Abstract
STUDY QUESTION
To what extent does multiple birth mediate the association between fertility treatment and congenital anomalies?
SUMMARY ANSWER
Multiple birth explained only a modest proportion of the increased risk of congenital anomalies associated with fertility treatment, suggesting that most of the excess risk is independent of multiple birth.
WHAT IS KNOWN ALREADY
Fertility treatments have been associated with an increased risk of congenital anomalies. Because fertility treatment also increases the probability of multiple birth, it remains unclear whether the observed increase in congenital anomalies is attributable to treatment itself, multiple gestation, or underlying infertility.
STUDY DESIGN, SIZE, DURATION
Population-based cohort study of all live and stillbirths delivered ≥22 weeks’ gestation from 2006 to 2021 among women with a history of infertility diagnosis in Ontario, Canada.
PARTICIPANTS/MATERIALS, SETTING, METHODS
Data were obtained from administrative health records routinely collected within a universal healthcare system for epidemiological surveillance. Exposure was defined as (1) infertility without fertility treatment, (2) ovulation induction (OI) or IUI, and (3) IVF or ICSI. Congenital anomalies were categorized as (1) any anomaly, (2) organ system, and (3) specific anomalies. Modified Poisson regression models generated adjusted relative risks (aRR). For statistically significant aRR > 1, causal mediation was used to decompose the total effect into direct and mediated effects to estimate proportion mediated by multiple birth.
MAIN RESULTS AND THE ROLE OF CHANCE
There were 274 893 births included in the cohort, of which 229 932 (83.6%) occurred among women with infertility who did not receive fertility treatment, 20 525 (7.5%) after OI/IUI, and 24 536 (8.9%) after IVF/ICSI. Multiple birth rates were 2.3%, 7.2%, and 13.3%, respectively. Compared with infertility without treatment, the aRR of any anomaly was 1.11 (95% CI 1.05–1.17) after OI/IUI and 1.28 (95% CI 1.22–1.34) after IVF/ICSI. Mediation analyses demonstrated that multiple birth accounted for only a minority of the excess risk, although the proportion mediated varied by anomaly type. The greatest mediation was observed for pulmonary artery stenosis, where multiple birth explained 33.9% of the association after OI/IUI and 44.4% after IVF/ICSI.
LIMITATIONS, REASONS FOR CAUTION
As with all studies using administrative health data, our findings are subject to potential misclassification of infertility status based on billing codes, particularly when consultations do not reflect a confirmed diagnosis, as well as residual confounding from unmeasured factors.
WIDER IMPLICATIONS OF THE FINDINGS
This study suggests that multiple birth explains only part of the increased risk of congenital anomalies observed after fertility treatment. While continued efforts to decrease multiple pregnancy remain important, future research should focus on disentangling the contribution of specific infertility diagnoses and treatment-related factors to the risk of congenital anomalies.
FUNDING
This study was funded by grant MFM-146444 from the Canadian Institutes of Health Research Institute of Human Development, Child & Youth Health, Clinician—Investigator Teams in Obstetrics and Maternal-Fetal Medicine. Bailey Milne received funding for this project from the Queen’s University Dean’s Doctoral Award. This study was supported by ICES, which is funded by an annual grant from the Ontario Ministry of Health (MOH) and the Ministry of Long-Term Care (MLTC). This document used data adapted from the Statistics Canada Postal CodeOM Conversion File, which is based on data licensed from Canada Post Corporation, and/or data adapted from the Ontario Ministry of Health Postal Code Conversion File, which contains data copied under license from ©Canada Post Corporation and Statistics Canada. Parts of this material are based on data and/or information compiled and provided by CIHI, the Ontario Ministry of Health, and the Better Outcomes Registry & Network (‘BORN’), part of the Children’s Hospital of Eastern Ontario. The analyses, conclusions, opinions and statements expressed herein are solely those of the authors and do not reflect those of the funding or data sources; no endorsement is intended or should be inferred.
DISCLOSURES
The authors have nothing to disclose.
TRIAL REGISTRATION NUMBER
N/A.
Keywords: infertility, assisted reproductive technologies, multiple birth, congenital anomalies, mediation analysis
Introduction
Congenital anomalies are a major contributor to infant morbidity and mortality and impose long-term burdens on families and health systems (World Health Organization, 2023). Fertility treatment has been associated with a higher risk of congenital anomalies (Hwang et al., 2018; Luke et al., 2021, 2022). However, most studies have compared births after fertility treatment with births among women without infertility, which may result in confounding by underlying infertility (Velez and Ray, 2026). Emerging evidence suggests that infertility itself, independent of treatment, may be associated with adverse pregnancy outcomes (Richmond et al., 2022; Velez et al., 2022; Wang et al., 2022).
Fertility treatment also substantially increases the likelihood of multiple birth (Velez et al., 2014, 2024c), and multiple births are at an increased risk of congenital anomalies compared to singleton births (Glinianaia et al., 2008; Bateni et al., 2016; Esposito et al., 2024; Shin et al., 2024). Therefore, the observed associations between fertility treatment and congenital anomalies may reflect both a direct association with treatment and an indirect association mediated through multiple birth. Previous studies have often excluded multiple births or adjusted for plurality as a covariate, approaches that may attenuate the estimated association between fertility treatment and congenital anomalies (Terho et al., 2022; Henningsen et al., 2023).
The extent to which multiple birth mediates the association between fertility treatment and congenital anomalies remains unclear. Therefore, we used a large population-based cohort within a universal healthcare system to quantify the mediating effect of multiple birth on the association between fertility treatment and congenital anomalies, using births among women with infertility who did not receive fertility treatment as the reference group.
Materials and methods
Study design and data sources
This population-based cohort study used administrative health data and registries from the province of Ontario, Canada held at ICES. ICES is an independent, non-profit research institute with designation under the Ontario Personal Health Information Protection Act to collect and analyze healthcare data for Ontario residents, without consent, for health system research (ICES, 2021). ICES maintains validated datasets that have a unique maternal-infant matching number to link mother-infant pairs and capture information on pregnancy and pregnancy outcomes. These databases house mandatory submissions from hospital and healthcare visits using billing codes for physician and hospital reimbursement.
The cohort included all live births and stillbirths at ≥22 weeks’ gestation from 2006 to 2021 among women aged 15–50 years with a history of infertility. Pregnancy and infant characteristics were obtained from the Better Outcomes Registry & Network (BORN) Ontario, which captures births at or greater than 20 weeks’ gestation; however, only births ≥22 weeks were included in our cohort. A birth refers to the complete expulsion or extraction of one or more fetuses ≥ 22 weeks gestation (Zegers-Hochschild et al., 2026). Maternal demographics, and pre-existing health conditions were obtained through linkage of ambulatory and hospital databases; the data sources and variables used are described in Supplementary Table S1. Mother–infant pairs with less than 5 years of eligibility in Ontario Health Insurance Program (OHIP) eligibility before pregnancy were excluded to minimize under-ascertainment of infertility diagnoses and healthcare utilization. Births resulting from gestational carriage were excluded, as they represent a distinct clinical context involving embryos genetically related to the intended parent(s) (Velez et al., 2024b, 2025).
The study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting based on EQUATOR guidelines (Vandenbroucke et al., 2007).
Exposure variables
Exposure was categorized as (1) infertility without fertility treatment, defined as physician consultation(s) for infertility within 2 years before pregnancy (OHIP ICD-9 628), and no record of fertility treatment, (2) ovulation induction (OI) or IUI, and (3) IVF or ICSI, consistent with previous population-based studies (Dayan et al., 2022; Fine et al., 2022; Richmond et al., 2022; Wang et al., 2022; Velez et al., 2023, 2024a). Information on treatment characteristics, including fresh versus frozen embryo transfer, cleavage versus blastocyst-stage transfer, assisted hatching, and preimplantation genetic testing was not available in the study datasets.
