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  Volume 2: No. 
          4, October 2005 
ORIGINAL RESEARCHMethods and Baseline Characteristics of Two Group-Randomized Trials 
    With Multiracial and Multiethnic Working-class Samples
Anne M. Stoddard, ScD, Nancy Krieger, PhD, Elizabeth M.
  Barbeau, ScD, Gary G. Bennett, PhD, Martha E. Fay, MPH, Glorian Sorensen, PhD,
  MPH, Karen Emmons, PhD
Suggested citation for this article: Stoddard AM, Krieger N, Barbeau
  EM, Bennett GG, Fay ME, Sorensen G, et al. Methods and baseline characteristics of two
  group-randomized trials with multiracial and multiethnic working-class samples. Prev Chronic Dis [serial online] 2005 Oct [date
  cited]. Available from: URL: http://www.cdc.gov/pcd/issues/2005/oct/05_0026.htm.
 PEER REVIEWED AbstractIntroductionFew papers address the methodological challenges in
  recruiting participants for studies of cancer prevention interventions 
  designed for multiracial and multiethnic working-class populations. This paper 
  reports the results of the sample selection and survey methods for two 
  group-randomized intervention studies.
 MethodsThe two group-randomized intervention studies, Healthy Directions–Small 
  Business (HD–SB) and Healthy Directions–Health Centers (HD–HC), included a worksite-based 
  study in 26 small manufacturing businesses and a study in 10 outpatient health 
  centers. We used selection and recruitment methods to obtain a
  multiracial and multiethnic working-class study sample. In 2000 and 2001, we
  assessed baseline measures of sociodemographic characteristics and behavioral
  outcomes by self-report. We then 
  computed intraclass 
  correlation coefficients (ICCs).
 ResultsOf the 1740 participants in the HD–SB study, 68% were
  non-Hispanic whites, and 76% had working-class occupations. In the HD–HC study, 59% of 2219 participants were non-Hispanic whites. Among those
  who worked, 51% had working-class occupations. Large percentages of both
  samples reported not meeting recommended guidelines for the target behaviors.
  For example, 86% of members of both samples consumed fewer than the
  recommended five servings of fruits and vegetables per day. The ICCs for the
  four target behaviors in HD–SB were between 0.006 and 0.02. In the HD–HC
  study, the ICCs ranged from 0.0004 to 0.003.
 ConclusionThe two studies were successful in recruiting multiracial and multiethnic 
  working-class participants. Researchers will find the estimates of the
  primary outcomes and their ICCs useful for planning future
  studies.
 Back to top IntroductionIncreasingly, there have been calls for reducing health disparities based 
  on
  socioeconomic position and race and ethnicity (1) and for implementing community interventions
  that address segments of the population in which risk for chronic disease is
  concentrated (2,3). Few papers in the literature, however, address
  the methodological challenges in recruiting participants for studies of such
  interventions. This paper describes and presents the results of the sample
  selection and survey methods for two group-randomized trials of cancer
  prevention interventions designed for multiracial and multiethnic 
  working-class
  populations. The Harvard Cancer Prevention Program Project, Healthy Directions, was 
  designed to develop and evaluate cancer prevention interventions for 
  multiracial and multiethnic working-class populations (4). The project comprised 
  two intervention studies, Healthy Directions–Small Business (HD–SB) and 
  Healthy Directions–Health Centers (HD–HC), and a cancer prevention policy model-analysis
  project. The intervention projects were group-randomized controlled studies
  that tested the shared primary hypotheses that mean levels of dietary and
  physical activity outcomes would improve more significantly in the
  intervention group than in the control group. The interventions developed for
  the two projects were based on a common conceptual framework (4) drawing on
  social ecological theory (3,5). Using this framework, the social context in
  which people live was incorporated into the design and delivery of the
  interventions. This framework encompasses several factors, including individual
  factors (e.g., material circumstances), interpersonal factors (e.g., family
  roles and responsibilities), organizational factors (e.g., access to health
  care), and community factors (e.g., neighborhood safety). In contrast to
  interventions designed for a specific racial or ethnic
  group, we used this framework to design interventions that were suitable for a
  multiracial and multiethnic population. HD–SB was a worksite-based
  intervention study designed to test the effectiveness of an integrated health
  promotion and occupational health protection intervention in 26 small
  manufacturing businesses in Massachusetts (6). HD–HC was a health-center–based intervention in 10
  community health centers in metropolitan Boston (7). The two intervention
  studies were aimed at four primary outcomes: increasing fruit and vegetable
  consumption, decreasing red meat consumption, increasing daily multivitamin
  use, and increasing physical activity. In both studies, the organization was
  the unit of randomization and intervention, and the individual worker or
  health center member was the unit of observation. Group-randomized trials are those in which groups of individuals are 
  randomized to study conditions, but observations are made on the individuals 
  within the groups (8). An advantage of this design is the ability to enhance 
  the intervention effectiveness through the social interactions among members 
  of the groups randomized. The main disadvantage is the loss of statistical 
  efficiency due to the correlation in behavior among members of the same group 
  (9). This study design has been increasing in popularity over the last 25 
  years, especially for the evaluation of community-based interventions (10). 
