public Health and Institute for Social Research, University of Michigan, Ann Arbor, MI, USA.
³³ Department of Pediatrics, Center for Child Health, Behavior, and Development, Seattle Children's Research Institute, Seattle, WA, USA.
³⁴ Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington, Seattle, WA, USA.
³⁵ Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA.
³⁶ Warren Alpert Medical School of Brown University, Brown University, Providence, RI, USA.

PMID: 39342237
PMCID: PMC11438038
DOI: 10.1186/s12889-024-20075-x

Do small effects matter more in vulnerable populations? an investigation using Environmental influences on Child Health Outcomes (ECHO) cohorts

Janet L Peacock et al. BMC Public Health. 2024.

. 2024 Sep 28;24(1):2655.

doi: 10.1186/s12889-024-20075-x.

Authors

Collaborators

Program Collaborators for Environmental influences on Child Health Outcomes:
P B Smith, L K Newby, L P Jacobson, D J Catellier, R Gershon, D Cella, J Cordero, J Meeker, L Gatzke-Kopp, M Swingler, J M Mansbach, J M Spergel, M E Samuels-Kalow, M D Stevenson, C S Bauer, D Koinis Mitchell, S Deoni, V D 'Sa, C S Duarte, C Monk, J Posner, G Canino, A J Elliott, J Gern, R Miller, E Zoratti, C Seroogy, D Jackson, L Bacharier, M Kattan, R Wood, K Rivera-Spoljaric, G Hershey, T Hartert, C Johnson, D Ownby, A Singh, T Bastain, S Farzan, R Habre, F Tylavsky, A Mason, Q Zhao, N Bush, K Z LeWinn, B Carter, S Pastyrnak, C Neal, L Smith, J Helderman, L Leve, J Neiderhiser, S T Weiss, G O Connor, R Zeiger, R Tepper, R Landa, S Ozonoff, S Dager, R Schultz, J Piven, H Simhan, C Buss, P Wadhwa, K Huff, R K Miller, E Oken, J M Kerver, C Barone, C Fussman, M Elliott, D Ruden, J Herbstman, S Schantz, J Stanford, C Porucznik, A Giardino, R J Wright, M Bosquet-Enlow, K Huddleston, R Nguyen, E Barrett, S Swan, F Perera

Affiliations

¹ Department of Epidemiology, Geisel School of Medicine at Dartmouth, Dartmouth College, Hanover, NH, 03756, USA. janet.l.peacock@dartmouth.edu.
² Department of Epidemiology, Geisel School of Medicine at Dartmouth, Dartmouth College, Hanover, NH, 03756, USA.
³ Bielefeld School of Public Health and Department of Economy and Business Administration, Bielefeld University, Bielefeld, Germany.
⁴ Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC, USA.
⁵ Department of Gynecology and Reproductive Biology, Brigham and Women's Hospital, Boston, MA, USA.
⁶ Emory University School of Medicine, Atlanta, GA, USA.
⁷ Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, MI, USA.
⁸ Department of Reproductive Sciences, School of Medicine, University of California San Francisco, San Francisco, CA, USA.
⁹ Department of Environmental Health Sciences, University of California, Berkeley, CA, USA.
¹⁰ Children's Environmental Health Center, University of Illinois, Urbana, IL, USA.
¹¹ Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
¹² Harvard TH Chan School of Public Health, Harvard University, Boston, MA, USA.
¹³ Department of Pediatrics, NYU Grossman School of Medicine, New York, NY, USA.
¹⁴ Kaiser Permanente Northern California Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA.
¹⁵ University of Rochester Medical Center, Rochester, NY, USA.
¹⁶ AJ Drexel Autism Institute, Drexel University, Philadelphia, PA, USA.
¹⁷ Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
¹⁸ Department of Civil and Environmental Engineering, Northeastern University, Boston, MA, USA.
¹⁹ Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA, USA.
²⁰ Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
²¹ Avera Research Institute, Sioux Falls, SD, USA.
²² Department of Pediatrics, University of South Dakota School of Medicine, Sioux Falls, SD, USA.
²³ National Farm Medicine Center, Marshfield Clinic Research Institute, Marshfield, WI, USA.
²⁴ Department of Public Health Sciences, School of Medicine, The MIND Institute, University of California Davis, Davis, CA, USA.
²⁵ Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.
²⁶ University of Chicago, Chicago, IL, USA.
²⁷ Department of Pediatrics, University of Washington, Seatle, WA, USA.
²⁸ Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA.
²⁹ Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, Brown University, Providence, RI, USA.
³⁰ George Washington University, Washington, DC, USA.
³¹ Department of Pediatrics, School of Medicine, Oregan Health and Science University, Portland, OR, USA.
³² University of Michigan School of Public Health and Institute for Social Research, University of Michigan, Ann Arbor, MI, USA.
³³ Department of Pediatrics, Center for Child Health, Behavior, and Development, Seattle Children's Research Institute, Seattle, WA, USA.
³⁴ Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington, Seattle, WA, USA.
³⁵ Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA.
³⁶ Warren Alpert Medical School of Brown University, Brown University, Providence, RI, USA.

