The article, “Outdoor Air Pollution and Uncontrolled Asthma in the San Joaquin Valley, California” by Meng et al. (2010) is on the epidemiology of asthma in the San Joaquin Valley (SJV) with a focus on the effects of outdoor air pollution. The study’s purpose was to examine the relationship between air pollution and cases of uncontrolled asthma in the SJV. The authors did not clearly state the study’s hypothesis but it could be deduced as – Air pollution in SJV is directly associated with asthma morbidity in the region.
The study population consisted of individuals living in the SJV with a self-reported physician diagnosis of asthma. Specifically, the eligible subjects were supposed to have had their health data collected between November 2000 and September 2001 by the California Health Interview Survey (CHIS). Therefore, for an individual to be included in the study (inclusion criteria), he or she had to have an asthma diagnosis to avoid misclassification of outcome due to other related respiratory diseases. Additionally, all participants were residents of the SJV, California, and they were required to have their health data collected by CHIS within the earlier indicated period. The final sample was drawn from individuals residing in areas close (5 miles) to a California Air Resources Board or local air-quality management district monitoring station. The 5 miles radius was selected to ensure a large area of study for enough sample size while at the same time controlling for the potential increase in exposure misclassification due to increasing residential distances. As such, those who did not meet these requirements were not included in the study (exclusion criteria). The final sample size for this study was made up of 1502 respondents.
The researchers used an observational cohort study design. The participants with asthma reporting daily or weekly symptoms in the previous year were compared with those reporting less-than-weekly symptoms to assess the relationship between exposure to poor quality air and asthma. Similarly, participants reporting at least one emergency department visit or hospitalization due to asthma-related complications were compared to those not reporting such healthcare utilization. As such, it suffices to argue that the study design is a cohort. The study had both primary and secondary designs. On the one hand, the researchers depended on data collected by the CHIS on people with asthma diagnosis living in the SJV, which underscores the secondary nature of such data. On the other hand, the researchers collected primary data from the selected participants, specifically on the frequency of asthma symptoms and emergency department visits due to asthma-related complications, which underscores the primary nature of such data. The authors employed logistic regression as a statistical method to evaluate the relationship between air pollution and asthma morbidity. According to Meng et al. (2010), “regression analyses incorporated sampling weights to take unequal probabilities of selection into the CHIS sample into account” (p. 143).
The main findings showed that 25.7 percent of respondents used in this study had experienced daily or weekly asthma symptoms in the previous year. The prevalence of such cases increased with age with those aged over 65 years being the most likely to report frequent symptoms. Additionally, poverty was directly linked to frequent daily or weekly symptoms as those without insurance coverage (hence lack of access to care or delayed care) were more likely to report such cases as compared to the insured. Similarly, the unemployed were more likely to report such daily/weekly symptoms as compared to those in gainful employment. The overall prevalence for asthma-related hospitalizations or emergency department visits among the participants was at 9.2 percent. In terms of age, children (participants aged 17 and below) had the highest prevalence of such healthcare utilization. In terms of race, Latinos, African-Americans, and Asians/Others had higher hospitalizations or emergency department visits than Caucasians. Latinos were twice likely to be hospitalized or visit the emergency department due to asthma-related complications as compared with Caucasians. Additionally, those in lower-income groups were more likely to report cases of hospitalizations and ED visits. The results showed that those with delayed care for asthma were almost three times more likely to be hospitalized or visit the emergency department than those who did not report delays in care.
The findings also showed that exposing the participants to a 10 ppb increase in annual average O3 increased the probability of having daily or weekly symptoms by 23 percent. Similarly, there was a 29 percent increase of such cases per 10 g/m3 increase in an annual average of PM10 (OR 1.29, 95% CI 1.05 to 1.57) and “an 82% increase per 10 g/m3 increase in PM2.5 (OR 1.82; 95% CI 1.11 to 2.98)” (Meng et al., 2010, p. 144). Additionally, there was a 49% increase in the prevalence of asthma-related ED visits or hospitalizations “per 10 ppb increase in annual average 03 (OR 1.49, 95% CI 1.05 to 2.11) and a 29% increase in odds per 10 g/m3 in PM10 (OR 1.29, 95% CI 0.99 to 1.69)” (Meng et al., 2010, p. 144). These observations were made after controlling for age, gender, race, and poverty. In terms of age, children had a 63 percent increase in hospitalizations or ED visits per 10 ppb increase in O3, but such an increase in exposure did not have any association with an increase in daily/weekly symptoms among the participants. However, among adults, an increase in exposure to O3, PM2.5, and PM10 led to an increase in daily/weekly symptoms.
The measures used in this study included interviews and surveys. Relative risk (RR), odds ratio (OR), and prevalence rates were used in determining whether exposure to air pollutants would increase asthma morbidity by comparing those exposed to the three pollutants with those not exposed. These measures seem plausible and strong because they determine the association between exposure to the three pollutants (O3, PM10, and PM2.5) and adverse health outcomes based on daily/weekly asthma symptoms and hospitalization or ED visits for asthma-related complications. For instance, the findings showed a positive correlation between exposure to all three pollutants and asthma morbidity for all participants even after controlling for various confounding factors, such as race, poverty, access to care, age, and gender. However, the study design has some biases that could affect the conclusions drawn from the findings. First, the study used participants with self-reported prior asthma diagnosis and such reporting could not be verified using objective measures. Second, under-diagnosis of asthma could be a major issue given the reported cases of delayed access to care, uninsured individuals, and poverty. Third, the use of ED visits or hospitalizations as an outcome could be biased given that some individuals could have sought care services for cases that were not emergent.
The study sample was sufficient given the nature of the study and it was well designed. However, there could be cases of recall bias given that participants were being asked to recall the frequency of daily/weekly symptoms of asthma and cases of hospitalization and ED visits for asthma-related complications in the previous 12 months. As such, some participants could have problems remembering such information with the accuracy needed for reliable data.
One of the article’s strengths is that it is well organized with extensive use of subheadings for easy reading. At the top, the authors gave an elaborate abstract that covers all the major points in the paper including background information, methodology, results, and conclusions. Additionally, data is presented using tables, which becomes easy for the reader to understand the contents of the paper, especially the study findings. Additionally, the authors acknowledged the various limitations of the study, which allows the reader to interpret the data presented and conclusions drawn objectively. However, the article does not clearly state how data was collected, which is a major weakness of this paper. I liked the article’s overall presentation, especially the tabulation of the collected data. I also liked that the authors sought approval from the University of California, Los Angeles Institutional Review Board. However, if I were to rewrite the paper, I would be elaborate on the data collection methods.
The authors concluded that exposure to both O3 and particulate matter (PM2.5 and PM10) directly contributes to frequent asthma-related hospitalizations or emergency department visits and asthma symptoms among the residents of the SJV, California. Therefore, policy-makers need to address the issue of air pollution in the SJV as a way of ensuring improved health outcomes among the residents.
Reference
Meng, Y. Y., Rull, R. P., Wilhelm, M., Lombardi, C., Balmes, J., & Ritz, B. (2010). Outdoor air pollution and uncontrolled asthma in the San Joaquin Valley, California. Journal of Epidemiology & Community Health, 64(2), 142-147.