  Planning for such studies requires estimates of the within-group correlation of the proposed 
  outcome measures, yet published estimates for specific behaviors and 
  populations are hard to find because there are few publications that include 
  these values in reports of results. This report focuses on our success in recruiting multiracial and 
  multiethnic working-class participants. We compare the characteristics of the participants
  with selected characteristics of the larger population within which they reside, and we provide
  point estimates of the outcome measures and estimates of the intraclass
  correlation coefficients (ICCs). The ICC is the fraction of the total 
  variation in a measure that is attributable to the clustering of the behavior 
  by members of the same group in comparison with members of different groups 
  (i.e., the health center or worksite). 
  This information is important for researchers planning group-randomized trials 
  in diverse working-class populations. Back to top MethodsThe methods of both studies were approved by Dana-Farber Cancer Institute’s 
  Office for the Protection of Research Subjects and the Harvard School of 
  Public Health’s Human Subjects Committee. Additionally, the methods of the 
  small business study were approved by Beth Israel Deaconess Medical Center’s 
  Committee on Clinical Investigations, and the methods of the health centers 
  study were approved by Harvard Vanguard Medical Associates–Department 
  of Ambulatory Care and Prevention. Study populationsSmall Business  For HD–SB, we identified 224 worksites through D&B
  (The D&B Corp, Short Hills, NJ; www.dnb.com*) listings of manufacturing
  businesses with Standard Industrial Classification (SIC) codes 20–39 (U.S.
  Department of Labor, Occupational Safety & Health Administration,
  Washington, DC; www.osha.gov/pls/imis/sicsearch.html) located in the
  metropolitan Boston area and employing between 30 and 150 workers. Businesses
  with these SIC codes were selected because they are more likely than those in
  other sectors to use potential carcinogens in work processes and thereby are
  suitable for cancer prevention interventions that integrate health protection 
  and health promotion. Further eligibility criteria included: 1) employing a
  multiracial and multiethnic population, defined as 25% of workers being first- or
  second-generation immigrants or people of color; 2) having an employee turnover rate of
  less than 20% in the previous year; and 3) being autonomous in decision-making
  power to participate in the study if part of a larger parent company. Of the
  224 businesses initially identified, 197 (88%) completed the prerecruitment
  survey assessing these eligibility criteria and, of these, 131 (66%) met
  the criteria. Finally, companies had to consent to being randomized to receive the
  behavioral and occupational health intervention and to provide time at work
  for employees to complete assessment surveys and to participate in the
  intervention activities. Of the 131 eligible companies, 26 (20%) consented to
  participate in the study. Details of the recruitment process and comparison of
  worksites recruited and not recruited are provided elsewhere (11). Worksites ranged in size from 32 to 137 workers. All employees who met the
  following criteria were eligible to receive the interviewer-administered
  survey: 1) permanent employee, 2) worked 20 hours or more per week, 3) worked 
  onsite, and 4) spoke English, Spanish, Portuguese, or Vietnamese. Interviews
  were conducted in English, Spanish, Portuguese, and Vietnamese between May and
  December 2000. Of 2096 eligible employees, 1740 (83%) completed the survey. Health Centers Harvard Vanguard Medical Associates, a 14-center
  multispecialty medical group practice serving more than 270,000 patients in
  the greater Boston area, provided the venues for the HD–HC study. We
  selected the 10 health centers with the most racial, ethnic, and socioeconomic
  diversity for this study. A random sample of health center members was
  selected from each center using a list of eligible patients and a random 
  number generator. Eligibility criteria included: 1) living in an
  eligible neighborhood (see below); 2) being 18 to 75 years old; 3) having a
  well-care or follow-up visit scheduled with a participating provider; 4) being
  able to speak and read either English or Spanish (unlike the worksites, 
  Portugese and Vietnamese were not commonly spoken languages); 5) not having cancer at the
  time of enrollment; and 6) not being employed by the participating health
  centers or a worksite participating in the small business study. Eligible
  neighborhoods were defined as census block groups that were predominantly
  working class (66% or more of employed persons are in working-class
  occupational groups comprised predominantly of nonsupervisory employees); or
  met the federal definition of a “poverty area” (20% or more of the
