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1.
NCHS Data Brief ; (448): 1-8, 2022 Nov.
Article in English | MEDLINE | ID: mdl-36342847

ABSTRACT

Alcohol use is a known risk factor for mortality, and the rates of alcohol induced deaths have risen over the past several years (1). Alcohol use in the United States increased during the first year of the Coronavirus Disease 2019 (COVID-19) pandemic, which may have affected mortality rates, especially for alcohol-induced deaths (2). Understanding trends in alcohol-induced mortality, with a particular focus on differences from 2019 to 2020, may help identify groups particularly affected during the COVID-19 pandemic. This report presents overall and sex-specific trends in alcohol-induced death rates from 2000 to 2020, and then focuses on the rates for 2019 and 2020 by sex, age group, and underlying cause of death.


Subject(s)
COVID-19 , Pandemics , Male , Female , United States/epidemiology , Humans , Alcohol Drinking/epidemiology , Risk Factors , Cause of Death , Mortality
2.
NCHS Data Brief ; (417): 1-8, 2021 Sep.
Article in English | MEDLINE | ID: mdl-34582331

ABSTRACT

In the United States, approximately 15% of the population resides in counties located in rural areas (1). Those living in rural areas often face greater public health challenges as they have more limited access to health care, are less likely to be insured, and are more likely to live in poverty (1,2). This report provides the latest national data for trends in age-adjusted death rates for all causes of death among rural and urban areas by sex. Rates for rural and urban areas for the 10 leading causes of death in 2019 are also presented by urbanrural status along with trends in selected causes of death.


Subject(s)
Rural Population , Humans , United States/epidemiology , Urban Population
3.
NCHS Data Brief ; (413): 1-8, 2021 Jul.
Article in English | MEDLINE | ID: mdl-34310274

ABSTRACT

Drowning deaths are the second leading cause of unintentional injury deaths for children aged 0-17 years and the leading cause for those aged 1-4 (1). Previous studies using national data have shown that unintentional drowning deaths can differ by sex, age, race and ethnicity, and urban-rural category (2,3). This report uses the latest mortality data from the National Vital Statistics System (NVSS) to present national trends in unintentional drowning death rates from 1999 through 2019 for children aged 0-17.


Subject(s)
Accidental Injuries , Drowning , Child , Ethnicity , Humans , Rural Population , United States/epidemiology
4.
Natl Health Stat Report ; (156): 1-15, 2021 06.
Article in English | MEDLINE | ID: mdl-34181517

ABSTRACT

Background-The National Cancer Institute (NCI) Joinpoint regression software is a widely used software program for evaluating trends. In addition to producing model estimates for trend models, this software can search for changes in slope along the trend line. One component of the software, which tests whether line segment slopes are zero, is different from the usual t-test of zero slope that is used in linear models. This report will demonstrate this Joinpoint software procedure through replication using the SAS Institute's statistical software (that is, SAS) and discuss the implications of the different assumptions used by Joinpoint and a typical SAS model for the test of zero slope. Methods-First, Joinpoint's procedure for testing a zero slope is compared with a typical test of zero slope using SAS, and the assumptions behind both approaches are evaluated. Second, the test from the Joinpoint software is replicated in SAS using its PROC REG procedure and additional SAS programming. Trend analyses of rates of drug overdose deaths involving fentanyl from the general population and among females are used as examples. Results-In the evaluation of the trend of drug overdose deaths for the total population, Joinpoint produces a similar result to the linear model test in SAS. For the female subgroup, however, Joinpoint and SAS produce differing results for the test of zero slope. The replication of the Joinpoint test of zero slope using SAS demonstrates that Joinpoint's procedure is based on fewer degrees of freedom, which results in a larger standard error estimate. Conclusion-The Joinpoint approach accounts for the fact that the joinpoints are estimated and thus leads to a more conservative hypothesis test, particularly when the number of points in a trend analysis is small.


Subject(s)
Drug Overdose , Fentanyl , Drug Overdose/epidemiology , Female , Humans , Linear Models , National Cancer Institute (U.S.) , Software , United States/epidemiology
5.
NCHS Data Brief ; (400): 1-8, 2021 Mar.
Article in English | MEDLINE | ID: mdl-33814039

ABSTRACT

Motor vehicle traffic deaths are one of the leading contributors to unintentional injury deaths in the United States (1). Recent studies have described changes in the rates of motor vehicle traffic deaths for different demographic groups (2-5). This report provides national trends in motor vehicle traffic deaths by sex, age group, and type of road user (i.e., motor vehicle occupant, motorcyclist, pedestrian, or pedal cyclist) from 1999 through 2019 using the latest mortality data from the National Vital Statistics System (NVSS).


