Sampling procedures
Data were derived from the baseline examination of a population-based cohort study called EpiFloripa carried out in Florianopolis, Southern Brazil, from September 2009 to January 2010 (http://www.epifloripa.ufsc.br). The objective of the EpiFloripa study was investigating health and life conditions of the adult population of the city. The study was conducted for teachers, and post-graduate students from the Federal University of Santa Catarina, from different departments. Furthermore, researches of other institutions collaborate in the design and analysis of EpiFloripa Study. The second wave of Epifloripa study began in 2011. Florianopolis is the capital of the state of Santa Catarina, with a population of 421,240 inhabitants [24], and presents a Gini Index of 0.40, lower that the country average (0.54) [24]. However, it still has striking social inequalities and, around 14% of population lives in poor housing conditions [25].
We selected 60 of the 420 urban residential census tracts of the city. All 420 urban census tracts of the city were ranked according to the average monthly income of the head of the family [26] classified into income deciles. Six tracts were randomly selected in each income decile. All selected census tracts were visited by the fieldwork team, and all occupied houses were enumerated. The enumeration identified some changes in the sizes of the census tracts. To reduce the variability in the number of households in each census tract, some of them were split and others aggregated taking into considering their income decile and geographic localization. This process resulted in sixty-three census tracts with 16,755 eligible households. Within each census tract we systematically selected 18 occupied households. In each household all adults were invited to take part in the survey.
Eligibility and exclusion criteria
All adults aged 20 to 59 years who were residents in the selected houses were eligible to participate. Exclusion criteria included amputees, bedridden individuals, individuals who could not remain in the proper position for the required measurements, and those who were unable to answer questionnaire due to physical or cognitive impairments. Anthropometric and blood pressure measurements were not obtained from pregnant women. Women who had delivered a baby within the past 6 months were excluded. We attempted to find all eligible adults in their home at least four times, with at least one visit on weekends and another in the evening; cases in which the interviewer could not locate the interviewee or there was a refusal to participate were considered losses.
Data collection
Before initiating data collection the questionnaire was pilot tested on 35 individuals and the procedures were pilot tested on 100 individuals who were not study participants Home visits included the administration of a face-to-face questionnaire, two blood pressure measurements, and anthropometric measurements such as weight and height. All interviewers (n = 35) were trained prior to field work.
Outcome
Participant reports of perceived neighborhood problems were the dependent variables. Neighborhood perceptions were evaluated based on responses to 16 items referring to: garbage, uneven pavements, unpleasant smells, air, water or ground pollution, lack of safe place to children play, traffic speed, urban transport, vandalism, burglaries, assaults, murders, drug use, safety walking after dark, bad reputation, and police problems. These items were adapted from a questionnaire developed by Ellaway et al. [27]. For each item the response options were none, some or many problems (related to the specific item) in the neighborhood, for analysis those options were codded as zero, one, or two, respectively.
Group-level covariates
We used the tertiles of the household head of the family average monthly per capita income from the 2000 Brazilian census (http://www.ibge.gov.br) for each of the 63 census tracts.
Individual-level covariates
The individual covariates included sex, age (years), educational attainment (12y and more, 9-11y, 5-8y or 0-4y), total of earnings in the last month by the household residents divided by the number of residents -per capita income in Reais (R$) (Brazilian currency; US$ 1.0 = R$1.7, during the period of data gathering), race/self-reported skin color (white, brown, and black) [24], length of time living in the neighborhood (years), and occupational status which was classified according the British Registrar General’s Social Class [28] (manual or non manual job, students, housekeeping; individual who had never worked at the moment of data gathering, were placed in a separate category).
Reliability was assessed by administering a short version of the questionnaire (n = 10) to 15% of the whole sample (n = 248) using a telephone interview. Reliability is defined as the extent to which the questionnaire produces the same results on repeated trials. The measure can be used to assess the stability or consistency of scores over time or across raters [29].
Kappa statistics and the intra-class correlation coefficient were calculated to assess reliability, and the values ranged from 0.6 (pain, medicine use and dental prosthesis) to 0.9 (length of residence time in the same neighborhood).
Statistical analysis
In order to group perceived neighborhood items in scales, we performed a principal factor analysis of all neighborhood questionnaire items after polychoric transformation [30], using orthogonal rotation. The scree test, factor loadings, scale internal consistency, and theoretical considerations were applied to define the number of factors to be extracted, as well as the items comprising each scale. The Cronbach’s Alpha was calculated to measure the internal consistency of the scales [31]. Sample size adequacy for factor analysis was evaluated using the Kaiser-Meyer-Olkin (KMO) test [32]. The values of KMO test ranged from 0.81 to 0.94 for vandalism and assaults, respectively, and the global value was 0.88.
Furthermore, assessing the measurement properties of ecological settings moves beyond an assessment of the psychometric properties to what has been termed ‘ecometrics’ [16]. Ecometrics is an extension of the two levels implicit in traditional psychometric assessments (scale item response nested within individuals) because it introduces a third level of neighborhoods. It allows the quantification not only of how consistently individuals respond to the different component items of a scale (the internal consistency measure of psychometrics) but also the extent to which residents of the same neighborhood rate their neighborhood similarly [16].
The ecometric properties of the neighborhood scales were assessed using three-level multilevel models [11]. Level 1 corresponds to item responses within individuals. Level 2 corresponds to persons nested within neighborhoods and finally level 3 corresponds to neighborhoods. Through those analyses variance components were estimated for each level: within-person, within-neighborhood, and between-neighborhood, for levels: 1, 2, and 3, respectively.
Using this estimates, we calculated the intra-class (intra-neighborhood) correlation coefficient (ICC), and the reliability of the neighborhood-level measure. The ICC quantifies the percentage of variability in the scale score that lies between neighborhoods [33]. The ICC ranges from 0 to 1, with a higher value indicating greater agreement between respondents within a neighborhood.
The neighborhood level reliability of the neighborhood score [11, 33] is a function of the ICC as well as the number of participants in each neighborhood (n
jk). It is calculated as the ratio of the “true” score variance (portion of the score which is replicable or reliable) to the observed score variance in the sample neighborhood mean, with values ranging from 0 to 1. The reliability will be high (close to 1) when: 1) the neighborhood means vary substantially across neighborhoods (holding constant the sample size per group), or 2) the sample size per neighborhood is large. Furthermore this measure also increases when the number of scale items raises.
The three-level multilevel analysis allowed the estimation of Bayesian estimates [11]. Crude scores were tested in relation to individual and census tract level variables. In order to evaluate the convergent validity, related to spread which scales were associated with other neighborhood characteristics in the expected direction, were investigated associations among perceived neighborhood scales and familiar per capita income from the Brazilian Census [24].
We fitted three different models for each neighborhood scale. The first model included demographic variables (sex, age, skin color and length of time living in the neighborhood); the second model added individual-level socioeconomic characteristics (per capita familiar income, educational attainment and occupational status), and the third model added census tract income. All variables were kept in the model. The ICC was calculated for each model.
The software STATA, version 12.0 was used to perform these analyses. Univariate and bivariate analyses were performed, taking the complex sample into account, considering unequal probability to participate of data gathering of residents from different census tract (weighted and clustered sample). All multilevel models were also weighted.
Ethical issues
The research project approved by the Ethics Committee of Research in Human Subjects of the Federal University of Santa Catarina – number 351/08. Informed consent was obtained from all participants.