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Status and Determinants of Individual Actions to Reduce Health Impacts of Air pollution in U.S. Adults a
b
c
a
Claudia Lissåker MPH , Evelyn O. Talbott MPH Dr.PH , Haidong Kan Ph.D & Xiaohui Xu Ph.D a a
Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, FL, USA b b
Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA. c c
Department of Environmental Health, School of Public Health, Fudan University, Shanghai, China, Accepted author version posted online: 02 Dec 2014.
Click for updates To cite this article: Claudia Lissåker MPH, Evelyn O. Talbott MPH Dr.PH, Haidong Kan Ph.D & Xiaohui Xu Ph.D (2014): Status and Determinants of Individual Actions to Reduce Health Impacts of Air pollution in U.S. Adults, Archives of Environmental & Occupational Health, DOI: 10.1080/19338244.2014.988673 To link to this article: http://dx.doi.org/10.1080/19338244.2014.988673
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Status and Determinants of Individual Actions to Reduce Health Impacts of Air pollution in U.S. Adults Claudia Lissåker, MPHa; Evelyn O. Talbottb, MPH, Dr.PH ; Haidong Kanc, Ph.D; Xiaohui Xua,
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Ph.D
a. Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, FL, USA b. Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA. Email: [email protected] c. Department of Environmental Health, School of Public Health, Fudan University, Shanghai, China. Email: [email protected]
Corresponding Author: Xiaohui Xu, Ph.D. 1225 Center Drive, Room 3119, Gainesville, FL 32610-0182 Email: [email protected]
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Abstract Although regulation of emissions is the primary strategy to reduce air pollution-related morbidity, individual-level interventions are also helpful in mitigating health impacts. We used data from 2007-2008 National Health and Nutrition Examination Survey to study the prevalence
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of individual-level action among the U.S. adult population if informed of air pollution, and to see if this differed by demographic and health factors. Only 13.5% (CI: 11.6-15.4%) of participants aware of air quality reported changing their individual behaviors. Male sex (AOR: 0.66, CI: 0.56-0.77), and those without cardiovascular disease (AOR: 0.58, CI: 0.47-0.71) were least likely to take action. Results show that individual action was infrequent among the population. Health promotion of individual intervention is necessary, and this effort may need to target specific subgroups of the population. Further studies on effective individual interventions are needed.
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ACCEPTED MANUSCRIPT Introduction Numerous epidemiological studies have consistently shown air pollution to be associated with an increased risk of mortality and morbidity in the general population, including deaths from chronic obstructive pulmonary disease (COPD) and heart disease.1,2 Annually, over 600,000 people die of heart disease3 and over 125,000 die of COPD4 in the United States.
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Because of these significant impacts of these diseases on health, reducing air pollution exposure has clear health benefits. Air pollution is a macro environmental problem which is caused by natural events such as wild fires and volcano eruption as well as human activities. Major anthropogenic sources of air pollution include the burning of fossil fuels such as coal, petroleum, and natural gas. 5 As industrialization progresses, anthropogenic sources of air pollution through traffic-related and industrial emissions, such as power plants, are becoming an increasing problem. 6 Traditionally, emission-based air pollution control has been regarded as the fundamental way to improve air quality and to reduce the adverse health effects of air pollution. Interventions at individual level such as behavioral change have largely been overlooked as a strategy to reduce air pollution exposure. Although there is no doubt that improving air quality is still the primary effort in reducing adverse health effects of air pollution, individual actions such as wearing masks, reducing outdoor activities, and using air filters might also be necessary to reduce air pollution exposure, particularly during a significant air pollution episode.7 Overall air quality has improved over the past decades in the U.S. following the Clean Air Acts; however, air pollution remains a major environmental problem in some areas of this country.8 Air pollution sources such as traffic exhaust emission, industrial emission and wildfires
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ACCEPTED MANUSCRIPT continue to worsen in some areas. Bad air quality is regularly reported in several areas, and during specific times. Individual intervention is perhaps the easiest manner to reduce exposure and, subsequently, the adverse health impacts of air pollution, as it does not require societal-level change. Furthermore, studies show that subgroups with certain characteristics, such as the elderly and those with certain comorbidities, are particularly sensitive to health effects of air pollution.9-
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Therefore, individual-level intervention might be particularly critical for these vulnerable
subpopulations to reduce exposure and their negative health consequences. However, few studies have determined whether individuals change their behaviors based on air pollution advisories or bad air quality and what factors are associated with this change. Those that do exist find that those most at risk and those that receive physician recommendations are more likely to change behaviors. These studies, however, are outdated or focus on a subsample of the populations (e.g. those with asthma or Hispanics only).12-17 To our knowledge, there are no current studies that investigate individuals’ likelihood of taking action during periods of bad air quality in the general population. This study used 2007-2008 data from the National Health and Nutrition Examination Survey (NHANES) to investigate how many individuals take actions to protect themselves from air pollution when they were informed of bad air quality among the U.S. adult population. Previous epidemiologic studies have found that certain subgroups, including those with low SES, may be more susceptible to air pollutants.18,19 Therefore our secondary aim is to evaluate if any subgroups of the population as defined by demographic factors and health conditions are more likely to take preventive actions. The ultimate objective is to provide health agencies with important information that can aid in the development of health education interventions to
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ACCEPTED MANUSCRIPT promote individual-level efforts in reducing air pollution exposure and further reducing the burden of diseases related to air pollution exposures.
