Undiagnosed diabetes among immigrant and racial/ethnic minority adults in the United States: National Health and Nutrition Examination Survey 2011-2018

Determinants of health and mortality in undiagnosed diabetes: A nationally representative US adult, 2011-2020

AIM

This study examines the determinants of health and mortality associated with undiagnosed diabetes among a nationally representative sample of US adults.

METHODS

Data are from the National Health and Nutrition Examination Survey between 2011 and 2012 and 2019-2020. Diabetes status is categorized into three groups: undiagnosed diabetes, diagnosed diabetes, and no diabetes. Multiple logistic regression is used to estimate the association between undiagnosed diabetes and three domains of risk factors, including sociodemographic and health behavioral and clinical factors. Cox proportional hazards models are performed to compare excess mortality risk between the three groups.

RESULTS

Young adults, racial minorities, the foreign-born, and individuals with limited access to health care are more likely to be unaware of their diabetes. Moreover, adults without a family history of diabetes and chronic conditions have a higher chance of undiagnosed diabetes. No health behavioral factors are found to be associated with undiagnosed diabetes. Adults with undiagnosed diabetes have a lower risk of all-cause and cardiovascular disease mortality compared to those with diagnosed diabetes, but a higher risk of all-cause mortality than those with no diabetes.

CONCLUSION

Targeted public health approaches should address sociodemographic and clinical factors to reduce the burden of undiagnosed diabetes.

Vulnerability or Resiliency? A Two-Wave Panel Analysis of Social Network Factors Associated with Glycemic Levels among Mexican Immigrants in the Bronx, NYC, Before and During COVID-19

Latinos have high rates of type 2 diabetes mellitus (T2DM) yet are characterized as having health-promoting social networks. The impacts of COVID-19 on personal networks were complex, especially in urban areas with high proportion of immigrants such as the Bronx in NYC. Our objective was to test the extent to which network characteristics increase vulnerability or resiliency for glycemic control based on data gathered from Mexican-origin Bronx dwellers. We used two-wave panel study analyzing self-reported personal social networks (n=30participants; 600network members) and HbA1c levels via dried blood spots in 2019, before the COVID-19 pandemic, and in 2021, a time after initial lockdowns and when the pandemic was still ravaging the community of study. Regression models adjusted for individual-level variables including sociodemographic and health indicators (i.e., physical health including COVID-19 and mental health). We found that an increase in the proportion of network members with diabetes predicted an increase in participant's HbA1c levels from 2019 to 2021 (β=0.044, p < 0.05). Also, a greater proportion of network members consuming "an American diet" in 2019 predicted a decrease in participant's HbA1c levels (β=-0.028, p < 0.01), while a greater proportion of network members that encouraged participants' health in 2019 predicted an increase in participant's HbA1c levels (β=0.033, p < 0.05). Our study sheds light on specific social network characteristics relevant to individual diabetes outcomes, including potential longitudinal mechanistic effects that played out at the peak of the COVID-19 crisis.

Effects of Medicare eligibility and enrollment at age 65 among immigrants and US-born residents

BACKGROUND

Understanding the impacts of Medicare coverage among immigrants is of high policy importance, but there is currently limited evidence. In this study, we examined the effects of near universal access to Medicare coverage at age 65 years between immigrants and US-born residents.

METHODS

Using the 2007-2019 Medical Expenditure Panel Survey, we employed a regression discontinuity design, which exploits the eligibility for Medicare at age 65 years. Our outcomes were health insurance coverage, healthcare spending, access to and use of health care, and self-reported health status.

RESULTS

Medicare eligibility at age 65 led to significant increases in Medicare coverage among immigrants and US-born residents (74.6 [95% CI: 71.6-77.5] and 81.6 [95% CI: 80.5-82.7] percentage points). Medicare enrollment at age 65 decreased total healthcare spending and out-of-pocket spending by $1579 (95% CI: -2092 to 1065) and $423 (95% CI: -544 to 303) for immigrants and $1186 (95% CI: -2359 to 13) and $450 (95% CI: -774 to 127) for US-born residents. After Medicare enrollment at age 65, immigrants reported only limited improvements in overall access to and use of health care, but they reported significant increases in the use of high-value care (11.5 [95% CI: 6.8-16.2], 8.3 [95% CI: 6.0-10.6], 8.4 [95% CI: 1.0-15.8], and 2.3 [95% CI: 0.9-3.7] percentage points increase for colorectal cancer screening, eye examination for diabetes, influenza vaccine, and cholesterol measurement) and improvements in self-reported health (5.9 [95% CI: 0.9-10.8] and 4.8 [95% CI: 0.5-9.0] percentage points increase for good perceived physical and mental health). Medicare enrollment also increased prescription drug spending by $705 (95% CI: 292-1117), despite the unchanged use of prescription drugs. For US-born residents, use of high-value care, self-reported health, and prescription drug use and spending did not change substantially after Medicare enrollment.

