Quantifying Selection Bias in Cross-Sectional Studies of Ovarian Hormones

Most studies of ovarian hormones in adult women collect data from a cross-sectional sample of participants meeting various selection criteria including not having been pregnant or breastfeeding for several months. Although this approach is intended to eliminate the effects of these factors on hormonal variation, it introduces a selection bias of unknown magnitude: in a non-contracepting population, those women with the highest fecundity are more likely to be either pregnant or lactating, and so not included in a study sample. Thus a cross-sectional sample disproportionately represents women with the lowest fecundity (and potentially the lowest hormone levels). Here we present a preliminary evaluation of the magnitude of this selection bias, focusing on progesterone ($P$) levels near the luteal peak. We use data from Project REPA, a longitudinal study of reproductive functioning in rural Bolivians, recruited without regard to reproductive status (Vitzthum, Spielvogel, and Thornburg \textit{Proceedings of the U.S. National Academy of Sciences/} 101, 1443 (2004)). Drawing from 542~non-conception cycles in 144~women, we construct simulated cross-sectional samples meeting various inclusion criteria and compare their anovulation rates and progesterone levels.National Science Foundation, University of California, Binghamton University, Indiana Universit

Characterizing physiological and symptomatic variation in menstrual cycles using self-tracked mobile health data

The menstrual cycle is a key indicator of overall health for women of reproductive age. Previously, menstruation was primarily studied through survey results; however, as menstrual tracking mobile apps become more widely adopted, they provide an increasingly large, content-rich source of menstrual health experiences and behaviors over time. By exploring a database of user-tracked observations from the Clue app by BioWink of over 378,000 users and 4.9 million natural cycles, we show that self-reported menstrual tracker data can reveal statistically significant relationships between per-person cycle length variability and self-reported qualitative symptoms. A concern for self-tracked data is that they reflect not only physiological behaviors, but also the engagement dynamics of app users. To mitigate such potential artifacts, we develop a procedure to exclude cycles lacking user engagement, thereby allowing us to better distinguish true menstrual patterns from tracking anomalies. We uncover that women located at different ends of the menstrual variability spectrum, based on the consistency of their cycle length statistics, exhibit statistically significant differences in their cycle characteristics and symptom tracking patterns. We also find that cycle and period length statistics are stationary over the app usage timeline across the variability spectrum. The symptoms that we identify as showing statistically significant association with timing data can be useful to clinicians and users for predicting cycle variability from symptoms or as potential health indicators for conditions like endometriosis. Our findings showcase the potential of longitudinal, high-resolution self-tracked data to improve understanding of menstruation and women's health as a whole.Comment: The Supplementary Information for this work, as well as the code required for data pre-processing and producing results is available in https://github.com/iurteaga/menstrual_cycle_analysi

Recognizing normal reproductive biology: A comparative analysis of variability in menstrual cycle biomarkers in German and Bolivian women

The idealized “normal” menstrual cycle typically comprises a coordinated ebb and flow of hormones over a 28-day span with ovulation invariably shown at the midpoint. It's a pretty picture—but rare. Systematic studies have debunked the myth that cycles occur regularly about every 28 days. However, assumptions persist regarding the extent and normalcy of variation in other cycle biomarkers. The processes of judging which phenotypic variants are “normal” is context dependent. In everyday life, normal is that which is most commonly seen. In biomedicine normal is often defined as an arbitrarily bounded portion of the phenotype's distribution about its statistical mean. Standards thus defined in one population are problematic when applied to other populations; population specific standards may also be suspect. Rather, recognizing normal female reproductive biology in diverse human populations requires specific knowledge of proximate mechanisms and functional context. Such efforts should be grounded in an empirical assessment of phenotypic variability. We tested hypotheses regarding cycle biomarker variability in women from a wealthy industrialized population (Germany) and a resource-limited rural agropastoral population (Bolivia). Ovulatory cycles in both samples displayed marked but nonetheless comparable variability in all cycle biomarkers and similar means/medians for cycle and phase lengths. Notably, cycle and phase lengths are poor predictors of mid-luteal progesterone concentrations. These patterns suggest that global and local statistical criteria for “normal” cycles would be difficult to define. A more productive approach involves elucidating the causes of natural variation in ovarian cycling and its consequences for reproductive success and women's health