Methods Data for this study were obtained from the 2007-2008 cycle of the NHANES. The
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NHANES uses a representative sample of the non-institutionalized population of the United States of all ages, recruiting around 10,000 participants each cycle. Basic demographic information is collected along with answers to medical measurements, laboratory tests, and a questionnaire on health behaviors.20 A total of 10,149 participants were surveyed in this cycle. Participants under 20 years older (n=4,055) were not considered in this study because information on respiratory conditions and cardiovascular disease was not available for that age group, and this study is interested in investigating whether those who should be heeding to advisories are doing so. In the 2007-2008 cycle, participants were asked the following question: “During the past 12 months, when {you thought/SP thought} or {were/was} informed air quality was bad, {did you/did SP} do anything differently?” There were 5935 people over 20 years older who were asked this question. Respondents who answered “yes” or “no” to this were included in this study. Those who replied that they “never thought/not informed bad air quality” and those who answered “don’t know” were excluded from this analysis. Therefore, a total of 5,434 respondents were included in the study. Covariates selected included age (classified as 20-29, 30-49, 50-69, and 70 or older), gender, race/ethnicity (non-Hispanic White, non-Hispanic Black, Mexican-American, and others), education (less than high school, high school graduate or GED completion, and college
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ACCEPTED MANUSCRIPT or above), ratio of family income to poverty (categorized as tertiles, low: ≤142% of poverty level, medium: 142% to 330% of pervert level, or high: >330% of poverty level), smoking status (currently smokes, smoked in the past, or never smoked), self-reported general health status (dichotomized as excellent/very good/good versus fair/poor). Age was categorized as such to reflect different outdoor behaviors and disease risk. For instance, those older than 50 are more
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likely to have heart disease than those who are younger21 and it is possible that those in their 30s and 40s have different outdoor behaviors than those 20-29 due to employment. Additionally, individuals aged 70 and older possibly have different outdoor habits than those who are younger than 70. From the medical conditions section of the questionnaire, we combined questions about asthma, emphysema, and chronic bronchitis into reporting having respiratory disease (dichotomized as ever had versus never had), and questions about congestive heart failure, coronary heart disease, angina/angina pectoris, heart attack, and stroke into reporting having cardiovascular disease (dichotomized as ever had versus never had). These questions were asked in the following manner: “Has a doctor or other health professional ever told 22 that {you have/s/he/SP has}…” followed by the health condition of interest; therefore included both active and inactive conditions. To indicate if a person ever had a respiratory or cardiovascular condition (yes vs. no) a separate variable was created that combined the two conditions above. All covariates were chosen based on prior literature12-17 and knowledge of vulnerable population with a higher risk to air pollution. We also investigated which actions participants responded to doing differently during a bad air pollution day. Respondents who reported changing behavior were asked: “Which of these {did you/did SP} do differently?” They could choose from the following options: wore a mask, spent less time outdoors, avoided roads that have heavy traffic,
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ACCEPTED MANUSCRIPT did less strenuous activities, took medication, closed windows of house, drove car less, canceled outdoor activities, exercised indoors instead of outside, used buses, trains, or subways, other (specify), refused, or don’t know. Though participants could chose more than one action, each was provided individually as either “yes” or “missing” for those not asked the question. Participants who responded anything other than “yes” to the question regarding whether or not
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they changed behavior were not asked this question. Statistical analyses were conducted using SAS version 9.2.23 Because of the complex sampling design of the NHANES, analyses that accounted for clustering, weighting, and stratification were used (proc surveyfreq and proc surveylogistic). Unadjusted and adjusted logistic regression models were created for all covariates. Odds ratios and 95% confidence intervals (95% CI) were calculated for both crude models (OR), and adjusted model (AOR).
