LA50 in burn injuries Surface létale 50% des patients brûlés

Burn injuries put a huge financial burden on patients and healthcare systems. They are the 8th leading cause of mortality and the 13th most common cause of morbidity in our country. We used data from our Burn Registry Program to evaluate risk factors for mortality and lethal area fifty percent (LA50) in all burn patients admitted over two years. We used multiple logistic regressions to identify risk factors for mortality. LA50 is a reliable aggregate index for hospital care quality and a good measure for comparing results, also with those of other countries. 28,690 burn patients sought medical attention in the Emergency Department, and 1721 of them were admitted. Male to female ratio was 1,75:1. 514 patients were under 15 years old. Median age was 25 (range: 3 months � 93 years). Overall, probability of death was 8.4. LA50 was 62.31 (CI 95: 56.57-70.02) for patients aged 15 and over and 72.52 (CI 95: 61.01-100) for those under 15. In the final model, we found that Adjusted OR was significant for age, female sex, TBSA and inhalation injury (P < 0.05). LA50 values showed that children tolerate more extensive burns. Female sex, burn size, age and inhalation injury were the main risk factors for death. Authorities should pay special attention to these variables, especially in prevention programs, to reduce mortality and improve patient outcome. Children have better outcome than adults given equal burn size. Suicide rates are higher for women than men in our country. © 2016, Mediterranean Club for Burns and Fire Disasters. All rights reserved

Continuous exposure to ambient air pollution and chronic diseases: Prevalence, burden, and economic costs

This is an accepted manuscript of an article published by De Gruyter in Reviews on Environmental Health on 22/04/2020, available online: https://doi.org/10.1515/reveh-2019-0106 The accepted version of the publication may differ from the final published version.Studies that assess the connection between the prevalence of chronic diseases and continuous exposure to air pollution are scarce in developing countries, mainly due to data limitations. Largely overcoming data limitations, this study aimed to investigate the association between the likelihood of reporting a set of chronic diseases (diabetes, cancer, stroke and myocardial infarction, asthma, and hypertension) and continuous exposure to carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), and coarse particulate matter (PM10). Using the estimated associations, the disease burden and economic costs of continuous exposure to air pollutants were also approximated. A 2011 Health Equity Assessment and Response Tool survey from Tehran, Iran, was used in the main analyses. A sample of 67,049 individuals who had not changed their place of residence for at least 2 years before the survey and reported all relevant socioeconomic information was selected. The individuals were assigned with the average monthly air pollutant levels of the nearest of 16 air quality monitors during the 2 years leading to the survey. Both single- and multi-pollutant analyses were conducted. The country’s annual household surveys from 2002 to 2011 were used to calculate the associated economic losses. The single-pollutant analysis showed that a one-unit increase in monthly CO (ppm), NO2 (ppb), O3 (ppb), and PM10 (μg/m3) during the 2 years was associated with 751 [confidence interval (CI): 512–990], 18 (CI: 12–24), 46 (CI: −27–120), and 24 (CI: 13–35) more reported chronic diseases in 100,000, respectively. The disease-specific analyses showed that a unit change in average monthly CO was associated with 329, 321, 232, and 129 more reported cases of diabetes, hypertension, stroke and myocardial infarction, and asthma in 100,000, respectively. The measured associations were greater in samples with older individuals. Also, a unit change in average monthly O3 was associated with 21 (in 100,000) more reported cases of asthma. The multi-pollutant analyses confirmed the results from single-pollutant analyses. The supplementary analyses showed that a one-unit decrease in monthly CO level could have been associated with about 208 (CI: 147–275) years of life gained or 15.195 (CI: 10.296–20.094) thousand US dollars (USD) in life-time labor market income gained per 100,000 30-plus-year-old Tehranis

Facial Mask Use and COVID-19 Protection Measures in Jefferson County, Kentucky: Results from an Observational Survey, November 5−11, 2020

