Associations of per- and polyfluoroalkyl substances (PFAS) and their mixture with risk of rheumatoid arthritis in the U.S. adult population.

BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) are known environmental contaminants with immunosuppressive properties. Their connection to rheumatoid arthritis (RA), a condition influenced by the immune system, is not well studied. This research explores the association between PFAS exposure and RA prevalence. METHODS: This research utilized data from the NHANES, encompassing a sample of 10,496 adults from the 2003-2018 cycles, focusing on serum levels of several PFAS. The presence of RA was determined based on self-reports. This study used multivariable logistic regression to assess the relationship between individual PFAS and RA risk, adjusting for covariates to calculate odds ratios (ORs). The combined effects of PFAS mixtures were evaluated using BKMR, WQS regression, and quantile g-computation. Additionally, sex-specific associations were explored through stratified analysis. RESULTS: Higher serum PFOA (OR = 0.88, 95% CI: 0.79, 0.98), PFHxS (OR = 0.91, 95% CI: 0.83, 1.00), PFNA (OR = 0.87, 95% CI: 0.77, 0.98), and PFDA (OR = 0.89, 95% CI: 0.81, 0.99) concentration was related to lower odds of RA. Sex-specific analysis in single chemical models indicated the significant inverse associations were only evident in females. BKMR did not show an obvious pattern of RA estimates across PFAS mixture. The outcomes of sex-stratified quantile g-computation demonstrated that an increase in PFAS mixture was associated with a decreased odds of RA in females (OR: 0.76, 95% CI: 0.62, 0.92). We identified a significant interaction term of the WQS*sex in the 100 repeated hold out WQS analysis. Notably, a higher concentration of the PFAS mixture was significantly associated with reduced odds of RA in females (mean OR = 0.93, 95% CI: 0.88, 0.98). CONCLUSIONS: This study indicates potential sex-specific associations of exposure to various individual PFAS and their mixtures with RA. Notably, the observed inverse relationships were statistically significant in females but not in males. These findings contribute to the growing body of evidence indicating that PFAS may have immunosuppressive effects.

Excess deaths and loss of life expectancy attributed to long-term NO2 exposure in the Chinese elderly.

BACKGROUND: Evidence linking nitrogen dioxide (NO2) air pollution to life span of high-vulnerability older adults is extensively scarce in low- and middle-income countries. This study seeks to quantify mortality risk, excess deaths, and loss of life expectancy (LLE) associated with long-term exposure to NO2 among elderly individuals in China. METHODS: A nationwide dynamic cohort of 20352 respondents ≥65 years old were enrolled from the China Longitudinal Health and Longevity Survey during 2005-2018. Residential exposures to NO2 and co-pollutants were assessed by well-validated spatiotemporal prediction models. A Cox regression model with time-dependent covariates was utilized to quantify the association of all-cause mortality with NO2 exposure, controlling for confounders such as demographics, lifestyle, health status, and ambient temperature. NO2-attributable deaths and LLE were evaluated for the years 2010 and 2020 based on the pooled NO2-mortality relation derived from multi-national cohort investigations. Decomposition analyses were conducted to dissociate net shift in NO2-related deaths between 2010 and 2020 into four primary contributing factors. RESULTS: A total of 14313 deaths were recorded during follow-up of approximately 100 hundred person-years (median 3.6 years). We observed an approximately linear relationship (nonlinear P = 0.882) of NO2 exposure with all-cause death across a broad range from 6.6 to 95.7 µg/m3. Every 10-µg/m3 rise in yearly average NO2 concentration was linked to a hazard ratio (HR) of 1.045 (95% confidence interval [CI]: 1.031-1.059). In the updated meta-analysis of this study and 9 existing cohorts, we estimated a pooled HR of 1.043 (95% CI: 1.023-1.063) for each 10-µg/m3 growth in NO2. Reaching a 10-µg/m3 counterfactual target of NO2 concentration in China could avoid 0.33 (95% empirical CI: 0.19-0.49) million premature deaths and an LLE of 0.40 (95% empirical CI: 0.23-0.59) years in 2010, which greatly dropped to 0.24 (95% empirical CI: 0.14-0.36) million deaths and 0.21 (95% empirical CI: 0.12-0.31) years of LLE in 2020. The net fall in NO2-attributable deaths (-26.8%) between 2010 and 2020 was primarily driven by the declines in both NO2 concentration (-41.6%) and mortality rate (-27.1%) under population growth (+41.0%) and age structure transition (+0.9%). CONCLUSIONS: Our findings provide national evidence for increased risk of premature death and loss of life expectancy attributed to later-life NO2 exposure among the elderly in China. In an accelerated aging society, strengthened clean air actions should be formulated to minimize the health burden and regional inequality in NO2-attributable mortality.

