Abstract
Objectives. We analyzed smoking survey data across communities in Chicago, Ill, to explore community-level variations in smoking behavior.
Methods. We conducted a health survey of 6 racially and ethnically diverse Chicago communities during 2002–2003. The survey included questions about current smoking, smoking history, and cessation attempts.
Results. Smoking prevalence varied from 18% in the wealthiest (predominately White) community to 39% in the poorest (predominately Black) community. In a contiguous pair of communities, one Mexican and the other Black, smoking prevalence varied by a factor of 2. Men, residents in poorer households and households without telephones, and residents with less education were most likely to smoke.
Conclusions. The high proportions of current smokers who had attempted to quit indicate a prevalent desire to stop smoking. However, less than 4% of the Master Tobacco Settlement Agreement funds are being spent on smoking prevention, or even on health in general, in Illinois. Although much is known about the prevalence of smoking at the national level, few studies of smoking have been done at the community level, presenting difficulties for the allocation of resources and the design of smoking cessation programs in response to community needs. Understanding community-level smoking rates could improve the allocation of resources and assist the shaping of culturally meaningful prevention efforts.
The health-related effects of cigarette smoking in the United States are far-reaching and costly. A study of actual causes of death for 1990 found smoking to be the leading preventable cause of death in the United States.1 A recently published 2000 replication of this study of causes of death produced the same findings.2 Morbidity attributable to the effects of smoking is also substantial,3–6 and medical expenses attributable to smoking-related disease top $150 billion annually.3
In the mid-1960s, when reliable data on cigarette smoking first became available, about 42% of US adults smoked.7 From 1965 to 1990, smoking rates declined fairly steadily, and rates since then have varied between 22% and 25%.8–10 Despite increasing discussion over the past 35 years about the health risks associated with smoking, about 45.8 million US adults continue to smoke.10 This proportion is almost double the Healthy People 2010 goal of 12% of the population.11,12
Although these national trends are important, smoking prevalence may not be the same for all communities. The National Health Interview Survey reports predominately national data and only some city and metropolitan area data,13 whereas the Behavioral Risk Factor Surveillance System, which usually reports state-specific results, has just begun to provide estimates of its survey measures including smoking prevalence for selected cities and counties.14 As has recently been noted by Brownson et al., “many communities lack the chronic disease and risk factor data required to effectively set priorities and evaluate programs. This issue is beginning to be addressed but remains a serious constraint at the county, city, and community level.”15p231 Interestingly, we were able to locate only 1 publication describing the smoking experience for a local community.16
A recently completed community health survey in Chicago obtained considerable data describing smoking in a diverse selection of 6 community areas (discussed under “Sample Selection”). We present community-specific data regarding smoking prevalence rates, efforts and intentions to stop smoking, and age at smoking initiation.
METHODS
Survey
Data analyzed were obtained from the Sinai Health System’s Improving Community Health Survey. The survey was developed by the Survey Design Committee (SDC), which is composed of 6 representatives from community-based and service organizations in the participating community areas, 3 representatives from local Chicago health agencies, and 4 representatives from the Sinai Health System. The questionnaire was administered face-to-face in selected households.
Topics were chosen by the SDC to respond to health concerns expressed by community residents. Epidemiologists who served as staff to this committee identified specific survey questions addressing these topics and submitted them to the SDC. Questions were required (1) to have been used in national or Illinois surveys so that comparison data would be available, and (2) to be culturally sensitive to the participating communities. After a 3-month survey development process, the 469-question survey, designed to take about an hour to complete, was finalized.17
The Survey Research Laboratory at the University of Illinois at Chicago, an organization with extensive experience with local Chicago community surveys, was subcontracted to conduct the survey. The survey was pretested in July and August 2002 and administered between September 2002 and April 2003.
The questions analyzed in this report were those contained in the smoking module of the survey. A current smoker was defined as a person who answered yes to both of the following questions: (1) “Have you smoked at least 100 cigarettes in your life?” and (2) “Do you currently smoke cigarettes?”
Interviewers were thoroughly trained (with 21 hours of formal training) and culturally sensitive to the communities in which the interviews were administered. In most cases the interviewers were from the communities being surveyed. All interviewers working in Spanish-speaking communities were required to be fluent in Spanish. Ten percent of each interviewer’s work was validated at random.
During the course of the survey, one interviewer was shot at and another was robbed at knifepoint. Both incidents were reported to the police department and to the involved institutional review boards.