Introduction: The transmission of respiratory infectious diseases such as COVID-19 can significantly decrease by mask-wearing. However, accurate information about the extent and proper use of the facial mask is scarce. This study’s main objective was to observe and analyze mask-wearing behavior and the level of COVID-19 protection measures in indoor public areas (PAs) of Jefferson County, Kentucky. Methods: For conducting the observational survey study, targets were indoor PAs, and zip codes were defined as surveying clusters. The number of selected PAs in each zip code was proportional to the population and the total number of PAs in that zip code. The PA pool in a zip code was divided into four groups, followed by random selection without replacement from each group. Results: A total of 191 PAs were surveyed: 50 of them were grocery stores, 56 were convenience stores or pharmacies, 39 were wine and liquor stores, and 46 were other stores. At least one unmasked and one incorrectly masked staff were observed in 26% and 40% of the sampled PAs, respectively. Also, in 29% and 35% of the PAs, at least one unmasked and one incorrectly masked visitor were observed, respectively. The rates varied by PA size and county district. Eighty percent of unmasked staff and 75% of the unmasked visitors were male. The rate of unmasked males varied from 50% to 100% across districts. About 66% of unmasked staff among all Jefferson County districts were young adults. More than one-fourth of all the PAs provided hand sanitizer for visitors’ use, and only 2% of the PAs provided masks to their visitors. Conclusion: Messaging about mask use and correct usage may need to particularly target the 19-44-year-old male population, as these individuals were the most prevalent among those unmasked and masked incorrectly. Additionally, businesses’ protective measures may depend on their resources to operate in such a manner. Hand sanitizer is easier to offer visitors, while staffing to regularly sanitize carts or funds to provide a sufficient number of wipes, gloves, or masks may present further opportunities for government assistance

Disability-adjusted life-years (DALYs) for 315 diseases and injuries and healthy life expectancy (HALE) in Iran and its neighboring countries, 1990–2015

BACKGROUND: Summary measures of health are essential in making estimates of health status that are comparable across time and place. They can be used for assessing the performance of health systems, informing effective policy making, and monitoring the progress of nations toward achievement of sustainable development goals. The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015) provides disability-adjusted life-years (DALYs) and healthy life expectancy (HALE) as main summary measures of health. We assessed the trends of health status in Iran and 15 neighboring countries using these summary measures. METHODS: We used the results of GBD 2015 to present the levels and trends of DALYs, life expectancy (LE), and HALE in Iran and its 15 neighboring countries from 1990 to 2015. For each country, we assessed the ratio of observed levels of DALYs and HALE to those expected based on socio-demographic index (SDI), an indicator composed of measures of total fertility rate, income per capita, and average years of schooling. RESULTS: All-age numbers of DALYs reached over 19 million years in Iran in 2015. The all-age number of DALYs has remained stable during the past two decades in Iran, despite the decreasing trends in all-age and age-standardized rates. The all-cause DALY rates decreased from 47,200 in 1990 to 28,400 per 100,000 in 2015. The share of non-communicable diseases in DALYs increased in Iran (from 42% to 74%) and all of its neighbors between 1990 and 2015; the pattern of change is similar in almost all 16 countries. The DALY rates for NCDs and injuries in Iran were higher than global rates and the average rate in High Middle SDI countries, while those for communicable, maternal, neonatal, and nutritional disorders were much lower in Iran. Among men, cardiovascular diseases ranked first in all countries of the region except for Bahrain. Among women, they ranked first in 13 countries. Life expectancy and HALE show a consistent increase in all countries. Still, there are dissimilarities indicating a generally low LE and HALE in Afghanistan and Pakistan and high expectancy in Qatar, Kuwait, and Saudi Arabia. Iran ranked 11th in terms of LE at birth and 12th in terms of HALE at birth in 1990 which improved to 9th for both metrics in 2015. Turkey and Iran had the highest increase in LE and HALE from 1990 to 2015 while the lowest increase was observed in Armenia, Pakistan, Kuwait, Kazakhstan, Russia, and Iraq. CONCLUSIONS: The levels and trends in causes of DALYs, life expectancy, and HALE generally show similarities between the 16 countries, although differences exist. The differences observed between countries can be attributed to a myriad of determinants, including social, cultural, ethnic, religious, political, economic, and environmental factors as well as the performance of the health system. Investigating the differences between countries can inform more effective health policy and resource allocation. Concerted efforts at national and regional levels are required to tackle the emerging burden of non-communicable diseases and injuries in Iran and its neighbors

