Roadmap for implementing the Chronic Care Model for weight management: Healthcare Institution's Response to Obesity (HIRO)

Background. Excess weight and obesity are at epidemic proportions in the United States and place individuals at increased risk for a variety of chronic conditions. Rates of diabetes, high blood pressure, coronary artery disease, stroke, cancer, and arthritis are all influenced by the presence of obesity. Small reductions in excess weight can produce significant positive clinical outcomes. Healthcare organizations have a vital role to play in the identification and management of obesity. Currently, healthcare providers do not adequately diagnose and manage excess weight in patients. Lack of skill, time, and knowledge are commonly cited as reasons for non-adherence to recommended standards of care. The Chronic Care Model offers an approach to healthcare organizations for chronic disease management. The model consists of six elements that work together to empower both providers and patients to have more productive interactions: the community, the health system itself, self-management support, delivery system design, decision support, and clinical information systems. The model and its elements may offer a framework through which healthcare organizations can adapt to support, educate, and empower providers and patients in the management of excess weight and obesity. Successful management of excess weight will reduce morbidity and mortality of many chronic conditions. Purpose. The purpose of this review is to synthesize existing research on the effectiveness of the Chronic Care Model and its elements as they relate to weight management and behaviors associated with maintaining a healthy weight. Methods: A narrative review of the literature between November 1998 and November 2008 was conducted. The review focused on clinical trials, systematic reviews, and reports related to the chronic care model or its elements and weight management, physical activity, nutrition, or diabetes. Fifty-nine articles are included in the review. Results. This review highlights the use of the Chronic Care Model and its elements that can result in improved quality of care and clinical outcomes related to weight management, physical activity, nutrition, and diabetes. Conclusions. Healthcare organizations can use the Chronic Care Model framework to implement changes within their systems to successfully address overweight and obesity in their patient populations. Specific recommendations for operationalizing the Chronic Care Model elements for weight management are presented.^

A community-based assessment of the spatiotemporal distribution of influenza in a U.S.-Mexico border county during the spring 2009 novel H1N1 swine-origin influenza A pandemic

This study retrospectively evaluated the spatial and temporal disease patterns associated with influenza-like illness (ILI), positive rapid influenza antigen detection tests (RIDT), and confirmed H1N1 S-OIV cases reported to the Cameron County Department of Health and Human Services between April 26 and May 13, 2009 using the space-time permutation scan statistic software SaTScan in conjunction with geographical information system (GIS) software ArcGIS 9.3. The rate and age-adjusted relative risk of each influenza measure was calculated and a cluster analysis was conducted to determine the geographic regions with statistically higher incidence of disease. A Poisson distribution model was developed to identify the effect that socioeconomic status, population density, and certain population attributes of a census block-group had on that area's frequency of S-OIV confirmed cases over the entire outbreak. Predominant among the spatiotemporal analyses of ILI, RIDT and S-OIV cases in Cameron County is the consistent pattern of a high concentration of cases along the southern border with Mexico. These findings in conjunction with the slight northward space-time shifts of ILI and RIDT cluster centers highlight the southern border as the primary site for public health interventions. Finally, the community-based multiple regression model revealed that three factors—percentage of the population under age 15, average household size, and the number of high school graduates over age 25—were significantly associated with laboratory-confirmed S-OIV in the Lower Rio Grande Valley. Together, these findings underscore the need for community-based surveillance, improve our understanding of the distribution of the burden of influenza within the community, and have implications for vaccination and community outreach initiatives.^

Using small area estimation and geographic information systems technology to target health services for the uninsured

The three articles that comprise this dissertation describe how small area estimation and geographic information systems (GIS) technologies can be integrated to provide useful information about the number of uninsured and where they are located. Comprehensive data about the numbers and characteristics of the uninsured are typically only available from surveys. Utilization and administrative data are poor proxies from which to develop this information. Those who cannot access services are unlikely to be fully captured, either by health care provider utilization data or by state and local administrative data. In the absence of direct measures, a well-developed estimation of the local uninsured count or rate can prove valuable when assessing the unmet health service needs of this population. However, the fact that these are “estimates” increases the chances that results will be rejected or, at best, treated with suspicion. The visual impact and spatial analysis capabilities afforded by geographic information systems (GIS) technology can strengthen the likelihood of acceptance of area estimates by those most likely to benefit from the information, including health planners and policy makers. ^ The first article describes how uninsured estimates are currently being performed in the Houston metropolitan region. It details the synthetic model used to calculate numbers and percentages of uninsured, and how the resulting estimates are integrated into a GIS. The second article compares the estimation method of the first article with one currently used by the Texas State Data Center to estimate numbers of uninsured for all Texas counties. Estimates are developed for census tracts in Harris County, using both models with the same data sets. The results are statistically compared. The third article describes a new, revised synthetic method that is being tested to provide uninsured estimates at sub-county levels for eight counties in the Houston metropolitan area. It is being designed to replicate the same categorical results provided by a current U.S. Census Bureau estimation method. The estimates calculated by this revised model are compared to the most recent U.S. Census Bureau estimates, using the same areas and population categories. ^

