Light-field tomographic fluorescence lifetime imaging microscopy.

Fluorescence lifetime imaging microscopy (FLIM) is a powerful imaging technique that enables the visualization of biological samples at the molecular level by measuring the fluorescence decay rate of fluorescent probes. This provides critical information about molecular interactions, environmental changes, and localization within biological systems. However, creating high-resolution lifetime maps using conventional FLIM systems can be challenging, as it often requires extensive scanning that can significantly lengthen acquisition times. This issue is further compounded in three-dimensional (3D) imaging because it demands additional scanning along the depth axis. To tackle this challenge, we developed a computational imaging technique called light-field tomographic FLIM (LIFT-FLIM). Our approach allows for the acquisition of volumetric fluorescence lifetime images in a highly data-efficient manner, significantly reducing the number of scanning steps required compared to conventional point-scanning or line-scanning FLIM imagers. Moreover, LIFT-FLIM enables the measurement of high-dimensional data using low-dimensional detectors, which are typically low cost and feature a higher temporal bandwidth. We demonstrated LIFT-FLIM using a linear single-photon avalanche diode array on various biological systems, showcasing unparalleled single-photon detection sensitivity. Additionally, we expanded the functionality of our method to spectral FLIM and demonstrated its application in high-content multiplexed imaging of lung organoids. LIFT-FLIM has the potential to open up broad avenues in both basic and translational biomedical research.

Call to action for a life course approach.

Gestational diabetes remains the most common medical disorder in pregnancy, with short-term and long-term consequences for mothers and offspring. New insights into pathophysiology and management suggest that the current gestational diabetes treatment approach should expand from a focus on late gestational diabetes to a personalised, integrated life course approach from preconception to postpartum and beyond. Early pregnancy lifestyle intervention could prevent late gestational diabetes. Early gestational diabetes diagnosis and treatment has been shown to be beneficial, especially when identified before 14 weeks of gestation. Early gestational diabetes screening now requires strategies for integration into routine antenatal care, alongside efforts to reduce variation in gestational diabetes care, across settings that differ between, and within, countries. Following gestational diabetes, an oral glucose tolerance test should be performed 6-12 weeks postpartum to assess the glycaemic state. Subsequent regular screening for both dysglycaemia and cardiometabolic disease is recommended, which can be incorporated alongside other family health activities. Diabetes prevention programmes for women with previous gestational diabetes might be enhanced using shared decision making and precision medicine. At all stages in this life course approach, across both high-resource and low-resource settings, a more systematic process for identifying and overcoming barriers to preventative care and treatment is needed to reduce the current global burden of gestational diabetes.

Maternal gestational diabetes and childhood adiposity risk from 6 to 8 years of age.

BACKGROUND/OBJECTIVE: Previous studies found conflicting results on the association between maternal gestational diabetes mellitus (GDM) and childhood overweight/obesity. This study was to assess the association between maternal GDM and offspring's adiposity risk from 6 to 8 years of age. METHODS: The present study longitudinally followed 1156 mother-child pairs (578 GDM and 578 non-GDM) at 5.9 ± 1.2 years postpartum and retained 912 mother-child pairs (486 GDM and 426 non-GDM) at 8.3 ± 1.6 years postpartum. Childhood body mass index (BMI), waist circumference, body fat and skinfold were measured using standardized methods. RESULTS: Compared with the counterparts born to mothers with normal glucose during pregnancy, children born to mothers with GDM during pregnancy had higher mean values of adiposity indicators (waist circumference, body fat, subscapular skinfold and suprailiac skinfold) at 5.9 and 8.3 years of age. There was a positive association of maternal GDM with changes of childhood adiposity indicators from the 5.9-year to 8.3-year visit, and ß values were significantly larger than zero: +0.10 (95% CI: 0.02-0.18) for z score of BMI for age, +1.46 (95% CI: 0.70-2.22) cm for waist circumference, +1.78% (95% CI: 1.16%-2.40%) for body fat, +2.40 (95% CI: 1.78-3.01) mm for triceps skinfold, +1.59 (95% CI: 1.10-2.09) mm for subscapular skinfold, and +2.03 (95% CI: 1.35-2.71) mm for suprailiac skinfold, respectively. Maternal GDM was associated with higher risks of childhood overweight/obesity, central obesity, and high body fat (Odd ratios 1.41-1.57 at 5.9 years of age and 1.73-2.03 at 8.3 years of age) compared with the children of mothers without GDM. CONCLUSIONS: Maternal GDM was a risk factor of childhood overweight/obesity at both 5.9 and 8.3 years of age, which was independent from several important confounders including maternal pre-pregnancy BMI, gestational weight gain, children's birth weight and lifestyle factors. This significant and positive association became stronger with age.

