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Impact of medical and behavioural factors on influenza-like illness, healthcare-seeking, and antiviral treatment during the 2009 H1N1 pandemic: USA, 2009–2010

Published online by Cambridge University Press:  25 March 2013

M. BIGGERSTAFF
Affiliation:
Epidemiology and Prevention Branch, Influenza Division, National Center for Immunization and Respiratory Disease, Centers for Disease Control and Prevention, Atlanta, GA, USA
M. A. JHUNG
Affiliation:
Epidemiology and Prevention Branch, Influenza Division, National Center for Immunization and Respiratory Disease, Centers for Disease Control and Prevention, Atlanta, GA, USA
C. REED
Affiliation:
Epidemiology and Prevention Branch, Influenza Division, National Center for Immunization and Respiratory Disease, Centers for Disease Control and Prevention, Atlanta, GA, USA
S. GARG
Affiliation:
Epidemiology and Prevention Branch, Influenza Division, National Center for Immunization and Respiratory Disease, Centers for Disease Control and Prevention, Atlanta, GA, USA Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, GA, USA
L. BALLUZ
Affiliation:
Division of Behavioral Surveillance, Office of Surveillance, Epidemiology, and Laboratory Services, Centers for Disease Control and Prevention, Atlanta, GA, USA
A. M. FRY
Affiliation:
Epidemiology and Prevention Branch, Influenza Division, National Center for Immunization and Respiratory Disease, Centers for Disease Control and Prevention, Atlanta, GA, USA
L. FINELLI
Affiliation:
Epidemiology and Prevention Branch, Influenza Division, National Center for Immunization and Respiratory Disease, Centers for Disease Control and Prevention, Atlanta, GA, USA
Corresponding
E-mail address:
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Summary

We analysed a cross-sectional telephone survey of U.S. adults to assess the impact of selected characteristics on healthcare-seeking behaviours and treatment practices of people with influenza-like illness (ILI) from September 2009 to March 2010. Of 216 431 respondents, 8·1% reported ILI. After adjusting for selected characteristics, respondents aged 18–64 years with the following factors were more likely to report ILI: a diagnosis of asthma [adjusted odds ratio (aOR) 1·88, 95% CI 1·67–2·13] or heart disease (aOR 1·41, 95% CI 1·17–1·70), being disabled (aOR 1·75, 95% CI 1·57–1·96), and reporting financial barriers to healthcare access (aOR 1·63, 95% CI 1·45–1·82). Similar associations were seen in respondents aged ⩾65 years. Forty percent of respondents with ILI sought healthcare, and 14% who sought healthcare reported receiving influenza antiviral treatment. Treatment was not more frequent in patients with high-risk conditions, except those aged 18–64 years with heart disease (aOR 1·90, 95% CI 1·03–3·51). Of patients at high risk for influenza complications, self-reported ILI was greater but receipt of antiviral treatment was not, despite guidelines recommending their use in this population.

Type
Original Papers
Copyright
Copyright © Cambridge University Press 2013

INTRODUCTION

During the 2009 pandemic, the Centers for Disease Control and Prevention (CDC) recommended early empirical influenza antiviral treatment for groups at risk for severe outcomes from influenza A(H1N1)pdm09 virus infection, including persons aged ⩾65 years and persons with underlying medical conditions such as asthma, diabetes, or heart disease [1]. Although evidence suggests that clinicians followed the Advisory Committee on Immunization Practices recommendations for use of antiviral agents in hospitalized patients [Reference Doshi2], little is known about the propensity of high-risk persons in the community to seek healthcare for influenza or how frequently they received antiviral treatment.

We utilized the Behavioral Risk Factor Surveillance System (BRFSS) to describe the characteristics of U.S. adults reporting symptoms consistent with influenza, healthcare-seeking behaviours, and influenza diagnosis and antiviral treatment during the 2009 pandemic.

METHODS

The BRFSS is a state-based, random-digit-dialled telephone survey among the non-institutionalized U.S. population aged ⩾18 years. It is the main source for state-based data on the prevalence of health-risk behaviours, chronic health conditions, and preventive health services related to chronic disease and injury; the survey methodology is described elsewhere [3].