Results Of the 5434 participants included in this study, 13.4% (n=727) reported changing their behavior due to bad air quality. Those who reported changing behavior compared to those who did not were more often in their 50s and 60s (16.6% versus 7.3% of ages 20-29, 13.7% of ages 30-49, and 14.8% of ages 70 and over), were more likely to be female (16.1% versus 10.7% of males), and more likely to be a college graduate or above (15.6% versus 11.3% who are high school graduates or possess a GED, and 10.7% who have less than a high school education) and have high family income (15.1% versus 12.7% with medium family income, and 11.7% with low family income). Respondents who reported changing their behavior were more likely to report a
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ACCEPTED MANUSCRIPT respiratory disease (21.5% versus 11.6%), and more likely to report a cardiovascular disease (17.9% versus 11.6%) (Table 1). Table 2 shows the weighted percentages of individual behaviors taken by those who were aware of bad air quality. Those who took no actions comprise the majority of the population at 86.5%. The majority of those who did take an individual action in response to air pollution
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responded that they spent less time outdoors (8.8%) or wore a mask (1.4%). Other actions included closing windows, canceling outdoor activities, and using or changing air filters among others. Unadjusted associations between changing behavior due to bad air quality and demographic, health behaviors, and health status are displayed in Table 3. Compared to the 2029 age group, all other age groups had a significantly higher crude odds ratio of changing behaviors (OR: 2.02, CI: 1.14-3.59 for those 30-49, OR: 2.53, CI: 1.44-4.45 for those 50-69, and OR: 2.20, CI: 1.27-3.81 for those 70 and over). Male respondents were at lower odds of taking any action compared to female respondents (OR: 0.62, CI: 0.54-0.72). Mexican-Americans also had statistically significant lower odds than Whites of changing behaviors due to bad air quality (OR: 0.49, CI: 0.28-0.86). College graduates were at a significantly higher odds of changing behaviors (OR: 1.54, CI: 1.14-2.09) compared to those with less than a high school education. Those reporting neither respiratory disease nor cardiovascular disease were less likely than those who reported a respiratory or cardiovascular disease to report changing their behaviors (OR: 0.54, CI: 0.45-0.66). The multivariable model was adjusted for age group, gender, race/ethnicity, education, family income, and having either respiratory disease or cardiovascular disease (Table 3). After
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ACCEPTED MANUSCRIPT adjustment, all age groups and college graduates had significantly higher odds of reporting behavior change. Those in the 50-69 age group had the highest odds of changing behavior (AOR: 2.49, CI: 1.39-4.44) when compared to those in the 20-29 age group. Males and those who did not have a respiratory or cardiovascular disease had significantly lower odds of reporting behavior change compared to females and those who did have either of respiratory or
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cardiovascular disease (AOR: 0.66, CI: 0.56-0.77 and AOR: 0.58, CI: 0.47-0.71, respectively).
Discussion According to results, a small proportion of the study population (13.4%) reported changing health behaviors due to bad air quality or air advisories. This is not reflective of a lack of knowledge or awareness about the issue as the NHANES provides an option for those who did not think about air pollution or were not aware of advisories.24 What this may show is a lack of awareness regarding potential negative outcomes of air pollution. Interestingly, groups that most likely obtain recommendations regularly, such as older respondents and those with respiratory or heart disease, showed an increased odds ratio of reporting a change in behavior due to bad air quality when adjusting for other covariates. This indicates that of those who are heeding warnings and taking action a large proportion belong to these vulnerable groups. However, the vast majority of the study population (86.5%) reported not changing health behaviors due to bad air quality or air advisories, indicating that a large proportion of those who belong to these susceptible populations are not taking individual action. Males and Mexican-Americans were less likely to report a change in behavior after adjustment for other factors, although the latter was not statistically significant after adjusting for
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ACCEPTED MANUSCRIPT other covariates. One plausible explanation for a lack of change in behavior is that previous studies have found that men are less susceptible than women to the effects of air pollution. 25,26 This may suggest that the decreased response to air pollution may stem from having fewer symptoms associated with it. Hispanics have been shown to be less concerned with the effects of air pollution and less cognizant of it than non-Hispanic whites, which varied with levels of
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acculturation.16 This study could not directly assess the effects of acculturation; however, variables that were controlled for such as age, education and family income may be proxies for how an individual has assimilated into the culture (would tend to be middle aged, higher education, higher income). Regardless, results did show an independent negative association between Mexican-Americans, a subgroup of the Hispanic ethnicity, and taking an action to protect oneself from air pollution, which indicates that culture may play a role on the perception of air pollution risk. Lastly, high education was a significantly associated with changing individual behaviors when aware of air pollution. This was true even after family income was included in the analysis, indicative that there may be reasons other than the possibility that those with higher education are more likely to have access to better healthcare and medical advice due to higher socioeconomic status. Though differences between sociodemographic groups are small in that overall report of behavior change is small, these results provide preliminary evidence that certain groups may be even less likely to take action during episodes of bad air pollution than others, and may benefit from interventions. Studies that are available regarding air pollution perception and behavior are either outdated or not generalizable. However, the available literature does suggest that respondents with certain characteristics are more likely to change behaviors than those others. For instance,
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ACCEPTED MANUSCRIPT Evans et al found that those who are most at risk for the negative impacts of air pollution are the ones who are most likely to report compliance with advisories.13 In this study’s sample, the same finding holds true for those who reported ever having respiratory disease or a cardiovascular disease. Similarly, one recent study done on the Behavioral Risk Factor Surveillance System (BRFSS) did find an association between being aware of media alerts and physician
