Group Title: BMC Public Health
Title: Rating neighborhoods for older adult health: results from the African American Health study
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Title: Rating neighborhoods for older adult health: results from the African American Health study
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Language: English
Creator: Andresen, Elena
Malmstrom, Theodore
Wolinsky, Fredric
Schootman, Mario
Miller, J. P.
Miller, Douglas
Publisher: BMC Public Health
Publication Date: 2008
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Abstract: BACKGROUND:Social theories suggest that neighborhood quality affects health. Observer ratings of neighborhoods should be subjected to psychometric tests.METHODS:African American Health (AAH) study subjects were selected from two diverse St. Louis metropolitan catchment areas. Interviewers rated streets and block faces for 816 households. Items and a summary scale were compared across catchment areas and to the resident respondents' global neighborhood assessments.RESULTS:Individual items and the scale were strongly associated with both the catchment area and respondent assessments. Ratings based on both block faces did not improve those based on a single block face. Substantial interviewer effects were observed despite strong discriminant and concurrent validity.CONCLUSION:Observer ratings show promise in understanding the effect of neighborhood on health outcomes. The AAH Neighborhood Assessment Scale and other rating systems should be tested further in diverse settings.
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Research article


Rating neighborhoods for older adult health: results from the
African American Health study
Elena M Andresen*1, Theodore K Malmstrom2, Fredric D Wolinsky3'4,
Mario Schootman5, J Philip Miller6 and Douglas K Miller7'8


Address: 'Department of Epidemiology and Biostatistics, College of Public Health and Health Professions, University of Florida Health Sciences
Center, PO Box 100231 Gainesville, FL 32610, USA, 2Department of Neurology & Psychiatry, School of Medicine, Saint Louis University, 1438
South Grand Boulevard, St. Louis, MO 63104, USA, 3Iowa City Veterans Affairs Medical Center, Highway 6 West, Iowa City, Iowa 52246, USA,
4Department of Health Management and Policy, College of Public Health, University of Iowa, 200 Hawkins Drive, E205 General Hospital, Iowa
City, Iowa 52242, USA, 5Departments of Medicine and Pediatrics, School of Medicine, Washington University, Campus Box 8504, 660 South
Euclid Avenue, St. Louis, MO 63110, USA, 6Division of Biostatistics, School of Medicine, Washington University, Campus Box 8067, 660 South
Euclid Avenue, St. Louis, MO 63110, USA, 7Indiana University Center for Aging Research, School of Medicine, Indiana University, IN, USA and
8Regenstrief Institute, Inc., 410 West 10th Street, Suite 2000, Indianapolis, IN 46202, USA
Email: Elena M Andresen* andresen@phhp.ufl.edu; Theodore K Malmstrom malmsttk@slu.edu; Fredric D Wolinsky fredric-
wolinsky@yiowa.edu; Mario Schootman mschootman@im.wustl.edu; J Philip Miller jphiliomiller@wustl.edu;
Douglas K Miller dokmille@iupui.edu
* Corresponding author



Published: 25 January 2008 Received: 10 January 2007
BMC Public Health 2008, 8:35 doi: 10.1 186/1471-2458-8-35 Accepted: 25 January 2008
This article is available from: http://www.biomedcentral.com/1471-2458/8/35
2008 Andresen et al; licensee BioMed Central Ltd.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0),
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.



Abstract
Background: Social theories suggest that neighborhood quality affects health. Observer ratings of
neighborhoods should be subjected to psychometric tests.
Methods: African American Health (AAH) study subjects were selected from two diverse St.
Louis metropolitan catchment areas. Interviewers rated streets and block faces for 816 households.
Items and a summary scale were compared across catchment areas and to the resident
respondents' global neighborhood assessments.
Results: Individual items and the scale were strongly associated with both the catchment area and
respondent assessments. Ratings based on both block faces did not improve those based on a single
block face. Substantial interviewer effects were observed despite strong discriminant and
concurrent validity.
Conclusion: Observer ratings show promise in understanding the effect of neighborhood on
health outcomes. The AAH Neighborhood Assessment Scale and other rating systems should be
tested further in diverse settings.



Background nomic status (SES) and measured by such individual
Researchers and practitioners have long noted the correla- factors as income, poverty, education, and other social cir-
tion between the social disadvantage of populations and cumstances. Nonetheless, a number of aspects of the built
individuals, and their health. In the U.S.A., social disad- and natural environments of the places people live have
vantage is usually operationalized as individual socioeco- come under increasing scrutiny. Researchers and practi-


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tioners embrace the concept that "place matters" in pro-
ducing disparate health outcomes [1-7]. Despite the
theoretical importance of the effects of neighborhoods on
health outcomes, few studies incorporate independent
observer ratings of neighborhood conditions. Methods
and measures that objectively rate people's physical
neighborhoods have not been accompanied by published
documentation of development or by methodological
tests to gauge possible problems in validity and reliability.

