Understanding knowledge, attitudes and behaviours related to dietary sodium intake in a multi-ethnic population in Singapore.

OBJECTIVE: This study aimed to fill the current gap in the understanding of the knowledge, attitudes and behaviours (KAB) related to dietary Na among adult residents in Singapore. DESIGN: A cross-sectional online survey was conducted between October and December 2020 on 955 participants selected through random sampling. SETTING: The survey was conducted in Singapore. PARTICIPANTS: Participants were recruited from the Singapore Population Health Study Online Panel. RESULTS: Participants' mean age was 46·6 ± 14·1 years old and 58 % of them were females. Most of the participants were Chinese (82·1 %), 10·5 % were Indian and 4·5 % were Malay. Findings from the weighted data showed that most participants were aware of the health impact of high Na consumption. However, many participants were unaware of the recommended intake for salt (68%) and Na (83%), had misconceptions, and were unable to correctly use food labels to assess NA content (69%). Findings also alluded to the presence of knowledge gaps in the sources of Na in their diet. While 59 % of the participants reported to be limiting their consumption of Na, many reported facing barriers such as not knowing how to limit their Na intake. Participants also felt that there were limited options for low-Na foods when eating out and were lacking awareness of low-Na products. CONCLUSIONS: Findings highlighted substantial gaps in participants' knowledge and skills in managing their Na consumption. This suggests the need for more public education and improvements in the food environment.

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.

Cost benefit analysis of alternative testing and quarantine policies for travelers for infection control: A case study of Singapore during the COVID-19 pandemic.

Background: Border control mitigates local infections but bears a heavy economic cost, especially for tourism-reliant countries. While studies have supported the efficacy of border control in suppressing cross-border transmission, the trade-off between costs from imported and secondary cases and from lost economic activities has not been studied. This case study of Singapore during the COVID-19 pandemic aims to understand the impacts of varying quarantine length and testing strategies on the economy and health system. Additionally, we explored the impact of permitting unvaccinated travelers to address emerging equity concerns. We assumed that community transmission is stable and vaccination rates are high enough that inbound travelers are not dissuaded from traveling. Methods: The number of travelers was predicted considering that longer quarantine reduces willingness to travel. A micro-simulation model predicted the number of COVID-19 cases among travelers, the resultant secondary cases, and the probability of being symptomatic in each group. The incremental net monetary benefit (INB) of Singapore was quantified under each border-opening policy compared to pre-opening status, based on tourism receipts, cost/profit from testing and quarantine, and cost and health loss due to COVID-19 cases. Results: Compared to polymerase chain reaction (PCR), rapid antigen test (ART) detects fewer imported cases but results in fewer secondary cases. Longer quarantine results in fewer cases but lower INB due to reduced tourism receipts. Assuming the proportion of unvaccinated travelers is small (8% locally and 24% globally), allowing unvaccinated travelers will accrue higher INB without exceeding the intensive care unit (ICU) capacity. The highest monthly INB from all travelers is $2,236.24 m, with 46.69 ICU cases per month, achieved with ARTs at pre-departure and on arrival without quarantine. The optimal policy in terms of highest INB is robust under changes to various model assumptions. Among all cost-benefit components, the top driver for INB is tourism receipts. Conclusions: With high vaccination rates locally and globally alongside stable community transmission, opening borders to travelers regardless of vaccination status will increase economic growth in the destination country. The caseloads remain manageable without exceeding ICU capacity, and costs of cases are offset by the economic value generated from travelers.

Economic Analysis of Border Control Policies during COVID-19 Pandemic: A Modelling Study to Inform Cross-Border Travel Policy between Singapore and Thailand.

