Associations between multiple metal exposure and fertility in women: A nested case-control study.

Metal pollution can cause a decline in female fertility, however, previous studies have focused more on the effect of a single metal on fertility. In this study, we evaluated the effect of metal mixtures on female fertility based on nested case-control samples. The plasma levels of 22 metal elements from 180 women were determined by an inductively coupled plasma mass spectrometer (ICP-MS). Minimum absolute contraction and selection operator (LASSO) penalty regression selected metals with the greatest influence on clinical outcome. Logistic regression was used to analyze the correlation between single metals and fertility while a Bayesian kernel function regression (BKMR) model was used to analyze the effect of mixed metals. Eight metals (Calcium (Ca), Chromium (Cr), Cobalt (Co), Copper (Cu), Zinc (Zn), Rubidium (Rb), Strontium (Sr) and Zirconium (Zr)) were selected by LASSO regression for subsequent analysis. After adjusting for covariates, the logistic model showed that Cu (Odds Ratio(OR):0.33, 95% CI: 0.13 - 0.84) and Co (OR:0.38, 95% CI: 0.15 -0.94) caused a significant reduction in fertility, and identified the protective effect of Zn (OR: 2.96, 95% CI:1.21 -7.50) on fertility. Trend tests showed that increased Cr, Cu, and Rb levels were associated with reduced fertility. The BKMR model showed that Cr, Co, Cu, and Rb had a nonlinear relationship with fertility decline when controlling for the concentrations of other metals and suggested that Cu and Cr might exert an influence on fertility. Analysis showed a negative correlation between Cu, Cr, Co, Rb, and fertility, and a positive correlation between Zn and fertility. Furthermore, we found evidence for the interaction between Cu and Cr. Our findings require further validation and may identify new mechanisms in the future.

Relationship between mental health, sleep status and screen time among university students during the COVID-19 pandemic: a cross-sectional study.

OBJECTIVE: On 20 July 2021, after the outbreak of COVID-19 at Nanjing Lukou International Airport, several universities started closed management and online teaching. This had a large impact on students' daily life and study, which may lead to mental health problems. The purpose of this study is to study the effect of screen time on mental health status of university students and the possible mediating effect of sleep status. METHODS: This was a cross-sectional study. A web-based questionnaire survey was employed that included demographic characteristics, sleep status and mental health status (depression, anxiety and loneliness). The Pittsburgh Sleep Quality Index scale was used to assess sleep status, while the Centre for Epidemiologic Studies Depression (CES-D) scale, Generalised Anxiety Disorder-7 (GAD-7) scale and Emotional versus Social Loneliness Scale (ESLS) were used to assess depression, anxiety and loneliness, respectively. Linear and logistic regression models were developed and adjusted for confounding factors, and finally the mediating effects were tested using the Karlson-Holm-Breen method. RESULTS: Finally, 1070 valid questionnaires were included. Among these, 604 (56.45%) indicated depressive symptoms (CES-D score ≥16) and 902 (84.30%) indicated anxiety symptoms (GAD-7 score ≥10). The mean ESLS score (for loneliness) was 26.51±6.64. The relationship between screen time and depressive symptoms (OR 1.118, 95% CI 1.072 to 1.166) and anxiety symptoms (OR 1.079, 95% CI 1.023 to 1.138) remained significant after adjusting for confounding factors. Meanwhile, sleep status plays an intermediary role in screen time and mental health status (depression and anxiety) and accounts for 13.73% and 19.68% of the total effects, respectively. We did not find a significant association between screen time and loneliness. CONCLUSION: During the outbreak of COVID-19, screen time is inevitably prolonged among university students. There is a relationship between mental health and screen time, and sleep status plays a mediating role.

The Association between Circulating Lipids and Female Infertility Risk: A Univariable and Multivariable Mendelian Randomization Analysis.