Disparate theories and applied research examples do not
produce consensus on which contextual factors to meas-
ure, nor agree on a uniform size and definition of the
appropriate spatial size that influences health [2,3,8-14].
In our ongoing cohort study of African American adults in
the St. Louis metropolitan area, we theorize that, in addi-
tion to individual SES characteristics, place matters [5].
The overall study goals address issues of health disparities
by investigating risks for adverse outcomes within an Afri-
can American cohort, rather than focusing on compari-
sons with other race and ethnic groups. This approach
eliminates the issue of confounding by race for our cohort
results. We explicitly incorporated multiple spatial levels
in sampling and in our measures. In addition to sampling
from two geographic areas of different composite SES
(below), we included direct observer ratings of neighbor-
hoods. For the purposes of our study, the block on which
the respondent lived was used as a proxy for a larger
implicit level of "neighborhood."

Neighborhood assessment at the cohort inception (wave
one) was based on an evaluation of the external appear-
ance of the block on which the respondent lived. Survey
team members completed this assessment during the
process of household enumeration in March and April of
2000. The 5-item scale was based on work by Krause [15]
and had been used specifically in research with older
adults. The component items included the condition of
houses, amount of noise (from traffic, industry, etc.), air
quality, condition of the streets, and condition of the
yards and sidewalks in front of homes, and each item was
rated excellent (1 point), good (2 points), fair (3 points),
or poor (4 points). This assessment tool had acceptable
psychometric properties, but we were not satisfied with its
discriminative ability or its inter-rater reliability [16]. Fur-
ther, we found a marked tendency for raters to choose
"good" ratings for most items (48% to 68% of all ratings
among the five items were rated "good"). This also
impacted the summary scores: 38% of all scale scores were
10.0 points (all 5 items rated "good"). Finally, when mod-
eling the association of neighborhood on scale scores, we
found that interviewers and characteristics of interviewers
also contributed to different ratings. As part of the fourth
wave, which was an in-home assessment (2004), we
strove to select and test an improved observer rating


method for future analysis of the impact on health out-
comes. We performed a small pilot to select a candidate
method, and then conducted three phases of analyses to
test the instrument. Phase 1 assessed items and produced
a potential brief scale; phase 2 tested the discriminant and
concurrent validity of items and the scale; and phase 3
examined potential interviewer effects.

Methods
Participants
The baseline sampling strategy for the African American
Health (AAH) study involved two St. Louis geographic
areas that differ widely in SES [17-23]. One catchment
area is a poor, predominantly African American inner city
neighborhood where 24% of AAH respondents report
annual incomes under $10,000. The second catchment
area is a suburban, integrated neighborhood, where 8% of
AAH respondents report annual incomes under $10,000.
Households were sampled based on an enumeration of all
housing units in the two catchment areas with at least
10% African American households by the 1990 Census.
Characteristics of this cohort have been described in detail
elsewhere [19]. Briefly, a total of 998 African American
adults aged 49 to 65 (76 percent of eligible subjects) were
recruited from random sampling of households from two
strata: a poor, inner-city area of St. Louis (n = 463), and
the near Northwest suburbs (n = 535). The cohort
included 41.8% men at baseline and had a mean age of
56.8 years.

Most participants resided on a block on which no other
AAH participant resided (65.9%). Only 3.6 percent of
block faces contained five or more participants. For these
analyses, we did not analyze this nesting between and
within block faces because there was not enough cluster-
ing of participants within block faces to support a robust
multi-level analytic approach [17]. In addition, 73.1 per-
cent of AAH respondents lived at the same address for
more than five years before their baseline interview, and
nearly three-quarter (74.6%) lived at the same address
during all three years of follow-up [17].

In-person baseline interviews were conducted in 2000-
2001, annual telephone interviews were conducted dur-
ing waves two (2002) and three (2003), and for wave four
(2004), in-person interviews were conducted with 90.0%
of the surviving members of the cohort [17]. In prepara-
tion for the in-home assessment of cohort members, we
asked experienced interviewers on our team for their feed-
back about the rating tool we used in wave one [15,16].
They indicated that the scale lacked specific and objective
criteria to assess and chose rating levels. They also recom-
mended that more thorough training, use of visual exam-
ples, and question-by-question guidelines would be
required before consistent ratings among interviewers


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would be possible. In addition to the five-item assessment
instrument from wave one, we pilot tested two other
instruments with three core experienced AAH interviewers
during protesting of the in-home assessments. We used an
11-item form rating inside subjects' homes and their
neighborhood that was adapted from the National Longi-
tudinal Survey of Youth [24]. We also piloted a 20-item
block assessment adapted and simplified from the Project
on Human Development in Chicago Neighborhoods
[10]. We conducted preliminary training on all three
forms using pictorial examples of items (e.g., street condi-
tions, litter). Thirty-one subject neighborhood ratings
using all three forms were piloted during several weeks,
including written qualitative feedback by the interviewers.
These experiences were then debriefed with members of
the investigator team and field supervisor. Interviewers
universally considered the adapted "Chicago" form to be
the easiest to rate and the most objective of the three. We
therefore adopted this form.

