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Exposure estimation model and validation with deterministic model

Background: Few studies have assessed long-term effects of particulate matter (PM) with aerodynamic diameter < 2.5 μm (PM2.5) on mortality for causes of cancer other than the lung; we assessed the effects on multiple causes. In Hong Kong, most people live and work in urban or suburban areas with high-rise buildings. This facilitates the estimation of PM2.5 exposure of individuals, taking into account the height of residence above ground level for assessment of the long-term health effects with sufficient statistical power.Methods: We recruited 66,820 persons who were ≥65 in 1998 to 2001 and followed up for mortality outcomes until 2011. Annual concentrations of PM at their residential addresses were estimated using PM2.5 concentrations measured at fixed-site monitors, horizontal–vertical locations, and satellite data. We used Cox regression model to assess the HR of mortality for cancer per 10 μg/m3 increase of PM2.5.Results: PM2.5 was associated with increased risk of mortality for all causes of cancer [HR, 1.22 (95% CI, 1.11–1.34)] and for specific cause of cancer in upper digestive tract [1.42 (1.06–1.89)], digestive accessory organs [1.35 (1.06–1.71)] in all subjects; breast [1.80 (1.26–2.55)] in females; and lung [1.36 (1.05–1.77)] in males.Conclusions: Long-term exposures to PM2.5 are associated with elevated risks of cancer in various organs.Impact: This study is particularly timely in China, where compelling evidence is needed to support the pollution control policy to ameliorate the health damages associated with economic growth. Cancer Epidemiol Biomarkers Prev; 25(5); 839–45. ©2016 AACR.

Urban green spaces are associated with many health outcomes, but the mechanisms underlying these links remain unclear. One explanation is that biodiverse microbiomes in green spaces affect human health by modifying immune function. Our systematic review included studies that investigated the relationship between green space and either health or biodiversity. Reported effects of green space on health were generally positive, but 22% of the papers identified either no effect or negative effects. We also found that although green space was commonly associated with biodiversity, few green‐space health studies simultaneously examined biodiversity. Overreliance on cross‐sectional studies, various definitions of green space, and a lack of research in tropical and developing nations limit the conclusions that can be drawn. A better understanding of the biological aspects of contact with nature is required before city planners can optimize green spaces for health gains.

Heavy rainfall is associated with increased risk of waterborne disease. However, it is not known whether the risk increment differs between wet and dry regions. We examined this question in New Zealand, which has a wide geographical variation of annual rainfall totals (10th–90th percentile difference ≥3000 mm). We conducted a nested case-crossover study within a prospective child cohort (born in 2009–2010) for assessing transient health effects when modified by longitudinal exposures to rainfall. Short-term heavy rainfall effects on hospitalizations due to enteric bacterial and viral infectious causes at lag of 0–14 days were assessed using a Cox regression model adjusted for daily temperature, relative humidity and evapotranspiration. We derived quantiles of time-weighted long-term rainfall levels at the children’s homes and these were added as an interaction term to the short-term effect model. Hospitalization risks were higher two days after heavy rainfall days (hazard ratio [95% confidence interval]: 1.73 [1.10–2.70]). The lowest-observable-adverse-effect-level was detected at the 94th percentile of daily rainfall total. Hospital admissions 1–2 days after heavy rainfall increased most in locations with the lowest and highest long-term rainfall. An interaction of this kind between short-term weather and long-term climate has not been reported previously. It is relevant to climate change risk assessments given global projections of increasing intensity of precipitation, against a background of more severe, and possibly more frequent, droughts and flooding.

In developed countries, exposure to wood or coal smoke occurs predominantly from neighbourhood emissions arising from household heating. The effect of this exposure on child health is not well characterized. Within a birth cohort study in New Zealand we assessed healthcare events associated with exposure to neighbourhood smoke from household heating. Our outcome measure was non-accidental presentations to hospital emergency departments (ED) before age three years. We matched small area-level census information with the geocoded home locations to measure the density of household heating with wood or coal in the neighbourhood and applied a time-weighted average exposure method to account for residential mobility. We then used hierarchical multiple logistic regression to assess the independence of associations of this exposure with ED presentations adjusted for gender, ethnicity, birth weight, breastfeeding, immunizations, number of co-habiting smokers, wood or coal heating at home, bedroom mold, household- and area-level deprivation and rurality. The adjusted odds ratio of having a non-accidental ED visit was 1.07 [95%CI: 1.03–1.12] per wood or coal heating household per hectare. We found a linear dose-response relationship (p-value for trend = 0.024) between the quartiles of exposure (1st as reference) and the same outcome (odds ratio in 2nd to 4th quartiles: 1.14 [0.95–1.37], 1.28 [1.06–1.54], 1.32 [1.09–1.60]). Exposure to neighbourhoods with higher density of wood or coal smoke-producing households is associated with an increased odds of ED visits during early childhood. Policies that reduce smoke pollution from domestic heating by as little as one household per hectare using solid fuel burners could improve child health.

We compared the injury risks of typical exposures to road cycling for transport with other common activities including do-it-yourself repairs (DIY) at home, horse riding, quad bike riding, rugby union and snow sports in New Zealand. Cycling on the road half an hour three times a week was similar to DIY twice a month and safer than horse riding 1.5 h twice a week (5-fold difference in injury claims), skiing half a day for 4–5 times per year (140-fold), and playing rugby once every 3 weeks (530-fold difference). In statistical terms, based on moderate injuries, cycling is less dangerous than many recreational and every day activities. We conclude that fear of cycling in car-dependent New Zealand arises mainly from other causes than risk of injury, associated with the marginal status of cyclists on the public road.

