Alignment-free estimation of sequence conservation for identifying functional sites using protein sequence embeddings.

Protein language modeling is a fast-emerging deep learning method in bioinformatics with diverse applications such as structure prediction and protein design. However, application toward estimating sequence conservation for functional site prediction has not been systematically explored. Here, we present a method for the alignment-free estimation of sequence conservation using sequence embeddings generated from protein language models. Comprehensive benchmarks across publicly available protein language models reveal that ESM2 models provide the best performance to computational cost ratio for conservation estimation. Applying our method to full-length protein sequences, we demonstrate that embedding-based methods are not sensitive to the order of conserved elements-conservation scores can be calculated for multidomain proteins in a single run, without the need to separate individual domains. Our method can also identify conserved functional sites within fast-evolving sequence regions (such as domain inserts), which we demonstrate through the identification of conserved phosphorylation motifs in variable insert segments in protein kinases. Overall, embedding-based conservation analysis is a broadly applicable method for identifying potential functional sites in any full-length protein sequence and estimating conservation in an alignment-free manner. To run this on your protein sequence of interest, try our scripts at https://github.com/esbgkannan/kibby.

Tree visualizations of protein sequence embedding space enable improved functional clustering of diverse protein superfamilies.

Protein language models, trained on millions of biologically observed sequences, generate feature-rich numerical representations of protein sequences. These representations, called sequence embeddings, can infer structure-functional properties, despite protein language models being trained on primary sequence alone. While sequence embeddings have been applied toward tasks such as structure and function prediction, applications toward alignment-free sequence classification have been hindered by the lack of studies to derive, quantify and evaluate relationships between protein sequence embeddings. Here, we develop workflows and visualization methods for the classification of protein families using sequence embedding derived from protein language models. A benchmark of manifold visualization methods reveals that Neighbor Joining (NJ) embedding trees are highly effective in capturing global structure while achieving similar performance in capturing local structure compared with popular dimensionality reduction techniques such as t-SNE and UMAP. The statistical significance of hierarchical clusters on a tree is evaluated by resampling embeddings using a variational autoencoder (VAE). We demonstrate the application of our methods in the classification of two well-studied enzyme superfamilies, phosphatases and protein kinases. Our embedding-based classifications remain consistent with and extend upon previously published sequence alignment-based classifications. We also propose a new hierarchical classification for the S-Adenosyl-L-Methionine (SAM) enzyme superfamily which has been difficult to classify using traditional alignment-based approaches. Beyond applications in sequence classification, our results further suggest NJ trees are a promising general method for visualizing high-dimensional data sets.

Using explainable machine learning to uncover the kinase-substrate interaction landscape.

MOTIVATION: Phosphorylation, a post-translational modification regulated by protein kinase enzymes, plays an essential role in almost all cellular processes. Understanding how each of the nearly 500 human protein kinases selectively phosphorylates their substrates is a foundational challenge in bioinformatics and cell signaling. Although deep learning models have been a popular means to predict kinase-substrate relationships, existing models often lack interpretability and are trained on datasets skewed toward a subset of well-studied kinases. RESULTS: Here we leverage recent peptide library datasets generated to determine substrate specificity profiles of 300 serine/threonine kinases to develop an explainable Transformer model for kinase-peptide interaction prediction. The model, trained solely on primary sequences, achieved state-of-the-art performance. Its unique multitask learning paradigm built within the model enables predictions on virtually any kinase-peptide pair, including predictions on 139 kinases not used in peptide library screens. Furthermore, we employed explainable machine learning methods to elucidate the model's inner workings. Through analysis of learned embeddings at different training stages, we demonstrate that the model employs a unique strategy of substrate prediction considering both substrate motif patterns and kinase evolutionary features. SHapley Additive exPlanation (SHAP) analysis reveals key specificity determining residues in the peptide sequence. Finally, we provide a web interface for predicting kinase-substrate associations for user-defined sequences and a resource for visualizing the learned kinase-substrate associations. AVAILABILITY AND IMPLEMENTATION: All code and data are available at https://github.com/esbgkannan/Phosformer-ST. Web server is available at https://phosformer.netlify.app.

Phosformer: an explainable transformer model for protein kinase-specific phosphorylation predictions.