Outcomes
Congenital anomalies were identified from the Canadian Institute of Health Information’s infant Discharge Abstract Database (DAD) using ICD-10 codes within the first year of life: Q000-Q999 and were classified using the Metropolitan Atlanta Congenital Defects Program algorithm, a surveillance system of the US Center for Disease Control and Prevention established in 1967 (Correa-Villaseñor et al., 2003). The DAD collects information on obstetrics, newborns and stillbirths from all acute inpatient hospitals in Ontario. Newborn and childhood anomaly diagnoses in acute hospitals are recorded and classified according to the 10th International Statistical Classification of Diseases and Related Health Problems, Canadian Adaptation (Canadian Institute for Health Information, 2016, 2018). The following outcome categories were modeled: (1) any anomaly, (2) organ system anomalies, and (3) specific anomalies as in prior ICES studies (Nelson et al., 2016; Brogly et al., 2017; Bowie et al., 2022).
Covariates
We adjusted for possible confounders of the association between fertility treatment and risk of congenital anomalies, including maternal age at delivery, income quintile, pre-existing diabetes, chronic hypertension, smoking, alcohol use, substance use disorder, rurality, obesity, and year of birth (codes provided in Supplementary Table S1 and expanded justification in Supplementary Table S2) (American Society for Reproductive Medicine, 2006; Luo et al., 2006; Hackshaw et al., 2011; Correa and Marcinkevage, 2013; Mavrogenis et al., 2014; Fan et al., 2017; Harris et al., 2017; de Angelis et al., 2020; Lorzadeh et al., 2020; Mattsson et al., 2021; Benavides et al., 2022; Bowie et al., 2022; Evans et al., 2022; Gautam et al., 2023; Imrie et al., 2023; Pethő et al., 2023; Scott and Sher, 2023; Dhage et al., 2024; Hedermann et al., 2024).
Statistical analysis
Patient characteristics were compared by exposure group using χ2 and ANOVA. Relative risks (RR) were derived using modified Poisson regression models with robust error variance to account for more than one birth by the same mother during the study period (Zou, 2004).
Causal mediation analysis
A causal mediation analysis was performed to estimate the mediating role of multiple birth on the association between fertility treatments and congenital anomalies. Only associations with a statistically significant increased risk between exposure and outcomes were modeled in mediation analysis. Causal mediation is based on the counterfactual framework and delineates the association between fertility treatment and risk of congenital anomalies (total effect), into the direct effect of fertility treatment on risk of anomalies and the indirect effect due to multiple birth (VanderWeele, 2015, 2016). The estimated proportion of the total effect mediated by multiple birth was reported.
Sensitivity analysis
We conducted a quantitative bias analysis using the E-value to assess potential unmeasured confounding. The E-value represents the minimum strength of association that an unmeasured confounder would need to have with both the exposure and the outcome, conditional on the measured covariates, to fully explain away the observed association (VanderWeele and Ding, 2017).
Ethical approval
The study was approved by the Queen’s Health Sciences and Affiliated Teaching Hospitals Research Ethics Board.
Results
There were 274 893 births included in the cohort (Fig. 1). Of these, 229 932 (83.6%) were among women with infertility who did not use fertility treatment, 20 525 (7.5%) after OI/IUI, and 24 536 (8.9%) after IVF/ICSI (Table 1). Compared with women with infertility who did not use fertility treatment, those who underwent fertility treatment were more likely to be older, nulliparous, and reside in higher income and urban areas. Women with infertility who did not use fertility treatment had higher rates of obesity and pre-existing diabetes than those who underwent IVF/ICSI, although the highest prevalence of both conditions was observed among those who underwent OI/IUI. Rates of pre-existing hypertension were similar among groups.
Figure 1.
Cohort creation flowchart. OHIP, Ontario Health Insurance Plan; ID, identifier.
Table 1.
Characteristics of all infants born in Ontario, 2006–2021, according to exposure group.
| Characteristic | Infertility without fertility treatment |
Ovulation induction or IUI |
IVF or ICSI |
P value | |||
|---|---|---|---|---|---|---|---|
| All births (n = 229 932) | Multiple births (n = 5211 2.3%) | All births (n = 20 525) | Multiple births (n = 1472, 7.2%) | All births (n = 24,536) | Multiple births (n = 2984, 13.3%) | ||
| Maternal age, y (mean ± SD) | 33.9 (4.5) | 34.6 (4.5) | 33.4 (4.4) | 33.6 (4.1) | 36.0 (4.6) | 35.5 (4.6) | <0.001 |
| 1—lowest | 36 617 (15.9) | 670 (12.8) | 2452 (11.9) | 153 (10.3) | 2375 (9.7) | 313 (9.5) | <0.001 |
| 2 | 41 103 (17.9) | 801 (15.3) | 3530 (17.2) | 251 (16.9) | 3813 (15.5) | 490 (14.9) | |
| 3 | 49 024 (21.3) | 1016 (19.4) | 4533 (22.0) | 293 (19.7) | 5236 (21.3) | 695 (21.3) | |
| 4 | 55 190 (24.0) | 1410 (27.0) | 5443 (26.5) | 447 (30.1) | 6581 (26.8) | 926 (28.2) | |
| 5—highest | 48 091 (20.9) | 1329 (25.4) | 4604 (22.4) | 340 (22.9) | 6565 (26.2) | 861 (26.2) | |
| Urban residence | 217 344 (94.5) | 4992 (95.5) | 19 341 (94.1) | 1428 (96.2) | 23 538 (95.8) | 3166 (96.4) | <0.001 |
| Parous | 145 409 (63.2) | 2389 (45.7) | 7543 (36.7) | 541 (36.5) | 8356 (34.0) | 955 (29.1) | <0.001 |
| Obese | 55 371 (24.1) | 969 (18.5) | 6324 (30.8) | 296 (19.9) | 5237 (21.3) | 502 (15.3) | <0.001 |
| Pre-existing diabetes | 4776 (2.1) | 119 (2.3) | 475 (2.3) | 47 (3.2) | 378 (1.5) | 65 (2.0) | <0.001 |
| Chronic hypertension | 3346 (1.5) | 81 (1.5) | 324 (1.6) | 20 (1.3) | 395 (1.6) | 33 (1.0) | <0.001 |
| Drug use including smoking, alcohol or other substances during pregnancy | 2645 (1.1) | 6 (0.1) | 214 (1.0) | ** | 199 (0.9) | ** | <0.001 |
Small cells <5.
P-values were obtained using ANOVA and chi-square tests.
Main analysis
The rate of congenital anomalies was 5.9% among births to women with infertility who did not use fertility treatment, 6.7% following OI/IUI, and 7.6% following IVF/ICSI. Multiple birth rates were 2.3%, 7.2%, and 13.3%, respectively.
Among births following OI/IUI, the risk of any congenital anomaly was higher than among births to women with infertility who did not use fertility treatment (adjusted relative risk [aRR] 1.11; 95% CI 1.05–1.17) (Table 2). Increased risks were also observed for CNS (aRR 1.39; 95% CI 1.07–1.80) and respiratory system anomalies (aRR 1.53, 95% CI 1.07–2.17). At the level of specific anomalies, increased risks were observed for atrial septal defects (aRR 1.24; 95% CI 1.06–1.45), pulmonary artery stenosis (aRR 1.56, 95% CI 1.06–2.29), and unspecified hypospadias (aRR 1.51; 95% CI 1.11–2.05) (Table 3).
Table 2.
