Estimating and comparing incidence and prevalence of chronic diseases by combining GP registry data: the role of uncertainty

Background: Estimates of disease incidence and prevalence are core indicators of public health. The manner in which these indicators stand out against each other provide guidance as to which diseases are most common and what health problems deserve priority. Our aim was to investigate how routinely collected data from different general practitioner registration networks (GPRNs) can be combined to estimate incidence and prevalence of chronic diseases and to explore the role of uncertainty when comparing diseases. Methods. Incidence and prevalence counts, specified by gender and age, of 18 chronic diseases from 5 GPRNs in the Netherlands from the year 2007 were used as input. Generalized linear mixed models were fitted with the GPRN identifier acting as random intercept, and age and gender as explanatory variables. Using predictions of the regression models we estimated the incidence and prevalence for 18 chronic diseases and calculated a stochastic ranking of diseases in terms of incidence and prevalence per 1,000. Results: Incidence was highest for coronary heart disease and prevalence was highest for diabetes if we looked at the point estimates. The between GPRN variance in general was higher for incidence than for prevalence. Since uncertainty intervals were wide for some diseases and overlapped, the ranking of diseases was subject to uncertainty. For incidence shifts in rank of up to twelve positions were observed. For prevalence, most diseases shifted maximally three or four places in rank. Conclusion: Estimates of incidence and prevalence can be obtained by combining data from GPRNs. Uncertainty in the estimates of absolute figures may lead to different rankings of diseases and, hence, should be taken into consideration when comparing disease incidences and prevalences

The cost-effectiveness of increasing alcohol taxes: a modelling study

<p>Abstract</p> <p>Background</p> <p>Excessive alcohol use increases risks of chronic diseases such as coronary heart disease and several types of cancer, with associated losses of quality of life and life-years. Alcohol taxes can be considered as a public health instrument as they are known to be able to decrease alcohol consumption. In this paper, we estimate the cost-effectiveness of an alcohol tax increase for the entire Dutch population from a health-care perspective focusing on health benefits and health-care costs in alcohol users.</p> <p>Methods</p> <p>The chronic disease model of the National Institute for Public Health and the Environment was used to extrapolate from decreased alcohol consumption due to tax increases to effects on health-care costs, life-years gained and quality-adjusted life-years gained, A Dutch scenario in which tax increases for beer are planned, and a Swedish scenario representing one of the highest alcohol taxes in Europe, were compared with current practice in the Netherlands. To estimate cost-effectiveness ratios, yearly differences in model outcomes between intervention and current practice scenarios were discounted and added over the time horizon of 100 years to find net present values for incremental life-years gained, quality-adjusted life-years gained, and health-care costs.</p> <p>Results</p> <p>In the Swedish scenario, many more quality-adjusted life-years were gained than in the Dutch scenario, but both scenarios had almost equal incremental cost-effectiveness ratios: €5100 per quality-adjusted life-year and €5300 per quality-adjusted life-year, respectively.</p> <p>Conclusion</p> <p>Focusing on health-care costs and health consequences for drinkers, an alcohol tax increase is a cost-effective policy instrument.</p

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Riociguat treatment in patients with chronic thromboembolic pulmonary hypertension: Final safety data from the EXPERT registry

Objective: The soluble guanylate cyclase stimulator riociguat is approved for the treatment of adult patients with pulmonary arterial hypertension (PAH) and inoperable or persistent/recurrent chronic thromboembolic pulmonary hypertension (CTEPH) following Phase

Accuracy of oscillometric blood pressure measurement in atrial fibrillation

The primary aim of this study was to assess the accuracy of automated oscillometry (AO) in outpatients with atrial fibrillation (AF). The secondary aim was to explore whether AO accuracy is influenced by beat-to-beat blood pressure (BP) variability or heart frequency (HF). Systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured by AO and beat-to-beat BP using a validated Volume Clamp Method (VCM) technique. AO accuracy was analyzed separately in tertiles of beat-to-beat BP variability and HF. The main study included 58 AF and 38 sinus rhythm (SR) patients in whom the Welch Allyn Spot Vital Signs (WASVS) was used. An auxiliary study in 23 AF patients used the Philips M3002A IntelliVue ×2. For AF and SR patients, respectively, SBP by WASVS deviated by +0.1 (±14.8) mmHg and -7.9 (±15.7) mmHg from VCM. WASVS-DBP was higher than VCM in AF and SR by 6.3 (±9.2) mmHg and 5.0 (±7.7) mmHg, respectively. High beat-to-beat BP variability and high HF decreased WASVS accuracy for both SBP and DBP. SBP and DBP measurements by Philips M3002A IntelliVue ×2 deviated by -6.8 (±13.2) mmHg and 9.4 (±8.1) mmHg, respectively. Overall, AO accuracy in AF is limited; in individual patients, AO inaccuracy may be considerable. AO accuracy is especially reduced in patients showing large beat-to-beat BP variability or high H

Accuracy of oscillometric blood pressure measurement in atrial fibrillation

OBJECTIVE: The primary aim of this study was to assess the accuracy of automated oscillometry (AO) in outpatients with atrial fibrillation (AF). The secondary aim was to explore whether AO accuracy is influenced by beat-to-beat blood pressure (BP) variability or heart frequency (HF). METHODS: Systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured by AO and beat-to-beat BP using a validated Volume Clamp Method (VCM) technique. AO accuracy was analyzed separately in tertiles of beat-to-beat BP variability and HF. RESULTS: The main study included 58 AF and 38 sinus rhythm (SR) patients in whom the Welch Allyn Spot Vital Signs (WASVS) was used. An auxiliary study in 23 AF patients used the Philips M3002A IntelliVue ×2. For AF and SR patients, respectively, SBP by WASVS deviated by +0.1 (±14.8) mmHg and -7.9 (±15.7) mmHg from VCM. WASVS-DBP was higher than VCM in AF and SR by 6.3 (±9.2) mmHg and 5.0 (±7.7) mmHg, respectively. High beat-to-beat BP variability and high HF decreased WASVS accuracy for both SBP and DBP. SBP and DBP measurements by Philips M3002A IntelliVue ×2 deviated by -6.8 (±13.2) mmHg and 9.4 (±8.1) mmHg, respectively. CONCLUSION: Overall, AO accuracy in AF is limited; in individual patients, AO inaccuracy may be considerable. AO accuracy is especially reduced in patients showing large beat-to-beat BP variability or high HF

Genetic studies of body mass index yield new insights for obesity biology.

Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P&nbsp;&lt;&nbsp;5&nbsp;×&nbsp;10(-8)), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for &gt;20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis

Defining the role of common variation in the genomic and biological architecture of adult human height

Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated ∼2,000, ∼3,700 and ∼9,500 SNPs explained ∼21%, ∼24% and ∼29% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/β-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants