Space-Time Analysis to Identify Areas at Risk of Mortality from Cardiovascular Disease

The distribution of cardiovascular diseases in Tanzania: a spatio-temporal investigation

Cardiovascular Disease (CVD) is currently the major challenge to people's health and the world's top cause of death. In Tanzania, deaths due to CVD account for about 13% of the total deaths caused by the non-communicable diseases. This study examined the spatio-temporal clustering of CVDs from 2010 to 2019 in Tanzania for retrospective spatio-temporal analysis using the Bernoulli probability model on data sampled from four selected hospitals. Spatial scan statistics was performed to identify CVD clusters and the effect of covariates on the CVD incidences was examined using multiple logistic regression. It was found that there was a comparatively high risk of CVD during 2011-2015 followed by a decline during 2015-2019. The spatio-temporal analysis detected two high-risk disease clusters in the coastal and lake zones from 2012 to 2016 (p<0.001), with similar results produced by purely spatial analysis. The multiple logistic model showed that sex, age, blood pressure, body mass index (BMI), alcohol intake and smoking were significant predictors of CVD incidence.

Spatiotemporal distribution characteristics and influencing factors of the rate of cardiovascular hospitalization in Ganzhou city of China

Aims

The objective of this study was to analyze hospitalization rates for cardiovascular diseases (CVD) in Ganzhou City, Jiangxi Province of China from 2015 to 2020 and to uncover the spatiotemporal distribution characteristics and influencing factors, and thus to provide reference for the prevention and control of CVD and public health resources planning.

Methods

The hospitalization data for CVDs from 2016 to 2020 was obtained from the First Affiliated Hospital of Gannan Medical University, and ArcGIS 10.8, SaTScan 9.5, and Matlab 20.0 were used to analyze the spatial autocorrelation, spatiotemporal scan statistics, and potential affecting factors of the hospitalization rates.

Results

The hospitalization rate for CVDs in Ganzhou City showed a slightly increasing trend from 2016 to 2020, with higher rates in winter and summer than that in spring and autumn, and the individuals aged 61 and above constitute a higher proportion compared to other age groups. Additionally, there was a positive correlation between hospitalization rates for CVDs and the counties and districts in Ganzhou City, with high-high aggregation areas mainly distributed in Nankang District, the western urban area of Ganzhou City. The spatial scan analysis identified three different types of significant aggregation areas: high-risk, low-risk, and middle-risk areas. The high-risk area was mainly centered around Zhanggong District or Shangyu County in the central and western regions, with a disease hospitalization rate 2-3 times higher than the rest areas. The study also found that environmental meteorological factors such as the annual average concentration of NO2, O3, average annual temperature, and annual maximum temperature diurnal range had a significant positive effect on hospitalization rates for CVDs in Ganzhou City, with O3 concentration and average annual temperature having significant positive indirect spatial spillover effects.

Conclusion

Winter and summer are the seasons with high hospitalization rate of cardiovascular diseases. County residents aged 61 and above are the higher-risk population that needs to pay more attention on for prevention and control of CVD in Ganzhou City, which exhibits significant spatiotemporal clustering. The urban areas of Zhanggong and Nankang in Ganzhou City are the key areas for prevention and control of CVD. The hospitalization rate of CVD in Ganzhou City is influenced by the aforementioned four environmental meteorological factors, with the annual maximum temperature diurnal range showing the most significant positive direct effect.

Spatio-temporal analysis of leprosy risks in a municipality in the state of Mato Grosso-Brazilian Amazon: results from the leprosy post-exposure prophylaxis program in Brazil

BACKGROUND

Leprosy post-exposure prophylaxis (LPEP) with single dose rifampicin (SDR) can be integrated into different leprosy control program set-ups once contact tracing has been established. We analyzed the spatio-temporal changes in the distribution of index cases (IC) and co-prevalent cases among contacts of leprosy patients (CP) over the course of the LPEP program in one of the four study areas in Brazil, namely the municipality of Alta Floresta, state of Mato Grosso, in the Brazilian Amazon basin.