MOTIVATION: The human genome encodes over 500 distinct protein kinases which regulate nearly all cellular processes by the specific phosphorylation of protein substrates. While advances in mass spectrometry and proteomics studies have identified thousands of phosphorylation sites across species, information on the specific kinases that phosphorylate these sites is currently lacking for the vast majority of phosphosites. Recently, there has been a major focus on the development of computational models for predicting kinase-substrate associations. However, most current models only allow predictions on a subset of well-studied kinases. Furthermore, the utilization of hand-curated features and imbalances in training and testing datasets pose unique challenges in the development of accurate predictive models for kinase-specific phosphorylation prediction. Motivated by the recent development of universal protein language models which automatically generate context-aware features from primary sequence information, we sought to develop a unified framework for kinase-specific phosphosite prediction, allowing for greater investigative utility and enabling substrate predictions at the whole kinome level. RESULTS: We present a deep learning model for kinase-specific phosphosite prediction, termed Phosformer, which predicts the probability of phosphorylation given an arbitrary pair of unaligned kinase and substrate peptide sequences. We demonstrate that Phosformer implicitly learns evolutionary and functional features during training, removing the need for feature curation and engineering. Further analyses reveal that Phosformer also learns substrate specificity motifs and is able to distinguish between functionally distinct kinase families. Benchmarks indicate that Phosformer exhibits significant improvements compared to the state-of-the-art models, while also presenting a more generalized, unified, and interpretable predictive framework. AVAILABILITY AND IMPLEMENTATION: Code and data are available at https://github.com/esbgkannan/phosformer. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Exclusive breastfeeding and its association with intimate partner violence during pregnancy: analysis from Pakistan demographic and health survey.

BACKGROUND: Intimate partner violence (IPV) is a global social issue and increasingly asks for the attention of policymakers. IPV is one of the main factors that affect the health of pregnant women and their infants during pregnancy and after childbirth; it will not only cause direct harm to women themselves but also reduce women's exclusive breastfeeding (EBF) behavior and pose a threat to newborn health. Existing facts on the association between IPV and EBF in the Pakistani context are negligible and incomplete to an enduring measure of IPV practice. To this effect, the present study aims to investigate the relationship between EBF and IPV practiced during the prenatal period and post-delivery. METHODS: The statistics study has drawn from the Pakistan Demographic and Health Survey (PDHS) 2018. A total of 1191 breastfeeding females aged 15-49 with children under 6 months were selected for the present study. T-test or chi-square test of Univariate test of hypothesis; Logistic regression model was utilized to explore the potential impact of IPV on female exclusive breastfeeding from three dimensions of physical, sexual and psychological violence, to provide data support for the Pakistani government to formulate policies to promote female EBF. All investigations have been performed in STATA software 16.0 (Stata Corp, College Station, TX, USA) at 95% confidence interval. RESULTS: Among the 1191 participants, 43.6% (520 / 1191) of the females were EBF, while the rates of physical, sexual, and emotional IPV were 47.44%, 30.23%, and 51.72%, respectively. Logistic regression analysis showed that females who have experienced physical IPV were 32% less likely to be exclusively breastfed (aOR = 0.68; 95% CI; 0.490, 0.980; P < 0.05), the chances of EBF were reduced by 22% in women who experienced IPV (aOR = 0.78; 95 CI; 0.55, 1.00; P < 0.05), females who experienced emotional IPV were 31% less probable to exclusively breastfed (aOR = 0.69; 95% CI; 0.47, 0.92; P < 0.05). CONCLUSIONS: This study determines the adverse effects of sexual and psychological violence on EBF practices in women. Policymakers in Pakistan should actively implement assistance programs to reduce IPV, emphasize monitoring women's experiences of IPV before and after giving birth, and encourage women to break the "culture of silence" when they experience IPV to maximize their access to assistance.

Income loss and subsequent poor psychological well-being among the Chinese population during the early COVID-19 pandemic.

BACKGROUND: The COVID-19 pandemic has had major ramifications for health and the economy at both the individual and collective levels. This study examined exogenous negative changes in household income and their implications on psychological well-being (PWB) among the Chinese population during the COVID-19 pandemic. METHODS: Data were drawn from the early China COVID-19 Survey, a cross-sectional anonymous online survey administered to the general population in China. Self-reported PWB was measured using a 5-point Likert scale with five questions related to the participants' recent psychological state. Hierarchical multiple linear regression was employed to examine whether income loss during the COVID-19 pandemic was associated with poor psychological health. RESULTS: This study included 8,428 adults, of which 90% had suffered from a moderate or severe loss of household income due to the early COVID-19 pandemic. Those who had experienced moderate or severe loss of income scored significantly lower on psychological well-being than those who did not experience income loss (19.96 or 18.07 vs. 21.46; P < 0.001); after controlling for confounders, income loss was negatively associated with PWB scores (moderate income loss: B = - 0.603, P < 0.001; severe income loss: B = - 1.261, P < 0.001). An interaction effect existed between the degree of income loss and pre-pandemic income groups. Specifically, participants in the middle-income group who had suffered severe income loss scored the lowest on PWB (B = - 1.529, P < 0.001). There was also a main effect on income loss, such that participants with varying degrees of income loss differed across five dimensions, including anhedonia, sleep problems, irritability or anger, difficulty with concentration, and repeated disturbing dreams related to COVID-19. CONCLUSIONS: Income loss during the pandemic has had detrimental consequences on psychological well-being, and the magnitude of the impact of income loss on psychological well-being varied according to previous income levels. Future policy efforts should be directed toward improving the psychological well-being of the economically vulnerable and helping them recover from lost income in the shortest time possible.

