Urban-rural disparity of preventive healthcare utilisation among children under the universal health insurance coverage in Taiwan: a national birth cohort analysis.

OBJECTIVE: In the context of universal health insurance coverage, this study aimed to determine whether urban-rural inequality still exists in preventive health care (PHC) amongst children in Taiwan. STUDY DESIGN: Prospective cohort study. METHODS: A total of 184,117 mothers and their children born in 2009 were identified as the study cohort. The number of children born in urban, satellite and rural areas was 40,176, 57,565 and 86,805, respectively. All children were followed for 7 years, before which a total of seven times PHC were provided by Taiwan's National Health Insurance (NHI) programme. Ordinal logistic regression models were used to associate urbanisation level with the frequency of PHC utilisation. Stratified analyses were further performed in accordance with the children's birth weight and the mothers' birthplace. RESULTS: Children from satellite areas had higher utilisation for the first four scheduled PHC visits. Children living in urban areas received more PHC for the fifth and sixth scheduled visits. Compared with those from rural areas, children in satellite areas exhibited a small but significant increase in odds in PHC utilisation, with a covariate-adjusted odds ratio (aOR) of 1.04 and 95% confidence interval (CI) of 1.02-1.06. By contrast, no significant difference was observed between rural and urban areas (aOR = 1.01). Further stratified analyses suggest more evident urban-rural difference in PHC utilisation amongst children with low birth weight and foreign-born mothers. CONCLUSIONS: Given a universal health insurance coverage and embedded mechanisms in increasing the availability of healthcare resources in Taiwan, a slight urban-rural difference is observed in PHC utilisation amongst children. Hence, sociodemographic inequality in utilisation of PHC still exists. This issue should be addressed through policy intervention.

NMR-based metabolomics for the environmental assessment of Kaohsiung Harbor sediments exemplified by a marine amphipod (Hyalella azteca).

Inflow of wastewater from upstream causes a large flux of pollutants to enter Kaohsiung Harbor in Taiwan daily. To reveal the ecological risk posed by Kaohsiung Harbor sediments, an ecological metabolomic approach was employed to investigate environmental factors pertinent to the physiological regulation of the marine amphipod Hyalella azteca. The amphipods were exposed to sediments collected from different stream inlets of the Love River (LR), Canon River (CR), Jen-Gen River (JR), and Salt River (SR). Harbor entrance 1 (E1) was selected as a reference site. After 10-day exposure, metabolomic analysis of the Hyalella azteca revealed differences between two groups: {E1, LR, CR} and {JR, SR}. The metabolic pathways identified in the two groups of amphipods were significantly different. The results demonstrated that NMR-based metabolomics can be effectively used to characterize metabolic response related to sediment from polluted areas.

[Carefully reviewing the history of diagnostic scales and paying more attention to the diagnostic value of Roussel - Uclaf causality assessment method scale for drug - induced liver injury].

Currently, the diagnostic criteria for drug-induced liver injury (DILI) used in the clinical studies and related literature in China are very confusing, making it difficult to compare and extend the use of the results, conclusions, and experience of these studies. Therefore, it is necessary to carefully review the developmental history of diagnostic scales and unify the diagnostic criteria and related knowledge of DILI. Since its publication in 1993, Roussel Uclaf Causality Assessment Method (RUCAM) scale has been widely used to assess the causality between drugs and liver injury, both in DILI studies and decisions on the regulation of drugs which may cause liver injury, in order to provide a useful analytical framework for clinical physicians in the diagnosis of DILI. At present, RUCAM scale should still be used to assess causality and assist diagnosis, unless markers with diagnostic significance are found in future.

Simultaneous assessment of the intraluminal pressure and transit time of the colon using a telemetry technique.

Colonic motility disorders are common conditions. However, our understanding of normal and pathological motor functions of the colon remains limited, mainly due to the technical difficulties in accessing this organ for study. To investigate colonic motility under normal physiological conditions, we have developed a novel monitoring system based on a telemetry technique. The system is capable of prolonged and noninvasive measurement of intraluminal pressure changes and transit time of intra-colonic contents. To test the in vivo performance of the monitoring system, 15 healthy volunteers and 15 patients with functional constipation (FC) participated in this study. A single-use telemetry capsule embedded with sensors was ingested by the subjects. The capsule is capable of transmitting colonic pressure and temperature wirelessly. The time of the telemetry capsule entering the segmental colon was detected by ultrasonic detection of the batteries in capsule. Pressure recordings confirmed in general a circadian behavior of colonic motility, as well as its response to waking and meals. In the FC patients, the contractile response to morning awakening and meal ingestion was significantly lower compared to the controls. The transit time measured using this method agreed with the time calculated from radiopaque markers (r = 0.89, p < 0.05). The clinical study proved both the reliability and the noninvasiveness of the system. This capsule-style manometric system may represent a useful tool for the study of physiology and pathology of colonic motor disorders.

Two-dimensional phase unwrapping with use of statistical models for cost functions in nonlinear optimization.

