Multimorbidity in type 1 diabetes is common and associated with increased mortality

Multimorbidity in type 1 diabetes is common and associated with increased mortality | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search Multimorbidity in type 1 diabetes is common and associated with increased mortality View ORCID Profile Anni Ylinen , View ORCID Profile Stefan Mutter , View ORCID Profile Stefanie Hägg-Holmberg , View ORCID Profile Susanna Satuli-Autere , View ORCID Profile Valma Harjutsalo , View ORCID Profile Per-Henrik Groop , View ORCID Profile Lena M Thorn the FinnDiane Study Group doi: https://doi.org/10.1101/2025.09.07.25334819 Anni Ylinen a Folkhälsan Research Center , Biomedicum Helsinki, Helsinki, Finland b Department of Nephrology, University of Helsinki and Helsinki University Hospital , Helsinki, Finland c Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki , Finland d Department of General Practice and Primary Health Care, University of Helsinki and Helsinki University Hospital , Helsinki, Finland Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Anni Ylinen Stefan Mutter a Folkhälsan Research Center , Biomedicum Helsinki, Helsinki, Finland b Department of Nephrology, University of Helsinki and Helsinki University Hospital , Helsinki, Finland c Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki , Finland Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Stefan Mutter Stefanie Hägg-Holmberg a Folkhälsan Research Center , Biomedicum Helsinki, Helsinki, Finland b Department of Nephrology, University of Helsinki and Helsinki University Hospital , Helsinki, Finland c Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki , Finland d Department of General Practice and Primary Health Care, University of Helsinki and Helsinki University Hospital , Helsinki, Finland Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Stefanie Hägg-Holmberg Susanna Satuli-Autere a Folkhälsan Research Center , Biomedicum Helsinki, Helsinki, Finland b Department of Nephrology, University of Helsinki and Helsinki University Hospital , Helsinki, Finland c Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki , Finland d Department of General Practice and Primary Health Care, University of Helsinki and Helsinki University Hospital , Helsinki, Finland Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Susanna Satuli-Autere Valma Harjutsalo a Folkhälsan Research Center , Biomedicum Helsinki, Helsinki, Finland b Department of Nephrology, University of Helsinki and Helsinki University Hospital , Helsinki, Finland c Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki , Finland Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Valma Harjutsalo Per-Henrik Groop a Folkhälsan Research Center , Biomedicum Helsinki, Helsinki, Finland b Department of Nephrology, University of Helsinki and Helsinki University Hospital , Helsinki, Finland e Department of Diabetes, Central Clinical School, Monash University , Melbourne, Victoria, Australia f Baker Heart and Diabetes Institute , Melbourne, Victoria, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Per-Henrik Groop Lena M Thorn a Folkhälsan Research Center , Biomedicum Helsinki, Helsinki, Finland b Department of Nephrology, University of Helsinki and Helsinki University Hospital , Helsinki, Finland c Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki , Finland d Department of General Practice and Primary Health Care, University of Helsinki and Helsinki University Hospital , Helsinki, Finland Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Lena M Thorn For correspondence: lena.thorn{at}helsinki.fi Abstract Full Text Info/History Metrics Supplementary material Data/Code Preview PDF Abstract Background Multimorbidity in type 1 diabetes has previously not been studied in detail. Therefore, we aimed to assess the prevalence of multimorbidity and its association with mortality in type 1 diabetes. Materials and methods This observational follow-up study includes 4,069 individuals with type 1 diabetes from the Finnish Diabetic Nephropathy study. The prevalence of multimorbidity (coexistence of two or more chronic conditions) was based on 32 conditions at baseline. Conditions were grouped into three subcategories: vascular comorbidities, autoimmune disorders, and other conditions. Hazard ratios (HR) for all-cause mortality were