Improving Data Surveillance Resilience Beyond COVID-19: Experiences of Primary heAlth Care quAlity Cohort In ChinA (ACACIA) Using Unannounced Standardized Patients.

We analyzed COVID-19 influences on the design, implementation, and validity of assessing the quality of primary health care using unannounced standardized patients (USPs) in China. Because of the pandemic, we crowdsourced our funding, removed tuberculosis from the USP case roster, adjusted common cold and asthma cases, used hybrid online-offline training for USPs, shared USPs across provinces, and strengthened ethical considerations. With those changes, we were able to conduct fieldwork despite frequent COVID-19 interruptions. Furthermore, the USP assessment tool maintained high validity in the quality checklist (criteria), USP role fidelity, checklist completion, and physician detection of USPs. Our experiences suggest that the pandemic created not only barriers but also opportunities to innovate ways to build a resilient data collection system. To build data system reliance, we recommend harnessing the power of technology for a hybrid model of remote and in-person work, learning from the sharing economy to pool strengths and optimize resources, and dedicating individual and group leadership to problem-solving and results. (Am J Public Health. 2022;112(6):913-922. https://doi.org/10.2105/AJPH.2022.306779).

Did the Integrated Urban and Rural Resident Basic Medical Insurance Improve Benefit Equity in China?

OBJECTIVES: The reform of merging 2 major health insurance schemes into Urban and Rural Resident Basic Medical Insurance (URRBMI) is recognized as a vital step to safeguard equal healthcare and benefit to each enrollee in China. Against this backdrop, this article aims to evaluate the impact of URRBMI integration on benefit and its contribution to benefit equity. METHODS: The data of this study were derived from the China Health and Retirement Longitudinal Study 2011 and 2015. A total of 11 383 individuals were included in the final sample. Coarsened exact matching with difference-in-difference approach was firstly adopted to investigate the treatment effects of URRBMI on benefits. Next, the decomposition of concentration index (CI) was conducted to explore the contribution of URRBMI to benefit equity. RESULTS: The coarsened exact matching with difference-in-difference results revealed that the consolidation of URRBMI has significantly improved outpatient benefit. The decomposition results showed that the contribution rates of URRBMI scheme to outpatient benefit rate (CI -0.0114), benefit probability (CI 0.0673), compensation fee (CI 0.0076), and reimbursement ratio (CI 0.0483) were 11.26%, -3.38%, -7.67%, and -0.81%, suggesting that this reform makes contribution to the propoor inequity in the outpatient benefit rate and relieves the prorich inequity in outpatient benefit probability and the degree of benefits. CONCLUSIONS: The findings of this study provide novel evidence of enhanced benefits and benefit equity for outpatient care with the integration of URRBMI. Further efforts should be made to the expansion of URRBMI coverage and the elimination of income disparities that affecting benefit equity.

Does social capital buffer or exacerbate mental health inequality? Evidence from the China Family Panel Study (CFPS).

BACKGROUND: Health inequality, including physical and mental health inequality, is an important issue. What role social capital plays in mental health inequality is still ambiguous, especially in developing countries. The aim of this study is to explore the relationship between social capital and mental health inequality in China. METHOD: Both family-level and community-/village-level social capitals are included in our analysis. Data is mainly extracted from the China Family Panel Studies in 2018, and lagged term of social capital in CFPS 2016 was used to link with other variables in 2018. Depressive symptoms and subjective well-being are set as indicators of mental health. A series of OLS regression models were conducted to estimate the effects of social capital on mental health and mental health inequality. RESULTS: Higher levels of social capital and income are related to a lower level of depressive symptoms and a higher level of subjective well-being. The positive coefficient of interaction term of family-level social capital and income level in the urban area indicates that the inhibiting effect of social capital on depressive symptoms is pro-poor. The negative coefficient of interaction term of village-level social capital and income level in the rural area suggests that the promoting effect of social capital on subjective well-being is pro-poor, too. CONCLUSION: The results show that severe mental health inequality exists in China; family-level social capital can buffer depressive symptom inequality, and village-level social capital can buffer SWB inequality. Although the amount of social capital of the poor is less than the rich, the poor can better use social capital to improve their mental health. Our study advocates enhancing social participation and communication for the poor to reduce mental health inequality.