Interactive effects of gestational diabetes and high pre-pregnancy body mass index on adverse growth patterns of offspring.

AIMS: To examine the independent and interactive effects of maternal gestational diabetes mellitus (GDM) and high pre-pregnancy body mass index (BMI) on the risk of offspring adverse growth patterns. MATERIALS AND METHODS: One thousand six hundred and eighty one mother-child pairs were followed for 8 years in Tianjin, China. Group-based trajectory modelling was used to identify offspring growth patterns. Logistic regression was performed to obtain odds ratios (ORs) and 95% confidence intervals (CIs) of GDM and high pre-pregnancy BMI for offspring adverse growth patterns. Restricted cubic spline was used to identify cut-off points. Additive interactions and multiplicative interactions were used to test interactive effects between GDM and high pre-pregnancy BMI for adverse growth patterns. RESULTS: Four distinct growth patterns were identified in offspring, including normal growth pattern, persistent lean growth pattern, late obesity growth pattern (LOGP), and persistent obesity growth pattern (POGP). Maternal high pre-pregnancy BMI was associated with LOGP and POGP (adjusted OR, 95% CI: 2.38, 1.74-3.25 & 4.92, 2.26-10.73). GDM greatly enhanced the adjusted OR of high pre-pregnancy BMI for LOGP up to 3.48 (95% CI: 2.25-5.38). Additive interactions and multiplicative interactions between both risk factors were significant for LOGP but not for POGP. CONCLUSIONS: Maternal high pre-pregnancy BMI was associated with increased risk of LOGP and POGP, whereas GDM greatly enhanced the risk of high pre-pregnancy BMI for LOGP.

Aromatic Amino Acids and Their Interactions with Gut Microbiota-Related Metabolites for Risk of Gestational Diabetes: A Prospective Nested Case-Control Study in a Chinese Cohort.

INTRODUCTION: The aim of this study was to explore associations of aromatic amino acids (AAA) in early pregnancy with gestational diabetes mellitus (GDM), and whether high AAA and gut microbiota-related metabolites had interactive effects on GDM risk. METHODS: We conducted a 1:1 case-control study (n = 486) nested in a prospective cohort of pregnant women from 2010 to 2012. According to the International Association of Diabetes and Pregnancy Study Group's criteria, 243 women were diagnosed with GDM. Binary conditional logistic regression was performed to examine associations of AAA with GDM risk. Interactions between AAA and gut microbiota-related metabolites for GDM were examined using additive interaction measures. RESULTS: High phenylalanine and tryptophan were associated with increased GDM risk (OR: 1.72, 95% CI: 1.07-2.78 and 1.66, 1.02-2.71). The presence of high trimethylamine (TMA) markedly increased the OR of high phenylalanine alone up to 7.95 (2.79-22.71), while the presence of low glycoursodeoxycholic acid (GUDCA) markedly increased the OR of high tryptophan alone up to 22.88 (5.28-99.26), both with significant additive interactions. Furthermore, high lysophosphatidylcholines (LPC18:0) mediated both interactive effects. CONCLUSIONS: High phenylalanine may have an additive interaction with high TMA, while high tryptophan may have an additive interaction with low GUDCA toward increased risk of GDM, both being mediated via LPC18:0.

IRDC-Net: An Inception Network with a Residual Module and Dilated Convolution for Sign Language Recognition Based on Surface Electromyography.

Deaf and hearing-impaired people always face communication barriers. Non-invasive surface electromyography (sEMG) sensor-based sign language recognition (SLR) technology can help them to better integrate into social life. Since the traditional tandem convolutional neural network (CNN) structure used in most CNN-based studies inadequately captures the features of the input data, we propose a novel inception architecture with a residual module and dilated convolution (IRDC-net) to enlarge the receptive fields and enrich the feature maps, applying it to SLR tasks for the first time. This work first transformed the time domain signal into a time-frequency domain using discrete Fourier transformation. Second, an IRDC-net was constructed to recognize ten Chinese sign language signs. Third, the tandem CNN networks VGG-net and ResNet-18 were compared with our proposed parallel structure network, IRDC-net. Finally, the public dataset Ninapro DB1 was utilized to verify the generalization performance of the IRDC-net. The results showed that after transforming the time domain sEMG signal into the time-frequency domain, the classification accuracy (acc) increased from 84.29% to 91.70% when using the IRDC-net on our sign language dataset. Furthermore, for the time-frequency information of the public dataset Ninapro DB1, the classification accuracy reached 89.82%; this value is higher than that achieved in other recent studies. As such, our findings contribute to research into SLR tasks and to improving deaf and hearing-impaired people's daily lives.