calculated. Results The prevalence of multimorbidity was 60.4% and increased with age and especially diabetes duration. Multimorbidity was associated with increased risk of mortality, HR 6.0 (95% CI 4.6–7.8), p<0.001. The HR for mortality increased by each additional condition and was 37.9 (95% CI 25.7–56.0) in those with ≥ eight conditions. Vascular comorbidities and other conditions were associated with increased mortality, HRs 5.9 (4.4–7.9) and 3.8 (2.4–5.9), p<0.001, separately, and in combination, HR 11.2 (8.3–15.2), p<0.001. Autoimmune disorders did not influence mortality. Conclusions Multimorbidity in type 1 diabetes is common and is associated with increased mortality. Comprehensive evaluation of all additional conditions is needed to tailor treatment individually. Key Messages The prevalence of multimorbidity in our study was 60.4% already at a median age of 38 years and the more chronic conditions an individual had, the higher the risk of mortality. A holistic approach is needed in the treatment of individuals with type 1 diabetes, considering also other conditions that negatively impact prognosis. Introduction Lately, the interest in multimorbidity has grown due to its substantial effects on individuals, healthcare, and society ( 1 ). Multimorbidity is commonly defined as the coexistence of two or more chronic conditions. It is often confused with comorbidity, which refers to additional disorders in relation to one index disease, whereas multimorbidity addresses all conditions in one individual at a certain point of time, not necessarily with any connection to each other ( 2 ). In the general population, the prevalence of multimorbidity increases with age ( 3 ), and is associated with increased mortality and decreased quality of life ( 4 ). A rise in multimorbidity has been seen in recent years due to more effective treatments, leading to individuals living longer ( 5 , 6 ). Diabetes is associated with higher probability of other chronic conditions ( 7 ). Type 1 diabetes is often followed by other chronic conditions at a relatively young age. It is typically associated with other autoimmune diseases ( 8 , 9 ) as well as micro- and macrovascular comorbidities. Furthermore, individuals with type 1 diabetes may have other conditions, such as cancer or dementia, with even more significant effect on their prognosis ( 10 , 11 ). Additional conditions may also influence the treatment of their diabetes, for example depression and dementia profoundly impact self-care ( 12 ). Despite this, multimorbidity in type 1 diabetes has gained little attention. An American study found that multimorbidity occurs in 84% of hospitalized adults with type 1 diabetes ( 13 ). Furthermore, the study showed that the number of chronic conditions relates to a higher probability of depression ( 13 ). The most common disorder to coincide with type 1 diabetes has been found to be hypertension ( 13 , 14 ), followed by dyslipidemia, dorsalgia, diabetic neuropathy, and depression ( 14 ). In addition, multimorbidity in type 1 diabetes has been associated with severe hypoglycemic episodes ( 15 , 16 ). No unified measure of multimorbidity is yet available. Different measures have been created (e.g., the Charlson Comorbidity Index ( 17 ), the Cumulative Illness Rating Scale ( 18 ), the Index of Coexistent Disease ( 19 ), and the Elixhauser Index ( 20 )) and simple counts of diseases have also been widely adopted. The choice of measure used to define multimorbidity is affected by the available data and targeted study outcomes. Disease counts have for example been recommended, when multiple outcomes are being considered and in the absence of a validated measure. ( 21 ) In 2022, a Delphi consensus study was published with recommendations by a panel of international experts on the definition and measurement of multimorbidity in research ( 22 ). The professional and public panel concluded on a list of 24 conditions to always be included when studying multimorbidity, and 37 conditions to usually be included. Recently, multimorbidity in type 1 diabetes was identified as a knowledge gap ( 1 ). Therefore, our aim was to explore the prevalence of multimorbidity and the number of chronic conditions according to sex, age, diabetes duration, and age at onset of type 1 diabetes. Further, we aimed to assess the impact of multimorbidity on mortality. In addition, we aimed to separate the risk related to autoimmune diseases, vascular comorbidities, and other chronic conditions. 