Maternal ozone exposure lowers infant's birthweight: A nationwide cohort of over 4 million livebirths in Iran.

BACKGROUND: Nationwide evidence linking maternal ozone exposure with fetal growth restriction (FGR) was extensively scarce, especially in the Middle East with dry climate and distinct religious culture. METHODS: We carried out a national retrospective birth cohort study using registry-based records from 749 hospitals across 31 provinces in Iran from 2013 to 2018. Monthly concentrations of maximum daily average 8-hour (MDA8) ozone at 0.125° × 0.125° resolution were extracted from well-validated spatiotemporal grid dataset. Linear and logistic regression models were employed to evaluate associations of maternal MDA8 ozone exposure with birthweight outcomes. Assuming causality, the comparative risk assessment framework was utilized to estimate the burden of low birthweight (LBW), small for gestational age (SGA), and birthweight loss per livebirth (BLL) attributable to ambient ozone pollution. RESULTS: Of 4030383 livebirths included in the study, 264304 (6.6%) were LBW and 484405 (12.0%) were SGA. Each 10-ppb increase in MDA8 ozone exposure was associated with an odds ratio of 1.123 (95% confidence interval [CI]: 1.104 to 1.142) for LBW and 1.210 (95% CI: 1.197 to 1.223) for SGA, and a 30.5-g (95% CI: 29.0 to 32.0) reduction in birthweight. We observed approximately linear exposure-response relationships of maternal MDA8 ozone exposure with LBW (Pnonlinear= 0.786), SGA (Pnonlinear= 0.156), and birthweight reduction (Pnonlinear= 0.104). Under the premise of causal association, we estimated 6.6% (95% CI: 5.7 to 7.5) of LBW, 10.1% (95% CI: 9.6 to 10.6) of SGA, and 18.8 g (95% CI: 17.9 to 19.7) of BLL could be attributable to maternal ozone exposure in Iran. Considerably greater risk and burden of ozone-related FGR were observed among younger, less-educated, and rural-dwelling mothers. CONCLUSIONS: Our study provided compelling evidence that maternal ozone exposure was associated with heightened FGR risk and burden, particularly among socioeconomically disadvantaged mothers. These findings underscored the urgent need for government to incorporate socioeconomic factors into future ozone-related health policies, not only to mitigate pollution, but also minimize inequality.

Linear and non-linear relationships between sulfur dioxide and semen quality: A longitudinal study in Anhui, China.

Existing evidence indicates that ambient air pollutants pose a threat to human semen quality; however, these findings are sparse and controversial. Besides, their non-linear dose-response relationship has not yet been well investigated. This study aimed to explore the linear and non-linear associations of gaseous air pollutants exposure with semen quality based on a large longitudinal cohort. A total of 15,112 males (with 28,267 semen tests) from the Anhui prospective assisted reproduction cohort were analyzed. Individual air pollutants exposure before semen tests in four exposure windows (i.e., 0-9, 10-14, 70-90, and 0-90 days) were estimated by inverse distance weighting interpolation. Linear mixed-effects models, cubic spline analysis and piecewise regression were used to test the potential linear and non-linear dose-response relationships. Ambient SO2 exposure was negatively associated with all semen quality parameters (all p values < 0.05), except for the progressive motility in the 0-90 and 70-90 days exposure windows. There were 'J' or 'U' shaped dose-response relationships of ambient SO2 exposure with total sperm count, progressive motility, total motility, progressively motile sperm count, and total motile sperm count (p values for non-linearity < 0.05), but not sperm concentration. Piecewise regression analysis also indicated a negative association of SO2 exposure with semen quality only when SO2 exposure was below the cut-off points identified by cubic spline analyses, which were all smaller than 40 µg/m3, the 2021 updated WHO air quality guideline level for SO2 exposure. Overall, we found that SO2 exposure was negatively associated with semen quality. Ambient SO2 exposure could reach the maximum hazardous dose even below the WHO air quality guideline level for SO2 exposure, suggesting a refinement to the current guideline.

