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Research Articles
Built and Social Environments
Associations with Adolescent Overweight and Activity
Melissa C. Nelson, PhD, RD, Penny Gordon-Larsen, PhD, Yan Song, PhD, Barry M. Popkin, PhD
Little is known about the patterning of neighborhood characteristics, beyond the basic
urban, rural, suburban trichotomy, and its impact on physical activity (PA) and overweight.
Nationally representative data (National Longitudinal Study of Adolescent Health, 1994–
1995, n ?20,745) were collected. Weight, height, PA, and sedentary behavior were
self-reported. Using diverse measures of the participants' residential neighborhoods (e.g.,
socioeconomic status, crime, road type, street connectivity, PA recreation facilities), cluster
analyses identified homogeneous groups of adolescents sharing neighborhood character-
istics. Poisson regression predicted relative risk (RR) of being physically active (five or more
bouts/week of moderate to vigorous PA) and overweight (body mass index equal or greater
than the 95th percentile, Centers for Disease Control and Prevention/National Center for
Health Statistics growth curves).
Six robust neighborhood patterns were identified: (1) rural working class; (2) exurban;
(3) newer suburban; (4) upper-middle class, older suburban; (5) mixed-race urban; and
(6) low-socioeconomic-status (SES) inner-city areas. Compared to adolescents living in newer
suburbs, those in rural working-class (adjusted RR[ARR]?1.38, 95% confidence interval
[CI]?1.13–1.69), exurban (ARR?1.30, CI?1.04–1.64), and mixed-race urban (ARR?1.31,
CI?1.05–1.64) neighborhoods were more likely to be overweight, independent of individual
SES, age, and race/ethnicity. Adolescents living in older suburban areas were more likely to be
physically active than residents of newer suburbs (ARR?1.11, CI?1.04–1.18). Those living in
low-SES inner-city neighborhoods were more likely to be active, though not significantly so,
compared to mixed-race urban residents (ARR?1.09, CI?1.00–1.18).
These findings demonstrate disadvantageous associations between specific rural and urban
environments and behavior, illustrating important effects of the neighborhood on health
and the inherent complexity of assessing residential landscapes across the United States.
Simple classical urban–suburban–rural measures mask these important complexities.
(Am J Prev Med 2006;31(2):109–117) © 2006 American Journal of Preventive Medicine
Built and social environments are important determi-
nants of obesity-related health behavior (e.g., physical
activity [PA]) and targets for intervention strategies.4
Research studying neighborhood effects on health has
relied largely on aggregate socioeconomic status (SES)
verweight and obesity have emerged as na-
tional public health concerns,1,2with adoles-
cence as an important developmental period.3
ments.5–9In an emerging literature exploring how
environment facilitates or restricts health behavior,
however, specific individual-level measures of neighbor-
hood factors (e.g., crime/safety,10–12street connectiv-
ity, road type/traffic,13–14and activity-related recre-
ation facility access15–18) have been independently
associated with PA.
Neither aggregate indices of SES nor specific aspects
of the built environment appear in isolation in neigh-
borhoods. Clearly, factors such as SES, crime, lack of
recreation facilities, and other community-level mea-
sures occur jointly.15In contrast to traditional risk
factor approaches to data analysis that examine the
independent effects of specific neighborhood charac-
teristics, pattern analyses allow examination of the
effects of multiple dimensions of the environment.
Both independent risk factor analysis and pattern anal-
ysis may make important contributions to understand-
ing how the environment affects behavior.
From the Division of Epidemiology and Community Health, Univer-
sity of Minnesota (Nelson), Minneapolis, Minnesota; and Depart-
ment of Nutrition, University of North Carolina (Nelson, Gordon-
Larsen, Popkin), Carolina Population Center (Nelson, Gordon-
Larsen, Popkin), and Department of City and Regional Planning
(Song), Chapel Hill, North Carolina
Address correspondence and reprint requests to: Melissa C. Nel-
son, PhD, RD, Division of Epidemiology and Community Health,
University of Minnesota, 1300 S. 2nd Street, WBOB Suite 300,
Minneapolis MN 55454-1015. E-mail: firstname.lastname@example.com.
The full text of this article is available via AJPM Online at
Am J Prev Med 2006;31(2)
© 2006 American Journal of Preventive Medicine • Published by Elsevier Inc.
0749-3797/06/$–see front matter
Page 2
While the importance of covariance and joint effects
of neighborhood features has gained recognition in
this growing area of interest in environmental determi-
nants of obesity, the study of patterning to date has
been limited largely to index development as a means
of measuring very specific aspects of the built environ-
ment.13,19There is little empirical evidence describing
the diversity and covariance of community characteris-
tics using data-driven techniques within nationally rep-
resentative data sets, including a wide array of residen-
tial landscapes, most importantly, rural areas that are
greatly understudied.
By using pattern analyses to measure the effects of
multiple environmental characteristics on behavior,
this research fills an important gap in the literature.
Using data from a nationally representative, ethni-
cally diverse sample of adolescents, the aims of this
study were to (1) identify meaningful patterns of
sociodemographic and built features in neighbor-
hood environments that have been identified as
potentially important determinants of PA, and
(2) describe the cross-sectional associations between
these neighborhood patterns and adolescent resi-
dents' PA and weight status.
Add Health
Add Health is a school-based longitudinal survey of youths,
grades 7 through 12. A random sample of 80 high schools and
52 junior high feeder schools was selected. The Add Health
sample was designed to be nationally representative of stu-
dents in grades 7 through 12 in 1995 in the United States.
Survey procedures20were previously approved by the Institu-
tional Review Board at the University of North Carolina at
Chapel Hill. The Wave-I in-home survey (1994–1995) in-
cluded 20,745 adolescent participants. Analyses were con-
ducted in 2005–2006.
Measuring Individual
Neighborhood Environments
(n ?20,612, 99.4%) Wave-I participants were identified and
geocoded, using primarily street-segment matches from com-
mercial geographic information system (GIS) databases
(n ?17,119) or global positioning system (GPS) units
(n ?3242) (when a street-segment match was unavailable).
When neither was available, residential location assignments
used a ZIP?4/ZIP?2 or 5-digit ZIP centroid match, or the
respondent's school location.15A relational database linked
the location of a participant's home to (1) neighborhood
attributes, based on buffers around each home; (2) block
group, tract, and county attributes from U.S. Census and
other federal sources; and (3) Add Health participants'
survey responses. Add Health was designed for national
representation of youth, not for geographic representation.
Yet, the data include a wide array of geographic areas across
the United States.
location. Homestreetaddresses ofmost
Buffers for respondent locations. To assess the variety of
neighborhood characteristics, a 3-km buffer was drawn
around each respondent's residential location using Euclid-
ean distance. While there is some suggestion that 5-mile
catchment areas may be relevant for adult PA,15,17it is likely
that smaller areas influence adolescent PA, where travel is
more limited. There is little empirical data to support appro-
priate buffer size for PA outcomes at a national level. Sensi-
tivity analyses were conducted to determine the appropriate
buffer size (3 km) for these analyses.
Physical activity facilities within 3 km. Commercially avail-
able, retrospective (1995), digitized Yellow Pages, using pro-
prietary 4-digit extensions to the Standard Industrial Classifi-
cation (SIC) codes, were obtained. These 8-digit codes
correspond with those used by the Census, allowing for the
detailed characterization of facility type. A comprehensive list
representing PA facility/resource types (n ?169) was com-
piled for these SIC codes.15SIC code counts were summed to
measure all activity-related facilities, and subdivided to specif-
ically assess parks. Park locations were verified using digital
aerial photographs from the U.S. Geological Survey.
Walkability within 3 km. High street connectivity, or "walk-
ability" (i.e., neighborhood street networks that are continu-
ous, integrated, and maximize linkages between starting
points and destinations, providing multiple route options)
has been positively associated with residential activity pat-
terns.13,21Indices of connectivity include (1) intersection
density (three-way and four-way intersections), (2) alpha
index (ratio of observed to maximum possible route alterna-
tives [circuitry] between nodes, where the maximum possible
circuits is the maximum number of links minus the number
of links in a minimally connected network), (3) gamma index
(ratio of observed node linkages to the maximum possible
links in the network), and (4) cyclomatic index (number of
route alternatives [circuits] between nodes).
