This study aims to quantitatively summarize the association between night shift work and the risk of metabolic syndrome (MetS), with special reference to the dose-response relationship with years of night shift work. We systematically searched all observational studies published in English on PubMed and Embase from 1971 to 2013. We extracted effect measures (relative risk, RR; or odd ratio, OR) with 95% confidence interval (CI) from individual studies to generate pooled results using meta-analysis approach. Pooled RR was calculated using random- or fixed-effect model. Downs and Black scale was applied to assess the methodological quality of included studies. A total of 13 studies were included. The pooled RR for the association between 'ever exposed to night shift work' and MetS risk was 1.57 (95% CI = 1.24-1.98, pheterogeneity  = 0.001), while a higher risk was indicated in workers with longer exposure to night shifts (RR = 1.77, 95% CI = 1.32-2.36, pheterogeneity  = 0.936). Further stratification analysis demonstrated a higher pooled effect of 1.84 (95% CI = 1.45-2.34) for studies using the NCEP-ATPIII criteria, among female workers (RR = 1.61, 95% CI = 1.10-2.34) and the countries other than Asia (RR = 1.65, 95% CI = 1.39-1.95). Sensitivity analysis confirmed the robustness of the results. No evidence of publication bias was detected. The present meta-analysis suggested that night shift work is significantly associated with the risk of MetS, and a positive dose-response relationship with duration of exposure was indicated.

In addition to top-down Health-Emergency and Disaster Risk Management (Health-EDRM) efforts, bottom-up individual and household measures are crucial for prevention and emergency response of the COVID-19 pandemic, a Public Health Emergency of International Concern (PHEIC). There is limited scientific evidence of the knowledge, perception, attitude and behavior patterns of the urban population. A computerized randomized digital dialing, cross-sectional, population landline-based telephone survey was conducted from 22 March to 1 April 2020 in Hong Kong Special Administrative Region, China. Data were collected for socio-demographic characteristics, knowledge, attitude and risk perception, and various self-reported Health-EDRM behavior patterns associated with COVID-19. The final study sample was 765. Although the respondents thought that individuals (68.6%) had similar responsibilities as government (67.5%) in infection control, less than 50% had sufficient health risk management knowledge to safeguard health and well-being. Among the examined Health-EDRM measures, significant differences were found between attitude and practice in regards to washing hands with soap, ordering takeaways, wearing masks, avoidance of visiting public places or using public transport, and travel avoidance to COVID-19-confirmed regions. Logistic regression indicated that the elderly were less likely to worry about infection with COVID-19. Compared to personal and household hygiene practices, lower compliance was found for public social distancing.

People with asthma should avoid exposure to adverse conditions by limiting outdoor activities during periods of extreme temperatures, combinations of high humidity and high temperature, and low humidity and low temperature, and high ozone levels.

BackgroundHong Kong, a major city in China, has one of the world's highest income inequalities and one of the world's highest average increases in urban ambient temperatures. Heat-related mortality in urban areas may vary with acclimatisation and population characteristics. This study examines how the effect of temperature on mortality is associated with sociodemographic characteristics at an intracity level in Hong Kong, China, during the warm season.MethodsData from the Hong Kong Observatory, Census and Statistics Department, Environmental Protection Department and government general outpatient clinics during 1998–2006 were used to construct generalised additive (Poisson) models to examine the temperature mortality relationship in Hong Kong. Adjusted for seasonality, long-term trends, pollutants and other potential confounders, effect modification of the warm season temperature–mortality association by demographic, socioeconomic factors and urban design were examined.ResultsAn average 1°C increase in daily mean temperature above 28.2°C was associated with an estimated 1.8% increase in mortality. Heat-related mortality varied with sociodemographic characteristics: women, men less than 75 years old, people living in low socioeconomic districts, those with unknown residence and married people were more vulnerable. Non-cancer-related causes such as cardiovascular and respiratory infection-related deaths were more sensitive to high temperature effects.ConclusionPublic health protection strategies that target vulnerable population subgroups during periods of elevated temperature should be considered.

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We conducted a population telephone survey in Hong Kong during the second wave of influenza A/H7N9 outbreak in 2014. Among the respondents, 50.5% of the respondents would like to accept A/H7N9 vaccination in future. Respondents had poor knowledge of A/H7N9 influenza and vaccines. More than 60% of respondents mixed up seasonal influenza this year and A/H7N9 influenza. Results show that socio-demographic factors were all independent of the vaccine uptake willingness while anxiety level and vaccine history were the main affecting factors. Vaccine promotion strategies may focus on influenza knowledge, attitude and behavior.

BackgroundHand, foot and mouth disease (HFMD) is an emerging enterovirus-induced infectious disease for which the environmental risk factors promoting disease circulation remain inconclusive. This study aims to quantify the association of daily weather variation with hospitalizations for HFMD in Hong Kong, a subtropical city in China.MethodsA time series of daily counts of HFMD public hospital admissions from 2008 through 2011 in Hong Kong was regressed on daily mean temperature, relative humidity, wind speed, solar radiation and total rainfall, using a combination of negative binomial generalized additive models and distributed lag non-linear models, adjusting for trend, season, and day of week.ResultsThere was a positive association between temperature and HFMD, with increasing trends from 8 to 20°C and above 25°C with a plateau in between. A hockey-stick relationship of relative humidity with HFMD was found, with markedly increasing risks over 80%. Moderate rainfall and stronger wind and solar radiation were also found to be associated with more admissions.ConclusionsThe present study provides quantitative evidence that short-term meteorological variations could be used as early indicators for potential HFMD outbreaks. Climate change is likely to lead to a substantial increase in severe HFMD cases in this subtropical city in the absence of further interventions.

BackgroundPrior studies from around the world have indicated that very high temperatures tend to increase summertime mortality. However possible effect modification by urban micro heat islands has only been examined by a few studies in North America and Europe. This study examined whether daily mortality in micro heat island areas of Hong Kong was more sensitive to short term changes in meteorological conditions than in other areas.MethodAn urban heat island index (UHII) was calculated for each of Hong Kong’s 248 geographical tertiary planning units (TPU). Daily counts of all natural deaths among Hong Kong residents were stratified according to whether the place of residence of the decedent was in a TPU with high (above the median) or low UHII. Poisson Generalized Additive Models (GAMs) were used to estimate the association between meteorological variables and mortality while adjusting for trend, seasonality, pollutants and flu epidemics. Analyses were restricted to the hot season (June-September).ResultsMean temperatures (lags 0–4) above 29°C and low mean wind speeds (lags 0–4) were significantly associated with higher daily mortality and these associations were stronger in areas with high UHII. A 1°C rise above 29°C was associated with a 4.1% (95% confidence interval (CI): 0.7%, 7.6%) increase in natural mortality in areas with high UHII but only a 0.7% (95% CI: −2.4%, 3.9%) increase in low UHII areas. Lower mean wind speeds (5th percentile vs. 95th percentile) were associated with a 5.7% (95% CI: 2.7, 8.9) mortality increase in high UHII areas vs. a −0.3% (95% CI: −3.2%, 2.6%) change in low UHII areas.ConclusionThe results suggest that urban micro heat islands exacerbate the negative health consequences of high temperatures and low wind speeds. Urban planning measures designed to mitigate heat island effects may lessen the health effects of unfavorable summertime meteorological conditions.