Interaction between self-perceived disease control and self-management behaviours among Chinese middle-aged and older hypertensive patients: the role of subjective life expectancy.

BACKGROUND: One of the effective ways to control hypertension is long-term self-management, which is difficult to maintain. Therefore, understanding how people engage in the process of self-management behaviour change is necessary. In this study, we aimed to examine the dynamic relationship between self-perceived disease control and self-management behaviours in Chinese middle-aged and older hypertensive patients, namely, medication use, self-monitoring, physical activity, tobacco and alcohol avoidance, and to explore the mediating role of subjective life expectancy (SLE) on this relationship. METHODS: Data were obtained from a nationally representative sample of 508 middle-aged and older hypertensive patients (aged 45+) from the 2013, 2015, and 2018 waves of the Chinese Longitudinal Healthy Longevity Survey. A cross-lagged panel model combined with mediation analysis was used to determine the dynamic relationship between self-perceived disease control and self-management behaviours and to clarify the mediating effect of SLE on this ascertained relationship. RESULTS: Good self-perceived disease control subsequently predicted good medication use, self-monitoring and physical activity, and vice versa. Subjective life expectancy (SLE) partially mediated the prospective reciprocal relationships between self-perceived disease control and these self-management behaviours, which accounted for 37.11, 25.88, and 19.39% of the total effect of self-perceived disease control on medication use, self-monitoring and physical activity, respectively. These self-management behaviours had a significant and positive feedback effect on self-perceived disease control. However, neither the direct and indirect effects (via SLE) of self-perceived disease control on tobacco and alcohol avoidance were revealed. CONCLUSIONS: Positive feedback loops of present self-perceived disease control, future SLE and self-management behaviours (medication use, self-monitoring, and physical activity) help middle-aged and older hypertensive patients adhere to these behaviours but are useless for the avoidance of addictive behaviours. Interventions aimed at enhancing the effect perception of general self-management behaviours (e.g., medication use, self-monitoring and physical activity) on the present disease control perspective, and future lifespan perspective would be beneficial for the consistent self-management behaviours of middle-aged and older hypertensive patients. The utility of present disease control perception to these self-management behaviours was much higher than the utility of future expectations. Alternative stress relief strategies may be conducive to long-term changes in addictive behaviours.

Artificial intelligence against the first wave of COVID-19: evidence from China.

BACKGROUND: The COVID-19 pandemic unexpectedly broke out at the end of 2019. Due to the highly contagious, widespread, and risky nature of this disease, the pandemic prevention and control has been a tremendous challenge worldwide. One potentially powerful tool against the COVID-19 pandemic is artificial intelligence (AI). This study systematically assessed the effectiveness of AI in infection prevention and control during the first wave of COVID-19 in China.  METHODS: To better evaluate the role of AI in a pandemic emergency, we focused on the first-wave COVID-19 in the period from the early December 2019 to the end of April 2020 across 304 cities in China. We employed three sets of dependent variables to capture various dimensions of the effect of AI: (1) the time to the peak of cumulative confirmed cases, (2) the case fatality rate and whether there were severe cases, and (3) the number of local policies for work and production resumption and the time span to having the first such policy. The main explanatory variable was the local AI development measured by the number of AI patents. To fit the features of different dependent variables, we employed a variety of estimation methods, including the OLS, Tobit, Probit, and Poisson estimations. We included a large set of control variables and added interaction terms to test the mechanisms through which AI took an effect. RESULTS: Our results showed that AI had highly significant effects on (1) screening and detecting the disease, and (2) monitoring and evaluating the epidemic evolution. Specifically, AI was useful to screen and detect the COVID-19 in cities with high cross-city mobility. Also, AI played an important role for production resumption in cities with high risk to reopen. However, there was limited evidence supporting the effectiveness of AI in the diagnosis and treatment of the disease. CONCLUSIONS: These results suggested that AI can play an important role against the pandemic.

Comparing the pelvis of Tibetan and Chinese Han women in rural areas of China: two population-based studies using coarsened exact matching.

