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Population Study Article
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Published: 05 March 2024

Global, regional, and national burden of type 1 diabetes in adolescents and young adults

Boshen Gong 1 ,
Wanyu Yang 1 ,
Yumin Xing 1 ,
Yaxin Lai 1 &
Zhongyan Shan 1

Pediatric Research ( 2024 ) Cite this article

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Type 1 diabetes (T1D) incidence in adolescents varies widely, but has increased globally in recent years. This study reports T1D burden among adolescents and young adults aged 10–24-year-old age group at global, regional, and national levels.

Based on the Global Burden of Disease Study 2019, we described the burden of T1D in the 10–24-year-old age group. We further analyzed these trends by age, sex, and the Social Development Index. Joinpoint regression analysis was used to assess temporal trends.

T1D incidence among adolescents and young adults increased from 7·78 per 100,000 population (95% UI, 5·27–10·60) in 1990 to 11·07 per 100,000 population (95% UI, 7·42–15·34) in 2019. T1D mortality increased from 5701·19 (95% UI, 4642·70–6444·08) in 1990 to 6,123·04 (95% UI, 5321·82–6887·08) in 2019, representing a 7·40% increase in mortality. The European region had the highest T1D incidence in 2019. Middle-SDI countries exhibited the largest increase in T1D incidence between 1990 and 2019.

T1D is a growing health concern globally, and T1D burden more heavily affects countries with low SDI. Specific measures and effective collaboration among countries with different SDIs are required to improve diabetes care in adolescents.

We assessed trends in T1D incidence and burden among youth in the 10–24-year-old age group by evaluating data from the Global Burden of Disease Study 2019.

Our results demonstrated that global T1D incidence in this age group increased over the past 30 years, with the European region having the highest T1D incidence.

Specific measures and effective collaboration among countries with different SDIs are required to improve diabetes care in adolescents.

Global, regional, and national burden and trend of diabetes in 195 countries and territories: an analysis from 1990 to 2025

National and sub-national burden and trend of type 1 diabetes in 31 provinces of Iran, 1990–2019

Characterizing the type 2 diabetes mellitus epidemic in Jordan up to 2050

Introduction.

The increasing burden of type 1 diabetes (T1D) in adolescents and young adults is a major healthcare concern worldwide. 1 T1D incidence in childhood and adolescence is steadily rising and now stands at 22·9 new cases per year per 100,000 children up to the age of 15 years in Germany. 2 T1D burden has been attributed to rapid economic development and urbanization. The cost of diabetes care is at least 3·2 times greater than the average per capita healthcare expenditure, rising to 9·4 times in the presence of complications. 3 A multicenter study in the US showed that the overall unadjusted estimated incidence rates of T1D in youths increased by 1·4% annually from 2002 to 2012. 4 Thus, understanding the global burden of T1D in adolescents is important for the optimal utilization of healthcare resources in different countries.

Children are more sensitive to a lack of insulin than adults and are at a higher risk of rapid development of diabetic ketoacidosis. 5 Prior studies have indicated geographic differences in T1D trends. A multicenter prospective registration study conducted in 26 European centers reported significant increases in T1D incidence among adolescents between 1989 and 2013. 6 A cross-sectional multicenter study of 3.47 million youths (aged 19 years or younger) in the US found a significant increase in the estimated prevalence of T1D, from 1·48 cases per 1000 youths to 2.15 cases per 1000 youths. 7 The International Diabetes Federation Atlas 10th edition reported that T1D incidence in children and adolescents varies widely, and is increasing in many nations. 8 In our study, we investigated the global burden and the most substantial changes in the trend of T1D in adolescents and young adults aged 10–24 years. Many countries, particularly those with a low or middle social development index (SDI), lack high-quality information regarding T1D trends in adolescents. Thus, there is an urgent need to characterize T1D burden in adolescents and provide more information to local governments to ease this burden. The Global Burden of Disease (GBD) Study 2019 is an international collaboration that offers an opportunity to analyze disease trends on a global scale. In this study, we aimed to analyze global trends in T1D prevalence, incidence, disability-adjusted life-year (DALY), and mortality rates among adolescents across every decade since 1990, based on the latest data from GBD 2019.

GBD 2019 provides the most up-to-date estimation of the descriptive epidemiological data including incidence, prevalence, mortality, and disability adjusted life years (DALY) on a total of 369 diseases and injuries for 204 countries and territories from 1990 to 2019. 9 All countries and territories were classified into 21 regions according to epidemiological similarities, and could be grouped into six regions (African region, Eastern Mediterranean region, European region, Region of the Americas, South-East Asia region, and Western Pacific region) by the WHO. 10 The number of incident cases, prevalent cases, deaths, and DALYs were extracted from GBD 2019. All disease estimated from GBD contains 95% uncertainty intervals (UI) for each metric, which are based on the 25th and 97.5th values of 1000 draws of the posterior distribution. Rates in our study are shown per 100 000 population. Details of data inputs, processing, synthesis, and final model are available in the accompanying GBD 2019 publications. 9 The GBD database had data on T1D for different age periods. The WHO defined adolescence is the phase of life between childhood and adulthood, from ages 10 to 19. It is a unique stage for adolescents to lay the foundations of good health. 11 Thus, we defined younger adolescents ages 10-14years as age subgroups, ages 15–19 could be defined older adolescent, and 20 to 24 young adults. 12 To comprehensively describe the global trend of T1D in the life phase of adolescents and young adults, we defined younger adolescent (aged 10–14 years), older adolescent (aged 15–19 years), and young adults (aged 20–24 years). Data were collected from the GBD 2019 database in three age groups (10–14 years, 15–19 years, and 20–24 years), and both sexes.

The GBD 2019 analyzed the Socio-demographic index (SDI) for each country, which is an indicator estimated as a compositive of income per capita, average years of schooling among adults aged 15 and older, and fertility rate in female under 25 years old. All countries and territories were grouped into five categories based on the SDI (low SDI, low-middle SDI, middle SDI, high-middle SDI, and High SDI).

We conducted comparisons between the sexes, age groups (three intervals; 10–14, 15–19, and 20–24 years), SDI (five categories), and WHO regions (six regions). Incidence, prevalence, death, and DALYs were reported with 95% UI to eliminate the effects caused by differences in population structures. Then, we used the Joinpoint Regression Analysis to identify the substantial changes in trends of above indicators, and we used a maximum of 5 Joinpoints as the option of analysis. We evaluated the incidence, prevalence, DALYs, and mortality trends in various countries and regions based on average annual percent change (AAPC) by Joinpoint regression analysis. 13 The Joinpoint regression model was used to subsection describe disease trends from 1990 to 2019, and found out if the junctions of different segments had statistically significant. Countries with missing or zero values in their decade data were excluded from the analysis because a Joinpoint regression could not be conducted in this circumstance. The value of the AAPC is computed as a weighted average of the annual percentage change (APC) values in the regression analysis. The approximate 95% CI for AAPC was calculated by the empirical quantile method. We calculated the AAPCs between 1990 and 1999, between 2000 and 2009, between 2010 and 2009, and between 1990 and 2019. All analyses were performed using RStudio software (version R-4.2.2), and Joinpoint Regression Program (version 4.9.1.0).

Global burdens of T1D in adolescents and young adults

From 1990 to 2019, the incidence and prevalence of T1D in adolescents and young adults showed an overall increasing trend (Table 1 ). T1D incidence increased between 1990 and 1999 (AAPC, 0·88 [95% confidence interval (CI), 0·86–0·91]) and rose rapidly between 2000 and 2009 (AAPC, 1·41 [95% CI, 1·32–1·50]). The overall incidence rate in 1990 (7·78) cases per 100,000 population [95% uncertainty interval (UI), 5·27–10·60] increased to 2019 (11·07 cases per 100,000 population [95%] UI, 7·42–15·34; AAPC, 1·22 [95% CI, 1·18–1·27]). The overall global prevalence of T1D increased from 2,376,444 (95%UI 1,761,701–3,073,758) in 1990 to 364,4613 (95%UI, 2,655,059–4,756,336) in 2019, representing a 53·36% increase over the 30-year period (Table 2 ). Joinpoint regression analysis showed that the increasing trend of T1D incidence could be divided into six periods: 1990–1994, 1994–2001, 2001–2010, 2010–2014, 2014–2017, and 2017–2019 (Fig. 1 ).

Joinpoint regression analysis of global T1D prevalence ( a ), incidence ( b ), mortality ( c ), and DALYs ( d ) in adolescents and young adults aged 10–24 years from 1990 to 2019. DALY disability-adjusted life year, AAPC average annual percentage change, APC annual percentage change.

From 1990 to 2019, T1D mortality and DALY rates initially exhibited an increasing trend (1990–1999), followed by a subsequent decline (Table 3 ). Joinpoint regression analysis identified a substantial change in both T1D mortality (in 2000, 2003, and 2014) and DALY (in 2000, 2003, and 2015) rates. T1D incidence and prevalence increased significantly during the 30-year period. The mortality rate in 2019 (0·33 deaths per 100,000 population [95% UI, 0·29–0·37]) was lower than that in 1990 (0·37 deaths per 100,000 population [95% UI, 0·30–0·42]; AAPC, –0·41 [95% CI, –0·60 to –0·22]). The global DALY rate significantly decreased after 2000, with the most notable decline observed between 2000 and 2003.

Global burdens of T1D in adolescents and young adults by sex

In the context of sex, among the 3,644,613 T1D cases among adolescents and young adults globally in 2019, 1,871,433 (53·91%) occurred in boys. Both sexes exhibited a significant increase in T1D prevalence and incidence over the 30-year period. T1D incidence in boys increased from 65,053·33 cases (95% UI, 44,514·79–87,999·81) in 1990 to 111,120·71 cases (95% UI, 75,271·16–153,830·34) in 2019, representing a 70·85% increase. T1 incidence in girls increased from 55,526·95 cases (95% UI, 37,333·90–75,781·23) in 1990 to 95,015·41 cases (95% UI, 63,469·04–132,623·84) in 2019, representing a 71·12% increase. In terms of T1D prevalence in boys, an increase from 1,206,677 cases (95% UI, 891,833·4–1,571,014) in 1990 to 1,871,433 cases (95% UI, 1,360,287·7–2,446,297) in 2019 was observed, representing a 55·09% increase. T1D prevalence in girls increased from 1,169,767 cases (95% UI, 865,724·6–1,507,234) in 1990 to 1,773,180 cases (95% UI, 1,288,764·3–2,325,674) in 2019, representing a 51·58% increase over the three decades. While the global DALY rate in boys increased (APCC, 0·28 [95% CI, 0·12–0·43]), both global mortality (APCC, -0·87 [95% CI, -1·00–-0·74]) and DALY (-0·43 [95% CI, -0·57–-0·28]) rates decreased among girls.

Global burdens of T1D in adolescents and young adults by age group

T1D trends among adolescents and young adults varied according to age. Globally, the most rapidly increasing in T1D incidence (AAPC, 1·78 [95% CI, 1·65–1·91]) and prevalence (AAPC, 0·96 [95% CI, 0·91–1·01]) over the past 30 years were observed in young adults aged 20–24 years. Despite the increase in T1D incidence and prevalence among all three age subgroups, mortality in all subgroups decreased. The largest decline in the T1D mortality rate between 1990 and 2019 was observed among older adolescents aged 15–19 years (from 0·34 deaths per 100,000 population [95% UI, 0·26–0·40] to 0·29 deaths per 100,000 population [95% UI, 0·24–0·33]; AAPC, -0·64 [95% CI, -0·88–-0·40]). While an increase in the DALY rate was observed among young adults aged 20–24 years (from 44·25 per 100,000 population [95% UI, 36·56–51·53] to 45·76 per 100,000 population [95% UI, 38·96–53·85]; AAPC, 0·14 [95% CI, 0·04–0·24]), a decrease was observed among those aged 10–14 years (from 25·44 per 100,000 population [95% UI, 18·23–31·77] to 23·82 per 100,000 population [95% UI, 19·36–29·81]; AAPC, -0·23 [95% CI, -0·48–0·03]) and 15–19 years (from 32·51 per 100,000 population [95% UI, 24·95–38·91] to 30·70 per 100,000 population [95% UI, 25·08–37·55]; AAPC, -0·22 [95% CI, -0·39–-0·04]) between 1990 and 2019.

Global burdens of T1D in adolescents and young adults by SDI

T1D burden among adolescents and young adults differed substantially according to the SDI. Countries with high SDI had the highest T1D prevalence (431·32 cases per 100,000 population [95% UI, 33·33–537·30]; AAPC, 0·70 [95% CI, 0·65–0·74]) and incidence (21·53 cases per 100,000 population [95% UI, 14·55–29·53]; AAPC, 1·25 [95% CI, 1·17–1·33]) rates in 2019, but the lowest mortality rate (0·16 deaths per 100,000 population [95% UI, 0·14–0·16]; AAPC, -0·66 [95% CI, -0·93–-0·40]). Notably, countries with a middle SDI had the lowest T1D prevalence (151·29 cases per 100,000 population [95% UI, 108·62–201·91]; AAPC, 1·52 [95% CI, 1·48–1·55]) and incidence (8·58 per 100,000 population [95% UI, 5·73–11·95]; AAPC, 1·79 [95% CI, 1·74–1·84]) rates in 2019. Countries with a low SDI had the highest mortality (0·44 deaths per 100,000 population [95% UI, 0·36–0·52]; AAPC, -0·41 [95% CI, -0·55–-0·28]) and DALY (39·73 per 100,000 population [95% UI, 32·90–47·47]; AAPC, -0·27 [95% CI, -0·38–-0·15]) rates in 2019. Over the past 30 years, both T1D prevalence and incidence increased across all SDI quintiles, whereas mortality rates decreased. All countries exhibited a reduction in the DALY rate from 1990 to 2019, with the exception of those countries categorized in the high SDI quintile group.

Regional and national burdens of T1D in adolescents and young adults

When classified according to World Health Organization (WHO) regions, the European region exhibited the most rapid increase in T1D incidence rate of T1D for adolescents and young adults between 1990 and 2019 (from 11·18 cases per 100,000 population [95% UI, 8·24–14·52] to 18·80 cases per 100,000 population [95% UI, 12·54–25·90]; AAPC, 1·81 [95% CI, 1·76–1·86]). The highest mortality rate in 2019 was observed in the Eastern Mediterranean region (0·43 deaths per 100,000 population [95% UI, 0·34–0·53]), followed by the African region (0·40 deaths per 100,000 population [95% UI, 0·33–0·48]). The Western Pacific region showed the lowest incidence (5·47 cases per 100,000 population [95% UI, 3·59–7·63]), prevalence (119·94 cases per 100,000 population [95% UI, 89·10–154·33]), mortality (0·18 deaths per 100,000 population [95% UI, 0·16–0·20]), and DALY (24·61 per 100,000 population [95% UI, 20·83–28·77]) rates in 2019. The African region exhibited a modest increase in T1D incidence rate (from 10·05 cases per 100,000 population [95% UI, 6·73–13·93] to 10·60 cases per 100,000 population [95% UI, 7·07–14·87]; AAPC, 0·18 [95% CI, 0·17–0·20]) and prevalence (from 151·65 cases per 100,000 population [95% UI, 106·87–204·70] to 160·79 cases per 100,000 population [95% UI, 113·36–217·61]; AAPC, 0·20 [95% CI, 0·20–0·21]) rates between 1990 and 2019.

