STANDARDIZED PROTOCOLS FOR CHARACTERIZING WOMEN S FERTILITY

Transcription

1 STANDARDIZED PROTOCOLS FOR CHARACTERIZING WOMEN S FERTILITY A DATA-DRIVEN APPROACH KHANDIS R. BLAKE THE UNIVERSITY OF NEW SOUTH WALES, AUS

2 DOES WOMEN S BEHAVIOR AND COGNITION DIFFER BETWEEN FERTILE AND NON-FERTILE CYCLE PHASES? YES NO Female sexual activity rigidly controlled by ovarian hormones with ovulation accompanying striking behavioral changes rats, cats, cattle, sheep (Dixson, 2012; Feder, 1981) BUT pattern isn t universal across mammals, esp. in some anthropoid primates (Wallen, 2001) BUT Women engage in sexual activity across the ovulatory cycle Sexual attractiveness judgements, sexual proceptivity, and self-report sexual receptivity all heighten during high fertility cycle phases (Gangestad & Haselton, 2015) Meta-analysis by Gildersleeve Haselton & Fales, 2014 BUT claims that positive findings are artifacts of poorly defined and variably applied methodology (Harris et al., 2014; Wood, 2015; Wood & Carden, 2014). AND Meta-analysis by Wood et al. 2014

3 WE PROVIDE A DATA-DRIVEN METHOD OF BEST PRACTICES FOR CHARACTERIZING WOMEN S FERTILE PHASE Forward-counting method Predicts ovulation will happen on Day 14 Backward-counting method Predicts ovulation will happen on Day -14 Six-day fertile window analysis Conception probability analysis We used four variations, varying in the manner that they predicted the new cycle onset ( by estimating the current cycle length) 1. BC from self-reported length 2. BC from prior length (last cycle measured within experiment) 3. BC from prior/rep average 4. BC from average of all cycle data (up to 5 months) Fertility is highest during a six-day window ending on the day of ovulation itself Probability of conception resulting from intercourse on a day relative to ovulation

4 HOW ACCURATELY DO COUNTING METHODS ESTIMATE OVULATION? Forward-counting method BC from reported length BC from prior length BC from prior + rep average Figure 1. Frequency distributions of detected LH surge days according to cycle method for ovulatory cycles.

5 HOW ACCURATELY DO CMS ESTIMATE THE SIX- DAY WINDOW & CONCEPTION PROBABILITIES? Table 3. Percentage of luteinizing hormone-verified fertile days in the fertile windows outlined by the counting methods (ovulatory cycles only). Forward-counting method Backward-counting methods Reported length Prior length Reported and prior averaged All months and reported averaged NF days F days NF days F days NF days F days NF days F days NF days F days Day Day Day Day Day Day Day Day Day Day Day Day Days predicted fertile Days actually fertile Percentage 40.6% 60.5% 58.4% 58.6% 59.2% Table 4. Associations between predicted and actual conception probabilities of alternate cycle length estimators for ovulatory cycles. Cycle length estimate Conception probability estimates for the predicted day of ovulation Conception probability estimates for the six-day fertile window Correlation between actual and predicted conception probability M (SD) Total N T a M (SD) Total N T b r [95% CI] Forward-counting method.115 (.088) ***.064 (.059) *** NS [-0.02, 0.13] Backward-counting methods Reported length.134 (.082) ***.103 (.058) *** 0.30 *** [0.20, 0.40] Length of prior cycle.135 (.084) ***.101 (.053) *** 0.20 *** [0.11, 0.28] Prior cycle + reported average.139 (.081) ***.101 (.056) *** 0.21 *** [0.13, 0.31] Average of all measured and.137 (.082) ***.101 (.056) *** 0.22 *** [0.13, 0.31] reported lengths Note. a Test value =.180; the average actual conception probability on the day of ovulation (see the ESM for values averaged). b Test value =.166; the average conception probability of the six high-fertility cycle days (see the ESM for values averaged). *** p <.001. NS = Not significant.

6 OUR DATA-DRIVEN, BEST PRACTICE PROTOCOL Future research should include direct measures of ovulation We provide pragmatic sampling guidelines and freely available documentation to support using this method. Note. This was part of a larger study on fertility effects on implicit and explicit sexual openness and general assertiveness. If youre interested in those results, come see me. THANK YOU TO MY COLLABORATORS: Siobhan O Dean; Barnaby Dixon, and Tom Denson