Trends and prediction in the incidence rate of hepatitis C in Shandong Province in China from 2004 to 2030.

BACKGROUND: Hepatitis C threatens human health and brings a heavy economic burden. Shandong Province is the second most populous province in China and has uneven regional economic development. Therefore, we analyzed the incidence rate trend and regional differences of hepatitis C in Shandong Province from 2004 to 2021. METHODS: The monthly and annual incidence rates of hepatitis C in Shandong Province from 2022 to 2030 were predicted by fitting Autoregressive Integrated Moving Average model (ARIMA), Long Short-Term Memory (LSTM) and ARIMA-LSTM combined model. RESULTS: From 2004 to 2021, annual new cases of hepatitis C in Shandong Province increased from 635 to 5834, with a total of 61,707 cases. The incidence rate increased from 0.69/100 thousand in 2004 to 6.40/100 thousand in 2019, with a slight decrease in 2020 and 2021. The average annual incidence rate was 3.47/100 thousand. In terms of regional distribution, the hepatitis C incidence rate in Shandong Province was generally high in the west and low in the east. It is estimated that the hepatitis C incidence rate in Shandong Province will be 9.21 per 100 thousand in 2030. CONCLUSION: The hepatitis C incidence rate in Shandong Province showed an increasing trend from 2004 to 2019 and a decreasing trend in 2020 and 2021. Significant regional variations in incidence rate existed. An upward trend in incidence rate is predicted from 2022 to 2030. It is necessary to strengthen the prevention and control of hepatitis C to achieve the goal of eliminating viral hepatitis by 2030.

The interaction effects between exposure to ambient PM2.5 and economic development on the settlement intention for floating population in China.

Limited studies examined the interaction effects between exposure to ambient PM2.5 and economic development on the settlement intention of floating population. We used binary logistic model to examine the association of PM2.5, per capita GDP (PGDP), PM2.5 [Formula: see text] PGDP on the settlement intention. Additive interaction term of PM2.5 and PGDP level was used to investigate their interactive effects. Overall, each one grade increment in annual average PM2.5 was associated with decreased probability of settlement intention (OR = 0.847, 95%CI: 0.811-0.885). The interaction effect between PM2.5 and PGDP on settlement intention was significant (OR = 1.168, 95%CI: 1.142-1.194). The stratified analysis showed PM2.5 exhibits lower settlement intention in the aged 55 years or above, engaged in low-skilled works, and living in the western China. This study indicates that PM2.5-exposed will decrease the settlement intention of floating population. High economic development level can weaken the relationship between PM2.5 and settlement intention. Policymakers should balance the socio-economic development and environmental health and focus on vulnerable population.

Provincial heterogeneity in the management of care cascade for hypertension, diabetes, and dyslipidaemia in China: Analysis of nationally representative population-based survey.

Background: This study aims to examine (1) province-level variations in the levels of cardiovascular disease (CVD) risk and behavioral risk for CVDs, (2) province-level variations in the management of cascade of care for hypertension, diabetes, and dyslipidaemia, and (3) the association of province-level economic development and individual factors with the quality of care for hypertension, diabetes, and dyslipidaemia. Methods: We used nationally representative data from the China Health and Retirement Longitudinal Study in 2015, which included 12,597 participants aged 45 years. Using a care cascade framework, we examined the quality of care provided to patients with three prevalent NCDs: hypertension, diabetes, and dyslipidaemia. The proportion of WHO CVD risk based on the World Health Organization CVD risk prediction charts, Cardiovascular Risk Score (CRS) and Behavior Risk Score (BRS) were calculated. We performed multivariable logistic regression models to determine the individual-level drivers of NCD risk variables and outcomes. To examine socio-demographic relationships with CVD risk, linear regression models were applied. Results: In total, the average CRS was 4.98 (95% CI: 4.92, 5.05), while the average BRS was 3.10 (95% confidence interval: 3.04, 3.15). The weighted mean CRS (BRS) in Fujian province ranged from 4.36 to 5.72 (P < 0.05). Most of the provinces had a greater rate of hypertension than diabetes and dyslipidaemia awareness and treatment. Northern provinces had a higher rate of awareness and treatment of all three diseases. Similar patterns of regional disparity were seen in diabetes and dyslipidaemia care cascades. There was no evidence of a better care cascade for CVDs in patients who reside in more economically advanced provinces. Conclusion: Our research found significant provincial heterogeneity in the CVD risk scores and the management of the cascade of care for hypertension, diabetes, and dyslipidaemia for persons aged 45 years or more. To improve the management of cascade of care and to eliminate regional and disparities in CVD care and risk factors in China, local and population-based focused interventions are necessary.