Instrument
The adapted Chicago form obtains information about the
neighborhood generally (e.g., noise, dust, street) as well
as information about the two block faces of the street of
each research respondent (e.g., housing conditions, pres-
ence of security measures, presence of commercial prop-
erty). We trained interviewers using digital photo images
of neighborhood conditions with variations in conditions
that spanned the full range of the rating levels. After fur-
ther development and protesting of the training protocol,
including feedback from the interviewer team leaders and
field supervisor, we created a detailed training manual
and supportive material for the final wave four protocol.
Twenty-six interviewers were trained on specific aspects of
the rating protocol during approximately 2.5 hours of a
weeklong research protocol-training program. A follow-
up refresher session was conducted about a month after
initial training. Prior to the refresher session, we reviewed
the first 269 results of the neighborhood assessments and
found satisfactory variation in item responses. We were
specifically concerned with the possibility of very frequent
ratings for variables that asked about housing and street
qualities, and found no strong pattern of common ratings.
During the field interview period, team leaders met
weekly with their group of interviewers, at which time
neighborhood rating was discussed, as needed. Through
this mechanism, any uncertainty in the rating methods
and unusual circumstances were identified and remedied
quickly, and coding clarifications were circulated to all
interviewers.

Interviewers usually completed the neighborhood assess-
ment following a scheduled wave four, in-home visit that
averaged 99 minutes. If the interviewer expected the post-
interview period to fall after dusk, the neighborhood


assessment was performed in daylight hours before the
appointment. Interviewers were assigned to conduct
assessments in both catchment areas (inner city, suburbs).
A few assessments (4.3%) were skipped when the
respondent was interviewed at a site that was not his/her
home, or if the interviewer felt unsafe staying in the neigh-
borhood for the assessment. All study procedures were
approved by the supervising academic institutions'
human subjects review committees (IRBs).

The original Chicago Neighborhood rating system incor-
porated assessments of a full four-sided block, and the
four streets and both sides of each of the streets of the
block (eight block face assessments) [10]. We used a sim-
plified version that incorporated five questions about the
street the respondent lived on (traffic volume, street con-
dition, noise, smells, dirt/dust) and 15 questions that
were completed for both the block face the respondent
lived on (Face A) and the opposite side of that street
(Block Face B). Block face questions asked about the pres-
ence of general litter and garbage as well as specific items
(cigarette products, alcohol containers, abandoned car,
condoms, needles). Questions included the presence of
graffiti, security measures on residences and commercial
property, types of residential and business land use, con-
dition of residential and business property, signs for
tobacco and alcohol products, for-sale signs, neighbor-
hood crime programs, vacant lots, parking lots, and the
presence of recreational faculties (parks, etc). Interviewers
provided ratings on simple Likert-type scales (e.g., for traf-
fic volume, four levels from none to heavy) and simple
checks for presence of items (e.g., abandoned car, empty
beer or liquor bottles, etc). The full survey and training
materials are available from the authors on request.

Analysis
A total of 84 descriptive variables of each respondent's
neighborhood was available, including multi-item check-
lists and both block faces for 15 items. In phase one, we
assessed items for frequencies and response categories,
finalized classification rules (e.g., collapsing categories),
and conducted exploratory factor analyses and scale inter-
nal consistency (coefficient alpha) tests for composing
multi-item scales. A series of exploratory factor analyses
for block face A items was done to assess the item proper-
ties of the neighborhood ratings and develop a neighbor-
hood rating scale. Factor analyses were then repeated
using items from block face A + B and compared to the
results of the initial factor analyses and internal consist-
ency.

