Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter.
Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.
Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.
OCR for page 73
6
Assessing State and Community Efforts
Key Points Noted in Presentations
• Policies at the state, county, and community levels are designed
to reduce obesity by addressing physical activity opportunities
and nutrition issues. These policies are highly varied in quality,
purpose, and implementation.
• The content of these policies is difficult to measure because of
the variability of available data and because the policies them-
selves vary to such a great degree.
• Innovative approaches to mining available data and foster-
ing collaboration across sectors and academic disciplines hold
promise for providing more comprehensive information about
obesity prevention-related policies.
Like federal policy makers, policy makers at the state, county, and
municipal levels all have an interest in the health of their citizens and can
play a significant role in efforts to reduce obesity. However, assessing the
effectiveness of policy interventions related to healthy eating, active living,
and obesity prevention can be difficult, Eduardo Sanchez, vice president
and chief medical officer, Blue Cross and Blue Shield of Texas, noted in
introducing a session on the role of states and communities. He observed
that it is frustrating to see effected policy change not have the accompany-
ing action necessary for the policy to make a difference, and that health
73
OCR for page 74
74 MEASURING PROGRESS IN OBESITY PREVENTION
impact assessments are important tools for guiding the development and
implementation of policies and programs. Panelists discussed existing mea-
sures for monitoring the reach and impact of the strategies used by state,
local, and municipal policy makers and the sorts of data that can be used
to track the progress of policy initiatives.
Maya Rockeymoore, president and CEO of Global Policy Solutions
and program director of Leadership for Healthy Communities (LHC), dis-
cussed efforts of the LHC program to reach policy makers about ways to
promote healthy eating and physical activity, with a particular emphasis on
reducing childhood obesity. Laura Kettel Khan, senior scientist for policy
and partnerships, Division of Nutrition, Physical Activity, and Obesity,
Centers for Disease Control and Prevention (CDC), spoke about commu-
nity strategies and measures in obesity prevention. Amy A. Eyler, associ-
ate research professor, George Warren Brown School of Social Work and
Prevention Research Center, Washington University in St. Louis, described
efforts of the Physical Activity Policy Research Network (PAPRN) to fos-
ter research collaboration. Jamie Chriqui, senior research scientist, Health
Policy Center, Institute for Health Research and Policy, and research associ-
ate professor in political science, University of Illinois at Chicago, described
approaches to surveillance of public policies. Finally, Brian Cole, program
manager and lead analyst, Health Impact Assessment Group, University of
California, Los Angeles (UCLA) School of Public Health, addressed assess-
ment of health impacts.
REACHING POLICY MAKERS
Presenter: Maya Rockeymoore
Obesity prevention involves “thinking about everything from the types
of commercials we watch to the types of foods we have available in our
communities to how communities are built, how buildings are constructed,
and even how streets and sidewalks are laid out,” explained Rockeymoore.
Most of these aspects of life are usually taken for granted, she added, so
efforts to reduce obesity entail “systematically calling into question fun-
damental assumptions about our daily lives.” Doing so requires a broad
policy perspective. It is policy makers who are responsible for the laws, reg-
ulations, and other factors that affect these aspects of society, she explained,
and the LHC program works with national associations of policy makers
to help educate their memberships about ways to promote healthy eating
and physical activity; as noted, the emphasis of the program is on reducing
OCR for page 75
75
ASSESSING STATE AND COMMUNITY EFFORTS
childhood obesity.1 Rockeymoore described the organization and a recent
evaluation of some of its results.
The program has two goals, Rockeymoore explained: to help build
policy makers’ commitment to pursuing policies that encourage healthy eat-
ing and active lifestyles, and to assist them in adopting, implementing, and
strengthening such policies. LHC gives grants to organizations that serve
those who govern tribes, states, local jurisdictions, and schools, in both the
executive and legislative branches of government. The National Confer-
ence of State Legislators, the National Congress of American Indians, and
the Association of State and Territorial Health Officials are just a few of
the approximately 15 associations with which the program has worked.
The grants support a range of activities all designed to promote, sponsor,
and support public policies and programs that encourage healthy diets
and physical activity. Examples of the ways the program works through
these leadership associations to influence policy makers include educating
members about promising policies and new research findings; elevating
childhood obesity as a priority focus; and promoting, supporting, and
sponsoring public policies that support obesity prevention.
LHC funds programs with a wide range of purposes and designs,
Rockeymoore explained. Some programs work with policy makers in dif-
ferent roles at the state level, for example, to encourage them to collaborate
on specific issues. Others provide technical assistance at the city or school
level. One program that works at the national level (the National Associa-
tion of Latino Elected and Appointed Officials) engages policy makers from
every level of government. That group provides training in the nature of
the childhood obesity problem and policy options for addressing it, as well
as technical assistance to policy makers as they implement changes in their
own communities.
