NCHS data briefPub Date : 2025-06-01DOI: 10.15620/cdc/174606
Nimit N Shah, Cheryl D Fryar, Namanjeet Ahluwalia, Lara J Akinbami
{"title":"Fast-food Intake Among Adults in the United States, August 2021-August 2023.","authors":"Nimit N Shah, Cheryl D Fryar, Namanjeet Ahluwalia, Lara J Akinbami","doi":"10.15620/cdc/174606","DOIUrl":"10.15620/cdc/174606","url":null,"abstract":"<p><strong>Introduction: </strong>This report presents estimates of the percentage of calories consumed from fast food on a given day among U.S. adults by selected characteristics during August 2021-August 2023, along with trends in percentage of calories consumed from fast food since 2013-2014.</p><p><strong>Methods: </strong>Data from the August 2021-August 2023 NHANES were used to estimate the percentage of calories consumed from fast food among U.S. adults and test for subgroup differences using orthogonal contrasts to calculate a Student's <i>t</i> statistic. Trends were assessed using data from four NHANES cycles (2013-2014, 2015-2016, 2017-March 2020, and August 2021-August 2023) with linear regression models evaluating linear and quadratic trends while adjusting for differential time between cycles. Statistical analyses, conducted in SAS-callable SUDAAN version 11.0, used orthogonal contrasts and regression models, with significance set at <i>p</i> < 0.05.</p><p><strong>Key findings: </strong>During August 2021-August 2023, about one-third (32.0%) of adults 20 years and older consumed fast food on a given day. Overall, adults consumed 11.7% of calories from fast food on a given day. The percentage of calories consumed from fast food on a given day decreased with age: 15.2% for ages 20-39, 11.9% for ages 40-59, and 7.6% for ages 60 and older. No significant differences were noted between men and women. The percentage of calories consumed from fast food among adults decreased from 14.1% during 2013-2014 to 11.7% during August 2021-August 2023.</p>","PeriodicalId":39458,"journal":{"name":"NCHS data brief","volume":" 533","pages":"1"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12434872/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145034488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
NCHS data briefPub Date : 2025-06-01DOI: 10.15620/cdc/174597
Susan M Schappert, Loredana Santo
{"title":"Emergency Department Visits for Tooth Disorders: United States, 2020–2022","authors":"Susan M Schappert, Loredana Santo","doi":"10.15620/cdc/174597","DOIUrl":"10.15620/cdc/174597","url":null,"abstract":"<p><strong>Introduction: </strong>On average, more than $45 billion in U.S. productivity is lost each year due to untreated dental disease. Oral disease can cause pain and infections, which lead to unplanned visits for emergency care, especially among those who do not have access to routine dental care. This report uses data from the National Hospital Ambulatory Medical Care Survey (NHAMCS) to study emergency department (ED) visits with either a reason for visit or diagnosis of a tooth disorder in 2020-2022.</p><p><strong>Methods: </strong>Data in this report are from NHAMCS, a nationally representative annual survey of nonfederal general and short-stay hospitals. Results are presented from 2020 through 2022. Estimates and their corresponding variances were calculated using SAS-callable SUDAAN. Differences between percentages were evaluated using two-sided significance <i>t</i> tests at the 0.05 level. Linear regression was used to test the significance of slope.</p><p><strong>Key findings: </strong>Tooth disorders accounted for an annual average of 1,944,000 ED visits during 2020-2022. The largest percentage of ED visits for tooth disorders was made by adults ages 25-34 (29.2%). White non-Hispanic people accounted for the largest percentage of ED visits for tooth disorders (52.7%), followed by Black non-Hispanic people (31.9%), and Hispanic people (14.5%). The majority of visits for tooth disorders had Medicaid as the primary expected source of payment (55.4%). Opioids as the sole pain relief drug given or prescribed at ED visits for tooth disorders decreased from 38.1% in 2014-2016 to 16.5% in 2020-2022. Visits with only nonopioid analgesics increased from 20.0% in 2014-2016 to 38.4% in 2020-2022.</p>","PeriodicalId":39458,"journal":{"name":"NCHS data brief","volume":" 531","pages":"1"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12278377/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144477192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Discussion.","authors":"Guangyu Zhang, Yulei He, Anna Oganian, Bill Cai","doi":"","DOIUrl":"","url":null,"abstract":"<p><strong>Background: </strong>Synthetic data has been gaining popularity in many fields as an approach to retain data utility (the validity of inference using synthetic data) and protect confidentiality. However, creating synthetic data for complex surveys remains a challenge.