In phase two, we examined the discriminant and concur-
rent validity of the items and the seven-item summary
scale that resulted from phase one. We hypothesized that
the scale resulting from phase 1 would exhibit discrimi-


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nant validity and would produce substantially lower scale
scores (better conditions) in the suburban catchment
area. For concurrent validity, we compared the scale scores
to the resident subjects' rating of their own neighborhood.
Each of these analyses was conducted first using data from
Block Face A only, and then the combined Block Face A +
B ratings. The inner-city catchment area, with poorer lev-
els of SES, was expected to produce higher (worse) total
and item scores. Item percentages were compared by chi-
square, and means compared by t-tests. We compared
item and scale agreements from the two block faces with
chi-square for categorical items, and intra-class correla-
tions (ICC) for the summary scale. For convergent valid-
ity, interviewer ratings were compared to a global rating of
the neighborhoods provided by resident study subjects,
who were asked, "All things considered, rate your neigh-
borhood as a place to live. Would you say it is excellent,
very good, good, fair, or poor?" Responses were coded
from 1 (excellent) to 5 (poor). Neighborhood was self-
defined by study subjects. The average score of interviewer
raters was compared for linear trend across the categories
of subjects' global neighborhood ratings using analysis of
variance.

In phase three, we investigated potential interviewer
effects on scale scoring. We constructed a linear regression
model predicting the total score for the seven-item scale
that resulted from phase one, first using Block Face A only,
and then the composite of Block Faces A + B. We grouped
interviewers into two categories of experience. Nine inter-
viewers had been involved in the study assessments or
training activities for this study during some or all of the
prior three years, and nine interviewers were new to the
study and new to research interviewing. We used forced
variable entry with catchment area, interviewer experi-
ence, and individual interviewer as dummy variables
comparing to a referent interviewer, selected as the person
with the maximum completed assessments (n = 102). We
excluded an additional set of new interviewers (7/25)
from this analysis who had not completed at least five
assessments in each catchment area. Analyses were con-
ducted using SPSS Version 12.0 [25].

Results
Phase I: Neighborhood rating scale in AAH
Neighborhood ratings were completed for nearly all sub-
jects who agreed to the in-home interview: 94.6% in the
city (n = 364 of 385) and 96.4% in the suburbs (n = 452
of 469). Each assessment took approximately five min-
utes. Examination of item and response category frequen-
cies led to a number of modifications of the assessment
instrument. Fortunately, interviewers found no drug para-
phernalia, and only noted one condom among 816
assessments (408 unique blocks with two block faces
rated). There were too few recreational faculties to include


a rating of their condition, and this item was dropped.
Only 13 block faces included any type of graffiti, and gang
and other graffiti categories were collapsed to "any" and
"no" graffiti. In addition, some extreme ratings were rare,
and response categories were collapsed. For example, nox-
ious smells and dirt/dust categories were collapsed to
"none" and "any" categories. Categories of how many res-
idences and buildings had security measures were also
were collapsed to "none" and "any" categories. Land use
details were simplified to residential compared to multi-
use neighborhood blocks. Residential housing types were
classified as detached single family, multi-family (duplex,
condo, row house), private apartment buildings, and pub-
lic housing buildings. Table 1 displays the items retained,
and coding levels for each. In all analyses reported below,
the addition of information from block face B provided
no substantive improvement of the results. Therefore,
tables provide only results using block face A.

Factor analyses of block face A items resulted in a single
factor scale including the following 7-items: traffic, street
condition, noise, beer/liquor bottles, cigarettes, garbage,
and residential unit condition. No other items combined
into multi-item scales with sufficient factor loadings, and
this summary scale was retained for further analysis. The
single forced factor accounted for 43.5% of variance in the
items with factor loadings ranging from 0.47 to 0.80. Spe-
cific factor loadings were traffic (0.47), street condition
(0.65), noise (0.53), beer/liquor bottles (0.65), cigarettes
(0.70), garbage (0.80), and residential unit condition
(0.76). The alpha for the 7-item block face A scale was
0.75. Deleting the item with the lowest factor loading
(traffic) reduced the alpha very slightly to 0.74. A subse-
quent factor analysis of the same scale using the block face
A + B results specifying a single factor solution yielded
similar scale properties, accounting for 44.9% of variance
in the items with factor loadings ranging from 0.49 to
0.80 and an alpha of 0.73. The means and standard devi-
ations for the scale using block face A are provided in
Table 1. The seven-item scale is shown in the Appendix.

Phase 2: Discriminant and concurrent validity
The scale and most items showed strong and consistent
differences in rating between the inner city and suburb
neighborhood ratings whether using data from Block Face
A only, or Block Face A + B combined. For example, using
Block Face A data, the scale scores were nearly 3 points
higher (worse) for inner city compared to suburban
neighborhood street (scale means 6.44 vs. 3.50, respec-
tively). Among items, there were striking differences in the
presence of problems like beer/liquor bottles (16.2%
inner city versus 3.3% suburbs) and cigarette litter (24.7%
versus 9.3%). There were some items where this pattern
appeared to be reversed (the observations were more com-
mon in the suburbs), but these items were also related to


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Table 1: Items & Scales of the Chicago Neighborhood Rating Method from Two Areas of Metropolitan St. Louis.