Risk factors for missed abortion: retrospective analysis of a single institution's experience.

OBJECTIVE: To explore the risk factors including the difference between mean gestational sac diameter and crown-rump length for missed abortion. METHODS: Hospitalized patients with missed abortion and patients with continuing pregnancy to the second trimester from Chengdu Women's and Children's Central Hospital from June 2018 to June 2021 were retrospectively analyzed. The best cut-off value for age and difference between mean gestational sac diameter and crown-rump length (mGSD-CRL) were obtained by x-tile software. Univariate and multivariate logistic regression analysis were adopted to identify the possible risk factors for missed abortion. RESULTS: Age, gravidity, parity, history of cesarean section, history of recurrent abortion (≥ 3 spontaneous abortions), history of ectopic pregnancy and overweight or obesity (BMI > 24 kg/m2) were related to missed abortion in univariate analysis. However, only age (≥ 30 vs < 30 years: OR = 1.683, 95%CI = 1.017-2.785, P = 0.043, power = 54.4%), BMI (> 24 vs ≤ 24 kg/m2: OR = 2.073, 95%CI = 1.056-4.068, P = 0.034, power = 81.3%) and mGSD-CRL (> 20.0vs ≤ 11.7 mm: OR = 2.960, 95% CI = 1.397-6.273, P = 0.005, power = 98.9%; 11.7 < mGSD-CRL ≤ 20.0vs > 20.0 mm: OR = 0.341, 95%CI = 0.172-0.676, P = 0.002, power = 84.8%) were identified as independent risk factors for missed abortion in multivariate analysis. CONCLUSION: Patients with age ≥ 30 years, BMI > 24 kg/m2 or mGSD-CRL > 20 mm had increasing risk for missed abortion, who should be more closely monitored and facilitated with necessary interventions at first trimester or even before conception to reduce the occurrence of missed abortion to have better clinical outcomes.

Machine learning risk score for prediction of gestational diabetes in early pregnancy in Tianjin, China.

AIMS: This study aimed to develop a machine learning-based prediction model for gestational diabetes mellitus (GDM) in early pregnancy in Chinese women. MATERIALS AND METHODS: We used an established population-based prospective cohort of 19,331 pregnant women registered as pregnant before the 15th gestational week in Tianjin, China, from October 2010 to August 2012. The dataset was randomly divided into a training set (70%) and a test set (30%). Risk factors collected at registration were examined and used to construct the prediction model in the training dataset. Machine learning, that is, the extreme gradient boosting (XGBoost) method, was employed to develop the model, while a traditional logistic model was also developed for comparison purposes. In the test dataset, the performance of the developed prediction model was assessed by calibration plots for calibration and area under the receiver operating characteristic curve (AUR) for discrimination. RESULTS: In total, 1484 (7.6%) women developed GDM. Pre-pregnancy body mass index, maternal age, fasting plasma glucose at registration, and alanine aminotransferase were selected as risk factors. The machine learning XGBoost model-predicted probability of GDM was similar to the observed probability in the test data set, while the logistic model tended to overestimate the risk at the highest risk level (Hosmer-Lemeshow test p value: 0.243 vs. 0.099). The XGBoost model achieved a higher AUR than the logistic model (0.742 vs. 0.663, p < 0.001). This XGBoost model was deployed through a free, publicly available software interface (https://liuhongwei.shinyapps.io/gdm_risk_calculator/). CONCLUSION: The XGBoost model achieved better performance than the logistic model.

Usefulness of cut-off points of International criteria for prediction of post-partum diabetes and prediabetes among Chinese women with gestational diabetes.