At the national level, Finland had the highest T1D incidence rate among adolescents and young adults in 2019 (32·56 cases per 100,000 population [95% UI, 22·41–44·59]; AAPC, -0·37 [95% CI, -0·78–0·04]), followed by Canada (31·89 cases per 100,000 population [95% UI, 21·83–44·01]; AAPC, 0·36 [95% CI, 0·20–0·53]) (Fig. 2 , Supplementary Tables 1 – 2 ). The Solomon Islands (1·20 deaths per 100,000 population [95% UI, 0·77–1·73]; AAPC, 0·75 [95% CI, 0·47–1·03]) had the highest mortality rate in 2019, followed by Turkmenistan (1·15 deaths per 100,000 population [95% UI, 0·90–1·45]; AAPC, 2·12 [95% CI, 1·21–3·03]) (Supplementary Table 3 ). Despite the declining trend in the global DALY rate due to T1D, rates remained high in countries with a low SDI; Turkmenistan had the highest DALY rate in 2019 (AAPC, 1·95 [95% CI, 1·17–2·73]), followed by Haiti (87·44 per 100,000 population [95% UI, 57·16–119·46]) (Supplementary Table 4 ).

Global map of 2019 prevalence ( a ), incidence ( b ), deaths ( c ), and DALYs ( d ) of T1D among adolescents from 1990 to 2019. DALY disability-adjusted life year.

This study provided an updated and comprehensive evaluation of global, regional, and national T1D burden among adolescents and young adults aged 10–24 years old, based on data from the GBD Study 2019. Diabetes is the third most common disease in children and adolescents aged <18 years. 14 Our study documented 206,136 new cases among young adult and adolescents worldwide in 2019, which led to 6123 deaths. In addition to systemic complications, T1D also has long-term effects on health-related quality of life and psychosocial functioning. 15 , 16 Previous studies have shown that the global T1D mortality rate among adolescents has decreased with improvements in diagnosis and treatment planning. 17 While we observed an overall decrease in global T1D mortality rate among adolescents between 1990 and 2019 (AAPC, –0·41 [95% CI, –0·60–-0·22]), there was also an increase between 1990 and 1999 (AAPC, 0·69 [95% CI, 0·56–0·82]). Our findings provide further insight into the global burden of the T1D epidemic among adolescents and young adults and highlight the need for government action to improve diabetes management for this age group.

Notably, our use of the SDI demonstrated a close association between T1D burden and socioeconomic development. 18 Inadequate T1D diagnosis and treatment are likely to be major contributors to early mortality, especially in low-SDI countries. 19 Our study showed that adolescents in countries with a greater SDI exhibited higher T1D incidence and prevalence rates in 2019, whereas middle-SDI countries had the lowest incidence and prevalence rates. Prior studies have shown that low socioeconomic status is associated with higher mortality and morbidity in adults with T1D, even in those who are capable of accessing a universal healthcare system. 20 Similarly, our results indicated that the T1D mortality rate among individuals aged 10–24 years was highest in low-SDI countries. We also found that countries with a low SDI had the highest DALY rate, despite a global declining trend among adolescents between 1990 and 2019.

Previous studies have attributed geographic differences in T1D prevalence and clinical characteristics to inherent variations among ethnic groups and migration between countries. 21 Our results showed that European countries had the highest T1D incidence among adolescents in 2019, whereas countries in the Western Pacific region had the lowest incidence. Prior studies have also found that T1D incidence among children aged 0–14 years differs between Nordic countries and their neighboring countries and that this may be related to differences in population density. 22 A study that examined T1D incidence and trends in the 15–39-year-old age group between 1992 and 1996 in Finland concluded that the risk of T1D extended into young adulthood. 23

Nonetheless, we observed that adolescents with T1D in low-SDI or developing countries tended to have higher mortality and DALY rates, which may have been due to a lack of financial support and poor diabetes management. Our results showed that the Solomon Islands had the highest T1D mortality rate in 2019, followed by Turkmenistan and Guyana. Diabetes is currently the fourth-leading cause of death in Guyana, South America. 24 Multiple risk factors have been implicated in the increasing incidence of T1D among adolescents. 25 Environmental factors, including childhood obesity, chronic viral infections, and maternal-child interactions, have been considered to be responsible for the current evolving pattern of T1D incidence. 26 Previous studies have reported that adversities during childhood may increase the risk of T1D through hyperactivation of the stress response system, especially in individuals exposed to increasing annual rates of childhood adversities. 27

There is strong evidence that sex plays an important role in T1D incidence among adolescents and young adults. Previous studies have shown that T1D incidence among children is higher in males than in females. 28 A Finnish study that analyzed 3,277 children (<10 years old) diagnosed with T1D reported that boys more often had insulin autoantibody-initiated autoimmunity, whereas glutamic acid decarboxylase-initiated autoimmunity was observed more frequently in girls. 29 In our study, the AAPC among females showed a declining trend compared to males, thus indicating that more attention should be paid to diabetes care for young males.

We found that age was an important factor affecting differences in the burden of T1D among adolescents and young adults. A US study estimating the total number of youth aged under 20 years with diabetes reported that T1D prevalence increased with age. 30 Analysis of a national registry that included 505 hospitals in China found that the peak incidence per 100,000 person-years occurred in the 10–14-year-old age group. 31 Consistent with previous studies, we observed that younger adolescents aged 10–14 years had the highest T1D incidence rate in 2019; the prevalence rate in young adults aged 20–24 years was 246·79 cases per 100,000 population, nearly twice that of younger adolescents aged 10–14 years (143·19 cases per 100,000 population). Notably, the mortality rate of T1D in 2019 among young adults was 0·49 deaths per 100,000 population, more than double that of those aged 10–14 years (0·22 deaths per 100,000 population). This is pertinent, as managing T1D in adolescents is challenging from both medical and psychosocial perspectives, due to the vulnerable period during which parental caretaking is normative and adolescent behavior is unpredictable. 32

Compared with a previous GBD study that analyzed diabetes burden, 33 , 34 we provided a more comprehensive and specific analysis of T1D among adolescents and young adults aged 10–24 years and identified the most prominent changes in global trends by using Joinpoint regression analysis. Nevertheless, our study had several limitations. First, our results were based on the GBD Study 2019, which collected data from 1990 to 2019 and included countries with large boundaries. This may have been a source of significant variation in our results. Second, the determination of T1D burden in the GBD Study 2019 may have been affected by the detection method used, screening quality, and availability of local medical resources. Thus, T1D burden in countries with a low SDI tended to be underestimated, which could have introduced bias into our results. Third, while ethnic factors have been reported to affect the distribution of T1D among adolescents, these parameters were not evaluated in the GBD Study 2019.

T1D among adolescents and young adults is a growing global health problem, especially in countries with a low SDI and less well-developed economy. The global burden of T1D among adolescents is substantial, although mortality and DALY rates have declined over the past 30 years due to advances in healthcare. As the incidence and severity of T1D among adolescents and young adults are still increasing, there is an urgent need for the implementation of lifestyle modification programs in childhood.

Data availability

All data used in this study can be freely accessed at the GBD 2019 study ( https://vizhub.healthdata.org/gbd-results ).

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Acknowledgements

We appreciated the work of the Global Burden of Disease Study 2019 collaborators or personal relations that could have appeared to influence the work reported in this paper.

This work was supported by Natural Science Foundation of China. (Grant number: 82300886), and Liaoning Revitalization Talents Program (No. XLYC2002084).

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B.S.G. drafted and design the initial manuscript. W.Y.Y. reviewed the manuscript. Y.M.X. revised the manuscript. Z.Y.S. conceptualized, revised the manuscript. Y.X.L. drafted the manuscript. All authors have directly accessed and verified the underlying data mentioned in the manuscript, and approved the final manuscript as submitted.

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Gong, B., Yang, W., Xing, Y. et al. Global, regional, and national burden of type 1 diabetes in adolescents and young adults. Pediatr Res (2024). https://doi.org/10.1038/s41390-024-03107-5

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Diabetes research

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We conduct experimental and clinical diabetes research. Our aim is to develop new treatments and drugs that can prevent or cure diabetes, which is a fast-growing chronic disease.

It is estimated that around 500 million people worldwide have diabetes. This number is expected to rise to more than 780 million by 2045.

Type 2 diabetes is the most common form of diabetes and accounts for the largest increase. It is not yet fully known what causes type 1 diabetes and type 2 diabetes.

Several research areas working together

Lund University Diabetes Centre (LUDC) conducts extensive and multifaceted research in several areas. Researchers conduct experimental basic research in modern laboratories, study people's lifestyles, and conduct clinical trials involving patients.

The overall aim is to develop individualised treatments that provide patients the right treatments at the right time. The long-term goal is to prevent and cure diabetes as well as improve the treatment of the disease and its complications.

Among other things, the researchers study:

classification of patient groups with diabetes for individualised treatments
how environmental and lifestyle factors influence the development of type 2 diabetes (epigenetics)
mechanisms that affect insulin secretion in diabetes
autoantibodies used to identify type 1 diabetes
ways to prevent complications and develop new treatments for diabetes
individualised dietary recommendations to reduce the risk of obesity and type 2 diabetes
the role of eating habits on health in people with and without diabetes.

State-of-the art research facilities

At LUDC, there is a cutting-edge laboratory where researchers collect cells and tissues from people with and without diabetes. This laboratory enables researchers to conduct experimental and clinical studies into the disease mechanisms associated with diabetes.

Moreover, LUDC houses a biobank containing plaques from people with atherosclerosis, a common complication of diabetes, which researchers are studying.

Application areas

Researchers at LUDC are working closely with Skåne University Hospital, pharmaceutical companies and other stakeholders to find new treatments and drugs to prevent, delay and cure diabetes. Some examples:

Individualised treatments

At Lund University, diabetes researchers have discovered that it is possible to categorise type 1 and type 2 diabetes into five distinct subgroups. This important discovery could lead to more individualised treatments of the disease. The researchers have also identified genetic differences between the four groups of type 2 diabetes, indicating different underlying causes to the disease.

The researchers aim is to use this genetic and clinical data to develop treatments that are tailored to each patient. The discovery is a significant step forward that can lead to improvements for people living with diabetes.

Epigenetics and genetics help illustrate how diabetes care can be individualised – ludc.lu.se

Biomarkers to identify type 1 diabetes

Researchers around the world strive to understand why some people develop type 1 diabetes and others do not. At Lund University, diabetes researchers are continuously studying various diabetes-related autoantibodies in children with a high risk of developing type 1 diabetes.

This research has led to the approval of these autoantibodies as a biomarker for the disease. This approval means that individuals who have at least two diabetes-related autoantibodies can participate in clinical studies designed to prevent the disease.

Blood testing in children leads to better understanding of type 1 diabetes

Sample collections that enable advanced diabetes research

Several research groups at Lund University are working together to study the mechanisms behind diabetes. An important resource for diabetes research is a sample collection of insulin-producing cells and tissues from the liver, muscles and fat of people both with and without diabetes. Researchers study the cells to understand what happens to insulin secretion in diabetes. This knowledge could lead to new treatments that improve insulin secretion in people with diabetes.

The researchers also have access to a biobank containing plaque samples from people with atherosclerosis, a common complication of diabetes known to trigger heart attacks and strokes. The researchers' studies of the mechanisms behind atherosclerosis could be instrumental in developing new treatments that target dangerous plaques.

Preventing diabetes complications

Diabetes can lead to complications such as stroke, heart attack and kidney disease. Researchers are studying various aspects, including epigenetic differences between various groups of people with type 2 diabetes, to try to predict the risk of these complications at an early stage.

Researchers are also examining the underlying mechanisms behind plaque rupture in atherosclerosis, a common complication of diabetes. The aim is to develop treatments that can prevent plaque rupture.

Research environments

The following links are to other websites.

Epidemiology
Global Platform for the Prevention of Autoimmune Diabetes (GPPAD)
Nutritional epidemiology
Malmö Diet and Cancer (MDC) and Malmö Preventive Project (MPP)
SCAPIS study
TEDDY study

Strategic research area

A significant part of diabetes research at Lund University is conducted within EXODIAB, which is a strategic research area (SRA) in Sweden.

Within EXODIAB, Lund University Diabetes Centre (LUDC) and Uppsala University work closely together. Their shared ambition is to develop new treatments and drugs that can prevent or cure diabetes.

Coordinator Allan Vaag, professor allan [dot] vaag [at] med [dot] lu [dot] se (allan[dot]vaag[at]med[dot]lu[dot]se) Vice coordinator Lena Eliasson, professor Phone: +46(0)40 39 1153 Mobile: +46(0)70 522 5414 lena [dot] eliasson [at] med [dot] lu [dot] se (lena[dot]eliasson[at]med[dot]lu[dot]se)

LUDC – ludc.lu.se

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Latest news in diabetes research

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Positive metabolic effects of gastric bypass disappear quickly

Isabel Goncalves, Jiangming Sun, and Andreas Edsfeldt studying two atherosclerotic plaques.

New discoveries about where atherosclerotic plaques rupture can lead to preventive treatments

ERC grants for research on diabetes and immunotherapy

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Incidence of type 1 diabetes in Sweden among individuals aged 0-34 years, 1983-2007: an analysis of time trends

Affiliation.

1 Department of Clinical Science, Umeå University, Umeå, Sweden. [email protected]
PMID: 21680725
PMCID: PMC3142045
DOI: 10.2337/dc11-0056

Objective: To clarify whether the increase in childhood type 1 diabetes is mirrored by a decrease in older age-groups, resulting in younger age at diagnosis.

Research design and methods: We used data from two prospective research registers, the Swedish Childhood Diabetes Register, which included case subjects aged 0-14.9 years at diagnosis, and the Diabetes in Sweden Study, which included case subjects aged 15-34.9 years at diagnosis, covering birth cohorts between 1948 and 2007. The total database included 20,249 individuals with diabetes diagnosed between 1983 and 2007. Incidence rates over time were analyzed using Poisson regression models.

Results: The overall yearly incidence rose to a peak of 42.3 per 100,000 person-years in male subjects aged 10-14 years and to a peak of 37.1 per 100,000 person-years in female subjects aged 5-9 years and decreased thereafter. There was a significant increase by calendar year in both sexes in the three age-groups <15 years; however, there were significant decreases in the older age-groups (25- to 29-years and 30- to 34-years age-groups). Poisson regression analyses showed that a cohort effect seemed to dominate over a time-period effect.