Relative risk of any congenital anomaly and organ system anomalies for births following fertility treatment compared to infertility without treatment.
| Congenital anomaly | Exposure | N of all infants with anomalies/N at risk | Unadjusted RR (95% CI) | Adjusted RR (95% CI) * |
|---|---|---|---|---|
| Any anomaly | Infertility without treatment | 13 478/229 832 | Referent | Referent |
| Ovulation induction or IUI | 1365/20 525 | 1.13 (1.07–1.20) | 1.11 (1.05–1.17) | |
| IVF or ICSI | 1873/24 536 | 1.30 (1.24–1.36) | 1.28 (1.22–1.34) | |
| Cardiovascular | Infertility without treatment | 2830/229 832 | Referent | Referent |
| Ovulation induction or IUI | 281/20 525 | 1.11 (0.98–1.25) | 1.12 (0.99–1.27) | |
| IVF or ICSI | 392/24 536 | 1.29 (1.16–1.44) | 1.31 (1.17–1.45) | |
| Cleft | Infertility without treatment | 320/229 832 | Referent | Referent |
| Ovulation induction or IUI | 29/20 525 | 1.01 (0.69–1.48) | 1.01 (0.69–1.48) | |
| IVF or ICSI | 23/24 536 | 0.67 (0.44–1.06) | 0.69 (0.45–1.05) | |
| Central nervous system | Infertility without treatment | 571/229 832 | Referent | Referent |
| Ovulation induction or IUI | 70/20 525 | 1.37 (1.06–1.77) | 1.39 (1.07–1.80) | |
| IVF or ICSI | 102/24 536 | 1.67 (1.35–2.07) | 1.67 (1.35–2.08) | |
| Eye | Infertility without treatment | 177/229 832 | Referent | Referent |
| Ovulation induction or IUI | 13/20 525 | 0.82 (0.45–1.44) | 0.82 (0.47–1.44) | |
| IVF or ICSI | 21/24 536 | 1.11 (0.70–1.75) | 1.11 (0.70–1.75) | |
| Ear, face and neck | Infertility without treatment | 321/229 832 | Referent | Referent |
| Ovulation induction or IUI | 40/20 525 | 1.40 (1.01–1.94) | 1.35 (0.97–1.88) | |
| IVF or ICSI | 40/24 536 | 1.17 (0.83–1.63) | 1.14 (0.82–1.60) | |
| Gastrointestinal | Infertility without treatment | 3510/229 832 | Referent | Referent |
| Ovulation induction or IUI | 336/20 525 | 1.07 (0.96–1.19) | 1.03 (0.92–1.15) | |
| IVF or ICSI | 438/24 536 | 1.17 (1.06–1.29) | 1.14 (1.03–1.26) | |
| Genital | Infertility without treatment | 1333/229 832 | Referent | Referent |
| Ovulation induction or IUI | 125/20 525 | 1.05 (0.88–1.26) | 1.03 (0.86–1.24) | |
| IVF or ICSI | 211/24 536 | 1.48 (1.28–1.72) | 1.46 (1.26–1.69) | |
| Musculoskeletal | Infertility without treatment | 1883/229 832 | Referent | Referent |
| Ovulation induction or IUI | 186/20 525 | 1.10 (0.95–1.28) | 1.10 (0.94–1.28) | |
| IVF or ICSI | 284/24 536 | 1.41 (1.25–1.60) | 1.44 (1.27–1.63) | |
| Neoplasms and tumors | Infertility without treatment | 466/229 832 | Referent | Referent |
| Ovulation induction or IUI | 42/20 525 | 1.01 (0.74–1.38) | 1.00 (0.73–1.37) | |
| IVF or ICSI | 82/24 536 | 1.65 (1.30–2.08) | 1.71 (1.35–2.16) | |
| Respiratory | Infertility without treatment | 225/229 832 | Referent | Referent |
| Ovulation induction or IUI | 35/20 525 | 1.53 (1.08–2.17) | 1.53 (1.07–2.17) | |
| IVF or ICSI | 37/24 536 | 1.75 (1.22–2.49) | 1.72 (1.21–2.46) | |
| Urinary | Infertility without treatment | 1632/229 832 | Referent | Referent |
| Ovulation induction or IUI | 166/20 525 | 1.14 (0.97–1.34) | 1.11 (0.95–1.31) | |
| IVF or ICSI | 210/24 536 | 1.20 (1.04–1.39) | 1.14 (0.99–1.32) |
Relative risks were adjusted for maternal age at delivery, income quintile, pre-existing diabetes, chronic hypertension, smoking, alcohol use, substance use disorder, rurality, obesity, and year of birth.
Table 3.
Relative risk of specific anomalies for births following fertility treatment compared to infertility without treatment.
| Exposure | N infants with anomaly/N at risk | Unadjusted RR (95% CI) | Adjusted RR (95% CI) * | |
|---|---|---|---|---|
| Atrial septal anomaly | Infertility without treatment | 1634/229 832 | Referent | Referent |
| Ovulation induction or IUI | 179/20 525 | 1.22 (1.04–1.42) | 1.24 (1.06–1.45) | |
| IVF or ICSI | 229/24 536 | 1.31 (1.14–1.51) | 1.32 (1.14–1.51) | |
| Ventricular septal anomaly | Infertility without treatment | 689/229 832 | Referent | Referent |
| Ovulation induction or IUI | 65/20 525 | 1.05 (0.82–1.36) | 1.08 (0.84–1.39) | |
| IVF or ICSI | 92/24 536 | 1.25 (1.00–1.55) | 1.25 (1.00–1.55) | |
| Stenosis of pulmonary artery | Infertility without treatment | 232/229 832 | Referent | Referent |
| Ovulation induction or IUI | 31/20 525 | 1.49 (1.01–2.18) | 1.56 (1.06–2.29) | |
| IVF or ICSI | 36/24 536 | 1.45 (1.02–2.06) | 1.57 (1.11–2.23) | |
| Tetralogy of Fallot | Infertility without treatment | 125/229 832 | Referent | Referent |
| Ovulation induction or IUI | 16/20 525 | 1.42 (0.85–2.39) | 1.40 (0.83–2.35) | |
| IVF or ICSI | 24/24 536 | 1.78 (1.15–2.76) | 1.67 (1.07–2.60) | |
| Other heart malformations | Infertility without treatment | 251/229 832 | Referent | Referent |
| Ovulation induction or IUI | 22/20 525 | 0.99 (0.64–1.52) | 0.98 (0.63–1.51) | |
| IVF or ICSI | 19/24 536 | 0.71 (0.44–1.13) | 0.76 (0.48–1.22) | |
| Unspecified heart malformations | Infertility without treatment | 135/229 832 | Referent | Referent |
| Ovulation induction or IUI | 7/20 525 | 0.58 (0.27–1.24) | 0.60 (0.28–1.29) | |
| IVF or ICSI | 8/24 536 | 0.55 (0.37–1.13) | 0.57 (0.28–1.17) | |
| Atrioventricular septal anomaly | Infertility without treatment | 147/229 832 | Referent | Referent |
| Ovulation induction or IUI | 8/20 525 | 0.61 (0.30–1.24) | 0.66 (0.32–1.34) | |
| IVF or ICSI | 14/24 536 | 0.89 (0.52–1.54) | 0.82 (0.47–1.43) | |
| Cleft lip | Infertility without treatment | 125/229 832 | Referent | Referent |
| Ovulation induction or IUI | 12/20 525 | 1.08 (0.60–1.95) | 1.09 (0.60–1.97) | |
| IVF or ICSI | 10/24 536 | 0.75 (0.40–1.43) | 0.78 (0.41–1.48) | |