</p><p><strong>Methods: </strong>This research compared three approaches to incorporate survey design information (stratification, clustering, and sampling weights) during the synthetic data-generating process using the Research and Development Survey (RANDS), a series of primarily web surveys conducted by the National Center for Health Statistics, Centers for Disease Control and Prevention. Both parametric (logistic and linear regression models) and nonparametric (classification and regression trees [CART]) methods were used to create synthetic data. Data utility and disclosure risk were evaluated via confidence interval overlap, propensity score measurement, and average matching probability for re-identification.</p><p><strong>Results: </strong>Using the original survey design information as predictors during the synthesis process improved data utility for the parametric method. However, the nonparametric method yielded results with better data utility but slightly higher disclosure risk.</p>","PeriodicalId":39458,"journal":{"name":"NCHS data brief","volume":" 212","pages":"1"},"PeriodicalIF":0.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144267562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
NCHS data briefPub Date : 2025-04-01DOI: 10.15620/cdc/174586
Guangyu Zhang, Yulei He, Anna Oganian, Bill Cai
{"title":"Creating Synthetic Data for Complex Surveys Using the Research and Development Survey: A Comparison Study.","authors":"Guangyu Zhang, Yulei He, Anna Oganian, Bill Cai","doi":"10.15620/cdc/174586","DOIUrl":"10.15620/cdc/174586","url":null,"abstract":"<p><strong>Background: </strong>Synthetic data has been gaining popularity in many fields as an approach to retain data utility (the validity of inference using synthetic data) and protect confidentiality. However, creating synthetic data for complex surveys remains a challenge.</p><p><strong>Methods: </strong>This research compared three approaches to incorporate survey design information (stratification, clustering, and sampling weights) during the synthetic data-generating process using the Research and Development Survey (RANDS), a series of primarily web surveys conducted by the National Center for Health Statistics, Centers for Disease Control and Prevention. Both parametric (logistic and linear regression models) and nonparametric (classification and regression trees [CART]) methods were used to create synthetic data. Data utility and disclosure risk were evaluated via confidence interval overlap, propensity score measurement, and average matching probability for re-identification.</p><p><strong>Results: </strong>Using the original survey design information as predictors during the synthesis process improved data utility for the parametric method. However, the nonparametric method yielded results with better data utility but slightly higher disclosure risk.</p>","PeriodicalId":39458,"journal":{"name":"NCHS data brief","volume":" 212","pages":"1-10"},"PeriodicalIF":0.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12336966/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144477191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
NCHS data briefPub Date : 2025-04-01DOI: 10.15620/cdc/174579
Debra J Brody, Jeffery P Hughes
{"title":"Depression Prevalence in Adolescents and Adults: United States, August 2021-August 2023.","authors":"Debra J Brody, Jeffery P Hughes","doi":"10.15620/cdc/174579","DOIUrl":"https://doi.org/10.15620/cdc/174579","url":null,"abstract":"<p><strong>Introduction: </strong>This report presents the most recent depression prevalence estimates in adolescents and adults, ages 12 years and older, based on the August 2021-August 2023 National Health and Nutrition Examination Survey (NHANES). Depression symptoms are measured using the Patient Health Questionnaire.</p><p><strong>Methods: </strong>Prevalence of depression was estimated using August 2021-August 2023 NHANES data. Depression was defined by score of 10 or greater on the Patient Health Questionnaire (PHQ-9), a validated screening instrument used to assess depression symptoms in the past 2 weeks. Standard errors of percentages were estimated using Taylor series linearization. A <i>t</i> statistic was used to test for differences between groups. Linear and nonlinear trends were evaluated using the orthogonal polynomials. The significance level for statistical testing was <i>p</i> < 0.05.</p><p><strong>Key findings: </strong>During August 2021-August 2023, depression prevalence was 13.1% in adolescents and adults ages 12 years and older and decreased with increasing age. Depression prevalence decreased with increasing family income overall and in males and females. From 2013-2014 to August 2021-August 2023, the prevalence of depression increased overall, and in males and females. Among adolescents and adults with depression, 87.9% reported at least some difficulty with work, home, or social activities due to their depression symptoms, and a higher percentage of females (43.0%) than males (33.2%) reported receiving therapy or counseling in the past 12 months.</p>","PeriodicalId":39458,"journal":{"name":"NCHS data brief","volume":" 527","pages":"1"},"PeriodicalIF":0.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12400127/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144973002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
NCHS data briefPub Date : 2025-04-01DOI: 10.15620/cdc/174589
Nazik Elgaddal, Julie D Weeks, Laryssa Mykyta
