Characterizing Fentanyl-Associated Mortality using  the Literal Causes of Death

ObjectiveTo characterize fentanyl-associated mortality in Florida using freetext queries of the literal causes of death listed on death certificates.IntroductionIn October 2015, the Centers for Disease Control and Prevention(CDC) released health advisory #384 to inform people about increasesin fentanyl fatalities. Florida’s statewide syndromic surveillancesystem, Electronic Surveillance System for the Early Notification ofCommunity-based Epidemics (ESSENCE-FL), captures electronicdeath record data in near real time which allows for the monitoringof mortality trends across the state. One limitation of using deathrecord data for fentanyl surveillance is the lack of a fentanyl-specificoverdose ICD-10 code; however, the literal cause of death fields(“literals”) provide a level of detail that is rich enough to capturementions of fentanyl use. The “literals” are a free text field on thedeath certificate, recorded by a physician at the time of death anddetail the factors that led to the death. ESSENCE-FL has the benefitof not only receiving death record data in near real-time, but alsoreceiving the literal cause of death fields. This work analyzes trendsin fentanyl-associated mortality in Florida over time by using theliteral cause of death fields within death records data obtained fromESSENCE-FL.MethodsThe “literals” elements of Florida Vital Statistics mortality datafrom 2010 through 2015 accessed via ESSENCE-FL were queriedfor the term ^fent^. No necessary negations or extra term inclusionswere deemed necessary after looking at the records pulled with ^fent^alone. Deaths were analyzed by various demographic and geographicvariables to characterize this population in order to assess whichgroups are most heavily burdened by fentanyl-associated mortality.Population estimates by county for 2015 were obtained from the U.S.Census Bureau to calculate mortality rates. Language processing in RStudio was used to determine which other substances were commonlyreported when fentanyl was listed on the death certificate, in order toassess polydrug use and its impact on increased mortality.ResultsCompared to the number of fentanyl-associated mortalities in 2010(82), fentanyl-associated mortality in 2015 (599) was 6.5 times higherafter controlling for the natural increase in total mortality between2010 and 2015. Almost three-fourths of the deaths in 2015 were male(73%), which is higher than the proportion of male deaths in 2010(55%). The age group with the largest burden of fentanyl-associatedmortality was the 30 – 39 age group, with almost one-third of thedeaths in 2015 coming from this age group (31%) compared to only10% in 2010, a roughly 200% increase. Fentanyl-associated mortalitywas almost exclusive to people that are Caucasian, with 94% of thefentanyl-associated mortalities in 2015 occurring among Caucasians.Multi-drug use was also identified for those with fentanyl-associatedmortality. Mentions of other drugs were present in at least 10% of thedeaths. Some of the other drugs mentioned in the “literals” includedheroin, cocaine, and alprazolam. There was county variation in thenumber of fentanyl morality deaths ranging from 21.19 deaths per100,000 to 0.29 deaths per 100,000 residents. Two counties with thehighest rates were located adjacent to one another.ConclusionsHaving death record data readily available within the statesyndromic surveillance system is beneficial for rapid analysisof mortality trends and the analytic methods used for syndromicsurveillance can be applied to mortality data. Free text querying ofthe “literals” in the vital statistics death records data allowed forsurveillance of fentanyl-associated mortality, similar to methods usedfor querying emergency department chief complaint data. Althoughunderlying ICD-10 codes can lack detail about certain causes ofdeath, the “literals” provide a clearer picture as to what caused thedeath. The “literals” also make it possible to look at potential drugcombinations that may have increased risk of mortality, which willbe explored more thoroughly. Further work will explore other datasources for fentanyl usage and mortality trends, as well as examinepotential risk factors and confounders.