  population lives below the poverty line); or had low levels of education (25%
  or more of the adult population has not completed high school) (12). All 117 providers (physicians, nurse practitioners, and physician
  assistants) practicing in the internal medicine departments of those centers
  were approached for permission to recruit from among their patients. A total
  of 97 (83%) of the 177 clinicians participated, with no differences in the rates of
  clinician participation between the intervention and control conditions.   We identified patients in the eligible age range who were
  scheduled for appointments with one of the participating providers through the
  health center’s automated central appointment system. To determine whether a
  potential participant lived in an eligible neighborhood, the residential
  address was geocoded to the census block group, a subdivision of the census
  tract and the smallest census geographic area (approximately 1000 people) that
  provides socioeconomic data. Socioeconomic data from the 1990 Census were used
  to identify eligible neighborhoods. Geocoding was conducted by a commercial
  firm with verified high accuracy (96%) (13). Potential participants received a letter describing the study and providing
  a number to call if they did not want to participate. Members who did not
  reply within 2 weeks were then contacted by telephone, and after their
  eligibility was confirmed, they were invited to participate. If they
  consented, they completed the oral survey at that time or made an appointment to be
  interviewed by telephone at another time. Study staff attempted to recruit
  8963 potentially eligible candidates during 2000 and 2001. Of these, 2547 were
  unreachable. Among the 6416 who were reached, 867 (14%) were ineligible; 3330
  (52%) refused to participate and 2219 (35%) were enrolled. Assuming that 14% of those
  unreachable were also ineligible, the response rate is 29% of those assumed
  eligible. MeasuresEach survey included a core set of items in addition
  to items unique to that project which reflected mediating and moderating
  variables. Sociodemographic Characteristics We assessed three dimensions of
  socioeconomic position (education, poverty status, and occupational class) and
  two dimensions of race and ethnicity (racial or ethnic identification and
  whether the respondent and his or her parents were born in the United States).
  Respondents reported their educational level in nine categories, which we
  subsequently collapsed to four (did not complete high school, high school
  diploma or equivalent, some post-high-school training, and baccalaureate
  degree or more). Household income was assessed in $10,000 increments from less
  than $10,000 per year to $50,000 per year or more. We combined the responses to this
  item with number of people supported by the income and the ages of household
  members to categorize respondents according to the federal poverty guidelines
  for food aid (14). In 2001, the poverty guideline for a single person was
  $9,214; for a family of two adults and two children it was $17,960. The
  guideline for eligibility for food stamps and The Special Supplemental
  Nutrition Program for Women, Infants, and Children (WIC) is no more than 185% of the
  poverty guideline. Respondents were classified as below the poverty guideline,
  above the poverty guideline but below 185% of the guideline, or above 185% of
  the poverty guideline.  We combined information about the respondent’s current or most recent job
  title into a three-category occupational class variable: working class
  (clerical, sales, skilled or unskilled labor), professional/managerial
  (professional, managerial, or technical), or no job title. This latter group
  included health center participants who were homemakers, disabled, and others
  who were not in the paid labor force and did not report a recent job title. Participants were asked whether they were of Hispanic or Latino heritage
  and whether they belonged to any of the four racial groups. We coded participants
  who reported being of Hispanic or Latino origin in the Hispanic group
  regardless of any other responses. For the rest, those who reported only one
  racial group were categorized in that group (i.e., American Indian or Alaska
  Native, Asian or Pacific Islander, black or African American, or white).
  Respondents who selected more than one racial group were classified as
  multiple heritage and were subsequently classified as those who included white
  and those who did not. We combined information about the participants’ and their parents’ birth 
  places into the following three-category measure of immigration status: 
  participant born outside the United States (defined as outside the 50 states and the
  District of Columbia), participant born in the United States but one or more parents
  born outside the United States, and participant and both parents born in the 
  United States.