Background A limited number of studies on long-term effects of particulate matter with aerodynamic diameter < 2.5 μm (PM2.5) on health suggest it can be an important cause of morbidity and mortality. In Asia where air quality is poor and deteriorating, local data on long-term effects of PM2.5 to support policy on air quality management are scarce. Objectives We assessed long-term effects of PM2.5 on the mortality in a single Asian city. Methods For 10–13 years, we followed up a cohort of 66,820 participants ≥ 65 years of age who were enrolled and interviewed in all 18 Elderly Health Centres of the Department of Health, Hong Kong, in 1998–2001. Their residential addresses were geocoded into x- and y-coordinates, and their proxy exposures to PM2.5 at their addresses in 1 × 1 km grids were estimated from the U.S. National Aeronautics and Space Administration (NASA) satellite data. We used Cox regression models to calculate hazard ratios (HRs) of mortality associated with PM2.5. Results Mortality HRs per 10-μg/m3 increase in PM2.5 were 1.14 (95% CI: 1.07, 1.22) for all natural causes, 1.22 (95% CI: 1.08, 1.39) for cardiovascular causes, 1.42 (95% CI: 1.16, 1.73) for ischemic heart disease, 1.24 (95% CI: 1.00, 1.53) for cerebrovascular disease, and 1.05 (95% CI: 0.90, 1.22) for respiratory causes. Conclusions Our methods in using NASA satellite data provide a readily accessible and affordable approach to estimation of a sufficient range of individual PM2.5 exposures in a single city. This approach can expand the capacity to conduct environmental accountability studies in areas with few measurements of fine particles. Citation Wong CM, Lai HK, Tsang H, Thach TQ, Thomas GN, Lam KB, Chan KP, Yang L, Lau AK, Ayres JG, Lee SY, Chan WM, Hedley AJ, Lam TH. 2015. Satellite-based estimates of long-term exposure to fine particles and association with mortality in elderly Hong Kong residents. Environ Health Perspect 123:1167–1172; http://dx.doi.org/10.1289/ehp.1408264

Adolescent smoking has been associated with general parenting style, although potential differences between fathers and mothers were seldom investigated, especially in non-Western populations. The aim of this study is to investigate associations between Hong Kong adolescents’ smoking and their perceptions of paternal and maternal parenting styles. In a school-based survey in 2006–2007, 33,408 adolescents (44.6 % boys; mean age 14.5 ± 1.3 years) provided information on smoking and the frequency of care and control by each parent, who was classified into one of four adolescent-reported parenting styles: authoritative (high care, high control), authoritarian (low care, high control), permissive (high care, low control), or neglectful (low care, low control). Logistic regression was used to calculate adjusted odds ratios (AORs) of current smoking (past 30 days) for parenting variables, considering potential effect modification by age, sex and parental smoking. Maternal care and control were strongly and significantly associated with lower odds of adolescent current smoking. However, such association was weak for paternal care and observed only in girls. Conversely, paternal control was positively associated with current smoking, especially if the father smoked. The lowest AORs of current smoking were associated with authoritative mothers, permissive fathers and combinations of maternal and paternal parenting styles with an authoritative mother whether or not the father was authoritative. Maternal care, control and authoritative parenting were associated with lower odds of adolescent smoking in Hong Kong. Paternal care was only weakly associated with lower odds of adolescent smoking, and paternal control was even associated with higher odds of smoking.

Air pollution in China, especially in the Pearl River Delta (PRD) region, has drastically increased in recent years. We modelled annual mean ground-level PM2.5 concentrations based on worldwide satellite information and meteorological data from 40 cities outside the PRD. The model of PM2.5 concentration (R = 0.845) was best explained by aerosol optical thickness (43.8%). We validated the spatial-temporal dimensions of the model and estimated that the annual mean PM2.5 concentration in PRD ranged between 22 and 65 μg m(-3). Then we used meta-analysis to obtain the pooled excess risks of mortality in China and assessed the health impacts. We found an inverse association between short-term excess risks of mortality and annual mean PM2.5 concentrations. Based on the above models and analyses, the associated excess deaths for all-cause and cardiopulmonary diseases were 3386 and 2639 respectively. The corresponding risk-standardized excess death rates were 2006 and 1069 per million people.

We aimed to investigate the relationship between alcohol consumption and sleep problems among Hong Kong adolescents.In the 2006 and 2007 Hong Kong Student Obesity Surveillance project, 33,692 secondary students completed an anonymous questionnaire on lifestyles and health. Alcohol consumption was categorized as nondrinkers (reference group), those who drank less than 1day per week (less than weekly drinkers), and those who drank 1 to 7 days per week (weekly drinkers, including some daily drinkers). Students reported if they had any sleep problems in the past 30 days, including difficulty initiating sleep (DIS), difficulty maintaining sleep (DMS), early morning awakening (EMA), snoring, and difficulty breathing during sleep (DBS). Insomnia was defined as any reports of DIS, DMS, or EMA. Logistic regression was used to assess the association between alcohol and each sleep problem. Multiple imputations were used to impute missing data.Compared with nondrinkers, less than weekly and weekly drinkers were more likely to report snoring with adjusted odds ratios (AOR) of 1.64 (95% confidence interval [CI], 1.40-1.92) and 1.82 (95% CI, 1.55-2.14), respectively (P.001). The corresponding figures were 1.24 (95% CI, 1.02-1.50) and 1.50 (95% CI, 1.24-1.82) for DBS (P.001) and 1.12 (95% CI, 1.02-1.22) and 1.15 (95% CI, 1.04-1.27) for insomnia (P=.002). Weekly drinking was positively associated with DMS but negatively associated with DIS and EMA. Less than weekly drinking was positively associated with DIS, DMS, and EMA.Both less than weekly drinking and weekly drinking were associated with snoring, DBS, and insomnia. The association of individual symptoms of insomnia with drinking varied with the frequency of consumption.

The World Health Organization (WHO) Air Quality Guidelines (AQG) were launched in 2006, but gaps remain in evidence on health impacts and relationships between short-term and annual AQG needed for health protection. We tested whether relationships between WHO short-term and annual AQG for particulates (PM10 and PM2.5) and nitrogen dioxide (NO2) are concordant worldwide and derived the annual limits for sulfur dioxide (SO2) and ozone (O3) based on the short-term AQG. We obtained air pollutant data over seven years (2004–2010) in seven cities from Asia-Pacific, North America and Europe. Based on probability distribution concept using maximum as the short-term limit and arithmetic mean as the annual limit, we developed a new method to derive limit value one from another in each paired limits for each pollutant with capability to account for allowable exceedances. We averaged the limit derived each year for each city, then used meta-analysis to pool the limit values in all cities. Pooled mean short-term limit for NO2 (140.5 μg/m3 [130.6–150.4]) was significantly lower than the WHO AQG of 200 μg/m3 while for PM10 (46.4 μg/m3 [95CI:42.1–50.7]) and PM2.5 (28.6 μg/m3 [24.5–32.6]) were not significantly different from the WHO AQG of 50 and 25 μg/m3 respectively. Pooled mean annual limits for SO2 and O3 were 4.6 μg/m3 [3.7–5.5] and 27.0 μg/m3 [21.7–32.2] respectively. Results were robust in various sensitivity analyses. The distribution relationships between the current WHO short-term and annual AQG are supported by empirical data from seven cities for PM10 and PM2.5, but not for NO2. The short-term AQG for NO2 should be lowered for concordance with the selected annual AQG for health protection. Keywords: Particulate matter, Nitrogen dioxide, Sulfur dioxide, Ozone, Air quality guidelines, Exceedance

