To provide some useful information about the control of air pollution in China, we studied the spatial-temporal characteristics of air pollution in China from 2001–2014. First, we drew several line charts and histograms of the Air Pollution Index (API) and Air Quality Index (AQI) of 31 capital cities and municipalities to research the distribution across different times and cities; then, we researched the spatial clustering of API and AQI; finally, we examined the shift of the gravity center of API and AQI in different years and months. The API values had a decreasing trend: the high values had a clustering trend in some northern cities, and the low values had a clustering trend in some southern cities. The AQI values were relatively low, from 15:00–17:00 during the day. The gravity center of API had a trend of moving south from 2001–2003, then fluctuated in an unordered pattern and moved north in the winter. The AQI gravity center did not have a regular shift during different months. In conclusion, the government should take action to mitigate air pollution in some typical cities, as well as air pollution during the winter.

Background: A valid and efficient stress measure is important for clinical and community settings. The objectives of this study were to translate the English version of the Perceived Stress Questionnaire (PSQ) into Chinese and to assess the psychometric properties of the Chinese version of the PSQ (C-PSQ). The C-PSQ evaluates subjective experiences of stress instead of a specific and objective status. Methods: Forward translations and back translations were used to translate the PSQ into Chinese. We used the C-PSQ to survey 2798 medical students and workers at three study sites in China from 2015 to 2017. Applying Rasch analysis (RA) and factor analysis (FA), we examined the measurement properties of the C-PSQ. Data were analyzed using the Rasch model for item fit, local dependence (LD), differential item functioning (DIF), unidimensionality, separation and reliability, response forms and person-item map. We first optimized the item selection in the Chinese version to maximize its psychometric quality. Second, we used cross-validation, by exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), to determine the best fitting model in comparison to the different variants. Measurement invariance (MI) was tested using multi-group CFA across subgroups (medical students vs. medical workers). We evaluated validity of the C-PSQ using the criterion instruments, such as the Chinese version of the Perceived Stress Scale (PSS-10), the Short Form-8 Health Survey (SF-8) and the Goldberg Anxiety and Depression Scale (GADS). Reliability was assessed using internal consistency (Cronbach’s alpha, Guttman’s lambda-2, and McDonald’s omegas) and reproducibility (test–retest correlation and intraclass correlation coefficient, [ICC]). Results: Infit and/or outfit values indicated that all items fitted the Rasch model. Three item pairs presented local dependency (residual correlations > 0.30). Ten items showed DIF. Dimensionality instruction suggested that eight items should be deleted. One item showed low discrimination. Thirteen items from the original PSQ were retained in the C-PSQ adaptation (i.e. C-PSQ-13). We tested and verified four feasible models to perform EFA. Built on the EFA models, the optimal CFA model included two first-order factors (i.e. constraint and imbalance) and a second-order factor (i.e., perceived stress). The first-order model had acceptable goodness of fit (Normed Chi-square = 8.489, TLI = 0.957, CFI = 0.965, WRMR = 1.637, RMSEA [90% CI] = 0.078 [0.072, 0.084]). The second-order model showed identical model fit. Person separation index (PSI) and person reliability (PR) were 2.42 and 0.85, respectively. Response forms were adequate, item difficulty matched respondents’ ability levels, and unidimensionality was found in the two factors. Multi-group CFA showed validity of the optimal model. Concurrent validity of the C-PSQ-13 was 0.777, − 0.595 and 0.584 (Spearman correlation, P < 0.001, the same hereinafter) for the Chinese version of the PSS-10, SF-8, and GADS. For reliability analyses, internal consistency of the C-PSQ-13 was 0.878 (Cronbach’s alpha), 0.880 (Guttman’s lambda-2), and 0.880 (McDonald’s omegas); test–retest correlation and ICC were 0.782 and 0.805 in a 2-day interval, respectively. Conclusion: The C-PSQ-13 shows good metric characteristics for most indicators, which could contribute to stress research given its validity and economy. This study also contributes to the evidence based regarding between-group factorial structure analysis.