CONCLUSION

Medicare has the potential to improve care among older adult immigrants.

Trends and Disparities in the Distribution of Outpatient Physicians' Annual Face Time with Patients, 1979-2018

BACKGROUND

Physician time is a valuable yet finite resource. Whether such time is apportioned equitably among population subgroups, and how the provision of that time has changed in recent decades, is unclear.

OBJECTIVE

To investigate trends and racial/ethnic disparities in the receipt of annual face time with physicians in the USA.

DESIGN

Repeated cross-sectional.

SETTING

National Ambulatory Medical Care Survey, 1979-1981, 1985, 1989-2016, 2018.

PARTICIPANTS

Office-based physicians.

MEASURES

Exposures included race/ethnicity (White, Black, and Hispanic); age (<18, 18-64, and 65+); and survey year. Our main outcome was patients' annual visit face time with a physician; secondary outcomes include annual visit rates and mean visit duration.

RESULTS

Our sample included n=1,108,835 patient visits. From 1979 to 2018, annual outpatient physician face time per capita rose from 40.0 to 60.4 min, an increase driven by a rise in mean visit length and not in the number of visits. However, since 2005, mean annual face time with a primary care physician has fallen, a decline offset by rising time with specialists. Face time provided per physician changed little given growth in the physician workforce. A racial/ethnic gap in physician visit time present at the beginning of the study period widened over time. In 2014-2018, White individuals received 70.0 min of physician face time per year, vs. 52.4 among Black and 53.0 among Hispanic individuals. This disparity was driven by differences in visit rates, not mean visit length, and in the provision of specialist but not primary care.

LIMITATION

Self-reported visit length.

CONCLUSION

Americans' annual face time with office-based physicians rose for three decades after 1979, yet is still allocated inequitably, particularly by specialists; meanwhile, time spent by Americans with primary care physicians is falling. These trends and disparities may adversely affect patient outcomes. Policy change is needed to assure better allocation of this resource.

Prevalence and factors associated with undiagnosed type 2 diabetes among adults in Iraq: analysis of cross-sectional data from the 2015 STEPS survey

OBJECTIVE

The purpose of the study was to assess the prevalence and correlates of undiagnosed type 2 diabetes (UT2D) among adults (aged 18 years and older) in Iraq.

DESIGN

Cross-sectional, population-based study.

SETTING

Nationally representative sample of general community-dwelling adult population in Iraq from the 2015 Iraq STEPS survey.

PARTICIPANTS

The sample included 3853 adults (mean age 41.8 years, SD=15.8), with complete fasting blood glucose values, from the 2015 Iraq STEPS survey.

OUTCOME MEASURES

Data collection included: (1) social and behavioural information, (2) physical parameters and blood pressure measurements and (3) biochemical measurements. UT2D was classified as not being diagnosed with T2D and fasting plasma glucose level ≥126 mg/dL. Multivariable multinomial and logistic regression was used to identify factors associated with UT2D.

RESULTS

The prevalence of UT2D was 8.1% and the prevalence of diagnosed T2D (DT2D) was 8.9%. Participants aged 50 years and older (adjusted relative risk ratio (ARRR): 2.11, 95% CI 1.30 to 3.43) and those with high cholesterol (ARRR: 1.54, 95% CI 1.05 to 2.24) had a higher risk of UT2D. Older age (≥50 years) (ARRR: 17.90, 95% CI 8.42 to 38.06), receipt of healthcare advice (ARRR: 2.15, 95% CI 1.56 to 2.96), history of cholesterol testing (ARRR: 2.17, 95% CI 1.58 to 2.99), stroke or heart attack (ARRR: 1.81, 95% CI 1.13 to 2.92), and high cholesterol (ARRR: 1.55, 95% CI 1.17 to 2.06) were positively associated with DT2D, and high physical activity (ARRR: 0.57, 95% CI 0.38 to 0.84) was negatively associated with DT2D. Higher than primary education (adjusted OR (AOR): 2.02, 95% CI 1.21 to 3.37) was positively associated with UT2D versus DT2D, while older age (≥50 years) (AOR: 0.12, 95% CI 0.06 to 0.25), healthcare advice (AOR: 0.45, 95% CI 0.29 to 0.70), and history of cholesterol screening (AOR: 0.37, 95% CI 0.24 to 0.58) were inversely associated with UT2D versus DT2D.