Road type within 3 km. Road networks were mapped using
retrospective U.S. Census TIGER (topologically integrated
geographic encoding and referencing) line files (www.
census.gov/geo/www/tiger/). Road types were assessed using
Census feature class codes (www.census.gov/geo/www/tiger/
appendxe.asc) (i.e., feature Class A categories). The presence
of smaller, local roads (category A4x, which are more likely to
have single traffic lanes, sidewalks, and lower speed limits)
were of particular interest for this research, in comparison to
the presence of larger roadways (A1x) on which walking/
biking is more difficult (e.g., primary highways). Road types
were assessed as the proportion of total roadways and the
absolute total length.
Census measures. Census data reflecting individuals' resi-
dential block groups were extracted from the 1990 Census of
Population and Housing summary tape file 3A (STF3A). A
block group is a relatively small administrative unit in the U.S.
Census (averaging 300 to 3000 residents). Variables used here
were education (proportion of adults aged ?25 years with a
college degree), minority (proportion of nonwhites), poverty
(proportion of people with incomes ?185% of poverty level),
housing units (proportion of housing units occupied by
renters, proportion vacant, median housing unit age), and
mobility (proportion of population living in same housing
unit since 1985, proportion of population working in county
American Journal of Preventive Medicine, Volume 31, Number 2 www.ajpm-online.net
Page 3
of residence). The metropolitan statistical area (MSA) of Add
Health schools was also identified, and regions were broadly
categorized as urban, suburban, or rural.
Crime. Reported crimes (per 100,000 population) were as-
sessed using 1995 U.S. Federal Bureau of Investigation Uni-
form Crime Reporting county-level data from the National
Archive of Criminal Justice Data (www.icpsr.umich.edu/
NACJD/index.html), which have been shown to be associated
with PA levels in this sample.22For Add Health respondents
(n ?366) in counties with no available 1995 crime data, crime
rates were used from a previous year (1990 to 1994). For three
counties (n ?95 individuals), crime was imputed as average
reported crime in surrounding counties.
Physical Activity/Sedentary Behaviors
Daily PA (e.g., housework, active play, sports, exercise) was
self-reported using standard epidemiologic 7-day recall method-
ology.23Surveys (www.cpc.unc.edu/projects/addhealth/code-
books) employed questions similar to those used and validated
in other large-scale studies.23–26Questions asked—variations on
"During the past week, how many times did you . . ."—allowed
estimation of activity frequency (bouts/week) by metabolic
to 8 METs.27
Adolescents also reported sedentary behaviors (e.g., watch-
ing/playing TV/videos, video or computer games [hours/
week]), using recreation centers, and playing sports with
parent(s). Overall activity frequency was summed to deter-
mine total weekly MVPA or sedentary behavior, as well as
whether individuals met national recommendations for PA
(i.e., recommendation is five or more bouts/week of
MVPA)28and did not meet recommendations for sedentary
behavior (i.e., recommendation is TO NOT exceed 14 hours/
week "screen time").29,30
Weight Status
Self-reported height and weight were used to calculate body
mass index (BMI) (kilograms/square meters).31The 95th
percentile of nationally representative data (2000 Centers for
Disease Control and Prevention/National Center for Health
Statistics growth curves), was used to classify overweight.32
Individuals aged 21 years (n ?9) were considered as 20-year-
olds for assessing overweight. Self-reported weight and height
have been shown to correctly classify a majority of Add Health
participants as overweight.33
Adolescents self-reported race/ethnicity; reports were vali-
dated during in-home parent interviews. Parents reported
highest level of achieved education, which was used to
estimate SES. Income was reported in $1000 increments and
imputed where missing, using parent occupation, family
structure, and school community.
Identifying Patterns in Environment
Cluster analyses were used to identify patterns of environmental
characteristics and to specify homogeneous, non-overlapping
clusters (or patterns) of neighborhoods sharing various mean-
partitioning data into different numbers of clusters4–10by
Euclidean distances between observations that were weighted
for national representation, using SAS FASTCLUS, SAS version
9 (Research Triangle Institute, Research Triangle Park NC,
2004). Representing different constructs of the neighborhood,
19 variables were used (Table 1). Z-score transformations of
variables were used to generate clusters, allowing for the appro-
priate weighting of variables with different scales.34
To identify initial cluster centers (i.e., seed values), 1000
iterations of each cluster procedure were conducted.35The
initial group center for each iteration was randomly generated.
The iteration with the largest overall r2value, which allowed for
the evaluation of relative heterogeneity between clusters (vs
homogeneity within clusters), was identified. Clusters best fitting
the data maximized this inter- to intra-variability ratio, yielding a
higher r2. (For the six-cluster solution series—i.e., the final
cluster solution—the maximum r2value identified through this
iterative process was 0.41.) Results of these numerous analyses
were assessed to identify common patterns appearing across
various procedures. The final presented clusters were those
representing the most robust data patterns.
Table 1. Measured constructs of the neighborhood environment
Construct Measure
Income/wealth Income to poverty level (% less than 185%)
Home age (year structure was built)
Ethnicity (% minority)
Education (% with college degree)
Occupancy status (% owner occupied, % renter occupied, % vacant)
Mobility (% living in same house since 1985), median house age
Proportion working in county of residence
Serious crimes (arrests) per 100,000 persons
Proportion of A1 and A4 roads in 3-km buffer
Total length of A1 and A4 roads in 3-km buffer
Intersection density in 3-km buffer
Gamma index in 3-km buffer
Cyclomatic index in 3-km buffer (total route alternatives)
Alpha index in 3-km buffer (observed total route alternatives)
For each facility type: count in 3-km buffers
Socioeconomic status and environment
Road type
Street connectivity (walkability)
Recreation facilities for physical activity
August 2006 Am J Prev Med 2006;31(2)
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Demonstrating Cluster Variability
Cluster analytic procedures detect underlying data patterns,
regardless of utility or substantive merit, but statistical meth-
ods for validating cluster analyses are limited.34To show that
clusters fit the data in a meaningful way, clusters are often
tested by predicting external variables not used to generate
the patterns (although associated with the clusters in theory).
To demonstrate meaningful variability between patterns
and to validate these findings, neighborhood clusters were
assessed as independent variables in generalized linear mod-
els predicting adolescent PA, sedentary behavior, and over-
weight. As another tool for comparison, broad neighborhood
characteristics were examined (e.g., broad urbanicity classifi-
cations of urban, suburban, and rural; median household
income; percent college-educated population; percent mi-
nority population), which have been used extensively in
previous literature.
All models controlled for important covariates (age,
race/ethnicity, parent education/income). Observations
with missing covariate or outcome data were excluded.
Participants who were severely disabled (n ?132) and/or
pregnant (n ?379) were also excluded. While logistic
regression is commonly used in health research, the odds
ratios yielded by these analyses substantially over-estimate
risk ratios (RRs) that are ?1.0 (and under-estimate those
that are ?1.0) when the outcome is not rare. The binomial
outcomes included in these analyses were not rare (i.e.,
prevalence ?10%), so Poisson regression was used with
robust variance estimates to generate valid estimates of the
adjusted relative risk (ARR) (and relatively conservative
confidence intervals [CIs]), instead of adjusted odds
Descriptive analyses of individual adolescent characteristics
used post-stratification sample weights, allowing results to be
nationally representative. Survey design effects of multiple
stages of cluster sampling were controlled using the survey
(SVY) procedure series in STATA, version 9.0 (Stata Corp,
College Station TX, 2004).
Descriptive Statistics and Final Cluster Solution
The analysis sample (n ?20,745) generating the neigh-
borhood clusters was composed of 50.1% males as well
as 68.5% white, 15.2% black, 11.4% Hispanic and 4.0%
Asian adolescents. Approximately 14.7% of partici-
pants' parents had less than a high school education,
32.5% had graduated from high school (or had a
general equivalency diploma), 27.8% had some col-
lege, and 25.0% had a college degree or higher. Mean
participant age was 15.4 (?0.12) years.
Six robust neighborhood pattern types were identified
by the final cluster solution and were observed across
numerous iterations of analyses, representing non-over-
lapping groups of U.S. neighborhoods sharing various
attributes. These clusters include (1) rural working class;
(2) exurban (urban/suburban outgrowth); (3) new sub-
urban developments (referent); (4) older, upper-middle
class suburbia with highway access; (5) mixed-race urban;
and (6) low-SES inner-city neighborhoods (Table 2).
These neighborhood patterns are distinguished by impor-
generate the final cluster solution, including SES, race/
ethnicity, socioenvironment, crime, road type, street con-
nectivity, and recreation facilities (Table 3).
