Objective To assess the effect of smoking on body mass index (BMI) among residents in Guangdong Province. Methods Using the method of multistage clustering random sampling, permanent residents aged 18 years and above were selected from Yuexiu District of Guangzhou City, Yuncheng District of Yunfu City, Town District of Shanwei City, Wuhua County of Meizhou City, Sihui County of Zhao qing City, Nanxiong County of Shaoguan City in 2010.Questionnaire survey and physical examination were conducted using the method of combination of focused and household investigations. Contents of the questionnaire included basic personal information, smoking, drinking, diet, physical activity, and family economic status. Rate and ratio were used for statistic description. T-test, One way ANOVA, and multiple linear regression were used to analyze the relationship between smoking and BMI. Results A total of 3 591 people were surveyed, including 1 621 men (45.14%) and 1 970 women (54.86%）. The rates of never smoking, current smoking, and past smoking were 72.29%（2 596/3 591）, 22.86%（821/3 591）, and 4.85%（174/3 591）, respectively. The average BMI of all participants was 22.96±3.32. The mean BMI of never smoking, current smoking, and past smoking were 23.29±3.64, 22.76±3.35, and 23.01±3.28, respectively. After controlling gender, age, occupation, educational level, family income per capita, alcohol, and the amount of exercise, differences among BMI of smoking 1 to 9 cigarettes/day, smoking 10 to 19 cigarettes/day and not smoking were statistically significant (P<0.05), and their average BMI (95% CI) were 22.27 (21.75-22.80), 22.12 (21.66-22.59), and 23.03 (22.90-23.16), respectively. Current smoking and BMI were negatively correlated after adjusting for gender, age, occupation, and other variables, and its beta value was -0.552(P<0.05). Conclusion The smoking rate of residents in Guangdong Province remained high. Smoking was negatively correlated with BMI, but BMI was reduced very less.

Objective To understand situation of Guangzhou residents’ KAP related to PM2.5, to provide the scientific basis for the government to formulate relevant policy.Methods Unified questionnaire with intercept survey was used anonymously in subway stations, park, residential communities, squares and some densely populated places from 17∶30-19∶30 during July 1 to 15, 2012, to investigate residents aged between 18 and 65 and living in Guangzhou more than three months, The survey contents included the residents’cognition to the knowledge related to PM2.5, attitude to the government to carry out the monitoring of PM2.5, and whether to take self-protection measures and ways in the air pollution Single factor chi-square test was adopted for rate comparison Unconditional logistic regression analysis was used for multiple factors analysis. Results Six hundred and five persons (310 males and 295 females, median age 38 years, range 18 to 65 years) were effectively responded from 714 interviewees, with a response rate of 84.7% (605/714). Their education levels were mainly middle school and polytechnics (44.5%,269/605). The awareness rate of PM2.5 was 27.9% (169/605). The result of multiple factors unconditional logistic regression analysis revealed that educational level（OR=1.36), age（OR=2.24-3.17） and career（OR=2.76-3.37） were the main factors affecting people to know PM2.5（P＜0.01，P＜0.05）.57.0% (166/291) of respondents paid attention to PM2.5monitoring data announced by the government 88.3% (257/291) of respondents supported the government to announce PM2.5monitoring data every day. The top three favorability ratings by residents about monitoring points to monitor PM2.5 were residential area (73.5%, 214/291), industrial area (65.3%, 190/291), and streets (64.6%, 188/291). The respondents believed that the main methods to control PM2.5 pollution were to strengthen the management of industrial pollution (89.4%, 260/291) and control automobile emission (86.9%, 253/291). 77.5% (469/605) of respondents took effective protection measures during the serious air pollution. People who knew PM2.5 supported that the main measures were to reduce going out (66.3%, 112/169), wear masks (58.6%, 99/169) and close the window (44.4%, 75/169) when the air pollution was serious, higher than those who did not know PM2.5（43.6%, 38.5%, and 29.9%, all P＜0.01). The result of multiple factors unconditional logistic regression analysis revealed that whether residents knew PM2.5 was the influencing factor (OR=2.35, P＜0.01) after adjusting for demographic characteristics when residents took protective measures in the condition of serious air pollution. Conclusion The cognitive level of people to PM2.5 remained to be further improved. Residents supported the government to announce PM2.5 monitoring data. Monitoring point setting for PM2.5 was closely related with their own requirements. The public required the government to implement measures of reducing pollution and emission, and had strong willingness to reduce the health hazard of PM2.5.