A SaTScan™ Macro Accessory for Cartography (SMAC) Package Implemented with SAS® Software

Background: SaTScan is a software program written to implement the scan statistic; it can be used to find clusters in space and/or time. It must often be run multiple times per day when doing disease surveillance. Running SaTScan frequently via its graphical user interface can be cumbersome, and the output can be difficult to visualize. Results: The SaTScan Macro Accessory for Cartography (SMAC) package consists of four SAS macros and was designed as an easier way to run SaTScan multiple times and add graphical output. The package contains individual macros which allow the user to make the necessary input files for SaTScan, run SaTScan, and create graphical output all from within SAS software. The macros can also be combined to do this all in one step. Conclusion: The SMAC package can make SaTScan easier to use and can make the output more informative

Consumers’ estimation of calorie content at fast food restaurants: cross sectional observational study

Objective: To investigate estimation of calorie (energy) content of meals from fast food restaurants in adults, adolescents, and school age children. Design: Cross sectional study of repeated visits to fast food restaurant chains. Setting: 89 fast food restaurants in four cities in New England, United States: McDonald’s, Burger King, Subway, Wendy’s, KFC, Dunkin’ Donuts. Participants: 1877 adults and 330 school age children visiting restaurants at dinnertime (evening meal) in 2010 and 2011; 1178 adolescents visiting restaurants after school or at lunchtime in 2010 and 2011. Main outcome measure Estimated calorie content of purchased meals. Results: Among adults, adolescents, and school age children, the mean actual calorie content of meals was 836 calories (SD 465), 756 calories (SD 455), and 733 calories (SD 359), respectively. A calorie is equivalent to 4.18 kJ. Compared with the actual figures, participants underestimated calorie content by means of 175 calories (95% confidence interval 145 to 205), 259 calories (227 to 291), and 175 calories (108 to 242), respectively. In multivariable linear regression models, underestimation of calorie content increased substantially as the actual meal calorie content increased. Adults and adolescents eating at Subway estimated 20% and 25% lower calorie content than McDonald’s diners (relative change 0.80, 95% confidence interval 0.66 to 0.96; 0.75, 0.57 to 0.99). Conclusions: People eating at fast food restaurants underestimate the calorie content of meals, especially large meals. Education of consumers through calorie menu labeling and other outreach efforts might reduce the large degree of underestimation

Using Automated Health Plan Data to Assess Infection Risk from Coronary Artery Bypass Surgery

We determined if infection indicators were sufficiently consistent across health plans to allow comparison of hospitals’ risks of infection after coronary artery bypass surgery. Three managed care organizations accounted for 90% of managed care in eastern Massachusetts, from October 1996 through March 1999. We searched automated inpatient and outpatient claims and outpatient pharmacy dispensing files for indicator codes suggestive of postoperative surgical site infection. We reviewed full text medical records of patients with indicator codes to confirm infection status. We compared the hospital-specific proportions of cases with an indicator code, adjusting for health plan, age, sex, and chronic disease score. A total of 536 (27%) of 1,953 patients had infection indicators. Infection was confirmed in 79 (53%) of 149 reviewed records with adequate documentation. The proportion of patients with an indicator of infection varied significantly (p<0.001) between hospitals (19% to 36%) and health plans (22% to 33%). The difference between hospitals persisted after adjustment for health plan and patients’ age and sex. Similar relationships were observed when postoperative antibiotic information was ignored. Automated claims and pharmacy data from different health plans can be used together to allow inexpensive, routine monitoring of indicators of postoperative infection, with the goal of identifying institutions that can be further evaluated to determine if risks for infection can be reduced

