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  • Subjects: Los Angeles Family and Neighborhood Survey (L.A.FANS): Wave 1 L.A.FANS participants included a representative cross-sectional sample of all households across 65 neighborhoods (census tracts) of in Los Angeles County; poor neighborhoods and families with children were oversampled. [25], [26] Participant interviews were completed between April 2000 and January 2002, with high completion rates among respondents selected for interview, 89% of primary care givers, 87% of randomly selected children, and 86% of siblings of randomly selected children. Interviews were successfully completed for 3200 children and adolescents (ages 0–17 years), with a balanced distribution across age groups. Wave 1 participants provided data on individual, familial, and neighborhood factors, for themselves and household members; census data was also incorporated to provide social characteristics of each neighborhood, such as poverty levels and racial/ethnic composition. Our analyses included 3,114 children and adolescents (ages 0–17 years) with data on our outcome of interest. We ascertained child’s lifetime asthma status via the primary caregiver’s report of an asthma diagnosis within the parent module of L.A.FANS. Children were categorized as asthmatic if the primary caregivers reported a positive response to the following item: “has a doctor or other health professional ever told you that [child’s name] has asthma?” Similar questions to ascertain asthma diagnosis have been used within the International Study of Asthma and Allergies in Childhood (ISAAC) survey and the National Survey of Children’s Health [27], [28] Over 97% of children within L.A.FANS had a response to this question. Perceived neighborhood safety was measured by several items administered in the adult module of L.A.FANS. Experiences of neighborhood crime were assessed via response to the following item, “while you have lived in this neighborhood, have you or anyone in your household had anything stolen or damaged inside or outside your home, including your cars or vehicles parked on the street?” An additional measure of perceived neighborhood safety was captured through the adult’s extent of agreement with the following item, “you can count on adults in this neighborhood to watch out that children are safe and do not get in trouble”; response options for this item were strongly agree, agree, unsure, disagree, and strongly disagree. Participants were also asked how safe is it to walk around alone after dark within your neighborhood, with response options as extremely safe, somewhat safe, somewhat dangerous, or extremely dangerous. At the individual level, child’s age, gender, and race/ethnicity were included. At the household level, we examined primary caregiver’s education (years), primary caregiver’s history of asthma, and primary caregiver’s current smoking status, health insurance status, and use of public assistance within the past 12 months. Covariates controlling for the home environment include whether the interviewer observed the presence of crowding, cleanliness or clutter, and potential health or structural hazards inside and immediately outside of the home at the time of the interview. To examine associations between asthma outcomes and perceived neighborhood safety, individual, and family characteristics, we conducted a series of two level multilevel logistic regression models of 3,114 children at level 1 nested within 65 census tracts at level 2. Use of multilevel modeling allows us to account for natural and sampling induced nesting within L.A.FANS, as well as model contextual heterogeneity; directing inquiry away from average effects, to inquire about differences and examine potential neighborhood variation in asthma. [29] Multilevel models are also appropriate when causal processes are thought to operate at more than one level; as asthma is a multi-factorial disease which is influenced not only by compositional factors (such as genetics) but also by contextual factors (such as neighborhood violence), single level regression models would be inappropriate. [30] We first examined the effects of neighborhood safety characteristics on the odds ratio of reporting an asthma diagnosis (Model 1) and subsequently adjusted for the effects of individual characteristics (Model 2), followed by primary caregiver’s characteristics (Model 3), and lastly physical characteristics of the indoor home environment and neighborhood poverty (Model 4). Quasi-likelihood methods were used to estimate the coefficients beginning with marginal quasi-likelihood (MQL) with 1st order Taylor linearization to obtain starting values for 2nd order penalized quasi-likelihood (PQL) approximation. Data manipulation and descriptive analyses were conducted using STATA 11, while multilevel models were conducted using MLwiN version 2.10. The data were collected by the RAND Corporation in collaboration with the UCLA School of Public Health. Written consent for participation in the study was obtained for L.A.FANS respondents by RAND Corporation in collaboration with the UCLA School of Public Health. Data for secondary analyses were obtained through submission of a restricted application process which included a data safeguarding plan, data user agreement, and IRB review. The research was approved by the Harvard School of Public Health Office of Human Research Administration.
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