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.

The cross-sectional and prospective associations of parental practices and environmental factors with 24-hour movement behaviours among school-aged Asian children.

BACKGROUND: Parental practices and neighbourhood environmental factors may influence children's movement behaviours. We aimed to investigate the cross-sectional and prospective associations of parental practices and neighbourhood environmental factors with accelerometer-measured 24-hour movement behaviours (24 h-MBs) among school-aged children in Singapore. METHODS: The Growing Up in Singapore Towards healthy Outcomes (GUSTO) study collected information on dimensions of parental practices and neighbourhood environment at age 5.5 years. Confirmatory factor analyses were performed to generate latent variables and used to compute overall parental practices [involvement in PA + support for PA + control of screen viewing context] and environmental scores [facilities for active play + active mobility facilitators + barriers*-1]. Children wore an accelerometer on their non-dominant wrist for seven consecutive days at ages 5.5 and 8 years. The R-package GGIR 2.6 was used to derive moderate-to-vigorous-intensity physical activity (MVPA), light-intensity physical activity (LPA), inactivity, and total-sleep (napping+night sleep) minutes per day. Associations were determined using compositional data analysis with multivariate linear regression models, taking into account potential confounders. RESULTS: Among 425 children (48% girls, 59% Chinese), higher parental involvement in PA, parental support for PA and overall parental practices were associated with 24 h-MBs at ages 5.5 and 8 years, specifically with greater time spent in MVPA and less time being inactive relative to the remaining movement behaviours. The corresponding mean changes in the overall 24 h-MB for increasing parental practices from lowest to highest scores (- 2 to + 2 z-scores) indicated potential increases of up to 15-minutes in MVPA, 20-minutes in LPA, 5-minutes in sleep duration, and a reduction of 40-minutes in inactivity at age 5.5 years. At age 8 years, this could translate to approximately 15-minutes more of MVPA, 20-minutes more of LPA, a 20-minute reduction in sleep duration, and a 20-minute reduction in inactivity. Parental control of screen viewing contexts and neighbourhood environmental factors were not associated with 24 h-MBs. CONCLUSIONS: Parental practices but not environmental factors were associated with higher MVPA and lower inactivity among Singaporean children, even at a later age. Further research may provide insights that support development of targeted public health strategies to promote healthier movement behaviours among children. STUDY REGISTRATION: This study was registered on 4th August 2010 and is available online at ClinicalTrials.gov: NCT01174875.

Promoting hEalthy Diet and Active Lifestyle (PEDAL): a protocol for the development and feasibility study of a multicomponent intervention among primary school children in Singapore.

BACKGROUND: Setting healthy lifestyle habits during the formative years of childhood is critical as habits can track to adulthood and help prevent obesity and chronic disease risks in later life. While multicomponent interventions have been shown to be effective in changing the lifestyle behaviours of children, there is a limited understanding of the feasibility of such interventions in primary schools in Singapore. A multiphase mixed method study was conducted to develop and examine the feasibility of a theory-based multicomponent school-based intervention-Promoting hEatlthy Eating and Active Lifestyle (PEDAL). METHODS: Underpinned by Kincaid's ideation model, the PEDAL intervention was developed to increase fruit and vegetable consumption and decrease sedentary behaviours among children. This study consists of three phases. Phase 1 details the development of PEDAL, which consists of four components: (A) a series of interactive health education lessons, (B) actionable home activities to support habit formation, (C) parental/guardian engagement, and (D) optimising the school environment. In Phase 2, components A and B of PEDAL were implemented in two public, co-educational primary schools among Primary 5 students (aged 10-12 years) in Singapore. Data was collected quantitatively using questionnaires and qualitatively using focus group discussions (FGDs) with students and teachers. The feasibility dimensions of components A and B, including recruitment capability, data collection, social validity, and practicality were examined, and ideation on healthy eating and physical activity was explored. In Phase 3, the full PEDAL intervention was pilot-tested in two other public, co-education primary schools with the same target population, using a concurrent mixed method quasi-experimental study design. Feasibility dimensions and potential effectiveness of the intervention will be assessed. DISCUSSION: This study will provide insights into the feasibility of PEDAL and inform its refinement. Findings from the pilot test will guide the planning of a larger-scale definitive trial. TRIAL REGISTRATION: Registered with ISRCTN registry (ISRCTN16114046) on 16 October 2022.

Trajectories of lifestyle patterns from 2 to 8 years of age and cardiometabolic risk in children: the GUSTO study.

