Although haze pollution with PM2.5 as the chief pollutant has become a critical threat worldwide, little research has examined the effects of PM2.5 concentrations on subjective well-being. Based on a longitudinal aggregated panel dataset from Chinese provinces, this study investigates the effects of PM2.5 concentrations on levels of happiness and the inequality of happiness. The results showed that high ground-level PM2.5 concentrations decreased the average level of happiness and high PM2.5 concentrations had stronger negative effects on the happiness of persons with high income than those with low income. In addition, PM2.5 concentrations were also significantly negatively related to inequality of happiness in Chinese provinces. Further empirical tests showed that the negative effects of PM2.5 concentrations on the inequality of happiness could be explained by the stronger influence of PM2.5 concentrations on the subjective well-being of individuals with a higher initial level of happiness than those with a lower initial level of happiness. This confirms that PM2.5 pollution can do harm to subjective well-being and reduce variations in the subjective well-being of individuals. The policy implications of controlling haze pollution and improving well-being are discussed.

Background As effective quality management tools, quality indicators (QIs) are widely used in laboratory medicine. This study aimed to analyze the results of QIs, identify errors and provide quality specifications (QSs) based on the state-of-the-art. Methods Clinical laboratories all over China participated in the QIs survey organized by the National Health Commission of People' Republic of China from 2015 to 2017. Most of these QIs were selected from a common model of QIs (MQI) established by the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC). All participants were asked to submit general information and original QIs data through a medical quality control data collection system. The results of QIs were reported in percentages and sigma, except turnaround time (TAT) which was measured in minutes. The 25th, 50th and 75th percentiles were, respectively, calculated as three levels of QSs, which were defined starting from the model proposed during the 1st Strategic Conference of the EFLM on "Defining analytical performance 15 years after the Stockholm Conference on Quality Specification in Laboratory Medicine". Results A total of 76 clinical laboratories from 25 provinces in China continuously participated in this survey and submitted complete data for all QIs from 2015 to 2017. In general, the performance of all reported QIs have improved or at least kept stable over time. Defect percentages of blood culture contamination were the largest in the pre-analytical phase. Intra-laboratory TAT was always larger than pre-examination TAT. Percentage of tests covered by inter-laboratory comparison was relatively low than others in the intra-analytical phase. The performances of critical values notification and timely critical values notification were the best with 6.0σ. The median sigma level of incorrect laboratory reports varied from 5.5σ to 5.7σ. Conclusions QSs of QIs provide useful guidance for laboratories to improve testing quality. Laboratories should take continuous quality improvement measures in all phases of total testing process to ensure safe and effective tests.