SummaryBackground-Chronic obstructive pulmonary disease (COPD), lung cancer, and tuberculosis are three leading causes of death in China, where prevalences of smoking and solid-fuel use are also high. We aimed to predict the effects of risk-factor trends on COPD, lung cancer, and tuberculosis.

This pilot study is the first to compare QFT-G, ELISPOT, and TST in ESRD patients on hemodialysis and demonstrates a high prevalence of LTBI in this population. In our study, the QFT-G was the more accurate method for identifying those truly infected with Mycobacterium tuberculosis, even in BCG-vaccinated individuals.

SummaryBackgroundDiabetes has been defined on the basis of different biomarkers, including fasting plasma glucose (FPG), 2-h plasma glucose in an oral glucose tolerance test (2hOGTT), and HbA1c. We assessed the effect of different diagnostic definitions on both the population prevalence of diabetes and the classification of previously undiagnosed individuals as having diabetes versus not having diabetes in a pooled analysis of data from population-based health examination surveys in different regions.MethodsWe used data from 96 population-based health examination surveys that had measured at least two of the biomarkers used for defining diabetes. Diabetes was defined using HbA1c (HbA1c ≥6·5% or history of diabetes diagnosis or using insulin or oral hypoglycaemic drugs) compared with either FPG only or FPG-or-2hOGTT definitions (FPG ≥7·0 mmol/L or 2hOGTT ≥11·1 mmol/L or history of diabetes or using insulin or oral hypoglycaemic drugs). We calculated diabetes prevalence, taking into account complex survey design and survey sample weights. We compared the prevalences of diabetes using different definitions graphically and by regression analyses. We calculated sensitivity and specificity of diabetes diagnosis based on HbA1c compared with diagnosis based on glucose among previously undiagnosed individuals (ie, excluding those with history of diabetes or using insulin or oral hypoglycaemic drugs). We calculated sensitivity and specificity in each survey, and then pooled results using a random-effects model. We assessed the sources of heterogeneity of sensitivity by meta-regressions for study characteristics selected a priori.FindingsPopulation prevalence of diabetes based on FPG-or-2hOGTT was correlated with prevalence based on FPG alone (r=0·98), but was higher by 2–6 percentage points at different prevalence levels. Prevalence based on HbA1c was lower than prevalence based on FPG in 42·8% of age–sex–survey groups and higher in another 41·6%; in the other 15·6%, the two definitions provided similar prevalence estimates. The variation across studies in the relation between glucose-based and HbA1c-based prevalences was partly related to participants' age, followed by natural logarithm of per person gross domestic product, the year of survey, mean BMI, and whether the survey population was national, subnational, or from specific communities. Diabetes defined as HbA1c 6·5% or more had a pooled sensitivity of 52·8% (95% CI 51·3–54·3%) and a pooled specificity of 99·74% (99·71–99·78%) compared with FPG 7·0 mmol/L or more for diagnosing previously undiagnosed participants; sensitivity compared with diabetes defined based on FPG-or-2hOGTT was 30·5% (28·7–32·3%). None of the preselected study-level characteristics explained the heterogeneity in the sensitivity of HbA1c versus FPG.InterpretationDifferent biomarkers and definitions for diabetes can provide different estimates of population prevalence of diabetes, and differentially identify people without previous diagnosis as having diabetes. Using an HbA1c-based definition alo...

These findings support the hypothesis that pain is associated with PD in the pre-motor stage of the disease. Further research is needed to clarify the role of sensory system involvement in the pre-motor phase of PD.

The introduction and scale-up of new tools for the diagnosis of Tuberculosis (TB) in developing countries has the potential to make a huge difference to the lives of millions of people living in poverty. To achieve this, policy makers need the information to make the right decisions about which new tools to implement and where in the diagnostic algorithm to apply them most effectively. These decisions are difficult as the new tools are often expensive to implement and use, and the health system and patient impacts uncertain, particularly in developing countries where there is a high burden of TB. The authors demonstrate that a discrete event simulation model could play a significant part in improving and informing these decisions. The feasibility of linking the discrete event simulation to a dynamic epidemiology model is also explored in order to take account of longer term impacts on the incidence of TB. Results from two diagnostic districts in Tanzania are used to illustrate how the approach could be used to improve decisions.

