ARCHIVED - Chronic Diseases in Canada

 

Volume 30, no. 3, June 2010

Child Health Ecological Surveillance System (CHESS) for childhood obesity: a feasibility study

R.C. Plotnikoff, PhD (1,2,3); P. Lightfoot, MHSA (4); S. McFall, MA (5); C. Spinola, MA (4); S. T. Johnson, PhD (2,3); T. Prodaniuk, MA (6); G. Predy, FRCPC, DHSA (4); M.S. Tremblay, PhD (7); L. Svenson, BSc (6)

https://doi.org/10.24095/hpcdp.30.3.04

Author References

  1. School of Education, University of Newcastle, Australia; and Centre for Health Promotion Studies, School of Public Health, and Faculty of Physical Education and Recreation, University of Alberta, Edmonton, Alberta, Canada

  2. Faculty of Physical Education and Recreation, University of Alberta, Edmonton, Alberta

  3. Alberta Centre for Active Living, Edmonton, Alberta, Canada

  4. Capital Health, Edmonton, Alberta, Canada

  5. Centre for Health Promotion Studies, University of Alberta, Edmonton, Alberta, Canada

  6. Alberta Health & Wellness, Edmonton, Alberta, Canada

  7. Children’s Hospital of Eastern Ontario Research Institute, Ottawa, Ontario, Canada

Correspondence: Professor Ronald C. Plotnikoff, School of Education, University of Newcastle, Callaghan,  NSW Australia 2308; E-mail: ron.plotnikoff@newcastle.edu.au

Abstract

Objective: To assess the feasibility of employing an ecologically guided childhood obesity relevant surveillance system

Methods: Cross-sectional qualitative and quantitative data were collected from 31 organizational representatives across 28 unique organizations and/or departments from three purposively sampled communities in the Capital Health Region in Alberta, Canada.

Results: All the organizational representatives surveyed reported awareness of childhood obesity and 36% reported participation in child obesity initiatives. Data to support a surveillance system are available but not in a suitable format, and privacy legislation present significant barriers. Interest in developing and sustaining an ecologically based surveillance system was low (18%).

Conclusion: Due to the heterogeneity of available data and limited vision for the development and implementation of a surveillance system, the application of an ecologically based surveillance system relevant to childhood obesity may be constrained. Broad-based awareness of childhood obesity by a wide range of organizations could assist in establishing an effective coalition to address this issue over the long term by supporting the establishment of a surveillance system.

Keywords: ecological surveillance system, child health, obesity, Alberta

Introduction

Prevalence rates of overweight and obesity in children and youth point to an urgent need to address this public health concern.1-4 Given the complex etiology of overweight and obesity, the low level of success of pediatric obesity treatment and the absence of a comprehensive surveillance system to monitor child health in Canada, there is a need for an ecologically driven child health surveillance strategy to inform research, policy and practice related to this public health concern.5-7

Within the context of moderating childhood obesity, the development and validation of a systematic approach to surveillance that considers individual and multilevel environmental factors could enhance capacity for ongoing surveillance, theoretical and applied research, and public health initiatives at a local level.8a-10 More specifically, such a framework could serve to explicate the interactions between the well-established individual behavioural determinants of childhood obesity (i.e. physical inactivity and excess energy intake) and the less understood social and environmental determinants of those behaviours.11-14

To gain further insight into the complex nature of childhood obesity, the Capital Health Region in Edmonton, Alberta, Canada, collaborated with the University of Alberta to initiate a research study addressing childhood obesity from a regional perspective. Initially the project involved the development of a pediatric ecological surveillance prototype whose objective was to address obesity prevention and management among children and youth living in the Capital Health Region. From this emerged the Child Health Ecological Surveillance System (CHESS), which incorporates a multilevel (i.e. individual and environmental) ecological framework that organizes and captures the important constructs and a range of outcomes (i.e. systems/services, research, knowledge and health) driven by existing infrastructure (e.g. resources), leadership (i.e. policy practice and scientific leadership) and the will to act (see Figure 1; the details of the CHESS framework are published elsewhere8b). The various outcomes are then fed back to local decision makers to modify the surveillance system as needed and to identify knowledge gaps and refine metrics, theory and interventions. The ongoing collection of local data on core measures at multiple levels will provide ongoing regional prevalence data, allow for the testing of theories related to secular trends in childhood obesity, and guide the development and evaluation of treatment and prevention programs by providing reliable information.

