Multimorbidity measures associated with cognitive function among community-dwelling older Chinese adults.

INTRODUCTION: Older adults with multimorbidity are at high risk of cognitive impairment development. There is a lack of research on the associations between different multimorbidity measures and cognitive function among older Chinese adults living in the community. METHODS: We used the Chinese Longitudinal Healthy Longevity Survey from 2002 to 2018 and included data on dementia-free participants aged ≥65 years. Multimorbidity measures included condition counts, multimorbidity patterns, and trajectories. The association of multimorbidity measures with cognitive function was examined by generalized estimating equation and linear and logistic regression models. RESULTS: Among 14,093 participants at baseline, 43.2% had multimorbidity. Multimorbidity patterns were grouped into cancer-inflammatory, cardiometabolic, and sensory patterns. Multimorbidity trajectories were classified as "onset-condition," "newly developing," and "severe condition." The Mini-Mental State Examination scores were significantly lower for participants with more chronic conditions, with cancer-inflammatory/cardiometabolic/sensory patterns, and with developing multimorbidity trajectories. DISCUSSION: Condition counts, sensory pattern, cardiometabolic pattern, cancer-inflammatory pattern, and multimorbidity developmental trajectories were prospectively associated with cognitive function. HIGHLIGHTS: Elderly individuals with a higher number of chronic conditions were associated with lower MMSE scores in the Chinese Longitudinal Healthy Longevity Survey data. MMSE scores were significantly lower for participants with specific multimorbidity patterns. Individuals with developing trajectories of multimorbidity were associated with lower MMSE scores and a higher risk of mild cognitive impairment.

Association of hypertensive disorders of pregnancy with infant growth in the first 36 months of life.

To investigate the association of chronic hypertension, gestational hypertension, and preeclampsia diseases with infant growth in the first 36 months of life, we conducted a retrospective birth cohort of 31,734 children born in Zhoushan Maternal and Child Care Hospital between January 2001 and May 2018. Birthweight, gestational age, and infant growth (weight, height, weight/height-for-age Z score, the weight gain during childhood) were the main outcomes. The associations of chronic hypertension, gestational hypertension, and preeclampsia diseases with birth outcomes and infant growth at children's age of 3, 6, 12, 18, and 24 months were analyzed by multivariable regression models. Gestational hypertension, preeclampsia diseases, and chronic hypertension were significantly associated with lower birthweight and shorter gestational age. Both gestational hypertension and preeclampsia diseases were respectively inversely associated with weight, weight-for-age Z score, height, and height-for-age Z score of children in the whole sample and sub-sample data analysis from birth to the age of 36 months, although correction for birthweight rendered the associations nonsignificant. No significant association of gestational hypertension, preeclampsia diseases, and chronic hypertension with weight gain was found. Conclusion: The inverse associations of gestational hypertension and preeclampsia diseases with infant growth in early childhood were mainly mediated by the effect of gestational hypertension and preeclampsia diseases on lower birthweight. What is Known: • Hypertensive disorders of pregnancy are associated with increased risk of adverse birth outcomes. What is New: • Both gestational hypertension and preeclampsia were respectively inversely associated with physical development of offspring from birth to the age of 36 months. • Lower birthweight might be the mediator of the inverse associations of gestational hypertension and preeclampsia diseases with infant growth in early childhood.

Identifying urban built environment factors in pregnancy care and maternal mental health outcomes.