From 1 September 2009 to 31 March 2010, BRFSS respondents in 49 states (excluding Vermont), the District of Columbia (D.C.), and Puerto Rico were interviewed using a module designed to evaluate the presence of symptoms of influenza-like illness (ILI) [Reference Biggerstaff4]. Respondents having fever with either cough or sore throat in the 30 days preceding interview date were defined as having had ILI. To determine if respondents with ILI sought medical care, they were asked if they had visited a healthcare professional for their illness. Respondents with ILI who sought medical care were asked about their clinical diagnosis and whether they were tested for influenza or received antiviral drugs intended for treating influenza (see Table 1 for details of questions in the BRFSS interview).

Table 1. Questions posed to respondents in the Behavioral Risk Factor Surveillance System (BRFSS) interview

ILI, Influenza-like illness.

Self-reported characteristics included demographics, underlying medical conditions, behavioural characteristics, and healthcare access factors. Demographic characteristics evaluated were age; sex; race/ethnicity; educational attainment; and employment status. Underlying medical conditions evaluated were asthma; diabetes (excluding a diagnosis only during pregnancy); heart disease (ever having been diagnosed with myocardial infarction; angina; or coronary heart disease); the World Health Organization's body mass index (BMI) classification (underweight, normal weight, overweight, obese) as calculated from self-reported weight and height. Disability (limited because of physical, mental, or emotional problems or any health problem that requires the use of special equipment) was also recorded. Behavioural factors evaluated were smoking [current smoker (having smoked at least 100 cigarettes and currently smoke every day or some days), former smoker (having smoked at least 100 cigarettes but currently does not smoke), and never smoked (have not smoked at least 100 cigarettes)]; binge drinking (males having ⩾5 drinks on one occasion; females having ⩾4 drinks on one occasion); and average daily alcohol consumption [non-drinker (no alcohol), moderate drinker (⩽2 drinks for men; ⩽1 drink for women); and heavy drinker (>2 drinks for men; >1 drink for women)]. Indicators of healthcare access evaluated were insurance status at the time of interview for those aged 18–64 years; report of having a personal doctor(s); and report of financial barriers to care (episodes in the past year when respondent needed to see a doctor but could not because of cost). Persons who reported current asthma, diabetes, or heart disease were defined as having had a high-risk medical condition.

We used SAS-callable SUDAAN® v. 10 statistical software (Research Triangle Institute, USA) to calculate population-weighted estimates and corresponding standard errors, 95% confidence intervals (CI), odds ratios (OR), and P values, taking into account the complex design of the BRFSS sampling plan. We used linear contrasts and χ 2 tests to evaluate differences in self-reported ILI, healthcare-seeking behaviour, influenza diagnosis and antiviral drug receipt by selected characteristics. P values <0·05 were considered statistically significant. To allow for comparison of the factors evaluated, prevalence estimates were sex- and age-adjusted using the standard year 2000 projected U.S. population when appropriate [Reference Klein and Schoenborn5]. Response rates for BRFSS were calculated using Council of American Survey and Research Organization's (CASRO) guidelines.

We examined independent associations between respondent characteristics and the report of ILI and receipt of antiviral treatment using logistic regression models. These models were stratified by age group (respondents aged 18–64 and ⩾65 years old) because the prevalence of underlying medical conditions, behavioural risk factors, and healthcare access differ by age [Reference Pleis, Ward and Lucas6]. We used the following candidate variables: age group; sex; race/ethnicity; education attainment; employment status; the presence of asthma, diabetes, heart disease, and disability; BMI classification; smoking, binge drinking, and daily alcohol consumption status; insurance status (excluding persons aged ⩾65 years because Medicare serves as their primary source of reimbursement for medical care); report of a personal doctor and financial barriers to care; and report of a clinical influenza diagnosis or an influenza test (for the influenza treatment model only). To develop multivariable models, we included all candidate variables in a logistic model and removed non-significant variables using step-wise elimination, starting with the variable with the smallest magnitude of effect, until all remaining variables had Wald F P values <0·05 or removing an additional variable significantly increased the –2 log likelihood of the model. We evaluated confounding by adding each excluded variable back into the final model individually and examining changes in the β-coefficients of the included variables; if addition of one of the excluded variables caused a change in a β-coefficient of ⩾10%, the variable was retained in the model.