Sample Selection
In 2000, Chicago was the third largest city in the United States, with a diverse population of almost 3 million, consisting of 36% non-Hispanic Blacks, 31% non-Hispanic Whites, and 26% Hispanics. Chicago, which a seminal study described as “hypersegregated,”18 is officially divided into 77 “community areas” that often serve as loci for gathering and analyzing health data, for delivering health care services, and for implementing community-based interventions.19 Community areas were created in 1943 for research purposes. Boundaries for these communities were drawn around existing neighborhoods and corresponded to landmarks such as rivers and railroad tracks. Community areas were redefined after O’Hare International Airport was annexed to the city, which necessitated the creation of a new community area. We selected 6 of these community areas for study. The community areas were chosen to reflect Mount Sinai’s catchment area and racial/ethnic and geographic diversity.
Table 1 ▶ presents the social and demographic characteristics of these communities. North Lawndale is almost entirely Black; South Lawndale is almost entirely Mexican; Humboldt Park is about half Black, one quarter Puerto Rican, and one quarter Mexican; West Town is about half White, one quarter Puerto Rican, and one quarter Mexican; Roseland is almost entirely Black; and Norwood Park is almost entirely White. The median household incomes (derived from the 2000 Census20) range from $18000 for North Lawndale to $53 000 for Norwood Park, versus $42 000 for the United States and $39000 for Chicago.
TABLE 1—
Norwood Park (n = 37 669) | Humboldt Park (n = 65 836) | West Town (n = 87 435) | South Lawndale (n = 91 071) | North Lawndale (n = 41 768) | Roseland (n = 52 723) | Chicago (n = 2 896 016) | |
Race/ethnicity, % | |||||||
Non-Hispanic Black | 1 | 47 | 9 | 13 | 94 | 98 | 36 |
Non-Hispanic White | 88 | 3 | 39 | 4 | 1 | 1 | 31 |
Hispanic | 6 | 48 | 47 | 83 | 5 | 1 | 26 |
Mexican | 3 | 24 | 25 | 76 | 3 | 0 | 18 |
Puerto Rican | 0 | 18 | 16 | 1 | 0 | 0 | 4 |
High school graduate, % | 83 | 50 | 70 | 37 | 60 | 77 | 72 |
Median household income, $ | 53 402 | 28 728 | 38 915 | 32 320 | 18 342 | 38 237 | 38 625 |
Unemployment rate, % | 3 | 18 | 7 | 12 | 26 | 17 | 10 |
Below poverty level, % | 4 | 31 | 21 | 27 | 45 | 18 | 20 |
Participants
The sample was stratified to complete approximately equal numbers of interviews within each of the 6 community areas. Within each area, a 3-stage probability sample design was employed.21 First, census blocks were chosen with probability proportionate to size sampling, meaning that the census blocks within each community were selected proportionate to the number of individuals aged 18 years and older who lived on each block.20 Second, addresses were randomly selected from the blocks. Third, 1 adult from each household was randomly selected with the methodology described by Trodahl and Carter.22
Prior to the visit by the interviewer, a letter on the stationery of one of the community-based organizations participating on the SDC was mailed to each selected address. The letter explained the purpose of the survey and how we hoped it would help the community. The goal of 300 completed interviews was met in 5 of the 6 communities. The sole exception was Norwood Park, a predominately White community area with the highest median household income. Here, only 190 interviews were completed.
Persons were eligible for the survey if they were between 18 and 75 years of age, spoke either English or Spanish, resided in 1 of the 6 community areas, and were physically and mentally able to participate. Participants were paid $40 in cash and were provided with brochures (in either Spanish or English) about different health issues relevant to their particular communities.
Response Rate
A total of 4888 listed addresses were initially selected for study. By the time the interviewers visited to solicit participation in the survey, some addresses were vacant, and some no longer existed (e.g., the building had burned down). At some, no one answered the door. A minimum of 12 attempts, on different days and at different times, were made to reach selected addresses.
Because this sampling process consisted of so many steps, we describe multiple aspects of the participation rate. About 10% of the originally selected 4888 addresses did not represent households. In about 24% of households, no one could be located; when residents could be contacted, about 24% refused to answer any of the screening questions or speak with the interviewers. A total of 1953 eligible persons were contacted for this survey, of whom 1699 agreed to participate; of these 1699, all completed the survey. Thus, 87% of the people who responded to the screening questions and were eligible went on to fully participate; this proportion might be termed the “participation rate.” The overall study response rate of 43.2% was calculated according to conservative procedures that employed the original list of addresses from census data as the denominator.23,24 This denominator includes buildings that no longer existed, addresses that did not represent households, and households at which we were never able to locate anyone, as well as residents who refused to participate.