BACKGROUNDS: Risk factors related to the built environment have been associated with women's mental health and preventive care. This study sought to identify built environment factors that are associated with variations in prenatal care and subsequent pregnancy-related outcomes in an urban setting. METHODS: In a retrospective observational study, we characterized the types and frequency of prenatal care events that are associated with the various built environment factors of the patients' residing neighborhoods. In comparison to women living in higher-quality built environments, we hypothesize that women who reside in lower-quality built environments experience different patterns of clinical events that may increase the risk for adverse outcomes. Using machine learning, we performed pattern detection to characterize the variability in prenatal care concerning encounter types, clinical problems, and medication prescriptions. Structural equation modeling was used to test the associations among built environment, prenatal care variation, and pregnancy outcome. The main outcome is postpartum depression (PPD) diagnosis within 1 year following childbirth. The exposures were the quality of the built environment in the patients' residing neighborhoods. Electronic health records (EHR) data of pregnant women (n = 8,949) who had live delivery at an urban academic medical center from 2015 to 2017 were included in the study. RESULTS: We discovered prenatal care patterns that were summarized into three common types. Women who experienced the prenatal care pattern with the highest rates of PPD were more likely to reside in neighborhoods with homogeneous land use, lower walkability, lower air pollutant concentration, and lower retail floor ratios after adjusting for age, neighborhood average education level, marital status, and income inequality. CONCLUSIONS: In an urban setting, multi-purpose and walkable communities were found to be associated with a lower risk of PPD. Findings may inform urban design policies and provide awareness for care providers on the association of patients' residing neighborhoods and healthy pregnancy.

Changing patterns of prenatal depression and anxiety status in different trimesters and modified form of Zung scales for pregnant women.

BACKGROUND: We described the changing patterns of depression and anxiety status in different trimesters among Chinese pregnant women, and identified the modified form of SDS/SAS for pregnant women and assessed its reliability and validity. METHODS: Changing patterns of depression/ anxiety status in different trimesters were described. The modified form of SDS/SAS was identified for pregnant women. Cohen's Kappa to measure agreement with SDS/SAS, and the ROC analysis was performed to assess its validity. RESULTS: The SDS score in 1st trimester was higher than 2nd and 3rd trimester; there was no significant difference between SDS score in 2nd and 3rd trimester. Modified form of SDS evaluated the depression; the areas under the curve (AUC) in testing group were up to 0.988, 0.989 and 0.992 for 1st, 2nd and 3rd trimester, respectively. Modified form of SAS evaluated the anxiety, the AUC in testing group were up to 0.987, 0.985, 0.987 for 1st, 2nd and 3rd trimester, respectively. CONCLUSION: Pregnant women had higher severity of depression and anxiety status in 1st trimester than that in 2nd and 3rd trimester. The modified form of SDS/SAS may be more brief and suitable to assess the depression and anxiety status in pregnant women.KEY POINTSPregnant women had a higher severity of depression and anxiety status in the 1st trimester than that in the 2nd and 3rd trimester.The present study suggests that prenatal depression and anxiety status are prevalent in Chinese pregnant women.Prevention or treatments focus on high-score items of SDS and SAS would be beneficial for rectifying prenatal depression and anxiety.

Uric acid fluctuation had no effect on renal function among gout patients.

BACKGROUND AND AIMS: To investigate the effects of serum uric acid (SUA) level and its fluctuation on renal dysfunction in gout patients. METHODS AND RESULTS: Data on gout patients was collected from Huzhou city electronic medical record system data sharing platform, and information about relevant diagnoses, prescriptions, biochemical indexes and imaging characteristics was extracted. The gout patients with baseline normal renal function were enrolled in this analysis, and the estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m2 was defined as renal dysfunction. The generalized estimating equation and Cox regression analysis were used. A total of 1009 patients with gout were enrolled. Compared with the reference group (normal baseline SUA with endpoint SUA to be < 6 mg/dL), endpoint SUA ≥ 10 mg/dL was associated with an increased risk of renal dysfunction (baseline normal SUA group: HR [95% CI] = 3.28 [1.21, 8.91]; baseline high SUA group: HR [95% CI] = 3.01 [1.43, 6.35]). Subgroup analysis of 771 SUA stable gout patients demonstrated that SUA levels at 8-10 (excluding 10), and ≥10 mg/dL were significantly associated with an increased risk for renal dysfunction, with HR [95%CI] to be 1.99 [1.05, 3.77], and 2.98 [1.38, 6.43], respectively. CONCLUSION: Regardless of the baseline SUA level, SUA >10 mg/dL was a significant risk factor for renal dysfunction. SUA between 6 and 10 mg/dL was a potential risk factor for renal dysfunction. No significant correlation of SUA fluctuation and renal function was found.

