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Is Maternal Menstrual Cycle Length Associated with Twinning? Author 1 Author 2.

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Presentation on theme: "Is Maternal Menstrual Cycle Length Associated with Twinning? Author 1 Author 2."— Presentation transcript:

1 Is Maternal Menstrual Cycle Length Associated with Twinning? Author 1 Author 2

2 Background Menstrual Cycles & Twinning Menstrual Cycles & Twinning –Shorter cycles -- ↑ Twinning Time to Pregnancy (TTP) & Twinning Time to Pregnancy (TTP) & Twinning – ↓ TTP -- ↑ Twinning Menstrual Cycles & Fertility Menstrual Cycles & Fertility –Regular menstrual cycles -- ↑ Fertility –Short & long cycles -- ↑ Spontaneous abortion Body Mass Index Body Mass Index – ↑ BMI -- long, irregular cycles – ↑ BMI -- ↑ twinning

3 Why this question? Goal to determine whether menstrual cycle characteristics can act as a surrogate for reproductive health Goal to determine whether menstrual cycle characteristics can act as a surrogate for reproductive health “Natural” twinning trends may be used as an indicator of reproductive health “Natural” twinning trends may be used as an indicator of reproductive health Unique cohort to study twinning Unique cohort to study twinning –223 Twins –Before ART and OC use were common Menstrual cycle length was asked before birth outcome (less recall bias) Menstrual cycle length was asked before birth outcome (less recall bias)

4 Study Population 97 Twins 31 Twins

5 Exposure & Outcome Menstrual Cycle Length: Menstrual Cycle Length: –Short (<25 days) –Average (25-35 days) –Long/Irregular (> 35 days) Twinning: Twinning: –In CHDS: 223/20307 births (1.07%) –Final dataset - 97 twins –Discordant sex twin dataset - 31 twins

6 Univariate Analyses Age* Age* Race* Race* Education* Education* Pre-pregnancy BMI Pre-pregnancy BMI Current BMI Current BMI Smoking status* Smoking status* Cigarettes/day* Cigarettes/day* Alcohol use Alcohol use Coffee intake* Coffee intake* Tea intake Tea intake Age of menarche* Age of menarche* Pregnancy outcome Pregnancy outcome Parity Parity Interval between pregnancies Interval between pregnancies * Associated with menstrual cycle length Associated with twinning

7 Chi Square Analyses Number and percents of singletons and twins for each category of menstrual cycle length, Child Health and Development Studies, Oakland, CA, 1959-1967. Menstrual Cycle Length Outcome Short n=597 (6.3%) Average n=6639 (69.7%) Long/ Irregular n=777 (24.0%)   P- value Singletons575 (98.1)6492 (98.9)2267 (99.4) 9.3 0.01 Twins11 (1.9)73 (1.1)13 (0.6)

8 Bivariate Analyses Proportion of Twinning (%) Characteristic Short Cycle n=586 Average Cycle n=6565 Stratum- Specific RR (95% CI) Mantel- Haenszel RR (95% CI) Breslow- Day Test for Homo- geneity All1.91.1NA1.7 (0.9, 3.2)NA EducationNA3.2 (0.1) <= High School0.71.0  > High School3.21.2  Log likelihood test: Wald  =3.88 p=0.14

9 Bivariate Analysis Proportion of Twinning (%) Characteristic Long/ Irreg n=2280 Average Cycle n=6565 Stratum- Specific RR (95% CI) Mantel- Haenszel RR (95% CI) Breslow- Day Test for Homo- geneity All0.61.1NA0.5 (0.3, 0.9)NA AgeNA9.7 (0.1) <200.80.0NA 20-240.31.1 0.2 (0.1, 1.1) 25-290.41.2 0.3 (0.1, 1.1) 30-340.81.4 0.6 (0.1, 2.5) >340.81.4 0.6 (0.1, 2.5) Log likelihood test: Wald  =12.0 p=0.21

10 Multivariable Analyses Crude Model Odds Ratio 95% CI Short1.70 (0.90, 3.23) Long/ Irregular 0.51 (0.28, 0.92)

11 Multivariable Analyses Crude Model Odds Ratio 95% CI Short1.70 (0.90, 3.23) Long/ Irregular 0.51 (0.28, 0.92) Adjusted Model Short1.83 (0.96, 3.51) Long/ Irregular 0.53 (0.29, 0.98) Age1.01 (0.98, 1.05) Pre-pregnancy BMI 1.10 (0.64, 1.90) Race1.41 (0.92, 2.16) Parity1.99 (1.09, 3.63) Smoke1.52 (0.99, 2.33) Age of menarche 1.36 (0.83, 2.22)

12 Multivariable Analyses Crude Model Odds Ratio 95% CI Short1.70 (0.90, 3.23) Long/ Irregular 0.51 (0.28, 0.92) Restricted to Different Sex Twins Short3.08 (1.24, 7.63) Long/ Irregular 0.39 (0.12, 1.31)

13 Conclusion Found association between menstrual cycle length and twinning Found association between menstrual cycle length and twinning Limitations include the large amount of missing data Limitations include the large amount of missing data Potential confounders did not change the estimate of the effect Potential confounders did not change the estimate of the effect Interaction was not significant Interaction was not significant

14 Future Directions ♀♂ ♀♀ ♂♂ ♀♀ DZ MZ Restricted Data Set Potential Exclusions


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