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Cultured epithelial autografts (CEA) with highly expanded mesh skin grafts were used for extensive adult burns covering more than 30% of the total body surface area. A prospective study on eight patients assessed subjective and objective findings up to a 12-month follow-up. The results of wound healing for over 1:6 mesh plus CEA, gap 1:6 mesh plus CEA, and 1:3 mesh were compared at 3, 6, and 12 months using extensibility, viscoelasticity, color, and transepidermal water loss by a generalized estimating equation (GEE) or generalized linear mixed model (GLMM). No significant differences were observed among the paired treatments at any time point. At 6 and 12 months, over 1:6 mesh plus CEA achieved significantly better expert evaluation scores by the Vancouver and Manchester Scar Scales (p < 0.01). Extended skin grafting plus CEA minimizes donor resources and the quality of scars is equal or similar to that with conventional low extended mesh slit-thickness skin grafting such as 1:3 mesh. A longitudinal analysis of scars may further clarify the molecular changes of scar formation and pathogenesis.

Providing a flexible framework for data analysis and model building, this text focuses on the statistical methods and models that can help predict the expected value of an outcome, dependent, or response variable. It offers a sound introduction to general and generalized linear models using the popular and powerful likelihood techniques. The authors enable a clear comparison between general and generalized linear models and cover Gaussian-based hierarchical models and hierarchical generalized linear models. They illustrate the methods with many real-world examples and use R throughout to solve the problems. Ancillaries are available on the book's website.

Background Although multimorbidity is a risk factor for disability, the relationship between the accumulative patterns of multimorbidity and disability remains poorly understood. The objective of this study was to identify the latent groups of multimorbidity trajectories among mid to older age adults and to examine their associations with incident disability. Methods We included 5,548 participants aged ≥ 45 years who participated in the China Health and Retirement Longitudinal Study from 2011 to 2018 and had no multimorbidity (≥ 2 chronic conditions) at baseline. The group-based multi-trajectory modeling was used to identify distinct trajectory groups of multimorbidity based on the latent dimensions underlying 13 chronic conditions. The association between multimorbidity trajectories and incident disability was analyzed using the generalized estimating equation model adjusting for potential confounders. Results Of the 5,548 participants included in the current analysis, 2,407 (43.39%) developed multimorbidity during the follow-up. Among participants with new-onset multimorbidity, four trajectory groups were identified according to the combination of newly diagnosed diseases: “Cardiometabolic” ( N  = 821, 34.11%), “Digestive-arthritic” ( N  = 753, 31.28%), “Cardiometabolic/Brain” ( N  = 618, 25.68%), and “Respiratory” ( N  = 215, 8.93%). Compared to participants who did not develop multimorbidity, the risk of incident disability was most significantly increased in the “Cardiometabolic/Brain” trajectory group (OR = 2.05, 95% CI: 1.55–2.70), followed by the “Cardiometabolic” (OR = 1.96, 95% CI: 1.52 –2.53) and “Digestive-arthritic” (OR = 1.70, 95% CI: 1.31–2.20) trajectory groups. Conclusions The growing burden of multimorbidity, especially the comorbid of cardiometabolic and brain diseases, may be associated with a significantly increased risk of disability for mid to older age adults. These findings improve our understanding of multimorbidity patterns that affect the independence of living and inform the development of strategies for the primary prevention of disability.

The relationship between tap water and health has been a topic of public concern and calls for better management in Canada since well-publicized contamination events in two provinces (Ontario and Saskatchewan) in 2000–2001. This study reports the perspectives on health risks from tap water and corresponding use of, and spending on, bottled water in a number of different communities in Canada. In 2009–2010, four First Nations communities (three from Ontario and one from Saskatchewan) and a geographically diverse sample of non-First Nations Canadians were surveyed about their beliefs concerning health risks from tap water and their spending practices for bottled water as a substitute. Responses to five identical questions were examined, revealing that survey respondents from Ontario First Nations communities were more likely than non-First Nations Canadians to believe bottled water is safer than tap water (OR 1.6); more likely to report someone became ill from tap water (OR 3.6); more likely to express water and health concerns related to tap water consumption (OR 2.4); and more likely to spend more on bottled water (OR 4.9). On the other hand, participants from one Saskatchewan First Nations community were less likely than non-First Nations Canadians to believe that someone had become ill from drinking tap water (OR 3.8), less likely to believe bottled water is safer than tap (OR 2.0), and less likely to have health concerns with tap water (OR 1.5). These differences, however, did not translate into differences in the likelihood of high bottled water expenditures or being a 100% bottled water consumer. The paper discusses how the differences observed may be related to water supply and regulation, trust, perceived control, cultural background, location, and past experience.