Perfluoroalkyl and polyfluoroalkyl substances and hypertensive disorders of pregnancy: A systematic review and meta-analysis.

Hypertensive disorders of pregnancy (HDP), including gestational hypertension (GH) and preeclampsia (PE), cause significant morbidity and mortality among pregnant women. Several environmental toxins, particularly those that affect the normal function of the placenta and the endothelium, are emerging as potential risk factors for HDP. Among them, per- and polyfluoroalkyl substances (PFAS), widely used in a variety of commercial products, have been related to a variety of adverse health effects including HDP. This study was conducted by searching three databases for observational studies reporting associations between PFAS and HDP, all of which were published before December 2022. We used random-effects meta-analysis to calculate pooled risk estimates, and assessing each combination of exposure and outcome for quality and level of evidence. In total, 15 studies were included in the systematic review and meta-analysis. The results from meta-analyses showed that risk of PE was increased with exposure to PFOA (perfluorooctanoic acid) (RR = 1.39, 95% CI = 1.05, 1.85; N = 6 studies; exposure = 1 ln-unit increment; low certainty), PFOS (perfluorooctane sulfonate) (RR = 1.51, 95% CI = 1.23, 1.86; N = 6 studies; exposure = 1 ln-unit increment; moderate certainty), and PFHxS (perfluorohexane sulfonate) (RR = 1.39, 95% CI = 1.10, 1.76; N = 6 studies; exposure = 1 ln-unit increment; low certainty). PFOS was also associated with an increased risk of HDP (RR = 1.39, 95% CI = 1.10, 1.76; exposure = 1 ln-unit increment; low certainty). Exposure to legacy PFAS (PFOA, PFOS, PFHxS) is associated with an increased risk of PE, and PFOS is further associated with HDP. In view of the limitations of meta-analysis and quality of evidence, these findings should be interpreted with caution. Further research is required that assesses exposure to multiple PFAS in diverse and well-powered cohorts.

Joint effects of prenatal exposure to air pollution and pregnancy-related anxiety on birth weight: A prospective birth cohort study in Ma'anshan, China.

BACKGROUND: A growing number of studies have shown that prenatal exposure to chemical and non-chemical stressors has effects on fetal growth. The co-exposure of both better reflects real-life exposure patterns. However, no studies have included air pollutants and pregnancy-related anxiety (PrA) as mixtures in the analysis. METHOD: Using the birth cohort study method, 576 mother-child pairs were included in the Ma'anshan Maternal and Child Health Hospital. Evaluate the exposure levels of six air pollutants during pregnancy using inverse distance weighting (IDW) based on the pregnant woman's residential address and air pollution data from monitoring stations. Prenatal anxiety levels were assessed using the PrA Questionnaire. Generalized linear regression (GLR), quantile g-computation (QgC) and bayesian kernel machine regression (BKMR) were used to assess the independent or combined effects of air pollutants and PrA on birth weight for gestational age z-score (BWz). RESULT: The results of GLR indicate that the correlation between the six air pollutants and PrA with BWz varies depending on the different stages of pregnancy and pollutants. The QgC shows that during trimester 1, when air pollutants and PrA are considered as a whole exposure, an increase of one quartile is significantly negatively correlated with BWz. The BKMR similarly indicates that during trimester 1, the combined exposure of air pollutants and PrA is moderately correlated with a decrease in BWz. CONCLUSION: Using the method of analyzing mixed exposures, we found that during pregnancy, the combined exposure of air pollutants and PrA, particularly during trimester 1, is associated with BWz decrease. This supports the view that prenatal exposure to chemical and non-chemical stressors has an impact on fetal growth.

The associations of gestational weight gain and midpregnancy lipid levels with placental size and placental-to-birth weight ratio: findings from a chinese birth cohort study.