This study aims to investigate the difference of pelvic size and shape between Tibetan and Chinese Han women. Data on pelvic dimension measures including interspinous diameter (IS), intercrestal diameter (IC), external conjugate (EC) and transverse outlet (TO) were acquired from two population-based studies amongst Tibetan women in Lhasa, and Chinese Han women in Shaanxi province in China. After coarsened exact matching, there was no statistical difference between any characteristics amongst Tibetan and Chinese Han women (p>.05). The generalised estimating equation models showed Tibetan women had significantly lower IS and IC means than Chinese Han women (IS: 24.39 cm vs. 24.77 cm, p<.001; IC: 26.35 cm vs. 26.93 cm, p<.001) but statistically higher in TO mean (9.12 cm vs. 9.03 cm, p<.001). This study showed Tibetan women have smaller pelvis compared to Chinese Han women. This should offer a useful literature on the comparison of pelvis between Tibetan and Chinese Han women although the difference is small.Impact StatementWhat is already known on this subject? Previous studies in China indicated different populations have different dimensions of pelvis, with the pelvis of Uighur women being bigger than Chinese Han women, and that of Zhuang and Tu women being smaller than Chinese Han women. Little research reports the specific size of Tibetan women's pelvis. Living at high altitude, the Tibetan population have differentiated demographics and show local adaptions, such as unelevated haemoglobin, and significant catch-up growth for infants compared with Chinese Han infants. Therefore, there is a strong rationale for better understanding pelvic characteristics amongst this population.What the results of this study add? This study showed Tibetan women have smaller pelvises compared to Chinese Han women. Tibetan women have a smaller interspinous diameter and intercrestal diameter than Chinese Han women, which leads to relatively narrow hip.What the implications are of these findings for clinical practice and/or further research? This study provides useful comparative information on pelvic features between Tibetan and Chinese Han women although the findings of differences were small. In addition, during the formulation of women's health policy, the results of this study can provide data to support the selection of appropriate indicators of obstetrics and gynaecology for different populations of pregnant women during antenatal care and delivery.

The benefits of an integrated social medical insurance for health services utilization in rural China: evidence from the China health and retirement longitudinal study.

BACKGROUND: Improving health equity is a fundamental goal for establishing social health insurance. This article evaluated the benefits of the Integration of Social Medical Insurance (ISMI) policy for health services utilization in rural China. METHODS: Using the China Health and Retirement Longitudinal study (2011‒2018), we estimated the changes in rates and equity in health services utilization by a generalized linear mixed model, concentration curves, concentration indices, and a horizontal inequity index before and after the introduction of the ISMI policy. RESULTS: For the changes in rates, the generalized linear mixed model showed that the rate of inpatient health services utilization (IHSU) nearly doubled after the introduction of the ISMI policy (8.78 % vs. 16.58 %), while the rate of outpatient health services utilization (OHSU) decreased (20.25 % vs. 16.35 %) after the implementation of the policy. For the changes in inequity, the concentration index of OHSU decreased significantly from - 0.0636 (95 % CL: -0.0846, - 0.0430) before the policy to - 0.0457 (95 % CL: -0.0684, - 0.0229) after it. In addition, the horizontal inequity index decreased from - 0.0284 before the implementation of the policy to - 0.0171 after it, indicating that the inequity of OHSU was further reduced. The concentration index of IHSU increased significantly from - 0.0532 (95 % CL: -0.0868, - 0.0196) before the policy was implemented to - 0.1105 (95 % CL: -0.1333, - 0.0876) afterwards; the horizontal inequity index of IHSU increased from - 0.0066 before policy implementation to - 0.0595 afterwards, indicating that more low-income participants utilized inpatient services after the policy came into effect. CONCLUSIONS: The ISMI policy had a positive effect on improving the rate of IHSU but not on the rate of OHSU. This is in line with this policy's original intention of focusing on inpatient service rather than outpatients to achieve its principal goal of preventing catastrophic health expenditure. The ISMI policy had a positive effect on reducing the inequity in OHSU but a negative effect on the decrease in inequity in IHSU. Further research is needed to verify this change. This research on the effects of integration policy implementation may be useful to policy makers and has important policy implications for other developing countries facing similar challenges on the road to universal health coverage.

The effects of family physician-contracted service on health-related quality of life and equity in health in China.

