At the heart of obesity prevalence and trends analyses are seemingly basic questions—How many people have obesity? Are any groups disproportionately affected? How has this changed over time? These questions, however, encompass tremendous methodological and interpretive complexity. Investigators have assessed obesity prevalence and trends from different perspectives, using a range of data sources and various analytic approaches. The inconsistencies across published reports have created barriers to interpreting and using such statistics. To understand how best to extract meaning from recent reports, to determine what data gaps need to be filled, and to consider how the future of data collection can be improved, a thorough evaluation of existing differences and why they exist is crucial. In providing such information, this report serves as an initial step toward obesity prevalence and trends estimates that are more transparent, aligned, and comprehensive.
To address its task (see Box 1-2), the committee assessed common data sources, extracted information from recent published reports, and reviewed associated protocols and data collection instruments. The committee considered other information sources, but primarily relied on the methodologic approaches to data collection and analysis presented in peer-reviewed published reports when formulating its conclusions and recommendations.
The interpretation of obesity prevalence and trends estimates is contingent on considerations specific to the assessment of obesity status, principles that are founded in epidemiology, and concepts that are fundamental to
statistics. This interplay of these elements, which span from general to specific, is reflected in the committee’s conclusions. Much of the available evidence indicates that at the core of several of the current limitations are seemingly basic challenges faced by any population-based prevalence or trends evaluation. The fact that these issues exist, however, underscores the challenges of finding viable solutions. The committee’s conclusions focus on key domains that cut across the broad literature base. These include current sources of data, data for specific population groups, measured versus reported data, estimates of changes and trends over time, and interpretations of estimates.
Current Sources of Data
A wide variety of data sources capture height and weight data. Population surveys serve as a primary source of nationally representative estimates, but often differ from each other in terms of overall design, sample size, target population(s), geographic representation (e.g., national, multiple states, and localities), and method for collecting height and weight data. Few data sources are designed to generate estimates of multiple states and those that do tend to describe select population groups (e.g., Youth Risk Behavior Surveillance System: high school students). School-based body mass index (BMI) assessments have emerged as a prominent source of data used to describe obesity prevalence and trends among school-aged children within states and smaller geographic areas (e.g., counties, school districts, individual schools). Such data, however, can be limited by issues related to data quality, data privacy, and sample representativeness and can be difficult to compare across states due to differing protocols. Clinical and public health administrative data also have been used as a source of data. Although such data sources often contain an enormous number of records with directly measured heights and weights, they can be limited for the purposes of obesity prevalence and trends estimation as they do not necessarily represent populations outside of those who use the services. Finally, cohort studies have been used in published reports to describe cross-sectional prevalence, longitudinal trends, and intrapersonal changes in obesity status. Cohort studies, however, are not as common in the obesity prevalence and trends literature as cross-sectional or repeated cross-sectional assessments, because they can be challenging and expensive to properly design and implement.
Conclusion 1: The committee concludes that existing data sources used to estimate prevalence and trends in obesity vary by factors, including study design, geographic representation, data collection methodologies, and overall intent. Each offers specific and distinct information about the state of obesity. The differences between data sources, however, can limit the comparability of reports.
Data for Specific Population Groups
Investigators divide analytic samples into subgroups to determine the extent to which obesity prevalence and trends vary within a broader population. Although participants are commonly grouped by geographic level (e.g., state, region, county) and demographic characteristics (e.g., age, race, ethnicity, socioeconomic status), the factors defining the groups (e.g., span of ages, race and ethnicity categories) can vary widely across reports, even those that analyze data from the same data source. Groupings do not always represent the level of detail captured during data collection, but rather often reflect decisions investigators make to best answer specific research question(s) given limitations of the data. Published reports often cite inadequate sample size as the reason for omitting one or multiples subgroups from the analyses or for combining heterogeneous groups into a single category. Advanced statistical techniques, such as small area estimation, are one means to generate model-based estimates for smaller geographic areas and population groups for which reliable direct survey estimates cannot be generated. These techniques are contingent on the quality and quantity of data used to develop such models and require a fair degree of statistical sophistication in order to provide meaningful results.
