Stefanie N Hinkle1, Emily M Mitchell1, Katherine L Grantz1, Aijun Ye2, Enrique F Schisterman1. 1. Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD. 2. Glotech, Inc, Rockville, MD.
Abstract
BACKGROUND: Studies examining total gestational weight gain (GWG) and outcomes associated with gestational age (GA) are potentially biased. The z-score has been proposed to mitigate this bias. We evaluated a regression-based adjustment for GA to remove the correlation between GWG and GA, and compared it to published weight-gain-for-gestational-age z-scores when applied to a study sample with different underlying population characteristics. METHODS: Using 65 643 singleton deliveries to normal weight women at 12 US clinical sites, we simulated a null association between GWG and neonatal mortality. Logistic regression was used to estimate approximate relative risks (RR) of neonatal mortality associated with GWG, unadjusted and adjusted for GA, and the z-score, overall and within study sites. Average RRs across 5000 replicates were calculated with 95% coverage probability to indicate model bias and precision, where 95% is nominal. RESULTS: Under a simulated null association, total GWG resulted in a biased mortality estimate (RR = 0.87; coverage = 0%); estimates adjusted for GA were unbiased (RR = 1.00; coverage = 94%). Quintile-specific RRs ranged from 0.97-1.03. Similar results were observed for site-specific analyses. The overall z-score RR was 0.97 (84% coverage) with quintile-specific RRs ranging from 0.64-0.90. Estimates were close to 1.0 at most sites, with coverage from 70-94%. Sites 1 and 6 were biased with RRs of 0.66 and 1.43, respectively, and coverage of 70% and 80%. CONCLUSIONS: Adjusting for GA achieves unbiased estimates of the association between total GWG and neonatal mortality, providing an accessible alternative to the weight-gain-for-gestational-age z-scores without requiring assumptions concerning underlying population characteristics.
BACKGROUND: Studies examining total gestational weight gain (GWG) and outcomes associated with gestational age (GA) are potentially biased. The z-score has been proposed to mitigate this bias. We evaluated a regression-based adjustment for GA to remove the correlation between GWG and GA, and compared it to published weight-gain-for-gestational-age z-scores when applied to a study sample with different underlying population characteristics. METHODS: Using 65 643 singleton deliveries to normal weight women at 12 US clinical sites, we simulated a null association between GWG and neonatal mortality. Logistic regression was used to estimate approximate relative risks (RR) of neonatal mortality associated with GWG, unadjusted and adjusted for GA, and the z-score, overall and within study sites. Average RRs across 5000 replicates were calculated with 95% coverage probability to indicate model bias and precision, where 95% is nominal. RESULTS: Under a simulated null association, total GWG resulted in a biased mortality estimate (RR = 0.87; coverage = 0%); estimates adjusted for GA were unbiased (RR = 1.00; coverage = 94%). Quintile-specific RRs ranged from 0.97-1.03. Similar results were observed for site-specific analyses. The overall z-score RR was 0.97 (84% coverage) with quintile-specific RRs ranging from 0.64-0.90. Estimates were close to 1.0 at most sites, with coverage from 70-94%. Sites 1 and 6 were biased with RRs of 0.66 and 1.43, respectively, and coverage of 70% and 80%. CONCLUSIONS: Adjusting for GA achieves unbiased estimates of the association between total GWG and neonatal mortality, providing an accessible alternative to the weight-gain-for-gestational-age z-scores without requiring assumptions concerning underlying population characteristics.
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