Andrew Brown

Dr. Andrew Brown

orcid

Research Focus & Metrics

Academic Career Length

19Years (2008-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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27 February 2017 in BMJ Open
Verified
Journal Article
Open access
PDF file
RBRohit Borah
Rohit Borah
ABAndrew Brown
Andrew Brown
PCPatrice L Capers
Patrice L Capers
KKKathryn A Kaiser
Kathryn A Kaiser
Objectives To summarise logistical aspects of recently completed systematic reviews that were registered in the International Prospective Register of Systematic Reviews (PROSPERO) registry to quantify the time and resources required to complete such projects. Design Meta-analysis. Data sources and study selection All of the 195 registered and completed reviews (status from the PROSPERO registry) with associated publications at the time of our search (1 July 2014). Data extraction All authors extracted data using registry entries and publication information related to the data sources used, the number of initially retrieved citations, the final number of included studies, the time between registration date to publication date and number of authors involved for completion of each publication. Information related to funding and geographical location was also recorded when reported. Results The mean estimated time to complete the project and publish the review was 67.3 weeks (IQR=42). The number of studies found in the literature searches ranged from 27 to 92 020; the mean yield rate of included studies was 2.94% (IQR=2.5); and the mean number of authors per review was 5, SD=3. Funded reviews took significantly longer to complete and publish (mean=42 vs 26 weeks) and involved more authors and team members (mean=6.8 vs 4.8 people) than those that did not report funding (both p<0.001). Conclusions Systematic reviews presently take much time and require large amounts of human resources. In the light of the ever-increasing volume of published studies, application of existing computing and informatics technology should be applied to decrease this time and resource burden. We discuss recently published guidelines that provide a framework to make finding and accessing relevant literature less burdensome.

13 November 2014 in International Journal of Obesity
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Journal Article
Closed access
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NDN V Dhurandhar
N V Dhurandhar
DSDale Schoeller
Dale Schoeller
ABAndrew Brown
Andrew Brown
SHSteven Heymsfield
Steven Heymsfield
DTDiana M Thomas
Diana M Thomas
TGthe Energy Balance Measurement Working Group
the Energy Balance Measurement Working Group

27 August 2019 in Addiction
Verified
Journal Article
Closed access
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SLSara Lappan
Sara Lappan
ABAndrew Brown
Andrew Brown
PHPeter S. Hendricks
Peter S. Hendricks

31 January 2013 in New England Journal of Medicine
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Journal Article
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KCKrista Casazza
Krista Casazza
KFKevin R. Fontaine
Kevin R. Fontaine
AAArne Astrup
Arne Astrup
LBLeann L. Birch
Leann L. Birch
ABAndrew Brown
Andrew Brown
DADavid B. Allison
David B. Allison
Many beliefs about obesity persist in the absence of supporting scientific evidence (presumptions); some persist despite contradicting evidence (myths). The promulgation of unsupported beliefs may yield poorly informed policy decisions, inaccurate clinical and public health recommendations, and an unproductive allocation of research resources and may divert attention away from useful, evidence-based information. Using Internet searches of popular media and scientific literature, we identified, reviewed, and classified obesity-related myths and presumptions. We also examined facts that are well supported by evidence, with an emphasis on those that have practical implications for public health, policy, or clinical recommendations. We identified seven obesity-related myths concerning the effects of small sustained increases in energy intake or expenditure, establishment of realistic goals for weight loss, rapid weight loss, weight-loss readiness, physical-education classes, breast-feeding, and energy expended during sexual activity. We also identified six presumptions about the purported effects of regularly eating breakfast, early childhood experiences, eating fruits and vegetables, weight cycling, snacking, and the built (i.e., human-made) environment. Finally, we identified nine evidence-supported facts that are relevant for the formulation of sound public health, policy, or clinical recommendations. False and scientifically unsupported beliefs about obesity are pervasive in both scientific literature and the popular press. (Funded by the National Institutes of Health.)

3 February 2016 in Nature
Verified
Journal Article
Closed access
DADavid B. Allison
David B. Allison
ABAndrew Brown
Andrew Brown
BGBrandon J. George
Brandon J. George
KKKathryn A. Kaiser
Kathryn A. Kaiser

21 October 2015 in PLOS ONE
Verified
Journal Article
Open access
PDF file
GFGordon Fisher
Gordon Fisher
ABAndrew Brown
Andrew Brown
MBMichelle M. Bohan Brown
Michelle M. Bohan Brown
AAAmy Alcorn
Amy Alcorn
CNCorey Noles
Corey Noles
DADavid B. Allison
David B. Allison
To compare the effects of six weeks of high intensity interval training (HIIT) vs continuous moderate intensity training (MIT) for improving body composition, insulin sensitivity (SI), blood pressure, blood lipids, and cardiovascular fitness in a cohort of sedentary overweight or obese young men. We hypothesized that HIIT would result in similar improvements in body composition, cardiovascular fitness, blood lipids, and SI as compared to the MIT group, despite requiring only one hour of activity per week compared to five hours per week for the MIT group. 28 sedentary overweight or obese men (age, 20 ± 1.5 years, body mass index 29.5 ± 3.3 kg/m2) participated in a six week exercise treatment. Participants were randomly assigned to HIIT or MIT and evaluated at baseline and post-training. DXA was used to assess body composition, graded treadmill exercise test to measure cardiovascular fitness, oral glucose tolerance to measure SI, nuclear magnetic resonance spectroscopy to assess lipoprotein particles, and automatic auscultation to measure blood pressure. A greater improvement in VO2peak was observed in MIT compared to HIIT (11.1% vs 2.83%, P = 0.0185) in the complete-case analysis. No differences were seen in the intention to treat analysis, and no other group differences were observed. Both exercise conditions were associated with temporal improvements in % body fat, total cholesterol, medium VLDL, medium HDL, triglycerides, SI, and VO2peak (P < 0.05). Participation in HIIT or MIT exercise training displayed: 1) improved SI, 2) reduced blood lipids, 3) decreased % body fat, and 4) improved cardiovascular fitness. While both exercise groups led to similar improvements for most cardiometabolic risk factors assessed, MIT led to a greater improvement in overall cardiovascular fitness. Overall, these observations suggest that a relatively short duration of either HIIT or MIT training may improve cardiometabolic risk factors in previously sedentary overweight or obese young men, with no clear advantage between these two specific regimes (Clinical Trial Registry number NCT01935323). ClinicalTrials.gov NCT01935323