Conclusions: Twenty-five years of prospective nationwide incidence registration demonstrates a clear shift to younger age at onset rather than a uniform increase in incidence rates across all age-groups. The dominance of cohort effects over period effects suggests that exposures affecting young children may be responsible for the increasing incidence in the younger age-groups.

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Lund University Diabetes Centre

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Large international study points at three pathways towards type 1 diabetes

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A large international study has identified three different pathways towards type 1 diabetes in children. Researchers at Lund University Diabetes Centre have contributed with data from a prospective study in southern Sweden. An important objective with the study published in Nature Communications is to gain a better understanding of how the disease develops to be able to take preventive measures.

“This study gives new insights into the development of the disease in children who are at high risk of developing the disease. We have gathered data from five prospective studies from several different countries, which is a great strength. Our research colleagues at IBM Research have the knowledge of machine learning and data visualisation that this project has required,” says Markus Lundgren, researcher in pediatric endocrinology at Lund University Diabetes Centre (LUDC) and one of the authors of the study, published in Nature Communications.

The study in Nature Communications includes data from 24.662 children, who have been followed for 15 years. Data are derived from five prospective studies of children in United States, Sweden, Germany and Finland. Researchers at Lund University Diabetes Centre have provided data from the study Diabetes prediction in Skåne, where children in southern Sweden have been screened for type 1 diabetes risk from infancy up to 15 years of age.

Three pathways

The research team studied the pathway from being a healthy individual to progression to type 1 diabetes in 652 individuals. Until now, type 1 diabetes has often been divided into different stages depending on how many diabetes related autoantibodies the individual has got. The new study shows that type 1 diabetes instead can be divided into three different groups based on the patterns of developing autoantibodies.

“We have been able to identify three distinct trajectories, or pathways, from healthy individual to diagnosis, that are associated with varying degree of disease risk,” says Bum Chul Kwon, first author of the study and researcher of data visualisation and visual analytics at IBM Research.

In discussing this new study in Nature Communications, Markus Lundgren, principal investigator of the study in southern Sweden says:

“This may be seen as a first step towards a categorisation of patients with type 1 diabetes into subgroups. We have identified that the groups differ and need to find out more about how they differ by for example studying genetic factors that may play a role.”

Screening for type 1 diabetes

It is currently not possible to prevent or cure type 1 diabetes, which is why research on prevention and early detection is important. The researchers behind the study hope that the new knowledge may pave the way for screening programmes for type 1 diabetes.

“An important goal is to create a disease progression model that will be able to predict the disease with high accuracy. It is however of great importance that the health care system has more to offer people at risk of developing the disease before screening can be a viable option, such as a treatment that will delay the disease progression,” says Markus Lundgren.

The study has been funded by JDRF International. Frank Martin, senior director at the organisation’s research department, thinks that the study has transformative potential.

“Only through better screening, monitoring, and risk education can we minimise the near- and long-term health consequences associated with missed diagnoses,” Frank Martin says.

The three groups

Diabetes related autoantibodies are often used to identify people at risk of developing type 1 diabetes. The researchers have been studying the following autoantibodies in diabetes: IAA, GADA and IA-2A. The study in Nature Communications has identified three groups of patients with different patterns of autoantibodies.

First group Individuals in this group had several of the diabetes related autoantibodies before the diagnosis could be confirmed.

Second group Children in the second group had autoantibodies against insulin (IAA) and developed other autoantibodies over time before the diagnosis could be confirmed.

Third group Individuals in the third group first developed autoantibodies against GAD65 (GADA) before other autoantibodies emerged and the diagnosis could be confirmed.

Markus Lundgren, specialist physician and researcher in paediatric endocrinology at Lund University

+46 70 995 09 90

markus [dot] lundgren [at] med [dot] lu [dot] se

Markus Lundgren’s profile in Lund University’s research portal

Åke Lernmark, professor of experimental diabetes at Lund University

+46 70 616 47 79 +46 40 39 19 01

ake [dot] lernmark [at] med [dot] lu [dot] se

Åke Lernmark's profile in Lund University's research portal

Type 1 diabetes

Type 1 diabetes is caused by an autoimmune reaction in which the body’s immune system attacks the insulin-producing beta cells of the pancreas. As a result, the body produces very little or no insulin. People with type 1 diabetes need daily insulin injections to maintain a glucose level in the appropriate range. There is currently no cure for this disease.

Type 1 diabetes may cause different complications. Ketoacidosis may occur in people who have high blood sugar levels and a lack of insulin. Hyperglycemia happens when the body does not produce enough insulin.

High blood sugar levels may be harmful to the body’s blood vessels and can lead to eye problems, poor kidney function, heart attack, stroke and angina.

The study in Nature Communications

The title of the study: Progression of type 1 diabetes from latency to symptomatic disease is predicted by distinct autoimmune trajectories

The study in Nature Communications is the result of a research collaboration between IBM Research and five prospective studies. Five prospective studies with children from four countries have been included in the study: DAISY, DEW-IT (USA), DiPiS (Sweden), DIPP (Finland) and BABYDIAB (Germany).

The study has been funded by JDRF International via JDRF Grants #1-RSC-2017-526-I-X and #1-SRA-2019-720-I-X to Lund University, in addition to JDRF grants to four other data contributing organisations and IBM.

Link to the study in Nature Communications

Latest news

New guidelines aim to increase accuracy in precision medicine research, new peptide may reduce the risk of diabetes complications, new method allows for large-scale screening for autoimmune diseases, research paves the way for sustainable dietary recommendations, research on obesity and gestational diabetes receive support from hjelt diabetes foundation.

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Recent trends in life expectancy for people with type 1 diabetes in Sweden

Published: 05 April 2016
Volume 59 , pages 1167–1176, ( 2016 )

Cite this article

Dennis Petrie ORCID: orcid.org/0000-0002-3882-2531 1 ,
Tom W. C. Lung 1 , 2 ,
Aidin Rawshani 3 ,
Andrew J. Palmer 4 ,
Ann-Marie Svensson 3 ,
Björn Eliasson 3 &
Philip Clarke 1

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Aims/hypothesis

People with type 1 diabetes have reduced life expectancy (LE) compared with the general population. Our aim is to quantify mortality changes from 2002 to 2011 in people with type 1 diabetes in Sweden.

This study uses health records from the Swedish National Diabetes Register (NDR) linked with death records. Abridged period life tables for those with type 1 diabetes aged 20 years and older were derived for 2002–06 and 2007–11 using Chiang’s method. Cox proportional hazard models were used to assess trends in overall and cause-specific mortality.

There were 27,841 persons aged 20 years and older identified in the NDR as living with type 1 diabetes between 2002 and 2011, contributing 194,685 person-years of follow-up and 2,018 deaths. For men with type 1 diabetes, the remaining LE at age 20 increased significantly from 47.7 (95% CI 46.6, 48.9) in 2002–06 to 49.7 years (95% CI 48.9, 50.6) in 2007–11. For women with type 1 diabetes there was no significant change, with an LE at age 20 of 51.7 years (95% CI 50.3, 53.2) in 2002–06 and 51.9 years (95% CI 50.9, 52.9) in 2007–11. Cardiovascular mortality significantly reduced, with a per year HR of 0.947 (95% CI 0.917, 0.978) for men and 0.952 (95% CI 0.916, 0.989) for women.

Conclusions/interpretation

From 2002–06 to 2007–11 the LE at age 20 of Swedes with type 1 diabetes increased by approximately 2 years for men but minimally for women. These recent gains have been driven by reduced cardiovascular mortality.

Mortality trends in type 1 diabetes: a multicountry analysis of six population-based cohorts

Life expectancy of type 1 diabetic patients during 1997–2010: a national australian registry-based cohort study, impact of age at diagnosis and duration of type 2 diabetes on mortality in australia 1997–2011.

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Introduction

It has long been established that people with type 1 diabetes have higher mortality and reduced life expectancy (LE) compared with the general population [ 1 , 2 ]. Having accurate LE estimates allows us to identify gaps between populations in order to identify areas for potential improvement and quantify improvements in healthcare over time [ 3 , 4 ]. LE estimates feed into life insurance premiums and allow insurance companies to quantify and manage risks [ 5 , 6 ]. The information can also be used by people with diabetes to make better planning decisions about matters such as retirement [ 7 ].

Previous studies have estimated the impact of type 1 diabetes on mortality and LE and compared these with variables in the general population [ 1 , 8 – 14 ]. There is some evidence that survival of people with type 1 diabetes relative to the general population has improved since the 1940s [ 6 ] and has continued to improve in recent years [ 15 ]. One Australian study comparing people with type 1 diabetes with the general population estimated that the standardised mortality ratio (SMR) decreased from 4.20 in 1997 to 3.08 in 2010 [ 16 ]. Similarly, LE has improved over time [ 5 ]. However, the gap still remains. A recent study in Scotland found that from 20 years of age, men and women with type 1 diabetes lose about 11 and 13 years of LE, respectively, compared with the general population [ 17 ]. Renal and cardiovascular disease (CVD) have been identified as comorbidities that contribute to excess mortality, especially after the first 10 years from type 1 diabetes onset [ 12 , 14 , 18 – 21 ]. There is some evidence to suggest that improvements in diabetes care have delayed the progression of renal disease [ 14 ].

The current paper addresses whether mortality and LE have changed for men and women with type 1 diabetes in Sweden from 2002 to 2011, and examine how these changes compare with changes in the general population. In addition, we also explore whether any secular trends in mortality over this period can be explained by improvements in risk factors associated with diabetes-related complications and further investigate mortality by cause to examine where recent gains have been made.

This study uses Swedish data for those with type 1 diabetes and compares their mortality with that of the general population in Sweden.

Diabetes population

The Swedish National Diabetes Register (NDR) stores individuals’ clinical details from registered centres across all of Sweden [ 22 ]. It records demographic data, diabetes duration and treatment modalities, as well as various risk factors measured at least annually and diabetes complications from actual patient visits in primary healthcare or hospital outpatient clinics for all diabetes patients [ 23 , 24 ].

This study is based on four sources of data: (1) risk factor data from the Swedish NDR (1 January 1987 to 31 December 2010); (2) hospital records of inpatient episodes from the National Inpatient Register (1 January 1987 to 31 December 2011) [ 25 ]; (3) death records (1 January 2002 to 31 December 2011); and (4) prescription data records (1 July 2005 to 31 December 2011) [ 26 ]. The data were confidentially linked at the patient level by the NDR. The Central Ethical Review Board at the University of Gothenburg approved the study.

Our sample included patients with type 1 diabetes who visited a clinic after 2002 and were registered in the NDR. The number of clinics that placed their patients’ data in the NDR rapidly increased from 2002 and currently there is nearly 90% coverage of the population with type 1 diabetes [ 27 ]. To ensure those with type 2 diabetes and emigrants are excluded, we defined a person as having type 1 diabetes if diagnosed under the age of 30 years, reported as being treated with insulin only at some clinic visit, and when alive, having had at least one prescription for insulin filled per year between 2006 and 2010 (full calendar years where prescription data were available) and without a prescription filled for metformin at any point between July 2005 and December 2010. A flow diagram with the numbers excluded at each criterion is given in electronic supplementary material (ESM) Fig. 1 . Patients entered as being at risk of death from the date of their first NDR clinic visit after 1 January 2002 until they died or were censored at the final study date (31 December 2011).

All HbA 1c values were converted to National Glycohemoglobin Standardization Program (NGSP) standard levels [ 28 ]. Microalbuminuria was defined as two positive tests out of three samples taken within a year, with albumin/creatinine ratio 3–30 mg/mmol or urinary albumin excretion rate (UAE) of 20–200 μg/min or 20–300 mg/l and macroalbuminuria as albumin/creatinine ratio >30 mg/mmol or UAE >200 μg/min or >300 mg/l. Estimated GFR (eGFR) was calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formula [ 29 ]. Descriptive statistics of risk factors and event history of those at their first NDR visit in 2002 and alive at the end of 2011 are reported by sex. Mean values adjusted using linear regression for current age and age at diagnosis are also reported. Given that the same individuals may have been alive in 2002 and at the end of 2011, we bootstrapped the sample at the individual level with 2,000 replications to test for significant differences in the means of the risk factors between 2002 and 2011.

Classification of deaths

For those with type 1 diabetes, deaths were classified by cause of death into deaths related to CVD, renal disease and other causes. Where a general diabetes-related ICD code was given as the primary cause of death, it was re-classified as CVD or renal death if a CVD or renal ICD code was found in the secondary causes [ 8 , 30 ]. The specific ICD codes used can be found in the ESM Methods .

General population

Annual mortality rates and LE information by sex for the general Swedish population were obtained from Eurostat [ 31 ]. These were then used to estimate for each NDR individual the expected mortality by year if they had been exposed to the same mortality as the general population. Cause-specific mortality rates for the general population were also used. However, 2010 cause-specific mortality rates from Eurostat were used for 2011 as the 2011 rates were not available.

Statistical analysis

We defined LE for people with type 1 diabetes as the expected remaining years to be lived for someone aged 20 with type 1 diabetes if they were exposed to the same mortality as the current mortality faced by older individuals alive and diagnosed with type 1 diabetes (a period life table assumption). To do this we used abridged period life tables by sex for those with type 1 diabetes in Sweden aged 20 years and older, derived for 2002–06 and 2007–11 using Chiang’s method for 5-year age intervals (plus an open-ended interval for 80 years and older) [ 32 ]. The mortality rates for each age–sex–time group were calculated based on the number of deaths observed for each age–sex–time group in the period divided by the total time at risk observed for each age–sex–time group. As the NDR does not have paediatric data, we considered LE from 20 years.

LE for people with type 1 diabetes was also compared with the LE of the general Swedish population. This allowed us to put into context changes observed in the population with type 1 diabetes vs the changes seen over this period in the general Swedish population and to quantify LE gaps at different ages. SMRs compared with rates in the general population were estimated using weights based on the population structure of individuals with type 1 diabetes in the NDR in 2010. In addition, to quantify the differences in type 1 diabetes LE across countries, the LE results were compared with a recent Scottish study (2008–10) [ 17 ]. Bootstrap techniques were used to derive the 95% CI for LE and SMR, with 1,000 samples generated and sampling conducted at the individual level to reflect the sampling design. When no deaths were recorded in the population with type 1 diabetes the general population mortality rate for that period was used instead [ 17 ].

A Cox proportional hazards model was then estimated for survival where, first, only a linear trend for the year and the age at diagnosis were included as explanatory factors to see whether there was a systematic improvement in mortality rates over time. Second, we also included a number of other time-varying risk factors to explore the extent to which any trends observed could be explained by variations in these risk factors over time. Risk factor values were carried forward and updated when available at subsequent clinic visits, including values for micro- and macroalbuminuria. We did not directly control for a history of diabetes-related complications or events as it is expected that changes in the risk factors would act through reducing the occurrence of these complications, and death would naturally be a consequence of many of these complications. Finally, the trend in relative mortality compared with the general population was considered by including the natural log of the general population mortality rate for each sex as an offset variable in the Cox proportional hazards model where its coefficient was restricted to one. This allowed investigation of relative mortality changes over time [ 33 , 34 ].