Background Event-related potentials (ERP) data are widely used in brain studies that measure brain responses to specific stimuli using electroencephalogram (EEG) with multiple electrodes. Previous ERP data analyses haven’t accounted for the structured correlation among observations in ERP data from multiple electrodes, and therefore ignored the electrode-specific information and variation among the electrodes on the scalp. Our objective was to evaluate the impact of early adversity on brain connectivity by identifying risk factors and early-stage biomarkers associated with the ERP responses while properly accounting for structured correlation. Methods In this study, we extend a penalized generalized estimating equation (PGEE) method to accommodate structured correlation of ERPs that accounts for electrode-specific data and to enable group selection, such that grouped covariates can be evaluated together for their association with brain development in a birth cohort of urban-dwelling Bangladeshi children. The primary ERP responses of interest in our study are N290 amplitude and the difference in N290 amplitude. Results The selected early-stage biomarkers associated with the N290 responses are representatives of enteric inflammation (days of diarrhea, MIP1b, retinol binding protein (RBP), Zinc, myeloperoxidase (MPO), calprotectin, and neopterin), systemic inflammation (IL-5, IL-10, ferritin, C Reactive Protein (CRP)), socioeconomic status (household expenditure), maternal health (mother height) and sanitation (water treatment). Conclusions Our proposed group penalized GEE estimator with structured correlation matrix can properly model the complex ERP data and simultaneously identify informative biomarkers associated with such brain connectivity. The selected early-stage biomarkers offer a potential explanation for the adversity of neurocognitive development in low-income countries and facilitate early identification of infants at risk, as well as potential pathways for intervention. Trial registration The related clinical study was retrospectively registered with https://doi.org/ClinicalTrials.gov , identifier NCT01375647, on June 3, 2011.

The relationship between exposure to polycyclic aromatic hydrocarbons and nasal symptoms currently remains unclear. Therefore, we herein examine this relationship in 51 adults living in Ishikawa prefecture, Japan, and conducted a 2 month follow-up survey on these participants. All participants were asked to record daily nasal symptoms in an allergy diary during the study period between 1 April to 31 May 2020. We collected air pollutant samples during the study period and determined the concentrations of PAHs and total suspended particulates by high-performance liquid chromatography. Sulfur dioxide and nitrogen dioxide concentrations were obtained through the Atmospheric Environmental Regional Observation System. We used generalized estimating equations to analyze the association between pollutant and nasal symptoms. After adjustment for confounding factors, the B values of fluoranthene, pyrene, and Benzo[k]fluoranthene were 2.389 (p = 0.026), 3.744 (p = 0.022) and 9.604 (p = 0.041), respectively, with a one-day lag. In contrast, the B value of indeno[1,2,3-cd]pyrene was −6.664 (p = 0.013) with no lag. Collectively, these results suggest ambient PAHs such as Flt, Pyr, and BkF were associated with nasal symptoms in adults. Further studies are needed to elucidate the mechanisms contributing to the relationships between specific PAHs and nasal symptoms.

Background Cardiovascular diseases (CVDs) are one of the global leading causes of concern due to the rising prevalence and consequence of mortality and disability with a heavy economic burden. The objective of the current study was to analyze the trend in CVD incidence, mortality, and mortality-to-incidence ratio (MIR) across the world over 28 years. Methods The age-standardized CVD mortality and incidence rates were retrieved from the Global Burden of Disease (GBD) Study 2017 for both genders and different world super regions with available data every year during the period 1990–2017. Additionally, the Human Development Index was sourced from the United Nations Development Programme (UNDP) database for all countries at the same time interval. The marginal modeling approach was implemented to evaluate the mean trend of CVD incidence, mortality, and MIR for 195 countries and separately for developing and developed countries and also clarify the relationship between the indices and Human Development Index (HDI) from 1990 to 2017. Results The obtained estimates identified that the global mean trend of CVD incidence had an ascending trend until 1996 followed by a descending trend after this year. Nearly all of the countries experienced a significant declining mortality trend from 1990 to 2017. Likewise, the global mean MIR rate had a significant trivial decrement trend with a gentle slope of 0.004 over the time interval. As such, the reduction in incidence and mortality rates for developed countries was significantly faster than developing counterparts in the period 1990–2017 ( p  < 0.05). Nevertheless, the developing nations had a more rather shallow decrease in MIR compared to developed ones. Conclusions Generally, the findings of this study revealed that there was an overall downward trend in CVD incidence and mortality rates, while the survival rate of CVD patients was rather stable. These results send a satisfactory message that global effort for controlling the CVD burden was quite successful. Nonetheless, there is an urgent need for more efforts to improve the survival rate of patients and lower the burden of this disease in some areas with an increasing trend of either incidence or mortality.