BACKGROUND: Tracking combinations of lifestyle behaviours during childhood ("lifestyle pattern trajectories") can identify subgroups of children that might benefit from lifestyle interventions aiming to improve health outcomes later in life. However, studies on the critical transition period from early to middle childhood are limited. We aimed to describe lifestyle patterns trajectories in children from 2 to 8 years of age and evaluated their associations with cardiometabolic risk markers at age 8 years in a multi-ethnic Asian cohort. METHODS: Twelve lifestyle behaviours related to child's diet, physical activity, screen use, and sleep were ascertained using questionnaires at ages 2, 5, and 8 years. Age-specific lifestyle patterns were derived using principal component analysis and trajectories were determined using group-based multi-trajectory modelling. Child cardiometabolic risk markers were assessed at age 8 years, and associations with trajectories examined using multiple regression, adjusted for confounders. RESULTS: Among 546 children, two lifestyle patterns "healthy" and "unhealthy" were observed at ages 2, 5, and 8 years separately. Three trajectory groups from 2 to 8 years were identified: consistently healthy (11%), consistently unhealthy (18%), and mixed pattern (71%). Children in the consistently unhealthy group (vs. mixed pattern) had increased odds of pre-hypertension (OR = 2.96 [95% CI 1.18-7.41]) and higher levels of diastolic blood pressure (ß = 1.91 [0.27-3.55] mmHg), homeostasis model assessment of insulin resistance (ß = 0.43 [0.13-0.74]), triglycerides (ß = 0.11 [0.00-0.22] mmol/L), and metabolic syndrome score (ß = 0.85 [0.20-1.49]), but not with BMI z-score or any anthropometric measurements. The consistently healthy group showed no differences in cardiometabolic outcomes compared to the mixed pattern group. CONCLUSION: Three distinct lifestyle pattern trajectories were identified from early to middle childhood. Children in the consistently unhealthy lifestyle group did not have a raised BMI but was associated with several elevated cardiometabolic risk markers. These findings suggest the potential benefits of initiating holistic lifestyle interventions to improve children's health and well-being from an early age. TRIAL REGISTRATION: Trial registration number: NCT01174875. Name of registry: ClinicalTrials.gov. URL of registry: https://classic. CLINICALTRIALS: gov/ct2/show/NCT01174875 . Date of registration: August 4, 2010. Date of enrolment of the first participant to the trial: June 2009.

Associations between screen viewing at 2 and 3.5 years and drawing ability at 3.5 years among children from the French nationwide Elfe birth cohort.

The effect of screen viewing on children's cognitive development has been of concern among parents and researchers. This study investigated the association between children screen time, as reported by parents, and drawing ability, and the confounding effects of socioeconomic characteristics (such as parental education, household income, migration status) and children's competing activities (such as drawing practice, extracurricular activity, outdoor time, sleep time, time playing with parents). Participants included 7577 children aged 3.5 years (50% girls) who underwent the Draw-a-person test (McCarthy score [range = 0-12 points]) in the French nationwide Elfe birth cohort, initiated in 2011. Sex-stratified zero-inflated Poisson regression models were used. Increased screen time was associated with a higher likelihood to obtain a null score in boys (OR 1.15, 95% CI 1.07-1.23) and girls (1.13 [1.03-1.24]) and a lower score in girls only (ß = - 0.02, 95% CI - 0.04; - 0.01). After adjusting for SES, associations were no longer observed, indicating that the association between screen time and drawing abilities was confounded by socioeconomic characteristics.

Development and validation of a lifestyle risk index to screen for metabolic syndrome and its components in two multi-ethnic cohorts.

BACKGROUND: Metabolic syndrome (MetS) is a precursor to cardiovascular diseases and type 2 diabetes. Existing MetS prediction models relied heavily on biochemical measures and those based on non-invasive predictors such as lifestyle behaviours were limited. We aim to (1) develop a weighted lifestyle risk index for MetS and (2) externally validate this index using two Asian-based cohorts in Singapore. METHODS: Using data from the Multi-Ethnic Cohort (MEC) 1 (n = 2873, 41% male), multiple logistic regression was used to identify predictors associated with MetS. A weighted lifestyle risk index was generated using coefficients of the selected predictors in the development cohort (MEC1). Subsequently, the performance of the lifestyle risk index in predicting the occurrence of MetS within 10 years was assessed by discrimination and calibration in an external validation cohort (MEC2) (n = 6070, 43% male). RESULTS: A lifestyle risk index for MetS with nine predictors was developed (age, sex, ethnicity, having a family history of diabetes, BMI, diet, physical activity, smoking status, and screen time). This index demonstrated acceptable discrimination in the development cohort [AUC (95% CI) = 0.74 (0.71, 0.76)] and the validation cohort [AUC (95% CI) = 0.79 (0.77, 0.81)]. CONCLUSION: This lifestyle risk index exhibits potential for risk stratification in population-based screening programmes. Future research could apply a similar methodology to develop disease-specific lifestyle risk indices using nationwide registry-based data.

