Ecological momentary assessment of digital food and beverage marketing exposure and impact in young adults: A feasibility study.

Unhealthy food marketing is contributing to the obesity epidemic, but real-time insights into the mechanisms of this relationship are under-studied. Digital marketing is growing and following food and beverage (F&B) brands on social media is common, but measurement of exposure and impact of such marketing presents novel challenges. Thus, this study aimed to evaluate the feasibility of collecting data on exposure and impact of digital F&B marketing (DFM) using a smartphone-based ecological momentary assessment (EMA) methodology. We hypothesized that DFM-induced food cravings would vary based on whether (or not) participants engaged with F&B brands online. Participants were Singapore residents (n = 95, 21-40 years), recruited via telephone from an existing cohort. Participants were asked to upload screenshots of all sightings of online F&B marketing messages for seven days, and answer in-app contextual questions about sightings including whether any cravings were induced. Participants provided a total of 1310 uploads (median 9 per participant, Q1-Q3: 4-21) of F&B marketing messages, 27% of which were provided on Day 1, significantly more than on other days (P < 0.001). Followers of food/beverage brands on social media encountered 25.6 percentage points (95% CI 11.4, 39.7) more marketing messages that induced cravings than participants who were not followers. University education was also associated with more (18.1 percentage points; 95% CI 3.1, 33.1) encounters with marketing messages that induced cravings. It was practical and acceptable to participants to gather insights into digital F&B marketing exposure and impact using EMA in young adults, although a shorter study period is recommended in future studies. Followers of food and beverage brands on social media appear to be more prone to experience cravings after exposure to digital F&B marketing.

Evaluating the Effects of Rewards and Schedule Length on Response Rates to Ecological Momentary Assessment Surveys: Randomized Controlled Trials.

BACKGROUND: Ecological momentary assessments (EMAs) are short, repeated surveys designed to collect information on experiences in real-time, real-life contexts. Embedding periodic bursts of EMAs within cohort studies enables the study of experiences on multiple timescales and could greatly enhance the accuracy of self-reported information. However, the burden on participants may be high and should be minimized to optimize EMA response rates. OBJECTIVE: We aimed to evaluate the effects of study design features on EMA response rates. METHODS: Embedded within an ongoing cohort study (Health@NUS), 3 bursts of EMAs were implemented over a 7-month period (April to October 2021). The response rate (percentage of completed EMA surveys from all sent EMA surveys; 30-42 individual EMA surveys sent/burst) for each burst was examined. Following a low response rate in burst 1, changes were made to the subsequent implementation strategy (SMS text message announcements instead of emails). In addition, 2 consecutive randomized controlled trials were conducted to evaluate the efficacy of 4 different reward structures (with fixed and bonus components) and 2 different schedule lengths (7 or 14 d) on changes to the EMA response rate. Analyses were conducted from 2021 to 2022 using ANOVA and analysis of covariance to examine group differences and mixed models to assess changes across all 3 bursts. RESULTS: Participants (N=384) were university students (n=232, 60.4% female; mean age 23, SD 1.3 y) in Singapore. Changing the reward structure did not significantly change the response rate (F3,380=1.75; P=.16). Changing the schedule length did significantly change the response rate (F1,382=6.23; P=.01); the response rate was higher for the longer schedule (14 d; mean 48.34%, SD 33.17%) than the shorter schedule (7 d; mean 38.52%, SD 33.44%). The average response rate was higher in burst 2 and burst 3 (mean 50.56, SD 33.61 and mean 48.34, SD 33.17, respectively) than in burst 1 (mean 25.78, SD 30.12), and the difference was statistically significant (F2,766=93.83; P<.001). CONCLUSIONS: Small changes to the implementation strategy (SMS text messages instead of emails) may have contributed to increasing the response rate over time. Changing the available rewards did not lead to a significant difference in the response rate, whereas changing the schedule length did lead to a significant difference in the response rate. Our study provides novel insights on how to implement EMA surveys in ongoing cohort studies. This knowledge is essential for conducting high-quality studies using EMA surveys. TRIAL REGISTRATION: ClinicalTrials.gov NCT05154227; https://clinicaltrials.gov/ct2/show/NCT05154227.

Associations between oral processing, saliva, and bolus properties on daily glucose excursions amongst people at risk of type-2 diabetes.

