Should we use absolute or relative measures when assessing foodscape exposure in relation to fruit and vegetable intake? Evidence from a wide-scale Canadian study.

OBJECTIVE: This paper explores which of absolute (i.e. densities of "healthy" and "unhealthy" food outlets taken separately) or relative (i.e. the percentage of "healthy" outlets) measures of foodscape exposure better predicts fruit and vegetable intake (FVI), and whether those associations are modified by gender and city in Canada. METHODS: Self-reported FVI from participants of four cycles (2007-2010) of the repeated cross-sectional Canadian Community Health Survey living in the five largest metropolitan areas of Canada (n=49,403) was analyzed. Absolute and relative measures of foodscape exposure were computed at participants' residential postal codes. Linear regression models, both in the whole sample and in gender- and city-stratified samples, were used to explore the associations between exposure measures and FVI. RESULTS: The percentage of healthy outlets was strongly associated with FVI among men both in Toronto/Montreal (ß=0.012; P<0.001), and in Calgary/Ottawa/Vancouver (ß=0.008; P<0.001), but not among women. Observed associations of absolute measures with FVI were either weak or faced multicollinearity issues. Overall, models with the relative measure showed the best fit. CONCLUSIONS: Relative measures should be more widely used when assessing foodscape influences on diet. The absence of a single effect of the foodscape on diet positions sub-group analysis as a promising avenue for research.

Addressing equity in interventions to reduce air pollution in urban areas: a systematic review.

OBJECTIVES: We did a systematic review to assess quantitative studies investigating the association between interventions aiming to reduce air pollution, health benefits and equity effects. METHODS: Three databases were searched for studies investigating the association between evaluated interventions aiming to reduce air pollution and heath-related benefits. We designed a two-stage selection process to judge how equity was assessed and we systematically determined if there was a heterogeneous effect of the intervention between subgroups or subareas. RESULTS: Of 145 identified articles, 54 were reviewed in-depth with eight satisfying the inclusion criteria. This systematic review showed that interventions aiming to reduce air pollution in urban areas have a positive impact on air quality and on mortality rates, but the documented effect on equity is less straightforward. CONCLUSIONS: Integration of equity in evidence-based public health is a great challenge nowadays. In this review we draw attention to the importance of considering equity in air pollution interventions. We also propose further methodological and theoretical challenges when assessing equity in interventions to reduce air pollution and we present opportunities to develop this research area.

Field validation of secondary data sources: a novel measure of representativity applied to a Canadian food outlet database.

BACKGROUND: Validation studies of secondary datasets used to characterize neighborhood food businesses generally evaluate how accurately the database represents the true situation on the ground. Depending on the research objectives, the characterization of the business environment may tolerate some inaccuracies (e.g. minor imprecisions in location or errors in business names). Furthermore, if the number of false negatives (FNs) and false positives (FPs) is balanced within a given area, one could argue that the database still provides a "fair" representation of existing resources in this area. Yet, traditional validation measures do not relax matching criteria, and treat FNs and FPs independently. Through the field validation of food businesses found in a Canadian database, this paper proposes alternative criteria for validity. METHODS: Field validation of the 2010 Enhanced Points of Interest (EPOI) database (DMTI Spatial®) was performed in 2011 in 12 census tracts (CTs) in Montreal, Canada. Some 410 food outlets were extracted from the database and 484 were observed in the field. First, traditional measures of sensitivity and positive predictive value (PPV) accounting for every single mismatch between the field and the database were computed. Second, relaxed measures of sensitivity and PPV that tolerate mismatches in business names or slight imprecisions in location were assessed. A novel measure of representativity that further allows for compensation between FNs and FPs within the same business category and area was proposed. Representativity was computed at CT level as ((TPs +|FPs-FNs|)/(TPs+FNs)), with TPs meaning true positives, and |FPs-FNs| being the absolute value of the difference between the number of FNs and the number of FPs within each outlet category. RESULTS: The EPOI database had a "moderate" capacity to detect an outlet present in the field (sensitivity: 54.5%) or to list only the outlets that actually existed in the field (PPV: 64.4%). Relaxed measures of sensitivity and PPV were respectively 65.5% and 77.3%. The representativity of the EPOI database was 77.7%. CONCLUSIONS: The novel measure of representativity might serve as an alternative to traditional validity measures, and could be more appropriate in certain situations, depending on the nature and scale of the research question.