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P099: Extending the trimodal distribution of death; trauma patients die at increased rates after discharge. Linking trauma registry data to vital statistics and hospital datasets identifies opportunities to save life

CJEM ◽

10.1017/cem.2020.305 ◽

2020 ◽

Vol 22 (S1) ◽

pp. S100-S100

Author(s):

J. French ◽

C. Somayaji ◽

D. Dutton ◽

S. Benjamin ◽

P. Atkinson

Keyword(s):

Mortality Rate ◽

Cause Of Death ◽

Causes Of Death ◽

Trauma Registry ◽

Vital Statistics ◽

Trauma Patients ◽

Age Group ◽

Post Discharge ◽

One Year

Introduction: The New Brunswick Trauma Registry is a database of injury admissions from eight hospitals throughout the province. Data tracks individuals in-hospital. By linking this information with vital statistics, we are able to observe outcomes post-discharge and can model health outcomes for participants. We want to know how outcomes for trauma patients compare with the general population post discharge. Methods: Using data from 2014-15, we followed over 2100 trauma registry observations for one year and tracked mortality rate per 1,000 people by age-group. We also compared the outcomes of this group to all Discharge Abstract Database (DAD) entries in the province (circa. 7500 total). We tracked mortality in-hospital, at six months, and one year after discharge. We truncated age into groups aged 40-64, 65-84, and 85 or older. Results: In-hospital mortality among those in the trauma registry is approximately 20 per 1,000 people for those age 40-64, 50 per 1,000 people for those aged 65-84, and 150 per 1,000 people aged 85 or older. For the oldest age group this is in line with the expected population mortality rate, for the younger two groups these estimates are approximately 2-4 times higher than expected mortality. The mortality at six-month follow-up for both of the younger groups remains higher than expected. At one-year follow-up, the mortality for the 65-84 age group returns to the expected population baseline, but is higher for those age 40-64. Causes of death for those who die in hospital are injury for nearly 50% of observations. After discharge, neoplasms and heart disease are the most common causes of death. Trends from the DAD are similar, with lower mortality overall. Of note, cardiac causes of death account for nearly as many deaths in the 6 months after the injury in the 40 -64 age group as the injury itself. Conclusion: Mortality rates remain high upon discharge for up to a year later for some age groups. Causes of death are not injury-related. Some evidence suggests that the injury could have been related to the eventual cause of death (e.g., dementia), but questions remain about the possibility for trauma-mitigating care increasing the risk of mortality from comorbidities. For example, cardiac death, which is largely preventable, is a significant cause of death in the 40-64 age group after discharge. Including an assessment of Framingham risk factors as part of the patients rehabilitation prescription may reduce mortality.

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Penyebab Kematian di Kabupaten Gianyar Tahun 2010-2012

Buletin Penelitian Kesehatan ◽

10.22435/bpk.v46i2.7 ◽

2018 ◽

Vol 46 (2) ◽

pp. 77-86

Author(s):

Oster Suriani Simarmata ◽

Dina Bisara Lolong ◽

Lamria Pangaribuan ◽

Ning Sulistiyowati ◽

Eva Sulistiowati

Keyword(s):

