Dietary Patterns and Cardiovascular Diseases in Asia: A Systematic Review and Meta-Analysis.

With emerging Asian-derived diet quality indices and data-driven dietary patterns available, we aimed to synthesize the various dietary patterns and quantify its association with cardiovascular diseases (CVDs) among Asian populations. We systematically searched PubMed, Embase, Scopus, and Web of Science for observational studies in South, Southeast, and East Asia. Dietary patterns were grouped "high-quality," which included high intakes of three or more of the following food groups: 1) fruits and vegetables, 2) whole grains, 3) healthy protein sources (legumes and nuts, fish and seafood, low-fat dairy, and lean meat and poultry), and 4) liquid plant oils. High-quality patterns were further subcategorized based on their derivation methods: non-Asian indices, Asian indices, data-driven patterns, and plant-based indices. Dietary patterns were grouped "low-quality," which included high intakes of two or more of the following: 5) ultraprocessed food, 6) beverages and foods with added sugars, 7) foods high in salt, and 8) alcoholic beverages. Data-driven dietary patterns characterized by animal food sources were labeled "animal-based," and studies using dietary diversity scores were labeled "diet diversity indices." Dietary patterns that could not be meaningfully categorized were summarized narratively. Study-specific effect estimates were pooled using a random-effects model. Forty-one studies were included in this review. Higher adherence to high-quality dietary patterns in the top compared with bottom tertile defined by non-Asian indices (RR: 0.78; 95% CI: 0.69, 0.88; GRADE: moderate), Asian indices (RR: 0.84; 95% CI: 0.79, 0.90; GRADE: low), and data-driven patterns (RR: 0.81; 95% CI: 0.74, 0.89; GRADE: moderate) were associated with lower CVD risk. Plant-based, low-quality, animal-based, and diet diversity indices dietary patterns were not associated with CVD. Associations of Asian diet quality indices and CVD risk were weaker than those with non-Asian indices, highlighting the need for current Asian diet quality criteria to be updated to better capture the impact of diet on CVD. The systematic review and meta-analysis was registered at PROSPERO as CRD42021244318.

Rationale, Design, and Baseline Characteristics of Participants in the Health@NUS mHealth Augmented Cohort Study Examining Student-to-Work Life Transition: Protocol for a Prospective Cohort Study.

BACKGROUND: Integration of mobile health data collection methods into cohort studies enables the collection of intensive longitudinal information, which gives deeper insights into individuals' health and lifestyle behavioral patterns over time, as compared to traditional cohort methods with less frequent data collection. These findings can then fill the gaps that remain in understanding how various lifestyle behaviors interact as students graduate from university and seek employment (student-to-work life transition), where the inability to adapt quickly to a changing environment greatly affects the mental well-being of young adults. OBJECTIVE: This paper aims to provide an overview of the study methodology and baseline characteristics of participants in Health@NUS, a longitudinal study leveraging mobile health to examine the trajectories of health behaviors, physical health, and well-being, and their diverse determinants, for young adults during the student-to-work life transition. METHODS: University students were recruited between August 2020 and June 2022 in Singapore. Participants would complete biometric assessments and questionnaires at 3 time points (baseline, 12-, and 24-month follow-up visits) and use a Fitbit smartwatch and smartphone app to continuously collect physical activity, sedentary behavior, sleep, and dietary data over the 2 years. Additionally, up to 12 two-week-long bursts of app-based ecological momentary surveys capturing lifestyle behaviors and well-being would be sent out among the 3 time points. RESULTS: Interested participants (n=1556) were screened for eligibility, and 776 participants were enrolled in the study between August 2020 and June 2022. Participants were mostly female (441/776, 56.8%), of Chinese ethnicity (741/776, 92%), undergraduate students (759/776, 97.8%), and had a mean BMI of 21.9 (SD 3.3) kg/m2, and a mean age of 22.7 (SD 1.7) years. A substantial proportion were overweight (202/776, 26.1%) or obese (42/776, 5.4%), had indicated poor mental well-being (World Health Organization-5 Well-Being Index ≤50; 291/776, 37.7%), or were at higher risk for psychological distress (Kessler Psychological Distress Scale ≥13; 109/776, 14.1%). CONCLUSIONS: The findings from this study will provide detailed insights into the determinants and trajectories of health behaviors, health, and well-being during the student-to-work life transition experienced by young adults. TRIAL REGISTRATION: ClinicalTrials.gov NCT05154227; https://clinicaltrials.gov/study/NCT05154227. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/56749.

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.

Genome-Wide Interaction Analysis With DASH Diet Score Identified Novel Loci for Systolic Blood Pressure.

BACKGROUND: The Dietary Approaches to Stop Hypertension (DASH) diet score lowers blood pressure (BP). We examined interactions between genotype and the DASH diet score in relation to systolic BP. METHODS: We analyzed up to 9 420 585 single nucleotide polymorphisms in up to 127 282 individuals of 6 population groups (91% of European population) from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (n=35 660) and UK Biobank (n=91 622) and performed European population-specific and cross-population meta-analyses. RESULTS: We identified 3 loci in European-specific analyses and an additional 4 loci in cross-population analyses at Pinteraction<5e-8. We observed a consistent interaction between rs117878928 at 15q25.1 (minor allele frequency, 0.03) and the DASH diet score (Pinteraction=4e-8; P for heterogeneity, 0.35) in European population, where the interaction effect size was 0.42±0.09 mm Hg (Pinteraction=9.4e-7) and 0.20±0.06 mm Hg (Pinteraction=0.001) in Cohorts for Heart and Aging Research in Genomic Epidemiology and the UK Biobank, respectively. The 1 Mb region surrounding rs117878928 was enriched with cis-expression quantitative trait loci (eQTL) variants (P=4e-273) and cis-DNA methylation quantitative trait loci variants (P=1e-300). Although the closest gene for rs117878928 is MTHFS, the highest narrow sense heritability accounted by single nucleotide polymorphisms potentially interacting with the DASH diet score in this locus was for gene ST20 at 15q25.1. CONCLUSIONS: We demonstrated gene-DASH diet score interaction effects on systolic BP in several loci. Studies with larger diverse populations are needed to validate our findings.

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.