| Cleft palate + cleft lip | Infertility without treatment | 113/229 832 | Referent | Referent |
| Ovulation induction or IUI | 12/20 525 | 1.19 (0.67–2.18) | 1.19 (0.65–2.17) | |
| IVF or ICSI | 9/24 536 | 0.76 (0.39–1.49) | 0.80 (0.41–1.58) | |
| Cleft palate unspecified | Infertility without treatment | 142/229 832 | Referent | Referent |
| Ovulation induction or IUI | 10/20 525 | 0.78 (0.41–1.49) | 0.77 (0.40–1.45) | |
| IVF or ICSI | 9/24 536 | 0.59 (0.30–1.17) | 0.61 (0.31–1.20) | |
| Hypertrophic pyloric stenosis | Infertility without treatment | 333/229 832 | Referent | Referent |
| Ovulation induction or IUI | 25/20 525 | 0.84 (0.56–1.26) | 0.86 (0.57–1.30) | |
| IVF or ICSI | 26/24 536 | 0.73 (0.49–1.09) | 0.87 (0.58–1.30) | |
| Ankyloglossia | Infertility without treatment | 2597/229 832 | Referent | Referent |
| Ovulation induction or IUI | 255/20 525 | 1.10 (0.97–1.25) | 1.04 (0.92–1.18) | |
| IVF or ICSI | 328/24 536 | 1.19 (1.06–1.33) | 1.12 (1.00–1.26) | |
| Hydronephrosis | Infertility without treatment | 582/229 832 | Referent | Referent |
| Ovulation induction or IUI | 65/20 525 | 1.25 (0.97–1.62) | 1.20 (0.93–1.55) | |
| IVF or ICSI | 71/24 536 | 1.14 (0.89–1.46) | 1.11 (0.87–1.42) | |
| Other kidney malformation | Infertility without treatment | 664/229 832 | Referent | Referent |
| Ovulation induction or IUI | 65/20 525 | 1.10 (0.85–1.42) | 1.08 (0.83–1.40) | |
| IVF or ICSI | 78/24 536 | 1.10 (0.87–1.40) | 1.00 (0.79–1.27) | |
| Hypospadias | Infertility without treatment | 173/229 832 | Referent | Referent |
| Ovulation induction or IUI | 15/20 525 | 0.97 (0.57–1.65) | 0.95 (0.56–1.61) | |
| IVF or ICSI | 31/24 536 | 1.56 (1.03–2.37) | 1.51 (1.00–2.29) | |
| Undescended testes | Infertility without treatment | 481/229 832 | Referent | Referent |
| Ovulation induction or IUI | 40/20 525 | 0.93 (0.67–1.28) | 0.91 (0.66–1.25) | |
| IVF or ICSIIVF or ICSI | 62/24 536 | 1.21 (0.93–1.57) | 1.19 (0.91–1.54) | |
| Other penis malformation | Infertility without treatment | 81/229 832 | Referent | Referent |
| Ovulation induction or IUI | ** | ** | ** | |
| IVF or ICSI | 8/24 536 | 0.92 (0.44–1.89) | 0.92 (0.44–1.91) | |
| Unspecified hypospadias | Infertility without treatment | 342/229 832 | Referent | Referent |
| Ovulation induction or IUI | 47/20 525 | 1.54 (1.13–2.08) | 1.51 (1.11–2.05) | |
| IVF or ICSI | 74/24 536 | 2.02 (1.57–2.61) | 1.99 (1.54–2.58) | |
| Craniosynostosis | Infertility without treatment | 162/229 832 | Referent | Referent |
| Ovulation induction or IUI | 17/20 525 | 1.17 (0.71–1.92) | 1.14 (0.70–1.88) | |
| IVF or ICSI | 25/24 536 | 1.44 (0.95–2.19) | 1.41 (0.92–2.14) | |
| Other feet malformation | Infertility without treatment | 280/229 832 | Referent | Referent |
| Ovulation induction or IUI | 28/20 525 | 1.12 (0.76–1.65) | 1.13 (0.77–1.66) | |
| IVF or ICSI | 32/24 536 | 1.07 (0.74–1.54) | 1.11 (0.77–1.60) | |
| Hemangioma of other sites | Infertility without treatment | 159/229 832 | Referent | Referent |
| Ovulation induction or IUI | 18/20 525 | 1.27 (0.78–2.06) | 1.26 (0.77–2.05) | |
| IVF or ICSI | 37/24 536 | 2.18 (1.52–3.11) | 2.22 (1.55–3.19) | |
| Plagiocephaly | Infertility without treatment | 109/229 832 | Referent | Referent |
| Ovulation induction or IUI | 11/20 525 | 1.13 (0.61–2.09) | 1.11 (0.60–2.06) | |
| IVF or ICSI | 20/24 536 | 1.72 (1.07–2.76) | 1.81 (1.13–2.92) | |
| Inguinal hernia | Infertility without treatment | 182/229 832 | Referent | Referent |
| Ovulation induction or IUI | 22/20 525 | 1.35 (0.85–2.14) | 1.36 (0.86–2.15) | |
| IVF or ICSI | 22/24 536 | 1.13 (0.73–1.77) | 1.14 (0.73–1.78) | |
| Pilonidal cyst | Infertility without treatment | 418/229 832 | Referent | Referent |
| Ovulation induction or IUI | 45/20 525 | 1.20 (0.89–1.64) | 1.17 (0.86–1.59) | |
| IVF or ICSI | 62/24 536 | 1.39 (1.06–1.82) | 1.35 (1.03–1.77) |
Relative risks were adjusted for maternal age at delivery, income quintile, pre-existing diabetes, chronic hypertension, smoking, alcohol use, substance use disorder, rurality, obesity, and year of birth.
Small cells.
Among births following IVF/ICSI, the risk of any congenital anomaly was higher than among births to women with infertility who did not use fertility treatment (aRR 1.28; 95% CI 1.22–1.34) (Table 2). Increased risks were observed across multiple organ systems, including cardiovascular (aRR 1.31, 95 CI 1.17–1.45), CNS (aRR 1.67, 95 CI 1.35–2.08); gastrointestinal (aRR 1.14, 95% CI 1.03–1.26), genital (aRR 1.46, 95% CI 1.26–1.69), musculoskeletal (aRR 1.44, 95% CI 1.27–1.63), neoplasms and tumors (aRR 1.71, 95% CI 1.35–2.16); and respiratory anomalies (aRR 1.72; 95% CI 1.21–2.46). At the level of specific anomalies, increased risks were observed for atrial septal defects (aRR 1.32, 95% CI 1.14––1.51), pulmonary artery stenosis (aRR 1.57; 95% CI 1.11–2.23), Tetralogy of Fallot (aRR 1.67; 95% CI 1.07–2.60), unspecified hypospadias (aRR 1.99, 95% CI 1.54–2.58), hemangioma (aRR 2.22, 95% CI 1.55–3.19), plagiocephaly (aRR 1.81; 95% CI 1.13–2.92), and pilonidal cysts (aRR 1.35; 95% CI 1.03–1.77) (Table 3).
Mediation analysis by multiple birth
The proportion of the association between fertility treatment and congenital anomalies mediated by multiple birth varied by treatment group and anomaly type (Tables 4 and 5). Among births following OI/IUI, the proportion mediated was greatest for pulmonary artery stenosis (33.9%), followed by CNS anomalies (30.2%) and atrial septal defect (27.1%). Among births following IVF/ICSI, the proportion mediated was greatest for pulmonary artery stenosis (44.4%), followed by CNS (32.2%), and cardiovascular system anomalies (28.6%).
Table 4.
