OBJECTIVE

This study examined the incidence of diabetes-related hospital admissions and described the characteristics among youth and emerging adults with type 1 (T1D) and type 2 diabetes (T2D) in California.

RESEARCH DESIGN AND METHODS

A retrospective study was conducted using the statewide inpatient database during the years 2014–2018. Individuals aged 13–24 years hospitalized with diabetic ketoacidosis (DKA) or severe hypoglycemia (SH) were recorded. Demographic characteristics and health measures among youth (ages 13–18) and young adults (ages 19–24) were compared.

RESULTS

A total of 34,749 admission encounters for T1D and 3,304 for T2D were analyzed. Hospitalization rates significantly increased with age during the transition to adulthood, from 70/100,000 California population at age 17 to 132/100,000 at age 19 in T1D. Higher hospitalization rates were demonstrated in young adults than in youth in T1D, and the rate was significantly higher in Black young adults (23.9%) than in youth (12.0%) among the age-adjusted population with diabetes (P < 0.0001). More young adults admitted were on public insurance, and approximately half were from the lowest income quartile. No difference was observed in hospital length of stay; however, hospital charges were higher among young adults. Young adults were three times more likely to be admitted for severe conditions.

CONCLUSIONS

We demonstrated a significant rise in hospital admission during the transition period in individuals with T1D. There were significantly more Black young adults who were on public insurance and had lower socioeconomic status. Our findings suggest that the health care system fails many emerging adults with diabetes, particularly for people of color, and that improving medical transition is crucial.

As adolescents with diabetes transition to adulthood, they may demonstrate poorer adherence to treatment regimens and may be vulnerable to complications such as diabetic ketoacidosis (DKA) or severe hypoglycemia (SH). The Type 1 Diabetes (T1D) Exchange Clinic Registry revealed that only 17% of adolescents (ages 13–17) and 14% of emerging adults (ages 18–25) are currently reaching American Diabetes Association (ADA)-recommended HbA1c targets (1). DKA is a diabetes emergency associated with high morbidity and mortality (2). It is a hallmark of T1D but is increasingly recognized in patients with type 2 diabetes (T2D). The U.S. Centers for Disease Control and Prevention (CDC) reported that age-adjusted hospitalizations for DKA among children and adults decreased 1.1% per year from 2000 to 2009 but increased 6.3% per year from 2009 onward in the U.S. (3). Several epidemiological studies have reported that hospitalization rates have increased worldwide, particularly in emerging adults (4,5). However, limited data are available in the state of California to study the rates of hospitalization and the characteristics among youth and young adults with both types of diabetes.

During childhood and adolescence, there is a gradual shift from diabetes care supervised by parents and other adults to self-care management. A transition period between pediatric and adult care often arises in later adolescence, and this developmental stage of life is termed “emerging adulthood” from the late teens through the 20s. There is a broad consensus that a lack of effective transition from pediatric to adult diabetes care may contribute to fragmentation in health care, decreased frequency of clinical follow-up, and adverse outcomes in young adults with diabetes. A number of important factors have been identified as risk factors for these poor outcomes during emerging adulthood, including loss of health insurance coverage, increased risk-taking behaviors, and difficulty coping with added responsibilities (6,7).

There are often gaps in health insurance during this period, and lack of access to adequate health care continues to be a significant barrier for the emerging adult population, particularly in the state of California. California Children’s Services (CCS) is a supplemental state medical insurance for low-income children with chronic medical conditions, including diabetes. As part of the program, children with T1D are eligible for devices such as insulin pumps and continuous glucose monitors (CGM). However, this program only supports children up to 21 years old, and additional criteria are often required to get the devices approved beyond age 21. In addition, CGMs are currently not covered by Medi-Cal, California’s Medicaid program. Thus it is not unexpected to find that children and young adults of lower socioeconomic status with lack of insurance coverage consistently demonstrated lower rates of CGM usage than those of higher socioeconomic status (8).

Given that individuals in the transition period to adulthood have had the highest rates of underinsurance or uninsurance and may lose CGM coverage after aging out of CCS, the reforms to expand CGM coverage to adults on Medi-Cal should be of particular benefit to emerging adults with diabetes in California. Thus, our study aims to provide local data on hospitalization rates in emerging adults with diabetes with the goal to inform efforts to improve health outcomes and prevent complications for vulnerable young adults during this challenging transition to independence.

### Date Sources

This was a retrospective cohort study using the inpatient database from the California Office of Statewide Health Planning and Development (OSHPD) during the years 2014–2018. Data were abstracted from facility-level utilization data on health care services from hospitals and health care facilities across the state of California. We identified all hospitalizations among individuals aged 13–24 whose primary diagnosis was DKA, hypoglycemia, or a closely related condition, such as nonketotic hyperglycemia, diabetes with hyperosmolarity, or diabetes with coma, with either T1D or T2D, using International Classification of Diseases (ICD) codes (Supplementary Material). These hospitalizations were referred to as “diabetes-related hospitalizations.” We excluded drug-induced hyperglycemia, monogenic diabetes, and gestational diabetes.

