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BACKGROUND: Low temperatures are adverse contributors to cardiovascular diseases, but the associations between short-term exposure to cold and the risk of death from aortic dissection and aneurysm remain unclear, particularly in tropical regions. OBJECTIVE: This study was conducted based on 123,951 records of deaths caused by aortic dissection and aneurysms extracted from the national Mortality Information System in Brazil between 2000 and 2019. METHODS: Relative risks and 95 % confidence intervals (CI) for the aortic-related deaths associated with low ambient temperatures were estimated using the conditional logistic model combined with the distributed lag nonlinear model. Subgroup analyses were performed by age group, sex, race, education level, and residential region. Furthermore, this study calculated the number and fraction of aortic-related deaths attributed to temperatures below the temperature threshold to quantify the cold-related mortality burden of aortic diseases. RESULTS: During the study period, aortic-related deaths and mortality rates in Brazil exhibited a steady increase, rising from 4419 (2.66/100,000) in 2000 to 8152 (3.88/100,000) in 2019. Under the identified temperature threshold (26 °C), per 1 °C decrease in daily mean temperature was associated with a 4.77 % (95 % CI: 4.35, 5.19) increase in mortality risk of aortic-related diseases over lag 0-3 days. Females, individuals aged 50 years or older, Asian and Black race, and northern residents were more susceptible to low temperatures. Low temperatures were responsible for 19.10 % (95 % CI: 17.71, 20.45) of aortic-related deaths in Brazil. CONCLUSION: This study highlights that low temperatures were associated with an increased risk of aortic-related deaths, with a remarkable burden even in this predominantly tropical country.
Subject(s)
Aortic Aneurysm , Aortic Dissection , Cold Temperature , Humans , Brazil/epidemiology , Male , Female , Middle Aged , Aortic Dissection/mortality , Aged , Aortic Aneurysm/mortality , Cold Temperature/adverse effects , Adult , Tropical Climate , Young Adult , Aged, 80 and over , Risk Factors , AdolescentABSTRACT
BACKGROUND: Air pollutants are important exogenous stimulants to eye diseases, but knowledge of associations between long-term exposure to air pollutants and the risk of primary open-angle glaucoma (POAG) is limited. This study aimed to determine whether long-term exposure to air pollutants, genetic susceptibility, and their joint effects lead to an elevated risk of incident POAG. METHODS: This is a population-based prospective cohort study from UK Biobank participants with complete measures of air pollution exposure and polygenetic risk scores. Cox proportional hazard models were fitted to assess the individual and joint effects of long-term exposure to air pollutants and genetics on the risk of POAG. In addition, the effect modification of genetic susceptibility was examined on an additive or multiplicative scale. RESULTS: Among 434,290 participants with a mean (SD) age of 56.5 (8.1) years, 6651 (1.53 %) were diagnosed with POAG during a median follow-up of 13.7 years. Long-term exposure to air pollutants was associated with an increased risk of POAG. The hazard ratios associated with per interquartile range increase in PM2.5, PM2.5 absorbance, PM10, NO2, and NOX individually ranged from 1.027 (95 % CI: 1.001-1.054) to 1.067 (95 % CI: 1.035-1.099). Compared with individuals residing in low-pollution areas and having low polygenic risk scores, the risk of incident POAG increased by 105.5 % (95 % CI: 78.3 %-136.9 %), 79.7 % (95 % CI: 56.5 %-106.5 %), 103.2 % (95 % CI: 76.9 %-133.4 %), 89.4 % (95 % CI: 63.9 %-118.9 %), and 90.2 % (95 % CI: 64.8 %-119.5 %) among those simultaneously exposed to high air pollutants levels and high genetic risk, respectively. Genetic susceptibility interacted with PM2.5 absorbance and NO2 in an additive manner, while no evidence of multiplicative interaction was found in this study. Stratification analyses revealed stronger effects in Black people and the elderly. CONCLUSION: Long-term air pollutant exposure was associated with an increased risk of POAG incidence, particularly in the population with high genetic predisposition.
Subject(s)
Air Pollutants , Air Pollution , Environmental Exposure , Genetic Predisposition to Disease , Glaucoma, Open-Angle , Humans , Glaucoma, Open-Angle/genetics , Glaucoma, Open-Angle/epidemiology , Glaucoma, Open-Angle/chemically induced , Air Pollution/statistics & numerical data , Air Pollution/adverse effects , Middle Aged , Air Pollutants/analysis , Female , Male , Prospective Studies , Environmental Exposure/statistics & numerical data , Particulate Matter , Incidence , United Kingdom/epidemiology , AgedABSTRACT
BACKGROUND: This study aimed to examine the prevalence and associated factors of malnutrition in older community-dwellers and explore the interaction between associated factors. METHODS: A total of 474,467 older community-dwellers aged 65 or above were selected in Guangzhou, China. We used a two-step methodology to detect the associated factors of malnutrition and constructed logistic regression models to explore the influencing factors and interactive effects on three patterns of malnutrition. RESULTS: The prevalence of malnutrition was 22.28%. Older adults with both hypertension and diabetes (RERI = 0.13), both meat or fish diet and hypertension (RERI = 0.79), and both meat or fish diet and diabetes (RERI = 0.81) had positive additive interaction effects on the risk of obesity, whereas those on a vegetarian diet with hypertension (RERI = -0.25) or diabetes (RERI = -0.19) had negative additive interaction effects. Moreover, the interactions of physical activity with a meat or fish diet (RERI = -0.84) or dyslipidemia (RERI = -0.09) could lower the risk of obesity. CONCLUSIONS: Malnutrition was influenced by different health factors, and there were interactions between these influencing factors. Pertinent dietary instruction should be given according to different nutritional status indexes and the prevalence of metabolic diseases to avoid the occurrences of malnutrition among older adults.
