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Background: Ensuring that the scale and hierarchical structure of health human resources are rational, and that medical services are efficient and fair, is an important task of practical significance. On this basis, examining the impact of health human resources on the level of medical services presents a new and formidable challenge. This study aims to delve into how the scale and hierarchical structure of health human resources in China's four major economic regions affect the fairness and efficiency of medical services, and to identify optimization strategies., Methods: This study utilizes provincial panel data from China's four major economic regions spanning the years 2009 to 2021. Initially, it provides a statistical description of the current state of health human resources and the level of medical services. Subsequently, it employs a fixed-effects model to analyze the impact of the scale and hierarchical structure of health human resources, as well as their interactive effects, on the fairness and efficiency of medical services, and discusses the interactive mechanisms between medical service fairness and medical service efficiency. Furthermore, after conducting a comprehensive evaluation of the level of medical services using the entropy weight method, it explores the regional heterogeneity and temporal dynamics in the influence of the scale and hierarchical structure of health human resources on the level of medical services. Finally, the study examines the scientific validity and rationality of the research findings through various robustness checks, including the substitution of research variables and models., Results: The study found that the scale of health human resources has a promoting effect on the equity of medical services (β ≤ 0.643, p ≤ 0.01), but exhibits an inhibitory effect on the efficiency of medical services (β ≥ -0.079, p ≤ 0.1); the hierarchical structure of health human resources shows a positive impact on both the equity and efficiency of medical services (β equity  ≤ 0.160, p ≤ 0.01; β efficiency  ≤ 0.341, p ≤ 0.05); at the same time, the results indicate that the interactive effect of the scale and hierarchical structure of health human resources promotes equity in medical services (β = 0.067, p ≤ 0.01), but restricts the efficiency of medical services (β ≥ -0.039, p ≤ 0.01); the mechanism by which health human resources affect the level of medical services in China's western and northeastern regions is more pronounced than in the central and eastern regions; after the implementation of the "Healthy China 2030" Planning Outline, the role of health human resources in the level of medical services has been strengthened; in the robustness tests, the model remains robust after replacing the core explanatory variables, with R 2 maintained between 0.869 and 0.972, and the dynamic GMM model test shows a significant second-order lag in the level of medical services (β equity  ≤ 0.149, p ≤ 0.01; β efficiency  ≤ 0.461, p ≤ 0.01); the channel test results prove that managerial personnel and other technical personnel are key pathways in regulating the impact of medical staff on the level of medical services., Conclusion: This study provides an in-depth analysis of the impact of health human resources on the level of medical services, revealing that both the scale and hierarchical structure of health human resources significantly affect the equity and efficiency of medical services. Furthermore, the influence of health human resources on the level of medical services exhibits regional heterogeneity and temporal characteristics. Robustness tests ensure the scientific validity and robustness of the research conclusions. This provides effective references for optimizing the allocation of health human resources and improving the level of medical services., (© 2024. The Author(s).)