BACKGROUND: Although observational studies have demonstrated that blood lipids are associated with female infertility, the causality of this association remains unclear. We performed a univariable and multivariable Mendelian randomization (MR) analysis to evaluate the causal relationship between blood lipids and female infertility. METHODS: Single-nucleotide polymorphisms associated with lipid traits in univariate analysis were obtained from the Million Veteran Program (MVP) and Global Lipids Genetics Consortium (GLGC), involving up to 215,551 and 188,577 European individuals, respectively. Blood lipids in multivariate analysis were obtained from the latest genome-wide association study meta-analysis with lipid levels in 73 studies encompassing >300,000 participants. Data on female infertility were obtained from the FinnGen Consortium R6 release, which included 6481 samples and 75,450 controls. Subsequently, MR analysis was performed using inverse variance-weighted (IVW), weighted median, weighted-mode, simple-mode and MR-Egger regression to demonstrate the causal relationship between lipids and female infertility. RESULTS: After controlling confounding factors including body mass index and age at menarche, two-sample MR demonstrated that genetically predicted LDL-C and TC were causally associated with the risk of female infertility (When the genetic instruments come from the MVP database, LDL-C and female infertility, IVW OR: 1.13, 95% CI: 1.001-1.269, p = 0.047; TC and female infertility, IVW OR: 1.16, 95% CI: 1.018-1.317, p = 0.025, and when the genetic instruments came from the GLGC database, LDL-C and female infertility, IVW OR: 1.10, 95% CI: 1.008-1.210, p = 0.033; TC and female infertility, IVW OR: 1.14, 95% CI: 1.024-1.258, p = 0.015). However, the IVW estimate showed that HDL-C was not significantly associated with the risk of female infertility (when the genetic instruments came from the MVP database, IVW OR: 1.00, 95% CI: 0.887-1.128, p = 0.999; when the genetic instruments came from the GLGC database, IVW OR: 1.00, 95% CI: 0.896-1.111, p = 0.968). The multivariable MR analysis also provided evidence that LDL-C (OR: 1.12, 95% CI: 1.006-1.243, p = 0.042) was significantly associated with the risk of female infertility after considering the correlation of all lipid-related traits. CONCLUSION: These findings support a causal relationship between increased LDL-cholesterol and increased female infertility risk. Furthermore, the association between lipid-related traits and female infertility risk merits more studies.

Elevated serum uric acid is associated with infertility in women living in America.

Excessive uric acid levels may affect several organs and systems in the body. There is limited evidence of the effects of high serum uric acid levels on the female reproductive system. This study used the National Health and Nutrition Examination Survey (NHANES) database to explore the relationship between serum uric acid and female infertility. This cross-sectional study included a total of 2197 eligible subjects using data from NHANES 2013-March 2020 pre-pandemic data. Self-reported infertility (ever experiencing an inability to conceive after 12 months of trying to become pregnant) was the main outcome. Logistic regression models and restricted cubic spline were used to analyze the relationship between serum uric acid and female infertility, and stratified analysis was carried out. A total of 295 women self-reported infertility (13.43%). The median uric acid level for all study subjects was 4.4 mg/dL (interquartile range [IQR]: 3.7, 5.1). Serum uric acid levels were higher in the infertility group than in the control group (4.7 mg/dL [IQR: 4.0, 5.3] vs. 4.4 mg/dL [IQR: 3.7, 5.1], P < 0.001). After adjusting for age, race, marital status, smoking, alcohol, history of pregnancy, history of diabetes, history of hypertension, fasting glucose, total cholesterol, creatinine in refrigerated serum, low-density lipoprotein cholesterol, direct high-density lipoprotein cholesterol, glycohemoglobin, and body mass index confounders, women with serum uric acid levels at Q3 (4.4-5.1 mg/dL) had a 73% (odds ratio [OR] = 1.73, 95% confidence interval [CI] 1.18, 2.54, P = 0.005) higher risk of infertility, and women with uric acid levels at Q4 (5.1-18.0 mg/dL) had an 83% (OR = 1.83, 95% CI 1.22, 2.75, P = 0.003) increased risk of infertility compared to women at Q1 (1.6-3.7 mg/dL). The restricted cubic spline also showed that when serum uric acid levels exceeded the reference value, the risk of infertility gradually increased. We also performed a sensitivity analysis based on the complete dataset and found that the results were robust. Higher serum uric acid levels were significantly associated with an increased risk of female infertility. Women planning a pregnancy should have increased serum uric acid monitoring.

