Identification of Anovulation and Transient Luteal Function Using a Urinary Pregnanediol-3-Glucuronide Ratio Algorithm

Institute of Toxicology and Environmental Health, University of California, Davis 95616, USA.
Environmental Health Perspectives (Impact Factor: 7.98). 04/1996; 104(4):408-13. DOI: 10.1289/ehp.96104408
Source: PubMed


The sensitivity and specificity of a urinary pregnanediol-3-glucuronide (PdG) ratio algorithm to identify anovulatory cycles was studied prospectively in two independent populations of women. Urinary hormone data from the first group was used to develop the algorithm, and data from the second group was used for its validation. PdG ratios were calculated by a cycles method in which daily PdG concentrations indexed by creatinine (CR) from cycle day 11 onward were divided by a baseline PdG (average PdG/Cr concentration for cycle days 6-10). In the interval method, daily PdG/CR concentrations from day 1 onward were divided by baseline PdG (lowest 5-day average of PdG/CR values throughout the collection period). Evaluation of the first study population (n = 6) resulted in cycles with PdG ratios > or = 3 for > or = 3 consecutive days being classified as ovulatory; otherwise they were anovulatory. The sensitivity and specificity of the PdG ratio algorithm to identify anovulatory cycles in the second population were 75% and 89.5%, respectively, for all cycles (n = 88); 50% and 88.3% for first cycles (n = 40) using the cycles method; 75% and 92.2%, respectively, for all cycles (n = 89); and 50% and 94.1% for first cycles (n = 40) using the interval method. The "gold standard" for anovulation was weekly serum samples < or = 2 ng/ml progesterone. The sensitivity values for all cycles and for the first cycle using both methods were underestimated because of apparent misclassification of cycles using serum progesterone due to infrequent blood collection. Blood collection more than once a week would have greatly improved the sensitivity and modestly improved the specificity of the algorithm. The PdG ratio algorithm provides an efficient approach for screening urine samples collected in epidemiologic studies of reproductive health in women.

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    • "Similar to each previous study of hormone-binge eating associations (Klump, Keel, Racine, et al., 2013; Klump et al., 2008), five-day rolling averages were calculated for hormones, negative affect, emotional eating , and BMI. Rolling averages minimize random variation in behavioral data due to environmental circumstances (Gladis & Walsh, 1987) and smooth the pattern of hormone variability (Kassam et al., 1996; Waller et al., 1998). Given that BMI was assessed at three time points rather than daily, we calculated rolling averages using visit 1 BMI for days in-between visits 1 and 2, visit 2 BMIs for days in-between visits 2 and 3, and visit 3 BMI for the last assessment day (day 45) All rolling averages were converted to within-person standardized scores based on each participant's overall mean and standard deviation across data collection. "
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    ABSTRACT: Within-person changes in estradiol and progesterone predict changes in binge eating tendencies across the menstrual cycle. However, all women have menstrual-cycle fluctuations in hormones, but few experience binge eating. Personality traits may be critical individual difference factors that influence who will engage in emotional eating in the presence of a vulnerable hormonal environment. Women (N=239) provided self-reports of emotional eating and saliva samples for hormone measurement for 45 consecutive days. Negative urgency and negative emotionality were measured once and were examined as moderators of hormone-emotional eating associations. Consistent with prior research, within-person changes in the interaction between estradiol and progesterone predicted emotional eating. Neither negative urgency nor negative emotionality interacted with changes in estradiol and progesterone to predict changes in emotional eating. Additional factors, other than the two personality traits examined, may account for individual differences in within-person associations between hormones and emotional eating.
    Eating behaviors 04/2013; 14(2):161-6. DOI:10.1016/j.eatbeh.2013.02.007
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    • "Five-day rolling averages were calculated for hormones, emotional eating, negative affect, and BMI. Rolling averages reduce the influence of hormone pulsatility and increase the signalto-noise ratio by minimizing random environmental variations (e.g., decreased opportunities to binge eat) (Gladis & Walsh, 1987; Kassam et al., 1996; Waller et al., 1998). Because BMI was assessed at only three time points, rolling averages were calculated using visit 1 BMI for days in between visits 1 and 2, visit 2 BMIs for days in between visits 2 and 3, and visit 3 BMI for the last assessment day (Day 45). "
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    ABSTRACT: Studies suggest that within-person changes in estrogen and progesterone predict changes in binge eating across the menstrual cycle. However, samples have been extremely small (maximum N = 9), and analyses have not examined the interactive effects of hormones that are critical for changes in food intake in animals. The aims of the current study were to examine ovarian hormone interactions in the prediction of within-subject changes in emotional eating in the largest sample of women to date (N = 196). Participants provided daily ratings of emotional eating and saliva samples for hormone measurement for 45 consecutive days. Results confirmed that changes in ovarian hormones predict changes in emotional eating across the menstrual cycle, with a significant estradiol × progesterone interaction. Emotional eating scores were highest during the midluteal phase, when progesterone peaks and estradiol demonstrates a secondary peak. Findings extend previous work by highlighting significant interactions between estrogen and progesterone that explain midluteal increases in emotional eating. Future work should explore mechanisms (e.g., gene-hormone interactions) that contribute to both within- and between-subjects differences in emotional eating. (PsycINFO Database Record (c) 2012 APA, all rights reserved).
    Journal of Abnormal Psychology 08/2012; 122(1). DOI:10.1037/a0029524 · 4.86 Impact Factor
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    • "There was only one subject in the described sample for whom this condition was not fulfilled and this subject was removed from analyses. Cycles were assigned as ovulatory when PdG daily values were at least three times higher when compared to the baseline and this increase in concentrations persisted for at least three days (Kassam et al., 1996). The day of ovulation was inferred from changes in E1G to PdG ratio during the cycle using the day of luteal transition algorithm (DLT), (Baird et al., 1991) with modification for low concentrations of PdG (Waller et al., 1998). "
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    ABSTRACT: Personality and temperament were hypothesized to function as important factors affecting life history strategies. Recent research has demonstrated the association between temperamental traits and reproduction in humans, however, the underlying mechanisms are still poorly understood. This study presents evidence for an association between temperamental traits and woman's fecundity, as indicated by levels of ovarian steroid hormones during the menstrual cycle. On a large sample of urban, reproductive age women (n = 108) we demonstrated that activity, endurance and emotional reactivity are associated with levels of estrogen and with a pattern of change of progesterone levels. Women high in activity, high in endurance and low in emotional reactivity had up to twice as high estradiol levels and more favorable progesterone profiles as women low in activity, low in endurance and high in emotional reactivity. The temperamental traits we measured highly overlap with extraversion, neuroticism and negative emotionality that were reported to correlate with reproductive success. Our findings thus suggest a possible explanation for these relationships, linking personality and women's reproductive success through a hormonal pathway.
    Hormones and Behavior 02/2012; 61(4):535-40. DOI:10.1016/j.yhbeh.2012.01.017 · 4.63 Impact Factor
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