Physical activity in three regional communities in Queensland

Objective
To describe physical activity participation in three Queensland regional communities.

Design
Cross-sectional mail survey of randomly selected residents, stratified by age and sex.

Setting
Esk, Mareeba and Mount Isa.

Participants
1219 (58% women) adults, with a mean age 46.7 (standard deviation 14.7) years.

Main outcome measures
Proportion of people inactive, meeting Australian activity guidelines (a minimum of 150 min week−1 and five sessions week−1) and walking a dog daily; time spent walking and cycling for transport; location and type of recreational physical activities.

Results
Overall, 18% of respondents were inactive, with the highest proportions among women (22.3%) and older adults in Mount Isa (24.3%). The proportion meeting activity guidelines was 47%, with the lowest proportion among women in Mount Isa (40.4%). Although 63% reported owning a dog, only 22% reported walking a dog daily. Few people reported walking or cycling for transport. The most common types of activities were walking, home-based exercise, running/jogging and swimming, and the most common location was at or near home.

Conclusions
Physical activity levels were lower in these regional communities than the state average. The findings indicate a need for physical activity policy and intervention strategies targeting regional and rural areas. This could focus on women and older adults, dog walking and physical activity opportunities in or near the home.

A generalization of the Bonferroni mean based on partitions

The mean defined by Bonferroni in 1950 (known by the same name) averages all non-identical product pairs of the inputs. Its generalizations to date have been able to capture unique behavior that may be desired in some decision-making contexts such as the ability to model mandatory requirements. In this paper, we propose a composition that averages conjunctions between the respective means of a designated subset-size partition. We investigate the behavior of such a function and note the relationship within a given family as the subset size is changed. We found that the proposed function is able to more intuitively handle multiple mandatory requirements or mandatory input sets.

Height, aging and cognitive abilities across Europe

Previous research has found that as a marker of childhood circumstances, height is correlated with cognitive functioning at older ages. Using data from the Survey of Health, Ageing, and Retirement in Europe (SHARE) and about 17,000 respondents from 11 countries, we find that height is positively and significantly associated with cognitive functioning in later life despite controlling for a myriad of possible confounding factors. A 10 cm increase in height is associated with a 0.04 standard deviation increase in a summary cognitive score (mean 0.02, std. dev. 0.77). We find that being born in a country where the infant mortality rate at the time of birth is high has a negative and significant influence on cognitive functioning in later life. A 10% increase in the infant mortality rate is associated with a 0.1 standard deviation decrease in the summary cognitive score. We also find some evidence that height serves as a protective factor against age related deterioration in cognitive functioning. For persons of average stature, age related decreases in cognition scores are 3–5 percentage points smaller if they move up a quartile in the height distribution. Our results also suggest that there is a significant positive association between height and cognitive abilities across countries for this pre-1950 birth cohort of respondents, with correlations ranging from 0.4 to 0.8.

Knowing doesn’t mean doing—bridging the colorectal cancer screening gap

Two behavioural approaches to influence colorectal cancer screening uptake were investigated. Results suggest that the impact of messages that address (1) ease and convenience and (2) social support and endorsement may depend upon the extent to which they successfully address concerns specific to an individual’s current state of readiness to participate.

Nurses' understanding of patient-centred care in Bhutan

Aim The purpose of the study was to explore nurses' perceptions and understanding of patient-centred care (PCC) in Bhutan. Background Nurses' perceptions and understanding of PCC in Bhutan are unknown. Methods A non-probability convenience sample was taken and a mixed method (quantitative and qualitative descriptive) used. Survey questionnaires were administered to 87 Bhutanese nurses in three types of hospitals -- the National Referral Hospital, the regional referral hospital and the district hospital. Descriptive statistics including frequency distribution, mean and standard deviation (SD) were used for analysis. Spearman's correlation coefficients were used to investigate relationships between demographic variables. Results The nursing labour force in Bhutan knows which behaviours are considered necessary for practising PCC. The mean (SD) rating of behaviours considered critical for practising PCC was 4.29 (0.22), five being the highest score. Bhutanese nurses described PCC, according to qualitative descriptive analysis, as being based on individual patient assessment (22/87 or 25% of respondents), using a holistic model of care (38/87 or 44%) that was based on evidence (38/87 or 44%). A higher level of education (79/87 or 91%) was found to be the main factor that would facilitate the development of PCC, while inadequate staffing, in terms of insufficient numbers of staff and lack of advanced practitioners (56/87 or 64%), was revealed as the main factor that hinders development of PCC. Conclusion Bhutanese nurses believed certain behaviours were critical to PCC. Reform of higher nursing education, putting an emphasis on PCC, would improve nursing practice and increase its scope.

