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SUMMARY:HE@Cam: Padraig Dixon - The causal effect of BMI on inpatient hosp
 ital costs: Mendelian Randomization analysis of the UK Biobank cohort - Dr
  Padraig Dixon\, University of Bristol
DTSTART:20181203T150000Z
DTEND:20181203T160000Z
UID:TALK112123@talks.cam.ac.uk
CONTACT:David Wastlund
DESCRIPTION:Health Economics at Cambridge (HE@Cam) are happy to present Dr
  Padraig Dixon\, University of Bristol\, for a talk on the use of new meth
 ods for estimating the causal effects of body mass index (BMI) upon inpati
 ent hospital costs.\n\nAlmost all evidence of the association between obes
 ity and inpatient costs is based on observational research prone to bias b
 ecause of reverse causation\, measurement error\, and residual confounding
 . During his talk\, Padraig will discuss the first use of genetic variants
  in a Mendelian Randomization framework to estimate the causal effect of B
 MI (or any other disease/trait) on healthcare costs. This type of analysis
  can be used to inform the cost-effectiveness of interventions and policie
 s targeting the prevention and treatment of overweight and obesity\, and f
 or setting research priorities.\n\nMore information and full abstract can 
 be found below. More information about Health Economics at Cambridge (HE@C
 am) can be found at "our website":https://www.iph.cam.ac.uk/network/specia
 l-interest-groups/health-economics-cambridge/\n\n*Time:* 15:00 - 16:00 Mon
 day 3rd December 2018\n*Venue:* Large seminar Room\, Institute of Public H
 ealth\, Cambridge\n\n*All welcome. Part of the HE@Cam seminars 2017/18 ser
 ies.*\nFor any questions\, please contact healtheconomics@medschl.cam.ac.u
 k\n\n*Background*\nHigh adiposity as measured by body mass index (BMI) is 
 associated with increased healthcare costs. Understanding this association
  is important for the formulation and evaluation of healthcare policies ta
 rgeting overweight and obesity\, for identifying research priorities\, and
  for planning future healthcare budgets.  However\, almost all evidence of
  this association is based on observational research prone to bias because
  of reverse causation\, measurement error\, and residual confounding.\n\n*
 Methods*\nWe used germline genetic variants as instrumental variables (IVs
 ) – a method known as Mendelian Randomization – to obtain causal estim
 ates of the effect of BMI on inpatient hospital costs. These variants – 
 pieces of the genetic code that differ between individuals – are precise
 ly measured\, are generally independent of confounders and are not affecte
 d by reverse causation. We estimated IV models of the marginal causal effe
 ct of BMI using 79 variants robustly associated with BMI in the largest an
 d most recent genome-wide association study of BMI. The association of the
 se variants with inpatient costs was modelled in a two-sample Mendelian Ra
 ndomization analysis using data from UK Biobank\, a large prospective coho
 rt study (n=502\,617) linked to records of inpatient hospital care. We ass
 essed potential violations of the instrumental variable assumptions\, part
 icularly the exclusion restriction via pleiotropy (i.e. variants affecting
  costs through paths other than BMI) using median-based IV methods (which 
 are consistent if no more than 50% of instruments are invalid)\, and mode-
 based IV models (which clusters IVs into groups based on similarity of cau
 sal effects). We investigated potential non-linear effects of BMI on hospi
 tal costs.\n\n*Results*\nPreliminary analysis suggests that the causal Men
 delian Randomization effect sizes are almost twice as large as the observa
 tional effect sizes. These effects attenuated under median and mode-based 
 sensitivity analyses\, but effect sizes remained larger than observational
  estimates. There was some evidence for modest non-linear effects.\n\n*Con
 clusions*\nThis paper is the first to use genetic variants in a Mendelian 
 Randomization framework to estimate the causal effect of BMI (or any other
  disease/trait) on healthcare costs. This type of analysis can be used to 
 inform the cost-effectiveness of interventions and policies targeting the 
 prevention and treatment of overweight and obesity\, and for setting resea
 rch priorities.
LOCATION:Large Seminar Room\, Institute of Public Health\, Cambridge
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