Accuracy of Reporting of Menstrual Cycle Length

Jukic, Anne Marie Z.; Weinberg, Clarice R.; Wilcox, Allen J.; McConnaughey, D. Robert; Hornsby, Paige P.; Baird, Donna D.

doi:10.1093/aje/kwm265

Cited by 121 publications

(100 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…nurses in the similar NHS I and NHS II were shown to report health data accurately for several medical conditions (31,32). Previous studies that have investigated the accuracy of self-reported menstrual cycle length by comparing initial self-reported "usual" length with prospective diaries, however, Jukic et al (33) and Small et al (34) reported that 21% of cycle length categories were misclassified.…”

Section: Lawson Et Almentioning

confidence: 99%

Work schedule and physically demanding work in relation to menstrual function: the Nurses’ Health Study 3

Lawson

Johnson²,

Chavarro³

et al. 2015

Scand J Work Environ Health

View full text Add to dashboard Cite

Section: Lawson Et Almentioning

confidence: 99%

Work schedule and physically demanding work in relation to menstrual function: the Nurses’ Health Study 3

Lawson

Johnson²,

Chavarro³

et al. 2015

Scand J Work Environ Health

View full text Add to dashboard Cite

“…Other studies have attempted to time specimen collection to key hormonal events based on self-reported cycle length or cycle day or the assumption that the luteal phase is 14 days [23][24][25], but these methods assume that women can reliably report their cycle length or that the timing of hormonal fluctuations is the same across women, both of which are unlikely to be true [26][27][28][29][30]. The 'gold standard' is daily collection of first-morning urine specimens, which ensures that critical hormone windows are captured if compliance is adequate, but the protocol is burdensome, which affects recruitment and compliance.…”

Section: Introductionmentioning

confidence: 99%

Identification and prediction of the fertile window with a new web-based medical device using a vaginal biosensor for measuring the circadian and circamensual core body temperature

Regidor¹,

Kaczmarczyk

Schiweck

et al. 2017

Gynecological Endocrinology

View full text Add to dashboard Cite

(2018) Identification and prediction of the fertile window with a new web-based medical device using a vaginal biosensor for measuring the circadian and circamensual core body temperature, Gynecological Endocrinology, 34:3, 256-260, DOI: 10.1080/09513590.2017 Fertility awareness-based (FAB) methods represent a term that includes all family planning methods that are based on the identification of the fertile window. They are based on the woman's observation of physiological signs of the fertile and infertile phases of the menstrual cycle. The first approach consists basically in symptothermal methods accompanied by cervical mucus measurements and clinical menstrual cycling data recording. The second most often used methods are the urinary measurement of E3G and luteinizing hormone (LH) with a personalized computer system. Hence these systems lack the efficacy of the continuous circadian and circamensual measurement of the core body temperature. Only this approach enables the accurate detection of the ovulation during the fertile window. A new medical device called OvulaRing has been developed to fill this gap. In the present study, the system and its first clinical results are presented. OvulaRing is a medical device used just like a tampon. The device is a vaginal ring of evatane that contains an integrated biosensor. This sensor measures continuously every 5 min the core body temperature throughout the entire cycle. This device allows a circadian and circamensual intravaginal exact measurement. With this system, 288 measurements are created per day. The system can detect retrospectively and predict prospectively the fertile window of the users. One hundred and fifty eight women aged between 18 and 45 years used this medical device in an open non-randomized clinical study for 15 months. A total of 470 cycles could be recorded and were able for analysis. By the same time in a subgroup of patients, hormonal assessments of LH, follicle-stimulating hormone, estradiol and progesterone as well as vaginal ultrasound were performed in parallel between the 9th and the 36th day of the cycle. The validation error due to software errors was 0.89% for the retrospective analysis; that means that the accuracy for the detection of the ovulation was 99.11%. Accuracy of 88.8% for a window of 3 days before ovulation, the day of ovulation and the 3 days after ovulation was achieved for the prospective analysis. In the subgroup of woman with recorded pregnancies, it could be shown that after 3.79 months of use (median) pregnancies were observed. In 67.72% in up to 3 months, in 16.36% between 3 and 6 months of use, in 7.27% between 7 and 9 months, in 5.45% between 10 and 12 months and in 1.82% between 13 and 15 months of use of the system. With this new web-based system, a precise determination of the fertile window even in women with ultralong cycles (>35 days) could be detected independently of their personal live circumstances. Exact determination of the fertile window is herewith possible so that OvulaRing represents an evolut...

show abstract

“…Other studies have suggested that retrospective self-reports of menstrual history are prone to have errors [20] with volatile accuracy between diary records and retrospectively recalled menstrual history. [21] Second, hormones such as estrogen, testosterone, sex hormonebinding globulin, follicle-stimulating hormone, and luteinizing hormone that may affect the associations between body fat and menstrual cycle characteristics were not examined, nor we were able to find whether women with irregular or variable cycles were anovulatory or oligo-ovulatory. A study has reported that obese women have increased estrogen, luteinizing hormone levels, or an increased ratio of androgen to estrogen.…”

Section: Discussionmentioning

confidence: 99%

Prevalence of menstrual irregularities in correlation with body fat among students of selected colleges in a district of Tamil Nadu, India

G¹,

D²,

C³

2017

Natl J Physiol Pharm Pharmacol

View full text Add to dashboard Cite

Background: Menstrual irregularities are usually due to imbalance of hormones. Although menstrual irregularities may be normal during the early postmenarchal years, pathological conditions require proper and prompt management. Obesity associated with many health consequences including hormonal imbalance has a direct effect on menstrual cycle. Hence, attention to obesity is obligatory for the inclusion of diagnosis and treatment of menstrual complaints which has become a leading issue in women's life. Aims and Objectives: The aims and objectives of the study are to assess the menstrual irregularities and to find the association between menstrual irregularities and body fat among students. Materials and Methods: A cross-sectional study was conducted in three selected colleges in a district of Tamil Nadu in India. A total of 399 samples were included in the study. A 10-item questionnaire was administered to assess the menstrual irregularity in each student. The demographic variables along with anthropometric measurements were collected. Anthropometric measurements were taken to calculate the body fat percentage using modified YMCA formula. Results: The prevalence of menstrual irregularities was high in obesity compared with those with normal body fat and particularly oligomenorrhea, amenorrhea, and hypomenorrhea had statistically significant increase in obese students. Conclusion: This study revealed 4-fold increase in the prevalence of menstrual irregularities in students with increased body fat when compared with the normal. Effective steps to reduce body fat by regular exercise, healthy eating habits and lifestyle modifications should be undertaken to revert menstrual irregularities back to normal. Young women can thus lead a normal active life and prevent infertility which has become a most striking event in this generation.

show abstract

Accuracy of Reporting of Menstrual Cycle Length

Cited by 121 publications

References 17 publications

Work schedule and physically demanding work in relation to menstrual function: the Nurses’ Health Study 3

Work schedule and physically demanding work in relation to menstrual function: the Nurses’ Health Study 3

Identification and prediction of the fertile window with a new web-based medical device using a vaginal biosensor for measuring the circadian and circamensual core body temperature

Prevalence of menstrual irregularities in correlation with body fat among students of selected colleges in a district of Tamil Nadu, India

Contact Info

Product

Resources

About