### Outcomes

Our primary outcome was the age-specific annualized diabetes-related hospitalization rates in individuals with either type of diabetes and whether there was any difference during the transition period. We averaged data for all study years. To calculate the DKA hospitalization rates, we used the estimated age-specific population in state of California as the denominator. We also estimated the age-specific population by race to calculate the race-specific hospitalization rates. Population data were collected from the U.S. Census Bureau, Population and Housing Unit Estimates in 2018 (9). In addition, we extrapolated the estimated age-specific numbers of patients with T1D in California from the ADA and the CDC to calculate the rates of hospitalization among the population with T1D (10,11). However, T2D data in youth were not available from existing national databases.

We defined two subgroups, youth (ages 13–18) and young adult (ages 19–24) in this cohort study. We calculated the diabetes-related hospitalization rates and evaluated the differences in demographic characteristics between the two groups. As a proxy for socioeconomic status, we used the median income of the patient’s ZIP code of residence (categorized into quartiles) and insurance type (public vs. private). ZIP code–estimated incomes were based on the American Community Survey (ACS) in 2016 (9). Patients were categorized based on the ICD codes into three disease severities: mild, moderate, and severe. Uncomplicated DKA or hypoglycemia was categorized as mild disease, and DKA with uncontrolled diabetes or with complications was categorized as moderate disease. Severe disease was defined as the presence of coma or need for intensive care.

No patients were involved in setting the research questions, in developing plans for design, interpretation, or implementation of the study. There were no plans to disseminate the results of the research to patient communities. Data were deidentified, and the study was deemed exempt from review by the University of California, San Francisco Institutional Review Board.

### Statistical Analysis

Demographic characteristics in the study are summarized using descriptive statistics. Sociodemographic characteristics were compared by using χ2 test for categorical variables and the t test for continuous variable for each diabetes type. We used two age categories: 13–18 years (youth) and 19–25 years (young adults). All analyses were performed separately for T1D and T2D, with a significance level of P < 0.05.

We identified and analyzed 38,053 hospital admission encounters in both youth and young adults with DKA or SH in California between years 2014 and 2018. There were 34,749 encounters for T1D and 3,304 for T2D. Mean ages were 17.3 ± 4.6 years in T1D and 17.9 ± 4.6 years in T2D. Males made up a larger percentage of those hospitalized with T2D than females (56.1%), whereas those with admitted with T1D were a slightly more likely to be female (53.1%). Youth and young adults admitted with T2D were disproportionately of Hispanic ethnicity compared with those with T1D (57.5% vs. 39.3%). A larger share of admitted youths and young adults (74.3%) with T2D resided in lower-income ZIP codes compared with ∼40% in T1D.

The diabetes-related hospitalization rates increased steadily with age, with a significant rise during the transition to adulthood, from 70/100,000 California population at age 17, increasing to 132/100,000 at age 19 in T1D (Fig. 1). Based on the age-specific diabetes population, the rates of hospital admission were 22.9/100 at age 17 and almost doubled to 43/100 at age 19 (Fig. 2). In contrast, the diabetes-related hospitalization rates by age for the T2D population remained similar during the transition period, ∼11/100,000 California population at age 17 to 10/100,000 at age 19, and rose slightly to 13/100,000 at age 23.

Figure 1

Diabetes-related hospitalization rates by age among the California population.

Figure 1

Diabetes-related hospitalization rates by age among the California population.

Figure 2

Diabetes-related hospitalization rates by age among the T1D population. DM, diabetes mellitus.

Figure 2

Diabetes-related hospitalization rates by age among the T1D population. DM, diabetes mellitus.

For both types of diabetes, we demonstrated higher hospitalization rates in young adults than in youth. Although the White population predominated in our cohort, there were disproportionately higher hospital admission rates in non-White minorities in both youth and young adults with T1D. Among the T1D population in California, there were 23.9 Black young adults and 3.4 White young adults per 100 hospital admissions admitted over the study years. This pattern was similar among the youth group (12.0 Black vs. 1.8 White per 100 hospital admissions). We observed that the rates of hospital admission were significantly higher in Black young adults than in Black youth (23.0 and 12.0 per 100 hospital admissions, respectively) among the age- and race-adjusted population with diabetes (P < 0.0001). More young adults were on public insurance, 65.0 young adults versus 45.1 youth per 100 hospital admissions in T1D. A similar trend was seen in T2D, with 50.4 youth rising to 68.0 young adults per 100 hospital admissions (P < 0.0001). The percentage of young adults without insurance was five times higher than youth in T2D. Diabetes-related hospitalizations were more frequent in lower-income ZIP codes and ∼41.6 and 48.8 cases per 100 hospital admissions were from the lowest income quartile in T1D and T2D, respectively (Table 1).