Air pollution control efficacy and health impacts: A global observational study from 2000 to 2016.

Particulate matter with aerodynamic diameter ≤2.5 µm (PM2.5) concentrations vary between countries with similar carbon dioxide (CO2) emissions, which can be partially explained by differences in air pollution control efficacy. However, no indicator of air pollution control efficacy has yet been developed. We aimed to develop such an indicator, and to evaluate its global and temporal distribution and its association with country-level health metrics. A novel indicator, ambient population-weighted average PM2.5 concentration per unit per capita CO2 emission (PM2.5/CO2), was developed to assess country-specific air pollution control efficacy (abbreviated as APCI). We estimated and mapped the global average distribution of APCI and its changes during 2000-2016 across 196 countries. Pearson correlation coefficients and Generalized Additive Mixed Model (GAMM) were used to evaluate the relationship between APCI and health metrics. APCI varied by country with an inverse association with economic development. APCI showed an almost stable trend globally from 2000 to 2016, with the low-income groups increased and several countries (China, India, Bangladesh) decreased. The Pearson correlation coefficients between APCI and life expectancy at birth (LE), infant-mortality rate (IMR), under-five year of age mortality rate (U5MR) and logarithm of per capita GDP (LPGDP) were -0.57, 0.65, 0.66, -0.59 respectively (all P values < 0.001). APCI could explain international variation of LE, IMR and U5MR. The associations between APCI and LE, IMR, U5MR were independent of per capita GDP and climatic factors. We consider APCI to be a good indicator for air pollution control efficacy given its relation to important population health indicators. Our findings provide a new metric to interpret health inequity across the globe from the point of climate change and air pollution control efficacy.

Socioeconomic disparity in the association between long-term exposure to PM2.5 and mortality in 2640 Chinese counties.

BACKGROUND: Although the association between long-term exposure to PM2.5 and mortality has been evaluated intensively, little is known about the socioeconomic disparity in the association. METHODS: We collected data on annual all-cause mortality, PM2.5 concentration, socioeconomic and demographic characteristics of 2640 counties from the two most recent Chinese censuses in 2000 and 2010. We applied the difference-in-differences (DID) method to estimate PM2.5-mortality association for counties at different quartiles of literacy rate, college rate, urbanization rate and GDP per capita, respectively. RESULTS: Overall, every 10 µg/m3 increase in annual average PM2.5 was associated with 3.8% (95% confidence interval [CI]: 3.0-5.0) increase of all-cause mortality. The stratified analysis suggested higher health impact of exposure in counties with lower socioeconomic status. For counties of the lowest quartile (Q1) of literacy rate, college rate, urbanization rate and GDP per capita, the effect estimates were 6.0% (95% CI: 4.2-7.7), 4.4% (95% CI: 2.8-6.0), 3.5% (95% CI: 2.0-5.1) and 4.9% (95% CI: 2.7-7.1), respectively. There was strong evidence for elevated risk in mortality associated with PM2.5 of all socioeconomic factors in the lowest quartile (Q1) compared with the highest quartile counties (Q4) (p-value for difference < 0.05). CONCLUSIONS: There was socioeconomic disparity in the PM2.5-mortality association in China. Dwellers living in less developed counties are more vulnerable to long-term exposure to ambient PM2.5 than those living in developed counties.