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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Respir Med. Author manuscript; available in PMC 2013 June 28.
Published in final edited form as:
PMCID: PMC3695444

Does the relationship between asthma and obesity differ by neighborhood?

Emily S. Tonorezos, MD MPH,1 Adam M. Karpati, MD MPH,2 Yuanjia Wang, PhD,3 and R. Graham Barr, MD DrPH4,5


Asthma and obesity are major public health challenges of increasing importance. The prevalence of obesity (defined as body mass index [BMI] >= 30 kg/ m2) has increased steadily among adults in the United States and Europe.(14) Obesity prevalence approximately doubled from the early 1960's to the late 1990's, increasing from 13.4% to 27.6% among men and from 15.8% to 33.2% among women.(3) During the same time period, asthma prevalence also increased. From 1980 to 1996, self-reported prevalence of current asthma among adults 18 and older in the United States increased from 3.14 to 5.46%.(5)

Although it continues to be debated, the relationship between obesity and asthma has been suggested by a variety of studies in the epidemiological literature,(69) and is unlikely to be explained by changes in physical activity (10) or medication use.(11) Prospective studies suggest that obesity and weight gain increase risk for subsequent diagnosis of asthma among adults, particularly women,(10,12) although discussion continues as to the accuracy of these diagnoses and possible mechanisms underlying the association.(13) Improvement in asthma symptoms(14,15) and lung function(15, 16) after weight loss and weight-reduction surgery (16,17) has also been described. One randomized trial of an 8-week weight loss intervention saw significant improvements in FEV1, FVC, and symptoms maintained for one year after weight loss. (15)

Residents of urban and low-income neighborhoods in the United States are particularly affected by both asthma and obesity. The prevalence of adults and children who reported ever having asthma was 9.7% in the United States in 1997 (5) but was 12.0% in 2003 in New York City.(18) Urban centers such as Chicago, New York, and Phoenix contribute disproportionately to high national asthma mortality rates.(19) Obesity is also more prevalent among low-income neighborhoods.(20) Numerous studies have confirmed the relationship between low socio-economic status, community disadvantage, and obesity in developed nations.(2123)

The aim of our study was to evaluate neighborhood differences in the relationship between asthma and obesity. Given the overlapping epidemics of obesity and adult asthma in low-income neighborhoods, we hypothesized that the population burden of adult asthma attributable to obesity would be greater in low-income than in middle-to-upper-income neighborhoods in New York City.


Study Population

From May to June of 2002, the New York City Department of Health and Mental Hygiene conducted the Community Health Survey, a representative, population-based, random digit-dialed telephone survey of adult residents of the five boroughs of New York City. Trained investigators from the Baruch College survey research unit performed the interviews. One adult (age ≥ 18) was identified from each participating household. Studies were pre-translated into eight other languages. Interviews were discontinued if the quota for that neighborhood had been met. Ten attempts were made to reach each telephone number.(24) An estimated 2.6% of households in New York City did not have telephone service at any given time.(25) The overall cooperation rate was 64%, resulting in an unweighted sample size of 9,674.(26,27)

The current study sample was restricted to respondents age less than 55 years (n=6,664), in order to minimize misclassification with chronic obstructive pulmonary disease (COPD), and to respondents who reported BMI > 15 and < 60 kg/m2 and height > 50 inches (127cm; n=6,119), in order to exclude likely erroneous height and BMI values.

Classification of Neighborhoods

The Community Health Survey used a stratified sample explicitly designed to produce neighborhood-specific estimates. Neighborhoods were defined using the United Hospital Fund's 42 aggregations of New York City zip codes. These aggregates correspond to community planning districts, and were created in consultation with staff from the New York City Department of Health and Mental Hygiene, Department of City Planning, and others.(27) Several neighborhoods were combined in the design phase due to demographic similarity, resulting in a total of 33 neighborhood groups.(28)

The median annual family income for each of the 33 neighborhoods was estimated by using population-weighted zip-code-level data from the 2000 U.S. Census files.(29) Low-income neighborhoods were defined as neighborhoods in the lowest quartile of median family income in New York City.