BACKGROUND: Family physician-contracted service (FPCs) has been recently implemented in Chinese primary care settings. This study was aimed at measuring the effects of FPCs on residents' health-related quality of life (HRQoL) and equity in health among the Chinese population. METHODS: The study data was drawn from the 2018 household health survey (Shaanxi Province, China) using multistage, stratified cluster random sampling. We measured HRQoL using EQ-5D-3L based on the Chinese-specific time trade-off values set. Coarsened exact matching (CEM) technique was used to control for confounding factors between residents with and without a contracted family physician. The concentration index (C) was calculated to measure equity in health. RESULTS: Individuals with a contracted family physician had significantly higher HRQoL than those without, after data matching (0.9355 vs. 0.8995; P <  0.001). Additionally, the inequity in HRQoL among respondents with a contracted family physician was significantly lower than those without a contracted family physician (Cs of EQ-5D utility score: 0.0084 vs. 0.0263; p <  0.001). CONCLUSIONS: This study highlights the positive effects of FPCs on HRQoL and socioeconomic-related equity in HRQoL. Future efforts should prioritize the economically and educationally disadvantaged groups, the expansion of service coverage, and the competency of family physician teams to further enhance health outcome and equity in health.

Trends in equity of inpatient health service utilization for the middle-aged and elderly in China: based on longitudinal data from 2011 to 2018.

BACKGROUND: The aim of this study was to assess the trends in equity of receiving inpatient health service utilization (IHSU) in China over the period 2011-2018. METHODS: Longitudinal data obtained from China Health and Retirement Longitudinal Studies were used to determine trends in receiving IHSU. Concentration curves, concentration indices, and horizontal inequity indices were applied to evaluate the trends in equity of IHSU. RESULTS: This study showed that the annual rate of IHSU gradually increased from 7.99% in 2011 to 18.63% in 2018. Logistic regression shows that the rates of annual IHSU in 2018 were nearly 3 times (OR = 2.86, 95%CL: 2.57, 3.19) higher for rural respondents and 2.5 times (OR = 2.49, 95%CL: 1.99, 3.11) higher for urban respondents than the rates in 2011 after adjusting for other variables. Concentration curves both in urban and rural respondents lay above the line of equality from 2011 to 2018. The concentration index remained negative and increased significantly from - 0.0147 (95% CL: - 0.0506, 0.0211) to - 0.0676 (95% CL: - 0.0894, - 0.458), the adjusted concentration index kept the same tendency. The horizontal inequity index was positive in 2011 but became negative from 2013 to 2018, evidencing a pro-low-economic inequity trend. CONCLUSIONS: We find that the inequity of IHSU for the middle-aged and elderly increased over the past 10 years, becoming more focused on the lower-economic population. Economic status, lifestyle factors were the main contributors to the pro-low-economic inequity. Health policies to allocate resources and services are needed to satisfy the needs of the middle-aged and elderly.

Ethnic group differences in obesity in Asian Americans in California, 2013-2014.

BACKGROUND: Obesity has been generally understudied in Asian Americans. It is important to identify subgroups of Asian Americans at high risk of obesity to help develop targeted interventions for those subgroups. This study aimed to examine the disparities in obesity among Asians (i.e., Chinese, Filipino, Japanese, Korean, and Vietnamese) living in California. METHODS: A sample of Adult Americans in California (n = 47,970) including Asian American adults (n = 3810) aged 18 years or older were obtained from the 2013-2014 California Health Interview Survey (the U.S. nation's largest state cross-sectional health survey). Body mass index was calculated using self-reported height and weight. Weight status was determined using the WHO Asian BMI cut points in 4 categories: < 18.5 kg/m2 (underweight), 18.5-22.9 kg/m2 (normal weight), 23-27.5 kg/m2 (overweight), and ≥ 27.5 kg/m2 (obese). Multiple logistic regression analyses were used to estimate odds ratio (OR) and 95% confidence interval (CI) after adjustment for covariates. RESULTS: Overall, the prevalence of Asians was 23.3% for obesity and 40.0% for overweight. The obesity prevalence was higher in Asians who were males, aged 45-64 years old, had higher family income, were current smokers, never got married, had lower education level, had an insufficient level of physical activity, and had more frequent consumption of fast foods. After adjusting for other factors, compared to Whites, being Hispanics and Blacks were associated with higher odds of obesity (OR = 1.47, 95%CI = 1.31-1.65; OR = 2.04, 95%CI = 1.65-2.53, respectively); being Chinese, Korean, and Vietnamese were associated with lower odds of obesity (OR = 0.28, 95%CI = 0.18-0.45; OR = 0.14, 95%CI = 0.04-0.46; OR = 0.28, 95%CI = 0.14-0.58, respectively). Compared to Chinese, being Japanese and Filipino were associated with higher odds of obesity (OR = 2.75, 95%CI = 1.52-4.95; OR = 2.90, 95%CI = 1.87-4.49, respectively). CONCLUSIONS: The prevalence of adult obesity was high among Asian Americans in California. Ethnic/racial disparities in obesity among Asian Americans in California were observed in 2013-2014. Compared to Whites, being Chinese, Korean, Vietnamese were associated with lower odds of obesity. Among Asians, compared to Chinese, being Japanese and being Filipino were associated with higher odds of obesity. These findings can help design better interventions to reduce racial and ethnic disparities in obesity, especially for Asian Americans.