Recombinant human growth hormone for the treatment of growth disorders in children: a systematic review and economic evaluation

Recombinant human growth hormone (rhGH) is licensed for short stature associated with growth hormone deficiency (GHD), Turner syndrome (TS), Prader-Willi syndrome (PWS), chronic renal insufficiency (CRI), short stature homeobox-containing gene deficiency (SHOX-D) and being born small for gestational age (SGA). To assess the clinical effectiveness and cost-effectiveness of rhGH compared with treatment strategies without rhGH for children with GHD, TS, PWS, CRI, SHOX-D and those born SGA. The systematic review used a priori methods. Key databases were searched (e.g. MEDLINE, EMBASE, NHS Economic Evaluation Database and eight others) for relevant studies from their inception to June 2009. A decision-analytical model was developed to determine cost-effectiveness in the UK. Two reviewers assessed titles and abstracts of studies identified by the search strategy, obtained the full text of relevant papers, and screened them against inclusion criteria. Data from included studies were extracted by one reviewer and checked by a second. Quality of included studies was assessed using standard criteria, applied by one reviewer and checked by a second. Clinical effectiveness studies were synthesised through a narrative review. Twenty-eight randomised controlled trials (RCTs) in 34 publications were included in the systematic review. GHD: Children in the rhGH group grew 2.7 cm/year faster than untreated children and had a statistically significantly higher height standard deviation score (HtSDS) after 1 year: -2.3 ± 0.45 versus -2.8 ± 0.45. TS: In one study, treated girls grew 9.3 cm more than untreated girls. In a study of younger children, the difference was 7.6 cm after 2 years. HtSDS values were statistically significantly higher in treated girls. PWS: Infants receiving rhGH for 1 year grew significantly taller (6.2 cm more) than those untreated. Two studies reported a statistically significant difference in HtSDS in favour of rhGH. CRI: rhGH-treated children in a 1-year study grew an average of 3.6 cm more than untreated children. HtSDS was statistically significantly higher in treated children in two studies. SGA: Criteria were amended to include children of 3+ years with no catch-up growth, with no reference to mid-parental height. Only one of the RCTs used the licensed dose; the others used higher doses. Adult height (AH) was approximately 4 cm higher in rhGH-treated patients in the one study to report this outcome, and AH-gain SDS was also statistically significantly higher in this group. Mean HtSDS was higher in treated than untreated patients in four other studies (significant in two). SHOX-D: After 2 years' treatment, children were approximately 6 cm taller than the control group and HtSDS was statistically significantly higher in treated children. The incremental cost per quality adjusted life-year (QALY) estimates of rhGH compared with no treatment were: 23,196 pounds for GHD, 39,460 pounds for TS, 135,311 pounds for PWS, 39,273 pounds for CRI, 33,079 pounds for SGA and 40,531 pounds for SHOX-D. The probability of treatment of each of the conditions being cost-effective at 30,000 pounds was: 95% for GHD, 19% for TS, 1% for PWS, 16% for CRI, 38% for SGA and 15% for SHOX-D.