Subject(s)
Data Mining , Hypertension , Malnutrition , Humans , Aged , China/epidemiology , Male , Female , Malnutrition/epidemiology , Prevalence , Hypertension/epidemiology , Risk Factors , Aged, 80 and over , Independent Living , Nutritional Status , Diabetes Mellitus/epidemiology , Obesity/epidemiology , Diet , Exercise , Logistic Models , Dyslipidemias/epidemiologyABSTRACT
Background: Previous studies on the effect of global warming on the global burden of disease have mainly focussed on the impact of high temperatures, thereby providing limited evidence of the effect of lower temperatures. Methods: We adopted a three-stage analysis approach using data from the Global Burden of Disease 2019 study. First, we explored the global burden of disease attributable to low temperatures, examining variations by gender, age, cause, region, and country. Second, we analysed temporal trends in low-temperature-related disease burdens from 1990 to 2019 by meta-regression. Finally, we fitted a mixed-effects meta-regression model to explore the effect modification of country-level characteristics. Results: In 2019, low temperatures were responsible for 2.92% of global deaths and 1.03% of disability-adjusted life years (DALYs), corresponding to a death rate of 21.36 (95% uncertainty interval (UI) = 18.26, 24.73) and a DALY rate of 335 (95% UI = 280, 399) per 100 000 population. Most of the deaths (85.12%) and DALYs (94.38%) attributable to low temperatures were associated with ischaemic heart disease, stroke, and chronic obstructive pulmonary disease. In the last three decades, we observed an upward trend for the annual number of attributable deaths (P < 0.001) and a downward trend for the rates of death (P < 0.001) and DALYs (P < 0.001). The disease burden associated with low temperatures varied considerably among regions and countries, with higher burdens observed in regions with middle or high-middle socio-demographic indices, as well as countries with higher gross domestic product per capita and a larger proportion of ageing population. Conclusions: Our findings emphasise the significance of raising public awareness and prioritising policies to protect global population health from the adverse effects of low temperatures, even in the face of global warming. Particular efforts should be targeted towards individuals with underlying diseases (e.g. cardiovascular diseases) and vulnerable countries or regions (e.g. Central Asia and central Europe).
Subject(s)
Global Burden of Disease , Pulmonary Disease, Chronic Obstructive , Humans , Quality-Adjusted Life Years , Temperature , Cost of Illness , Pulmonary Disease, Chronic Obstructive/epidemiology , Global Health , Risk FactorsABSTRACT
BACKGROUND: Count time series (e.g., daily deaths) are a very common type of data in environmental health research. The series is generally autocorrelated, while the widely used generalized linear model is based on the assumption of independent outcomes. None of the existing methods for modelling parameter-driven count time series can obtain consistent and reliable standard error of parameter estimates, causing potential inflation of type I error rate. METHODS: We proposed a new maximum significant ρ correction (MSRC) method that utilizes information of significant autocorrelation coefficient ρ estimate within 5 orders by moment estimation. A Monte Carlo simulation was conducted to evaluate and compare the finite sample performance of the MSRC and classical unbiased correction (UB-corrected) method. We demonstrated a real-data analysis for assessing the effect of drunk driving regulations on the incidence of road traffic injuries (RTIs) using MSRC in Shenzhen, China. Moreover, there is no previous paper assessing the time-varying intervention effect and considering autocorrelation based on daily data of RTIs. RESULTS: Both methods had a small bias in the regression coefficients. The autocorrelation coefficient estimated by UB-corrected is slightly underestimated at high autocorrelation (≥ 0.6), leading to the inflation of the type I error rate. The new method well controlled the type I error rate when the sample size reached 340. Moreover, the power of MSRC increased with increasing sample size and effect size and decreasing nuisance parameters, and it approached UB-corrected when ρ was small (≤ 0.4), but became more reliable as autocorrelation increased further. The daily data of RTIs exhibited significant autocorrelation after controlling for potential confounding, and therefore the MSRC was preferable to the UB-corrected. The intervention contributed to a decrease in the incidence of RTIs by 8.34% (95% CI, -5.69-20.51%), 45.07% (95% CI, 25.86-59.30%) and 42.94% (95% CI, 9.56-64.00%) at 1, 3 and 5 years after the implementation of the intervention, respectively. CONCLUSIONS: The proposed MSRC method provides a reliable and consistent approach for modelling parameter-driven time series with autocorrelated count data. It offers improved estimation compared to existing methods. The strict drunk driving regulations can reduce the risk of RTIs.