Cause Of Death ◽

Causes Of Death ◽

Malignant Neoplasm ◽

Vital Statistics ◽

Communicable Diseases ◽

Cervix Uteri ◽

Double Burden ◽

Civil Registration ◽

Icd 10 ◽

Key Indicators

Abstract Cause of death statistics is one of key indicators to determine the health status of Gianyar community for 3 years (2010-2012) as part of Civil Registration and Vital Statistics (CRVS) study. The instruments used were Verbal Autopsy (AV) questionnaire and Causes of Death Form (FKPK). Data were collected from 13 puskesmas and 4 hospitals and analyzed descriptively according to ICD 10. Based on demoghraphic characteristics, the number of deaths is higher among males and older groups, and mostly occurred at home. The highest cause of death is non- communicable diseases (stroke, COPD, IHD, and malignant neoplasm of cervix uteri) followed by communicable diseases (TB and diarrhoea) and transportation accidents. The top ten causes of death in Gianyar show that a non-communicable and communicable diseases would be a double burden for health services. It is essential to establish integrated posts for elderly and NCD, and measures for prevention of TB transmissions and treaments as well as early detection malignant neoplasm of cervix uteri for women had married or sexually active, and to increase the implementation of safe traffic programs. Keywords : cause of death, vital registration, Gianyar Abstrak Penyebab kematian merupakan salah satu indikator kunci untuk menggambarkan status kesehatan masyarakat di masyarakat Gianyar sebagai bagian dari penelitian registrasi sipil dan statistik vital selama 3 tahun (2010-2012) dengan menggunakan kuesioner Autopsi Verbal (AV) dan Formulir Keterangan Penyebab Kematian (FKPK) dari WHO. Data kematian dikumpulkan dari 13 puskesmas dan 4 rumah sakit, dianalisis dengan metode deskriptif, dengan pengelompokan penyebab kematian berdasarkan ICD 10. Berdasarkan karakteristik demografi jumlah kematian lebih banyak laki-laki, kelompok umur tua, dan di rumah. Penyebab kematian tertinggi disebabkan oleh penyakit tidak menular (stroke, PPOK PJK, dan kanker serviks.) diikuti penyakit menular (TB dan diare) dan kecelakaan lalu lintas. Sepuluh besar penyebab kematian terbanyak memperlihatkan adanya penyakit tidak menular dan menular yang merupakan beban ganda bagi pelayanan kesehatan yang harus dihadapi dalam pembangunan bidang kesehatan. Perlunya prioritas program promotif dan preventif seperti mengaktifkan posbindu (Pos Pembinaan Terpadu) lansia dan PTM, sosialisasi tentang upaya pencegahan penularan TB dan adanya program OAT gratis, deteksi dini kanker serviks pada wanita yang sudah menikah atau berhubungan seksual, dan penegakkan peraturan tata tertib pengguna jalan raya lebih ditingkatkan.Kata kunci : pola penyebab kematian, vital registrasi, Gianyar

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Ten-Year Mortality Trends and Natural Causes of Death in the Iraqi Kurdistan

The Open Public Health Journal ◽

10.2174/1874944502114010264 ◽

2021 ◽

Vol 14 (1) ◽

pp. 264-271

Author(s):

Shahla O. Salih ◽

Stefania Moramarco ◽

Daniele Di Giovanni ◽

Sivar A. Qadir ◽

Haveen H. Alsilefanee ◽

...

Keyword(s):

Causes Of Death ◽

Health Information System ◽

Vital Statistics ◽

Quality Data ◽

Mortality Data ◽

Mortality Trends ◽

High Quality Data ◽

Iraqi Kurdistan ◽

Icd 10 ◽

Reported Data

Background: Mortality and causes of death are among the most important statistics used in assessing the effectiveness of a country’s health system. Several countries do not have information systems for collecting these data, and they must therefore be estimated from surveys. Objective: This study analyzes mortality data retrieved from official government databases in Iraqi Kurdistan to describe ten-year trends in natural causes of death. Methods: Data for natural causes of death, reported from 2009 to 2018, were extracted from the databases of the Registration Bureau of Births and Deaths and of the Forensic Medicine of the Province of Sulaymaniyah. A sample of 16,433 causes of death was analyzed. Results: Causes of death were coded according to the ICD-10 classification. Overall, cardiovascular diseases were the leading cause of mortality (52.6%), followed by neoplasms (17.7%), infectious and parasitic diseases (8.9%), and genitourinary diseases (6.3%). Neonatal conditions, congenital anomalies, and neurological conditions each accounted for less than 1% each. Numbers of natural deaths by cause and cause-specific mortality rates have been estimated for the entire Region of Iraqi Kurdistan. Comparisons with other sources suggest that there is a substantial amount of underreporting, especially in relation to deaths of infants and under-five children. Conclusion: Our findings confirm that the region is facing a burden of non-communicable diseases, coupled with high proportions of infectious diseases. However, the lack of effective vital statistics with combined under-reported data collection highlights the need for implementation of health monitoring systems. Advancements in generating high-quality data are essential in improving health and reducing preventable deaths. The establishment of a novel Health Information System is discussed.

