Longitudinal trends in gasoline price and physical activity: the CARDIA study

Abstract

Objective: To investigate longitudinal associations between community-level gasoline price and physical activity (PA).

Method: In the Coronary Artery Risk Development in Young Adults study, 5115 black and white participants aged 18-30 at baseline 1985-86 were recruited from four U.S. cities (Birmingham, Chicago, Minneapolis and Oakland) and followed over time. We used data from 3 follow-up exams: 1992-93, 1995-96, and 2000-01, when the participants were located across 48 states. From questionnaire data, a total PA score was summarized in exercise units (EU) based on intensity and frequency of 13 PA categories. Using Geographic Information Systems, participants' residential locations were linked to county-level inflation-adjusted gasoline price data collected by the Council for Community & Economic Research. We used a random-effect longitudinal regression model to examine associations between time-varying gasoline price and time-varying PA, controlling for age, race, gender, baseline study center, and time-varying education, marital status, household income, county cost of living, county bus fare, census block-group poverty, and urbanicity.

Results: Holding all control variables constant, a 25-cent increase in inflation-adjusted gasoline price was significantly associated with an increase of 9.9 EU in total PA (95% CI: 0.8-19.1).

Conclusion: Rising prices of gasoline may be associated with an unintended increase in leisure PA.

Figure 1

Predicted changes in total physical activity a and its 13 sub-categories b, per 25 cent increase in inflation-adjusted gasoline price using two-part marginal effect modeling with bootstrap, among black and white American adults from the CARDIA Study c, U.S.A., 1992–2001. ^*p<0.05 ^aBy random-effect longitudinal regression model (Table 3). ^bBy two-part models controlled for season that gasoline prices were collected, individual-level variables including age, gender, race, education level, marriage status, inflation-adjusted household income, baseline study center; and community-level variables including, county-level cost of living index, county-level inflation-adjusted bus fare, BG-level poverty, BG-level employment status, BG-level % workers age ≥16 travel 30+ min to work, BG-level % workers walk to work, BG-level % workers bicycle to work, dummy indicator of urbanicity, 1km-buffer level street connectivity and population density, and dummy indicator of imputed gasoline prices. Then we performed Bootstrap with 1000 replications to estimate standard error for the derived point estimate. ^cCoronary Artery Risk Development in Young Adults Study (U.S., 1992–93 to 2000–01), with black and white young adults recruited from four U.S. cities at baseline ^dNon-strenuous sports such as softball, shooting baskets, volleyball, ping pong, or leisure jogging, swimming or biking (moderate intensity) ^eStrenuous sports such as basketball, football, skating, or skiing ^fSnow shoveling or moving heavy objects or weight lifting at home ^gVigorous job activities such as lifting, carrying, or digging