Exploring diurnal variation using piecewise linear splines:an example using blood pressure

Background: There are many examples of physiological processes that follow a circadian cycle and researchers are interested in alternative methods to illustrate and quantify this diurnal variation. Circadian blood pressure (BP) deserves additional attention given uncertainty relating to the prognostic significance of BP variability in relation to cardiovascular disease. However, the majority of studies exploring variability in ambulatory blood pressure monitoring (ABPM) collapse the data into single readings ignoring the temporal nature of the data. Advanced statistical techniques are required to explore complete variation over 24 h. Methods: We use piecewise linear splines in a mixed-effects model with a constraint to ensure periodicity as a novel application for modelling daily blood pressure. Data from the Mitchelstown Study, a cross-sectional study of Irish adults aged 47–73 years (n = 2047) was utilized. A subsample (1207) underwent 24-h ABPM. We compared patterns between those with and without evidence of subclinical target organ damage (microalbuminuria). Results: We were able to quantify the steepest rise and fall in SBP, which occurred just after waking (2.23 mmHg/30 min) and immediately after falling asleep (−1.93 mmHg/30 min) respectively. The variation about an individual’s trajectory over 24 h was 12.3 mmHg (standard deviation). On average those with microalbuminuria were found to have significantly higher SBP (7.6 mmHg, 95% CI 5.0–10.1) after adjustment for age, sex and BMI. Including an interaction term between each linear spline and microalbuminuria did not improve model fit. Conclusion: We have introduced a practical method for the analysis of ABPM where we can determine the rate of increase or decrease for different periods of the day. This may be particularly useful in examining chronotherapy effects of antihypertensive medication. It offers new measures of short-term BP variability as we can quantify the variation about an individual’s trajectory but also allows examination of the variation in slopes between individuals (random-effects)

Changes in the incidence of pneumonia, bacterial meningitis, and infant mortality 5 years following introduction of the 13-valent pneumococcal conjugate vaccine in a "3+0" schedule

Streptococcus pneumoniae causes about 826,000 deaths of children in the world each year and many health facility visits. To reduce the burden of pneumococcal disease, many nations have added pneumococcal conjugate vaccines to their national immunization schedules. Nicaragua was the first country eligible for GAVI Alliance funding to introduce the 13-valent pneumococcal conjugate vaccine (PCV13) in 2010, provided to infants at 2, 4, and 6 months of age. The goal of this study was to evaluate the population impact of the first five years of the program.Numbers of visits for pneumonia, pneumonia-related deaths, and bacterial meningitis in both children and adults, and infant deaths between 2008 and 2015 were collected from all 107 public health facilities in León Department. Vital statistics data provided additional counts of pneumonia-related deaths that occurred outside health facilities. Adjusted incidence rates and incidence rate ratios (IRRa) in the vaccine (2011-2015) and pre-vaccine periods (2008-2010) were estimated retrospectively using official population estimates as exposure time.The IRRa for pneumonia hospitalizations was 0.70 (95% confidence interval [CI]: 0.66, 0.75) for infants, and 0.92 (95% CI: 0.85, 0.99) for one year-olds. The IRRa for post-neonatal infant mortality was 0.56 (95% CI: 0.41, 0.77). In the population as a whole, ambulatory visits and hospitalizations for pneumonia, as well as pneumonia-related mortality and rates of bacterial meningitis were lower in the vaccine period.During the first five years of program implementation, reductions were observed in health facility visits for pneumonia in immunized age groups and infant mortality, which would be hard to achieve with any other single public health intervention. Future study is warranted to understand whether the lack of a booster dose (e.g., at 12 months) may be responsible for the small reductions in pneumonia hospitalizations observed in one year-olds as compared to infants

The Matthew Effect in the Italian Digital Context: The Progressive Marginalisation of the “Poor”

The Matthew effect describes a model according to which, over time, inequal- ities fuel ever-widening gaps among individuals and social groups on the basis of the wellknown adage: ‘‘the rich get richer and the poor get poorer’’. In this paper, we analyse the results of the Matthew effect in Italy in relation to first and second level digital divide, in order to determine the trajectories of closure, persistence or reinforcement of inequal- ities within the population. The central research question of the work aims to understand whether, when compared with a higher level of dissemination of technology over time, the adoption curves trace a model of progressive inclusion for the ‘‘poor’’ which approach the ‘‘richest’’, or whether progressive increases are recorded in gaps. Considering a time span of more than a decade, microdata from the Istat multipurpose ‘‘Aspects of daily life’’ survey were used to find an empirically grounded answer to this research question. In terms of methodology, indices of absolute and relative digital exclusion and marginalisation which are necessary to take into account the changing nature of the phenomenon were proposed and used. Techniques of multivariate analysis (cluster analysis and multiple factor analysis) were also applied to detect any changes in the structure of variables and trajectories of the socio-demographic characteristics in question. The main results show the existence of a relative Matthew effect in Italy: despite the general increase in the spread of technologies, we are witnessing a progressive impoverishment of the weakest sectors of the population