Table 1 Comparison of variables between Seattle and Paris data sets
From: Food environment and socioeconomic status influence obesity rates in Seattle and in Paris
Seattle | Paris | |
|---|---|---|
Variable name | Age (years) | Age (years) |
Measurements | <45 | <45 |
45–<65 | 45–<65 | |
>=65 | >=65 | |
Variable name | Gender | Gender |
Measurements | Male | Male |
Female | Female | |
Variable name | Living alone | Living alone |
Measurements | Yes | Yes |
No | No | |
Variable name | Annual household income | Rvuc (Revenu du ménage par unité de consummation: Household income per unit of consummation per euro per month) |
Measurements | Tertile 1 (<50 000) | Tertile 1 (<1200) |
Tertile 2 (⩾50 000–<100 000) | Tertile 2 (⩾1200 to <2200) | |
Tertile 3 (⩾100 000) | Tertile 3 (⩾2200) | |
Variable name | Highest education completed | Nivetude_cgi (Niveau d’instruction individuel: education level) |
Measurements | High school or less | 1: ne sait pas lire ou écrire le français et sans diplôme; (No education) 2:CAP, BEPC ou brevet des colleges (primary school and lower secondary school) |
Some college | 3: BAC, BTS ou BAC+2 (higher secondary school and lower tertiary school) | |
College graduates or higher | 4: supérieur à BAC+2 (higher tertiary school) | |
Variable name | Store type by price | Type de supermarché: |
Measurements | Low cost | hard_discount=1 |
Medium cost | hypermarche=1 OR gd_supermarche=1 OR pt_supermarche=1 | |
High cost | citymarche=1 OR magasins_bio=1 | |
Variable name | BMI | BMI |
Measurements | Obese (BMI⩾30 kg m−2) | Obese (BMI⩾=30 kg m−2) |
Non-obese (BMI<30 kg m−2) | Non-obese (BMI<30 kg m−2) | |
Variable name | Perceived health status | Santé_percue |
Measurements | Fair/poor | Fair/poor: Scale 0–7 (47%) |
Good/very good/excellent | Good/very good/excellent: Scale 8–10 (53%) | |
Variable name | Neighborhood assessed property value (property value within the 833 m circular buffer, measured in $). | Housingrank_500 m (neighborhood property value within the 500 m circular buffer, measured on a 1–1000 scale). |
Measurements | 70 381–193 106 | 1–301 |
193 107–248 011 | 302–420 | |
248 012–334 445 | 421–536 | |
334 446–1 086 587 | 537–1000 | |
Variable name | Distance from home to primary supermarket | Distance_netw_surf (distance entre le supermarché et le lieu de résidence du participant par le réseau de rues: network distance between the supermarket and place of residence of the participant) |
Measurements | Km | Km |
Variable name | Within the city of Seattle boundary | Within the city of Paris boundary |
Measurements | Yes or no | Yes or no |