Conclusion 2: The committee concludes that inclusion of subgroups in data sources provides essential insight into how obesity prevalence and trends estimates vary within and between population groups. However, insufficient sample size is a primary limitation to generating reliable estimates.
Measured Versus Reported Data
Comparing BMI to a population reference, typically the 2000 Centers for Disease Control and Prevention (CDC) sex-specific BMI-for-age growth charts and associated cut point, is the prevailing approach for classifying obesity status among children, adolescents, and young adults. Height and weight data used to calculate BMI are collected through direct measurement, proxy-report, and self-report. Within each collection approach, variability exists in the specific data collection protocol. Proxy- and self-reported height and weight questions have been incorporated into various population surveys in which factors such as the overall design and mode of delivery (e.g., phone interview) do not allow for direct measurement. These surveys often have large sample sizes and some have been used to generate estimates that are compared across states and select localities. Factors such as sex, age, and weight status can affect the degree to which reported height and weight values differ from directly measured values. Evidence indicates
that use of proxy-reported data for young and school-aged children generally does not lead to accurate estimates of prevalence. As such, some population surveys (i.e., National Health Interview Survey, previous cycles of the National Survey of Children’s Health) have discontinued collecting proxy-reported height and weight data and/or generating obesity prevalence estimates from such data for these age groups (children younger than ages 10 to 12 years). Limited evidence, based on different nationally representative surveys, suggests that trends in obesity estimated from self-reported and directly measured heights and weights among high school-aged individuals exhibit similar patterns, albeit at different values.
Conclusion 3: The committee concludes that although all measures have limitations, directly measured height and weight data collected using a standardized protocol provide the best estimates of obesity prevalence. Self- and proxy-reported height and weight data can be used to fill data gaps and provide insight into overall obesity trends, although these data collection methods do not produce prevalence estimates comparable to those based on direct measure.
Estimates of Changes and Trends Over Time
Published reports assessing obesity prevalence over time have presented findings as change (the difference between two time points) or trends (the difference over three or more time points). Such estimates pertain only to the specific time points included in the analyses. Trend estimates typically become more precise and nuanced as the number of time points increases. However, the number of time points is dependent, in part, on the reliability of the prevalence estimates. Investigators often combine multiple years or cycles of data to increase the reliability of the estimates used to determine the trend, thereby reducing the number of data points. Changes to the time interval included in the trend analyses directly affect the estimate and its meaning.
Conclusion 4: The committee concludes that comparability of trend reports is enhanced when analyses use similar start and end dates and time intervals to define the trend.
Interpretation of Estimates
Factors that affect the interpretation of obesity prevalence and trends estimates not only include characteristics of a data source, but also encompass decisions made during analysis. Data sources differ with respect to who the sample is designed to represent and who contributes data. Changes to the sampling or data collection procedures over time affect what data
are available for trend analyses. The portion of the overall sample that is used for analysis varies across published reports for a number of reasons, including: what question(s) is being asked of the data, how the data were prepared for analysis, and whether the samples size led to reliable estimates of prevalence. Differences exist in data collection methodologies, with the options height and weight data collection leading to estimates that are generally not equivalent. The statistical analyses are varied and are guided by the intent of the specific report, the quality control measures taken during data collection, the study design from which the data were derived, and the amount of data available.
Conclusion 5: The committee concludes that appropriate interpretation of estimates of obesity prevalence and trends requires consideration of the population in the sample, the data collection methodologies, and the analytic procedures together in a guided way.
