Does Public Transit Promote Physical Activity?

An Analysis of a 2015 Study

Shauna Ayres, Ashley Crawford, Camille McGirt, Sarah Shaughnessy and Anne Schmidt

Public Health Problem

A Push for Physical Activity

Adequate levels of physical activity (PA) can reduce the risk of obesity, diabetes, and heart disease

A Push for Public Transit

More efficient mode of transport

Reduces environmental pollution

Previous Research

Cross-sectional studies have shown an association between healthy PA levels

and use of public transit 1 2 but there are limitations

• Confounders: neighborhood context, ridership characteristics

Are people who use public transit already more active?

• Substitution effect

Does public transit generate new PA?

1. Brown, et al (2015) 2. Saelens, et al (2014)

New AssessmentPublic transit generates new physical activity: Evidence from

individual GPS and accelerometer data before and after light rail

construction in a neighborhood of Salt Lake City, Utah, USA.

Harvey J. Miller a,b,n, Calvin P. Tribby a,b, Barbara B. Brown c, Ken R. Smith c,d, Carol M.

Werner e, Jean Wolf f, Laura Wilson f, Marcelo G. Simas Oliveira f

Longitudinal study: n=536

Three forms of analysis:1. Within-person differences of PA before and after

construction of the light rail

2. Spatial clustering of PA around transit stops

3. Comparison of time spent on PA on days when

participants used LRT and days when they did not

Conceptual Model and Hypotheses

Sampling and Representativeness

TARGET POPULATION

Salt Lake City Residents

SAMPLING FRAME

Residents within 2km of LRT line

SAMPLE

536 residents

Coverage Error

Non-probability

sampling

Construct Validity of IV (manipulated)

Novelty Effects:

Riding the new LRT is initially appealing, but this appeal

fades over time.

Reactivity to the Experimental Situation:

Participants may be more active because they know the

researchers are studying PA

Construct Validity of DV

Face Validity:• GPS with accelerometers can measure movements• Can determine duration and intensity

Content Validity:• Doesn’t measure all types of PA• Doesn’t measure in all environments• May measure non-PA as PA• Missing Heart Rate data

Criterion-Related Validity:• Gold standard=

Doubly Labeled Water (DLW) device(Andre, 2007)

Study DesignPre-experimental:

one group pretest-posttest design

O1 X O2

Miller et al. claim that public transit generates new physical activity

Internal Validity

Findings:

• Association: the IV and DV both vary

• Temporality: the IV occurs before the DV

• Nonspuriousness: cannot be established

Analysis:

• Main threat: maturation

• Other threats:

history & testing

• Not threats: selection,

instrumentation,

regression to the mean,

& differential attrition

Statistical Conclusion Validity

Strengths• Reliable measures: accelerometer and GPS recorder (Jarret et al. 2015

and Aaland et al. 2015 & Noury-Dasvaux 2011 & Schipperijin 2014)

• Large sample size:n=536 (good statistical power)

• Paired t-test

Weakness• Attritionlost 403 participants

Generalizability

Who: demographics are not presented

Where: small-medium metropolitan areas

When: currently relevant

How:

IV- type of public transit

DV- type of physical activity

Improving the Study

Recruiting Method:

• “Door to door canvassing”- Too Arduous • Web/digital methods for recruitment

More accurate measures of PA:• Defined PA: Minimum duration of 5 min. with a minimum of 1000 accelerometer counts per minute

PA-Total=PA regardless of relationship with PA PA-Transit=PA within a trip that contains public transportation PA Other=PA that does not occur with a public transit segment

Longer assessment period:

• Possible Interrupted Time Series Design

O1 O2 X O3 O4

Overall Assessment

Study Strengths:• Inclusion of literature • Comparable results • Study participants wore

accelerometers AND GPS recorders• PA time relates to changes in transit

use • Policy implications • Reliables measures and large sample

size

Study Weaknesses:• Attrition n=939 to n=536• Non-probability sampling • Did not complete additional

assessments• Demographics • Possible coverage error• Information recording • Threats to internal & external

validity

USPSTF

II-3: Evidence from multiple time series with or without intervention

Quality

Fair