2. Material and Methods 2.1 Study population Our study is part of the Finnish Diabetic Nephropathy (FinnDiane) Study, which is an ongoing, nationwide multicenter study founded in 1997, including 77 study centers (Supplemental Table S1) ( 23 ). The aim of the FinnDiane Study is to identify clinical, environmental, and genetic risk factors for diabetic complications. The final goal is to prevent diabetic complications, to enable personalized treatment, and to improve the quality of life of people with diabetes. Out of the 4,961 individuals with type 1 diabetes, who participated in the FinnDiane Study before the end of 2017, we excluded 892 with incomplete data on the selected conditions. The characteristics of the included vs the excluded participants are provided in Supplemental Table S2, with no observed difference in sex, age, diabetes duration, or age at diabetes onset. The cohort is nationally representative and consists of 4,069 individuals. Sex was defined as the sex assigned at birth. Type 1 diabetes was defined as age at onset below 40 years and insulin therapy initiated within one year from diagnosis. The FinnDiane Study does not register the ethnicity of the participants, but the vast majority are of Caucasian origin. The study has been approved by the Ethics Committee of the Helsinki and Uusimaa Hospital District. Written informed consent was given by each participating individual, and the study was conducted in accordance with the Declaration of Helsinki. 2.2 Baseline study visit Data at baseline were collected at regular visits to the attending physician, where information on medical history and medications was registered. Height and body weight, and office blood pressure were measured. Blood samples were drawn and analyzed for blood lipids and lipoproteins, creatinine, and HbA 1c . In addition, 24-hour urine samples were collected to measure the urinary albumin excretion. The participants completed questionnaires regarding their medical history and smoking habits. 2.3 Definition of multimorbidity Multimorbidity was defined based on the individuals having diabetes and at least one more chronic condition. The burden of multimorbidity was defined according to the number of conditions. The accumulation of diseases was defined based on the number of chronic conditions at baseline from a list consisting of 32 conditions (Supplemental Table S3). This list was gathered after reviewing the literature; the conditions were chosen based on a previous large study and the Charlson Index ( 3 , 17 ), and we included all chronic conditions with available data. The included conditions show a good overlap with the Delphi consensus study, that was published after our data collection ( 22 ). Data were collected from clinical records, questionnaires filled out both by the individual and the attending physician, the Finnish Care Register for Health Care, and Statistics Finland. Autoimmune diseases were also identified from the Finnish National Drug Reimbursement Register, the Drug Prescription Register, and the National Health Insurance Dietary Grant Register ( 8 ). Data from all different sources were combined. Information on definition of conditions is provided in Supplemental Table S3. The conditions were further grouped into three subcategories: vascular comorbidities, autoimmune diseases, and other disorders ( Table 1 ). For sub-analysis, the cohort was also grouped by age at onset below (n=2,240) or above 15 years (n=1,829). View this table: View inline View popup Download powerpoint Table 1. Clinical characteristics of the cohort 2.4 Follow-up data on mortality Data on mortality were retrieved from the Finnish Cause of Death Register, Statistics Finland, until the end of 2017. Follow-up data were available for all participants. Follow-up started at the FinnDiane baseline visit and continued until death or the end of 2017, with median follow-up of 16.7 (13.6–18.8) years. 