Data sources that capture height and weight largely operate in isolation or within a single surveillance system, resulting in designs and protocols that differ from each other. Although these differences often limit comparability of prevalence and trends estimates, their existence underscores the diverse context in which decisions and compromises have to be made in the design, collection, and analysis of the data. Given this landscape, the committee offers recommendations in three areas: assessing published reports on obesity prevalence and trends; improving future data collection efforts; and conducting research to address data gaps.
Assessing Obesity Prevalence and Trends Reports
Because understanding and appropriately applying estimates of obesity prevalence and trends is a complex process, the committee provides the Assessing Prevalence and Trends (APT) Framework as a conceptual guide for stakeholders who seek to better understand and use reports. The framework draws on the committee’s synthesis of key considerations related to inconsistencies that exist in the literature while simultaneously drawing on fundamental principles of epidemiology and statistics. The framework emphasizes that the population assessed, methods used, and analyses performed are not simply discrete characteristics of a published report, but interconnected elements that inform each other and the interpretation of obesity prevalence and trends estimates. The committee considers determining the utility of estimates presented in published reports a highly individualized process, determined by the end user’s overall goal and specific data needs.
Recommendation 1: The committee recommends that stakeholders who use or seek to use estimates of obesity prevalence and trends to inform policy making, program planning, and decision making follow the Assessing Prevalence and Trends (APT) Framework to guide their interpretation of published reports.
The committee recognizes that end users who operate at the national, state, and local levels often have different information needs. The extent to which available analyses meet those needs varies considerably. Individual end users are therefore likely to have different priorities when it comes to the strengths and weaknesses of published reports. In order to be adaptable to a range of possible applications, the APT Framework integrates consideration of the end user’s context to guide the assessment.
The relevance or importance of the framework elements and guiding questions will vary by end users. As the framework is disseminated, used, and evaluated, opportunities to refine and adapt its various components will emerge. The committee foresees application of the framework beyond evaluating existing published reports. The concepts presented in the framework have the potential to guide the design of new prevalence and trends studies and to better align reporting practices of investigators publishing their research.
Future Data Collection
By evaluating the methodological approaches presented in published literature on obesity prevalence and trends, this report serves as an important starting point for moving toward comparable, more unified data collection, analysis, and reporting practices. Current practices, however, are determined by more than just the analytic and scientific rationale presented in a published report. Factors such as cost, existing infrastructure, and available resources play a role in the selection of a study design and the success of its implementation. As such, the committee recognizes that it would be premature to offer explicit, prescriptive guidance on specific methodologies to be used by the research and public health surveillance communities. Such a determination requires consideration of the experiential knowledge of those who fund, develop, and carry out such activities.
Recommendation 2: The committee recommends that an organization with a track record of cross-sector leadership in the field of obesity, such as the National Collaborative on Childhood Obesity Research or the Robert Wood Johnson Foundation, convene relevant stakeholders to examine and identify feasible and practical approaches to stan
dardizing methodologies for data collection and reporting, appropriate for application at the national, state, and local levels to enhance comparability of obesity prevalence and trend analyses.
The committee envisions the proposed convening of stakeholders as a vital next step needed to inform the decision of which methodologies should be used to generate comparable estimates of obesity prevalence and trends nationally. Guided by the APT Framework and methodologic considerations presented throughout this report, the proposed convening would serve as an opportunity to discuss challenges to implementation that exist and consider opportunities for innovation. The committee recommends a range of relevant topics be considered, including
- Determining ways to leverage existing infrastructure and surveillance systems, and improve and sustain capacity.
- Harmonizing time periods used to determine trends.
- Defining the level of detail of information that should be presented in published reports and ways in which it should be presented (e.g., relative versus absolute change).
- Considering opportunities to overcome sample size limitations so that reliable estimates can be determined and trends can be assessed for a broad range of population subgroups.