Table 2. Major neighborhood types identified through cluster analysis procedures
Type Description
Rural working classLow SES, moderate-to-low minority population, little mobility
Low connectivity (i.e., low intersection density and few possible routes between any two points)
Low access to PA facilities, very low overall density of roadways
Moderate SES, low minority population
High % of relatively recently built housing units
High % of population commuting to work outside of county of residence
Low access to PA facilities, low street connectivity and low crime
High proportion of large arterial roadways
High SES, low minority population
Relatively recently built housing units
Low access to PA facilities, very poor street connectivity
Few roadways overall (with high proportion of these roadways being of local)
High SES population with somewhat mixed racial/ethnic composition, little mobility
High % of older housing units
Moderate access to PA facilities, moderate street connectivity in linking intersections (and
moderate-to-high number of alternative street routes between any two points)
High density of roads overall (with a moderate proportion of large arterial roadways)
Low SES, high poverty population
Moderate access to PA facilities, moderate-to-high street connectivity and crime
High density of local roadways
Low SES, very high minority and very high poverty population
Large proportion of older housing units
Very high access to PA facilities, very high street connectivity and intersection density
High crime, high density of local roadways
Exurban (urban/
New suburban
Older, upper-
middle class
suburbia with
highway access
Low SES, inner city
PA, physical activity; SES, socioeconomic status.
American Journal of Preventive Medicine, Volume 31, Number 2 www.ajpm-online.net
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Table 3. Mean frequency of specific neighborhood characteristics by clustera
Cluster 1Cluster 2Cluster 3
New suburban
(n ? 3371)
Cluster 4
Older suburban
(n ? 4280)
Cluster 5
ethnicity urban
(n ? 3609)
Cluster 6
inner city
(n ? 2582)
Rural working class
(n ? 4725)
(n ? 2178)
% population with a college
education (in block group)
% nonwhite population (in block
% population with income ?185%
poverty line (in block group)
% renter-occupied housing units (in
block group)
% vacant housing units (in block
Median house age (years) (in block
% population living in the same
house for ?5 years (in block
group) (i.e., % low morbidity)
% population working in county of
residence (in block group)
Number of facilities for physical
activity (in 3 km)
Number of parks (in 3 km)
Alpha index of road connectivity (in 3
Gamma index of road connectivity (in
3 km)
Cyclomatic index of road connectivity
(in 3 km)
Intersection density (in 3 km)
Reported crime rate (in county)
Total length (meters) of major arterial
roadways (in 3 km)
Total length (meters) of local
roadways (in 3 km)
% roadways that are major arterial
roadways (in 3 km)
% roadways that are local roads (in 3
14.5 ? 0.1 (?0.56)
21.2 ? 0.3 (?0.11) 34.5 ? 0.2 (0.77)32.9 ? 0.3 (0.67)
17.0 ? 0.2 (?0.39)16.2 ? 0.2 (?0.45)
20.0 ? 0.4 (?0.41)15.7 ? 0.6 (?0.54) 15.0 ? 0.3 (?0.56) 36.5 ? 0.5 (0.06)
50.8 ? 0.5 (0.47)75.1 ? 0.6 (1.17)
38.1 ? 0.2 (0.35)
26.1 ? 0.4 (?0.23)14.7 ? 0.2 (?0.79)14.8 ? 0.1 (?0.78)
45.8 ? 0.3 (0.73)48.5 ? 0.4 (0.86)
20.3 ? 0.2 (?0.44)20.6 ? 0.3 (?0.43)20.0 ? 0.3 (?0.45) 21.6 ? 0.3 (?0.38)
47.9 ? 0.3 (0.87)54.6 ? 0.4 (1.18)
11.6 ? 0.2 (0.44)7.0 ? 0.2 (?0.10)7.5 ? 0.2 (?0.04)3.0 ? 0.1 (?0.57)8.8 ? 0.1 (0.12)8.9 ? 0.2 (0.12)
23.9 ? 0.1 (?0.19) 21.5 ? 0.2 (?0.38)
13.2 ? 0.1 (?1.03)
31.2 ? 0.2 (0.38)28.7 ? 0.2 (0.18)41.1 ? 0.2 (1.15)
62.6 ? 0.1 (0.47)
58.6 ? 0.3 (0.20)45.7 ? 0.3 (?0.65)
62.6 ? 0.2 (0.47)
45.8 ? 0.2 (?0.64) 54.5 ? 0.3 (?0.07)
70.5 ? 0.3 (?0.36)
67.4 ? 0.5 (?0.52)
75.1 ? 0.4 (?0.14)81.9 ? 0.3 (0.19)87.9 ? 0.2 (0.48)83.9 ? 0.4 (0.29)
3.3 ? 0.1 (?0.66) 5.7 ? 0.1 (?0.58) 8.1 ? 0.1 (?0.49)
32.5 ? 0.2 (0.37)
23.5 ? 0.2 (0.05)
68.7 ? 0.9 (1.65)
?0.01 ? 0.001 (?0.21)
0.25 ? 0.001 (0.16)
0.01 ? 0.002 (?0.20)
0.19 ? 0.001 (?0.49)
0.01 ? 0.001 (?0.20)
0.16 ? 0.001 (?0.81)
0.04 ? 0.003 (?0.11)
0.22 ? 0.001 (?0.20)
0.02 ? 0.002 (?0.16)
0.26 ? 0.001 (0.22)
0.55 ? 0.018 (1.21)
0.35 ? 0.002 (1.19)
0.51 ? 0.001 (0.22)0.46 ? 0.001 (?0.51)0.44 ? 0.001 (?0.86)0.48 ? 0.001 (?0.22) 0.51 ? 0.001 (0.21) 0.57 ? 0.001 (1.23)
84.4 ? 1.2 (?0.86) 120.9 ? 2.1 (?0.77)185.8 ? 2.4 (?0.61)548.8 ? 3.5 (0.32)584.7 ? 3.2 (0.41)
1172.3 ? 5.0 (1.91)
5.0 ? 0.1 (?1.00)
3635.5 ? 29.3 (?0.83)
114.6 ? 13.5 (?0.91)
8.5 ? 0.1 (?0.81)
4483.8 ? 46.6 (?0.53)
17,937.3 ? 139.6 (0.69)
14.0 ? 0.2 (?0.51)
6003.6 ? 37.5 (?0.004)
2910.7 ? 89.7 (?0.66)
33.2 ? 0.2 (0.53)
6195.1 ? 30.2 (0.06)
18,365.9 ? 180.9 (0.73)
32.3 ? 0.2 (0.48)
6997.9 ? 35.0 (0.34)
11,229.8 ? 159.4 (0.09)
53.9 ? 0.2 (1.65)
9640.2 ? 61.6 (1.27)
16,951.1 ? 197.7 (0.60)
55,425.6 ? 381.8 (?1.07)79,429.1 ? 810.7 (?0.81)113,899.3 ? 971.7 (?0.44)
206,137.1 ? 682.8 (0.57)204,157.2 ? 845.8 (0.55)291,885.8 ? 960.8 (1.51)
0.1 ? 0.02 (?0.78)
16.1 ? 0.1 (1.99)
1.6 ? 0.1 (?0.51) 6.6 ? 0.1 (0.34)4.1 ? 0.1 (?0.09)4.5 ? 0.1 (?0.03)
77.2 ? 0.2 (0.20)
62.8 ? 0.2 (?1.26)
80.2 ? 0.1 (0.51)
73.7 ? 0.1 (?0.16)
76.8 ? 0.1 (0.16)76.0 ? 0.1 (0.08)
aMean ? standard error (mean z-score) of neighborhood characteristics (unweighted).
August 2006
Am J Prev Med 2006;31(2)
Page 6
Neighborhood–Overweight Associations
Using the neighborhood clusters, important differ-
ences in the relative risk of overweight by community
type were identified. Compared to adolescents living in
newer suburban developments, those who lived in
(1) rural working class, (2) exurban, and (3) mixed-
race urban neighborhoods were 30% to 40% more
likely to have a BMI?95th percentile of age- and
gender-specific national growth curves (Figure 1), in-
dependent of SES, adolescent age, and race/ethnicity.
Conversely, analyses using individual components or
traditional measures of neighborhood characteristics
show less-clear associations (Table 4). Using traditional
analyses, no difference in the risk of overweight be-
tween low- and moderate-SES communities was found,
although high-SES communities were less likely to be
overweight, compared to moderate-SES communities.