Type A behavior and blood pressure during adolescence

In The Woodlands, Texas, 346 students in grades 9-12, age 14-18 participated in a screening examination for cardiovascular risk factors. The relationships between blood pressure with Type-A-behavior and its components were evaluated. Type-A-behavior was measured using the Hunter-Wolf Type-A-behavior scale.^ The following results refer to the current 24-item version of the Hunter-Wolf Type-A-behavior scale and subscales derived in the Bogalusa study which thereafter were applied to The Woodlands population.^ No significant differences in blood pressure were observed among children in the highest vs. lowest quintile of the Type-A-behavior score or subscales scores. The correlation coefficients of blood pressure with the Type-A-behavior and its components were small and non-significant in both boys and girls. Multiple regression analyses conducted by sex, showed that after adjustment for age, weight and height, the addition of the total Type-A-behavior score or subscale scores did not increase significantly the amount of the variability explained for any of the blood pressure components.^ These analyses were repeated with results from the original 17-item version of the Hunter-Wolf Type-A-behavior scale and subscales derived in Bogalusa. Similarly, no relationship was observed between the 17-item Type-A-behavior score or subscales scores with blood pressure levels in The Woodlands population.^ Finally, it was important to determine whether subscales derived within The Woodlands population would differ from those described in Bogalusa and would relate differently to blood pressure among students in The Woodlands. The corresponding analyses showed that the subscales derived from the two studies were different, but in fact neither set of subscales was importantly related with blood pressure in The Woodlands population.^ The results of this study are largely consistent with those obtained by Hunter and Wolf in Bogalusa, who among the white population found only the factor "Eagerness-Energy" to be associated with fourth phase diastolic blood pressure among girls. Even this relationship which they observed was weak and inconsistent across sex-race groups and blood pressure components. This study does not support even this positive finding. In conclusion, evidence indicates that blood pressure is not associated with Type-A-behavior or its components as measured by the Hunter-Wolf Type-A-behavior scale among white adolescents. ^

COSTS AND EFFECTS OF ARKANSAS' LONG-TERM CARE DEMONSTRATION PROJECT (MEDICAID, CHANELLING, COMMUNITY ASSESSMENT)

The purpose of this study was to assess the impact of the Arkansas Long-Term Care Demonstration Project upon Arkansas' Medicaid expenditures and upon the clients it serves. A Retrospective Medicaid expenditure study component used analyses of variance techniques to test for the Project's effects upon aggregated expenditures for 28 demonstration and control counties representing 25 percent of the State's population over four years, 1979-1982.^ A second approach to the study question utilized a 1982 prospective sample of 458 demonstration and control clients from the same 28 counties. The disability level or need for care of each patient was established a priori. The extent to which an individual's variation in Medicaid utilization and costs was explained by patient need, presence or absence of the channeling project's placement decision or some other patient characteristic was examined by multiple regression analysis. Long-term and acute care Medicaid, Medicare, third party, self-pay and the grand total of all Medicaid claims were analyzed for project effects and explanatory relationships.^ The main project effect was to increase personal care costs without reducing nursing home or acute care costs (Prospective Study). Expansion of clients appeared to occur in personal care (Prospective Study) and minimum care nursing home (Retrospective Study) for the project areas. Cost-shifting between Medicaid and Medicare in the project areas and two different patterns of utilization in the North and South projects tended to offset each other such that no differences in total costs between the project areas and demonstration areas occurred. The project was significant ((beta) = .22, p < .001) only for personal care costs. The explanatory power of this personal care regression model (R('2) = .36) was comparable to other reported health services utilization models. Other variables (Medicare buy-in, level of disability, Social Security Supplemental Income (SSI), net monthly income, North/South areas and age) explained more variation in the other twelve cost regression models. ^

Objective assessment of the built environment and its relationship to physical activity and obesity