BACKGROUND: The placenta serves as the sole maternal organ responsible for transmitting nutrients to the fetus, playing a crucial role in supporting standard fetal growth and development. To date, only a small number of studies have investigated the impact of maternal gestational weight gain and lipid concentrations on placental development. This study aimed to explore the influence of weight gain during pregnancy and lipid levels in the second trimester on placental weight, volume, and the placental weight ratio. METHODS: This birth cohort study encompassed 1,358 mother-child pairs. Placental data for each participant was gathered immediately post-delivery, and the study incorporated data on gestational weight gain throughout pregnancy and lipid profiles from the mid-trimester. A linear regression model was employed to assess the correlations between gestational weight gain, mid-trimester lipid levels, and metrics such as placental weight, placental volume, and the placental-to-birth weight ratio (PFR). RESULTS: In the study groups of pre-pregnancy underweight, normal weight, and overweight, the placental weight increased by 4.93 g (95% CI: 1.04-8.81), 2.52 g (95% CI: 1.04-3.99), and 3.30 g (95% CI: 0.38-6.22) per 1 kg of gestational weight gain, respectively. Within the pre-pregnancy underweight and normal weight groups, the placental volume increased by 6.79 cm^3 (95% CI: 3.43-10.15) and 2.85 cm^3 (95% CI: 1.31-4.39) per 1 kg of gestational weight gain, respectively. Additionally, placental weight exhibited a positive correlation with triglyceride (TG) levels (ß = 9.81, 95% CI: 3.28-16.34) and a negative correlation with high-density lipoprotein (HDL-C) levels (ß = - 46.30, 95% CI: - 69.49 to - 23.11). Placental volume also showed a positive association with TG levels (ß = 14.54, 95% CI: 7.69-21.39). Conversely, PFR demonstrated a negative correlation with increasing HDL-C levels (ß = - 0.89, 95% CI: - 1.50 to - 0.27). CONCLUSIONS: Gestational weight gain was significantly correlated with both placental weight and volume. This association was especially pronounced in women who, prior to pregnancy, were underweight or of normal weight. Additionally, TG and HDL-C levels during the mid-trimester were linked to placental development.

The effects of gestational diabetes mellitus on fetal growth: is it different for low-risk and medium-high-risk pregnant women?

BACKGROUND: It has been suggested that gestational diabetes mellitus (GDM) alters the growth trajectory of a fetus and increases the risk of abnormal birth weight. In spite of this, there is still a significant debate regarding the mode and optimal timing of diagnosing this condition. Our aim was to determine fetal growth velocity and birth biometry in pregnant women with GDM at varying risk levels. METHODS: We conducted a cohort study involving 1023 pregnant women at a maternity hospital in Ma'anshan, China. All women completed an oral glucose tolerance test at 24-28 weeks' gestation. We measured fetal head circumference (HC), femoral length (FL), abdominal circumference (AC), biparietal diameter (BPD), and estimate fetal weight (EFW) by ultrasound at 17, 24, 31, and 35 weeks' gestation, respectively. RESULTS: Overall, 5115 ultrasound scans were performed. Among both low-risk and medium-high-risk pregnant women at 17-24 weeks' gestation, GDM exposure was associated with an increase in fetal growth velocity. Neonates born to women with GDM at medium-high risk had significantly larger birth weights than those born to women without GDM, while this was not observed in women at low risk. CONCLUSION: In medium-high-risk pregnant women, exposure to GDM has a greater effect on the fetus, leading to abnormal fetal growth velocity that lasts beyond week 24. It is evident from our results that the effects of GDM on fetal growth differ between medium-high-risk pregnant women and low-risk pregnant women, and therefore a different screening program based on the risk factor for GDM is warranted.

CoCoCs: co-optimized compressive imaging driven by high-level vision.

Compressive imaging senses optically encoded high-dimensional scene data with far fewer measurements and then performs reconstruction via appropriate algorithms. In this paper, we present a novel noniterative end-to-end deep learning-based framework for compressive imaging, dubbed CoCoCs. In comparison to existing approaches, we extend the pipeline by co-optimizing the recovery algorithm with optical coding as well as cascaded high-level computer vision tasks to boost the quality of the reconstruction. We demonstrate the proposed framework on two typical compressive imaging systems, i.e., single pixel imaging and snapshot video compressive imaging. Extensive results, including conventional image quality criteria, mean opinion scores, and accuracy in image classification and motion recognition, confirm that CoCoCs can yield realistic images and videos, which are friendly to both human viewing and computer vision. We hope CoCoCs will give impetus to bridge the gap between compressive imagers and computer vision and the perception of human.

