Asthma Among Adults and Children by Urban–Rural Classification Scheme, United States, 2016-2018

2021 ◽  
pp. 003335492110475
Author(s):  
Zijing Guo ◽  
Xiaoting Qin ◽  
Cynthia A. Pate ◽  
Hatice S. Zahran ◽  
Josephine Malilay

Objectives Although data on the prevalence of current asthma among adults and children are available at national, regional, and state levels, such data are limited at the substate level (eg, urban–rural classification and county). We examined the prevalence of current asthma in adults and children across 6 levels of urban–rural classification in each state. Methods We estimated current asthma prevalence among adults for urban–rural categories in the 50 states and the District of Columbia and among children for urban–rural categories in 27 states by analyzing 2016-2018 Behavioral Risk Factor Surveillance System survey data. We used the 2013 National Center for Health Statistics 6-level urban–rural classification scheme to define urban–rural status of counties. Results During 2016-2018, the current asthma prevalence among US adults in medium metropolitan (9.5%), small metropolitan (9.5%), micropolitan (10.0%), and noncore (9.6%) areas was higher than the asthma prevalence in large central metropolitan (8.6%) and large fringe metropolitan (8.7%) areas. Current asthma prevalence in adults differed significantly among the 6 levels of urban–rural categories in 19 states. In addition, the prevalence of current asthma in adults was significantly higher in the Northeast (9.9%) than in the South (8.7%) and the West (8.8%). The current asthma prevalence in children differed significantly by urban–rural categories in 7 of 27 states. For these 7 states, the prevalence of asthma in children was higher in large central metropolitan areas than in micropolitan or noncore areas, except for Oregon, in which the prevalence in the large central metropolitan area was the lowest. Conclusions Knowledge about county-level current asthma prevalence in adults and children may aid state and local policy makers and public health officers in establishing effective asthma control programs and targeted resource allocation.

2018 ◽  
Vol 16 (4) ◽  
pp. 296-306
Author(s):  
Justin T McDaniel ◽  
Robert J McDermott ◽  
Mary P Martinasek ◽  
Robin M White

Objective We sought to determine variables associated with asthma among children from military and non-military families. Methods We performed secondary data analysis on the 2016 Behavioral Risk Factor Surveillance System. Parents with and without military experience ( n = 61,079) were asked whether a child ever had asthma and currently has asthma. We used two multiple logistic regression models to determine the influence of rurality and geographic region on “ever” and “current” asthma in children of military and non-military families, while controlling for socio-demographic and behavioral variables. Results Overall childhood asthma prevalence for children in military families was lower than non-military families (ever, 9.7% vs. 12.9%; currently, 6.2% vs. 8.2%) in 2016. However, multiple logistic regression showed variation in “ever” and “current” asthma among children of military and non-military families by rurality and race. Discussion Developers of public health asthma interventions should consider targeting African-American children of military families living in urban areas. This population is approximately twice as likely to have asthma as Caucasian children of non-military families.


2021 ◽  
pp. eabh3826
Author(s):  
Heather Kalish ◽  
Carleen Klumpp-Thomas ◽  
Sally Hunsberger ◽  
Holly Ann Baus ◽  
Michael P Fay ◽  
...  

Asymptomatic SARS-CoV-2 infection and delayed implementation of diagnostics have led to poorly defined viral prevalence rates in the United States and elsewhere. To address this, we analyzed seropositivity in 9,089 adults in the United States who had not been diagnosed previously with COVID-19. Individuals with characteristics that reflected the US population (n = 27,716) were selected by quota sampling from 462,949 volunteers. Enrolled participants (n = 11,382) provided medical, geographic, demographic, and socioeconomic information, and dried blood samples. Survey questions coincident with the Behavioral Risk Factor Surveillance System survey, a large probability-based national survey, were used to adjust for selection bias. The majority (88.7%) of blood samples were collected between May 10th and July 31st, 2020 and were processed using ELISA to measure seropositivity (IgG and IgM antibodies against SARS-CoV-2 spike protein and the spike protein receptor binding domain). The overall weighted undiagnosed seropositivity estimate was 4.6% (95% CI: 2.6-6.5%) with race, age, sex, ethnicity, and urban/rural subgroup estimates ranging from 1.1% to 14.2%; the highest seropositivity estimates were in African American participants, younger, female, and Hispanic participants, and residents of urban centers. These data indicate that there were 4.8 undiagnosed SARS-CoV-2 infections for every diagnosed case of COVID-19, and an estimated 16.8 million infections were undiagnosed by mid-July 2020 in the United States.


Author(s):  
Hongying Dai ◽  
Brian R. Lee ◽  
Jianqiang Hao

Asthma is one of the most common chronic diseases that has a profound impact on people’s well-being and our society. In this study, we link multiple large-scale data sources to construct an epidemiological model to predict asthma prevalence across geographic regions. We use: (1) the Social Media Monitoring (SMM) data from Twitter ( N = 500 million tweets/day), (2) the 2014 Behavioral Risk Factor Surveillance System (BRFSS) ( N = 464,664), and (3) the 2014 American Community Survey (ACS) conducted by the U.S. Census Bureau ( N = 3.5 million per year). We predict asthma prevalence in the traditional survey (BRFSS) using social media information collected from Twitter and socioeconomic factors collected from ACS. The evidence suggests that monitoring asthma-related tweets may provide real-time information that can be used to predict outcomes from traditional surveys.


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