Survey respondents were asked to report age, gender, race/ethnicity, educational attainment, weight in pounds, and height in inches. Respondents were asked, “About how much do you weigh without shoes?” and “About how tall are you without shoes?” BMI was calculated as weight (kg) divided by height (m) squared. Obesity was defined as BMI ≥ 30. Current asthma was defined as positive answers to both of the questions: “Have you ever been told by a doctor, nurse, or other health professional that you had asthma?” and “During the past 12 months, have you had an episode of asthma or an asthma attack?”(28) Of note, no further respiratory questions were included in the Community Health Survey.

Statistical Analysis

Responses were weighted according to the probability of selection to participate in the survey (number of adults in each household / number of residential phone lines) and post-stratification weight, determined by weighting each record up to the population of the neighborhood, while taking into account the respondent's age, sex, and race. Neighborhood population was estimated using the 2000 U.S. Census files.(29)

We first calculated age-adjusted prevalences of current asthma and obesity weighted by sampling schema and corresponding one-sample 95% confidence intervals. Prevalence differences were calculated as the weighted prevalence of asthma among obese individuals minus the weighted prevalence of asthma among normal-weight individuals. A description of how multivariate risk differences, attributable risks, and risk ratios were calculated can be found in the Supplement.

Analyses were performed using SAS version 9.(30) The study was approved by the Institutional Review Boards of the Department of Health and Mental Hygiene and Columbia University.


The Community Health Survey included 6,119 respondents age 18–54 years with acceptable height and weight measures. This sample corresponded to a weighted population estimate of 3,947,000 persons in New York City. The prevalence of obesity was 16.1% (95% CI: 14.9%, 17.2%) and the prevalence of current asthma was 4.5% (95% CI: 3.9%, 5.1%).

Table 1 shows characteristics of the adult population estimates of New York City from this survey stratified by categories of BMI. Obese and very obese respondents (BMI > 30) were more likely to be of Black or Hispanic race/ethnicity, have lower educational attainment and income, and to have been born in the United States compared to normal weight individuals (BMI 18–25) (p<0.001 for all comparisons). Obese and very obese respondents were less likely to never have smoked (p = 0.075) and to have exercised in the past thirty days (p<0.001).

Table 1
Characteristics of the population of New York City, age 18–54 years, based on Community Health Survey, stratified by categories of body mass index.

Obesity and Asthma in New York City

The age-adjusted prevalence of current asthma was 6.7% among obese (>30 kg/m2) individuals and was 4.0% among normal weight (18–25 kg/m2) individuals, yielding an age-adjusted prevalence difference for current asthma related to obesity of 2.7% (95% CI: 1.0%, 4.4%; p=0.001) across all of New York City. After additional adjustment for age, gender, race/ethnicity, smoking status and educational attainment, the multivariate prevalence difference for current asthma was 2.0% (95% CI: 0.5%, 3.6%; p=0.01).

Multivariate prevalence differences can be interpreted as attributable risks if the observed relationship is assumed to be causal and unique. If this assumption is made, the absolute risk of asthma among obese New Yorkers attributable to obesity was 2.0% (95% CI: 0.5%, 3.6%). The attributable risk percent, which is the percent of asthma cases among obese subjects attributable to obesity, was 33.8% (95% CI: 8.3%, 52.1%). The population attributable risk percent, which represents the percent of asthma attributable to obesity among all (obese and non-obese) New Yorkers, was 8.5% (95% CI: 2.1%, 13.1%).

Neighborhood Characteristics

Median annual family income in low-income neighborhoods was approximately $25,000, compared to approximately $56,000 in middle-to-upper income neighborhoods. Table 2 shows age, gender, race/ethnicity, education, and smoking status in low-income neighborhoods compared to middle-to-upper income neighborhoods. A map illustrating neighborhoods in New York City stratified by median household income (Panel A), prevalence of obesity (Panel B), and prevalence of asthma (Panel C) can be found in the Supplement.

Table 2
Neighborhood characteristics by median income.