Table 1

Characteristics of youth and young adults in T1D and T2D

T1DT2D
Age, years 15.8 21.6  15.6 21.8
Sex, % female 54.1 53.0 0.1018 47.7 41.0 0.0003
Ethnicity and race, %
Hispanic 40.1 47.0 <0.0001 64.1 52.6 <0.0001
Non-Hispanic, White 36.0 37.6  12.7 21.3
Non-Hispanic, Black 14.2 15.6  11.9 18.2
Income quartile, %
<25th 40.0 41.6 <0.0001 47.1 48.8 <0.0001
25–50th 25.1 26.4  25.5 26.8
50–75th 20.5 18.5  18.0 15.3
>75th 13.8 10.1  9.2 6.1
Insurance types, %
Public 45.1 64.0 <0.0001 50.4 68.4 <0.0001
Commercial 35.7 29.0  22.5 22.5
Self-pay 1.6 2.4  0.8 4.1
Others 17.6 4.6  26.3 5.0
T1DT2D
Age, years 15.8 21.6  15.6 21.8
Sex, % female 54.1 53.0 0.1018 47.7 41.0 0.0003
Ethnicity and race, %
Hispanic 40.1 47.0 <0.0001 64.1 52.6 <0.0001
Non-Hispanic, White 36.0 37.6  12.7 21.3
Non-Hispanic, Black 14.2 15.6  11.9 18.2
Income quartile, %
<25th 40.0 41.6 <0.0001 47.1 48.8 <0.0001
25–50th 25.1 26.4  25.5 26.8
50–75th 20.5 18.5  18.0 15.3
>75th 13.8 10.1  9.2 6.1
Insurance types, %
Public 45.1 64.0 <0.0001 50.4 68.4 <0.0001
Commercial 35.7 29.0  22.5 22.5
Self-pay 1.6 2.4  0.8 4.1
Others 17.6 4.6  26.3 5.0

Individuals with diabetes-related hospitalization did have worse outcomes and higher financial burdens. We observed that more young adults were admitted for moderate or severe conditions with coma than youth in both T1D and T2D. In T1D, there were 78.8 moderate or severe cases per 100 hospital admissions among young adults and 71.0 cases among youth. On the other hand, we observed 79.0 moderate or severe cases per 100 hospital admissions among young adults, which was double the number among youth in T2D (30.7 cases per 100 hospital admission). The hospitalization rates of severe DKA increased with age in T1D and significantly increased from 3 in 100,000 at age 17 to 12 in 100,000 population at age 19 (P < 0.0001). However, no difference was observed in the population with T2D. Only a small number of cases were admitted for severe hypoglycemia in T1D in our cohort. Mean hospital length of stay was similar between both types of diabetes; however, the hospital charges per visit were significantly higher among young adults in both T1D ($41,370 in young adults vs.$36,160 in youth) and T2D ($37,218 in young adults vs.$30,991 in youth, P < 0.0001).

Diabetes-related hospitalization rates increased with age during emerging adulthood in the state of California. Particularly, the rates of hospitalization were higher among transitioning young adults of color, who were more likely to be publicly insured and reside in low-income ZIP codes in both T1D and T2D populations. The disparity widened after age 18, implicating socioeconomic factors as important contributors to the rising trend.

Based on the statewide data, we found the difference in diabetes prevalence was less likely to explain the differences in diabetes-related hospitalization we observed. In 2016, the prevalence of adults diagnosed with T1D was 0.55% and that of T2D was 8.6%. Approximately 0.25% of Americans younger than age 20 are estimated to have a diagnosis of diabetes of either type (1215). The peak incidence of new-onset T1D usually occurred in children between 4 and 7 years and in youth ages 10–14 years. In our cohort, we observed a rapid increase during the transitioning period, which then became steady in the mid-20s, a pattern that could not be explained by the incidence of new-onset diabetes diagnoses.

One possible reason for the rising hospitalization during the transitioning period was that emerging adults in California lacked effective transition from pediatric to adult diabetes care and frequently underwent health insurance changes, resulting in changes of care providers (pediatric vs. adult), decreased frequency of clinical follow-up, or even loss of insurance after transitioning into adulthood (16). Studies demonstrated that a large proportion of youth and young adults with T1D experienced substantial barriers (e.g., access to care, not having a regular provider, and not receiving contextual care [care that takes into account personal and family context]) (17,18). Youth and young adults often age out from their parental insurances and CCS coverage, which might contribute to the sharp rise in diabetes-related hospitalization. Underinsurance reduces the use of diabetic specialty care, and underinsured patients are more likely to visit the emergency department for diabetes-related complications. In addition, high prescription drugs costs may reduce insulin adherence and even lead to discontinuation of insulin therapy. An increasing number of studies have shown that use of technology devices, such as pump and CGM, are significantly impacted by the insurance types (19,20).

