Characterization and determinant factors of critical illness and in-hospital mortality of COVID-19 patients: A retrospective cohort of 1,792 patients in Kenya.

Limited data is available on the coronavirus disease 2019 (COVID-19), critical illness rate, and in-hospital mortality in the African setting. This study investigates determinants of critical illness and in-hospital mortality among COVID-19 patients in Kenya. We conducted a retrospective cohort study at Kenyatta National Hospital (KNH) in Kenya. Multivariate logistic regression and Cox proportional hazard regression were employed to determine predictor factors for intensive care unit (ICU) admission and in-hospital mortality, respectively. In addition, the Kaplan-Meier model was used to compare the survival times using log-rank tests. As a result, 346 (19.3%) COVID-19 patients were admitted to ICU, and 271 (15.1%) died. The majority of those admitted to the hospital were male, 1,137 (63.4%) and asymptomatic, 1,357 (75.7%). The most prevalent clinical features were shortness of breath, fever, and dry cough. In addition, older age, male, health status, patient on oxygen (O2), oxygen saturation levels (SPO2), headache, dry cough, comorbidities, obesity, cardiovascular diseases (CVDs), diabetes, chronic lung disease (CLD), and malignancy/cancer can predicate the risk of ICU admission, with an area under the receiver operating characteristic curve (AUC-ROC) of 0.90 (95% confidence interval [CI]: 0.88-0.92). Survival analysis indicated 271 (15.1%) patients died and identified older age, male, headache, shortness of breath, health status, patient on oxygen, SPO2, headache, comorbidity, CVDs, diabetes, CLD, malignancy/cancer, and smoking as risk factors for mortality (AUC-ROC: 0.90, 95% CI: 0.89-0.91). This is the first attempt to explore predictors for ICU admission and hospital mortality among COVID-19 patients in Kenya.

Spatial-temporal analysis of cause-specific cardiovascular hospital admission in Beijing, China.

BACKGROUND: The main aim of this study was to explore the spatial-temporal patterns of cause-specific CVD admission in Beijing using retrospective SaTScan analysis. METHODS: A spatial-temporal analysis was conducted at the district level based on the rates of total and cause-specific CVD admissions, including coronary heart disease (CHD), atrial fibrillation (AF), and heart failure (HF) from 2013 to 2017. We used joint point regression, Global Moran's I and Anselin's local Moran's I, together with Kulldorff's scan statistic. RESULTS: Hospital admission trend decreased during the study period. Admission rates followed a spatially clustered pattern with differences occurring between cause-specific CVDs. Clusters were mainly identified in ecological preservation areas, with a more likely cluster found in Daxing, Fangshan, Xicheng district for total CVD, CHD, AF and HF, respectively. CONCLUSIONS: Hospital admission of cause-specific CVD showed spatial clustered pattern, especially in ecological preservation areas.

Acute effects of fine particulate matter (PM2.5) on hospital admissions for cardiovascular disease in Beijing, China: a time-series study.

BACKGROUND: Air pollution and cardiovascular disease are increasing problems in China. However, the short-term association between fine particulate matter (PM2.5) and cardiovascular disease (CVD) is not well documented. The purpose of this study is to estimate the short-term effects of PM2.5 on CVD admissions in Beijing, China. METHODS: In total, 460,938 electronic hospitalization summary reports for CVD between 2013 and 2017 were obtained. A generalized additive model using a quasi-Poisson distribution was used to investigate the association between exposure to PM2.5 and hospitalizations for total and cause-specific CVD, including coronary heart disease (CHD), atrial fibrillation (AF), and heart failure (HF) after controlling for the season, the day of the week, public holidays, and weather conditions. A stratified analysis was also conducted for age (18-64 and ≥ 65 years), sex and season. RESULTS: For every 10 µg/m3 increase in the PM2.5 concentration from the previous day to the current (lag 0-1) there was a significant increase in total CVD admissions (0.30, 95% CI: 0.20, 0.39%), with a strong association for older adults (aged ≥65 years), CHD (0.34, 95% CI: 0.22 to 0.45%) and AF (0.29, 95% CI, 0.03 to 0.55%). However, the observed increased risk was not statistically significant for HF hospitalizations. The associations in the single-pollutant models were robust to the inclusion of other pollutants in a two-pollutant model. No differences were found after stratification by sex and season. CONCLUSIONS: Exposure to PM2.5 increased the risk of hospitalizations from CVD, especially for CHD, and appeared to have more influence in the elderly. Precautions and protective measures and efforts to reduce exposure to PM2.5 should be strengthened, especially for the elderly.