Effectiveness of holistic mobile health interventions on diet, and physical, and mental health outcomes: a systematic review and meta-analysis.

Background: Good physical and mental health are essential for healthy ageing. Holistic mobile health (mHealth) interventions-including at least three components: physical activity, diet, and mental health-could support both physical and mental health and be scaled to the population level. This review aims to describe the characteristics of holistic mHealth interventions and their effects on related behavioural and health outcomes among adults from the general population. Methods: In this systematic review and meta-analysis, we searched MEDLINE, Embase, Cochrane Central Register of Controlled Trials, PsycINFO, Scopus, China National Knowledge Infrastructure, and Google Scholar (first 200 records). The initial search covered January 1, 2011, to April 13, 2022, and an updated search extended from April 13, 2022 to August 30, 2023. Randomised controlled trials (RCTs) and non-randomised studies of interventions (NRSIs) were included if they (i) were delivered via mHealth technologies, (ii) included content on physical activity, diet, and mental health, and (iii) targeted adults (≥18 years old) from the general population or those at risk of non-communicable diseases (NCDs) or mental disorders. Studies were excluded if they targeted pregnant women (due to distinct physiological responses), individuals with pre-existing NCDs or mental disorders (to emphasise prevention), or primarily utilised web, email, or structured phone support (to focus on mobile technologies without exclusive human support). Data (summary data from published reports) extraction and risk-of-bias assessment were completed by two reviewers using a standard template and Cochrane risk-of-bias tools, respectively. Narrative syntheses were conducted for all studies, and random-effects models were used in the meta-analyses to estimate the pooled effect of interventions for outcomes with comparable data in the RCTs. The study was registered in PROSPERO, CRD42022315166. Findings: After screening 5488 identified records, 34 studies (25 RCTs and 9 pre-post NRSIs) reported in 43 articles with 5691 participants (mean age 39 years, SD 12.5) were included. Most (91.2%, n = 31/34) were conducted in high-income countries. The median intervention duration was 3 months, and only 23.5% (n = 8/34) of studies reported follow-up data. Mobile applications, short-message services, and mobile device-compatible websites were the most common mHealth delivery modes; 47.1% (n = 16/34) studies used multiple mHealth delivery modes. Of 15 studies reporting on weight change, 9 showed significant reductions (6 targeted on individuals with overweight or obesity), and in 10 studies reporting perceived stress levels, 4 found significant reductions (all targeted on general adults). In the meta-analysis, holistic mHealth interventions were associated with significant weight loss (9 RCTs; mean difference -1.70 kg, 95% CI -2.45 to -0.95; I2 = 89.00%) and a significant reduction in perceived stress levels (6 RCTs; standardised mean difference [SMD] -0.32; 95% CI -0.52 to -0.12; I2 = 14.52%). There were no significant intervention effects on self-reported moderate-to-vigorous physical activity (5 RCTs; SMD 0.21; 95%CI -0.25 to 0.67; I2 = 74.28%) or diet quality scores (5 RCTs; SMD 0.21; 95%CI -0.47 to 0.65; I2 = 62.27%). All NRSIs were labelled as having a serious risk of bias overall; 56% (n = 14/25) of RCTs were classified as having some concerns, and the others as having a high risk of bias. Interpretation: Findings from identified studies suggest that holistic mHealth interventions may aid reductions in weight and in perceived stress levels, with small to medium effect sizes. The observed effects on diet quality scores and self-reported moderate-to-vigorous physical activity were less clear and require more research. High-quality RCTs with longer follow-up durations are needed to provide more robust evidence. To promote population health, future research should focus on vulnerable populations and those in middle- and low-income countries. Optimal combinations of delivery modes and components to improve efficacy and sustain long-term effects should also be explored. Funding: National Research Foundation, Prime Minister's Office, Singapore, under its Campus for Research Excellence and Technological Enterprise (CREATE) Programme and Physical Activity and Nutrition Determinants in Asia (PANDA) Research Programme.

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.

Device-Measured Physical Activity and Sedentary Behavior in Relation to Cardiovascular Diseases and All-Cause Mortality: Systematic Review and Meta-Analysis of Prospective Cohort Studies.

