Observed versus predicted risk of 5-year incident stoke by risk decile—derivation and validation cohorts.

<p>Panel A = males; Panel B = females. *Statistically significant difference between observed and predicted risk.</p

Stroke Population Risk Tool (SPoRT)–Model.

<p>Stroke Population Risk Tool (SPoRT)–Model.</p

Predicted 5-year risk of stroke by age group and SPoRT behavioural index value.

<p>Predicted 5-year risk of stroke by age group and SPoRT behavioural index value.</p

Secondary analysis—observed (O) versus predicted (P) risk of 5-year incident stoke by risk decile, combined development and validation cohorts.

<p>Panel A = males; Panel B = females. Abbreviations: O = observed; P = predicted. *Primary outcome.</p

Observed versus predicted risk of 5-year incident stoke by health behaviour, BMI, and stress.

<p>Panel A = males; Panel B = females.</p

Noting non-personal choice reasons for non-adherence to health behavior change or non-receipt of monitoring tests: Low income vs. High income.

<p>Noting non-personal choice reasons for non-adherence to health behavior change or non-receipt of monitoring tests: Low income vs. High income.</p

Baseline Characteristics, overall and stratified by income status.

<p>*CV = 16.5–33 (Interpret with caution); Abbreviations: CI – confidence interval; PRR – prevalence rate ratio; sep/div – separated or divorced; SK – Saskatchewan; MB – Manitoba; BC – British Columbia.</p

The Association of Income with Health Behavior Change and Disease Monitoring among Patients with Chronic Disease

<div><p>Background</p><p>Management of chronic diseases requires patients to adhere to recommended health behavior change and complete tests for monitoring. While studies have shown an association between low income and lack of adherence, the reasons why people with low income may be less likely to adhere are unclear. We sought to determine the association between household income and receipt of health behavior change advice, adherence to advice, receipt of recommended monitoring tests, and self-reported reasons for non-adherence/non-receipt.</p><p>Methods</p><p>We conducted a population-weighted survey, with 1849 respondents with cardiovascular-related chronic diseases (heart disease, hypertension, diabetes, stroke) from Western Canada (n = 1849). We used log-binomial regression to examine the association between household income and the outcome variables of interest: receipt of advice for and adherence to health behavior change (sodium reduction, dietary improvement, increased physical activity, smoking cessation, weight loss), reasons for non-adherence, receipt of recommended monitoring tests (cholesterol, blood glucose, blood pressure), and reasons for non-receipt of tests.</p><p>Results</p><p>Behavior change advice was received equally by both low and high income respondents. Low income respondents were more likely than those with high income to not adhere to recommendations regarding smoking cessation (adjusted prevalence rate ratio (PRR): 1.55, 95%CI: 1.09–2.20), and more likely to not receive measurements of blood cholesterol (PRR: 1.72, 95%CI 1.24–2.40) or glucose (PRR: 1.80, 95%CI: 1.26–2.58). Those with low income were less likely to state that non-adherence/non-receipt was due to personal choice, and more likely to state that it was due to an extrinsic factor, such as cost or lack of accessibility.</p><p>Conclusions</p><p>There are important income-related differences in the patterns of health behavior change and disease monitoring, as well as reasons for non-adherence or non-receipt. Among those with low income, adherence to health behavior change and monitoring may be improved by addressing modifiable barriers such as cost and access.</p></div

Integration of high and low field H-1 NMR to analyse the effects of bovine dietary regime on milk metabolomics and protein-bound moisture characterisation of the resulting mozzarella cheeses during ripening

The influence of dairy cow feeding regime was investigated using H-1 nuclear magnetic resonance (NMR). Two different NMR analytical systems were deployed: high field H-1 NMR to investigate the influence on milk metabolomics and low field NMR to characterise proton relaxation linked to changes in the state of mozzarella cheese moisture during ripening. The metabolomics results showed that grass-based feeding increased the concentration of a biological marker that signifies near-organic milk production conditions. On the other hand, the investigation of cheese moisture distribution showed that grass-based diets reached final moisture partitioning in a shorter time, which implied the formation of a more compact protein structure in the cheese matrix. These results indicate that pasture-based dairying may be differentiated in terms of the provenance of milk produced along with the accrual of additional benefits during ripening of the resulting mozzarella cheeses. (C) 2018 Elsevier Ltd. All rights reserved

Noting “personal choice” as reason for non-adherence to health behavior change or non-receipt of monitoring tests: Low income vs. High income.

<p>Noting “personal choice” as reason for non-adherence to health behavior change or non-receipt of monitoring tests: Low income vs. High income.</p