LHC itself provides technical assistance and various forms of com-
munication and outreach on reducing obesity. It also evaluates the results
of the outcomes of programs it funds, impacts on policy makers, and the
effectiveness of its own efforts. Evaluating the results of policy advocacy
is difficult and is an evolving science, Rockeymoore observed. “Outcomes
are often nebulous, attribution is difficult . . . and external influences are
numerous and dynamic,” she added. For example, the Let’s Move Cities
and Towns initiative launched by First Lady Michelle Obama2 is likely to
have had an impact in many of the same areas that LHC is targeting, and
identifying the respective influence of each is difficult.
1 For details about the organization, see http://www.leadershipforhealthycommunities.org/
(accessed August 2011).
2 For more information about the initiative, see http://www.letsmove.gov/ (accessed Septem-
ber 2011).
OCR for page 76
76 MEASURING PROGRESS IN OBESITY PREVENTION
LHC, which was formed in 2002, completed an evaluation of the first
cohort of organizations to which it awarded grants (Leadership for Healthy
Communities, 2011). The evaluation was designed to collect information
about the extent to which these 11 organizations increased their capacity to
address childhood obesity, the nature and results of the outreach in which
these 11 organizations engaged, the extent to which they effected increase
in the political will of their members to act on obesity reduction goals, and
the effectiveness of the processes they used. LHC used a range of evaluation
tools. It asked both staff at the grantee institutions and policy makers tar-
geted by the funded projects to complete surveys and conducted interviews
with the policy makers. It required grantees to distribute evaluation forms
at events and tallied those results. It also reviewed resolutions passed by
grantee institutions and external data on state policy trends.
Rockeymoore presented the evaluation’s findings. One is that through
its grantees, LHC has reached a group of lawmakers who are primarily
nonpartisan (although those with a declared affiliation are more likely to
be Democrats), and 70 percent are white. Of the 11 grantees, 7 reported
new commitments by their governing bodies related to reducing childhood
obesity. Many increased staffing for obesity-related efforts and held work-
shops or conferences on the topic. All of the organizations also endorsed a
strategy toolkit prepared by LHC, and many distributed LHC-sponsored
publications. Several obtained additional funding from other sources to
expand their efforts.
Rockeymoore reported a 19 percent increase in the number of “policy
makers who agree or strongly agree that it is a policy maker’s role to take
action to help solve the childhood obesity crisis”—an increase from 79
percent in 2006 to 94 percent in 2009. She also noted that high proportions
of the surveyed policy makers reported that the LHC-sponsored programs
had raised their awareness and influenced them to take a range of actions.
For example, the city of Charleston, South Carolina, created a master plan
for children’s health that incorporates obesity-reduction goals; the Colo-
rado State Board of Education enacted new school beverage regulations
that included a ban on the sale of sodas; and San Fernando, California,
developed a new park—all changes initiated or supported by organizations
that had received LHC grants.
COMMUNITY STRATEGIES AND MEASURES
Presenter: Laura Kettel Khan
Like the LHC program, CDC supports local governments and commu-
nities in obesity prevention. As Kettel Khan explained, CDC recommends
both strategies and corresponding measures with which local governments
OCR for page 77
77
ASSESSING STATE AND COMMUNITY EFFORTS
can plan and monitor their progress. These recommendations were devel-
oped in collaboration with an expert advisory group and the International
City/County Management Association, a professional organization for
urban planners and city managers, so that communities could use common
measures that are relatively easy to put in place as they engage in long-term
planning and funding decisions.
The approach to designing the recommendations grew out of recogni-
tion that there is scant knowledge of what works best for community efforts
toward population-based obesity prevention, Kettel Khan explained. The
process is grounded in existing evidence and expert opinion—as opposed
to consensus—and is in some ways “aspirational, or even exploratory,” she
added. The developers hoped that by ensuring an open process, in which all
stakeholders would be involved in both decision making and documenta-
tion of each step, they would be able to begin the process of building a base
of evidence about what works.
Kettel Khan and her colleagues used a two-part methodology for the
analysis on which the recommendations were based. They developed a set
of rating criteria to identify the highest-priority strategies:
• Reach—the strategy is likely to affect a large percentage of the
target population
• Mutability—the strategy is in the realm of the community’s control
• Transferability—the strategy can be implemented in communities
that differ in size, resources, and demographics
• Sustainability—the health effects of the strategy will endure over
time
• Effect size—the potential magnitude of the health effect for the
strategy is meaningful
A similar process was used to nominate and select the most useful
measures, based on the following criteria:
• Utility—the measure serves the information needs of communi-
ties for planning and monitoring community-level programs and
strategies
• Feasibility—the measure can be collected and used by local gov-
ernments (e.g., cities, counties, and towns) without the need for
surveys, access to proprietary data, specialized equipment, com-
plex analytical techniques and expertise, or unrealistic resource
expenditure
• Construct validity—the measure accurately assesses the environ-
mental strategy or policy it is intended to measure
OCR for page 78
78 MEASURING PROGRESS IN OBESITY PREVENTION
Having little basis for the initial selection of measures, the develop-
ment team pilot tested possible measures to ensure that their collection was
truly feasible. For example, one strategy selected was to improve access to
supermarkets. One possible measure for this strategy was the number of
supermarkets per capita, and another was the percentage of households
within a 2-mile radius of each supermarket in a community. Applying the
above criteria pointed the team to the second measure, which they pilot
tested in 20 communities. They found that this was a feasible measure and
selected it.
