Paul Z. Siegel

Training practitioners in evidence-based chronic disease prevention for global health.

Too often, public health decisions are based on short-term demands rather than long-term research and objectives. Policies and programmes are sometimes developed around anecdotal evidence. The Evidence-Based Public Health (EBPH) programme trains public health practitioners to use a comprehensive, scientific approach when developing and evaluating chronic disease programmes. Begun in 2002, the EBPH programme is an international collaboration. The course is organized in seven parts to teach skills in: 1) assessing a communitys needs; 2) quantifying the issue; 3) developing a concise statement of the issue; 4) determining what is known about the issue by reviewing the scientific literature; 5) developing and prioritizing programme and policy options; 6) developing an action plan and implementing interventions; and 7) evaluating the programme or policy. The course takes an applied approach and emphasizes information that is readily available to busy practitioners, relying on experiential learning and includes lectures, practice exercises, and case studies. It focuses n using evidence-based tools and encourages participants to add to the evidence base in areas where intervention knowledge is sparse. Through this training programme, we educated practitioners from 38 countries in 4 continents. This article describes the evolution of the parent course and describes experiences implementing the course in the Russian Federation, Lithuania, and Chile. Lessons learned from replication of the course include the need to build a “critical mass” of public health officials trained in EBPH within each country and the importance of international, collaborative networks. Scientific and technologic advances provide unprecedented opportunities for public health professionals to enhance the practice of EBPH. To take full advantage of new technology and tools and to combat new health challenges, public health practitioners must continually improve their skills.

Food Insecurity and Self-Reported Hypertension Among Hispanic, Black, and White Adults in 12 States, Behavioral Risk Factor Surveillance System, 2009

Food insecurity is positively linked to risk of hypertension; however, it is not known whether this relationship persists after adjustment for socioeconomic position (SEP). We examined the association between food insecurity and self-reported hypertension among adults aged 35 or older (N = 58,677) in 12 states that asked the food insecurity question in their 2009 Behavioral Risk Factor Surveillance System questionnaire. After adjusting for SEP, hypertension was more common among adults reporting food insecurity (adjusted prevalence ratio, 1.27; 95% confidence interval, 1.19–1.36). Our study found a positive relationship between food insecurity and hypertension after adjusting for SEP and other characteristics.

Self reported hypertension among unemployed people in the United States

Higher death rates from cardiovascular diseases have been reported among unemployed people in several countries after age, socioeconomic status, and marital status have been controlled for. Other studies have found that blood pressure and serum cholesterol concentration rise before and after loss of a job. Moreover, unemployed people consult doctors about cardiovascular conditions including hypertension, more often than do employed people.1 We used data from a cross sectional survey of American adults to estimate the risk of hypertension among unemployed people after controlling for other risk factors. In 1992, 48 states and the District of Columbia participated in the behavioural risk factor surveillance system, which entailed interviewing people by telephone who had been contacted by dialling random numbers. A total of 96 213 people were interviewed. The median percentage of complete interviews for all the …

Patterns of health risk behaviors for chronic disease: A comparison between adolescent and adult american indians living on or near reservations in Montana

PURPOSE To compare the chronic disease health risk behavior patterns of adolescents and adults among American Indians living on or near reservations in Montana. METHODS We analyzed data from the 1993 Youth Risk Behavior Survey of American Indians in Grades 9-12 living on or near Montana reservations. Risk factors included tobacco use, low physical activity, attempted weight loss, and low consumption of fruits, vegetables, and green salad. Similar data were analyzed from a 1994 Behavioral Risk Factor Survey of American Indian adults living on or near reservations in Montana. RESULTS The prevalence of most adolescent health risk behaviors was high, especially cigarette smoking (45% for males, 57% for females), smokeless tobacco use (44% for males, 30% for females), and infrequent consumption of salad or vegetables (59-76%). With the exception of daily cigarette smoking and inadequate fruit consumption among adolescents of both genders and physical inactivity among adolescent males, the prevalence of chronic disease health risk behaviors among adolescents was similar to or higher than the prevalence of the same risk behaviors among adults. CONCLUSIONS Many health risk behaviors for chronic diseases are common by the time this group of American Indians in Montana has reached adolescence. Possible reasons may include modeling of familial behaviors, peer pressure, advertising, or age cohort effects. If these risk behavior patterns continue into adulthood, morbidity and mortality from chronic diseases are likely to remain high. Substantial efforts are needed to prevent or reduce health risk behaviors among adolescents and adults in this population.

Mentorship and competencies for applied chronic disease epidemiology.

To understand the potential and establish a framework for mentoring as a method to develop professional competencies of state-level applied chronic disease epidemiologists, model mentorship programs were reviewed, specific competencies were identified, and competencies were then matched to essential public health services. Although few existing mentorship programs in public health were identified, common themes in other professional mentorship programs support the potential of mentoring as an effective means to develop capacity for applied chronic disease epidemiology. Proposed competencies for chronic disease epidemiologists in a mentorship program include planning, analysis, communication, basic public health, informatics and computer knowledge, and cultural diversity. Mentoring may constitute a viable strategy to build chronic disease epidemiology capacity, especially in public health agencies where resource and personnel system constraints limit opportunities to recruit and hire new staff.