  Respondents were also asked their birth date and sex. Health Behaviors The target levels of the health behaviors, based
  on well-established recommendations (1,15,16), were: five or more servings of
  fruit and vegetables per day, three or fewer servings of red meat per week,
  daily multivitamin use, and at least 2.5 hours of moderate or vigorous
  physical activity per week. For each 
  of the target behaviors we dichotomized the continuously scaled summary 
  measures at the intervention target level so that we could compute the 
  percentage of participants who met the intervention target. Servings of fruits and vegetables consumed per day were assessed using a screener (17-19) 
  that asked about usual consumption over
  the last 4 weeks of seven common foods (orange and grapefruit juice, other
  fruit juice, green salad, fried potatoes, potatoes other than fried, fruit,
  and other vegetables). For each food, respondents chose 1 of 10 precoded
  responses from never to five or more times per day. The responses were recoded
  to equivalent servings per day and summed to obtain total fruit and vegetable
  servings per day. We then computed a dichotomous measure of either five or
  more servings per day or less than five servings per day. Servings of red meat were assessed using an abbreviated form of the
  semiquantitative food frequency questionnaire (20). The screener asked about
  usual consumption over the last 4 weeks of six common foods (processed
  meat; hamburger; beef, ham, pork, or lamb in a sandwich or mixed dish; 4 to 6
  ounces of beef, ham, pork, or lamb as a main dish; 4 to 6 ounces of poultry;
  and 3 to 5 ounces of fish). The six response categories ranged from never to
  one or more times per day. The responses were recoded to equivalent servings
  per week and summed for total servings of red meat per week. The totals were
  dichotomized to three or fewer servings or more than three servings per week. We based our physical activity assessment on the questionnaire used in the
  Nurses’ Health Study (21). We asked how often on average in the last four
  weeks respondents engaged in each of eight moderate or vigorous leisure
  activities. We adapted the items to include specific activities that might be
  more common in the study population. Activities included walking for exercise;
  jogging; running; bicycling; aerobics or aerobic dancing; lifting weights;
  playing soccer, rugby, basketball, lacrosse, baseball, or football; or other
  activities that get the respondent out of breath. There were eight response
  categories ranging from never to more than 6 hours per week. In addition, we
  asked about usual walking pace. The responses were recoded to equivalent
  minutes per week and summed for total minutes of physical activity per week.
  Walking was included if usual pace was reported to be faster than “easy,
  casual.” The sum was collapsed to 150 minutes (2.5 hours) or more per week or more
  compared with fewer than 150 minutes per week. Furthermore, we asked respondents on average how many days they take a
  multivitamin. Respondents were coded as taking a multivitamin daily if they
  reported taking one 6 or 7 days per week. Data analysisFor each study sample, we report the number and percentage of participants
  according to the measures of sociodemographic characteristics and their levels
  of health behaviors. For comparison purposes, we also present available 2000 
  census data for the consolidated
  metropolitan statistical area (CMSA) covering eastern Massachusetts (22). We
  present the sex distribution for the population aged 18 years and older,
  educational attainment for the population aged 25 years and older,
  occupational class for the employed population aged 16 years and older, and
  percentage below the poverty line for individuals aged 18 years and older. We
  report race and ethnicity (Hispanic and non-Hispanic white) and percentage
  of non-U.S.–born for the population as a whole. For each health behavior, we computed the adjusted percentage of
  respondents who practice the behavior, controlling for the clustering of
  participants in randomization units, health centers, or worksites. We also
  computed the ICC of each health behavior in each study. The adjusted
  percentages and ICCs were computed using linear logistic regression analysis
  with group (health center or worksite) as a random effect (8). Computations were carried out using the GLIMMIX macro to the SAS
  statistical software (SAS Institute Inc, Cary, NC) (23,24). Back to top ResultsSociodemographic characteristics of the two samplesTable 1 shows the sociodemographic 
  characteristics of the two samples and of the greater Boston area. The 
  population of the eastern Massachusetts CMSA is 81%
  non-Hispanic white, compared with 68% of the HD–SB sample and 59% of the HD–HC
  sample. The HD–SB sample included 13% Hispanic or Latino ethnicity and
  approximately equal percentages of blacks (5%) and Asians (7%). In the HD–HC
  sample, 26% were black and 8% were Hispanic. About one third (34%) of the HD–SB
  participants and 22% of the HD–HC participants were born outside the United 
  States. Additionally, 10% of the U.S.-born HD–SB participants and 18% of the 
