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Table 2 Effects of traffic density or traffic-related air pollution on BMI level (intercept) and growth (slope)

From: Traffic-related air pollution and obesity formation in children: a longitudinal, multilevel analysis

  Combined effect modeling
Exposure based on 10-90th percentile contrast Male and Female
  Intercept β (SE) Slope β (SE)
Traffic densitya 0.0012* (0.0006) 0.0002* (0.0001)
Non-Freeway NOx a 0.3831** (0.1552) 0.0861** (0.0255)
Traffic densityb 0.0012* (0.0006) 0.0002 (0.0001)
Non-Freeway NOx b 0.3867** (0.1552) 0.0873** (0.0255)
  1. **p < 0.05.
  2. *p < 0.1.
  3. aModels include the same confounders: whether the child has ever had asthma, parental education as a marker for socioeconomic position, whether the questionnaire was answered in Spanish as a marker for recent immigrant status, normalized difference vegetation index within 500 m of the home as a measure of green cover, street connectivity as measured by the gamma index, recreational programming within 5 km of the home, and fast food access within 500 m of the home.
  4. bConfounders selected based on modeling procedure described in the methods for each exposure. The traffic density model includes parental education as a marker for socioeconomic position, whether the questionnaire was answered in Spanish as a marker for recent immigrant status, normalized difference vegetation index within 500 m of the home as a measure of green cover, and recreational programming within 5 km of the home.
  5. The non-freeway NOx model includes parental education as a marker for socioeconomic position, whether the questionnaire was answered in Spanish as a marker for recent immigrant status, normalized difference vegetation index within 500 m of the home as a measure of green cover, street connectivity as measured by the gamma index, recreational programming within 5 km of the home, and fast food access within 500 m of the home.
  6. All of the above models include indicator functions for community of residence and variables for sex and race or ethnicity.