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Diabetes Prevalence In New Jersey Case Study

ADDRESSING THE DIABETES EPIDEMIC IN PATERSON, NJ

Addressing the Diabetes Epidemic in Paterson, NJ: A Comprehensive Case Study

A. Introduction

Diabetes mellitus is a chronic metabolic disorder characterized by elevated blood glucose levels resulting from insufficient insulin production or the body's inability to use insulin effectively. In recent years, diabetes has emerged as a critical public health concern in Paterson, New Jersey, a diverse urban community with approximately 150,000 residents.

This case study focuses on diabetes as a significant population health issue in Paterson due to its high prevalence, severe health consequences, and substantial economic burden on the healthcare system. According to recent data from the New Jersey Department of Health, the age-adjusted diabetes prevalence in Passaic County, where Paterson is located, is 10.2%, higher than the state average of 9.2% (NJDOH, 2022). This translates to approximately 15,000 Paterson residents living with diagnosed diabetes, with potentially many more undiagnosed cases.

Several factors drive the decision to focus on diabetes. Firstly, diabetes is a huge risk factor for numerous health complications, including cardiovascular disease, kidney failure, blindness, and lower-limb amputations. Secondly, the disease disproportionately affects racial and ethnic minorities, which is particularly relevant in Paterson's diverse community. Lastly, type 2 diabetes, the most common form, is largely preventable through lifestyle modifications, presenting opportunities for impactful public health interventions.

Risk factors associated with diabetes in Paterson include obesity, physical inactivity, poor dietary habits, and limited access to healthcare services. Protective factors include maintaining a healthy weight, a balanced diet, regular physical activity, and early screening and intervention. The consequences of uncontrolled diabetes for public health are severe, including increased healthcare costs, reduced quality of life, and premature mortality.

B. Epidemiology

To fully understand the diabetes epidemic in Paterson, it is crucial to examine relevant epidemiological data. This section will present and analyze descriptive and analytical epidemiological information, considering risk factors, trends over time, and comparisons with other populations.

Prevalence and Incidence

According to the Behavioral Risk Factor Surveillance System (BRFSS) data, the age-adjusted prevalence of diagnosed diabetes in Passaic County, which includes Paterson, is 10.2% (NJDOH, 2022). This is higher than both the New Jersey state average (9.2%) and the national average (10.5%) (CDC, 2023).

Estimated diabetes prevalence in Paterson (2022)

Total population: ~150,000

Diagnosed diabetes: ~15,000 (10%)

Undiagnosed diabetes: ~5,000 (3.3%) (based on CDC estimates that 1 in 4 people with diabetes are undiagnosed)

Prediabetes: ~50,000 (33.3%) (based on CDC estimates that 1 in 3 U.S. adults have prediabetes).

Figure 1: The estimated distribution of diabetes status among Paterson's population

Demographic Distribution

Diabetes prevalence in Paterson varies significantly across demographic groups:

1. Age: The prevalence increases with age, with the highest rates being with those 65 years and older (25.2%) (NJDOH, 2022).

2. Race/Ethnicity: Hispanic (14.3%) and Black (13.8%) residents have higher prevalence rates compared to White (8.9%) residents (NJDOH, 2022).

3. management services (U.S. Census Bureau, 2023).

Figure 3: The prevalence of key risk factors for diabetes in Passaic County.

Trends Over Time

The prevalence of diabetes in Passaic County has increased from 8.5% in 2012 to 10.2% in 2022,...

…partnerships for health improvement

Challenges

May face opposition from businesses concerned about costs

Requires careful design to ensure equitable access across different types of businesses

Strategy 2: Improve Access to Healthcare through Community Health Worker Programs

Policy Advancement Options

Workforce Development Policy

Establish a city-wide policy to train and employ community health workers (CHWs) specializing in diabetes prevention and management.

Implementation

Develop a policy framework for a CHW training and certification program focused on diabetes.

Allocate city funds for CHW training and employment, possibly through a dedicated tax or reallocating existing health funds.

Come together with local educational institutions to develop and deliver the training program.