2.5 Statistical analyses Continuous variables were tested for normality. Parametric continuous variables were tested with the unpaired t test to compare means and non-parametric ones were tested with Mann-Whitney U-tests. The results are presented as means with standard deviation or medians with interquartile ranges. The 2 -test was used to test differences in categorical variables between groups and the Fisher’s exact test was used if observations in groups were ≤ 5. Hazard ratios (HRs) for all-cause mortality were calculated in sex- and age-adjusted Cox regression models, according to the number of diseases, the three subcategories, and the different conditions separately. The results are presented as HR with 95% confidence interval (CI). A p-value <0.05 was considered statistically significant. Statistical analyses were performed with SPSS Statistics 29.0 software (IBM Corporation, Armonk, NY, USA). 3. Results 3.1 Baseline characteristics of the cohort The cohort consists of 4,069 individuals with type 1 diabetes (48.6% women). Median age at baseline was 37.7 (28.9–46.9) years, median duration of diabetes was 21.8 (12.2–31.4) years, and median age at onset was 13.9 (9.1–22.1) years. Clinical characteristics of the cohort are presented in Table 1 . 3.2 Prevalence of multimorbidity and chronic conditions The prevalence of multimorbidity was 60.4 % (n=2,458). The prevalence of the different conditions is presented in Supplemental Table S4. Hypertension was the most common chronic condition (40.6%, n=1,653), followed by severe retinopathy (35.1%, n=1,427), diabetic kidney disease (24.6%, n=1,002), thyroid disease (8.8%, n=358), and coronary heart disease (5.9%, n=242). The most common subcategory was vascular comorbidities, present in 49.2%, (n=2,000), autoimmune disorders were present in 12.7% (n=515), and other conditions in 19.8% (n=807). The prevalence of number of conditions in the participants is presented in Table 2 . View this table: View inline View popup Download powerpoint Table 2. Prevalence and risk of mortality according to number of diseases 3.3 Multimorbidity by sex There was no difference in the prevalence of multimorbidity between men and women (60.8% [n=1,271] vs 60.0% [n=1,187] p=0.641). Of the subcategories, vascular comorbidities were more common in men (53.1% [n=1,110] vs 45.0% [n=890], p<0.001), whereas autoimmune disorders were more frequent in women (18.2% [n=360] vs 7.4% [n=155], p<0.001). There was no difference between men and women regarding the prevalence of the other conditions (18.9% [n=396] vs 20.8% [n=411], p=0.137). 3.4 Multimorbidity by age The prevalence of multimorbidity clearly increased by age ( Figure 1A ): the prevalence in individuals <25 years was 25.7% (n=170), 25–30 years 38.6% (n=181), 30–35 years 54.7% (n=327), 35–40 years 65.2% (n=368), 40–45 years 72.2% (n=416), 45–50 years 78.0% (n=369), 50–55 years 84.0% (n=336), 55–60 years 85.0% (n=153), and >60 years 93.2% (n=138), p<0.001. The figure also displays the number of conditions in each age group. Download figure Open in new tab Figure 1. Prevalence of multimorbidity and the number of conditions. Panel A: According to age groups, Panel B: According to age at onset and age groups, and Panel C: According to age at onset and diabetes duration. 3.5 Multimorbidity by age at onset of diabetes All participants were divided into two groups based on their age at onset of diabetes, below or above 15 years. Individuals with age at onset of diabetes below 15 years were younger (34.4 [25.5–43.6] vs 41.6 [32.8–50.6] years, p<0.001), had a longer duration of diabetes (26.0 [17.2–34.4] vs 16.4 [7.4–26.2] years, p<0.001), and by default a lower age at onset (9.6 [6.1– 12.3] vs 23.3 [18.6–29.0] years, p<0.001). The prevalence of multimorbidity was significantly higher in individuals with age at onset of diabetes below 15 years (67.5% [n=1,511] vs 51.8% [n=947], p<0.001), despite the younger age. The prevalence of multimorbidity, as well as the number of conditions according to age at onset below or above 15 years, in the different age groups is presented in Figure 1B . The prevalence of multimorbidity was clearly higher in the onset <15 years group until the age of 55, after which there was no significant difference between the two groups. Further, the prevalence of multimorbidity in groups by duration of diabetes, according to age at onset below or above 15 years, is presented in Figure 1C . This figure shows no clear trend in the differences in the prevalence of multimorbidity between the age at onset groups. In all except for two duration-categories, there was no significant difference in the prevalence of multimorbidity between individuals with diabetes onset below or above 15 years. 