Objective Obesity was not identified as a risk factor for influenza until the recent 2009 H1N1 pandemic. Based on a cohort of 66,820 subjects aged 65 years and over with the follow-up period from July 1998 to December 2010 in Hong Kong, we assessed the modifying effect of obesity on mortality risks specifically attributable to influenza infections (termed as “influenza associated mortality risks”). Methods A Cox proportional model with time dependent covariates was adopted to assess the hazard ratio of mortality in each obesity group when influenza activity increased 10% in the community. Results Hazard ratio of influenza-associated all-cause mortality was 1.081 (95% confidence interval 1.013, 1.154), 1.047 (1.012, 1.084), 0.981 (0.936, 1.028), 1.018 (0.980, 1.058) and 1.062 (0.972, 1.162) in the underweight, normal, overweight, moderate obesity and severe obesity groups, respectively. A similar U shape pattern across the obesity groups was also observed in influenza associated mortality risks of respiratory diseases, pneumonia and influenza. This pattern was more evident among ever smokers, although the influenza effect estimates in each obesity group had overlapping confidence intervals. Conclusion There is some but limited evidence to suggest that underweight and obesity were associated with higher mortality risks of influenza in old population.

Please cite this paper as: Wong et al. (2012) Cigarette smoking as a risk factor for influenza-associated mortality: evidence from an elderly cohort. Influenza and Other Respiratory Viruses 7(4), 531–539. Background The effects of individual lifestyle factors on the mortality risk after influenza infection have not been explored. Objectives In this study, we assessed the modifying effects of cigarette smoking on mortality risks associated with influenza in a cohort of Hong Kong elders with a follow-up period of 1998–2009. Methods We used the Cox proportional hazards model with time-dependent covariates of weekly proportions of specimens positive for influenza (termed as influenza virus activity), to calculate the hazard ratio of mortality associated with a 10% increase in influenza virus activity for never, ex- and current smokers. Other individual lifestyle and socioeconomic factors as well as seasonal confounders were also added into the models. Results The overall hazard ratio associated with influenza was 1·028 (95% confidence interval, 1·006, 1·051) for all natural cause mortality and 1·035 (1·003, 1·068) for cardiovascular and respiratory mortality. We found that influenza-associated hazard ratio was greater in current and ex-smokers than in never smokers for mortality of all natural causes, cardiovascular and respiratory diseases. Conclusions The findings suggest that smoking might increase influenza-associated mortality risks among elders.

To investigate the association between weight misperception and psychosocial health problems among normal weight Chinese adolescent boys and girls.In the Youth Smoking Survey 2003-04, 20 677 normal weight students aged 11-18 years from 85 randomly selected schools throughout Hong Kong were analysed. Students who perceived themselves as very thin, thin, fat or very fat were classified as having weight misperception in contrast to the reference group who correctly perceived themselves as normal weight. Psychosocial health outcomes included headache, feeling stressful, feeling depressed, poorer appetite, sleepless at night, having nightmares and less confidence in getting along with friends. Logistic regression yielded adjusted odds ratios (ORs) for each outcome by weight misperception in boys and girls separately.In girls, misperceived fatness was associated with all outcomes, while misperceived thinness was associated with poorer appetite and less confidence. Boys who misperceived themselves as very thin or fat had greater odds of all outcomes except having nightmares. In general, greater ORs were observed for misperceived fatness than thinness in girls, but similar ORs were observed in boys. Misperceived thinness and fatness accounted for 0.6% to 45.1% of the psychosocial health problems in adolescents.Normal weight adolescents with weight misperception were more likely to have psychosocial health problems, and the associations were stronger for extreme misperceptions (i.e., very fat or very thin) in both boys and girls.

Background The effects of workplace second-hand smoke (SHS) on lung function remain uncertain because of a lack of objective measures for SHS exposures. Objective To determine whether an exposure–response association exists between lung function and two different markers of SHS based on indoor fine particulate (PM 2.5 ) and urinary cotinine levels in non-smoking catering workers. Design A cross-sectional study during a 1.5-year exemption of licensed catering premises from smoke-free legislation. Participants 186 non-smoking catering workers aged 18–65 years in Hong Kong were recruited. A declared non-smoking status was accepted in workers with exhaled breath carbon monoxide levels Main outcome measures Lung function measures of forced expiratory volume in 1s (FEV 1 in litres), forced vital capacity (FVC in litres) and forced expiratory flow as 25–75% of FVC (FEF 25–75 in l/s) were recorded. Results Indoor fine particulate (PM 2.5 ) concentrations were 4.4 times as high in smoking premises (267.9 μg/m 3 ) than in non-smoking premises (60.3 μg/m 3 ) and were strongly associated with the probability of permitted smoking (R 2 =0.99). Smoking was the dominant source of particulates (R 2 =0.66). Compared with workers exposed to the lowest indoor PM 2.5 stratum ( 3 ), lung function was lower in the three higher PM 2.5 strata (25–75, 75–175, >175 μg/m 3 ) with FEV 1 −0.072 (95% CI −0.123 to −0.021), −0.078 (95% CI –0.132 to −0.024), −0.101 (95% CI −0.187 to −0.014); FEF 25–75 −0.368 (95% CI −0.660 to −0.077), −0.489 (95% CI −0.799 to −0.179), −0.597 (95% CI −0.943 to −0.251); and FEV 1 /FVC (%) −2.9 (95% CI −4.8 to −1.0), −3.2 (95% CI −5.1 to −1.4) and −4.4 (95% CI −7.4 to −1.3), respectively. Urinary cotinine was associated positively with indoor PM 2.5 but negatively with lung function. Consistently lower values for lung function per unit increase of indoor PM 2.5 were found. Conclusion Lung function is inversely associated with workplace SHS. Workplace exemptions and delays in implementing smoke-free policies and current moves to relax legislation are a major threat to the health of workers.

