Population effects on individual systolic blood pressure: A multilevel analysis of the World Health Organization MONICA project

Individuals from the same population share a number of contextual circumstances that may condition a common level of blood pressure over and above individual characteristics. Understanding this population effect is relevant for both etiologic research and prevention strategies. Using multilevel regression analyses, the authors quantified the extent to which individual differences in systolic blood pressure (SBP) could be attributed to the population level. They also investigated possible cross-level interactions between the population in which a person lived and pharmacological (antihypertensive medication) and nonpharmacological (body mass index) effects on individual SBP. They analyzed data on 23,796 men and 24,986 women aged 35-64 years from 39 worldwide Monitoring of Trends and Determinants in Cardiovascular Disease (MONICA) study populations participating in the final survey of this World Health Organization project (1989-1997). SBP was positively associated with low educational achievement, high body mass index, and use of antihypertensive medication and, for women, was negatively associated with smoking. About 7-8% of all SBP differences between subjects were attributed to the population level. However, this population effect was particularly strong (i.e., 20%) in antihypertensive medication users and overweight women. This empirical evidence of a population effect on individual SBP emphasizes the importance of developing population-wide strategies to reduce individual risk of hypertension.

A broad-scale analysis of links between coastal fisheries production and mangrove extent: A case-study for northeastern Australia

The paradigm that mangroves are critical for sustaining production in coastal fisheries is widely accepted, but empirical evidence has been tenuous. This study showed that links between mangrove extent and coastal fisheries production could be detected for some species at a broad regional scale (1000s of kilometres) on the east coast of Queensland, Australia. The relationships between catch-per-unit-effort for different commercially caught species in four fisheries (trawl, line, net and pot fisheries) and mangrove characteristics, estimated from Landsat images were examined using multiple regression analyses. The species were categorised into three groups based on information on their life history characteristics, namely mangrove-related species (banana prawns Penaeus merguiensis, mud crabs Scylla serrata and barramundi Lates calcarifer), estuarine species (tiger prawns Penaeus esculentus and Penaeus semisulcatus, blue swimmer crabs Portunus pelagicus and blue threadfin Eleutheronema tetradactylum) and offshore species (coral trout Plectropomus spp.). For the mangrove-related species, mangrove characteristics such as area and perimeter accounted for most of the variation in the model; for the non-mangrove estuarine species, latitude was the dominant parameter but some mangrove characteristics (e.g. mangrove perimeter) also made significant contributions to the models. In contrast, for the offshore species, latitude was the dominant variable, with no contribution from mangrove characteristics. This study also identified that finer scale spatial data for the fisheries, to enable catch information to be attributed to a particular catchment, would help to improve our understanding of relationships between mangroves and fisheries production. (C) 2005 Elsevier B.V. All rights reserved.

Repeated occurrence of basal cell carcinoma of the skin and multifailure survival analysis: Follow-up data from the nambour skin cancer prevention trial

The aim of this study was to apply multifailure survival methods to analyze time to multiple occurrences of basal cell carcinoma (BCC). Data from 4.5 years of follow-up in a randomized controlled trial, the Nambour Skin Cancer Prevention Trial (1992-1996), to evaluate skin cancer prevention were used to assess the influence of sunscreen application on the time to first BCC and the time to subsequent BCCs. Three different approaches of time to ordered multiple events were applied and compared: the Andersen-Gill, Wei-Lin-Weissfeld, and Prentice-Williams-Peterson models. Robust variance estimation approaches were used for all multifailure survival models. Sunscreen treatment was not associated with time to first occurrence of a BCC (hazard ratio = 1.04, 95% confidence interval: 0.79, 1.45). Time to subsequent BCC tumors using the Andersen-Gill model resulted in a lower estimated hazard among the daily sunscreen application group, although statistical significance was not reached (hazard ratio = 0.82, 95% confidence interval: 0.59, 1.15). Similarly, both the Wei-Lin-Weissfeld marginal-hazards and the Prentice-Williams-Peterson gap-time models revealed trends toward a lower risk of subsequent BCC tumors among the sunscreen intervention group. These results demonstrate the importance of conducting multiple-event analysis for recurring events, as risk factors for a single event may differ from those where repeated events are considered.

Regression to the mean: what it is and how to deal with it

Background Regression to the mean (RTM) is a statistical phenomenon that can make natural variation in repeated data look like real change. It happens when unusually large or small measurements tend to be followed by measurements that are closer to the mean. Methods We give some examples of the phenomenon, and discuss methods to overcome it at the design and analysis stages of a study. Results The effect of RTM in a sample becomes more noticeable with increasing measurement error and when follow-up measurements are only examined on a sub-sample selected using a baseline value. Conclusions RTM is a ubiquitous phenomenon in repeated data and should always be considered as a possible cause of an observed change. Its effect can be alleviated through better study design and use of suitable statistical methods.