Subject(s)
Time Factors , Humans , Linear Models , Computer Simulation , Bias , ChinaABSTRACT
BACKGROUND: Meteorological factors are associated with various health outcomes. However, it remains uncertain whether ambient temperature affects animal aggressive behaviors and causes mammalian-related injuries (MRI) in humans. The study aimed to examine the effect of daily mean temperature on MRI in Guangzhou, China. METHODS: Individual cases of MRI were obtained from Guangzhou Injury Surveillance System during 2014-2019. A combination of a distributed lag nonlinear model and conditional quasi-Poisson regression, implemented within a time-stratified case-crossover design, was employed to evaluate the association between temperature and MRI. Subgroup analyses were conducted by sex, age group, education level, and types of mammals. RESULT: This study included 24,206 MRI cases among which 89.7 % were caused by cats or dogs. We observed a nonlinear relationship between daily mean temperature and MRI. The impact of high temperatures was most pronounced on the current day and remained statistically significant on the next day. Compared with the reference temperature with a minimum risk of injuries (9.3 °C, approximately 2nd percentile of temperature), 75th percentile of temperature (27.4 °C) exerted the greatest relative risk (RR) of injuries (RR = 1.45, 95 % CI: 1.25-1.68) over lag 0-1 days. In subgroup analyses, the effects of high temperatures among males and females were similar. Individuals aged 15-34 years and 35-59 years were more susceptible to MRI at high temperatures compared to other age groups. The risk of injuries caused by cats or dogs consistently increased with high temperatures. We did not find significant impacts of low temperatures. CONCLUSION: Short-term heat exposure plays an important role in the occurrence of MRI. The findings highlight the importance of enhancing public awareness regarding the high temperature-associated hazards posed by mammals. There is a need for enhanced regulations and measures on the management for cats and dogs to mitigate the harm caused in hot seasons.
Subject(s)
Hot Temperature , Wounds and Injuries , Animals , Cats , Dogs , Female , Humans , Male , China/epidemiology , Cold Temperature , Mammals , Seasons , Temperature , Adolescent , Young Adult , Adult , Middle Aged , Cross-Over StudiesABSTRACT
BACKGROUND: The high prevalence of hepatitis A delivered a blow to public health decades ago. The World Health Organization (WHO) set a goal to eliminate viral hepatitis including hepatitis A by 2030. In 2008, hepatitis A vaccines were integrated into the Expanded Program on Immunization (EPI) in China to alleviate the burden of hepatitis A, although the effectiveness of the EPI has not been well investigated. OBJECTIVE: We aimed to evaluate the intervention effect at both provincial and national levels on the incidence of hepatitis A in the Chinese mainland from 2005 to 2019. METHODS: Based on the monthly reported number of hepatitis A cases from 2005 to 2019 in each provincial-level administrative division, we adopted generalized additive models with an interrupted time-series design to estimate province-specific effects of the EPI on the incidence of hepatitis A among the target population (children aged 2-9 years) from 2005 to 2019. We then pooled province-specific effect estimates using random-effects meta-analyses. We also assessed the effect among the nontarget population and the whole population. RESULTS: A total of 98,275 hepatitis A cases among children aged 2-9 years were reported in the Chinese mainland from 2005 to 2019, with an average annual incidence of 5.33 cases per 100,000 persons. Nationally, the EPI decreased the hepatitis A incidence by 80.77% (excess risk [ER] -80.77%, 95% CI -85.86% to -72.92%) during the study period, guarding an annual average of 28.52 (95% empirical CI [eCI] 27.37-29.00) cases per 100,000 persons among the target children against hepatitis A. Western China saw a more significant effect of the EPI on the decrease in the incidence of hepatitis A among the target children. A greater number of target children were protected from onset in Northwest and Southwest China, with an excess incidence rate of -129.72 (95% eCI -135.67 to -117.86) and -66.61 (95% eCI -67.63 to -64.22) cases per 100,000 persons on average, respectively. Intervention effects among nontarget (ER -32.88%, 95% CI -39.76% to -25.21%) and whole populations (ER -31.97%, 95% CI -39.61% to -23.37%) were relatively small. CONCLUSIONS: The EPI has presented a lasting positive effect on the containment of hepatitis A in the target population in China. The EPI's effect on the target children also provided a degree of indirect protection for unvaccinated individuals. The continuous surveillance of hepatitis A and the maintenance of mass vaccination should shore up the accomplishment in the decline of hepatitis A incidence to ultimately achieve the goal set by the WHO.