Introduction: This review synthesized evidence from prospective cohort studies on the association of device-measured physical activity and sedentary behavior with cardiovascular disease and all-cause mortality among adults. Methods: Five databases were searched from 2000 through April 29, 2020. Study quality was appraised using the NIH Quality Assessment Tool. Pooled hazard ratio and 95% CI were obtained from random-effects meta-analyses. Subgroup analyses by age and sex were conducted for studies on all-cause mortality. Results: Of 29 articles included in the systematic review, 5 studies on cardiovascular disease mortality and 15 studies on all-cause mortality were included in meta-analyses. Comparing the highest with the lowest exposure categories, the pooled hazard ratios (95% CIs) for cardiovascular disease mortality were 0.29 (CI=0.18, 0.47) for total physical activity, 0.37 (CI=0.25, 0.55) for moderate-to-vigorous physical activity, 0.62 (0.41-0.93) for light physical activity, and 1.89 (CI=1.09, 3.29) for sedentary behavior. The pooled hazard ratios (95% CIs) for all-cause mortality were 0.42 (CI=0.34, 0.53) for total physical activity, 0.43 (CI=0.35, 0.53) for moderate-to-vigorous physical activity, 0.58 (CI=0.43, 0.80) for light physical activity, and 1.58 (CI=1.19, 2.09) for sedentary behavior. The pooled hazard ratio (95% CI) for all-cause mortality was 0.35 (CI=0.29, 0.42) for steps per day, but the studies available for analysis were conducted in older adults. The results of subgroup analyses were consistent with the main results. Discussion: Rapidly accumulating evidence suggests that more physical activity and less sedentary behavior are associated with a lower risk of cardiovascular disease and all-cause mortality. Similar beneficial relationships were found for step counts and all-cause mortality among older adults. Future studies employing standardized research methodologies and up-to-date data processing approaches are warranted to recommend specific amounts of physical activity and limits to sedentary behavior.

Cross-sectional and prospective associations between children's 24-h time use and their health-related quality of life: a compositional isotemporal substitution approach.

Background: Promoting active, balanced lifestyles among children may be an important approach to optimising their health-related quality of life (HRQoL). However, the relationships between children's movement behaviours and HRQoL remain unclear. Methods: We examined the associations between movement behaviours (sleep, inactivity, light and moderate-to-vigorous intensity physical activity) assessed using accelerometers at ages 8 and 10 years and self-reported HRQoL scores (overall, and physical and emotional well-being, self-esteem, relationship with family and friends, and school functioning domains) at age 10 years among 370 children in a local birth cohort using compositional isotemporal substitution techniques. Findings: Cross-sectionally, light and moderate-to-vigorous intensity physical activities were associated with better self-esteem (ß = 15.94 [2.71, 29.18]) and relationship with friends (ß = 10.28 [3.81, 16.74]) scores respectively. Prospectively, inactivity was associated with lower overall HRQoL (ß = -10.00 [-19.13, -0.87]), relationship with friends (ß = -16.41 [-31.60, -1.23]) and school functioning (ß = -15.30 [-29.16, -1.44]) scores, while sleep showed a positive trend with overall HRQoL (ß = 10.76 [-1.09, 22.61]) and school functioning (ß = 17.12 [-0.87, 35.10]) scores. Children's movement behaviours were not associated with their physical and emotional well-being, or relationship with family scores. The isotemporal substitution analyses suggest that increasing time spent in physical activity and/or sleep at the expense of inactivity may benefit children's HRQoL. Interpretation: Our findings suggest that sleep and physical activity may be associated with better HRQoL, with the inverse for inactivity. However, the relationship between children's movement behaviours and HRQoL is complex and warrants further research. Funding: Singapore National Research Foundation, Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research.

Patterns and correlates of physical activity and sedentary behavior among Bangkok residents: A cross-sectional study.