3.6 Multimorbidity and mortality During a median follow-up time of 16.7 (13.6–18.8) years, 784 (19.3%) of the participants died. In age- and sex-adjusted Cox-regression analysis, multimorbidity was associated with increased risk of mortality, HR 6.01 (4.55–7.94, p<0.001). Sex- and age-adjusted Cox-regression analysis was performed according to the number of diseases and each higher number of diseases was associated with significantly higher risk of mortality ( Table 2 ). The HRs for mortality for the separate conditions are presented in Supplemental Table S4. Figure 2 displays the HRs for mortality from age- and sex-adjusted Cox-regression analyses in the different subcategories. Vascular comorbidities (p<0.001) and other conditions (p<0.001) alone were associated with increased risk of mortality, while autoimmune disorders alone were not associated with any increased risk of mortality. Furthermore, in individuals with both vascular comorbidities and other conditions, the risk of mortality was markedly increased. Autoimmune disorders did not further increase the risk of mortality in combination with vascular comorbidities or other conditions, or when all three subcategories were combined. Download figure Open in new tab Figure 2. Risk of mortality according to subcategories of the different conditions. 4. Discussion We found that the prevalence of multimorbidity in type 1 diabetes is high and increases by age and especially by duration of type 1 diabetes. Multimorbidity is already present at young age, most clearly in individuals with diabetes onset before the age of 15 years. Multimorbidity in type 1 diabetes is associated with increased mortality: the higher the number of conditions, the higher the risk of mortality, with a striking 38-fold increased risk of mortality in those with eight chronic conditions or more. The increased mortality related to multimorbidity is largely driven by vascular comorbidities, and this risk is further increased by other chronic conditions, while autoimmune disorders do not influence the risk. These findings help us understand the previously declared research gap in multimorbidity in type 1 diabetes ( 1 ). In our study, the prevalence of multimorbidity in type 1 diabetes was high, 60.4%, as we expected. Previous studies have found the prevalence to be even higher, 82–84% ( 13 , 14 ). The individuals in these studies were, however, older and one of the studies ( 13 ) was conducted on hospitalized patients, which likely included sicker individuals, and this could have impacted the higher prevalence of multimorbidity. The number and type of studied conditions can also impact the reported prevalence. We chose to focus on more severe chronic conditions than one of the previous studies ( 14 ), which also included milder diseases. Most striking in our study is that our participants are relatively young, and in relation to this, the prevalence of multimorbidity is significant. In line with previous studies, we found that hypertension was the most common additional condition in type 1 diabetes ( 13 , 14 ). While multimorbidity in type 1 diabetes has been understudied previously, in type 2 diabetes, the health burden has been shown to be markedly greater than in individuals without diabetes ( 24 ). The prevalence of multimorbidity in type 2 diabetes has generally been studied on older individuals than in our study, and the prevalence has been reported to be 70–93% in individuals with mean age of 60–71 years ( 25 – 28 ). Individuals with youth-onset type 2 diabetes have been shown to have a high burden of microvascular complications ( 29 ). Our study shows that in type 1 diabetes, the high prevalence of multimorbidity already at young age is mainly present in individuals with young age at onset, below 15 years. Interestingly, when comparing these groups (age at onset of diabetes below or above 15 years) at the same duration of diabetes, the prevalence of multimorbidity was similar between the groups, indicating that the duration of diabetes is the factor driving multimorbidity, rather than the young age at onset per se . We showed that multimorbidity in type 1 diabetes is associated with