Several sensitivity analyses were conducted. First, we examined year-to-year trends by including a dummy variable for each year. Second, we included dummy variables for the year of NDR entry as additional explanatory variables to explore whether results were influenced by possible selection bias due to those entering the NDR sample earlier being systematically sicker or healthier than those who entered later. Third, we considered an expanded sample that included all those diagnosed under the age of 30 (including those on metformin or with insulin prescriptions missing). Fourth, we used multiple imputation with chained regressions (five imputations) to adjust for missing risk factor data [ 35 ].

To further investigate potential trends in specific causes of death, we employed a competing risk Cox proportional hazards model where deaths were split by the major causes of excess mortality in the population with type 1 diabetes: CVD-related, renal-disease-related and other causes. We explored whether a linear time trend was observed for each cause of death while controlling for age at diabetes diagnosis, as well as trends in relative mortality, by offsetting the model with the natural log of the general population cause-specific mortality rate by age group. All analyses were undertaken using STATA (StataCorp 2011. Stata Statistical Software: release 12.1. College Station, TX, USA).

There were 27,841 people identified in the NDR as living with type 1 diabetes in Sweden and at risk of death at some point between 2002 and 2011 inclusive, contributing 194,685 person-years of follow-up. Overall, 2,018 deaths were observed. The ages ranged from 17.0 to 97.7 years.

Table 1 provides descriptive statistics, by sex, of risk factors and event history of those in the NDR at the first NDR visit in 2002 and alive at the end of 2011. The numbers alive in the registry increased during this period as more clinics registered their data in the NDR (see ESM Results for individuals added each year). The average level of some important risk factors changed significantly over this period: 17% more men and 13% more women reported being on lipid-lowering medication and also had lower HDL-cholesterol, LDL-cholesterol and triacylglycerols; HbA 1c and BMI slightly increased while systolic BP and the proportion of smokers decreased. Renal function improved, with 5–6% fewer people with microalbuminuria and 3–4% fewer people with macroalbuminuria, while eGFR increased. The proportion of people alive with a history of diabetes-related events increased significantly for most event types for both men and women. Similar risk factor differences were seen even after adjusting for differences in age and age at diagnosis between the 2 years.

LE trends for people with type 1 diabetes in Sweden

Figure 1a, b illustrates cumulative mortality for the period 2002–06 and 2007–11 for those with type 1 diabetes and the general population for men and women, respectively. These graphs show a significant improvement in survival for men and little change for women over the two time periods. However, a large gap persists between the men and women with type 1 diabetes and the general populations.

All-cause and CVD cumulative mortality by age and sex of those with type 1 diabetes vs the general population from 2002–06 to 2007–11. ( a ) Men, all-cause mortality; ( b ) women, all-cause mortality; ( c ) men, CVD mortality events; and ( d ) women, CVD mortality events. Blue, NDR population with type 1 diabetes 2002–06; red, NDR population with type 1 diabetes 2007–11; green, general population 2002–06; orange, general population 2007–11. Dotted lines represent 95% CI for cumulative mortality. Mortality for the general population is the expected cumulative mortality if those with type 1 diabetes had the same annual mortality rate as the general population. The logrank test for the two time periods found significant differences for all-cause ( p = 0.001) and CVD ( p < 0.001) mortality for men but no significant evidence for all-cause ( p = 0.968) or CVD mortality ( p = 0.063) for women, though a test for a trend in the mortality function for women based on the year found a significant trend for CVD mortality ( p = 0.023)

For those with type 1 diabetes, the estimated remaining LE at age 20 increased from 47.7 (95% CI 46.6, 48.9) and 51.7 years (95% CI 50.3, 53.2) in 2002–06 to 49.8 (95% CI 49.0, 50.7) and 51.9 years (95% CI 50.9, 52.9) in 2007–11 for men and women, respectively. Male LE significantly increased by 2.1 years (95% CI 0.7, 3.4), but female LE was unchanged (95% CI −1.6, 1.9). Figure 2a, b compares the expected remaining LE at each age for men and women with type 1 diabetes with that of the general population.

Remaining LE for those with type 1 diabetes compared with the general population. ( a ) Men; and ( b ) women. Blue, NDR population with type 1 diabetes 2002–06; red, NDR population with type 1 diabetes 2007–11; green, general population 2002–06; orange, general population 2007–11. Dotted lines represent 95% CI around the expected remaining LE at each age for the NDR population

LE gaps and SMRs compared with the general population for people with type 1 diabetes in Sweden

Overall, the Swedish LE gap at age 20 between those with type 1 diabetes and the general population changed from 11.4 (95% CI 10.2, 12.4) to 10.2 years (95% CI 9.4, 11.1) for men and from 11.6 (95% CI 10.1, 13.0) to 12.0 years (95% CI 11.0, 13.0) for women from 2002–06 to 2007–11. Neither of these changes was significant. The 2002–06 SMR for men and women with type 1 diabetes compared with the general population was 3.03 (95% CI 2.76, 3.31) and 3.38 (95% CI 2.98, 3.82), respectively. For 2007–11, the SMR was significantly lower at 2.56 (95% CI 2.37, 2.75) for men, while there was no significant change for women (3.74 [95% CI 3.42, 4.06]). Similar results hold for the extended sample including all those diagnosed < 30 years of age (see ESM Results ).

Testing for linear trends in mortality with survival models

The Cox proportional hazards model with only a linear trend and age at diagnosis included shows men with type 1 diabetes experienced a significant negative trend in terms of mortality with HR 0.971 (95% CI 0.950, 0.992) implying an approximate 3% reduction in mortality per year from 2002 till 2011 (Table 2 ). The same trend was absent for women, being both very small and not significant (0.996 [95% CI 0.970, 1.023]) (see ESM Fig. 2 for non-linear trend results). The second model in Table 2 estimated the HR for the trend for mortality relative to the general population to be 0.993 (95% CI 0.972, 1.016) and 1.017 (95% CI 0.990, 1.044) for men and women, respectively. These are insignificant and close to 1, suggesting a consistent trend in mortality for both the populations with type 1 diabetes and the general Swedish population. The third model in Table 2 illustrates that after controlling for changes in a number of clinical risk factors over time, the male trend in mortality was no longer significant (95% CI 0.979, 1.032). Significant risk factors for both male and female mortality included HbA 1c , BMI, BP, triacylglycerol, microalbuminuria, macroalbuminuria, eGFR and smoking status. High BMI and systolic BP are, however, significant predictors of lower mortality after controlling for other factors. The results do not change when possible selection bias is accounted for (see ESM Results ) and when multiple imputation is conducted for missing risk factor values (see ESM Results ).

Type 1 diabetes mortality trends by cause of death

Figure 1c, d shows the cumulative CVD mortality events for men and women with type 1 diabetes and the general population. There were improvements for both men and women with type 1 diabetes over the two periods, but only the improvements in men were significant with logrank testing. Large differences were observed for CVD mortality events for those with type 1 diabetes vs the general population. However, renal and other causes showed little change over time (see ESM Fig. 3 ).

Table 3 shows the linear trends in mortality, by sex, using Cox competing mortality models for CVD, renal disease and other mortality. Of the 1,183 total deaths in men, 50% (588) were related to CVD, 6% (66) to renal disease and 45% (529) to other causes. For the 833 deaths in women, 48% (404), 6% (49) and 46% (380) were classified as related to CVD, renal disease and other causes, respectively. The Cox competing risk models for CVD mortality showed a significant reduction in mortality over time, with a per year HR of 0.947 (95% CI 0.917, 0.978) for men and 0.952 (95% CI 0.916, 0.989) for women. This suggests for both sexes an approximate 5% relative reduction in CVD mortality rates per year. As expected, an earlier age at diagnosis significantly increased cardiovascular mortality for both men and women. There was no significant relationship found between age at diabetes diagnosis and mortality for renal disease or other causes, though given the small number of deaths related to renal disease there was little power to detect such a relationship. A significant positive trend was found for other-cause mortality for women with type 1 diabetes relative to the general population.

The estimated mortality rates of those with type 1 diabetes at different ages were comparable but slightly lower than those found in other studies [ 15 ]. From 2002–06 to 2007–11 the LE of those with type 1 diabetes in Sweden increased for men by about 2 years, with no comparable evidence of any increase for women. However, this has not significantly closed the LE gap with the general population for men in absolute terms as a similar improvement was seen in the general population. Given that the mortality trend for men disappeared when we controlled for risk factors, the secular trend for men could potentially be explained by changes in risk factors. When mortality was broken down into CVD, renal disease and other causes, we found that mortality relating to CVD significantly decreased from 2002–10 for both men and women. The improvement in CVD mortality coincided with the large increase in the proportion of the population with type 1 diabetes who reported being on lipid-lowering medication and the associated decrease in cholesterol over this period. However, similar relative improvements in the general Swedish population for CVD were also observed, which suggests a similar uptake in lipid-lowering medication in the general population [ 36 ]. Also, reductions in smoking rates for the population with type 1 diabetes were also likely to have contributed to the lower CVD mortality. For Swedes with type 1 diabetes at the age of 20, the LE gap vs the general population was about 10–11 and 11–12 years for men and women, respectively. Interestingly, the secular trend in mortality was no longer significant for men when we controlled for metabolic risk factors, many of which have a significant impact on mortality (e.g. the association between triacylglycerol level and mortality for both men and women) [ 37 ]. The seemingly counterintuitive results for BMI may be because a high BMI is a marker for good historic glycaemic control—in the DCCT study the intensive-treatment group had significantly higher BMI [ 38 ]—or because the positive effects of greater lean mass in overweight and obese older people counterbalance the negative effects of greater fat mass on mortality [ 39 ]. In addition, low systolic BP may be a marker for underlying poor health rather than a cause of mortality, particularly in people with heart failure [ 40 ].

The Swedish LE results for 2007–11 can be compared with evidence from Scottish people with type 1 diabetes (2008–10), where the remaining LE at age 20 for men was estimated to be 46.2 years (95% CI 45.3, 47.3) and for women 48.1 years (95% CI 46.9, 49.3) [ 17 ]. Thus, 20 year olds with type 1 diabetes in Sweden have, on average, an LE 3.5 (95% CI 2.2, 4.8) and 3.8 years (95% CI 2.2, 5.2) longer than their Scottish counterparts for men and women, respectively. The Swedish type 1 diabetes LE gaps with the general population at age 20 are smaller than the Scottish gaps by 0.8 (95% CI −0.5, 2.2) and 0.9 (95% CI −0.6, 2.4) years for men and women, respectively, though these are not significant [ 17 ]. The SMRs estimated in this study are of a similar magnitude to those found in a cohort covering a similar time span in Denmark [ 15 ], but were significantly lower than the SMRs found for men (3.8) and women (5.8) in a recent meta-analysis [ 41 ]. The ratio of female to male SMRs was lower in Sweden for the period 2002–06 (1.12), but higher for the period 2007–11 (1.46) than the ratio in a recent meta-analysis (1.37) [ 41 ]. However, care needs to be taken when making conclusions by comparing SMRs across populations with differences in underlying mortality risk because a larger relative difference in mortality may still be a smaller difference in absolute terms [ 42 , 43 ]. This also applies to the current paper where gaps in LE are reported in absolute terms while the trends in the Cox regressions examine mortality differences in relative terms.

Compared with previous studies that have estimated LE in people with type 1 diabetes [ 5 , 17 ], the strengths of this study are the large representative sample, the long length of follow-up, measurement of clinical risk factors and completeness of data. This is attributable to the NDR data, a large register that has been linked to hospital, prescription and death data. The NDR includes the vast majority of the Swedish type 1 diabetes population; 91% of 18–34 year olds identified with type 1 diabetes from a 2009 prescribing registry data could be matched to those in the NDR [ 44 ]. This makes the consistent estimation of life tables for this population possible. However, participation in the NDR is not compulsory and our analysis requires patients to make at least one clinic visit in or after 2002; hence our analysis may have excluded a small proportion of the older and sicker patients in the earlier years. The NDR tracks patients using their personal identification number. However, for patients who emigrate it is not possible to know whether or when they died, or information that would allow them to be censored. Those alive and without at least one insulin prescription filled per year after 2005 were excluded from the analysis, and this should have excluded all those with type 1 diabetes who emigrated. Given the short-term nature of the data available, the LE estimates are from period life tables rather than cohort life tables. This means that recent improvements in care that take time to translate into reduced mortality may not show up in such an analysis. In addition, there may be misclassified causes of death [ 45 ], with renal-disease-related deaths misclassified as CVD or vice versa [ 13 ]. The Swedish renal mortality rates reported here are lower than those previously seen in a younger Japanese and US cohort where an expert committee based the cause of death classification on information from the attending physician or death certificates [ 14 , 46 – 48 ]. However, the rates of end stage renal disease (ESRD) for those with type 1 diabetes in Sweden have previously been found to be low [ 49 ].

There is still some way to go in terms of improvement in care for those with type 1 diabetes in order to close the gap with the general population. A significant proportion have elevated HbA 1c levels and a recent paper based on the Swedish NDR highlighted the stark differences in mortality for those with well-controlled vs poorly controlled HbA 1c [ 50 ]. In addition, with 10% of men and 13% of women still reported as current smokers in 2011, additional smoking cessation programmes could generate further improvements. While there have been large increases in the use of lipid-lowering medication, further expansion could generate additional gains given this population’s high underlying CVD risk. Future research might also provide individual specific LE estimates based on an individual’s characteristics in terms of their age at diagnosis, and risk factor and comorbidity profiles. This would provide useful information for an individual and allow them to better grasp the likely benefits of improving their overall risk.

Abbreviations

Estimated GFR

End stage renal disease

Life expectancy

Swedish National Diabetes Register

Standardised mortality ratio

Urinary albumin excretion rate

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Centre for Health Policy, Melbourne School of Population and Global Health, University of Melbourne, Carlton, Melbourne, VIC, 3053, Australia

Dennis Petrie, Tom W. C. Lung & Philip Clarke

The George Institute for Global Health, University of Sydney, Sydney, NSW, Australia

Tom W. C. Lung

Institute of Medicine, Sahlgrenska University Hospital, University of Gothenburg, Gothenburg, Sweden

Aidin Rawshani, Ann-Marie Svensson & Björn Eliasson

The Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia

Andrew J. Palmer

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Correspondence to Dennis Petrie .

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The Swedish Association of Local Authorities and Regions funds the NDR. The study was supported in part by a National Health and Medical Research Council (NHMRC) Project Grant (1028335). This research was supported under the Australian Research Council’s Discovery Early Career Awards funding scheme (Project DE150100309). The views expressed herein are those of the authors and are not necessarily those of the Australian Research Council.