  U.S.-born HD–HC 
  participants had a parent or parents who were born outside the United States. In the eastern Massachusetts CMSA, 41% of the adults have a high school education or less,
  slightly less than those in the HD–SB sample (46%) but more than those in the 
  HD–HC sample (28%). Only 24% of the HD–SB participants were professional,
  managerial, or technical workers. The remaining 76% were employed in 
  working-class occupations (i.e., clerical, sales, skilled or unskilled labor). Among
  HD–HC participants, approximately equal percentages were employed in
  professional, managerial, or technical positions (45%) and in working-class
  occupations (44%). In the greater Boston area, 57% of employed adults are
  employed in working-class occupations. Although most of the participants in
  both studies were at or above 185% of the poverty guideline, 15% of HD–SB
  participants were below this cut point, even though they were all employed. In
  the HD–HC sample, 18% of participants were below 185% of poverty. At baseline, most participants in both studies did not meet the
  intervention targets for fruit and vegetable consumption and daily
  multivitamin use (Table 2). In the HB–SB study, most participants did not
  meet the target for red meat consumption, but among HB–HC participants,
  almost half met that target. Surprisingly high percentages (73% for HB–SB
  and 65% for HB–HC) of participants reported at least 2.5 hours of physical
  activity per week in both studies. Estimates of  ICCs for the primary outcomesTable 3 presents the adjusted prevalence of each health behavior
  controlling for the clustering of respondents in randomization units, along
  with the ICC. The adjusted prevalences of the target behaviors are very
  close to the unadjusted prevalences presented in Table 2. The ICCs for the
  four target behaviors in HD–SB were between 0.006 and 0.02, indicating a
  small level of concordance among workers in the same worksites. In the HD–HC
  study, the ICCs were considerably smaller, ranging from 0.0004 to 0.003. Back to top DiscussionThese two studies were successful in sampling a multiracial and multiethnic
  subpopulation of eastern Massachusetts residents. The sampling strategies of
  both studies reached a subpopulation that is more heterogeneous in racial and
  ethnic make-up than the greater Boston area. Furthermore, the HD–SB sample
  has a larger percentage of members with working-class occupations and those
  with a high school education or less than the general population of adults.  Health
  disparities in the United States are often described in terms of racial or ethnic
  inequalities; yet, within racial and ethnic groups, there is
  variability in both socioeconomic position and morbidity and mortality risk.
  Nevertheless, populations of color bear a disproportionate burden of poverty
  (25-27). It is well known that socioeconomic deprivation adversely affects
  health and increases mortality (12,28). The concepts of social class and
  socioeconomic position are complex and encompass occupational class, income,
  poverty, wealth, education, and prestige or status at the individual,
  household, and area levels (12). We have measured two dimensions of race and
  ethnicity and three of socioeconomic position. Maintaining these separate
  characteristics, rather than attempting to define a single measure of
  socioeconomic position, will allow us to explore the interactions among them
  in understanding the determinants of successful interventions. Small percentages of the study sample respondents lived in households that
  were below the poverty threshold, as expected among a population of working-class participants and
  those with health insurance. Nevertheless, a substantial proportion of our
  samples would be eligible for food aid — 15% in the HD–SB sample and 18% in
  the HD–HC sample. These categorizations do not take into consideration
  regional differences in cost of living. The greater Boston area is one of the
  most expensive areas in the country; the self-sufficiency standard for a
  family of four in that area was $42,564 in 1998 and $54,612 in 2003 (29). Although both study samples represent multiracial and multiethnic 
  working-class populations, the two samples differ from one another. The HD–SB sample was
  somewhat younger and included more men than the HD–HC sample. The HD–SB
  sample had a higher percentage of Asian and Hispanic respondents and a higher
  percentage of recent immigrants than the HD–HC sample. The HD–HC sample
  had a higher percentage of participants with household incomes below 185% of
  poverty than the HD–SB sample. The HD–SB sample has a higher percentage of
  respondents with less than a high school education than the HD–HC sample. The differences between the two study samples in the levels of the health
  behaviors reported by the participants reflect these sociodemographic
  differences. The workers in the HD–SB sample were more physically active
  than those in the HD–HC sample were, and a higher percentage of the HD–HC
  sample members reported taking a multivitamin daily. These differences may be
  attributable to the differences in age, sex, education, or other factors.