The response rates and their component rates varied substantially among the 6 community areas. For example, in North Lawndale, the poorest of the 6 community areas, the occupancy rate (percentage of occupied addresses) was 85%, and the refusal rate was 10%. In Norwood Park, the richest of the 6 community areas, the occupancy rate was 98%, and the refusal rate was 35%. Thus, although 15% of houses in North Lawndale were vacant or had burned down, 90% of the potential participants we located completed the survey. In Norwood Park, by contrast, most of the housing units were occupied, but only 65% of eligible persons agreed to participate. More than 85% of interviews were conducted during evening and weekend hours.
Data Analysis
Data were weighted to account for the probability of selection (at the block, household, and respondent levels) and to ensure that the sample resembled the community area populations. Data were analyzed with Stata (Stata Corp, College Station, Tex).
A 95% confidence level was employed for all analyses. The significance among prevalence proportions was tested with the t test. Trends among the results from the 6 community areas were tested for statistical significance by calculation of binomial probabilities. The χ2 test was used to test the similarity of distributions.
RESULTS
Smoking prevalence data are presented in Table 2 ▶. The proportion of self-reported current smokers ranged from 18% in Norwood Park and 20% in South Lawndale to 39% in North Lawndale and 35% in Humboldt Park. The prevalence ratios, with Norwood Park as the referent, ranged from 1.09 for South Lawndale to 2.11 for North Lawndale. Only the ratio for South Lawndale was not statistically significant. Data presented in Table 2 ▶ also show that a majority of current smokers (ranging from 46% to 58% across community areas) reported that they tried to quit during the past year and that 49% to 75% of current smokers were still trying to stop.
TABLE 2—
No. of Respondents | Smoking Prevalence (95% CI) | Prevalence Ratio | Pa | Tried to Quit in Past 12 Months, % | Still Trying to Quit at Interview, % | |
Norwood Park | 190 | 0.184 (0.158, 0.214) | Reference | … | 54 | 57 |
Humboldt Park | 298 | 0.349 (0.270, 0.438) | 1.9 | <.001 | 58 | 68 |
West Town | 303 | 0.318 (0.257, 0.386) | 1.72 | <.001 | 46 | 49 |
South Lawndale | 300 | 0.201 (0.154, 0.259) | 1.09 | NS | 58 | 75 |
North Lawndale | 303 | 0.389 (0.334, 0.448) | 2.11 | <.001 | 46 | 70 |
Roseland | 302 | 0.328 (0.249, 0.419) | 1.78 | <.01 | 51 | 65 |
Note. CI = confidence interval; NS = not significant.
aP values given for significant differences only.
Table 3 ▶ presents smoking prevalences for each community area, stratified by 4 social and demographic measures. In all 6 communities, men were more likely than women to smoke, but in none of the 6 communities was this difference statistically significant. However, this difference in smoking prevalence by gender among all 6 communities taken together was significant (P=.02). Income showed a generally nonsignificant negative association with smoking. In 5 of the communities (the exception being West Town), people living in households with an annual income below $30000 smoked at a higher rate compared to those residents with a higher income. Only in Roseland was the association of a lower household income with current smoking significant (P<.01).
