Background Hong 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. Methods Data 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. Results An 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. Conclusion Public health protection strategies that target vulnerable population subgroups during periods of elevated temperature should be considered.

Prior 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. An 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). Mean 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 (5^th percentile vs. 95^th 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. The 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.

This study aimed to conduct a systematic review to sum up evidence of the associations between different aspects of night shift work and female breast cancer using a dose–response meta-analysis approach. We systematicly searched all cohort and case–control studies published in English on MEDLINE, Embase, PSYCInfo, APC Journal Club and Global Health, from January 1971 to May 2013. We extracted effect measures (relative risk, RR; odd ratio, OR; or hazard ratio, HR) from individual studies to generate pooled results using meta-analysis approaches. A log-linear dose–response regression model was used to evaluate the relationship between various indicators of exposure to night shift work and breast cancer risk. Downs and Black scale was applied to assess the methodological quality of included studies. Ten studies were included in the meta-analysis. A pooled adjusted relative risk for the association between ‘ever exposed to night shift work’ and breast cancer was 1.19 [95% confidence interval (CI) 1.05–1.35]. Further meta-analyses on dose–response relationship showed that every 5-year increase of exposure to night shift work would correspondingly enhance the risk of breast cancer of the female by 3% (pooled RR = 1.03, 95% CI 1.01–1.05; P_{heterogeneity} < 0.001). Our meta-analysis also suggested that an increase in 500-night shifts would result in a 13% (RR = 1.13, 95% CI 1.07–1.21; P_{heterogeneity} = 0.06) increase in breast cancer risk. This systematic review updated the evidence that a positive dose–response relationship is likely to present for breast cancer with increasing years of employment and cumulative shifts involved in the work.

Background Previous studies have found associations between meteorological variables and asthma hospitalisations but the nature of these associations has varied and few studies have been done in subtropical areas or evaluated effect modification by age. Objectives This study aimed to evaluate associations between asthma hospitalisations and meteorological factors and to assess effect modification of these associations by age and season in Hong Kong. Methods Poisson generalised additive models combined with distributed lag nonlinear models and piecewise linear models were used to model associations between daily asthma hospitalisations from 2004 to 2011 and meteorological factors and air pollutants, adjusting for day of week, seasonality and trend. Subgroup analyses by age and season were performed. Results In the hot season, hospitalisations were lowest at 27°C, rose to a peak at 30°C, then plateaued between 30°C and 32°C. The cumulative relative risk for lags 0–3 days (RRlag0–3) for 30°C vs 27°C was 1.19 (95% CI 1.06 to 1.34). In the cold season, temperature was negatively associated with asthma hospitalisations. The cumulative RRlag0–3 for 12°C vs 25°C was 1.33 (95% CI 1.13 to 1.58). Adult admissions were most sensitive to temperatures in both seasons while admissions among children under 5 were least associated. Higher humidity and ozone levels in the hot season, and low humidity in the cold season were also associated with more asthma admissions. Conclusions 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.

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.