Overall n = 816


General conditions

Inner City n = 364


Suburbs n = 452


Rating not done %

*Traffic volume none to heavy
(Mean 0-3 SD)
*Street condition very good to
poor (Mean 0-3 SD)
*Noise very quiet to very noisy
(Mean 0-3 SD)
Smells % yes
Dirt & dust % yes

Abandoned car % yes
*Beer/liquor bottles % yes
*Cigarettes % yes
*Garbage, litter none to heavy
(mean 0-3, SD)
Graffiti % yes
Neighborhood crime signs % yes
Security signs % yes
For sale signs % yes
Commercial property % yes
% Poor/fair condition
% With pull down blinds/iron
gates
% With security bars/grates/
boards
Primary housing type
% Single family
% Private multi family
% Private apartments
% Public housing
*Residential condition very good
to poor (Mean 0-3 SD)
Security bars/grates on residences
% yes
Recreational facilities % yes
*Scale: traffic, street condition,
noise, beer, cigarettes, garbage,
residential unit condition (Mean 0-
15 SD)

* Items sum for the rating scale (range 0-
SD = standard deviation


Items rating entire street
1.04 ( 0.9) 1.32 ( 0.9)

1.16 (0.8) 1.39 ( 0.8)

0.71 ( 0.8) 0.89 ( 0.8)

2.6% 3.3%
1.1% 1.9%
Items rated on block face of respondent's residence
1.7% 2.7%
9.1% 16.2%
16.2% 24.7%
0.53 ( 0.8) 0.86 ( 0.9)


1.0%
4.5%
44.9%
7.7%
8.2% (67)
2.9%
3.1%


2.2%
3.3%
38.5%
8.2%
14.6% (53)
5.8%
6.3%


65.1%
16.9%
12.9%
5.1%
1.1 1 ( 0.9)

27.4%

1.3%
4.81( 3.2)


42.6%
34.9%
12.9%
9.6%
1.55 ( 0.9)

47.8%

1.4%
6.44 ( 3.0)


15 points for Block Face A). Higher scores represent worse neighborhood conditions.


expected catchment area neighborhood composition. For
example, while security bars and grates were more com-
mon in the inner city, neighborhood crime signs (indicat-
ing neighborhood collaborations) and security signs (for
formal electronic systems and surveillance contracts) were
more common in the suburbs. The condition of both res-
idential and commercial structures was better (lower
scores) in suburban ratings. In addition, single-family
housing was the predominant type in the suburbs (83.2%
for Block Face A) compared to the inner city, where it rep-
resented less than half (42.6%) of housing. The only sub-
stantive difference in results using Block Face A only or


both Block Faces A + B was that, given the possibility of
affirmative answer for either block face, percentages were
higher for conditions when both block faces were com-
bined.

Table 2 presents the results of testing convergent validity
of interviewer rater scale scores and resident subjects rat-
ing, and also a more detailed view of city and suburb dif-
ferences. Comparison of the global rating by AAH subjects
to the interviewer rating scale demonstrated a striking
trend of increasing scale scores with lower ratings moving
from an average of about 3 points for subjects who rated


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Item/Scale


0.82( 0.8)

0.98( 0.8)

0.56 ( 0.7)

2.0%
0.4%

0.9%
3.3%
9.3%
0.26 ( 0.5)

0.0%
5.5%
50.0%
7.3%
3.1% (14)
0.7%
0.4%

0.7%


83.2%
2.4%
12.8%
1.5%
0.75 ( 0.7)


10.9%


1.3%
3.50 ( 2.7)


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Table 2: Seven-Item Interviewer Observed AAH Neighborhood Scale* Results Compared to Residents' Global Rating of their
Neighborhood.


Mean Interviewer Rated Scale Scores


Resident Subjects' Global
Rating of their Neighborhood

Excellent
Very Good
Good
Fair
Poor
p-value for linear trend


Total Sample


2.96
3.66
5.14
6.18
6.98
<.001


Inner City


4.92
5.38
6.51
7.02
7.07
<.001


Suburbs


2.40
3.03
4.00
4.71
6.60
<.001


* Sum of the seven-item rating scale (range 0-15 points for Block Face A). Higher scores represent worse neighborhood conditions.


their neighborhood as "excellent" to about 7 points for
ratings of "poor" (Table 2). These strong and significant
trends were also apparent when separating the results by
City and Suburban strata.

