Preventing Chronic Disease最新文献

Prediabetes disproportionately affects racial and ethnic minority groups in Hawai'i. The National Diabetes Prevention Program lifestyle change program (National DPP LCP) decreases the risk of developing diabetes. However, enrolling and retaining participants is a challenge for program providers. This evaluation aimed to understand factors that influence racial and ethnic minority groups in Hawai'i to enroll in and complete the program. From 2018 through 2023, two federally qualified health centers (FQHCs) in rural Hawai'i administered 6 year-long cohorts. Trained lifestyle coaches, who were FQHC staff members, recruited participants and facilitated the evidence-based curriculum. In 2023, the evaluation team conducted semistructured interviews with 14 of the 40 enrolled participants (35%), all of whom were women aged 25 to 74 years. Six participants identified as Native Hawaiian or Other Pacific Islander and 3 as Filipino. Eight participants reported completing the program. We used qualitative methodology to analyze transcripts. We identified themes around motivators, barriers, facilitators, and suggestions for improvement. Recruitment by trusted individuals in their communities motivated participants to enroll. Caregiving and work obligations were attendance barriers for early withdrawers and graduates. Social support from lifestyle coaches and enrolled friends and family were facilitators for program completion. Suggestions included improving class availability and incorporating culturally relevant recipes. Barriers experienced by Native Hawaiian or Other Pacific Islander and Filipino participants were similar to those reported by racial and ethnic groups in other studies. Program providers in rural communities should use trusted individuals as lifestyle coaches and recruit family and friends, regardless of National DPP LCP eligibility, to reduce caregiving barriers and engage critical support systems to facilitate completion.

Purpose and objectives: The Diabetes Prevention Program (DPP), an effective evidence-based strategy to reduce the incidence of type 2 diabetes, has been widely implemented in various locations, including workplaces. However, most people do not remain engaged in the program for the recommended full year. Limited qualitative research exists around participant engagement in the workplace DPP. Our study aimed to explore participant engagement in the DPP delivered through the employer-based clinic (EBC) at a large technology company.

Intervention approach: The DPP was implemented through the EBC at a large technology company in Southern California, beginning in September 2019 by using in-person and virtual synchronous group classes before and during the COVID-19 pandemic.

Evaluation methods: Virtual focus groups with DPP participants from 2 inaugural cohorts were conducted via Zoom from October 2020 to February 2021. Data were analyzed by using inductive thematic analysis.

Results: Five focus groups with 2 to 3 participants in each (total n = 12) were conducted, 2 focus groups per cohort and 1 focus group with the group instructors. Barriers and facilitators to engagement in the DPP were grouped into thematic domains: Individual Drivers, Small Group Community, Workplace Setting, Integrated EBC, and the COVID-19 Pandemic. Results showed that prepandemic workplace demands (ie, meetings, travel) affected DPP participation, yet the group setting provided social support in the workplace to engage in and maintain healthy habits. With the move to a virtual synchronous offering during the pandemic, participants valued the group setting but expressed a preference for in-person meetings. Collectively, participant engagement was bolstered by shared buy-in and collaboration between the employer and the EBC.

Implications for public health: Our findings suggest that engagement in a workplace DPP can be supported by addressing workplace-specific barriers and gaining buy-in from employers. Delivering the DPP, in person and virtually, through an EBC has the potential to engage employees who have prediabetes.

Introduction: The high prevalence of mental disorders among adolescents calls for community-based and population-level prevention strategies. Diet is an important intervention target for primary prevention of mental disorders among adolescents. We used data from a large longitudinal study of Canadian adolescents (aged 14-18 y) to examine prospective associations between diet and mental health outcomes.

Methods: We estimated the effect of diet (ie, consumption of vegetables and fruit and sugar-sweetened beverages [SSBs]) at baseline on depressive symptoms, anxiety symptoms, and psychological well-being (measured by the Center for Epidemiologic Studies Depression Scale-Revised, Generalized Anxiety Disorder 7 scale, and Flourishing Scale, respectively) and at 1-year follow-up in a sample of 13,887 Canadian secondary school students who participated in the 2017-2018 and 2018-2019 cycles of the Cannabis, Obesity, Mental health, Physical activity, Alcohol, Smoking, and Sedentary (COMPASS) behavior study. We applied linear mixed-effects methods informed by a directed acyclic graph. Sensitivity analyses assessed the robustness of the effect estimates to unmeasured confounding variables.