 

Figure 1
Framework for action on healthy body weight in children

figure 1 Framework for action on healthy body weight in children
Figure 1, Text Equivalent

Figure 1
Framework for action on healthy body weight in children

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The framework for action on healthy body weights in children is driven by the Child Health Ecological Surveillance System (CHESS), which integrates research and practice allowing for surveillance of individual, social, organizational, community, policy and physical environmental influences relevant to childhood obesity. Core to the system are biomedical, clinical, health services and population health variables that serve as important points for the collection of system, service, research and knowledge outcomes. Feedback loops via leadership and will to act generate the ongoing development and recalibration of surveillance system metrics. The information collected by the surveillance system can be used by local decision makers to estimate regional prevalence, test theories related to secular trends in childhood obesity and guide the development and evaluation of treatment and prevention programs.

 

Although CHESS was developed with certain applications in mind, it is thus far only conceptual8c and questions remain as to the practicality and sustainability of the framework at a regional level. Therefore, we sought to further develop CHESS by (1) delineating fundamental system and operational characteristics and determining the metrics (core and subsidiary) within 6 explicit ecological levels* relevant to childhood obesity (study objective 1), and (2) testing the feasibility of applying the framework at a regional level (study objective 2). The primary aim of this paper is to provide evidence for the feasibility of applying CHESS at a regional level within the context of childhood obesity.

Methods

This feasibility study was conducted over 2 phases with the primary aim of testing the practicality and sustainability of applying a global ecological surveillance framework such as CHESS to a local community. The study’s steering committee, which was purposively sampled, included a physician, a scientist, 2 senior public health administrators, 2 epidemiologists and a project coordinator. They contributed knowledge and expertise in the relevant areas of community health, influencing systems and designing health surveillance initiatives. The group was charged with developing an information collection protocol (phase 1) utilizing both qualitative and quantitative data/information gathering techniques.15a Subsequent testing of the newly developed information-gathering protocol (described below) was completed in phase 2.

Phase 1: Creating the Healthy-weight Information Protocol

Using an interactive hybrid Delphi method,16 the Healthy-weight Information Protocol (HIP) was created based on a review of published literature and expert stakeholder input. It includes a working typology of potentially feasible and ecologically relevant indicators/targets of childhood obesity in keeping with guiding principles of the World Health Organization,17-21a and is sorted into core(essential) and subsidiary or additional (useful, ideal) metrics.

Creating the HIP was a necessary first step towards the development of an information-gathering protocol to facilitate the systematic collection and analysis of data for the feasibility testing of CHESS (phase 2). The goals of the HIP were to develop a user-friendly and straightforward system capable of collecting and maintaining longitudinal data using the 6 ecological levels (i.e. individual, social, organizational, community, policy and physical environments); identify gaps in the information needed to determine the significant indicators affecting rates of obesity; create a plan for analyzing the data and develop a variety of multilevel community programs and health initiatives that address child/youth obesity from a population health perspective. The HIP is regionally directed; it builds on existing regional programs and services, provides valuable longitudinal information regarding children’s weight gain at the regional population level, and integrates research and action. The ultimate aim is to produce a theoretically sound and cost-effective tool for collecting relevant information regarding children’s health/obesity in regions throughout Canada and stimulating viable community action regarding child obesity from a population health perspective.

Central to the HIP was the creation of an interview guide to gather pertinent information about community organizations relevant to CHESS within the context of childhood obesity. The interview guide contained 17 questions which sought to describe the organization’s current involvement and perceived commitment to childhood obesity issues (5 questions); estimate relevant and available data/information systems and resources (8 questions); and probe current levels of awareness regarding organizational and community capacity and the degree of perceived motivation within the community and the organization (4 questions). While the questions were primarily open-ended, 7 questions included Likert-type scales enabling the quantification of responses. The HIP Interview Guide (see Table 1) was field tested and changes were made prior to the feasibility assessment (phase 2).

