Intracule functional models. IV. Basis set effects

We have calculated position and dot intracules for a series of atomic and molecular systems, starting from an unrestricted Hartree-Fock wave function, expanded using the STO-3G, 6-31G, 6-311G, 6-311++G, 6-311++G(d,p), 6-311++G(3d,3p), and 6-311++G(3df,3pd) basis sets as well as the nonpolarized part of Dunning's cc-pV5Z basis. We find that the basis set effects on the intracules are small and that correlation energies from the dot intracule ansatz are remarkably insensitive to the basis set quality. Mean absolute errors in correlation energies across the G1 data set agree to within 2 mE(h) for all basis sets tested.P.M.W.G. thanks the APAC Merit Allocation Scheme for a generous grant of supercomputer resources and the Australian Research Council Grant Nos. DP0664466 and DP0771978 for funding

Increasing physical activity in older adults using STARFISH, an interactive smartphone application (app); a pilot study

Background:Increasing physical activity in older adults has preventative and therapeutic health benefits. We have developed STARFISH, a smartphone application, to increase physical activity. This paper describes the features of STARFISH, presents the views of older users on the acceptability and usability of the app and reports the results of a six week pilot study of the STARFISH app in older adults. Methods:The operationalisation of the behaviour change techniques (BCTs) within the STARFISH app was mapped against the BCT Taxonomy of Michie et al. Sixteen healthy older adults (eight women and eight men; age 71.1 ± 5.2 years) used the app, in groups of four, for six weeks. Focus groups explored the user experience and objective measure of steps per day recorded. Results:Participants were very positive about using the STARFISH app, in particular the embedded BCTs of self-monitoring, feedback and social support (in the form of group rewards). Objective step data, available for eight participants, showed that step counts increased by an average of 14% (p = 0.077, d = 0.56). Conclusion:The STARFISH app was acceptable and straightforward to use for older adults. STARFISH has potential to increase physical activity in older adults; however, a fully powered randomised controlled trial is required

Effects of diabetes family history and exercise training on the expression of adiponectin and leptin and their receptors

The daughters of patients with diabetes have reduced insulin sensitivity index (ISI) scores compared with women with no family history of diabetes, but their ISI increase more in response to exercise training(1). The present study aimed to determine whether differences between these groups in exercise-induced changes in circulating adiponectin and leptin concentrations and expression of their genes and receptors in subcutaneous adipose tissue (SAT), could explain differences in the exercise-induced changes in ISI between women with and without a family history of diabetes

Prospective relationships between body weight and physical activity: an observational analysis from the NAVIGATOR study

Objectives: While bidirectional relationships exist between body weight and physical activity, direction of causality remains uncertain and previous studies have been limited by self-reported activity or weight and small sample size. We investigated the prospective relationships between weight and physical activity. Design: Observational analysis of data from the Nateglinide And Valsartan in Impaired Glucose Tolerance Outcomes Research (NAVIGATOR) study, a double-blinded randomised clinical trial of nateglinide and valsartan, respectively. Setting Multinational study of 9306 participants. Participants: Participants with biochemically confirmed impaired glucose tolerance had annual measurements of both weight and step count using research grade pedometers, worn for 7 days consecutively. Along with randomisation to valsartan or placebo plus nateglinide or placebo, participants took part in a lifestyle modification programme. Outcome measures: Longitudinal regression using weight as response value and physical activity as predictor value was conducted, adjusted for baseline covariates. Analysis was then repeated with physical activity as response value and weight as predictor value. Only participants with a response value preceded by at least three annual response values were included. Results: Adequate data were available for 2811 (30%) of NAVIGATOR participants. Previous weight (χ2=16.8; p<0.0001), but not change in weight (χ2=0.1; p=0.71) was inversely associated with subsequent step count, indicating lower subsequent levels of physical activity in heavier individuals. Change in step count (χ2=5.9; p=0.02) but not previous step count (χ2=0.9; p=0.34) was inversely associated with subsequent weight. However, in the context of trajectories already established for weight (χ2 for previous weight measurements 747.3; p<0.0001) and physical activity (χ2 for previous step count 432.6; p<0.0001), these effects were of limited clinical importance. Conclusions: While a prospective bidirectional relationship was observed between weight and physical activity, the magnitude of any effect was very small in the context of natural trajectories already established for these variables