Subject(s)
Hepatitis A Vaccines , Hepatitis A , Child , Humans , Hepatitis A Vaccines/therapeutic use , Hepatitis A/epidemiology , Hepatitis A/prevention & control , Immunization Programs , China/epidemiology , ImmunizationABSTRACT
BACKGROUND: Quantitative evidence on the impact of meteorological factors on influenza transmissibility across different virus types/subtypes is scarce, and no previous studies have reported the effect of hourly temperature variability (HTV) on influenza transmissibility. Herein, we explored the associations between meteorological factors and influenza transmissibility according to the influenza type and subtype in Guangzhou, a subtropical city in China. METHODS: We collected influenza surveillance and meteorological data of Guangzhou between October 2010 and December 2019. Influenza transmissibility was measured using the instantaneous effective reproductive number (Rt). A gamma regression with a log link combined with a distributed lag non-linear model was used to assess the associations of daily meteorological factors with Rt by influenza types/subtypes. RESULTS: The exposure-response relationship between ambient temperature and Rt was non-linear, with elevated transmissibility at low and high temperatures. Influenza transmissibility increased as HTV increased when HTV < around 4.5 °C. A non-linear association was observed between absolute humidity and Rt, with increased transmissibility at low absolute humidity and at around 19 g/m3. Relative humidity had a U-shaped association with influenza transmissibility. The associations between meteorological factors and influenza transmissibility varied according to the influenza type and subtype: elevated transmissibility was observed at high ambient temperatures for influenza A(H3N2), but not for influenza A(H1N1)pdm09; transmissibility of influenza A(H1N1)pdm09 increased as HTV increased when HTV < around 4.5 °C, but the transmissibility decreased with HTV when HTV < 2.5 °C and 3.0 °C for influenza A(H3N2) and B, respectively; positive association of Rt with absolute humidity was witnessed for influenza A(H3N2) even when absolute humidity was larger than 19 g/m3, which was different from that for influenza A(H1N1)pdm09 and influenza B. CONCLUSIONS: Temperature variability has an impact on influenza transmissibility. Ambient temperature, temperature variability, and humidity influence the transmissibility of different influenza types/subtypes discrepantly. Our findings have important implications for improving preparedness for influenza epidemics, especially under climate change conditions.
Subject(s)
Influenza A Virus, H1N1 Subtype , Influenza, Human , Humans , Influenza, Human/epidemiology , Influenza A Virus, H3N2 Subtype , Meteorological Concepts , Temperature , Humidity , China/epidemiologyABSTRACT
Haze weather, characterized by low visibility due to severe air pollution, has aroused great public concern. However, haze definitions are inconclusive, and multicentre studies on the health impacts of haze are scarce. We collected data on the daily number of deaths and environmental factors in 190 Chinese cities from 2014 to 2020. The city-specific association was estimated using quasi-Poisson regression and then pooled using meta-analysis. We found a negative association between daily visibility and non-accidental deaths, and mortality risk sharply increased when visibility was < 10 km. Haze weather, defined as a daily average visibility of < 10 km without a limit for humidity, produced the best model fitness and greatest effect on mortality. A haze day was associated with an increase of 2.53% (95% confidence interval [CI]:1.96, 3.10), 2.84 (95% CI: 2.13, 3.56), and 2.99% (95% CI: 1.94, 4.04) in all non-accident, cardiovascular and respiratory mortality, respectively. Haze had the greatest effect on lung cancer mortality. The haze-associated risk of mortality increased with age. Severe haze (visibility <2 km) and damp haze (haze with relative humidity >90%) had greater health impacts. Our findings can help in the development of early warning systems and effective public health interventions for haze.
Subject(s)
Air Pollution , Mortality , Weather , Humans , Air Pollution/adverse effects , China/epidemiology , Cities/epidemiologyABSTRACT
Objectives: Neonatologists and obstetricians are crucial decision-makers regarding the resuscitation of extremely preterm infants (EPIs). However, there is a scarcity of research regarding the differing perspectives on EPI resuscitation between these medical professionals. We aim to determine the differences and influential factors of their attitudes towards EPIs resuscitation in China. Methods: This cross-sectional study was conducted in public hospitals of 31 provinces in Chinese mainland from June to July 2021. Influential factors of binary variables and those of ordinal variables were analyzed by modified Poisson regression models and multinomial logistic regression models due to the invalid parallel line assumption of ordinal logistic regression models. Results: A total of 832 neonatologists and 1,478 obstetricians who were deputy chief physicians or chief physicians participated. Compared with obstetricians, neonatologists delivered a larger proportion of infants of <28-week gestational age (87.74% vs. 84.91%) and were inclined to think it inappropriate to use 28 weeks as the cutoff of gestational age for providing full care to premature infants [63.34% vs. 31.60%, adjusted prevalence ratio = 1.61 (95% CI: 1.46-1.77)], and to suggest smaller cutoffs of gestational age and birth weight for providing EPIs resuscitation. Notably, 46.49% of the neonatologists and 19.01% of the obstetricians believed infants ≤24 weeks' gestation should receive resuscitation. Conclusions: In China, notable disparities exist in attitudes of neonatologists and obstetricians towards resuscitating EPIs. Strengthening collaboration between these two groups and revising the pertinent guidelines as soon as possible would be instrumental in elevating the resuscitation rate of EPIs.
