Health Forecasting at UCLA

September 2011

In This Edition:


Twitter Update


Acculturation, Changing Health Behaviors and the Long-Term Consequences for Health of Latinos in California

California's Obesity Prevalence Still on the Rise, but Not as Fast as Previously Forecast

New Health Forecasting Tool Feature: Basic Reporting

About Us

Our Projects



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Health Forecasting Quarterly Newsletter •  September 2011

Health Forecasting was established at the UCLA School of Public Health nearly ten years ago. We use the best available data and analysis to produce empirically sound and credible forecasts of health trends to support health advocates, researchers, elected and government officials in their efforts to anticipate, prepare, and plan for healthier communities.

We invite you to learn more about UCLA Health Forecasting:


Twitter Update

In the June edition of the Health Forecasting Newsletter, we announced the induction of our online presence via Twitter. Since then, our online presence has grown immensely. We have established a network of research institutions, public health departments, government agencies and officials as well as non-profit organizations from across the country. We all share the common goal of improving public health for Americans.


Our Twitter account, HealthForecast, serves as a platform to disseminate our team’s work and the work of other’s, relaying health-related statistics and information to bring awareness to some of today’s most pressing public health issues.


Follow us on Twitter and join the conversation to help build healthier communities:

Twitter Profile Name: HealthForecast


Acculturation, Changing Health Behaviors, and the Long-Term Consequences for Health of Latinos in California

Across the board, Latinos in California tend to have better health outcomes and exhibit lower mortality rates than non-Latinos. Despite having better overall health outcomes, Latinos who have spent more time in the U.S. are more likely to be obese and have diabetes and/or cardiovascular disease relative to recent immigrants. The rapid increase in the Latino population, expected to become the largest ethnic group in California by 2020, along with a health profile that deteriorates with time spent in the U.S., adds urgency to better understand how health outcomes may evolve and how programs and policies may be designed to effectively improve future health outcomes.



Our two-year National Institutes of Health sponsored project focuses on expanding the Health Forecasting Tool to help anticipate the impact of acculturation, as measured in years lived in the United States and English proficiency, in addition to changing health behaviors on Latino health.


To build the foundation for this work, we use the California Health Interview Survey to quantify the impact of the retail food environment, parks, public and private recreational facilities, on weight gain among Latinos, stratified by the amount of time lived in the United States. We are finding that in addition to physical characteristics of neighborhoods, social and demographic characteristics, such as ethnic composition of a neighborhood, play a role in shaping health behaviors of new arrivals.


The pattern of growth in the Latino population in Los Angeles County and California is expected to continue in a similar manner across the United States. Understanding the variation in health outcomes among Latinos based on the level of acculturation within the Latino community is an important public health issue, given the growing and ever changing population.


California's Obesity Prevalence Still on the Rise, But Not as Fast as Previously Forecast

The number of obese Americans has grown exponentially in the past few decades. In 2007, Health Forecasting released obesity projections and the associated anticipated medical expenditures in an issue brief. These were also made available online through the Health Forecasting Tool. The issue brief quantified the current and future impact of overweight and obesity trends as well as their effect on mortality and medical expenditures in California.     


Health Forecasting utilized the dataset from the Survey Research Group's California Behavioral Risk Factor Surveillance System  (BRFSS) to forecast overweight and obesity. Obesity prevalence was estimated by extrapolating trends in body mass index (BMI) by gender, race/ethnicity, and age, and then overlaying demographic trends in California. Using this approach we forecast an increase in obesity prevalence of 4 percentage points from 2005 to 2010 (from 20% to 24%), with obesity prevalence expected to increase another 11 percentage points by 2020.


Two of the largest health behavior survey datasets, the Center for Disease Control and Prevention (CDC) Behavioral Risk Factor Surveillance System and the California Health Interview Survey (CHIS), have released obesity data which confirm Health Forecasting's projection of an upward trend, however the magnitude of the increase is only about ½ of that forecast in 2007 (CDC: 2 percentage point increase; CHIS: 1½ percentage point increase from 2005 to 2009). The direct benefit of a slower increase in obesity prevalence is a slower increase in direct personal medical expenditures, and excess mortality attributed to overweight and obesity. Still, even if obesity prevalence stays at current levels, we estimate that by 2025 overweight and obesity will contribute $18 billion in direct personal medical expenditures each year and cause an additional 5,000 deaths each year.  