Analysis of lipoproteins using 2D diffusion-edited NMR spectroscopy and multi-way chemometrics

This study represents the first application of multi-way calibration by N-PLS and multi-way curve resolution by PARAFAC to 2D diffusion-edited H-1 NMR spectra. The aim of the analysis was to evaluate the potential for quantification of lipoprotein main- and subtractions in human plasma samples. Multi-way N-PLS calibrations relating the methyl and methylene peaks of lipoprotein lipids to concentrations of the four main lipoprotein fractions as well as 11 subfractions were developed with high correlations (R = 0.75-0.98). Furthermore, a PARAFAC model with four chemically meaningful components was calculated from the 2D diffusion-edited spectra of the methylene peak of lipids. Although the four extracted PARAFAC components represent molecules of sizes that correspond to the four main fractions of lipoproteins, the corresponding concentrations of the four PARAFAC components proved not to be correlated to the reference concentrations of these four fractions in the plasma samples as determined by ultracentrifugation. These results indicate that NMR provides complementary information on the classification of lipoprotein fractions compared to ultracentrifugation. (C) 2004 Elsevier B.V. All rights reserved.

Disorders of breathing and continence have a stronger association with back pain than obesity and physical activity

Although obesity and physical activity have been argued to predict back pain, these factors are also related to incontinence and breathing difficulties. Breathing and continence mechanisms may interfere with the physiology of spinal control, and may provide a link to back pain. The aim of this study was to establish the association between back pain and disorders of continence and respiration in women. We conducted a cross-sectional analysis of self-report, postal survey data from the Australian Longitudinal Study on Women's Health. We used multinomial logistic regression to model four levels of back pain in relation to both the traditional risk factors of body mass index and activity level, and the potential risk factors of incontinence, breathing difficulties, and allergy. A total of 38 050 women were included from three age-cohorts. When incontinence and breathing difficulties were considered, obesity and physical activity were not consistently associated with back pain. In contrast, odds ratios (OR) for often having back pain were higher for women often having incontinence compared to women without incontinence (OR were 2.5, 2.3 and 2.3 for young, mid-age! and older women, respectively). Similarly, mid-aged and older women had higher odds of having back pain often when they experienced breathing difficulties often compared to women with no breathing problems (OR of 2.0 and 1.9, respectively). Unlike obesity and physical activity, disorders of continence and respiration were strongly related to frequent back pain. This relationship may be explained by physiological limitations of co-ordination of postural, respiratory and continence functions of trunk muscles.

Multi-level zero-inflated Poisson regression modelling of correlated count data with excess zeros

Count data with excess zeros relative to a Poisson distribution are common in many biomedical applications. A popular approach to the analysis of such data is to use a zero-inflated Poisson (ZIP) regression model. Often, because of the hierarchical Study design or the data collection procedure, zero-inflation and lack of independence may occur simultaneously, which tender the standard ZIP model inadequate. To account for the preponderance of zero counts and the inherent correlation of observations, a class of multi-level ZIP regression model with random effects is presented. Model fitting is facilitated using an expectation-maximization algorithm, whereas variance components are estimated via residual maximum likelihood estimating equations. A score test for zero-inflation is also presented. The multi-level ZIP model is then generalized to cope with a more complex correlation structure. Application to the analysis of correlated count data from a longitudinal infant feeding study illustrates the usefulness of the approach.

Physical activity and strength of the femoral neck during the adolescent growth spurt: A longitudinal analysis

Loading of the femoral neck (FN) is dominated by bending and compressive stresses. We hypothesize that adaptation of the FN to physical activity would be manifested in the cross-sectional area (CSA) and section modulus (Z) of bone, indices of axial and bending strength, respectively. We investigated the influence of physical activity on bone strength during adolescence using 7 years of longitudinal data from 109 boys and 121 girls from the Saskatchewan Paediatric Bone and Mineral Accrual Study (PBMAS). Physical activity data (PAC-Q physical activity inventory) and anthropometric measurements were taken every 6 months and DXA bone scans were measured annually (Hologic QDR2000, array mode). We applied hip structural analysis to derive strength and geometric indices of the femoral neck using DXA scans. To control for maturation, we determined a biological maturity age defined as years from age at peak height velocity (APHV). To account for the repeated measures within individual nature of longitudinal data, multilevel random effects regression analyses were used to analyze the data. When biological maturity age and body size (height and weight) were controlled, in both boys and girls, physical activity was a significant positive independent predictor of CSA and Z of the narrow region of the femoral neck (P < 0.05). There was no independent effect of physical activity on the subperiosteal width of the femoral neck. When leg length and leg lean mass were introduced into the random effects models to control for size and muscle mass of the leg (instead of height and weight), all significant effects of physical activity disappeared. Even among adolescents engaged in normal levels of physical activity, the statistically significant relationship between physical activity and indices of bone strength demonstrate that modifiable lifestyle factors like exercise play an important role in optimizing bone strength during the growing years. Physical activity differences were explained by the interdependence between activity and lean mass considerations. Physical activity is important for optimal development of bone strength. (c) 2005 Elsevier Inc. All rights reserved.