Background: A greater time spent with glucose above the normal range (TAR) has been associated with poorer glycaemic control amongst pre-diabetic individuals. Individual differences in oral processing behaviours and saliva amylase activity have been shown to influence glucose responses. Objective: The current study is a preliminary exploration of the associations of oral processing behaviours, bolus characteristics, and salivary amylase activity with the variability in daily glucose excursions within a free-living setting in populations with an elevated risk of type-2 diabetes. Method: Participant oral processing behaviour was derived from video recordings while they consumed a test meal. Post-meal bolus characteristics and saliva properties were measured. Participants were fitted with a continuous glucose monitor (CGM) which monitored blood glucose fluctuation over 7 consecutive free-living days. Dietary intake was recorded through a smartphone application and physical activity was monitored using a wrist worn accelerometer. Results: Participants varied in daily time spent with glucose above the normal range (>7.8 mmol l-1) from 0% to 15%. Greater saliva uptake in the bolus was associated with a higher time spent above the normal range for glucose (ß = 0.067 [95% CI = 0.015, 0.120]; p < 0.05), which remained significant after adjustment for dietary carbohydrate intake and BMI. Salivary amylase and saliva flow rate were not significantly associated with the time spent above the normal range. Conclusion: In addition to conventional dietary factors, more research is needed to understand how eating behaviours such as oro-sensory exposure, bolus surface area, and saliva uptake contribute to daily variations in postprandial glucose excursions among populations with a higher risk of developing type-2 diabetes.

Advancing understanding of dietary and movement behaviours in an Asian population through real-time monitoring: Protocol of the Continuous Observations of Behavioural Risk Factors in Asia study (COBRA).

Background: Modifiable risk factors for non-communicable diseases, including eating an unhealthy diet and being physically inactive, are influenced by complex and dynamic interactions between people and their social and physical environment. Therefore, understanding patterns and determinants of these risk factors as they occur in real life is essential to enable the design of precision public health interventions. Objective: This paper describes the protocol for the Continuous Observations of Behavioural Risk Factors in Asia study (COBRA). The study uses real-time data capture methods to gain a comprehensive understanding of eating and movement behaviours, including how these differ by socio-demographic characteristics and are shaped by people's interaction with their social and physical environment. Methods: COBRA is an observational study in free-living conditions. We will recruit 1500 adults aged 21-69 years from a large prospective cohort study. Real-time data capture methods will be used for nine consecutive days: an ecological momentary assessment app with a global positioning system enabled to collect location data, accelerometers to measure movement, and wearable sensors to monitor blood glucose levels. Participants receive six EMA surveys per day between 8 a.m. and 9.30 p.m. to capture information on behavioural risk factors including eating behaviours and diet composition movement behaviours (physical activity, sedentary behaviour, sleep), and related contextual factors. The second wave of ecological momentary assessment surveys with a global positioning system enabled will be sent 6 months later. Data will be analysed using generalised linear models to examine associations between behavioural risk factors and contextual determinants. Discussion: Findings from this study will advance our understanding of dietary and movement behaviours as they occur in real-life and inform the development of personalised interventions to prevent chronic diseases.

Diet and Physical Activity as Determinants of Continuously Measured Glucose Levels in Persons at High Risk of Type 2 Diabetes.

We examined how dietary and physical activity behaviors influence fluctuations in blood glucose levels over a seven-day period in people at high risk for diabetes. Twenty-eight participants underwent a mixed meal tolerance test to assess glucose homeostasis at baseline. Subsequently, they wore an accelerometer to assess movement behaviors, recorded their dietary intakes through a mobile phone application, and wore a flash glucose monitoring device that measured glucose levels every 15 min for seven days. Generalized estimating equation models were used to assess the associations of metabolic and lifestyle risk factors with glycemic variability. Higher BMI, amount of body fat, and selected markers of hyperglycemia and insulin resistance from the meal tolerance test were associated with higher mean glucose levels during the seven days. Moderate- to vigorous-intensity physical activity and polyunsaturated fat intake were independently associated with less variation in glucose levels (CV%). Higher protein and polyunsaturated fatty acid intakes were associated with more time-in-range. In contrast, higher carbohydrate intake was associated with less time-in-range. Our findings suggest that dietary composition (a higher intake of polyunsaturated fat and protein and lower intake of carbohydrates) and moderate-to-vigorous physical activity may reduce fluctuations in glucose levels in persons at high risk of diabetes.

mHealth interventions targeting movement behaviors in Asia: A scoping review.