Data from the adult and pediatric populations show that CGM use has been associated with a reduction in HbA1c levels and a significant reduction in time spent in hypoglycemia. The availability of real-time CGM data allows the individual or caregiver to be aware of dangerously high or low blood glucose levels and adjust diet and medications to avert adverse hyperglycemic or hypoglycemic events (21). The ADA stated the CGM are essential tools to assess therapy and detect incipient hypoglycemia and modified its recommended age range from prescribing CGM from 25 years of age to starting at age 18 years in 2018 (22). Studies revealed a CGM dose-dependent improvement in HbA1c across all age groups, including adolescents and emerging adults, demonstrating the effectiveness of this technology in those who use it consistently (2325). In addition, CGM nearly eliminates the need for finger sticks and has been shown to be superior to self-monitoring of blood glucoses. As part of the CCS program, children and young adults with T1D are eligible for technology devices. However, young adults are at risk for losing coverage once they age out of CCS coverage. Those devices are not covered under Medi-Cal and only some under Medicaid after the Affordable Care Act. Last year, the bill to add CGM and related supplies to the schedule of Medi-Cal benefits for diabetes treatment was vetoed by Governor Gavin Newsom due to costs to the General Fund (26). Other studies have shown that individuals with lower socioeconomic status and lack of insurance coverage consistently demonstrated lower rates of CGM use than those of higher socioeconomic status (8). Furthermore, studies reported that the use of technology among Caucasians is higher than its use in other racial and ethnic groups, particularly African Americans (20,2729,). We speculate the low CGM coverage for all people with diabetes under public insurance is related to the potential high cost purchasing all of the supplies. However, it may not be actually cost-effective, because the cost of diabetes supplies, such as CGMs, account for only 1.1% of the total cost of diabetes, while the costs of treating complications and lost productivity accounts for 73.1% of total diabetes costs (30). Both expenses can actually be reduced with widespread CGM use. Thus, CGMs should not be the focus of cost-cutting efforts.

To our knowledge, this is the first study with a large sample size looking at diabetes-related hospitalization rates in youth and young adults in California. There were a few limitations of the study. We based the type of diabetes classification on the reported ICD codes, which might have the possibility of inaccurate or miscoding. In addition, we only captured the numbers of hospital encounters rather than the numbers of patients, which meant that one patient might have multiple admissions. Thus, we might overestimate the rates of diabetes-related hospitalizations. However, we believed that given such a large sample size, the differences would be less significant.

Second, we were not able to exclude admission for a new-onset diagnosis due to the limitation of the diagnostic codes. Thus, it might also overestimate the hospitalization rates because new-onset T1D often presents in DKA. However, national data demonstrated that the peak incidence of new-onset T1D usually occurred in children and youth ages 4–14 years (10,31). Our study demonstrated the highest diabetes-related hospitalization during the transition period to young adulthood, which most likely represented hospital admission for known diabetes other than a new diagnosis.

Third, individual information, such as glycemic control/HbA1c, use of pumps or CGM, was not available in our cohort. We were unable to evaluate the association between glycemic control, use of technology devices, and hospital admission or to determine numbers of CGM use with and without CCS coverage. Further studies thus are warranted to specifically look at the impact on CGM use after loss of CCS. We did have large sample size for T1D; however, the sample was relatively small for T2D. It was not surprising because T2D patients had lower risk for DKA or severe hypoglycemia that required hospital admission. Further studies with larger T2D sample size are warranted. Although CCS is a California-specific public health service, there are similar public health services across the U.S. that may fail many emerging adults with diabetes in a similar way (32). Our study provided important information to support the need for improved medical transition for emerging adults with diabetes.

### Conclusion

We demonstrated a significant rise in diabetes-related hospitalization rates during the transition to adulthood in individuals with T1D. Among hospitalizations in both types of diabetes, there were significantly more Black young adults who were on public insurance and had lower socioeconomic status. This population group had poorer health outcomes with a higher incidence for moderate and severe complications, and they accumulated more hospital charges than the youth population with both types of diabetes. Our findings suggest that the U.S. health care system fails many emerging adults with diabetes, particularly for people of color, and that improving the medical transition is crucial. More resources should be focused on this at-risk population from a healthcare system perspective.

Duality of Interest. No potential conflicts of interest relevant to this article were reported.

Author Contributions. A.S.Y.N. and M.L. wrote the manuscript, researched data, contributed to the discussion, and reviewed the manuscript. A.S.Y.N. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Prior Presentation. Parts of this study were presented in abstract form at the Endocrine Society ENDO 2021 virtual meeting, 20–23 March 2021.

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