Biomedical subjects

Germaine M Buck Louis

Publications and source records attributed to Germaine M Buck Louis.

6 recordsLinked to original sources

PubMed2006

Preconception maternal polychlorinated biphenyl concentrations and the secondary sex ratio.

The secondary sex ratio is the ratio of male to female live births and historically has ranged from 102 to 106 males to 100 females. Temporal declines have been reported in many countries prompting authors to hypothesize an environmental etiology. Blood specimens were obtained from 99 women aged 24-34 prior to attempting pregnancy and quantified for 76 polychlorinated biphenyl (PCB) congeners using dual column gas chromatography with electron capture detection. Women were prospectively followed until pregnancy or 12 cycles of trying. The odds of a male birth for three PCB groupings (total, estrogenic, anti-estrogenic) controlling for maternal characteristics were estimated using logistic regression. Among the 50 women with live births and PCB data, 26 female and 24 male infants were born (ratio 0.92). After adjusting for age and body mass index, odds of a male birth were elevated among women in the second (OR=1.29) and third (OR=1.48) tertiles of estrogenic PCBs; odds (OR=0.70) were reduced among women in the highest tertile of anti-estrogenic PCBs. All confidence intervals included one. The direction of the odds ratios in this preliminary study varied by PCB groupings, supporting the need to study specific PCB patterns when assessing environmental influences on the secondary sex ratio.

Adult↗

PubMed2006

Environmental influences on female fecundity and fertility.

An increasing body of evidence suggests that environmental exposures are adversely influencing female fecundity and fertility. Endocrine-disrupting compounds (EDCs) are of particular concern, due to their ability to interfere with the body's hormonal milieu. An overview of the literature regarding the effect of EDCs on female fecundity and fertility end points such as puberty, menstruation, endometriosis, time to pregnancy, pregnancy loss, reproductive senescence, and secondary sex ratio is presented. Methodologic challenges in studying the effects EDCs on sensitive reproductive end points are discussed and include exposure to mixtures, the choice of biologic media in which to measure compounds, laboratory methods, and varying modeling techniques. Also reviewed are novel technologies for home-based biospecimen collection and testing that offer promise for field-based research aimed at addressing questions about environmental influences on female fecundity and fertility.

Endocrine Disruptors↗

PubMed2006

Is conception delay a risk factor for reduced gestation or birthweight?

Previous studies have suggested an association between delays in conception and adverse perinatal outcomes, specifically, low birthweight and preterm birth. We investigated the relationship between conception delay (defined as >6 months to become pregnant) and three perinatal outcomes: low birthweight (LBW; <2500 g), preterm birth (PTB; <37 weeks), and small-for-gestational-age (SGA; <10th percentile weight for given gestational age) using data from the Collaborative Perinatal Project. The study cohort was limited to pregnancies with a known time-to-pregnancy (n = 8465; 15%). Generalised estimating equations were used to estimate odds ratios (OR) and 95% confidence intervals [CI] for risk of adverse perinatal outcomes accounting for the clustering of pregnancy outcomes for women with more than one pregnancy. After adjusting for confounders, all ORs were close to the null (LBW, OR = 1.01; 95% CI = 0.86, 1.20), (PTB, OR = 1.10; 95% CI = 0.95, 1.27), (SGA, OR = 1.06; 95% CI = 0.91, 1.25). Thus, we found no evidence to support an adverse relationship between conception delay and decrements in gestation or birthweight among this select sample of fertile women, even after varying the cut-point for defining conception delay.

Adult↗

PubMed2006

Estimation of the day-specific probabilities of conception: current state of the knowledge and the relevance for epidemiological research.