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HAI-Proactive: Development of an Automated Surveillance System for Healthcare-Associated Infections in Sweden

Infection Control and Hospital Epidemiology ◽

10.1017/ice.2020.519 ◽

2020 ◽

Vol 41 (S1) ◽

pp. s39-s39

Author(s):

Pontus Naucler ◽

Suzanne D. van der Werff ◽

John Valik ◽

Logan Ward ◽

Anders Ternhag ◽

...

Keyword(s):

Positive Predictive Value ◽

Electronic Health Record ◽

Predictive Value ◽

Surveillance System ◽

Free Text ◽

Health Record ◽

Electronic Health Record Data ◽

Record Data ◽

Electronic Health ◽

Healthcare Associated

Background: Healthcare-associated infection (HAI) surveillance is essential for most infection prevention programs and continuous epidemiological data can be used to inform healthcare personal, allocate resources, and evaluate interventions to prevent HAIs. Many HAI surveillance systems today are based on time-consuming and resource-intensive manual reviews of patient records. The objective of HAI-proactive, a Swedish triple-helix innovation project, is to develop and implement a fully automated HAI surveillance system based on electronic health record data. Furthermore, the project aims to develop machine-learning–based screening algorithms for early prediction of HAI at the individual patient level. Methods: The project is performed with support from Sweden’s Innovation Agency in collaboration among academic, health, and industry partners. Development of rule-based and machine-learning algorithms is performed within a research database, which consists of all electronic health record data from patients admitted to the Karolinska University Hospital. Natural language processing is used for processing free-text medical notes. To validate algorithm performance, manual annotation was performed based on international HAI definitions from the European Center for Disease Prevention and Control, Centers for Disease Control and Prevention, and Sepsis-3 criteria. Currently, the project is building a platform for real-time data access to implement the algorithms within Region Stockholm. Results: The project has developed a rule-based surveillance algorithm for sepsis that continuously monitors patients admitted to the hospital, with a sensitivity of 0.89 (95% CI, 0.85–0.93), a specificity of 0.99 (0.98–0.99), a positive predictive value of 0.88 (0.83–0.93), and a negative predictive value of 0.99 (0.98–0.99). The healthcare-associated urinary tract infection surveillance algorithm, which is based on free-text analysis and negations to define symptoms, had a sensitivity of 0.73 (0.66–0.80) and a positive predictive value of 0.68 (0.61–0.75). The sensitivity and positive predictive value of an algorithm based on significant bacterial growth in urine culture only was 0.99 (0.97–1.00) and 0.39 (0.34–0.44), respectively. The surveillance system detected differences in incidences between hospital wards and over time. Development of surveillance algorithms for pneumonia, catheter-related infections and Clostridioides difficile infections, as well as machine-learning–based models for early prediction, is ongoing. We intend to present results from all algorithms. Conclusions: With access to electronic health record data, we have shown that it is feasible to develop a fully automated HAI surveillance system based on algorithms using both structured data and free text for the main healthcare-associated infections.Funding: Sweden’s Innovation Agency and Stockholm County CouncilDisclosures: None

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PUBLIC HEALTH

PEDIATRICS ◽

10.1542/peds.25.2.343 ◽

1960 ◽

Vol 25 (2) ◽

pp. 343-347

Author(s):

George M. Wheatley ◽

Stephen A. Richardson

Keyword(s):

Public Health ◽

United States ◽

Cause Of Death ◽

United States Public Health ◽

The United States ◽

Vital Statistics ◽

West Germany ◽

Medical Attention ◽

Age Group ◽

Number Of Children

IN ALL COUNTRIES for which there are vital statistics, accidents are a major cause of death and disability among children. In countries where the food supply is adequate and infectious diseases have been brought under control, accidents have become the leading cause of death in the age group 1 to 19 years. For example, in such countries as Australia, Canada, Sweden, West Germany, and the United States, more than one-third of all deaths in this age group are caused by accidents. The number of children who are injured by accidents fan exceeds the number who are killed. Although no accurate international figures are available, the Morbidity Survey conducted by the United States Public Health Service indicates that in the United States, for every child under 15 killed by accident, 1,100 children are injured severely enough to require medical attention or to be restricted in their activity for at least a day.