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DP, AP, BE, A-MS and PC contributed to the conception and design of the study; DP, TL, AR, AP, BE, AS and PC were involved in the data collection, analysis and interpretation; and DP, TL, AP and PC were involved in drafting the manuscript. All authors reviewed/edited the manuscript and approved the final version. DP is the guarantor of this work.

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Petrie, D., Lung, T.W.C., Rawshani, A. et al. Recent trends in life expectancy for people with type 1 diabetes in Sweden. Diabetologia 59 , 1167–1176 (2016). https://doi.org/10.1007/s00125-016-3914-7

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Accepted : 19 February 2016

Published : 05 April 2016

Issue Date : June 2016

DOI : https://doi.org/10.1007/s00125-016-3914-7

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Type 1 Diabetes in Sweden

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Type 1 Diabetes is a dangerous autoimmune condition that can affect anyone in Sweden.

Type 1 diabetes is growing rapidly and can affect anyone, in sweden, t1d is growing at 2.9% each year compared with 2.2 % for type 2 diabetes.

“In too many places, T1D is an invisible disease, not on the radar of the healthcare community and often diagnosed only when it's too late.” - James Reid, Program Officer, Helmsley Charitable Trust

Type 1 diabetes is a dangerous condition that steals years of healthy life

The average ten year old in sweden enjoys 84 healthy years of life, if they develop type 1 diabetes, on average they will lose 18 of those healthy years.

“With type 1 diabetes once you get to the point where your body makes no insulin, you need insulin to survive, or you will die. The commonest cause of death for young people with diabetes globally is a lack of diagnosis right at the start.” - Dr Graham Ogle, paediatric endocrinologist, General Manager, Life for a Child

There are four things we can do to change the story for type 1 diabetes

With access to timely diagnosis unknown years, with access to insulin and strips unknown years, with access to pumps and cgms 4.4 healthy years can be restored, with access to prevention and cures full life can be restored, timely diagnosis.

In Sweden an unknown number of young people are never diagnosed. Globally we estimate 36,000 are lost to T1D each year without ever receiving a diagnosis.

Simple things, like a $1 educational poster can help make a diagnosis and save a life.

Insulin and strips

0 healthy years restored

If everyone in Sweden had access to insulin, test strips and good self-management, we could restore 0 years of healthy life per person

If everyone with type 1 diabetes in sweden received insulin and glucose test strips, we could restore 0 years of healthy life per person.

Management of type 1 diabetes involves multiple daily injections and frequent monitoring

In Sweden, 771 people are not alive today for the sake of a small vial of insulin and a tiny test strip.

Each extra test strip used can add 1 hours of healthy life.

Together we can change the story for people living with type 1 diabetes in Sweden.

Pumps and CGMs

4.4 healthy years restored

If everyone in Sweden had access to devices, we could restore another 4.4 healthy years to the average person with type 1 diabetes.

If everyone in sweden had access to technology that automates glucose monitoring and insulin delivery, we could restore 4.4 years of healthy life per person.

Without devices, the average person with type 1 diabetes spends 18 days a year managing the condition

Devices like pumps and CGMs reduce the work of managing type 1 diabetes.

CGM sensors are usually replaced twice a month. Every time it restores 39.7 hours of healthy life to the average person in Sweden with type 1 diabetes

Prevention and cures

full life expectancy restored

To restore all the years lost to type 1, we need to continue investing in prevention and cures.

To restore all the years lost to Type 1 diabetes, we need to continue investing in prevention and cures.

Research works—In the last 50 years of progress

25 years have been added to the lifespan of a person receiving the latest care.

We are working to make T1D a thing of the past.

One day we will discover how to restore the body's ability to make insulin again—eradicating T1D

Help us turn type 1 into type none through impactful research.

Together we can change the story for people living with type 1 diabetes in Sweden

There are four things we can do to map a better future for type 1 diabetes, intervention 1.

Only visible on mobile

Final slide only visible on mobile Intervention 2 Intervention 3 Intervention 4

Intervention 2

Final slide only visible on mobile

Intervention 3

Intervention 4, final action.

With delayed animation

Content Warning

People who should still be alive today, healthy years lost, definitions:.

'People who should still be alive today' are people who would still be alive if they had not died young due to T1D

'Healthy years of life lost' is an estimate of how much time the average person who develops T1D loses over their lifetime. It includes time invested in treatment, a percentage deduction for any years lived with disabilities, and time lost to shortened lives. It's similar to the DALY metric .

How we calculate average family size

Population growth, loss case study.

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How we calculate healthy years lost

Here's a quick breakdown of those factors for Sweden and its leading peers (i.e. top 25% of countries in the same income group):

	Sweden	Leading peers
Treatment/care	3.3 years	2.6 years
Complications	7.6 years	6.7 years
Shorter life	6.9 years	7.7 years
Cost of care	TBD*	TBD*
Mental health	TBD*	TBD*
Quality of life	TBD*	TBD*

But simple things like a $1 educational poster can help make a diagnosis and save a life.

Insulin and Strips

How blood sugar levels affect risks in type 1 diabetes

28 August 2019

A major new study from Linköping University and Sahlgrenska Academy, University of Gothenburg, on the association between blood glucose levels and risks of organ impairment in people with type 1 diabetes can make a vital contribution to diabetes care, in the researchers’ view.

Close up of Doctor taking sample of diabetic patient's blood using lancet pen,Healthcare and Medical concept

The Swedish study now published in BMJ (British Medical Journal) covers more than 10,000 adults and children with type 1 diabetes. Using the Swedish Diabetes Register, the researchers have been able to monitor the study participants for 8–20 years.

The researchers analyzed existing risks at various long-term blood glucose (sugar) levels, averaged over a two- to three-month period. The results of the study are particularly interesting given that there is no international consensus on the optimal blood glucose level to aim for.

Risks at various levels

For many years, a biomarker known as HbA1c has been used to measure mean blood glucose levels. In Sweden, the target HbA1c value in people with type 1 diabetes is 52 mmol/mol or below, and 47 or lower in children. Elsewhere in the world, the guidelines range from 48 to 58 mmol/mol, and are often higher in children than in adults.

“We were unable to see that fewer instances of organ damage occurred at these lower levels. As for loss of consciousness and cramp, which are unusual, low blood glucose caused a 30 percent rise in risk. Patients with low HbA1c need to make sure they don’t have excessively low glucose levels, fluctuations or efforts in managing their diabetes,” says Marcus Lind, professor of diabetology and first author.

Knowledge for parents too

“Knowing more about the association between blood glucose level and risk is extremely important since the health care services, the community, patients and their parents make heavy use of resources in attaining a particular blood glucose level. Attaining a low HbA1c value may, in some cases, require children to be woken up several times a night, plus extra glucose monitoring and strict attention to diet and physical activity day after day, which can be extremely burdensome”, Ludvigsson says. Article:   HbA1c level as a risk factor for retinopathy and nephropathy in children and adults with type 1 diabetes: Swedish population-based cohort study

Johnny Ludvigsson

Professor Emeritus

Department of Biomedical and Clinical Sciences (BKV)
Division of Children's and Women's Health (BKH)
johnny.ludvigsson@ liu.se
+4613286854

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Department of Clinical and Experimental Medicine (IKE)
Faculty of Medicine and Health Sciences (MEDFAK)

RESEARCH DESIGN AND METHODS

Conclusions, acknowledgments, east africans in sweden have a high risk for type 1 diabetes.

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Anders Hjern , Ulf Söderström , Jan Åman; East Africans in Sweden Have a High Risk for Type 1 Diabetes . Diabetes Care 1 March 2012; 35 (3): 597–598. https://doi.org/10.2337/dc11-1536

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To investigate the prevalence of type 1 diabetes in children with an origin in Sub-Saharan Africa in Sweden.

Nationwide register study based on retrieved prescriptions of insulin during 2009 in children aged 0–18 years. The study population consisted of 35,756 children in families with an origin in Sub-Saharan Africa and 1,666,051 children with native Swedish parents.

The odds ratio (OR) for insulin medication in Swedish-born children in families originating in East Africa was 1.29 (95% CI 1.02–1.63) compared with offspring of native Swedish parents, after adjustment for age and sex, and less common in children who themselves were born in East Africa: 0.50 (0.34–0.73). Offspring of parents from other parts of Sub-Saharan Africa had a comparatively low risk for insulin medication.

This study indicates that Swedish-born children with an origin in East Africa have a high risk of type 1 diabetes.

The incidence of type 1 diabetes varies greatly among different populations in the world ( 1 ). Finland is the nation with the highest recorded population rate in the world followed by Sweden in second place, whereas the incidence has been found to be particularly low in East Asia (Korea) ( 2 ). The incidence in Sub-Saharan Africa is not well known ( 2 ), but available studies have shown low rates of type 1 diabetes in child populations ( 3 ), with a prevalence ranging from 3.5 to 12 out of 100,000 ( 4 , 5 ). In this study, we exploit the information available in Swedish national registers to investigate the prevalence of type 1 diabetes in child populations, with an origin in Sub-Saharan Africa in exile in Sweden.

This study was based on Swedish national registers held by the National Board of Health and Welfare and Statistics Sweden. All Swedish residents are assigned a unique 10-digit identification number at birth or immigration. This identification number was used to link information from different register sources after the study had been approved by the regional ethics committee in Stockholm.

Study population

All individuals born in 1991–2008, who were alive and registered as residents in Sweden on 31 December 2008, were identified in the Register of the Total Population (RTB). Biological and/or adoptive parents of these individuals were identified in the Multi-Generation Register.

Information about region of birth, date of immigration, sex, and year of birth in RTB was linked to the study subjects and their parents. On the basis of this information, we categorized the offspring of two parents born in a country in Sub-Saharan Africa into Swedish-born and Africa-born by the child’s own record of country of birth. These categories were further divided into East Africa (Ethiopia, Somalia, and Eritrea) and South and West Africa by parental country of birth. Children with a record of adoption in the Multi-Generation Register were excluded from the study population. To this population of 35,756 children in families with an origin in Sub-Saharan Africa, we added 1,666,051 Swedish-born residents with two native Swedish parents as a comparison group.

The Swedish Prescribed Drug Register contains data with unique patient identifiers for all drugs prescribed and dispensed to the whole population of Sweden (>9 million inhabitants) since July 2005 ( 6 ). The retrieval of at least one prescription of a drug with an Anatomical Therapeutic Chemical-code that started with A10A (insulin-containing drugs) during the calendar year 2009, according to this register, was used to create the outcome variable of the study: insulin.

To check the validity of this variable, we also identified all patients in the Swedish Patient Discharge Register who had been discharged with a diagnosis equivalent to E10 in ICD-10, insulin-dependent diabetes/type 1 diabetes, in all Swedish-born individuals in the study population during 1990–2008. A total of 99.4% of all children with insulin medication in 2009 had been discharged with such a diagnosis, and 96.0% of all who had been discharged with such a diagnosis had received insulin medication in 2009.

Statistical analysis

Logistic regression was used to calculate odds ratios (OR) with 95% CI with insulin medication during 2009, defined above, as the outcome variable. We adjusted the analysis to age in a linear fashion, in accordance with the roughly linear increment in prevalence of insulin medication, and to sex. All statistical analyses were performed using SPSS version 18.0 for Windows.

There were 8,047 children in the age range of 0–18 years with Swedish-born parents and 107 children with parents born in Sub-Saharan Africa who had retrieved at least one prescription of insulin during 2009.

Table 1 presents incidence rates and demographic patterns in the study groups. Swedish-born offspring of parents born in Eritrea had the highest overall incidence of 6.7 out of 1,000, whereas the lowest incidence, 0.7 out of 1,000, was found in African-born offspring of parents from South and West Africa. Swedish-born offspring of parents from all of East Africa had an OR of 1.29 for type 1 diabetes compared with the Swedish comparison group, whereas children who themselves were born in East Africa had an OR of only 0.50. Swedish-born and African-born children with parents born in South and West Africa had ORs of only 0.30 and 0.11, respectively.

Demographic indicators and offspring medication with insulin during 2009 by own and parental country/region of birth in children aged 0–18 years

This study indicates that populations with an origin in East Africa have a high risk to develop type 1 diabetes when they are born and raised in exile in a high-income country such as Sweden. The lower risk in children who themselves were born in East Africa has to be interpreted with caution, because type 1 diabetes might often be an undetected and deadly disease in this impoverished region and may also go undetected to a certain extent during the first years in exile.

Previous Swedish studies of children in immigrant families with an origin in regions with low or moderate rates of type 1 diabetes have demonstrated that the risk of type 1 diabetes tends to remain on the same level as the population of origin for children who were born in the same country as their parents, whereas it tends to increase for children born in Sweden ( 7 , 8 ). The rate of type 1 diabetes in the children who themselves were born in East Africa in this study was much higher than previous studies conducted in this region. If rates for East African immigrants also tend to remain on the same level as in the country of origin, this study suggests that previous studies in this region may have grossly underestimated the risk of type 1 diabetes. It is, however, also possible that East Africans are vulnerable to yet unidentified environmental risk factors in a high-income country such as Sweden. Further studies in Africa and Sweden are needed to clarify these issues.

This study was funded by the National Board of Health and Welfare and the Södermanland County Council.

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

A.H. designed this study, analyzed the data, and wrote the first draft of the manuscript. U.S. and J.A. reviewed and edited the manuscript. A.H. 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.

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Diabetes Can Age the Brain, but a Healthy Lifestyle Could Slow the Clock

Type 2 diabetes can increase the brain’s biological age by as much as 4 years — but physical activity and other positive lifestyle habits can counteract that effect.

The findings, however, highlight that physical activity, abstention from smoking, and avoiding heavy alcohol consumption could help keep brains young.

Elevated Blood Sugar Could Add Years to Brain Age

For the analysis, the researchers referred to medical information from more than 31,000 dementia-free adults from the UK Biobank, which included measures of cardiometabolic risk factors ( obesity , hypertension , and cholesterol) as well as lifestyle behaviors like smoking, drinking, and physical activity.

According to the data, 53 percent had normal blood glucose, 43 percent were considered prediabetic, and 4 percent had type 2 diabetes.

By using a machine learning model, the researchers were able to estimate brain age in relation to a patient’s chronological age.

The results, published this week in the journal Diabetes Care , showed that type 2 diabetes was associated with brains that were 2.3 years older than their chronological age, while prediabetes increased brain aging by about four months.

The researchers further noted that the brains of individuals with poorly controlled diabetes appeared more than four years older than their chronological age.

When they reviewed a subset of about 2,400 patients who underwent up to two MRIs over a follow-up of 11 years, researchers observed a slight increase in brain aging over time in patients with diabetes — just over three months annually.

“This study shows that even slightly high glucose levels — that aren't considered high enough to be diabetes but are consistent with prediabetes — can affect the brain and cause the brain to age more rapidly,” says Susan Elizabeth Spratt, MD , a professor of medicine at Duke University in Durham, North Carolina, with a specialty in endocrinology, metabolism, and nutrition, who was not involved in the current research.