Key frames assisted hybrid encoding for high-quality compressive video sensing.

Snapshot compressive imaging (SCI) encodes high-speed scene video into a snapshot measurement and then computationally makes reconstructions, allowing for efficient high-dimensional data acquisition. Numerous algorithms, ranging from regularization-based optimization and deep learning, are being investigated to improve reconstruction quality, but they are still limited by the ill-posed and information-deficient nature of the standard SCI paradigm. To overcome these drawbacks, we propose a new key frames assisted hybrid encoding paradigm for compressive video sensing, termed KH-CVS, that alternatively captures short-exposure key frames without coding and long-exposure encoded compressive frames to jointly reconstruct high-quality video. With the use of optical flow and spatial warping, a deep convolutional neural network framework is constructed to integrate the benefits of these two types of frames. Extensive experiments on both simulations and real data from the prototype we developed verify the superiority of the proposed method.

On-chip photonic diffractive optical neural network based on a spatial domain electromagnetic propagation model.

An integrated physical diffractive optical neural network (DONN) is proposed based on a standard silicon-on-insulator (SOI) substrate. This DONN has compact structure and can realize the function of machine learning with whole-passive fully-optical manners. The DONN structure is designed by the spatial domain electromagnetic propagation model, and the approximate process of the neuron value mapping is optimized well to guarantee the consistence between the pre-trained neuron value and the SOI integration implementation. This model can better ensure the manufacturability and the scale of the on-chip neural network, which can be used to guide the design and manufacturing of the real chip. The performance of our DONN is numerically demonstrated on the prototypical machine learning task of prediction of coronary heart disease from the UCI Heart Disease Dataset, and accuracy comparable to the state-of-the-art is achieved.

Optical random speckle encoding based on hybrid wavelength and phase modulation.

Optical random speckle encoding suffers from a contradiction between the generation speed and pattern amount. Spatial light modulators are commonly used for random speckle generation at relatively low speeds. Wavelength scanning combined with a scattering medium has a fast speed, while the pattern amount is limited by the optical bandwidth. To increase the performance of optical random speckle encoding, a novel, to the best of our knowledge, scheme combining wavelength and phase hybrid modulation is proposed and demonstrated. Through optical encoding in the two dimensions of wavelength and phase, the number of speckle patterns can reach one million, which is over 10,000 times that generated by only wavelength scanning. This scheme can be used in ghost imaging systems to increase the resolution of reconstructed images.

Ambient air pollution exposure and risk of chronic kidney disease: A systematic review of the literature and meta-analysis.

Ambient air pollution has been identified as one of the leading causes of global burden of disease. The relationship between ambient air pollution exposure and risk of chronic kidney disease (CKD) has stimulated increasing scientific interest in the past few years. However, evidence from human epidemiological studies is still limited and inconsistent. We performed an updated systematic review and meta-analysis to clarify the potential association comprehensively. Selected electronic databases were searched for related English language studies until March 1, 2020 with a final follow-up in December 31, 2020. Risk of bias assessment for individual studies were assessed using the OHAT (Office of Health Assessment and Translation) risk-of-bias rating tool. Confidence rating and level-of-evidence conclusions were developed for bodies of evidence for a given ambient air pollutant. Summary effect estimates were calculated using random-effects meta-analyses when three or more studies are identified for the same air pollutant-CKD combination. A total of 13 studies were finally identified in our study. The meta-analytic estimates (ORs) for risk of CKD were 1.15 (95% CI: 1.07, 1.24) for each 10 µg/m3 increase in PM2.5, 1.25 (95% CI: 1.11, 1.40) for each 10 µg/m3 increase in PM10, 1.10 (95% CI: 1.03, 1.17) for each 10 ppb increase in NO2, 1.06 (95% CI: 0.98, 1.15) for each 1 ppb increase in SO2 and 1.04 (95% CI: 1.00, 1.08) for each 0.1 ppm increase in CO, respectively. The level of evidence was appraised as moderate for four of the five tested air pollutant-CKD combinations using an adaptation of the GRADE (Grading of Recommendations Assessment, Development and Evaluation) tool. In conclusion, this study suggests that certain ambient air pollutant exposure was significantly associated with an increased risk of CKD. Given the limitations, the results of this study should be interpreted with caution, and further well-designed epidemiological studies are needed to draw a definite evidence of a causal relationship.