CONCLUSION

Almost one in ten adults in Iraq had UT2D, and various associated factors were identified that could be useful in planning interventions.

Radiomics-based machine learning (ML) classifier for detection of type 2 diabetes on standard-of-care abdomen CTs: a proof-of-concept study

PURPOSE

To determine if pancreas radiomics-based AI model can detect the CT imaging signature of type 2 diabetes (T2D).

METHODS

Total 107 radiomic features were extracted from volumetrically segmented normal pancreas in 422 T2D patients and 456 age-matched controls. Dataset was randomly split into training (300 T2D, 300 control CTs) and test subsets (122 T2D, 156 control CTs). An XGBoost model trained on 10 features selected through top-K-based selection method and optimized through threefold cross-validation on training subset was evaluated on test subset.

RESULTS

Model correctly classified 73 (60%) T2D patients and 96 (62%) controls yielding F1-score, sensitivity, specificity, precision, and AUC of 0.57, 0.62, 0.61, 0.55, and 0.65, respectively. Model's performance was equivalent across gender, CT slice thicknesses, and CT vendors (p values > 0.05). There was no difference between correctly classified versus misclassified patients in the mean (range) T2D duration [4.5 (0-15.4) versus 4.8 (0-15.7) years, p = 0.8], antidiabetic treatment [insulin (22% versus 18%), oral antidiabetics (10% versus 18%), both (41% versus 39%) (p > 0.05)], and treatment duration [5.4 (0-15) versus 5 (0-13) years, p = 0.4].

CONCLUSION

Pancreas radiomics-based AI model can detect the imaging signature of T2D. Further refinement and validation are needed to evaluate its potential for opportunistic T2D detection on millions of CTs that are performed annually.

Sick Days: Logical Versus Survey Identification of the Foreign-Born Population in the United States

The self-reported number of workdays missed due to injury or illness, or sick days, is a reliable measure of health among working-aged adults. Although sick days is a relatively underexplored health-related outcome in migration studies, it can provide a multidimensional understanding of immigrant wellbeing and integration. Current understandings of the association between migration status and sick days are limited for two reasons. First, in the United States, few nationally representative surveys collect migration status information. Second, researchers lack consensus on the most reliable approach for assigning migration status. We use the 2008 Survey of Income and Program Participation (SIPP) to examine sick days and draw comparisons between two methods for assigning migration status—a logical approach and a survey approach. The logical method assigns migration status to foreign-born respondents based on characteristics such as government employment or welfare receipt, while the survey approach relies on self-reported survey responses. Sick days among immigrants was correlated with and predicted by other health conditions available in the SIPP. Comparisons of sick days by migration status vary based on migration assignment approach. Lawful Permanent Residents (LPRs) reported more sick days than non-LPRs and appear less healthy when migration status is assigned using the logical approach. The logical approach also produced a gap in sick days between LPRs and non-LPRs that is not replicated in the survey approach. The results demonstrate that if migration status is not measured directly in the data, interpretation of migration status effects should proceed cautiously.

The association between type 2 diabetes and major depression in apnoeic individuals

Given the few studies available in the literature, the aim of this study was to investigate the association between type 2 diabetes and major depression in a large sample of apnoeic individuals. Demographic and polysomnographic data from 395 apnoeic individuals recruited from the clinical database of the Erasme Hospital Sleep Laboratory were analysed. Only individuals with a diagnosis of type 2 diabetes according to the diagnostic criteria of the American Diabetes Association at admission were included in the "diabetes" group. Logistic regression analyses were used to study the association between type 2 diabetes and major depression in apnoeic individuals. The prevalence of type 2 diabetes was 19.7% in our sample of apnoeic individuals. After adjusting for major confounding factors, multivariate logistic regression analyses demonstrated that unlike remitted major depression and mild major depression, only moderate to severe major depression was significantly associated with higher likelihood of type 2 diabetes in apnoeic individuals. In our study, we found that moderate to severe major depression is significantly associated with type 2 diabetes in apnoeic individuals, which seems to justify more systematic screening and adequate therapeutic management of this psychiatric disorder to allow better glycaemic control in this subpopulation at high risk of diabetic micro/macrovascular complications.

