Catch It Report: - Web based weight loss RCTPresentation Transcript
CATCH-IT Report Bennett GG, Herring SJ, Puleo E, Stein EK, Emmons KM, and Gillman MW. Web-based Weight Loss in Primary Care: A Randomized Controlled Trial. Obesity (2009) doi:10.1038/oby.2009.242 November 16, 2009
Selected for CATCH-IT Review
Recent (published online August 2009)
Personal Interest in Obesity
RCT of Web-Based Intervention
Potential Impact on Policy Makers, Healthcare Providers, Patients
Gary G. Bennett, Ph.D .
Associate professor in the Department of Psychology & Neuroscience at Duke University
Bachelor’s degree in psychology from Morehouse College .
Graduate studies in clinical psychology (with a focus in behavioral medicine) at Duke University .
Internship in clinical health psychology at the Duke University Medical Center
Postdoctoral studies in social epidemiology as an Alonzo Smythe Yerby Research Fellow at the Harvard School of Public Health
Was a faculty member at the Harvard School of Public Health and Dana-Farber Cancer Institute until joining Duke University in January 2009
In 2004, he was named one of Boston's Ten Outstanding Young Leaders.
44 papers cited on PubMed
Sharon J. Herring MD, MPH
Assistant Professor of Medicine and Public Health, Temple University School of Medicine
Research Interests: Pregnancy related weight gain and obesity risk, Obesity prevention in primary care, Health outcomes in women with gestational diabetes mellitus, Psychosocial factors in chronic disease prevention
9 papers cited on PubMed
Associate Dean for Research, University of Massachusetts, School of Public Health and Health Sciences
51 papers cited on PubMed
Puleo E, Zapka JG, Goins KV, Yood MU, Mouchawar J, Manos M, Somkin C, Taplin S. Recommendations for care related to follow-up of abnormal cancer screening tests: accuracy of patient report. Eval Health Prof. 2005 Sep;28(3):310-27.
Puleo E, Zapka J, White MJ, Mouchawar J, Somkin C, Taplin S. Caffeine, cajoling, and other strategies to maximize clinician survey response rates. Eval Health Prof. 2002 Jun;25(2):169-84.
Puleo E, Ory SJ, Christakos AC 45, X/46, XY gonadal dysgenesis. A case report. J Reprod Med. 1983 Mar;28(3):215-6
Evelyn K. Stein
The Center for Community-Based Research, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
Karen M. Emmons, PhD
Professor of Society, Harvard School of Public Health, Human Development and Health
Research Area: Community-Based Cancer Prevention
144 papers cited on PubMed
Matthew W. Gillman, M.D. S.M.
Associate Professor in the HMS Department of Ambulatory Care and Prevention
Research interests: early life prevention of adult chronic disease, optimal nutrition for children and adults, and clinical epidemiology.
178 papers cited on PubMed
CONSORT versus STARE-HI
1/3 US population are obese
Comorbidities represent major challenge to primary care setting
Web-based intervention is low cost, adaptable, scalable and efficacious
Why web-based behaviour counselling?
Reach larger population
Effective for weight loss
Why obese patients with hypertension in primary care
“ Evidence is lacking regarding the utility of web-based weight loss interventions in primary care; this is particularly the case for obese patients with hypertension—a population responsible for a large proportion of primary care patient visits” (Ref 19 ).
Reference 19 Burt C, McCaig L, Rechtsteiner E . Ambulatory medical care utilization estimates for 2005. Advance data from vital and health statistics. Hyattsville, MD: National Center for Health Statistics, 2007 < http://www.cdc.gov/nchs/data/ad/ad388.pdf >.
M. V. Chakravarthy, M. J. Joyner, F. W. Booth, .An Obligation for Primary Care Physicians to Prescribe Physical Activity to Sedentary Patients to Reduce the Risk of Chronic Health Conditions,. Mayo Clinic Proceedings 77, 2 (2002): pp. 165.173.
Access to behavioural therapy via primary care
Evaluate the short-term efficacy of a web-based behavioural weight loss intervention among primary care patients with obesity and hypertension
Age 25 to 65 years
BMI 30 to 40 kg/m2
Diagnosed hypertension and utilization of hypertension medication
Non-smoker status at least 6 months prior to recruitment
English language fluency
Availability of computer with internet access at home or work
those with history of condition that would prohibit exercise (such as dementia, cancer, or stroke)
390 patients identified through review of from large outpatient practice in Cambridge Massachusetts, between June 2005 and June 2006
Welcome letter mailed out with opt out instructions
Telephoned those who did not refuse additional contact
Participant Flow Baseline assessment Follow-up assessment Research staff collecting evaluation data blinded to randomization status predetermined assignments enclosed in non-transparent randomization envelopes) Dates, setting, informed consent, blinding (participant, care provider) ?? unclear
Baseline and follow-up assessments
Anthropometric measures and blood pressure (Research staff)
$25 for attending assessment
Reference 20 Unclear Results?