The impact of confounding on the associations of different adiposity measures with the incidence of cardiovascular disease: a cohort study of 296 535 adults of white European descent

Aims: The data regarding the associations of body mass index (BMI) with cardiovascular (CVD) risk, especially for those at the low categories of BMI, are conflicting. The aim of our study was to examine the associations of body composition (assessed by five different measures) with incident CVD outcomes in healthy individuals. Methods and results: A total of 296 535 participants (57.8% women) of white European descent without CVD at baseline from the UK biobank were included. Exposures were five different measures of adiposity. Fatal and non-fatal CVD events were the primary outcome. Low BMI (≤18.5 kg m−2) was associated with higher incidence of CVD and the lowest CVD risk was exhibited at BMI of 22–23 kg m−2 beyond, which the risk of CVD increased. This J-shaped association attenuated substantially in subgroup analyses, when we excluded participants with comorbidities. In contrast, the associations for the remaining adiposity measures were more linear; 1 SD increase in waist circumference was associated with a hazard ratio of 1.16 [95% confidence interval (CI) 1.13–1.19] for women and 1.10 (95% CI 1.08–1.13) for men with similar magnitude of associations for 1 SD increase in waist-to-hip ratio, waist-to-height ratio, and percentage body fat mass. Conclusion: Increasing adiposity has a detrimental association with CVD health in middle-aged men and women. The association of BMI with CVD appears more susceptible to confounding due to pre-existing comorbidities when compared with other adiposity measures. Any public misconception of a potential ‘protective’ effect of fat on CVD risk should be challenged

Sleep characteristics modify the association between genetic predisposition to obesity and anthropometric measurements in 119,679 UK Biobank participants

Background - Obesity is a multifactorial condition influenced by genetics, lifestyle and environment. Objective - To investigate whether the association between a validated genetic profile risk score for obesity (GPRS-obesity) with body mass index (BMI) and waist circumference (WC) was modified by sleep characteristics. Design - This study included cross-sectional data from 119,859 white European adults, aged 37-73 years, participating on the UK Biobank. Interactions between GPRS-obesity, and sleep characteristics (sleep duration, chronotype, day napping, and shift work) in their effects on BMI and WC were investigated. Results - The GPRS-obesity was associated with BMI (β:0.57 kg.m-2 per standard deviation (SD) increase in GPRS, [95%CI:0.55, 0.60]; P=6.3x10-207) and WC (β:1.21 cm, [1.15, 1.28]; P=4.2x10-289). There were significant interactions between GPRS-obesity and a variety of sleep characteristics in their relationship with BMI (P-interaction <0.05). In participants who slept <7 hrs or >9 hrs daily, the effect of GPRS-obesity on BMI was stronger (β:0.60 [0.54, 0.65] and 0.73 [0.49, 0.97] kg.m-2 per SD increase in GPRS, respectively) than in normal length sleepers (7-9 hours; β:0.52 [0.49, 0.55] kg.m-2 per SD). A similar pattern was observed for shiftworkers (β:0.68 [0.59, 0.77] versus 0.54 [0.51, 0.58] kg.m-2 for non-shiftworkers) and for night-shiftworkers (β:0.69 [0.56, 0.82] versus 0.55 [0.51, 0.58] kg.m-2 for non-night- shiftworkers), for those taking naps during the day (β:0.65 [0.52, 0.78] versus 0.51 [0.48, 0.55] kg.m-2 for those who never/rarely had naps) and for those with a self-reported evening chronotype (β:0.72 [0.61, 0.82] versus β:0.52 [0.47, 0.57] kg.m-2 for morning chronotype). Similar findings were obtained using WC as the outcome. Conclusions – This study shows that the association between genetic risk for obesity and phenotypic adiposity measures is exacerbated by adverse sleeping characteristics