Agriculture is a significant source of carbon emissions, which have a substantial environmental impact. The digital economy plays a vital role in mitigating these emissions through innovative digital solutions. As a leading agricultural nation, China faces substantial pressure to reduce its agricultural carbon emissions(ACE). This paper aims to thoroughly examine the relationship between the growth of the rural digital economy and ACE. To achieve this, we utilize an extensive panel dataset covering China's provinces from 2011 to 2020, analyzing the dynamic and spatial effects of digital economy development on ACE. The key findings of this research are as follows: (1) The rapid expansion of the digital economy significantly reduces ACE. (2) The impact of digital economic development on lowering ACE varies spatially, with a clear progression from eastern to western regions. (3) The digital economy helps reduce ACE through three specific channels: fostering technological innovation, enhancing scale efficiency management, and providing agricultural financial incentives. Based on these findings, this study proposes policy recommendations to improve digital infrastructure, promote balanced regional development in the digital economy, and optimize the management of agricultural science and technology. These policy insights aim to transform agriculture and achieve the goal of reducing ACE, thereby contributing to broader environmental sustainability., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Objectives: This study investigated the longitudinal association between marital satisfaction and active social engagement among older adults, while also considering potential gender differences in these associations., Methods: Seven waves of data from the Korean Longitudinal Study of Aging from 2006 to 2019 were utilized (N = 2,568, aged 65 or older). Fixed-effects Poisson regression models were employed to account for unobserved individual-level confounders. To capture active social engagement comprehensively, multiple activity types including social interaction, physical activity, travel activity, and volunteer activity were considered. An interaction model was used to examine potential gender differences., Results: The results of this study suggested that an individual's marital satisfaction is associated with an increase in their active social engagement. A one-standard deviation increase in marital satisfaction was associated with a 1.9%, 2.9%, 5.8%, and 18.1% higher incidence rate of engagement in social interaction, physical activity, travel activity, and volunteer activity, respectively, after accounting for individual-specific factors. The associations for social interaction and travel activity were largely driven by older men. In contrast, the associations for physical activity and volunteer activity were similar for older men and older women., Discussion: Marital satisfaction plays a crucial role in fostering active social engagement among older adults. Interventions designed to address social and financial obstacles within marital relationships among older adults could effectively improve their health and well-being by promoting various types of activities. The impact of these interventions may differ based on gender and the specific types of activities involved., (© The Author(s) 2023. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Problematic smartphone use (PSU) and sleep disorders (SD) are common public health problems among college students. While previous cross-sectional studies have found a relationship between PSU and SD, the causal direction of this relationship remains unclear. This study aims to examine the longitudinal changes of PSU and SD during the COVID-19 pandemic, determine the causal relationship between them, and identify confounding factors that affect this association., Methods: The study sample consisted of 1186 Chinese college students (47.7% male) with a mean age of 18.08 years. Participants completed the Smartphone Addiction Scale - Short Version (SAS-SV) and the Pittsburgh Sleep Quality Index (PSQI) at both baseline and follow-up surveys, conducted one year apart. The cross-lagged panel model (CLPM) was used to examine the causal relationship between PSU and SD, stratified by gender and duration of daily physical activity. The fixed effect panel regression was used to confirm the findings of CLPM., Results: The results of the CLPM analysis showed a significant bidirectional relationship between PSU and SD for the overall sample, which was consistent with the fixed effects model findings. However, subgroup analyses revealed that the bidirectional association disappeared among males or those who engaged in daily physical activity for more than 1 h., Conclusions: Our study shows a significant bidirectional association between PSU and SD, with variations across gender and daily physical activity levels. Encouraging physical activity may serve as a potential intervention to disrupt the bidirectional association between PSU and SD, which has important implications for public health strategies aimed at reducing the negative consequences of PSU and SD., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Green development is a comprehensive concept incorporating environmental protection, playing a vital role in industrial upgrading and economic transformation. Under the current national status of political centralization and fiscal decentralization, decentralized environmental governance exerts a noticeable impact on green development (GTFP). The direct, mediating mechanism, and the spillover effects of environmental decentralization (ED) on GTFP are examined according to 30 Chinese areas dataset from 2005 to 2019. We reveal that a significant negative impact of ED on GTFP. The mediating effect of industrial upgrading is found during impact of ED on GTFP process. Furthermore, with the rising ED of surrounding areas, the GTFP of its region will be weakened. Meanwhile, an overall negative spillover effect of ED on the GTFP of neighboring areas is confirmed. ED in eastern and central China negatively impact GTFP, and such impact in the western area is insignificant. The spillover effects are also heterogeneous., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background and Objectives: Marital satisfaction has been established as an essential factor for promoting health and well-being in older adults. However, it is unclear whether marital satisfaction is also associated with cognitive health in this population. This study aimed to investigate the longitudinal association between marital satisfaction and cognitive function, while also exploring variations in this relationship by gender and across the cognitive function distribution., Research Design and Methods: This study used 6 waves of the Korean Longitudinal Study of Ageing (KLoSA) and employed gender-stratified unconditional quantile regression (UQR) models with fixed effects (FE) to estimate the association between marital satisfaction and cognitive function across different quantiles of the cognitive function distribution. FE models controlled for unobserved individual-level confounders such as genetics, cognitive and noncognitive skills, and early childhood social and cultural background., Results: The results of this study revealed that marital satisfaction was positively associated with cognitive function ( b  = 0.305), and this association was stronger in older men than in older women ( b  = 0.392 for older men vs b  = 0.181 for older women). The UQR-FE models suggested that stronger association between marital satisfaction and cognitive function was observed among older men with lower cognitive function ( b  = 0.817 for 10th percentile vs b  = 0.118 for 90th percentile). Among older women, no clear patterns of heterogeneity were found across the cognitive function distribution., Discussion and Implications: The findings of this study highlight a significant degree of heterogeneity in the relationship between marital satisfaction and cognitive function among older men, with stronger associations observed in the lower percentiles of the cognitive function distribution. Interventions aimed at improving marital quality could be an effective strategy for promoting cognitive health in older adults, with an approach tailored to the individual's characteristics., Competing Interests: None., (© The Author(s) 2023. Published by Oxford University Press on behalf of The Gerontological Society of America.)

