Assessment 1: Identifying Community Health Needs
Name
Capella University
NURS-FPX 5003
Professor’s Name
May, 2024
Identifying Community Health Needs
Understanding community health needs in California involves examining a diverse range of demographic data to identify prevalent health concerns. Through data measurement and analysis, we aim to uncover patterns and trends that highlight the impact of diabetes on different populations across the state. This data-driven approach is crucial for developing targeted health promotion and disease prevention strategies tailored to the unique needs of Californians affected by diabetes. As we navigate through demographic reports and governmental data, our focus is on linking health concerns to specific demographic groups within California. By identifying highly impacted subgroups, we can better address the most significant health needs and ensure our efforts are targeted and effective in improving the overall health and wellness of the communities we serve.
Demographic Characteristics
California, being one of the most populous states in the U.S., exhibits a diverse demographic makeup with significant implications for diabetes prevalence. According to recent data from the California Department of Public Health (CDPH), the state’s population is predominantly composed of individuals of White, Hispanic, Asian, and Black or African American descent. Among these groups, there are notable variations in the prevalence of diabetes (Moriarty, 2020).
In terms of ethnic breakdown, the CDPH reports that approximately 9.8% of Whites in California are affected by diabetes. This is followed by a higher prevalence among Hispanic individuals, with around 13.9% affected by diabetes. Asians in California show a diabetes prevalence of approximately 8.2%, while the Black or African American population experiences a higher prevalence at about 13.2% (Divers et al., 2020). These statistics underscore the importance of understanding demographic factors in assessing the burden of diabetes within different racial and ethnic communities.
Moreover, when considering the broader demographic makeup of California’s population, it’s essential to recognize the impact of socioeconomic factors. Data from the California Health Interview Survey (CHIS) highlights disparities in diabetes prevalence based on income levels and educational attainment (Cleveland et al., 2023). People with limited income and educational attainment often experience elevated diabetes rates, indicating a need for targeted interventions and healthcare initiatives to address these disparities.
The demographic characteristics of diabetes in California reveal distinct patterns across ethnic groups and socioeconomic strata. Understanding these demographics is crucial for developing effective public health strategies, healthcare policies, and community interventions aimed at preventing and managing diabetes in diverse populations across the state.
Population Related Patterns
Age-related Patterns
One significant pattern related to diabetes prevalence is age. Information sourced from the Centers for Disease Control and Prevention (CDC) reveals that the elderly population, particularly those aged 65 and above, have a higher prevalence of diabetes compared to younger age groups (Team, 2020). Diabetes prevalence tends to increase with age. In California, adults aged 45-64 have the highest prevalence of diabetes at 13.7%, followed by those aged 65 and older at 22.1%, according to the CDPH (Kang et al., 2020). This pattern is attributed to factors such as age-related physiological changes, longer exposure to risk factors like obesity and sedentary lifestyles, and potential genetic predispositions.
Ethnicity-related Patterns
Another notable pattern is observed in ethnic disparities regarding diabetes. For instance, Hispanic and Black or African American populations in California exhibit higher rates of diabetes compared to Whites and Asians. Hispanic or Latino adults in California have a higher prevalence of diabetes compared to other racial/ethnic groups. The BRFSS data shows that 12.7% of Hispanic or Latino adults have diabetes, while the prevalence among White adults is 8.7% (Adam et al., 2021). This pattern reflects complex interactions between genetic factors, cultural practices, socioeconomic status, access to healthcare, and environmental influences that contribute to varying diabetes prevalence among different ethnic groups.
Gaps in Available Data
Despite the wealth of data on diabetes prevalence and related factors, there are notable gaps that could impact the understanding of trends and effective interventions. One gap is the lack of comprehensive data on diabetes subtypes and complications among different population groups (Ali et al., 2021). Comprehensive information regarding type 1 and 2 diabetes, gestational diabetes, and associated complications is crucial for developing customized prevention and treatment plans.
Another gap is the limited data on diabetes prevalence in specific geographic regions within California. While statewide data provide valuable insights, localized data at the county or community level are necessary for targeted interventions and resource allocation. Improved data collection efforts and collaboration between healthcare institutions and public health agencies are needed to fill these gaps and enhance diabetes surveillance and management strategies.
Impact of Diabetes on the Specific Groups
Hispanic or Latino Community
Within the Hispanic or Latino population, individuals of Mexican descent have a particularly high prevalence of diabetes. According to the Centers for Disease Control and Prevention (CDC), individuals of Mexican American descent have nearly double the likelihood of being identified with diabetes compared to non-Hispanic White individuals (Morales et al., 2020).
Older Adults
Among older adults aged 65 and above, diabetes not only poses a significant health risk but also contributes to complications such as cardiovascular diseases, kidney problems, and vision impairment (Tang et al., 2020). This underscores the importance of tailored healthcare strategies for this age group to manage and prevent diabetes-related complications effectively.
By analyzing demographic data and understanding specific population patterns, healthcare professionals can target interventions and allocate resources effectively to tackle the effects of diabetes on diverse populations within the community or state population.