TABLE 3—
No. of Respondents | Smoking Prevalence (95% CI) | Pa | |
Norwood Park | |||
Gender | |||
Male | 93 | 0.204 (0.145, 0.263) | NS |
Female | 97 | 0.166 (0.086, 0.247) | |
Income, $ | |||
< 30 000 | 12 | 0.205 (0.058, 0.352) | NS |
≥ 30 000 | 166 | 0.193 (0.162, 0.223) | |
Education | |||
< High school diploma | 9 | 0.463 (0.172, 0.754) | <.05 |
High school diploma | 50 | 0.186 (0.075, 0.298) | |
> High school diploma | 129 | 0.151 (0.098, 0.204) | |
Presence of working phone | |||
No | 4 | 0.597 (0.038, 1.000) | NS |
Yes | 186 | 0.179 (0.149, 0.208) | |
Humboldt Park | |||
Gender | |||
Male | 117 | 0.407 (0.276, 0.538) | NS |
Female | 181 | 0.297 (0.242, 0.353) | |
Income, $ | |||
< 30 000 | 182 | 0.404 (0.324, 0.484) | NS |
≥ 30 000 | 96 | 0.263 (0.129, 0.397) | |
Education | |||
< High school diploma | 114 | 0.365 (0.246, 0.484) | NS |
High school diploma | 81 | 0.366 (0.230, 0.502) | |
> High school diploma | 98 | 0.276 (0.154, 0.398) | |
Presence of working phone | |||
No | 40 | 0.415 (0.225, 0.606) | NS |
Yes | 258 | 0.339 (0.249, 0.428) | |
West Town | |||
Gender | |||
Male | 136 | 0.357 (0.250, 0.464) | NS |
Female | 167 | 0.274 (0.201, 0.347) | |
Income, $ | |||
< 30 000 | 127 | 0.302 (0.216, 0.388) | NS |
≥ 30 000 | 153 | 0.36 (0.260, 0.459) | |
Education | |||
< High school diploma | 60 | 0.287 (0.131, 0.442) | NS |
High school diploma | 47 | 0.326 (0.196, 0.457) | |
> High school diploma | 194 | 0.333 (0.258, 0.408) | |
Presence of working phone | |||
No | 42 | 0.384 (0.171, 0.597) | NS |
Yes | 261 | 0.308 (0.243, 0.373) | |
South Lawndale | |||
Gender | |||
Male | 123 | 0.222 (0.173, 0.270) | NS |
Female | 177 | 0.17 (0.042, 0.298) | |
Income, $ | |||
< 30 000 | 200 | 0.204 (0.139, 0.269) | NS |
≥ 30 000 | 64 | 0.176 (0.057, 0.295) | |
Education | |||
< High school diploma | 184 | 0.171 (0.102, 0.241) | NS |
High school diploma | 63 | 0.239 (0.072, 0.405) | |
> High school diploma | 44 | 0.273 (0.145, 0.402) | |
Presence of working phone | |||
No | 64 | 0.257 (0.035, 0.479) | NS |
Yes | 236 | 0.183 (0.104, 0.262) | |
North Lawndale | |||
Gender | |||
Male | 109 | 0.412 (0.339, 0.486) | NS |
Female | 194 | 0.373 (0.308, 0.438) | |
Income, $ | |||
< 30 000 | 210 | 0.395 (0.326, 0.465) | NS |
≥ 30 000 | 70 | 0.389 (0.239, 0.539) | |
Education | |||
< High school diploma | 73 | 0.497 (0.343, 0.651) | NS |
High school diploma | 88 | 0.377 (0.264, 0.489) | |
> High school diploma | 141 | 0.33 (0.250, 0.410) | |
Presence of working phone | |||
No | 39 | 0.35 (0.231, 0.468) | NS |
Yes | 264 | 0.395 (0.336, 0.455) | |
Roseland | |||
Gender | |||
Male | 107 | 0.406 (0.277, 0.534) | NS |
Female | 195 | 0.269 (0.202, 0.335) | |
Income, $ | |||
< 30 000 | 164 | 0.397 (0.315, 0.480) | <.01 |
≥ 30 000 | 124 | 0.236 (0.147, 0.324) | |
Education | |||
< High school diploma | 60 | 0.349 (0.236, 0.462) | NS |
High school diploma | 102 | 0.37 (0.210, 0.531) | |
> High school diploma | 140 | 0.283 (0.181, 0.386) | |
Presence of working phone | |||
No | 24 | 0.613 (0.386, 0.839) | <.025 |
Yes | 278 | 0.308 (0.226, 0.390) |
Note. CI = confidence interval; NS = not significant. P trend for gender = .02; P trend for income = .11; P trend for education (< high school diploma vs > high school diploma) = .36; P trend for presence of working phone > .11.
aP values given for significant differences only.
Table 3 ▶ also presents smoking proportions for a trichotomized education variable. In 4 of the 6 communities, the lowest proportion of smokers was found among people with more than a high school education. For West Town and South Lawndale, education was positively associated with smoking. For each community, we compared the smoking proportion among people with less than a high school education with the proportion among those with more than a high school education. This proportion was significant only for Norwood Park.
The proportion of households without telephone service (excluding cellular phones) ranged from 2% in Norwood Park to 21% in South Lawndale. Because 5 of the 6 communities demonstrated higher smoking proportions among households without telephones, a telephone survey would have underestimated smoking prevalence in these communities. However, the inverse association of presence of a telephone with smoking prevalence was statistically significant only in Roseland (P<.025).
