Table 2 Study characteristics of the included studies
First author (year) | Country | Study population | % female and age range | Sample size | Methods of exposure data collection(a) | Food environment assessment based on GPS data(b) | Tracking duration and frequency of GPS sampling(c) | Temporal aspects(d) | Type and distribution of outcome(e) |
|---|---|---|---|---|---|---|---|---|---|
Widener 2018a | Canada | (Young) Adults | 66.5 16–30 years | 496 | Smartphone: CFSMobile app | Food environment data source: 2016 DMTI business directory; Food environment assessed: the number of grocery stores, convenience stores, fruit and vegetable markets, limited-service restaurants and ‘all food retailers’; GPS-based food exposure measures: regular activity space locations (defined as the top 1% and 10% of the time-weighted kernel density estimate surface) | 7 days Frequency not reported | Not reported | Webform (Counts food purchasing) |
Wray (2021)b | Canada | High school students | 63.6 13–18 years | 154 | Smartphone: SmartAPPetite | Food environment data source: lists of food store places from the government; Food environment assessed: standardized count of logged GPS points within the buffer of retail food outlets's ads (quick service, restaurants, grocery, and variety); GPS-based food exposure measures: Euclidean buffers around outlets (150 m), billboards (150 m), bus shelters (75 m), and street posters (75 m) | 12 weeks Every 120 s or when a user enters the geofenced area surrounding a retail food outlet | Not reported | Food purchases, categorical (quick service purchases, restaurants purchases, grocery purchases, variety purchases, all types of purchases) |
Sadler (2016)c | Canada | Students | 58.7 9–13 years | 654 | GPS device | Food environment data source: lists of food store places from public health inspectors; Food environment assessed: the number of minutes during which a child was exposed (i.e., within 50 m) to fast food, variety stores, pizza places or ice cream shops (ranges from 0 s to 350 min); GPS-based food exposure measures: 50 m buffers on food outlets | 2 weeks Every second | Not reported | Junk food purchases outcome (binary), indicating whether junk food was purchased or not on the trip. Junk food was considered unhealthy food items purchased from fast food or variety stores, pizza places and ice cream shops |
Shearer (2015)d | Canada | Students | Not reported 12–16 years | 380 | GPS device (20 channel EM-408 SiRFstar III chipset GSP receiver) | Food environment data source: lists of food store places from a commercial company (DMTI); Food environment assessed: The number of fast food (major fast food chains with a focus on take-away meals), restaurants (all other types), grocery and convenience stores, and average distances to every accessible and actually visited food locations within GPS route buffers from a participant's home and school origin; GPS-based food exposure measures: 50 m GPS route buffer | 7 days Every second | Not reported | diet quality index ranging from 0 to 100 with higher scores reflecting better diet quality |
Zenk (2011)e | USA | All ages | 75.0  < 45, 45–64, > 64 years | 120 | GPS device: Foretrex 201 | Food environment data source: lists of food store places from the government; Food environment assessed: fast food outlet density and the number of chain full-service grocery stores or supercenters; GPS-based food exposure measures: one standard deviation ellipse on GPS points and 0.5-mile daily path area on GPS points | 7 days 30 s intervals | Not reported | Set of Food frequency questionnaire items reporting on saturated fat intake, fruit and vegetable intake, and whole grain intake (validation of FFQ not reported) |
Elliston (2020)f | Australia | Adults | 71.0 18 + years | 72 | Smartphone | Food environment data source: lists of food store places from the government; Food environment assessed: The number of food outlets; GPS-based food exposure measures: 50 m GPS point buffer | 2 weeks Once the user report food intake | Not reported | Eating/Non-eating and food intake (collected by food reports and EMA measures: prompts, 4–5 times a day during a period of 2 weeks |
Gustafson (2013)g | USA | Adults | 58.0 18 + years | 121 | GPS device (Qstarz BT-Q1000XT Travel Recorder) | Food environment data source: lists of food store places from a commercial company (InfoUSA); Food environment assessed: the retail food environment index as a ratio of healthy (Supermarkets/grocery stores, farmers’ markets, and produce stands) relative to unhealthy (supercenters, convenience stores, fast-food restaurants, and gas stations with convenience stores, or less healthy venues) food venues; GPS-based food exposure measures: 0.5 mile GPS route buffer | 3 days (2 weekdays and 1 weekend day) Frequency not reported | Not reported | Based on the NEMS-S protocol, availability, price, and quality of food were collected for 15 food categories (fruit, vegetables, milk, cheese, meat, baked goods, chips, beverages, canned items, cereal, desserts, prepared food items, snack foods, frozen meals, and beans) and 55 unique food items were assessed |
