Hospitalizations for Cardiovascular Diseases Sensitive to Primary Health Care in Paraná State, Brazil: A Bayesian Spatiotemporal Model.

PURPOSE: To analyze spatiotemporal trends in hospitalizations for cardiovascular diseases (CVD) sensitive to primary health care (PHC) among individuals aged 50-69 years in Paraná State, Brazil, from 2014 to 2019 and investigate correlations between PHC services and the Social Development Index. METHODS: We conducted a cross-sectional ecological study using publicly available secondary data to analyze the municipal incidence of hospitalizations for CVD sensitive to PHC and to estimate the risk of hospitalization for this group of diseases and associated factors using hierarchical Bayesian spatiotemporal modeling with Markov chain Monte Carlo simulation. RESULTS: There was a 5% decrease in the average rate of hospitalizations for PHC-sensitive CVD from 2014 to 2019. Regarding standardized hospitalization rate (SHR) according to population size, we found that no large municipality had an SHR >2. Likewise, a minority of these municipalities had SHR values of 1-2 (33%). However, many small and medium-sized municipalities had SHR values >2 (47% and 48%, respectively). A greater Social Development Index value served as a protective factor against hospitalizations, with a relative risk of 0.957 (95% credible interval, 0.929-0.984). CONCLUSIONS: The annual risk of hospitalization decreased over time; however, small municipalities had the greatest rates of hospitalization, indicating an increase in health inequity. The inverse association between social development and hospitalizations for CVD sensitive to PHC raises questions about intersectionality in health care.

Prevalence of ß(S)-globin gene haplotypes, α-thalassemia (3.7 kb deletion) and redox status in patients with sickle cell anemia in the state of Paraná, Brazil.

The aim of this study was to determine the frequency of beta S-globin gene (ß(S) globin) haplotypes and alpha thalassemia with 3.7 kb deletion (-α(3.7kb) thalassemia) in the northwest region of Paraná state, and to investigate the oxidative and clinical-hematological profile of ß(S) globin carriers in this population. Of the 77 samples analyzed, 17 were Hb SS, 30 were Hb AS and 30 were Hb AA. The ß(S)globin haplotypes and -α(3.7kb) thalassemia were identified using polymerase chain reaction.Trolox equivalent antioxidant capacity (TEAC) and lipid peroxidation (LPO) were assessed spectophotometrically. Serum melatonin levels were determined using high-performance liquid chromatography coupled to coulometric electrochemical detection. The haplotype frequencies in the SS individuals were as follows: Bantu- 21 (62%), Benin - 11 (32%) and Atypical- 2 (6%). Bantu/Benin was the most frequent genotype. Of the 47 SS and AS individuals assessed, 17% (n = 8) had the -α(3.7kb) mutation. Clinical manifestations, as well as serum melatonin, TEAC and LPO levels did not differ between Bantu/Bantu and Bantu/Benin individuals (p > 0.05). Both genotypes were associated with high LPO and TEAC levels and decreased melatonin concentration. These data suggest that the level of oxidative stress in patients with Bantu/Bantu and Bantu/Benin genotypes may overload the antioxidant capacity.

Built environment influence on the incidence of elderly pedestrian collisions in a medium-large city in southern Brazil: a spatial analysis.

Trauma disproportionately affects vulnerable road users, especially the elderly. We analyzed the spatial distribution of elderly pedestrians struck by vehicles in the urban area of Maringa city, from 2014 to 2018. Hotspots were obtained by kernel density estimation and wavelet analysis. The relationship between spatial relative risks (RR) of elderly run-overs and the built environment was assessed through Qualitative Comparative Analysis (QCA). Incidents were more frequent in the central and southeast regions of the city, where the RR was up to 2.58 times higher. The QCA test found a significant association between elderly pedestrian victims and the presence of traffic lights, medical centers/hospitals, roundabouts and schools. There is an association between higher risk of elderly pedestrians collisions and specific elements of built environments in Maringa, providing fundamental data to help guide public policies to improve urban mobility aimed at protecting vulnerable road users and planning an age-friendly city.

Fire association with respiratory disease and COVID-19 complications in the State of Pará, Brazil.