We also estimated the average age at which residents started to smoke. For both current smokers and those who had ever smoked, the mean and median ages fell into a narrow range, from age 14.7 years to 17.2 years (data not shown). In addition, the vast majority of current smokers started smoking while they were teenagers; percentages ranged from a low of 77% in North Lawndale to a high of 92% in South Lawndale (data not shown).
DISCUSSION
Nationally, Black and White men and women smoke at similar rates. For example, in 2000, 25.9% of US adults smoked—28.4% of men, 23.6% of women, 24.7% of Blacks, and 27.5% of Whites.25 This national homogeneity might not apply on the local level.
By necessity, national estimates of smoking prevalence are averages of the prevalence for many smaller areas—states, counties, cities, and communities. National averages are essential to mark the progress of the country as a whole in reducing smoking. However, to the extent that smoking rates in different communities affect the content and goals of smoking interventions, community interventions to prevent smoking will be weakened if they are based on national data. For example, if the smoking burden for North Lawndale (actually 39%) were assumed to be similar to the overall US prevalence (22%), the urgency of targeting smoking cessation intervention efforts to this community might not be seen. Additionally, intervention planners will be unable to direct resources to those communities in greatest need. The local data gathered in these 6 Chicago communities illustrate this potential problem.
Consider a comparison of West Town with Norwood Park. West Town is not a poor community; its 2000 median household income was similar to Chicago’s and slightly less than the US median (Table 1 ▶). Norwood Park has a higher median household income than West Town, but 10 community areas in Chicago have higher median household incomes. Yet, the smoking rate in West Town was 72% higher than the rate in Norwood Park (Table 2 ▶), a difference that could not be predicted on the basis of national data. Furthermore, the smoking rate among White adults in West Town (41%; data not shown) was more than 2 times higher than the rate among White adults in Norwood Park (18%; data not shown), suggesting a need for urgent intervention in West Town.
The need to incorporate local data into local intervention design is illustrated by the disparate smoking rates of the contiguous communities of South Lawndale (smoking prevalence=20%) and North Lawndale (smoking prevalence=39%). One can literally stand in both communities at the same time. Yet, the smoking prevalence in North Lawndale is 94% higher than that in South Lawndale (Table 2 ▶). Another way to think about these differences is to note that whereas the prevalence of smoking in South Lawndale is currently lower than the US prevalence, the smoking prevalence in North Lawndale is about where the US prevalence was in 1965 (42%).26 That is, North Lawndale lags behind US smoking cessation levels by about 35 years. Additionally, North Lawndale’s smoking prevalence is even higher than that for Blacks in the lowest income group in the National Health Interview Survey (33%).25
The socioeconomic correlates of smoking in these communities are generally similar to those reported in previous studies,16,27 although most of the associations found by our study were not statistically significant. Demographic groups that were more likely to be current smokers included men, people living in households with lower incomes (< $30 000 per year) or without working telephones, and people without a high school diploma. We also found that the mean and median ages for smoking initiation fell in the range of approximately 15 to 17 years, that more than 90% of all current smokers started smoking while they were teenagers, and that most current smokers smoke about half a pack a day.
As previously noted, the 6 communities that were selected for this survey were not randomly selected to obtain a representative sample of city residents. Instead, they were selected because we believed that studying them would help us pursue interventions in a diverse array of community areas in the very segregated city of Chicago. Although North Lawndale is poor, it is only the 9th poorest community area (out of 77) in the city, and several of the neighboring communities are similar in almost all sociodemographic characteristics. And although Norwood Park is comparatively well off, it is only the 10th most wealthy community area in the city and, in fact, one of the least wealthy of the predominately White community areas. Had we selected communities closer to both income extremes, we quite likely would have found even greater differences in smoking prevalence.
We are aware of only 1 local-area study that has produced smoking prevalence data. The Harlem Household Survey was implemented in randomly selected households in 1992–1994.16,28 The goal of the survey was to assess the behavioral risk factors for excess morbidity and mortality in Harlem, New York City’s oldest African American community.29 The smoking prevalence among adults was near 44%, almost twice the smoking prevalence reported for US adults in 1992–1994.30 Because we have no longitudinal smoking data for any local communities, it is difficult to know how Harlem’s 44% prevalence rate, assessed 10 years ago, might compare with the 39% rate found in North Lawndale and the 33% rate found in Roseland, the 2 predominately Black communities in our survey. The order of magnitude does appear similar, especially given a decade’s worth of smoking cessation efforts in the interim.