 

Table 1
Healthy-weight Information Protocol (HIP) interview guide
CHILD OBESITY CONCERN/INTEREST/INITIATIVES
1. Tell me how strongly you agree or disagree with the following statement: “Child health is of concern for our community.”
Strongly disagree Disagree Neither agree/disagree Agree Strongly agree
1 2 3 4 5
2. Are there specific programs/services/initiatives/coalitions presently operating in the community that address child health concerns? Tell me about them.
3. Tell me how strongly you agree or disagree with the following statement: “Child obesity is of concern for your community?”
Strongly disagree Disagree Neither agree/disagree Agree Strongly agree
1 2 3 4 5
4. Are there specific programs/services/initiatives/coalitions presently operating in the community that address concerns related to child obesity? (Yes/No) Tell me about them.
5. Has the organization collaborated with any of the following groups/organizations on issues related to child health and/or obesity concerns in the past twelve months?

 

  Child Health Child Obesity
Yes No Yes No
Government
Municipal
Provincial
Federal
Professional Associations
Unions
Businesses outside the health sector
Private sector
Consultants
Universities/colleges
Schools
Public Health
Names/contacts:

 

 
INFORMATION/DATA
1. What types of information/data does your organization presently collect? (Demographic, social, health, program, etc. How the information is collected, i.e. ecological models, form, etc.)
Type of information/data collected:
2. The information presently collected by our organization is used to develop policy, plans and programs/services.
To what degree do you agree/disagree with this statement?
Strongly disagree Disagree Neither agree/disagree Agree Strongly agree
1 2 3 4 5
Other specific uses:
3. How much of the information presently collected by your organization is specifically related to children’s health?
Estimated best guess _______% (for each of the items 3-5)
4. How much of the information presently collected is specifically related to child obesity?
5. How much of the information presently analyzed and utilized by your organization is used to address child health and obesity concerns in the community?
6. Is your organization presently involved in a project that links the information you gather on a regular basis with another organization?
(Yes/No) Discuss the collaboration and the linkage.
7. Tell me what challenges your organization dealt with or might deal with if linking information with another organization?
What supports this type of collaboration?
8. Tell me about the information systems operating in your organization that collect, analyze, and utilize data/information. Specialized dept. staffing, resources etc.

 

 
COMMUNITY BUILDING
This section explores the potential capacity you think your organization and the
Community has for developing, maintaining and utilizing CHESS. We are interested in obtaining your feedback in this section.
1. This organization has the capacity for developing, maintaining and utilizing a Child Health Ecological Surveillance System. (How would you identify/characterize the capacity of your organization to collaborate?)
Strongly disagree Disagree Neither agree/disagree Agree Strongly agree
1 2 3 4 5
2. This community has the capacity for developing, maintaining and utilizing a Child Health Ecological Surveillance System. (Identify/characterize the capacity of the community to collaborate.)
Strongly disagree Disagree Neither agree/disagree Agree Strongly agree
1 2 3 4 5

 

3. CHESS could be useful in helping our organization to address child health concerns in the following ways. Circle each option.
Our Organization
Policy Strongly disagree Disagree Neither agree/disagree Agree Strongly agree
Planning Strongly disagree Disagree Neither agree/disagree Agree Strongly agree
Programs/Services Strongly disagree Disagree Neither agree/disagree Agree Strongly agree
Awareness Strongly disagree Disagree Neither agree/disagree Agree Strongly agree
Program evaluation Strongly disagree Disagree Neither agree/disagree Agree Strongly agree
Research Strongly disagree Disagree Neither agree/disagree Agree Strongly agree
Other Strongly disagree Disagree Neither agree/disagree Agree Strongly agree

 

4. CHESS could help our community address child health concerns in the following ways. Circle each option.
Our Community
Policy Strongly disagree Disagree Neither agree/disagree Agree Strongly agree
Planning Strongly disagree Disagree Neither agree/disagree Agree Strongly agree
Programs/Services Strongly disagree Disagree Neither agree/disagree Agree Strongly agree
Awareness Strongly disagree Disagree Neither agree/disagree Agree Strongly agree
Program evaluation Strongly disagree Disagree Neither agree/disagree Agree Strongly agree
Research Strongly disagree Disagree Neither agree/disagree Agree Strongly agree
Other Strongly disagree Disagree Neither agree/disagree Agree Strongly agree

 

Phase 2: Feasibility assessment

The HIP facilitated the evaluation of the applicability of CHESS in terms of degree of interest and motivation within a community; the quantity and quality of relevant data; the availability of both human and financial capacity; and the potential for sustainability of CHESS at the community level.