The results of this analysis were published in 2009. An article in Mor-
bidity and Mortality Weekly Report details the methodology in detail (Khan
et al., 2009), while another document describes the implementation of the
strategies and measures and provides examples for communities to use as
guidance (Keener et al., 2009). Kettel Khan stressed, however, that while
the recommended strategies are grounded in evidence, they are suggestions,
not validated standards.
This was a novel process for CDC, Kettel Khan explained, and she
summarized what was learned from it. First, she noted, “simplicity was
the key.” These strategies engage local government personnel who are not
deeply involved in research or prepared to conduct primary data collection.
Thus, the strategies need to be grounded in secondary data sources that are
easy to obtain. Second, the partnership between local government officials
and public health professionals that is needed for these strategies is not well
established and requires attention. Kettle Khan explained that both sides
had to think in new ways about the vocabulary they use and that public
health workers needed to focus on messages that appealed to the interests of
local government workers. In response to a question, she noted that at pres-
ent, there is a paucity of data available to support guidance to communities
about how long it is likely to take before results from any of these strategies
are evident, and she agreed that that this represents an added challenge for
those implementing strategies at the community level.
Many states have started to implement some or all of the recommended
strategies, Kettel Khan noted, while a smaller number of states have made
efforts to implement some of the measures. Minnesota, for example, which
has an advanced state department of health surveillance system, has com-
mitted to incorporating all of the recommended obesity measures into its
system, and Wisconsin has undertaken a validation study, using its elec-
tronic medical record system, of all 24 recommended measures. Funding
from a CDC Preventive Health and Health Services Block Grant and a deci-
sion by the Department of Housing and Urban Development to incorporate
the measures into several initiatives are likely to further expand the reach
of the recommendations. In response to a question about whether CDC
planned to systematically monitor or conduct surveillance of adoption of
OCR for page 79
79
ASSESSING STATE AND COMMUNITY EFFORTS
the recommendations in communities statewide or nationwide, Kettel Khan
indicated that there was no formal plan or designated funding to do so at
the time of the workshop.
A number of other programs, both within CDC and sponsored by oth-
ers, target obesity in various ways, Kettle Khan noted. Another CDC pro-
gram, Communities Putting Prevention to Work (CPPW), which is focused
on reducing morbidity and mortality associated with obesity and tobacco
use, provides a “phenomenal, once-in-a-lifetime opportunity for investment
in prevention,” Kettel Khan explained.3 It has several components, includ-
ing $450 million in funding to support 50 communities (urban, rural, and
tribal) in efforts to:
• stabilize or decrease the prevalence of obesity,
• increase levels of physical activity,
• improve nutrition,
• decrease the prevalence of smoking and decrease teen smoking
initiation, and
• decrease exposure to second-hand smoke.
Some of the funding will be in the form of direct grants to communities,
and some will provide technical support for implementation and evaluation.
Another component of CPPW is an investment of $125 million at the state
and territory level, and the program is reaching every state and territory
and numerous communities around the country, Kettel Khan explained.
Kettel Khan also mentioned the Nutrition and Obesity Policy Research
and Evaluation Network, a group of researchers who conduct transdisci-
plinary research on policy identification, development, and implementa-
tion.4 This is one example of a research network designed to link research
efforts focused on an obesity-related theme, and PAPRN is another, dis-
cussed next.5
FOSTERING RESEARCH COLLABORATION
Presenter: Amy A. Eyler
PAPRN was developed in response to a finding that population-based
improvements in physical activity “will most likely come from changes at
3 For details about this program, see http://www.cdc.gov/communitiesputtingpreventionto
work/ (accessed September 2011).
4 For details, see http://www.nopren.org/ (accessed September 2011).
5 More information on PAPRN can be found at http://paprn.wustl.edu/Pages/Homepage.
aspx (accessed September 2011).
OCR for page 80
80 MEASURING PROGRESS IN OBESITY PREVENTION
the macro, policy, or environmental level,” Eyler explained. PAPRN is a
special-interest project funded through CDC’s Prevention Research Centers.
It facilitates coordination among approximately 15 research centers around
the country, some funded and some participating on a volunteer basis. With
this many partners, Eyler explained, challenges were initially encountered
in reaching consensus on PAPRN’s mission and the projects it would under-
take. The mission ultimately developed was to identify physical activity
policies and their determinants, describe the process of their implementa-
tion, and determine their outcomes. Figure 6-1, a framework that guides
the network in developing its projects, illustrates the way policies operate
at different levels and how they interact.