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Purpose: Obstructive sleep apnea (OSA) is a disease with high morbidity and is associated with adverse health outcomes. Screening potential severe OSA patients will improve the quality of patient management and prognosis, while the accuracy and feasibility of existing screening tools are not so satisfactory. The purpose of this study is to develop and validate a well-feasible clinical predictive model for screening potential severe OSA patients. Patients and Methods: We performed a retrospective cohort study including 1920 adults with overnight polysomnography among which 979 cases were diagnosed with severe OSA. Based on demography, symptoms, and hematological data, a multivariate logistic regression model was constructed and cross-validated and then a nomogram was developed to identify severe OSA. Moreover, we compared the performance of our model with the most commonly used screening tool, Stop-Bang Questionnaire (SBQ), among patients who completed the questionnaires. Results: Severe OSA was associated with male, BMI≥ 28 kg/m2, high blood pressure, choke, sleepiness, apnea, white blood cell count ≥9.5×109/L, hemoglobin ≥175g/L, triglycerides ≥1.7 mmol/L. The AUC of the final model was 0.76 (95% CI: 0.74-0.78), with sensitivity and specificity under the optimal threshold selected by maximizing Youden Index of 73% and 66%. Among patients having the information of SBQ, the AUC of our model was statistically significantly greater than that of SBQ (0.78 vs 0.66, P = 0.002). Conclusion: Based on common clinical examination of admission, we develop a novel model and a nomogram for identifying severe OSA from inpatient with suspected OSA, which provides physicians with a visual and easy-to-use tool for screening severe OSA.
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Importance: High-risk human papillomavirus (hrHPV) is recognized as an etiologic agent for cervical cancer, and hrHPV DNA testing is recommended as the preferred method of cervical cancer screening in recent World Health Organization guidelines. Cervical cancer prediction models may be useful for screening and monitoring, particularly in low-resource settings with unavailable cytological and colposcopic examination results, but previous studies did not include women infected with hrHPV. Objectives: To develop and validate a cervical cancer prediction model that includes women positive for hrHPV infection and examine whether the inclusion of HPV genotypes improves the cervical cancer prediction ability. Design, Setting, and Participants: This diagnostic study included diagnostic data from 314â¯587 women collected from 136 primary care centers in China between January 15, 2017, and February 28, 2018. The data set was separated geographically into data from 100 primary care centers in 6 districts for model development (training data set) and 36 centers in 3 districts for model validation. A total of 24â¯391 women identified with positive hrHPV test results in the cervical cancer screening program were included in the study. Data were analyzed from January 1, 2022, to July 14, 2022. Main Outcomes and Measures: Cervical intraepithelial neoplasia grade 3 or worse (CIN3+) was the primary outcome, and cervical intraepithelial neoplasia grade 2 or worse (CIN2+) was the secondary outcome. The ability of the prediction models to discriminate CIN3+ and CIN2+ was evaluated using the area under the receiver operating characteristic curve (AUROC), sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio. The calibration and clinical utility of the models were assessed using calibration plots and decision curves, respectively. Results: After excluding women without screening outcomes, the study included 21â¯720 women (median [IQR] age, 50 [44-55] years). Of 14â¯553 women in the training data set, 349 (2.4%) received a diagnosis of CIN3+ and 673 (4.6%) of CIN2+. Of 7167 women in the validation set, 167 (2.3%) received a diagnosis of CIN3+ and 228 (3.2%) of CIN2+. Including HPV genotype in the model improved the AUROC by 35.9% for CIN3+ and 41.7% for CIN2+. With HPV genotype, epidemiological factors, and pelvic examination as predictors, the stacking model had an AUROC of 0.87 (95% CI, 0.84-0.90) for predicting CIN3+. The sensitivity was 80.1%, specificity was 83.4%, positive likelihood ratio was 4.83, and negative likelihood ratio was 0.24. The model for predicting CIN2+ had an AUROC of 0.85 (95% CI, 0.82-0.88), with a sensitivity of 80.4%, specificity of 81.0%, positive likelihood ratio of 4.23, and negative likelihood ratio of 0.24. The decision curve analysis indicated that the stacking model provided a superior standardized net benefit when the threshold probability for clinical decision was lower than 23% for CIN3+ and lower than 17% for CIN2+. Conclusions and Relevance: This diagnostic study found that inclusion of HPV genotypes markedly improved the ability of a stacking model to predict cervical cancer among women who tested positive for hrHPV infection. This prediction model may be an important tool for screening and monitoring cervical cancer, particularly in low-resource settings.