increased risk of mortality and that the risk is notably greater with increasing multimorbidity. This has not been studied in type 1 diabetes previously, but multimorbidity has been associated with increased risk of mortality in type 2 diabetes ( 25 ). We also showed that the increased mortality is largely driven by vascular complications, with a six-fold increase in risk of mortality. This finding was expected based on previous research ( 30 – 32 ). Interestingly, the other conditions also had a substantial impact on mortality with an almost four-fold increase and was especially seen in combination with vascular comorbidities, leading to an 11-fold increase in mortality. Furthermore, autoimmune diseases were not associated with increased mortality alone, nor did they affect the risk related to vascular complications or other conditions. A recent Swedish study found similar results, with no link between autoimmune diseases and mortality risk ( 33 ). Studying multimorbidity is complicated, partly because widely various measures have been used ( 34 ). Recently researchers have published a Delphi Consensus Study for guidance to promote consistency in studying multimorbidity and for future studies to be more comparable ( 22 ). However, during the process of deciding which conditions to include in studies, it is impossible to include all the conditions in any individual. Many conditions remain undiagnosed, and some are difficult to include in studies on multimorbidity due to how they are reported. Consequently, our studied prevalence of multimorbidity is more likely an underestimation of the actual prevalence of multimorbidity in type 1 diabetes. This study represents a well-characterized cohort of individuals with type 1 diabetes, with a long follow-up time, which is a major strength of the study. However, we have likely not been able to detect all chronic conditions. Another limitation of this study is that the definition of some conditions may be imprecise, for example the conditions defined based on the use of medications. Often medications have more than one indication, thus, they can be used for more than one disease. Despite the medications not being specific, the use of a medication reveals something about the health of an individual and, in addition, describes the health burden, which is what we aimed to capture in this study. It is important to bear in mind that our study is a good representation of individuals of Caucasian origin, but our results may not be generalizable to other populations. In conclusion, multimorbidity in type 1 diabetes is very common at young age and the prevalence increases by age, and especially by longer diabetes duration. Our findings highlight the importance of disease prevention in type 1 diabetes, since multimorbidity is associated with increased risk of mortality. In a clinical setting, our study is a reminder that people with type 1 diabetes already at young age present with many other conditions that impact their prognosis, and it is, thus, important to consider the whole disease burden of an individual, in addition to the separate conditions. The impact of multimorbidity on individuals with type 1 diabetes requires further research to understand the interplay between different conditions and their significance for the management of diabetes. Data Availability The datasets generated and/or analyzed during the current study are not publicly available due to the local legislation and the written consents of the FinnDiane study participants, which do not allow sharing individual-level phenotype data. The data that support the findings are available from the corresponding author upon reasonable request. Funding details This work was supported by grants from Folkhälsan Research Foundation, Wilhelm and Else Stockmann Foundation, Liv och Hälsa Society, Sigrid Jusélius Foundation, Medical Society of Finland, and state funding for university-level health research by Helsinki University Hospital. In addition, A.Y. was supported by personal grants from Perklén Foundation and Biomedicum Helsinki Foundation. None of the funding bodies had had any role in the study design, collection, analysis, or interpretation of data. Nor had the funding bodies any role in the writing of the report, nor in the decision to submit the paper for publication. Disclosure of interest S.M. received a lecture honorarium from Encore Medical Education. P.