What Magnetic Resonance Imaging Reveals

Through the use of MRIs, scientists captured measures such as brain volume, thickness of the cortex (also called gray matter, or the brain's outermost layer of nerve cell tissue), and degradation of white matter (networks of nerve fibers in the brain).

While this type of imaging may give detailed insight into brain aging for research, it may not be practical for evaluating cognition, according to Ajaykumar D. Rao, MD , the chief of the section of endocrinology, diabetes, and metabolism at the Lewis Katz School of Medicine at Temple University in Philadelphia, who was not involved in the study.

“We can't be subjecting all those living with prediabetes and diabetes to multiple MRIs — they may not be clinically meaningful,” says Dr. Rao, who was not involved in the study. “I think it's important for those patients to meet with their primary care teams and discuss whether they should undergo neurocognitive testing.”

How Healthy Living Helps

On the positive side, the study authors found that certain lifestyle habits significantly reduced the chances of rapid brain aging.

For Thomas Vidic, MD , an adjunct clinical professor of neurology at Indiana University School of Medicine at South Bend and a practicing physician at the Elkhart Clinic, the results were not surprising, since diabetes causes vascular disease and inflammation, and those factors can affect blood supply to the brain and affect brain tissue. Exercise, on the other hand, can improve blood flow to the brain. He further stresses that alcohol and smoking can be toxic to brain cells, while abstention protects them.

“Brain health is a lifelong process, and we need to take care of all aspects of brain health throughout our lifetime,” says Dr. Vidic, who is also a fellow of the American Academy of Neurology and not an author of the new study. “It's not one of those things that you turn 65 and say, ‘I need to get started on this.’”

Everyday Health follows strict sourcing guidelines to ensure the accuracy of its content, outlined in our editorial policy . We use only trustworthy sources, including peer-reviewed studies, board-certified medical experts, patients with lived experience, and information from top institutions.

Malik A et al. Cognitive Impairment in Type 2 Diabetes Mellitus. Cureus . February 14, 2022.
Xu W et al. Mid- and Late-Life Diabetes in Relation to the Risk of Dementia. Diabetes . January 2009.
Dove A et al. Diabetes, Prediabetes, and Brain Aging: The Role of Healthy Lifestyle. Diabetes Care . August 28, 2024.
A Healthy Lifestyle May Counteract Diabetes-Associated Brain Aging. Karolinska Institute . August 28, 2024.
Adult Activity: An Overview. Centers for Disease Control and Prevention . December 20, 2023.

Don Rauf has been a freelance health writer for over 12 years and his writing has been featured in HealthDay, CBS News, WebMD, U.S. News & World Report, Mental Floss, United Press International (UPI), Health , and MedicineNet. He was previously a reporter for DailyRx.com where he covered stories related to cardiology, diabetes, lung cancer, prostate cancer, erectile dysfunction, menopause, and allergies. He has interviewed doctors and pharmaceutical representatives in the U.S. and abroad.

He is a prolific writer and has written more than 50 books, including Lost America: Vanished Civilizations , Abandoned Towns , and Roadside Attractions . Rauf lives in Seattle, Washington.

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Sleep duration in type 2 and tackling the type 1 immune attack: Research Highlights August 2024

Diabetes UK shares the biggest diabetes research stories of 2020

In this series we take a look at some of the exciting diabetes research developments announced recently, and what the findings could mean for people living with or affected by diabetes.

Psoriasis medication might help to stop the type 1 immune attack

Immunotherapies have the potential to transform how we treat type 1 diabetes by tackling its root cause for the first time and moving us closer to preventing and curing the condition.

Right now, our researchers are developing and testing several different types of immunotherapies for type 1 diabetes. These work in different ways, but all are designed to stop the immune system from attacking insulin-making beta cells in the pancreas.

The findings of a recent study suggest that an immunotherapy medication currently used to treat the skin condition psoriasis, called Ustekinumab, might also be beneficial for type 1 diabetes by helping to shield insulin-making beta cells from the immune system attack.

Researchers at Cardiff, King’s College London, Swansea, and the University of Calgary tested Ustekinumab in adolescents aged between 12 and 18 years who were newly diagnosed with type 1 diabetes.

Forty-one participants received the drug and 21 in the control group took a placebo. After 12 months, C-peptide levels, a marker of insulin production, were found to be 49% higher in the group who received Ustekinumab than C-peptide levels in the control group. The increase in insulin production in the Ustekinumab group was linked to a decrease in the number of destructive immune cells.

Ustekinumab was found to be safe and tolerated by the participants, although it needs to be tested in larger groups of people who differ in age and stages of type 1 diabetes in further trials.

How tiny blood vessels are impacted by sleep duration in type 2 diabetes

Diabetes can cause complications on a tiny scale which can have a very big impact. These ‘microvascular’ complications, like retinopathy , which affects the eyes, result from damage to small blood vessels. This damage can harm larger blood vessels, and lead to the development of macrovascular complications, like coronary artery disease or stroke.

A growing body of evidence suggests that the risk of developing these diabetes-related complications is influenced by sleep quantity and quality. Now researchers in Denmark have showed that, in people living with type 2 diabetes , getting too little or too much sleep is linked to an increased risk of damage to small blood vessels.

The team explored whether sleep duration is linked to microvascular damage in 396 people newly diagnosed with type 2 diabetes. They classified sleep duration into three categories: short (less than 7 hours), optimal (between 7-9 hours), and long (9 hours or more), and identified those with microvascular damage by assessing specific markers in the blood and by the presence of retinopathy.

The researchers found that the proportion of people with microvascular damage was 38%, 18%, and 31% for short, optimal, and long sleep duration groups respectively. Short sleep duration was linked with a 2.6-fold increased risk of microvascular damage compared with optimal sleep duration. Similarly, long sleep duration was linked to a 2.3-fold elevated risk compared to optimal sleep duration.

The risk of microvascular damage was particularly heightened in older people who didn’t get enough sleep. Participants aged 62 years and over who slept less than seven hours had a 5.7 times increased risk of small blood vessel damage compared to people the same age in the optimal sleep duration group. This finding suggests that older individuals with type 2 diabetes who habitually sleep less than seven hours a night may be more vulnerable to diabetes complications.

These findings will be presented at the Annual Meeting of the European Association for the Study of Diabetes (EASD) in September.

The unique pieces in the puzzle of diabetes distress

Diabetes distress is what people feel when they are overwhelmed by the relentlessness of living with diabetes. Diabetes distress can make it much harder to manage the condition which in turn can increase the risk of diabetes complications.

We need to understand what drives diabetes distress and how to alleviate it. While technology to track blood sugars in real-time (continuous glucose monitoring or CGM) can help with daily diabetes management, not much is known about if CGM adds to or reduces diabetes distress.

A research team from Germany has recently investigated if diabetes distress is most influenced by what people perceive their blood sugars to be or by actual CGM readings. They conducted an observational study over 17 days on 379 participants with type 1 diabetes or type 2 diabetes.

They combined data collected using an app with CGM data to map links between blood sugars and diabetes distress. The app gathered people’s perceptions of their blood sugars (the extent to which they felt burdened by low, high, and fluctuations in their blood sugars) and CGM-recorded blood sugar data. Participants were followed up three months later.

Overall, findings showed that how people perceived their blood sugars was more influential on diabetes distress than blood sugar data collected by CGM.

Those whose distress was mostly linked to their perception of their blood sugars also reported poorer mental health at the three-month follow up. Whereas individuals whose distress was more strongly driven by their CGM-collected data had better mental health at three months. However, the researchers found there were a lot of differences in how people responded to perceived and CGM-collected blood sugar levels.

These varying results crucially highlight the need to further understand the complex drivers of diabetes distress and that the experience of diabetes distress is unique for each person.By increasing this knowledge, personalised treatment strategies can be developed.

Clarity in a sea of mixed results: gestational diabetes & breast cancer

Gestational diabetes occurs when pregnancy hormones make the body less sensitive to insulin. This is known as insulin resistance and results in high blood sugar levels.

Insulin resistance has also been linked to breast cancer. However, whether gestational diabetes increases the risk of breast cancer is contested in the research world, with some studies suggesting that it increases the risk while others that it decreases the risk.

In one of the largest studies to date on gestational diabetes and breast cancer, researchers from Denmark looked at data over a 22-year period on over 700,000 women who gave birth in Denmark. The researchers studied the women for nearly 12 years. Findings showed that 24,140 women developed gestational diabetes in one or more pregnancies and 7,609 women were diagnosed with breast cancer.

This study concluded that women who had gestational diabetes were no more likely to develop breast cancer than those without gestational diabetes. This was the case across all cancer categories: breast cancer overall, premenopausal breast cancer, and postmenopausal breast cancer.

Despite this, Dr Christensen urged women with gestational diabetes to remain vigilant:

"(They) need to be alert to the fact that they are at higher risk of some conditions, including type 2 diabetes. And all women, regardless of whether or not they have had gestational diabetes, should be breast aware and check their breasts regularly for changes."

It’s important to note that the study population were predominantly Caucasian so now we need further research into other populations and healthcare systems.

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Diabetes Ther
v.15(9); 2024 Sep
PMC11330427

PIONEER REAL Sweden: A Multicentre, Prospective, Real-World Observational Study of Oral Semaglutide Use in Adults with Type 2 Diabetes in Swedish Clinical Practice

Sergiu-bogdan catrina.

1 Department of Molecular Medicine and Surgery, Karolinska Institute, Stockholm, Sweden

2 Centrum for Diabetes, Academic Specialist Centrum, Stockholm, Sweden

7 K1 Molekylär Medicin Och Kirurgi, K1 MMK Tillväxt & Metabolism, 171 76 Stockholm, Sweden

Hanan Amadid

3 Novo Nordisk A/S, Søborg, Denmark

Uffe C. Braae

Jonatan dereke, neda rajamand ekberg, boris klanger.

4 LäkarGruppen, Källgatan 10, 722 11 Västerås, Sweden

Stefan Jansson

5 Faculty of Medicine and Health, University Health Care Research Center, Örebro University, Örebro, Sweden

6 Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden

Associated Data

Data are available upon reasonable request. Data will be shared with bona fide researchers submitting a research proposal approved by the independent review board. Access request proposals can be found at novonordisk-trials.com. Data will be made available after research completion and approval of the product and product use in the European Union and the United States. Individual participant data will be shared in data sets in a de-identified/anonymised format.

Introduction

The study was designed to assess outcomes with once-daily oral semaglutide in adults with type 2 diabetes (T2D) naïve to injectable glucose-lowering agents, in Swedish clinical practice.

In this non-interventional, multicentre study, participants initiated oral semaglutide and were followed for 34–44 weeks. The primary endpoint was glycated haemoglobin (HbA 1c ) change from baseline to end of study (EOS). Secondary endpoints included body weight (BW) change from baseline to EOS, proportion of participants achieving HbA 1c < 7%, and proportion achieving both a HbA 1c reduction ≥ 1% and BW reduction of ≥ 3% or ≥ 5%, at EOS. Participants completed Diabetes Treatment Satisfaction Questionnaires (DTSQ status/change) and a dosing conditions questionnaire.

A total of 187 participants (mean age 62.5 years) initiated oral semaglutide. Baseline mean HbA 1c and BW were 7.8% ( n = 177) and 96.9 kg ( n = 165), respectively. Estimated mean changes in HbA 1c and BW were − 0.88%-points (95% confidence interval [CI] − 1.01 to − 0.75; P < 0.0001) and − 4.72% (95% CI − 5.58 to − 3.86; P < 0.0001), respectively. At EOS, 64.6% of participants had HbA 1c < 7%, and 22.9% achieved HbA 1c reduction of ≥ 1% and BW reduction of ≥ 5%. DTSQ status and change scores improved by 1.44 ( P = 0.0260) and 12.3 points ( P < 0.0001), respectively. Oral semaglutide was easy or very easy to consume for 86.4% of participants. Most common adverse events (AEs) were gastrointestinal disorders; nine participants (4.8%) had serious AEs; one (0.5%) experienced severe hypoglycaemia.

In this real-world study population, we observed significant reductions in HbA 1c and BW in people living with T2D when prescribed semaglutide tablets as part of routine clinical practice in Sweden, with improved treatment satisfaction among participants and no new safety concerns.

Trial Registration

NCT04601753.

Graphical Abstract

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Supplementary Information

The online version contains supplementary material available at 10.1007/s13300-024-01614-6.

Key Summary Points

The prevalence of type 2 diabetes is increasing in Sweden.

Oral semaglutide is routinely used for the treatment of type 2 diabetes but efficacy and safety data associated with its use in real-world clinical practice are scarce. The PIONEER REAL programme comprises 13 non-interventional studies, each in a different country, assessing the use of oral semaglutide in a real-world setting.

The PIONEER REAL Sweden study was designed to evaluate clinical outcomes in people with type 2 diabetes who initiated treatment with once-daily oral semaglutide in Swedish clinical practice.

We observed clinically significant improvements in glycaemic control and body weight, and improvements in treatment satisfaction. The safety profile reported was consistent with previous phase 3 clinical trials.

The findings of PIONEER REAL Sweden corroborate the results of the phase 3 PIONEER clinical trial programme and provide valuable insight into the use of once-daily oral semaglutide in a real-world adult population with type 2 diabetes.

Digital Features

This article is published with digital features, including a graphical abstract, to facilitate understanding of the article. To view digital features for this article, go to 10.6084/m9.figshare.26064211.

The prevalence of diabetes in Sweden among people aged 20–79 years was estimated at 5% in 2021 and it is projected to increase to 6% by 2045 [ 1 ]. Among individuals in Sweden with type 2 diabetes (T2D), delays in achieving glycaemic control and complications arising from T2D can have considerable negative impacts on individuals’ lives, in terms of work absenteeism, costs and life expectancy [ 2 , 3 ]. Therefore, effective T2D management is imperative [ 4 ]. The latest Swedish national diabetes guidelines for adults emphasise the importance of preventing T2D as well as preventing diabetes complications by addressing the risk factors that have the strongest relationship to cardiovascular disease (CVD). The guidelines therefore highlight the need for use of evidence-based treatment to control blood glucose, blood pressure and blood lipids, together with the treatment of lifestyle factors [ 4 ].

Achievement and maintenance of glycaemic control is central to T2D management; weight loss is a primary target to achieve this, to reduce cardiometabolic risk factors and improve people’s quality of life [ 5 ]. Traditionally, metformin was recommended as first-line glucose-lowering therapy; more recently, glucagon-like peptide 1 receptor agonists (GLP-1RA) and sodium-glucose co-transporter 2 (SGLT-2) inhibitors are recommended independently from metformin for individuals with, or at risk of, CVD, heart failure or chronic kidney disease (CKD), thanks to their benefits for CV and renal outcomes [ 6 ].