Subject(s)
Papillomavirus Infections , Uterine Cervical Dysplasia , Uterine Cervical Neoplasms , Female , Humans , Middle Aged , Human Papillomavirus Viruses , Papillomavirus Infections/complications , Early Detection of Cancer/methods , GenotypeABSTRACT
Some studies have investigated the effects of PM2.5 on cardiovascular diseases based on the population-average exposure data from several monitoring stations. No one has explored the short-term effect of PM2.5 on cardiovascular hospitalizations using individual-level exposure data. We assessed the short-term effects of individual exposure to PM2.5 on hospitalizations for myocardial infarction (MI) and stroke in Guangzhou, China, during 2014-2019. The population-based data on cardio-cerebrovascular events were provided by Guangzhou Center for Disease Control and Prevention. Average annual percent changes (AAPCs) were used to describe trends in the hospitalization rates of MI and stroke. The conditional logistic regression model with a time-stratified case-crossover design was applied to estimate the effects of satellite-retrieved PM2.5 with 1-km resolution as individual-level exposure. Furthermore, we performed stratified analyses by demographic characteristics and season. There were 28,346 cases of MI, 188,611, and 36,850 cases of ischemic stroke (IS) and hemorrhagic stroke (HS), respectively, with an annual average hospitalization rate of 37.2, 247, and 48.4 per 100,000 people. Over the six-year study period, significant increasing trends in the hospitalization rates were observed with AAPCs of 12.3% (95% confidence interval [CI]: 7.24%, 17.6%), 13.1% (95% CI: 9.54%, 16.7%), and 9.57% (95% CI: 6.27%, 13.0%) for MI, IS, and HS, respectively. A 10 µg/m3 increase in PM2.5 was associated with an increase of 1.15% (95% CI: 0.308%, 1.99%) in MI hospitalization and 1.29% (95% CI: 0.882%, 1.70%) in IS hospitalization. A PM2.5-associated reduction of 1.17% (95% CI: 0.298%, 2.03%) was found for HS hospitalization. The impact of PM2.5 was greater in males than in females for MI hospitalization, and greater effects were observed in the elderly (≥ 65 years) and in cold seasons for IS hospitalization. Our study added important evidence on the adverse effect of PM2.5 based on satellite-retrieved individual-level exposure data.
Subject(s)
Air Pollutants , Air Pollution , Myocardial Infarction , Stroke , Male , Female , Humans , Aged , Cross-Over Studies , Particulate Matter/analysis , Air Pollution/analysis , Hospitalization , Myocardial Infarction/epidemiology , Myocardial Infarction/chemically induced , China/epidemiology , Stroke/epidemiology , Hospitals , Environmental Exposure/analysis , Air Pollutants/analysisABSTRACT
BACKGROUND: The effect of urbanization on the morbidity of hepatitis A remains unclear. We aimed to estimate the association between various urbanization-related indices and hepatitis A morbidity in China. METHODS: Data on the annual morbidity of hepatitis A, urbanization-related measures (i.e., gross domestic product per capita, the number of hospitalization beds per 1000 persons, illiteracy rate, tap water coverage, motor vehicles per 100 persons, population density, and the proportion of arable land), and meteorological factors in 31 provincial-level administrative divisions of Chinese mainland during 2005-2018 were collected from the National Population and Health Science Data Sharing Platform, China Statistical Yearbooks, and the China Meteorological Data Sharing Service System, respectively. Generalized linear mixed models were applied to quantify the impacts of different urbanization-related indices on the morbidity of hepatitis A in China after adjusting for covariates. RESULTS: A total of 537,466 hepatitis A cases were reported in China during 2005-2018. The annual morbidity had a decline of 79.4% from 5.64 cases to 1.16 cases per 100,000 people. There were obvious spatial variations with higher morbidity in western China. Nationally, gross domestic product per capita and the number of hospitalization beds per 1000 persons increased from 14,040 to 64,644 CNY and from 2.45 to 6.03 during 2005-2018, respectively. The illiteracy rate decreased from 11.0 to 4.9%. Gross domestic product per capita [relative risk (RR) = 0.96, 95% confidence interval (CI): 0.92-0.99], and the number of hospitalization beds per 1000 persons (RR = 0.79, 95% CI: 0.75-0.83) were associated with the declined morbidity of hepatitis A. By contrast, the increased morbidity of hepatitis A was linked to the illiteracy rate (RR = 1.04, 95% CI: 1.02-1.06). Similar influential factors were detected for children and adults, with greater effects witnessed for children. CONCLUSIONS: People in the western region suffered the heaviest burden of hepatitis A in Chinese mainland. Nationally, there was a sharp decline in the morbidity of hepatitis A. The urbanization process was associated with the reduction of hepatitis A morbidity in China during 2005-2018.