The prevalence of obesity was 23.2% (95% CI: 20.9%, 25.6%) in low-income neighborhoods and 13.7% (95%CI: 12.4%, 15.0%) in middle-to-upper-income neighborhoods. The prevalence of current asthma was 5.8% (95% CI: 4.6%, 7.0%) in low-income neighborhoods and 4.1% (95% CI: 3.3%, 4.8%) in middle-to-upper-income neighborhoods.(Table 2)

Obesity and Asthma by Neighborhood Income

In low-income neighborhoods, the prevalence of current asthma was 6.7% among obese individuals and 5.2% among normal-weight individuals, which yielded an age-adjusted prevalence difference of 1.5% (95% CI: −1.1%, 4.5%; p=0.24). In middle-to-upper-income neighborhoods, the prevalence of asthma was 5.7% among obese individuals and 3.5% among normal-weight individuals, which yielded an age-adjusted prevalence difference of 2.2% (95% CI: 0.3%, 4.2%; p=0.03).

After multivariate adjustment for age, gender, and race/ethnicity, the prevalence difference for asthma due to obesity was 1.3% (95% CI: −1.5%, 4.0%; p=0.36) in low-income neighborhoods and 2.0% (95% CI: 0.1%, 3.9%; p=0.04) in middle-to-upper income neighborhoods. Due to modest sample sizes and the modeling approach, the multivariate model did not converge when smoking status and educational attainment were included as covariates. Separate models in which smoking status or educational attainment were retained at the exclusion of other variables, however, did not differ in the direction or magnitude (data not shown).

The corresponding attributable risks, assuming causality, of 1.3% and 2.0% were therefore not higher among obese New York City adults living in low-income neighborhoods compared to in middle-to upper-income neighborhoods, respectively (P=0.66). On a percentage basis, the percent of asthma among obese individuals attributable to obesity was 20.6% (95% CI: −29.9%, 51.5%) in low-income neighborhoods and 37.9% (95% CI: 3.9%, 59.8%) in middle-to-upper-income neighborhoods.

The population attributable risk percent, which is the percent of asthma in the entire population attributable to obesity, was also not greater in low-income neighborhoods (7.3%; 95% CI: −10.6%, 18.3%) than in middle-to-upper-income neighborhoods (7.7%; 95% CI: 0.8%, 12.1%). These results suggest that the risk of asthma attributable to obesity among New Yorkers in low-income neighborhoods was not greater than that among New Yorkers in middle-to-upper-income neighborhoods.

Additional Analyses

We further examined the relationship of obesity and asthma further on a multiplicative scale for the city as a whole (Table 3) and stratified by neighborhood income (Table 4). Risk ratios from these multivariate models are of similar magnitude and in the same direction as prevalence difference and attributable risk results. Further description of these results can be found in the Supplement.

Table 3
Weighted risk ratios for cases of current asthma in New York City, age 18–54 years, based on Community Health Survey, stratified by categories of body mass index.
Table 4
Weighted risk ratios for cases of current asthma in New York City, age 18–54 years, based on Community Health Survey, stratified by categories of body mass index and by low-income versus non-low income neighborhoods.


Obesity was confirmed as an important risk factor for current asthma in this study of the adult population of New York City. However, in spite of the higher prevalence of both asthma and obesity in low-income neighborhoods in New York City, the risk of asthma attributable to obesity was not higher in low-income neighborhoods compared to middle-to-upper-income neighborhoods. These findings make it unlikely that obesity causes excess asthma prevalence in low-income neighborhoods in New York City. Instead, alternative causes of excess asthma in low-income neighborhoods should be sought.

This study is the first to examine whether the association between obesity and adult asthma differs by neighborhood. Prior studies have shown an effect of neighborhood beyond individual health characteristics using ecologic or multi-level analysis,(31) but few studies have examined how neighborhood and individual characteristics may interact for specific health outcomes.(32) A recent study of the effect of aeroallergens on adult asthma hospitalizations found a stronger association among subjects with lower education levels, but neighborhood was not examined, and no difference was found by income level.(33) When the same group looked at air pollutants, neither education nor income level modified the effect of air pollution on asthma.(34) In a multi-level model created by Cagney and Browning, “physician diagnosis of a weight problem” was a significant predictor of asthma diagnosis but was unchanged by the addition of neighborhood characteristics, such as collective efficacy, to the model.(35)