BACKGROUND: Physical inactivity and sedentary behavior are significant risk factors for various non-communicable diseases. Bangkok, Thailand's capital, is one of the fastest-growing metropolitans in Southeast Asia. Few studies have investigated the epidemiology of physical activity and sedentary behavior among Bangkok residents. This study aims to investigate the prevalence of combined physical activity and sedentary behavior patterns among Bangkok residents and examine relationships between participants' characteristics and the combined movement patterns. METHODS: We analyzed data from the nationally representative 2021 Health Behavior Survey conducted by the Thailand National Statistical Office. The Global Physical Activity Questionnaire was used to assess physical activity and sedentary behavior. 'Sufficiently active' was defined as meeting the World Health Organization's guidelines for aerobic physical activity (≥150 minutes of moderate-to-vigorous physical activity per week). 'Low sedentary time' was defined as sitting for ≤7 hours per day. Participants were categorized into one of four movement patterns: highly active/low sedentary, highly active/highly sedentary, low active/low sedentary, and low active/highly sedentary. Multinomial logistic regression was used to identify the factors associated with each group of four movement patterns. RESULTS: Among the 3,137 individuals included in the study, the majority were categorized as highly active/highly sedentary (64.8%), followed by highly active/low sedentary (17.9%) and low active/highly sedentary (14.3%). Only a few (3.0%) of participants were categorized as being low active/low sedentary. Compared to males, female participants had a significantly higher likelihood of belonging to the highly active/low sedentary (AOR = 1.69, 95%CI: 1.25, 2.28) or highly active/highly sedentary (AOR = 1.51, 95%CI: 1.19, 1.93) group, rather than the low active/high sedentary group. Compared to unemployed/retired participants, those in labor-intensive occupations had a significantly higher likelihood of being in the highly active/low sedentary group (AOR = 1.89, 95%CI: 1.22, 2.94). Compared to participants with no chronic physical conditions, participants who reported multimorbidity had a significantly lower likelihood of being in the highly active/low sedentary group (AOR = 0.60, 95%CI: 0.37, 0.98). CONCLUSION: This study provides valuable insights into the patterns of physical activity and sedentary behavior among residents of Bangkok using up-to-date data. The majority belonged to the highly active/highly sedentary group, followed by the highly active/low sedentary group. Correlates such as sex, occupation, and chronic conditions were associated with these patterns. Targeted interventions in recreational activities, workplaces, and urban areas, including screen time control measures, movement breaks and improved built environments, are crucial in reducing sedentary behavior and promoting physical activity.

Acculturation as a Determinant of Obesity and Related Lifestyle Behaviors in a Multi-Ethnic Asian Population.

Limited attention has been given to the role of cultural orientation towards different ethnic groups in multi-ethnic settings without a dominant host culture. We evaluated whether acculturation levels, reflecting cultural orientation towards other ethnic groups, were associated with obesity and related lifestyle behaviors in a cosmopolitan Asian population. We conducted the current study based on data from the Singapore Multi-Ethnic Cohort (N = 10,622) consisting of ethnic Chinese, Malays, and Indians aged 21 to 75 years. Multivariable linear and logistic regression analyses were used to examine associations between the acculturation level (z-score), obesity, and related lifestyle behaviors, including dietary habits and physical activity. A higher acculturation level was directly associated with a higher prevalence of obesity among Chinese, whereas an inverse association was found for ethnic Indians, and no significant association in Malays. In ethnic Malays, greater acculturation was significantly associated with higher dietary quality and less sedentary time. Furthermore, a high acculturation level was significantly associated with higher sugar-sweetened beverage consumption and more leisure-time PA in all ethnic groups. Our findings suggest that greater cultural orientation towards other ethnic groups was associated with convergence in obesity levels. More research is required to understand how acculturation affects obesity-related lifestyle factors in multi-ethnic settings.

Risk prediction models for type 2 diabetes using either fasting plasma glucose or HbA1c in Chinese, Malay, and Indians: Results from three multi-ethnic Singapore cohorts.

AIMS: To assess three well-established type 2 diabetes (T2D) risk prediction models based on fasting plasma glucose (FPG) in Chinese, Malays, and Indians, and to develop simplified risk models based on either FPG or HbA1c. METHODS: We used a prospective multiethnic Singapore cohort to evaluate the established models and develop simplified models. 6,217 participants without T2D at baseline were included, with an average follow-up duration of 8.3 years. The simplified risk models were validated in two independent multiethnic Singapore cohorts (N = 12,720). RESULTS: The established risk models had moderate-to-good discrimination (area under the receiver operating characteristic curves, AUCs 0.762 - 0.828) but a lack of fit (P-values < 0.05). Simplified risk models that included fewer predictors (age, BMI, systolic blood pressure, triglycerides, and HbA1c or FPG) showed good discrimination in all cohorts (AUCs ≥ 0.810), and sufficiently captured differences between the ethnic groups. While recalibration improved fit the simplified models in validation cohorts, there remained evidence of miscalibration in Chinese (p ≤ 0.012). CONCLUSIONS: Simplified risk models including HbA1c or FPG had good discrimination in predicting incidence of T2D in three major Asian ethnic groups. Risk functions with HbA1c performed as well as those with FPG.

The physical activity at work (PAW) study: a cluster randomised trial of a multicomponent short-break intervention to reduce sitting time and increase physical activity among office workers in Thailand.

