Mortality rates due to respiratory tract diseases in Tehran, Iran during 2008-2018: a spatiotemporal, cross-sectional study

Respiratory-related deaths and associated factors in Alicho-Weriro district, southern Ethiopia: verbal autopsy data analysis

BACKGROUND

Respiratory diseases disproportionately affect people living in resource-limited settings. However, obtaining information that explains respiratory-related deaths has been difficult, mainly due to a lack of medical certification of death and the fact that most deaths occur outside of health institutions. This study aimed to determine the proportion of respiratory-related deaths and identify associated factors in Alicho-Weriro district, southern Ethiopia, using the verbal autopsy method.

METHODS

A community-based cross-sectional study was conducted from April to June 2022. All deceased people in the study area from January 2020 to December 2021 were included in the study. Trained physicians ascertained the cause of death from verbal autopsy data that were collected using a pre-tested and modified WHO-designed questionnaire. The binary logistic regression models were used to identify factors associated with respiratory-related deaths.

RESULTS

Respiratory-related deaths accounted for 25% of the deaths from all causes, with 20.8% of male and 29.5% of female deaths. Of which, 9.7% were from tuberculosis, 8.3% were from asthma and 6.2% were from acute lower-respiratory tract infections. Moreover, being female (adjusted OR, AOR: 3.3; 95% CI: (1.75 to 6.22)), age 50-64 years (AOR: 9.3; 95% CI: (1.16 to 73.90)), age above 64 years (AOR: 8.9; 95% CI: (1.130 to 70.79)), family size of five persons or more (AOR: 1.9; 95% CI: (1.15 to 3.29)), smoking (AOR: 3.9; 95% CI: (1.86 to 8.35)), using wood and/or animal dung for household cooking (AOR: 6.6; 95% CI: (1.92 to 22.59)) and poor house ventilation (AOR: 3.1; 95% CI: (1.75 to 5.38)) were significantly associated with increased odds of dying from respiratory-related diseases.

CONCLUSION

This study has determined that about a quarter of deaths from all causes were due to respiratory diseases, mainly tuberculosis, asthma and acute lower respiratory tract infections. Therefore, interventions to reduce this burden should focus on supporting early case detection and treatment, promoting healthy lifestyles, exercising women's equality at the household level and improving housing conditions.

Cancer patterns in Iran: a gender-specific spatial modelling of cancer incidence during 2014-2017

BACKGROUND

Cancer is a significant public health concern and the second leading cause of death. This study aims to visualize spatial patterns of top common cancer types and identify high-risk and low-risk counties for these cancers in Iran from 2014 to 2017.

METHODS

In this study, we analyzed 482,229 newly diagnosed cancer cases recorded by the Iranian National Population-Based Cancer Registry from 2014 to 2017. We employed a purely spatial scanning model and local Moran I analysis to explore spatial patterns across Iran.

RESULTS

Approximately 53% of all cases were male. The average age of cancer diagnosis was 62.58 ± 17.42 years for males and 56.11 ± 17.33years for females. Stomach cancer was the most common cancer in men. The northern and northwestern regions of Iran were identified as high-risk areas for stomach cancer in both genders, with a relative risk (RR) ranging from 1.26 to 2.64 in males and 1.19 to 3.32 in females. These areas recognized as high-risk areas for trachea, bronchus, and lung (TBL) cancer specifically in males (RR:1.15-2.02). Central regions of Iran were identified as high-risk areas for non-melanoma skin cancers in both genders, ranking as the second most common cancer (RR:1.18-5.93 in males and 1.24-5.38 in females). Furthermore, bladder cancer in males (RR:1.32-2.77) and thyroid cancer in females (RR:1.88-3.10) showed concentration in the central part of Iran. Breast cancer, being the most common cancer among women (RR:1.23-5.54), exhibited concentration in the northern regions of the country. Also, northern regions of Iran were identified as high-risk clusters for colon cancer (RR:1.31-3.31 in males and 1.33-4.13 in females), and prostate cancer in males (RR:1.22-2.31). Brain, nervous system cancer, ranked sixth among women (RR:1.26-5.25) in central areas.

CONCLUSIONS

The study's revelations on the spatial patterns of common cancer incidence in Iran provide crucial insights into the distribution and trends of these diseases. The identification of high-risk areas equips policymakers with valuable information to tailor targeted screening programs, facilitating early diagnosis and effective disease control strategies.