Association between active commuting and incident cardiovascular disease, cancer, and mortality: prospective cohort study

Objective: To investigate the association between active commuting and incident cardiovascular disease (CVD), cancer, and all cause mortality. Design: Prospective population based study. Setting: UK Biobank. Participants: 263 450 participants (106 674 (52%) women; mean age 52.6), recruited from 22 sites across the UK. The exposure variable was the mode of transport used (walking, cycling, mixed mode v non-active (car or public transport)) to commute to and from work on a typical day. Main outcome measures: Incident (fatal and non-fatal) CVD and cancer, and deaths from CVD, cancer, or any causes. Results: 2430 participants died (496 were related to CVD and 1126 to cancer) over a median of 5.0 years (interquartile range 4.3-5.5) follow-up. There were 3748 cancer and 1110 CVD events. In maximally adjusted models, commuting by cycle and by mixed mode including cycling were associated with lower risk of all cause mortality (cycling hazard ratio 0.59, 95% confidence interval 0.42 to 0.83, P=0.002; mixed mode cycling 0.76, 0.58 to 1.00, P<0.05), cancer incidence (cycling 0.55, 0.44 to 0.69, P<0.001; mixed mode cycling 0.64, 0.45 to 0.91, P=0.01), and cancer mortality (cycling 0.60, 0.40 to 0.90, P=0.01; mixed mode cycling 0.68, 0.57 to 0.81, P<0.001). Commuting by cycling and walking were associated with a lower risk of CVD incidence (cycling 0.54, 0.33 to 0.88, P=0.01; walking 0.73, 0.54 to 0.99, P=0.04) and CVD mortality (cycling 0.48, 0.25 to 0.92, P=0.03; walking 0.64, 0.45 to 0.91, P=0.01). No statistically significant associations were observed for walking commuting and all cause mortality or cancer outcomes. Mixed mode commuting including walking was not noticeably associated with any of the measured outcomes. Conclusions: Cycle commuting was associated with a lower risk of CVD, cancer, and all cause mortality. Walking commuting was associated with a lower risk of CVD independent of major measured confounding factors. Initiatives to encourage and support active commuting could reduce risk of death and the burden of important chronic conditions

Reliability, minimal detectable change and responsiveness to change: indicators to select the best method to measure sedentary behaviour in older adults in different study designs

Introduction : Prolonged sedentary behaviour (SB) is associated with poor health. It is unclear which SB measure is most appropriate for interventions and population surveillance to measure and interpret change in behaviour in older adults. The aims of this study: to examine the relative and absolute reliability, Minimal Detectable Change (MDC) and responsiveness to change of subjective and objective methods of measuring SB in older adults and give recommendations of use for different study designs. Methods : SB of 18 older adults (aged 71 (IQR 7) years) was assessed using a systematic set of six subjective tools, derived from the TAxonomy of Self report Sedentary behaviour Tools (TASST), and one objective tool (activPAL3c), over 14 days. Relative reliability (Intra Class Correlation coefficients-ICC), absolute reliability (SEM), MDC, and the relative responsiveness (Cohen's d effect size (ES) and Guyatt's Responsiveness coefficient (GR)) were calculated for each of the different tools and ranked for different study designs. Results : ICC ranged from 0.414 to 0.946, SEM from 36.03 to 137.01 min, MDC from 1.66 to 8.42 hours, ES from 0.017 to 0.259 and GR from 0.024 to 0.485. Objective average day per week measurement ranked as most responsive in a clinical practice setting, whereas a one day measurement ranked highest in quasi-experimental, longitudinal and controlled trial study designs. TV viewing Previous Week Recall (PWR) ranked as most responsive subjective measure in all study designs. Conclusions : The reliability, Minimal Detectable Change and responsiveness to change of subjective and objective methods of measuring SB is context dependent. Although TV viewing-PWR is the more reliable and responsive subjective method in most situations, it may have limitations as a reliable measure of total SB. Results of this study can be used to guide choice of tools for detecting change in sedentary behaviour in older adults in the contexts of population surveillance, intervention evaluation and individual care