Gender differences in depressive symptoms of rural Chinese grandparents caring for grandchildren.

BACKGROUND: Caring for grandchildren is regarded as one of the principle roles of middle- and old-aged adults, especially among rural Chinese grandparents. This study aims to examine the gender differences in depressive symptoms of rural Chinese grandparents caring for grandchildren, based on the gender differences in grandparental role engagement and the theories of role strain and role enhancement. METHODS: A total of 4833 rural citizens with one or more grandchildren were selected from the China Health and Retirement Longitudinal Study (CHARLS) conducted in 2015. Grandchild care was measured by continuous variable (duration) and categorical variable (no care, low intensity, moderate intensity, high intensity). Depressive symptoms were assessed by the Center for Epidemiologic Studies Depression Scale (CES-D). We used coarsened exact matching (CEM) to balance the covariates of caregivers and non-caregivers. Following CEM, 1975 non-caregivers and 2212 caregivers were identified (N = 4187). Multilevel linear regression was employed to examine the gender differences in depressive symptoms. We also tested for the moderating role of gender on the association between grandchild care and depressive symptoms. RESULTS: Grandmothers were more likely to provide grandchild care (54.42% vs 51.43%) at high intensity (61.46% vs 51.01%), with longer duration (39.24 h vs 33.15 h) than that given by grandfathers. Grandmothers suffered more from depressive symptoms than grandfathers, and such gap increased when grandparents were involved in high-intensity care. Grandmothers providing grandchild care, particularly at moderate intensity, were associated with fewer depressive symptoms (Coef. = - 0.087, 95%CI: - 0.163, - 0.010; Coef. = - 0.291, 95%CI: - 0.435, - 0.147), compared with non-caregivers. Grandmothers giving moderate intensity of grandchild care were also associated with fewer depressive symptoms (Coef. = - 0.171, 95% CI: - 0.313, - 0.029), compared with those with low-intensity care. However, such associations were not significant among grandfathers. CONCLUSIONS: Our findings highlight the gender differences in depressive symptoms of rural Chinese grandparents caring for grandchildren. Grandparents should be encouraged to engage in grandchild care, but at moderate intensity. The health status of middle- and old-aged adults, particularly females, should be monitored closely. Humanistic care, preventive care and curative treatment strategies focusing on such populations should be developed and refined.

Comparison of inequity in health-related quality of life among unemployed and employed individuals in China.

BACKGROUND: In China, achieving health equity has been regarded as a key issue for health reform and development in the current context. It is well known that unemployment has a negative effect on health. However, few studies have addressed the association between unemployment and inequity in health-related quality of life (HRQOL). This study aims to compare the inequality and inequity in HRQOL between the unemployed and employed in China. METHODS: The material regarding this study was derived from the Chinese National Health Services Survey of Shaanxi Province for 2013. We controlled for confounding factors by utilizing the coarsened exact matching method. Finally, 7524 employed individuals and 283 unemployed individuals who were 15 to 64 years old in urban areas were included in this study. We used HRQOL as the outcome variable, which was evaluated by using the Chinese version of EQ-5D-3L. The health concentration index, decomposition analysis based on the Tobit model, and the horizontal inequity index were employed to compute the socioeconomic-related equity between the unemployed and employed and the contribution of various factors. RESULTS: After matching, unemployed people tended to have poorer EQ-5D utility scores than employed people. There were statistically pro-rich inequalities in HRQOL among both employed and unemployed people, and the pro-rich health inequity of unemployed people was substantially higher than that of employed people. Economic status, age, education, smoking and health insurance were the factors influencing inequality in HRQOL between employed and unemployed individuals. Education status and basic health insurance have reduced the pro-rich inequity in HRQOL for unemployed people. CONCLUSION: It is suggested that unemployment intensifies inequality and inequity in HRQOL. According to policymakers, basic health insurance is still a critical health policy for improving health equity for the unemployed. Intervention initiatives aiming to tackle long-term unemployment through active labour market programmes, narrow economic gaps, improve educational equity and promote the health status of the unemployed should be considered by the government to achieve health equity.