Relationship between fine particulate matter (PM2.5) concentration and risk of hospitalization due to chronic obstructive pulmonary disease: a systematic review and meta-analysis

BACKGROUND

Short-term exposure to PM2.5 has been associated with human health risks. However, evidence on the association between short-term exposure to PM2.5 and the risk of chronic obstructive pulmonary disease (COPD) remains limited and controversial. This study aimed to specifically assess the relationship between exposure to PM2.5 and the risk of hospitalization due to COPD.

METHODS

A systematic search was conducted in PubMed, Web of Science, and Google Scholar databases from January 1, 2010 to May 1, 2022. The odds ratio (OR) statistic was calculated as a common measure of effect size. Publication bias was also examined in all eligible studies on COPD hospitalization using funnel plots and Egger's test, as well as trim-and-fill method for missing studies on COPD hospitalization.

RESULTS

A total of 19 studies were included in this meta-analysis. Random-effects models were plotted to calculate the pooled effect size by measuring OR (χ2 = 349.95; df = 18; I2 = 94.86%; P = 0.007; Z = 2.68; P < 0.001). A 10-mg/m3 daily increase in PM2.5 concentration was associated with a 1.6% (95% CI: 0.4-2.9%) increase in COPD hospitalization. There was no publication bias regarding the association between COPD hospitalization and PM2.5 (bias = 1.508; 95% CI: -1.475, 4.491; t = 1.066; P = 0.301). The subgroups of age ≥ 65 years and Asian countries were associated with an increased risk of COPD hospitalization. Besides, higher risks were estimated in the subgroups of studies performed in the warm season, case-crossover studies, studies with three lag days, and studies without adjustments for humidity and temperature confounders, with very small heterogeneity.

CONCLUSION

Evidence suggests that short-term exposure to PM2.5 increases COPD hospitalization. Further studies are needed to understand the mechanism of the association between PM2.5 and COPD for reducing air pollution, which can be beneficial for COPD patients.

The COVID-19 Mortality Rate Is Associated with Illiteracy, Age, and Air Pollution in Urban Neighborhoods: A Spatiotemporal Cross-Sectional Analysis

There are different area-based factors affecting the COVID-19 mortality rate in urban areas. This research aims to examine COVID-19 mortality rates and their geographical association with various socioeconomic and ecological determinants in 350 of Tehran's neighborhoods as a big city. All deaths related to COVID-19 are included from December 2019 to July 2021. Spatial techniques, such as Kulldorff's SatScan, geographically weighted regression (GWR), and multi-scale GWR (MGWR), were used to investigate the spatially varying correlations between COVID-19 mortality rates and predictors, including air pollutant factors, socioeconomic status, built environment factors, and public transportation infrastructure. The city's downtown and northern areas were found to be significantly clustered in terms of spatial and temporal high-risk areas for COVID-19 mortality. The MGWR regression model outperformed the OLS and GWR regression models with an adjusted R² of 0.67. Furthermore, the mortality rate was found to be associated with air quality (e.g., NO₂, PM₁₀, and O₃); as air pollution increased, so did mortality. Additionally, the aging and illiteracy rates of urban neighborhoods were positively associated with COVID-19 mortality rates. Our approach in this study could be implemented to study potential associations of area-based factors with other emerging infectious diseases worldwide.

Role of urban boundary layer dynamics and ventilation efficiency in a severe air pollution episode in Tehran, Iran

Tehran faces a significant health challenge due to severe air pollution episodes during wintertime, which are associated with high concentrations of fine particulate matter with a diameter less than 2.5 µm (PM2.5). In this study, we investigated meteorology conditions of one of the severe air pollution episodes, occurred from 27th December 2020 to 15th January 2021, using the Weather Research and Forecasting (WRF) model. To gain insights into this episode, we also modeled a clean episode for comparison. Model validation of land surface temperature using remote sensing showed acceptable performance as well as ground observations for other parameters. We then calculated the ventilation coefficient (VC) from the WRF outputs and analyzed the results statistically. Results indicate the severe reduction in both VC and planetary boundary layer height (PBLH) during the polluted episode. We further linked the decrease in PBLH and VC of the polluted episode to a high-pressure system above 1020 hPa. In contrast, the results for the clean episode indicate that the low-pressure system as low as 1010 hPa led to higher PBLH and VC than during the polluted episode. This low-pressure system favors the reduction of PM2.5 levels to lower than 21 μgm−3.