{"title":"Characteristics of Adults Age 18 and Older Who Took Prescription Medication for Depression: United States, 2023.","authors":"Nazik Elgaddal, Julie D Weeks, Laryssa Mykyta","doi":"10.15620/cdc/174589","DOIUrl":"10.15620/cdc/174589","url":null,"abstract":"<p><strong>Introduction: </strong>This report uses the most recent National Health Interview Survey data on the use of prescription medication for depression and explores differences in use of medication for depression by age, sex, race and Hispanic origin, disability status, living alone, family income, education level, region, and urbanization level among U.S. adults in 2023.</p><p><strong>Methods: </strong>Data from the 2023 National Health Interview Survey were used for this analysis. Point estimates and corresponding variances were calculated using SAS-callable SUDAAN software version 11.0 to account for the survey's complex sample design. All estimates are based on self-report and meet NCHS data presentation standards for proportions. Differences between percentages were evaluated using two-sided significance tests at the 0.05 level. Linear and quadratic trends by age group and family income were evaluated using orthogonal polynomials in logistic regression.</p><p><strong>Key findings: </strong>In 2023, the percentage of adults age 18 and older who took prescription medication for depression was 11.4%; women were more than twice as likely to take medication for depression than men. White non-Hispanic adults and adults of other and multiple races non-Hispanic were more likely to take medication for depression compared with all other race and Hispanic-origin groups. Adults with disabilities were nearly three times as likely to take medication for depression than adults without disabilities. Taking medication for depression decreased with increasing family income. The percentage of adults taking medication for depression was higher in the Midwest compared to other regions and increased with decreasing urbanization level.</p>","PeriodicalId":39458,"journal":{"name":"NCHS data brief","volume":" 528","pages":"1"},"PeriodicalIF":0.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12451496/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145065983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
NCHS data briefPub Date : 2025-03-01DOI: 10.15620/cdc/174581
Joyce A Martin, Michelle J K Osterman
{"title":"Increases in Neonatal Intensive Care Admissions in the United States, 2016-2023.","authors":"Joyce A Martin, Michelle J K Osterman","doi":"10.15620/cdc/174581","DOIUrl":"10.15620/cdc/174581","url":null,"abstract":"<p><strong>Objectives: </strong>This report examines trends in neonatal intensive care unit (NICU) admission in the United States overall and by maternal age, race and Hispanic origin, gestational age and birthweight of the newborn, and state of residence of the mother from 2016 to 2023.</p><p><strong>Methods: </strong>Data are from the National Vital Statistics System birth files. The percentage of total NICU admissions in the United States from 2016 to 2023 are presented. Also presented are percentages of NICU admissions by maternal age, race and Hispanic origin, gestational age and birthweight of the newborn, and state of residence of the mother from 2016 to 2023.</p><p><strong>Key findings: </strong>The percentage of infants admitted to a neonatal intensive care unit (NICU) in the United States rose 13% from 2016 to 2023, from 8.7% to 9.8%. Increases from 2016 to 2023 were seen for all maternal age, race and Hispanic origin groups, gestational age and birthweight categories and in 40 states.</p>","PeriodicalId":39458,"journal":{"name":"NCHS data brief","volume":" 525","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12038910/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143765369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
NCHS data briefPub Date : 2025-03-01DOI: 10.15620/cdc/174582
Sally C Curtin
{"title":"Trends in Death Rates for Leading Methods of Injury: United States, 2003-2023.","authors":"Sally C Curtin","doi":"10.15620/cdc/174582","DOIUrl":"10.15620/cdc/174582","url":null,"abstract":"<p><strong>Introduction: </strong>This data brief presents trends in injury death rates, in total and by the three leading intents (unintentional, suicide, homicide) for 2003 to 2023. Trends in unintentional injury, suicide, and homicide death rates are then presented by the three leading methods for each intent.</p><p><strong>Methods: </strong>Mortality data for 2003-2020 are from the National Center for Health Statistics' 1999-2020 Underlying Cause of Death by Bridged-Race Categories and data for 2021-2023 are from the 2018-2023 Underlying Cause of Death by Single-Race Categories. Age-adjusted death rates are based on the 2000 standard U.S. population and are per 100,000 population. Injury deaths are identified using <i>International Classification of Diseases,10th Revision</i> codes. Rates are presented for the three leading injury intents (unintentional, suicide, homicide), which are based on the number of deaths. Rates for the three leading methods within each intent are then presented.