With countries progressing towards high COVID-19 vaccination rates, strategies for border reopening are required. This study focuses on Thailand and Singapore, two countries that share significant tourism visitation, to illustrate a framework for optimizing COVID-19 testing and quarantine policies for bilateral travel with a focus on economic recovery. The timeframe is the month of October 2021, when Thailand and Singapore were preparing to reopen borders for bilateral travel. This study was conducted to provide evidence for the border reopening policy decisions. Incremental net benefit (INB) compared to the pre-opening period was quantified through a willingness-to-travel model, a micro-simulation COVID-19 transmission model and an economic model accounting for medical and non-medical costs/benefits. Multiple testing and quarantine policies were examined, and Pareto optimal (PO) policies and the most influential components were identified. The highest possible INB for Thailand is US $125.94 million, under a PO policy with no quarantine but with antigen rapid tests (ARTs) pre-departure and upon arrival to enter both countries. The highest possible INB for Singapore is US $29.78 million, under another PO policy with no quarantine on both sides, no testing to enter Thailand, and ARTs pre-departure and upon arrival to enter Singapore. Tourism receipts and costs/profits of testing and quarantine have greater economic impacts than that from COVID-19 transmission. Provided healthcare systems have sufficient capacity, great economic benefits can be gained for both countries by relaxing border control measures.

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.

The socioeconomic landscape of the exposome during pregnancy.

BACKGROUND: While socioeconomic position (SEP) is consistently related to pregnancy and birth outcome disparities, relevant biological mechanisms are manifold, thus necessitating more comprehensive characterization of SEP-exposome associations during pregnancy. OBJECTIVES: We implemented an exposomic approach to systematically characterize the socioeconomic landscape of prenatal exposures in a setting where social segregation was less distinct in a hypotheses-generating manner. METHODS: We described the correlation structure of 134 prenatal exogenous and endogenous sources (e.g., micronutrients, hormones, immunomodulatory metabolites, environmental pollutants) collected in a diverse, population-representative, urban, high-income longitudinal mother-offspring cohort (N = 1341; 2009-2011). We examined the associations between maternal, paternal, household, and areal level SEP indicators and 134 exposures using multiple regressions adjusted for precision variables, as well as potential effect measure modification by ethnicity and nativity. Finally, we generated summary SEP indices using Multiple Correspondence Analysis to further explore possible curved relationships. RESULTS: Individual and household SEP were associated with anthropometric/adiposity measures, folate, omega-3 fatty acids, insulin-like growth factor-II, fasting glucose, and neopterin, an inflammatory marker. We observed paternal education was more strongly and consistently related to maternal exposures than maternal education. This was most apparent amongst couples discordant on education. Analyses revealed additional non-linear associations between areal composite SEP and particulate matter. Environmental contaminants (e.g., per- and polyfluoroalkyl substances) and micronutrients (e.g., folate and copper) showed opposing associations by ethnicity and nativity, respectively. DISCUSSION: SEP-exposome relationships are complex, non-linear, and context specific. Our findings reinforce the potential role of paternal contributions and context-specific modifiers of associations, such as between ethnicity and maternal diet-related exposures. Despite weak presumed areal clustering of individual exposures in our context, our approach reinforces subtle non-linearities in areal-level exposures.

Estimating direct and spill-over impacts of political elections on COVID-19 transmission using synthetic control methods.

Mass gathering events have been identified as high-risk environments for community transmission of coronavirus disease 2019 (COVID-19). Empirical estimates of their direct and spill-over effects however remain challenging to identify. In this study, we propose the use of a novel synthetic control framework to obtain causal estimates for direct and spill-over impacts of these events. The Sabah state elections in Malaysia were used as an example for our proposed methodology and we investigate the event's spatial and temporal impacts on COVID-19 transmission. Results indicate an estimated (i) 70.0% of COVID-19 case counts within Sabah post-state election were attributable to the election's direct effect; (ii) 64.4% of COVID-19 cases in the rest of Malaysia post-state election were attributable to the election's spill-over effects. Sensitivity analysis was further conducted by examining epidemiological pre-trends, surveillance efforts, varying synthetic control matching characteristics and spill-over specifications. We demonstrate that our estimates are not due to pre-existing epidemiological trends, surveillance efforts, and/or preventive policies. These estimates highlight the potential of mass gatherings in one region to spill-over into an outbreak of national scale. Relaxations of mass gathering restrictions must therefore be carefully considered, even in the context of low community transmission and enforcement of safe distancing guidelines.

