Levels and predictors of exercise referral scheme uptake and adherence: A systematic review

Background The effectiveness of exercise referral schemes (ERS) is influenced by uptake and adherence to the scheme. The identification of factors influencing low uptake and adherence could lead to the refinement of schemes to optimise investment. Objectives To quantify the levels of ERS uptake and adherence and to identify factors predictive of uptake and adherence. Methods A systematic review and meta-analysis was undertaken. MEDLINE, EMBASE, PsycINFO, Cochrane Library, ISI WOS, SPORTDiscus and ongoing trial registries were searched (to October 2009) and included study references were checked. Included studies were required to report at least one of the following: (1) a numerical measure of ERS uptake or adherence and (2) an estimate of the statistical association between participant demographic or psychosocial factors (eg, level of motivation, self-efficacy) or programme factors and uptake or adherence to ERS. Results Twenty studies met the inclusion criteria, six randomised controlled trials (RCTs) and 14 observational studies. The pooled level of uptake in ERS was 66% (95% CI 57% to 75%) across the observational studies and 81% (95% CI 68% to 94%) across the RCTs. The pooled level of ERS adherence was 49% (95% CI 40% to 59%) across the observational studies and 43% (95% CI 32% to 54%) across the RCTs. Few studies considered anything other than gender and age. Women were more likely to begin an ERS but were less likely to adhere to it than men. Older people were more likely to begin and adhere to an ERS. Limitations Substantial heterogeneity was evident across the ERS studies. Without standardised definitions, the heterogeneity may have been reflective of differences in methods of defining uptake and adherence across studies. Conclusions To enhance our understanding of the variation in uptake and adherence across ERS and how these variations might affect physical activity outcomes, future trials need to use quantitative and qualitative methods.

Insights into PBDE uptake, body burden, and elimination gained from Australian age–Concentration trends observed shortly after peak exposure

Background Population pharmacokinetic models combined with multiple sets of age– concentration biomonitoring data facilitate back-calculation of chemical uptake rates from biomonitoring data. Objectives We back-calculated uptake rates of PBDEs for the Australian population from multiple biomonitoring surveys (top-down) and compared them with uptake rates calculated from dietary intake estimates of PBDEs and PBDE concentrations in dust (bottom-up). Methods Using three sets of PBDE elimination half-lives, we applied a population pharmacokinetic model to the PBDE biomonitoring data measured between 2002–2003 and 2010–2011 to derive the top-down uptake rates of four key PBDE congeners and six age groups. For the bottom-up approach, we used PBDE concentrations measured around 2005. Results Top-down uptake rates of Σ4BDE (the sum of BDEs 47, 99, 100, and 153) varied from 7.9 to 19 ng/kg/day for toddlers and from 1.2 to 3.0 ng/kg/day for adults; in most cases, they were—for all age groups—higher than the bottom-up uptake rates. The discrepancy was largest for toddlers with factors up to 7–15 depending on the congener. Despite different elimination half-lives of the four congeners, the age–concentration trends showed no increase in concentration with age and were similar for all congeners. Conclusions In the bottom-up approach, PBDE uptake is underestimated; currently known pathways are not sufficient to explain measured PBDE concentrations, especially in young children. Although PBDE exposure of toddlers has declined in the past years, pre- and postnatal exposure to PBDEs has remained almost constant because the mothers’ PBDE body burden has not yet decreased substantially.

Molecular and biochemical characterisation of transgenic banana lines containing iron uptake and storage enhancing genes

This thesis investigated the basis for availability of iron (Fe) and zinc (Zn) content in different banana fruits grown in Uganda and Australia. Rather than micronutrient content levels in different banana cultivar, genotype and environment interactions explained much of the differences. Such information should provide important insights for future developments in the biofortification of banana. Bananas consumed in Uganda did not contain sufficient levels of Fe and Zn that meet the nutrient requirements for vulnerable groups.