Three diverse communities—based on social/cultural, economic and population size indicators—within the Capital Health Region of Alberta were purposively sampled15b for data-gathering using HIP. The populations of the 3 communities range from 15 000 to approximately 50 000, and the overall median family incomes approximate $78,000.§

Key individuals within organizations in the 3 communities were included in the assessment if they had expertise and current or potential involvement in child obesity. They were identified through a snowball sampling technique with names initially selected by the study’s steering committee. In each of the 3 communities, groups/organizations within 5 distinct organizational categories (Tables 2 and 3) were targeted and at least one person from each organization was interviewed in person by the study coordinator. Two individuals from relevant government departments (Education and Child Services), an economist and a social marketing researcher were also interviewed. All interviewees resided and/or worked in one of the 3 study communities.

This study received ethics approval from the University of Alberta Health Research Ethics Board.

 

Table 2
Categorical organization for feasibility assessment of a child health ecological surveillance system
Organizational categories Groups/organizations Relevant ecological level
Municipal Government Planning
Parks and Recreation
Public policya
Institutional factorsb
Physical environmentc
Community Services Family and Child Social Services
Non-profit children’s clubs and organizations
Food banks
Community factorsd
Public policya
Education Day Care
    Public/Private
School
    Elementary/Junior/High
Public policya
Institutional factorsb
Medical Health Services Personal factorse
Interpersonal processf
Business Food Industry
Fitness Centres
Organizational factorsb

 

a Macroeconomic policy level including municipal and provincial policies related to nutrition, regional/provincial statistical reports related to obesity, regulations for food services for schools and daycares, and provincial regulations regarding physical activity (PA) in schools.

b Organizational level including nutrition information regarding school meals and access to healthy choices, access to dietician/nurse in schools, daily PA at school.

c Physical environments include proximity to and number of fast food outlets in a neighbourhood, number of schools with vending machines selling junk foods, access to public transit (cost and location), available infrastructure (parks, cycling and walking paths, secure bike racks, number of cross-walks), design of community buildings, and space for PA.

d Community level including local media campaigns and the number, accessibility and cost of physical activity–related programs to community members.

e Individual level, i.e. height, weight, physical activity (PA) levels, nutrition patterns and practices, attitudes, body fat.

f Social level, e.g. parental attitudes and food choices.

 

 

Table 3
Organizational and personal characteristics of feasibility study participants
  Total number Community Expert
  A B C  
Organizations 28        
Municipal Government 7 3 2 2
Schools/Daycares 6 2 2 2
Community Resources 5 1 3 1
Fast Food Industry 3 1 1 1
Health Services 3 1 1 1
Fitness Industry 2 1 0 1
Provincial Government 2 0 0 8
Individual representatives 31        
Men/women 13/18 4/6 5/4 4/6 0/2
Years employed in current position          
Less than 2 2 3 2 0
  3–5 4 4 3 0
  6–10 2 0 2 1
  More than 10 2 2 3 1
Job Position
Manager 2 2 3 1
Owner 2 2 0 0
Director 3 2 3 1
Programmer 0 0 1 0
Planner 1 1 1 0
Coordinator 1 2 0 0
Educator 1 0 2 0

 

Results

Both qualitative and quantitative cross-sectional data were collected and collated from 31 representatives (58% women; n =18) across 28 unique organizations and/or departments relevant to childhood obesity. All the individuals approached completed the interviews. (See Tables 3 and 4 for further details.)

 

Table 4
Organizational awareness, interest and current involvement in the issue of childhood obesity, available data, and potential ability to sustain a child health ecological surveillance system (number of positive responses)
  Number of positive responses
Organizations
(N=28)
Aware
of topic
Interested
in topic
Provision
of child health program
or service
Obesity
initiatives
Individual
child health
data
Program
data
Easy and practical access to records Interest
in develo-
ping