Subject(s)
Hepatitis A , Urbanization , Adult , Child , Humans , Hepatitis A/epidemiology , China/epidemiology , Morbidity , Gross Domestic ProductABSTRACT
BACKGROUND: Accurate estimation of the influenza death burden is of great significance for influenza prevention and control. However, few studies have considered the short-term harvesting effects of influenza on mortality when estimating influenza-associated excess deaths by cause of death, age, sex, and subtype/lineage. OBJECTIVE: This study aimed to estimate the cause-, age-, and sex-specific excess mortality associated with influenza and its subtypes and lineages in Guangzhou from 2015 to 2018. METHODS: Distributed-lag nonlinear models were fitted to estimate the excess mortality related to influenza subtypes or lineages for different causes of death, age groups, and sex based on daily time-series data for mortality, influenza, and meteorological factors. RESULTS: A total of 199,777 death certificates were included in the study. The average annual influenza-associated excess mortality rate (EMR) was 25.06 (95% empirical CI [eCI] 19.85-30.16) per 100,000 persons; 7142 of 8791 (81.2%) deaths were due to respiratory or cardiovascular mortality (EMR 20.36, 95% eCI 16.75-23.74). Excess respiratory and cardiovascular deaths in people aged 60 to 79 years and those aged ≥80 years accounted for 32.9% (2346/7142) and 63.7% (4549/7142) of deaths, respectively. The male to female ratio (MFR) of excess death from respiratory diseases was 1.34 (95% CI 1.17-1.54), while the MFR for excess death from cardiovascular disease was 0.72 (95% CI 0.63-0.82). The average annual excess respiratory and cardiovascular mortality rates attributed to influenza A (H3N2), B/Yamagata, B/Victoria, and A (H1N1) were 8.47 (95% eCI 6.60-10.30), 5.81 (95% eCI 3.35-8.25), 3.68 (95% eCI 0.81-6.49), and 2.83 (95% eCI -1.26 to 6.71), respectively. Among these influenza subtypes/lineages, A (H3N2) had the highest excess respiratory and cardiovascular mortality rates for people aged 60 to 79 years (20.22, 95% eCI 14.56-25.63) and ≥80 years (180.15, 95% eCI 130.75-227.38), while younger people were more affected by A (H1N1), with an EMR of 1.29 (95% eCI 0.07-2.32). The mortality displacement of influenza A (H1N1), A (H3N2), and B/Yamagata was 2 to 5 days, but 5 to 13 days for B/Victoria. CONCLUSIONS: Influenza was associated with substantial mortality in Guangzhou, occurring predominantly in the elderly, even after considering mortality displacement. The mortality burden of influenza B, particularly B/Yamagata, cannot be ignored. Contrasting sex differences were found in influenza-associated excess mortality from respiratory diseases and from cardiovascular diseases; the underlying mechanisms need to be investigated in future studies. Our findings can help us better understand the magnitude and time-course of the effect of influenza on mortality and inform targeted interventions for mitigating the influenza mortality burden, such as immunizations with quadrivalent vaccines (especially for older people), behavioral campaigns, and treatment strategies.
Subject(s)
Cardiovascular Diseases , Influenza A Virus, H1N1 Subtype , Influenza, Human , Aged , Humans , Male , Female , Influenza A Virus, H3N2 Subtype , Nonlinear Dynamics , SeasonsABSTRACT
BACKGROUND: Evidence concerning effects of air pollution on influenza-like illness (ILI) from multi-center is limited and little is known about how regional factors might modify this relationship. METHODS: In this ecological study, ILI cases defined as outpatients with temperature ≥38 °C, accompanied by cough or sore throat, were collected from National Influenza Surveillance Network in China. We adopted generalized additive model with quasi-Poisson to estimate province-specific association between air pollution and ILI in 30 Chinese provinces during 2015-2019, after adjusting for time trend and meteorological factors. We then pooled province-specific association by using random-effect meta-analysis. Potential effect modifications of season and regional characteristics were explored. FINDINGS: A total of 26, 004, 853 ILI cases and 777, 223, 877 hospital outpatients were collected. In general, effects of air pollutants were acute. An inter-quartile range increase of PM2.5, SO2, PM10, NO2 and CO at lag0, and O3 at lag0-2 was associated with 3.08% (95% CI: 1.91%, 4.27%), 3.00% (1.86%, 4.16%), 6.46% (4.71%, 8.25%), 7.21% (5.73%, 8.71%), 4.37% (3.05%, 5.70%), and -9.26% (-11.32%, -7.14%) change of ILI at national level, respectively. Associations between air pollutants and ILI varied by season and regions, with higher effect estimates in cold season, eastern and central regions and provinces with more humid condition and larger population. INTERPRETATION: This study indicated that most air pollutants increased the risk of ILI in China. Our findings might provide implications for the development of policies to protect public health from air pollution and influenza. FUNDING: National Natural Science Foundation of China and Chongqing Health Commission Program.
Subject(s)
Air Pollutants , Air Pollution , Influenza, Human , Humans , Influenza, Human/epidemiology , Influenza, Human/etiology , Air Pollution/adverse effects , Air Pollutants/adverse effects , Air Pollutants/analysis , China/epidemiology , Seasons , Particulate Matter/adverse effects , Particulate Matter/analysisABSTRACT