PMID: 39342237
PMCID: PMC11438038
DOI: 10.1186/s12889-024-20075-x

Abstract

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.

Keywords: Child health outcome; Environmental exposure; Health disparities; Pregnancy outcomes; Social determinants of health.

PubMed Disclaimer

Conflict of interest statement

The authors declare no competing interests.

Figures

**Fig. 1**
Illustration of the impact of a small effect, 0.25 standard deviations, in general populations compared with vulnerable populations showing that the same decrease in mean value has a greater impact in vulnerable populations. The hypothetical distributions are standard Normal with means in the unexposed distribution of 0 (general population) and -1 (vulnerable population), and standard deviation 1. High risk is defined as below 5th centile (< -1.645)

**Fig. 2**
Modeled percentage of low birthweight (LBW) in unexposed and exposed populations by social factors associated with a change in mean birthweight of 50g (N = 28,496)

**Fig. 3**
Modeled percentage of low birthweight (LBW) in unexposed and exposed populations by social factors associated with a change in mean birthweight of 125g (N = 28,496)

**Fig. 4**
Modeled percentage of low birthweight (LBW) in unexposed and exposed populations by social factors associated with a change in mean birthweight of 167g (N = 28,496)

**Fig. 5**
Modeled percentage of low birthweight (LBW) in unexposed and exposed populations by social factors associated with a change in mean birthweight of 250g (N = 28,496)

**Fig. 6**
Summarizing the effects on low birthweight by the subgroup mean birthweight by the shift in the mean. 21 sub-populations

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References

1. Cohen J. Statistical power analysis for the behavioral sciences. 2nd ed. Hillsdale, N.J.: L. Erlbaum Associates; 1988.
1. Greenland S, Senn SJ, Rothman KJ, et al. Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations. Eur J Epidemiol. 2016;31(4):337–50. 10.1007/s10654-016-0149-3. - PMC - PubMed
1. Organisation WH. Low birth weight. https://www.who.int/data/nutrition/nlis/info/low-birth-weight. Accessed 21 Sept 2024.
1. Peacock JL, Sauzet O, Ewings SM, Kerry SM. Dichotomising continuous data while retaining statistical power using a distributional approach. Stat Med. 2012;31(26):3089–103. 10.1002/sim.5354. - PubMed
1. Sauzet O, Ofuya M, Peacock JL. Dichotomisation using a distributional approach when the outcome is skewed. BMC Med Res Methodol. 2015;15:40. 10.1186/s12874-015-0028-8. - PMC - PubMed

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[1] Cohen J. Statistical power analysis for the behavioral sciences. 2nd ed. Hillsdale, N.J.: L. Erlbaum Associates; 1988.

[2] Cohen J. Statistical power analysis for the behavioral sciences. 2nd ed. Hillsdale, N.J.: L. Erlbaum Associates; 1988.

[3] Greenland S, Senn SJ, Rothman KJ, et al. Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations. Eur J Epidemiol. 2016;31(4):337–50. 10.1007/s10654-016-0149-3. - PMC - PubMed

[4] Greenland S, Senn SJ, Rothman KJ, et al. Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations. Eur J Epidemiol. 2016;31(4):337–50. 10.1007/s10654-016-0149-3. - PMC - PubMed

[5] Organisation WH. Low birth weight. https://www.who.int/data/nutrition/nlis/info/low-birth-weight. Accessed 21 Sept 2024.

[6] Organisation WH. Low birth weight. https://www.who.int/data/nutrition/nlis/info/low-birth-weight. Accessed 21 Sept 2024.

[7] Peacock JL, Sauzet O, Ewings SM, Kerry SM. Dichotomising continuous data while retaining statistical power using a distributional approach. Stat Med. 2012;31(26):3089–103. 10.1002/sim.5354. - PubMed

[8] Peacock JL, Sauzet O, Ewings SM, Kerry SM. Dichotomising continuous data while retaining statistical power using a distributional approach. Stat Med. 2012;31(26):3089–103. 10.1002/sim.5354. - PubMed

[9] Sauzet O, Ofuya M, Peacock JL. Dichotomisation using a distributional approach when the outcome is skewed. BMC Med Res Methodol. 2015;15:40. 10.1186/s12874-015-0028-8. - PMC - PubMed

[10] Sauzet O, Ofuya M, Peacock JL. Dichotomisation using a distributional approach when the outcome is skewed. BMC Med Res Methodol. 2015;15:40. 10.1186/s12874-015-0028-8. - PMC - PubMed

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Do small effects matter more in vulnerable populations? an investigation using Environmental influences on Child Health Outcomes (ECHO) cohorts

Collaborators

Affiliations

Do small effects matter more in vulnerable populations? an investigation using Environmental influences on Child Health Outcomes (ECHO) cohorts

Authors

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Affiliations

Abstract

Conflict of interest statement

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