Association between short-term exposure to ambient nitrogen dioxide and the risk of conjunctivitis in Hefei, China: A time-series analysis.

BACKGROUND: Conjunctivitis, one of the most common ocular surface diseases, can be caused by many contributors. However, the important role of air pollution has been inadequately evaluated, particularly in countries with poor air quality. This study aims to explore the possible association of short-term ambient nitrogen dioxide (NO2) exposure with the risk of outpatient visits for conjunctivitis. METHODS: A total of 43,462 conjunctivitis patients from January 1, 2014 to December 31, 2018 were identified from the Department of Ophthalmology of The Second Affiliated Hospital of Anhui Medical University, Hefei, China. Such data were linked to the daily mean concentration of NO2 at ten fixed air quality monitoring stations. A distributed lag nonlinear model (DLNM) combined with a quasi-Poisson generalized linear regression model was employed to assess the association between NO2 exposure and the risk of outpatient visits for conjunctivitis. Stratified analyses were also performed on the basis of gender, age group and season. RESULTS: The association of NO2 exposure with the risk of outpatient visits for conjunctivitis was statistically significant. In the single-day lags (lag 0 to lag 11) analysis, the largest effect estimates were observed at lag 0. In the moving average exposure lags (lag 0-1 to lag 0-11) analysis, the cumulative effects were stronger than the single-day lag effects. The stratified analyses suggested that the effect of NO2 exposure was more pronounced in females and patients aged 19-65 years and in the cold season. CONCLUSIONS: This study confirms the evidence that short-term NO2 exposure is associated with an increased risk of conjunctivitis outpatient visits. Our research encourages individuals to avoid outdoor activities on severe air pollution days and the government is obliged to adopt more stringent environmental policies to alleviate the effects of air pollution on human health, particularly for individuals at risk of developing conjunctivitis.

Residential greenness and birth outcomes: A systematic review and meta-analysis of observational studies.

BACKGROUND: The amount of natural vegetation surrounding homes (residential greenness) has been proposed as a mitigation measure to buffer the adverse health effects of urban living, associated with promoting health and wellbeing including birth outcomes. This study aimed to systematically review the epidemiological evidence on the association of residential greenness with birth outcomes and quantitatively provide summary effect estimates of the current literature. METHODS: We extensively searched epidemiological studies related to residential greenness and birth outcomes in three electronic databases (EMBASE, Web of Science, and PubMed) using terms related to residential greenness and birth outcomes before July 10, 2020. Summary effect estimates of residential greenness on birth outcomes including SGA (small for gestational age), PTB (preterm birth), LBW (low birth weight), and birth weight were calculated for each 0.1 unit increase in residential greenness exposure, as well as comparing the highest to the lowest categories using random-effects meta-analyses. We assessed the risk of bias of each individual study, and the overall quality of the body of evidence and level of evidence for each exposure-outcome were also evaluated. RESULTS: The initial search identified 161 studies, of which 29 studies were finally included. Meta-analysis for continuous exposure suggested that an increase in residential greenness, measured by NDVI (normalized difference vegetation index) with different buffer sizes, was generally associated with higher birth weights ranging from 7.99 g [95% confidence interval (CI) = 4.29-11.70] to 15.35 g (95% CI = 11.41-19.29) and lower odds of LBW ranging from 0.79 (95% CI = 0.65-0.96) to 0.93 (95% CI = 0.86-1.00), but associations between residential greenness and PTB or SGA were not significant. When introducing the exposure as high versus low categories, similar results were found. The overall evidence for each exposure-outcome combination was considered to be of "moderate" certainty. CONCLUSIONS: This study indicated a potential positive association between residential greenness and several birth outcomes. However, because of the moderate to high between-study heterogeneity, further studies with better adjustment of covariates, improved residential greenness assessment in a longitudinal approach throughout pregnancy rather than a cross-sectional approach at time of delivery, and accounting thoroughly for socioeconomic status, are warranted to replicate these findings as well as to explore in greater detail in their implications.

Investigation on factors related to uterine fibroids in rural women of northern Anhui province.