PurposeDyslipidemia is considered as one mechanism causing cardiovascular sequelae in obstructive sleep apnea (OSA). Continuous positive airway pressure (CPAP) can reduce cardiovascular morbidities but its effect on lipid profiles is inconclusive. This study aimed to investigate the effects of CPAP on lipid profiles by a meta-analysis of the existing randomized controlled trials.MethodsStudies were retrieved from MEDLINE/PubMed, EMBASE, CENTRAL, commercial websites, and article references up to August 2013 following the protocols (PROSPERO CRD42012002636). Randomized controlled trials investigating the CPAP effects on changes in lipid profiles in adult patients with OSA were included. Two independent researchers extracted relevant data in duplicate. The pooled effect was analyzed by fixed-effect generic inverse variance, and the heterogeneity was assessed using the I2 statistic.ResultsSix trials with 348 patients and 351 controls were included. CPAP significantly lowered total cholesterol (mean, −6.23 mg/dl; 95% CI, −8.73 to –3.73; I2, 0 %; p < 0.001), triglyceride (mean, −12.60 mg/dl; 95% CI, −18.80 to −6.41; I2, 25 %; p < 0.001), and high-density lipoprotein (mean, −1.05 mg/dl; 95% CI, −1.69 to −0.40; I2, 0 %; p = 0.001), but not low-density lipoprotein (mean, −1.01 mg/dl; 95% CI, −5.04 to 3.02; I2, 0 %; p = 0.62). The lipid-lowering effects were homogeneous across the studies. By subgroup analysis, the reductions of lipid profiles were associated with the cross-over design, subtherapeutic CPAP as placebo, enrolled patients with moderate-to-severe OSA or daytime sleepiness, and CPAP treatment with short-term duration or good compliance.ConclusionsThis meta-analysis validates the observation that CPAP can reduce lipid profiles in patients with OSA.Electronic supplementary materialThe online version of this article (doi:10.1007/s11325-014-1082-x) contains supplementary material, which is available to authorized users.

The aim of this study was to investigate the association between diabetes mellitus (DM) and tuberculosis (TB) relapse using the nationwide TB registry in Taiwan. We conducted a case-control study nested within a nationwide cohort of all incident cases of pulmonary TB that were notified during 2006–2007 and had completed anti-TB treatment. The relapse of TB was confirmed by bacteriological or pathological findings. For each relapse case, one control was selected from the study cohort matching by time since treatment completion. DM status was ascertained by medical chart review and cross-matching with the National Health Insurance claims database. A total of 305 cases of relapse were identified after a median follow-up of 3 years (relapse rate: 488 per 100,000 person-year; 95% confidence interval (CI): 434–546). Presence of DM during previous anti-TB treatment was 34.0% and 22.7% in cases and controls, respectively. After adjusting for other potential confounders, DM was associated with increased risk of TB relapse (adjusted odds ratio: 1.96, 95% CI: 1.22–3.15). Only one-third of the DM-TB patients in our study received glycaemic monitoring using HbA1c during anti-TB treatment. Presence of DM was independently associated with risk of TB relapse. TB programs should seriously consider rigorous glucose control in DM-TB patients.

From 1985 to 2016, the prevalence of underweight decreased, and that of obesity and severe obesity increased, in most regions, with significant variation in the magnitude of these changes across regions. We investigated how much change in mean body mass index (BMI) explains changes in the prevalence of underweight, obesity, and severe obesity in different regions using data from 2896 population-based studies with 187 million participants. Changes in the prevalence of underweight and total obesity, and to a lesser extent severe obesity, are largely driven by shifts in the distribution of BMI, with smaller contributions from changes in the shape of the distribution. In East and Southeast Asia and sub-Saharan Africa, the underweight tail of the BMI distribution was left behind as the distribution shifted. There is a need for policies that address all forms of malnutrition by making healthy foods accessible and affordable, while restricting unhealthy foods through fiscal and regulatory restrictions.