RESULTS

Report of ILI

From September 2009 to March 2010, self-reported ILI data were available from 216 431 respondents. Median survey response rate was 55% (state range 24–74%), calculated as the percentage of persons who completed interviews among all eligible persons, including those who were not contacted. Median cooperation rate was 75% (state range 55–95%), calculated as the percentage of persons who completed interviews among all eligible persons who were contacted.

Of respondents, 8·1% reported ILI in the month before interview [Reference Biggerstaff4]. Compared to respondents not reporting ILI, those with ILI were younger and significantly more likely to be women, as well as less educated, unable to work, or disabled (Table 2). Respondents with ILI were also significantly more likely to have a high-risk condition, be current smokers or binge drinkers, lack health insurance, and report financial barriers to care compared to those who did not report ILI. Regardless of the age group examined, respondents with a high-risk condition reported ILI more often than respondents without a high-risk condition (P<0·01 for all three age groups examined; Fig. 1).

Fig. 1 [colour online]. Comparison between adults aged ⩾18 years with and without high-risk conditions of influenza-like illness (ILI), healthcare seeking for ILI, and influenza antiviral receipt in those who sought care, by age group (Behavioral Risk Factor Surveillance System, 1 September 2009 to 31 March 2010). HR, High-risk respondent (i.e. respondent ever told they had myocardial infarction, angina, coronary heart disease, current asthma, or diabetes).

Table 2. Age- and sex-adjusted characteristics of respondents aged ⩾18 years who did and did not report influenza-like illness (ILI) and healthcare seeking (Behavioral Risk Factor Surveillance System, 1 September 2009 to 31 March 2010)

n.a., Not available.

Values given are% (s.e.).

* Estimate not age- and sex-adjusted since variable includes an age or sex component.

Respondent never told they had myocardial infarction, angina, coronary heart disease, current asthma, or diabetes.

Respondent ever told they had myocardial infarction, angina, coronary heart disease, current asthma, or diabetes.

§ For respondents who reported an influenza test.

Estimate unavailable because influenza testing and the result only ascertained for respondents with ILI who sought medical care.

Multivariable logistic regression models controlling for potential confounders identified several factors independently associated with greater ILI in respondents aged 18–64 and ⩾65 years, including a current or former diagnosis of asthma or heart disease, having a disability, being a current smoker, or reporting financial barriers to healthcare (Tables 3 and 4). Respondents aged 18–64 years who were obese also had increased odds of reporting ILI (Table 3). After adjusting for other factors, the association between ILI and diabetes was increased but not significant in either age group.

Table 3. Characteristics associated with influenza-like illness (ILI) in respondents aged 18–64 years in multivariable analysis (Behavioral Risk Factor Surveillance System, 1 September 2009 to 31 March 2010)

aOR, Adjusted odds ratio.

Table 4. Characteristics associated with influenza-like illness in respondents aged ⩾65 years (Behavioral Risk Factor Surveillance System, 1 September 2009 to 31 March 2010)

aOR, Adjusted odds ratio.

Report of healthcare seeking

Of 14 601 respondents with ILI, 40% sought healthcare for their illness. Compared to respondents who did not seek healthcare, those who did were more likely to be older, female, and unable to work (Table 2). Several high-risk medical conditions and reported disability were also more common in respondents who sought healthcare. In every age group, respondents with high-risk conditions sought healthcare more often than respondents without high-risk conditions (P<0·01 for respondents aged 18–49 and 50–64 years, and P = 0·02 for respondents aged ⩾65 years; Fig. 1). Of respondents who sought healthcare, 32% reported having been tested for influenza and 42% of those tested recalled a positive influenza test result.

Compared to respondents who sought healthcare, those who did not were more likely to be current smokers; be binge, moderate, or heavy drinkers; not have health insurance or a personal doctor; or report financial barriers to healthcare (Table 2).

Report of a clinical influenza diagnosis

Of 6148 respondents with ILI who sought healthcare, 26% received a clinical diagnosis of influenza. None of the underlying medical conditions, behavioural, or healthcare access factors we analysed varied significantly between those who were and were not diagnosed with influenza (data not shown). However, when compared to respondents not receiving an influenza diagnosis, respondents receiving an influenza diagnosis were more likely to be younger (persons aged 18–64 years: 93·7% of respondents with an influenza diagnosis vs. 89·5% of respondents without an influenza diagnosis, P<0·01) and Hispanic (Hispanic: 18·2% of respondents with an influenza diagnosis, 11·8% of respondents without an influenza diagnosis, P = 0·02).