PAPRN also needed to establish what sorts of policies it would con-
sider, and Eyler and her colleagues developed a working definition of a
physical activity policy: “a legislative action, organized guidance, or rule
that may affect the physical activity environment or lifestyle behavior. These
policies can be in the form of formal written codes, written standards that
guide choices, or common practices.” Because this definition encompasses
many different approaches, studying their outcomes can be difficult, Eyler
observed. As discussed in Chapter 2, physical activity policies may affect
such aspects of a community as access to recreation areas or parks; bicycle
rack policies at schools, libraries, or community centers; school recess
options; the safety of play areas for children; workplace exercise options;
and access to public transportation.
Data on such policies are collected in different formats, and the evi-
dence base is better for some than for others, Eyler noted. For example,
research has shown that physical education classes in schools will increase
children’s exercise rates if they include significant amounts of moderate and
vigorous physical activity for allotted times in a conducive environment.
The evidence regarding the effects of building a community trail or sidewalk
is still emerging, however. Comprehensive policy study requires multiple
methodologies: surveys, case studies, and detailed qualitative studies set the
stage for larger, more quantitative studies. In addition, evaluation must take
into account the specific ways in which policies are implemented, which will
also affect outcomes, Eyler added.
Eyler described several PAPRN studies and some of the lessons she and
her colleagues have learned. Two PAPRN studies have examined state leg-
islation. For a study of physical education (PE) plans (Eyler et al., 2010a),
researchers used a legislative database called Netscan to identify almost
800 bills related to physical activity. For the years 2001 through 2007,
they found that approximately 20 percent of the bills were enacted (a rate
similar to that for other health-related bills) but that very few of those bills
contained the components of PE that research has identified as important:
time allotted, activity level, teacher certification, and the environment in
OCR for page 81
81
Outcomes of Policy
Policy
Develop and Implement Policy
Determinants of Policy
Identify Policies
Health
Local
Transportation
Regional
Parks/Public Spaces
State
Worksite
Sector Scale National
School
FIGURE 6-1 Physical Activity Policy Research Network framework.
6-2.eps
SOURCE: Reprinted, with permission, from T. L. Schmid, M. Pratt, and L. Witmer,
2006, “A framework for physical activity policy research,” Journal of Physical
Activity and Health 3(Suppl 1):S20-S29.
which the PE is offered. Moreover, little funding has been allocated for
evaluation of these bills’ effects. Although PAPRN found that more work is
needed on the content of legislation, as well as implementation and evalu-
ation, Eyler noted that these results provide a good basis for future policy
surveillance. The content analysis tool developed for this study has also
been valuable in other PAPRN studies.
Another study of state legislation focused on provisions for public
walking trails between 2000 and 2008 (Eyler et al., 2010b). Of the 991
bills the researchers found on this subject, a little more than half concerned
the allocation of federal funds, so they analyzed those bills separately
from purely local measures. Of the 475 bills not related to federal funds,
29 percent were enacted. Emerging evidence indicates that such factors as
connectivity, accessibility, maintenance, funding, and liability influence the
extent to which a new trail will boost physical activity, but the data are not
as firm as those for the critical components of PE.
From these two studies, Eyler and her colleagues found, first, that
states collect a significant amount of information on legislation and that
it is relatively easy to scan some physical activity-related topics—such as
PE—using databases such as Westlaw or Lexis-Nexis. Other topics require
more tedious effort, she added, and states vary in the quality of both what
they report and the legislation they put forward, as well as in the language
they use to refer to physical activity-related elements. This variation can
make it difficult to interpret and compare bills without the assistance of
OCR for page 82
82 MEASURING PROGRESS IN OBESITY PREVENTION
policy experts or lawyers. Looking at bills that were not enacted can also be
instructive, Eyler added, and it is critical to look as well at the implementa-
tion of those that were.
PAPRN researchers also analyzed state obesity plans and programs,
comparing the planning that was done, the frameworks, and the goals
and objectives related to physical activity. Forty-three states have some
sort of plan, although they vary in form and focus. Few have an in-depth
orientation toward physical activity, Eyler noted, and none address all the
components of the National Physical Activity Plan.6 State plans are more
likely to focus on traditional approaches, such as PE, she added, than on
such emerging issues as land use and community design, transportation,
and parks and recreation. Like the legislation research, Eyler explained,
this study provides a good basis for further study. PAPRN is developing a
template states can use to develop more comprehensive plans that is based
on this research, as well as a similar tool based on a study (Steinman et al.,
2010) of regional master plans for bicycle use and pedestrian traffic.
Another PAPRN study (Eyler and Swaller, in press) examined policies
on community use of public school facilities (also known as “joint use”)
in Missouri school districts. The researchers found that 71 percent of the
districts had a plan for community use in place, but that the majority had
copied the policies of either the School Board Association or Missouri
Consultants for Education. They concluded that influencing policies at the
school board level or the consultant level is likely to have a wide influence
on district policy.
Eyler highlighted several conclusions from the work PAPRN has done.