METHODS

Leprosy cases were mapped, and socioeconomic indicators were evaluated to explain the leprosy distribution of all leprosy cases diagnosed in the period 2016-2018. Data were obtained on new leprosy cases [Notifiable diseases information system (Sinan)], contacts traced by the LPEP program, and socioeconomic variables [Brazilian Institute of Geography and Statistics (IBGE)]. Kernel, SCAN, factor analysis and spatial regression were applied to analyze changes.

RESULTS

Overall, the new case detection rate (NCDR) was 20/10 000 inhabitants or 304 new cases, of which 55 were CP cases among the 2076 examined contacts. Changes over time were observed in the geographic distribution of cases. The highest concentration of cases was observed in the northeast of the study area, including one significant cluster (Relative risk = 2.24; population 27 427, P-value < 0.001) in an area characterized by different indicators associated with poverty as identified through spatial regression (Coefficient 3.34, P-value = 0.01).

CONCLUSIONS

The disease distribution was partly explained by poverty indicators. LPEP influences the spatial dynamic of the disease and results highlighted the relevance of systematic contact surveillance for leprosy elimination.

Atmospheric Pollution Exposure Increases Disease Activity of Systemic Lupus Erythematosus

Previous studies have shown that high levels of air pollutants may increase activity of systemic lupus erythematosus (SLE). The aim of this study is to analyze the association between pollutants originating from the Brazilian Legal Amazon and SLE activity. This is a retrospective longitudinal cohort study with patients with SLE in the General Hospital in Cuiabá, Brazil. The association with SLE activity was measured using the SLE disease activity index (SLEDAI) and data on air quality-PM2.5 and CO, published on the websites of the State Department of Environment and the Center for Weather Forecasting and Climate Studies. To assess the effect of daily concentrations of pollutants on SLEDAI scores, the generalized estimation equation (GEE) model was used. A total of 32 female patients were assessed, in 96 doctor's appointments. The average SLEDAI score was 6 points (±5.05). GEE showed an association of disease activity with both higher rates of wildfires (p = 0.021) and average CO rate (p = 0.013), but there was no statistical association between particulate levels and SLE activity. The results suggest that variations in air pollution are associated with the activity of autoimmune rheumatic diseases.

A Bayesian spatiotemporal statistical analysis of out-of-hospital cardiac arrests

We propose a Bayesian spatiotemporal statistical model for predicting out-of-hospital cardiac arrests (OHCAs). Risk maps for Ticino, adjusted for demographic covariates, are built for explaining and forecasting the spatial distribution of OHCAs and their temporal dynamics. The occurrence intensity of the OHCA event in each area of interest, and the cardiac risk-based clustering of municipalities are efficiently estimated, through a statistical model that decomposes OHCA intensity into overall intensity, demographic fixed effects, spatially structured and unstructured random effects, time polynomial dependence, and spatiotemporal random effect. In the studied geography, time evolution and dependence on demographic features are robust over different categories of OHCAs, but with variability in their spatial and spatiotemporal structure. Two main OHCA incidence-based clusters of municipalities are identified.

Urban Green Space Is Spatially Associated with Cardiovascular Disease Occurrence in Women of Mashhad: a Spatial Analysis of Influential Factors on their Presence in Urban Green Spaces

Chronic diseases have spread around the world. Cardiovascular diseases (CVD), the most important of the chronic diseases and the leading cause of death in women of Mashhad, are impacted by environmental factors. Urban green spaces (UGSs) are important environmental factors playing a critical role in the prevention and control of CVD. Spatial analysis is useful in understanding the application of UGSs in CVD prevention. To identify the spatial distribution of CVD in Mashhad, Moran's index was used and 7539 home addresses of female patients with CVD were imported into ArcMap. Moran's coefficient was estimated to be 0.34, revealing a clustered distribution of CVD. The spatial autocorrelation between CVD and UGSs was analyzed using Moran's I. Moran's I index value was calculated to be - 0.15, and four types of clusters were identified in eight sub-districts of Mashhad municipality. To find the factors influencing the presence in UGSs among women affected by CVD, 607 female patients living in the selected sub-districts were asked to take part in a telephone survey. Data were analyzed using ordinary least squares (OLS) and geographically weighted regression (GWR) at block level (343 statistical blocks in total). Accordingly, the spatial diversity and effects of three variables of income, level of education, and access to UGSs among female patients with CVD were measured. According to OLS results and the standard residual, two clusters were removed. Finally, vulnerable blocks were identified that could be helpful in the development of prevention policies and place-based interventions.