Background: As one of the most common cancers in the female population, cervical cancer has ranked as the second most incident gynecological cancer in recent years, trailing only breast cancer. We aimed to assess and compare the secular trends in cervical cancer mortality in China and the United States and analyze the independent effects of chronological age, time period and birth cohort using age-period-cohort (APC) analysis. Methods: We performed an age-period-cohort analysis using the intrinsic estimator method to estimate the independent effects of age, time period, and birth cohort on cervical cancer mortality. We collected mortality data for China and the United States from the WHO Mortality Database and China Health Statistical Yearbook database. Results: We examined the general trends in cervical mortality rates in China and the United States during the periods 1988–2012 and 1953–2012, respectively. The age-standardized mortality rates (ASMRs) for cervical cancer in urban China, rural China and the U.S. showed a general decreasing trend during the observation period, except for urban China, which experienced a significant increase beginning in 2002. The mortality rates for cervical cancer in the three areas showed a general increasing trend with age, regardless of the period effect. Period effects declined steadily in both rural China (from 0.19 to −0.26) and the U.S. (from −0.20 to −0.43); however, a slight increasing trend was identified (from −0.25 to 0.33) in urban China, which indicated that the risk of mortality increased with time. Cohort effects peaked in the cohort born in 1911–1915 in both rural China and urban China, declined consistently in the cohort born before 1950, and then decreased again in the cohort born after 1976–1980. The cohort effect in the U.S. peaked in the birth cohort born in 1876–1880, then leveled off and slightly decreased in younger generations. Conclusions: Our study showed that in general, cervical cancer mortality rates increased with age and decreased with birth cohort in the U.S., while the risk of mortality was highest in the cohort born during 1946–1975 in urban China. Additionally, the risk of mortality consistently increased with age in women younger than 64 years old in urban and rural China and began to decline in older groups. Although the age and cohort effects were relatively strong, the period effect may be the key factor affecting cervical cancer mortality trends, mainly reflecting the immediate effects of effective treatment and the implementation of screening.

To describe the temporal trends of breast cancer mortality in East Asia and to better understand the causes of these trends, we analyzed the independent effects of chronological age, time period and birth cohort on breast cancer mortality trends using age-period-cohort (APC) analysis. We chose three main countries in East Asia, namely China, South Korea, and Japan, which have reported death status to the WHO Mortality Database, and used the United States as a comparison population. Our study shows that in general, breast cancer mortality rates in females increased in all three East Asian countries throughout the study period. By APC analysis, we confirmed that there is, in fact, a difference in age-specific mortality rate patterns between the Eastern and the Western countries, which is presumably caused by the two-disease model. While the cause of the decrease from approximately the 1950s generation is still in question, we believe that increasing general awareness and improvements in the health-care system have made a significant contribution to it. Although the age and cohort effects are relatively strong, the period effect may be a more critical factor in the mortality trend, mainly reflecting the increase in exposures to carcinogens and behavioral risk factors.

In this study, we analyzed the temporal and spatial variations of stroke mortality attributable to ambient particulate matter pollution (stroke mortality-PM_2.5) in China from 1990 to 2015. Data were collected from the Global Burden of Disease (GBD) 2015 study and analyzed by an age-period-cohort model (APC) with an intrinsic estimator (IE) algorithm, as well as spatial autocorrelation based on the Geographic Information System. Based on APC analysis with the IE method, stroke mortality-PM_2.5 increased exponentially with age, its relative risk reaching 42.85 (95% CI: 28.79, 63.43) in the 75–79 age group. The period effects showed a reversed V-shape and its highest relative risk was 1.22 (95% CI: 1.15, 1.27) in 2005. The cohort effects decreased monotonically from 1915–1919 to 1990–1994. The change rate fluctuated from 1920–1924 to 1990–1994, including three accelerating and three decelerating decreases. There was a positive spatial autocorrelation in stroke mortality-PM_2.5 from 1990 to 2015. Hot-spots moved from the northeastern areas to the middle and southwestern areas, whereas cold-spots lay mostly in coastal provinces. Besides the aging process in recent years, stroke mortality-PM_2.5 had significantly declined from 2005 to 2015 due to socio-economic and healthcare development. Stroke mortality-PM_2.5 varied substantially among different regions, and cost-effective prevention and control should be implemented more in the middle and southwestern areas of China.

The aim of this study is to explore the long-term trends of suicide mortality in China. We implemented the age-period-cohort (APC) framework, using data from the Global Burden of Disease Study 2013. Our results showed that the net drift of suicide mortality was −4.727% (95% CI: −4.821% to −4.634%) per year for men and −6.633% (95% CI: −6.751% to −6.515%) per year for women, and the local drift values were below 0 in all age groups (p < 0.01 for all) for both sexes during the period of 1994–2013. Longitudinal age curves indicated that, in the same birth cohort, suicide death risk increased rapidly to peak at the life stage of 20–24 years old and 15–24 years old for men and women, respectively, and then showed a decelerated decline, followed by a rise thereafter after 54 years old for men and a slight one after 69 years old for women. The estimated period and cohort RRs were found to show similar monotonic downward patterns (significantly with p < 0.01 for all) for both sexes, with more quickly decreasing for women than for men during the whole period. The decreasing trend of suicide was likely to be related to the economic rapid growth, improvements in health care, enhancement on the level of education, and increasing awareness of suicide among the public in China. In addition, fast urbanization and the effective control of pesticides and rodenticides might be the special reasons behind these trends we observed in this study.