Occurrence, fate, and risk assessment of antibiotics in conventional and advanced drinking water treatment systems: From source to tap.

The occurrence and removal of 38 antibiotics from nine classes in two drinking water treatment plants (WTPs) were monitored monthly over one year to evaluate the efficiency of typical treatment processes, track the source of antibiotics in tap water and assess their potential risks to ecosystem and human health. In both source waters, 18 antibiotics were detected at least once, with average total antibiotic concentrations of 538.5 ng/L in WTP1 and 569.3 ng/L in WTP2. The coagulation/flocculation and sedimentation, sand filtration and granular activated carbon processes demonstrated limited removal efficiencies. Chlorination, on the other hand, effectively eliminated antibiotics by 48.7 ± 11.9%. Interestingly, negative removal was observed along the distribution system, resulting in a significant antibiotic presence in tap water, with average concentrations of 131.5 ng/L in WTP1 and 362.8 ng/L in WTP2. Source tracking analysis indicates that most antibiotics in tap water may originate from distribution system. The presence of antibiotics in raw water and tap water posed risks to the aquatic ecosystem. Untreated or partially treated raw water could pose a medium risk to infants under six months. Water parameters, for example, temperature, total nitrogen and total organic carbon, can serve as indicators to estimate antibiotic occurrence and associated risks. Furthermore, machine learning models were developed that successfully predicted risk levels using water quality parameters. Our study provides valuable insights into the occurrence, removal and risk of antibiotics in urban WTPs, contributing to the broader understanding of antibiotic pollution in water treatment systems.

Why are male Chinese smokers unwilling to quit? A multicentre cross-sectional study on smoking rationalisation and intention to quit.

OBJECTIVE: We aimed to describe the rationalisation beliefs endorsed by Chinese male smokers and to examine the association between rationalisation and the intention to quit. SETTING: Questionnaires were conducted among male smokers in three cities (Shanghai, Nanning and Mudanjiang) which represent different geographical locations, economic development levels and legislative status of tobacco control in China. DESIGN AND PARTICIPANTS: It was a multicentre cross-sectional survey involved a total of 3710 male smokers over 18 years. OUTCOME MEASURES: Primary outcomes were intention to quit, smoking rationalisation scores and sub scores in six dimensions. Smoking rationalisation was assessed using a newly developed Chinese rationalisation scale. Multivariable logistic regression was performed to examine the relationship between rationalisation and intention to quit. RESULTS: On average, smokers scored 3.3 out of 5 on the smoking rationalisation scale. With a one point increase in total rationalisation scale, the odds for intention to quit in the next 6 months decreased by 48% (OR=0.52, 95% CI: 0.44 to 0.61; p<0.001). Separate logistic regressions for six subscales of rationalisation shown consistent inverse associations with intention to quit (all p values <0.001). Believing that smoking was socially acceptable was the strongest predictor (OR=0.62, 95% CI: 0.55 to 0.71; p<0.001). CONCLUSIONS: Rationalisation beliefs could be important barriers to smoking cessation. Some beliefs have stronger association with quit intention than others. Eroding rationalisation beliefs endorsed by smokers is a potential strategy for smoking cessation intervention.

Correlates of smoke-free home policies in Shanghai, China.

BACKGROUND: Approximately 63.7% of nonsmokers in China are exposed to secondhand smoke (SHS) in their homes. The current study documents the prevalence and correlates of smoke-free home policies in Shanghai, as well as reasons for implementing such a policy and places where smoking is most commonly allowed. METHODS: We conducted in-person surveys of 500 participants using a multistage proportional random sampling design in an urban and suburban district. RESULTS: Overall, 35.3% had a smoke-free home policy. In the logistic regression, having higher income, not having smokers in the home, having children in the home, having fewer friends/relatives who permit smoking at home, and not being a current smoker were correlates of having a smoke-free home policy (P < 0.05). Concern about the health impact of SHS was reportedly the most important reason for establishing a smoke-free home. Among participants with no or partial bans, the most common places where smoking was allowed included the living room (64.2%), kitchen (46.1%), and bathroom (33.8%). CONCLUSIONS: Smoke-free home policies were in place for a minority of households surveyed. Establishing such a policy was influenced by personal smoking behavior and social factors. These findings suggest an urgent need to promote smoke-free home policies through tobacco control programs.