Dietary fat and total energy intake modifies the association of genetic profile risk score on obesity: evidence from 48 170 UK Biobank participants

Background: Obesity is a multifactorial condition influenced by both genetics and lifestyle. The aim of this study was to investigate whether the association between a validated genetic profile risk score for obesity (GPRS-obesity) and body mass index (BMI) or waist circumference (WC) was modified by macronutrient intake in a large general population study. Methods: This study included cross-sectional data from 48 170 white European adults, aged 37–73 years, participating on the UK Biobank. Interactions between GPRS-obesity, and macronutrient intake (including total energy, protein, fat, carbohydrate and dietary fibre intake) and its effects on BMI and WC were investigated. Results: The 93-SNPs genetic profile risk score was associated with a higher BMI (β:0.57 kg.m−2 per standard deviation (s.d.) increase in GPRS, [95%CI:0.53–0.60]; P=1.9 × 10−183) independent of major confounding factors. There was a significant interaction between GPRS and total fat intake (P[interaction]=0.007). Among high fat intake individuals, BMI was higher by 0.60 [0.52, 0.67] kg.m−2 per s.d. increase in GPRS-obesity; the change in BMI with GPRS was lower among low fat intake individuals (β:0.50 [0.44, 0.57] kg.m-2). Significant interactions with similar patterns were observed for saturated fat intake (High β:0.66 [0.59, 0.73] versus Low β:0.49 [0.42, 0.55] kg.m-2, P-interaction=2 × 10-4), and total energy intake (High β:0.58 [0.51, 0.64] versus Low β:0.49 [0.42, 0.56] kg.m−2, P-interaction=0.019), but not for protein intake, carbohydrate intake and fiber intake (P-interaction >0.05). The findings were broadly similar using WC as the outcome. Conclusions: These data suggest that the benefits of reducing the intake of fats and total energy intake, may be more important in individuals with high genetic risk for obesity

Associations between diabetes and both cardiovascular disease and all-cause mortality are modified by grip strength: evidence from UK Biobank, a prospective population-based cohort study

OBJECTIVE Grip strength and diabetes are predictors of mortality and cardiovascular disease (CVD), but whether these risk factors interact to predispose to adverse health outcomes is unknown. This study determined the interactions between diabetes and grip strength and their association with health outcomes. RESEARCH DESIGN AND METHODS We undertook a prospective, general population cohort study by using UK Biobank. Cox proportional hazards models were used to explore the associations between both grip strength and diabetes and the outcomes of all-cause mortality and CVD incidence/mortality as well as to test for interactions between diabetes and grip strength. RESULTS 347,130 UK Biobank participants with full data available (mean age 55.9 years, BMI 27.2 kg/m2, 54.2% women) were included in the analysis, of which 13,373 (4.0%) had diabetes. Over a median follow-up of 4.9 years (range 3.3–7.8 years), 6,209 died (594 as a result of CVD), and 4,301 developed CVD. Participants with diabetes were at higher risk of all-cause and CVD mortality and CVD incidence. Significant interactions (P < 0.05) existed whereby the risk of CVD mortality was higher in participants with diabetes with low (hazard ratio [HR] 4.05 [95% CI 2.72, 5.80]) versus high (HR 1.46 [0.87, 2.46]) grip strength. Similar results were observed for all-cause mortality and CVD incidence. CONCLUSIONS Risk of adverse health outcomes among people with diabetes is lower in those with high grip strength. Low grip strength may be useful to identify a higher-risk subgroup of patients with diabetes. Intervention studies are required to determine whether resistance exercise can reduce risk