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ObjectivesTo determine the national prevalence of risk factors of non-communicable diseases (NCD) in the adult population of Bangladesh.DesignThe study was a population-based national cross-sectional study.SettingThis study used 496 primary sampling units (PSUs) developed by the Bangladesh Bureau of Statistics. The PSUs were equally allocated to each division and urban and rural stratum within each division.ParticipantsThe participants were adults aged 18 to 69 years, who were usual residents of the households for at least 6 months and stayed the night before the survey. Out of 9900 participants, 8185 (82.7%) completed STEP-1 and STEP-2, and 7208 took part in STEP-3.Primary and secondary outcomeThe prevalence of behavioural, physical and biochemical risk factors of NCD. Data were weighted to generate national estimates.ResultsTobacco use was significantly (p<0.05) higher in the rural (45.2%) than the urban (38.8%) population. Inadequate fruit/vegetable intake was significantly (p<0.05) higher in the urban (92.1%) than in the rural (88.9%) population. The mean salt intake per day was higher in the rural (9.0 g) than urban (8.9 g) population. Among all, 3.0% had no, 70.9% had 1 to 2 and 26.2% had ≥3 NCD risk factors. The urban population was more likely to have insufficient physical activity (adjusted OR (AOR): 1.2, 95% CI: 1.2 to 1.2), obesity (AOR: 1.5, 95% CI: 1.5 to 1.5), hypertension (AOR: 1.3, 95% CI: 1.3 to 1.3), diabetes (AOR: 1.6, 95% CI: 1.6 to 1.6) and hyperglycaemia (AOR: 1.1, 95% CI: 1.1 to 1.1).ConclusionsConsidering the high prevalence of the behavioural, physical and biochemical risk factors, diverse population and high-risk group targeted interventions are essential to combat the rising burden of NCDs.

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Background Several large outbreaks of chikungunya have been reported in the Indian Ocean region in the last decade. In 2017, an outbreak occurred in Dhaka, Bangladesh, one of the largest and densest megacities in the world. Population mobility and fluctuations in population density are important drivers of epidemics. Measuring population mobility during outbreaks is challenging but is a particularly important goal in the context of rapidly growing and highly connected cities in low- and middle-income countries, which can act to amplify and spread local epidemics nationally and internationally. Methods We first describe the epidemiology of the 2017 chikungunya outbreak in Dhaka and estimate incidence using a mechanistic model of chikungunya transmission parametrized with epidemiological data from a household survey. We combine the modeled dynamics of chikungunya in Dhaka, with mobility estimates derived from mobile phone data for over 4 million subscribers, to understand the role of population mobility on the spatial spread of chikungunya within and outside Dhaka during the 2017 outbreak. Results We estimate a much higher incidence of chikungunya in Dhaka than suggested by official case counts. Vector abundance, local demographics, and population mobility were associated with spatial heterogeneities in incidence in Dhaka. The peak of the outbreak in Dhaka coincided with the annual Eid holidays, during which large numbers of people traveled from Dhaka to other parts of the country. We show that travel during Eid likely resulted in the spread of the infection to the rest of the country. Conclusions Our results highlight the impact of large-scale population movements, for example during holidays, on the spread of infectious diseases. These dynamics are difficult to capture using traditional approaches, and we compare our results to a standard diffusion model, to highlight the value of real-time data from mobile phones for outbreak analysis, forecasting, and surveillance.

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