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recommendations and a change in behavior among adults with asthma.17 However this study conducted by Wen and colleagues does not include other groups beyond those with asthma and is limited only to six states in the United States, which cannot be assumed to be generalizable to the entire population. Another study found that concern for air pollution was inversely associated with age; that is, younger people tended to be more concerned about air pollution. 12 In the present study, those in the older groups were the more likely to change behavior when compared to the youngest group. This does not imply that younger respondents were unconcerned with air pollution, simply that they were less likely to change behavior. This may be due to certain responsibilities such as school or work taking precedence over staying indoors in episodes of bad air quality. Another possibility is that though a general concern for air quality is present, awareness of the potential health effects is lacking. This study has several limitations. Because there was no information on perceptions towards air pollution or whether conditions listed were current or happened in the past, this study cannot assess if a lack of response to bad air quality is due to a lack of concern with the potential health effects. For instance, those with a history of asthma that occurred many years prior to the study may be less concerned with air pollution and less likely to take action than those with a recent diagnosis of asthma, but this study cannot differentiate these groups. Also, the data set had
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ACCEPTED MANUSCRIPT a large amount of missing data. However, the current study was not able to assess the direction of this bias because of lack of information. We also cannot ascertain that the question regarding behavior change is measuring actual behavior change. Though information from the NHANES is collected by highly trained staff with strict protocols, there is always a possibility for bias with non-validated self-reported outcomes, in other words, we cannot verify if an individual actually
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performed the task he or she reported to have done. This bias is likely non-differential, which would bias our results towards the null. With the publicly available NHANES dataset, this study cannot adjust for area in which the respondent lives. It may be that those who live in rural areas are less likely to think about air quality and have different characteristics than those who live in urban areas, which may confound results. Similarly, many other covariates, such as occupation, local policy efforts, and individual knowledge, which may significantly impact a person’s response to bad air quality advisories, are not available in the dataset. Despite these limitations, this study also had several strengths. One, it uses nationally representative data. Therefore, this is likely to be generalizable to the United States population. The data set also has a fairly large sample size, which makes it unlikely that this study was underpowered and missed any important significant differences. Lastly, data collected for the NHANES was used, which ensures that data were obtained using rigorous sampling and interviewing procedures. Future studies should investigate the outlets from which individuals are getting information on air pollution quality. We could not ascertain actual media used using the present dataset, but this type of data could be integral to figuring out why certain individuals responded to not receiving any information on air quality. Another area of focus is on reasons why a person did not change behavior regarding air pollution, or similarly if they did or did not think air
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ACCEPTED MANUSCRIPT pollution affected them and why. Potential reasons may be lack of knowledge about medical recommendations or negative health outcomes, inability to change daily routines, or, as Johnson demonstrated, a lack of preoccupation with air pollution that may stem from cultural perceptions.16 If the public health community can pinpoint the actual reason for not following recommendations to avoid bad air pollution episodes, then steps can be taken to target those
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individuals and their barriers. Consequently, research should also focus on effective methods that individuals can apply to protect themselves from and avoid air pollution. For instance, one study has found that women who consume greater amounts of fish during pregnancy confer some protection to the fetus against the harmful effects of air pollution.27 Lastly, future studies should be done regarding children’s exposure to air pollution and individual actions taken to protect them from it. This study was only able to include adults aged 20 years and older; but, as mentioned previously, children are also vulnerable to the negative effects of air pollution. This study found that certain groups are more likely to change behaviors when they are aware of bad air quality. These included the elderly and those with either respiratory or cardiovascular disease. Although this shows that some of the most susceptible groups are in fact protecting themselves against air pollution, over 85% of the population is not taking any action. This includes the majority of those who are highly susceptible. Interventions need be developed to bring awareness to the entire population of the detrimental effects of air pollution exposure, and they should specifically target males, Mexican-Americans, and those with less education in addition to groups that are already known to be vulnerable. Acknowledgements Claudia Lissåker is funded through a fellowship from the University of Florida Graduate School.
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Table 1 Weighted percentage of persons who changed behavior due to bad air quality among U.S adults, 2007-2008 NHANES (N=5,434) Variable
Number of sampled
Total sample
persons who
Weighted percentage (95% CI)
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changed behavior Age groups 20-29
55
821
7.3 (3.6-11.0)
30-49
230
1801
13.7 (11.3-16.2)
50-69
300
1776
16.6 (12.9-20.3)
70+
142
1036
14.8 (12.4-17.1)
Male
292
2660
10.7(8.9-12.5)
Female
435
2774
16.1 (13.8-18.5)
Non-Hispanic White
382
2528
14.3 (11.7-17.0)
Non-Hispanic Black
170
1200
13.3 (9.4-17.2)
Mexican-Americans
87
914
7.6 (3.3-11.8)
Others
88
792
12.8 (8.3-17.4)
Gender
Race/ethnicity
Education
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Status and Determinants of Individual Actions to Reduce Health Impacts of Air pollution in U.S. Adults a
b
c
a
Claudia Lissåker MPH , Evelyn O. Talbott MPH Dr.PH , Haidong Kan Ph.D & Xiaohui Xu Ph.D a a
Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, FL, USA b b
Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA. c c
Department of Environmental Health, School of Public Health, Fudan University, Shanghai, China, Accepted author version posted online: 02 Dec 2014.