How It Works: The Biological Mechanisms that Generate Demographic Diversity

Tinbergen (1963) proposed that a complete understanding of any behavior requires knowledge of its function, evolutionary history, developmental history, and mechanism of operation. This chapter is largely concerned with gaining some insight into the nature of the biological mechanisms generating variation in human fertility and, consequently, demographic diversity within and across populations. My inquiry is informed by life history theory, an analytical framework within evolutionary theory for studying maturation, reproduction, and aging and the associated behavioral and physiological mechanisms underlying the allocation of resources to these processes. Different allocation patterns are referred to as life history strategies (LHSs) and are subject to natural selection. Biological mechanisms can be usefully conceptualized as a set of suitably timed strategic responses to signals. I discuss this and other ideas about the mechanisms that underlie the implementation of LHSs, and introduce the concepts of "ecomarkers" and "the physiological fallacy." Drawing on empirical studies and theoretical models, I examine some intriguing features of human reproductive physiology that are directly relevant to demographic research in both low- and high-fertility populations. Several points, some contrary to common assumptions, emerge from this inquiry. For example: (1) The marked within- and between-population variation in many features of female reproductive functioning challenges the widespread assumption that there is a universal "normal" human biology. (2) The most likely outcome of a human conception is early loss. This unseen natural selection in the production of offspring may hamper investigations of hypothesized associations of post-natal reproductive success with resources or with offspring quality, even in low fertility populations. (3) Competition between incompatible but essential functions shape the timing and operation of various mechanisms. Some biological, psychological and behavioral functions cannot readily co-occur. Of necessity, successful LHSs must juggle such incompatibilities regardless of the abundance of energy and other resources, therefore some reproductive mechanisms may not depend upon (or be responsive to) energy availability. (4) Biomedically, the absence of ovulation is typically considered a pathology (and in some cases it may be). But from a life history perspective, each option of ovulating/not ovulating is a fork in the reproductive road at which there is a strategic decision to continue engaging in the possibility of reproduction or to forego the current opportunity. Not ovulating in a given cycle can be the best strategy for optimizing lifetime reproductive success

Links among inflammation, sexual activity and ovulation Evolutionary trade-offs and clinical implications

Background and objectives: We examined a mechanism that may coordinate trade-offs between reproduction and immune response in healthy women, namely, changes in inflammation across the ovarian cycle. Methodology: We investigated C-reactive protein (CRP), an inflammation marker, across two consecutive ovarian cycles in 61 Bolivian women. Participants provided saliva samples every other day, and dried blood spots on 5–6 days spread across weeks 2–3 of each cycle. Cycles were characterized as ovulatory/ anovulatory based on profiles of reproductive hormones. Participants also reported whether they were sexually partnered with a male or sexually abstinent during the study. Results: High early-cycle, but not late-cycle, CRP was associated with anovulation. High inflammation at the end of one cycle was not associated with anovulation in the subsequent cycle. Among ovulatory cycles, women with sexual partners had significantly lower CRP at midcycle, and higher CRP at follicular and luteal phases; in contrast, sexually abstinent women had little cycle-related change in CRP. In anovulatory cycles, partnership had no effect on CRP. CRP varied significantly with socioeconomic status (higher in better-off than in poorer women). Conclusions and implications: These findings suggest that the cycle-specific effect of inflammation on ovarian function may be a flexible, adaptive mechanism for managing trade-offs between reproduction and immunity. Sociosexual behavior may moderate changes in inflammation across the ovarian cycle, suggesting that these shifts represent evolved mechanisms to manage the trade-offs between reproduction and immunity. Clinically, these findings support considering both menstrual cycle phase and sexual activity in evaluations of pre-menopausal women’s CRP concentrations

Inter-Organizational Learning in Technology Acquisitions: Procuring More Than Knowledge

The fifth wave of Merger and Acquisition includes an increasing amount of technology acquisitions. Large firms acquire small, technology-centric firms as an external source of knowledge and innovation. A major challenge in these acquisitions is to capture the knowledge of the acquired firm as well as to assimilate and utilize it in the acquiring company. We extend March’s (1991) model of organizational learning through exploration and exploitation with an agent-based model allowing knowledge transfer across organizational boundaries from a target organization to an acquiring organization through (1) retention of employees from the smaller company into the large one or through (2) appropriation of the smaller target company’s organizational code by incorporation of industry best practice or cutting-edge technology. Our preliminary results qualify and extend March’s (1991) conclusions

