Contributions of mean and shape of blood pressure distribution to worldwide trends and variations in raised blood pressure: A pooled analysis of 1018 population-based measurement studies with 88.6 million participants

© The Author(s) 2018. Background: Change in the prevalence of raised blood pressure could be due to both shifts in the entire distribution of blood pressure (representing the combined effects of public health interventions and secular trends) and changes in its high-blood-pressure tail (representing successful clinical interventions to control blood pressure in the hypertensive population). Our aim was to quantify the contributions of these two phenomena to the worldwide trends in the prevalence of raised blood pressure. Methods: We pooled 1018 population-based studies with blood pressure measurements on 88.6 million participants from 1985 to 2016. We first calculated mean systolic blood pressure (SBP), mean diastolic blood pressure (DBP) and prevalence of raised blood pressure by sex and 10-year age group from 20-29 years to 70-79 years in each study, taking into account complex survey design and survey sample weights, where relevant. We used a linear mixed effect model to quantify the association between (probittransformed) prevalence of raised blood pressure and age-group- and sex-specific mean blood pressure. We calculated the contributions of change in mean SBP and DBP, and of change in the prevalence-mean association, to the change in prevalence of raised blood pressure. Results: In 2005-16, at the same level of population mean SBP and DBP, men and women in South Asia and in Central Asia, the Middle East and North Africa would have the highest prevalence of raised blood pressure, and men and women in the highincome Asia Pacific and high-income Western regions would have the lowest. In most region-sex-age groups where the prevalence of raised blood pressure declined, one half or more of the decline was due to the decline in mean blood pressure. Where prevalence of raised blood pressure has increased, the change was entirely driven by increasing mean blood pressure, offset partly by the change in the prevalence-mean association. Conclusions: Change in mean blood pressure is the main driver of the worldwide change in the prevalence of raised blood pressure, but change in the high-blood-pressure tail of the distribution has also contributed to the change in prevalence, especially in older age groups

Worldwide trends in hypertension prevalence and progress in treatment and control from 1990 to 2019: a pooled analysis of 1201 population-representative studies with 104 million participants

Background Hypertension can be detected at the primary health-care level and low-cost treatments can effectively control hypertension. We aimed to measure the prevalence of hypertension and progress in its detection, treatment, and control from 1990 to 2019 for 200 countries and territories. Methods We used data from 1990 to 2019 on people aged 30–79 years from population-representative studies with measurement of blood pressure and data on blood pressure treatment. We defined hypertension as having systolic blood pressure 140 mm Hg or greater, diastolic blood pressure 90 mm Hg or greater, or taking medication for hypertension. We applied a Bayesian hierarchical model to estimate the prevalence of hypertension and the proportion of people with hypertension who had a previous diagnosis (detection), who were taking medication for hypertension (treatment), and whose hypertension was controlled to below 140/90 mm Hg (control). The model allowed for trends over time to be non-linear and to vary by age. Findings The number of people aged 30–79 years with hypertension doubled from 1990 to 2019, from 331 (95% credible interval 306–359) million women and 317 (292–344) million men in 1990 to 626 (584–668) million women and 652 (604–698) million men in 2019, despite stable global age-standardised prevalence. In 2019, age-standardised hypertension prevalence was lowest in Canada and Peru for both men and women; in Taiwan, South Korea, Japan, and some countries in western Europe including Switzerland, Spain, and the UK for women; and in several low-income and middle-income countries such as Eritrea, Bangladesh, Ethiopia, and Solomon Islands for men. Hypertension prevalence surpassed 50% for women in two countries and men in nine countries, in central and eastern Europe, central Asia, Oceania, and Latin America. Globally, 59% (55–62) of women and 49% (46–52) of men with hypertension reported a previous diagnosis of hypertension in 2019, and 47% (43–51) of women and 38% (35–41) of men were treated. Control rates among people with hypertension in 2019 were 23% (20–27) for women and 18% (16–21) for men. In 2019, treatment and control rates were highest in South Korea, Canada, and Iceland (treatment >70%; control >50%), followed by the USA, Costa Rica, Germany, Portugal, and Taiwan. Treatment rates were less than 25% for women and less than 20% for men in Nepal, Indonesia, and some countries in sub-Saharan Africa and Oceania. Control rates were below 10% for women and men in these countries and for men in some countries in north Africa, central and south Asia, and eastern Europe. Treatment and control rates have improved in most countries since 1990, but we found little change in most countries in sub-Saharan Africa and Oceania. Improvements were largest in high-income countries, central Europe, and some upper-middle-income and recently high-income countries including Costa Rica, Taiwan, Kazakhstan, South Africa, Brazil, Chile, Turkey, and Iran. Interpretation Improvements in the detection, treatment, and control of hypertension have varied substantially across countries, with some middle-income countries now outperforming most high-income nations. The dual approach of reducing hypertension prevalence through primary prevention and enhancing its treatment and control is achievable not only in high-income countries but also in low-income and middle-income settings