Report of influenza antiviral treatment

Receipt of influenza antiviral treatment was ascertained for 5265 respondents with ILI who sought healthcare. Overall, 14% of respondents and 36% of respondents who received a clinical diagnosis of influenza received influenza antiviral treatment; those receiving antiviral treatment were more likely to have been tested for influenza and received a positive influenza test result (Table 5). Respondents receiving antiviral treatment were also more likely to be younger and employed than respondents who did not receive antiviral treatment. No other underlying conditions, behavioural factors, or healthcare access factors were significantly associated with receipt of antiviral treatment. Notably, having a high-risk condition was not significantly associated with receiving influenza antiviral treatment, regardless of age group (P>0·05 for all three age groups examined, Fig. 1).

Table 5. Age- and sex-adjusted prevalence of characteristics of adults with influenza-like illness who sought healthcare and did/did not report receipt of influenza antiviral drugs (Behavioral Risk Factor Surveillance System, 1 September 2009 to 31 March 2010)

* Estimate not age- and sex-adjusted since variable includes an age or sex component.

Estimate unavailable because the unweighted sample size for the denominator is <50 or the confidence interval half width is >10.

Respondent never told they had myocardial infarction, angina, coronary heart disease, current asthma, or diabetes.

§ Respondent ever told they had myocardial infarction, angina, coronary heart disease, current asthma, or diabetes.

Respondents who reported an influenza test.

Multivariable logistic regression models controlling for potential confounders found an almost 13-fold increased odds of influenza antiviral treatment with an influenza diagnosis in respondents aged 18–64 years (OR 12·7, 95% CI 8·1–20·0) while the effect of an influenza diagnosis was less than half this value for respondents aged ⩾65 years (OR 5·50, 95% CI 2·5–12·0) (see Supplementary Tables S1, S2). Additionally, receiving an influenza test was associated with greater odds of influenza antiviral treatment for respondents aged 18–64 years (OR 2·7, 95% CI 1·8–4·1) and ⩾65 years old (OR 2·4, 95% CI 1·1–5·4). Respondents aged 25–34 years (OR 2·1; 95% CI 1·0–4·2) or who reported heart disease (OR 1·90; 95% CI 1·0–3·5) had increased odds of receiving influenza antiviral treatment, and persons reporting unemployment had decreased odds of receiving influenza antiviral treatment (OR 0·4, 95% CI 0·2–0·88). Respondents aged ⩾65 years who reported other employment (unemployed, homemaker, student, or retired) (OR 0·30, 95% CI 0·11–0·85) or having no personal doctor (OR 0·02, 95% CI 0·00–0·48) had decreased odds of receiving influenza antiviral treatment.

COMMENT

This large study of community-dwelling persons during the 2009 pandemic found that prevalence of ILI and healthcare seeking for ILI varied by underlying medical condition, behavioural factors, and healthcare access factors of respondents. In contrast, treatment of influenza with antiviral agents was similar in patients with and without many of the high-risk conditions evaluated and was decreased in the unemployed and patients aged ⩾65 years.

Younger adults, current smokers, and those reporting asthma, heart disease, or disability were more likely to report ILI, suggesting an increased susceptibility to ILI in these groups. Increased illness from H1N1pdm09 virus infection in younger persons is well documented [Reference Shrestha7, Reference Hancock8], but to our knowledge, no study has systematically assessed influenza susceptibility or the likelihood of developing ILI in those with high-risk conditions, and behavioural risk factors (e.g. smoking or heavy alcohol consumption) [Reference Fiore9]. Limited evidence can be found in vaccine trials, community studies, or outbreak investigations, which suggest that smoking [Reference Finklea, Sandifer and Smith10Reference Waldman15], asthma [Reference Miller16Reference Smolderen20], obesity [Reference Kropp19], and heart disease [Reference Currier21] are associated with either increased ILI, increased influenza, or an increased likelihood of developing ILI, although findings are not specific to H1N1pdm09 or the age groups evaluated in this study. Moreover, other studies fail to confirm these relationships [Reference Monto, Higgins and Ross22Reference Govaert24].