Human ovarian reserve from conception to the menopause

Current understanding is that the human ovary contains a fixed number of several million non-growing follicles (NGF), established by five months of gestational age, that declines with increasing age to the menopause when approximately 1,000 NGF remain at an average age of 50-51 years. With approximately 450 ovulatory monthly cycles in the normal human reproductive lifespan, this progressive decline in NGF numbers is attributed to follicle death by apoptosis. Individual histological studies have quantified NGF numbers over limited age ranges. However, no model describing the rate of establishment and decline of the NGF population from conception to menopause has been previously reported. Here we describe the best fitting model of the age-related NGF population in the human ovary from conception to menopause. Our model matches the log-adjusted NGF population to a five-parameter asymmetric double Gaussian cumulative (ADC) curve (r2 = 0.81). Furthermore we found that the rate of NGF recruitment into growing follicles for all women increases from birth until approximately age 14 years (coinciding with puberty) then decreases towards the menopause. The explanation for this new finding remains unclear but is likely to involve both paracrine and endocrine factors. We describe and analyse the best fitting model for the establishment and decline of human NGF; our model extends our current understanding of human ovarian reserve

Decaying Raphia farinifera Palm Trees Provide a Source of Sodium for Wild Chimpanzees in the Budongo Forest, Uganda

For some years, chimpanzees have been observed eating the pith of decaying palm trees of Raphia farinifera in the Budongo Forest, Uganda. The reasons for doing this have until now been unknown. An analysis of the pith for mineral content showed high levels of sodium to be present in the samples. By contrast, lower levels were found in bark of other tree species, and also in leaf and fruit samples eaten by chimpanzees. The differences between the Raphia samples and the non-Raphia samples were highly significant (p<0.001). It is concluded that Raphia provides a rich and possibly essential source of sodium for the Budongo chimpanzees. Comparison of a chewed sample (wadge) of Raphia pith with a sample from the tree showed a clear reduction in sodium content in the chewed sample. Black and white colobus monkeys in Budongo Forest also feed on the pith of Raphia. At present, the survival of Raphia palms in Budongo Forest is threatened by the use of this tree by local tobacco farmers

Dental metric assessment of the Omo fossils: Implications for the phylogenetic position of Australopithecus africanus

The discovery of Australopithecus afarensis has led to new interpretations of hominid phylogeny, some of which reject A. africanus as an ancestor of Homo. Analysis of buccolingual tooth crown dimensions in australopithecines and Homo species by Johanson and White (Science 202 :321–330, 1979) revealed that the South African gracile australopithecines are intermediate in size between Laetoli/Hadar hominids and South African robust hominids. Homo , on the other hand, displays dimensions similar to those of A. afarensis and smaller than those of other australopithecines. These authors conclude, therefore, that A. africanus is derived in the direction of A. robustus and is not an ancestor of the Homo clade. However, there is a considerable time gap (ca. 800,000 years) between the Laetoli/Hadar specimens and the earliest Homo specimens; “gracile” hominids from Omo fit into this chronological gap and are from the same geographic area. Because the early specimens at Omo have been designated A. afarensis and the later specimens classified as Homo habilis , Omo offers a unique opportunity to test hypotheses concerning hominid evolution, especially regarding the phylogenetic status of A. africanus. Comparisons of mean cheek teeth breadths disclosed the significant (P < 0.05) differences between the Omo sample and the Laetoli/Hadar fossils (P 4 , M 2 , and M 3 ), the Homo fossils (P 3 , P 4 , M 1 , M 2 , and M 1 ), and A. africanus (M 3 ). Of the several possible interpretations of these data, it appears that the high degree of similarity between the Omo sample and the South African gracile australopithecine material warrants considering the two as geographical variants of A. africanus. The geographic, chronologic, and metric attributes of the Omo sample argue for its lineal affinity with A. afarensis and Homo. In conclusion, a consideration of hominid postcanine dental metrics provides no basis for removing A. africanus from the ancestry of the Homo lineage.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/37635/1/1330710203_ftp.pd

Body size variation in baboons: A reconsideration of ecological determinism

Popp (1983) presented an intriguing argument regarding the covariation of body size in baboons and rainfall. However, a reanalysis of the data indicates that “Principle 2” of the model is not supported.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/41603/1/10329_2006_Article_BF02380856.pd