Click for updates To cite this article: Claudia Lissåker MPH, Evelyn O. Talbott MPH Dr.PH, Haidong Kan Ph.D & Xiaohui Xu Ph.D (2014): Status and Determinants of Individual Actions to Reduce Health Impacts of Air pollution in U.S. Adults, Archives of Environmental & Occupational Health, DOI: 10.1080/19338244.2014.988673 To link to this article: http://dx.doi.org/10.1080/19338244.2014.988673
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Status and Determinants of Individual Actions to Reduce Health Impacts of Air pollution in U.S. Adults Claudia Lissåker, MPHa; Evelyn O. Talbottb, MPH, Dr.PH ; Haidong Kanc, Ph.D; Xiaohui Xua,
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Ph.D
a. Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, FL, USA b. Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA. Email: [email protected] c. Department of Environmental Health, School of Public Health, Fudan University, Shanghai, China. Email: [email protected]
Corresponding Author: Xiaohui Xu, Ph.D. 1225 Center Drive, Room 3119, Gainesville, FL 32610-0182 Email: [email protected]
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Abstract Although regulation of emissions is the primary strategy to reduce air pollution-related morbidity, individual-level interventions are also helpful in mitigating health impacts. We used data from 2007-2008 National Health and Nutrition Examination Survey to study the prevalence
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of individual-level action among the U.S. adult population if informed of air pollution, and to see if this differed by demographic and health factors. Only 13.5% (CI: 11.6-15.4%) of participants aware of air quality reported changing their individual behaviors. Male sex (AOR: 0.66, CI: 0.56-0.77), and those without cardiovascular disease (AOR: 0.58, CI: 0.47-0.71) were least likely to take action. Results show that individual action was infrequent among the population. Health promotion of individual intervention is necessary, and this effort may need to target specific subgroups of the population. Further studies on effective individual interventions are needed.
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ACCEPTED MANUSCRIPT Introduction Numerous epidemiological studies have consistently shown air pollution to be associated with an increased risk of mortality and morbidity in the general population, including deaths from chronic obstructive pulmonary disease (COPD) and heart disease.1,2 Annually, over 600,000 people die of heart disease3 and over 125,000 die of COPD4 in the United States.
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Because of these significant impacts of these diseases on health, reducing air pollution exposure has clear health benefits. Air pollution is a macro environmental problem which is caused by natural events such as wild fires and volcano eruption as well as human activities. Major anthropogenic sources of air pollution include the burning of fossil fuels such as coal, petroleum, and natural gas. 5 As industrialization progresses, anthropogenic sources of air pollution through traffic-related and industrial emissions, such as power plants, are becoming an increasing problem. 6 Traditionally, emission-based air pollution control has been regarded as the fundamental way to improve air quality and to reduce the adverse health effects of air pollution. Interventions at individual level such as behavioral change have largely been overlooked as a strategy to reduce air pollution exposure. Although there is no doubt that improving air quality is still the primary effort in reducing adverse health effects of air pollution, individual actions such as wearing masks, reducing outdoor activities, and using air filters might also be necessary to reduce air pollution exposure, particularly during a significant air pollution episode.7 Overall air quality has improved over the past decades in the U.S. following the Clean Air Acts; however, air pollution remains a major environmental problem in some areas of this country.8 Air pollution sources such as traffic exhaust emission, industrial emission and wildfires
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ACCEPTED MANUSCRIPT continue to worsen in some areas. Bad air quality is regularly reported in several areas, and during specific times. Individual intervention is perhaps the easiest manner to reduce exposure and, subsequently, the adverse health impacts of air pollution, as it does not require societal-level change. Furthermore, studies show that subgroups with certain characteristics, such as the elderly and those with certain comorbidities, are particularly sensitive to health effects of air pollution.9-
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Therefore, individual-level intervention might be particularly critical for these vulnerable
subpopulations to reduce exposure and their negative health consequences. However, few studies have determined whether individuals change their behaviors based on air pollution advisories or bad air quality and what factors are associated with this change. Those that do exist find that those most at risk and those that receive physician recommendations are more likely to change behaviors. These studies, however, are outdated or focus on a subsample of the populations (e.g. those with asthma or Hispanics only).12-17 To our knowledge, there are no current studies that investigate individuals’ likelihood of taking action during periods of bad air quality in the general population. This study used 2007-2008 data from the National Health and Nutrition Examination Survey (NHANES) to investigate how many individuals take actions to protect themselves from air pollution when they were informed of bad air quality among the U.S. adult population. Previous epidemiologic studies have found that certain subgroups, including those with low SES, may be more susceptible to air pollutants.18,19 Therefore our secondary aim is to evaluate if any subgroups of the population as defined by demographic factors and health conditions are more likely to take preventive actions. The ultimate objective is to provide health agencies with important information that can aid in the development of health education interventions to
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ACCEPTED MANUSCRIPT promote individual-level efforts in reducing air pollution exposure and further reducing the burden of diseases related to air pollution exposures.