Semaglutide is a human GLP-1 analogue approved as an adjunct to diet and exercise for improving glycaemic control in adults with T2D; it is the first of its kind available for both once-weekly subcutaneous use (0.25, 0.5, 1.0 and 2.0 mg) and once-daily oral administration (3, 7 and 14 mg) [ 7 , 8 ]. The phase 3 PIONEER clinical development programme demonstrated superior reductions in glycated haemoglobin (HbA 1c ) and body weight with oral semaglutide versus placebo and several active comparators, along with a safety profile consistent with other GLP-1RAs, in participants with T2D [ 9 – 15 ].

The ongoing PIONEER REAL programme comprises 13 non-interventional phase 4 studies in Europe, North America, the Middle East and East Asia, with each study run in a separate country. The programme is investigating the use of oral semaglutide in routine clinical practice in real-world populations of adults with T2D who had not previously been treated with injectable glucose-lowering medications, to provide insights on how oral semaglutide performs in this setting. It is anticipated that the PIONEER REAL programme will involve over 3000 adults with T2D. To date, PIONEER REAL studies in Canada, Japan, Switzerland and in the Netherlands have been completed. The aim of the PIONEER REAL Sweden study was to assess the clinical outcomes associated with the use of once-daily oral semaglutide initiated within routine clinical practice in adults with T2D in Sweden (ClinicalTrials.gov registration NCT04601753).

Study Design and Procedures

PIONEER REAL Sweden was a non-interventional, single-arm, phase 4, prospective, open-label study conducted across 28 centres in Sweden. It was part of the wider PIONEER REAL clinical programme and, as such, had a similar study design, procedures and endpoints to PIONEER REAL Switzerland [ 16 ]. In PIONEER REAL Sweden, participants received oral semaglutide in accordance with Swedish clinical practice. Treatment initiation was at the treating physician’s discretion. At the start of the study (visit 1), participants or their legally acceptable representative provided informed consent, demographic and medical history data were collected, and treating physicians recorded the reason(s) for initiating oral semaglutide. Baseline data were collected at, or ≤ 90 days before, visit 1. Visit 1 was considered to have occurred when participants initiated once-daily oral semaglutide in accordance with local clinical practice. Participants could then have intermediate visits depending on local clinical practice (visit 2. x ) before the end of study (EOS) visit (visit 3) at 34–44 weeks. As a consequence of the coronavirus disease 2019 (COVID-19) pandemic participants were allowed to have EOS visits outside the study duration of 44 weeks at the discretion of the treating physician. The EOS visit between 34 and 44 weeks was registered as visit 3, but if a HbA 1c measurement was not available during that period, the first HbA 1c measurement taken after that time period and up to last participant last visit was recorded.

The study was conducted in line with Good Pharmacoepidemiology Practices [ 17 ] and Good Pharmacovigilance Practices [ 18 ], and physicians had to comply with applicable regulatory requirements and the requirements in the Declaration of Helsinki. Study-specific documentation was submitted to the relevant national body, and the study was approved by the independent ethics committee or institutional review board for each participating centre. The independent ethics committee for each site was Etikprövningsmyndigheten, Uppsala, Sweden. Participants provided written informed consent prior to commencement of any study-related activity.

Participants and Physicians

Male and female participants aged ≥ 18 years with a diagnosis of T2D and an available HbA 1c ≤ 90 days prior to visit 1 or a HbA 1c measurement at visit 1 in line with local clinical practice were included. Participants were also required to be treatment-naïve to injectable glucose-lowering drugs, except for short-term insulin treatment for acute illness lasting for a total of ≤ 14 days. Participants were excluded if they had previously participated in this study, had received treatment with an investigational drug ≤ 30 days prior to enrolment, or had mental incapacity, unwillingness or language barriers precluding understanding or co-operation.

Glycaemic and Weight Changes Over Time

The primary endpoint was change from baseline to EOS in HbA 1c (percentage-points). Key secondary endpoints included relative (percentage) and absolute (kilograms) change from baseline to EOS in body weight. Estimated changes from baseline in HbA 1c and body weight were analysed to EOS. Participants included in this analysis were those who had complete covariates dependent and variable information, and contributed to the primary analysis of mean change in HbA 1c and body weight.

Glycaemic and Weight Targets

Other key secondary endpoints included the proportion of participants with HbA 1c < 7% at EOS, the proportion of participants with both a reduction in HbA 1c of ≥ 1%-points and a body weight reduction of ≥ 3%, and the proportion of participants with both a reduction in HbA 1c of ≥ 1%-points and body weight reduction of ≥ 5% from baseline at EOS. Exploratory endpoints assessed the proportion of participants who achieved < 7% at EOS and the change from baseline in waist circumference (centimetres) to EOS.

Participant- and Physician-Reported Outcomes

The Diabetes Treatment Satisfaction Questionnaire status (DTSQs) and Diabetes Treatment Satisfaction Questionnaire change (DTSQc) were employed as key secondary endpoints and measured absolute (DTSQs) and relative (DTSQc) treatment satisfaction from baseline to EOS. The DTSQs was completed at visit 1 and visit 3, whereas the DTSQc was completed at visit 3 only. The DTSQs comprised eight items to measure participant satisfaction with their diabetes treatment, answered on a Likert scale from 0 (very dissatisfied) to 6 (very satisfied); six of the items were summed to produce a Total Satisfaction score. The DTSQc used the same eight items, but participants rated their change in treatment satisfaction with semaglutide versus before initiating oral semaglutide, on a scale of − 3 (much less satisfied now) to + 3 (much more satisfied now).

As an exploratory endpoint, a dosing conditions questionnaire was administered to participants at visit 3 or at the time of treatment discontinuation if discontinuation occurred prior to visit 3, to ascertain how semaglutide was taken and the ease of taking it. Physicians also assessed whether participants had achieved clinical success in relation to the reason for initiating oral semaglutide, at the EOS visit.

Treatment Patterns

Exploratory endpoints measured at EOS included the number of participants treated with oral semaglutide, semaglutide dose, and the addition or removal of glucose-lowering medications and increase or decrease in glucose-lowering medication doses.

Self-reported severe hypoglycaemia (requiring the assistance of another person to actively administer carbohydrate or glucagon, or take other corrective action) between baseline and visit 3 was recorded as an exploratory endpoint. All other adverse events (AEs) were recorded from visit 1 to visit 3 and were assessed by the treating physician.

Statistical Analysis

As outlined earlier, this study was part of the PIONEER REAL study programme and the statistical analysis has been previously described [ 16 ]. Here, we provide a brief summary. In total, 145 participants with HbA 1c measurements were needed to ensure 90% and 99% probability of detecting changes in HbA 1c of ≥ 0.46%-points and ≥ 1%-points from baseline, respectively. All clinical endpoints and safety evaluations were based on the full analysis set (FAS). A description of the FAS and observation periods (in-study and on-treatment) used for the primary and secondary analyses have been detailed previously [ 16 ]. Continuous secondary and exploratory endpoints were analysed using a mixed model for repeated measurements (MMRM) or analysis of covariance (ANCOVA, DTSQ endpoints) on the FAS (in-study observation period). Categorical secondary and exploratory endpoints were measured as proportions of participants at EOS, based on the FAS.

Analyses were performed with a crude and adjusted model. Estimated response and change in response analyses used the baseline measure in question (HbA 1c , body weight, DTSQs), age and baseline BMI as covariates, and sex, oral antidiabetics at baseline, diabetes duration and site as fixed factors. For change from baseline in HbA 1c and body weight, time and time-squared were also included as covariates; DTSQ analyses also included baseline HbA 1c as a covariate. Tests were performed as two-sided tests with a significance level of 0.05, with no adjustments for multiple comparisons.

Statistical analyses were conducted using SAS version 9.4 (SAS institute, North Carolina, USA). Information on the sensitivity analyses performed can be found in the supplementary materials (Appendix 1 ).

The study was performed between 12 November 2020 and 3 March 2023. Participants received oral semaglutide for a median (range) of 36.1 (0.1–87.7) weeks; the corresponding in-study and on-treatment median observation periods were 40.7 (3.7–87.9) and 36.3 (0.1–87.7) weeks, respectively.

Overall, 187 participants were enrolled and received oral semaglutide (the FAS); 141 were still on oral semaglutide treatment at the EOS visit (Fig. 1 ).

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Participant disposition. Abbreviations: EOS end of study, n number of participants. † Participants who initiated oral semaglutide and attended the EOS visit. ‡ Participants who were taking oral semaglutide and attended the EOS visit

A total of 178 participants attended visit 2, nine participants had no intermediate visit between visits 2 and 3, 68 participants had one intermediate visit, 49 participants had two intermediate visits, 31 participants had three intermediate visits and 30 participants had four or more intermediate visits. As a result of the COVID-19 pandemic, 31 (17.4%) participants attended visit 3 at 45–52 weeks and eight (4.5%) participants attended visit 3 after 52 weeks.

Participant characteristics are summarised in Table 1 . Most participants were aged 45–65 years, and 17.1% were ≥ 75 years old. Participants had a mean (SD) T2D duration of 6.8 years (5.7) at baseline. Mean (SD) HbA 1c was 7.7% (1.2) and 72.2% of participants had an HbA 1c level of ≥ 7% at baseline.

Table 1

Participant demographics, baseline characteristics and initiation of oral semaglutide (FAS)

Characteristic	Participants = 187
Male, (%)	121 (64.7)
Age in years, mean (SD)	62.5 (10.98)
Age group, (%)
< 45 years	10 (5.3)
45–65 years	96 (51.3)
65–75 years	49 (26.2)
> 75 years	32 (17.1)
Race, (%)
Asian	10 (5.3)
Black or African American	2 (1.1)
White	171 (91.4)
Other	4 (2.1)
Duration of T2D in years, mean (SD) [ ]	6.8 (5.7) [116]
Duration of T2D, (%)
≤ 1 year	11 (5.9)
1–5 years	61 (32.6)
5–10 years	53 (28.3)
> 10 years	62 (33.2)
Body weight in kg, mean (SD) [ ]	97.3 (19.5) [181]
Baseline body weight for participants who had a complete set of information for the primary analysis (SD) [ ]	96.9 (19.75) [165]
BMI in kg/m , mean (SD) [ ]	32.4 (5.8) [180]
Waist circumference in cm, mean (SD) [ ]	112.5 (13.4) [130]
Baseline waist circumference for participants who had a complete set of information for the primary analysis (SD) [ ]	111.5 (13.30) [101]
HbA
%, mean (SD)	7.7 (1.2)
mmol/mol, mean (SD)	61.0 (12.9)
Baseline HbA for participants who had a complete set of information for the primary analysis [ ]
%, mean (SD)	7.8 (1.23) [177]
mmol/mol, mean (SD)	61.7 (13.44) [177]
HbA level thresholds, (%)
< 14%	187 (100.0)
< 12%	184 (98.4)
< 10%	178 (95.2)
< 8%	128 (68.4)
< 7.5%	99 (52.9)
< 7%	52 (27.8)
CV-related medical history, (%)	121 (64.7)
CV-related medical history including CKD, microalbuminuria, haemoglobinopathy and dyslipidaemia, (%)	138 (73.8)
Calculated eGFR (CKD-EPI) in mL/min/1.73 m , mean (SD)	87.3 (18.25)
LDL cholesterol in mg/dL, mean (SD)	101.4 (41.51)
LDL cholesterol in mmol/L, mean (SD)	2.6 (1.08)
Systolic blood pressure in mmHg, mean (SD)	134.1 (14.05)
Diastolic blood pressure in mmHg, mean (SD)	79.7 (9.57)
Anti-diabetic medications, mean (SD)	1.2 (0.84)
Type of concomitant anti-diabetic medications, (%)
Metformin	147 (78.6)
Sulfonylureas	12 (6.4)
Thiazolidinediones	9 (4.8)
DPP4 inhibitors	9 (4.8)
SGLT2 inhibitors	40 (21.4)
Meglitinides	6 (3.2)
Other	3 (1.6)
Fixed-dose combination	6 (3.2)
Prescribed starting dose of oral semaglutide, (%)
3 mg	178 (95.2)
7 mg	9 (4.8)
14 mg	0 (0)

Abbreviations: ATC Anatomical Therapeutic Chemical, BMI body mass index, CKD chronic kidney disease, CKD-EPI Chronic Kidney Disease Epidemiology Collaboration, CV cardiovascular, DPP4 dipeptidyl peptidase 4, eGFR estimated glomerular filtration rate, FAS full analysis set, HbA 1c glycated haemoglobin, LDL low-density lipoprotein, N number of participants with data for characteristic (where different from total number of participants), n number of participants with given characteristic, SD standard deviation, SGLT2 sodium-glucose co-transporter 2, T2D type 2 diabetes

† Duration of T2D presented for participants who provided date of T2D diagnosis

‡ CV-related medical history includes atrial fibrillation, chronic heart failure, coronary heart disease, hypertension, peripheral artery disease, revascularisation, stroke or transient ischaemic attack

§ Includes medications other than listed ATC for respective indications (diabetes, CV disease, obesity and hypothyroidism)

The most common concomitant medications for the treatment of diabetes among participants were metformin (78.6%) and SGLT2 inhibitors (21.4%). Of participants with available data, 78 (41.7%) were current or past smokers, 54 (50%) stated that their highest level of education was high school or equivalent and 60 (42.6%) were retired.

Most of the participants had a physician in primary care ( n = 184; 98.4%) and 149 (79.7%) participants had a physician with previous experience with prescribing GLP-1RAs. Nearly all physicians prescribed a starting oral semaglutide dose of 3 mg. Oral semaglutide was primarily prescribed to improve glycaemic control and/or reduce body weight (Table 1 ).

Approximately two thirds of participants had a CV-related medical history and nearly three quarters of participants met an expanded definition of CV disease, including CKD, haemoglobinopathy, dyslipidaemia and microalbuminuria (Table 1 ).

There was a significant reduction from baseline to EOS in HbA 1c , assessed in 177 participants, as shown by an estimated mean (95% CI) change of − 0.88%-points (− 1.01 to − 0.75; P < 0.0001) or − 9.64 mmol/mol (− 11.05 to − 8.22; P < 0.0001; Fig. 2 A). The estimated mean decreases in HbA 1c occurred primarily within the first 28 weeks of treatment (Fig. 2 B).

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Object name is 13300_2024_1614_Fig2_HTML.jpg

Estimated change from baseline to week 38 in HbA 1c and body weight, for A HbA 1c ( N = 177), B HbA 1c over time ( N = 177), and C body weight ( N = 165) (FAS); D Proportion of participants achieving HbA 1c < 7%, and composite endpoints of HbA 1c and body weight reduction. Figure 2B At week 0, observed mean at baseline for participants having at least one post-baseline assessment is plotted. The outer lines of the band represent 95% CI. Abbreviations: CI confidence interval, FAS full analysis set, HbA 1c glycated haemoglobin, N number of participants included in the analyses

Secondary and sensitivity analyses of the primary endpoint yielded comparable results. The secondary analysis of the primary endpoint revealed little difference between the ‘in-study’ and ‘on-treatment’ periods. The additional sensitivity analysis showed that the COVID-19-related amendment to extend visit 3 to outside the 34–44-week window had very little impact on the primary endpoint (Fig. S1 ).