INTRODUCTION Smoke-free workplace legislation often exempts certain venues. Do smoking (exempted) and nonsmoking (nonexempted) catering premises' workers in Hong Kong report different perceptions of risk from and reactions to nearby smoking as well as actual exposure to secondhand smoke (SHS)? METHODS In a cross-sectional survey of 204 nonsmoking catering workers, those from 67 premises where smoking is allowed were compared with workers from 36 nonsmoking premises in Hong Kong on measures of perceptions of risk and behavioral responses to self-reported SHS exposure, plus independent exposure assessment using urinary cotinine. RESULTS Self-reported workplace SHS exposure prevalence was 57% (95% CI = 49%-65%) in premises prohibiting and 100% (95% CI = 92%-100%) in premises permitting smoking (p < .001). Workers in smoking-permitted premises perceived workplace air quality as poorer (odds ratio [OR] = 9.3, 95% CI = 4.2-20.9) with higher associated risks (OR = 3.7, 95% CI = 1.6-8.6) than workers in smoking-prohibited premises. Workers in smoking-prohibited premises were more bothered by (OR = 0.2, 95% CI = 0.1-0.5) and took more protective action to avoid SHS (OR = 0.2, 95% CI = 0.1-0.4) than workers in smoking-permitted premises. Nonwork exposure was negatively associated with being always bothered by nearby smoking (OR = 0.3, 95% CI = 0.1-0.9), discouraging nearby smoking (OR = 0.5, 95% CI = 0.2-1.1), and discouraging home smoking (OR = 0.4, 95% CI = 0.2-0.9). Urinary cotinine levels were inversely related to workers' avoidance behavior but positively related to their perceived exposure-related risks. CONCLUSIONS Different workplace smoking restrictions predicted actual SHS exposure, exposure-related risk perception, and protective behaviors. Workers from smoking-permitted premises perceived greater SHS exposure-related risks but were more tolerant of these than workers in smoking-prohibited premises. This tolerance might indirectly increase both work and nonwork exposures.

Purpose To investigate the association between fish consumption and mortality in 36,003 Chinese. Methods A case-control study collected 81% of all deaths of those aged 30+ from all four Hong Kong death registries in 1998. Relatives registering the deaths provided demographic, dietary and other lifestyle data for the deceased (case) and a similarly aged living person (control). Causes of death were provided by the Department of Health. Logistic regression was used to calculate the mortality odds ratios (ORs) for fish consumption adjusting for potential confounders in the 23,608 cases and 12,395 controls. Results Compared with the lowest fish consumption of less than or equal to three times a month, higher consumption of one to three times a week was associated with lower mortality ORs (95% confidence interval [CI]) of 0.75 (0.62–0.89) for all-cause, 0.66 (0.48–0.92) for ischemic heart disease (IHD), 0.70 (0.50–0.98) for stroke, 0.66 (0.53–0.82) for cancer, but not for injury and poisoning. The highest level of fish consumption of greater than or equal to four times a week also reduced mortality with ORs (95% CI) of 0.80 (0.68–0.94) for all-cause and 0.63 (0.47–0.85) for IHD. Conclusions Fish consumption significantly reduced mortality from several causes in this sample. Further longitudinal studies to confirm the association are needed.

We conducted a health impact assessment of the government's proposed new air quality objectives (AQO) in Hong Kong, a high pollution environment. We based this on the World Health Organization (WHO) 2005 Air Quality Guidelines (AQG) and used a lognormal probability density function to model possible changes in annual mean pollutant levels resulting from the new AQO. All of the proposed short-term AQO were based on WHO interim targets (IT) or AQG, but allowed additional exceedances of these single limit values. Compliance with these short-term AQO may reduce (18-30%) the current annual mean concentrations but the distribution proportions exceeding the annual or annualized AQG remain high (83-100%). For SO2, the proposed 24-hr AQO of 125 μg m -3 , with 3 days exceedances, cannot ensure reduction of the current annual mean but may legally permit an increase of the pollutant concentration distribution. If the proposed legal limits of AQO are fully exploited by polluters, we estimated the annual number of avoidable deaths at 1860, and avoidable health care events at 5.2 million doctor visits and 92745 hospital bed-days with a total annual community cost of US$2.6 billion. The proposed AQO may only reduce the current air pollution health impacts by 17% but could achieve 41% reduction if additional exceedances were not permitted. An epidemiologic approach should be adopted to assess external costs arising from modifications of WHOAQG and support accountability in air quality management. This analysis of the WHOAQG in a high pollution setting demonstrates problems arising from the absence of annual limits for some pollutants and the discordance between the short-term and annual AQG, suggesting that revisions based on a lognormal probability model should be considered.

Respiratory ill-health effects due to particulate air exposure at different geographical locations in Hong Kong that aggregate individual living locations were estimated based on satellite information. We assessed the presence of respiratory symptoms of a frequent cough or sputum in school students aged 11-20 years old (n = 9,881). Daily particulate air pollution levels at students' living locations were derived from the surface extinction coefficients measured by satellite and measurements from the air pollutant monitoring stations at ground level. Adjusted odds ratio (OR) [95% CI] of respiratory symptoms was 1.047 [1.005, 1.091] per 10 microg m(-3) increase in PM(10) concentration. Specificity tests showed that adjusted OR of having other symptoms is not significant (p = 0.20-0.94). Exposures to PM(10) at different geographical locations is associated with increased odds of having respiratory symptoms (cough or sputum) but not with other symptoms unrelated to air pollution.

OBJECTIVE: No study has ever reported the association between persistent respiratory symptoms and exposure to secondhand smoke (SHS) in adolescent smokers. The impact of SHS exposure on child health could be largely underestimated by not taking into account such effects. We investigated the association between exposure to SHS and respiratory symptoms among adolescent current smokers. METHODS: A total of 32506 students aged 11 to 20 years from 85 randomly selected secondary schools in Hong Kong completed a self-administered questionnaire that included persistent respiratory symptoms (for 3 consecutive months in the past 12 months), number of days of SHS exposure per week at home and outside home, smoking status, amount of active smoking, and other basic demographic characteristics and socioeconomic status. RESULTS: Adolescent current smokers who were exposed to SHS at home 1 to 4 and 5 to 7 days/wk were 50% (95% confidence interval [CI]: 3%–121%) and 77% (95% CI: 5%–199%) more likely, respectively, to report respiratory symptoms compared with those who were unexposed (P = .01 for trend). The corresponding figures for exposure outside home were 41% (95% CI: 3%–94%) and 85% (95% CI: 31%–161%; P = .004 for trend). Such associations were also observed among never-smokers, but they were weaker than those among current smokers (P < .01 for interaction). CONCLUSIONS: This is the first evidence that SHS exposure is associated with increased risks for persistent respiratory symptoms among adolescent current smokers. Health promotion programs should aim at SHS reduction as well as smoking cessation among adolescent smokers.

Many epidemiological investigations indicate that excess risks of mortality and morbidity may vary among specific PM(2.5) components. Nickel (Ni) and vanadium (V) particulate metal species may potentially be related to increasing respiratory and cardiovascular mortality and morbidity. This review focuses on exposure concentrations of these two species in various settings, their health effects based on epidemiological and toxicological studies and the underlying mechanisms. The evidence shows that environmental exposure concentrations of Ni and V in general setting are lower than the World Health Organization standard (V, 1 microg/m(3)/day) in 2000, or the European Environment Agency standard (Ni, 1 microg/m(3)/day) in 2003, but their associations with cardiopulmonary diseases can still be found. The toxicological mechanism can be explained by laboratory-based studies. Updated safe guidelines on environmental and human exposure of Ni and V are necessary in order to clarify the associations between them and cardiopulmonary diseases and provide environmental intervention policies.

