Nathan Yau at Flowing Data has an interactive graphic showing the growth of obesity rates by state, year (since 1985) and gender.
Archive for the 'Population Health & Health Disparities' Category
A post by Sunmoo Yoon in the NIH OBSSR blog looks at the potential of data mining to offer insights into predictors of physical activity in older urban adults:
Only two out of ten older adults meet the national guidelines for physical activity in the United States. Little is known about interrelationships of many socio-ecological factors to improve physical activity behavior among Hispanic older adults. As we move towards a precision medicine approach, we need innovative strategies to discover precisely tailored targets and accurate interventions. Data mining has the potential to offer such insights.
The U.S. Census Bureau released two new reports: Income and Poverty in the United States: 2014 and Health Insurance Coverage in the United States: 2014. The reports find no real change in either income or poverty level, but the percentage of people without health insurance has declined.
From the press release:
The nation’s official poverty rate in 2014 was 14.8 percent, which means there were 46.7 million people in poverty. Neither the poverty rate nor the number of people in poverty were statistically different from 2013 estimates. This marks the fourth consecutive year in which the number of people in poverty was not statistically different from the previous year’s estimate.
Median household income in the United States in 2014 was $53,657, not statistically different in real terms from the 2013 median income. This is the third consecutive year that the annual change was not statistically significant, following two consecutive annual declines.
The percentage of people without health insurance coverage for the entire 2014 calendar year was 10.4 percent, down from 13.3 percent in 2013. The number of people without health insurance declined to 33.0 million from 41.8 million over the period.
This is a report on the NCI/SEERS web portal on a way to create residential histories of respondents/decadents for epidemiological research. The report (below) details how three commercial vendors were able to match the residential history of a small sample of federal government employees. Also available are the algorithms and software to reconcile conflicting addresses. Interested folks might want to browse other tools/papers in the NCI Geographical Information Systems and Science for Cancer Control webiste. https://gis.cancer.gov/index.html
Flowing Data has a new data visualization of smokers in 1994 and 2014 by gender, education, income, and race & origin.
Two decades out from the 1995 law in California, along with the known impact of smoking on one’s health, you’d think smoking rates would be way down. And you’d be right for many demographic groups, but for some, smoking is still the same as it ever was.
[The charts] show estimated percentage of adult smokers among different groups, for 1994 and 2014. Estimates are based on survey data from the Behavioral Risk Factor Surveillance System.
The most recent post in Inside NIA underscores several ways they are working to enhance research in aging and health disparities. These include funding opportunities — Health Disparities and Alzheimer’s Disease (R01), Emerging Directions for Addressing Health Disparities in Alzheimer’s Disease (R03), and the administrative supplement program, “Aging Research to Address Health Disparities” — and a framework for future research.
Since 2014, The ACA Implementation Network (of the Rockefeller Institute of SUNY, the Brookings Institution and the Fels Institute of Government of the University of Pennsylvania) has been producing state-wide reports to try to answer the following questions:
- Who governs state health reform initiatives and activities?
- What new federal-state and inter-agency relationships have developed under the ACA?
- And how have states put the principal coverage-related policies into operation, and with what effects?
H/T Data Detectives
The NIH Office of Behavioral and Social Sciences blog highlighted research by Ann Marie White and Melanie Funchess on the use of “Twitter data to prevent violence and suicide through community-based helping networks.”
Their recent BSSR talk, “To tweet or not to tweet: Community-based participatory research approaches to advance wellness and violence prevention via social media,” highlighted their progress in developing community-based helping networks that take advantage of social media tools to improve public health in their neighborhoods.
The World Bank has a new interactive chart showing how the leading causes of death are changing worldwide:
From The DataBlog:
Worldwide, the leading causes of death are changing, and they vary between rich and poor countries. In low-income countries, deaths from communicable diseases such as malaria and HIV/AIDS have fallen, while deaths from non-communicable diseases such as stroke and diabetes are on the rise.
Julie Mack of MLive.com put together mortality statistics from the Michigan Department of Health and Human Services and found some interesting trends.
A century ago, in 1914, 13 percent of people died from heart disease and 6 percent from cancer. That’s an era when contagious disease and infection killed many people at a much younger age.
In 1964, a half-century ago, after the introduction of antibiotics, heart disease and cancer together accounted for 55 percent of Michigan deaths.
In recent years, heart disease has been declining as a cause of death, while cancer has been on the increase.
Remember: Causes of death are a zero-sum situation. Since everybody dies, if one cause goes down, another must increase.
See also: Michigan’s top 10 causes of death.