The role of physical activity in the promotion of individual and population health has been well documented in research and policy publications. Significant research activities have produced compelling evidence for the support of the positive association between physical activity and improved health. Despite the knowledge about these public health benefits of physical activity, over half of US adults do not engage in physical activity at levels consistent with public health recommendations. Just as physical inactivity is of significant public health concern in the US, the prevalence of obesity (and its attendant co-morbidities) is also increasing among US adults.^ Research suggests racial and ethnic disparities relevant to physical inactivity and obesity in the US. Various studies have shown more favorable outcomes among non-Hispanic whites when compared to other minority groups as far as physical activity and obesity are concerned. The health disparity issue is especially important because Mexican-Americans who are the fastest growing segment of the US population are disproportionately affected by physical inactivity and obesity by a significant margin (when compared to non-Hispanic whites), so addressing the physical inactivity and obesity issues in this group is of significant public health concern. ^ Although the evidence for health benefits of physical activity is substantial, various research questions remain on the potential motivators for engaging in physical activity. One area of emerging interest is the potential role that the built environment may play in facilitating or inhibiting physical activity.^ In this study, based on an ongoing research project of the Department of Epidemiology at the University of Texas M. D. Anderson Cancer Center, we examined the built environment, measured objectively through the use of geographical information systems (GIS), and its association with physical activity and obesity among a cohort of Mexican- Americans living in Harris County, Texas. The overall study hypothesis was that residing in dense and highly connected neighborhoods with mixed land-use is associated with residents’ increased participation in physical activity and lowered prevalence of obesity. We completed the following specific aims: (1) to generate a land-use profile of the study area and create a “walkability index” measure for each block group within the study area; (2) to compare the level of engagement in physical activity between study participants that reside in high walkability index block groups and those from low walkability block groups; (3) to compare the prevalence of obesity between study participants that reside in high walkability index block groups and those from low walkability block groups. ^ We successfully created the walkability index as a form of objective measure of the built environment for portions of Harris County, Texas. We used a variety of spatial and non-spatial dataset to generate the so called walkability index. We are not aware of previous scholastic work of this kind (construction of walkability index) in the Houston area. Our findings from the assessment of relationships among walkability index, physical activity and obesity suggest the following, that: (1) that attempts to convert people to being walkers through health promotion activities may be much easier in high-walkability neighborhoods, and very hard in low-walkability neighborhoods. Therefore, health promotion activities to get people to be active may require supportive environment, walkable in this case, and may not succeed otherwise; and (2) Overall, among individuals with less education, those in the high walkability index areas may be less obese (extreme) than those in the low walkability area. To the extent that this association can be substantiated, we – public health practitioners, urban designers, and policy experts – we may need to start thinking about ways to “retrofit” existing urban forms to conform to more walkable neighborhoods. Also, in this population especially, there may be the need to focus special attention on those with lower educational attainment.^

Posttraumatic stress disorder among veterans of the Operation Iraqi Freedom (OIF) and Operation Enduring Freedom (OEF) wars: Psychological comorbidities, postdeployment social support and unit support

Much attention has been given to treating Operation Iraqi Freedom/Operation Enduring (OIF/OEF) Veterans with posttraumatic stress disorder (PTSD). However, little attention is given to those Veterans who do not meet diagnostic criteria for PTSD but who may still benefit from intervention. Research is needed to investigate the impact of how different racial/ethnic backgrounds, different levels of social support and comorbid mental health disorders impact OIF/OEF Veterans with varying levels of PTSD. The purpose of this dissertation is to examine the association of comorbid Axis I disorders, race/ethnicity, different levels of postdeployment social support and unit support on OIF/OEF Veterans with varying levels of PTSD. Data for this dissertation were from postdeployment screenings of OIF/OEF Veterans from a large Veterans Affairs hospital in southeast Texas. To examine the study hypotheses, we conducted multinomial logistic regressions of the clinician reported data. ^ The first article examined the prevalence of subthreshold and full levels of PTSD and compared Axis I and alcohol use comorbidity rates among 1,362 OIF/OEF Veterans with varying levels of PTSD. Results suggest that OIF/OEF Veterans with subthreshold PTSD experience similar levels of psychological distress as those with full PTSD and highlight the need to provide timely and appropriate mental health services to individuals who may not meet the diagnostic criteria for full PTSD. ^ These results suggest that OIF/OEF Veterans of all race/ethnicities can benefit from strong social support systems. Postdeployment social support was found to be a protective factor against the development of PTSD among White, Black and Hispanic veterans while deployment unit support was a protective factor only among Black Veterans. The second article investigated the association between postdeployment social support and unit support with varying levels of PTSD by race/ethnicity among 1,115 OIF/OEF Veterans. ^ The results of this study can help to formulate treatment and interventions for OIF/OEF Veterans with varying levels of PTSD and social support systems.^

Correlates of post-diagnosis weight management among female breast cancer survivors: An Internet survey

Objective. Weight gain after cancer treatment is associated with breast cancer recurrence. In order to prolong cancer-free survivorship, interventions to manage post-diagnosis weight are sometimes conducted. However, little is known about what factors are associated with weight management behaviors among cancer survivors. In this study, we examined associations of demographic, clinical, and psychosocial variables with weight management behaviors in female breast cancer survivors. We also examined whether knowledge about post-diagnosis weight gain and its risk is associated with weight management behaviors. ^ Methods. 251 female breast cancer survivors completed an internet survey. They reported current performance of three weight management behaviors (general weight management, physical activity, and healthy diet). We also measured attitude, elf-efficacy, knowledge and social support regarding these behaviors along with demographic and clinical characteristics. ^ Results. Multiple regression models for the weight management behaviors explained 17% of the variance in general weight management, 45% in physical activity and 34% in healthy dieting. The models had 9–14 predictor variables which differed in each model. The variables associated with all three behaviors were social support and self-efficacy. Self-efficacy showed the strongest contribution in all models. The knowledge about weight gain and its risks was not associated with any weight management behaviors. However, women who obtained the knowledge during cancer treatment were more likely to engage in physical activity and healthy dieting. ^ Conclusions. The findings suggest that an intervention designed to increase their self-efficacy to manage weight, to be physically active, to eat healthy will effectively promote survivors to engage in these behaviors. Knowledge may motivate women to manage post-diagnosis weight about risk if information is provided during cancer treatment.^