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Premature Mortality in Canada

University of Toronto Journal of Public Health ◽

10.33137/utjph.v1i1.33812 ◽

2020 ◽

Vol 1 (1) ◽

Author(s):

Catherine Liang ◽

Emmalin Buajitti ◽

Laura Rosella

Keyword(s):

Cause Of Death ◽

Descriptive Analysis ◽

Premature Mortality ◽

Mortality Rates ◽

Vital Statistics ◽

Income Quintile ◽

Mortality Trends ◽

Premature Deaths ◽

Central Canada ◽

Over Time

Introduction: Premature mortality (deaths before age 75) is a well-established metric of population health and health system performance. In Canada, underlying differences between provinces/territories present a need for stratified mortality trends. Methods: Using data from the Canadian Vital Statistics Database, a descriptive analysis of sex-specific adult premature deaths over 1992-2015 was conducted by province, census divisions (CD), socioeconomic status (SES), age, and underlying cause of death. Premature mortality rates were calculated as the number of deaths per 100,000 individuals aged 18 to 74, per 8-year era. SES was measured using the income quintile of the neighbourhood of residence. Absolute and relative inequalities were respectively summarized using slope and relative indices of inequality, produced via unadjusted linear regression of the mortality rate on income rank. Results: Premature mortality in Canada declined by 21% for males and 13% for females between 1992-1999 and 2008-2015. The greatest reductions were in Central Canada, while Newfoundland saw notable increases. CD-level improvements appeared mostly in the southern half of Canada. As of 2008-2015, Newfoundland, Nova Scotia, and Nunavut had the highest mortality rates. Low area-level income was associated with higher mortality. SES inequalities grew over time. Newfoundland’s between-quintile differences rose from 1292 to 2389 deaths per 100k males, or 1.33 to 2.12-fold, and 586 to 1586 per 100k females, or 1.24 to 1.74-fold. In 2008-2015, mortality rates of the bottom quintile in Manitoba and Saskatchewan were more than 2.5 times those of the top. Mortality increased with age, and varied regionally. Low mortality in Central Canada and BC, and high mortality in the Territories were consistent across eras and sexes. Cause of death distributions shifted with age and sex, with more external deaths in younger males. Conclusion: Improvements were seen in adult premature mortality rates over time, but were unequal across geographies. Evidence exists for growing socioeconomic disparities in mortality.

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Detecting Mortality Trends in the Netherlands Across 625 Causes of Death

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph16214150 ◽

2019 ◽

Vol 16 (21) ◽

pp. 4150 ◽

Cited By ~ 2

Author(s):

Marianna Mitratza ◽

Anton E. Kunst ◽

Jan W. P. F. Kardaun

Keyword(s):

Causes Of Death ◽

Multinomial Logistic Regression ◽

Linear Regression Models ◽

Short Term ◽

Mortality Trends ◽

Term Trend ◽

Icd 10 ◽

Cubic Model ◽

Long Term Trend

Cause of death (COD) data are essential to public health monitoring and policy. This study aims to determine the proportion of CODs, at ICD-10 three-position level, for which a long-term or short-term trend can be identified, and to examine how much the likelihood of identifying trends varies with COD size. We calculated annual age-standardized counts of deaths from Statistics Netherlands for the period 1996–2015 for 625 CODs. We applied linear regression models to estimate long-term trends, and outlier analysis to detect short-term changes. The association of the likelihood of a long-term trend with COD size was analyzed with multinomial logistic regression. No long-term trend could be demonstrated for 216 CODs (34.5%). For the remaining 409 causes, a trend could be detected, following a linear (211, 33.8%), quadratic (126, 20.2%) or cubic model (72, 11.5%). The probability of detecting a long-term trend increased from about 50% at six mean annual deaths, to 65% at 22 deaths and 75% at 60 deaths. An exceptionally high or low number of deaths in a single year was found for 16 CODs. When monitoring long-term mortality trends, one could consider a much broader range of causes of death, including ones with a relatively low number of annual deaths, than commonly used in condensed lists.

