The Cascade of Diabetes Care in the Republic of the Marshall Islands: Investigation of the Gaps in Diabetes Screening and Management Open Access

Stadnik, Carlen A. (Spring 2020)

Permanent URL: https://etd.library.emory.edu/concern/etds/9g54xj700?locale=pt-BR%2A
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Abstract

Aims: The prevalence of diabetes in the Republic of Marshall Islands (RMI) has doubled in the past 25 years, yet there are few data regarding diabetes screening and self-management practices in RMI. We applied a Cascade of Care framework to understand diabetes detection and management among RMI adults.

Methods: Data were from RMI’s 2018 population-based Hybrid Survey (n=2,869 aged 18+). This survey combined questionnaire data with physical (height, weight, and blood pressure) and biochemical (fasting blood glucose and blood cholesterol) measurements to assess prevalence of diabetes and related risk factors in RMI. All descriptive analyses were performed in the total sample and by socio-demographic characteristics. Diabetes status was classified as previously diagnosed, newly diagnosed at the time of survey, or no diabetes. We examined the prevalence of NCD risk factors and morbidities by diabetes status. We also described four indicators of the diabetes Cascade of Care: diabetes awareness, receipt of treatment, controlled fasting blood glucose, and multiple risk-factor control. Engagement with care and self-management behaviors by diabetes status were also described. We estimated unadjusted and adjusted multiple logistic regression models to evaluate the association between selected socio-demographic characteristics and multiple risk-factor control.

Results: The prevalence of diabetes was 24.7% (95% CI: 23.1-26.3) in the total sample. The prevalence of previously diagnosed diabetes was 12.5% while the prevalence of newly diagnosed diabetes was 15.7%. Among those with prevalent diabetes (n=810), 44.4% were aware that they had diabetes, 8.3% were receiving treatment for diabetes, 12.6% had controlled fasting blood glucose, and 10.2% had controlled multiple risk factors. We observed significant bivariate associations of age, sex, region of residence, and education level with multiple risk factor control. In fully adjusted analyses, only urban region of residence (OR: 2.7, 95% CI: 1.2-6.0; ref=rural) was statistically significantly associated with multiple risk factor control.

Conclusion: The prevalence of diabetes in RMI is double the global average. Less than half of RMI adults with diabetes are aware of their disease status, and fewer than one in ten adults is being treated for diabetes. Findings motivate urgent attention for proactive prevention, screening, and management interventions for diabetes.

Table of Contents

Background 9

-Diabetes in the global context 9

-Diabetes in the US-affiliated Pacific Islands 10

-Historical context and the diabetes burden in The Republic of the Marshall Islands 11

-Marshallese cultural norms, beliefs, and perceptions 12

-Engagement in care and risk-factor control 13

-The Cascade of Care framework applied to diabetes 14

-Objectives 14

Methods 15

-Data source 15

-Sample selection 15

-Data collection 16

-Diabetes status 16

-Indicators of the diabetes care cascade 17

-Engagement with diabetes care 17

-Demographic characteristics and health risk factors 18

-Statistical analyses 18

Results 19

-Table 1. Socio-demographic characteristics of adults across the RMI population 19

-Table 2. Health risk factors and morbidities of the RMI population, stratified by diabetes diagnosis 19

-Figure 2. The cascade of diabetes care 24

-Table 3. Diabetes prevalence and diabetes care continuum among adults with Diabetes in RMI by socio-demographic factors 20

-Table 4. Engagement with care and self-management behaviors among adults with diabetes in RMI by diabetes awareness 22

-Figure 3. Diabetes care and control measures 24

-Table 5. Multiple logistic regression analysis of multiple risk-factor control by socio-demographic factors 23

Discussion 25

-Public health implications 25

-Strengths and limitations 25

-Remaining gaps in knowledge and future directions 26

-Conclusions 27

References 29

Figures 34

Tables 37

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