Communication of Demographic Data and Health Needs
When communicating demographic data and health needs related to diabetes to various audiences, clarity and understanding are crucial. Use plain language and avoid jargon, especially when addressing non-medical audiences (Gainey et al., 2022). For instance, instead of using complex medical terms, explaining concepts in simple terms like “blood sugar levels” instead of “glycemic index” can enhance comprehension. Visual aids such as charts or graphs can also be helpful, providing a clear visual representation of data trends and health disparities among different demographic groups.
Another important approach is tailoring the communication to the specific audience. For example, when addressing policymakers or healthcare administrators, focusing on the economic impact of diabetes and the potential cost savings of preventive measures can be persuasive (Burgette et al., 2020). On the other hand, when communicating with community members, highlighting the personal health benefits of lifestyle changes or early detection can be more impactful. Engaging in two-way communication channels, such as community forums or feedback sessions, allows for active participation and ensures that the message is relevant and resonates with the target audience’s needs and concerns.
NURS FPX 5003 Assessment 1 : Identifying Community Health Needs Conclusion :
In conclusion, addressing community health needs, particularly concerning diabetes prevalence, requires a multifaceted approach that integrates clear communication strategies, targeted interventions, and collaboration among healthcare professionals and community stakeholders. By leveraging accessible language, visual aids, and tailored messaging, healthcare organizations can effectively convey demographic data and health needs to diverse audiences, fostering understanding and engagement. Furthermore, proactive measures aimed at promoting health literacy, preventive care, and equitable access to resources are essential for mitigating the impact of diabetes on vulnerable populations and improving overall community health outcomes. This research underscores the significance of strategic communication and evidence-based interventions in addressing complex public health challenges like diabetes.
NURS FPX 5003 Assessment 1 : Identifying Community Health Needs References :
Adam, E. E., White, M. C., & Saraiya, M. (2021). US hysterectomy prevalence by age, race and ethnicity from BRFSS and NHIS. Cancer Causes & Control, 33(1), 161–166. https://doi.org/10.1007/s10552-021-01496-0
Ali, M. K., Pearson, J., Selvin, E., & Gregg, E. W. (2021). Interpreting global trends in type 2 diabetes complications and mortality. Diabetologia, 65(1), 3–13. https://doi.org/10.1007/s00125-021-05585-2
Burgette, J. M., Vujicic, M., Booth, M., Meltzer, D., Best, T. J., Neill, J., Conicella, M. L., Joskow, R. W., & Chalmers, N. I. (2020). Advancing oral health policy through persuasive messaging and effective research measures. Journal of Public Health Dentistry, 81(1), 77–83. https://doi.org/10.1111/jphd.12422
Cleveland, J. C., Espinoza, J., Holzhausen, E. A., Goran, M. I., & Alderete, T. L. (2023). The impact of social determinants of health on obesity and diabetes disparities among Latino communities in Southern California. BMC Public Health, 23(1). https://doi.org/10.1186/s12889-022-14868-1
Divers, J., Mayer, E. J., Lawrence, J. M., Isom, S., Dabelea, D., Dolan, L., Imperatore, G., Marcovina, S., Pettitt, D. J., Pihoker, C., Hamman, R. F., Saydah, S., & Wagenknecht, L. E. (2020). Trends in incidence of Type 1 and Type 2 Diabetes among youths — Selected counties and Indian reservations, United States, 2002–2015. Morbidity and Mortality Weekly Report, 69(6), 161–165. https://doi.org/10.15585/mmwr.mm6906a3
Gainey, K. M., Smith, J., McCaffery, K., Clifford, S., & Muscat, D. M. (2022). What author instructions do health journals provide for writing plain language summaries. The Patient: Patient-Centered Outcomes Research, 16(1), 31–42. https://doi.org/10.1007/s40271-022-00606-7
Kang, M., Horman, S. F., Taplitz, R. A., Clay, B., Millen, M., Sitapati, A., Myers, F. E., McDonald, E. C., Abeles, S. R., Wallace, D. R., Stous, S., & Torriani, F. J. (2020). Public health role of academic medical center in community outbreak of hepatitis A, san diego county, California, USA. Emerging Infectious Diseases, 26(7), 1374–1381. https://doi.org/10.3201/eid2607.191352
Morales, J., Glantz, N., Larez, A., Bevier, W., Conneely, M., Fan, L., Reed, B., Alatorre, C., Paczkowski, R., Ahmed, T., Mackenzie, A., Duncan, I., & Kerr, D. (2020). Understanding the impact of five major determinants of health (genetics, biology, behavior, psychology, society/environment) on type 2 diabetes in U.S. Hispanic/Latino families. BMC Endocrine Disorders, 20(1). https://doi.org/10.1186/s12902-019-0483-z
Moriarty, L. F. (2020). Public health responses to COVID-19 outbreaks on cruise ships worldwide. Morbidity and Mortality Weekly Report, 69. https://doi.org/10.15585/mmwr.mm6912e3
Tang, O., Matsushita, K., Coresh, J., Sharrett, A. R., McEvoy, J. W., Windham, B. G., Ballantyne, C. M., & Selvin, E. (2020). Mortality implications of prediabetes and diabetes in older adults. Diabetes Care, 43(2), 382–388. https://doi.org/10.2337/dc19-1221
Team, C. R. (2020). Preliminary estimates of the prevalence of selected underlying health conditions among patients with coronavirus disease 2019 in United States. Morbidity and Mortality Weekly Report, 69(13), 382–386. https://www.jstor.org/stable/26917081
