The objective of this study was to determine the association of 19 mutations with frequencies ≥ 10% in the core promoter region of hepatitis B virus (HBV) with chronic hepatitis B (CHB), liver cirrhosis, and hepatocellular carcinoma (HCC).Eight hundred forty-six asymptomatic hepatitis B surface antigen carriers (ASCs), 235 CHB patients, 188 cirrhosis patients, and 190 HCC patients with intact data of HBV genotyping, DNA sequencing, and serological parameters were studied. Nucleotides with the highest frequencies in HBV genotypes B and C from all ASCs were treated as wild-type nucleotides.Mutations at nt.1674, nt.1719, nt.1762, nt.1764, nt.1846, nt.1896, and nt.1913 in genotype C were significantly associated with CHB, cirrhosis, and HCC, as compared with ASCs. C1673T, A1726C, A1727T, C1730G, C1766T, T1768A, C1773T, and C1799G in genotype C were significantly associated with cirrhosis compared with the CHB patients, whereas these mutations were inversely associated with HCC compared with the cirrhosis patients. Multivariate regression analyses showed that age, male, abnormal alanine aminotransferase (ALT), T1768A, A1762T/G1764A, and A1846T were independently associated with cirrhosis compared with ASCs and the patients with CHB. Age, abnormal ALT, HBV DNA (≥10(4) copies/ml), genotype C, C1653T, T1674C/G, T1753V, and A1762T/G1764A were independently associated with HCC compared with those without HCC. Haplotypic carriages with two or more HBV mutations were significantly associated with HCC. T1674C/G, C1653T, and T1753V were specific for HCC. A1762T/G1764A had a moderate sensitivity and specificity for HCC.C1673T, A1726C, A1727T, C1730G, C1766T, T1768A, C1773T, and C1799G in genotype C are specific for cirrhosis. A1846T and T1674C/G are novel factors independently associated with cirrhosis and HCC, respectively.
Devastating health effects from recent heat waves in China have highlighted the importance of understanding health consequences from extreme heat stress. Despite the increasing mortality from extreme heat, very limited studies have quantified the effects of summer extreme temperature on heat-related illnesses in China. The associations between extreme heat and daily heat-related illnesses that occurred in the summers of 2011–2013 in Ningbo, China, have been examined, using a distributed lag non-linear model (DLNM) based on 3862 cases. The excess morbidities of heat-related illness during each heat wave have been calculated separately and the cumulative heat wave effects on age-, sex-, and cause-specific illnesses in each year along lags have been estimated as well. After controlling the effect of relative humidity, it is found that maximum temperature, rather than heat index, was a better predictor of heat-related illnesses in summers. A positive association between maximum temperatures and occurrence of heat-related diseases was apparent, especially at short lag effects. Six heat waves during the period of 2011–2013 were identified and all associated with excess heat-related illnesses. Relative to the average values for the corresponding periods in 2011 and 2012, a total estimated 679 extra heat-related illnesses occurred during three heat waves in 2013. The significant prolonged heat wave effects on total heat-related illnesses during heat waves in three study years have also been identified. The strongest cumulative effect of heat waves was on severe heat diseases in 2013, with a 10-fold increased risk. More males than females, individuals with more severe forms of illness, were more affected by the heat. However, all age groups were vulnerable. Recent heat waves had a substantial and delayed effect on heat illnesses in Ningbo. Relevant active well-organized public health initiatives should be implemented to reduce the adverse effects of heat extremes on the illnesses.