Humidity May Modify the Relationship between Temperature and Cardiovascular Mortality in Zhejiang Province, China

Background: The evidence of increased mortality attributable to extreme temperatures is widely characterized in climate-health studies. However, few of these studies have examined the role of humidity on temperature-mortality association. We investigated the joint effect between temperature and humidity on cardiovascular disease (CVD) mortality in Zhejiang Province, China. Methods: We collected data on daily meteorological and CVD mortality from 11 cities in Zhejiang Province during 2010–2013. We first applied time-series Poisson regression analysis within the framework of distributed lag non-linear models to estimate the city-specific effect of temperature and humidity on CVD mortality, after controlling for temporal trends and potential confounding variables. We then applied a multivariate meta-analytical model to pool the effect estimates in the 11 cities to generate an overall provincial estimate. The joint effects between them were calculated by the attributable fraction (AF). The analyses were further stratified by gender, age group, education level, and location of cities. Results: In total, 120,544 CVD deaths were recorded in this study. The mean values of temperature and humidity were 17.6 °C and 72.3%. The joint effect between low temperature and high humidity had the greatest impact on the CVD death burden over a lag of 0–21 days with a significant AF of 31.36% (95% eCI: 14.79–38.41%), while in a condition of low temperature and low humidity with a significant AF of 16.74% (95% eCI: 0.89, 24.44). The AFs were higher at low temperature and high humidity in different subgroups. When considering the levels of humidity, the AFs were significant at low temperature and high humidity for males, youth, those with a low level of education, and coastal area people. Conclusions: The combination of low temperature and high humidity had the greatest impact on the CVD death burden in Zhejiang Province. This evidence has important implications for developing CVD interventions.

Climatic variability and morbidity and mortality associated with particulate matter

OBJECTIVE

The objective of this study has been to analyze whether fine particulate matter (PM_2.5), as well as its synergistic effect with maximum temperature, humidity, and seasons, is associated with morbidity and mortality from cardiovascular diseases.

METHODS

This is an ecological study of time series. We have used as outcomes the daily death and hospitalization records of adults aged 45 years and over from 2009 to 2011 of the municipalities of Cuiabá and Várzea Grande, State of Mato Grosso, Brazil. We have used Poisson regression using generalized additive models, assuming a significance level of 5%. The model has been controlled for temporal trend, seasonality, average temperature, humidity, and season effects. Daily concentrations of PM_2.5 (particulate material with aerodynamic diameter less than 2.5 micrometers) have been obtained by converting the values of optical aerosol thickness. Maximum temperature, humidity, and seasons have been separately included in the model as dummy variables for the analysis of the synergistic effect of PM_2.5 with morbidity and mortality from cardiovascular disease. We have calculated the percentage increase of relative risk (%RR) of deaths and hospitalizations for the linear increase of 10 μg/m³ of PM_2.5.

RESULTS

Between 2009 and 2011, the increase in PM_2.5 was associated with a %RR 2.28 (95%CI 0.53–4.06) for hospitalizations on the same day of exposure and RR% 3.57 (95%CI 0.82–6.38) for deaths with a lag of three days. On hot days, %RR 4.90 (95%CI -0.61–9.38) was observed for deaths. No modification of the effect of PM_2.5 was observed for maximum temperature in relation to hospitalizations. On days with low humidity, %RR was 5.35 (95%CI -0.20–11.22) for deaths and 2.71 (95%CI -0.39–5.92) for hospitalizations. In the dry season, %RR was 2.35 (95%CI 0.59–4.15) for hospitalizations and 3.43 (95%CI 0.58–6.35) for deaths.

CONCLUSIONS

The PM_2.5 is associated with morbidity and mortality from cardiovascular diseases and its effects may be potentiated by heat and low humidity and during the dry season.