Mediation analysis of the effect of multifetal birth on the association between fertility treatment and risk of organ system anomalies compared to infertility without treatment.
|
Adjusted
* relative risk (95% CI) |
||||
|---|---|---|---|---|
| Congenital anomaly assessed and exposure | Total effect | Direct effect | Indirect effect | Proportion mediated (%) |
| Any anomaly | ||||
| Ovulation induction or IUI | 1.08 (1.02–1.15) | 1.09 (1.02–1.16) | 1.03 (1.02–1.04) | 26.3** |
| IVF or ICSI | 1.23 (1.15–1.31) | 1.26 (1.18–1.34) | 1.06 (1.04–1.08) | 19.7** |
| Cardiovascular system anomalies | ||||
| IVF or ICSI | 1.16 (1.01–1.34) | 1.22 (1.06–1.40) | 1.08 (1.05–1.12) | 28.6** |
| Central Nervous System anomalies | ||||
| Ovulation induction or IUI | 1.29 (0.92–1.81) | 1.24 (0.90–1.72) | 1.10 (1.06–1.14) | 30.2** |
| IVF or ICSI | 1.56 (1.09– 2.21) | 1.48 (1.06–2.07) | 1.21 (1.12–1.30) | 32.2** |
| Gastrointestinal system anomalies | ||||
| IVF or ICSI | 1.13 (1.00–1.27) | 1.16 (1.03–1.30) | 0.98 (0.93–1.03) | NA |
| Genital anomalies | ||||
| IVF or ICSI | 1.54 (1.23–1.92) | 1.54 (1.23–1.93) | 1.05 (0.99–1.12) | 10.1 |
| Musculoskeletal anomalies | ||||
| IVF or ICSI | 1.42 (1.18–1.71) | 1.44 (1.20–1.72) | 1.08 (1.02–1.13) | 16.7** |
| Neoplasms and Tumors | ||||
| IVF or ICSI | 1.89 (1.25–2.85) | 1.71 (1.15–2.55) | 1.15 (1.05–1.27) | 21.0** |
| Respiratory system anomalies | ||||
| Ovulation induction or IUI | 1.90 (1.03–3.50) | 2.14 (1.13–4.06) | 0.93 (0.77–1.12) | NA |
| IVF or ICSI | 1.50 (0.87–2.58) | 1.47 (0.87–2.49) | 1.13 (0.99–1.30) | 24.8 |
Relative risks were adjusted for maternal age at delivery, income quintile, pre-existing diabetes, chronic hypertension, smoking, alcohol use, substance use disorder, rurality, obesity, and year of birth.
Statistically significant natural indirect effect at a P-value of less than 0.05.
NA: Results are due to the natural direct effect and the natural indirect effect operating in opposite directions. The proportion mediated is rendered meaningless when the natural direct and indirect effects are approximately the same magnitude, but opposite signs.
Table 5.
Mediation analysis of the effect of multifetal birth on the association between fertility treatment and risk of specific anomalies compared to infertility without treatment.
|
Adjusted relative risk (95% CI)
*
|
||||
|---|---|---|---|---|
| Congenital anomaly assessed and mode of conception | Total effect | Natural direct effect | Natural indirect effect | Proportion mediated (%) |
| Atrial septal anomalies | ||||
| Ovulation induction or IUI | 1.16 (0.96–1.41) | 1.17 (0.97–1.42) | 1.06 (1.04–1.09) | 27.1** |
| IVF or ICSI | 1.15 (0.96–1.38) | 1.24 (1.03–1.49) | 1.08 (1.03–1.13) | 25.1** |
| Stenosis of pulmonary artery | ||||
| Ovulation induction or IUI | 1.30 (0.75–2.25) | 1.25 (0.75–2.11) | 1.12 (1.06–1.19) | 33.9** |
| IVF or ICSI | 1.25 (0.73–2.13) | 1.25 (0.75–2.09) | 1.20 (1.08–1.33) | 44.4** |
| Tetralogy of Fallot | ||||
| IVF or ICSI | 2.09 (1.00–4.39) | 1.75 (0.84–3.64) | 1.07 (0.88–1.31) | 11.0 |
| Unspecified hypospadias | ||||
| Ovulation induction or IUI | 1.62 (1.01–2.56) | 1.59 (1.00–2.53) | 1.05 (0.99–1.13) | 10.2 |
| IVF or ICSI | 2.43 (1.45–4.01) | 2.22 (1.33–3.67) | 1.20 (1.07–1.35) | 18.8** |
| Hemangioma of other sites | ||||
| IVF or ICSI | 2.79 (1.24–6.27) | 2.34 (1.09–5.03) | 1.29 (1.10–1.52) | 23.2** |
| Plagiocephaly | ||||
| IVF or ICSI | 1.72 (0.72–4.12) | 1.69 (0.76–3.78) | 1.26 (1.03– 1.55) | 30.8** |
| Pilonidal cyst | ||||
| IVF or ICSI | 1.37 (0.93–2.00) | 1.35 (0.93–1.96) | 1.07 (0.97–1.20) | 19.3 |
Relative risks were adjusted for maternal age at delivery, income quintile, pre-existing diabetes, chronic hypertension, smoking, alcohol use, substance use disorder, rurality, obesity, and year of birth.
Statistically significant natural indirect effect at a P-value of less than 0.05.
NA: Results are due to the natural direct effect and the natural indirect effect operating in opposite directions. The proportion mediated is rendered meaningless when the natural direct and indirect effects are approximately the same magnitude, but opposite signs.
Sensitivity analysis
E-value analyses were conducted for all statistically significant associations (Supplementary Tables S3 and S4). The smallest E-values were observed for any congenital anomaly following OI/IUI (E-value: 1.46; lower confidence limit 1.28) and IVF/ICSI (E-value 1.74; lower confidence limit 1.28), indicating that relatively modest unmeasured confounding could explain these associations. In contrast, the largest E-values approached 4.0, suggesting that a substantially stronger unmeasured confounder would be required to fully explain the observed associations, which is less plausible.
Discussion
In this population-based cohort study, births following fertility treatment had a slightly higher risk of congenital anomalies compared with births to women with infertility who did not use fertility treatment. This association was only partially mediated by multiple birth.
Multiple birth has been proposed as an important mechanism underlying the increased risk of congenital anomalies following fertility treatment (Tang et al., 2006; Glinianaia et al., 2008). Multiple gestations are associated with intrauterine crowding and reduced nutrient availability, which have been linked to an increased risk of structural anomalies (Zhu et al., 2006; Grantz et al., 2016). Twins, for example, have higher risks of specific defects compared with singletons, including Tetralogy of Fallot, pulmonary valve stenosis, coarctation of the aorta, and cleft lip with or without cleft palate (Li et al., 2003; Tang et al., 2006). Consistent with this, a large European cohort study reported modestly increased risk of non-chromosomal congenital anomalies among multiple birth compared with singletons (RRs ranging from 1.19 [95% CI 1.07–1.33] to 1.31 [95% CI 1.24–1.38]) (Marleen et al., 2024).
Despite these associations, multiple birth explained only a portion of the increased risk of congenital anomalies observed following fertility treatment. Few studies have evaluated the mediating role of multiple birth. A cohort study comparing fertility treatments with births to women without infertility reported that 47.5% of any congenital anomaly, 63.2% of cardiac anomalies, 36.2% of non-cardiac anomalies, 42.7% of Tetralogy of Fallot, and 50.2% of hypospadias anomalies were mediated through multiple birth (Liberman et al., 2017). These estimates were generally higher than those observed in our study. One possible explanation is the choice of reference group. Unlike that study, we compared births to women with infertility who did not use fertility treatment, thereby reducing confounding by underlying infertility (Velez and Ray, 2026). Consequently, our findings may provide a more specific estimate of the proportion of risk attributable to multiple birth rather than to infertility itself.