Reference 20 NHANES Food Questionnaire Centers for Disease Control and Prevention (CDC), National Center for Health Statistics (NCHS). National Health and Nutrition Examination Survey Questionnaire. Hyattsville, MD, 2004 < http://www.cdc.gov/nchs/data/nhanes/nhanes_03_04/tq_fpq_c.pdf >
Intervention vs Usual Care 84% of intervention 84% of usual care Aim for Healthy Weight material Web-based behaviour treatment + health coach ??
3 month access to website Interactive weight loss approach (iOTA)
Aims to create energy deficit through modification of routine obesogenic lifestyle behaviours
Purpose to facilitate easy, daily self-monitoring of adherence to obesogenic behaviour change goals
Four counselling sessions with health coach
Two 20-min in-person motivational coaching session
Algorithm to select four obesogenic behaviour change goals (week 1)
participant select new obesogenic behaviour change goals (week 6)
Two, 20-min biweekly session via telephone (week 3 and week 9)
Figure 1 W ebsite-based tracking system screenshot
Step Up, Trim Down Trial
Goal: login at least 3 times weekly
Raffle entry for each login.
Two raffles for $50 over 3 month period.
Website presented behavioural skills need to effectively adhere to set of obesogenic behaviour change goals (e.g., stimulus control, portion control, label reading, eating out) and updated biweekly
Website also included social networking forum , recipes, messaging feature for direct communication with coach
iOTA behaviour change goals
“Watch 2 hr or less of TV every day”
“Avoid sugar-sweetened beverages”
“Avoid fast food”
“Eat breakfast every day”
“No late night meals and snacks”
Participants randomized to the web-based intervention would demonstrate greater weight losses compared to those in usual care
Two sided type 1 error rate of 5%
100 participants (50 per group) need to detect at least 5 kg mean weight difference between groups with 80% power
Univariate analyses of variables of interest to test for baseline group differences, outliers and distributional assumptions
Analysis of variance, regression models and nonparametric tests as necessary to test group differences in each of the study outcomes
For intent-to-treat analyses, baseline carried forward imputation approach was used
Change in body weight (kg) at 12 weeks
Blood pressure control
Frequency of logins
Primary Outcome Weight loss by condition in the Step Up Trim Down weight loss trial ( n = 101) Suggestion to include % weight loss 25.6% of intervention participants lost >5% body weight by week 12 (none in control)
Secondary outcome -0.38 mm Hg (95% CI -4.03, 3.27) diastolic blood pressure -1.30 mm Hg (95% CI -3.38, 5.99) systolic blood pressure -1.87 cm (95% CI -3.97, 0.23) waist circumference -1.07 kg/m2 (95% CI -1.49, -0.64) BMI Mean Difference (Intervention versus Usual Care)
Secondary outcome Weekly website logins among participants with >= 1 login participant who did not log in once omitted from analysis??
Those who met login goal for >= 6 weeks lost more wt (-3.30 +/- 3.78 kg) than those who did not (-0.42 +/- 1.78 kg) Mean diff: -2.88 kg (95% CI -1.56, -4.60)
Those meeting login goal for >=10 weeks loss more wt (-4.50 +/-3.29 kg) than those who did not (-0.60 +/- 1.87 kg); Mean diff: -3.90 kg; 95% CI -2.43, -5.36). declining
Association between frequency of website logins and weight loss (20.99-2 =18.99) (50.49-21=29.49) (71.99-50.50=21.49) (130-72=58.0) 0 – 2 missing? Data intervals not proportional
Coaching sessions and weight loss
80.4% received all coaching sessions within 1 week of scheduled appointment
No association between participation in all 4 coaching sessions and weight loss
Likely due to high adherence rates
Discussion (by author) Primary care setting What does study add Contributes to growing body of evidence on internet delivery of weight loss intervention Relationship to prior knowledge
Answers study question
Explanation for modest weight loss observed
No caloric restriction
Motivation not controlled
Small sample size
Generalizable only to patient with internet access in similarly structured primary care settings
Design did not allow cost estimates
Unable to isolate the independent contribution of intervention components (coaching calls, raffle)
Limitations Magnitude of intervention efficacy and coaching support What future research is needed
Unrestricted grant from Sanofi Aventis.
G.G.B. is also supported by grant from National Cancer Institute.
S.J.H. was supported by an institutional Ruth L. Kirschstein National Research Service Award (5 T32 HP11001-19) from the Health Resources and Services Administration and the Department of Ambulatory Care and Prevention at Harvard Medical School and Harvard Pilgrim Health Care in Boston, Massachusetts.
K.M.E. is supported by grant from the National Cancer Institute.
Public health approach to prevent obesity effectiveness of programs for weight loss via lifestyle change (controlled energy intake, increased physical activity) is highly variable and infrequent result in sustainable weight loss
Obesity guidelines (CMAJ)
Was it a weight loss intervention or behaviour modification to promote healthy lifestyle?
Why only a behavioural intervention? Studies suggest the need for multiple interventions
Why 12 weeks? Doesn’t address the challenges facing obesity interventions (long term sustainability)
Does research of a based tool in the primary care setting provide new knowledge?
How generalizable is study with raffle to increase web login?
Why was attrition rate higher than those reported in literature?