Association of trimester-specific gestational weight gain with birth weight and fetal growth in a large community-based population.

BACKGROUND: Previous studies showed that the association of gestational weight gain (GWG) with fetal birthweight and offspring developmental growth was unclear. The aim of this study is to investigate the respective effect of 1 kg of GWG during three trimesters on birthweight and offspring growth from birth to 3 years of age. METHODS: We extracted the decoded information from the Maternal and Child Health Information Management System of Zhoushan Maternal and Child Health Hospital in Zhejiang, China from October 2001 to March 2015, and used multiple linear and logistic regression models. RESULTS: This study included 20,232 women with a full-term singleton birth and 15,557 newborns who took regular health check-ups. Compared to that in the 2nd and 3rd trimester, 1 kg GWG increasing in the 1st trimester had the strongest positive association with higher birthweight, body weight, and height from 1 to 36 months. Their associations with BMI after birth were similar among the three trimesters. In addition, some positive dose-response effects found between quartiles of GWG in the 1st trimester and offspring body weight, as well as BMI. The 1 kg GWG in 1st trimester played the strongest role in contributing to birth weight and benefiting to body growth among children aged up to 3 years. CONCLUSION: The 1 kg GWG in 1st trimester contributed more to birth weight and body development from birth to 3 years compared to the 2nd and 3rd trimesters. The possible beneficial effects of GWG in the 1st trimester on birthweight and offspring development in under/normal weight mothers are found.

The relationship of dietary diversity score with depression and anxiety among prenatal and post-partum women.

AIM: The objective of the study is to explore the relationship between the dietary diversity score (DDS) and anxiety and depression of perinatal women. METHODS: The Self-Rating Anxiety Scale (SAS), Self-Rating Depression Scale (SDS) and the dietary recall questionnaire were used to measure the status of depression, anxiety and dietary diversity at T1 (first trimester), T2 (second trimester), T3 (third trimester) and T4 (post-partum). The association of dietary diversity and food groups with depression and anxiety status were estimated by linear and logistic regression models. RESULTS: The prevalence of depression and anxiety status were the highest at T1, which were 35.58% and 22.57%, respectively. Cross-sectional and longitudinal association of DDS with SDS and SAS was estimated by ordinary or multilevel linear or logistic model. In the cross-sectional analysis, high dietary status (>6) was negatively associated with depression status [T1: OR (95% CI) = 0.56 (0.46, 0.69); T2: 0.55 (0.36, 0.84); T3: 0.45 (0.31, 0.65); T4: 0.58 (0.34, 0.99)] and anxiety status [T1: OR (95% CI) = 0.70 (0.56, 0.88); T2: 0.42 (0.27, 0.65)]. In the longitudinal analysis, it was demonstrated that the DDS level was negatively associated with SDS [ß(se) = -0.99 (0.09), P = <0.0001] and SAS scores [ß(se) = -0.37 (0.08), P = <0.0001] throughout pregnancy. There was a negative relationship between some food groups and SDS or SAS scores at different periods. CONCLUSION: A negative relationship between DDS and depression as well as anxiety was found among prenatal and post-partum women.

Prevalence and relevant factors of anxiety and depression among pregnant women in a cohort study from south-east China.