Background: The Central Government of India introduced the National Health Mission (NHM) in 2005 to improve health outcomes by enhancing publicly financed (government) health expenditure and health infrastructure at the state level. This study aims to examine the effects of the state-level heterogeneity in publicly financed spending on health services on major health outcomes such as life expectancy, infant mortality rate, child mortality rate, the incidence of malaria, and immunization coverage (i.e., BCG, Polio, Measles, and Tetanus)., Methods: This study investigates the relationships between publicly financed health expenditure and health outcomes by controlling income and infrastructure levels across 28 Indian States from 2005 to 2016. Along with all states, the empirical analysis has also been carried out for high-focus and non-high-focus states as per the NHM fund flow criteria. It has applied panel fixed-effects and random effects model wherever required based on the Hausman test., Results: The empirical results show that publicly financed health expenditure reduces infant mortality, child mortality, and malaria cases. At the same time, it improves life expectancy and immunization coverage in India. It also finds that the relationship between publicly financed health expenditure and health outcomes is weak, especially in the high-focus states., Conclusions: Given the healthcare need for achieving desirable health outcomes, Indian States should enhance publicly financed expenditure on health services. This study augments essential guidance for implementing public health policies in developing countries., (© 2023. The Author(s).)

Given the global ecological environment deteriorating, the ESG (environmental, social, and governance) concept advocates that economic growth and environmental protection must go hand in hand. Green taxations, in particular, are critical to economic development as they serve as a key lever for the government in regulating the national economy and improving environmental quality. This paper aims to examine the pollution reduction effect of green taxation in China. We constructed fixed effect model using provincial panel data from 2012 to 2017 to empirically examine the effect of green taxation-including environment protection tax, consumption tax, resource tax, and vehicle purchase tax-on pollution emissions. The findings show that environmental protection tax has a significant inhibitory effect on exhaust gas emissions but a poor inhibitory effect on wastewater and industrial solid waste emissions. Other green taxations-consumption tax, resource tax, and vehicle purchase tax-do not have an ideal inhibitory effect on pollution emissions. The paper concludes with policy recommendations organized around improving the environmental protection tax, actively promoting the ESG concept, and optimizing the top-level design of the green taxation system., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Internet development has changed Chinese people's consumption behavior, gradually expanding from survival consumption (SC) to development and enjoyment consumption (DEC) trends. Consumption is the new engine driving China's economic growth and the terminal of carbon emissions. Simultaneously, China is undergoing a profound change toward the "double carbon" goal, the space for carbon emission reduction in traditional fields is gradually compressed. Therefore, it is necessary to explore carbon emissions from the perspective of consumption terminals. Based on provincial panel data, we use the fixed effects model and mediating effects model to explore the relationship between Internet development, consumption upgrading, and carbon emissions in a unified research framework. The findings show that: (1) Internet development leads to an increase in carbon emissions. A finding remains significant after using instrumental variables to mitigate endogeneity; (2) Internet development promotes consumption upgrading, reflected in development and enjoyment consumption expenditure; (3) Internet development contributes to increasing carbon emissions through consumption upgrading. Heterogeneity analysis shows that Internet development in eastern China significantly contributes to carbon emissions through consumption upgrading, while it is insignificant in central and western regions. The Internet development leading region contributes to an increase in carbon emissions through consumption upgrading. In comparison, the lagging region is insignificant. This study can provide a reference for policymakers in China or other countries to formulate energy-saving and emission-reduction policies in the Internet industry and provide a scientific basis for advocating people's low-carbon consumption behavior and achieving carbon emission reduction at the consumption terminal.

The COVID-19 virus has challenged the development of the cultural industries seriously, so far, however few studies have used empirical methods to analyze the impact of the pandemic on the overall cultural industries. Based on the panel data of listed companies, this paper explores the impact of COVID-19 on cultural industries from the perspective of stock market returns. The empirical results show that the pandemic has a significant negative impact on the stock market returns of cultural industries, but the degrees of impact on various creative sub-sectors are significantly different. The findings also indicate that digitalization can effectively reduce the negative impact of COVID-19 on cultural companies, and the epidemic has bigger negative impacts on small and newly-established cultural companies. Moreover, we find that the stock market returns of cultural industries have an inverted U-shaped relationship with the daily growth in total confirmed cases and in total cases of death caused by COVID-19, indicating that the negative marginal impact of COVID-19 on the cultural industries increases firstly and then gradually decreases. Finally, implications for companies and governments are presented respectively based on the findings., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Zhang, Ji, Pang and Suo.)

Stepped-wedge cluster randomized trials (SW-CRTs) are typically analyzed using mixed effects models. The fixed effects model is a useful alternative that controls for all time-invariant cluster-level confounders and has proper control of type I error when the number of clusters is small. In principle, all clusters in SW-CRTs are designed to eventually receive the intervention, but in real-world research, some trials can end with unexposed clusters (clusters that never received the intervention), such as when a trial is terminated early based on interim analysis results. Typically, unexposed clusters are expected to contribute no information to the fixed effects intervention effect estimator and are excluded from fixed effects analyses. In this article we mathematically prove that inclusion of unexposed clusters improves the precision of the fixed effects least squares dummy variable (LSDV) intervention effect estimator, re-analyze data from a recent SW-CRT of a novel palliative care intervention containing an unexposed cluster, and evaluate the methods by simulation. We found that including unexposed clusters improves the precision of the fixed effects LSDV intervention effect estimator in both real and simulated datasets. Our simulations also reveal an increase in power and decrease in root mean square error. These improvements are present even if the assumptions of constant residual variance and period effects are violated. In the case that a SW-CRT concludes with unexposed clusters, these unexposed clusters can be included in the fixed effects LSDV analysis to improve precision, power, and root mean square error., (© 2022 John Wiley & Sons Ltd.)