This study identified the key determinants associated with the indoor benzene concentrations that were measured between 1996 and 2000 using the EXPOLIS protocol in the residences of six European cities, including Athens (Greece), Basel (Switzerland), Helsinki (Finland), Milan (Italy), Oxford (United Kingdom), and Prague (Czech Republic). Two consecutive days of home indoor and home outdoor measurements of benzene were carried out at the homes of adult participants on different dates and seasons during the sampling period. Regression models, with interactions searched by all-possible subset method, were used to assess the city effects and the determinants of home indoor benzene (adjusted R2=0.57, n=412). Outdoor benzene concentrations, outdoor temperature, wind speed, the use of anti-moth products, and indoor smoking in terms of number of cigarettes consumed per day were shown to be the key determinants of indoor benzene concentrations. The model was further used to predict the indoor benzene levels in cities. Non-linear relationships were commonly found, indicating that a unit change in the indoor concentration cannot be simply estimated by a proportional change of the determinant, and the pattern of relationships could be differed in different places. This finding is important in formulating indoor air quality guidelines as well as calculating an accurate health risk estimate based on the estimates of population's lifetime exposure levels.

Background: Few studies have assessed long-term effects of particulate matter (PM) with aerodynamic diameter < 2.5 μm (PM2.5) on mortality for causes of cancer other than the lung; we assessed the effects on multiple causes. In Hong Kong, most people live and work in urban or suburban areas with high-rise buildings. This facilitates the estimation of PM2.5 exposure of individuals, taking into account the height of residence above ground level for assessment of the long-term health effects with sufficient statistical power. Methods: We recruited 66,820 persons who were ≥65 in 1998 to 2001 and followed up for mortality outcomes until 2011. Annual concentrations of PM at their residential addresses were estimated using PM2.5 concentrations measured at fixed-site monitors, horizontal–vertical locations, and satellite data. We used Cox regression model to assess the HR of mortality for cancer per 10 μg/m3 increase of PM2.5. Results: PM2.5 was associated with increased risk of mortality for all causes of cancer [HR, 1.22 (95% CI, 1.11–1.34)] and for specific cause of cancer in upper digestive tract [1.42 (1.06–1.89)], digestive accessory organs [1.35 (1.06–1.71)] in all subjects; breast [1.80 (1.26–2.55)] in females; and lung [1.36 (1.05–1.77)] in males. Conclusions: Long-term exposures to PM2.5 are associated with elevated risks of cancer in various organs. Impact: This study is particularly timely in China, where compelling evidence is needed to support the pollution control policy to ameliorate the health damages associated with economic growth. Cancer Epidemiol Biomarkers Prev; 25(5); 839–45. ©2016 AACR.

Social and demographic factors have been found to play a significant role in differences between time–activity patterns of population subgroups. Since time–activity patterns largely influence personal exposure to compounds as individuals move across microenvironments, exposure subgroups within the population may be defined by factors that influence daily activity patterns. Socio-demographic and environmental factors that define time–activity subgroups also define quantifiable differences in VOC personal exposures to different sources and individual compounds in the Expolis study. Significant differences in exposures to traffic-related compounds ethylbenzene, m- and p-xylene and o-xylene were observed in relation to gender, number of children and living alone. Categorization of exposures further indicated time exposed to traffic at work and time in a car as important determinants. Increased exposures to decane, nonane and undecane were observed for males, housewives and self-employed. Categorization of exposures indicated exposure subgroups related to workshop use and living downtown. Higher exposures to 3-carene and α-pinene commonly found in household cleaning products and fragrances were associated with more children, while exposures to traffic compounds ethylbenzene, m- and p-xylene and o-xylene were reduced with more children. Considerable unexplained variation remained in categorization of exposures associated with home product use and fragrances, due to individual behavior and product choice. More targeted data collection methods in VOC exposure studies for these sources should be used. Living alone was associated with decreased exposures to 2-methyl-1-propanol and 1-butanol, and traffic-related compounds. Identification of these subgroups may help to reduce the large amount of unexplained variation in VOC exposure studies. Further they may help in assessing impacts of urban planning that result in changes in behavior of individuals, resulting in shifts in the patterns of exposure experienced by the population.

EXPOLIS was a large-scale population-based study of urban adult exposures to multiple pollutants, and was conducted between 1996 and 2000 in six European cities. Measurements made using standardised protocols in Athens (Greece), Basel (Switzerland), Helsinki (Finland), Milan (Italy), Oxford (UK), and Prague (Czech Republic), allow similarities and differences between contrasting European regions, climates and populations to be identified. Two consecutive days of home indoor and home outdoor measurements of fine particulate matter (PM2.5), black smoke (BS), and nitrogen dioxide (NO2) were carried out at the homes of adult participants on different dates and seasons during the sampling period. Regression models with interactions searched by all-possible subset method were used to assess the city effects and the determinants of home indoor PM2.5 (adj R2=0.60, n=413), BS (adj R2=0.79, n=382) and NO2 (adj R2=0.67, n=302) levels. Both bi-directional (positive and negative signs of associations) and unidirectional (consistently either positive or negative sign of associations) city effects on different determinants in each indoor model were shown. Smoking, gas-stove usage, outdoor temperature, and wind speed were the common determinants in all three indoor models. Other determinants, including the presence of wooden material, heating, and being located in suburb area, were also identified. They were likely linked to cultural and socio-economic factors.

Evaluation of relationships between median residential indoor, indoor workplace and population exposures may obscure potential strategies for exposure reduction. Evaluation of participants with personal exposures above median levels in the EXPOLIS study in Athens, Helsinki, Oxford and Prague illustrated that these participants frequently showed a different relationship to indoor and workplace levels than that shown by the population median. Thus, prioritization of environments for control measures based on median exposures may exclude important areas where effectively focused control measures are possible, and may therefore have little impact on the highest and most harmful exposures. Further, personal exposures at the upper end of the distribution may exceed the US EPA inhalation reference concentration (Rfc), illustrated here using hexane, naphthalene and benzene. For example upper 90th percentile personal exposures to benzene in Athens and Prague were 64 and 27 μg m−3 with peak exposures of 217 and 38 μg m−3, respectively for non-ETS exposed participants relative to an Rfc of 30 μg m−3. Strategies to reduce exposures to individual compounds, therefore, may benefit from focus on the high end of the distribution to identify activities and behaviors that result in elevated exposures. Control strategies targeting activities that lead to exposures in the upper end of the distribution would reduce the variability associated with population median values by bringing the upper end of the exposure distribution closer to median values. Thus, compliance with health-based standards would be more protective of the higher exposed fraction of the population, in whom health effects would be more expected.