The effects of perfluoroalkyl and polyfluoroalkyl substances on female fertility: A systematic review and meta-analysis.

OBJECTIVE: The reproductive toxicity of perfluoroalkyl and polyfluoroalkyl substances (PFAS) has been verified in both animal and in vitro experiments, however, the association between PFAS and female fertility remains contradictory in population studies. Therefore, in this systematic review and meta-analysis, we evaluated the effects of PFAS on female fertility based on population evidence. METHODS: Electronic searches of the Web of Science, PubMed, The Cochrane Library, and Embase databases were conducted (from inception to March 2022) to collect observational studies related to PFAS and female fertility. Two evaluators independently screened the literature, extracted information and evaluated the risk of bias for the included studies, meta-analysis was performed using R software. RESULTS: A total of 5468 records were searched and 13 articles fully met the inclusion criteria. Meta-analysis showed that perfluorooctanoic acid (PFOA) exposure was negatively associated with the female fecundability odds ratio (FOR = 0.88, 95% confidence interval (Cl) [0.78; 0.98]) and positively associated with the odds ratio for infertility (OR = 1.33, 95%Cl [1.03; 1.73]). Perfluorooctane sulfonate (PFOS) exposure was negatively associated with the fecundability odds ratio (FOR = 0.94, 95% CI [0.90; 0.98]). Pooled effect values for perfluorononanoic acid (PFNA), perfluorodecanoic acid (PFDA), and perfluorohexane sulfonate (PFHxS) exposure did not find sufficient evidence for an association with female fertility. CONCLUSION: Based on the evidence provided by the current study, increased levels of PFAS exposure are associated with reduced fertility in women, this was characterized by a reduction in fecundability odds ratio and an increase in odds ratio for infertility. This finding could partially explain the decline in female fertility and provide insight into risk assessment when manufacturing products containing PFAS.

Effects of physical activity and sleep duration on fertility: A systematic review and meta-analysis based on prospective cohort studies.

Objective: Subfertility is a common problem for couples in modern society. Many studies have confirmed that lifestyle factors can affect fertility although there are conflicting conclusions relating to the effects of physical activity and sleep duration on fertility. In this study, we aimed to summarize and analyze the available evidence. Methods: PubMed, Web of Science, Cochrane, and Embase databases (as of October 14, 2022) were systematically searched for eligible prospective cohort studies. Data were extracted and effect values were combined. We also performed methodological quality and bias risk assessments for all the included studies. Results: A total of 10 eligible articles were included in our analysis; seven investigated the relationship between physical activity and fertility, and three investigated the effect of sleep duration on fertility. Compared with the lowest level of physical activity, high intensity physical activity (the highest levels of physical activity) was negatively correlated with fertility [odds ratio (OR) = 0.84; 95% confidence interval (CI): 0.70, 1.00, I 2 = 64%]. However, we did not find an association between moderate intensity physical activity and fertility (OR = 1.09; 95% CI: 0.98, 1.22, I 2 = 60%). We observed an inverse association between limited sleep duration (≤ 7 h) and fertility (OR = 0.92; 95% CI: 0.84, 1.00, I 2 = 0%) compared with 8 h of sleep. The relationship between long sleep duration (≥9 h) and fertility was not statistically significant (OR = 0.85; 95% CI: 0.60, 1.21, I 2 = 83%). According to the Newcastle-Ottawa Scale score, the overall quality of the research articles included was ranked as medium to high (6-9). Through GRADE system, the quality of evidence for the impact of high intensity physical activity and limited sleep duration on fertility was moderate, while the quality of evidence for the impact of moderate intensity physical activity and long sleep duration on fertility was low. Conclusion: The current evidence shows that high intensity physical activity and limited sleep time are negatively related to fertility. But there was great heterogeneity among studies, and the quality of research evidence was low to median. Thus, further high-quality research is needed to confirm this conclusion. PROSPERO registration number: CRD42022298137.