OBJECTIVE: To describe the prevalence rate of prenatal anxiety and depression among pregnant women in a prospective cohort study and to explore the relevant factors of anxiety and depression during each trimester. METHODS: Pregnant women were recruited into the Zhoushan Pregnant Women Cohort at Zhoushan Maternal and Child Care Hospital from September 2011 to March 2015. A self-made questionnaire was used to collect information about social demography, reproductive history, physical activity, and life behaviour at the first, second and third trimester, respectively. The Self-Rating Anxiety Scale (SAS) and the Self-Rating Depression Scale (SDS) were used to assess anxiety and depression status at each trimester, respectively. Prevalence rates of prenatal anxiety and depression at each trimester were described. RESULTS: The prevalence of anxiety status was 22.7%, 17.4% and 20.8% in the first, second and third trimester, respectively. The corresponding prevalence rate of depression status was 35.7%, 24.0% and 26.1%, respectively. Furthermore, women with a lower education level (junior high school or below) and a more physical occupation had higher prevalence of anxiety and depression status. CONCLUSIONS: The prevalence of prenatal anxiety and depression status was very common during pregnancy among pregnant women. Lower educational level and more physical occupations were associated with higher prevalence of anxiety and depression status.

Sleep was associated with depression and anxiety status during pregnancy: a prospective longitudinal study.

The purpose of this study was to reveal the cross-sectional and longitudinal association of sleep with depression and anxiety among Chinese pregnant women. Pregnant women were recruited in Zhoushan Pregnant Women Cohort at Zhoushan Maternal and Child Care Hospital from 2011 to 2015. Self-rating depression scales (SDS) and self-rating anxiety scales (SAS) were used for evaluating depression and anxiety status at each trimester; corresponding sleep quality and duration were reported by pregnant women. Ordinary or multilevel linear and logistic regression model were used to estimate the cross-sectional or longitudinal association of sleep with depression and anxiety. The prevalence rates were 35.64, 24.23, and 26.24% for depression and 22.57, 17.41, and 21.04% for anxiety at 1st (T1), 2nd (T2), and 3rd trimester (T3), respectively. Controlling for potential confounders, it revealed significant cross-sectional and longitudinal associations of sleep with depression and anxiety status. In cross-sectional analysis, women who slept less than 8 h/day had higher risk of depression (T1: OR (95%CI) = 1.75 (1.39, 2.20); T2: 1.52 (1.26, 2.05); T3: 1.60 (1.18, 2.05)) and anxiety (T1: 2.00 (1.57, 2.55); T2: 1.86 (1.37, 2.54); T3: 1.33 (0.99, 1.79)). In the longitudinal analysis, multilevel model revealed that women with subjective "fair" or "bad" sleep quality had elevated risk of depression (OR ranging from 1.54 to 3.71) and anxiety (2.38 to 7.53) during pregnancy. Prenatal depression and anxiety status were prevalent in pregnant women. Sleep quality was associated with depression and anxiety status in both cross-sectional and longitudinal analyses, implying that improving sleep quality should benefit for mental health of pregnant women.

Serum thyroid hormone levels among Chinese pregnant women.

AIM: The aim of this study is to examine gestational serum thyroid hormone levels and influencing factors among Chinese pregnant women with high dietary iodine intake. METHODS: The study was conducted from 2011 and 2013 in Zhoushan Women & Children's Hospital, Zhejiang, China. A total of 1991 pregnant women were enrolled and their serum levels of free thyroid hormones (FT4, FT3, and TSH) were detected by chemiluminescence method. RESULTS: Gestational serum FT4 and FT3 decreased with gestational week while TSH increased. Furthermore, the prevalence rate of subclinical hypothyroid increased with gestational stages, especially in the third trimester. Women aged more than 30 years had lower FT4 and FT3 in the first trimester and lower FT4 in the second trimester. No significant difference was found in the association of gestational serum thyroid hormones with maternal height and the gender of fetuses. CONCLUSION: Gestational serum thyroid hormones significantly changed with gestational week and were associated with the age of women. Specific normal range of thyroid hormones might be modified so as to better evaluate the thyroid hormone levels of pregnant women during pregnancy.

Outdoor temperature and temperature maintenance associated with blood pressure in 438,811 Chinese adults.