Our results also suggest that adherence by healthcare providers to antiviral treatment recommendations during the pandemic was poor in the outpatient setting. Receipt of antiviral treatment was uncommon in adults with ILI who sought care for their illness and was not significantly affected by the presence of most high-risk conditions. In this survey, asthma, diabetes, heart disease, and age ⩾65 years were associated with greater healthcare seeking for ILI. However, no high-risk condition, except heart disease in respondents aged 18–64 years, was significantly associated with greater receipt of influenza antiviral treatment compared to persons without these high-risk conditions. Additionally, although not significant, the effect of a clinical diagnosis of influenza on receipt of antiviral treatment in respondents aged ⩾65 years was half that of respondents aged 18–64 years, and overall proportions of influenza antiviral treatment in this age group were low. For adults, these underlying medical conditions, as well as age ⩾65 years, are known to increase the risk for complications from influenza [Reference Fiore9]. During the 2009 pandemic, early antiviral treatment was recommended for persons with high-risk conditions, regardless of influenza severity [1]. Prompt treatment with antiviral medications has been shown to reduce the risk of complications from seasonal influenza [Reference Kaiser25, Reference Hernan and Lipsitch26], and treatment for persons with high-risk conditions should not be delayed while awaiting results of diagnostic testing. In this study, however, the likelihood of receiving antiviral treatment was much greater in those who received an influenza test than in those who did not, although we were unable to distinguish patients who received antiviral treatment concurrently with an influenza test being ordered from those who received treatment after an influenza test result was known. The widespread reports that persons aged ⩾65 years may have some pre-existing immunity to H1N1pdm09 may have contributed to the reduction in influenza antiviral treatment, as well as the small decrease in influenza diagnosis compared to those aged <65 years. However, an explanation for the lack of increased antiviral receipt in those with high-risk conditions remains unclear.

Less than half of respondents overall sought healthcare for ILI, and healthcare access factors reduced healthcare-seeking behaviour. Lack of insurance (for respondents aged 18–64 years), a personal doctor, or the ability to afford healthcare reduced healthcare seeking significantly in the nearly 15000 respondents with ILI in this study. Additionally, although unemployed respondents were not less likely to seek healthcare, those who did were less likely to receive influenza antiviral treatment. Thus, it is possible that access to appropriate medical care, including receipt of influenza antiviral drugs, may have been affected for some persons by their healthcare access or employment status. Unemployment and lack of medical insurance have been associated with delayed or missed medical care or prescriptions because of cost [Reference Driscoll and Bernstein27, Reference Lasser, Himmelstein and Woolhandler28] while adults with a personal doctor experience improved health outcomes [Reference Starfield and Shi29]. Furthermore, the U.S. unemployment rate may be associated with increased state reports of widespread influenza [Reference Cornwell30], and more severe outcomes from seasonal and H1N1pdm09 influenza infection have been observed in high poverty areas [Reference Balter31, Reference Yousey-Hindes and Hadler32]. If receipt of appropriate medical care was affected by access to healthcare or unemployment status, then the 10% of adults who reported unemployment [33], the 15% of adults who reported foregoing medical care because of cost [34], and the almost 18% of persons aged 18–64 years who reported a lack of health insurance [34] during the 2009 pandemic could represent an unexplored risk group. To prepare for future pandemics, a better understanding of how reduced healthcare access may affect the appropriate treatment of persons with ILI is needed.

Interestingly, we also found that respondents who reported financial barriers to healthcare were more likely to report ILI, even after controlling for age, medical conditions, and employment. The reasons for this are unclear, but adults who report financial barriers to healthcare are more likely to have chronic conditions or poor health status [Reference Schoen35]. Therefore, these respondents may have had other chronic conditions not evaluated in this study that place them at increased risk for influenza or may represent persons with poorly controlled chronic medical conditions.

