Gathering and Using Data
Where will I find the Toolkit section?
Gathering and Using Data to Identify and Monitor Obesity Disparities through a Health Equity Lens begins on p.25 of the Toolkit!
What will I find in the Toolkit section?
- Descriptions of different types of quantitative and qualitative data on obesity disparities and social and environmental factors.
- Recommended sources for secondary, state-level quantitative and qualitative data.
Why collect data?
Data collection is an important step for addressing obesity disparities throughout multiple stages of program development and implementation. Quantitative data define in which populations obesity disparities exist, how large the discrepancies are, and what factors relate to their development. Qualitative data are often used to add depth to research findings, expounding upon quantitative data for a richer understanding of health issues. Data collected from either secondary or primary sources will serve as the foundation for the development of your program, as well as program refinement.
When to collect data?
Collecting and using data is useful at several points throughout the overall planning process, and may be conducted:
- As an initial step in the planning process (prior to program development
- At this point, data may identify obesity disparities and provide the baseline for implementing your program. From this baseline, benchmarks or desired outcomes are set.
- Simultaneously with ongoing partnership development activities.
- Data should be reviewed by your assigned working group or members of your coalition together. Having representatives from a variety of partnerships review and understand baseline data will increase the likelihood of stakeholder buy-in. This comprehensive review will also ensure that the “voice” of multiple sectors is heard in the translation of data to programs and policies.
- As a task of ongoing monitoring and evaluation activities.
- Quantitative data collected for this purpose will inform practitioners if a program is or has been effective at reaching benchmarks for change. Qualitative data may be used in an outcome or impact evaluation to help describe “why” or “why not” a program is found to be effective.
How to collect data?
Both quantitative and qualitative data may be collected through a variety of methodologies and sources. You may choose to conduct primary data collection, or access secondary data sources such as those referenced in the Toolkit. Data may be collected and shared between engaged partners. Having collected all of your data, it is time to address how you will use it to direct the subsequent steps in your program development process.
How to communicate data?
As recommended in the Toolkit, your data should be reviewed by a team of representatives across your program’s working group partners. The objective of this review is to identify and prioritize target populations. Tools for organizing your team are recommended on pp. 32-37 of the Toolkit. Remember when discussing data as a group to take into account cultural considerations of the target populations.
For specific guidance on how to share research findings and data within your working group, or how to communicate findings to a broader group of stakeholders, review these resources:
- Making Data Talk: Communicating Public Health Data to the Public, Policy Makers and the Press (Oxford University Press, 2009)
- In their book, Drs. David Nelson, Brad Hesse, and Bob Croyle provide evidence-based suggestions to guide practitioners in the communication of data to stakeholders.
- Making Data Talk: A Workbook [PDF–2.03Mb]
- This complementary publication by the National Cancer Institute (NCI) at the National Institutes of Health (NIH) is intended to highlight the main lessons within the book Making Data Talk: Communicating Public Health Data to the Public, Policy Makers and the Press.
- Practical exercises for applying the lessons learned within the book are also included and may be applied to a variety of health-related topics and disciplines.
What to do with my data?
The analysis and presentation of your data will depend on factors such as the source of data (i.e., is this primary research or secondary data?), the type of data (i.e., qualitative, quantitative, or mixed methods), and intended audience.
In addition to the resources on pp. 26-28 of the Toolkit, here are some additional tools for utilizing data effectively:
- Health Disparities Calculator
- The Health Disparities Calculator (HD*Calc) was released by the Surveillance, Epidemiology and End Results (SEER) Program of the NCI.
- Data sets are imported into this statistical software to generate a variety of summary measures for evaluating health disparities.
- Although originally designed for evaluating health disparities as they relate to cancer, the HD*Calc program may be applied to any population-based data set.
- Geographic Information System (GIS)
- GIS integrates computer software and hardware with data to produce geographical representations of your findings. These might take the form of cluster maps, globes, charts, or tables. Obesity health disparities may be represented geographically, by density, or by patterns over time. These systems are an exceptional tool for visualizing, communicating, and interpreting data.
- Although GIS systems have traditionally integrated quantitative data, it is possible to incorporate qualitative data as well. In doing so, the user is able to create an even more dynamic model to interpret not only the “who”, “what”, “where” and “when”, but the “why” and “how” of an issue as well.
- Additional Resources:
- Overview to GIS provided by the Environmental Systems Research Institute (ESRI) discusses the GIS approach to data analysis, and provides tools and trainings.
- The CDC overview of GIS site describes GIS and provides opportunities for training.
- The Division for Heart Disease and Stroke Prevention (DHDSP) at CDC provides a forum for discussions, publications and training tools relating to the application of GIS to chronic disease.
- Qualitative GIS: A Mixed Methods Approach (Sage Publications, 2009) is a book by Meghan Cope and Sarah Elwood which describes the recent integration of qualitative data into GIS software.