Background: Sedentary behaviour increases the risks of non-communicable diseases. The objective of this trial was to evaluate the effect of the Physical Activity at Work multicomponent intervention to reduce sedentary behaviour in Thai office workers. Methods: Offices under the Ministry of Public Health Thailand, were randomly allocated to the intervention and control group in a 1:1 ratio, stratified by office size. The intervention included individual (pedometer and lottery-based financial incentives), social (group movement breaks), environmental (posters), and organisational (leader encouragement) components. At baseline and 6-month follow-up, participants wore ActiGraphTM on the waist for ten days. The primary outcome was the between-group difference in sedentary time at 6-month, analysed using a linear mixed-effects model. Other outcomes were physical activity, biomarkers, productivity, and musculoskeletal health. Trial registration: The PAW study was registered at the Thai Clinical Trials Registry (ID TCTR20200604007) on 02 June 2020. Findings: 282 office workers were recruited and randomly allocated to the control group (142 participants, nine offices) and the intervention group (140 participants, nine offices). The mean age was 38.6 years (SD = 10.4), and 81% were women. There was no evidence of intervention effects on sedentary time during waking hours (-26.8; 95% CI = -69.2 to 15.7 min), physical activity levels, or biomarkers between groups at 6-month. In the adjusted analysis, increases in time spent in moderate-to-vigorous physical activity (5.45; 95% CI = -0.15 to 11.1 min) and step count (718; 95% CI = -45 to 1481 steps) during waking hours were observed, although there was no evidence of a difference between groups. Interpretation: The intervention did not significantly reduce sedentary time in Thai office workers. Suboptimal intervention uptake due to Covid-19 pandemic restrictions and loss of statistical power associated with recruitment constraints may explain this result. Further investigations are needed to evaluate the processes of the trial. Funding: The Thai Health Promotion Foundation and the International Decision Support Initiative (iDSI).

Association Between Domain-Specific Physical Activity and Cardiometabolic Factors in a Multiethnic Asian Population: A Longitudinal Study.

AIMS: To examine the association between domain-specific physical activity (PA) and cardiometabolic factors with longitudinal data, which is limited in current literature. METHODS: Participants who attended the Singapore Multi-Ethnic Cohort and follow-up surveys were included in this study (N = 3950, mean age: 44.7 y, female: 57.9%). Self-reported moderate- to vigorous-intensity PA (MVPA) for each domain (leisure-time, transportation, occupation, and household) was categorized into 4 levels: no, low, middle, and high MVPA. The longitudinal associations of domain-specific MVPA with cardiometabolic factors including systolic and diastolic blood pressures, low-density and high-density lipoprotein cholesterols, triglycerides, and body mass index were examined using Generalized Estimating Equations, accounting for confounding factors and repeated measurements. RESULTS: There were 5.2% participants who had no MVPA. For each domain, this rate ranged from 22.6% (household) to 83.3% (occupation). Leisure-time and occupation MVPAs had positive and linear associations with high-density lipoprotein cholesterols, corresponding to 0.030 (95% confidence interval, 0.015 to 0.045) mmol/L (leisure-time) and 0.063 (95% confidence interval, 0.043 to 0.083) mmol/L (occupation), when compared high with no respective MVPA. Occupation and household MVPAs were associated with low-density lipoprotein cholesterol. Transportation and occupation exhibited a positive and linear relationship with diastolic blood pressure. None of the domains were associated with body mass index, systolic blood pressures, or triglycerides. CONCLUSIONS: This study showed that each domain had differential association with individual cardiometabolic risk factors. As occupation, transportation, or household PA had unfavorable associations with low-density lipoprotein cholesterol or diastolic blood pressure, the overall beneficial impact of higher PA levels may not necessarily hold in the context of domain-specific PA and cardiovascular health. Further investigation is needed to corroborate our findings.

Development of "LvL UP 1.0": a smartphone-based, conversational agent-delivered holistic lifestyle intervention for the prevention of non-communicable diseases and common mental disorders.