The observed multiple birth rates in this study likely reflect the inclusion of births from an era when double embryo transfer was more common in Canada. Previous population-based research from Ontario demonstrated a marked decline in multifetal pregnancy rates following the introduction of publicly funded IVF and an elective single embryo transfer policy in 2015 (Velez et al., 2024c).
We observed an increased risk of genital anomalies, including unspecified hypospadias, following fertility treatment that was not mediated by multiple birth. This finding is consistent with prior cohort studies reporting an increased risk of hypospadias after ICSI (Wennerholm et al., 2000; Fedder et al., 2013). Hypospadias has been hypothesized to reflect underlying parental factors, particularly male factor infertility, through heritable alterations in androgen production or Y-chromosome microdeletions (Feng et al., 2008; Simpson, 2014). Supporting this hypothesis, a large Nordic cohort study reported an increased risk of hypospadias among births following ICSI for male factor infertility (Henningsen et al., 2023).
However, parental factors associated with infertility may extend beyond male factor infertility. Recent population-based work from our group has demonstrated an increased risk of congenital anomalies among births to women with endometriosis, including hypospadias (aRR 1.47; 95% CI 1.04–2.09), among other anomalies (Milne et al., 2026). These findings suggest that the increased risk of congenital anomalies observed following fertility treatment may, at least in part, reflect underlying infertility-related factors rather than treatment itself.
This study benefits from a large, population-based cohort from a diverse population in Ontario with publicly funded fertility treatment (Bougie et al., 2021; Velez et al., 2022), and datasets capturing 99% of births (Better Outcomes Registry & Network). Ontario had a universal healthcare system and publicly funded fertility treatment during part of the study period. Differences in healthcare coverage, access to fertility treatment, eligibility criteria, and funding models may limit the direct generalizability of these findings to other jurisdictions. Although our models were adjusted for birth year to account for temporal changes in fertility treatment access and practice patterns, caution is warranted when extrapolating these findings to healthcare systems with substantially different models of fertility care.
Unlike most prior studies, we used births to women with infertility without treatment as the reference group to reduce confounding by underlying infertility. However, given that this group was defined using administrative data, misclassification of infertility status is possible when billing codes capture consultations in which difficulty achieving pregnancy was discussed without a confirmed diagnosis, potentially introducing residual confounding. Furthermore, pharmaceutical dispensing data were not available in the study cohort, and some patients may have received oral OI medication outside of a fertility clinic or without a fertility treatment procedure code, which could result in exposure misclassification. However, the proportion of multiple birth in the infertility without treatment group was low, at 2.3%, compared with 7.2% after OI/IUI and 13.3% after IVF/ICSI, suggesting that substantial misclassification of OI exposure in the reference group is unlikely. Data regarding IVF cycle characteristics and laboratory procedures were also not captured within the available databases; therefore, the contribution of treatment-related factors such as fresh versus frozen embryo transfer, embryo stage at transfer, assisted hatching, and preimplantation genetic testing could not be assessed. As with all studies using administrative health data, unmeasured confounding remains possible. E-value analyses suggested that modest unmeasured confounding could explain some associations, whereas others would require stronger confounding. Potential unmeasured factors include race/ethnicity. Lastly, there was limited statistical power to assess outcomes, particularly specific congenital anomalies, among births following ICSI. Therefore, ICSI was combined with IVF into a single exposure category.
In conclusion, this population-based study suggests that multiple birth partially mediates the slightly increased risk of congenital anomalies among births following fertility treatment, while a substantial proportion of the observed association appears independent of multiple gestation. These findings suggest that while continued efforts to reduce multiple pregnancy following fertility treatment may reduce part of the excess risk (Velez et al., 2013, 2014, 2024c) further research is needed to disentangle the contribution of specific infertility diagnoses (i.e. endometriosis, polycystic ovary syndrome, male factor) and treatment-related factors (e.g., fresh versus frozen embryo transfer, cleavage versus blastocyst-stage transfer, assisted hatching) to the risk of congenital anomalies.
Supplementary Material
Contributor Information
B M Milne, Department of Public Health Sciences, Queen’s University, Kingston, ON, Canada.
M P Velez, Department of Obstetrics and Gynecology, McGill University, Montreal, QC, Canada; ICES, Kingston, ON, Canada.
J Shellenberger, ICES, Kingston, ON, Canada.
S B Brogly, ICES, Kingston, ON, Canada; Department of Surgery, Queen’s University, Kingston, ON, Canada.
Data availability
The dataset used for this study is held at ICES in coded form. Legal agreements prohibit ICES from making the dataset publicly available; however, the dataset creation plan and analytical code are available from the authors upon request. The coding templates and macros used to conduct the analysis may be unique to ICES and may be inaccessible.
Authors’ roles
B.M.M and J.S. had full access to all of the data in the study and take responsibility for the integrity of the data and accuracy of the data analysis. Concept and design: B.M.M., S.B.B., M.P.V. Acquisition, analysis or interpretation of the data: B.M.M., S.B.B., J.S., M.P.V. Statistical analysis and drafting the work: B.M.M. Obtained funding: M.P.V. Administrative, technical or material support, and reviewing the manuscript critically for important intellectual content: M.P.V., S.B.B.
Funding
This study was funded by grant MFM-146444 from the Canadian Institutes of Health Research Institute of Human Development, Child & Youth Health, Clinician—Investigator Teams in Obstetrics and Maternal-Fetal Medicine. Bailey Milne received funding for this project from the Queen’s University Dean’s Doctoral Award. This study was supported by ICES, which is funded by an annual grant from the Ontario Ministry of Health (MOH) and the Ministry of Long-Term Care (MLTC). This document used data adapted from the Statistics Canada Postal CodeOM Conversion File, which is based on data licensed from Canada Post Corporation, and/or data adapted from the Ontario Ministry of Health Postal Code Conversion File, which contains data copied under license from ©Canada Post Corporation and Statistics Canada. Parts of this material are based on data and/or information compiled and provided by CIHI, the Ontario Ministry of Health, and the Better Outcomes Registry & Network (‘BORN’), part of the Children’s Hospital of Eastern Ontario. The analyses, conclusions, opinions and statements expressed herein are solely those of the authors and do not reflect those of the funding or data sources; no endorsement is intended or should be inferred.
Disclosures
The authors have nothing to disclose.
References
- American Society for Reproductive Medicine. Aging and infertility in women. Fertil Steril 2006;86:S248–S252. [DOI] [PubMed] [Google Scholar]
- Bateni Z, Aryan S, Hosseinzadeh P, Shamshirsaz A. Congenital anomalies in infants conceived by infertility treatment. Reprod Sci 2016;23:85A–86A. [Google Scholar]
- Benavides E, Lupo PJ, Sosa M, Whitworth KW, Canfield MA, Langlois PH, Schraw JM. Urban-rural residence and birth defects prevalence in Texas: a phenome-wide association study. Pediatr Res 2022;91:1587–1594. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Better Outcomes Registry & Network. About BORN. https://www.bornontario.ca/about-us/ (1 November 2025, date last accessed).