Benefits

Creates job opportunities while addressing health needs

Ensures a culturally competent healthcare workforce

Challenges

Requires significant initial investment

May face opposition from traditional healthcare providers

Healthcare Integration Policy

Advocate for state-level policy changes to formally integrate CHWs into healthcare teams and reimbursement models.

Implementation

Work with state legislators to introduce a bill recognizing CHWs as part of the healthcare workforce and establishing reimbursement mechanisms for their services.

Collaborate with healthcare systems and insurers to develop protocols for CHW integration.

If passed, work with the state health department to establish CHW certification and practice standards.

Benefits

Provides sustainable funding for CHW programs

Legitimizes the role of CHWs in healthcare delivery

Challenges

Requires navigating complex healthcare regulations

May face opposition from some healthcare professional groups

Data Sharing and Care Coordination Policy

Develop a local policy mandating data sharing and care coordination between CHWs, primary care providers, and specialists for diabetes care.

Implementation

Draft a policy outlining requirements for secure data sharing and care coordination protocols.

Work with local healthcare providers and technology vendors to develop compatible systems for information exchange.

Implement privacy safeguards and obtain necessary approvals from relevant authorities.

Benefits

Improves continuity of care for diabetes patients

Enhances efficiency of healthcare delivery

Challenges

Requires addressing complex privacy and data security issues

May face resistance from healthcare providers concerned about increased administrative burden

These policy advancement options provide a range of approaches to support the implementation of community-based…

Sources used in this document:

References

American Diabetes Association. (2023). Statistics about diabetes. https://diabetes.org/about-us/statistics/about-diabetes

Centers for Disease Control and Prevention (CDC). (2023). National Diabetes Statistics Report. https://www.cdc.gov/diabetes/data/statistics-report/index.html

Ely, E. K., Gruss, S. M., Luman, E. T., Gregg, E. W., Ali, M. K., Nhim, K., Rolka, D. B., & Albright, A. L. (2017). A national effort to prevent type 2 diabetes: Participant-level evaluation of CDC's National Diabetes Prevention Program. Diabetes Care, 40(10), 1331-1341. https://doi.org/10.2337/dc16-2099Lee, S. W. H., Chan, C. K. Y., Chua, S. S., & Chaiyakunapruk, N. (2018). Comparative effectiveness of telemedicine strategies on type 2 diabetes management: A systematic review and network meta-analysis. Scientific Reports, 8(1), 3286. https://doi.org/10.1038/s41598-018-22113-2

New Jersey Department of Health (NJDOH). (2022). New Jersey State Health Assessment Data. https://www-doh.state.nj.us/doh-shad/

Palmas, W., March, D., Darakjy, S., Findley, S. E., Teresi, J., Carrasquillo, O., & Luchsinger, J. A. (2015). Community health worker interventions to improve glycemic control in people with diabetes: A systematic review and meta-analysis. Journal of General Internal Medicine, 30(7), 1004-1012. https://doi.org/10.1007/s11606-015-3247-0

U.S. Census Bureau. (2023). QuickFacts: Paterson city, New Jersey. https://www.census.gov/quickfacts/patersoncitynewjerseyViola, D., Arno, P. S., Maroko, A. R., Schechter, C. B., Sohler, N., Rundle, A., Neckerman, K. M., & Maantay, J. (2013). Overweight and obesity: Can we reconcile evidence about supermarkets and fast food retailers for public health policy? Journal of Public Health Policy, 34(3), 424-438. https://doi.org/10.1057/jphp.2013.19

Wang, Y., Cai, L., Wu, Y., Wilson, R. F., Weston, C., Fawole, O., Bleich, S. N., Cheskin, L. J., Showell, N. N., Lau, B. D., Chiu, D. T., Zhang, A., & Segal, J. (2015). What childhood obesity prevention programmes work? A systematic review and meta-analysis. Obesity Reviews, 16(7), 547-565. https://doi.org/10.1111/obr.12277World Health Organization. (2021). Global Diabetes Compact. https://www.who.int/initiatives/the-who-global-diabetes-compact

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