Conception, as defined by the fertilisation of an ovum by a sperm, marks the beginning of human development. Currently, a biomarker of conception is not available; as conception occurs shortly after ovulation, the latter can be used as a proxy for the time of conception. In the absence of serial ultrasound examinations, ovulation cannot be readily visualised leaving researchers to rely on proxy measures of ovulation that are subject to error. The most commonly used proxy measures include: charting basal body temperature, monitoring cervical mucus, and measuring urinary metabolites of oestradiol and luteinising hormone. Establishing the timing of the ovulation and the fertile window has practical utility in that it will assist couples in appropriately timing intercourse to achieve or avoid pregnancy. Identifying the likely day of conception is clinically relevant because it has the potential to facilitate more accurate pregnancy dating, thereby reducing the iatrogenic risks associated with uncertain gestation. Using data from prospective studies of couples attempting to conceive, several researchers have developed models for estimating the day-specific probabilities of conception. Elucidating these will allow researchers to more accurately estimate the day of conception, thus spawning research initiatives that will expand our current limited knowledge about the effect of exposures at critical periconceptional windows. While basal body temperature charting and cervical mucus monitoring have been used with success in field-based studies for many years, recent advances in science and technology have made it possible for women to get instant feedback regarding their daily fertility status by monitoring urinary metabolites of reproductive hormones in the privacy of their own homes. Not only are innovations such as luteinising hormone test kits and digital fertility monitors likely to increase study compliance and participation rates, they provide valuable prospective data that can be used in epidemiological research. Although we have made great strides in estimating the timing and length of the fertile window, more work is needed to elucidate the day-specific probabilities of conception using proxy measures of ovulation that are inherently subject to error. Modelling approaches that incorporate the use of multiple markers of ovulation offer great promise to fill these important data gaps.

Biomarkers↗

PubMed2005

Association of endometriosis with body size and figure.

OBJECTIVE: To determine whether body size and perceived figure, both current and historical, are associated with a diagnosis of endometriosis on laparoscopy. DESIGN: Cohort study of consecutively identified patients undergoing laparoscopy for tubal sterilization or as a diagnostic procedure. SETTING: Two university-affiliated hospitals. PATIENT(S): A cohort of 84 women aged 18-40 years. Endometriosis was visualized in 32 cases; 52 women (controls) had no visualized endometriosis, including 22 undergoing tubal sterilization and 30 with other gynecologic pathology. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): Body mass index (BMI, kg/m2) from self-report and perception of body figure were compared for their ability to predict case status (diagnosed endometriosis), using logistic regression models. Longitudinal trends in BMI based on perceived figure at 5-year intervals from age 15 years were compared using mixed linear models. RESULT(S): Based on self-report, women diagnosed with endometriosis were taller, thinner, and had a significantly lower BMI. In this series, cases were more likely to be late maturers (menarche at > or = 14 y) and late to initiate sexual activity (> or = 21 y), and they were less likely to be gravid, parous, and a current smoker. Adjusting for age (in years), being tall (height > or = 68 in), and parity (yes vs. no), a higher current BMI was statistically protective for a diagnosis of endometriosis, regardless of whether BMI was determined by self-report (adjusted odds ratio [AOR] = 0.88, 95% confidence interval [CI] 0.79-0.99) or from perceived figure (AOR = 0.86, 95% CI 0.75-0.99). For every unit increase in BMI (kg/m2), there was an approximate 12%-14% decrease in the likelihood of being diagnosed with endometriosis. In an adjusted repeated measures model, BMI was 21.3 +/- 0.6 kg/m2 (estimate +/- SE) for women with endometriosis, compared with 23.2 +/- 0.4 kg/m2 for the controls, a difference over all ages of -1.9 +/- 0.8 kg/m2. This is a consistent difference of about 10 lb at every age, assuming an average height of about 64.5 in. CONCLUSION(S): In a laparoscopy cohort, women diagnosed with endometriosis were found to have a lower BMI (leaner body habitus), both at the time of diagnosis and historically. That women diagnosed with endometriosis may have a consistently lean physique during adolescence and young adulthood lends support to the suggestion of there being an in utero or early childhood origin for endometriosis.

Adolescent↗

PubMed2005

Lipid adjustment in the analysis of environmental contaminants and human health risks.

The literature on exposure to lipophilic agents such as polychlorinated biphenyls (PCBs) is conflicting, posing challenges for the interpretation of potential human health risks. Laboratory variation in quantifying PCBs may account for some of the conflicting study results. For example, for quantification purposes, blood is often used as a proxy for adipose tissue, which makes it necessary to model serum lipids when assessing health risks of PCBs. Using a simulation study, we evaluated four statistical models (unadjusted, standardized, adjusted, and two-stage) for the analysis of PCB exposure, serum lipids, and health outcome risk (breast cancer). We applied eight candidate true causal scenarios, depicted by directed acyclic graphs, to illustrate the ramifications of misspecification of underlying assumptions when interpreting results. Statistical models that deviated from underlying causal assumptions generated biased results. Lipid standardization, or the division of serum concentrations by serum lipids, was observed to be highly prone to bias. We conclude that investigators must consider biology, biologic medium (e.g., nonfasting blood samples), laboratory measurement, and other underlying modeling assumptions when devising a statistical plan for assessing health outcomes in relation to environmental exposures.

Bias↗