To include a range of participants, the committee recommends that the organization(s) sponsoring the proposed activity not only have a national prominence, but also strong ties to stakeholders who operate at the state and local levels. The organizations included in the recommendation—the National Collaborative on Childhood Obesity Research (NCCOR) and the Robert Wood Johnson Foundation (RWJF)—have missions and experience that are well aligned with the recommendation goals. With a goal of improving childhood obesity surveillance at the national, state, and local levels, NCCOR represents one potential sponsor. The funding partners of NCCOR are the CDC, the National Institutes of Health, RWJF, and the U.S. Department of Agriculture (USDA). Similarly, RWJF has a documented history of cross-sector collaboration and, as the sponsor of this study, may seek to continue building on the work of this committee. These are two examples of potential conveners. However, the committee notes that other conveners or collaborators may enrich the proposed activity as well.
The committee further recommends that a broad range of stakeholders who operate at the national, state, and local levels be involved in this activity, including, but not limited to
- Local and state public health agencies;
- Federal governmental agencies (e.g., CDC, USDA, Agency for Healthcare Research and Quality);
- Community-based organizations;
- School officials (e.g., state Departments of Education, superintendents, school nurses, and physical education teachers);
- Academic researchers;
- Research organizations;
- Research funders;
- Obesity oriented and public health professional organizations; and
- Other decision makers at who operate at the national, state, and local levels.
Research to Address Gaps
The assessment of obesity prevalence and trends estimates continues to change with technological, methodological, and statistical advancements. Some of the inconsistencies and limitations that currently exist in the literature represent prime opportunities for improvement and progress.
Recommendation 3: The committee recommends that the research community design and conduct studies to strengthen the evidence base and improve methodological approaches to assessing obesity.
Opportunities for improvement encompass a wide range disciplines. The research community described in the recommendation includes, but is not limited to, federally funded researchers, clinical researchers, social scientists, and engineers.
Specific research initiatives could include
- Evaluating how the 2000 CDC BMI-for-age growth charts can better provide continuity to obesity classification across the life course. The committee acknowledges that the 2000 CDC BMI-forage growth charts are the predominant reference currently in use in the United States for children ages 2 years and older and supports its continued use as a platform for comparability of estimates of obesity among children and adolescents. The committee anticipates findings from current and future initiatives (e.g., the Dietary Guidance Development Project for Birth to 24 Months and Pregnancy [B-24/P], the INTERGROWTH-21st Fetal and Newborn Growth Consortium, and the Environmental Influences on Child Health Outcomes [ECHO] Program) will inform an evidence-based consensus on how weight status should be classified for children
younger than age 2 years. Additionally, opportunities exist to clarify when and how best to transition young adults to the adult criterion for obesity classification.
- Identifying appropriate measures of core demographic variables—including but not limited to race and ethnicity, socioeconomic status, and rurality—that can be captured in a consistent manner across various data collection efforts at the national, state, and local levels. As the demographic landscape of the country continues to change, it will become increasingly vital to characterize populations in ways that capture the diversity that exists.
- Developing innovative, practical, and accurate tools for assessing adiposity. Although BMI is the predominant measure of relative weight used to classify obesity status, it is not without limitations. For the purposes of population-based assessments, a new measure of obesity will need to be a simple alternative that provides comparable or improved predictive ability, that can be measured in a variety of settings, and that is relevant to diverse population groups across the life course.
- Preventing the misclassification of data from individuals with severe obesity as biologically implausible values. Technology-based systems that are used for direct data entry often have features that automatically detect extreme values in height and weight. Identification at the time of measurements allows for the values to be corrected or properly documented. Data collection procedures that first record measurements on paper or in systems without automatic detection of extreme values often have limited ability to check the quality of data until entry into a database or analysis. Opportunities exist to expand the use of technology in data collection to enhance the accuracy of recorded measurements.
- Identifying innovative opportunities to capture longitudinal data throughout childhood. A variety of data sources—including electronic health records and school-based BMI assessments—are primed to be used in novel ways to serve as the basis for or supplement longitudinal evaluations.
This page intentionally left blank.