Page 102

Proefschrift binnenwerk Manon Ernst_DEF.indd

C H A P T E R   6   tribute  to  the  prevention  of  overweight  at  an  early  age.  However,  most  of  these  risk   factors   are   mainly   subjective   and   difficult   to   change.   Therefore,   a   more   objective   parameter   like   the   PI   in   our   prediction   model   can   be   very   helpful   in   preventive   strategies.  If  the  meaning  of  the  PI  value  is  carefully  explained  to  the  parents,  this   might   contribute   to   a   greater   awareness   and   risk   perception   of   overweight.   The   prediction   model,   as   described   in   this   manuscript,   can   simply   be   used   in   practice   and   added   to   the   resources   that   health   care   practitioners   use   in   preventing   over-­‐ weight  in  childhood,  at  the  moment.     Most   interventions,   targeted   at   the   prevention   and   reduction   of   overweight,   are   applied   from   the   age   of   2   years.   Mainly,   they   are   focused   on   environmental   and   behavioral  factors,  like  promoting  healthy  food  and  drinks,  creating  sport  facilities   and   safe   zones   for   cycling   to   school,   restrictions   on   the   advertising   of   soft   drinks   and  energy  dense  food  and  demotivating  sedentary  recreation,  like  watching  TV  or   playing   computer   games18.   In   this   manuscript   we   focused   on   the   prediction   of   overweight  by  using  the  PI  in  early  childhood  (0-­‐1  year).  By  using  our  model,  pre-­‐ diction  and  thereby  prevention  of  overweight  can  already  initiated  at  a  very  early   age,  even  before  it  can  be  diagnosed.     In   the   Netherlands   the   Youth   Health   Care   is   concerned   with   the   healthy   physical   and   psychosocial   development   of   children,   between   0   and   19   years   of   age.   With   respect  to  the  growth  of  children  in  their  early  years,  the  Youth  Health  Care  exam-­‐ ines   children   regularly   during   their   visits   to   the   Youth   Health   Care   centers   with   their   parents.   During   the   first   year   of   life,   there   are   approximately   10   measure-­‐ ments   of   the   child   by   the   youth   health   care,   thereafter   approximately   5   measure-­‐ ments  until  the  age  of  5  years.  By  means  of  these  frequent  examinations,  it  is  possi-­‐ ble   to   monitor   the   growth   of   a   child   and   to   intervene   at   the   moment   that   a   child   tends   to   become   overweight.   Our   prediction   model   can   be   a   useful   additional   in-­‐ strument  in  the  prevention  of  overweight.     If   this   prediction   model   could   be   implemented   in   the   electronic   child   record,   the   Youth   Health   Care   physician,   pediatrician   or   nurse   can   show   parents   the   risk   of   their  child  of  becoming  overweight,  taken  a  cut-­‐off  point  of  PIm  >  PIe     +  2SD  at  the   age  of  1  year.  Only  the  data  of  PI  at  birth,  based  on  birth  weight  and  birth  length  and   the  actual  age  of  the  child  are  needed  in  the  risk  calculation.  By  digital  registration,   it   is   possible   to   immediately   show   the   risk   of   becoming   overweight   on   their   com-­‐ puter   screen.   For   example,   if   the   child   is   not   at   risk,   the   screen   will   show   a   green   color;  if  the  child  is  at  risk,  the  screen  will  show  a  red  color.     To  countervail  the  risk  that  the  parents  do  not  accept  the  advice  of  the  health  care   practitioner,   because   the   risk   is   a   calculated   risk   which   does   not   exist   yet,   it   is   of   great  importance  to  train  the  health  care  practitioners  in  motivational  interviewing.   Motivational  interviewing  assumes  that  behavior  change  is  affected  more  by  moti-­‐ 100    


Proefschrift binnenwerk Manon Ernst_DEF.indd
To see the actual publication please follow the link above