AIMS: This study tests whether cut-off points of the International Association of Diabetes and Pregnancy Study Group's (IADPSG) criteria had threshold effects on post-partum prediabetes and diabetes among Chinese pregnant women with gestational diabetes mellitus (GDM). MATERIALS AND METHODS: A total of 507 out of 1000 women with GDM (948 of them enrolled in a lifestyle trial during pregnancy) turned up for the follow-up study and underwent a 75-g 2-h oral glucose tolerance test. GDM was diagnosed based on the IADPSG's criteria while post-partum diabetes and prediabetes were defined by the World Health Organization's. Generalized logit model was used to obtain odds ratios (OR) and 95% confidence interval (CI) of fasting, 1-h and 2-h plasma glucoses (PGs) for post-partum diabetes and prediabetes. Restricted cubic spline was used to identify any threshold effects. RESULTS: At a median of 9.1 weeks post-partum, 3.7% (n = 19) women developed post-partum diabetes and 35.1% (n = 178) developed post-partum prediabetes. Fasting PG ≥ 5.1 mmol/L was associated with markedly increased risk of post-partum diabetes without a discernible threshold (adjusted OR: 3.87, 95% CI: 1.03-14.52) while 2-h PG ≥ 8.5 and ≥ 9.0 mmol/L had threshold effects on post-partum prediabetes (2.10, 1.33-3.30) and diabetes (4.02, 1.04-15.56). The 1-h PG also had a threshold at ≥10.0 mmol/L for prediabetes (1.67, 1.06-2.64), but it was not significant for post-partum diabetes. CONCLUSIONS: Among Chinese women with GDM, fasting PG ≥ 5.1 mmol/L was associated with post-partum diabetes without any discernible threshold effects while 2-h PG ≥ 8.5 and ≥ 9.0 mmol/L respectively identified women at high risk of post-partum prediabetes and diabetes.

Maternal gestational diabetes and childhood hyperlipidemia.

AIMS: Aim of this study is to assess dyslipidemia risk between children exposed to maternal gestational diabetes mellitus (GDM) and those not exposed. METHODS: We recruited 1144 mother-child pairs (572 GDM and 572 non-GDM women matched by their offspring's age and sex). The age of offspring ranged from 3 to 9 years old. We used general linear models to compare mean values of different lipid profiles among children born to mothers with and without GDM. Logistic regression models were used to assess associations of maternal GDM with abnormal lipid profiles in offspring. RESULTS: After adjustment for maternal and children's characteristics, children born to mothers with GDM had lower mean values of high-density-lipoprotein (HDL) cholesterol (1.40 ± 0.01 vs. 1.50 ± 0.01; p < 0.001) and higher mean levels of triglycerides/HDL cholesterol ratio (0.37 ± 0.01 vs. 0.35 ± 0.01; p < 0.05) in comparison with their counterparts born to mothers without GDM. Multivariate-adjusted odds ratios among children exposed to mothers with GDM compared with the counterparts were 2.11 (95% confidence interval [CI 1.15-3.88]) for low HDL cholesterol and 1.35 (95% CI 1.00-1.81) for high triglycerides/HDL cholesterol ratio, respectively. CONCLUSIONS: Maternal GDM was associated with an increased risk of hyperlipidemia in the offspring during early childhood aged from 3 to 9 years old.

Physical activity and sleep duration during pregnancy have interactive effects on caesarean delivery: a population-based cohort study in Tianjin, China.

BACKGROUND: There were inconsistent findings in the literature regarding the associations of physical activity and sleep duration during pregnancy with caesarean delivery for different reasons. It was also unknown whether physical activity and sleep duration during pregnancy had interactive effects on the risks of different types of caesarean delivery. The study aimed to investigate the effects of physical activity, sleep duration and their interactions on the risk of caesarean delivery for medical reasons and non-medical reasons. METHODS: From October 2010 to August 2012, a prospective population-based cohort of 13,015 pregnant women was established in six central urban districts of Tianjin, China. Pregnancy outcomes were retrieved from an electronic database and caesarean delivery was divided into caesarean delivery for medical reasons and caesarean delivery for non-medical reasons. Physical activity and sleep status were collected at 24-28 weeks of gestation using self-reported questionnaires. Logistic regression and additive interaction were used to examine physical activity, sleep duration and their interactive effects on risk of caesarean delivery. RESULTS: In the cohort, 5692 (43.7%) and 2641 (20.3%) of women had caesarean delivery for medical reasons and non-medical reasons, respectively. Low physical activity increased the risk of caesarean delivery for medical reasons (adjusted OR: 1.13, 95%CI 1.04-1.23) but not caesarean delivery for non-medical reasons. Sleep duration < 7 h/day and poor sleep quality were not associated with caesarean delivery. Sleep duration ≥9 h/day increased the risk of caesarean delivery for medical reasons (1.12, 1.02-1.22) and caesarean delivery for non-medical reasons (1.16, 1.05-1.29). Co-presence of low physical activity and sleep duration ≥9 h/day increased risk of caesarean delivery (1.25, 1.12-1.41), and their additive interaction was statistically significant for caesarean delivery for medical reasons but not for caesarean delivery for non-medical reasons. CONCLUSIONS: Low physical activity and excessive sleep duration during pregnancy each increased the risk of caesarean delivery, and they had an interactive effect on the risk of caesarean delivery for medical reasons but not on the risk of caesarean delivery for non-medical reasons. Increasing physical activity and maintaining recommended sleep duration during pregnancy may have benefits for perinatal health.