Ghosh Roy (2019)h | USA | African American Women | 100 25–65 years | 79 | GPS device (Qstarz BT-Q1000XT GPS, Qstarz) | Food environment data source: lists of food store places from a commercial company (Dun & Bradstreet); Food environment assessed: The number of fast food restaurants and convenience stores; GPS-based food exposure measures: 400 m GPS route buffer | 7 days Every minute | Not reported | Snack food item and sweetened beverage intake dichotomized into non or one (0) or more than one (1) |
Seto (2016)i | China | Students | 66.7 18–31 years | 12 | Smartphone: CalFit Chi and Dong | Food environment data source: lists of food store places from Google Maps; Food environment assessed: average number of bakeries, bar, cafe, convenience store, food, grocery or supermarket, liquor store, meal delivery, meal takeaway, and restaurant; GPS-based food exposure measures: 250 m circular buffers on activity locations | 6 days Every 10 s | Not reported | Portion size was recorded with video. Later, two trained dietitians familiar with local diets review the contents of the videos, and code the portion sizes and food groups associated with each food consumed. Subjects’ diet recordings were coded by both dietitians to assess inter-rater reliability |
Liu (2020)j | Canada | (Young) Adults | 65.0 16–30 years | 591 | Smartphone: Itinerium | Food environment data source: lists of food store places from opensource platform (OpenStreetMap); Food environment assessed: the number of fast food outlets, and the proportion of the sum of the number of fast food outlets, supermarkets, green groceries, and convenience stores within each activity space; GPS-based food exposure measures: 500 m, 1000 m, and 1500 m circular buffers on activity locations | 7 days Frequency not reported | Time-weighted exposure was considered by calculating the proportion of the time a participant spent at each activity location in the total time spent in all activity space | Self-reported fast-food intake |
Christian (2012)k | USA | Adults | 56.4 18–65 years | 121 | GPS device (Qstarz BT-Q1000XT Travel Recorder) | Food environment data source: lists of food store places from the government; Food environment assessed: the retail food environment index calculated as the sum of fast food restaurants plus convenience stores, divided by the sum of supermarkets plus fruit/vegetable markets, the proportion and density of limited-service outlets and supermarket; GPS-based food exposure measures: 0.5 mile GPS route buffer | 3 days Every 3 s | Not reported | Continues dietary intake of added sugar, red meat, fried potatoes, fruits and vegetables, whole grains. Weight status categorized into overweight and obese |
Burgoine (2015)l | USA | Children | 48.9 5–11 years | 94 | GPS device (Qstarz BT-Q1000XT GPS, Qstarz) | Food environment data source: lists of food store places from a commercial company (Reference USA); Food environment assessed: Density of takeaway food outlets and all food outlets categorized within tertiles with the highest tertile indicating more exposure to food outlets; GPS-based food exposure measures: 100 m GPS route buffer | 7 days Every 60 s | Not reported | Height and weight were measured by trained research staff (using a Seca 124 Portable stadiometer and a Tanita BWB-800 portable scale, respectively), and age-specific BMI z-scores calculated relative to growth charts from the US CDC |
Tamura (2018)m | USA | Adults | 51.9 18 + years | 102 | GPS device (Qstarz BT-Q1000XT GPS, Qstarz) | Food environment data source: lists of food store places from the government; Food environment assessed: Density of fast-food restaurants, wait-service restaurants, corner stores, grocery stores and supermarkets; GPS-based food exposure measures: 200 m and 400 m daily mobility path on GPS points | 7 days Every 30 s | Not reported | Tanita 351 scale was used to measure participants' heights and weights, wich were then used to compute BMI. Blood pressure was measured for 15–40 s SBP and DBP (based on mmHg) was assess with a Welch Allyn Vital Signs 300 monitor |
Wang (2018)n | USA | Adults | 60.8 18–65 + years | 46 | GPS device | Food environment data source: lists of food store places from the government; Food environment assessed: environmental context exposure index and density of fast-food restaurants, convenience stores, meat markets, pizzerias, bakeries, and candy and nut stores; GPS-based food exposure measures: 100 m 3-D GPS trajectory buffers (geolocation and time considered), 100 m GPS trajectory buffers, standard deviation ellipses with one or two standard deviations on GPS points, and minimum convex polysons of GPS points | 3 weeks Every minute | Opening hours of food stores were considered | BMI was calculated by dividing the subject's weight (kg) with height in meters squared (m2) (not reported whether it was self-reported or not) |