Female fecundability is associated with pre-pregnancy allostatic load: Analysis of a Chinese cohort.

INTRODUCTION: Allostatic load (AL) is a practical index that reflects multi-system physiological changes which occur in response to chronic psychosocial stress. This study investigated the association between female pre-pregnancy allostatic load and time to pregnancy. MATERIAL AND METHODS: We enrolled 444 women who met the inclusion criteria and were attempting to achieve pregnancy. Their allostatic load scores at baseline were evaluated by nine indicators (systolic blood pressure, diastolic blood pressure, fasting plasma glucose, plasma cortisol, noradrenaline, interleukin-6, hypersensitive C-reactive protein, high density lipoprotein cholesterol and body mass index). The participants were followed up and their pregnancy outcome ascertained 1 year later; we then calculated time-to-pregnancy. Cox models were used to estimate fecundability ratios and their 95% confidence intervals (95% CI) for different allostatic load scores. RESULTS: The median allostatic load score was 1 with a range of 0-6. The females were divided into four groups according to allostatic load score: group A (allostatic load = 0, 150/444, 33.8%), group B (allostatic load = 1-2, 156/444, 35.1%), group C (allostatic load = 3-4, 100/444, 22.5%) and group D (allostatic load = 5-6, 38/444, 8.6%). The cumulative pregnancy rate over 12 months for the four groups (A-D) was 55.4%, 44.5%, 50.9% and 26.9%, respectively (log-rank test, p = 0.042). After adjusting for potential confounding factors, group D showed a 59% reduction of fecundability compared with group A (fecundability ratio = 0.41, 95% CI 0.21-0.83). CONCLUSIONS: Women with a higher allostatic load score may have lower fecundability. Our findings suggest that the assessment of allostatic load during pre-conception consultation would be highly prudent.

The association between the pre-pregnancy vaginal microbiome and time-to-pregnancy: a Chinese pregnancy-planning cohort study.

BACKGROUND: Although sexually transmitted infections are regarded as the main cause of tubal infertility, the association between the common vaginal microbiome and female fecundability has yet to be determined. The objective of this study was to find convincing evidence relating to the impact of the vaginal bacterial structure on the fecundability of women planning pregnancy. METHODS: We recruited women who took part in the Free Pre-pregnancy Health Examination Project from 13 June 2018 to 31 October 2018 (n = 89, phase I) and from 1 November 2018 to 30 May 2020 (n = 389, phase II). We collected pre-pregnancy vaginal swabs from each subject; then, we followed up each subject to acquire the pregnancy-planning outcome in 1 year. In phase I, 16S rRNA gene sequencing was performed to investigate the vaginal bacterial content between the pregnancy and non-pregnancy groups. These findings were verified in phase II by applying a quantitative real-time polymerase chain reaction for the measurement of the absolute abundance of specific species. Cox models were used to estimate fecundability ratios (FR) for each vaginal microbiome type. RESULTS: In phase I, 59.6% (53/89) of women became pregnant within 1 year. The principal coordinate analysis showed that the pre-pregnancy vaginal microbial community structures of the pregnant and non-pregnant groups were significantly different (PERMANOVA test, R2 = 0.025, P = 0.049). The abundance of the genus Lactobacillus in the pregnancy group was higher than that of the non-pregnant group (linear discriminant analysis effect size (LDA) > 4.0). The abundance of the genus Gardnerella in the non-pregnant group was higher than those in the pregnant group (LDA > 4.0). In phase II, female fecundability increased with higher absolute loads of Lactobacillus gasseri (quartile Q4 vs Q1, FR = 1.71, 95%CI 1.02-2.87) but decreased with higher absolute loads of Fannyhessea vaginae (Q4 vs Q1, FR = 0.62, 95%CI 0.38-1.00). Clustering analysis showed that the vaginal microbiome of type D (characterized by a higher abundance of Lactobacillus iners, a lower abundance of Lactobacillus crispatus and Lactobacillus gassri) was associated with a 55% reduction of fecundability (FR = 0.45, 95%CI 0.26-0.76) compared with type A (featuring three Lactobacillus species, low Gardnerella vaginalis and Fannyhessea vaginae abundance). CONCLUSIONS: This cohort study demonstrated an association between the pre-pregnancy vaginal microbiome and female fecundability. A vaginal microbiome characterized by a higher abundance of L. iners and lower abundances of L. crispatus and L. gasseri appeared to be associated with a lower fecundability. Further research now needs to confirm whether manipulation of the vaginal microenvironment might improve human fecundability.