Future and potential spending on health 2015-40: Development assistance for health, and government, prepaid private, and out-of-pocket health spending in 184 countries

Background: The amount of resources, particularly prepaid resources, available for health can affect access to health care and health outcomes. Although health spending tends to increase with economic development, tremendous variation exists among health financing systems. Estimates of future spending can be beneficial for policy makers and planners, and can identify financing gaps. In this study, we estimate future gross domestic product (GDP), all-sector government spending, and health spending disaggregated by source, and we compare expected future spending to potential future spending. Methods: We extracted GDP, government spending in 184 countries from 1980-2015, and health spend data from 1995-2014. We used a series of ensemble models to estimate future GDP, all-sector government spending, development assistance for health, and government, out-of-pocket, and prepaid private health spending through 2040. We used frontier analyses to identify patterns exhibited by the countries that dedicate the most funding to health, and used these frontiers to estimate potential health spending for each low-income or middle-income country. All estimates are inflation and purchasing power adjusted. Findings: We estimated that global spending on health will increase from US$9.21 trillion in 2014 to$24.24 trillion (uncertainty interval [UI] 20.47-29.72) in 2040. We expect per capita health spending to increase fastest in upper-middle-income countries, at 5.3% (UI 4.1-6.8) per year. This growth is driven by continued growth in GDP, government spending, and government health spending. Lower-middle income countries are expected to grow at 4.2% (3.8-4.9). High-income countries are expected to grow at 2.1% (UI 1.8-2.4) and low-income countries are expected to grow at 1.8% (1.0-2.8). Despite this growth, health spending per capita in low-income countries is expected to remain low, at $154 (UI 133-181) per capita in 2030 and$195 (157-258) per capita in 2040. Increases in national health spending to reach the level of the countries who spend the most on health, relative to their level of economic development, would mean $321 (157-258) per capita was available for health in 2040 in low-income countries. Interpretation: Health spending is associated with economic development but past trends and relationships suggest that spending will remain variable, and low in some low-resource settings. Policy change could lead to increased health spending, although for the poorest countries external support might remain essential

Future and potential spending on health 2015-40 : development assistance for health, and government, prepaid private, and out-of-pocket health spending in 184 countries

Background The amount of resources, particularly prepaid resources, available for health can affect access to health care and health outcomes. Although health spending tends to increase with economic development, tremendous variation exists among health financing systems. Estimates of future spending can be beneficial for policy makers and planners, and can identify financing gaps. In this study, we estimate future gross domestic product (GDP), all-sector government spending, and health spending disaggregated by source, and we compare expected future spending to potential future spending. Methods We extracted GDP, government spending in 184 countries from 1980-2015, and health spend data from 1995-2014. We used a series of ensemble models to estimate future GDP, all-sector government spending, development assistance for health, and government, out-of-pocket, and prepaid private health spending through 2040. We used frontier analyses to identify patterns exhibited by the countries that dedicate the most funding to health, and used these frontiers to estimate potential health spending for each low-income or middle-income country. All estimates are inflation and purchasing power adjusted. Findings We estimated that global spending on health will increase from US$9.21 trillion in 2014 to$24.24 trillion (uncertainty interval [UI] 20.47-29.72) in 2040. We expect per capita health spending to increase fastest in upper-middle-income countries, at 5.3% (UI 4.1-6.8) per year. This growth is driven by continued growth in GDP, government spending, and government health spending. Lower-middle income countries are expected to grow at 4.2% (3.8-4.9). High-income countries are expected to grow at 2.1% (UI 1.8-2.4) and low-income countries are expected to grow at 1.8% (1.0-2.8). Despite this growth, health spending per capita in low-income countries is expected to remain low, at $154 (UI 133-181) per capita in 2030 and$195 (157-258) per capita in 2040. Increases in national health spending to reach the level of the countries who spend the most on health, relative to their level of economic development, would mean $321 (157-258) per capita was available for health in 2040 in low-income countries. Interpretation Health spending is associated with economic development but past trends and relationships suggest that spending will remain variable, and low in some low-resource settings. Policy change could lead to increased health spending, although for the poorest countries external support might remain essential.Peer reviewe