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Mortality in Emergency Services in a University Teaching Hospital: A Retrospective Study

Journal of Institute of Medicine ◽

10.3126/jiom.v41i2.26542 ◽

2019 ◽

Vol 41 (2) ◽

pp. 17-20

Author(s):

Tirtha Man Shrestha ◽

Ramesh P Aacharya ◽

Ram P Neupane ◽

Bigyan Prajapati

Keyword(s):

Chronic Obstructive Pulmonary Disease ◽

Septic Shock ◽

Mortality Rate ◽

Cause Of Death ◽

Causes Of Death ◽

Emergency Services ◽

University Teaching ◽

Chronic Obstructive ◽

Age Group ◽

Obstructive Pulmonary Disease

Introduction: Emergency services are the gateway between the community and hospital that provides 24-hour access for most needy patients in critical and emergency conditions. Mortality rate varies in emergency department across the world and even in different emergency units of the same hospital. This retrospective study was done in adult emergency services of a tertiary hospital to determine mortality rate and analyze causes of death. Methods: A retrospective observational study of mortality cases to analyze mortality rate and causes of death of patients for a period of 6 months between October 2017 to March 2018 was carried out in the adult emergency services of Tribhuvan University Teaching Hospital, Kathmandu. Data required were collected from copies of death certificates. Results: During the study period, a total of 128 patients died in emergency, accounting 0.5% of total patient. Male deaths (52.3%) were slightly higher compared to female deaths (47.7%). Age group 66-75 years had the highest (24.2%) of total mortalities in the emergency. The most common immediate cause of death was sepsis/septic shock (21.9%) followed by cardiopulmonary arrest, aspiration, respiratory failure, other causes of shock and poisoning. The commonest antecedent cause of death was attributed to respiratory causes. Similarly, the most common contributory cause of death was chronic obstructive pulmonary disease. Conclusion: Older age group is prone to the mortality risk. Sepsis/septic shock was the most common immediate cause of death. Pneumonia was the most common antecedent causes of death. Chronic obstructive pulmonary disease was the commonest contributory cause.

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Sickle Cell Disease Mortality in the United States: Age at Death and Contributing Causes.

Blood ◽

10.1182/blood.v110.11.81.81 ◽

2007 ◽

Vol 110 (11) ◽

pp. 81-81 ◽

Cited By ~ 6

Author(s):

Carlton Haywood ◽

Sophie Lanzkron

Keyword(s):