Increased Dengue Transmissions in Singapore Attributable to SARS-CoV-2 Social Distancing Measures.

Social distancing (SD) measures aimed at curbing the spread of SARS-CoV-2 remain an important public health intervention. Little is known about the collateral impact of reduced mobility on the risk of other communicable diseases. We used differences in dengue case counts pre- and post implementation of SD measures and exploited heterogeneity in SD treatment effects among different age groups in Singapore to identify the spillover effects of SD measures. SD policy caused an increase of over 37.2% in dengue cases from baseline. Additional measures to preemptively mitigate the risk of other communicable diseases must be considered before the implementation/reimplementation of SARS-CoV-2 SD measures.

Revealing two dynamic dengue epidemic clusters in Thailand.

BACKGROUND: Thailand is home to around 69 million individuals. Dengue is hyper-endemic and all 4 serotypes are in active circulation in the country. Dengue outbreaks occur almost annually within Thailand in at least one province but the spatio-temporal and environmental interface of these outbreaks has not been studied. METHODS: We develop Bayesian regime switching (BRS) models to characterize outbreaks, their persistence and infer their likelihood of occurrence across time for each administrative province where dengue case counts are collected. BRS was compared against two other classification tools and their agreement is assessed. We further examine how these spatio-temporal clusters of outbreak clusters arise by comparing reported dengue case counts, urban population, urban land cover, climate and flight volumes on the province level. RESULTS: Two dynamic dengue epidemic clusters were found nationally. One cluster consists of 47 provinces and is highly outbreak prone. Provinces with a large number of case counts, urban population, urban land cover and incoming flight passengers are associated to the epidemic prone cluster of dengue. Climate has an effect on determining the probability of outbreaks over time within provinces, but have less influence on whether provinces belong to the epidemic prone cluster. BRS found high agreement with other classification tools. CONCLUSIONS: Importation and urbanization drives the risk of outbreaks across regions strongly. In provinces estimated to have high epidemic persistence, more resource allocation to vector control should be applied to those localities as heightened transmission counts are likely to occur over a longer period of time. Clustering of epidemic and non-epidemic prone areas also highlights the need for prioritization of resource allocation for disease mitigation over provinces in Thailand.

Ethnicity, Neighborhood and Individual Socioeconomic Status, and Obesity: The Singapore Multiethnic Cohort.

OBJECTIVE: It remains unclear whether ethnicity has an impact on obesity independent of socioeconomic status (SES) and environmental factors. Singapore provides a unique opportunity to address this issue because three major Asian ethnic groups are represented, and government policies prevent ethnic segregation. Therefore this study examined associations between ethnicity, SES, and obesity within neighborhoods in Singapore. METHODS: Cross-sectional data from 29,819 participants of the Singapore Multiethnic Cohort who were aged 21 to 75 years and of Chinese, Malay, and Indian ethnicity were used. Obesity was defined using Asian criteria. Multilevel models used obesity as the dependent variable and age, marital status, ethnicity, education level, income, and neighborhood SES as independent variables. RESULTS: Education level was more strongly inversely associated with obesity than income level or neighborhood SES. The association between ethnicity and obesity was not substantially explained by measures of individual and neighborhood SES. In females, the fully adjusted odds ratio of obesity was 5.01 for Malay ethnicity and 4.81 for Indian ethnicity as compared with Chinese ethnicity. In males, these odds ratios were 2.61 and 2.07, respectively. CONCLUSIONS: Ethnicity was strongly associated with obesity independent of SES and neighborhood environment. More research on sociocultural factors contributing to ethnic differences in obesity is warranted.

Impact of sars-cov-2 interventions on dengue transmission.