Phase 3: Interviewer effects
Eighteen (72%) of the 25 interviewers completed 5 or
more assessments in each catchment area. The seven inter-
viewers with fewer than five assessments/area completed
15.8% (135/816) of the neighborhood assessments.
There was no association of interviewer experience and
scale score (P coefficient 0.326, p = 0.135), and this varia-


Table 3: Interviewer Effects on Neighborhood Scale Scores.


ble was dropped from the final model. Table 3 displays
the results of the analysis of interviewer effects using Block
Face A scale ratings only. There were substantial inter-
viewer differences in mean scores, although the strongest
relationship with scale score was catchment area (city ver-
sus suburbs). Using only Block Face A, eight interviewers
varied significantly (p < .05) from the reference inter-
viewer, and using Block Faces A + B, ratings differed signif-
icantly for 11 interviewers (data not shown). In an
additional analysis we repeated this modeling using Block
Face A and including only interviewers (6/25) with at least
ten observations in both catchment areas, with minimal


Variable


Constant
Catchment area Inner City vs. Suburbs
Interviewers (vs #1)
Interviewer 2
Interviewer 3
Interviewer 4
Interviewer 5
Interviewer 6
Interviewer 7
Interviewer 8
Interviewer 9
Interviewer 10
Interviewer I I
Interviewer 12
Interviewer 13
Interviewer 14
Interviewer I 5
Interviewer 16
Interviewer 17
Interviewer 18


+ Scale includes summary of items measuring traffic, street condition, noise, beer, cigarettes, garbage, and residential unit condition. Scale ranges
from 0-15 points. Higher scores represent worse neighborhood conditions.
* Unstandardized beta coefficients
R2 for this model = 0.320


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Neighborhood Scale'


B coefficient*


3.630
3.405

1.845
-1.554
0.607
-1.336
-1.105
-1.007
-1.098
-0.979
2.623
-0.715
-0.91 I1
-0.473
-1.173
-1.927
-0.299
-0.077
-1.742


p-value

<.001
< .001

.001
.003
.158
.033
.015
.065
.053
.070
<.001
.368
.079
.313
.009
< .001
.707
.898
.002


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changes in the number and magnitude of the interviewer
differences. We also introduced the resident subjects' glo-
bal neighborhood rating variable (analysis of this global
rating also shown in Table 2) to potentially account for
some real differences in the neighborhoods rated by inter-
viewers, also with minimal changes in the magnitude of
score differences among interviewers. Finally, in an ad hoc
analysis, we constructed an interaction model of inter-
viewer by catchment area and added this to the regression
model in Table 3. Of the 17 interactions, two were statis-
tically significant (p < .05): interviewer 10 provided worse
(higher scores) ratings overall, but also significantly worse
for inner city ratings; interviewer 13 provided better
(lower) ratings overall, but they were significantly worse
(higher scores) in the city ratings. The addition of these
interaction terms changed the R2 for the model slightly:
for the main effect model in Table 3 it was 0.320, and for
the model with two interaction terms it was 0.332.

Discussion
This study demonstrates that observer ratings of neighbor-
hood characteristics achieve substantial discriminant and
convergent validity. This was evident in both individual
items, like housing stock, and the seven-item scale we
constructed in phase one. The addition of observer ratings
of a second block face did not provide any substantive
improvement over the information provided by a single
block face, suggesting that the time and labor of our
neighborhood assessment tool can be reduced. The seven-
item scale produced a striking difference of 2.94 points
between inner city and suburban neighborhood rating
within a scale range of 0-15 points. This approximately 3-
point difference is equivalent to one item with multiple
response levels (e.g., noise, residence condition) changing
3 points, or the two dichotomous items (presence of liq-
uor, cigarettes) changing from "no" to "yes" and one other
item changing one category, etc. This reflects a real differ-
ence between the neighborhoods, and not an artifact of
measurement. In addition, the ratings by interviewers
showed a strong linear relationship to subjects' own glo-
bal ratings of their neighborhood in both catchment
areas.

Neighborhood and SES are part of the conceptual frame-
work in the AAH cohort. Consequently, recruitment was
targeted to maximize neighborhood diversity, and neigh-
borhood effects are not confounded by race because the
cohort is composed entirely ofAfrican Americans. Because
this is a study of one minority group of mature adults in a
single metropolitan area, the results may not extend to
other urban areas and populations. In particular, it is pos-
sible that confounding by race might be present in a
multi-race study due to racial differences in how residents
rate their own neighborhoods. Finally, the spatial size that


we used in this study may not be appropriate for other
studies with different populations or objectives.

Despite substantial training, ongoing monitoring, and the
generally positive psychometric results of the neighbor-
hood assessments by items or the scale, we did not elimi-
nate individual interviewer rating variability. Our adapted
scale and items demonstrated more item response varia-
tion than our prior work with a simple five-item scale
[16], and we detected no problem with a response "set" as
in the prior rating scale where we found that a large per-
centage of neighborhood ratings were placed at the same
level of "good" conditions. In addition, interviewers
reported that the new rating scale was relatively easy to use
because of clear criteria for classification of what they
observed and because the items were relatively objective
(i.e., presence of alcohol containers, security bars, traffic
volume, etc).