Results: Baseline SSB consumption was associated with greater severity of depressive (β = 0.04; 95% CI, 0.01-0.06) and anxiety (β = 0.02; 95% CI, 0-0.05) symptoms, particularly among male students, and poorer psychological well-being (β = -0.03; 95% CI, -0.05 to -0.01) at follow-up. Baseline vegetables and fruit consumption was positively associated with psychological well-being (β = 0.06; 95% CI, 0.03-0.10) but not other mental health outcomes at follow-up.

Conclusion: Our results support the notion that diet should be part of comprehensive mental health prevention and promotion interventions to reduce the prevalence of mental health disorders among adolescents.

Introduction: Previous research suggests that rural-urban disparities in diabetes mortality, hospitalization, and incidence rates may manifest differently across US regions. However, no studies have examined disparities in diabetes prevalence by metropolitan residence and region.

Methods: We used data from the 2019-2022 National Health Interview Survey to compare diabetes status, socioeconomic characteristics, and weight status among adults in each census region (Northeast, Midwest, South, West) according to county metropolitan status of residence (large central metro, large fringe metro, small/medium metro, and nonmetro). We used χ² tests and logistic regression models to assess the association of metropolitan residence with diabetes prevalence in each region.

Results: Diabetes prevalence ranged from 7.0% in large fringe metro counties in the Northeast to 14.8% in nonmetro counties in the South. Compared with adults from large central metro counties, those from small/medium metro counties had significantly higher odds of diabetes in the Midwest (age-, sex-, and race and ethnicity-adjusted odds ratio [OR] = 1.24; 95% CI, 1.06-1.45) and South (OR = 1.15; 95% CI, 1.02-1.30). Nonmetro residence was also associated with diabetes in the South (OR = 1.62 vs large central metro; 95% CI, 1.43-1.84). After further adjustment for socioeconomic and body weight status, small/medium metro associations with diabetes became nonsignificant, but nonmetro residence in the South remained significantly associated with diabetes (OR = 1.22; 95% CI, 1.07-1.39).

Conclusion: The association of metropolitan residence with diabetes prevalence differs across US regions. These findings can help to guide efforts in areas where diabetes prevention and care resources may be better directed.

Cardiovascular disease (CVD) is the leading cause of illness and death in the US and is substantially affected by social determinants of health, such as social, economic, and environmental factors. CVD disproportionately affects groups that have been economically and socially marginalized, yet health care and public health professionals often lack tools for collecting and using data to understand and address CVD inequities among their populations of focus. The Health Equity Indicators for Cardiovascular Disease Toolkit (HEI for CVD Toolkit) seeks to address this gap by providing metrics, measurement guidance, and resources to support users collecting, measuring, and analyzing data relevant to their CVD work. The toolkit includes a conceptual framework (a visual model for understanding health inequities in CVD); a comprehensive list of health equity indicators (metrics of inequities that influence CVD prevention, care, and management); guidance in definitions, measures, and data sources; lessons learned and examples of HEI implementation; and other resources to support health equity measurement. To develop this toolkit, we performed literature scans to identify primary topics and themes relevant to addressing inequities in CVD, engaged with subject matter experts in health equity and CVD, and conducted pilot studies to understand the feasibility of gathering and analyzing data on the social determinants of health in various settings. This comprehensive development process resulted in a toolkit that can help users understand the drivers of inequities in their communities or patient populations, assess progress, evaluate intervention outcomes, and guide actions to address CVD disparities.

Introduction: Many mental disorders begin in early childhood. Without timely treatment, mental disorders experienced by young children can impair their learning ability and relationships with others, causing lifelong complications. However, not all children with a mental disorder in early childhood receive treatment.

Methods: Using data collected from 46,424 children aged 2 to 8 years in the 2 most recent cycles of the National Survey of Children's Health (2021 and 2022), we estimated the prevalence of having a mental disorder and investigated factors associated with young children not receiving mental health care when needed. All analyses were adjusted for survey weights to account for the complex sampling design and nonresponse biases in generating nationally representative estimates.

Results: In 2021 and 2022, 19.0% of US children aged 2 to 8 years had 1 or more mental disorders. Of these children, 9.1% reported not receiving any needed health care in the previous 12 months, and of these, 45.8% reported not receiving mental health services when needed. The primary reasons for not receiving needed health care were problems getting an appointment (72.1%), issues related to cost (39.3%), and services needed not being available in the area (38.5%). Poor experiences with health care providers were consistently associated with not receiving needed mental health services among children with mental disorders.

Conclusion: Our findings suggest a strong link between health care factors and not receiving needed mental health services among US children with a mental disorder in early childhood. In addition to increasing the availability of mental health services and expanding health insurance coverage, future public health efforts should prioritize enhancing patients' experiences with health care providers.