Hypertension is one of the crucial risk factors for morbidity and mortality around the world, and South Africa has a significant unmet need for hypertension care. This study aims to establish the potential risk factors of hypertension amongst adults in South Africa attributable to high systolic and diastolic blood pressure over time by fitting panel quantile regression models. Data obtained from the South African National Income Dynamics Study (NIDS) Household Surveys carried out from 2008 to 2018 (Wave 1 to Wave 5) was employed to develop both the fixed effects and random effects panel quantile regression models. Age, BMI, gender (males), race, exercises, cigarette consumption, and employment status were significantly associated with either one of the BP measures across all the upper quantiles or at the 75th quantile only. Suggesting that these risk factors have contributed to the exacerbation of uncontrolled hypertension prevalence over time in South Africa.

The utilization of health screening and other community health services has been a hot topic in China. Thus, this study examined the effect of health changes (self-rated health, physical health, and mental health) on older people's community health screening participation in China. We derived the data from the 2016 and 2018 waves of the Chinese Longitudinal Aging Social Survey (CLASS). This paper included 10,992 observations in two waves. We tested the causal relationship using the fixed effects model. Approximately 29.56% of the respondents participated in a health screening. Notably, after controlling for covariates, changes in mental and physical health both significantly influenced seniors' participation in health screenings (self-rated health: β = 0.188, 95% CI [-0.037, -0.413]; physical health: β = 0.078, 95% CI [0.032, -0.124]; mental health: β = 0.034, 95% CI [-0.057, -0.002]). The findings showed age, educational level, income level, and family support to be significant factors associated with community health screening participation. Additionally, we identified a partial mediating effect of mental health between self-rated health and health screening participation and a partial mediating effect of depression between physical health and health screening participation. The results highlight the important role of health changes in influencing participation and promoting health screening in China. On this basis, healthcare providers in the community may consider health changes as a screening criterion to promote health screening, guiding other health promotion and prevention programs while promoting healthy aging., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Du and Mu.)

As China's economy continues to grow, more and more attention is being paid to environmental pollution issues, including haze pollution, which is the most prominent of the air problems. In order to alleviate the haze pollution problem while ensuring the normal operation of the economy, the government has adopted an environmental regulation policy along with the introduction of foreign direct investment. This study uses a fixed effects model and two-stage least squares to examine the correlation of foreign direct investment and environmental regulation to the haze pollution level by using the Chinese provincial panel data from 2008 to 2019. We found a positive interaction between the foreign direct investment and environmental regulation, where a high-quality investment promotes the haze reduction, and the environmental regulation can enhance this effect. The results approve the possibilities that China can bring the merit investment and reduce its air pollution simultaneously, but how to balance the interaction between environmental regulation and the investment needs to draw attention., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Introduction: It has been posited that policies to promote child health and prevent obesity should target neighborhood environments but evidence on the impact of neighborhoods on child weight is conflicting and longitudinal studies (which have benefits for causal inference) are scarce., Methods: We used electronic health records (2007-2016) from an urban, pediatric integrated delivery system and linked children (N = 51,873, ages 6-19 years, 77% African American) to neighborhood-level data to investigate how changes in neighborhood environments relate to changes in body mass index (BMI). Measures of neighborhood environment were resources for healthy foods and physical activity ('resources'), greenness, violent crime rate, perceived safety and social cohesion. Fixed effects models estimated associations between changes in neighborhood environment exposures and changes in BMI z-score and whether effects differed by sex, baseline age, neighborhood socioeconomic status and population density., Results: Approximately 22% of the cohort was obese (BMI z-score ≥ 95th percentile). In adjusted models, increases in neighborhood greenness and perceived safety were associated with decreases in BMI z-score (mean change in BMI z-score for 1-SD increase for both: -0.012; 95% CI= (-0.018, -0.007)). Increases in neighborhood safety had a stronger effect in children ages 6-10 years than in older children. Increases in social cohesion were associated with increases in BMI z-score (mean change: 0.005 95% CI = (0.003, 0.008)) especially in boys. Increases in food and physical activity resources were not associated with changes in BMI., Conclusions: This study suggests that increasing neighborhood greenness and safety are potential approaches to reduce children's BMI., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