Subject(s)
Accidents, Traffic/mortality , Adolescent , Adult , Age Factors , Aged , Child , Child, Preschool , Female , Humans , Infant , Infant, Newborn , Male , Middle Aged , Mortality/trends , Motor Vehicles , Sex Factors , United States/epidemiology , Vital Statistics , Young Adult
6.
Natl Health Stat Report ; (141): 1-19, 2020 06.
Article in English | MEDLINE | ID: mdl-32600515

ABSTRACT

Objective-This report demonstrates the utility of linking the restricted-use 2014 National Hospital Care Survey (NHCS), 2014-2015 National Death Index (NDI), and 2014-2015 Drug-Involved Mortality (DIM) data to study opioid-involved emergency department (ED) visits, hospitalizations, and mortality within 1 year post-discharge. Example research questions and unweighted results are presented. Results are not nationally representative. Methods-Patient records from the 2014 NHCS with sufficient identifying information were linked to the 2014-2015 NDI and DIM data. Visits were considered opioid-involved if they had International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis codes 304.00-304.02, 304.70-304.72, 305.50-305.52, 760.72, 965.00-965.02, 965.09, 970.1, or E850.0-E850.2 in any diagnosis or external cause of injury code field. Opioid-involved drug overdose deaths were deaths with an International Classification of Diseases, 10th Revision (ICD-10) underlying cause-of-death code of X40-44, X60-64, X85, or Y10-Y14 and a multiple cause code of T40.0-T40.4 or T40.6. Results-In the 2014 NHCS, there were 15,495 patients with an opioid-involved ED-only visit and 24,059 patients with an opioid-involved hospitalization. Of the 20,962 patients with an opioid-involved hospitalization eligible to be linked to NDI, 1,805 died (9%) within 1 year of discharge. Of these deaths, 341 (19%) resulted from a drug overdose. Of drug overdose deaths, 243 (71%) involved an opioid, where 12% died within 30 days post-discharge, 19% within 31-90 days, and 69% within 91-365 days. Opioids most frequently mentioned included heroin (46%), fentanyl (20%), oxycodone (13%), methadone (12%), and morphine (12%). These categories are not mutually exclusive because a death may involve more than one drug. For approximately 22% of patients who died of an opioid-involved drug overdose in 2014, their last ED-only visit or hospitalization was opioid-involved. Conclusion-While the NHCS data are not nationally representative, these unlinked and linked National Center for Health Statistics data allow for exploratory analyses of ED visits, hospitalizations, and associated mortality outcomes.


Subject(s)
Aftercare , Analgesics, Opioid , Emergency Service, Hospital , Hospitalization , Hospitals , Humans , Patient Discharge , United States/epidemiology
7.
Natl Vital Stat Rep ; 68(3): 1-19, 2019 Mar.
Article in English | MEDLINE | ID: mdl-31112123

ABSTRACT

Objectives-Fentanyl, a synthetic opioid, has been increasingly identified in drug overdose deaths. This report describes trends in drug overdose deaths involving fentanyl by demographic characteristics and geographic regions from 2011 through 2016. Methods-Drug overdose deaths were identified from the National Vital Statistics System-Mortality (NVSS-M) multiple cause-of-death files (2011-2016) using International Classification of Diseases, 10th Revision underlying causes of death (codes X40-X44, X60-X64, X85, or Y10-Y14). NVSS-M records for drug overdose deaths were linked with literal text from death certificates. Drug overdose deaths involving fentanyl were identified using a methodology established collaboratively by the National Center for Health Statistics and U.S. Food and Drug Administration-referred to as the Drugs Mentioned with Involvement (DMI) methodology-supplemented with search terms identified using text analytics software. Fentanyl involvement was determined by the presence of any string term or phrase listing fentanyl, or any fentanyl metabolite, precursor, analog, or misspelling identified in the death certificate literal text fields (i.e., the causes of death from Part I, significant conditions contributing to death from Part II, and a description of how the injury occurred). Trends were evaluated using the National Cancer Institute's Joinpoint Regression Program. Results-The number of drug overdose deaths involving fentanyl was stable in 2011 (1,663) and 2012 (1,615), and began to increase in 2013, rising to 18,335 deaths in 2016. The ageadjusted rate increased from 0.5 per 100,000 standard population in 2011 to 5.9 per 100,000 in 2016, with the increase starting in 2013 (0.6 in 2013 to 1.3 in 2014 and 2.6 in 2015). Numbers and rates increased for all sex, age, and racial and ethnic subgroups, and most public health regions. Adjustment for improved drug reporting over the study period did not change the trend patterns observed.


Subject(s)
Drug Overdose/mortality , Fentanyl/poisoning , Adolescent , Adult , Black or African American/statistics & numerical data , Aged , Death Certificates , Drug Overdose/ethnology , Female , Hispanic or Latino/statistics & numerical data , Humans , Male , Middle Aged , Mortality/trends , United States/epidemiology , White People/statistics & numerical data , Young Adult
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