First, she noted that experience with other issues that have been the focus
of public health efforts for some time, such as tobacco and food policy, is
likely to be useful in work on physical activity. Consistent methodology—
for example, for tracking, evaluation, and measures—makes it easier to
compare and assess existing efforts. Also important is to pay attention to
the level at which policies are initiated and the settings in which they are to
be implemented. The ways in which policies at different levels may interact
are important influences on outcomes, Eyler added. Above all, policy mak-
ers and funders want to know whether policies work and if so, how.
SURVEILLANCE OF PUBLIC POLICIES
Presenter: Jamie Chriqui
Understanding the precise nature of existing laws and policies is critical
to assessing implementation and impact, observed Chriqui. She described
6 See http://www.physicalactivityplan.org/ (accessed September 2011) for more information.
OCR for page 83
83
ASSESSING STATE AND COMMUNITY EFFORTS
several approaches to conducting surveillance of public policies, and offered
a definition of public health policy surveillance similar to that of the more
familiar surveillance of public health issues: “the ongoing, systematic col-
lection, analysis, interpretation, and dissemination of information about a
given body of public health law and policy” (Chriqui et al., 2011).
Chriqui distinguished policy surveillance from policy tracking, noting
that surveillance is a way of examining change over time. Quantitative
measures that can be linked with epidemiologic and other outcome data
are used in surveillance, whereas policy tracking systems tend to use text
to describe the elements of bills or simply record the existence of bills that
address a particular issue. Surveillance data are tied to specific points in time
so that the elapsed time between enactment and impact can be assessed,
whereas tracking systems tend to report on new bills introduced within a
time window. Policy surveillance, Chriqui added, is designed primarily for
evaluation, whereas policy tracking is designed for reporting and advocacy.
Box 6-1 lists examples of both tracking and surveillance systems.
Chriqui highlighted in particular the CLASS (Classification of Laws Asso-
ciated with School Students) and Bridging the Gap programs as providing a
wealth of information on state laws associated with school-based nutrition
and physical education issues and with state nutrition and obesity laws,
respectively. State governments and boards of education use these data as
they plan changes to their laws and policies. Data from these projects have
supported such initiatives as the federal Healthy, Hunger-Free Kids Act, the
U.S. Department of Agriculture’s efforts to develop nationwide standards
for competitive foods in schools, and the White House report on childhood
obesity (White House Task Force on Childhood Obesity, 2010).
Policy measurement is “an emerging area of need,” Chriqui observed,
but like any other science, it requires systematic, reliable, and valid mea-
sures. “It’s easy to do it wrong,” she noted, “and very hard to do it right.”
Existing measures vary. For example, current measures of the policies
affecting the built environment were not formulated for scientific purposes,
but groups such as the American Planning Association have developed
auditing tools to fill the gap. As an example of what can be done, said
Chriqui, researchers have developed a detailed tool for coding wellness poli-
cies that provides approximately 50 pages of coding guidance. It includes
individual variables for each category of nutrition education, physical activ-
ity and physical education, school meals, competitive foods sold in schools,
implementation, evaluation, communications, and marketing environments
in schools (Schwartz et al., 2009).
Several resources exist for state-level data, Chriqui noted, such as
Westlaw, Lexis-Nexis, and State Net, but there are no comparable, compre-
hensive resources for community-level policies. In many cases researchers
must collect information directly from municipalities and counties or school
OCR for page 84
84 MEASURING PROGRESS IN OBESITY PREVENTION
BOX 6-1
Examples of Public Policy Tracking and Surveillance Systems
Obesity-Related Tracking Systems
• enters for Disease Control and Prevention’s (CDC’s) Division of Nutri-
C
tion and Physical Activity Legislative Database (http://apps.nccd.cdc.gov/
DNPALeg/index.asp)
• ational Association of State Boards of Education (NASBE) School Healthy
N
Policies Database (http://nasbe.org/healthy_schools/hs/index.php)
• ational Conference of State Legislatures Bill Summaries Database (http://
N
www.ncsl.org)
• ale Rudd Center for Food Policy & Obesity Legislative Updates (http://
Y
www.yaleruddcenter.org/legislation/)
Obesity-Related Surveillance Systems
• ational Cancer Institute’s Classification of Laws Associated with School
N
Students (CLASS) System (school-based nutrition and physical education
policies currently) (http://class.cancer.gov/About.aspx)
• ridging the Gap/ImpacTeen State Obesity-related Policy Data (http://www.
B
bridgingthegapresearch.org/research/sodasnack_taxes)
• ridging the Gap Wellness Policy Coding System (http://www.bridging
B
thegapresearch.org/research/district_wellness_policies)
Surveillance Systems Not Related to Obesity
• DC’s State Tobacco Activities Tracking and Evaluation System (http://
C
apps.nccd.cdc.gov/statesystem/Default/Default.aspx)
• ational Institute on Alcohol Abuse and Alcoholism (NIAAA) Alcohol Policy
N
Information System (APIS) (http://alcoholpolicy.niaaa.nih.gov/)
SOURCE: Chriqui, 2011.
districts if they are interested in district-level policies. Chriqui suggested
that data collected directly tend to be more accurate than survey data when
the goal is to understand what policies are “on the books” compared with
what policies are being implemented in practice (surveys of local officials
being well suited to the latter).