We propose a framework for general Bayesian inference. We argue that a valid update of a prior belief distribution to a posterior can be made for parameters which are connected to observations through a loss function rather than the traditional likelihood function, which is recovered as a special case. Modern application areas make it increasingly challenging for Bayesians to attempt to model the true data-generating mechanism. For instance, when the object of interest is low dimensional, such as a mean or median, it is cumbersome to have to achieve this via a complete model for the whole data distribution. More importantly, there are settings where the parameter of interest does not directly index a family of density functions and thus the Bayesian approach to learning about such parameters is currently regarded as problematic. Our framework uses loss functions to connect information in the data to functionals of interest. The updating of beliefs then follows from a decision theoretic approach involving cumulative loss functions. Importantly, the procedure coincides with Bayesian updating when a true likelihood is known yet provides coherent subjective inference in much more general settings. Connections to other inference frameworks are highlighted.

This paper concerns statistical inference for longitudinal data with ultrahigh dimensional covariates. We first study the problem of constructing confidence intervals and hypothesis tests for a low-dimensional parameter of interest. The major challenge is how to construct a powerful test statistic in the presence of high-dimensional nuisance parameters and sophisticated within-subject correlation of longitudinal data. To deal with the challenge, we propose a new quadratic decorrelated inference function approach which simultaneously removes the impact of nuisance parameters and incorporates the correlation to enhance the efficiency of the estimation procedure. When the parameter of interest is of fixed dimension, we prove that the proposed estimator is asymptotically normal and attains the semiparametric information bound, based on which we can construct an optimal Wald test statistic. We further extend this result and establish the limiting distribution of the estimator under the setting with the dimension of the parameter of interest growing with the sample size at a polynomial rate. Finally, we study how to control the false discovery rate (FDR) when a vector of high-dimensional regression parameters is of interest. We prove that applying the Storey (J. R. Stat. Soc. Ser. B. Stat. Methodol. 64 (2002) 479–498) procedure to the proposed test statistics for each regression parameter controls FDR asymptotically in longitudinal data. We conduct simulation studies to assess the finite sample performance of the proposed procedures. Our simulation results imply that the newly proposed procedure can control both Type I error for testing a low dimensional parameter of interest and the FDR in the multiple testing problem. We also apply the proposed procedure to a real data example.

This study examined the prevalence of suboptimal health among Chinese adults based on a large-scale national survey and clarified the relationship between suboptimal health and lifestyle factors. We used multi-level generalized estimating equation models to examine the relationships between suboptimal health and lifestyle factors. Of the 48,978 respondents, 34,021 reported one or more suboptimal health symptoms, giving a suboptimal health status prevalence of 69.46%. After controlling for the cluster effect of living areas and confounding effect of demographic characteristics, factors associated with suboptimal health were: current smoking (odds ratio (OR) = 1.083, 95% confidence interval (CI): 1.055–1.111), drinking alcohol (OR = 1.075, 95% CI: 1.025–1.127), family history of disease (OR = 1.203, 95% CI: 1.055–1.111), sleeping <6 h per day (OR = 1.235, 95% CI: 1.152–1.256), poor sleep quality (OR = 1.594, 95% CI: 1.515–1.676), stress (OR = 1.588, 95% CI: 1.496–1.686), negative life events (OR = 1.114, 95% CI: 1.045–1.187), unhealthy diet choices (OR = 1.093, 95% CI: 1.033–1.156), and not regularly having meals at fixed hours (OR = 1.231, 95% CI: 1.105–1.372). Respondents who exercised regularly had lower odds of having suboptimal health status (OR = 0.913, 95% CI: 0.849–0.983). Suboptimal health has become a serious public health challenge in China. The health status of the population could be effectively improved by improving lifestyle behaviors.