Mortality due to noninfectious lower respiratory diseases: A spatiotemporal, cross-sectional study

Background and Aims

Geography plays an important role in the incidence of respiratory diseases. The aim of this study was to investigate the epidemiology and geographical distribution of death due to noninfectious lower respiratory diseases (NILRDs).

Methods

Data related to all death due to NILRD in Kerman Province between 2012 and 2018 were extracted from the National Mortality Registry. The underlying causes of death were extracted from the registry based on the assigned codes from ICD-10 (International Classification of Diseases 10th Revision) classification. The existence of spatial clusters and outliers was evaluated using local indicators of spatial association statistics.

Results

The frequency of death due to NILRD was 8005 persons during the 7 years of the study. The main cause of death was chronic lower respiratory disease (54.2%). Other causes of death were, respectively, lung diseases due to external agents (1.09%), other respiratory diseases mainly affecting the interstitium (1.16%), other diseases of pleura (0.57%), and other diseases of the respiratory system (42.13%). The age- and sex-adjusted mortality rates due to NILRD in the north and center of the province increased significantly from 2012 to 2018. Also, the results of cluster analysis identified northern regions as the clustered areas of NILRD.

Conclusions

Our findings showed a significant increase in mortality due to NILRD in Kerman Province during the 7 years of the study. To reduce this type of death, health policymakers should have environmental health plans and basic solutions, such as a warning system to reduce the commuting on highly air-polluted days and to control pollutants, especially in the industrial areas of the north of this province.

Promoting Health Literacy and Perceived Self-Efficacy in People with Chronic Obstructive Pulmonary Disease

Background

Chronic Obstructive Pulmonary Disease (COPD) is an irreversible condition and it is of great importance for the patients to practice self-care. Given the impact of inadequate health literacy on people's self-efficacy in a self-care program, the aim of this study was to improve health literacy and self-efficacy in people with COPD.

Materials and Methods

The present quasi-experimental study was conducted on 70 patients with COPD admitted to Shahrekord educational hospitals in 2019. Using random allocation software, the samples were randomly divided into intervention and control groups. Data collection tools included three questionnaires including demographic, health literacy, and perceived self-efficacy questionnaires. A training program, with three weekly sessions of theoretical and practical trainings, was conducted for the intervention group in classes in the hospital. The time of each session was 40 min. Data were collected three times i.e., before, immediately after, and three months after the trainings. Data were analyzed by means of SPSS 21 statistical software using descriptive and inferential statistics.

Results

Before the intervention, the mean scores of perceived self-efficacy and health literacy did not differ significantly between the two groups, but after the intervention, the scores of the members in the intervention group increased significantly (f = 62.15, p < 0.05).

Conclusions

The results of the study indicated an increase in the scores of perceived self-efficacy and health literacy in people with COPD. The use of targeted educational interventions can have a positive effect on the treatment and control of the disease.

A decision support system for prioritised COVID-19 two-dosage vaccination allocation and distribution

This study proposes a decision support system (DSS) that integrates GIS, analytics, and simulation methods to help develop a priority-based distribution of COVID-19 vaccines in a large urban setting. The methodology applies novel hierarchical heuristic-simulation procedures to create a holistic algorithm for prioritising the process of demand allocation and optimising vaccine distribution. The Melbourne metropolitan area in Australia with a population of over five million is used as a case study. Three vaccine supply scenarios, namely limited, excessive, and disruption, were formulated to operationalise a two-dose vaccination program. Vaccine distribution with hard constraints were simulated and then further validated with sensitivity analyses. The results show that vaccines can be prioritised to society's most vulnerable segments and distributed using the current logistics network with 10 vehicles. Compared with other vaccine distribution plans with no prioritisation, such as equal allocation of vaccines to local government areas based on population size or one on a first-come-first-serve basis, the plans generated by the proposed DSS ensure prioritised vaccination of the most needed and vulnerable population. The aim is to curb the spread of the infection and reduce mortality rate more effectively. They also achieve vaccination of the entire population with less logistical resources required. As such, this study contributes to knowledge and practice in pandemic vaccine distribution and enables governments to make real-time decisions and adjustments in daily distribution plans. In this way any unforeseen disruptions in the vaccine supply chain can be coped with.