There was no difference in overweight status by the
race/ethnicity of the community. The traditional ur-
ban–suburban–rural status (using MSAs) suggest a
lower likelihood of overweight in adolescents residing
in urban areas, but no differences in rural and subur-
ban neighborhoods. A comparison of the traditional
urban–suburban–rural breakdown with the approach
presented in Table 3 highlights the differences in the
two approaches.
Neighborhood–Activity Associations
Among adolescents living in older suburban neigh-
borhoods, 39% reported engaging in five or more
bouts of weekly MPVA, compared to 28% of adoles-
cents living in mixed-race urban areas (data not
shown). These findings indicate notable distinctions
within suburban and urban community types; for
example, independent of SES, race/ethnicity, and
age, adolescents living in older suburban develop-
ments were 11% more likely to be physically active
than thoselivingin
(ARR?1.11, CI?1.04–1.18) (Figure 2). In addition,
those living in low-SES inner-city areas were more
likely to be active compared to those in mixed-race
urban neighborhoods (RR?1.09, CI?1.00–1.18).
newersuburban areas
Figure 1. Adjusted risk ratios (95% confidence intervals) of
overweight (BMI ?95th percentile) by data-driven neighbor-
hood cluster definitions (n ? 19,029). Note: adjusted for
household income, parental education, adolescent age, and
Table 4. Adjusted risk ratios (95% confidence intervals) of adolescent overweight (?95th percentile body mass index) using
broad, independent, and traditional measures of neighborhood characteristics
Adjusted risk ratio of overweight by neighborhood features
Low tertile Moderate tertileHigh tertile
Median household incomea
% of population with
?college educationb
% of minority populationc
MSA classification of schoold
1.03 (0.91–1.17)
1.10 (0.99–1.22)
1.0 (ref)
1.0 (ref)
0.83 (0.71–0.98)
0.74 (0.65–0.85)
1.00 (0.85–1.15)
Rural: 1.9 (0.94–1.27)
1.0 (ref)1.13 (0.97–1.31)
Urban: 0.85 (0.75–0.97)Suburban: 1.0 (ref)
Note: Adjusting for individual parental education, household income, race/ethnicity, and age of adolescent.
aLow-income tertile: median household income ?$23,775/year, moderate tertile: ?$23,775 to ?$36,440/year, high tertile: ?$36,440/year at the
census block–group level (n ? 19,029 in model).
bLow education tertile: ?14.4% of population college educated; moderate tertile: ?14.4% to ?26.5%; high tertile: ?26.5% at the census
block–group level (n ? 19,025 in model).
cLow minority tertile: ?6.1% of population is minority, moderate tertile: ?6.1% to ?49.4%, high tertile: ?49.4% at the census block–group level
(n ? 19,025 in model).
dMSA, metropolitan statistical area (n ? 18,709 in model).
Figure 2. Adjusted risk ratios (and 95% confidence intervals)
of achieving five or more bouts of moderate-to-vigorous
physical activity (MVPA)/week by data-driven neighborhood
cluster definition and type (rural, suburban and urban) (n ?
19,531, across three models). Note: Adjusted for household
income, parental education, adolescent age and race/ethnic-
American Journal of Preventive Medicine, Volume 31, Number 2 www.ajpm-online.net
Page 7
Independent of SES, race/ethnicity, and age, teens
living in low-SES inner-city and older suburban areas
were least likely to report playing a sport with a
parent(s), and those living in the low-SES inner-city,
mixed-race urban, and older suburban areas were the
most likely to report using a neighborhood recre-
ation facility. High levels of screen time (?14 hours/
week, which is above recommended levels) were most
likely among those living in low-SES inner-city neigh-
borhoods (Table 5).
Using cluster analysis, six robust patterns in residential
neighborhood characteristics were identified, incorpo-
rating a range of sociodemographic and built environ-
ment characteristics: (1) rural working class, (2)
exurban, (3) new suburban, (4) older suburban, (5)
mixed-race urban, and (6) low-SES inner-city areas. To
our knowledge, this is the first study using data-driven
techniques to characterize neighborhoods by sociode-
mographic and built environment features in a nation-
ally representative survey of adolescents. These results
show differences in neighborhood patterns by adoles-
cent PA and overweight (such as the disadvantageous
associations between rural and urban environments
and health). Rural populations have been particularly
understudied; these findings indicate that these indi-
viduals have unique neighborhood characteristics that
deserve further attention.
These findings show other important differences by
activity and weight status. Contrary to recent reports
supporting positive relationships between sprawl and
adult overweight/obesity,19,37,38the current results in-
dicate some beneficial associations between suburban
living and activity/overweight. Cross-sectionally, these
findings indicate that adolescents living in rural work-
ing class, exurban, and mixed-race urban areas were at
the highest risk of overweight compared to those in the
newer suburban cluster type. Teens living in older
suburban communities were most likely to be physically
active. In adolescence, there may be protective factors
shared by those living in suburban communities (e.g.,
school-based sports/activity facilities, community orga-
nizations, low crime) overriding the deleterious effects
of suburbia, which are believed to be at play in restrict-
ing activity of adult residents (e.g., low walkability,
dependence on automobiles).
The natural patterns of neighborhood characteristics
underlying these data represent diverse settings that
span urban, suburban, and rural regions, and are
shown to be valid through empirical evidence and
theoretical frameworks. For example, these results are
consistent with previous findings that low-income, ra-
cial/ethnic minority, and rural populations are less
physically active and more overweight and obese.3,39–41
In addition, the findings are supported by theoretical
Table 5. Adjusted risk ratios (and 95% confidence intervals) of adolescent physical activity and sedentary behavior by detailed data-driven neighborhood cluster
Cluster 1
Cluster 2
Cluster 3
Cluster 4
Cluster 5
Cluster 6
working class
New suburban
Older suburban
ethnicity urban
inner city
?5 bouts/week of any
moderate-to-vigorous physical
activity (n ? 19,531)
1.03 (0.96–1.09)
1.04 (0.97–1.12)
1.11 (1.05–1.18)
0.96 (0.89–1.03)
1.05 (0.97–1.14)
Played a sport with a parent in
the last month (n ? 19,495)
0.95 (0.79–1.16)
1.01 (0.81–1.26)
0.78 (0.63–0.96)
0.81 (0.64–1.01)
0.63 (0.48–0.82)
Uses a neighborhood recreation
center (n ? 19,424)
1.11 (0.83–1.47)
0.97 (0.73–1.28)
1.41 (1.21–1.63)
1.40 (1.20–1.62)
1.51 (1.24–1.84)
?14 hours/week of TV/video
viewing and video/computer
gaming (n ? 19,521)
1.03 (0.96–1.10)
1.06 (1.00–1.15)
1.06 (0.99–1.15)
1.06 (0.99–1.12)
1.12 (1.05–1.20)
Note: Poisson regression, adjusting for parental education, household income, race/ethnicity, and age of adolescent.
SES, socioeconomic status.
August 2006Am J Prev Med 2006;31(2)
Page 8
constructs of transect planning, an approach to urban
planning emphasizing breadth and range in commu-
nity design to recognize a broad range of human and
environmental needs, rather than a "one size fits all"
approach.42These neighborhood patterns overlap
many of the eco-zones outlined in the transect planning
literature, which to date has been based largely on
theory and empirical evidence from smaller geographic
samples with restrictive analytic approaches. Guided by
these eco-zones in the transect theory literature, in
conjunction with the empirically derived cluster defini-
tions of this study (e.g., described by mean frequency of
specific neighborhood characteristics by clusters),
these neighborhood types may be re-created and ex-
plored in other data sets. In characterizing multidimen-
sional neighborhood features, it is understood that they
vary in structure and sociodemographic composition,
and likely have differential impacts on population
health behavior. By better understanding the complex-
ities of today's American residential landscape, there is
the opportunity to better conceptualize how to en-
hance built and social environments and tailor solu-
tions that will promote healthy lifestyles.
While these data show important dimensions of U.S.
communities and their association with health behav-
ior, they are not without limitation. First, the data on
PA and BMI are derived from self-reported measures,
which are subject to error and bias. Second, these
findings are cross-sectional, thus limiting causal infer-
ence, and may be influenced by residual confounding
(due to unmeasured characteristics for which there is
no control). Third, it is difficult to assess the true
validity of the cluster method, given that cluster analysis
will detect underlying patterns in data, regardless of
meaning or utility. To address this issue, this research
utilized several approaches, similar to those used in
other previous applications of cluster methods, includ-
ing (1) assessing numerous iterations of cluster solu-
tions to ensure that the final solution represents robust
patterns in the data, (2) comparing these findings to
established theoretical frameworks, such as the eco-
zones of transect planning, and (3) contrasting these
clusters with external variables (that were not used in
the cluster creation), such as PA and overweight status.
