Resting energy expenditure in children with inflammatory bowel disease

OBJECTIVES: There is controversy in the literature regarding the effect of inflammatory bowel disease (IBD) on resting energy expenditure (REE). In many cases this may have resulted from inappropriate adjustment of REE measurements to account for differences in body composition. This article considers how to appropriately adjust measurements of REE for differences in body composition between individuals with IBD. PATIENTS AND METHODS: Body composition, assessed via total body potassium to yield a measure of body cell mass (BCM), and REE measurements were performed in 41 children with Crohn disease and ulcerative colitis in the Royal Children's Hospital, Brisbane, Australia. Log-log regression was used to determine the power function to which BCM should be raised to appropriately adjust REE to account for differences in body composition between children. RESULTS: The appropriate value to "adjust" BCM was found to be 0.49, with a standard error of 0.10. CONCLUSIONS: Clearly, there is a need to adjust for differences in body composition, or at the very least body weight, in metabolic studies in children with IBD. We suggest that raising BCM to the power of 0.5 is both a numerically convenient and a statistically valid way of achieving this aim. Under circumstances in which the measurement of BCM is not available, raising body weight to the power of 0.5 remains appropriate. The important issue of whether REE is changed in cases of IBD can then be appropriately addressed. © 2007 Lippincott Williams & Wilkins, Inc.

Using Lifespan developmental theory and methods as a viable alternative to the study of generational differences at work

I agree with Costanza and Finkelstein (2015) that it is futile to further invest in the study of generational differences in the work context due to a lack of appropriate theory and methods. The key problem with the generations concept is that splitting continuous variables such as age or time into a few discrete units involves arbitrary cutoffs and atheoretical groupings of individuals (e.g., stating that all people born between the early 1960s and early 1980s belong to Generation X). As noted by methodologists, this procedure leads to a loss of information about individuals and reduced statistical power (MacCallum, Zhang, Preacher, & Rucker, 2002). Due to these conceptual and methodological limitations, I regard it as very difficult if not impossible to develop a “comprehensive theory of generations” (Costanza & Finkelstein, p. 20) and to rigorously examine generational differences at work in empirical studies.

Comparison of treatment effect sizes associated with surrogate and final patient relevant outcomes in randomised controlled trials: meta-epidemiological study

Objective To quantify and compare the treatment effect and risk of bias of trials reporting biomarkers or intermediate outcomes (surrogate outcomes) versus trials using final patient relevant primary outcomes. Design Meta-epidemiological study. Data sources All randomised clinical trials published in 2005 and 2006 in six high impact medical journals: Annals of Internal Medicine, BMJ, Journal of the American Medical Association, Lancet, New England Journal of Medicine, and PLoS Medicine. Study selection Two independent reviewers selected trials. Data extraction Trial characteristics, risk of bias, and outcomes were recorded according to a predefined form. Two reviewers independently checked data extraction. The ratio of odds ratios was used to quantify the degree of difference in treatment effects between the trials using surrogate outcomes and those using patient relevant outcomes, also adjusted for trial characteristics. A ratio of odds ratios >1.0 implies that trials with surrogate outcomes report larger intervention effects than trials with patient relevant outcomes. Results 84 trials using surrogate outcomes and 101 using patient relevant outcomes were considered for analyses. Study characteristics of trials using surrogate outcomes and those using patient relevant outcomes were well balanced, except for median sample size (371 v 741) and single centre status (23% v 9%). Their risk of bias did not differ. Primary analysis showed trials reporting surrogate endpoints to have larger treatment effects (odds ratio 0.51, 95% confidence interval 0.42 to 0.60) than trials reporting patient relevant outcomes (0.76, 0.70 to 0.82), with an unadjusted ratio of odds ratios of 1.47 (1.07 to 2.01) and adjusted ratio of odds ratios of 1.46 (1.05 to 2.04). This result was consistent across sensitivity and secondary analyses. Conclusions Trials reporting surrogate primary outcomes are more likely to report larger treatment effects than trials reporting final patient relevant primary outcomes. This finding was not explained by differences in the risk of bias or characteristics of the two groups of trials.

Impact of malnutrition on 12-month mortality following acute hip fracture

Background Studies investigating the relationship between malnutrition and post-discharge mortality following acute hip fracture yield conflicting results. This study aimed to determine whether malnutrition independently predicted 12-month post-fracture mortality after adjusting for clinically relevant covariates. Methods An ethics approved, prospective, consecutive audit was undertaken for all surgically treated hip fracture inpatients admitted to a dedicated orthogeriatric unit (November 2010–October 2011). The 12-month mortality data were obtained by a dual search of the mortality registry and Queensland Health database. Malnutrition was evaluated using the Subjective Global Assessment. Demographic (age, gender, admission residence) and clinical covariates included fracture type, time to surgery, anaesthesia type, type of surgery, post-surgery time to mobilize and post-operative complications (delirium, pulmonary and deep vein thrombosis, cardiac complications, infections). The Charlson Comorbidity Index was retrospectively applied. All diagnoses were confirmed by the treating orthogeriatrician. Results A total of 322 of 346 patients were available for audit. Increased age (P = 0.004), admission from residential care (P < 0.001), Charlson Comorbidity Index (P = 0.007), malnutrition (P < 0.001), time to mobilize >48 h (P < 0.001), delirium (P = 0.003), pulmonary embolism (P = 0.029) and cardiovascular complication (P = 0.04) were associated with 12-month mortality. Logistic regression analysis demonstrated that malnutrition (odds ratio (OR) 2.4 (95% confidence interval (CI) 1.3–4.7, P = 0.007)), in addition to admission from residential care (OR 2.6 (95% CI 1.3–5.3, P = 0.005)) and pulmonary embolism (OR 11.0 (95% CI 1.5–78.7, P = 0.017)), independently predicted 12-month mortality. Conclusions Findings substantiate malnutrition as an independent predictor of 12-month mortality in a representative sample of hip fracture inpatients. Effective strategies to identify and treat malnutrition in hip fracture should be prioritized.

Valence and spatial explanations for voting in the 2013 Australian election

This paper examines the 2013 Australian federal election to test two competing models of vote choice: spatial politics and valence issues. Using data from the 2013 Australian Election Study, the analysis finds that spatial politics (measured by party identification and self-placement on the left-right spectrum) and valence issues both have significant effects on vote choice. However, spatial measures are more important than valence issues in explaining vote choice, in contrast with recent studies from Britain, Canada and the United States. Explanations for these differences are speculative, but may relate to Australia’s stable party and electoral system, including compulsory voting and the frequency of elections. The consequently high information burden faced by Australian voters may lead to a greater reliance on spatial heuristics than is found elsewhere.