Abstract
Objective.
The study aimed to examine the community characteristics of vulnerable communities where obesity is one of the top three chronic conditions with the greatest disparity compared to the Delaware statewide obesity rate to demonstrate the need for community specific education and interventions.
Methods.
The study is a secondary analysis using a subset of the CHAMG research project dataset and includes 47 vulnerable communities. The dataset included official data reported between 2019 and 2022 and abstracted from My Healthy Communities Delaware data portal and the IP3 data portal.
Results.
The study communities differed notably from Delaware’s general population and from each other. The average poverty rate was greater (21% compared 11%) and the average obesity rate was greater (41% compared to 34%). The minority population in the study communities ranged from 6% to 93% Black and from 2% to 70% Hispanic. The average age ranged from 27 years old to 54 years old. The poverty rate ranged from 4% to 50%. Eleven (23%) of the vulnerable communities with obesity disparity were rural. Depression and heart disease ranked in the top three most disparate chronic conditions in at least half of the study communities and HPB in 36% of the study communities. Fewer community assets were identified in the study communities, including fewer medical professionals, lower rates of HBP management, and lower English proficiency.
Conclusions.
Vulnerable communities with high rates of obesity differ from Delaware’s general population. They have fewer community assets and greater prevalence of obesity-related chronic conditions. There is notable variation across the study communities, underscoring the need for community specific education and interventions.
Public Health Implications.
Obesity is a key multi-solver health condition. Because obesity is correlated with other chronic conditions, mental health diagnoses, and well-being indicators, community specific obesity education and interventions will likely decrease obesity rates and improve other health and well-being conditions.
Introduction
In 2013, the AMA designated obesity as a chronic disease. Many hoped this designation would positively impact access to care, advances in treatment, and reduction in stigma.1 Despite the AMA designation, rates of obesity continue to rise. It has more than doubled since 1990, from 19% to 43%.2,3 Worldwide, 1 in 8 persons is obese, representing 16% of adults. In the US, 40% of adults are obese with adults between 40 and 59 years old having the highest prevalence at 46%. Obesity is slightly more prevalent among women (41%) than among men (39%). Almost one tenth of American adults are severely obese, with a higher prevalence among women (13%) compared to men (7%). Although the prevalence of obesity in the US has not changed significantly since its AMA chronic condition designation, severe obesity has increased by about 2%.4 Race and ethnic differences are also notable. In 2022, non-Hispanic Black females have the highest prevalence of obesity, at 57%. The prevalence of obesity among Hispanic females is about 10% lower at 49%. Hispanic males, non-Hispanic White males and females, and non-Hispanic Black males had similar prevalence, about 42%.3
Delaware ranks 34th in adult obesity, meaning that only 16 states have higher obesity rates. About 38% of adult Delawareans are obese, a 10% increase over the previous decade. The prevalence of obesity among adult men and women is similar. However, differences by race and ethnicity are evident with 49% of Black adults but only 35% of White and Hispanic adults being obese. About 45% of Delawareans between 45 and 54 years old are obese. The rate of prevalence of obesity is lowest among 18- to 24-year-olds at 29%.5
In the past decade, many advances have been made in addressing obesity. Research demonstrates that altering eating habits reduces weight and improves other health indicators.6,7 Physical activity has been proven to be a core element of weight management and reduction.8 Multi-prong approaches where diet, physical activity and other interventions are administered in combination, frequently referred to as intensive lifestyle interventions (ILI), have been shown to be the most effective behavioral interventions.9 Clinical research on bariatric surgery has the longest track record, showing a 25% reduction in total body weight sustained long-term.10 The most recent development, anti-obesity medications (AOM), has demonstrated indisputable clinical effectiveness for weight loss, diabetes management, and other chronic health conditions.11
Despite evidence of effectiveness, intervention uptake as well as long term weight loss continue to be issues. Participation in weight loss and management programs is very low, about 5%, and less than 1% of Americans eligible for bariatric surgery receive it.1 An extensive review of weight loss clinical trials and found that about eight weeks after a weight loss intervention, many participants began to gain weight and some experienced regaining all the weight lost.12