Development of a web-geographical information system application for plotting tuberculosis cases

In the last few decades, public health surveillance has increasingly applied statistical methods to analyze the spatial disease distributions. Nevertheless, contact tracing and follow up control measures for tuberculosis (TB) patients remain challenging because public health officers often lack the programming skills needed to utilize the software appropriately. This study aimed to develop a more user-friendly application by applying the CodeIgniter framework for server development, ArcGIS JavaScript for data display and a web application based on JavaScript and Hypertext Preprocessor to build the server's interface, while a webGIS technology was used for mapping. The performance of this approach was tested based on 3325 TB cases and their sociodemographic data, such as age, gender, race, nationality, country of origin, educational level, employment status, health care worker status, income status, residency status, and smoking status between 1st January 2013 and 31st December 2017 in Gombak, Selangor, Malaysia. These data were collected from the Gombak District Health Office and Rawang Health Clinic. Latitude and longitude of the location for each case was geocoded by uploading spatial data using Google Earth and the main output was an interactive map displaying location of each case. Filters are available for the selection of the various sociodemographic factors of interest. The application developed should assist public health experts to utilize spatial data for the surveillance purposes comprehensively as well as for the drafting of regulations aimed at to reducing mortality and morbidity and thus minimizing the public health impact of the disease.

Measuring COVID-19 vaccination coverage: an enhanced age-adjusted two-step floating catchment area model

BACKGROUND

There are only limited studies on access to COVID-19 vaccines and identifying the most appropriate health centres for performing vaccination in metropolitan areas. This study aimed to measure potential spatial access to COVID-19 vaccination centres in Mashhad, the second-most populous city in Iran.

METHODS

The 2021 age structure of the urban census tracts was integrated into the enhanced two-step floating catchment area model to improve accuracy. The model was developed based on three different access scenarios: only public hospitals, only public healthcare centres and both (either hospitals or healthcare centres) as potential vaccination facilities. The weighted decision-matrix and analytic hierarchy process, based on four criteria (i.e. service area, accessibility index, capacity of vaccination centres and distance to main roads), were used to choose potential vaccination centres looking for the highest suitability for residents. Global Moran's index (GMI) was used to measure the spatial autocorrelation of the accessibility index in different scenarios and the proposed model.

RESULTS

There were 26 public hospitals and 271 public healthcare centres in the study area. Although the exclusive use of public healthcare centres for vaccination can provide the highest accessibility in the eastern and north-eastern parts of the study area, our findings indicate that including both public hospitals and public healthcare centres provide high accessibility to vaccination in central urban part. Therefore, a combination of public hospitals and public healthcare centres is recommended for efficient vaccination coverage. The value of GMI for the proposed model (accessibility to selected vaccination centres) was calculated as 0.53 (Z = 162.42, P < 0.01). Both GMI and Z-score values decreased in the proposed model, suggesting an enhancement in accessibility to COVID-19 vaccination services.

CONCLUSIONS

The periphery and poor areas of the city had the least access to COVID-19 vaccination centres. Measuring spatial access to COVID-19 vaccination centres can provide valuable insights for urban public health decision-makers. Our model, coupled with geographical information systems, provides more efficient vaccination coverage by identifying the most suitable healthcare centres, which is of special importance when only few centres are available.

Spatio-temporal patterns of the COVID-19 pandemic, and place-based influential factors at the neighborhood scale in Tehran

Since its emergence in late 2019, the COVID-19 pandemic has attracted the attention of researchers in various fields, including urban planning and design. However, the spreading patterns of the disease in cities are still not clear. Historically, preventing and controlling pandemics in cities has always been challenging due to various factors such as higher population density, higher mobility of people, and higher contact frequency. To shed more light on the spread patterns of the pandemic, in this study we analyze 43,000 confirmed COVID-19 cases at the neighborhood level in Tehran, the capital of Iran. To examine spatio-temporal patterns and place-based factors contributing to the spread of the pandemic, we used exploratory spatial data analysis and spatial regression. We developed a geo-referenced database composed of 12 quantitative place-based variables related to physical attributes, land use and public transportation facilities, and demographic status. We also used the geographically weighted regression model for the local examination of spatial non-stationarity. According to the results, population density (R² = 0.88) and distribution of neighborhood centers (R² = 0.59), drugstores (R² = 0.64), and chain stores (R² = 0.59) are the main factors contributing to the spread of the disease. Additionally, density of public transportation facilities showed a varying degree of contribution. Overall, our findings suggest that demographic composition and major neighborhood-level physical attributes are important factors explaining high rates of infection and mortality. Results contribute to gaining a better understanding of the role of place-based attributes that may contribute to the spread of the pandemic and can inform actions aimed at achieving Sustainable Development Goals, particularly Goals 3 and 11.