- Bougie O, McClintock C, Pudwell J, Brogly SB, Velez MP. Short-term outcomes of endometriosis surgery in Ontario: a population-based cohort study. Acta Obstet Gynecol Scand 2021;100:1140–1147. [DOI] [PubMed] [Google Scholar]
- Bowie AC, Werler MM, Velez MP, Li W, Camden A, Guttmann A, Brogly SB. Prescribed opioid analgesics in early pregnancy and the risk of congenital anomalies: a population-based cohort study. CMAJ 2022;194:E152–E162. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Brogly SB, Turner S, Lajkosz K, Davies G, Newman A, Johnson A, Dow K. Infants born to opioid-dependent women in Ontario, 2002-2014. J Obstet Gynaecol Can 2017;39:157–165. [DOI] [PubMed] [Google Scholar]
- Canadian Institute for Health Information. CIHI DAD Data Elements 2015–2016. Ottawa, Ontario, Canada: Canadian Institute for Health Information, 2016. [Google Scholar]
- Canadian Institute for Health Information. CIHI Discharge Abstract Database Metadata (DAD). Ottawa, Ontario, Canada: Canadian Institute for Health Information, 2018. [Google Scholar]
- Correa A, Marcinkevage J. Prepregnancy obesity and the risk of birth defects: an update. Nutr Rev 2013;71:S68–S77. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Correa-Villaseñor A, Cragan J, Kucik J, O’Leary L, Siffel C, Williams L. The Metropolitan Atlanta Congenital Defects Program: 35 years of birth defects surveillance at the Centers for Disease Control and Prevention. Birth Defects Res A Clin Mol Teratol 2003;67:617–624. [DOI] [PubMed] [Google Scholar]
- Dayan N, Velez MP, Vigod S, Pudwell J, Djerboua M, Fell DB, Basso O, Nguyen TV, Joseph KS, Ray JG. Infertility treatment and postpartum mental illness: a population-based cohort study. CMAJ Open 2022;10:E430–E438. [DOI] [PMC free article] [PubMed] [Google Scholar]
- de Angelis C, Nardone A, Garifalos F, Pivonello C, Sansone A, Conforti A, Di Dato C, Sirico F, Alviggi C, Isidori A et al. Smoke, alcohol and drug addiction and female fertility. Reprod Biol Endocrinol 2020;18:21. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Dhage VD, Nagtode N, Kumar D, Bhagat AK. A narrative review on the impact of smoking on female fertility. Cureus 2024;16:e58389. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Esposito G, Parazzini F, Viganò P, Cantarutti A, Franchi M, Corrao G, La Vecchia C, Somigliana E. Multiple births from medically assisted reproduction: contribution of different types of procedures and trends over time. Eur J Obstet Gynecol Reprod Biol 2024;300:63–68. [DOI] [PubMed] [Google Scholar]
- Evans WN, Acherman RJ, Restrepo H. Critical congenital heart disease and maternal comorbidities: an observation. Prog Pediatr Cardiol 2022;64:101433. [Google Scholar]
- Fan D, Liu L, Xia Q, Wang W, Wu S, Tian G, Liu Y, Ni J, Wu S, Guo X et al. Female alcohol consumption and fecundability: a systematic review and dose-response meta-analysis. Sci Rep 2017;7:13815. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Fedder J, Loft A, Parner ET, Rasmussen S, Pinborg A. Neonatal outcome and congenital malformations in children born after ICSI with testicular or epididymal sperm: a controlled national cohort study. Hum Reprod 2013;28:230–240. [DOI] [PubMed] [Google Scholar]
- Feng C, Wang LQ, Dong MY, Huang HF. Assisted reproductive technology may increase clinical mutation detection in male offspring. Fertil Steril 2008;90:92–96. [DOI] [PubMed] [Google Scholar]
- Fine A, Dayan N, Djerboua M, Pudwell J, Fell DB, Vigod SN, Ray JG, Velez MP. Attention-deficit hyperactivity disorder in children born to mothers with infertility: a population-based cohort study. Hum Reprod 2022;37:2126–2134. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Gautam D, Purandare N, Maxwell CV, Rosser ML, O’Brien P, Mocanu E, McKeown C, Malhotra J, McAuliffe FM; FIGO Committee on Impact of Pregnancy on Long-term Health and the FIGO Committee on Reproductive Medicine, Endocrinology and Infertility. The challenges of obesity for fertility: a FIGO literature review. Int J Gynaecol Obstet 2023;160:50–55. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Glinianaia SV, Rankin J, Wright C. Congenital anomalies in twins: a register-based study. Hum Reprod 2008;23:1306–1311. [DOI] [PubMed] [Google Scholar]
- Grantz KL, Grewal J, Albert PS, Wapner R, D’Alton ME, Sciscione A, Grobman WA, Wing DA, Owen J, Newman RB et al. Dichorionic twin trajectories: the NICHD fetal growth studies. Am J Obstet Gynecol 2016;215:221.e1–221.e16. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Hackshaw A, Rodeck C, Boniface S. Maternal smoking in pregnancy and birth defects: a systematic review based on 173 687 malformed cases and 11.7 million controls. Hum Reprod Update 2011;17:589–604. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Harris JA, Menke MN, Haefner JK, Moniz MH, Perumalswami CR. Geographic access to assisted reproductive technology health care in the United States: a population-based cross-sectional study. Fertil Steril 2017;107:1023–1027. [DOI] [PubMed] [Google Scholar]
- Hedermann G, Hedley PL, Gadsboll K, Thagaard IN, Krebs L, Hagen CM, Sorensen TIA, Christiansen M, Ekelund CK. Maternal obesity, interpregnancy weight changes and congenital heart defects in the offspring: a nationwide cohort study. Int J Obes (Lond) 2024;48:1126–1132. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Henningsen A-KA, Opdahl S, Wennerholm U-B, Tiitinen A, Rasmussen S, Romundstad LB, Bergh C, Gissler M, Forman JL, Pinborg A. Risk of congenital malformations in live-born singletons conceived after intracytoplasmic sperm injection: a Nordic study from the CoNARTaS group. Fertil Steril 2023;120:1033–1041. [DOI] [PubMed] [Google Scholar]
- Hwang SS, Dukhovny D, Gopal D, Cabral H, Missmer S, Diop H, Declercq E, Stern JE. Health of infants after ART-treated, subfertile, and fertile deliveries. Pediatrics 2018;142:e20174069. [DOI] [PMC free article] [PubMed] [Google Scholar]
- ICES. ICES. 2021. https://www.ices.on.ca/ (1 November 2025, date last accessed).