Collecting such data is time and resource intensive, Chriqui pointed out,
explaining that this is an emerging field in which relatively few researchers
are engaged. Most currently available obesity-related policy measures focus
on school settings, she added; fewer address broader aspects of the com-
munity, the built environment, and the food environment. Therefore, much
work remains to be done. Nationwide measures of such polices would be
valuable, Chriqui added, so that researchers and policy makers could look
OCR for page 85
85
ASSESSING STATE AND COMMUNITY EFFORTS
more systematically at the policies that are being implemented in order to
understand why or why not they are having the intended effect. As others
had mentioned earlier in the workshop, few existing measures correspond
specifically to research-based recommendations for reducing obesity. Thus
in Chriqui’s view, “we need the capacity to develop systems to do longi-
tudinal, ongoing policy surveillance on issues related to the physical and
food environments.”
Several participants probed the challenges of understanding what states
and communities are doing, given their significant variability, and wondered
how that variability might be reduced. “The next stage of policy change
may be to work closely with policy makers to help them understand the
elements that make policies stronger, such as accountability structures and
funding mechanisms,” one observed. In response to a question, Chriqui
explained that while 43 states have obesity plans, most adopted them
because doing so is a requirement for receiving CDC funding, and few
states have focused on implementation and evaluation. Comparing policies
is difficult, Eyler added, because there is no common unit. Looking just at,
say, bicycle-pedestrian master plans, “a city as big as Chicago or a group
of three communities in Missouri [might have plans, so] we’re comparing
apples to oranges,” she noted.
ASSESSING IMPACTS ON HEALTH
Presenter: Brian Cole
Cole discussed two tools for influencing decision making related to
obesity reduction efforts: health impact assessment (HIA) and health fore-
casting. HIA is a way of systematically evaluating, synthesizing, and com-
municating information, but it typically focuses outside the sectors with
which public health and health care experts are usually concerned, he
added. It is based on the idea that many opportunities for significant
improvements in public health may lie outside the typical public health pur-
view, such as, in the case of obesity reduction, farm subsidies or transporta-
tion policy. Some of the connections to obesity are straightforward, Cole
noted, but others are less so. For example, an HIA of oil and gas production
on the north slope of Alaska identified significant impacts on subsistence
hunting and probable increases in rates of diabetes among neighboring
populations. A similar analysis of proposed drilling in an oil field located in
a high-density park area in Los Angeles showed that it would significantly
reduce opportunities for physical activity in that area.
HIA is designed to identify the potential health effect of a proposed pol-
icy or project, Cole explained, including intended and unintended benefits
and harms. In this way it differs from environmental impact assessments,
OCR for page 86
86 MEASURING PROGRESS IN OBESITY PREVENTION
which focus only on the prevention of harm. HIA uses a mix of qualitative
and quantitative methods within a standardized framework, with the goal
of producing information that stakeholders and policy makers can readily
use in decision making. For that reason, Cole added, it is important for
experts from different sectors and community stakeholders to help guide
the assessment.
Health forecasting, which can be a tool in an HIA or be used on its
own, is way of applying different scenarios—such as environmental expo-
sures, demographic shifts, or policy changes—to a synthetic population to
explore possible outcomes. In conducting such analyses, researchers apply
existing research evidence—such as data on associations between particular
exposures and effects or trends in the prevalence and distribution of health
conditions and risk factors—as well as established rules regarding the inter-
actions among risk factors, to develop alternative models of what might
happen over time. “The time component is really important,” Cole added,
because HIAs generally do not look at incremental changes that manifest
themselves gradually. Health forecasting models have been used to address
such issues as the health and economic costs of overweight in California
(Fielding et al., 2007), associations between physical activity and coronary
heart disease (van Meijgaard et al., 2009), and the lifetime medical cost bur-
den of overweight and obesity (Finkelstein et al., 2008) (for other examples,
see Edwards and Clarke, 2009, and Roux et al., 2008).
Both HIA and health forecasting, Cole explained, bring a structured
analytic approach to bridging the gap between research and policy. For
example, based on the findings from an HIA of the Atlanta Beltline Project
(a program to improve a land corridor surrounding Atlanta), the Envi-
ronmental Protection Agency awarded a $1 million grant to help clean up
abandoned industrial sites in the study area. Another HIA in Atlanta, of the
Buford Highway corridor, spurred DeKalb County to invest in improving
pedestrian infrastructure to enhance safety and boost physical activity. An
HIA of California’s Proposition 49 revealed that it could potentially exac-
erbate existing disparities in access to after-school programs. After release
of the HIA and briefings with state lawmakers, rules implementing the law
were modified to help ensure that after-school funds would go to schools
and students most in need.