Religious Affiliation, Daily Spirituals, and Private Religious Factors Promote Marital Commitment Among Married Couples: Does Religiosity Help People Amid the COVID-19 Crisis?

Religious studies are a vital branch of social science that seeks to explain the beliefs of human society and deals with the practices and beliefs of individuals. This distinctive study focuses on such influential aspects of a healthy life, which could play a vital role in the marital quality and matrimonial commitment of individuals. The study principally focused on inspecting the role of religiosity in healthy marital commitment among individuals. It is a distinctive and central value in regulating a healthy social life. This research designed a conceptual model for assessing marital commitment, and the study model comprised two primary variables. The study received datasets through a survey questionnaire based on participants from five private and public sectors. The research study conducted an empirical analysis to test the proposed conceptual framework. The findings exhibited that the value of the R 2 model was 0.484, meaning the level of religiosity had a substantial impression on healthy and lasting marital commitment. According to the final outline of the model factors associated with building religious support factors (β = 0.491), the marital commitment had a better and healthier impact. The goodness-of-fit of the measurement of the conceptual model showed a value of 0.51, which indicated that the theoretical model had sufficient consistency and rationality, and accurately fitted the data. Such an advanced statistical model is missing from the previous literature. The study results provide helpful insight to elucidate the social dynamics of marital commitment. The findings designate that religious practices strengthen and promote nuptial commitment. The study is novel in the context of religiosity impact on martial commitment with a cultural background of Pakistan. The generalizability of the study does not apply to the entire population or other regions. Future studies can investigate other religious variables to explore further research findings. The findings are helpful for decision-makers and policymakers to concentrate on marital issues and challenges confronted by couples worldwide.

Spatio-temporal epidemiology of the tuberculosis incidence rate in Iran 2008 to 2018

Background

Effective reduction of tuberculosis (TB) requires information on the distribution of TB incidence rate across time and location. This study aims to identify the spatio-temporal pattern of TB incidence rate in Iran between 2008 and 2018.

Methods

This cross-sectional study was conducted on aggregated TB data (50,500 patients) at the provincial level provided by the Ministry of Health in Iran between 2008 and 2018. The Anselin Local Moran’s I and Getis-Ord Gi* were performed to identify the spatial variations of the disease. Furthermore, spatial scan statistic was employed for purely temporal and spatio-temporal analyses. In all instances, the null hypothesis of no clusters was rejected at p ≤ 0.05.

Results

The overall incidence rate of TB decreased from 13.46 per 100,000 (95% CI: 13.19–13.73) in 2008 to 10.88 per 100,000 (95% CI: 10.65–11.11) in 2018. The highest incidence rate of TB was observed in southeast and northeast of Iran for the whole study period. Additionally, spatial cluster analysis discovered Khuzestan Province, in the West of the country, having significantly higher rates than neighbouring provinces in terms of both total TB and smear-positive pulmonary TB (SPPTB). Purely temporal analysis showed that high-rate and low-rate clusters were predominantly distributed in the time periods 2010–2014 and 2017–2018. Spatio-temporal results showed that the statistically significant clusters were mainly distributed from centre to the east during the study period. Some high-trend TB and SPPTB statistically significant clusters were found.

Conclusion

The results provided an overview of the latest TB spatio-temporal status In Iran and identified decreasing trends of TB in the 2008–2018 period. Despite the decreasing incidence rate, there is still need for screening, and targeting of preventive interventions, especially in high-risk areas. Knowledge of the spatio-temporal pattern of TB can be useful for policy development as the information regarding the high-risk areas would contribute to the selection of areas needed to be targeted for the expansion of health facilities.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-11157-1.