Several barriers to access and long-term success have been identified, including physician bias as well as weight stigma, cost, and insurance benefits.1,13 Most concerning, however, is the cumulative effect these and other barriers have on limiting the availability of obesity interventions for those who need it most. The correlation between poverty and obesity is well established.14,15 According to the U.S. Department of Health and Human Services, 40% of Americans with incomes less than $25,000 are obese compared to 28% of those with incomes of $150,000 or greater.16 In general, as income increases the prevalence of obesity decreases. This trend is evident in Delaware as well. Among Delawareans with an annual income less than $25,000, 41% are obese; whereas only 34% of Delawareans with an annual income of $150,000 or more are obese.5
In this article we examine the obesity disparity using data collected through a recent needs assessment of chronic conditions in Delaware’s vulnerable communities. We present the rates of obesity as well as the prevalence of related chronic conditions. We also examine the neighborhood assets necessary to address obesity and address the obesity disparity in the context of the 5 As of access and make suggestions for action.17 Finally, we present obesity as a multi-solver issue. We discuss the potential of a multi-pronged approach across the socioecological framework focusing on community specific obesity education and intervention to improve health and wellbeing outcomes in Delaware’s most vulnerable communities.
Methods
In 2023, the Community Health Advocacy Mobilization Group (CHAMG), a coalition of over 40 community organizations promoting health equity through advocacy and community engagement, led a mixed methods research project to promote health equity through advocacy for data-driven policies and practice changes. CHAMG partnered with Delaware Health and Social Services Division of Public Health Bureau of Health Equity and the Delaware State University Interdisciplinary Health Research Center Community Engagement and Dissemination Core. The original research project aimed to demonstrate how data at the census tract level and dynamic, continuous community engagement could drive the development of solutions, grounded in social determinants and community assets, that were relevant to vulnerable communities with the greatest need of community appropriate and acceptable resources and services.18
The CHAMG research project focused on vulnerable communities, frequently referred to underserved and/or marginalized communities. It used the Social Vulnerability Index (SVI) to select the communities of interest for the research project. The CDC adopted the SVI to identify communities’ level of need. The index is based on 16 social factors, including poverty, and scores 0.0 to 1.0, with 0.0 representing the lowest vulnerability and 1.0 representing the highest. Of Delaware’s 218 census tracts, 52 (24%) had scores of .75 or higher on the SVI. This group of communities comprised the sample for the CHAMG report.
The chronic condition data examined in the CHAMG study was abstracted from the Delaware Division of Public Health’s My Healthy Community (MHC) data portal. The MHC data portal provided census tract level data, including SVI scores, demographic and population health indicators as well as environmental and social determinants of health data.18 The MHC data was a robust, easily searchable, free data source accessible by the public. The MHC portal was sunset at the end of 2025, making the CHAMG research project a vital source of data while DPH transitions to another publicly accessible data portal.
The nine chronic health conditions included in the CHAMG study were arthritis, cancer, chronic obstructive pulmonary disease (COPD), depression, diabetes, heart disease, high blood pressure, high cholesterol, and obesity. These chronic health conditions were selected due to their significance established in the health literature. The disparity for each health condition was quantified by calculating the difference between state prevalence and census tract prevalence. Health conditions for which prevalence was higher in the census tract than in the state were identified and ranked in descending order according to the magnitude of the difference. The three conditions exhibiting the greatest disparity were designated as the greatest disparity, second greatest disparity, and third greatest disparity. Every census tract demonstrated at least one chronic health condition with a disparity, although some tracts were assigned only one or two ranked conditions. In instances where two or more health conditions had identical differences between census tract prevalence and state prevalence, they were assigned the same rank. For two of the census tracts, the prevalence for the nine chronic health conditions was not available because the census tract population was too small to report health data publicly.18
The CHANG report also used IP3 source of community assets information. The IP3 ASSESS platform, a digital data tool developed by the Institute for People, Place, and Possibility (IP3), is designed to assist organizations in examining population health, equity, and community requirements. The platform employs strategic frameworks such as the Seven Vital Conditions to convert raw data into practical insights for community development.