- Imrie R, Ghosh S, Narvekar N, Vigneswaran K, Wang Y, Savvas M. Socioeconomic status and fertility treatment outcomes in high-income countries: a review of the current literature. Hum Fertil (Camb) 2023;26:27–37. [DOI] [PubMed] [Google Scholar]
- Li SJ, Ford N, Meister K, Bodurtha J. Increased risk of birth defects among children from multiple births. Birth Defects Res A Clin Mol Teratol 2003;67:879–885. [DOI] [PubMed] [Google Scholar]
- Liberman RF, Getz KD, Heinke D, Luke B, Stern JE, Declercq ER, Chen X, Lin AE, Anderka M. Assisted reproductive technology and birth defects: effects of subfertility and multiple births. Birth Defects Res 2017;109:1144–1153. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Lorzadeh N, Kazemirad N, Kazemirad Y. Human immunodeficiency: extragonadal comorbidities of infertility in women. Immun Inflamm Dis 2020;8:447–457. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Luke B, Brown MB, Wantman E, Forestieri NE, Browne ML, Fisher SC, Yazdy MM, Ethen MK, Canfield MA, Watkins S et al. The risk of birth defects with conception by ART. Hum Reprod 2021;36:116–129. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Luke B, Brown MB, Wantman E, Schymura MJ, Browne ML, Fisher SC, Forestieri NE, Rao C, Nichols HB, Yazdy MM et al. The risks of birth defects and childhood cancer with conception by assisted reproductive technology. Hum Reprod 2022;37:2672–2689. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Luo Z-C, Wilkins R, Kramer MS; Fetal and Infant Health Study Group of the Canadian Perinatal Surveillance System. Effect of neighbourhood income and maternal education on birth outcomes: a population-based study. CMAJ 2006;174:1415–1420. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Marleen S, Kodithuwakku W, Nandasena R, Mohideen S, Allotey J, Fernández-García S, Gaetano-Gil A, Ruiz-Calvo G, Aquilina J, Khalil A et al. Maternal and perinatal outcomes in twin pregnancies following assisted reproduction: a systematic review and meta-analysis involving 802 462 pregnancies. Hum Reprod Update 2024;30:309–322. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Mattsson K, Nilsson-Condori E, Elmerstig E, Vassard D, Schmidt L, Ziebe S, Jöud A. Fertility outcomes in women with pre-existing type 2 diabetes—a prospective cohort study. Fertil Steril 2021;116:505–513. [DOI] [PubMed] [Google Scholar]
- Mavrogenis S, Urban R, Czeizel AE, Acs N. Possible association of maternal factors with the higher risk of isolated true undescended testis: a population-based case-control study. Congenit Anom (Kyoto) 2014;54:178–183. [DOI] [PubMed] [Google Scholar]
- Milne B, Velez M, Shellenberger J, Brogly S. Risk of congenital anomalies for infants born to patients with endometriosis: a population-based cohort study. CMAJ 2026;198:E688–E697. 10.1503/cmaj.250439 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Nelson KE, Rosella LC, Mahant S, Guttmann A. Survival and surgical interventions for children with trisomy 13 and 18. Jama 2016;316:420–428. [DOI] [PubMed] [Google Scholar]
- Pethő B, Mátrai Á, Agócs G, Veres DS, Harnos A, Váncsa S, Bánhidy F, Hegyi P, Ács N. Maternal age is highly associated with non‐chromosomal congenital anomalies: analysis of a population‐based case‐control database. BJOG 2023;130:1217–1225. [DOI] [PubMed] [Google Scholar]
- Richmond E, Ray J, Pudwell J, Djerboua M, Gaudet L, Walker M, Smith G, Velez M. Caesarean birth in women with infertility: population‐based cohort study. BJOG 2022;129:908–916. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Scott S, Sher J. Effect of alcohol during pregnancy: a public health issue. Lancet Public Health 2023;8:e4–e5. [DOI] [PubMed] [Google Scholar]
- Shin JE, Ko HS, Bae JY, Seong WJ, Ahn TG, Han YJ, Cho GJ, Park IY. Congenital anomalies in multiple pregnancy: a literature review. Obstet Gynecol Surv 2024;79:167–175. [DOI] [PubMed] [Google Scholar]
- Simpson JL. Birth defects and assisted reproductive technologies. Semin Fetal Neonatal Med 2014;19:177–182. [DOI] [PubMed] [Google Scholar]
- Tang Y, Ma CX, Cui W, Chang V, Ariet M, Morse SB, Resnick MB, Roth J. The risk of birth defects in multiple births: a population-based study. Matern Child Health J 2006;10:75–81. [DOI] [PubMed] [Google Scholar]
- Terho AM, Tiitinen A, Martikainen H, Gissler M, Pelkonen S. Health of singletons born after frozen embryo transfer until early adulthood: a Finnish Register Study. Hum Reprod 2022;37:2899–2907. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Vandenbroucke JP, von Elm E, Altman DG, Gøtzsche PC, Mulrow CD, Pocock SJ, Poole C, Schlesselman JJ, Egger M; STROBE Initiative. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): explanation and elaboration. Epidemiology (Fairfax) 2007;18:805–835. [DOI] [PubMed] [Google Scholar]
- Vanderweele TJ. Explanation in Causal Inference: methods for Mediation and Interaction. Oxford, UK: Oxford University Press, 2015. [Google Scholar]
- VanderWeele TJ. Mediation analysis: a practitioner’s guide. Annu Rev Public Health 2016;37:17–32. [DOI] [PubMed] [Google Scholar]
- VanderWeele TJ, Ding P. Sensitivity analysis in observational research: introducing the E-value. Ann Intern Med 2017;167:268–274. [DOI] [PubMed] [Google Scholar]
- Velez MP, Bougie O, Bahta L, Pudwell J, Griffiths R, Li W, Brogly SB. Mode of conception in patients with endometriosis and adverse pregnancy outcomes: a population-based cohort study. Fertil Steril 2022;118:1090–1099. [DOI] [PubMed] [Google Scholar]
- Velez MP, Chapman O, Bougie O, Pudwell J, Li W, Brogly SB. Endometriosis, severe maternal morbidity, and the effect of infertility: population-based cohort study. J Obstet Gynaecol Can 2024a;46:102582. [DOI] [PubMed] [Google Scholar]
- Velez MP, Connolly MP, Kadoch IJ, Phillips S, Bissonnette F. Universal coverage of IVF pays off. Hum Reprod 2014;29:1313–1319. [DOI] [PubMed] [Google Scholar]
- Velez MP, Dayan N, Shellenberger J, Pudwell J, Kapoor D, Vigod SN, Ray JG. Infertility and risk of autism spectrum disorder in children. JAMA Netw Open 2023;6:e2343954. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Velez MP, Dayan N, Vigod SN, Buckett W, Flatt S, Shellenberger J, Ray JG. New-onset mental illness among gestational carriers. JAMA Netw Open 2025;8:e2523428. [DOI] [PubMed] [Google Scholar]
- Velez MP, Ivanova M, Shellenberger J, Pudwell J, Ray JG. Severe maternal and neonatal morbidity among gestational carriers: a cohort study. Ann Intern Med 2024b;177:1482–1488. [DOI] [PubMed] [Google Scholar]
- Velez MP, Kadoch IJ, Phillips SJ, Bissonnette F. Rapid policy change to single-embryo transfer while maintaining pregnancy rates per initiated cycle. Reprod Biomed Online 2013;26:506–511. [DOI] [PubMed] [Google Scholar]
- Velez MP, Ray JG. Assisted reproduction and offspring neurodevelopment-untangling confounding by indication. Paediatr Perinat Epidemiol 2026;40:94–96. [DOI] [PubMed] [Google Scholar]
- Velez MP, Soule A, Gaudet L, Pudwell J, Nguyen P, Ray JG. Multifetal pregnancy after implementation of a publicly funded fertility program. JAMA Netw Open 2024c;7:e248496. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Wang YP, Ray JG, Pudwell J, Gaudet L, Peng Y, Velez MP. Mode of conception and risk of spontaneous vs. provider-initiated preterm birth: population-based cohort study. Fertil Steril 2022;118:926–935. [DOI] [PubMed] [Google Scholar]
- Wennerholm UB, Bergh C, Hamberger L, Lundin K, Nilsson L, Wikland M, Kallen B. Incidence of congenital malformations in children born after ICSI. Hum Reprod 2000;15:944–948. [DOI] [PubMed] [Google Scholar]
- World Health Organization. Congenital Disorders. Geneva, Switzlerand: World Health Organization, 2023. [Google Scholar]
- Zegers-Hochschild F, Dyer S, Adamson GD, Baker V, Barnhart K, Bhattacharya S, Boothroyd C, Chambers G, de Mouzon J, Elgindy E et al. The international glossary on infertility and fertility care, 2025. Fertil Steril 2026;126:127–149. [DOI] [PubMed] [Google Scholar]
- Zhu JL, Basso O, Obel C, Bille C, Olsen J. Infertility, infertility treatment, and congenital malformations: Danish National Birth Cohort. BMJ 2006;333:679–681. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Zou G. A modified Poisson regression approach to prospective studies with binary data. Am J Epidemiol 2004;159:702–706. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The dataset used for this study is held at ICES in coded form. Legal agreements prohibit ICES from making the dataset publicly available; however, the dataset creation plan and analytical code are available from the authors upon request. The coding templates and macros used to conduct the analysis may be unique to ICES and may be inaccessible.