AIM: Given the increasing prevalence of hysteromyoma among the Chinese rural women of childbearing age, it is imperative that more attention should be given to researching risk factors that predispose women to this condition so that early preventive measures may be taken. Our study investigates potential risk factors for uterine fibroids such as participants' demographic characteristics (age, ethnicity, education), physiological characteristics (age at menarche, primiparous age), and the occurrence of several different female reproductive diseases (vaginitis, pelvic inflammatory disease). METHODS: 2200 rural women of reproductive age were screened from a cross-sectional study carried out in the northern Anhui province. Data were collected by questionnaire surveys, gynecological and laboratory examinations and were subjected to univariate and multivariate analysis to evaluate the risk factors for uterine fibroids. RESULTS: Of the 2200 women, 440 had uterine fibroids. In general, women with endometriosis, ovarian cysts and early menarche were more likely to suffer from hysteromyoma. Factors including higher parity, late age of first childbirth, and a regular menstrual cycle were associated with the reduced risk of uterine fibroids. CONCLUSIONS: Our findings indicate that parameters such as earlier age of menarche, early primiparous age, lower parity and a variety of female reproductive diseases were associated with an increased risk of uterine fibroids. These findings may be used to guide the formulation of effective prevention and intervention protocols to improve the reproductive health of rural women.

Short-term effect of ambient temperature change on the risk of tuberculosis admissions: Assessments of two exposure metrics.

BACKGROUND: Although the effects of seasonal variations and ambient temperature on the incidence of tuberculosis (TB) have been well documented, it is still unknown whether ambient temperature change is an independent risk factor for TB. The aim of this study was to assess the association between ambient temperature change and the risk of TB admissions. METHOD: A distributed lag non-linear model (DLNM) combined with Poisson generalized linear regression model was performed to assess the association between ambient temperature change and the risk of TB admissions from 2014 to 2018 in Hefei, China. Two temperature change metrics including temperature change between neighboring days (TCN) and diurnal temperature range (DTR) were used to assess the effects of temperature change exposure. Subgroup analyses were performed by gender, age and season. Besides, the attributable risk was calculated to evaluated the public health significance. RESULTS: The overall exposure-response curves suggested that there were statistically significant associations between two temperature change metrics and the risk of TB admissions. The maximum lag-specific relative risk (RR) of TB admissions was 1.088 (95%CI: 1.012-1.171, lag 4 day) for exposing to large temperature drop (TCN= -4 °C) in winter. Besides, the overall cumulative risk of TB admissions increased continuously and peaked at a lag of 7 days (RR=1.350, 95%CI: 1.120-1.628). Subgroup analysis suggested that exposure to large temperature drop had an adverse effect on TB admissions among males, females and adults. Similarly, large level of DTR exposure (DTR=15 °C) in spring also increased the risk of TB admissions on lag 0 day (RR=1.039, 95%CI: 1.016-1.063), and the cumulative RRs peaked at a lag of 1 days (RR=1.029, 95%CI: 1.012-1.047). We also found that females and elderly people were more vulnerable to the large level of DTR exposure. Additionally, the assessment of attributable risk suggested that taking target measures for the upcoming large temperature drop (b-AF = 4.17%, 95% eCI: 1.24%, 7.22%, b-AN = 1195) may achieve great public health benefits for TB prevention. CONCLUSION: This study suggests that ambient temperature change is associated with the risk of TB admissions. Besides, TCN may be a better predictor for the TB prevention and public health.

Association between short-term exposure to ambient air pollutants and the risk of tuberculosis outpatient visits: A time-series study in Hefei, China.