The role of epidemiology in chronic disease prevention and health promotion programs.

Although the role for epidemiology is widely accepted in public health programs in general, its role in chronic disease programs is not as widely recognized. One possible barrier to improving epidemiologic capacity in chronic disease prevention and health promotion programs is that chronic disease program managers and public health decision makers may have a limited understanding of basic chronic disease epidemiology functions. We describe the assessment process of data collection, analysis, interpretation, and dissemination, and, using examples from two states, illustrate how this approach can be used to support program and policy development in three areas: by defining the problem, finding programs that work, and evaluating the effects of the program over time. Given the significant burden of chronic diseases in the United States, the scientific guidance provided by epidemiology is essential to help public health leaders identify priorities and intervene with evidence-based and effective prevention and control programs.

Models for count data with an application to Healthy Days measures: are you driving in screws with a hammer?

Introduction Count data are often collected in chronic disease research, and sometimes these data have a skewed distribution. The number of unhealthy days reported in the Behavioral Risk Factor Surveillance System (BRFSS) is an example of such data: most respondents report zero days. Studies have either categorized the Healthy Days measure or used linear regression models. We used alternative regression models for these count data and examined the effect on statistical inference. Methods Using responses from participants aged 35 years or older from 12 states that included a homeownership question in their 2009 BRFSS, we compared 5 multivariate regression models — logistic, linear, Poisson, negative binomial, and zero-inflated negative binomial — with respect to 1) how well the modeled data fit the observed data and 2) how model selections affect inferences. Results Most respondents (66.8%) reported zero mentally unhealthy days. The distribution was highly skewed (variance = 58.7, mean = 3.3 d). Zero-inflated negative binomial regression provided the best-fitting model, followed by negative binomial regression. A significant independent association between homeownership and number of mentally unhealthy days was not found in the logistic, linear, or Poisson regression model but was found in the negative binomial model. The zero-inflated negative binomial model showed that homeowners were 24% more likely than nonowners to have excess zero mentally unhealthy days (adjusted odds ratio, 1.24; 95% confidence interval, 1.08–1.43), but it did not show an association between homeownership and the number of unhealthy days. Conclusion Our comparison of regression models indicates the importance of examining data distribution and selecting models with appropriate assumptions. Otherwise, statistical inferences might be misleading.

Does Perceived Neighborhood Walkability and Safety Mediate the Association Between Education and Meeting Physical Activity Guidelines

The role of neighborhood walkability and safety in mediating the association between education and physical activity has not been quantified. We used data from the 2010 and 2012 Communities Putting Prevention to Work Behavioral Risk Factor Surveillance System and structural equation modeling to estimate how much of the effect of education level on physical activity was mediated by perceived neighborhood walkability and safety. Neighborhood walkability accounts for 11.3% and neighborhood safety accounts for 6.8% of the effect. A modest proportion of the important association between education and physical activity is mediated by perceived neighborhood walkability and safety, suggesting that interventions focused on enhancing walkability and safety could reduce the disparity in physical activity associated with education level.

Increasing chronic disease epidemiology capacity without increasing workforce: a success story in Ohio.

In many states the epidemiology capacity of specific chronic disease programs, for example, cardiovascular disease or diabetes, is limited by the skill set of a single epidemiologist who has been assigned to that program. To improve epidemiology support across categorical programs, the Division of Prevention at the Ohio Department of Health initiated a new policy early in 2003 whereby each program epidemiologist is responsible for learning to analyze data from at least two datasets as well as continuing to be the lead data person for his or her program. Now, for each critical dataset at least one epidemiologist is capable of conducting data analysis and providing support to other programs. Without the addition of new epidemiology staff, this policy has enabled the Ohio Department of Health to produce reports that better describe the burden of chronic diseases, make more informed decisions on what populations to target, and plan well-thought-out interventions.

Summarizing health-related quality of life (HRQOL): development and testing of a one-factor model

BackgroundHealth-related quality of life (HRQOL) is a multi-dimensional concept commonly used to examine the impact of health status on quality of life. HRQOL is often measured by four core questions that asked about general health status and number of unhealthy days in the Behavioral Risk Factor Surveillance System (BRFSS). Use of these measures individually, however, may not provide a cohesive picture of overall HRQOL. To address this concern, this study developed and tested a method for combining these four measures into a summary score.MethodsExploratory and confirmatory factor analyses were performed using BRFSS 2013 data to determine potential numerical relationships among the four HRQOL items. We also examined the stability of our proposed one-factor model over time by using BRFSS 2001–2010 and BRFSS 2011–2013 data sets.ResultsBoth exploratory factor analysis and goodness of fit tests supported the notion that one summary factor could capture overall HRQOL. Confirmatory factor analysis indicated acceptable goodness of fit of this model. The predicted factor score showed good validity with all of the four HRQOL items. In addition, use of the one-factor model showed stability, with no changes being detected from 2001 to 2013.ConclusionInstead of using four individual items to measure HRQOL, it is feasible to study overall HRQOL via factor analysis with one underlying construct. The resulting summary score of HRQOL may be used for health evaluation, subgroup comparison, trend monitoring, and risk factor identification.