Although the prevalence of obesity was higher in low-income neighborhoods, the relationship between obesity and asthma was weaker in low-income neighborhoods than in medium-to-high neighborhoods. Our finding suggests that other factors might contribute to the pathogenesis of asthma in low-income neighborhoods and modify or lessen the importance of obesity as a cause of asthma in these neighborhoods. Ambient air pollution, indoor air pollution, allergens, stress, and violence are all potentially worse in low-income compared to middle-to-upper income neighborhoods. Ambient air pollution is a well-established cause of emergency room visits and hospitalization for asthma.(36) Nitrogen oxides, ozone, and diesel exhaust are asthma triggers that may be higher in low-income neighborhoods, particularly with nearby bus and truck routes.(3740) Indoor air pollution (41) and allergens, including cockroach allergen (42) and mouse allergen,(43) may be higher in low-income neighborhoods. Matsui and colleagues found that settled dust concentrations of mouse allergen were a log-fold higher in inner-city homes compared to suburban homes.(44) Stress is a well-described asthma trigger,(45) which is likely to be worse in low-income neighborhoods. Community violence may play a role as well; the Inner-City Asthma Study found an association between exposure to violence and asthma symptom-days in a model which controlled for socioeconomic status, housing deterioration, and negative life events.(46) Furthermore, Wright and Steinbach recently described cases from the Boston City Hospital where exposure to violence appeared to precipitate asthma symptoms.(47)

Recent work supporting a genetic mechanism for the link between asthma and obesity should also be considered (48). In an analysis of twin pairs in the University of Washington Twin Registry, Hallstrand and colleagues found that 8% of the genetic component of obesity is shared with asthma. While environmental determinants were considered in the analysis, neighborhood of residence was not explored. Genetic variation by neighborhood may contribute to the differences in asthma and obesity prevalence, but further studies are needed; our survey did not include questions about family history or collect genetic material.

A limitation of this study is its use of self-reported height and weight to calculate BMI. Other studies have validated the use of self-reporting in this setting, however. An examination of self-reported BMI in an adult Scottish population found a sensitivity and specificity of 83% and 96% respectively for men, and 89% and 97%, respectively, for women.(49) If the misreporting of BMI and asthma were severe in low-income neighborhoods and absent in middle-to-high-income neighborhoods, this might have resulted in a stronger asthma-obesity relationship in the latter neighborhoods. However, it is unlikely that misreporting were differential in that direction: multiethnic studies have found that nonwhite subjects and subjects with less education report weight and height more accurately than White, more educated subjects.(50)

The cooperation rate for the Community Health Survey was lower than desired. Although the Community Health Survey targeted a random sample of the New York City population, not all contacted households agreed to participate in the study. Additionally, the survey did not capture households without a telephone, cell phone-only households, or institutionalized adults.(28) The relationship between asthma and obesity could differ among respondents and non-respondents; however, it is unlikely that any resultant bias would be strong.. Furthermore, the cooperation rate for the Community Health Survey is comparable to that of other cross-sectional population-based studies.(51)

The use of self-reported asthma diagnosis is a further limitation of this study. We defined current asthma as a doctor or nurse diagnosis of asthma plus self-report of asthma symptoms in the past 12 months. While self-report of asthma symptoms may be subject to misclassification, this combination of questions may be specific enough to reduce differential misclassification. One study comparing histamine challenge to the question of asthma during the last year found a sensitivity of 55% and specificity of 96% for this question, compared to a sensitivity of 44% and specificity of 98% for bronchial hyperresponsiveness on histamine challenge.(52) A 2002 study in Central Harlem, New York City found an asthma prevalence of 14%, (53) which is higher than the asthma prevalence reported in our study (5.8% in low-income neighborhoods). This difference in asthma prevalence is not surprising, however, as our definition of asthma was more stringent. The Central Harlem study did not ask about symptoms in the past year and did not exclude subjects over the age of 55, which may have resulted in misclassification of COPD cases as asthma cases. Nonetheless, we cannot eliminate the possibility of misclassification of asthma cases due to imperfect self-report.

Our study is unique in that it encompasses a large urban population and includes a high proportion of participants living in the inner-city. Although almost 6% of adult New Yorkers living in low-income neighborhoods had current asthma and 23% of them were obese, we did not find a stronger relationship between current asthma and obesity in low-income neighborhoods. Our findings suggest that the epidemic of inner-city asthma is not attributable disproportionately to obesity; other causes, such as allergen sensitization and indoor air pollution, also require further exploration.

