Overview of the 2019 National Health Interview Survey Questionnaire Redesign.

Data System. Federal health surveys, like the National Health Interview Survey (NHIS), represent important surveillance mechanisms for collecting timely, representative data that can be used to monitor the health and health care of the US population. Data Collection/Processing. Conducted by the National Center for Health Statistics (NCHS), NHIS uses an address-based, complex clustered sample of housing units, yielding data representative of the civilian noninstitutionalized US population. Survey redesigns that reduce survey length and eliminate proxy reporting may reduce respondent burden and increase participation. Such were goals in 2019, when NCHS implemented a redesigned NHIS questionnaire that also focused on topics most relevant and appropriate for surveillance of child and adult health. Data Analysis/Dissemination. Public-use microdata files and selected health estimates and detailed documentation are released online annually. Public Health Implications. Declining response rates may lead to biased estimates and weaken users' ability to make valid conclusions from the data, hindering public health efforts. The 2019 NHIS questionnaire redesign was associated with improvements in the survey's response rate, declines in respondent burden, and increases in data quality and survey relevancy. (Am J Public Health. 2023;113(4):408-415. https://doi.org/10.2105/AJPH.2022.307197).

Update: Characteristics of Health Care Personnel with COVID-19 - United States, February 12-July 16, 2020.

As of September 21, 2020, the coronavirus disease 2019 (COVID-19) pandemic had resulted in 6,786,352 cases and 199,024 deaths in the United States.* Health care personnel (HCP) are essential workers at risk for exposure to patients or infectious materials (1). The impact of COVID-19 on U.S. HCP was first described using national case surveillance data in April 2020 (2). Since then, the number of reported HCP with COVID-19 has increased tenfold. This update describes demographic characteristics, underlying medical conditions, hospitalizations, and intensive care unit (ICU) admissions, stratified by vital status, among 100,570 HCP with COVID-19 reported to CDC during February 12-July 16, 2020. HCP occupation type and job setting are newly reported. HCP status was available for 571,708 (22%) of 2,633,585 cases reported to CDC. Most HCP with COVID-19 were female (79%), aged 16-44 years (57%), not hospitalized (92%), and lacked all 10 underlying medical conditions specified on the case report form† (56%). Of HCP with COVID-19, 641 died. Compared with nonfatal COVID-19 HCP cases, a higher percentage of fatal cases occurred in males (38% versus 22%), persons aged ≥65 years (44% versus 4%), non-Hispanic Asians (Asians) (20% versus 9%), non-Hispanic Blacks (Blacks) (32% versus 25%), and persons with any of the 10 underlying medical conditions specified on the case report form (92% versus 41%). From a subset of jurisdictions reporting occupation type or job setting for HCP with COVID-19, nurses were the most frequently identified single occupation type (30%), and nursing and residential care facilities were the most common job setting (67%). Ensuring access to personal protective equipment (PPE) and training, and practices such as universal use of face masks at work, wearing masks in the community, and observing social distancing remain critical strategies to protect HCP and those they serve.

Prevalence of Diagnosed Diabetes in Adults by Diabetes Type - United States, 2016.

Currently 23 million U.S. adults have been diagnosed with diabetes (1). The two most common forms of diabetes are type 1 and type 2. Type 1 diabetes results from the autoimmune destruction of the pancreas's beta cells, which produce insulin. Persons with type 1 diabetes require insulin for survival; insulin may be given as a daily shot or continuously with an insulin pump (2). Type 2 diabetes is mainly caused by a combination of insulin resistance and relative insulin deficiency (3). A small proportion of diabetes cases might be types other than type 1 or type 2, such as maturity-onset diabetes of the young or latent autoimmune diabetes in adults (3). Although the majority of prevalent cases of type 1 and type 2 diabetes are in adults, national data on the prevalence of type 1 and type 2 in the U.S. adult population are sparse, in part because of the previous difficulty in classifying diabetes by type in surveys (2,4,5). In 2016, supplemental questions to help distinguish diabetes type were added to the National Health Interview Survey (NHIS) (6). This study used NHIS data from 2016 to estimate the prevalence of diagnosed diabetes among adults by primary type. Overall, based on self-reported type and current insulin use, 0.55% of U.S. adults had diagnosed type 1 diabetes, representing 1.3 million adults; 8.6% had diagnosed type 2 diabetes, representing 21.0 million adults. Of all diagnosed cases, 5.8% were type 1 diabetes, and 90.9% were type 2 diabetes; the remaining 3.3% of cases were other types of diabetes. Understanding the prevalence of diagnosed diabetes by type is important for monitoring trends, planning public health responses, assessing the burden of disease for education and management programs, and prioritizing national plans for future type-specific health services.

Comparison of several survey-based algorithms to ascertain type 1 diabetes among US adults with self-reported diabetes.

INTRODUCTION: Defining type of diabetes using survey data is challenging, although important, for determining national estimates of diabetes. The purpose of this study was to compare the percentage and characteristics of US adults classified as having type 1 diabetes as defined by several algorithms. RESEARCH DESIGN AND METHODS: This study included 6331 respondents aged ≥18 years who reported a physician diagnosis of diabetes in the 2016-2017 National Health Interview Survey. Seven algorithms classified type 1 diabetes using various combinations of self-reported diabetes type, age of diagnosis, current and continuous insulin use, and use of oral hypoglycemics. RESULTS: The percentage of type 1 diabetes among those with diabetes ranged from 3.4% for those defined by age of diagnosis <30 years and continuous insulin use (algorithm 2) to 10.2% for those defined only by continuous insulin use (algorithm 1) and 10.4% for those defined as self-report of type 1 (supplementary algorithm 6). Among those defined by age of diagnosis <30 years and continuous insulin use (algorithm 2), by self-reported type 1 diabetes and continuous insulin use (algorithm 4), and by self-reported type 1 diabetes and current insulin use (algorithm 5), mean body mass index (BMI) (28.6, 27.4, and 28.5 kg/m2, respectively) and percentage using oral hypoglycemics (16.1%, 11.1%, and 19.0%, respectively) were lower than for all other algorithms assessed. Among those defined by continuous insulin use alone (algorithm 1), the estimates for mean age and age of diagnosis (54.3 and 30.9 years, respectively) and BMI (30.9 kg/m2) were higher than for other algorithms. CONCLUSIONS: Estimates of type 1 diabetes using commonly used algorithms in survey data result in varying degrees of prevalence, characteristic distributions, and potential misclassification.