-H.G. has received investigator-initiated research grants from Eli Lilly and Roche, is an advisory board member for AbbVie, Astellas, AstraZeneca, Bayer, Boehringer Ingelheim, Cebix, Eli Lilly, Janssen, Medscape, Merck Sharp & Dohme, Mundipharma, Nestlé, Novartis, Novo Nordisk and Sanofi; and has received lecture fees from Astellas, AstraZeneca, Bayer, Berlin Chemie, Boehringer Ingelheim, Eli Lilly, Elo Water, Genzyme, Menarini, Merck Sharp & Dohme, Medscape, Novartis, Novo Nordisk, PeerVoice, Sanofi, and Sciarc. The other authors declare no disclosures. Author Contributions and Guarantor Statement A.Y. had the main responsibility for analyzing the data and writing the first draft of the paper and contributed to the acquisition and processing of data. As a supervisor, L.M.T. greatly contributed to study design, acquisition and processing of data, data analysis, and critical revision of the paper. S.M. contributed to study design, data analysis, and critical revision of the paper. S.H.-H., S.S.-A., V.H., and P.-H.G contributed to study design, acquisition of data, and critical revision of the paper. All authors reviewed and approved the final version of the manuscript. L.M.T. is the guarantor of this work and, as such, had full access to all the data and takes responsibility for the integrity of the data and the accuracy of the data analysis. Data and Resource Availability The datasets generated and/or analyzed during the current study are not publicly available due to the local legislation and the written consents of the FinnDiane study participants, which do not allow sharing individual-level phenotype data. The data that support the findings are available from the corresponding author upon reasonable request. Acknowledgements Personal thanks: We acknowledge all the participants and the physicians and nurses at each study center participating in the collection of the study population (Supplemental Table S1). We are indebted to the late Carol Forsblom, the international coordinator of the FinnDiane Study Group, for his contribution to this work. Abbreviations FinnDiane Finnish Diabetic Nephropathy Study References 1. ↵ Khunti K , Chudasama Y V , Gregg EW , Kamkuemah M , Misra S , Suls J , et al. Diabetes and Multiple Long-term Conditions: A Review of Our Current Global Health Challenge . Diabetes Care . 2023 Dec 1 ; 46 ( 12 ): 2092 – 101 . OpenUrl CrossRef PubMed 2. ↵ van den Akker M , Buntinx F , Knottnerus JA . Comorbidity or multimorbidity . European Journal of General Practice . 1996 Jan 11 ; 2 ( 2 ): 65 – 70 . OpenUrl CrossRef 3. ↵ Barnett K , Mercer SW , Norbury M , Watt G , Wyke S , Guthrie B . Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study . Lancet . 2012 Jul 7 ; 380 ( 9836 ): 37 – 43 . OpenUrl CrossRef PubMed Web of Science 4. ↵ Farmer C , Fenu E , O’Flynn N , Guthrie B . Clinical assessment and management of multimorbidity: summary of NICE guidance . BMJ . 2016 Sep 21 ; 354 : i4843 . 5. ↵ GBD 2015 Mortality and Causes of Death Collaborators . Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980-2015: a systematic analysis for the Global Burden of Disease Study 2015 . Lancet . 2016 Oct 8 ; 388 ( 10053 ): 1459 – 544 . OpenUrl CrossRef PubMed 6. ↵ Chowdhury SR , Chandra Das D , Sunna TC , Beyene J , Hossain A . Global and regional prevalence of multimorbidity in the adult population in community settings: a systematic review and meta-analysis . EClinicalMedicine . 2023 Mar ; 57 : 101860 . OpenUrl PubMed 7. ↵ Zemedikun DT , Gray LJ , Khunti K , Davies MJ , Dhalwani NN . Patterns of Multimorbidity in Middle-Aged and Older Adults: An Analysis of the UK Biobank Data . Mayo Clin Proc . 2018 Jul ; 93 ( 7 ): 857 – 66 . OpenUrl CrossRef PubMed 8. ↵ Mäkimattila S , Harjutsalo V , Forsblom C , Groop PH , FinnDiane Study Group . Every Fifth Individual With Type 1 Diabetes Suffers From an Additional Autoimmune Disease: A Finnish Nationwide Study . Diabetes Care . 2020 May ; 43 ( 5 ): 1041 – 7 . OpenUrl Abstract / FREE Full Text 9. ↵ Nederstigt C , Uitbeijerse BS , Janssen LGM , Corssmit EPM , de Koning EJP , Dekkers OM . Associated auto-immune disease in type 1 diabetes patients: a systematic review and meta-analysis . Eur J Endocrinol . 