Implications
The Master Tobacco Settlement Agreement in Illinois, signed into effect at the end of 1998, awarded the state $9.1 billion, or about $364 million over a 25-year period.31 Despite this windfall, Illinois officials report that the state has spent only $12 million on tobacco prevention in each of the past 2 fiscal years.32 And very little money has been targeted at communities most in need of smoking prevention funds. Indeed, this situation was inevitable, because, until this study, data on community-level differences in smoking have not been available. The Centers for Disease Control and Prevention has estimated the approximate amount of money that states should be spending annually on tobacco prevention.32 For Illinois, this amount is between $65 million and $179 million, or more than 5 to nearly 15 times actual expenditures.32
In addition, although Medicaid will allow reimbursement for behavioral counseling for smoking cessation, which has been documented to be effective in many rigorous analyses,33–35 Illinois, like most other states, does not provide such reimbursement.36 This lack of support for smoking cessation is especially discouraging in light of the rather large proportion of current smokers in our survey who reported both that they had tried to quit smoking during the past year and that they still wanted to stop (Table 2 ▶). It is also notable that the smallest proportion of people who had ever smoked and stopped were found in the 2 poorest community areas, North Lawndale (30%) and Humboldt Park (31%) (data not shown). The finding that poor people who smoke are less likely to stop smoking is consistent with previous reports describing smoking cessation efforts.36–38 Adequate assistance for smokers who want to stop must be provided.
Methodological Considerations
Implementing a survey in Chicago’s most disenfranchised communities presents significant challenges. Many of the randomly selected addresses no longer existed when we returned for the interviewing after field enumeration, which resulted in a response rate that was below the recommended conservative calculations for the response rate. On the other hand, 87% of the people to whom we spoke agreed to participate and completed the survey. It is unclear how these response rates affected our findings. Nonrespondents often fare worse than respondents on many health measures,39,40 which suggests that we may have overestimated the quality of residents’ health in these communities. However, the 6 communities are quite homogenous.
It must be emphasized here that there is no reason to suppose that the 6 community areas we selected represent all the residents of Chicago. Indeed, a Behavioral Risk Factor Surveillance System survey conducted in Chicago in 2000 revealed that 21% of adults were current smokers,14 a statistic that may reasonably be compared with our much higher weighted average for the 6 communities of 28.9% (95% confidence interval = 26.2, 31.8). Furthermore, we cannot assume that the 2 predominately Black community areas we sampled are representative of the smoking experiences of Black Chicagoans.
Conclusions
A recent commentary in The Lancet noted that January 11, 2004, marked the 40th anniversary of the US surgeon general’s report on smoking and health.41p97 During those 40 years, the smoking rate of adults in the United States has fallen about half—from 42% to 23%. It must be reduced by half again to meet the Healthy People 2010 goal of 12%.12 Whether this goal can be accomplished will depend on our ability to allocate resources appropriately. We know how to help people to stop smoking,38,42,43 and we know many effective activities that will prevent people from starting.38,44
What we need now are the critical resources and the political will to deploy those resources. It is possible that local-area smoking data, which have substantial potential for galvanizing support and targeting prevention funds, could serve as an important tool in this pursuit. This study and others16 have shown that collecting such data can be accomplished despite clear obstacles.
Acknowledgments
This study was funded through the generous support of The Robert Wood Johnson Foundation (grant 043026). Additional support was provided by the Chicago Community Trust and the Michael Reese Health Trust.
We would also like to acknowledge the assistance of all members of the Sinai Urban Health Institute in the implementation of this project, several of whom were funded by the Michael Reese Health Trust.
Human Participant Protection This study was approved by the institutional review boards of the Sinai Health System and the University of Illinois at Chicago.
Peer Reviewed
Contributors J. L. Dell designed the smoking module and led the writing of the article. S. Whitman conceptualized the study and supervised all aspects of its implementation. A. M. Shah supervised all daily aspects of the study and assisted with analyses. A. Silva led analyses of the data. D. Ansell contributed to conceptualization of the study and assisted with writing the article. All of the authors helped to conceptualize ideas, interpret findings, and review drafts of the article.