Since 2000, the year the first HIA was completed in the United States,
approximately 130 such analyses have been conducted, Cole noted. His
review of the 75 for which comprehensive information was available
revealed that many (32) examined local projects such as urban redevelop-
ment transit efforts; 22 concerned land use; and 16 focused on social poli-
cies such as labor laws, living wage policies, paid leave, and school policies.
Only a few such analyses to date have examined resource policies, but Cole
regards those as important because they offer the potential to establish links
OCR for page 87
87
ASSESSING STATE AND COMMUNITY EFFORTS
with environmental impact assessments. These studies have explored fac-
tors, or potential disease pathways, such as
• exposure to air pollutants;
• housing adequacy and affordability;
• traffic injuries;
• parks and green space;
• income adequacy and social equity;
• noise;
• mental health;
• social capital and community cohesion;
• access to jobs, stores, schools, and recreation;
• walkability and physical activity; and
• diet, nutrition, food safety, and food insecurity.
Many sorts of data are used in HIAs, Cole explained. Figure 6-2 illus-
trates the data needed for an HIA of a redevelopment project designed to
improve walkability. Baseline data on the original conditions and preva-
lence of walking in the targeted areas are needed. Analysts also need details
on the effects the project was expected to have. Thus, the researchers exam-
ine audits, survey data, the research literature, and other materials. Cole
noted, however, that in many cases, improved data are needed to support
an HIA of physical activity. Specifically, he cited the importance of:
• assessing total minutes of physical activity (on a daily or weekly
basis), as opposed to bouts or days;
• using higher sampling rates to provide robust estimates of physical
activity for small areas and populations (i.e., at the level of counties
or smaller);
• including all types of physical activity, not just activities labeled
“exercise”;
• using longitudinal data to track physical activity over the life span;
• evaluating community interventions that track cohorts before and
after interventions;
• paying greater attention to cross-validation of self-reported physi-
cal activity and accelerometry7 data in diverse populations; and
using off-the-shelf tools8 to estimate physical activity in small
•
areas—for example, to infer physical activity for small areas or
7 An objective measure of physical activity.
8 For example, akin to those developed for the EpiQMS (Epidemiologic Query and Mapping
System) developed by the Pennsylvania Department of Health; see http://app2.health.state.
pa.us/epiqms/Asp/ChooseDataset.asp (accessed October 14, 2011).
OCR for page 88
88 MEASURING PROGRESS IN OBESITY PREVENTION
1 2
Health
Determinant of
Policy
Proximate Impact Outcomes
Health
(e.g., redevelopment
(e.g., walkability)
project) (e.g., CHD)
(e.g., walking)
5
3 4
1. Baseline walkability (walkability audit, planning data)
2. Baseline walking in the affected population (survey data)
3. Information on the expected direct impact of policy or project on walkability
(specifications of policy/project)
4. Dose-response effect of walkability on walking (review of research)
5. Research on the dose-response effect of walking on CHD risk
6-3.eps
FIGURE 6-2 Data needed for a health impact assessment of a redevelopment proj-
landscape
ect designed to improve walkability.
SOURCE: Cole, 2011.
populations from larger samples for which demographic and envi-
ronmental determinants are known.
Cole closed with a few thoughts on how HIA and health forecasting
could be used even more effectively. Sharing of data resources—particularly
those not typically used in peer-reviewed studies, such as analyses con-
ducted by county health departments—is important. Cross-sector and inter-
disciplinary meetings and other connections can facilitate data sharing and
build awareness of what is available from other sectors. Important as well
is to include more environmental factors associated with physical activity in
data collection, and greater communication and collaboration can help with
that. A national, web-based clearinghouse called HIA-CLIC (Health Impact
Assessment Clearinghouse Learning and Information Center)9 provides
information, tutorials, and other resources related to HIAs, Cole noted,
including an archive of HIAs that have been conducted in the United States.
Workshop participants discussed ways to increase the use and reach
of HIAs. One noted that during the Clinton administration, “there was
a mandate for environmental justice to be considered in environmental
impact statements,” and wondered whether a similar mandate could work
in the case of obesity. Environmental impact statements are required only
when there is an expected change in the environment as a direct result of
9 See http://www.hiaguide.org/ (accessed September 2011).
OCR for page 89
89
ASSESSING STATE AND COMMUNITY EFFORTS
a proposed project, another participant noted. Another promising avenue
might be funding mechanisms, a participant suggested. If an HIA require-
ment were integrated into the funding arrangements for new developments,
it might help to “integrate [HIA] into the way we conceptualize building
our communities—and be a mechanism for considering the health impact
of everything from walkability to the quality of the air we breathe.” This
participant suggested that environmental impact statements have had the
greatest benefit by affecting planning from the outset—once people are
aware that minimizing environmental impacts is easiest if it is a design
consideration from the beginning.