surveil-
lance
system
Potential for
developing infras-tructure
Vision/
leadership
Community Resources n = 5
Community A 3 3 3 3 3 3 3 2 3 1
Community B 1 1 1 1 1 1 1 1
Community C 1 1 1 1 1 1 1 1
Fast Food Industry n = 3
Community A 1 1 1 1 1 1
Community B 1 1 1 1 1 1
Community C 1 1 1 1 1 1
Fitness Industry n = 2
Community A 0 n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a
Community B 1 1 1 1 1 1 1
Community C 1 1 1 1 1 1 1 1
Health Services n = 3
Community A 1 1 1 1 1 1 1 1 1
Community B 1 1 1 1 1 1 1 1 1 1 1
Community C 1 1 1 1 1 1 1 1 1 1 1
Municipal Govt. Dept. n = 7
Community A 2 2 2 1 2 2 1 1 2
Community B 3 3 3 1 3 3 1 1
Community C 2 2 2 1 2 2 1 2
Schools/Daycare n = 6
Community A 2 2 2 2 2 2
Community B 2 2 2 1 1 2 2 1 1
Community C 2 2 2 1 1 2 2 1
Provincial Govt. n = 2
  2 2 2 2 2 2 2 2 2 2 2
Total positive responses 28 28 19 10 28 28 11 5 18 12
% of orgs. with positive responses 100% 100% 68% 36% 100% 100% 39% 18% 64% 43%

 

Abbreviations: –, not present in the representative organization; N, overall sample size; n, sub-sample size; n/a = no representative organization.

Note: all data from various participating organizations were stored in electronic formats.

 

Organizational awareness, involvement and interest

All the interviewees (N = 31) reported being aware of childhood obesity and expressed interest in the topic (Table 4).

Data

Based on interviewees’ responses, of the 28 organizations that completed the study, 68% provide some form of child health service or program, 36% participate in childhood obesity prevention initiatives, 100% have individual child health data and all have program data relevant to childhood obesity readily available (Table 4). Although all the relevant data are in an electronic format, these data are managed using a variety of platforms and thus only 39% of the available data are potentially accessible and in a practical format for addressing the childhood obesity components germane to CHESS.8d

Table 5 shows general health indicators and data associated with childhood obesity available from the various organizations within the levels outlined in the CHESS framework.8e

 

Table 5
Application of the HIP model based on organizations with accessible information from the 3 communities
Ecological level Application Measures Organizations with the information
Individual/intrapersonala Child health Demographic Most of the participants; Statistics Canada
Child obesity BMI Regional Health Authority
Social/interpersonalb Child health TV watching Community Services; Food Banks
Child obesity
Organizationalc Child health Demographic Public schools; Recreation Centres
Child obesity Monitoring of nutrition and physical activity; journaling Public high schools
Communityd Child health Program registration, wellness, fitness statistics, sports team data Recreation; Community Services; Boys and Girls Clubs of Canada
Child obesity
Macroeconomic policye Child health Hot lunch programs; Daycare nutrition programs Daycares; Provincial and Municipal Governments
Child obesity Mandatory daily fitness programf Provincial Government
Physical environmentg Child health Playgrounds, trail usage, parks, planning and development information, playing field usage Municipal Government

 

Abbreviations: BMI, body mass index; HIP Healthy-weight Information Protocol.

a Individual (intrapersonal) levels include genetic, biomedical, behavioural cognitive and attitudinal behaviours.

b Social (interpersonal) aspects such as family, peers, neighbours, other groups and larger social networks.

c Organizational aspects such as norms, culture, structures, rules, regulations and incentives in schools and other institutions that relate to children.

d Community aspects such as area economics, media, community services, neighbourhood organizations, folk practices, relationships among organizations in the community, municipal structures, formal and informal leadership.

e Macroeconomic policy such as local, provincial and federal legislation, policy, taxes, regulatory agencies.

f Introduced in January 2005.

g Physical environments such as facilities, playgrounds, parks, trails, prevalence of convenience/fast foods versus more healthy options, safety factors, and geographical aspects such as climate.

 

Sustainability
While 64% of the representative organizations reported the availability of an infrastructure suitable for the development and maintenance of a surveillance system, interest in developing such a surveillance system was expressed by only 18% and seemed to possess the requisite vision and leadership to initiate and sustain it was reported by 43%.

Discussion

Childhood obesity is an important public health concern, yet there is little evidence of practical and sustainable surveillance strategies to inform research, policy and best practice. To address this gap, we sought to assess the feasibility of employing a multilevel childhood obesity–related surveillance system at a regional level.