BACKGROUND: The current evidence has presented mixed results between air pollutants exposure and the progression of tuberculosis (TB). The purpose of this study was to explore the association between short-term exposure to air pollutants and the risk of TB outpatient visits in Hefei, China. METHODS: Time-series analysis was used to assess the effect of short-term exposure to ambient air pollutants on the risk of TB outpatient visits. A Poisson generalized linear regression model combined with a distributed lag non-linear model (DLNM) was applied to explore the association. The effects of different gender (male, female), age (≤65 years old, >65 years old) and season (cold season, warm season) on the risk of TB were investigated by stratified analysis. Sensitivity analyses were conducted to test the robustness of our findings. RESULTS: A total of 22,749 active TB cases were identified from November 1, 2013 to December 31, 2018 in Hefei. The overall exposure-response curve showed that the concentration of particulate matter with aerodynamic diameter less than 2.5 µm (PM2.5) and nitrogen dioxide (NO2) exposure were positively correlated with the risk of TB outpatient visits, while ozone (O3) and sulfur dioxide (SO2) exposure were negatively correlated with the risk of TB outpatient visits. The maximum lag-specific and cumulative relative risk (RR) of TB outpatient visits were 1.057 [95%CI: 1.002-1.115, lag 3 day] and 1.559 (95%CI: 1.057-2.300, lag 13 days) for each 10 µg/m³ increase in PM2.5; 1.026 (95% CI: 1.008-1.044, lag 0 day) and 1.559 (95%CI: 1.057-2.300, lag 07 days) for each 10 µg/m³ increase in NO2; 0.866 (95% CI: 0.801-0.935, lag 5 day) and 0.852 (95%CI: 1.01-1.11, lag 0-14 days) for each 10 µg/m³ increase in SO2 in the single-pollutant model. There was only a negative association between O3 exposure and the cumulative risk of TB outpatient visits (RR = 0.960, 95%CI: 0.936-0.984, lag 07 days). Stratified analyses showed that the effects of SO2 and O3 exposure were different between warm and cold seasons. The effect of NO2 exposure remained statistically significant in male, younger, and cold season subgroups. Besides, elderly people are more susceptible to PM2.5 exposure. CONCLUSION: This study suggests that exposure to PM2.5, NO2, SO2, and O3 are associated with the risk of TB outpatient visits. Seasonal variation may have a greater impact on the risk of TB outpatient visits compared with gender and age.

Human epidemiological evidence about the association between air pollution exposure and gestational diabetes mellitus: Systematic review and meta-analysis.

BACKGROUND: Previous studies have shown that ambient air pollution exposure can increase the risk of type 2 diabetes mellitus (T2DM) significantly. In consideration of the common underlying pathophysiologic mechanisms, exposure to air pollution may also increase the risk of gestational diabetes mellitus (GDM), but the current evidence was inconsistent and has not well been systematically reviewed. Our goal was to perform a systematic review and meta-analysis assessing the association between air pollution exposure and GDM. METHODS: An extensive literature search was conducted in selected electronic databases for related human epidemiological studies published in English language. Summary effect estimates were calculated using random-effect models for a) risk per unit increase in continuous air pollutant concentration and b) risk of high versus low exposure level in individual study if each exposure that had been examined in ≥2 studies. We evaluated the heterogeneity using Cochran's Q test and quantified it by I2 statistic. Publication bias was also evaluated through the funnel plot when sufficient number of studies are available. RESULTS: A total of 11 studies evaluating the association between GDM and exposure to air pollution were identified finally. The summary odds ratio (OR) for incidence of GDM following a 10 µg/m3 increase in PM2.5 exposure during the second trimester was 1.04 (95% Confidence Interval (CI): 1.01, 1.09) and in NOx during the first trimester was 1.03 (95%CI: 1.00, 1.07) per 10 ppb increase, while for high versus low SO2 exposure during the second trimester was 1.25 (95%CI: 1.02, 1.53). High heterogeneity among study-specific results in majority of the analyses were observed, and attributed to different exposure assessment methods, populations, study locations, and covariates adjustment. Publication bias cannot be excluded because of the inclusion of small number of studies. CONCLUSIONS: The present study supports the evidence that air pollution exposure increases the risk the GDM, albeit the existence of high heterogeneity. Further studies are necessary to elaborate the suggestive associations. These results are of public health significance since worsening air pollution in developing countries has been expected to increase the risk of GDM development.

Single-shot ultrafast phase retrieval photography.

Single-shot ultrafast photography is a powerful tool for science research and industry applications. In this Letter, a novel strategy for ultrafast imaging of two-dimensional complex (amplitude and phase) objects, which is termed single-shot ultrafast phase retrieval photography (SUP), is proposed and demonstrated. The key component of SUP is a silicon photonic integrated chip, which not only has the function of multi-angle illumination, but also provides ultra-short delays for each illumination source. Combined with an ultra-short pulse source and coherent diffraction imaging, SUP can realize ultrafast single-shot imaging. As a proof of concept, the self-developed multiplexed time delay illumination chip was used for experiments, and we demonstrated the reconstructing of a static complex-valued object with a frame sequence depth of 16 frames from single-shot ptychographic data.