Association of obesity status and metabolic syndrome with site-specific cancers: a population-based cohort study.

BACKGROUND: Obesity and metabolic syndrome (MetS) appear in clusters and are both associated with an increased risk of cancer. However, it remains unknown whether obesity status with or without MetS increases the risk of site-specific cancers. METHODS: We used data derived from 390,575 individuals (37-73 years old) from the UK Biobank who were enrolled from 2006-2016 with a median of 7.8 years of follow-up. Obesity was defined by BMI ≥ 30 kg/m2 and MetS was defined by the criteria of the Adult Treatment Panel-III (ATP-III). Cox proportional hazards models were used to investigate the associations of BMI and MetS with 22 cancers. RESULTS: Metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO) phenotypes represented 6.7% and 17.9% of the total analytic samples and 27.1% and 72.9% of the included subpopulation with obesity, respectively. Obesity was independently associated with higher risks of 10 of 22 cancers. Stratified by metabolic status, the MUO phenotype was consistently associated with 10 obesity-related cancers. In contrast, the MHO phenotype was only associated with increased risks of five cancers: endometrium, oesophagus, kidney, pancreas and postmenopausal breast cancers. CONCLUSION: Even in metabolically healthy individuals, obesity was associated with increased risks of five cancers, whereas we did not find that these individuals were associated with increased risks of several other obesity-related cancers.

Digitally tailoring arbitrary structured light of generalized ray-wave duality.

Structured lights, particularly those with tunable and controllable geometries, are highly topical due to a myriad of their applications from imaging to communications. Ray-wave duality (RWD) is an exotic physical effect in structured light that the behavior of light can be described by both the geometric ray-like trajectory and a coherent wave-packet, thus providing versatile degrees of freedom (DoFs) to tailor more general structures. However, the generation of RWD geometric modes requires a solid-state laser cavity with strict mechanical control to fulfill the ray oscillation condition, which limits the flexiblility of applications. Here we overcome this confinement to generate on-demand RWD geometric modes by digital holographic method in free space without a cavity. We put forward a theory of generalized ray-wave duality, describing all previous geometric modes as well as new classes of RWD geometric modes that cannot be generated from laser cavities, which are verified by our free-of-cavity creation method. Our work not only breaks the conventional cavity limit on RWD but also enriches the family of geometric modes. More importantly, it offers a new way of digitally tailoring RWD geometric modes on-demand, replacing the prior mechanical control, and opening up new possibilities for applications of ray-wave structured light.

Progression of diabetic kidney disease and trajectory of kidney function decline in Chinese patients with Type 2 diabetes.

Diabetes is a major cause of end stage renal disease (ESRD), yet the natural history of diabetic kidney disease is not well understood. We aimed to identify patterns of estimated GFR (eGFR) trajectory and to determine the clinical and genetic factors and their associations of these different patterns with all-cause mortality in patients with type 2 diabetes. Among 6330 patients with baseline eGFR >60 ml/min per 1.73 m2 in the Hong Kong Diabetes Register, a total of 456 patients (7.2%) developed Stage 5 chronic kidney disease or ESRD over a median follow-up of 13 years (incidence rate 5.6 per 1000 person-years). Joint latent class modeling was used to identify different patterns of eGFR trajectory. Four distinct and non-linear trajectories of eGFR were identified: slow decline (84.3% of patients), curvilinear decline (6.5%), progressive decline (6.1%) and accelerated decline (3.1%). Microalbuminuria and retinopathy were associated with accelerated eGFR decline, which was itself associated with all-cause mortality (odds ratio [OR] 6.9; 95% confidence interval [CI]: 5.6-8.4 for comparison with slow eGFR decline). Of 68 candidate genetic loci evaluated, the inclusion of five loci (rs11803049, rs911119, rs1933182, rs11123170, and rs889472) improved the prediction of eGFR trajectories (net reclassification improvement 0.232; 95% CI: 0.057--0.406). Our study highlights substantial heterogeneity in the patterns of eGFR decline among patients with diabetic kidney disease, and identifies associated clinical and genetic factors that may help to identify those who are more likely to experience an accelerated decline in kidney function.