Supplementary Material





The authors wish to thank Thomas Matte, MD and Bonnie Kerker, PhD for their helpful comments on the manuscript.

FUNDING: Robert Wood Johnson Generalist Physician Faculty Scholars Award, National Institutes of Health, National Research Service Award T32-HP10025


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AUTHORS' CONTRIBUTIONS Emily S. Tonorezos – study conception and planning, data analysis, manuscript preparation.

Adam M. Karpati – study conception and planning, creation of figures, manuscript preparation

Yuanjia Wang – study conception and planning, data analysis, manuscript preparation.

R Graham Barr – study conception and planning, creation of asthma supplemental questionnaire dataset, data analysis, manuscript preparation, and funding.

All authors contributed to the drafting of the report.


(1) Kuczmarski RJ, Flegal KM, Campbell SM, Johnson CL. Increasing prevalence of overweight among US adults. The National Health and Nutrition Examination Surveys, 1960 to 1991. JAMA. 1994 Jul 20;272(3):205–211. [PubMed]
(2) Seidell JC. Obesity, insulin resistance and diabetes — a worldwide epidemic. British Journal of Nutrition. 2000;83(Supplement 1):5–8. [PubMed]
(3) Hedley AA, Ogden CL, Johnson CL, Carroll MD, Curtin LR, Flegal KM. Prevalence of overweight and obesity among US children, adolescents, and adults, 1999–2002. JAMA. 2004 Jun 16;291(23):2847–2850. [PubMed]
(4) Ogden CL, Carroll MD, Curtin LR, McDowell MA, Tabak CJ, Flegal KM. Prevalence of overweight and obesity in the United States, 1999–2004. JAMA. 2006 Apr 5;295(13):1549–1555. [PubMed]
(5) Mannino DM, Homa DM, Akinbami LJ, Moorman JE, Gwynn C, Redd SC. Surveillance for asthma--United States, 1980–1999. MMWR Surveill Summ. 2002 Mar 29;51(1):1–13. [PubMed]
(6) Ford ES, Mannino DM. Time trends in obesity among adults with asthma in the United States: findings from three national surveys. J Asthma. 2005 Mar;42(2):91–95. [PubMed]
(7) Shaheen SO, Sterne JA, Montgomery SM, Azima H. Birth weight, body mass index and asthma in young adults. Thorax. 1999 May;54(5):396–402. [PMC free article] [PubMed]
(8) Celedon JC, Palmer LJ, Litonjua AA, et al. Body mass index and asthma in adults in families of subjects with asthma in Anqing, China. Am J Respir Crit Care Med. 2001 Nov 15;164(10 Pt 1):1835–1840. [PubMed]
(9) Akerman MJ, Calacanis CM, Madsen MK. Relationship between asthma severity and obesity. J Asthma. 2004 Aug;41(5):521–526. [PubMed]
(10) Beckett WS, Jacobs DR, Jr, Yu X, Iribarren C, Williams OD. Asthma is associated with weight gain in females but not males, independent of physical activity. Am J Respir Crit Care Med. 2001 Dec 1;164(11):2045–2050. [PubMed]
(11) Hedberg A, Rossner S. Body weight characteristics of subjects on asthma medication. Int J Obes Relat Metab Disord. 2000 Sep;24(9):1217–1225. [PubMed]
(12) Camargo CA, Jr, Weiss ST, Zhang S, Willett WC, Speizer FE. Prospective study of body mass index, weight change, and risk of adult-onset asthma in women. Arch Intern Med. 1999 Nov 22;159(21):2582–2588. [PubMed]
(13) Beuther DA, Weiss ST, Sutherland ER. Obesity and asthma. Am J Respir Crit Care Med. 2006 Jul 15;174(2):112–119. [PMC free article] [PubMed]
(14) Dixon JB, Chapman L, O'Brien P. Marked improvement in asthma after Lap-Band surgery for morbid obesity. Obes Surg. 1999 Aug;9(4):385–389. [PubMed]
(15) Stenius-Aarniala B, Poussa T, Kvarnstrom J, Gronlund EL, Ylikahri M, Mustajoki P. Immediate and long term effects of weight reduction in obese people with asthma: randomised controlled study. BMJ. 2000 Mar 25;320(7238):827–832. [PMC free article] [PubMed]