Interferometric radar techniques often necessitate two-dimensional (2-D) phase unwrapping, defined here as the estimation of unambiguous phase data from a 2-D array known only modulo 2pi rad. We develop a maximum a posteriori probability (MAP) estimation approach for this problem, and we derive an algorithm that approximately maximizes the conditional probability of its phase-unwrapped solution given observable quantities such as wrapped phase, image intensity, and interferogram coherence. Examining topographic and differential interferometry separately, we derive simple, working models for the joint statistics of the estimated and the observed signals. We use generalized, nonlinear cost functions to reflect these probability relationships, and we employ nonlinear network-flow techniques to approximate MAP solutions. We apply our algorithm both to a topographic interferogram exhibiting rough terrain and layover and to a differential interferogram measuring the deformation from a large earthquake. The MAP solutions are complete and are more accurate than those of other tested algorithms.

Assessment of endocrine disruptors: approaches, issues, and uncertainties.

This paper focuses on the quantitative risk assessment of environmental endocrine-disrupting chemicals (EDCs) to human health. An EDC can be defined as an exogenous agent that interferes with the normal endocrine signaling and communication mechanisms. The normal feedback control system of natural hormones is responsible for regulatory mechanisms that maintain homeostasis. Hormones deliver their message to target cells by interacting with receptors, initiating signal transduction, gene transcription, and mRNA translation, and ultimately leading to cellular response. Because effects of EDCs include diverse disease endpoints such as cancer, reproductive toxicity, developmental toxicity, immune system effects, acute toxicity, and neurotoxicity, risk assessment of EDCs is necessarily endpoint-specific. From the quantitative viewpoint, it is best to model the normal endocrinology and then extend the model to include impacts attributable to a particular exogenous agent. A practical approach to such a complex process is to break the spectrum of biochemical and biological events into modular components: e.g., pharmacokinetics, biochemical/molecular (including cellular signaling), and cellular response/dynamics. A flexible mathematical procedure that is capable of modeling each of these components is suggested. However, a real biologically based model is not yet feasible because of a lack of necessary biological information. A challenge to risk assessors is how to develop a hybrid risk assessment approach that can use the limited biological information available for a specific agent and avoid relying on a default approach that incorporates no biological information. The USEPA's default approach is to derive benchmark dose (BMD) or benchmark concentration (BMC) on the basis of a predetermined empirical dose-response model. BMD (or BMC) is the highest dose (or concentration and duration) of exposure that is considered unlikely to cause adverse effects in a human population, including sensitive subgroups. Data from two studies are used to stimulate discussion of issues and the needs for new quantitative approaches and data for assessing endocrine disruptors. Statistical concepts about threshold effect and the U-shaped dose-response relationship are also discussed. This report is a condensed version of the one to be published in the monograph of the NATO Advanced Research Workshop, Endocrine Disrupters and Carcinogenesis Risk Assessment" held May 8-12, 2001, in Bialystok, Poland.

Empirical Bayes approach to estimating the number of HIV-infected individuals in hidden and elusive populations.

In this paper we estimate the numbers of intravenous drug users (IVDUs) and commercial sex workers (CSWs) in Thailand infected with human immunodeficiency virus (HIV) who have not developed acquired immunodeficiency syndrome (AIDS) directly from the semi-annual HIV serosurveillance data of Thailand from June 1993 to June 1995. We propose a 'generalized removal model for open populations' for estimating HIV-infected population size within a hidden, elusive, and perhaps high-risk population group, for all sampling time when capture probabilities vary with time. We apply empirical Bayes methodology to the generalized removal model for open populations by using the Gibbs sampler, a Markov chain Monte Carlo method. No assumption on the size of the hidden population in question is needed to implement this procedure. The statistical method proposed here requires very little computing and only a minimum of two sets of serosurvey data to obtain an estimate, thereby providing a simple and viable option in epidemiological studies when either powerful computing facilities or abundant sampling data are lacking.

Incorporation of biological information in cancer risk assessment: example--vinyl chloride.

Vinyl chloride (VC) is used as an example to demonstrate how biological information can be incorporated into quantitative risk assessment. The information included is the pharmacokinetics of VC in animals and humans and the data-generated hypothesis that VC primarily affects the initiation stage of the multistage carcinogenesis. The emphasis in this paper is on the improvement of risk assessment methodology rather than the risk assessment of VC per se. Sufficient data are available to construct physiologically-based pharmacokinetic models for both animals and humans. These models are used to calculate the metabolized dose corresponding to exposure scenarios in animals and in humans. On the basis of the data on liver angiosarcomas and carcinomas in rats, the cancer risk per unit of metabolized dose is comparable, irrespective of routes (oral or inhalation) of exposure. The tumor response from an intermittent/partial lifetime exposure is shown to be consistent with that from a lifetime exposure when VC is assumed to affect the first (initiation) stage of the multistage carcinogenic process. Furthermore, the risk estimates calculated on the basis of animal data are shown to be consistent with the human experience.