Dataset Information

Accounting for length-bias and selection effects in estimating the distribution of menstrual cycle length.

ABSTRACT: Prospective pregnancy studies are a valuable source of longitudinal data on menstrual cycle length. However, care is needed when making inferences of such renewal processes. For example, accounting for the sampling plan is necessary for unbiased estimation of the menstrual cycle length distribution for the study population. If couples can enroll when they learn of the study as opposed to waiting for the start of a new menstrual cycle, then due to length-bias, the enrollment cycle will be stochastically larger than the general run of cycles, a typical property of prevalent cohort studies. Furthermore, the probability of enrollment can depend on the length of time since a woman's last menstrual period (a backward recurrence time), resulting in selection effects. We focus on accounting for length-bias and selection effects in the likelihood for enrollment menstrual cycle length, using a recursive two-stage approach wherein we first estimate the probability of enrollment as a function of the backward recurrence time and then use it in a likelihood with sampling weights that account for length-bias and selection effects. To broaden the applicability of our methods, we augment our model to incorporate a couple-specific random effect and time-independent covariate. A simulation study quantifies performance for two scenarios of enrollment probability when proper account is taken of sampling plan features. In addition, we estimate the probability of enrollment and the distribution of menstrual cycle length for the study population of the Longitudinal Investigation of Fertility and the Environment Study.

SUBMITTER: Lum KJ

PROVIDER: S-EPMC4263226 | biostudies-literature | 2015 Jan

REPOSITORIES: biostudies-literature

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Accounting for length-bias and selection effects in estimating the distribution of menstrual cycle length.

Lum Kirsten J KJ Sundaram Rajeshwari R Louis Thomas A TA

Biostatistics (Oxford, England) 20140714 1

Prospective pregnancy studies are a valuable source of longitudinal data on menstrual cycle length. However, care is needed when making inferences of such renewal processes. For example, accounting for the sampling plan is necessary for unbiased estimation of the menstrual cycle length distribution for the study population. If couples can enroll when they learn of the study as opposed to waiting for the start of a new menstrual cycle, then due to length-bias, the enrollment cycle will be stochas ...[more]

PMID: 25027273

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Project description:BackgroundLocal inflammation plays an important role in normal folliculogenesis and ovulation, and conditions of chronic systemic inflammation, such as obesity and polycystic ovarian syndrome, can disrupt normal follicular dynamics.ObjectiveThis study aimed to determine the association between systemic inflammation, as measured by C-reactive protein levels, and menstrual cycle length.Study designThis study was a secondary analysis using data from Time to Conceive, a prospective time-to-pregnancy cohort study. The association between cycle length and C-reactive protein was analyzed using multivariable linear mixed and marginal models adjusted for age, race, education, body mass index, time since oral contraceptive use, alcohol, smoking, caffeine consumption, and exercise. Time to Conceive enrolled women aged 30 to 44 years with no history of infertility who were attempting to conceive for <3 months. Serum C-reactive protein levels were measured on cycle day 2, 3, or 4. Participants recorded daily menstrual cycle data for ≤4 months.ResultsMain outcome measures included menstrual cycle length and follicular and luteal phase lengths. Multivariable analysis included 1409 cycles from 414 women. There was no linear association between C-reactive protein levels and menstrual cycle length. However, compared with <1 mg/L, a C-reactive protein level >10 mg/L was associated with >3 times the odds (adjusted odds ratio, 3.7; 95% confidence interval, 1.67-8.11) of long cycles (defined as ≥35 days). When evaluating follicular phase length, a C-reactive protein level of >10 mg/L was associated both with follicular phases that were 1.7 (95% confidence interval, 0.23-3.09) days longer and with >2 times the odds of a long follicular phase (adjusted odds ratio, 2.2; 95% confidence interval, 1.05-4.74).ConclusionThere is a potential pathophysiological association between systemic inflammation and menstrual cycle changes. Further studies are needed to determine if systemic inflammation alters the menstrual cycle or if long menstrual cycles are a marker for elevated systemic inflammation.

Dataset Information

Accounting for length-bias and selection effects in estimating the distribution of menstrual cycle length.

Publications

Accounting for length-bias and selection effects in estimating the distribution of menstrual cycle length.

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