Gary M. Shaw, Wei Yang, Kari A. Weber, Andrew F. Olshan, Tania A. Desrosiers, The National Birth Defects Prevention Study
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Here, we further interrogated both studies that observed this association with the objective to identify factors from a much larger number of factors that might explain the association.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>By employing a machine learning algorithm (random forest), we investigated a baseline set of over 200 variables. These analyses produced the top 10 variables in each data set for cases and controls that predicted periconceptional low carbohydrate intake.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>Examining those prediction variables with logistic regression modeling, we did not observe any particular variable that substantially contributed to the NTD-low carbohydrate association in either data set.</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>If there are underlying factors that explain the association, our findings suggest that none of the 200+ variables we examined were sufficiently correlated with what that true explanatory exposure may be. Alternatively, our findings may suggest that there are other unidentified factor(s) at play, or the association observed in two independent data sets is directly related to low carbohydrate intake.</p>\n </section>\n </div>","PeriodicalId":9121,"journal":{"name":"Birth Defects Research","volume":"116 3","pages":""},"PeriodicalIF":1.6000,"publicationDate":"2024-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A search for factors associated with reduced carbohydrate intake and NTD risk in two population-based studies\",\"authors\":\"Gary M. Shaw, Wei Yang, Kari A. Weber, Andrew F. Olshan, Tania A. Desrosiers, The National Birth Defects Prevention Study\",\"doi\":\"10.1002/bdr2.2328\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Background</h3>\\n \\n <p>Two population-based case–control studies have reported an increased risk of neural tube defect (NTD)-affected pregnancies among women with low carbohydrate diet in the periconceptional period. Given that only two studies have investigated this association, it is unclear to what degree the findings could be impacted by residual confounding. Here, we further interrogated both studies that observed this association with the objective to identify factors from a much larger number of factors that might explain the association.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>By employing a machine learning algorithm (random forest), we investigated a baseline set of over 200 variables. These analyses produced the top 10 variables in each data set for cases and controls that predicted periconceptional low carbohydrate intake.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>Examining those prediction variables with logistic regression modeling, we did not observe any particular variable that substantially contributed to the NTD-low carbohydrate association in either data set.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusions</h3>\\n \\n <p>If there are underlying factors that explain the association, our findings suggest that none of the 200+ variables we examined were sufficiently correlated with what that true explanatory exposure may be. 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A search for factors associated with reduced carbohydrate intake and NTD risk in two population-based studies
Background
Two population-based case–control studies have reported an increased risk of neural tube defect (NTD)-affected pregnancies among women with low carbohydrate diet in the periconceptional period. Given that only two studies have investigated this association, it is unclear to what degree the findings could be impacted by residual confounding. Here, we further interrogated both studies that observed this association with the objective to identify factors from a much larger number of factors that might explain the association.
Methods
By employing a machine learning algorithm (random forest), we investigated a baseline set of over 200 variables. These analyses produced the top 10 variables in each data set for cases and controls that predicted periconceptional low carbohydrate intake.
Results
Examining those prediction variables with logistic regression modeling, we did not observe any particular variable that substantially contributed to the NTD-low carbohydrate association in either data set.
Conclusions
If there are underlying factors that explain the association, our findings suggest that none of the 200+ variables we examined were sufficiently correlated with what that true explanatory exposure may be. Alternatively, our findings may suggest that there are other unidentified factor(s) at play, or the association observed in two independent data sets is directly related to low carbohydrate intake.
期刊介绍:
The journal Birth Defects Research publishes original research and reviews in areas related to the etiology of adverse developmental and reproductive outcome. In particular the journal is devoted to the publication of original scientific research that contributes to the understanding of the biology of embryonic development and the prenatal causative factors and mechanisms leading to adverse pregnancy outcomes, namely structural and functional birth defects, pregnancy loss, postnatal functional defects in the human population, and to the identification of prenatal factors and biological mechanisms that reduce these risks.
Adverse reproductive and developmental outcomes may have genetic, environmental, nutritional or epigenetic causes. Accordingly, the journal Birth Defects Research takes an integrated, multidisciplinary approach in its organization and publication strategy. The journal Birth Defects Research contains separate sections for clinical and molecular teratology, developmental and reproductive toxicology, and reviews in developmental biology to acknowledge and accommodate the integrative nature of research in this field. Each section has a dedicated editor who is a leader in his/her field and who has full editorial authority in his/her area.