The CHAMG research project found that the most common chronic condition with the greatest disparity was obesity. Obesity was ranked as one of the top three chronic conditions with the greatest disparity in 47 (94%) of Delaware’s vulnerable communities. It was the chronic condition with the greatest disparity in 39 (78%) of the communities. These findings alone justify a closer examination of obesity in Delaware’s communities most impacted by obesity. Coupling the disparity in obesity prevalence and the disparity in co-occurring chronic conditions, such as heart disease, diabetes, and depression, the need to focus on obesity becomes imperative.
This study is a secondary analysis of the chronic condition dataset created and used in the CHAMG research project. The primary aim is to examine the community characteristics of vulnerable communities where obesity is one of the top three chronic conditions with the greatest disparity compared to the Delaware statewide obesity rate. A subset of the CHAMG research project data, including 47 communities, was curated to examine the vulnerable communities where the prevalence of obesity was ranked as one of the top three chronic conditions with the greatest disparity compared to the state prevalence. The dataset included community demographics, community assets, health literacy, and chronic condition rates for obesity, chronic obstructive pulmonary disease, diabetes, depression, heart disease, and high blood pressure.
Results
As expected, the obesity and poverty rates of the vulnerable community in this study were higher than the state rates. Obesity rates for the study communities ranged from 34% to 52% with an average of 41% compared to Delaware’s rate of 34%. On average, the poverty rate at 21% was twice that of the state average of 11%. The vulnerable communities included in the study differed from the state’s general population by race/ethnicity and age characteristics (Table 1). The race/ethnicity composition of the study communities was 42% Black, 47% White and 16% Hispanic. Comparatively, Delaware’s population is 22% Black, 67% White and 9% Hispanic. The vulnerable communities included in this study, on average, were home to more minorities than the Delaware’s overall population with almost twice as many Black and Hispanic residents and notably fewer White residents. The average age was younger than the state average, 36 years old compared to 41 years old.
Table 1. Delaware Demographic Characteristics Compared to Study Communities Demographic Characteristics.
| Demographic Characteristics | Delaware | Vulnerable Communities with Obesity Disparity |
|---|---|---|
| Race/Ethnicity Black White Hispanic |
22% 67% 9% |
42% 47% 16% |
| Median Age | 41 years old | 36 years old |
| Poverty Rate | 11% | 21% |
| Obesity Rate | 34% | 41% |
The differences between study communities are important to note. The poverty rate ranged from 4% to 50%, underscoring that poverty alone does not define community vulnerability. The minority population in the study communities ranged from 6% to 93% Black and from 2% to 70% Hispanic. The average age ranged from 27 years old to 54 years old.
Eleven (23%) of the vulnerable communities with obesity disparity are rural. Not surprisingly, all are in Kent and Sussex Counties. The rural communities included in the sample include five (83%) of Kent County’s six vulnerable communities and six (55%) of the eleven Sussex County vulnerable communities.
Table 2 presents the number of communities in the study sample which also had notably high rates of other chronic conditions associated with obesity, including COPD, depression, diabetes, heart disease and high blood pressure. Half of the study communities also had high rates of depression and heart disease that ranked in the top three most disparate chronic conditions. In about one third of the study communities, high blood pressure (HPB) was also one of the top three chronic conditions with higher rates of prevalence than the state rate. In about one quarter of the study communities, chronic obstructive pulmonary disease (COPD) and diabetes were one of the top three chronic conditions with higher rates of prevalence than the state rate.