Between 1998 and 2000 in Oxford, UK, simultaneous personal exposures and microenvironmental measurements (home indoor, home outdoor and work indoor) to fine particulate matters PM2.5, volatile organic compounds (VOC), nitrogen dioxide (NO2) and carbon monoxide (CO) were carried out once per person among 50 adults over a 48-h period. Thirty-seven elements in PM2.5 and 30 different VOCs were analysed. Questionnaires were distributed to record their time-activity patterns and exposure-related information. Results showed that participants spent more time (89.5%) in all indoors than in other microenvironments. Geometric mean (GM) of personal and home indoor levels of PM2.5, 14 elements (aluminium, arsenic, bromine, calcium, copper, iron, gallium, potassium, sodium, phosphorus, lead, selenium, silicon, titanium), total VOC (TVOC) and 8 individual compounds (nonane, decane, undecane, trimethylbenzene, toluene, benzaldehyde, alpha-pinene and d-limonene) were over 20% higher than their GM outdoor levels. Those of NO2, 5 aromatic VOCs (benzene, o-xylene, ethylbenzene, propylbenzene, m,p-xylene) and 5 other elements (chlorine, magnesium, manganese, sulphur, zinc) were close to their GM outdoor levels. For PM2.5 and TVOC, personal exposures and residential indoor levels (in GM) were about 2 times higher among the tobacco-smoke exposed group compared to the non-smoke exposed group, suggesting that smoking is an important determinant of these exposures. Determinants for CO were visualised by real-time monitoring, and we showed that the peak levels of personal exposure to CO were associated with smoking, cooking and transportation activities. Moderate to good correlations were only found between the personal exposures and residential indoor levels for both PM2.5 ( r = 0.60 , p 0.001 ) and NO2 ( r = 0.47 , p = 0.003 ).

After the implementation of a regulation restricting sulfur to 0.5% by weight in fuel on July 1, 1990, in Hong Kong, sulfur dioxide (SO2*) levels fell by 45% on average and as much as 80% in the most polluted districts (Hedley et al. 2002). In addition, a reduction of respiratory symptoms and an improvement in bronchial hyperresponsiveness in children were observed (Peters et al. 1996; Wong et al. 1998). A recent time-series study (Hedley et al. 2002) found an immediate reduction in mortality during the cool season at six months after the intervention, followed by an increase in cool-season mortality in the second and third years, suggesting that the reduction in pollution was associated with a delay in mortality. Proportional changes in mortality trends between the 5-year periods before and after the intervention were measured as relative risks and used to assess gains in life expectancy using the life table method (Hedley et al. 2002). To further explore the relation between changes in pollution-related mortality before and after the intervention, our study had three objectives: (1) to evaluate the short-term effects on mortality of changes in the pollutant mix after the Hong Kong sulfur intervention, particularly with changes in the particulate matter (PM) chemical species; (2) to improve the methodology for assessment of the health impact in terms of changes in life expectancy using linear regression models; and (3) to develop an approach for analyzing changes in life expectancy from Poisson regression models. A fourth overarching objective was to determine the relation between short- and long-term benefits due to an improvement in air quality.For an assessment of the short-term effects on mortality due to changes in the pollutant mix, we developed Poisson regression Core Models with natural spline smoothers to control for long-term and seasonal confounding variations in the mortality counts and with covariates to adjust for temperature (T) and relative humidity (RH). We assessed the adequacy of the Core Models by evaluating the results against the Akaike Information Criterion, which stipulates that, at a minimum, partial autocorrelation plots should be between -0.1 and 0.1, and by examining the residual plots to make sure they were free from patterns. We assessed the effects for gaseous pollutants (NO2, SO2, and O3), PM with an aerodynamic diameteror = 10 microm (PM10), and its chemical species (aluminum [Al], iron [Fe], manganese [Mn], nickel [Ni], vanadium [V], lead [Pb], and zinc [Zn]) using the Core Models, which were developed for the periods 5 years (or 2 years in the case of the sensitivity analysis) before and 5 years after the intervention, as well as in the10-year (or 7-year in the case of the sensitivity analysis) period pre- and post-intervention. We also included an indicator to separate the pre- and post-intervention periods, as well as the product of the indicator with an air pollution concentration variable. The health outcomes were mortality for all natural causes and for cardiovascular and respiratory causes, at all ages and in the 65 years or older age group. To assess the short- and long-term effects, we developed two methods: one using linear regression models reflecting the age-standardized mortality rate D(j) at day j, divided by a reference D(ref); and the other using Poisson regression models with daily mortality counts as the outcome variables. We also used both models to evaluate the relation between outcome variables and daily air pollution concentrations in the current day up to all previous days in the past 3 to 4 years. In the linear regression approach, we adjusted the data for temperature and relative humidity. We then removed season as a potential confounder, or deseasonalized them, by calculating a standard seasonal mortality rate profile, normalized to an annual average of unity, and dividing the mortality rates by this profile. Finally, to correct for long-term trends, we calculated a reference mortality rate D(ref)(j) as a moving average of the corrected and deseasonalized D(j) over the observation window. Then we regressed the outcome variable D(j)/D(ref) on an entire exposure sequence {c(i)} with lags up to 4 years in order to obtain impact coefficient f(i) from the regression model shown below: deltaD(j)/D (ref) = i(max)sigma f(i) c(j - i)(i = 0). The change in life expectancy (LE) for a change of units (deltac) in the concentration of pollutants on T(day)--representing the short interval (i.e., a day)--was calculated from the following equation (deltaL(pop) = average loss in life expectancy of an entire population): deltaL(pop) = -deltac T(day) infinity sigma (j = 0) infinity sigma f(i) (i = 0). In the Poisson regression approach, we fitted a distributed-lag model for exposure to previous days of up to 4 years in order to obtain the cumulative lag effect sigma beta(i). We fit the linear regression model of log(LE*/LE) = gamma(SMR - 1) + alpha to estimate the parameter gamma by gamma, where LE* and LE are life expectancy for an exposed and an unexposed population, respectively, and SMR represents the standardized mortality ratio. The life expectancy change per Ac increase in concentration is LE {exp[gamma delta c(sigma beta(i))]-1}.In our assessment of the changes in pollutant levels, the mean levels of SO2, Ni, and V showed a statistically significant decline, particularly in industrial areas. Ni and V showed the greatest impact on mortality, especially for respiratory diseases in the 5-year pre-intervention period for both the all-ages and 65+ groups among all chemical species. There were decreases in excess risks associated with Ni and V after the intervention, but they were nonsignificant. Using the linear regression approach, with a window of 1095 days (3 years), the losses in life expectancy with a 10-microg/m3 increase in concentrations, using two methods of estimation (one with adjustment for temperature and RH before the regression against pollutants, the other with adjustment for temperature and RH within the regression against pollutants), were 19.2 days (95% CI, 12.5 to 25.9) and 31.4 days (95% CI, 25.6 to 37.2) for PM10; and 19.7 days (95% CI, 15.2 to 24.2) and 12.8 days (95% CI, 8.9 to 16.8) for SO2. The losses in life expectancy in the current study were smaller than the ones implied by Elliott and colleagues (2007) and Pope and colleagues (2002) as expected since the observation window in our study was only 3 years whereas these other studies had windows of 16 years. In particular, the coefficients used by Elliott and colleagues (2007) for windows of 12 and 16 years were non-zero, which suggests that our window of at most 3 years cannot capture the full life expectancy loss and the effects were most likely underestimated. Using the Poisson regression approach, with a window of 1461 days (4 years), we found that a 10-microg/m3 increase in concentration of PM10 was associated with a change in life expectancy of -69 days (95% CI, -140 to 1) and a change of -133 days (95% CI, -172 to -94) for the same increase in SO2. The effect estimates varied as expected according to most variations in the sensitivity analysis model, specifically in terms of the Core Model definition, exposure windows, constraint of the lag effect pattern, and adjustment for smoking prevalence or socioeconomic status.Our results on the excess risks of mortality showed exposure to chemical species to be a health hazard. However, the statistical power was not sufficient to detect the differences between the pre- and post-intervention periods in Hong Kong due to the data limitations (specifically, the chemical species data were available only once every 6 days, and data were not available from some monitoring stations). Further work is needed to develop methods for maximizing the information from the data in order to assess any changes in effects due to the intervention. With complete daily air pollution and mortality data over a long period, time-series analysis methods can be applied to assess the short- and long-term effects of air pollution, in terms of changes in life expectancy. Further work is warranted to assess the duration and pattern of the health effects from an air pollution pulse (i.e., an episode of a rapid rise in air pollution) so as to determine an appropriate length and constraint on the distributed-lag assessment model.