References
- 1.McGinnis JM, Foege WH. Actual causes of death in the United States. JAMA. 1993;270:2207–2212. [PubMed] [Google Scholar]
- 2.Mokdad AH, Marks JS, Stroup DF, Gerberding JL. Actual causes of death in the United States. JAMA. 2004;291:1238–1245. [DOI] [PubMed] [Google Scholar]
- 3.Centers for Disease Control and Prevention. Annual smoking-attributable mortality, years of potential life lost, and economic costs—United States, 1995–1999. MMWR Morb Mortal Wkly Rep. 2002;51:300–303. [PubMed] [Google Scholar]
- 4.Rigotti NA. A 36-year-old woman who smokes cigarettes. JAMA. 2000;284:741–749. [DOI] [PubMed] [Google Scholar]
- 5.Bartecchi CE, MacKenzie TD, Schrier RW. The human costs of tobacco use. N Engl J Med. 1994;330:907–912. [DOI] [PubMed] [Google Scholar]
- 6.Centers for Disease Control and Prevention. Special focus: reducing tobacco use. The National Tobacco Control Program. Chronic Dis Notes Rep. 2001;14:8–9. [Google Scholar]
- 7.Pamuk E, Makuc D, Heck K, Reuben C, Lochner K. Socioeconomic Status and Health Chartbook. Hyattsville, Md: National Center for Health Statistics; 1998:273.
- 8.Centers for Disease Control and Prevention. Behavioral Risk Factor Surveillance System. Available at: http://apps.nccd.cdc.gov/brfss/Trends/trendchart.asp?qkey=1000&state=US. Accessed February 27, 2005.
- 9.Centers for Disease Control and Prevention. Cigarette smoking among adults—United States, 2000. MMWR Morb Mortal Wkly Rep. 2002;51:642–645. [PubMed] [Google Scholar]
- 10.Centers for Disease Control and Prevention. State-specific prevalence of current cigarette smoking among adults—United States, 2003. MMWR Morb Mortal Wkly Rep. 2004;53:1035–1037. [PubMed] [Google Scholar]
- 11.Task Force on Community Preventive Services. Strategies for reducing exposure to environmental tobacco smoke, increasing tobacco-use cessation, and reducing initiation in communities and health-care systems. MMWR Recomm Rep. 2000;49(RR-12): 1–11. [PubMed] [Google Scholar]
- 12.Healthy People 2010: Understanding and Improving Health. 2nd ed. Washington, DC: US Dept of Health and Human Services;2000:30–31.
- 13.Botman SL, Moore TF, Moriarity CL, Parsons VL. Design and estimation for the National Health Interview Survey, 1995–2004. Vital Health Stat 2. 2000;No. 130:1–31. [PubMed] [Google Scholar]
- 14.Centers for Disease Control and Prevention. Cigarette smoking in 99 metropolitan areas—United States, 2000. MMWR Morb Mortal Wkly Rep. 2001;50:1107–1113. [PubMed] [Google Scholar]
- 15.Brownson RC, Bright FS. Chronic disease control in public health practice: looking back and moving forward. Public Health Rep. 2004;119:230–238. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Northridge ME, Morabia A, Ganz ML, et al. Contribution of smoking to excess mortality in Harlem. Am J Epidemiol. 1998;147:250–258. [DOI] [PubMed] [Google Scholar]
- 17.Shah AM, Williams C, Delgado J, Whitman S. A Participatory Approach to Designing a Community Health Survey: A Report on the Survey Development Process. Chicago, Ill: Sinai Health System; 2003.
- 18.Massey DS, Denton NA. American Apartheid: Segregation and the Making of the Underclass. Cambridge, Mass: Harvard University Press; 1993.
- 19.The Chicago Fact Book Consortium. Local Community Fact Book: Chicago Metropolitan Area, 1990. Chicago, Ill: Academy Chicago Publishers; 1995.
- 20.US Census Bureau. 2000 Census of Population and Housing, Summary File 3. Washington, DC: US Census Bureau; 2002: Table DP-3. Available at: http://www.nipc.org/test/dp234_CA_2000.htm. Accessed February 27, 2005.
- 21.Kish L.Survey Sampling. New York, NY: John Wiley & Sons; 1965.
- 22.Troldahl V, Carter RE. Random selection of respondents within households in phone surveys. J Marketing Res. 1964;1:71–76. [Google Scholar]
- 23.Standard Definitions: Final Dispositions of Case Codes and Outcome Rates for Surveys. Ann Arbor, Mich: American Association for Public Opinion Research; 2004.
- 24.Johnson TP, Owens L. Survey response rate reporting in the professional literature. In: American Statistical Association. 2003 Proceedings of the Section on Survey Research Methods. Alexandria, Va: American Statistical Association. In press.
