Follow up duration ranged from 8 to 20 years across studies, with a median of 11.5 years. Of these, three studies were conducted in the United States, two in European countries, and one in Canada. Table 1 presented the characteristics of six studies examining whether depression predicts onset of asthma. Statistical analysis was performed using Stata 12.0 (Stata Corp, College Station, Texas, USA) and Cochrane Collaboration Review Manager 5.1.2 (Cochrane Collaboration, Oxford, UK) software. Begg's and Egger's test were used to estimate the severity of publication bias, with a P value <0.05 considered statistically significant. The sensitivity analyses and publication bias were performed only for depression predicting asthma but not asthma predicting depression due to the small numbers of studies available. Potential publication bias was assessed by visual inspection of the funnel plot in which the log RRs were plotted against their standard error. We also investigated the impact of a single study on the overall pooled estimate by omitting one single study at a time and recalculating the pooled effect estimate of other remaining studies. sex, age and race), depression measure, asthma diagnosis, degree of adjustment, follow-up periods, we further conducted sensitivity analyses to explore possible explanations and to examine the robustness of the pooled risk estimates based on various exclusion criteria. Given that the studies differed in sample characteristics (i.e. A random-effects model, which considered both within-study and between-study variation, was used to obtain the combined risk estimates regardless of heterogeneity. Heterogeneity across the studies were tested by using the I 2 statistic, which is a quantitative measure of inconsistency across studies, with suggested thresholds for low (25%-50%),moderate (50%-70%) and high (>75%) heterogeneity, respectively. low, medium, high depression symptoms), we only used the estimate for the highest category. For studies presenting with graded relationships (i.e. smoking status), we combined the estimates using a random-effects model and then the pooled estimate was used for the meta-analyses. If a study only presented stratified risk estimates (i.e. Two separate analyses were conducted: depression predicting asthma, and asthma predicting depression. The hazard ratios (HRs) and odds ratios (ORs) were directly considered equivalent to RRs. The RRs were used as the common measure of association between depression and asthma across studies. Therefore, the aim of this study was to systematically examine whether depression predicts asthma and, conversely, whether asthma predicts depression by conducting a meta-analysis of prospective studies. Since then, many more well-designed prospective studies have been published, allowing for a more detailed analysis of the temporal relationship between these two illness. However, this meta-analysis only included studies published before 2007, and was lacking in studies which specifically address the relationship between depression and asthma (there were only two investigating depression predicting asthma and none examined asthma predicting depression). A previous meta-analysis of prospective studies reported a bidirectional relationship between psychosocial factors and atopic disorders. Because both depression and asthma impose substantial public health burdens, the association between these two conditions has attracted attention over the past several decades.Ī number of prospective studies have assessed the temporal association between depression and asthma however, the results were inconclusive. Equally detrimental, asthma affects 39.5 million Americans, 29.0 million of which are adults, and 300 million individuals worldwide, with increasing prevalence in many countries. Approximately 16% of adults in the United States are diagnosed with major depression disorder, and 5.8% of men and 9.5% of women will likely experience an episode of depression within a 12-month period. Depression and asthma are two highly prevalent chronic diseases in the United States and worldwide, imposing unacceptable social and economic burdens on the public healthcare system.
0 Comments
Leave a Reply. |