(16) Aaron SD, Fergusson D, Dent R, Chen Y, Vandemheen KL, Dales RE. Effect of weight reduction on respiratory function and airway reactivity in obese women. Chest. 2004 Jun;125(6):2046–2052. [PubMed]
(17) Dhabuwala A, Cannan RJ, Stubbs RS. Improvement in co-morbidities following weight loss from gastric bypass surgery. Obes Surg. 2000 Oct;10(5):428–435. [PubMed]
(18) New York City Department of Health and Mental Hygiene Asthma Facts. Second ed. Department of Health and Mental Hygiene; New York: 2003.
(19) Weiss KB, Wagener DK. Geographic variations in US asthma mortality: small-area analyses of excess mortality, 1981–1985. Am J Epidemiol. 1990 Jul;132(1 Suppl):S107–15. [PubMed]
(20) Drewnowski A, Specter SE. Poverty and obesity: the role of energy density and energy costs. Am J Clin Nutr. 2004 Jan;79(1):6–16. [PubMed]
(21) Robert SA, Reither EN. A multilevel analysis of race, community disadvantage, and body mass index among adults in the US. Soc Sci Med. 2004 Dec;59(12):2421–2434. [PubMed]
(22) Zhang Q, Wang Y. Socioeconomic inequality of obesity in the United States: do gender, age, and ethnicity matter? Soc Sci Med. 2004 Mar;58(6):1171–1180. [PubMed]
(23) Manios Y, Panagiotakos DB, Pitsavos C, Polychronopoulos E, Stefanadis C. Implication of socio-economic status on the prevalence of overweight and obesity in Greek adults: the ATTICA study. Health Policy. 2005 Oct;74(2):224–232. [PubMed]
(24) Frieden TR, Mostashari F, Kerkler BD, Miller N, Hajat A, Frankel M. Adult tobacco use levels after intensive tobacco control measures: New York City, 2002–2003. Am J Public Health. 2005;95(6):1016–23. [PubMed]
(25) New York City Department of City Planning Socioeconomic profile: New York City and Boroughs, 1999–2000. 2000.
(26) Task force on completion rates On the definition of response rates. Council of American Survey Research Organizations; New York: 1982.
(27) United Hospital Fund [Accessed March 5, 2008];New York City Community Health Atlas. 2002 Available at:
(28) New York City Department of Health and Mental Hygiene [Accessed March 5, 2008];Community Health Survey. 2002 Available at:
(29) United States Census Bureau [Accessed March 5, 2008];Census 2000 data for the state of New York. 2006 Available at: Id=&_lang=en&_ts=
(30) SAS Institute Cary, NC. SAS version 9 2004.
(31) Diez-Roux AV, Nieto FJ, Muntaner C, et al. Neighborhood environments and coronary heart disease: a multilevel analysis. Am J Epidemiol. 1997 Jul 1;146(1):48–63. [PubMed]
(32) Diez Roux AV. Investigating neighborhood and area effects on health. Am J Public Health. 2001 Nov;91(11):1783–1789. [PubMed]
(33) Cakmak S, Dales RE, Judek S, Coates F. Does socio-demographic status influence the effect of pollens and molds on hospitalization for asthma? Results from a time-series study in 10 Canadian cities. Ann Epidemiol. 2005 Mar;15(3):214–218. [PubMed]
(34) Cakmak S, Dales RE, Judek S. Do gender, education, and income modify the effect of air pollution gases on cardiac disease? J Occup Environ Med. 2006 Jan;48(1):89–94. [PubMed]
(35) Cagney KA, Browning CR. Exploring neighborhood-level variation in asthma and other respiratory diseases: the contribution of neighborhood social context. J Gen Intern Med. 2004 Mar;19(3):229–236. [PMC free article] [PubMed]
(36) Dominici F, Peng RD, Bell ML, et al. Fine particulate air pollution and hospital admission for cardiovascular and respiratory diseases. JAMA. 2006 Mar 8;295(10):1127–1134. [PMC free article] [PubMed]
(37) Garshick E, Laden F, Hart JE, Caron A. Residence near a major road and respiratory symptoms in U.S. Veterans. Epidemiology. 2003 Nov;14(6):728–736. [PMC free article] [PubMed]
