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Who is at Risk? Investigating the Determinants of Physical Activity in Young Adult Women
Transcript of Who is at Risk? Investigating the Determinants of Physical Activity in Young Adult Women
Data from surveys 2 to 5 (2000, 2003, 2006, 2009)
=> 1 survey walking minutes + moderate leisure minutes + vigorous leisure minutes Physical activity score <600 MET*min/week = inactive;
=>600 MET*min/week = active BMI
Country of birth
Area of residence
Number of children Occupational status
Hours worked per week Smoking status
Stress Work-related Lifestyle Socio-demographic Analyses 1. Descriptives for all potential determinants and physical activity 2. Generalised estimating Equations (GEE)
Univariable age-adjusted GEEs
Multivariable age-adjusted GEE - stepwise removal of least significant variables 3. GEEs repeated for women who responded to all four surveys (N=5,334) The data in SPSS Descriptives By survey 5:
more than half had completed a University/ higher degree
Almost 2/3 were married
=>60% had at least 1 child Majority born in Australia
and living in urban areas % active women declined over the years (from 55% to 47%) * 3.0 METs * 4.0 METs * 7.5 METs 11835 women responded to
=> 1 survey Final sample of 11,699 women 92 women did not provide sufficient data 44 women excluded because long-term illness/disability Results Time lag model PA model Marital status S1
Marital status S2
Marital status S3
Marital status S4 Physical activity S2
Physical activity S3
Physical activity S4
Physical activity S5 3 years between survey's Constant low activity = close to zero
Constant high BMI (e.g.) = close to zero Statistics will not show the real picture! The Study Statistics The Sample Measuring PA Potential 11 potential determinants measured up to 4 times over 9 years 1 dichotomous PA variable 11,699 women Now what? So... Léonie Uijtdewilligen
Jannique van Uffelen
Wendy Brown Results from the Australian Longitudinal Study on Women's Health (ALSWH) Total PA score in MET*min/week
Further classification: * Designed to track health in three different age cohorts
* Random sampling Medicare database
* Three-phase mailing protocol
* Young cohort: 39.000 questionnaires sent 14.792 completed in 1996
(41% response) Univariable GEE ALL variables significantly associated with physical activity status! determinants Born in Asia MOST likely to be INACTIVE: Multivariable GEE Who are married or in a de facto relationship With less than 12 years of education With at least one child Non- or rare drinkers ? Asian women priority focus
? Targeted approach for the less educated
? Aim at physical activity for the WHOLE family
? Reinforce alcohol consumption ;)... Please raise your hand for ideas!