The spatio-temporal analysis of the incidence of tuberculosis and the associated factors in mainland China, 2009-2015.

BACKGROUND: Tuberculosis is still one of the most infectious diseases in China. This study aimed to explore the spatio-temporal distribution of TB and the associated factors in mainland China from 2009 to 2015. METHODS: A Bayesian spatio-temporal model was utilized to analyse the correlation of socio-economic, healthcare, demographic and meteorological factors with the population level number of TB. RESULTS: The Bayesian spatio-temporal analysis showed that for the population level number of TB, the estimated parameters of the ratio of males to females, the number of beds in medical institutions, the population density, the proportion of the population that is rural, the amount of precipitation, the largest wind speed and the sunshine duration were 0.556, 0.197, 0.199, 29.03,0.1958, 0.0854 and 0.2117, respectively, demonstrating positive associations. However, health personnel, per capita annual gross domestic product, minimum temperature and humidity indicated negative associations, and the corresponding parameters were -0.050, -0.095, -0.0022 and -0.0070, respectively. CONCLUSIONS: Socio-economic, number of health personnel, demographic and meteorological factors could affect the case notification number of TB to different degrees and in different directions.

Spatial distribution of tuberculosis and its association with meteorological factors in mainland China.

BACKGROUND: The incidence of tuberculosis (TB) remains high worldwide. Current strategies will not eradicate TB by 2035; instead, by 2182 is more likely. Therefore, it is urgent that new risk factors be identified. METHODS: An ecological study was conducted in 340 prefectures in China from 2005 to 2015. The spatial distribution of TB incidence was shown by clustering and hotspot analysis. The relationship between the distribution patterns and six meteorological factors was evaluated by the geographically weighted regression (GWR) model. RESULTS: During the 11 years of the study period, TB incidence was persistently low in the east and high in the west. Local coefficients from the GWR model showed a positive correlation between TB incidence and yearly average rainfall (AR) but a negative correlation with other meteorological factors. Average relative humidity (ARH) was negatively correlated with the incidence of TB in all prefectures (p < 0.05). CONCLUSION: Meteorological factors may play an important role in the prevention and control of TB.

Spatial-temporal analysis of tuberculosis in the geriatric population of China: An analysis based on the Bayesian conditional autoregressive model.

BACKGROUND: Tuberculosis (TB) remains a clinical and epidemiological challenge in the geriatric population. We aim to examine the spatial-temporal pattern of TB in the geriatric population and its relationship with meteorological & sociodemographic factors using the Bayesian conditional autoregressive (CAR) model. METHOD: An ecological design was used in the geriatric (age > = 65 years) population from 2005 to 2015. Spatial autocorrelation and hot spots were explored using geographical information system (GIS) statistics. The Bayesian CAR model was used for modeling TB to estimate the parameters using the WinBUGS software. Deviance information criteria (DIC) were used to select the best performing model. RESULTS: Spatially, TB was clustered in Central China and southeast of China. Temporally, an increasing trend and high peak of TB was detected during the spring. TB was significantly associated with air temperature at the posterior mean: -0.165 (95%CI: -0.235, -0.108), and it was negatively associated with average wind speed: -0.028 (95%CI: -0.043, -0.018) and positively associated with rainfall: 0.095 (95%CI: 0.045, 0.163). TB was significantly and positively associated with population density: 0.088(95%CI: 0.031, 0.129) and sex ratio (M: F): 0.162 (95%CI: 0.091, 0.284) and was negatively related with gross domestic product (GDP): -0.046(95%CI: -0.156, -0.037). Out of 31 provinces, 17 provinces had a higher risk for TB. CONCLUSION: TB shows a clear spatial and seasonal variation; it is geographically aggregated, and more men are affected than women. Areas with an underprivileged economy, high population density, high rainfall, low wind speed, and low temperature have a higher risk for TB.