OBJECTIVES: The association of temperature maintenance with blood pressure (BP) has not been studied and the association of temperature with season-related BP was not being well understood. The present study aims to be further aware of season-related BP variation in Chinese adults. METHODS: We used decoded data from adults who visited the hospital for health examination from January 2008 to November 2013. Multivariate regression models were used to analyses the association between outdoor temperature and BP. RESULTS: The analysis included 438,811 adults. Larger change of BP accompanied with unit change of average outdoor temperature among outpatient than inpatient patients. The association of temperature with BP was stronger in normotensives than that in hypertensives. Compared with temperature variation, the impact of temperature maintenance on BP was smaller. These associations were stronger in men, older individuals. CONCLUSIONS: Temperature was strongly inversely associated with BP in Chinese adults. Temperature maintenance was mildly associated with BP compared to temperature variance. Seasonal temperature variation should be considered when screening for hypertension.

Multimorbidity patterns, leisure activities, and cognitive function: A population-based longitudinal study.

BACKGROUND: There is limited knowledge about the effect of leisure activities on cognitive decline related to different multimorbidity patterns. The study aimed to examine the role of leisure activities in the association between multimorbidity patterns and cognitive function. METHODS: We conducted a community-based cohort study based on the 2002-2018 Chinese Longitudinal Health Longevity Survey (CLHLS). Multimorbidity patterns were examined by exploratory factor analysis. Multivariable linear and logistic regression models were used to assess the associations between multimorbidity, leisure activities and cognitive function. RESULTS: The study included 14,093 older adults. Those with specific multimorbidity patterns had lower MMSE scores. Compared to individuals with cardio-metabolic and sensory patterns who frequently engaged in activities such as housework, garden work, and watching TV/listening to the radio, those who participated in these activities less regularly had lower MMSE scores. Furthermore, a higher frequency change of participation and a greater variety of leisure activities were associated with better cognitive function. CONCLUSIONS: The older individuals with multimorbidity are associated with lower MMSE scores, while those who participated in more leisure activities had higher cognitive function. Diverse, and frequent leisure activities may help delay cognitive decline in Chinese older adults with different multimorbidities.

Deep learning model to discriminate diverse infection types based on pairwise analysis of host gene expression.

Accurate detection of pathogens, particularly distinguishing between Gram-positive and Gram-negative bacteria, could improve disease treatment. Host gene expression can capture the immune system's response to infections caused by various pathogens. Here, we present a deep neural network model, bvnGPS2, which incorporates the attention mechanism based on a large-scale integrated host transcriptome dataset to precisely identify Gram-positive and Gram-negative bacterial infections as well as viral infections. We performed analysis of 4,949 blood samples across 40 cohorts from 10 countries using our previously designed omics data integration method, iPAGE, to select discriminant gene pairs and train the bvnGPS2. The performance of the model was evaluated on six independent cohorts comprising 374 samples. Overall, our deep neural network model shows robust capability to accurately identify specific infections, paving the way for precise medicine strategies in infection treatment and potentially also for identifying subtypes of other diseases.

The association of handgrip strength with all-cause and cardiovascular mortality: results from the National Health and Nutrition Examination Survey database prospective cohort study with propensity score matching.