Hidden in the Middle : Culture, Value and Reward in Bioinformatics

Bioinformatics - the so-called shotgun marriage between biology and computer science - is an interdiscipline. Despite interdisciplinarity being seen as a virtue, for having the capacity to solve complex problems and foster innovation, it has the potential to place projects and people in anomalous categories. For example, valorised 'outputs' in academia are often defined and rewarded by discipline. Bioinformatics, as an interdisciplinary bricolage, incorporates experts from various disciplinary cultures with their own distinct ways of working. Perceived problems of interdisciplinarity include difficulties of making explicit knowledge that is practical, theoretical, or cognitive. But successful interdisciplinary research also depends on an understanding of disciplinary cultures and value systems, often only tacitly understood by members of the communities in question. In bioinformatics, the 'parent' disciplines have different value systems; for example, what is considered worthwhile research by computer scientists can be thought of as trivial by biologists, and vice versa. This paper concentrates on the problems of reward and recognition described by scientists working in academic bioinformatics in the United Kingdom. We highlight problems that are a consequence of its cross-cultural make-up, recognising that the mismatches in knowledge in this borderland take place not just at the level of the practical, theoretical, or epistemological, but also at the cultural level too. The trend in big, interdisciplinary science is towards multiple authors on a single paper; in bioinformatics this has created hybrid or fractional scientists who find they are being positioned not just in-between established disciplines but also in-between as middle authors or, worse still, left off papers altogether

Genomic analysis of male puberty timing highlights shared genetic basis with hair colour and lifespan

Abstract: The timing of puberty is highly variable and is associated with long-term health outcomes. To date, understanding of the genetic control of puberty timing is based largely on studies in women. Here, we report a multi-trait genome-wide association study for male puberty timing with an effective sample size of 205,354 men. We find moderately strong genomic correlation in puberty timing between sexes (rg = 0.68) and identify 76 independent signals for male puberty timing. Implicated mechanisms include an unexpected link between puberty timing and natural hair colour, possibly reflecting common effects of pituitary hormones on puberty and pigmentation. Earlier male puberty timing is genetically correlated with several adverse health outcomes and Mendelian randomization analyses show a genetic association between male puberty timing and shorter lifespan. These findings highlight the relationships between puberty timing and health outcomes, and demonstrate the value of genetic studies of puberty timing in both sexes

Estimation of Newborn Risk for Child or Adolescent Obesity: Lessons from Longitudinal Birth Cohorts

Objectives: Prevention of obesity should start as early as possible after birth. We aimed to build clinically useful equations estimating the risk of later obesity in newborns, as a first step towards focused early prevention against the global obesity epidemic. Methods: We analyzed the lifetime Northern Finland Birth Cohort 1986 (NFBC1986) (N = 4,032) to draw predictive equations for childhood and adolescent obesity from traditional risk factors (parental BMI, birth weight, maternal gestational weight gain, behaviour and social indicators), and a genetic score built from 39 BMI/obesity-associated polymorphisms. We performed validation analyses in a retrospective cohort of 1,503 Italian children and in a prospective cohort of 1,032 U.S. children. Results: In the NFBC1986, the cumulative accuracy of traditional risk factors predicting childhood obesity, adolescent obesity, and childhood obesity persistent into adolescence was good: AUROC = 0·78[0·74–0.82], 0·75[0·71–0·79] and 0·85[0·80–0·90] respectively (all p<0·001). Adding the genetic score produced discrimination improvements ≤1%. The NFBC1986 equation for childhood obesity remained acceptably accurate when applied to the Italian and the U.S. cohort (AUROC = 0·70[0·63–0·77] and 0·73[0·67–0·80] respectively) and the two additional equations for childhood obesity newly drawn from the Italian and the U.S. datasets showed good accuracy in respective cohorts (AUROC = 0·74[0·69–0·79] and 0·79[0·73–0·84]) (all p<0·001). The three equations for childhood obesity were converted into simple Excel risk calculators for potential clinical use. Conclusion: This study provides the first example of handy tools for predicting childhood obesity in newborns by means of easily recorded information, while it shows that currently known genetic variants have very little usefulness for such prediction

Risk threshold and predictive properties corresponding to the 75° percentile of calculated risk for the obesity phenotypes in the NFBC1986.

<p>Risk threshold and predictive properties corresponding to the 75° percentile of calculated risk for the obesity phenotypes in the NFBC1986.</p

Characteristics of the NFBC1986 cohort.

<p>Data are given as MEAN (range) or as N (percentage).</p

Estimates of risk percentages for childhood obesity for given pairs of parental BMIs according to the NFBC1986 equation.

<p>Estimates are provided for three different combinations of birth weight, maternal professional category, number of household members and maternal gestational smoking, corresponding to three progressively higher risk backgrounds. Grey cells correspond to risk estimates within the highest risk quartile in the overall population.</p