BACKGROUND: High-risk human papillomavirus (hrHPV) infection is a necessary cause of almost all cervical cancers. Relative to hrHPV 16/18 infection, non-16/18 hrHPV infection is of less concern. However, the increasing prevalence of non-16/18 hrHPV infections has become an important public health issue. The early identification and treatment of cervical cytological abnormalities in women infected with non-16/18 hrHPV reduces the incidence of cervical cancer. To date, no study has examined the risk factors for cytological abnormalities in this high-risk population. OBJECTIVE: This population-based, cross-sectional study aimed to identify the risk factors for cervical cytological abnormalities in women infected with non-16/18 hrHPV. METHODS: A total of 314,587 women from the general population were recruited for cervical cancer screening at 136 primary care hospitals in Xiangyang, China. Of these, 311,604 women underwent HPV genotyping, and 17,523 non-16/18 hrHPV-positive women were referred for cytological screening according to the screening program. A logistic regression model was used to assess the risk factors for cytological abnormalities among these non-16/18 hrHPV-positive women. A separate analysis was performed to determine the factors influencing high-grade cytological abnormalities. RESULTS: The non-16/18 hrHPV infection rate was 5.88% (18,323/311,604), which was 3-fold higher than that of hrHPV 16/18 (6068/311,604, 1.95%). Among the non-16/18 hrHPV-positive women who underwent ThinPrep cytologic test, the overall prevalence rates of cervical cytological abnormalities and high-grade cytological abnormalities were 13.46% (2359/17,523) and 1.18% (206/17,523), respectively. Multivariate logistic regression analysis revealed that women with middle or high school educational attainment were at a higher risk of having cytological abnormalities than those who received primary education (odds ratio [OR] 1.31, 95% CI 1.17-1.45; P<.001, and OR 1.32, 95% CI 1.14-1.53; P<.001, respectively). Living in rural areas (OR 2.58, 95% CI 2.29-2.90; P<.001), gravidity ≥3 (OR 2.77, 95% CI 1.19-6.45; P=.02), cervix abnormalities detected in pelvic examination (OR 1.22, 95% CI 1.11-1.34; P<.001), and having a cervical cancer screening 3 years ago (OR 0.79, 95% CI 0.62-1.00; P=.048) were associated with cytological abnormalities. The risk factors for high-grade cytological abnormalities included middle school education (OR 1.45, 95% CI 1.07-1.98; P=.02), living in rural regions (OR 1.52, 95% CI 1.10-2.10; P=.01), and cervix abnormality (OR 1.72, 95% CI 1.30-2.26; P<.001). CONCLUSIONS: The dominant epidemic of non-16/18 hrHPV infection is revealed in Chinese women. Multiple risk factors for cervical cytological abnormalities have been identified in women infected with non-16/18 hrHPV. These findings can provide important information for clinically actionable decisions for the screening, early diagnosis, intervention, and prevention of cervical cancer in non-16/18 hrHPV-positive women.
Subject(s)
Uterine Cervical Neoplasms , Humans , Female , Cross-Sectional Studies , Uterine Cervical Neoplasms/epidemiology , Human Papillomavirus Viruses , Early Detection of Cancer , Risk FactorsABSTRACT
BACKGROUND: The global spread of infectious diseases is currently a prominent threat to public health, with the accelerating pace of globalization and frequent international personnel intercourse. The present study examined the epidemiological characteristics of overseas imported cases of acute infectious diseases in Guangzhou, China. METHODS: We retrospectively investigated the distribution of diseases, demographic characteristics, and temporal and spatial variations of imported cases of acute infectious diseases in Guangzhou based on the surveillance data of notifiable infectious diseases from 2005 to 2019, provided by Guangzhou center for Disease Control and Prevention. The Cochran-Armitage trend test was applied to examine the trend in the number of imported cases over time. RESULTS: A total of 1,025 overseas imported cases of acute infectious diseases were identified during the study period. The top three diseases were dengue (67.12%), malaria (12.39%), and influenza A (H1N1) pdm09 (4.10%). Imported cases were predominantly males, with a sex ratio of 2.6: 1 and 75.22% of the cases were those aged 20-49 years. Businessmen, workers, students and unemployed persons accounted for a large proportion of the cases (68.49%) and many of the cases came from Southeast Asia (59.02%). The number of imported cases of acute infectious diseases increased during the study period and hit 318 in 2019. A clear seasonal pattern was observed in the number of imported cases with a peak period between June and November. Imported cases were reported in all of the 11 districts in Guangzhou and the central districts were more seriously affected compared with other districts. CONCLUSIONS: The burden of dengue imported from overseas was substantial and increasing in Guangzhou, China, with the peak period from June to November. Dengue was the most common imported disease. Most imported cases were males aged 20-49 years and businessmen. Further efforts, such as strengthening surveillance of imported cases, paying close attention to the epidemics in hotspots, and improving the ability to detect the imported cases from overseas, are warranted to control infectious diseases especially in the center of the city with a higher population density highly affected by imported cases.
Subject(s)
Communicable Diseases , Influenza A Virus, H1N1 Subtype , Humans , Retrospective Studies , China/epidemiology , Sex Ratio , Communicable Diseases/epidemiologyABSTRACT
The traditional campaign-style enforcement in environmental governance has been debated whether its rebound effect is likely to eat away the short-term environmental benefits and subsequently bring about severer pollution. There are methodological challenges in assessing the effect of temporary environmental intervention. By applying the generalized synthetic control method (GSCM), we quantified and characterized the effectiveness of environmental regulations implemented for the G20 Hangzhou Summit held on 4-5 September, 2016. The summit was successful in reducing Air Quality Composite Index by 17.40% (95% CI: 9.53%, 24.60%), 13.30% (95% CI: 4.23%, 21.50%), and 10.09% (95% CI: 2.01%, 17.51%) in the core, strictly-regulated and regulated areas respectively, comparing with the index expected under a "No-G20" scenario during the preparatory period and the summit period (July-September 2016), and the reduction of the levels in specific pollutants (PM10, PM2.5, NO2, and CO) was also observed. Besides, the environmental benefits lasted for at least 3 months after the summit. This study demonstrates that the pollution control measures during the G20 Hangzhou Summit improved air quality immediately and continuously, and the GSCM provides a useful tool for evaluating the intervention effects of environmental regulations.