This report is subject to several limitations. First, data in this study are self-reported and subject to recall and social desirability bias. Therefore, report of a clinical diagnosis of influenza or receiving an influenza diagnostic test may not represent actual clinical practice or decision-making. However, most estimates for chronic disease prevalence and high-risk behaviours from the BRFSS are similar when compared to other national surveys [Reference Nelson36]. Additionally, the trends in ILI and receipt of influenza antiviral treatment in this report are similar to independent U.S. estimates of the number of H1N1pdm09 cases and the number of antiviral drug prescriptions filled for the treatment of influenza [Reference Shrestha7, Reference Atkins37]. Second, we only assessed risk factors available in the BRFSS during the 2009–2010 influenza season; we did not have information on other medical conditions known to confer increased risk for complications from influenza, which range in prevalence from <1% to 4·4% in the U.S. adult population [Reference Fiore9, Reference Fowlkes38]. Therefore, some persons with high-risk conditions could be misclassified as not having high-risk medical conditions. However, we included those who reported any type of disability to capture some of these persons [39]. Third, we did not ascertain the duration between illness onset and first healthcare encounter for persons reporting ILI. Effectiveness of influenza antiviral treatment declines between 2 and 7 days after illness onset [Reference Fiore9], and physicians may be less likely to prescribe antiviral treatment to individuals presenting during this period. Thus, the proportion of respondents receiving influenza antiviral treatment we report may underestimate the fraction that would have been treated if presenting earlier. The 2010–2011 BRFSS ILI survey contains the time from illness onset to first healthcare encounter; inclusion of these data will help address this weakness in future analyses. Fourth, BRFSS data are collected only from households with a landline telephone, and our study is subject to selection bias resulting from exclusion of households with only cellular phones [40]. Finally, the BRFSS is a household survey that does not collect information from persons in institutions, nursing homes, long-term-care facilities, and correctional institutions. Therefore, the results presented in this analysis do not generalize to these populations.

In conclusion, our findings suggest a higher risk for symptomatic influenza in persons with certain underlying medical conditions, behavioural factors, and healthcare access restrictions. It also identified areas of the 2009 pandemic response that could have been improved. Despite recommendations to administer prompt antiviral treatment to high-risk individuals or persons aged ⩾65 years with suspected or confirmed influenza, receipt of influenza antivirals was not significantly higher for these groups. The data on antiviral use in high-risk or persons aged ⩾65 years presented in this report can inform communication efforts to physicians who care for these populations and improve compliance with antiviral treatment guidance. Finally, reduced healthcare access observed in this report may have delayed or prevented appropriate medical care for some respondents with ILI; future pandemic planning efforts should consider individual barriers to healthcare when designing response strategies.

SUPPLEMENTARY MATERIAL

For supplementary material accompanying this paper visit http://dx.doi.org/10.1017/S0950268813000654.

ACKNOWLEDGEMENTS

The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.

DECLARATION OF INTEREST

None.