Table 2. Study Communities and Other Obesity Related Chronic Conditions.
| Obesity Ranking | Number of Vulnerable Communities by Obesity Ranking | Number of Study Communities with Other Obesity Related Chronic Conditions Ranked in Top Three Greatest Disparity | ||||
|---|---|---|---|---|---|---|
| COPD | Depression | Diabetes | Heart Disease | HPB | ||
| 1 | 39 (83%) | --- | 7 (15%) | --- | --- | 1 (2%) |
| 2 | 5 (11%) | 3 (6%) | 15 (32%) | 2 (4%) | 6 (13%) | 15 (32%) |
| 3 | 3 (6%) | 8 (17%) | 3 (6%) | 10 (21%) | 18 (38%) | 1 (2%) |
| TOTAL | 47 (100%) | 11 (23%) | 25 (53%) | 12 (26%) | 24 (51%) | 17 (36%) |
Understanding community assets, or the lack thereof, are important in developing community level interventions. For the 47 vulnerable communities included in this study, many of them lacked adequate structural assets key to health and wellbeing. The community asset data was abstracted from the IP3 data portal. Table 3 defines the six community assets using the IP3 definition and presents the state prevalence of each. The state prevalence indicates the percentage of census tracts with adequate community resources. Inadequate data was available for three additional essential community assets: exercise opportunities, food insecurity, and mental health professionals per 100,000 residents.
Table 3. Delaware Prevalence of Community Assets.
| Community Asset | Definition | State Prevalence |
|---|---|---|
| Low Food Access | Percentage of population with low food access, defined as living beyond 1 mile (urban) or 10 miles (rural) of supermarket | 42% |
| Recent Primary Care Visit | Percentage of adults aged 18 years and older who report having been to a doctor for a routine checkup in the past year | 75% |
| Medical Professionals per 1,000 Residents | Number of health diagnosing and treating practitioners per 1,000 population | 21.4 |
| HBP Management | Percentage of adults aged 18 years and older with high blood pressure who report taking medicine for high blood pressure | 83% |
| Parks | Percentage of the population living within 0.5 miles of a park | 63% |
| Limited English | Percentage of the population aged 5 years and older who speak English less than "very well" | 5% |
Table 4 shows the number of study communities with fewer assets than the state prevalence by county. Five (11%) of the study communities had lower food access than the state with similar differences across the counties. Almost half (47%) of the study communities had lower rates of primary care visits compared to the state. This disparity was most evident in the New Castle County vulnerable communities. Most (83%) of the study communities had fewer medical professionals than the state rate with the greatest number of communities in New Castle and Sussex Counties. Across all the study communities, the number of communities with adults aged 18 years and older with high blood pressure who reported taking medicine for high blood pressure was much lower than the state rate. All of the study communities in New Castle and Sussex Counties and 83% of the Kent County study communities had a lower rate of HBP medication compliance than the state rate. About one third of the study communities had a lower prevalence of access to parks than the state. However, there is a clear geographical difference in access to parks. None of the New Castle County vulnerable communities but all of the Kent and Sussex County vulnerable communities had fewer accessible parks compared to the state park accessibility rate. Overall, about two thirds (68%) of study communities had lower rates of English proficiency than the state with notable variation by county. Ten (91%) of the Kent County study communities compared to two thirds of the New Castle County and one third of the Kent County study communities had higher rates of limited English proficiency.