We assessed the effects of apparent temperature (AT) on mortality and the effect modifications attributable to individual characteristics in Hong Kong with subtropical climate conditions. Two datasets are used for analyses: one from mortality data of the general elderly population in 1998–2009; the other from an elderly cohort with 66,820 subjects recruited in 1998–2001 with mortality outcomes followed up until 2009. We found that AT below 20.8 °C was associated with an increase in mortality risk of 1.99% (95% confidence interval: 0.64%, 2.64%) for all causes, 2.48% (0.57%, 4.36%) for cardiovascular disease, and 3.19% (0.59%, 5.73%) for respiratory disease for every 1 °C decrease in AT over the following 3 days. The associations were modified by sex and body mass index, in particular stronger associations were observed for females and for obese subjects., Highlights • Cold stress was a significant predictor of mortality for elders in Hong Kong. • The strongest effects were found on mortality from respiratory diseases. • Females and obese subjects were more susceptible to cold stress., Cold stress was a significant predictor of mortality for elders in Hong Kong, especially for females and obese subjects.

Supplemental Digital Content is available in the text, Little is known about the effect of air pollution on the gastrointestinal (GI) system. We investigated the association between long-term exposures to outdoor fine particles (PM2.5) and hospitalization for peptic ulcer diseases (PUDs) in a large cohort of Hong Kong Chinese elderly. A total of 66,820 subjects aged ≥65 years who were enrolled in all 18 Government Elderly Health Service centers of Hong Kong participated in the study voluntarily between 1998 and 2001. They were prospectively followed up for more than 10 years. Annual mean exposures to PM2.5 at residence of individuals were estimated by satellite data through linkage with address details including floor level. All hospital admission records of the subjects up to December 31, 2010 were retrieved from the central database of Hospital Authority. We used Cox regression to estimate the hazard ratio (HR) for PUD hospitalization associated with PM2.5 exposure after adjustment for individual and ecological covariates. A total of 60,273 subjects had completed baseline information including medical, socio-demographic, lifestyle, and anthropometric data at recruitment. During the follow-up period, 1991 (3.3%) subjects had been hospitalized for PUD. The adjusted HR for PUD hospitalization per 10 μg/m3 of PM2.5 was 1.18 (95% confidence interval: 1.02–1.36, P = 0.02). Further analysis showed that the associations with PM2.5 were significant for gastric ulcers (HR 1.29; 1.09–1.53, P = 0.003) but not for duodenal ulcers (HR 0.98; 0.78 to 1.22, P = 0.81). Long-term exposures to PM2.5 were associated with PUD hospitalization in elder population. The mechanism underlying the PM2.5 in the development of gastric ulcers warrants further research.

Global marine vessels emissions are adversely affecting human health particularly in southeast Asia. But health burdens from both ocean- and river-going vessels in Pearl River Delta (PRD) regions are not quantified. We estimated the potential health impacts using pooled relative risks of mortality and hospital admissions in China, and the model derived concentrations of sulfur dioxide (SO₂), particulate matter (PM₁₀), nitrogen dioxide (NO₂) and ozone (O₃) due to vessels emissions. SO₂ concentrations due to marine emissions in Hong Kong were 13.6 μg m⁻³ compared with 0.7 μg m⁻³ in PRD regions that were far from the marine vessels. In PRD regions, the estimated annual numbers (per million people) of excess deaths from all natural causes and hospital admissions from cardiorespiratory causes attributable to SO₂, NO₂, O₃ and PM₁₀ combined from marine emissions were 45 and 265 respectively. Marine emission control measures could contribute a large reduction in mortality and hospital admissions in PRD regions especially in Hong Kong.

Background and Aims: A wide body of epidemiological evidence demonstrated consistent associations between temperature and daily mortality mainly from ecological time series studies. But few studies...