Objective: To investigate the association between handgrip strength (HGS) with all-cause and cardiovascular disease (CVD) mortality in US adults. Method: We analyzed data from the National Health and Nutrition Examination Survey (NHANES) prospective cohort study (2011-2014) with 10,470 participants. The cox regression analysis, Kaplan-Meier survival curves, fitted curves, ROC curves, and propensity score-matched analysis (PSM) with inverse probability of treatment weighting (IPTW), SMRW (PSM with repeated weights), PA (pairwise algorithm), and OW (overlap weighting) regression analysis were performed to assess the relationship between HGS and all-cause and CVD mortality. Results: The low HGSs (men <37.4 kg, women <24 kg), was found to be associated with higher all-cause and CVD mortality in a reverse J-shaped curve (p < 0.05). Adjusting for multiple covariates including age, BMI, race, education level, marriage status, smoking and alcohol use, and various comorbidities, the hazard ratio (HR) for all-cause mortality in the lowest HGS quintile 1 (Q1) was 3.45 (2.14-5.58) for men and 3.3 (1.88-5.79) for women. For CVD mortality, the HR was 2.99 (1.07-8.37) for men and 10.35 (2.29-46.78) for women. The area under the curve (AUC) for HGS alone as a predictor of all-cause mortality was 0.791 (0.768-0.814) for men and 0.780 (0.752-0.807) for women (p < 0.05), while the AUC for HGS and age was 0.851 (0.830-0.871) for men and 0.848 (0.826-0.869) for women (p < 0.05). For CVD mortality, the AUC for HGS alone was 0.785 (95% CI 0.738-0.833) for men and 0.821 (95% CI 0.777-0.865) for women (p < 0.05), while the AUC for HGS and age as predictors of all-cause mortality was 0.853 (0.861-0.891) for men and 0.859 (0.821-0.896) for women (p < 0.05). The HGS Q1 (men <37.4 kg and women <24 kg) was matched separately for PSM. After univariate, multivariate Cox regression models, PSM, IPTW, SMRW, PA, and OW analyses, women had 2.37-3.12 and 2.92-5.12 HRs with low HGS for all-cause and CVD mortality, while men had 2.21-2.82 and 2.33-2.85 for all-cause and CVD mortality, respectively (p < 0.05). Conclusion: Adults with low HGS exhibited a significantly increased risk of both all-cause and CVD mortality, regardless of gender. Additionally, low HGS served as an independent risk factor and predictor for both all-cause and CVD mortality.

The relationship between sarcopenia and mortality in Chinese community-dwelling adults: a 7-year cohort study with propensity score matching and Mendelian randomization.

Background: Sarcopenia has been linked to adverse health outcomes, including an increased risk of mortality. This study aimed to assess the 7-year mortality risk of sarcopenia in a community-based population in China and explore the causal relationship between components of sarcopenia and any death. Methods: Data were sourced from the China Health and Retirement Longitudinal Study (CHARLS) conducted between 2011 and 2018. Sarcopenia was diagnosed using the Asian Working Group for Sarcopenia (AWGS) 2019 criteria. Logistic regression, Kaplan-Meier (KM) survival analysis, and propensity score matching with inverse probability of treatment weighting were used. Mendelian randomization (MR) analyses, conducted using European population data, were utilized to assess causality between sarcopenia and any death. Results: The study included 9,006 participants: 3,892 had no sarcopenia, 3,570 had possible sarcopenia, 1,125 had sarcopenia, and 419 had severe sarcopenia. Over 7 years of follow-up, there were 871 deaths, including 196 with sarcopenia and 133 with severe sarcopenia. The KM curves showed that sarcopenia had a higher risk of mortality. Compared to those of no sarcopenia, the odds ratios (ORs) of sarcopenia for 7-year mortality were 1.41 (95% CI, 1.06-1.87) after adjusting for confounding variables (p < 0.05). The ORs of severe sarcopenia were 2.11 (95% CI, 1.51-2.95). Propensity score matching analysis and inverse probability of treatment weighting analysis confirmed these findings. The adjusted ORs of sarcopenia and 7-year mortality were 2.94 (95% CI, 1.6-5.39) in the 45-60 age group, 1.72 (95% CI, 1.11-2.68) in the 60-80 age group, and 5.03 (95% CI, 0.48-52.65) in the ≥80 age group. The ORs of severe sarcopenia and 7-year mortality were 6.92 (95% CI, 1.95-24.5) in the 45-60 age group, 2.59 (95% CI, 1.61-4.17) in the 60-80 age group, and 12.52 (95% CI, 1.18-133.18) in the ≥80 age group. The MR analyses, leveraging the inverse variance weighted (IVW) method, unveiled substantial causal links between low hand grip strength in individuals aged 60 and older, the usual walking pace, and mortality risk. Conclusion: This study underscores the significant impact of sarcopenia and its components on mortality risk within the Chinese population. Particularly, low hand grip strength and usual walking pace emerged as noteworthy contributors to mortality risk.

Prototypical Graph Contrastive Learning.