The persistence of an interviewer effect for rating neigh-
borhoods is troubling, and not easy to explain. It does not
appear to be dependent on which neighborhood was
rated, and our test of interaction between interviewer and
area yielded only two possible interactions a finding
that should be viewed with caution due to the multiple
testing and the lack of a consistent pattern. Gauvin and
colleagues [26] reported a small amount of variation (4%
to 14.8%) from observers based on four pairs of trained
observers of randomly selected Montreal street segments.
Their rating system was quite different from the one we
report here, and the largest variability was for the dimen-
sion of "activity friendliness." In our own test of the five-
item neighborhood rating measure we used during the
baseline of the AAH cohort, we found adequate inter-rater
reliability despite interviewer effects [16]. In another St.
Louis area study that audited street segments for commu-
nity indicators to improve physical activity, inter-rater
reliability results were variable among measures of envi-
ronmental attributes ranging from built environment
items to social and aesthetic items [27]. We are unaware
of any other published results of observer neighborhood
rating scales that can provide evidence that this problem
of interviewer effects is relatively common, or if it is a
result of our choice of AAH catchment areas, our training,
or the instruments. Neighborhood rating systems, includ-
ing the AAH Neighborhood Assessment, need to be tested
in diverse settings. In addition, additional formal testing
ofinterrater reliability is necessary to assess the magnitude
of inconsistency among raters.

Conclusion
Overall, the AAH Neighborhood Assessment and its
resulting seven-time scale produced strong differences in
neighborhood scores representing real differences
between areas with known SES differences. Observer rat-


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ings of neighborhoods show promise as a measure of
neighborhood and the effect of neighborhood conditions
on health outcomes.

Competing interests
The authors) declare that they have no competing inter-
ests.

Authors' contributions
All authors contributed to the concept, design, and/or
analysis and interpretation of data. The corresponding
author completed the initial draft and all authors assisted
with revising the manuscript. All authors have reviewed
the final version of the manuscript and approved it for
publication.

Appendix
African American Health Seven-Item Neighborhood
Assessment scale
The first 3 questions refer to the full block and street on which
the respondent lives.

1. Volume of traffic


0. No Traffic


3. Very noisy difficult to hear a person talking near
to you

Items 4 *-liou: l1 7 are answered based on observations of the
side of the street on the block where the respondent lives (block
face).

4. Are empty beer or liquor bottles in street, yard, or alley
present?

1. Yes

0. No

5. Are there cigarette or cigar butts or discarded cigarette
packages on the sidewalk or in the gutters?

1. Yes

0. No

6. Is there garbage, litter, or broken glass in the street or on
the sidewalks?


0. None


1. Light (occasional cars)


1. Light (some visible)


2. Moderate


2. Moderate


3. Heavy (steady stream of cars)

2. Condition of the street

0. Under construction


1. Very poor (many sizeable cracks, potholes, or bro-
ken curbs)

2. Fair

3. Moderately good (no sizeable cracks, potholes, or
broken curbs)

4. Very good

3. How noisy is the street?

0. Very quiet easy to hear almost anything

1. Fairly quiet can hear people walking by talking,
though you may not understand them

2. Somewhat noisy voices are not audible unless very
near


3. Heavy (visible along most or all of street)


7. In general, how would you rate the condition of most
of the residential units in the block face?

0. Very well kept/good condition attractive for its
type

1. Moderately well kept condition

2. Fair condition (peeling paint, needs repair)

3. Poor/Badly deteriorated condition

Acknowledgements
This research was supported by a grant from the National Institutes of
Health to Dr. D. K. Miller (RO I AG- 10436). Dr. Wolinsky is supported, in
part, as a Research Scientist at the Department of Veterans Affairs Medical
Center of Iowa City, IA. We extend our thanks to Arlene Major and Kevin
Mickelsen for their photography used in the AAH Neighborhood Assess-
ment training.

References
I. Kawachi I, Berkman LF, Eds: Neighborhoods and health New York:
Oxford University Press; 2003.