Introduction: Stroke, a leading cause of illness, death, and long-term disability in the US, presents with significant disparities across the country, most notably in southeastern states comprising the "Stroke Belt." This study intended to identify differences between Stroke Belt states (SBS) and non-Stroke Belt states (NSBS) in terms of prevalence of stroke, sociodemographic and behavioral risk factors, and health-related quality of life (HRQOL).

Methods: We analyzed data from the 2019 Behavioral Risk Factor Surveillance System to compare demographic characteristics, risk factors, physical activity adherence, functional independence, and HRQOL among stroke survivors in SBS and NSBS.

Results: Of 18,745 stroke survivors, 4,272 were from SBS and 14,473 were from NSBS. Stroke was more prevalent in SBS (odds ratio [OR] = 1.39; 95% CI, 1.35-1.44; P < .001), with significant differences by age, sex, and race and ethnicity, except for Hispanic ethnicity. Selected stroke risk factors were more common in every category in SBS. Stroke survivors in SBS were less likely to meet physical activity guidelines for aerobic (OR = 0.77; 95% CI, 0.69-0.86; P < .001) and aerobic and strengthening combined (OR = 0.77; 95% CI, 0.70-0.86; P < .001) activities. Stroke survivors in SBS were more likely to not meet either physical activity guideline (OR = 1.31; 95% CI, 1.22-1.41; P < .001).

Conclusions: Living in SBS significantly increased the odds of stroke occurrence. Stroke survivors from SBS reported lower HRQOL and insufficient physical activity as well as lower functional independence. Specific strategies are needed for residents of SBS, with a focus on policies and primary and secondary prevention practices across healthcare professions.

Introduction: Mental health conditions and poor oral health outcomes share bidirectional links, and both are linked to factors related to socioeconomic position (SEP). We used nationally representative survey data to describe the complex interplay of SEP, mental health, oral health behaviors, dental treatment seeking, and oral health.

Methods: We used data from the 2022 State of Oral Health Equity in America survey, which collects data from US adults on prior depression diagnosis and current depressive symptoms via the Patient Health Questionnaire-9 and demographic characteristics (age, sex/gender, race, ethnicity), SEP (education, income, employment, home ownership, dental insurance), oral health behaviors (brushing and flossing frequency), dental treatment seeking (time since last visit, plans for visit in the coming year), and self-rated oral health (feeling self-conscious due to poor oral health, having symptoms of poor oral health). We used structural equation modeling to identify latent variables and fit the path analytic models.

Results: In the total sample (N = 5,682), SEP was significantly associated with dental treatment seeking (standardized parameter estimate [SE] = 0.55 [0.05]), oral health behaviors (standardized parameter estimate [SE] = 0.34 [0.04]), and mental health (standardized parameter estimate [SE] = 0.59 [0.05]). These factors, in turn, were significantly associated with self-rated oral health (estimates ranging from 0.20 to 0.54, SEs ranging from 0.04 to 0.05).

Conclusion: SEP, which involves several major social determinants of health, is directly associated with mental health and indirectly associated with self-rated oral health status, with mental health modifying the relationship between SEP and self-rated oral health. Findings emphasize the need to integrate medical, dental, and behavioral health with the goal of providing comprehensive person-centered care.

Introduction: Multimorbidity - having 2 or more chronic diseases - is a national public health concern that entails burdensome and costly care for patients, their families, and public health programs. Adults residing in socially deprived areas often have limited access to social and material resources. They also experience a greater multimorbidity burden.

Methods: We conducted a retrospective cohort analysis of electronic health record (EHR) data from 678 community-based health centers (CHCs) in 27 states from the Accelerating Data Value Across a National Community Health Center (ADVANCE) Network, a clinical research network, from 2012-2019. We used mixed-effects Poisson regression to examine the relationship of area-level social deprivation (eg, educational attainment, household income, unemployment) to chronic disease accumulation among a sample of patients aged 45 years or older (N = 816,921) residing across 9,362 zip code tabulation areas and receiving care in safety-net health organizations.

Results: We observed high rates of chronic disease among this national sample. Prevalence of multimorbidity varied considerably by geographic location, both within and between states. People in more socially deprived areas with Social Deprivation Index (SDI) scores in quartiles 2, 3, and 4 had greater initial chronic disease counts - 17.1%, 17.7%, and 18.0%, respectively - but a slower rate of accumulation compared with people in the least-deprived quartile. Our findings were consistent for models of the composite SDI and those evaluating disaggregated measures of area-level educational attainment, household income, and unemployment.

Conclusion: Social factors play an important role in the development and progression of multimorbidity, which suggests that an assessment and understanding of area-level social deprivation is necessary for developing public health strategies to address multimorbidity.