Background: Non-communicable diseases (NCDs) and common mental disorders (CMDs) are the leading causes of death and disability worldwide. Lifestyle interventions via mobile apps and conversational agents present themselves as low-cost, scalable solutions to prevent these conditions. This paper describes the rationale for, and development of, "LvL UP 1.0″, a smartphone-based lifestyle intervention aimed at preventing NCDs and CMDs. Materials and Methods: A multidisciplinary team led the intervention design process of LvL UP 1.0, involving four phases: (i) preliminary research (stakeholder consultations, systematic market reviews), (ii) selecting intervention components and developing the conceptual model, (iii) whiteboarding and prototype design, and (iv) testing and refinement. The Multiphase Optimization Strategy and the UK Medical Research Council framework for developing and evaluating complex interventions were used to guide the intervention development. Results: Preliminary research highlighted the importance of targeting holistic wellbeing (i.e., both physical and mental health). Accordingly, the first version of LvL UP features a scalable, smartphone-based, and conversational agent-delivered holistic lifestyle intervention built around three pillars: Move More (physical activity), Eat Well (nutrition and healthy eating), and Stress Less (emotional regulation and wellbeing). Intervention components include health literacy and psychoeducational coaching sessions, daily "Life Hacks" (healthy activity suggestions), breathing exercises, and journaling. In addition to the intervention components, formative research also stressed the need to introduce engagement-specific components to maximise uptake and long-term use. LvL UP includes a motivational interviewing and storytelling approach to deliver the coaching sessions, as well as progress feedback and gamification. Offline materials are also offered to allow users access to essential intervention content without needing a mobile device. Conclusions: The development process of LvL UP 1.0 led to an evidence-based and user-informed smartphone-based intervention aimed at preventing NCDs and CMDs. LvL UP is designed to be a scalable, engaging, prevention-oriented, holistic intervention for adults at risk of NCDs and CMDs. A feasibility study, and subsequent optimisation and randomised-controlled trials are planned to further refine the intervention and establish effectiveness. The development process described here may prove helpful to other intervention developers.

Safety, Tolerability, and Pharmacokinetics of ß-Cryptoxanthin Supplementation in Healthy Women: A Double-Blind, Randomized, Placebo-Controlled Clinical Trial.

BACKGROUND: ß-cryptoxanthin is a dietary carotenoid for which there have been few studies on the safety and pharmacokinetics following daily oral supplementation. METHODS: 90 healthy Asian women between 21 and 35 years were randomized into three groups: 3 and 6 mg/day oral ß-cryptoxanthin, and placebo. At 2, 4, and 8 weeks of supplementation, plasma carotenoid levels were measured. The effects of ß-cryptoxanthin on blood retinoid-dependent gene expression, mood, physical activity and sleep, metabolic parameters, and fecal microbial composition were investigated. RESULTS: ß-cryptoxanthin supplementation for 8 weeks (3 and 6 mg/day) was found to be safe and well tolerated. Plasma ß-cryptoxanthin concentration was significantly higher in the 6 mg/day group (9.0 ± 4.1 µmol/L) compared to 3 mg/day group (6.0 ± 2.6 µmol/L) (p < 0.03), and placebo (0.4 ± 0.1 µmol/L) (p < 0.001) after 8 weeks. Plasma all-trans retinol, α-cryptoxanthin, α-carotene, ß-carotene, lycopene, lutein, and zeaxanthin levels were not significantly changed. No effects were found on blood retinol-dependent gene expression, mood, physical activity and sleep, metabolic parameters, and fecal microbial composition. CONCLUSIONS: Oral ß-cryptoxanthin supplementation over 8 weeks lead to high plasma concentrations of ß-cryptoxanthin, with no impact on other carotenoids, and was well tolerated in healthy women.

Holistic mHealth interventions for the promotion of healthy ageing: protocol for a systematic review.

INTRODUCTION: Maintaining physical and mental health is essential for healthy ageing. It can be supported by modifying lifestyle factors such as physical activity and diet. Poor mental health, in turn, contributes to the opposing effect. The promotion of healthy ageing may therefore benefit from holistic interventions integrating physical activity, diet and mental health. These interventions can be scaled up to the population level by using mobile technologies. However, systematic evidence regarding the characteristics and effectiveness of such holistic mHealth interventions remains limited. This paper presents a protocol for a systematic review that aims to provide an overview of the current state of the evidence for holistic mHealth interventions, including their characteristics and effects on behavioural and health outcomes in general adult populations . METHODS AND ANALYSIS: We will conduct a comprehensive search for randomised controlled trials and non-randomised studies of interventions published between January 2011 and April 2022 in MEDLINE, Embase, Cochrane Central Register of Controlled Trials, PsycINFO, Scopus, China National Knowledge Infrastructure and Google Scholar (first 200 records). Eligible studies will be mHealth interventions targeting general adult populations with content on physical activity, diet and mental health. We will extract information on all relevant behavioural and health outcomes, as well as those related to intervention feasibility. Screening and data extraction processes will be carried out independently by two reviewers. Cochrane risk-of-bias tools will be used to assess risk of bias. We will provide a narrative overview of the findings from eligible studies. With sufficient data, a meta-analysis will be conducted. ETHICS AND DISSEMINATION: Ethical approval is not required because this study is a systematic review based on published data. We intend to publish our findings in a peer-reviewed journal and present the study at international conferences. PROSPERO REGISTRATION NUMBER: CRD42022315166.