Methods Data for this study were obtained from the 2007-2008 cycle of the NHANES. The
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NHANES uses a representative sample of the non-institutionalized population of the United States of all ages, recruiting around 10,000 participants each cycle. Basic demographic information is collected along with answers to medical measurements, laboratory tests, and a questionnaire on health behaviors.20 A total of 10,149 participants were surveyed in this cycle. Participants under 20 years older (n=4,055) were not considered in this study because information on respiratory conditions and cardiovascular disease was not available for that age group, and this study is interested in investigating whether those who should be heeding to advisories are doing so. In the 2007-2008 cycle, participants were asked the following question: “During the past 12 months, when {you thought/SP thought} or {were/was} informed air quality was bad, {did you/did SP} do anything differently?” There were 5935 people over 20 years older who were asked this question. Respondents who answered “yes” or “no” to this were included in this study. Those who replied that they “never thought/not informed bad air quality” and those who answered “don’t know” were excluded from this analysis. Therefore, a total of 5,434 respondents were included in the study. Covariates selected included age (classified as 20-29, 30-49, 50-69, and 70 or older), gender, race/ethnicity (non-Hispanic White, non-Hispanic Black, Mexican-American, and others), education (less than high school, high school graduate or GED completion, and college
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ACCEPTED MANUSCRIPT or above), ratio of family income to poverty (categorized as tertiles, low: ≤142% of poverty level, medium: 142% to 330% of pervert level, or high: >330% of poverty level), smoking status (currently smokes, smoked in the past, or never smoked), self-reported general health status (dichotomized as excellent/very good/good versus fair/poor). Age was categorized as such to reflect different outdoor behaviors and disease risk. For instance, those older than 50 are more
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likely to have heart disease than those who are younger21 and it is possible that those in their 30s and 40s have different outdoor behaviors than those 20-29 due to employment. Additionally, individuals aged 70 and older possibly have different outdoor habits than those who are younger than 70. From the medical conditions section of the questionnaire, we combined questions about asthma, emphysema, and chronic bronchitis into reporting having respiratory disease (dichotomized as ever had versus never had), and questions about congestive heart failure, coronary heart disease, angina/angina pectoris, heart attack, and stroke into reporting having cardiovascular disease (dichotomized as ever had versus never had). These questions were asked in the following manner: “Has a doctor or other health professional ever told 22 that {you have/s/he/SP has}…” followed by the health condition of interest; therefore included both active and inactive conditions. To indicate if a person ever had a respiratory or cardiovascular condition (yes vs. no) a separate variable was created that combined the two conditions above. All covariates were chosen based on prior literature12-17 and knowledge of vulnerable population with a higher risk to air pollution. We also investigated which actions participants responded to doing differently during a bad air pollution day. Respondents who reported changing behavior were asked: “Which of these {did you/did SP} do differently?” They could choose from the following options: wore a mask, spent less time outdoors, avoided roads that have heavy traffic,
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ACCEPTED MANUSCRIPT did less strenuous activities, took medication, closed windows of house, drove car less, canceled outdoor activities, exercised indoors instead of outside, used buses, trains, or subways, other (specify), refused, or don’t know. Though participants could chose more than one action, each was provided individually as either “yes” or “missing” for those not asked the question. Participants who responded anything other than “yes” to the question regarding whether or not
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they changed behavior were not asked this question. Statistical analyses were conducted using SAS version 9.2.23 Because of the complex sampling design of the NHANES, analyses that accounted for clustering, weighting, and stratification were used (proc surveyfreq and proc surveylogistic). Unadjusted and adjusted logistic regression models were created for all covariates. Odds ratios and 95% confidence intervals (95% CI) were calculated for both crude models (OR), and adjusted model (AOR).