The latter is critical for ensuring meaningful interpret-
ability of the cluster results.
Finally, the strength in this study of using data charac-
terizing multiple sites across the nation may also limit the
all of the neighborhood characteristics are relevant to
individual participants, they represent varying degrees of
"neighborhood," potentially carrying varying degrees of
influence. Methods for defining one's neighborhood are
highly debated; there is no consensus on appropriate
buffer sizes to capture relevant exposure areas. The
exposure areas assessed here may not be the most appro-
priate size (e.g., 1-mile buffers, county-level crime). In-
deed, this is an important area for future research,
including detailed analyses on methods of measuring
environmental characteristics and important aspects of
influential neighborhood features.
This is possibly the first research characterizing the
national landscape in this way, understanding how
neighborhoods function as a whole (rather than as
individual components) and how they are associated
with adolescent health behaviors and outcomes. Indi-
viduals live in neighborhoods rather than income
brackets, and are simultaneously affected by factors
such as crime, facility access, and street connectivity,
which work in concert to affect health behavior. While
traditional risk factor analysis provides important in-
sights into the association between environment and
behavior, these findings show that broad, traditional
measures of neighborhood characteristics (e.g., me-
dian household income) may not capture the fine-grain
detail and complexity needed to better understand how
environments influence behavior. Thus, using pattern
analysis with detailed environmental measures supple-
ments the understanding of covariance in the environ-
ment and important environment–behavior relation-
ships. Effective population-wide health promotion
strategies and public policies need to address pre-
existing neighborhoods, which are composed of a
variety of factors, many of which may be important
determinants of activity patterns.
The patterns of neighborhood features identified
here show meaningful variation, supported by urban
planning theory and empirical evidence. Not only do
these findings help illustrate the important effects of
neighborhood on health, but they also demonstrate the
inherent complexity of these relationships. This re-
search highlights the extent to which neighborhoods
vary, as well as how individuals may function differently
in different environments, and points to the challenges
of increasing population-wide PA through community
design. Future research is needed to explore the spe-
cific mechanisms through which neighborhood form
affects population health, as well as the interactive
effects of a spectrum of co-varying community charac-
teristics and the extent to which effective intervention
and policy strategies can be tailored to promote healthy
Funding for this study and the development of the prelimi-
nary spatial measures comes from the National Institutes of
Health, including the National Institute of Child Health and
Human Development (NICHD) (R01-HD39183-01, R01
HD041375-01, and K01 HD044263-01), National Institute of
Diabetes and Digestive and Kidney Diseases (DK56350),
National Instituteof Environmental
(P30ES10126); a Cooperative Agreement with the Centers for
Disease Control and Prevention (CDC SIP 5-00); and a New
Investigator Dissertation Award from the Robert Wood John-
son Foundation's Active Living Research Program (050752).
Health Sciences
American Journal of Preventive Medicine, Volume 31, Number 2 www.ajpm-online.net
Page 9
We also thank the Spatial Analysis Unit at the University of
North Carolina at Chapel Hill, particularly Phil Page, Jay
Stewart, and Evan Hammer, for their assistance in data
collection and processing.
This research used data from Add Health, a program
project designed by J. Richard Udry, Peter S. Bearman, and
Kathleen Mullan Harris, and funded by the NICHD (P01-
HD31921), with cooperative funding from 17 other agen-
cies. Special acknowledgment is due Ronald R. Rindfuss
and Barbara Entwisle for assistance in the original design.
Anyone interested in obtaining data files from Add Health
should contact Add Health, Carolina Population Center,
123 W. Franklin Street, Chapel Hill NC, 27516-2524
No financial conflict of interest was reported by the authors
of this paper.
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August 2006Am J Prev Med 2006;31(2)


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text:
Wilson: Top-down thinking won't solve poverty
Few things in life satisfy as well as a pithy quote, and minister Angeloe Burch delivered a well-crafted zinger at a meeting earlier this month on what to do about Northeast Central Durham.
"Before I stand in the pulpit and preach about going to hell," Burch thundered, "I want to deal with the folks who are living in it."
Burch was talking about Mayor Bill Bell's initiative aimed at turning around one of the city's most pathological areas. Specifically, Bell has zeroed in on Blocks 2 and 3 of Census Tract 10.01, the worst of the worst.
Now, Northeast Central Durham isn't really an outlier of the infernal regions, but it's close enough to qualify as a contender.
Durham has wrestled with the violence, poverty, drug abuse and other indicators of socioeconomic failure in Northeast Central Durham for more than 20 years. Essentially, nothing has changed.
So you really can't blame the residents for being skeptical of Bell's anti-poverty initiative. Been there, done that.
This time, however, some of the stalwarts in Northeast Central Durham got up a head of steam and walked out of the second of three planning sessions for initiative volunteers and leaders. They disinvited themselves, saying the effort is too much of what has produced so little: government direction from the top down.
This mini-rebellion left the meeting adrift, and Bell was quick to recognize that his initiative needed a new rudder. He postponed the third and final meeting to regroup and refit.
The walkout was orchestrated by Communities in Partnership, an ad hoc group in Northeast Central Durham that rightly demands appointment of more residents to the initiative's leadership.
Bully for the partnership. If it took an embarrassing episode to get attention and action, the group scored a hit. At the time, there was little representation from Northeast Central Durham in the initiative, and none in the leadership.
All these people want is a voice in determining the future of their neighborhoods. Retired district court judge Craig Brown went to the core of the issue when he said Northeast Central Durham will be heard or "I'm going to have to raise some hell."
What Bell and the other initiative planners seemed to miss is that people live in neighborhoods. They do not identify with numbers like Census Tract 10.01. Such sterile designations are the product of the census bureaucracy, which drapes them with all manner of statistics useful for Bell's initiative.
And by any measure, Census Tract 10.01 is fertile ground as a test case for the initiative. Unemployment is endemic, per capita income is in the cellar, housing is among the worst in Durham, crime is a constant in the lives of residents – you name it, you'll find it there.
If Bell's initiative has any chance of success, the people who live in Northeast Central Durham must not only be brought into the process but also given a stake in its direction. After all, they are the ones directly affected by it.
Direction from the top down amounts to nothing more than central planning. It objectifies people, strips them of individuality and neuters them. They become, as the residents of Northeast Central Durham have become, weary of unfulfilled promises.
They see a new, increasingly prosperous downtown rising, but they are restricted to the margins, a caste of disposable people whose poverty reproduces itself in every generation.
It's been said time and again that money alone can't cure poverty, but it certainly helps.
Money comes from jobs, and there aren't enough in Northeast Central Durham to sustain it. Just one well-paying firm with 100 employees could inject a continuing stream of money and hope into the blighted area.
One thing for sure: Government can't bring prosperity to Northeast Central Durham, but it can lay the foundation for revitalization by making the area more attractive to businesses with tax and other incentives.
Perhaps those who walked out on Mayor Bell will now walk in as full-fledged contributors to his initiative. I think he got the message.
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The Week in iPad Cases: Playing for keeps
@mtabini, @joelmmathis
- The Week in iOS Accessories: Apple Watch accessories are proliferating
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Covers the concepts and techniques behind efficient photo management and backup, which becomes increasingly important as a photo collection grows.
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The staff at IAAP Headquarters wants to celebrate Administrative Professionals Day with you. Join us in Kansas City for an open house on APD. Meet the staff and celebrate your positive contribution to
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In What Year Did Childern Ages 0-12 Became Infected With Hiv/aids In The Country Of Haiti
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HIV and Aging...the Need for Social Support for the HIV-Positive Aging Population Taking Care of Yourself The Aging HIV Population Is Growing HIV began mostly as a disease of young men, but today the epidemic impacts people of all ages, including older people (age 50 and over). Issues related to HIV and older people are receiving more and more attention as this population grows. In fact, on September 18, 2009, the first National HIV/AIDS and...
Ask the Experts
Death (HIV/AIDS A CHRONIC, NOT ALWAYS SO MANAGEABLE, CONDITION, 2010) ( HIV AND ACCELERATED AGING, 2010)I think the p.c. word is morbidity . I recently had an argument with one of the very few friends iv disclosed to who stated , "people don't die from aids anymore". For whatever reason after 4 years despite three meds ( kaletra, truvada, instentra) I...