An estimated 105 million dengue infections occur per year across 120 countries, where traditional vector control is the primary control strategy to reduce contact between mosquito vectors and people. The ongoing sars-cov-2 pandemic has resulted in dramatic reductions in human mobility due to social distancing measures; the effects on vector-borne illnesses are not known. Here we examine the pre and post differences of dengue case counts in Malaysia, Singapore and Thailand, and estimate the effects of social distancing as a treatment effect whilst adjusting for temporal confounders. We found that social distancing is expected to lead to 4.32 additional cases per 100,000 individuals in Thailand per month, which equates to 170 more cases per month in the Bangkok province (95% CI: 100-242) and 2008 cases in the country as a whole (95% CI: 1170-2846). Social distancing policy estimates for Thailand were also found to be robust to model misspecification, and variable addition and omission. Conversely, no significant impact on dengue transmission was found in Singapore or Malaysia. Across country disparities in social distancing policy effects on reported dengue cases are reasoned to be driven by differences in workplace-residence structure, with an increase in transmission risk of arboviruses from social distancing primarily through heightened exposure to vectors in elevated time spent at residences, demonstrating the need to understand the effects of location on dengue transmission risk under novel population mixing conditions such as those under social distancing policies.

Modelling the epidemic extremities of dengue transmissions in Thailand.

Significant health risks arise in Thailand from dengue but little work has been conducted to quantify the extremities of dengue outbreaks - where health systems are likely to be most stretched. In this paper, we detail the utility of tools derived from extreme value theory (EVT) in modelling the extremes in dengue case counts observed during outbreaks using 25 years of province level dengue case count data in Thailand from 1993 to 2018. We assess the validity of the EVT toolkit by comparing them against 8 competing benchmarks. The inhomogeneous point process representation (IPP) was found to perform best on 5 in and out of sample criterion such as parameter stability, distributional characteristics and out of sample coverage. Lastly, by using the IPP to infer future extreme dengue events, IPP found stark differences at the province level in the mean level of dengue case counts that is expected to be exceeded over the next 10 years. The IPP model also found that high probability that dengue extreme events will reach levels above and beyond the observed historical maximums. EVT shows considerable potential in aiding health planners for the risk management of dengue. The results in this paper can be easily translatable to any infectious disease observed over a long period.

Revealing regional disparities in the transmission potential of SARS-CoV-2 from interventions in Southeast Asia.

SARS-CoV-2 is a new pathogen responsible for the coronavirus disease 2019 (COVID-19) outbreak. Southeast Asia was the first region to be affected outside China, and although COVID-19 cases have been reported in all countries of Southeast Asia, both the policies and epidemic trajectories differ substantially, potentially due to marked differences in social distancing measures that have been implemented by governments in the region. This paper studies the across-country relationships between social distancing and each population's response to policy, the subsequent effects of these responses to the transmissibility and epidemic trajectories of SARS-CoV-2. The analysis couples COVID-19 case counts with real-time mobility data across Southeast Asia to estimate the effects of host population response to social distancing policy and the subsequent effects on the transmissibility and epidemic trajectories of SARS-CoV-2. A novel inference strategy for the time-varying reproduction number is developed to allow explicit inference of the effects of social distancing on the transmissibility of SARS-CoV-2 through a regression structure. This framework replicates the observed epidemic trajectories across most Southeast Asian countries, provides estimates of the effects of social distancing on the transmissibility of disease and can simulate epidemic histories conditional on changes in the degree of intervention scenarios and compliance within Southeast Asia.

Explicit characterization of human population connectivity reveals long run persistence of interregional dengue shocks.

