NEWS ALERT: HHS Prevention and Wellness Initiative. September 18, 2009
Posted by Michelle Lugalia in Policymaking, Politics, Research.add a comment
Big news from Sebelius! Great steps forward for public health. I look forward to seeing what community initiatives will burgeon from this…
Check it out below and in full length at the website.
The Department of Health and Human Services (HHS) has created a comprehensive initiative for the $650 million allotted for chronic disease prevention efforts in the American Recovery and Reinvestment Act of 2009. The goal of this initiative – Communities Putting Prevention to Work – is to reduce risk factors, prevent/delay chronic disease, promote wellness in children and adults, and provide positive, sustainable health change in communities.
Communities Putting Prevention to Work will address the leading preventable causes of death and disability, namely obesity and tobacco use, by expanding the use of evidence-based strategies and programs, mobilizing local resources at the community-level, and strengthening the capacity of states. As a result of these efforts, powerful models of success are expected to emerge that can be replicated in other states and communities.
The cornerstone of the initiative is the Community Program ($373 million), with cooperative agreements to be awarded to communities through a competitive selection process.
- The Centers for Disease Control and Prevention will support evidence-based community approaches to chronic disease prevention and control in selected communities (urban and rural) to achieve the following prevention outcomes:
- Increased levels of physical activity;
- Improved nutrition;
- Decreased overweight/obesity prevalence;
- Decreased tobacco use; and
- Decreased exposure to secondhand smoke.
- Communities will implement a set of evidence-based interventions related to the behaviors listed above which aim to achieve broad reach, high impact, and sustainable change. The specific amount of funding per community will be determined by a mix of interventions, population size, ability to reduce health disparities, and likelihood of success.
- Communities will assemble an effective communitywide consortium with a history of working with partners such as local and state health departments and other governmental agencies, health centers, schools, businesses, community and faith-based organizations, academic institutions, health care, mental health/substance abuse organizations, health plans, and other community partners to promote health and prevent chronic diseases.
- This component also includes a robust support plan to ensure funded communities are successful and that the communities are able to evaluate the impact of their efforts. The plan consists of a three-pronged approach: program support, community mentoring, and evaluation.
KISS for Self-Rated Health? July 26, 2009
Posted by Katelyn Mack in Research.Tags: health, public health, surveys
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KISS — the acronym widely recognized for the philosophy ‘Keep It Simple Stupid’ — has characterized the measurement of overall population health in many epidemiogical surveys, including some of the largest in the US. This measure: self-rated health.
The question: ”Would you say your health in general is excellent, very good, good, fair or poor?” Is asked in major nationally representative surveys such as the National Health Interview Survey (NHIS), the Behavioral Risk Factor Surveillance Survey (BRFSS), the National Health and Nutrition Examination Survey (NHANES), and the Current Population Survey (CPS). Many public health professionals and epidemiologists have relied on responses to this question to measure a groups’ overall health and wellbeing. It is clearly easier to ask someone to rate their own overall health than to take blood pressure, pulse, weight, height, and ask a slew of disease-specific questions.
The downfall to this type of measurement of health is obvious: it is impossible to know why someone rates their health as excellent vs. fair. Nonetheless, researchers have used this measure to track trends in health over time and as a stand-in when other more invasive health measures are not available. Often, those who respond to this questions are categorized as in either “excellent, very good, or good” health or “fair or poor” health.
The use of this binary categorization may be flawed according to a recent article in the American Journal of Epidemiology by J. Salomon and colleagues, which challenges the reliability and consistency of this question to measure trends in population health over time.
Salomon et al. present data from the 4 health surveys mentioned above with data from 1998 to 2007 and compares trends in self-rated health, breaking it down by gender, age, race/ethnicity, and education. They report conflicting trends across the surveys (e.g. NHIS shows an increase in fair/poor health over time, while CPS shows a decrease in fair/poor health). They also find that certain subgroups have a higher likelihood of having inconsistent reports across surveys: young people (20-49 years), Hispanics, and those who lack a high school education. Because fair/poor responses are mostly inconsistent across surveys when looking over time, the authors suggest using an “excellent” or “excellent/very good” if analyzing data using this measure.
With reliable, accurate information being at the heart of any social epidemiological study it is imperative that these inconsistencies be reviewed and improved upon. How might this impact social and behavioral research? We have used and relied upon this measure of ‘health’ for a long time and applaud the fact that it is ‘reliable’ and easy to administer (i.e. cheap). The authors highlight the implications that these inconsistencies might have on disparities research and studies on socioeconomic status — since those with the lowest education, and racial/ethnic minorities are less likely to have consistent trends across surveys.
A thought: Even though the authors break this data up by subgroups (gender, age, race, education) — might the differences in sampling methodology and design (even the timing, placement, and order of the question within the survey!) have the consequence of creating the inconsistencies that we see?
We need to keep it simple – for time and money’s sake. But let’s make sure we avoid acting stupid. What could be a better way to quickly and easily capture peoples’ overall health status? Do you have a different ‘favorite’ measure?
Get your data on! June 13, 2009
Posted by Michelle Lugalia in Research.add a comment
Ever needed the right piece of data to make your argument or paper more convincing?
Ever needed those elusive census numbers that often take forever to find?
Ever just needed to look up some random fact on trends from some random U.S. Agency?
Have no fear! Search no more! DATA.gov is here!!!
Search your heart out! I am so loving our administration right now.
Also!
check out Wolfram Alpha….they are revolutionizing the internet and possibly your future biostats problem sets. These folks’ goal is to: “make all systematic knowledge immediately computable and accessible to everyone. We aim to collect and curate all objective data; implement every known model, method, and algorithm; and make it possible to compute whatever can be computed about anything”.
thank you Wolfram Alpha…