- 25.Barbeau EM, Krieger N, Soobader MJ. Working class matters: socioeconomic disadvantage, race/ethnicity, gender, and smoking in NHIS 2000. Am J Public Health. 2004;94:269–278. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.National Center for Health Statistics. Health, United States, 2004. Chartbook on Trends in the Health of Americans. Hyattsville, Md: National Center for Health Statistics; 2004: Table 60.
- 27.Nelson DE, Powell-Griner E, Town M, Kovar MG. A comparison of national estimates from the National Health Interview Survey and the Behavioral Risk Factor Surveillance System. Am J Public Health. 2003;93:1335–1341. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Fullilove RE, Fullilove MT, Northridge ME, et al. Risk factors for excess mortality in Harlem. Findings from the Harlem Household Survey. Am J Prev Med. 1999;16(3 suppl):22–28. [DOI] [PubMed] [Google Scholar]
- 29.Fullilove RE. Community-based prevention programs: Harlem Project. Presented at: Public Health in the 21st Century: Behavioral and Social Science Contributions; May 7–9, 1998; Atlanta, Ga. Available at: http://www.apa.org/pi/pubhealth/abs21.html. Accessed February 27, 2005.
- 30.Epidemiology and Statistics Unit. Trends in Tobacco Use. Best Practices and Program Services. New York, NY: American Lung Association; 2002.
- 31.Tobacco Settlement Update. Springfield, Ill: Illinois Economic and Fiscal Commission; February 2001.
- 32.Campaign for Tobacco-Free Kids. Special reports: state tobacco settlement—Illinois. Available at: http://tobaccofreekids.org/reports/settlements/state.php? StateID=IL. Accessed February 27, 2005.
- 33.Bier ID, Wilson J, Studt P, Shakleton M. Auricular acupuncture, education, and smoking cessation: a randomized, sham-controlled trial. Am J Public Health. 2002;92:1642–1647. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Zhu SH, Anderson CM, Tedeschi GJ, et al. Evidence of real-world effectiveness of a telephone quit-line for smokers. N Engl J Med. 2002;347:1087–1093. [DOI] [PubMed] [Google Scholar]
- 35.Sharif I, Oruwariye T, Waldman G, Ozuah PO. Smoking cessation counseling by pediatricians in an inner-city setting. J Natl Med Assoc. 2002;94:841–845. [PMC free article] [PubMed] [Google Scholar]
- 36.Centers for Disease Control and Prevention. State Medicaid coverage for tobacco-dependence treatments—United States, 1994–2002. MMWR Morb Mortal Wkly Rep. 2004;53:54–57. [PubMed] [Google Scholar]
- 37.Centers for Disease Control and Prevention. Cigarette smoking among adults—United States, 2002. MMWR Morb Mortal Wkly Rep. 2004;53:427–431. [PubMed] [Google Scholar]
- 38.Fiore MC, Croyle RT, Curry SJ, et al. Preventing 3 million premature deaths and helping 5 million smokers quit: a national action plan for tobacco cessation. Am J Public Health. 2004;94:205–210. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Shahar E, Folsom AR, Jackson R. The effect of nonresponse on prevalence estimates for a referent population: insights from a population-based cohort study. Ann Epidemiol. 1996;6:498–506. [DOI] [PubMed] [Google Scholar]
- 40.Cohen G, Duffy JC. Are nonrespondents to health surveys less healthy than respondents? J Off Stat. 2002;18(1):13–23. [Google Scholar]
- 41.Blum A, Solberg E, Wolinsky H. The Surgeon General’s report on smoking and health 40 years later: still wandering in the desert. Lancet. 2004;363:97–98. [DOI] [PubMed] [Google Scholar]
- 42.Hopkins DP, Briss PA, Ricard CJ, et al. Reviews of evidence regarding interventions to reduce tobacco use and exposure to environmental tobacco smoke. Am J Prev Med. 2001;20(2 suppl):16–66. [DOI] [PubMed] [Google Scholar]
- 43.Katz DA, Muehlenbruch DR, Brown RL, Fiore MC, Baker TB, AHRQ Smoking Cessation Guideline Study Group. The effectiveness of implementing the Agency for Healthcare Research and Quality Smoking Cessation Clinical Practice Guideline: a randomized, controlled trial. J Natl Cancer Inst. 2004;96:594–603. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Centers for Disease Control and Prevention. Effect of ending an anti-tobacco youth campaign on adolescent susceptibility to cigarette smoking—Minnesota, 2002–2003. MMWR Morb Mortal Wkly Rep. 2004;53:301–304. [PubMed] [Google Scholar]