Longitudinal Analysis of Patterns and Correlates of Physical Activity and Sedentary Behavior in Women From Preconception to Postpartum: The Singapore Preconception Study of Long-Term Maternal and Child Outcomes Cohort.

OBJECTIVE: Longitudinal changes in physical activity (PA) and sedentary behavior patterns from preconception to postpartum are not fully characterized. We examined changes and baseline sociodemographic/clinical correlates of PA and sedentary behavior in women from preconception to postpartum. METHODS: The Singapore Preconception Study of Long-Term Maternal and Child Outcomes cohort recruited 1032 women planning pregnancy. Participants completed questionnaires at preconception, 34 to 36 weeks gestation, and 12 months postpartum. Repeated-measures linear regression models were used to analyze changes in walking, moderate to vigorous PA (MVPA), screen time, and total sedentary time, and to identify sociodemographic/clinical correlates associated with these changes. RESULTS: Of the 373 women who delivered singleton live births, 281 provided questionnaires for all time points. Walking time increased from preconception to late pregnancy but decreased postpartum (adjusted means [95% CI]: 454 [333-575], 542 [433-651], and 434 [320-547] min/wk, respectively). Vigorous-intensity PA and MVPA decreased from preconception to late pregnancy but increased postpartum (vigorous-intensity PA: 44 [11-76], 1 [-3-5], and 11 [4-19] min/wk, MVPA: 273 [174-372], 165 [95-234], and 226 [126-325] min/wk, respectively). Screen time and total sedentary time remained consistent from preconception to pregnancy but decreased postpartum (screen: 238 [199-277], 244 [211-277], and 162 [136-189] min/d, total: 552 [506-598], 555 [514-596], and 454 [410-498] min/d, respectively). Individual characteristics of ethnicity, body mass index, employment, parity, and self-rated general health significantly influenced women's activity patterns. CONCLUSION: During late pregnancy, walking time increased, while MVPA declined significantly, and partially returned to preconception levels postpartum. Sedentary time remained stable during pregnancy but decreased postpartum. The identified set of sociodemographic/clinical correlates underscores need for targeted strategies.

Exploring the potential of mobile health interventions to address behavioural risk factors for the prevention of non-communicable diseases in Asian populations: a qualitative study.

BACKGROUND: Changing lifestyle patterns over the last decades have seen growing numbers of people in Asia affected by non-communicable diseases and common mental health disorders, including diabetes, cancer, and/or depression. Interventions targeting healthy lifestyle behaviours through mobile technologies, including new approaches such as chatbots, may be an effective, low-cost approach to prevent these conditions. To ensure uptake and engagement with mobile health interventions, however, it is essential to understand the end-users' perspectives on using such interventions. The aim of this study was to explore perceptions, barriers, and facilitators to the use of mobile health interventions for lifestyle behaviour change in Singapore. METHODS: Six virtual focus group discussions were conducted with a total of 34 participants (mean ± SD; aged 45 ± 3.6 years; 64.7% females). Focus group recordings were transcribed verbatim and analysed using an inductive thematic analysis approach, followed by deductive mapping according to perceptions, barriers, facilitators, mixed factors, or strategies. RESULTS: Five themes were identified: (i) holistic wellbeing is central to healthy living (i.e., the importance of both physical and mental health); (ii) encouraging uptake of a mobile health intervention is influenced by factors such as incentives and government backing; (iii) trying out a mobile health intervention is one thing, sticking to it long term is another and there are key factors, such as personalisation and ease of use that influence sustained engagement with mobile health interventions; (iv) perceptions of chatbots as a tool to support healthy lifestyle behaviour are influenced by previous negative experiences with chatbots, which might hamper uptake; and (v) sharing health-related data is OK, but with conditions such as clarity on who will have access to the data, how it will be stored, and for what purpose it will be used. CONCLUSIONS: Findings highlight several factors that are relevant for the development and implementation of mobile health interventions in Singapore and other Asian countries. Recommendations include: (i) targeting holistic wellbeing, (ii) tailoring content to address environment-specific barriers, (iii) partnering with government and/or local (non-profit) institutions in the development and/or promotion of mobile health interventions, (iv) managing expectations regarding the use of incentives, and (iv) identifying potential alternatives or complementary approaches to the use of chatbots, particularly for mental health.