The current situation and future directions for the study on time-to-pregnancy: a scoping review.

INTRODUCTION: As problems associated with infertility and population aging increase, there is a growing interest in the factors that cause a decline in human fertility. Time-to-pregnancy (TTP) is a good indicator with which to reflect human fecundability. Here, we present a comprehensive overview of this topic. METHODS: Relevant qualitative and quantitative studies were identified by searching the Web of science and PubMed electronic databases. We included all literature, written in English, from inception to the 10th April 2021 providing the focus was on TTP. We conducted a narrative synthesis using thematic analysis. RESULTS: Traditional TTP-related study protocols include prospective and retrospective cohorts that provide a wealth of data to reveal potential influences on TTP. Thus far, a variety of factors have been shown to be associated with TTP in couples preparing for pregnancy, including basic demographic characteristics, menstrual status, chronic disease status, environmental endocrine disruptor exposure, and lifestyles. However, there are inevitable epidemiological bias in the existing studies, including recall bias, selection bias and measurement bias. Some methodological advances have brought new opportunities to TTP research, which make it possible to develop precision interventions for population fertility. Future TTP studies should take advantage of artificial intelligence, machine learning, and high-throughput sequencing technologies, and apply medical big data to fully consider and avoid possible bias in the design. CONCLUSION: There are many opportunities and future challenges for TTP related studies which would provide a scientific basis for the "precise health management" of the population preparing for pregnancy.

As the problems of infertility and population aging increase, there is a growing interest in the factors that cause a decline in human fertility. Time-to-pregnancy (TTP) is a good indicator with which to reflect human fecundability, and a longer TTP is known to reflect a reduction in fertility. Many original studies, with different designs, have used TTP to explore the factors that might influence fertility, including basic demographic characteristics, chronic disease status, environmental endocrine disruptor exposure, and lifestyles. However, much of the existing evidence is inconsistent and limited by various types of bias. This review provides a synopsis of recent TTP studies, and highlights new opportunities and future challenges.

The associations between low abundance of Mycoplasma hominis and female fecundability: a pregnancy-planning cohort study.

OBJECTIVE: To explore the impact of pre-pregnancy vaginal Mycoplasma hominis (M. hominis) colonization of low abundance on female fecundability. METHODS: In total, 89 females participating in a pre-pregnancy health examination program were included, and their pregnancy outcomes were followed up for 1 year. Vaginal swabs were collected, 16S rRNA genes were sequenced, and M. hominis colonization was confirmed by qPCR. Cox models were used to estimate the fecundability odds ratio (FOR) for women with M. hominis. RESULTS: The prevalence of M. hominis was 22.47% (20/89), and the abundance was relatively low (the cycle thresholds of the qPCR were all more than 25). In terms of the vaginal microbiome, the Simpson index of the positive group was significantly lower than that of the negative group (P = 0.003), which means that the microbiome diversity appeared to increase with M. hominis positivity. The relative abundance of M. hominis was negatively correlated with Lactobacillus crispatus (rho = - 0.24, P = 0.024), but positively correlated with Gardnerella vaginalis, Atopobium vaginae and Prevotella bivia (P all < 0.05). The cumulative one-year pregnancy rate for the M. hominis positive group was lower than that in the negative group (58.96% vs 66.76%, log-rank test: P = 0.029). After controlling for potential confounders, the risk of pregnancy in the M. hominis positive group was reduced by 38% when compared with the positive group (FOR = 0.62, 95% CI: 0.42-0.93). CONCLUSION: The vaginal colonization of M. hominis at a low level in pre-pregnant women is negatively correlated with female fecundability.