Page 8 of 9
(page number not for citation purposes)


BMC Public Health 2008, 8:35








http://www.biomedcentral.com/1471-2458/8/35


2. Browning CR, Cagney KA: Moving beyond poverty: neighbor-
hood structure, social processes, and health. J Health Soc Behav
2003, 44:552-571.
3. Glass TA, McAtee MJ: Behavioral science at the crossroads in
public health: extending horizons, envisioning the future. Soc
Sci Med 2006, 62:1650-1671.
4. Satariano WA: Epidemiology of aging. An ecological approach Sudbury
MA: Jones & Bartlett Publishers; 2006.
5. Andresen EM, Miller DK: The future (history) of socioeconomic
measurement and implications for improving health out-
comes among African Americans. J Gerontol A Biol Sci Med Sci
2005, 60A: 1345-1350.
6. Cagney KA, Browning CR, Wen M: Racial disparities in self-rated
health at older ages: what difference does the neighborhood
make? J Gerontol 8 Psychol Sci Soc Sci 2005, 60B:S 181 -S 190.
7. Pickett K, Pearl M: Multilevel analyses of neighborhood socioe-
conomic context and health outcomes: a critical review. j
Epidemiol Community Health 2001, 55:1 I I -122.
8. Diez-Roux AV: The study of group-level factors in epidemiol-
ogy: rethinking variables, study designs, and analytic
approaches. Epidemiol Rev 2004, 26:104- II I.
9. Diez-Roux AV: Investigating neighborhood and area effects on
health. Am J Public Health 2001, 91:1783-1789.
10. Sampson RJ, Raudenbush SW: Systematic social observation of
public spaces: a new look at disorder in urban neighbor-
hoods. Am Sociol 1999, 105:603-65 1.
I I. Hoehner CM, Brennan-Ramirez LK, Elliott MB, Handy SL, Brownson
RC: Perceived and objective environmental measures and
physical activity among urban adults. Am ] Prev Med 2005,
28:105-116.
12. Li F, Fisher KJ, Brownson RC: A multilevel analysis of chance in
neighborhood walking activity in older adults. J Aging Phys Act
2005, 13:145-159.
13. Sampson RJ, Morenoff JD, Earls F: Beyond social capitol: spatial
dynamics of collective efficacy for children. Am Sociol Rev 1999,
64:633-659.
14. Wen M, Browning CR, Cagney K: Poverty, affluence, and income
inequality: Neighborhood economic structure and its impli-
cations for health. Soc Sci Med 2003, 57:843-860.
15. Krause N: Neighborhood deterioration, religions coping, and
changes in health during late life. Gerontologist 1998, 38:653-664.
16. Andresen EM, Malmstrom TK, Miller DK, Wolinsky FD: Reliability
and validity of observer ratings of neighborhoods. J Aging
Health 2006, 18:28-36.
17. Schootman M, Andresen EM, Wolinsky FD, Malmstrom TK, MillerJP,
Miller DK: Neighborhood conditions and risk of incident
lower-body functional limitations among middle-aged Afri-
can Americans. Am J Epidemiol 2006, 163:450-458.
18. Miller DK, Malmstrom TK,Joshi S, Andresen EM, MorleyJE, Wolinsky
FD: Clinically relevant levels of depressive symptoms in com-
munity-dwelling middle aged African Americans. J Am Geriatr
Soc 2004, 52:741-748.
19. Miller DK, Wolinsky FD, Malmstrom TK, Andresen EM, Miller JP:
Inner city middle aged African Americans have excess pre-
mature frank and subclinical disability. J GerontolA Biol Sci Med
Sci 2005, 60A:207-212.
20. Wilson M-MG, Miller DK, Andresen EM, Malmstrom TK, Miller JP,
Wolinsky FD: Fear of falling and related activity restriction
among middle aged African Americans. J GerontolA Biol Sci Med
Sci 2005, 60A:355-360.
21. Wolinsky FD, Miller DK, Andresen EM, Malmstrom TK, Miller JP:
Health related quality of life in middle aged African Ameri-
cans. j Gerontol B Psychol Sci Soc Sci 2004, 59B:S I 18-S 123.
22. Andresen EM, Malmstrom TK, Miller DK, Miller JP, Wolinsky FD:
Retest reliability of self-reported function, self-care, and dis-
ease history. Med Care 2005, 43:93-97.
23. Andresen EM, Wolinsky FD, MillerJP, Wilson M-MG, Malmstrom TK,
Miller DK: Cross-sectional and longitudinal risk factors for
falls, fear of falling, and falls efficacy in a cohort of middle
aged African Americans. Gerontologist 2006, 46:249-257.
24. Bradley RH, Caldwell BM: The HOME Inventory and family
demographics. Dev Psychol 1984, 20:315-320.
25. Statistical Package for the Social Sciences: SPSS 12 brief guide Chicago:
Author; 2004.
26. Gauvin L, Richard L, Craig CL, Spivock M, Riva M, Forster M, Laforest
S, Laberge S, Fournel MC, Gagnon H, Gagne S, Potvin L: From walk-


ability to active living potential: an "ecometric" validation
study. AmJ Prevy Med 2005, 28:126-133.
27. Brownson RC, Hoehner CM, Brennan LK, Cook RA, Elliott MB,
McMullen KM: Reliability of two instruments for auditing the
environment for physical activity. J Physical Activity Health 2004,
1:189-207.

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