Relationship between steatosis, inflammation, and fibrosis in chronic hepatitis C: A meta-analysis of individual patient data

Background & Aims: Steatosis is a frequent histologic finding in chronic hepatitis C (CHC), but it is unclear whether steatosis is an independent predictor for liver fibrosis. We evaluated the association between steatosis and fibrosis and their common correlates in persons with CHC and in subgroup analyses according to hepatitis C virus (HCV) genotype and body mass index. Methods: We conducted a meta-analysis on individual data from 3068 patients with histologically confirmed CHC recruited from 10 clinical centers in Italy, Switzerland, France, Australia, and the United States. Results: Steatosis was present in 1561 patients (50.9%) and fibrosis in 2688 (87.6%). HCV genotype was 1 in :1694 cases (55.2%), 2 in 563 (18.4%), 3 in 669 (21.8%), and 4 in :142 (4.6%). By stepwise logistic regression, steatosis was associated independently with genotype 3, the presence of fibrosis, diabetes, hepatic inflammation, ongoing alcohol abuse, higher body mass index, and older age. Fibrosis was associated independently with inflammatory activity, steatosis, male sex, and older age, whereas HCV genotype 2 was associated with reduced fibrosis. In the subgroup analyses, the association between steatosis and fibrosis invariably was dependent on a simultaneous association between steatosis and hepatic inflammation. Conclusions: In this large and geographically different group of CHC patients, steatosis is confirmed as significantly and independently associated with fibrosis in CHC. Hepatic inflammation may mediate fibrogenesis in patients with liver steatosis. Control of metabolic factors (such as overweight, via lifestyle adjustments) appears important in the management of CHC.

Normal ranges for automated analysis of global LV function using 2D Strain

Background: Automated measurement of LV function could extend the clinical utility of echo by less expert readers. We sought to define normal ranges of global 2D strain (2DS) and strain-rate (SR) in an international, multicenter study of healthy subjects, and to assess the determinants of variation. Methods: SR and 2DS were measured in 18 myocardial segts in both apical and short axis views of 227 normal subjects (38% men, 48±14y) with no cardiac history, risk factors or drug therapy. The association of age and resting hemodynamics with global strain indices was sought using multiple regression. Differences in variance were expressed as F values. Results: Baseline SBP was 127±18 mmHg, pulse was 76±13/min and ejection fraction 50±20%. Although global longitudinal strain was influenced by endsystolic volume (F=4.2, p

Effect of sample geometry on regression rate of the melting interface for carbon steel burned in oxygen

Promoted-ignition testing on carbon steel rods of varying cross-sectional area and shape was performed in high pressure oxygen to assess the effect of sample geometry on the regression rate of the melting interface. Cylindrical and rectangular geometries and three different cross sections were tested and the regression rates of the cylinders were compared to the regression rates of the rectangular samples at test pressures around 6.9 MPa. Tests were recorded and video analysis used to determine the regression rate of the melting interface by a new method based on a drop cycle which was found to provide a good basis for statistical analysis and provide excellent agreement to the standard averaging methods used. Both geometries tested showed the typical trend of decreasing regression rate of the melting interface with increasing cross-sectional area; however, it was shown that the effect of geometry is more significant as the sample's cross sections become larger. Discussion is provided regarding the use of 3.2-mm square rods rather than 3.2-mm cylindrical rods within the standard ASTM test and any effect this may have on the observed regression rate of the melting interface.

Regression with Gaussian processes

The Bayesian analysis of neural networks is difficult because the prior over functions has a complex form, leading to implementations that either make approximations or use Monte Carlo integration techniques. In this paper I investigate the use of Gaussian process priors over functions, which permit the predictive Bayesian analysis to be carried out exactly using matrix operations. The method has been tested on two challenging problems and has produced excellent results.

Gaussian processes for regression

The Bayesian analysis of neural networks is difficult because a simple prior over weights implies a complex prior distribution over functions. In this paper we investigate the use of Gaussian process priors over functions, which permit the predictive Bayesian analysis for fixed values of hyperparameters to be carried out exactly using matrix operations. Two methods, using optimization and averaging (via Hybrid Monte Carlo) over hyperparameters have been tested on a number of challenging problems and have produced excellent results.

Gaussian regression and optimal finite dimensional linear models

The problem of regression under Gaussian assumptions is treated generally. The relationship between Bayesian prediction, regularization and smoothing is elucidated. The ideal regression is the posterior mean and its computation scales as O(n³), where n is the sample size. We show that the optimal m-dimensional linear model under a given prior is spanned by the first m eigenfunctions of a covariance operator, which is a trace-class operator. This is an infinite dimensional analogue of principal component analysis. The importance of Hilbert space methods to practical statistics is also discussed.