Table 4. Number and Percentage of Study Communities Lacking Adequate Community Assets.
| County (number of study communities) | Low Food Access | Recent Primary Care Visit | Medical Professionals per 1,000 residents | HBP Management | Parks | Limited English |
| New Castle (30) | 4 (13%) | 18 (60%) | 26 (87%) | 30 (100%) | --- | 20 (67%) |
| Kent (6) | --- | 1 (17%) | 4 (67%) | 5 (83%) | 6 (100%) | 2 (33%) |
| Sussex (11) | 1 (9%) | 1 (9%) | 9 (82%) | 11 (100%) | 11 (100%) | 10 (91%) |
| Study Total (47) | 5 (11%) | 20 (43%) | 39 (83%) | 46 (98%) | 17 (36%) | 32 (68%) |
Discussion
The secondary analysis of the CHAMG research project dataset demonstrates its viability in examining specific chronic conditions in Delaware’s most vulnerable communities. Our findings clearly show that vulnerable communities with high rates of obesity differ from Delaware’s general population by race/ethnicity, age, and income characteristics. They also differ from the state in terms of community assets. Within the sample, notable differences in community characteristics and assets were also evident, underscoring the need for community specific education and interventions.
As noted in the CHAMG report, creating a census tract level profile allows for community specific interventions.18 Penchansky and Thomas offer a framework to create community specific education and intervention efforts.17 They define access beyond costs and location. The five As of access are defined as: 1) Access - how much a service costs and the ability and willingness of the community member to pay; 2) Availability - the existence of the services in the community to meet the needs of the community members; 3) Accessibility - how easily the community member can get to the service; 4) Accommodation – how well the service meets the preferences and constraints of the community member; and 5) Acceptability - the extent to which the community member and the provider of the service are comfortable and can relate to each other. These elements can be used as a checklist to ensure that education and interventions are community specific.
Community level responses to obesity or any other health conditions cannot be developed using only official data.19,20 Without input from community members, critical information about the five As, particularly acceptability, will be limited. The community culture, preferences, understanding of obesity as a chronic condition, and readiness for change will be limited and most likely weaken the effectiveness of the intervention. To this end, CHAMG in partnership with the DSU IHER Center CED Core will use the information produced by this study to engage with residents of vulnerable communities most greatly impacted by obesity to gain better insight in their understanding of obesity as a chronic condition and their suggestions for acceptable community level education and interventions.
Lowering obesity rates in Delaware is not solely a community level intervention. As established in the American Diabetes Association (ADA)’s Obesity Association Standards of Care in Overweight and Obesity, it requires changing the conversation and approach in the doctor’s office, in the workplace, in the community, and in the legislature.21 Research has shown that physician bias against overweight and obese patients worsens stigma and reduces intervention uptake.13,22 Education of health care providers needs to include how they view obesity and how they empower their patients with culturally and linguistically appropriate guidance to adopt practices to promote healthy lifestyles.21 The conversation and culture in the workplace need to shift to support employees with obesity to reduce their health risks and have information to make healthier choices, increasing their productivity and overall well-being.21 The community, including grassroots and community-based organizations, neighborhood groups, and coalitions, need to advocate for and implement community-driven education and place-based approaches. Structural investments designed to increase community assets need to be made.22 Policy changes must include community members to ensure that, like educational materials and interventions, are appropriate for and acceptable to the individuals and communities they are designed to help.23,24
Public Health Implications
The findings from this study have two significant public health implications. First, it demonstrated that using community level data to examine obesity in the context of community characteristics, community assets, and other chronic conditions produces community specific profiles that are essential for identifying data-driven responses. However, quantitative data must be coupled with community voice and input to create truly community defined and acceptable interventions.
Second, because obesity is correlated with other chronic conditions, mental health diagnoses, and well-being indicators, it is a key multi-solver health condition. If community specific education and interventions are developed, resourced, and administered, it is likely that not only will obesity rates decrease but additional health and well-being concerns will also be alleviated. Addressing multiple, correlated health conditions simultaneously reduces the potential for mixed or contradictory messages and random acts with limited impact. It allows for coordinated and mutually beneficial interventions, such as strengthening community assets that are known to improve multiple health conditions. And it will reduce healthcare costs and increase sustainable improvement over time.
Funding Statement
This study was supported by NIH grant U54MD15959.
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