Graph-level representations are critical in various real-world applications, such as predicting the properties of molecules. However, in practice, precise graph annotations are generally very expensive and time-consuming. To address this issue, graph contrastive learning constructs an instance discrimination task, which pulls together positive pairs (augmentation pairs of the same graph) and pushes away negative pairs (augmentation pairs of different graphs) for unsupervised representation learning. However, since for a query, its negatives are uniformly sampled from all graphs, existing methods suffer from the critical sampling bias issue, i.e., the negatives likely having the same semantic structure with the query, leading to performance degradation. To mitigate this sampling bias issue, in this article, we propose a prototypical graph contrastive learning (PGCL) approach. Specifically, PGCL models the underlying semantic structure of the graph data via clustering semantically similar graphs into the same group and simultaneously encourages the clustering consistency for different augmentations of the same graph. Then, given a query, it performs negative sampling via drawing the graphs from those clusters that differ from the cluster of query, which ensures the semantic difference between query and its negative samples. Moreover, for a query, PGCL further reweights its negative samples based on the distance between their prototypes (cluster centroids) and the query prototype such that those negatives having moderate prototype distance enjoy relatively large weights. This reweighting strategy is proven to be more effective than uniform sampling. Experimental results on various graph benchmarks testify the advantages of our PGCL over state-of-the-art methods. The code is publicly available at https://github.com/ha-lins/PGCL.

Using machine learning algorithms for predicting cognitive impairment and identifying modifiable factors among Chinese elderly people.

Objectives: This study firstly aimed to explore predicting cognitive impairment at an early stage using a large population-based longitudinal survey of elderly Chinese people. The second aim was to identify reversible factors which may help slow the rate of decline in cognitive function over 3 years in the community. Methods: We included 12,280 elderly people from four waves of the Chinese Longitudinal Healthy Longevity Survey (CLHLS), followed from 2002 to 2014. The Chinese version of the Mini-Mental State Examination (MMSE) was used to examine cognitive function. Six machine learning algorithms (including a neural network model) and an ensemble method were trained on data split 2/3 for training and 1/3 testing. Parameters were explored in training data using 3-fold cross-validation and models were evaluated in test data. The model performance was measured by area-under-curve (AUC), sensitivity, and specificity. In addition, due to its better interpretability, logistic regression (LR) was used to assess the association of life behavior and its change with cognitive impairment after 3 years. Results: Support vector machine and multi-layer perceptron were found to be the best performing algorithms with AUC of 0.8267 and 0.8256, respectively. Fusing the results of all six single models further improves the AUC to 0.8269. Playing more Mahjong or cards (OR = 0.49,95% CI: 0.38-0.64), doing more garden works (OR = 0.54,95% CI: 0.43-0.68), watching TV or listening to the radio more (OR = 0.67,95% CI: 0.59-0.77) were associated with decreased risk of cognitive impairment after 3 years. Conclusions: Machine learning algorithms especially the SVM, and the ensemble model can be leveraged to identify the elderly at risk of cognitive impairment. Doing more leisure activities, doing more gardening work, and engaging in more activities combined were associated with decreased risk of cognitive impairment.

Development and validation of a machine learning algorithm for predicting the risk of postpartum depression among pregnant women.

OBJECTIVE: There is a scarcity in tools to predict postpartum depression (PPD). We propose a machine learning framework for PPD risk prediction using data extracted from electronic health records (EHRs). METHODS: Two EHR datasets containing data on 15,197 women from 2015 to 2018 at a single site, and 53,972 women from 2004 to 2017 at multiple sites were used as development and validation sets, respectively, to construct the PPD risk prediction model. The primary outcome was a diagnosis of PPD within 1 year following childbirth. A framework of data extraction, processing, and machine learning was implemented to select a minimal list of features from the EHR datasets to ensure model performance and to enable future point-of-care risk prediction. RESULTS: The best-performing model uses from clinical features related to mental health history, medical comorbidity, obstetric complications, medication prescription orders, and patient demographic characteristics. The model performances as measured by area under the receiver operating characteristic curve (AUC) are 0.937 (95% CI 0.912 - 0.962) and 0.886 (95% CI 0.879-0.893) in the development and validation datasets, respectively. The model performances were consistent when tested using data ending at multiple time periods during pregnancy and at childbirth. LIMITATIONS: The prevalence of PPD in the study data represented a treatment prevalence and is likely lower than the illness prevalence. CONCLUSIONS: EHRs and machine learning offer the ability to identify women at risk for PPD early in their pregnancy. This may facilitate scalable and timely prevention and intervention, reducing negative outcomes and the associated burden.

