A Systematic Comparison of Designs to Study Human Fecundity
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A Systematic Comparison of Designs to Study Human Fecundity. / Eijkemans, Marinus J C; Leridon, Henri; Keiding, Niels; Slama, Rémy.
In: Epidemiology (Cambridge, Mass.), Vol. 30, 2019, p. 120-129.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - A Systematic Comparison of Designs to Study Human Fecundity
AU - Eijkemans, Marinus J C
AU - Leridon, Henri
AU - Keiding, Niels
AU - Slama, Rémy
PY - 2019
Y1 - 2019
N2 - BACKGROUND: Several epidemiologic designs allow studying fecundability, the monthly probability of pregnancy occurrence in non-contracepting couples in the general population. These designs may, to varying extents, suffer from attenuation bias and other biases. We aimed to compare the main designs: incident and prevalent cohorts, pregnancy-based, and current duration approaches.METHODS: A realistic simulation model produced individual reproductive lives of a fictitious population. We drew random population samples according to each study design, from which the cumulative probability of pregnancy was estimated. We compared the abilities of the designs to highlight the impact of an environmental factor influencing fecundability, relying on the Cox model with censoring after 12 or 6 months.RESULTS: Regarding the estimation of the cumulative probability of pregnancy, the pregnancy-based approach was the most prone to bias. When we considered a hypothetical factor associated with a hazard ratio (HR) of pregnancy of 0.7, the estimated HR was in the 0.78-0.85 range, according to designs. This attenuation bias was largest for the prevalent cohort and smallest for the current duration approach, which had the largest variance. The bias could be limited in all designs by censoring durations at 6 months.CONCLUSION: Attenuation bias in HRs cannot be ignored in fecundability studies. Focusing on the effect of exposures during the first 6 months of unprotected intercourse through censoring removes part of this bias. For risk factors that can accurately be assessed retrospectively, retrospective fecundity designs, although biased, are not much more strongly so than logistically more intensive designs entailing follow-up.
AB - BACKGROUND: Several epidemiologic designs allow studying fecundability, the monthly probability of pregnancy occurrence in non-contracepting couples in the general population. These designs may, to varying extents, suffer from attenuation bias and other biases. We aimed to compare the main designs: incident and prevalent cohorts, pregnancy-based, and current duration approaches.METHODS: A realistic simulation model produced individual reproductive lives of a fictitious population. We drew random population samples according to each study design, from which the cumulative probability of pregnancy was estimated. We compared the abilities of the designs to highlight the impact of an environmental factor influencing fecundability, relying on the Cox model with censoring after 12 or 6 months.RESULTS: Regarding the estimation of the cumulative probability of pregnancy, the pregnancy-based approach was the most prone to bias. When we considered a hypothetical factor associated with a hazard ratio (HR) of pregnancy of 0.7, the estimated HR was in the 0.78-0.85 range, according to designs. This attenuation bias was largest for the prevalent cohort and smallest for the current duration approach, which had the largest variance. The bias could be limited in all designs by censoring durations at 6 months.CONCLUSION: Attenuation bias in HRs cannot be ignored in fecundability studies. Focusing on the effect of exposures during the first 6 months of unprotected intercourse through censoring removes part of this bias. For risk factors that can accurately be assessed retrospectively, retrospective fecundity designs, although biased, are not much more strongly so than logistically more intensive designs entailing follow-up.
U2 - 10.1097/EDE.0000000000000916
DO - 10.1097/EDE.0000000000000916
M3 - Journal article
C2 - 30198936
VL - 30
SP - 120
EP - 129
JO - Epidemiology
JF - Epidemiology
SN - 1044-3983
ER -
ID: 208816132