REFERENCES
Chriqui, J. 2011. Nutrition and physical activity policy surveillance and measurement: What
do we know, what do we need to know, and what challenges should we consider? Pre-
sented at the Institute of Medicine Workshop on Measurement Strategies for Accelerating
Progress in Obesity Prevention, March 24, Irvine, CA.
Chriqui, J. F., J. C. O’Connor, and F. J. Chaloupka. 2011. What gets measured, gets changed:
Evaluating law and policy for maximum impact. Journal of Law, Medicine and Ethics
39(Suppl. 1):21-26.
Cole, B. L. 2011. Accelerating progress in obesity prevention with health impact assessment
and health forecasting. Presented at the Institute of Medicine Workshop on Measure-
ment Strategies for Accelerating Progress in Obesity Prevention, March 24, Irvine, CA.
Edwards, K. L., and G. P. Clarke. 2009. The design and validation of a spatial microsimulation
model of obesogenic environments for children in Leeds, UK: SimObesity. Social Science
and Medicine 69(7):1127-1134.
Eyler, A. A., and E. Swaller. in press. Community use policies in Missouri. Journal of School
Health.
Eyler, A. A., R. C. Brownson, S. A. Aytur, A. L. Cradock, M. Doescher, K. R. Evenson, J. Kerr,
J. Maddock, D. L. Pluto, L. Steinman, N. O’Hara Tompkins, P. Troped, and T. L. Schmid.
2010a. Examination of trends and evidence-based elements in state physical education
legislation: A content analysis. Journal of School Health 80(7):326-332.
Eyler, A., T. Lankford, J. Kruger, J. Chriqui, K. Evenson, N. Ohara-Tompkins, C. Voorhees,
S. Zeiff, and R. Brownson. 2010b. An analysis of state legislation on community trails.
Journal of Physical Activity and Health 7(Suppl. 1):S40-S47.
Fielding, J. E., G. F. Kominski, D. E. Hayes-Bautista, and J. van Meijgaard. 2007. Trends and
forecast of health and economic costs of overweight and obesity in California. July issue
brief. Los Angeles, CA: UCLA Health Forecasting Project.
Finkelstein, E. A., J. G. Trogdon, D. S. Brown, B. T. Allaire, P. S. Dellea, and S. J. Kamal-
Bahl. 2008. The lifetime medical cost burden of overweight and obesity: Implications for
obesity prevention Obesity 16(8):1843-1848.
Keener, D., K. Goodman, A. Lowry, S. Zaro, and L. Kettel Khan. 2009. Recommended com-
munity strategies and measurements to prevent obesity in the United States: Implemen-
tation and measurement guide. Atlanta, GA: U.S. Department of Health and Human
Services, Centers for Disease Control and Prevention.
Khan, L. K., K. Sobush, D. Keener, K. Goodman, A. Lowry, J. Kakietek, and S. Zaro. 2009.
Recommended community strategies and measurements to prevent obesity in the United
States. Morbidity and Mortality Weekly Report 58(RR-7):1-26.
OCR for page 90
90 MEASURING PROGRESS IN OBESITY PREVENTION
Leadership for Healthy Communities. 2011. Leadership for Healthy Communities program
evaluation report: 2007-2010. Washington, DC: Leadership for Healthy Communities.
Roux, L., M. Pratt, T. O. Tengs, M. M. Yore, T. L. Yanagawa, J. Van Den Bos, C. Rutt, R. C.
Brownson, K. E. Powell, G. Heath, H. W. Kohl III, S. Teutsch, J. Cawley, I. M. Lee, L.
West, and D. M. Buchner. 2008. Cost effectiveness of community-based physical activity
interventions. American Journal of Preventive Medicine 35(6):578-588.
Schmid, T. L., M. Pratt, and L. Witmer. 2006. A framework for physical activity policy re-
search. Journal of Physical Activity and Health 3(Suppl. 1):S20-S29.
Schwartz, M. B., A. E. Lund, H. M. Grow, E. McDonnell, C. Probart, A. Samuelson, and L.
Lytle. 2009. A comprehensive coding system to measure the quality of school wellness
policies. Journal of the American Dietetic Association 109(7):1256-1262.
Steinman, L., M. Doescher, D. Levinger, C. Perry, L. Carter, A. Eyler, S. Aytur, A. L. Cradock,
K. Evenson, K. Heinrich, J. Kerr, J. Litt, Y. Severcan, and C. Voorhees. 2010. Master
plans for pedestrian and bicycle transportation: Community characteristics. Journal of
Physical Activity and Health 7(Suppl. 1):S60-S66.
van Meijgaard, J., J. Fielding, R. Shimkhada, and S. Teutsch. 2009. How do improvements in
physical activity compare to better clinical coronary heart disease management? August
policy issue brief. Los Angeles, CA: UCLA Health Forecasting Project.
White House Task Force on Childhood Obesity. 2010. Solving the problem of childhood
obesity within a generation: White House Task Force on Childhood Obesity report to
the President. Washington, DC: Executive Office of the President of the United States.
