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Who is at Risk? Investigating the Determinants of Physical Activity in Young Adult Women

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Léonie Uijtdewilligen

on 21 May 2015

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Transcript of Who is at Risk? Investigating the Determinants of Physical Activity in Young Adult Women

WHO IS AT RISK OF INACTIVE BEHAVIOUR?
Women from youngest ALSWH cohort (born in 1973-1978)
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
Educational qualification
Marital status
Number of children
Occupational status
Hours worked per week
Smoking status
Alcohol 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
Geeske Peeters
Jannique van Uffelen
Jos Twisk
Amika Singh
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!
Full transcript