Dengue is hyper-endemic in Singapore and Malaysia, and daily movement rates between the two countries are consistently high, allowing inference on the role of local transmission and imported dengue cases. This paper describes a custom built sparse space-time autoregressive (SSTAR) model to infer and forecast contemporaneous and future dengue transmission patterns in Singapore and 16 administrative regions within Malaysia, taking into account connectivity and geographical adjacency between regions as well as climatic factors. A modification to forecast impulse responses is developed for the case of the SSTAR and is used to simulate changes in dengue transmission in neighbouring regions following a disturbance. The results indicate that there are long-term responses of the neighbouring regions to shocks in a region. By computation of variable inclusion probabilities, we found that each region's own past counts were important to describe contemporaneous case counts. In 15 out of 16 regions, other regions case counts were important to describe contemporaneous case counts even after controlling for past local dengue transmissions and exogenous factors. Leave-one-region-out analysis using SSTAR showed that dengue transmission counts could be reconstructed for 13 of 16 regions' counts using external dengue transmissions compared to a climate only approach. Lastly, one to four week ahead forecasts from the SSTAR were more accurate than baseline univariate autoregressions.

Projected burden of type 2 diabetes mellitus-related complications in Singapore until 2050: a Bayesian evidence synthesis.

OBJECTIVE: We examined the effects of age, gender, and ethnicity on the risk of acute myocardial infarction, stroke, and end-stage renal disease according to type 2 diabetes mellitus status among adults aged 40-79 in Singapore. METHODS: A Bayesian inference framework was used to derive age-specific, gender-specific and ethnicity-specific prevalence of type 2 diabetes mellitus from the 2010 Singapore National Health Survey, and age-standardized gender and ethnicity-specific incidence rates of acute myocardial infarction, stroke and end-stage renal disease from the National Registry of Diseases Office. Population forecasts were used in tandem with incidence rates to project the future chronic disease burden until 2050. RESULTS: The highest relative risk of acute myocardial infarction was observed in the youngest age group (aged 40-44), with higher relative risk for women (men: 4.3 (2.7-6.4); women: 16.9 (9.3-28.3)). A similar trend was observed for stroke (men: 6.5 (4.2-9.7); women: 10.7 (6.0-17.4)). For end-stage renal disease, the highest relative risk was for men aged 45-50 (11.8 (8.0-16.9)) and women aged 55-60 (16.4 (10.7-24.0)). The annual incidence of acute myocardial infarction is projected to rise from 9300 (in 2019) to 16 400 (in 2050), the number of strokes from 7300 to 12 800, and the number of end-stage renal disease cases from 1700 to 2700. CONCLUSIONS: Type 2 diabetes mellitus was associated with an increased risk of complications and is modulated by age and gender. Prevention and early detection of type 2 diabetes mellitus can reduce the increasing burden of secondary complications.

Evaluating smoking control policies in the e-cigarette era: a modelling study.

BACKGROUND: In jurisdictions in which electronic cigarettes are currently prohibited, policy makers must weigh the potentially lower risk compared with conventional cigarettes against the risk of initiation of e-cigarettes among non-smokers. METHODS: We simulated a synthetic population over a 50-year time horizon with an open cohort model using data from Singapore, a country where e-cigarettes are currently prohibited, and data from the USA, the UK and Japan. Using the smoking prevalence and the quality-adjusted life year gained calculated, we compared tobacco control policies without e-cigarettes-namely, raising the minimum legal age (MLA), introducing a smoke-free generation (SFG) and tax rises on tobacco consumption-with policies legalising e-cigarettes, either taking a laissez-faire approach or under some form of restriction. We also evaluated combinations of these policies. RESULTS: Regardless of the country informing the transition probabilities to and from e-cigarette use in Singapore, a laissez-faire e-cigarette policy could reduce the smoking prevalence in the short term, but it is not as effective as other policies in the long term. The most effective single policies evaluated were SFG and aggressive tax rises; the most effective combination of policies considered was MLA plus moderate tax rises and e-cigarettes on prescription. CONCLUSION: Policy makers in jurisdictions in which e-cigarettes are not yet established may be advised not to prioritise e-cigarettes in their tobacco end-game strategy, unless their use can be restricted to current smokers seeking to quit.