Rapid discrimination and determination of polyunsaturated fatty acid composition in marine oils by FTIR Spectroscopy and Multivariate Data Analysis

A rapid analytical approach for discrimination and quantitative determination of polyunsaturated fatty acid (PUFA) contents, particularly eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), in a range of oils extracted from marine resources has been developed by using attenuated total reflection Fourier transform infrared spectroscopy and multivariate data analysis. The spectral data were collected without any sample preparation; thus, no chemical preparation was involved, but data were rather processed directly using the developed spectral analysis platform, making it fast, very cost effective, and suitable for routine use in various biotechnological and food research and related industries. Unsupervised pattern recognition techniques, including principal component analysis and unsupervised hierarchical cluster analysis, discriminated the marine oils into groups by correlating similarities and differences in their fatty acid (FA) compositions that corresponded well to the FA profiles obtained from traditional lipid analysis based on gas chromatography (GC). Furthermore, quantitative determination of unsaturated fatty acids, PUFAs, EPA and DHA, by partial least square regression analysis through which calibration models were optimized specifically for each targeted FA, was performed in both known marine oils and totally independent unknown n - 3 oil samples obtained from an actual commercial product in order to provide prospective testing of the developed models towards actual applications. The resultant predicted FAs were achieved at a good accuracy compared to their reference GC values as evidenced through (1) low root mean square error of prediction, (2) good coefficient of determination close to 1 (i.e., R 2≥ 0.96), and (3) the residual predictive deviation values that indicated the predictive power at good and higher levels for all the target FAs. © 2014 Springer Science+Business Media New York.

Dynamic regime marginal structural mean models for estimation of optimal dynamic treatment regimes, Part I: main content

Dynamic treatment regimes are set rules for sequential decision making based on patient covariate history. Observational studies are well suited for the investigation of the effects of dynamic treatment regimes because of the variability in treatment decisions found in them. This variability exists because different physicians make different decisions in the face of similar patient histories. In this article we describe an approach to estimate the optimal dynamic treatment regime among a set of enforceable regimes. This set is comprised by regimes defined by simple rules based on a subset of past information. The regimes in the set are indexed by a Euclidean vector. The optimal regime is the one that maximizes the expected counterfactual utility over all regimes in the set. We discuss assumptions under which it is possible to identify the optimal regime from observational longitudinal data. Murphy et al. (2001) developed efficient augmented inverse probability weighted estimators of the expected utility of one fixed regime. Our methods are based on an extension of the marginal structural mean model of Robins (1998, 1999) which incorporate the estimation ideas of Murphy et al. (2001). Our models, which we call dynamic regime marginal structural mean models, are specially suitable for estimating the optimal treatment regime in a moderately small class of enforceable regimes of interest. We consider both parametric and semiparametric dynamic regime marginal structural models. We discuss locally efficient, double-robust estimation of the model parameters and of the index of the optimal treatment regime in the set. In a companion paper in this issue of the journal we provide proofs of the main results.

Dynamic regime marginal structural mean models for estimation of optimal dynamic treatment regimes, Part II: proofs of results

In this companion article to "Dynamic Regime Marginal Structural Mean Models for Estimation of Optimal Dynamic Treatment Regimes, Part I: Main Content" [Orellana, Rotnitzky and Robins (2010), IJB, Vol. 6, Iss. 2, Art. 7] we present (i) proofs of the claims in that paper, (ii) a proposal for the computation of a confidence set for the optimal index when this lies in a finite set, and (iii) an example to aid the interpretation of the positivity assumption.

An optimized mean variance estimation method for uncertainty quantification of wind power forecasts

A statistical optimized technique for rapid development of reliable prediction intervals (PIs) is presented in this study. The mean-variance estimation (MVE) technique is employed here for quantification of uncertainties related with wind power predictions. In this method, two separate neural network models are used for estimation of wind power generation and its variance. A novel PI-based training algorithm is also presented to enhance the performance of the MVE method and improve the quality of PIs. For an in-depth analysis, comprehensive experiments are conducted with seasonal datasets taken from three geographically dispersed wind farms in Australia. Five confidence levels of PIs are between 50% and 90%. Obtained results show while both traditional and optimized PIs are hypothetically valid, the optimized PIs are much more informative than the traditional MVE PIs. The informativeness of these PIs paves the way for their application in trouble-free operation and smooth integration of wind farms into energy systems. © 2014 Elsevier Ltd. All rights reserved.