The issue brief for this article is available on our website:

Trends and Forecast of Health and Economic Costs of Overweight and Obesity in California (July 2007)


Data and graphs for this issue brief are available online:California Obesity (2007)


New Health Forecasting Tool Feature: Basic Reporting

The Health Forecasting Tool now includes a new way to view data in a simple, easy-to-use format.  The charts and data generated by the tool can be used to assess future trends in health outcomes, such as mortality, disease incidence, and morbidity and how these outcomes will vary across population subgroups. It is a useful analytic tool that allows decision-makers to anticipate the future public health effects of current decisions and actions to design policy effectively.  

What is the Health Forecasting Tool?

It is an innovative, interactive tool available online where individuals can access population-level health characteristics and outcomes of current and future populations and subgroups by race, ethnicity, age, gender, and geography. It also allows users to project health impacts of potential changes in programs and policies taking into account socio-economic and behavioral characteristics as well as changes in demographics.

How it works?

The tool operates via a microsimulation model. It is based on known historical data derived from various resources, such as the Census, Center for Disease Control and Prevention, California Department of Education and Demographic Research Unit of the California Department of Finance among other definitive sources. These figures are then integrated with evidence-based population health trends and expected future population shifts to project health outcomes at the population-level. There are three types of reports available according to the degree of specificity.


Types of Reports generated by the Health Forecasting Tool:


Quick Reports

Pre-made graphs and analysis on select topics primarily drawn from Health Forecasting issue briefs


Basic Reports (New Feature)

Quick, click-and-point custom charts for a given population for all Health Forecasting studies. Graphs drawn from each study focus on one topic, such as total medical expenditures, and one category, which include census year, demographic and health characteristics.


Advanced Reports

Users can create custom, multilayer graphs and compare charts across one category. It provides detail specific data for each study. For example, the California Obesity study graph can be created by topic, such as an examination of mortality, then by a particular ethnic group (Latinos), and by body mass index (BMI) filtered to include only obese Latinos.

Other Special Features

It is also possible to create a subset of the study population based on your own community or constituency if you have population figures. Population characteristic, such as age, ethnicity, and/or gender can be included in the Define a Population function. Once the newly created population is saved, graphs and data can be generated for that population in any Health Forecasting study. Reports can be saved as a PDF or in JPG format.


If you have any questions regarding the new feature, or the Health Forecasting Tool in general, please contact us: Peggy J. Vadillo or call us at (310) 206-7820.


About Us

Health Forecasting is based at the UCLA Fielding School of Public Health, and is a collaborative effort with the California Department of Public Health and the Los Angeles County Department of Public Health.


Our Projects


The California Endowment

Expanding the capabilities of the UCLA Health Forecasting Tool by incorporating education and income, two critical social determinants of health, and focusing on interventions relevant to underserved individuals and communities in California.




National Institute of Environmental Health Sciences

Examining drivers of health and longevity among Latinos in California and understanding the effects of interventions focusing on diabetes and cardiovascular disease for this population. 






National Institutes of Health

Forecasting and improving Latino health by examining the role of acculturation and physical activity to account for health disparities among the Latino population.  






Robert Wood Johnson Foundation

Incorporating additional risk factors (i.e. smoking) and disease outcomes (i.e. lung cancer) into the forecasting model and applying the model to other states, beginning with Arkansas and Wisconsin.




UniHealth Foundation

Supporting local not-for-profit hospitals in assessing current and future characteristics of the populations they serve and identifying long-term planning needs of local communities.  Providing information on future health and health disparities among subpopulations in the absence of additional effective health promotion and disease prevention efforts.

  Evidence-based model to support advocacy of public health, research, and programs