Lactation intensity and duration to postpartum diabetes and prediabetes risk in women with gestational diabetes.

OBJECTIVE: To investigate the association of lactation intensity and duration with postpartum diabetes and prediabetes risks among Chinese women with a history of gestational diabetes (GDM). METHODS: We included 1260 women with a history of GDM who participated in the whole population's GDM universal screening survey by using the 1999 World Health Organization's criteria. Lactation intensity and lactation duration were collected by a standardized questionnaire. Postpartum diabetes and prediabetes risk were confirmed by an oral glucose tolerance test. RESULTS: During a mean postpartum period of 3.65 years, we identified 114 cases of diabetes and 417 cases of prediabetes. The multivariable-adjusted hazard ratios based on different lactation intensity (exclusive formula, mixed feeding, and exclusive lactation) were 1.00, 0.68, 0.45 for diabetes (Ptrend  = 0.008), and 1.00, 0.74, and 0.61 for prediabetes (Ptrend  = 0.006), respectively. The multivariable-adjusted hazard ratios associated with different lactation duration (none, 0-6 months, 6-12 months, 12-18 months, and ≥18 months) were 1.00, 0.66, 0.42, 0.66, and 0.25 for diabetes (Ptrend  = 0.013), and 1.00, 0.82, 0.62, 0.67, and 0.63 for prediabetes (Ptrend  = 0.021), respectively. A restricted cubic spline curve showed a graded inverse association of lactation duration with the risks of diabetes and prediabetes (Ptrend  < 0.001). CONCLUSIONS: Higher-lactation intensity and longer-lactation duration were significantly associated with lower risks of postpartum diabetes and prediabetes among Chinese women with a history of GDM.

Human α defensins promote the expression of the inflammatory cytokine interleukin-8 under high-glucose conditions: Novel insights into the poor healing of diabetic foot ulcers.

Sustained infection and chronic inflammation are the most common features and complex mechanisms of diabetic foot disease. In this study, we examined the expression and functional roles of human endogenous α defensins in diabetic foot ulcer. The expression levels of human α defensins HNP1, HNP3, and HNP4 were significantly higher in the wound center than the edge of diabetic foot ulcers. And the inflammatory cytokine interleukin IL-8 (IL-8) was also highly expressed in wound exudates. In human foreskin fibroblasts, these human α defensins were found only slightly to affect IL-8 expression directly. hemoglobin A1C (HbA1c) is the main clinical indicator of diabetic foot disease. Advanced glycation end products of bovine serum albumin (AGE-BSA), as HbA1c analogue, was found to promote IL-8 expression. Human α defensins, in the presence of AGE-BSA, further significantly promoted IL-8 expression. These findings showed that human α defensins aggravated the inflammatory response in diabetic foot ulcers patients, providing new insights in to the poor healing of diabetic foot ulcers.

Passive smoking and postpartum depression among Chinese women: A prospective cohort study in Tianjin, China.

Smoking has been associated with depression in the general population. Whether passive smoking is also associated with postpartum depression (PPD) is uncertain. From 2010 to 2012, we recruited 8,842 pregnant women in Tianjin, China. The mainland Chinese version of the Edinburgh Postnatal Depression Scale was used to evaluate postpartum depressive symptoms after birth, with a score of >9 defining PPD. Data were collected using specially designed questionnaires or data from the electronic database of Tianjin Maternal and Child Health Information System. Odds ratios (OR) and 95 percent confidence intervals (CI) were obtained for the association of smoking status with PPD using binary logistic regression. Passive smoke exposure rates before and during pregnancy were 40.9 percent and 52.1 percent, respectively. A total of 8.5% (n = 747) of participants had PPD. Compared with those not exposed, women passively exposed to smoke before and during pregnancy had higher odds of PPD (before pregnancy: OR: 1.24, 95 percent CI: 1.03-1.50; during pregnancy: OR: 1.43, 95 percent CI: 1.16-1.77) after adjustment for confounding factors. Passive smoking before and during pregnancy were associated with PPD in Chinese women. Reducing passive smoke exposure may reduce PPD in Chinese women; further longitudinal studies are warranted to replicate these findings.