Sickle Cell Disease ◽

Cause Of Death ◽

Sickle Cell ◽

Causes Of Death ◽

College Education ◽

Age At Death ◽

Cell Disease ◽

Time Period ◽

Icd 10 ◽

The U.S

Abstract BACKGROUND: In the early 1990’s, the Cooperative Study of Sickle Cell Disease (CSSCD) estimated a median life expectancy of 42 years for males, and 48 years for females with sickle cell anemia. We used death certificate data from the late 1990’s and early 2000’s to examine age at death and contributing causes of death for persons with sickle cell disease (SCD). METHODS: We used the National Center for Health Statistics Multiple Cause of Death (MCOD) files to examine age at death and contributing causes of death for persons in the U.S. with SCD during the years 1999 to 2004. The MCOD files contain data from all death certificates filed in the U.S. Each observation in the data has listed an underlying (primary) cause of death, as well as up to 20 conditions thought to contribute to the death. We used ICD-10 codes D570-D578 to identify all deaths attributed to SCD during the time period under study. Records with the ICD-10 code for sickle cell trait (D573) were excluded from further analyses. We used the Clinical Classification Software provided by the Healthcare Cost and Utilization Project to collapse all listed ICD-10 codes into smaller categories. Analyses of age at death were conducted using t-tests, median tests, ANOVA, and multiple linear regression as appropriate. RESULTS: From 1999 to 2004, there were 4553 deaths in the U.S. attributed to SCD (mean = 759/yr, sd = 42.6). SCD was listed as the primary cause in 65% of the deaths. 95% of the deaths were attributed to HbSS disease, and approximately 1% of the deaths were attributed to double heterozygous sickle cell disorders (SC/SD/SE/Thal). 50.4% of the deaths were among males. 64% of the decedents had a high school education or less. 54% of the decedents lived in the South. 68% of the decedents died as inpatients in a hospital. The mean age at death for the time period was 38.2 years (sd = 15.6). There was no change in the mean age at death during the time period. Females were older than males at death (39.4 vs. 36.9, p < 0.0001). Those with HbSS were younger than those with a double heterozygous disorder (38 vs. 47, p < 0.02). Having SCD listed as the primary cause of death was associated with younger age at death (36.8 vs. 40.7, p < 0.0001). Decedents with at least some college education were older at death than those with high school educations or less (40.9 vs. 37.0 p < 0.0001). There were no regional differences in mean age at death. In a multivariate model of age at death with the predictors gender, region, education, and whether or not SCD was listed as the primary cause of death, being female and having some college education remained associated with older age at death, while having SCD listed as the primary cause of death remained associated with younger age at death. Septicemia, pulmonary heart disease, liver disease and renal failure were among the top contributing causes of death for adults, while septicemia, acute cerebrovascular disease and pneumonia were among the top contributing causes of death for kids. CONCLUSIONS: Persons dying from SCD during 1999 to 2004 experienced ages at death that are not improved over those reported by the CSSCD, suggesting the continued need for societal efforts aimed at improving the quality of care for SCD, especially among adults with the condition. Educational attainment is associated with age at death among the SCD population, though it is not possible from the cross-sectional nature of this data to determine the causal directionality of this association.

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Mortality rate of adolescents in the Republic of Serbia

Medicinski pregled ◽

10.2298/mpns0810503r ◽

2008 ◽

Vol 61 (9-10) ◽

pp. 503-506

Author(s):

Nevenka Roncevic ◽

Aleksandra Stojadinovic

Keyword(s):

Mortality Rate ◽

Regional Differences ◽

Causes Of Death ◽

Health Indicators ◽

Vital Statistics ◽

Male Adolescents ◽

Icd 10 ◽

Causes Of Mortality ◽

The Republic ◽

External Causes

Introduction. Adolescents are the healthiest age group of the population but many studies show that period of adolescence is marked by significant morbidity and mortality. Health indicators of adolescent population have been getting worse during past decades. The aim of this study was to determine mortality rate of adolescents in the Republic of Serbia to determine most common causes of death in adolescence and to explore regional differences in adolescent mortality. Materials and methods: Documentation tables of vital statistics in the Republic of Serbia in 2004, and Documentation Tables of Census 2002 were used. The causes of mortality were classified according to ICD 10. Results and discussion. Specific morality rate in the Republic of Serbia is 32.08 on 100.000 adolescents. The leading causes of death in adolescence are injuries, malignancies and non specified causes, and there are significant regional differences, as well as gender and age differences. The mortality rate of male adolescents is about 2.4 times higher than the mortality rates in female adolescents. The mortality rate of older adolescents is significantly higher than mortality rate of younger adolescents. The mortality of adolescents is higher in Vojvodina than in Central Serbia. Precise data of external causes of death do not exist in vital statistics in our country. Conclusion. The mortality of adolescents is high, especially for older male adolescents (15 to 19 years of age) and majority of deaths among adolescents could be prevented. It is necessary to improve data of vital statistics to get better insight into causes of adolescent death.

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