Response from Robert J. Frascino, M.D.
The Robert James Frascino AIDS Foundation...Hello Pillboy,Morbidity means illness. Mortality refers to pushing up daisies.Your friend is woefully misinformed. HIV/AIDS is a slowly progressive disease that does not have a cure. That makes it a terminal (fatal) condition. Yes, we have made... Read more »
"The Age Of AIDS"Thanks for the info about this PBS program. Just wanted to let you know I found it for free at pbs.org and by typing The Age of AIDS into the search field. I believe you said it could be found at Net Flicks and Blockbuster, which is good for...
Response from Robert J. Frascino, M.D.
The Robert James Frascino AIDS Foundation...Hi,I'm glad you found "The Age of AIDS" on pbs.org. It does a good job describing the first 25 years of the epidemic.Regarding a documentary that follows newly Read more »
Hiv-Aids will could be cured in 4 years time says Hiv Noble prize winning ProfessorWE COULD HAVE HIV-AIDS CURE IN 4 YEARS WITH PROBER FUNDING says the professor that found HIVOct 13, 2008 Hi Dr Ewald, you are our shining light with the countless hours and time you put into helping people with hiv live a normal life... Noble prize...
Response from Ewald Horwath, M.D.
University of Miami School of MedicineI certainly hope that he is right. Let's pray that he is. Read more »
WE COULD HAVE HIV-AIDS CURE IN 4 YEARS WITH PROBER FUNDING says the professor that found HIVHi Keith, you are our shining light with the countless hours and time you put into helping people with hiv live a normal life...Noble prize winner prof Luc Montagnier has stated a cure for hiv can be on hand with in 4 years with proper govement...
Response from Keith Henry, M.D.
University of Minnesota, School of Medicine...deserves hie Novel Prize I take issue with his statements that an effective therapeutic vaccine can/well be available within 4 years. It pains me to state that we do not know enough about the human immune system to develop and effectively test... Read more »
Haiti Making Progress Against HIV/AIDS, Challenges Remain, Opinion Piece Says...Chelala writes that United Nations data show that about 2.2% of Haiti's population -- or 120,000 people -- are living with HIV/AIDS and that AIDS-related deaths in the country have decreased in recent years. This compares with an HIV/AIDS... Read more »
United States to Grant $7 Million to Curb Mother-to-Child HIV/AIDS Transmission in Ethiopia...run jointly by the Ethiopian Ministry of Health and the HIV/AIDS Prevention and Control Ofice, in conjunction with the U.S. Agency for International Development , CDC and UNICEF , Xinhua News Agency reports ( Xinhua News Agency , 9/8). ... Read more »
NMAC Honors the Tenth Annual National Black HIV/AIDS Awareness Day... Washington, D.C. -- The National Minority AIDS Council (NMAC) will honor the tenth annual National Black HIV/AIDS Awareness Day on February 7th. Held during Black History Read more »
Amid Unrest, Haiti Gains in Fight on AIDS...address acute inequities that emerged in the late 1990s, a time when expensive new drug cocktails transformed HIV/AIDS into a manageable disease in rich nations, while patients in poor countries continued to die because they could not afford... Read more »
Connect With Others
HIV/AIDS Year in Review: Looking Back on 2010
Posted by bartleby...So much has happened this past year. We're rolling out end-of-the-year reviews . So check it out! You'll find: Top HIV/AIDS Clinical Developments of 2010 The Buzz Factor: Most Talked-About Stories on TheBody.com in 2010 and you can even... Read more »
Excellent article on HIV & aging, "New York" mag.
Posted by BrokenWingedBird, 2 Replies... "Another Kind of AIDS Crisis" A striking number of HIV patients are living longer but getting older fastershowing early signs of dementia and bone weakness usually seen in the elderly. Read more »
Age of AIDS to air on PBS May 30 and 31
Posted by ScotCharles, 2 Replies...http://www.pbs.org/wgbh/pages/frontline/aids/ PBS Frontline will air a documentary on HIV/AIDS from the first mysterious cases in the late 70's to the present pandemic. Read more »
On the rise 3.5 years post HIV/AIDS diagnosis
Posted by PositiveInPVD, 5 Replies...Well, just some words of encouragement for anyone who is particularly new to this whole thing. After diagnosis in Dec 2002 when I was in very bad shape by the time Read more »
Resource Centers
Guides for People With HIV


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Originally written on WZR Online | Last updated 11/20/14
– TNA Gut Check winner Jay Bradley is officially under contract with TNA Wrestling. He is currently down at Ohio Valley Wrestling working on his ring skills. – Not including the UK tour, TNA's average live event attendance in January 2013 went down 54% to 550 from the 1200 in January 2012. iMPACT! in January 2012 averaged a 1.15 rating and 1.61 million viewers but in January 2013 it averaged a 1.12 rating with 1.53 million viewers. – As noted Wednesday morning here on the website, Jules Wortman was fired as VP of Public Relations in TNA Wrestling. Wortman, whom reported directly to Dixie Carter, also runs her own Public Relations firm called Worman Works. She was fired over something that happened over TNA Lockdown weekend. Wortman's TNA departure comes on the heels of Chris Thomas giving his notice that he was leaving the company for another job in Hollywood. Thomas was someone that routinely handled the media for TNA and had been in touch with us numerous times.
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Darden Restaurants (DRI) sees FQ3 (ending Feb. 26) EPS of $1.23-1.25, ahead of Street consensus...
Darden Restaurants (DRI) sees FQ3 (ending Feb. 26) EPS of $1.23-1.25, ahead of Street consensus of $1.19. The company notes a benefit from the shift in the Lenten season - which started during FQ3 this year - as well as less severe winter weather. Shares +0.8% premarket. (PR)
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The Christian As a "Sermon"
How one lives is a better "sermon" any day than what he says. What kind of sermons does your life preach?
How one lives is a better "sermon" any day than what he says. What kind of sermons does your life preach?
The book of Hebrews is a marvelous treatise revealing the superiority of Christ and his New Covenant system over that of the preparatory Mosaic regime. The first chapter presents some fascinating portraits of the Lord Jesus.
When the apostle Matthew wrote that an Old Testament prophecy had been "fulfilled" by Christ, just what did he mean? Engage in this study with us.
Some years ago a few scientists declared that the theory of evolution was as well established as the rotundity of the earth. But evolution is still a theory, not a law. All of the basics of this theory stand in opposition to known science.
Is it possible that dinosaurs and humans inhabited the same early earth? If so, why aren't dinosaurs mentioned in Genesis 1? Study this issue with us.
The Fundamentalist Mormon Church has been in the news of late, with the raid on the Texas Temple and the rescue of women and children from their peril. News outlets have repeatedly stated that this "Fundamentalist" movement bears no relationship to the Mormon Church in Salt Lake City. That is a serious misconception.
Expelled: No Intelligence Allowed is the title of a documentary movie that premiers across the nation on Friday, April 18. We encourage our readers to see this presentation.
In Revelation 13, John sees a vision of two beasts—one arising from the sea, another from the earth. What do these images represent?
How do atheists determine what is moral or immoral? While they frequently claim there is a "standard," closer examination reveals that the name of the game is "make up your own rules."
Ants are amazing little creatures. In many ways they exhibit "design," hence argue for a Creator who designed them for their various functions.


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Working with Your Spouse: How Close Is Too Close?
If one goes by conventional wisdom, then working with your spouse in the same organisation is not a good idea. Every relationship requires breathing time and being together 24*7 is considered a little too close for comfort. However, this trend seems to be changing. In light of 21st century relationships getting affected by erratic work timings, most often a couple that follows a similar work routine survives into ripe old age. Even though some companies or sectors do not allow couples to work within the same departments, some others like healthcare, education, media and IT, are increasingly encouraging couple co-workers. But how fine a line can a couple stay away from and what does working together do to the relationship? Let's take a closer look.
A few benefits of sharing office life:
- A heightened sense of accomplishment when the couple works together.
- If he or she is your business partner, then it becomes easy to trust him or her implicitly in business.
- It also becomes easier to handle children emergencies. For example, if you and your spouse work in the same organisation, then it becomes easier to figure out who is supposed to handle the emergency phonecall at school.
- Working together may keep you well motivated on the track, by bringing the best in both of you. It is often seen that people tend to find work more motivating when their partner encourages their work actions. Another benefit arises due to this - the partners understand each other's work pressure. This enables them to fight less, and have more realistic expectations from each other's time and attention.