The impact of maternal gestational weight gain on cardiometabolic risk factors in children.

AIMS/HYPOTHESIS: Accumulating evidence suggests an impact of gestational weight gain (GWG) on pregnancy outcomes; however, data on cardiometabolic risk factors later in life have not been comprehensively studied. This study aimed to evaluate the relationship between GWG and cardiometabolic risk in offspring aged 7 years. METHODS: We included a total of 905 mother-child pairs who enrolled in the follow-up visit of the multicentre Hyperglycemia and Adverse Pregnancy Outcome study, at the Hong Kong Centre. Women were classified as having gained weight below, within or exceeding the 2009 Institute of Medicine (IOM) guidelines. A standardised GWG according to pre-pregnancy BMI categories was calculated to explore for any quadratic relationship. RESULTS: Independent of pre-pregnancy BMI, gestational hyperglycaemia and other confounders, women who gained more weight than the IOM recommendations had offspring with a larger body size and increased odds of adiposity, hypertension and insulin resistance (range of p values of all the traits: 4.6 × 10-9 < p < 0.0390) than women who were within the recommended range of weight gain during pregnancy. Meanwhile, women who gained less weight than outlined in the recommendations had offspring with increased risks of hypertension and insulin resistance, compared with those who gained weight within the recommended range (7.9 × 10-3 < p < 0.0477). Quadratic relationships for diastolic blood pressure, AUC for insulin, pancreatic beta cell function and insulin sensitivity index were confirmed in the analysis of standardised GWG (1.4 × 10-3 < pquadratic < 0.0282). Further adjustment for current BMI noticeably attenuated the observed associations. CONCLUSIONS/INTERPRETATION: Both excessive and inadequate GWG have independent and significant impacts on childhood adiposity, hypertension and insulin resistance. Our findings support the notion that adverse intrauterine exposures are associated with persistent cardiometabolic risk in the offspring.

Low triglyceride as a marker for increased risk of cardiovascular diseases in patients with long-term type 2 diabetes: A cross-sectional survey in China.

BACKGROUND: There are inconsistent findings regarding associations between triglyceride levels and cardiovascular disease (CVD) in type 2 diabetes mellitus (T2DM). This study aimed to test whether the association between triglycerides and CVD depends upon duration of diabetes. METHODS: From April 1, 2012, to June 30, 2012, we conducted a cross-sectional survey of 223 612 patients with T2DM from 630 hospitals in China. Cardiovascular disease was defined as having either prior coronary heart disease or stroke, or diabetic foot. Binary logistic regression was used to estimate odds ratios of triglyceride for CVD. Relative excess risk due to interaction, attributable proportion due to interaction, and synergy index were used to estimate effect size of additive interaction between low triglyceride, ie, <1.7 mmol/L, and duration of diabetes, ie, ≥15 years. RESULTS: Among 223 612 T2DM patients, 31 898 (14.27%) suffered from CVD. A low level of triglyceride was associated with decreased risk of CVD (univariable OR, 0.91, 95% CI, 0.88-0.93; multivariable OR, 0.94, 95% CI, 0.92-0.97) among patients with <15 years of duration of diabetes but increased risk of CVD (univariable OR, 1.12, 95% CI, 1.04-1.21; multivariable OR, 1.18, 95% CI, 1.09-1.27) among those patients with 15 and more years of duration of diabetes with significant additive interactions (relative excess risk due to interaction, 0.39, 95% CI, 0.25-0.52; attributable proportion due to interaction, 0.20, 95% CI, 0.14-0.27; and synergy index, 1.80, 95% CI, 1.43-2.28). CONCLUSIONS: Whereas a high triglyceride level was associated with increased risk of CVD in short-term T2DM, low triglyceride was associated with increased CVD risk in long-term T2DM. Low triglyceride may be a marker of CVD risk in Chinese patients with long-term T2DM.