BACKGROUND: Few studies have examined longitudinal asthma incidence rates (IRs) from a public health surveillance perspective. OBJECTIVE: Our aim was to calculate descriptive asthma IRs in children over time with consideration for demographics and parental asthma history. METHODS: Data from 9 US birth cohorts were pooled into 1 population covering the period from 1980 to 2017. The outcome was earliest parental report of a doctor diagnosis of asthma. IRs per 1,000 person-years were calculated. RESULTS: The racial/ethnic backgrounds of the 6,283 children studied were as follows: 55% European American (EA), 25.5% African American (AA), 9.5% Mexican-Hispanic American (MA) and 8.5% Caribbean-Hispanic American (CA). The average follow-up was 10.4 years (SD = 8.5 years; median = 8.4 years), totaling 65,291 person-years, with 1789 asthma diagnoses yielding a crude IR of 27.5 per 1,000 person-years (95% CI = 26.3-28.8). Age-specific rates were highest among children aged 0 to 4 years, notably from 1995 to 1999, with a decline in EA and MA children in 2000 to 2004 followed by a decline in AA and CA children in 2010 to 2014. Parental asthma history was associated with statistically significantly increased rates. IRs were similar and higher in AA and CA children versus lower but similar in EA and MA children. The differential rates by sex from birth through adolescence principally resulted from a decline in rates among males but relatively stable rates among females. CONCLUSIONS: US childhood asthma IRs varied dramatically by age, sex, parental asthma history, race/ethnicity, and calendar year. Higher rates in the 0- to 4-year-olds group, particularly among AA/CA males with a parental history of asthma, as well as changes in rates over time and by demographic factors, suggest that asthma is driven by complex interactions between genetic susceptibility and variation in time-dependent environmental and social factors.
BACKGROUND: Few studies have examined longitudinal asthma incidence rates (IRs) from a public health surveillance perspective. OBJECTIVE: Our aim was to calculate descriptive asthma IRs in children over time with consideration for demographics and parental asthma history. METHODS: Data from 9 US birth cohorts were pooled into 1 population covering the period from 1980 to 2017. The outcome was earliest parental report of a doctor diagnosis of asthma. IRs per 1,000 person-years were calculated. RESULTS: The racial/ethnic backgrounds of the 6,283 children studied were as follows: 55% European American (EA), 25.5% African American (AA), 9.5% Mexican-Hispanic American (MA) and 8.5% Caribbean-Hispanic American (CA). The average follow-up was 10.4 years (SD = 8.5 years; median = 8.4 years), totaling 65,291 person-years, with 1789 asthma diagnoses yielding a crude IR of 27.5 per 1,000 person-years (95% CI = 26.3-28.8). Age-specific rates were highest among children aged 0 to 4 years, notably from 1995 to 1999, with a decline in EA and MA children in 2000 to 2004 followed by a decline in AA and CA children in 2010 to 2014. Parental asthma history was associated with statistically significantly increased rates. IRs were similar and higher in AA and CA children versus lower but similar in EA and MA children. The differential rates by sex from birth through adolescence principally resulted from a decline in rates among males but relatively stable rates among females. CONCLUSIONS: US childhood asthma IRs varied dramatically by age, sex, parental asthma history, race/ethnicity, and calendar year. Higher rates in the 0- to 4-year-olds group, particularly among AA/CA males with a parental history of asthma, as well as changes in rates over time and by demographic factors, suggest that asthma is driven by complex interactions between genetic susceptibility and variation in time-dependent environmental and social factors.
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Authors: Charles Washington; Matthew Dapas; Arjun Biddanda; Kevin M Magnaye; Ivy Aneas; Britney A Helling; Brooke Szczesny; Meher Preethi Boorgula; Margaret A Taub; Eimear Kenny; Rasika A Mathias; Kathleen C Barnes; Gurjit K Khurana Hershey; Carolyn M Kercsmar; Jessica D Gereige; Melanie Makhija; Rebecca S Gruchalla; Michelle A Gill; Andrew H Liu; Deepa Rastogi; William Busse; Peter J Gergen; Cynthia M Visness; Diane R Gold; Tina Hartert; Christine C Johnson; Robert F Lemanske; Fernando D Martinez; Rachel L Miller; Dennis Ownby; Christine M Seroogy; Anne L Wright; Edward M Zoratti; Leonard B Bacharier; Meyer Kattan; George T O'Connor; Robert A Wood; Marcelo A Nobrega; Matthew C Altman; Daniel J Jackson; James E Gern; Christopher G McKennan; Carole Ober Journal: Genome Med Date: 2022-09-29 Impact factor: 15.266