Results Of the 5434 participants included in this study, 13.4% (n=727) reported changing their behavior due to bad air quality. Those who reported changing behavior compared to those who did not were more often in their 50s and 60s (16.6% versus 7.3% of ages 20-29, 13.7% of ages 30-49, and 14.8% of ages 70 and over), were more likely to be female (16.1% versus 10.7% of males), and more likely to be a college graduate or above (15.6% versus 11.3% who are high school graduates or possess a GED, and 10.7% who have less than a high school education) and have high family income (15.1% versus 12.7% with medium family income, and 11.7% with low family income). Respondents who reported changing their behavior were more likely to report a
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ACCEPTED MANUSCRIPT respiratory disease (21.5% versus 11.6%), and more likely to report a cardiovascular disease (17.9% versus 11.6%) (Table 1). Table 2 shows the weighted percentages of individual behaviors taken by those who were aware of bad air quality. Those who took no actions comprise the majority of the population at 86.5%. The majority of those who did take an individual action in response to air pollution
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responded that they spent less time outdoors (8.8%) or wore a mask (1.4%). Other actions included closing windows, canceling outdoor activities, and using or changing air filters among others. Unadjusted associations between changing behavior due to bad air quality and demographic, health behaviors, and health status are displayed in Table 3. Compared to the 2029 age group, all other age groups had a significantly higher crude odds ratio of changing behaviors (OR: 2.02, CI: 1.14-3.59 for those 30-49, OR: 2.53, CI: 1.44-4.45 for those 50-69, and OR: 2.20, CI: 1.27-3.81 for those 70 and over). Male respondents were at lower odds of taking any action compared to female respondents (OR: 0.62, CI: 0.54-0.72). Mexican-Americans also had statistically significant lower odds than Whites of changing behaviors due to bad air quality (OR: 0.49, CI: 0.28-0.86). College graduates were at a significantly higher odds of changing behaviors (OR: 1.54, CI: 1.14-2.09) compared to those with less than a high school education. Those reporting neither respiratory disease nor cardiovascular disease were less likely than those who reported a respiratory or cardiovascular disease to report changing their behaviors (OR: 0.54, CI: 0.45-0.66). The multivariable model was adjusted for age group, gender, race/ethnicity, education, family income, and having either respiratory disease or cardiovascular disease (Table 3). After
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ACCEPTED MANUSCRIPT adjustment, all age groups and college graduates had significantly higher odds of reporting behavior change. Those in the 50-69 age group had the highest odds of changing behavior (AOR: 2.49, CI: 1.39-4.44) when compared to those in the 20-29 age group. Males and those who did not have a respiratory or cardiovascular disease had significantly lower odds of reporting behavior change compared to females and those who did have either of respiratory or
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cardiovascular disease (AOR: 0.66, CI: 0.56-0.77 and AOR: 0.58, CI: 0.47-0.71, respectively).
Discussion According to results, a small proportion of the study population (13.4%) reported changing health behaviors due to bad air quality or air advisories. This is not reflective of a lack of knowledge or awareness about the issue as the NHANES provides an option for those who did not think about air pollution or were not aware of advisories.24 What this may show is a lack of awareness regarding potential negative outcomes of air pollution. Interestingly, groups that most likely obtain recommendations regularly, such as older respondents and those with respiratory or heart disease, showed an increased odds ratio of reporting a change in behavior due to bad air quality when adjusting for other covariates. This indicates that of those who are heeding warnings and taking action a large proportion belong to these vulnerable groups. However, the vast majority of the study population (86.5%) reported not changing health behaviors due to bad air quality or air advisories, indicating that a large proportion of those who belong to these susceptible populations are not taking individual action. Males and Mexican-Americans were less likely to report a change in behavior after adjustment for other factors, although the latter was not statistically significant after adjusting for
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ACCEPTED MANUSCRIPT other covariates. One plausible explanation for a lack of change in behavior is that previous studies have found that men are less susceptible than women to the effects of air pollution. 25,26 This may suggest that the decreased response to air pollution may stem from having fewer symptoms associated with it. Hispanics have been shown to be less concerned with the effects of air pollution and less cognizant of it than non-Hispanic whites, which varied with levels of
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acculturation.16 This study could not directly assess the effects of acculturation; however, variables that were controlled for such as age, education and family income may be proxies for how an individual has assimilated into the culture (would tend to be middle aged, higher education, higher income). Regardless, results did show an independent negative association between Mexican-Americans, a subgroup of the Hispanic ethnicity, and taking an action to protect oneself from air pollution, which indicates that culture may play a role on the perception of air pollution risk. Lastly, high education was a significantly associated with changing individual behaviors when aware of air pollution. This was true even after family income was included in the analysis, indicative that there may be reasons other than the possibility that those with higher education are more likely to have access to better healthcare and medical advice due to higher socioeconomic status. Though differences between sociodemographic groups are small in that overall report of behavior change is small, these results provide preliminary evidence that certain groups may be even less likely to take action during episodes of bad air pollution than others, and may benefit from interventions. Studies that are available regarding air pollution perception and behavior are either outdated or not generalizable. However, the available literature does suggest that respondents with certain characteristics are more likely to change behaviors than those others. For instance,