Supplementary Information

The online version contains supplementary material available at 10.1007/s41105-021-00359-0.

Disparities in diabetes between US-born and foreign-born population: using three diabetes indicators

We investigated disparities in diabetes between the US-born and foreign-born populations using three diabetes measures: diagnosed diabetes, undiagnosed diabetes, and total diabetes, either diagnosed or undiagnosed diabetes. We analyzed adults aged 30-84 years drawn from the National Health and Nutrition Examination Survey 2009-2018 (n = 21,390). Of cohorts in 2009-2018, foreign-born adults had significantly higher age-standardized prevalence of diagnosed (12.6% vs. 10.6%) and undiagnosed diabetes (4.5% vs. 2.6%), and total diabetes (17.1% vs. 13.2%) than US-born adults. Results from logistic and multinomial regressions adjusting for age, sex, race/ethnicity, limited access to healthcare and BMI showed that the foreign-born had significantly higher odds of total diabetes (OR: 1.25, 95% CI: 1.04-1.50) and undiagnosed diabetes (OR: 1.83, 95% CI: 1.44-2.32) compared to the US-born. There was no significant difference in diagnosed diabetes by nativity (OR: 1.12, 95% CI: 0.96-1.53). Our results show that foreign-born adults were at higher risk of diabetes than US-born adults, and the difference by nativity was largely attributable to BMI and racial/ethnic composition. In addition, we demonstrated the importance of choosing measures of diabetes in studying diabetes mainly due to the foreign-born group's high prevalence of undiagnosed diabetes, which biases the prevalence of diabetes downward when diagnosed diabetes is used.

Inappropriately sweet: Environmental endocrine-disrupting chemicals and the diabetes pandemic

Afflicting hundreds of millions of individuals globally, diabetes mellitus is a chronic disorder of energy metabolism characterized by hyperglycemia and other metabolic derangements that result in significant individual morbidity and mortality as well as substantial healthcare costs. Importantly, the impact of diabetes in the United States is not uniform across the population; rather, communities of color and those with low income are disproportionately affected. While excessive caloric intake, physical inactivity, and genetic susceptibility are undoubted contributors to diabetes risk, these factors alone fail to fully explain the rapid global rise in diabetes rates. Recently, environmental contaminants acting as endocrine-disrupting chemicals (EDCs) have been implicated in the pathogenesis of diabetes. Indeed, burgeoning data from cell-based, animal, population, and even clinical studies now indicate that a variety of structurally distinct EDCs of both natural and synthetic origin have the capacity to alter insulin secretion and action as well as global glucose homeostasis. This chapter reviews the evidence linking EDCs to diabetes risk across this spectrum of evidence. It is hoped that improving our understanding of the environmental drivers of diabetes development will illuminate novel individual-level and policy interventions to mitigate the impact of this devastating condition on vulnerable communities and the population at large.

Barriers to accessing preventive health care among African-born individuals in King County, Washington: A qualitative study involving key informants

Studies of African immigrant health in the U.S. have traditionally focused on infectious diseases. However, the rising burden of non-communicable diseases (NCDs) indicates the increasing importance of general preventive health care. As part of a series of community health events designed for African-born individuals in King County, Washington, we administered key informant interviews (KIIs) with 16 health event participants, medical professionals, and community leaders to identify barriers and facilitators to use of preventive health care among African-born individuals. We used descriptive thematic analysis to organize barriers according to the socio-ecological model. Within the individual domain, KII participants identified lack of knowledge and awareness of preventive health benefits as barriers to engagement in care. Within the interpersonal domain, language and cultural differences frequently complicated relationships with health care providers. Within the societal and policy domains, healthcare costs, lack of insurance, and structural racism were also reported as major barriers. Participants identified community outreach with culturally competent and respectful providers as key elements of interventions to improve uptake. In conclusion, African immigrant communities face several barriers, ranging from individual to policy levels, to accessing health services, resulting in substantial unmet need for chronic disease prevention and treatment. Community-centered and -led care may help facilitate uptake and engagement in care.