Structural changes in a protein fragment from abalone shell during calcium carbonate precipitation

Mineralized tissues grow up through biological controlled processes in which specific macromolecules are involved. Some of these molecules, present in very low concentrations and difficult to localize and characterize, become entrapped into the mineralized tissue. In this study a protein fragment, GP, obtained by the alkaline digestion of the green sheet of abalone shell, is used as a probe to study the changes in the molecular structure that occur during a precipitation process of calcium carbonate. This important goal was achieved by exploiting a fluorescent tag in GP. The experimental results obtained using spectroscopic, chromatographic and microscopic techniques indicate that GP controls the precipitation kinetics and the morphology of calcium carbonate crystals, and undergoes a structural reorganization only when entrapped into calcium carbonate crystals. To our knowledge this represents one of the first studies on the conformational changes of a protein fragment involved in biomineralization processes moving from the solution into the mineral phase

High-throughput massively parallel sequencing for fetal aneuploidy detection from maternal plasma.

Circulating cell-free (ccf) fetal DNA comprises 3-20% of all the cell-free DNA present in maternal plasma. Numerous research and clinical studies have described the analysis of ccf DNA using next generation sequencing for the detection of fetal aneuploidies with high sensitivity and specificity. We sought to extend the utility of this approach by assessing semi-automated library preparation, higher sample multiplexing during sequencing, and improved bioinformatic tools to enable a higher throughput, more efficient assay while maintaining or improving clinical performance.Whole blood (10mL) was collected from pregnant female donors and plasma separated using centrifugation. Ccf DNA was extracted using column-based methods. Libraries were prepared using an optimized semi-automated library preparation method and sequenced on an Illumina HiSeq2000 sequencer in a 12-plex format. Z-scores were calculated for affected chromosomes using a robust method after normalization and genomic segment filtering. Classification was based upon a standard normal transformed cutoff value of z = 3 for chromosome 21 and z = 3.95 for chromosomes 18 and 13.Two parallel assay development studies using a total of more than 1900 ccf DNA samples were performed to evaluate the technical feasibility of automating library preparation and increasing the sample multiplexing level. These processes were subsequently combined and a study of 1587 samples was completed to verify the stability of the process-optimized assay. Finally, an unblinded clinical evaluation of 1269 euploid and aneuploid samples utilizing this high-throughput assay coupled to improved bioinformatic procedures was performed. We were able to correctly detect all aneuploid cases with extremely low false positive rates of 0.09%, <0.01%, and 0.08% for trisomies 21, 18, and 13, respectively.These data suggest that the developed laboratory methods in concert with improved bioinformatic approaches enable higher sample throughput while maintaining high classification accuracy

Paired comparison of z-scores.

<p>Z-scores were calculated for 1269 paired samples with previously described GC normalized, repeat masked z-scores on the x-axis <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057381#pone.0057381-Palomaki1" target="_blank">[7]</a> and z-scores from the high-throughput assay on the y-axis. Samples classified by karyotype analysis as trisomies for A) Chromsome 21, B) Chromosome 13, or C) Chromosome 18 are shown in blue; unaffected samples for each aneuploidy condition are shown in gray. Red horizontal and vertical lines in each plot represent the respective classification cutoff for that chromosome (z = 3 for chromosome 21, z = 3.95 for chromosomes 13 and 18). Black line in plot represents y = x.</p

Summary of analysis results for each of the studies performed. Sens = sensitivity.

<p>Spec = specificity; NA = Not applicable.</p

Paired comparison of z-scores.

<p>Z-scores were calculated for paired samples with previously described GC normalized, repeat masked z-scores on the x-axis <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057381#pone.0057381-Palomaki1" target="_blank">[7]</a> and z-scores from the same libraries sequenced in 12-plex on the y-axis. Samples classified by karyotype analysis as trisomies for A) Chromosome 21, B) Chromosome 13, or C) Chromosome 18 are shown in blue; unaffected samples for each aneuploidy condition are shown in gray. Red horizontal and vertical lines in each plot represent the respective classification cutoff for that chromosome (z = 3 for chromosome 21, z = 3.95 for chromosomes 13 and 18).</p

Summary of sample types utilized for each of the studies performed.

<p>Summary of sample types utilized for each of the studies performed.</p