摘要：Objectives. Using data on 2868 children born in the Western Australian Pregnancy Cohort (Raine) Study, we examined the association between changes in family socioeconomic status and childhood asthma. Methods. We determined the likelihood (odds ratio) of a child having asthma at ages 6 and 14 years for 4 family-income trajectories (chronic low, increasing, decreasing, and never low) over the child's lifetime. The trajectories were created from longitudinal latent-class models. Results. We found a 2-fold increased risk of asthma at age 14 years among children who had lived in a low-income family since birth, especially for girls. Asthma was less likely to occur in children born to single parents; income rose over time in many of these families. Compared with children in chronic low-income families, children in households with increasing incomes had a 60% lower risk of asthma. Single-point measures of low income were not found to be associated with asthma. Conclusions. Chronic exposure to a low-income environment from birth was associated with the development of persistent asthma. There was also a protective effect against asthma among those children whose families had moved out of poverty. Asthma disproportionately burdens children living in economically disadvantaged urban communities. Some of this disparity can be attributed to the observation that once asthma is established, lower utilization of prophylactic medications and higher rates of hospitalization are more common among low-income children than among high-income children. 1 , 2 Evidence for the link between socioeconomic status (SES) and the development of asthma is less strong—and is, in fact, contradictory. 1 , 3 Many studies report asthma to be more prevalent among low-SES children, even in countries with universal health care insurance. 4 – 7 However, no association with SES was reported in 1 study, 8 and another study documented lower rates of asthma among low-SES children. 9 The latter finding is congruent with the lower prevalence of atopic disease in developing countries 10 and with the “hygiene” hypothesis, which proposes that exposure to infections and endotoxin is protective against atopic asthma. 11 Low-income children have higher infection rates, although endotoxin levels are not always elevated in low-income households. 12 Despite this level of uncertainty, it is common for household SES to be treated as a confounding factor and to be used to statistically adjust models testing the association between early life exposures and the development of childhood asthma. As low-income mothers are more likely to smoke and less likely to breastfeed, 13 , 14 SES acts as a proxy measure for these exposures in the absence of available data. However, there is a lack of recognition that contradictory findings on the association of SES with childhood asthma may be a function of the validity of the SES measure. Low-income variables are fraught with measurement error, and there may be considerable fluctuation in household income over the course of a child's life from birth to adolescence. 15 Measures of cumulative income, such as the frequency of low-income episodes over time, have shown stronger associations with poor health than have single-point measures. 16 Other SES trajectories, such as downward or upward social mobility, have been reported to increase and decrease risk of cardiovascular disease, respectively. 17 Fluctuations in family income also affect family functioning and maternal mental health. 18 The effects of chronic poverty on child functioning and health have long been recognized. 19 , 20 However, few studies have evaluated childhood asthma in relation to cumulative household income or income trajectories from the time of birth. 21 Low-income households and neighborhoods are characterized by high levels of chronic stress, 1 , 22 but no longitudinal studies have investigated the relationship between chronic poverty, chronic stress, and asthma development. To fill this gap in the literature, we studied the relationship between family SES trajectories starting from birth of the child and asthma development in early school age and adolescence. We used maximum-likelihood longitudinal latent-class modeling techniques to identify SES trajectories over time. 15 , 23