Association between weather seasonality and blood parameters in riverine populations of the Brazilian Amazon

OBJECTIVE

To analyze the seasonality of blood parameters related to iron homeostasis, inflammation, and allergy in two riverine populations from the Brazilian Amazon.

METHODS

This was a cross-sectional study of 120 children and adolescents of school age, living in riverine communities of Porto Velho, Rondonia, Brazil, describing the hematocrit, hemoglobin, ferritin, serum iron, total white blood cell count, lymphocytes, eosinophils, C-reactive protein, and immunoglobulin E levels in the dry and rainy seasons. The chi-squared test and the prevalence ratio were used for the comparison of proportions and mean analysis using paired Student's t-test.

RESULTS

Hemoglobin (13.3g/dL) and hematocrit (40.9%) showed higher average values in the dry season. Anemia prevalence was approximately 4% and 12% in the dry and rainy seasons, respectively. Serum iron was lower in the dry season, with a mean of 68.7 mcg/dL. The prevalence of iron deficiency was 25.8% in the dry season and 9.2% in the rainy season. Serum ferritin did not show abnormal values in both seasons; however, the mean values were higher in the dry season (48.5ng/mL). The parameters of eosinophils, lymphocytes, global leukocyte count, C-reactive protein and immunoglobulin E showed no seasonal differences. C-reactive protein and immunoglobulin E showed abnormal values in approximately 7% and 60% of the examinations, respectively.

CONCLUSION

Hematological parameters of the red cell series and blood iron homeostasis had seasonal variation, which coincided with the dry season in the region, in which an increase in atmospheric pollutants derived from fires is observed.

Fatores de risco para mortalidade por doenças cardiovasculares associados à alta exposição ao tráfego veicular

RESUMO: Objetivo: Identificar áreas e fatores de risco para a mortalidade causada por doenças cardiovasculares (DC) associados à poluição do ar proveniente da alta exposição ao tráfego. Métodos: Estudo transversal da mortalidade por DC em 2.617 indivíduos de 45 a 85 anos residentes na zona urbana de Cuiabá e Várzea Grande, Mato Grosso, entre 2009 e 2011. Utilizou-se a proximidade residencial de até 150 metros de uma via de grande fluxo de veículos como proxy da alta exposição à poluição atmosférica proveniente do tráfego. A associação entre idade, sexo, renda e intensidade do trânsito com a exposição ao tráfego foi avaliada por meio de regressão logística múltipla. Foram realizadas análises estratificadas para observar a influência das estações do ano e dos grupos de causas. Utilizou-se modelo espacial de probabilidade de Bernoulli para identificação de áreas de risco. Resultados: Os principais fatores de risco para mortalidade por DC associados à alta exposição ao tráfego foram: residir em setores censitários com renda muito desigual (OR = 1,78; IC95% 1,36 - 2,33), trânsito intenso (OR = 1,20; IC95% 1,01 - 1,43) e sexo feminino (OR = 1,18; IC95% 1,01 - 1,38). O risco de mortalidade por DC aumenta cerca de 10% no período de seca. Foram identificadas nove áreas de risco. Conclusão: A alta exposição ao tráfego está associada à mortalidade por DC em Cuiabá e Várzea Grande. A desigualdade de renda, a intensidade do trânsito e o sexo feminino apresentaram-se como os principais determinantes dessa exposição, além da estação seca potencializá-la.

Geographical variation in a fatal outcome of acute myocardial infarction and association with contact to a general practitioner

BACKGROUND

Geographical variation in incidence and mortality of acute myocardial infarction (AMI) is present in Denmark. We aimed at examining the association between contact to a general practitioner (GP) the year before AMI and a fatal outcome of AMI.

METHODS

Register-based data and individual-level addresses including 69,608 individuals with AMI in 2006-2011. A Bayesian hierarchical logistic regression model was used to examine the association.

RESULTS

A fatal outcome of AMI was seen among 12.0% (78%) of individuals with (without) contact to a GP the year before AMI. A significant association was estimated.

CONCLUSIONS

A fatal outcome of AMI was significantly associated with contact to a GP. A high population to GP ratio and long distance to GP could not explain the increased odds of a fatal outcome of AMI for individuals with no contact to a GP.