A reference interval provides a basis for physicians to determine whether a measurement is typical of a healthy individual. It can be interpreted as a prediction interval for a new individual from the overall population. However, a reference interval based on a single study may not be representative of the broader population. Meta-analysis can provide a general reference interval based on the overall population by combining results from multiple studies. Methods for estimating the reference interval from a random effects meta-analysis have been recently proposed to incorporate the within and between-study variation, but a random effects model may give imprecise estimates of the between-study variation with only few studies. In addition, the normal distribution of underlying study-specific means, and equal within-study variance assumption in these methods may be inappropriate in some settings. In this article, we aim to estimate the reference interval based on the fixed effects model assuming study effects are unrelated, which is useful for a meta-analysis with only a few studies (e.g., ≤5). We propose a mixture distribution method only assuming parametric distributions (e.g., normal) for individuals within each study and integrating them to form the overall population distribution. This method is compared to an empirical method only assuming a parametric overall population distribution. Simulation studies have shown that both methods can estimate a reference interval with coverage close to the targeted value (i.e., 95%). Meta-analyses of women daytime urination frequency and frontal subjective postural vertical measurements are reanalyzed to demonstrate the application of our methods., (© 2021 John Wiley & Sons Ltd.)

The main objective of the presented study was to examine the associations between the use of renewable energy sources in selected sectors (transport, electricity, heating, and cooling) and the prevalence of selected groups of diseases in the European Union, with an emphasis on the application of statistical methods considering the structure of data. The analyses included data on 27 countries of the European Union from 2010 to 2019 published in the Eurostat database and the Global Burden of Disease Study. Panel regression models (pooling model, fixed (within) effects model, random effects model) were primarily used in analytical procedures, in which a panel variable was represented by countries. In most cases, positive and significant associations between the use of renewable energy sources and the prevalence of diseases were confirmed. The results of panel regression models could be generally interpreted as meaning that renewable energy sources are associated with the prevalence of diseases such as cardiovascular diseases, diabetes and kidney diseases, digestive diseases, musculoskeletal disorders, neoplasms, sense organ diseases, and skin and subcutaneous diseases at a significance level (α) of 0.05 and lower. These findings could be explained by the awareness of the health problem and the response in the form of preference for renewable energy sources. Regarding statistical methods used for country data or for data with a specific structure, it is recommended to use the methods that take this structure into account. The absence of these methods could lead to misleading conclusions.

Purpose: To describe and demonstrate methods for analyzing longitudinal correlated eye data with a continuous outcome measure., Methods: We described fixed effects, mixed effects and generalized estimating equations (GEE) models, applied them to data from the Complications of Age-Related Macular Degeneration Prevention Trial (CAPT) and the Age-Related Eye Disease Study (AREDS). In CAPT (N = 1052), we assessed the effect of eye-specific laser treatment on change in visual acuity (VA). In the AREDS study, we evaluated effects of systemic supplement treatment among 1463 participants with AMD category 3., Results: In CAPT, the inter-eye correlations (0.33 to 0.53) and longitudinal correlations (0.31 to 0.88) varied. There was a small treatment effect on VA change (approximately one letter) at 24 months for all three models ( p = .009 to 0.02). Model fit was better with the mixed effects model than the fixed effects model ( p < .001). In AREDS, there was no significant treatment effect in all models ( p > .55). Current smokers had a significantly greater VA decline than non-current smokers in the fixed effects model ( p = .04) and the mixed effects model with random intercept ( p = .0003), but marginally significant in the mixed effects model with random intercept and slope ( p = .08), and GEE models ( p = .054 to 0.07). The model fit was better with the fixed effects model than the mixed effects model ( p < .0001)., Conclusion: Longitudinal models using the eye as the unit of analysis can be implemented using available statistical software to account for both inter-eye and longitudinal correlations. Goodness-of-fit statistics may guide the selection of the most appropriate model.

The hasty economic development in developing countries comes along with poorer air quality, which has severe toxicological effects on the environment and human health. This study is carried out to explore and empirically investigate the relationship between industrial pollution and health using the panel of middle-income countries (MIC) over 1990-2016. This study uses two indicators of health status, namely life expectancy and infant mortality, and two indicators of industrial pollution, namely carbon dioxide emissions and nitrous oxide emissions. This analysis is carried out using fixed effects (FE) technique on the grounds of the Hausman test. The empirical results suggest that industrial pollution tends to decrease life expectancy and increases infant mortality. In addition, this study suggests that the adverse impact of industrial pollution is greater in lower-middle-income countries (LMIC) in comparison with upper-middle-income countries (UMIC). This study recommends the programs to improve human health status and needs to focus on policies that mitigate industrial pollution burden.

Factorial designs are in general more efficient for experiments that involve the study of the effects of two or more factors. In this paper we consider a p U factorial model with U factors, each one having a p prime number of levels. We consider a balanced ( r replicates per treatment) prime factorial with fixed effects. Our goal is to extend these models to the case where it is not possible to known in advance the number of treatments replicates, r . In these situations is more appropriate to consider r as a realization of a random variable R , which will be assumed to be geometrically distributed. The proposed approach is illustrated through an application considering simulated data., Competing Interests: No potential conflict of interest was reported by the authors., (© 2019 Informa UK Limited, trading as Taylor & Francis Group.)

