242795 Commuting distance and its association with cardiorespiratory fitness and metabolic risk

Wednesday, November 2, 2011: 1:05 PM

Christine Hoehner, PhD, MSPH , School of Medicine, Washington University in St. Louis, St. Louis, MO
Beth Wright , Cooper Institute, Dallas, TX
Background: Sitting may have effects on metabolic risk independent from physical activity (PA). No known evidence exists on the metabolic risk correlates of prolonged sitting in motor vehicles. Objective: To examine the association between commuting distance, cardiorespiratory fitness (CRF) and metabolic risk. Methods: This cross-sectional analysis included 3,929 adults, mostly white and well educated, aged 18-90 years who had a comprehensive medical examination between 2000-2007 and with geocoded home and work addresses in 12 Texas metropolitan counties. ~95% of workers in this region commute by automobile. The primary exposure variable was commuting distance along the road network. Outcome variables included meeting public health PA recommendations (≥150 weekly minutes of self-reported PA), high CRF (≥ 60th percentile for age-sex distribution from a maximal treadmill test), obesity (BMI>30 kg/m2), and metabolic risk variables using the International Diabetes Federation criteria (high waist circumference (WC), raised fasting triglycerides, raised plasma glucose, reduced HDL cholesterol, raised blood pressure (BP), and metabolic syndrome (MS)). Logistic regression models were adjusted for socio-demographics, smoking status, alcohol intake, family history of diabetes, BMI, and history of high cholesterol (for blood lipids models). Results: Commuting >15 versus ≤5 miles was negatively associated (p<0.05) with meeting PA recommendations (adjusted OR[aOR]=0.72) and high CRF (aOR=0.80), and positively associated with obesity (aOR=1.5), high WC (aOR=1.4), raised BP (aOR=1.3), and MS (aOR=1.3). Associations with obesity and BP remained after adjustment for CRF. Conclusions: Commuting long distances may adversely affect health. Future research in more diverse populations is needed.

Learning Areas:
Clinical medicine applied in public health
Social and behavioral sciences

Learning Objectives:
1. Describe challenges in preparing addresses from large clinical datasets to geocode for studies that examine spatial and neighborhood influences on objectively measured health outcomes; 2. Describe network analyst as a spatial tool for calculating home to work routes; 3. Describe mechanisms that may explain the association between sedentary commuting, fitness, and metabolic risk outcomes. 4. Identify possible intervention strategies among adults with long commutes and how these differ from strategies to reduce other forms of sedentary time (e.g., time spent watching TV); 5. Discuss policy implications of adverse health effects of long commuting distances in light of regional development patterns in the U.S.

Keywords: Exercise, Geographic Information Systems

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I am qualitifed to present because I conduct public health-related research at a research university.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.