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ACCEPTED MANUSCRIPT Evans et al found that those who are most at risk for the negative impacts of air pollution are the ones who are most likely to report compliance with advisories.13 In this study’s sample, the same finding holds true for those who reported ever having respiratory disease or a cardiovascular disease. Similarly, one recent study done on the Behavioral Risk Factor Surveillance System (BRFSS) did find an association between being aware of media alerts and physician
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recommendations and a change in behavior among adults with asthma.17 However this study conducted by Wen and colleagues does not include other groups beyond those with asthma and is limited only to six states in the United States, which cannot be assumed to be generalizable to the entire population. Another study found that concern for air pollution was inversely associated with age; that is, younger people tended to be more concerned about air pollution. 12 In the present study, those in the older groups were the more likely to change behavior when compared to the youngest group. This does not imply that younger respondents were unconcerned with air pollution, simply that they were less likely to change behavior. This may be due to certain responsibilities such as school or work taking precedence over staying indoors in episodes of bad air quality. Another possibility is that though a general concern for air quality is present, awareness of the potential health effects is lacking. This study has several limitations. Because there was no information on perceptions towards air pollution or whether conditions listed were current or happened in the past, this study cannot assess if a lack of response to bad air quality is due to a lack of concern with the potential health effects. For instance, those with a history of asthma that occurred many years prior to the study may be less concerned with air pollution and less likely to take action than those with a recent diagnosis of asthma, but this study cannot differentiate these groups. Also, the data set had
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ACCEPTED MANUSCRIPT a large amount of missing data. However, the current study was not able to assess the direction of this bias because of lack of information. We also cannot ascertain that the question regarding behavior change is measuring actual behavior change. Though information from the NHANES is collected by highly trained staff with strict protocols, there is always a possibility for bias with non-validated self-reported outcomes, in other words, we cannot verify if an individual actually
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performed the task he or she reported to have done. This bias is likely non-differential, which would bias our results towards the null. With the publicly available NHANES dataset, this study cannot adjust for area in which the respondent lives. It may be that those who live in rural areas are less likely to think about air quality and have different characteristics than those who live in urban areas, which may confound results. Similarly, many other covariates, such as occupation, local policy efforts, and individual knowledge, which may significantly impact a person’s response to bad air quality advisories, are not available in the dataset. Despite these limitations, this study also had several strengths. One, it uses nationally representative data. Therefore, this is likely to be generalizable to the United States population. The data set also has a fairly large sample size, which makes it unlikely that this study was underpowered and missed any important significant differences. Lastly, data collected for the NHANES was used, which ensures that data were obtained using rigorous sampling and interviewing procedures. Future studies should investigate the outlets from which individuals are getting information on air pollution quality. We could not ascertain actual media used using the present dataset, but this type of data could be integral to figuring out why certain individuals responded to not receiving any information on air quality. Another area of focus is on reasons why a person did not change behavior regarding air pollution, or similarly if they did or did not think air
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ACCEPTED MANUSCRIPT pollution affected them and why. Potential reasons may be lack of knowledge about medical recommendations or negative health outcomes, inability to change daily routines, or, as Johnson demonstrated, a lack of preoccupation with air pollution that may stem from cultural perceptions.16 If the public health community can pinpoint the actual reason for not following recommendations to avoid bad air pollution episodes, then steps can be taken to target those
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individuals and their barriers. Consequently, research should also focus on effective methods that individuals can apply to protect themselves from and avoid air pollution. For instance, one study has found that women who consume greater amounts of fish during pregnancy confer some protection to the fetus against the harmful effects of air pollution.27 Lastly, future studies should be done regarding children’s exposure to air pollution and individual actions taken to protect them from it. This study was only able to include adults aged 20 years and older; but, as mentioned previously, children are also vulnerable to the negative effects of air pollution. This study found that certain groups are more likely to change behaviors when they are aware of bad air quality. These included the elderly and those with either respiratory or cardiovascular disease. Although this shows that some of the most susceptible groups are in fact protecting themselves against air pollution, over 85% of the population is not taking any action. This includes the majority of those who are highly susceptible. Interventions need be developed to bring awareness to the entire population of the detrimental effects of air pollution exposure, and they should specifically target males, Mexican-Americans, and those with less education in addition to groups that are already known to be vulnerable. Acknowledgements Claudia Lissåker is funded through a fellowship from the University of Florida Graduate School.
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Table 1 Weighted percentage of persons who changed behavior due to bad air quality among U.S adults, 2007-2008 NHANES (N=5,434) Variable
Number of sampled
Total sample
persons who
Weighted percentage (95% CI)
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changed behavior Age groups 20-29
55
821
7.3 (3.6-11.0)
30-49
230
1801
13.7 (11.3-16.2)
50-69
300
1776
16.6 (12.9-20.3)
70+
142
1036
14.8 (12.4-17.1)
Male
292
2660
10.7(8.9-12.5)
Female
435
2774
16.1 (13.8-18.5)
Non-Hispanic White
382
2528
14.3 (11.7-17.0)
Non-Hispanic Black
170
1200
13.3 (9.4-17.2)
Mexican-Americans
87
914
7.6 (3.3-11.8)
Others
88
792
12.8 (8.3-17.4)
Gender
Race/ethnicity
Education
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