However, a couple that works together is not without challenges. For instance, the dinner time conversations may be about work, work and more work. If the couple doesn't draw a line that separates the can-discuss to the must-never-discuss points, then this could lead to gray areas in the relationship that cause fights often. Further, the couple must be mature enough to deal with situations such as only one of the two getting a promotion, only on of the two being selected for an important project, and so on. Professional competitiveness can be handled in an efficient way only if both the partners are mature enough to handle the aspect of working in the same organisation.
Thus, it becomes important to set the rules straight.
- Do not treat the decision to work together lightly. Join the same company, or start the same business only if both of you have planned it mutually and not because other options didn't work out in your favour.
- Make sure that you understand that there will be competition. If you or your partner will respond to competitiveness with jealousy, then you're in for a hard time.
- Never get stuck in gender roles if you are working with your spouse. Be it office or home, start with a clean sheet of paper.
- Never involve professional feelings in your personal life and vice versa. Schedule long weekends with zero work talk.
- Decide priorities between work and personal life.
- Meet a relationship counsellor if you think you need somebody to remind you that your marriage is a priority.
To wrap it all in brief, we strongly believe that work is just another vehicle en route to bigger things. In actuality, a healthy mind-life balance is about being a better and more aware individual. This balance can only be gained through careful sizing up of your personal and professional preferences. Once you achieve a clear line of thought, you will find it easier to participate in a mature relationship, which is not harmed by too much proximity to your loved one.
*Image courtesy: © Thinkstock photos/ Getty Images
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Jasper Johns / In Press: The Crosshatch Works and the Logic of Print
Tue, May 22 - Sat, Aug 18, 2012
Times: Tuesday-Saturday, 10am-5pm; closed major holidays.
Venue: Arthur M. Sackler Museum
485 Broadway, Cambridge, MA 02138
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Centering on Harvard's collection of Johns's signature "crosshatch" works of the 1970s, this exhibition explores the impact of print on his oeuvre. It examines "print" and "the press" in terms not only of printmaking and Johns's celebrated experiments in that medium, but also in informational terms, tracing his frequent use of newspaper collage and its material, temporal, and political implications. Also featured is comparative material exploring Johns's relationship to the history of printing.
Brew Woo – Worcester's Original Craft Beer Festival
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Fuse Creativity System Project Guide: Fun Party Themes, Idea for Handmade Cards, And More Paper Crafts from Fiskars
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Best Fishes
By: Karen Hunsaker for Spellbinders
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This shimmery card from Spellbinders is perfect for a fisherman. It's so pretty and glittery that little girls will love it, too!
- S3-038 Butterflies
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- Cut green shimmer cardstock to make 5½ x 4¼" card. Cut blue cardstock 5¼ x 4".
- Create wave pattern on 5½ x 4¼" piece of scrap paper, taping twine in place.
- Run blue cardstock through Wizard™ with an embossing sandwich: placing the blue cardstock on top of the wave and the embossing mat on top of that.
- Cut S4-210 Lattice Pendants from scrap cardstock.
- Cut S4-137 Classic Scalloped Heart (with #1 being the smallest) from F-001 Red Premium Craft Foil. Emboss heart by placing it over a portion of the die cut Lattice Pendant. Adhere to center of card with foam square.
- Cut two fish from F-003 Blue Premium Craft Foil. Emboss with Magic Mesh by leaving the foil in the die template and running it through the Wizard™. Remove the die cut and lightly sand. Adhere to card front with foam squares as shown.
- Wrap ribbon around blue wave cardstock ½" from bottom.
- Print or stamp sentiment on green shimmer cardstock. Cut/emboss with S3-149 Double Ended Tags. Adhere to card front, over ribbon.
- Place small scraps of blue foil over circles of S3-038 Butterflies die template. Cut and emboss. Remove the dots and use hot glue to adhere to tag ends.
- Glue blue wave cardstock to card front.
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QAD President and Chairman Pam Lopker Named Top Woman in Business
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Latest laser ablation Stories
Presentations at Stanford Biodesign New Arrhythmia Technologies Retreat and Heart Rhythm Society (HRS) Continue Focus on Atrial Fibrillation Ablation MARLBOROUGH, Mass., May 5, 2014 /PRNewswire/
Latest joint application of these two technologies provides direct, intraoperative visualization during surgery to treat a childhood brain tumor MINNEAPOLIS, MN and IRVINE,
The Comprehensive Epilepsy Care Center at North Shore-LIJ's Cushing Neuroscience Institute is one of the first in the United States and the first in the New York metro area to use a new combination
Men with low-risk prostate cancer who previously had to choose between aggressive treatment, with the potential for significant side effects, and active surveillance, with the risk of disease progression, may have a new option.
Engineers have discovered details about the behavior of ultrafast laser pulses that may lead to new applications in manufacturing, diagnostics and other research.
For people who care about the appearance of their legs, compression hosiery, which is universally recommended for both surgical and non-surgical treatments of varicose veins and spider veins, works to promote leg health and may also be worn to alleviate aching, tired, or restless legs.
Physicians at Mayo Clinic's Florida campus are among the first in the nation to use a technique known as MRI-guided laser ablation to heat up and destroy kidney and liver tumors.
Laser ablation is well known in medical applications like dermatology and dentistry, and for more than a decade it has been used to vaporize materials that are difficult to evaporate for high-tech applications like deposition of superconductors.
HOUSTON, Aug. 30 /PRNewswire-USNewswire/ -- As one of the leading medical centers in the U.S. diagnosing and treating twin-to-twin transfusion syndrome (TTTS), Texas Children's Fetal Center is proud to announce the successful completion of its 200th TTTS laser ablation surgery.
- Forsooth! indeed! originally a parenthetical phrase used in repeating the words of another with more or less contempt or disdain.


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Our special coverage of the closest race for years
Explore the personal stories of Syrian refugees in Lebanon
06 Aug 2009 03:09 GMT
Clinton's high stakes N Korea dash Inside North Korea's labour camps N Korea's nuclear trump card 'Stark choice' for N Korea N Korea seeks direct talks with US North Korea's future Video: N Korea frees US journalists
"We were taken to a location and when we walked through the doors, we saw standing before us President Bill Clinton. We were shocked, but we knew instantly in our hearts that the nightmare of our lives was finally coming to an end. And now we stand here home and free."
The pardon followed a visit by Clinton to Pyongyang, the North Korean capital, for talks with Kim Jong-il on freeing the journalists.
North Korean authorities arrested Ling, 32, and Lee, 36, in March, saying they had crossed the border with China illegally "for the purpose of making animation files to be used for an anti-DPRK [North Korea] smear campaign over its human rights issue".
The two, who worked for the California-based Current TV co-founded by Al Gore, Clinton's vice-president, were found guilty after a trial and sentenced to 12 years of hard labour in June. 'Private visit'
Barack Obama, the US president, thanked Clinton for his work towards securing the release of Ling and Lee.
"I want to thank President Bill Clinton - I had a chance to talk to him - for the extraordinary humanitarian effort that resulted in the release of the two journalists," he said.
But the Obama adminstration has insisted that the former president was acting as a private citizen and the trip was limited to securing the freedom of Ling and Lee.
Hillary Clinton, the US secretary of state, said the journalists' release was a separate matter to talks on North Korea's nuclear ambitions.
Speaking during a visit to Kenya on Wednesday, Clinton urged Pyongyang to engage with the international community.
"The future of our relationship with the North Koreans is really up to them. They have a choice," Clinton said at a news conference with Moses Wetangula, the Kenyan foreign minister, in Nairobi."We have always considered that a totally separate issue from our efforts to re-engage the North Koreans and have them return to the six-party talks and work for a commitment for the full, verifiable denuclearisation of the Korean peninsula," she said.
'Propaganda coup'North Korea's state-run KCNA news agency said Bill Clinton had apologised on behalf of the women and relayed a message of gratitude from Barack Obama, the US president.It said that the visit would "contribute to deepening the understanding between the DPRK [North Korea] and the US and building the bilateral confidence".Christopher Nelson, an Asia analyst in the US who edits the Nelson Report on international affairs, told Al Jazeera that more than just the release of the two journalists needed to have come from the visit for it to be considered a success by Washington.He said the North Koreans "definitely wanted the propaganda coup of getting [Clinton] to go there and show respect to Dear Leader - to the leader of North Korea - and ... they got that in spades".