Childhood obesity prevention initiatives are available at regional and provincial levels. For example, the Government of Alberta, Department of Education, has mandated daily physical activity guidelines and, more recently, province-wide nutrition guidelines.21b-23 Initiatives such as the promotion of healthy body weights at health centres where children are vaccinated, specialized pediatric centres dedicated to obesity management and the formation of various partnerships with local business exist at the regional level.24-25 Also, data from our study suggest that daycare operators are attempting to increase daily physical activity and provide healthier food options, and that Parks and Recreation departments are actively marketing outdoor activity opportunities (i.e. nature trails) as a part of building healthy communities. In one community, the city logo was recently changed to highlight the benefits of outdoor activity in creating a healthy community. Fast food and fitness organizations are offering additional menu choices and fitness programs appropriate to children and youth. Thus, there appears to be some initiative and capacity to address childhood obesity at different levels and settings.

Not surprisingly, our findings show that organizations and their representatives from the three communities are mindful of the epidemic nature of childhood obesity. However, despite cogent personal will to address childhood obesity, there are over-powering infrastructure barriers, such as data in different forms, legislative barriers and organizations with funded mandates for which they are accountable, leaving scant excess capacity to address this public health issue.

Based on the information collected, there is not yet sufficient and/or suitable data to populate an ecological model such as CHESS. Thus, there continues to be a need to collect data specific to childhood obesity, at all levels of the ecological framework.8f There exist, however, pockets of information that serve as a solid platform to create a useful surveillance system. Two key conclusions can be drawn from this feasibility assessment of CHESS within the context of childhood obesity:

1) Disparate data, in a variety of formats, present both technical and accessibility challenges to the application of an ecological model.

Essential to the feasible application and utilization of an ecological framework is the availability of relevant data in a format easy to capture and transfer. Our study suggests that cross-sectional data regarding the general health of children and youth are being collected by a variety of organizations, but not data that specifically relates to childhood obesity (for example, there are no data on physical activity and nutrition).

While some degree of information on physical activity and nutrition exists at the organizational, community and macroeconomic policy levels, data at social levels are either non-existent, cannot be shared due to differing data formats or are withheld due to confidentiality concerns. Moreover, longitudinal data at all levels are lacking. These data limitations make effective assessments of interventions and policy changes problematic.

In terms of physical activity indicators, municipalities (Parks, Recreation, Community Services and Planning Departments) have general information concerning parks and trail usage, program statistics, current resource distribution as well as the types of resources necessary to facilitate or foster physical activity in each community. Comparable nutrition specific information appears to be non-existent.

Based on the evidence collected in this feasibility study, most available data are stored in electronic mediums; however, these data may not be congruent in terms of measurement, collection and synthesis appropriate for populating the ecological model. Although information access was acknowledged as a technical challenge, participants generally agreed to share data with others.

2) Broad-based awareness and interest regarding child obesity by a wide range of groups and organizations could facilitate establishing an effective coalition to address the issue over the long term.

Even in the absence of an overarching, multilevel community-based policy targeting for child health and childhood obesity, there are a number of initiatives, programs and services operating in all three communities. A wide range of after-school and recreational sports and activity programs, and the intentional actions on the part of daycare centres and schools to provide healthy food choices, address general child health concerns.

This broad-based interest in child health establishes a viable context for collaborating on the issue of childhood obesity. Existing initiatives speak positively to the interest that has already spawned action in a number of the categories. Potential partners are equipped with a significant level of knowledge and data given their existing commitment and community connections. A number of participants, particularly private businesses, suggested that if they were to collaborate they would want to know the benefits for their organization. Broad-based awareness of childhood obesity by a wide range of organizations could assist in establishing an effective coalition to address this issue over the long term by supporting the establishment of a surveillance system. Public Health departments may be the cornerstone organization to lead such initiatives.

Limited vision, human resources and financial support at the local level were detected. Consequently, any action towards the development of a regional surveillance system for childhood obesity may require leadership from provincial and regional bodies that are already involved. It is also evident that limited human and financial resources in addition to other competing mandates are barriers to participation in the development of a large-scale, broad-based initiative on childhood obesity such as CHESS.