The study attempts to investigate the features and determinants of the performance of Taiwanese Traditional Chinese Medicine (TCM) Clinics with data for 4905 TCM clinics over the 1998 to 2012 period. The empirical results from the fixed effects model and the Hausman-Taylor Model with cluster-robust standard errors reveal several interesting findings. First, consumer characteristics such as the frequency of disabling injuries has positive impacts on the volume of medical services provided by TCM clinics. These results imply that people are likely to select TCM as the option for medical treatment when they face the occurrence of physical injury in Taiwan. In addition, the scale measurements for TCM clinics including the numbers of physicians, medical personnel and divisions have significantly positive effects on the performance of TCM clinics, while their survival length also has the same effect. Finally, the global budget system under the NHI plays a key role in suppressing the revenue of TCM clinics through the peer review mechanism., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Background: Naloxone is a prescription medication that can quickly and effectively reverse opioid overdose. Medicaid is a major payer of substance use disorder services, and Medicaid beneficiaries experience especially high rates of opioid overdose. As opioid overdose rates have risen sharply, every state has modified its laws to make naloxone easier to access. The aim of this paper is to determine whether implementation of different provisions of naloxone access laws led to increased naloxone dispensing financed by Medicaid., Methods: We reviewed naloxone legislation passed by every state between 2007 and 2016. We used the Medicaid State Drug Utilization dataset to examine the effect of different types of state naloxone access law provisions, separately and as a whole, on the number of outpatient naloxone prescriptions reimbursed by Medicaid from 2007 to 2016. We included state-level covariates in our models that may be correlated with naloxone utilization in Medicaid and passage of naloxone access laws., Results: We found that the presence of any naloxone law was significantly associated with increases in outpatient naloxone reimbursed through Medicaid. Laws containing standing order provisions were most consistently associated with increases in naloxone dispensing across models. Standing order provisions led on average to an increase of approximately 33 naloxone prescriptions per state-quarter, which is equivalent to 74% of the average number of naloxone prescriptions per state-quarter., Conclusions: Naloxone access laws, particularly those with standing order provisions, appear to be an effective policy approach to increasing naloxone access among Medicaid beneficiaries., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Porcine reproductive and respiratory syndrome (PRRS) is an endemic disease causing important economic losses to the US swine industry. The complex epidemiology of the disease, along with the diverse clinical outputs observed in different types of infected farms, have hampered efforts to quantify PRRS' impact on production over time. We measured the impact of PRRS on the production of weaned pigs using a log-linear fixed effects model to evaluate longitudinal data collected from 16 sow farms belonging to a specific firm. We measured seven additional indicators of farm performance to gain insight into disease dynamics. We used pre-outbreak longitudinal data to establish a baseline that was then used to estimate the decrease in production. A significant rise of abortions in the week before the outbreak was reported was the strongest signal of PRRSV activity. In addition, production declined slightly one week before the outbreak and then fell markedly until weeks 5 and 6 post-outbreak. Recovery was not monotonic, cycling gently around a rising trend. At the end of the study period (35 weeks post-outbreak), neither the production of weaned pigs nor any of the performance indicators had fully recovered to baseline levels. This result suggests PRSS outbreaks may last longer than has been found in most other studies. We assessed PRRS' effect on farm efficiency as measured by changes in sow production of weaned pigs per year. We translated production losses into revenue losses assuming an average market price of $45.2/weaned pig. We estimate that the average PRSS outbreak reduced production by approximately 7.4%, relative to annual output in the absence of an outbreak. PRRS reduced production by 1.92 weaned pigs per sow when adjusted to an annual basis. This decrease is substantially larger than the 1.44 decrease of weaned pigs per sow/year reported elsewhere.

When multiple imperfect dichotomous diagnostic tests are applied to an individual, it is possible that some or all of their results remain dependent even after conditioning on the true disease status. The estimates could be biased if this conditional dependence is ignored when using the test results to infer about the prevalence of a disease or the accuracies of the diagnostic tests. However, statistical methods correcting for this bias by modelling higher-order conditional dependence terms between multiple diagnostic tests are not well addressed in the literature. This paper extends a Bayesian fixed effects model for 2 diagnostic tests with pairwise correlation to cases with 3 or more diagnostic tests with higher order correlations. Simulation results show that the proposed fixed effects model works well both in the case when the tests are highly correlated and in the case when the tests are truly conditionally independent, provided adequate external information is available in the form of fixed constraints or prior distributions. A data set on the diagnosis of childhood pulmonary tuberculosis is used to illustrate the proposed model., (Copyright © 2017 John Wiley & Sons, Ltd.)