"So people here [in the US] are worried, with cause, that if all we get are the two women being returned - and we're personally thankful for that, of course - then maybe we gave the North Koreans a little too much."
Bill Clinton "didn't go to negotiate this, he went to reap the fruits of the negotiation", Sneider told the Associated Press news agency.Relations between North Korea and the US have worsened following Pyongyang's second nuclear test on May 25 and consequent United Nations sanctions.
North Korea pulled out of six-party talks on its nuclear programme, expelled nuclear inspectors and test-fired a barrage of missiles in defiance of the sanctions.
It also repeatedly issued bellicose rhetoric against South Korea and the US, but indicated last week that it was open to direct talks with Washington.
The US has maintained that the six-party arrangement is the appropriate forum for dialogue.
Source: Al Jazeera and agencies
Ex-US president Bill Clinton secures pardon and release for jailed reporters.
Former president's "face-saving" visit may open new chapter in US-N Korea relations.
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Born Name: Aamir Hussain Khan
Nick Name: Aamir, AK, Mr. Perfectionist, Tom Hanks of India
Date of Birth: 14 March 1965
Place of Birth: Mumbai, Maharashtra, India
Sun Sign: Pisces
Nationality: Indian
Religion: Islam
Education: Aamir khan was not interested in studies as he more focus and always busy with dramatics. He has done his pre-college education from Narsee Monjee College in Mumbai. But he barely attended classes. He was a state tennis champion during his school days.
Profession: Indian film actor, producer, director and writer


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Ishpeming-Negaunee, Westwood take swim meet titles
January 27, 2015 NEGAUNEE — The Ishpeming-Negaunee boys and Westwood girls picked up high school swimming and diving victories on Monday. more »»
R-M girls fall at Ewen-TC
January 27, 2015 EWEN — The Republic-Michigamme girls basketball team got off to a rough start Monday and wasn't able to recover as the Hawks fell at Ewen-Trout Creek 42-25. Jazzmond Pantoja led R-M with nine points. more »»
Newberry boys fall to Rudyard
January 27, 2015 NEWBERRY — John Paramski recorded team highs of 12 points and nine rebounds, but it wasn't enough to prevent the Newberry High School boys basketball team from falling at home, 81-50, to Rudyard on... more »»
No baskets, no problem
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January 23, 2015 EBEN — The Republic-Michigamme girls basketball team took the court with heavy hearts Thursday following last weekend's death of head coach Matt Davidson, but they honored him well by picking up... more »»
Boburka, Nelson lead Westwood
January 23, 2015 HOUGHTON — Fred Boburka and Nathen Nelson each had a hand in three victories as the Westwood High School boys swimming and diving team lost a 97-62 decision at Houghton on Thursday. more »»
Mountaineers zip past Manistique
January 23, 2015 IRON MOUNTAIN — Iron Mountain shook off Manistique in the second half to post a 62-42 Mid-Peninsula Conference boys basketball victory on Thursday. more »»
Briones preparing for next level
January 22, 2015 MARQUETTE — Whether an Upper Peninsula player or somebody from anywhere else in the country, getting to play NCAA Division I football is a pretty rare feat. more »»
Ishpeming can't stop Gladstone on wrestling mat
January 22, 2015 GLADSTONE — It didn't take long for two prep wrestling teams to decide the outcome here Wednesday night as the Gladstone Braves posted a 41-24 triumph over the Ishpeming Hematite. more »»
Stewart leads MSHS gymnasts to victory
January 22, 2015 MARQUETTE — Senior Dinele Stewart led a 1-2-3 sweep of the all-around to help Marquette gain a 13-point victory over Escanaba in a girls' high school gymnastics meet held at the Redettes' gym on... more »»
Grinding and clawing
January 21, 2015 ISHPEMING — Sometimes, even the best of teams have to claw their way to a win. Such was the case for the Class ABC No. more »»
Patriots' offensive outburst falls just short
January 21, 2015 ESCANABA — It was a tight basketball game from start to finish Tuesday night as the Escanaba boys outlasted the Westwood Patriots 62-60 in a nonconference matchu. more »»
Ishpeming's Willey wins 100th
January 21, 2015 ISHPEMING — Ishpeming senior wrestler Johnathan Willey won his 100th high school varsity match Monday night against Gwinn. more »»
Johnson leads Negaunee girls to win
January 21, 2015 L'ANSE — The Negaunee Miners used a strong first half Tuesday night to roll past L'Anse 45-33 in high school girls basketball action. more »»
Norway ready to leave Mid-Peninsula Conference
January 21, 2015 NORWAY — Norway High School has applied for membership to the Mid-Eastern Football and Skyline Central conferences, principal and athletic director Joe Tinti confirmed. more »»
Gwinn rights ship after tough 1st half
January 21, 2015 GLADSTONE — All Darren Sinnaeve could do was sit on the bench with his head in his hand. more »»
Kingsford retains football coach, but promises changes
January 21, 2015 KINGSFORD — "Major changes" will be instituted in the Kingsford High School football program, Breitung Township Schools Superintendent Craig Allen announced Sunday through the school system's online... more »»
Redmen clamp down on defense
January 21, 2015 ESCANABA — The Marquette Redmen high school hockey team survived multiple bursts of pressure, played disciplined hockey in the neutral zone and severely limited scoring chances in skating to a 2-0... more »»
Rapid River girls end 48-game losing streak with buzzer beater
January 21, 2015 RAPID RIVER — The Rapid River girls put quite the exclamation point on their first victory on the basketball court in nearly three seasons. more »»
1,000-point club
January 20, 2015 MARQUETTE — It was no surprise. Hunter Viitala knew it was coming. more »»
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Posts Tagged 'The Bachelor Ratings'
February 6th, 2013 at 1:50 pm
Tuesday Final Ratings: 'Smash', 'New Girl' & 'The Bachelor' Adjusted Up; 'Betty White's 2nd Annual 90th Birthday Special' and 'Vegas' Adjusted Down
Tuesday's final broadcast primetime TV ratings.[Read-More]
February 6th, 2013 at 11:16 am
Stars From ABC's Hit Shows Participate in Live Twitter Chats Saturday, February 9 through Friday, February 15 Including Genie Francis, Jorge Garcia & Anthony Edwards
ABC celebrates your favorite ABC sweethearts with live Twitter chats from various cast members during their Valentine's Day-inspired episodes, as well as[Read-More]
February 6th, 2013 at 9:48 am
'The Taste' is Up & 'The Bachelor' Wins from 9-11PM on ABC
ABC ran a competitive second on Tuesday in Adults 18-49 to CBS' original drama lineup, beating Fox's 2-hour comedy block by 21%[Read-More]
February 6th, 2013 at 8:31 am
TV Ratings Tuesday: 'Smash' Premiere Crashes, 'NCIS' Wins Night, 'The Mindy Project' 'The Bachelor' & 'Hart of Dixie' Up
CBS was the number one network in adults 18-49 and with total viewers.[Read-More]
February 5th, 2013 at 1:56 pm
Monday Final Ratings: 'The Biggest Loser', 'Bones', '2 Broke Girls', & 'Mike & Molly Adjusted Up; 'Deception' Adjusted Down
Monday's final broadcast ratings.[Read-More]
February 5th, 2013 at 11:08 am
ABC Delivers 4 of the Week's Top 20 TV Shows Among Adults 18-49
During the week of January 28, 2013, with most of its Wednesday schedule in repeats and facing the Super Bowl on Sunday,[Read-More]
February 5th, 2013 at 8:55 am
ABC's 'The Bachelor' Beats 'The Biggest Loser' By a Season-Best 20 Percent
Gaining week to week (+11%), ABC earned its most-watched Monday since November 26, 2012 The Net ranked #1 on Monday with Women[Read-More]
February 5th, 2013 at 8:39 am
TV Ratings Monday: 'How I Met Your Mother' & 'The Carrie Diaries' Hit Highs, 'The Following' Down, 'Rules of Engagement' Premiere Solid
CBS was number one with adults 18-49 and with total viewers.[Read-More]


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Interesting! I've never seen them "fresh" before and had never really thought about what they'd look like. They could almost be mistaken for green beans!
Yes, it's curious how they even figured out how to cure and dry them, to make them palatable.
I think there are MANY curiosities in the world of food - who figured out which parts of the blowfish were poisonous and which are not, for instance?? I would have hated to be a slave in that guy's household.... Okay - you try this piece, and you try this piece.... Bingo! What did that guy who dropped dead have again?