References

1. Centers for Disease Control and Prevention. Updated interim recommendations for the use of antiviral medications in the treatment and prevention of influenza for the 2009–2010 season (http://www.cdc.gov/h1n1flu/recommendations.htm). Accessed 2012.Google Scholar
2. Doshi, S, et al. Description of antiviral treatment among adults hospitalized with influenza before and during the 2009 pandemic: United States, 2005–2009. Journal of Infectious Diseases 2011; 204: 18481856.CrossRefGoogle ScholarPubMed
3. Centers for Disease Control and Prevention. Behavioral Risk Factor Surveillance System Operational and User's Guide (ftp://ftp.cdc.gov/pub/Data/Brfss/userguide.pdf). Accessed 2012.Google Scholar
4. Biggerstaff, M, et al. Self-reported influenza-like illness and receipt of influenza antiviral drugs during the 2009 pandemic, United States, 2009–2010. American Journal of Public Health 2012; 102: e2126.CrossRefGoogle ScholarPubMed
5. Klein, RJ, Schoenborn, CA. Age adjustment using the 2000 projected U.S. population. Healthy People 2010 Statistical Notes 2001; 20: 110.Google Scholar
6. Pleis, JR, Ward, BW, Lucas, JW. Summary health statistics for U.S. adults: National Health Interview Survey, 2009. Vital and Health Statistics 2010; 10: 1207.Google Scholar
7. Shrestha, SS, et al. Estimating the burden of 2009 pandemic influenza A (H1N1) in the United States (April 2009–April 2010). Clinical Infectious Diseases 2011; 52 (Suppl. 1): S7582.CrossRefGoogle Scholar
8. Hancock, K, et al. Cross-reactive antibody responses to the 2009 pandemic H1N1 influenza virus. New England Journal of Medicine 2009; 361: 19451952.CrossRefGoogle ScholarPubMed
9. Fiore, AE, et al. Antiviral agents for the treatment and chemoprophylaxis of influenza – recommendations of the Advisory Committee on Immunization Practices (ACIP). Morbidity and Mortality Weekly Report 2011; 60: 124.Google Scholar
10. Finklea, JF, Sandifer, SH, Smith, DD. Cigarette smoking and epidemic influenza. American Journal of Epidemiology 1969; 90: 390399.CrossRefGoogle ScholarPubMed
11. Kark, JD, Lebiush, M. Smoking and epidemic influenza-like illness in female military recruits: a brief survey. American Journal of Public Health 1981; 71: 530532.CrossRefGoogle ScholarPubMed
12. Kark, JD, Lebiush, M, Rannon, L. Cigarette smoking as a risk factor for epidemic A(H1N1) influenza in young men. New England Journal of Medicine 1982; 307: 10421046.CrossRefGoogle ScholarPubMed
13. MacKenzie, JS, MacKenzie, IH, Holt, PG. The effect of cigarette smoking on susceptibility to epidemic influenza and on serological responses to live attenuated and killed subunit influenza vaccines. Journal of Hygiene (London) 1976; 77: 409417.CrossRefGoogle ScholarPubMed
14. Nicholson, KG, Kent, J, Hammersley, V. Influenza A among community-dwelling elderly persons in Leicestershire during winter 1993–4; cigarette smoking as a risk factor and the efficacy of influenza vaccination. Epidemiology and Infection 1999; 123: 103108.CrossRefGoogle ScholarPubMed
15. Waldman, RH, et al. An evaluation of influenza immunization: influence of route of administration and vaccine strain. Bulletin of the World Health Organization 1969; 41: 543548.Google ScholarPubMed
16. Miller, EK, et al. Influenza burden for children with asthma. Pediatrics 2008; 121: 18.CrossRefGoogle ScholarPubMed
17. Hirota, Y, et al. Various factors associated with the manifestation of influenza-like illness. International Journal of Epidemiology 1992; 21: 574582.CrossRefGoogle ScholarPubMed
18. Gordon, A, et al. Prevalence and seasonality of influenza-like illness in children, Nicaragua, 2005–2007. Emerging Infectious Diseases 2009; 15: 408414.CrossRefGoogle ScholarPubMed
19. Kropp, RY, et al. Pandemic (H1N1) 2009 outbreak at Canadian Forces cadet camp. Emerging Infectious Diseases 2010; 16: 19861989.CrossRefGoogle ScholarPubMed
20. Smolderen, KG, et al. Personality, psychological stress, and self-reported influenza symptomatology. BMC Public Health 2007; 7: 339.CrossRefGoogle ScholarPubMed
21. Currier, M, et al. Influenza vaccine efficacy in a Maryland nursing home. Maryland Medical Journal 1988; 37: 781783.Google Scholar
22. Monto, AS, Higgins, MW, Ross, HW. The Tecumseh study of respiratory illness. VIII. Acute infection in chronic respiratory disease and comparison groups. American Review of Respiratory Disease 1975; 111: 2736.Google ScholarPubMed
23. Cruijff, M, et al. The effect of smoking on influenza, influenza vaccination efficacy and on the antibody response to influenza vaccination. Vaccine 1999; 17: 426432.CrossRefGoogle ScholarPubMed
24. Govaert, TM, et al. The efficacy of influenza vaccination in elderly individuals. A randomized double-blind placebo-controlled trial. Journal of the American Medical Association 1994; 272: 16611665.CrossRefGoogle ScholarPubMed
25. Kaiser, L, et al. Impact of oseltamivir treatment on influenza-related lower respiratory tract complications and hospitalizations. Archives of Internal Medicine 2003; 163: 16671672.CrossRefGoogle ScholarPubMed
26. Hernan, MA, Lipsitch, M. Oseltamivir and risk of lower respiratory tract complications in patients with flu symptoms: a meta-analysis of eleven randomized clinical trials. Clinical Infectious Diseases 2011; 53: 277279.CrossRefGoogle ScholarPubMed
27. Driscoll, AK, Bernstein, AB. Health and access to care among employed and unemployed adults: United States 2009–2010. Hyattsville, MD, USA: National Center for Health Statistics, 2012 (NCHS data brief, no. 83).Google Scholar
28. Lasser, KE, Himmelstein, DU, Woolhandler, S. Access to care, health status, and health disparities in the United States and Canada: results of a cross-national population-based survey. American Journal of Public Health 2006; 96: 13001307.CrossRefGoogle ScholarPubMed
29. Starfield, B, Shi, L. The medical home, access to care, and insurance: a review of evidence. Pediatrics 2004; 113: 14931498.Google Scholar
30. Cornwell, B. Unemployment and widespread influenza in America, 1999–2010. Influenza and Other Respiratory Viruses 2012; 6: 6370.CrossRefGoogle ScholarPubMed
31. Balter, S, et al. Pandemic (H1N1) 2009 surveillance for severe illness and response, New York, New York, USA, April–July 2009. Emerging Infectious Diseases 2010; 16: 12591264.CrossRefGoogle Scholar
32. Yousey-Hindes, KM, Hadler, JL. Neighborhood socioeconomic status and influenza hospitalizations among children: New Haven County, Connecticut, 2003–2010. American Journal of Public Health 2011; 101: 17851789.CrossRefGoogle Scholar
33. Bureau of Labor Statistics. Labor force statistics from the current population survey (http://data.bls.gov/timeseries/LNS14000000). Accessed 2012.Google Scholar
34. Centers for Disease Control and Prevention. Behavioral risk factor surveillance system survey data (http://apps.nccd.cdc.gov/s_broker/WEATSQL.exe/weat/freq_analysis.hsql?survey_year=2009). Accessed 2012.Google Scholar
35. Schoen, C, et al. Insured but not protected: how many adults are underinsured? Health Affairs (Millwood) 2005; Suppl. Web Exclusives: W5-289-W285-302.CrossRefGoogle ScholarPubMed
36. Nelson, DE, et al. A comparison of national estimates from the National Health Interview Survey and the Behavioral Risk Factor Surveillance System. American Journal of Public Health 2003; 93: 13351341.CrossRefGoogle ScholarPubMed
37. Atkins, CY, et al. Estimating effect of antiviral drug use during pandemic (H1N1) 2009 outbreak, United States. Emerging Infectious Diseases 2011; 17: 15911598.CrossRefGoogle Scholar
38. Fowlkes, AL, et al. Epidemiology of 2009 pandemic influenza A (H1N1) deaths in the United States, April-July 2009. Clinical Infectious Diseases 2011; 52 (Suppl. 1): S6068.CrossRefGoogle ScholarPubMed
39. Centers for Disease Control and Prevention. Prevalence and most common causes of disability among adults – United States, 2005. Morbidity and Mortality Weekly Report 2009; 58: 421426.Google ScholarPubMed
40. Centers for Disease Control and Prevention. Methodologic changes in the Behavioral Risk Factor Surveillance System in 2011 and potential effects on prevalence estimates. Morbidity and Mortality Weekly Report 2012; 61: 410413.Google ScholarPubMed
Figure 0