Background and Aims: It is important to ensure the short-term and annual AQG are valid and robust to provide support to setting standards which, if enforced, will reliably ensure that exposure reduction targets are met effectively for health protection. Methods: We developed a lognormal distribution model to examine the relationship between short-term and annual AQG for NO2 using data in 2010 in Hong Kong and London. This model, which takes into account the allowable exceedances of AQG, was robust after extreme values (4 times the geometric standard deviation above the geometric mean) were excluded [2]. Results: The WHOAQG of 40•g/m cannot be achieved through compliance with short-term limit of 200•g/m. The predicted 1hr AQG is sensitive to the standard deviation of the ambient mass concentration, and estimated to be 140•g/m and 128•g/m in Hong Kong and London respectively. In the model validation using WHO 24-hr AQG for PM10 / PM2.5, we obtained reliable prediction of annual AQG for PM10 (21.5•g/m ) and PM2.5 (10.3•g/m ) in Hong Kong. Conclusions: The large difference between WHO 1-hr limit (200•g/m) and the predicted limit indicates statistical discordance between the short-term and annual NO2 limits in the current WHOAQG, in contrast to other criteria pollutants. Based on public health principles, the shortand long-term epidemiologic evidence and need to ensure validity of health impact assessments, the 1-hr AQG should be between 128 and 140•g/m given the standard deviations observed in typical traffic dense environments. Factors affecting the standard deviation may include number of monitors, sampling locations, pollution sources, and meteorological factors. Data from other cities is needed.

To investigate the effect of comprehensive smoke-free legislation in 2007 on the exposure of children to secondhand smoke (SHS) in Hong Kong.Two cross-sectional questionnaire surveys were conducted, before (2006) and after (2008) the implementation of smoke-free legislation, among primary 2-4 students (equivalent to US grades 2-4) from 19 and 24 randomly selected schools, respectively. Adjusted ORs for SHS exposure at home and outside home post-legislation compared with pre-legislation were calculated. The strength of the association between SHS exposure and respiratory symptoms in each survey was used as an indirect indicator of the intensity of exposure.Among 3243 and 4965 never smoking students in the 2006 and 2008 surveys, the prevalence of SHS exposure in the past 7 days increased both at home (from 10.2% to 14.1%) and outside home (from 19.8% to 27.2%). Post-legislation, students were 56% more likely (p0.01) to report SHS exposure at home coupled with an insignificantly stronger association between SHS exposure and respiratory symptoms. Similarly, students were 60% more likely (p0.001) to report SHS exposure outside home in 2008, but the association between SHS exposure and respiratory symptoms became insignificantly weaker. Parental smoking rates were similar before and after legislation.The prevalence of exposure to SHS at home and outside home have both increased among primary school students in Hong Kong post-legislation. Comprehensive smoke-free legislation without strong support for smoking cessation might have displaced smoking into the homes of young children.

Background: Little is known about the effect of physical exercise on influenza-associated mortality. Methods and Findings: We collected information about exercise habits and other lifestyle, and socioeconomic and demographic status, the underlying cause of death of 24,656 adults (21% aged 30-64, 79% aged 65 or above who died in 1998 in Hong Kong, and the weekly proportion of specimens positive for influenza A (H3N1 and H1N1) and B isolation during the same period. We assessed the excess risks (ER) of influenza-associated mortality due to all-natural causes, cardiovascular diseases, or respiratory disease among different levels of exercise: never/seldom (less than once per month), low/moderate (once per month to three times per week), and frequent (four times or more per week) by Poisson regression. We also assessed the differences in ER between exercise groups by case-only logistic regression. For all the mortality outcomes under study in relation to each 10% increase in weekly proportion of specimens positive for influenza A+B, never/seldom exercise (as reference) was associated with 5.8% to 8.5% excess risks (ER) of mortality (P, published_or_final_version

Personal exposure to environmental substances is largely determined by time-microenvironment-activity patterns while moving across locations or microenvironments. Therefore, time-microenvironment-activity data are particularly useful in modeling exposure. We investigated determinants of workday time-microenvironment-activity patterns of the adult urban population in seven European cities. The EXPOLIS study assessed workday time-microenvironment-activity patterns among a total of 1427 subjects (age 19-60 years) in Helsinki (Finland), Athens (Greece), Basel (Switzerland), Grenoble (France), Milan (Italy), Prague (Czech Republic), and Oxford (UK). Subjects completed time-microenvironment-activity diaries during two working days. We present time spent indoors--at home, at work, and elsewhere, and time exposed to tobacco smoke indoors for all cities. The contribution of sociodemographic factors has been assessed using regression models. More than 90% of the variance in indoor time-microenvironment-activity patterns originated from differences between and within subjects rather than between cities. The most common factors that were associated with indoor time-microenvironment-activity patterns, with similar contributions in all cities, were the specific work status, employment status, whether the participants were living alone, and whether the participants had children at home. Gender and season were associated with indoor time-microenvironment-activity patterns as well but the effects were rather heterogeneous across the seven cities. Exposure to second-hand tobacco smoke differed substantially across these cities. The heterogeneity of these factors across cities may reflect city-specific characteristics but selection biases in the sampled local populations may also explain part of the findings. Determinants of time-microenvironment-activity patterns need to be taken into account in exposure assessment, epidemiological analyses, exposure simulations, as well as in the development of preventive strategies that focus on time-microenvironment-activity patterns that ultimately determine exposures.

Smoking scenes in movies, exploited by the tobacco industry to circumvent advertisement bans, are linked to adolescent smoking. Recently, a Hong Kong romantic comedy Love in a puff put smoking at centre stage, with numerous smoking scenes and words that glamourise smoking. Although WHO has issued guidelines on reducing the exposure of children to smoking in movies, none is adopted in Hong Kong. Comprehensive tobacco control strategies are urgently needed to protect young people in Hong Kong from cigarette promotion in movies.

To study the association between exposure to secondhand smoke (SHS) and academic performance in non-smoking adolescents.A questionnaire survey of 23 052 non-smoking students aged 11 to 20 years was conducted. Information on academic performance, number of days of SHS exposure per week at home and outside the home, number of smokers at home and their relationship with the student, and sociodemographic characteristics was recorded.Students exposed to SHS at home 1 to 4 and 5 to 7 days per week were 14% (95% confidence interval, 5%-25%) and 28% (15%-41%) more likely, respectively, to report poor academic performance compared with students who were not exposed to SHS. Living with one, two, and ≥ 3 smokers, compared with no smoker, was also associated with 10% (0.1%-20%), 43% (23%-65%) and 87% (54%-127%), respectively, higher odds of poor academic performance (P for trend.001). The greatest excess risks were observed with SHS exposure from co-residing non-relatives, followed by siblings, visitors, co-residing grandparents and relatives, and parents.SHS exposure is associated linearly with poor academic performance in non-smoking adolescents, and the effect of SHS exposure at home is stronger from smokers other than the parents.