  Despite these differences in health behavior practices, the percentages of
  respondents in both samples who were at lower levels of the target behaviors
  are high, indicating a need for the behavior change interventions in both
  subpopulations. The mean hours of physical activity reported by members of both samples is
  surprisingly high. Although we asked about leisure time activity, participants
  may have conflated their reports to include activities related to occupational
  activities, domestic chores, childcare, and walking for transportation, for
  example. A small validity study done in conjunction with this project
  indicated, however, that total hours of activity were reported accurately
  (data not shown). The response rate to the baseline survey in HD–HC was low, due in part to
  the fact that potential participants were agreeing to participate in a
  randomized trial, not just a health survey. This is similar to the low
  recruitment rate for the businesses in the HD–SB study. The internal
  validity of the intervention trials is assured by randomization, and the
  survey is a valid baseline assessment of the levels of behaviors in the two
  intervention groups prior to intervention implementation. For other
  researchers who might use the baseline measures and ICCs to plan studies, the
  generalizability to health center members and workers in worksites who would
  consent to participate in such a study is also appropriate.   Planning for group-randomized trials of the effectiveness of interventions
  targeting modifiable health behaviors requires estimates of the means,
  variances, and ICCs of the behaviors within the study population of interest
  (8,10). The estimates reported here apply to four specific health behaviors
  and two types of randomization groups. The estimated ICCs in the HD–SB
  sample are similar to those found in other worksite-based intervention studies
  (30). The estimated ICCs in the HD–HC sample are lower than those in the HD–SB
  sample are but are similar to those at the district health authority level in
  England (31). Nevertheless, the ICCs in both studies are sufficient to
  influence the error variance of the test statistic for evaluating the
  effectiveness of the intervention and must be included in power calculations
  for group-randomized studies. In summary, the procedures developed by these two intervention studies to
  sample multiracial and multiethnic working-class populations in eastern
  Massachusetts were successful in identifying such groups. These samples are
  more diverse in their racial and ethnic make-up and other sociodemographic
  characteristics than the greater Boston  population. Although the
  subpopulations resided in the same geographic area and may overlap in other
  ways, the HD–HC sample was restricted explicitly to exclude anyone in the HD–SB
  sample. Despite the close proximity of these two subpopulations, they differ
  in ways that would be expected by their provenance. Furthermore, both samples
  represent populations with high percentages of members who have cancer-related
  risk behaviors. There has been a call for research on the effectiveness of interventions
  targeting modifiable health behaviors (28), yet intervention approaches have
  not been designed for or sufficiently tested in working class, ethnically
  diverse populations (32). Our explicit aim was to recruit from the large
  multiracial and multiethnic group of working-class men and women at elevated risk
  for adverse health outcomes. This group is confronted with constraints and
  limited resources that may influence patterns of health behaviors. We have
  developed behavioral interventions that respond to the social contextual
  realities of this group  as an approach to reducing the excess burden of
  cancer borne by communities of color and lower socioeconomic position (4). To
  fully evaluate the effectiveness of these interventions, it is important to
  study a diverse population. Future manuscripts will report on the
  effectiveness of the interventions in promoting change in the behaviors and
  the influence of the social context on behavior and behavior change. Back to top AcknowledgmentsThis work was supported by a grant from the National Cancer
  Institute (P01 CA75308). The studies and analysis reported were the product of
  the authors and not the NCI. Back to top Author InformationCorresponding Author: Anne M. Stoddard, ScD, New England Research
  Institutes, 9 Galen St, Watertown, MA 02472. Telephone: 617-932-7747, ext 331.
  E-mail: astoddard@neriscience.com. Author Affiliations:  Nancy Krieger, PhD, Martha E. Fay, MPH, Department of Society,
  Human Development and Health, Harvard School of Public Health, Boston, Mass; Elizabeth M. Barbeau, ScD, Gary G. Bennett, PhD, Glorian Sorensen, PhD, MPH, Karen Emmons,
  PhD, Department of Society, Human Development and Health, Harvard School of Public
  Health, and Center for Community Based Research, Dana-Farber Cancer Institute, 
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