Body weight decrease from baseline to EOS was assessed in 165 participants. Body weight significantly decreased, as shown by estimated mean (95% CI) relative and absolute changes of − 4.72% (− 5.58 to − 3.86; P < 0.0001) and − 4.62 kg (− 5.46 to − 3.79; P < 0.0001), respectively (Fig. 2 C). The percentage of participants who had a body weight reduction ≥ 10% from baseline to EOS was 13.7%.

Glycaemic and Weight Thresholds

Overall, 64.6% of participants had a HbA 1c < 7% by EOS, compared with 27.8% at baseline; among the 72.2% of participants with a baseline HbA 1c of ≥ 7%, over half achieved HbA 1c < 7% (Fig. 2 D). In addition, 28.5% and 22.9% of participants achieved the composite endpoints of a reduction in HbA 1c of ≥ 1%-point with body weight reduction of ≥ 3% and ≥ 5% by EOS, respectively (Fig. 2 D). Furthermore, the estimated mean change from baseline in waist circumference (cm) was − 4.15 (SD [95% CI], 0.64 [− 5.44 to − 2.87]; P < 0.0001).

Participants reported a significant increase in their treatment satisfaction with oral semaglutide compared with treatment before initiating oral semaglutide (Fig. 3 A, B). The dosing conditions questionnaire revealed that most participants found oral semaglutide very easy to consume (Fig. 3 C); further details on dosing conditions are in Table S1 .

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Object name is 13300_2024_1614_Fig3_HTML.jpg

Participant-reported satisfaction and ease of treatment to consume: A absolute treatment satisfaction measured with DTSQs, B relative treatment satisfaction measured by DTSQc, and C ease of consumption for oral semaglutide, measured by the dosing conditions questionnaire. Abbreviations: CI confidence interval, DTSQc Diabetes Treatment Satisfaction Questionnaire change, DTSQs Diabetes Treatment Satisfaction Questionnaire status, EOS end of study, N number of participants in the analysis, SD standard deviation. † Observed change was also 12.3 (SD 6.98)

Overall, when judged against their reason for initiating oral semaglutide (Table 1 ), physicians considered treatment a clinical success in 130 (73.9%) cases. More specifically, physicians reported that glycaemic control was improved in 72.9% of participants, body weight was reduced in 71.6% of participants and convenience was achieved for 60.0% of participants. In addition, there were no issues with hypoglycaemia in 95.7% of participants while they were receiving oral semaglutide. Almost half (46.2%) of participants achieved clinical success in relation to addressing CV risk as reported by their physicians and 40.2% in relation to simplifying the current treatment regimen for participants (Table S2 ).

In the dosing conditions questionnaire, 60.0% of participants who responded rated oral semaglutide as 6 on the easy to consume scale (0 being very difficult and 6 being very easy) and 86.4% of participants gave a 4, 5 or 6 for this response (Table S1 ).

At EOS, among 141 participants still taking oral semaglutide, only nine (6.4%) remained on semaglutide 3 mg, whereas 56 (39.7%) participants were taking semaglutide 7 mg at EOS. Additionally, 75 participants (53.2%) had increased to the maximum 14 mg dose and one participant had temporarily discontinued oral semaglutide at EOS.

Twenty-four participants (12.8%) had a new glucose-lowering medication added, or increased the baseline glucose-lowering medication dose, during the study period. Conversely, 13 participants (7.0%) had a glucose-lowering medication removed or the dose reduced during the study period.

Overall in the in-study observation period, 48 participants (25.7%) experienced a total of 68 AEs; most were mild or moderate in severity and nine participants (4.8%) experienced serious AEs. Most AEs were considered probably related to study drug (Table 2 ). AEs that led to study-drug withdrawal were reported in 25 participants. The most common AEs occurred in the system organ class of gastrointestinal disorders. One case of severe hypoglycaemia was reported by one participant (0.5%); this participant was not receiving insulin or sulfonylurea. The participant also had known hypertension and was receiving treatment with empagliflozin, metformin and enalapril in addition to oral semaglutide. The blood glucose levels of this participant are unavailable, and the severe hypoglycaemia was classified according to the criteria stated in the endpoints safety section.

Table 2

Summary of AEs over the in-study period (FAS)

AE, (%)	(%) = 187	Number of AEs (event rate )
Any AE	48 (25.7)	68 (46.8)
Serious AEs	9 (4.8)	9 (6.2)
AE severity
Mild	33 (17.6)	43 (29.6)
Moderate	15 (8.0)	20 (13.8)
Severe	5 (2.7)	5 (3.4)
Causality
Probable	33 (17.6)	43 (29.6)
Possible	9 (4.8)	15 (10.3)
Unlikely	10 (5.3)	10 (6.9)
AEs leading to drug withdrawal	25 (13.4)	30 (20.6)
AEs by system organ class in ≥ 2 participants
Gastrointestinal disorders	36 (19.3)	47 (32.3)
Nervous system disorders	6 (3.2)	6 (4.1)
Respiratory, thoracic and mediastinal disorders	3 (1.6)	3 (2.1)
Neoplasms benign, malignant and unspecified (including cysts and polyps)	2 (1.1)	2 (1.4)

Abbreviations: AE adverse event, FAS full analysis set

† Event rate per 100 years of observation time, total observation time = 145.4 years

One fatal AE was reported in a 77-year-old woman who died as a result of disseminated uterine cancer 250 days after treatment initiation; the death was deemed unlikely to be related to study drug.

In this prospective, non-interventional study in participants with T2D in routine clinical practice in Sweden, oral semaglutide was associated with significant decreases in HbA 1c and body weight; more than 20% of participants achieved a reduction in HbA 1c of ≥ 1.0%-points and a reduction in body weight of ≥ 5%. Furthermore, participant satisfaction with treatment improved over the course of the study, and the majority of the participants found the medication easy to take. The treatment was also considered clinically successful by physicians in more than 70% of cases. These results further reinforce the use of oral semaglutide. Further, the safety profile was consistent with that reported in the oral semaglutide phase 3 clinical study programme and no new safety findings were observed [ 9 – 15 ]. In addition, the extent of weight loss with oral semaglutide in this study was consistent with that reported in the subcutaneous semaglutide clinical study programme in T2D [ 19 – 24 ]. Taken together, these findings show that the benefit–risk profile of oral semaglutide remains positive.

The decrease in HbA 1c of 0.88%-points (9.64 mmol/mol) in this study compares to a mean 0.9%-point decrease reported in the IGNITE study, an observational study ( n = 211) evaluating oral semaglutide use in routine clinical practice in participants with T2D in the USA [ 25 ], and to a mean 1.3% reduction in the Swedish cohort ( n = 195) of the SURE study, an observational study of subcutaneously administered semaglutide use in routine clinical practice [ 26 ]. In the same analysis of SURE, the reduction in body weight among Swedish participants ( n = 193) was 5.7 kg, as compared to 4.6 kg in the present study [ 26 ]. It should be noted that Swedish participants in the SURE study had higher HbA 1c (8.0%) and body weight (101.9 kg) values at baseline, a much longer disease duration (10.3 years) than participants included in the current study, and that the study used a different analysis which only included participants on-treatment at EOS, limiting comparisons between these study populations. Similarly, in the PIONEER REAL Canada study, participants achieved a slightly greater decrease in HbA 1c of 1.1%-points; however, the participants in the Canada study had higher baseline HbA 1c than those in this study, and this is reflected in the proportion of participants achieving HbA 1c of < 7%, which was 53.7% in the PIONEER REAL Canada study and 64.6% in the present study. Participants in the PIONEER REAL Canada study also achieved greater reductions in body weight (7.2%) than in the present study (4.7%) [ 27 ]. However, these real-world populations will vary in their characteristics (e.g. different baseline HbA 1c or T2D duration), and caution is required when comparing results between studies.

The relatively high proportions of participants achieving HbA 1c < 7% further indicates that oral semaglutide could help individuals with poorly controlled T2D to achieve the proposed glycaemic target of HbA 1c ≤ 7% [ 5 ], thus preventing complications. The oral formulation may also be preferred by some individuals with aversions to injections. However, in this study, over 90% of the participants were white, while in Sweden, the risk of T2D appears to be higher in minority ethnic groups, particularly in individuals with South Asian or Middle Eastern ethnicity [ 28 , 29 ]. These individuals were underrepresented in the present study; however, the vast majority of people with T2D in Sweden are white which implies good generalisability of these findings to the wider T2D population in Sweden [ 30 ]. Other ongoing studies may provide more specific information about the CV effects of semaglutide in individuals living with T2D and established CVD and/or CKD [ 31 ].

The majority of participants in PIONEER REAL Sweden reported concomitant glucose-lowering medication use at baseline (78.6% were on concomitant metformin and 21.4% were on concomitant SGLT2 inhibitors), which is to be expected since more than 90% of participants had T2D for longer than 1 year (mean duration of T2D was 6.8 years in participants who provided a date of T2D diagnosis). In a recent survey study conducted in almost 4500 Italian patients with T2D initiating oral semaglutide treatment in specialist care, the most common glucose-lowering treatment reported at baseline was also the concomitant use of metformin (79.9%) [ 32 ], similar to PIONEER REAL Sweden.

As a real-world evidence study, the PIONEER REAL Sweden study provides insights into how oral semaglutide performs in a diverse population of adults with T2D encountered in routine clinical practice in Sweden, and into the perceptions of physicians and participants in using oral semaglutide. However, this study also had a few limitations. The observational nature of the study and lack of a comparator arm mean that other explanations for the changes in HbA 1c and body weight, such as changes in medication throughout the study, cannot be excluded. In addition, the clinical reasons to initiate semaglutide could have affected the observed changes in HbA 1c , potentially influencing the results of this study. The data were collected as part of routine clinical practice rather than through mandatory assessments at prespecified time points, which could impact the robustness and completeness of data. Given the design of this study, it is not possible to make causal inferences between treatment and observed outcomes. A placebo effect cannot be ruled out with regard to participant- and physician-reported outcomes; however, questionnaires, such as the Diabetes Treatment Satisfaction Questionnaire, are a common method for assessing treatment satisfaction and participant and physician viewpoints and as a result of the observational nature of the study would mirror their use in everyday clinical practice.

Conclusions

The clinical outcomes observed in PIONEER REAL Sweden showed significant improvement in glycaemic control, with no new safety concerns, and an improvement in treatment satisfaction among adults with T2D who were prescribed once-daily oral semaglutide, in the clinical practice setting. As part of the wider PIONEER REAL study programme, this provides insights into the use of oral semaglutide in routine clinical practice in a diverse real-world population of adults with T2D.

Below is the link to the electronic supplementary material.

Acknowledgements

The authors thank the study participants, investigators and trial site staff who conducted the study.

Medical Writing/Editorial Assistance

Medical writing support was provided by Kate Silverthorne, PhD, a contract writer working on behalf of Apollo, OPEN Health Communications, and William Townley, MRes, of Apollo, OPEN Health Communications, and funded by Novo Nordisk, under the direction of the authors and in accordance with Good Publication Practice (GPP) guidelines ( www.ismpp.org/gpp-2022 ).

Author Contribution

Data were analysed by the sponsor. Sergiu-Bogdan Catrina, Hanan Amadid, Uffe C. Braae, Jonatan Dereke, Neda Rajamand Ekberg, Boris Klanger and Stefan Jansson participated in interpretation of data, contributed to the discussion, and wrote, reviewed and edited the manuscript. All authors approved the manuscript for submission.

This study and the journal’s Rapid Service Fee was sponsored by Novo Nordisk A/S and is registered with ClinicalTrials.gov (NCT04601753).

Data Availability

Declarations.

Sergiu-Bogdan Catrina and Neda Rajamand Ekberg have nothing to disclose. Hanan Amadid, Uffe C. Braae and Jonatan Dereke are employees of and shareholders in Novo Nordisk. Boris Klanger has received grants for co-operation with the following companies during the last 5 years: Novo Nordisk, Boehringer Ingelheim, Bayer, AstraZeneca, Pfizer, Lilly, Abbott, Sanofi, Amgen, Amarin, Teva, Region Västmanland and Novartis. Stefan Jansson’s employer has received all his speaking fees from AstraZeneca, Boehringer Ingelheim, Eli Lilly and Novo Nordisk.

Type 2 diabetes and prediabetes linked to accelerated brain aging

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Type 2 diabetes and prediabetes are associated with accelerated brain aging, according to a new study from Karolinska Institutet in Sweden published in the journal Diabetes Care. The good news is that this may be counteracted by a healthy lifestyle.

Type 2 diabetes is a known risk factor for dementia, but it is unclear how diabetes and its early stages, known as prediabetes, affect brain ageing in people without dementia. Now, a comprehensive brain imaging study shows that both diabetes and prediabetes can be linked to accelerated brain ageing.

The study included more than 31,000 people between 40 and 70 years of age from the UK Biobank who had undergone a brain MRI scan (magnetic resonance imaging). The researchers used a machine learning approach to estimate brain age in relation to the person's chronological age.

Prediabetes and diabetes were associated with brains that were 0.5 and 2.3 years older than chronological age, respectively. In people with poorly controlled diabetes, the brain appeared more than four years older than chronological age. The researchers also noted that the gap between brain age and chronological age increased slightly over time in people with diabetes . These associations were attenuated among people with high physical activity who abstained from smoking and heavy alcohol consumption.

Having an older-appearing brain for one's chronological age can indicate deviation from the normal aging process and may constitute an early warning sign for dementia. On the positive side, it seems that people with diabetes may be able to influence their brain health through healthy living." Abigail Dove, study's lead author, PhD student at the Department of Neurobiology, Care Sciences and Society, Karolinska Institutet

Repeated MRI data were available for a small proportion of the study participants. Follow-up MRI scans are ongoing and researchers are now continuing to study the association between diabetes and brain ageing over time.

"There's a high and growing prevalence of type 2 diabetes in the population," says Abigail Dove. "We hope that our research will help prevent cognitive impairment and dementia in people with diabetes and prediabetes."

The study was mainly funded by the Swedish Alzheimer's Foundation, the Dementia Research Fund, the Swedish Research Council and Forte (the Swedish Research Council for Health, Working Life and Welfare).

Karolinska Institutet

Dove, A., et al . (2024) Diabetes, Prediabetes, and Brain Aging: The Role of Healthy Lifestyle. Diabetes Care. doi.org/10.2337/dc24-0860 .

Posted in: Medical Science News | Medical Research News | Medical Condition News

Tags: Aging , Alcohol , Brain , Dementia , Diabetes , Healthy Lifestyle , Healthy Living , Imaging , Machine Learning , Magnetic Resonance Imaging , Physical Activity , Prediabetes , Research , Smoking , Type 2 Diabetes , UK Biobank

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