The Association of Gene Variants in the Vitamin D Metabolic Pathway and Its Interaction with Vitamin D on Gestational Diabetes Mellitus: A Prospective Cohort Study.

The present prospective study included 2156 women and investigated the effect of gene variants in the vitamin D (VitD) metabolic and glucose pathways and their interaction with VitD levels during pregnancy on gestational diabetes mellitus (GDM). Plasma 25(OH)D concentrations were measured at the first and second trimesters. GDM subtype 1 was defined as those with isolated elevated fasting plasma glucose; GDM subtype 2 were those with isolated elevated postprandial glucose at 1 h and/or 2 h; and GDM subtype 3 were those with both elevated fasting plasma glucose and postprandial glucose. Six Gc isoforms were categorized based on two GC gene variants rs4588 and rs7041, including 1s/1s, 1s/2, 1s/1f, 2/2, 1f/2 and 1f/1f. VDR-rs10783219 and MTNR1B-rs10830962 were associated with increased risks of GDM and GDM subtype 2; interactions between each other as well as with CDKAL1-rs7754840 were observed (Pinteraction < 0.05). Compared with the 1f/1f isoform, the risk of GDM subtype 2 among women with 1f/2, 2/2, 1s/1f, 1s/2 and 1s/1s isoforms and with prepregnancy body mass index ≥24 kg/m2 increased by 5.11, 10.01, 10, 14.23, 19.45 times, respectively. Gene variants in VitD pathway interacts with VitD deficiency at the first trimester on the risk of GDM and GDM subtype 2.

Hemoglobin concentration and iron supplement during pregnancy were associated with an increased risk of gestational diabetes mellitus.

BACKGROUND: Hemoglobin (Hb) measurement is a conventional test during perinatal visits. Hb concentration is related to iron supplement. However, studies focusing on Hb levels, iron supplement, and pregnancy outcomes are scarce. This study aimed to determine whether Hb levels and iron supplement were associated with the risk of gestational diabetes mellitus (GDM). METHODS: A running hospital-based cohort was conducted from August, 2011. The demographic data and medical information were collected individually through questionnaires and patient medical records. Multiple linear regression was applied for the association between Hb levels, iron supplement, and blood glucose. Multiple logistic regression was used for evaluating odds ratios between Hb levels, iron supplement, and GDM. RESULTS: Hb levels during first (T1) and second trimester (T2) of pregnancy were significantly and positively associated with blood glucose and GDM risk. After adjusting for age, prepregnancy body mass index, and other risk factors, pregnant women with Hb ≥ 11 g/dL and iron supplement had higher postprandial blood glucose at 1 hour (Hb ≥ 11 g/dL in T2 and iron supplement in T1: ß = 0.860，P = <0.001; Hb ≥ 11 g/dL in T2 and iron supplement in T2: ß = 0.960，P < 0.001; Hb ≥ 11 g/dL in T1 and iron supplement in T2: ß = 1.133, P = 0.033) and GDM risks (odds ratio [OR] = 1.53, 95% confidence interval [CI]: 1.05-2.24; OR = 1.92, 95% CI: 1.13-3.35; OR = 2.15, 95% CI: 1.07-4.34, respectively), compared with those with Hb < 11 g/dL and without iron supplement. CONCLUSION: High Hb concentration and iron supplements without anemia increased postprandial blood glucose and risks for GDM. It indicates that pregnant women with good Hb levels should not be advised to take iron supplements during pregnancy.