BACKGROUND: Brazil has faced two simultaneous problems related to respiratory health: forest fires and the high mortality rate due to COVID-19 pandemics. The Amazon rain forest is one of the Brazilian biomes that suffers the most with fires caused by droughts and illegal deforestation. These fires can bring respiratory diseases associated with air pollution, and the State of Pará in Brazil is the most affected. COVID-19 pandemics associated with air pollution can potentially increase hospitalizations and deaths related to respiratory diseases. Here, we aimed to evaluate the association of fire occurrences with the COVID-19 mortality rates and general respiratory diseases hospitalizations in the State of Pará, Brazil. METHODS: We employed machine learning technique for clustering k-means accompanied with the elbow method used to identify the ideal quantity of clusters for the k-means algorithm, clustering 10 groups of cities in the State of Pará where we selected the clusters with the highest and lowest fires occurrence from the 2015 to 2019. Next, an Auto-regressive Integrated Moving Average Exogenous (ARIMAX) model was proposed to study the serial correlation of respiratory diseases hospitalizations and their associations with fire occurrences. Regarding the COVID-19 analysis, we computed the mortality risk and its confidence level considering the quarterly incidence rate ratio in clusters with high and low exposure to fires. FINDINGS: Using the k-means algorithm we identified two clusters with similar DHI (Development Human Index) and GDP (Gross Domestic Product) from a group of ten clusters that divided the State of Pará but with diverse behavior considering the hospitalizations and forest fires in the Amazon biome. From the auto-regressive and moving average model (ARIMAX), it was possible to show that besides the serial correlation, the fires occurrences contribute to the respiratory diseases increase, with an observed lag of six months after the fires for the case with high exposure to fires. A highlight that deserves attention concerns the relationship between fire occurrences and deaths. Historically, the risk of mortality by respiratory diseases is higher (about the double) in regions and periods with high exposure to fires than the ones with low exposure to fires. The same pattern remains in the period of the COVID-19 pandemic, where the risk of mortality for COVID-19 was 80% higher in the region and period with high exposure to fires. Regarding the SARS-COV-2 analysis, the risk of mortality related to COVID-19 is higher in the period with high exposure to fires than in the period with low exposure to fires. Another highlight concerns the relationship between fire occurrences and COVID-19 deaths. The results show that regions with high fire occurrences are associated with more cases of COVID deaths. INTERPRETATION: The decision-make process is a critical problem mainly when it involves environmental and health control policies. Environmental policies are often more cost-effective as health measures than the use of public health services. This highlight the importance of data analyses to support the decision making and to identify population in need of better infrastructure due to historical environmental factors and the knowledge of associated health risk. The results suggest that The fires occurrences contribute to the increase of the respiratory diseases hospitalization. The mortality rate related to COVID-19 was higher for the period with high exposure to fires than the period with low exposure to fires. The regions with high fire occurrences is associated with more COVID-19 deaths, mainly in the months with high number of fires. FUNDING: No additional funding source was required for this study.

Evaluation, intervention, and follow-up of patients with diabetes in a primary health care setting in Brazil: the importance of a specialized mobile consultancy.

BACKGROUND: Studies show that educational interventions improve glycemic control in patients with diabetes mellitus (DM), reducing the occurrence of complications associated with the disease. OBJECTIVES: To evaluate the effects of a mobile DM consultancy on clinical and laboratory parameters, disease knowledge, and quality of life in patients with type 2 DM (T2DM) at a primary health care network in Brazil. METHODS: Randomized clinical trial conducted in a city in southern Brazil with 52 patients with T2DM receiving care at a primary health care setting. The intervention lasted for 6 months and consisted of a follow-up with an endocrinologist (five meetings), treatment adjustment based on clinical evaluation and laboratory tests, and educational activities with conversation maps in DM. The statistical analysis included comparison and association tests, considering p values ≤0.05 as statistically significant. RESULTS: The mean age of the patients was 63.8 years. Most participants were female (63.5 %), had low educational level (59.6 %) and family history of T2DM (71.2 %), used only oral hypoglycemic agents to manage their DM (73.2 %), presented unfavorable anthropometric and laboratory parameters, a high or medium risk of complications (84.6 %), and inadequate glycemic control (67.3 %; with 71 % of the high-risk patients presenting a HbA1c level >9 %). Adjustment in pharmacological treatment was required in 63.5 % of the patients. After the intervention, we observed a significant 0.46 % decrease in mean HbA1c level (p = 0.0218), particularly among individuals with inadequate glycemic control (0.71 %; p = 0.0136). Additionally, there was an increase in disease knowledge scores and a significant decrease in mean body mass index, waist circumference, and disease impact scores. CONCLUSION: The intervention improved glycemic control and disease knowledge, reduced the values of body mass index and waist circumference, and the impact of the disease on patients' lives. This indicates that care and educational measures improve the experience of the patients with DM and control of the disease.

Brazilian road traffic fatalities: a spatial and environmental analysis.

BACKGROUND: Road traffic injuries (RTI) are a major public health epidemic killing thousands of people daily. Low and middle-income countries, such as Brazil, have the highest annual rates of road traffic fatalities. In order to improve road safety, this study mapped road traffic fatalities on a Brazilian highway to determine the main environmental factors affecting road traffic fatalities. METHODS AND FINDINGS: Four techniques were utilized to identify and analyze RTI hotspots. We used spatial analysis by points by applying kernel density estimator, and wavelet analysis to identify the main hot regions. Additionally, built environment analysis, and principal component analysis were conducted to verify patterns contributing to crash occurrence in the hotspots. Between 2007 and 2009, 379 crashes were notified, with 466 fatalities on BR277. Higher incidence of crashes occurred on sections of highway with double lanes (ratio 2∶1). The hotspot analysis demonstrated that both the eastern and western regions had higher incidences of crashes when compared to the central region. Through the built environment analysis, we have identified five different patterns, demonstrating that specific environmental characteristics are associated with different types of fatal crashes. Patterns 2 and 4 are constituted mainly by predominantly urban characteristics and have frequent fatal pedestrian crashes. Patterns 1, 3 and 5 display mainly rural characteristics and have higher prevalence of vehicular collisions. In the built environment analysis, the variables length of road in urban area, limited lighting, double lanes roadways, and less auxiliary lanes were associated with a higher incidence of fatal crashes. CONCLUSIONS: By combining different techniques of analyses, we have identified numerous hotspots and environmental characteristics, which governmental or regulatory agencies could make use to plan strategies to reduce RTI and support life-saving policies.