Metabolically healthy obese phenotype and risk of cardiovascular disease: Results from the China Health and Retirement Longitudinal Study.

BACKGROUND: Epidemiologic evidence on metabolically healthy obese (MHO) phenotype and cardiovascular diseases (CVD) risk remains controversial. AIMS: We aim to examine the relationship between MHO and risk of CVD among the Chinese population. METHODS: The China Health and Retirement Longitudinal Study is a prospective cohort study of 7849 participants aged ≥45 years without CVD at baseline. Metabolic health status was assessed based on blood pressure, triglycerides, high-density lipoprotein cholesterol, glycated hemoglobin, fasting glucose, and C-reactive protein. A cutoff point of body mass index of 24.0 kg/m2 was used to define over-weight/obesity (≥24.0 kg/m2) or normal weight (<24.0 kg/m2). CVD was based on self-reported doctor's diagnosis of heart problems and stroke. Incidence rate ratio (IRR) with 95% confidence interval (CI) was deduced from modified Poisson regression. RESULTS: During a mean 3.6 years of follow-up, 880 incident CVD events were recorded. 789 (10.05%) were identified MHO among 3321 (42.3%) obese individuals. Compared with metabolically healthy normal weight individuals, the multivariable adjusted IRR of CVD was 1.33 (95%CI: 1.19-1.49) for MHO, 1.29 (95%CI: 1.22-1.38) for metabolically unhealthy normal weight, and 1.61 (95%CI: 1.51-1.75) for metabolically unhealthy obese in the full adjusted model. CONCLUSIONS: MHO individuals are associated with the increased risk of cardiovascular diseases among the Chinese population.

Effects of ambient carbon monoxide on daily hospitalizations for cardiovascular disease: a time-stratified case-crossover study of 460,938 cases in Beijing, China from 2013 to 2017.

BACKGROUND: Evidence focused on exposure to ambient carbon monoxide (CO) and the risk of hospitalizations for cardiovascular diseases (CVD) is lacking in developing countries. This study aimed to examine the effect of CO exposure on hospitalizations for CVD in Beijing, China. METHODS: A total of 460,938 hospitalizations for cardiovascular diseases were obtained from electronic hospitalization summary reports from 2013 to 2017. A time-stratified case-crossover design was conducted to investigate the association between CO exposure and hospitalizations for total and cause-specific CVD, including coronary heart disease (CHD), atrial fibrillation (AF), and heart failure (HF). Stratified analysis was also conducted by age group (18-64 years and ≥ 65 years) and sex. RESULTS: Linear exposure-response curves for the association between ambient CO exposure and hospitalizations for CVD was observed. Ambient CO was positively associated with hospitalizations for total CVD and CHD. However, the observed increased risk was not statistically significant for hospitalizations for AF and HF. The strongest effect of CO concentration was observed on the current- and previous-day of exposure (lag 0-1 day). For a 1 mg/m3 increase in a 2-day moving average CO concentration, an increase of 2.8% [95% confidence interval (CI): 2.2 to 3.3%] and 3.0% (95% CI: 2.4 to 3.6%) in daily hospital admissions for CVD and CHD were estimated, respectively. This association was robust after adjusting for other copollutants and did not vary by age group and sex. CONCLUSIONS: Ambient CO exposure increased the risk of hospitalizations for CVD, especially for CHD in Beijing. Further studies are warranted to explore the association between ambient CO and hospitalizations for AF and HF.

Spatial and temporal clustering analysis of tuberculosis in the mainland of China at the prefecture level, 2005-2015.