Whether high government subsidies reduce the healthcare provision of township healthcare centers in rural China.

BACKGROUND: China's government launched a large-scale healthcare reform from 2009. One of the main targets of this round reform was to improve the primary health care system. Major reforms for primary healthcare institutions include increasing government investment. However, there are insufficient empirical studies based on large sample to catch long-term effect of increased government subsidy and lack of sufficient incentives on township healthcare centers (THCs), therefore, this study aims to provide additional empirical evidence on the concern by conducting an empirical analysis of THCs in Shaanxi province in China. METHODS: We collected nine years (2009 to 2017) data of THCs from the Health Finance Annual Report System (HFARS) that was acquired from the Health Commission of Shaanxi Province. We applied two-way fixed effect model and continue difference-in-difference (DID) model to estimate the effect of percentage of government subsidy on medical provision. RESULTS: A clear jump of the average percentage of government subsidy to total revenue of THCs can be found in Shaanxi province in 2011, and the average percentage has been more than 60% after 2011. Continue DID models indicate every 1% percentage of government subsidy to total revenue increase after 2011 resulted in a decrease of 1.1 to 3.5% in THCs healthcare provision (1.9% in medical revenue, 1.2% in outpatient visit, 3.5% in total occupy beds of inpatient, 1.1% in surgery revenue, 2.1% in sickbed utilization rate). The results show that the THCs with high government subsidy reduce the number of medical services after 2011. CONCLUSIONS: We think that it is no doubt that the government should take more responsibility for the financing of primary healthcare institutions, the problem is when government plays a central role in the financing and delivery of primary health care services, more effective incentives should be developed.

Rural and urban differences in patient experience in China: a coarsened exact matching study from the perspective of residents.

BACKGROUND: Patient experience is a key measure widely used to evaluate quality of healthcare, yet there is little discussion about it in China using national survey data. This study aimed to explore rural and urban differences in patient experience in China. METHODS: Data regarding this study were drawn from Chinese General Social Survey (CGSS) 2015, with a sample size of 9604. Patient experience was measured by the evaluation on healthcare services. Coarsened exact matching (CEM) method was used to balance covariates between the rural and urban respondents. Three thousand three hundred seventy-two participants finally comprised the matched cohort, including 1592 rural residents and 1780 urban residents. Rural and urban differences in patient experience were tested by ordinary least-squares regression and ordered logistic regression. RESULTS: The mean (SD) score of patient experience for rural and urban residents was 72.35(17.32) and 69.45(17.00), respectively. Urban residents reported worse patient experience than rural counterparts (Crude analysis: Coef. = - 2.897, 95%CI: - 4.434, - 1.361; OR = 0.706, 95%CI: 0.595, 0.838; Multivariate analysis: Coef. = - 3.040, 95%CI: - 4.473, - 1.607; OR = 0.675, 95%CI: 0.569, 0.801). Older (Coef. = 2.029, 95%CI: 0.338, 3.719) and healthier (Coef. = 2.287, 95%CI: 0.729, 3.845; OR = 1.217, 95%CI: 1.008, 1.469) rural residents living in western area (Coef. = 2.098, 95%CI: 0.464, 3.732; OR = 1.276, 95%CI: 1.044, 1.560) with higher social status (Coef. = 1.158, 95%CI: 0.756, 1.561; OR = 1.145, 95%CI: 1.090, 1.204), evaluation on adequacy (Coef. = 7.018, 95%CI: 5.045, 8.992; OR = 2.163, 95%CI: 1.719, 2.721), distribution (Coef. = 4.464, 95%CI: 2.471, 6.456; OR = 1.658, 95%CI: 1.312, 2.096) and accessibility (Coef. = 2.995, 95%CI: 0.963, 5.026; OR = 1.525, 95%CI: 1.217, 1.911) of healthcare resources had better patient experience. In addition, urban peers with lower education (OR = 0.763, 95%CI: 0.625, 0.931) and higher family economic status (Coef. = 2.990, 95%CI: 0.959, 5.021; OR = 1.371, 95%CI: 1.090,1.723) reported better patient experience. CONCLUSIONS: Differences in patient experience for rural and urban residents were observed in this study. It is necessary to not only encourage residents to form a habit of seeking healthcare services in local primary healthcare institutions first and then go to large hospitals in urban areas when necessary, but also endeavor to reduce the disparity of healthcare resources between rural and urban areas by improving quality and capacity of rural healthcare institutions and primary healthcare system of China.