Leisure-time physical activity volume, intensity, and duration from mid-to late-life in U.S. subpopulations by race and sex. The Atherosclerosis Risk in communities (ARIC) study

Mitigating age-related disease and disability presents challenges. Physical activity (PA) may be influential for prolonging health and functioning, warranting characterization of its patterns over the life course in population-based data. With the availability of up to three self-reported assessments of past year leisuretime PA (LTPA) over multiple decades in 15,036 participants (26% African American; 55% women; mean baseline age=54; median follow-up=23 years) from the Atherosclerosis Risk in Communities (ARIC) Study sampled from four U.S. communities, race-sex-stratified trajectories of average weekly intensity (metabolic equivalent of task (MET), duration (hours), and energy expenditure or volume (MET-h) of LTPA were developed from age 45 to 90 using joint models to accommodate expected non-ignorable attrition. Declines in weekly LTPA intensity, duration, and volume from age 70 to 90 were observed in white women (2.9 to 1.2 MET; 2.5 to 0.6 h; 11.1 to 2.6 MET-h), white men (2.5 to 1.0 MET; 3.5 to 1.8 h; 15.5 to 6.4 MET-h), African American women (2.5 to 2.4 MET; 0.8 to 0.1 h; 6.7 to 6.0 MET-h), and African American men (2.3 to 1.4 MET; 1.5 to 0.6 h; 8.0 to 2.3 MET-h). These data reveal population-wide shifts towards less active lifestyles in older adulthood

Targeting physical activity interventions for adults: When should intervention occur?

Understanding demographic differences in transitions across physical activity (PA) levels is important for informing PA-promoting interventions, yet few studies have examined these transitions in contemporary multi-ethnic adult populations. We estimated age-, race/ethnicity-, and sex-specific 1-year net transition probabilities (NTPs) for National Health and Nutrition Examination Survey (2007–2012, n = 11,556) and Hispanic Community Health Study/Study of Latinos (2008–2011, n = 15,585) adult participants using novel Markov-type state transition models developed for cross-sectional data. Among populations with ideal PA (≥ 150 min/week; ranging from 56% (non-Hispanic black females) to 88% (non-Hispanic white males) at age 20), NTPs to intermediate PA (> 0–<149 min/week) generally increased with age, particularly for non-Hispanic black females for whom a net 0.0% (95% confidence interval (CI): 0.0, 0.2) transitioned from ideal to intermediate PA at age 20; by age 70, the NTP rose to 3.6% (95% CI: 2.3, 4.8). Heterogeneity in intermediate to poor (0 min/week) PA NTPs also was observed, with NTPs peaking at age 20 for Hispanic/Latino males and females [age 20 NTP = 3.7% (95% CI: 2.0, 5.5) for females and 5.0% (1.2, 8.7) for males], but increasing throughout adulthood for non-Hispanic blacks and whites [e.g. age 70 NTP = 7.8% (95% CI: 6.1, 9.6%) for black females and 8.1% (4.7, 11.6) for black males]. Demographic differences in PA net transitions across adulthood justify further development of tailored interventions. However, innovative efforts may be required for populations in which large proportions have already transitioned from ideal PA by early adulthood

A phenome-wide association study (PheWAS) in the Population Architecture using Genomics and Epidemiology (PAGE) study reveals potential pleiotropy in African Americans

We performed a hypothesis-generating phenome-wide association study (PheWAS) to identify and characterize cross-phenotype associations, where one SNP is associated with two or more phenotypes, between thousands of genetic variants assayed on the Metabochip and hundreds of phenotypes in 5,897 African Americans as part of the Population Architecture using Genomics and Epidemiology (PAGE) I study. The PAGE I study was a National Human Genome Research Institute-funded collaboration of four study sites accessing diverse epidemiologic studies genotyped on the Metabochip, a custom genotyping chip that has dense coverage of regions in the genome previously associated with cardio- metabolic traits and outcomes in mostly European-descent populations. Here we focus on identifying novel phenome-genome relationships, where SNPs are associated with more than one phenotype. To do this, we performed a PheWAS, testing each SNP on the Metabochip for an association with up to 273 phenotypes in the participating PAGE I study sites. We identified 133 putative pleiotropic variants, defined as SNPs associated at an empirically derived p-value threshold of p<0.01 in two or more PAGE study sites for two or more phenotype classes. We further annotated these PheWAS-identified variants using publicly available functional data and local genetic ancestry. Amongst our novel findings is SPARC rs4958487, associated with increased glucose levels and hypertension. SPARC has been implicated in the pathogenesis of diabetes and is also known to have a potential role in fibrosis, a common consequence of multiple conditions including hypertension. The SPARC example and others highlight the potential that PheWAS approaches have in improving our understanding of complex disease architecture by identifying novel relationships between genetic variants and an array of common human phenotypes

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

The relationship between body mass index and health-related quality of life: comparing the EQ-5D, EuroQol VAS and SF-6D

Background: no other studies have compared the relationship between body mass index (BMI) and health-related quality of life (HRQL) on more than one utility measure. Estimating the HRQL effects of obesity on a (common) utility scale enables the relative cost-effectiveness of interventions designed to alleviate obesity to be estimated.Objective: to examine the relationship between BMI and HRQL according to the EQ-5D, EuroQol visual analogue scale (EQ-VAS) and SF-6D.Methods: patients aged &gt;/=45 years at one UK general practice were asked to complete the EQ-5D, EQ-VAS, SF-36 questionnaire (used to derive the SF-6D), and information on their characteristics and co-morbidity. Body mass index was categorized according to the World Health Organization (WHO) recommendations. Regression analysis was used to compare the HRQL of normal BMI patients to the HRQL of patients in other BMI categories, while controlling for patient characteristics and co-morbidity.Results: a total of 1865 patients responded (67%), mean BMI 26.0 kg/m(2), 16% obese (BMI&gt;/=30). Patients with back pain, hip pain, knee pain, asthma, diabetes or osteoarthritis were also significantly more likely to be obese. After controlling for other factors, compared to normal BMI patients, obese patients had a lower HRQL according to the EQ-5D (P&lt;0.01), EQ-VAS (P&lt;0.001) and SF-6D (P&lt;0.001). Pre-obese patients were not estimated to have a significantly lower HRQL, and underweight patients were only estimated to have a significantly lower HRQL according to the SF-6D. These results arose because, on the EQ-5D, obese patients were found to have significantly more problems with mobility and pain, compared to physical functioning, social functioning and role limitations on the SF-6D. Whereas, according to the SF-6D, underweight patients had significantly more problems on the dimension of role limitation.Conclusions: the EQ-5D, EQ-VAS and SF-6D were in agreement that, relative to a normal BMI, obesity is associated with a lower HRQL, even after controlling for patient characteristics and co-morbidity. These three measures are thereby sensitive to the HRQL effects of obesity and can be used to estimate the cost-effectiveness of interventions designed to alleviate obesity.</p