(38) Romieu I, Meneses F, Ruiz S, et al. Effects of intermittent ozone exposure on peak expiratory flow and respiratory symptoms among asthmatic children in Mexico City. Arch Environ Health. 1997 Sep-Oct;52(5):368–376. [PubMed]
(39) Millstein J, Gilliland F, Berhane K, et al. Effects of ambient air pollutants on asthma medication use and wheezing among fourth-grade school children from 12 Southern California communities enrolled in The Children's Health Study. Arch Environ Health. 2004 Oct;59(10):505–514. [PubMed]
(40) Gilmour MI, Jaakkola MS, London SJ, Nel AE, Rogers CA. How exposure to environmental tobacco smoke, outdoor air pollutants, and increased pollen burdens influences the incidence of asthma. Environ Health Perspect. 2006 Apr;114(4):627–633. [PMC free article] [PubMed]
(41) Breysse PN, Buckley TJ, Williams D, et al. Indoor exposures to air pollutants and allergens in the homes of asthmatic children in inner-city Baltimore. Environ Res. 2005 Jun;98(2):167–176. [PubMed]
(42) Leaderer BP, Belanger K, Triche E, et al. Dust mite, cockroach, cat, and dog allergen concentrations in homes of asthmatic children in the northeastern United States: impact of socioeconomic factors and population density. Environ Health Perspect. 2002 Apr;110(4):419–425. [PMC free article] [PubMed]
(43) Chew GL, Perzanowski MS, Miller RL, et al. Distribution and determinants of mouse allergen exposure in low-income New York City apartments. Environ Health Perspect. 2003 Aug;111(10):1348–1351. [PMC free article] [PubMed]
(44) Matsui EC, Simons E, Rand C, et al. Airborne mouse allergen in the homes of inner-city children with asthma. J Allergy Clin Immunol. 2005 Feb;115(2):358–363. [PubMed]
(45) Rietveld S, Everaerd W, Creer TL. Stress-induced asthma: a review of research and potential mechanisms. Clin Exp Allergy. 2000 Aug;30(8):1058–1066. [PubMed]
(46) Wright RJ, Mitchell H, Visness CM, et al. Community violence and asthma morbidity: the Inner-City Asthma Study. Am J Public Health. 2004 Apr;94(4):625–632. [PubMed]
(47) Wright RJ, Steinbach SF. Violence: an unrecognized environmental exposure that may contribute to greater asthma morbidity in high risk inner-city populations. Environ Health Perspect. 2001 Oct;109(10):1085–1089. [PMC free article] [PubMed]
(48) Hallstrand TS, Fischer ME, Wurfel MM, Afari N, Buchwald D, Goldberg J. Genetic pleiotropy between asthma and obesity in a community-based sample of twins. J Allergy Clin Immunol. 2005;116:1235–1241. [PMC free article] [PubMed]
(49) Bolton-Smith C, Woodward M, Tunstall-Pedoe H, Morrison C. Accuracy of the estimated prevalence of obesity from self reported height and weight in an adult Scottish population. J Epidemiol Community Health. 2000 Feb;54(2):143–148. [PMC free article] [PubMed]
(50) Nieto-Garcia FJ, Bush TL, Keyl PM. Body mass definitions of obesity: sensitivity and specificity using self-reported weight and height. Epidemiology. 1990 Mar;1(2):146–152. [PubMed]
(51) Mokdad AH, Stroup DF, Giles WH, Behavioral Risk Factor Surveillance Team Public health surveillance for behavioral risk factors in a changing environment. Recommendations from the Behavioral Risk Factor Surveillance Team. MMWR. 2003;52(R-9):1–12. Recommendations and reports. [PubMed]
(52) Burney PG, Laitinen LA, Perdrizet S, et al. Validity and repeatability of the IUATLD (1984) Bronchial Symptoms Questionnaire: an international comparison. Eur Respir J. 1989 Nov;2(10):940–945. [PubMed]
(53) Northridge ME, Meyer IH, Dunn L. Overlooked and underserved in Harlem: a population-based survey of adults with asthma. Environ Health Perspect. 2002 Apr;110(Suppl 2):217–220. [PMC free article] [PubMed]