Insufficient leadership at the local level does not mean that there are limited opportunities to explore potential collaboration—technological, survey and system. Planning departments in all three communities provided a wealth of broad-based information, as did Parks and Recreation departments. The expansion of existing community service programs and services to incorporate childhood obesity initiatives is feasible according to the organizations who participated in this study. In addition, local organizations with a national network (e.g. Boys and Girls Clubs of Canada) have access to national data and programs in addition to their local information. This information may be useful in the development of a regiona system.

 

Conclusion

The feasibility of operating a surveillance system like CHESS in the three targeted communities may be complicated by a mandate for action rather than surveillance on the part of local organizations; limited applicability of tools that measure physical activity and nutrition within the ecological model; limited access to local resources (both human and financial); competing organizational mandates; and differing formats of electronic data and privacy legislation. In addition, the absence of developed strategic plans and a leadership framework significantly limits the sustainability of a childhood obesity agenda.

It is also important to acknowledge the limitations of this study, which include the minimal number of communities examined and the incongruence in the number of organization types surveyed within each of the 3 communities, thereby potentially limiting the generalizability of the study results. Future research may examine the generalizability of these findings by applying CHESS to other regional health jurisdictions and including a wider group of organizations.

Despite these limitations, our findings (including the process evaluation components) indicate that diverse initiatives exist and the information gathered is being applied in a variety of contexts at individual and multi-environmental levels. Although developing a large-scale system (populated with multilevel data) is still the ultimate recommended goal for local communities to tackle the child obesity epidemic, other interim staged strategies are required for the development and maintenance of an integrated framework such as CHESS. For example, an incremental process of data gathering capitalizing on easily accessible and affordable metrics may be more practical in the short term, and a more interactive, cohesive, yet flexible framework with a project-centered focus may need to be developed. At a minimum, it is recommended that local jurisdictions obtain the core individual-level measures (i.e. height, weight, physical activity behaviour, and nutrition behaviour) and, where possible, any of the environmental levels. As the capacity for generating quality data improves, local jurisdictions can continue to populate the multilevel database with appropriate metrics in a strategic and co-ordinated fashion. Further, it may be warranted for academic experts to work with organizations to identify data that would be useful for the organizations, identify the indicators organizations could use and provide support as needed.26 Comparable organizations could use the same indicators and the experts could compile and report back results specific to each organization (along with aggregated data, i.e. across all organizations) for particular indicators. Such information could assist organizations with their planning, programming and evaluation. Such approaches underscore the importance of partnerships between researchers, practitioners and policy-makers.

Acknowledgements

Financial Support for this study was provided by the Canadian Institutes for Health Research (CIHR). Professor Ronald C. Plotnikoff holds salary awards from CIHR (Applied Research Chair) and Alberta Heritage Foundation for Medical Research (Health Scholar).

Footnotes

* Individual (intrapersonal) levels include genetic, biomedical, behavioural cognitive and attitudinal behaviours; social (interpersonal) aspects such as family, peers, neighbours, other groups and larger social networks; organizational aspects such as norms, culture, structures, rules, regulations and incentives in schools and other institutions that relate to children; community aspects such as area economics, media, community services, neighbourhood organizations, folk practices, relationships among organizations in the community, municipal structures, formal and informal leadership; macroeconomic policy such as local, provincial and federal legislation, policy, taxes, regulatory agencies; and physical environments such as facilities, playgrounds, parks, trails, prevalence of convenience/fast foods versus more healthy options, safety factors, and geographical aspects such as climate.

Core metrics at the individual or intrapersonal ecological level consist of height, weight, physical activity (PA) and nutrition levels.

‡ Subsidiary metrics at the individual (intrapersonal) ecological level include energy expenditure, PA and nutrition patterns and practices, attitudes and body fat; at the social (interpersonal) ecological level, include parental attitudes and food choices; at the organizational level, include information regarding the nutritional value of school meals and access to healthy choices, access to dietician/nurse in schools and daily PA in school; at the community level, include local media campaigns and the number, accessibility and cost of community-based PA programs; at the macroeconomic policy level, include municipal, regional and/or provincial policies related to nutrition, statistical reports related to obesity, and regulations for food services and PA in schools and daycares; at the level of physical environments, include proximity to and number of fast food outlets, number of schools with vending machines selling junk foods, access to public transit (cost and location), available infrastructure (parks, cycling walking paths, secure bike racks, number of cross-walks), design of community buildings and space for PA.

§ http://www.albertafirst.com/ profiles/community/

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