mHealth interventions can promote healthy movement behaviors (physical activity, sedentary behavior, and sleep). However, recent reviews include few studies from Asia, despite it being home to over 60% of the world population. The aim is to map the current evidence for mHealth interventions targeting movement behaviors in Asia. Six databases were searched up until August 2021. Included studies described an mHealth intervention targeting one or more movement behaviors, delivered in a country/territory in Asia, to a general population. A total of 3986 unique records were screened for eligibility in duplicate. Eighty studies with 1,413,652 participants were included. Most were randomized (38.8%) or quasi-experimental (27.5%) trials. Studies were from 17 countries/territories (out of 55); majority were high- (65.0%) or upper middle-income (28.7%). Physical activity was targeted most often (93.8%), few targeted sedentary behavior (7.5%), or sleep (8.8%). Most targeted one movement behavior (90.0%), and none targeted all three together. Interventions typically incorporated a single mHealth component (70.0%; app, pedometer, text messages, wearable) and were delivered remotely (66.3%). The average intervention length was 121.8 (SD 127.6) days. mHealth interventions in Asia have primarily targeted physical activity in high- and upper middle-income countries. There are few interventions targeting sedentary behavior or sleep, and no interventions in low-income countries.

Increased oral processing and a slower eating rate increase glycaemic, insulin and satiety responses to a mixed meal tolerance test.

PURPOSE: Variations in specific oral processing behaviours may contribute to differences in glucose, insulin and satiety responses to a standardised test meal. This study tested how natural variations in oral processing between slower and faster eaters contribute to differences in post-prandial glucose (PP glucose), insulin response (PP insulin) and post-meal satiety for a standardised test meal. METHODS: Thirty-three participants with higher risk for type 2 diabetes consumed a standardised test-meal while being video recorded to derive specific oral processing behaviours. Plasma glucose, insulin and satiety measures were collected at baseline, during and post meal. Participants were split into slower and faster eaters using median split based on their eating rates and individual bolus properties were analysed at the point of swallow. RESULTS: There were large variations in eating rate (p < 0.001). While there was no significant difference in PP glucose response (p > 0.05), slower eaters showed significantly higher PP insulin between 45 and 60 min (p < 0.001). Slower eaters had longer oro-sensory exposure and increased bolus saliva uptake which was associated with higher PP glucose iAUC. Faster eating rate and larger bolus particle size at swallow correlated with lower PP glucose iAUC. A slower eating rate with greater chews per bite significantly increased insulin iAUC. Faster eaters also consistently rated their hunger and desire to eat higher than slower eaters (p < 0.05). CONCLUSIONS: Natural variations in eating rate and the associated oral processing contributed to differences in PP glucose, PP insulin and satiety responses. Encouraging increased chewing and longer oral-exposure time during consumption, may promote early glucose absorption and greater insulin and satiety responses, and help support euglycaemia. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT04522063.

Factors influencing medication adherence in patients with gout: A descriptive correlational study.

AIMS AND OBJECTIVES: To examine the factors influencing adherence to urate-lowering therapy in patients with gout in Singapore. BACKGROUND: Gout is the most common type of chronic inflammatory arthritis. Urate-lowering therapy is used to treat gout by reducing serum uric acid levels. However, adherence to urate-lowering therapy among patients remains poor. To date, there have been no available studies based on a conceptual framework that examined factors influencing medication adherence in patients with gout. DESIGN: Cross-sectional, descriptive correlational study. METHODS: A convenience sample of outpatients (n = 108) was recruited between October 2014-January 2015 from a tertiary hospital in Singapore. Outcomes were measured by relevant valid and reliable instruments. Descriptive statistics and parametric tests including multiple linear regression were used to analyse the data. RESULTS: Although 44.4% of the participants were high adherers to urate-lowering therapy, the mean adherence level was moderate. Significant differences in medication adherence scores were found among the subgroups of gender, ethnicity, marital status, employment status and presence of comorbidity. Medication adherence was positively significantly correlated with age, number of comorbidities and beliefs about medicines. Linear regression showed that higher level of beliefs about medicines, presence of comorbidity and being married were factors positively influencing medication adherence. CONCLUSIONS: This study revealed moderate adherence to urate-lowering therapy in patients with gout in Singapore, indicating the need for strategies to improve adherence by considering its main influencing factors. Future research should be conducted to develop interventions targeted at modifying patients' beliefs about medicines in order to improve medication adherence. RELEVANCE TO CLINICAL PRACTICE: Findings from this study allow healthcare providers to quickly and easily identify patients who may have low adherence. Nurses should take the lead in educating patients on the mechanism of urate-lowering therapy and highlight the importance of adhering to it.