This study aimed to identify circulating influenza virus strains and vulnerable population groups and investigate the distribution and seasonality of influenza viruses in Ningbo, China. Then, an autoregressive integrated moving average (ARIMA) model for prediction was established. Influenza surveillance data for 2006–2014 were obtained for cases of influenza-like illness (ILI) (n = 129,528) from the municipal Centers for Disease Control and virus surveillance systems of Ningbo, China. The ARIMA model was proposed to predict the expected morbidity cases from January 2015 to December 2015. Of the 13,294 specimens, influenza virus was detected in 1148 (8.64%) samples, including 951 (82.84%) influenza type A and 197 (17.16%) influenza type B viruses; the influenza virus isolation rate was strongly correlated with the rate of ILI during the overall study period (r = 0.20, p < 0.05). The ARIMA (1, 1, 1) (1, 1, 0)12 model could be used to predict the ILI incidence in Ningbo. The seasonal pattern of influenza activity in Ningbo tended to peak during the rainy season and winter. Given those results, the model we established could effectively predict the trend of influenza-related morbidity, providing a methodological basis for future influenza monitoring and control strategies in the study area.
Numerous studies have found associations between ambient fine particulate matter (PM2.5) and increased mortality risk. However, little evidence is available on associations between PM2.5 and years of life lost (YLL). We aimed to estimate the YLL due to chronic obstructive pulmonary disease (COPD) mortality related to ambient PM2.5 exposure. A time-series study was conducted based on the data on air pollutants, meteorological conditions and 18,472 registered COPD deaths in Ningbo, China, 2011–2015. The effects of PM2.5 on YLL and daily death of COPD were estimated, after controlling long term trend, meteorological index and other confounders. The impact of PM2.5 on YLL due to COPD lasted for 5 days (lag 0–4). Per 10 μg/m3 increase in PM2.5 was associated with 0.91 (95%CI: 0.16, 1.66) years increase in YLL. The excess YLL of COPD mortality were 8206 years, and 0.38 day per person in Ningbo from 2011 to 2015. The exposure-response curve of PM2.5 and YLL due to COPD showed a non-linear pattern, with relatively steep at low levels and flattened out at higher exposures.. Furthermore, the effects were significantly higher in the elderly than those in the younger. Our findings explored burden of PM2.5 on YLL due to COPD and highlight the importance and urgency of ambient PM2.5 pollution control and protection of the vulnerable populations.
Limited information is available on the perceptions of stakeholders concerning the health co-benefits of greenhouse gas (GHG) emission reductions. The purpose of this study was to investigate the perceptions of urban residents on the health co-benefits involving GHG abatement and related influencing factors in three cities in China. Beijing, Ningbo and Guangzhou were selected for this survey. Participants were recruited from randomly chosen committees, following quotas for gender and age in proportion to the respective population shares. Chi-square or Fisher's exact tests were employed to examine the associations between socio-demographic variables and individuals' perceptions of the health co-benefits related to GHG mitigation. Unconditional logistic regression analysis was performed to investigate the influencing factors of respondents' awareness about the health co-benefits. A total of 1159 participants were included in the final analysis, of which 15.9% reported that they were familiar with the health co-benefits of GHG emission reductions. Those who were younger, more educated, with higher family income, and with registered urban residence, were more likely to be aware of health co-benefits. Age, attitudes toward air pollution and governmental efforts to improve air quality, suffering from respiratory diseases, and following low carbon lifestyles are significant predictors of respondents' perceptions on the health co-benefits. These findings may not only provide information to policy-makers to develop and implement public welcome policies of GHG mitigation, but also help to bridge the gap between GHG mitigation measures and public engagement as well as willingness to change health-related behaviors.
Hand, foot, and mouth disease (HFMD) is a globally-prevalent infectious disease. However, few data are available on prevention measures for HFMD. The purpose of this investigation was to evaluate the impacts of temperature, humidity, and air pollution, particularly levels of particulate matter with an aerodynamic diameter 10 micrometers (PM10), on the incidence of HFMD in a city in Eastern China. Daily morbidity, meteorological, and air pollution data for Ningbo City were collected for the period from January 2012 to December 2014. A total of 86,695 HFMD cases were enrolled in this study. We used a distributed lag nonlinear model (DLNM) with Poisson distribution to analyze the nonlinear lag effects of daily mean temperature, daily humidity, and found significant relationships with the incidence of HFMD; in contrast, PM10 level showed no relationship to the incidence of HFMD. Our findings will facilitate the development of effective preventive measures and early forecasting of HFMD outbreaks.
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