In the Washington State population we studied, obese mothers had a mildly increased risk of orofacial clefts in their offspring compared with women of normal BMI. By using birth certificate and hospital discharge information, the lack of precise information on confounders may have limited our ability to adjust completely, even for measured confounders. Thus the very modest observed elevation in risk could be due to residual confounding. However, it is also possible that imprecision of the primary exposure could have biased the results. Our measurement of maternal BMI was based primarily on self-report, and as people tend to underestimate weight and overestimate height on average,41
such non-differential misclassification is most likely to bias results towards the null.
Nonetheless, a notable feature of the results we obtained is the close agreement with other studies that were of similar magnitude. Our results are similar to those obtained in individual studies,4,11,23,25,26
in which adjusted ORs ranged from 1.3 to 2.2, and to those obtained through a meta-analysis of the relationship of maternal overweight and obesity with orofacial clefting risk [OR for CL + P: 1.20; 95% CI 1.03, 1.40].2
Although there have also been results reported that are closer to the null,3,42,43
heterogeneity of categorisation of type of clefting and small sample sizes may explain the observed lack of association.
Despite the relatively weak association, its close agreement with other similar studies motivated us to perform Monte Carlo-based bias analyses. This type of analysis combines estimated ORs based on the observed data and estimates based on the assumed prior distributions for bias sources. This probabilistic method allows for a range of possible sensitivity and specificity values to be evaluated. The resulting simulation intervals portray the uncertainty from the combination of both random and systematic errors.39,44
The bias analyses cannot provide any stronger evidence against the null hypothesis than the original data.45
Results of the bias analyses are dependent also on the parameters selected as well as other assumptions (such as that errors are independent).39
However, this type of analysis provides a quantitative model of how, given these assumptions, specific sources of bias may have affected the results obtained. This may be particularly important when one relies on existing data sources, as we did, as it allows for a quantitative assessment of the inadequacies that often exist when performing secondary analysis of existing data, such as missing variables or incomplete data. The results of such bias analyses suggest that, as a result of misclassification of BMI, it is possible that the estimated ORs reflect underlying true ORs of much stronger magnitude than those observed. In the bias analyses, the magnitude of the simulated OR was particularly influenced by low specificity. Although specificity of the exposure is likely to be closer to 99% than 75%,41
we included this range because inaccuracies in birth certificate data can be fairly common for medical data.46
The bias analyses also suggested that if the presence of an unmeasured confounder was responsible for producing non-null results, this unknown risk factor would have had to be very common, to have been unmeasured in all studies and to have had a very strong association with orofacial clefts. Conditional on the assumed bias models, these analyses suggest that although we and others have observed only weak associations, they may represent a true positive association between maternal obesity and orofacial clefting risk in offspring.
In unadjusted analyses, we observed an increased risk of clefts for mothers with pre-existing diabetes. Although the analysis was limited by the small number of exposed cases, this finding is supported by previous research.8–12
However, we did not observe an association for gestational diabetes, contrary to results from several previous studies.8,24
The lack of a positive finding of an association between maternal gestational diabetes and orofacial clefts might appear to suggest that abnormal glucose metabolism is not involved in the aetiology of clefting. However, gestational diabetes develops towards the latter part of gestation, while orofacial clefts develop within the first 2 months of pregnancy. Thus, the discrepant findings regarding established vs. gestational diabetes may not detract from the overall hypothesis regarding impaired glucose metabolism. In addition, women with abnormalities of glucose metabolism due to insulin resistance may still have a normal result on a formal oral glucose tolerance test, and such underdiagnosis could have attenuated an association if one exists.47
In secondary analyses, we observed an increased risk of CL ± P associated with maternal obesity in male infants, but no increased risk in female infants. CL + P is more common in males, while CPO is more common in females.34
Although this finding is not conclusive, it is not entirely implausible. Orofacial clefts have been postulated to be caused by maternal hormone imbalance.35
In addition, inflammatory cytokines produced by adipose tissue appear to increase the expression of oestrogen-producing enzymes.48,49
Based on these relationships, one could speculate that abnormalities in the maternal hormonal profile caused by obesity, such as excess oestrogen, might be detrimental only to a male fetus.
This study has several strengths. It is population based and relatively robust against selection bias. As with other registry-based studies, analyses included data for a very large number of subjects ascertained over a long period of time. In some studies, conclusions about the relationship between maternal obesity and orofacial clefting have been limited by small numbers of cases.11,23,26,43
The birth certificate data and hospital discharge records are rich data sources with respect to information on potential confounders. In addition, accessing information from both data sources is likely to have increased the completeness of case ascertainment and ascertainment of medical conditions. For example, the sensitivity of ascertaining gestational diabetes from the birth certificate has been estimated to be 64% from birth certificates alone and 93% from both data sources combined.46
As orofacial clefts are usually easily visually identifiable, they are likely to be recorded at birth more reliably than many other birth defects. However, the possibility does remain that we missed some cases (particularly infants with CPO) that were identified after the birth hospitalisation.
A potentially important limitation of this study was the considerable amount of missing data for maternal BMI and pre-pregnancy weight, primarily because maternal weight was not recorded prior to 1992, and partly because of missing height data for the period 1992–2002. Women with missing BMI data were also more likely to have less than 12 years of education than women without missing data. As all analyses were adjusted for educational level, this limitation is not expected to have biased our results substantially. In addition, we conducted secondary analyses with imputation of missing data, in part to evaluate whether the association between missing BMI and other covariates could have biased the results. We observed a slight attenuation of results for the primary analyses, but no substantial difference. While these results are reassuring, the possibility for bias remains if missing BMI was also related to unmeasured covariates that are also strongly associated with risk of orofacial clefting.