Table 1. Questions posed to respondents in the Behavioral Risk Factor Surveillance System (BRFSS) interview

Figure 1

Fig. 1 [colour online]. Comparison between adults aged ⩾18 years with and without high-risk conditions of influenza-like illness (ILI), healthcare seeking for ILI, and influenza antiviral receipt in those who sought care, by age group (Behavioral Risk Factor Surveillance System, 1 September 2009 to 31 March 2010). HR, High-risk respondent (i.e. respondent ever told they had myocardial infarction, angina, coronary heart disease, current asthma, or diabetes).

Figure 2

Table 2. Age- and sex-adjusted characteristics of respondents aged ⩾18 years who did and did not report influenza-like illness (ILI) and healthcare seeking (Behavioral Risk Factor Surveillance System, 1 September 2009 to 31 March 2010)

Figure 3

Table 3. Characteristics associated with influenza-like illness (ILI) in respondents aged 18–64 years in multivariable analysis (Behavioral Risk Factor Surveillance System, 1 September 2009 to 31 March 2010)

Figure 4

Table 4. Characteristics associated with influenza-like illness in respondents aged ⩾65 years (Behavioral Risk Factor Surveillance System, 1 September 2009 to 31 March 2010)

Figure 5

Table 5. Age- and sex-adjusted prevalence of characteristics of adults with influenza-like illness who sought healthcare and did/did not report receipt of influenza antiviral drugs (Behavioral Risk Factor Surveillance System, 1 September 2009 to 31 March 2010)

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