</p><p><strong>Key findings: </strong>After a period of stability from 2003 to 2013, the total injury death rate increased 21% from 2013 to 2019 and an additional 25% through 2021 before declining 4% through 2023. This pattern of an increase before 2019 and an even greater increase from 2019 to 2021 was seen for both unintentional injury and homicide deaths. Suicide, however, exhibited a different pattern, with increases from 2003 to 2018 and then a decline from 2018 to 2020 before resuming its increase. Drug overdose was the leading method of unintentional injury deaths during the period. Death rates increased from 2003 to 2022, with the largest increase from 2019 to 2022. The rate declined from 2022 to 2023. Firearms were the leading method for both suicide and homicide, with rates generally increasing over the period. Since 2021, firearm-involved homicide rates declined, while firearm-involved suicide rates were stable.</p>","PeriodicalId":39458,"journal":{"name":"NCHS data brief","volume":" 526","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12038913/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144000848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
NCHS data briefPub Date : 2025-01-01DOI: 10.15620/cdc/174583
Anjel Vahratian, Elizabeth M Briones, Ahmed Jamal, Kristy L Marynak
{"title":"Electronic Cigarette Use Among Adults in the United States, 2019-2023.","authors":"Anjel Vahratian, Elizabeth M Briones, Ahmed Jamal, Kristy L Marynak","doi":"10.15620/cdc/174583","DOIUrl":"10.15620/cdc/174583","url":null,"abstract":"<p><strong>Introduction: </strong>This report uses data from the 2019-2023 National Health Interview Survey (NHIS) to present 5-year trends in electronic cigarette use among adults and to show how prevalence estimates changed between 2019 and 2023 for men and women and by age and race and ethnicity.</p><p><strong>Methods: </strong>Point estimates and the corresponding confidence intervals for this analysis were calculated using SAS-callable SUDAAN software to account for the complex sample design of NHIS. Differences between percentages were evaluated using two-sided significance tests at the 0.05 level. Linear and quadratic trends by year and age were evaluated using orthogonal polynomials.</p><p><strong>Key findings: </strong>The percentage of adults who used electronic cigarettes increased from 4.5% in 2019 to 6.5% in 2023. In both 2019 and 2023, men were more likely than women to use electronic cigarettes. In 2023, young adults ages 21-24 were most likely to use electronic cigarettes (15.5%). The percentage of adults who used electronic cigarettes varied by race and Hispanic ethnicity in both 2019 and 2023.</p>","PeriodicalId":39458,"journal":{"name":"NCHS data brief","volume":" 524","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12035660/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143558326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kelly L Myrick, Marko Salvaggio, Lacreisha Ejike-King, Sheba K Dunston, Rashida Dorsey-Johnson, Meena Khare, Denys T Lau
{"title":"Planning, Development, Design, and Operation of the 2016 National Culturally and Linguistically Appropriate Services Survey for Office-based Physicians","authors":"Kelly L Myrick, Marko Salvaggio, Lacreisha Ejike-King, Sheba K Dunston, Rashida Dorsey-Johnson, Meena Khare, Denys T Lau","doi":"","DOIUrl":"","url":null,"abstract":"<p><strong>Objectives: </strong>This report describes the development and operations of the 2016 National Culturally and Linguistically Appropriate Services Survey for Office-based Physicians (National CLAS Physician Survey). The survey was developed to understand awareness, adoption, and implementation of the National CLAS Standards in health and health care among office-based physicians.</p><p><strong>Methods: </strong>Survey development included a literature review of survey and assessment instruments that evaluated cultural and linguistic appropriateness in health care. Survey questions were pretested during a cognitive interview study of 20 office-based physicians in the District of Columbia metropolitan area. The cognitive interviews were analyzed using a grounded theory approach. The final survey was administered via web, mail, and computer-assisted telephone interview to 2,400 sampled physicians between August 2016 and December 2016. A nonresponse bias assessment was conducted.</p><p><strong>Results: </strong>The literature review identified five survey and assessment instruments. Collectively, survey content included: cultural competency training, cultural awareness, and adoption of the National CLAS Standards. Cognitive interviews showed respondent difficulty in question interpretation and survey completion of some items. Survey revisions addressed these issues. The final overall weighted survey response rate was 33.8%. Final weights produced a lower standardized bias than base weights.</p><p><strong>Conclusions: </strong>The National CLAS Physician Survey is the first nationally representative survey to describe the use and implementation of culturally and linguistically appropriate services by office-based physicians. Data can serve as a baseline for future studies and as a benchmark for meeting the key objectives of the National CLAS Standards.</p>","PeriodicalId":39458,"journal":{"name":"NCHS data brief","volume":" 67","pages":"1"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145055987","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}