Even though consistency is an important issue in multi-regional clinical trials and inconsistency is often anticipated, solutions for handling inconsistency are rare. If a region's treatment effects are inconsistent with that of the other regions, pooling all the regions to estimate the overall treatment effect may not be reasonable. Unlike the multiple center clinical trials conducted in the USA and Europe, in multi-regional clinical trials, different regional regulatory agencies may have their own ways to interpret data and approve new drugs. It is therefore practical to consider the case in which the data from the region with the minimal observed treatment effect is excluded from the analysis in order to attain the regulatory approval of the study drug. Under such cases, what is the appropriate statistical approach for the remaining regions? We provide a solution first formulated within the fixed effects framework and then extend it to discrete random effects models. Copyright © 2016 John Wiley & Sons, Ltd., (Copyright © 2016 John Wiley & Sons, Ltd.)

The meta-analysis has become a widely used tool for many applications in bioinformatics, including genome-wide association studies. A commonly used approach for meta-analysis is the fixed effects model approach, for which there are two popular methods: the inverse variance-weighted average method and weighted sum of z-scores method. Although previous studies have shown that the two methods perform similarly, their characteristics and their relationship have not been thoroughly investigated. In this paper, we investigate the optimal characteristics of the two methods and show the connection between the two methods. We demonstrate that the each method is optimized for a unique goal, which gives us insight into the optimal weights for the weighted sum of z-scores method. We examine the connection between the two methods both analytically and empirically and show that their resulting statistics become equivalent under certain assumptions. Finally, we apply both methods to the Wellcome Trust Case Control Consortium data and demonstrate that the two methods can give distinct results in certain study designs.

This paper examines the impact of local (county-level) house prices on individual self-reported mental health using individual level data from the United States Behavioral Risk Factor Surveillance System between 2005 and 2011. Exploiting a fixed-effects model that relies on within-county variations, relative to the corresponding changes in other counties, I find that while individuals are likely to experience worse self-reported mental health when local house prices decline, this association is most pronounced for individuals who are least likely to be homeowners. This finding is not consistent with a prediction from a pure wealth mechanism but rather with the hypothesis that house prices act as an economic barometer. I also demonstrate that the association between self-reported mental health and local house prices is not driven by unemployment or foreclosure. The primary result-that lower local house prices have adverse impact on self-reported mental health of homeowners and renters-is consistent with studies using data from the United Kingdom.

A number of scoring systems for proficiency testing and interlaboratory comparison are in use by the metrology community. The choice of scoring system for a given study is often based on the study coordinator's experience and anecdotal knowledge, perhaps attributable to a historic lack of detailed and formal explanation about the foundation of these systems. This has influenced the development of new scoring systems, some of them departing from the well-established hypothesis testing theory. Often, different scoring systems give different results not because one may be better than the others but because, as they are documented, the user cannot control the confidence level of the test. We present a formal evaluation of seven of these systems under the fixed effects model assuming known variances. Under these sound assumptions, the systems analyzed all have the same statistical properties. Furthermore, these systems are all members of a family of systems based on strictly increasing functions in which the statistical decision problem is invariant. Under the fixed effects model with known variances, no unbiased scoring system can provide greater statistical power than the members of this family of systems. We apply these results to the lead content of water example provided in International Standard ISO 13528:2015 "Statistical methods for use in proficiency testing by interlaboratory comparisons.", Competing Interests: Conflict of interest The authors declare that they have no conflict of interest.

Background: It has been known that smoking is negatively related to weight-related outcomes. However, it has been difficult to determine whether the relationship is causal, and if so, how strong it is. We attempted to estimate the approximately causal effects of smoking on weight, body mass index (BMI), and obesity., Methods: The Indonesian Family Life Survey provided a sample of over 9000 men aged 15-55 years-each of them was observed in 1993, 1997, 2000 and 2007. The preferred method was a fixed effects model; that is, we related changes in smoking status or smoking intensity to changes in weight-related outcomes, while controlling for time-varying covariates. We also compared these results to those estimated by ordinary least squares and assessed the importance of controlling for time invariant individual heterogeneity., Results: Although the effects of smoking were precisely estimated in a statistical sense, their size was minuscule: a quitter would gain weight by at most 1 kg, or a smoker would lose weight by the same amount. The results were similar for BMI and obesity. When we did not control for time invariant individual heterogeneity, the size of the relationship was overestimated at least three times., Conclusions: Smoking exerted little influence on weight, and it was important to control for bias stemming from time invariant individual heterogeneity.