BACKGROUND: Tuberculosis (TB) is still one of the most serious infectious diseases in the mainland of China. So it was urgent for the formulation of more effective measures to prevent and control it. METHODS: The data of reported TB cases in 340 prefectures from the mainland of China were extracted from the China Information System for Disease Control and Prevention (CISDCP) during January 2005 to December 2015. The Kulldorff's retrospective space-time scan statistics was used to identify the temporal, spatial and spatio-temporal clusters of reported TB in the mainland of China by using the discrete Poisson probability model. Spatio-temporal clusters of sputum smear-positive (SS+) reported TB and sputum smear-negative (SS-) reported TB were also detected at the prefecture level. RESULTS: A total of 10 200 528 reported TB cases were collected from 2005 to 2015 in 340 prefectures, including 5 283 983 SS- TB cases and 4 631 734 SS + TB cases with specific sputum smear results, 284 811 cases without sputum smear test. Significantly TB clustering patterns in spatial, temporal and spatio-temporal were observed in this research. Results of the Kulldorff's scan found twelve significant space-time clusters of reported TB. The most likely spatio-temporal cluster (RR = 3.27, P <  0.001) was mainly located in Xinjiang Uygur Autonomous Region of western China, covering five prefectures and clustering in the time frame from September 2012 to November 2015. The spatio-temporal clustering results of SS+ TB and SS- TB also showed the most likely clusters distributed in the western China. However, the clustering time of SS+ TB was concentrated before 2010 while SS- TB was mainly concentrated after 2010. CONCLUSIONS: This study identified the time and region of TB, SS+ TB and SS- TB clustered easily in 340 prefectures in the mainland of China, which is helpful in prioritizing resource assignment in high-risk periods and high-risk areas, and to formulate powerful strategy to prevention and control TB.

Knowledge of direct obstetric causes of maternal mortality and associated factors among reproductive age women in Aneded woreda, Northwest Ethiopia; a cross-sectional study.

INTRODUCTION: in Ethiopia, 20,000 women die each year from complications related to pregnancy and childbirth with much more maternal morbidity occurring for each maternal death. Good knowledge of women related with direct causes of maternal mortality is important in reducing maternal morbidity and mortality. Therefore, the aim of this study was to assess knowledge of direct obstetric causes of maternal mortality and associated factors among reproductive age of women in Aneded woreda, Northwest Ethiopia. METHODS: A community-based cross-sectional study was conducted using multi-stage sampling followed by simple random sampling technique. The study was conducted in Aneded woreda, Northwest Ethiopia. A total of 844 reproductive age women were included in the study. Pre-tested semi-structured questionnaire was used to collect the data. Data was collected through face-to-face interviews by 12 data collectors. Data was cleaned, coded and entered into Epi-data, then exported and analyzed using SPSS software. Bivariate and multivariable logistic regression analysis were computed to identify factors related to knowledge of obstetric causes of maternal mortality. The crude and adjusted odds ratios together with their corresponding 95% confidence intervals (CI) were computed. A P-value less than 0.05 was used to declare statistical significance. RESULTS: This study found that almost half (49.6%) of respondents have good knowledge level towards obstetric causes of maternal mortality. Significant variables associated with knowledge towards obstetric causes of maternal mortality were; being government employee (AOR=3.6, 95% CI=1.4-8.9), respondents who had additional monthly income from family members (AOR=1.54, 95% CI=1.04-2.27), respondents who attended primary school and above (AOR=1.6, 95% CI=1.13-2.25), distance of health facility in which the time it took less than 20 minutes (AOR=2.25, 95% CI(1.24-4.09), 20-39minutes (AOR=3.06, 95% CI=1.66-5.64), 40-60 minutes (AOR=2.38, 95% CI=1.52-5.26), and previous history of prolonged labor (AOR=1.4, 95% CI=1.04 -2.03) were the significant variables. CONCLUSION: This study indicated that the reproductive age women in the study area had poor knowledge towards about obstetric causes of maternal mortality. Therefore, to improve maternal knowledge and thereby reduce maternal death, the identified significant factors should be addressed through maternal and child health services. Designing appropriate strategies including the provision of targeted information, education, and communication is important.