Article Text

Asthma exacerbations in children immediately following stressful life events: a Cox’s hierarchical regression
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  1. S Sandberg1,
  2. S Järvenpää2,
  3. A Penttinen2,
  4. J Y Paton3,
  5. D C McCann4
  1. 1Department of Mental Health Sciences, Royal Free and University College London Medical School, London, UK
  2. 2Department of Mathematics and Statistics, University of Jyväskylä, Jyväskylä, Finland
  3. 3Division of Developmental Medicine, University of Glasgow, Glasgow, UK
  4. 4School of Psychology, University of Southampton, Southampton, UK
  1. Correspondence to:
    Dr S Sandberg
    Department of Mental Health Sciences, University College London, London W1N 8AA, UK;s.sandbergucl.ac.uk

Abstract

Background: A recent prospective study of children with asthma employing a within subject, over time analysis using dynamic logistic regression showed that severely negative life events significantly increased the risk of an acute exacerbation during the subsequent 6 week period. The timing of the maximum risk depended on the degree of chronic psychosocial stress also present. A hierarchical Cox regression analysis was undertaken to examine whether there were any immediate effects of negative life events in children without a background of high chronic stress.

Methods: Sixty children with verified chronic asthma were followed prospectively for 18 months with continuous monitoring of asthma by daily symptom diaries and peak flow measurements, accompanied by repeated interview assessments of life events. The key outcome measures were asthma exacerbations and severely negative life events.

Results: An immediate effect evident within the first 2 days following a severely negative life event increased the risk of a new asthma attack by a factor of 4.69 (p = 0.00). In the period 3–10 days after a severe event there was no increased risk of an asthma attack (p = 0.5). In addition to the immediate effect, an increased risk of 1.81 was found 5–7 weeks after a severe event (p = 0.002). This is consistent with earlier findings. There was a statistically significant variation due to unobserved factors in the incidence of asthma attacks between the children.

Conclusion: The use of statistical methods capable of investigating short time lags showed that stressful life events significantly increase the risk of a new asthma attack immediately after the event; a more delayed increase in risk was also evident 5–7 weeks later.

  • asthma
  • children
  • stress
  • Cox’s hierarchical regression

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  • Publisher Correction

    Please note that some of the statistics have been incorrectly presented.

    In the Results section of the abstract on page 1046, the first sentence should read:
    "An immediate effect evident within the first 2 days following a severely negative life event increased the risk of a new asthma attack by a factor of 4.69, 95% confidence interval 2.33 to 9.44 (p <_0.001. p="p"> The third sentence should read:
    "In addition to the immediate effect, an increased risk of 1.81 (95% confidence interval 1.24 to 2.65) was found 5�7 weeks after a severe event (p=0.002)".

    On page 1049 the third paragraph should read:
    "The effect of a severely negative life event was as follows. The immediate effect corresponding to 1�2 days after the event increased the risk of a new asthma exacerbation by a factor of 4.69 (95% confidence interval 2.33 to 9.44) which was statistically significant (p <_0.001 whereas="whereas" the="the" effect="effect" for="for" days="days" _310="_310" after="after" event="event" was="was" not="not" statistically="statistically" significant="significant" p="p" risk="risk" of="of" an="an" asthma="asthma" attack="attack" varied="varied" considerably="considerably" between="between" children="children" frailty="frailty" term="term" highly="highly" p0.001.="p0.001."> The errors are much regretted.

Footnotes

  • This study was supported by the Medical Research Council, UK (grant G9102413N), the Academy of Finland (grant 41224), and Laboratory of Data Analysis, Center for Mathematical and Computational Modelling, University of Jyväskylä, Finland.

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