We show that the positive relation between income deprivation and mental health is affected by an individual's non-cognitive skills. Income deprivation is operationalized as the Yitzhaki index, i.e., as a function of the sum of income differences between an individual and others in her reference group who are more affluent. Non-cognitive skills are extracted from a Locus of Control questionnaire and the Big Five Inventory, a self-report measurement of an individual in regard to five aspects of personality: conscientiousness, neuroticism, extraversion, agreeableness and open-mindedness. The results, based on the 2002-2010 waves of the German Socio-Economic Panel dataset (SOEP), show that deprivation is negative and significantly related with mental health. However, neurotic individuals are more deprivation-sensitive than are others. Compared to the mean effect, a one standard deviation rise in neuroticism is associated with a deprivation effect that is 36.6% and 51.9% larger among men and women, respectively. Although to a lesser extent, extraverted men and conscientious women are also found to be more deprivation-sensitive than are others, the corresponding figures being 31.1% and 45.9%, respectively. These findings suggest that personality differences should be taken into account in the design of policies, practices and initiatives aimed at alleviating the well-being costs of income deprivation., (Copyright © 2014 Elsevier B.V. All rights reserved.)

The Vaccine Safety Datalink project captures electronic health record data including vaccinations and medically attended adverse events on 8.8 million enrollees annually from participating managed care organizations in the United States. While the automated vaccination data are generally of high quality, a presumptive adverse event based on diagnosis codes in automated health care data may not be true (misclassification). Consequently, analyses using automated health care data can generate false positive results, where an association between the vaccine and outcome is incorrectly identified, as well as false negative findings, where a true association or signal is missed. We developed novel conditional Poisson regression models and fixed effects models that accommodate misclassification of adverse event outcome for self-controlled case series design. We conducted simulation studies to evaluate their performance in signal detection in vaccine safety hypotheses generating (screening) studies. We also reanalyzed four previously identified signals in a recent vaccine safety study using the newly proposed models. Our simulation studies demonstrated that (i) outcome misclassification resulted in both false positive and false negative signals in screening studies; (ii) the newly proposed models reduced both the rates of false positive and false negative signals. In reanalyses of four previously identified signals using the novel statistical models, the incidence rate ratio estimates and statistical significances were similar to those using conventional models and including only medical record review confirmed cases., (© 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Although recent evidence shows significant and long-lasting detrimental effects of armed conflict on child health, there is lack of studies rigorously assessing the effectiveness of different social and economic development interventions aiming to mitigate the impact of armed conflict on child health. In order to fill this knowledge gap, this study assesses the impact of health projects and water, sanitation, and waste management interventions financed by the Angola Social Action Fund (ASAF) from 1994 to 2001 on child health. I use data from Inquérito aos Agregados Familiares sobre Despesas e Receitas 2000/2001(IDR 2001), a household survey on expenditures and incomes conducted between February 2000 and February 2001 in Angola. IDR 2001 uses a stratified sampling design in which 12 households were surveyed in a random fashion in each aldeia (village) in rural areas and bairro (neighborhood) in urban areas. Using propensity score matching, a fixed effects model, and propensity-based weighted regression, I find that ASAF leads to a statistically significant increase of the height-for-age Z-scores (HAZ) by 0.335 standard deviations of children less than 5 years. This finding is robust to different implementations of the propensity score model specification and when conducting the sensitivity analysis of hidden bias. The main result that emerges from an analysis of heterogeneous effects shows that ASAF has no impact on children living in war displaced households. Despite many challenges faced by conflict affected countries, social funds which are one the key instruments of the World Bank used to promote development at the local level can be used to mitigate the impact of armed conflict on child health. For children living in war displaced households, specific interventions should be designed to mitigate the impact of armed conflict., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

Conditional Poisson models have been used to analyze vaccine safety data from self-controlled case series (SCCS) design. In this paper, we derived the likelihood function of fixed effects models in analyzing SCCS data and showed that the likelihoods from fixed effects models and conditional Poisson models were proportional. Thus, the maximum likelihood estimates (MLEs) of time-varying variables including vaccination effect from fixed effects model and conditional Poisson model were equal. We performed a simulation study to compare empirical type I errors, means and standard errors of vaccination effect coefficient, and empirical powers among conditional Poisson models, fixed effects models, and generalized estimating equations (GEE), which has been commonly used for analyzing longitudinal data. Simulation study showed that both fixed effect models and conditional Poisson models generated the same estimates and standard errors for time-varying variables while GEE approach produced different results for some data sets. We also analyzed SCCS data from a vaccine safety study examining the association between measles mumps-rubella (MMR) vaccination and idiopathic thrombocytopenic purpura (ITP). In analyzing MMR-ITP data, likelihood-based statistical tests were employed to test the impact of time-invariant variable on vaccination effect. In addition a complex semi-parametric model was fitted by simply treating unique event days as indicator variables in the fixed effects model. We conclude that theoretically fixed effects models provide identical MLEs as conditional Poisson models. Because fixed effect models are likelihood based, they have potentials to address methodological issues in vaccine safety studies such as how to identify optimal risk window and how to analyze SCCS data with misclassification of adverse events.