2019 Feb 1 ; 180 ( 2 ): 135 – 44 . OpenUrl PubMed 10. ↵ Swerdlow AJ , Jones ME , Slater SD , Burden ACF , Botha JL , Waugh NR , et al. Cancer incidence and mortality in 23D000 patients with type 1 diabetes in the UK: Long-term follow-up . Int J Cancer . 2023 Aug 1 ; 153 ( 3 ): 512 – 23 . OpenUrl PubMed 11. ↵ Satuli-Autere S , Harjutsalo V , Eriksson MI , Hägg-Holmberg S , Öhman H , Claesson TB , et al. Increased incidence of neurodegenerative diseases in Finnish individuals with type 1 diabetes . BMJ Open Diabetes Res Care . 2024 Sep 5 ; 12 ( 4 ). 12. ↵ Piette JD , Kerr EA . The Impact of Comorbid Chronic Conditions on Diabetes Care [Internet] . 2006 . Available from: http://diabetesjournals.org/care/article-pdf/29/3/725/593980/zdc00306000725.pdf 13. ↵ Chima CC , Salemi JL , Wang M , Mejia de Grubb MC , Gonzalez SJ , Zoorob RJ . Multimorbidity is associated with increased rates of depression in patients hospitalized with diabetes mellitus in the United States . J Diabetes Complications . 2017 Nov 1 ; 31 ( 11 ): 1571 – 9 . OpenUrl PubMed 14. ↵ van den Boom L , Buchal G , Kaiser M , Kostev K . Multimorbidity Among Adult Outpatients With Type 1 Diabetes in Germany . J Diabetes Sci Technol . 2022 Jan 1 ; 16 ( 1 ): 152 – 60 . OpenUrl PubMed 15. ↵ McCoy RG , Lipska KJ , Van Houten HK , Shah ND . Association of Cumulative Multimorbidity, Glycemic Control, and Medication Use With Hypoglycemia-Related Emergency Department Visits and Hospitalizations Among Adults With Diabetes . JAMA Netw Open . 2020 ; 3 ( 1 ): e1919099 . OpenUrl 16. ↵ Song SH , Frier BM . Severe hypoglycaemia in adults presenting to a hospital emergency department: Clinical characteristics, comorbidities, and mortality outcomes . Diabetes Obes Metab . 2023 Oct ; 25 ( 10 ): 2824 – 34 . OpenUrl PubMed 17. ↵ Charlson ME , Pompei P , Ales KL , MacKenzie CR . A new method of classifying prognostic comorbidity in longitudinal studies: development and validation . J Chronic Dis . 1987 ; 40 ( 5 ): 373 – 83 . OpenUrl CrossRef PubMed Web of Science 18. ↵ Linn BS , Linn MW , Gurel L . Cumulative illness rating scale . J Am Geriatr Soc . 1968 May ; 16 ( 5 ): 622 – 6 . OpenUrl CrossRef PubMed Web of Science 19. ↵ Greenfield S , Apolone G , McNeil BJ , Cleary PD . The importance of co-existent disease in the occurrence of postoperative complications and one-year recovery in patients undergoing total hip replacement. Comorbidity and outcomes after hip replacement . Med Care . 1993 Feb ; 31 ( 2 ): 141 – 54 . OpenUrl CrossRef PubMed Web of Science 20. ↵ Elixhauser A , Steiner C , Harris DR , Coffey RM . Comorbidity measures for use with administrative data . Med Care . 1998 Jan ; 36 ( 1 ): 8 – 27 . OpenUrl CrossRef PubMed Web of Science 21. ↵ Johnston MC , Crilly M , Black C , Prescott GJ , Mercer SW . Defining and measuring multimorbidity: a systematic review of systematic reviews . Eur J Public Health . 2019 Feb 1 ; 29 ( 1 ): 182 – 9 . OpenUrl CrossRef PubMed 22. ↵ Ho ISS , Azcoaga-Lorenzo A , Akbari A , Davies J , Khunti K , Kadam UT , et al. Measuring multimorbidity in research: Delphi consensus study . BMJ medicine . 2022 ; 1 ( 1 ): e000247 . OpenUrl CrossRef 23. ↵ Thorn LM , Forsblom C , Fagerudd J , Thomas MC , Pettersson-Fernholm K , Saraheimo M , et al. Metabolic syndrome in type 1 diabetes: association with diabetic nephropathy and glycemic control (the FinnDiane study) . Diabetes Care . 2005 Aug ; 28 ( 8 ): 2019 – 24 . OpenUrl Abstract / FREE Full Text 24. ↵ Veugen MGJ , Onete VG , Henry RMA , Brunner-La Rocca HP , Koster A , Dagnelie PC , et al. Health burden in type 2 diabetes and prediabetes in The Maastricht Study . Sci Rep . 2022 May 5 ; 12 ( 1 ): 7337 . OpenUrl PubMed 25. ↵ Chiang JI , Hanlon P , Li TC , Jani BD , Manski-Nankervis JA , Furler J , et al. Multimorbidity, mortality, and HbA1c in type 2 diabetes: A cohort study with UK and Taiwanese cohorts . PLoS Med . 2020 May ; 17 ( 5 ): e1003094 . OpenUrl PubMed 26. Chiang JI , Furler J , Mair F , Jani BD , Nicholl BI , Thuraisingam S , et al. Associations between multimorbidity and glycaemia (HbA1c) in people with type 2 diabetes: cross-sectional study in Australian general practice . BMJ Open . 2020 Nov 26 ; 10 ( 11 ): e039625 . OpenUrl Abstract / FREE Full Text 27. Koto R , Nakajima A , Miwa T , Sugimoto K. Multimorbidity, Polypharmacy, Severe Hypoglycemia, and Glycemic Control in Patients Using Glucose-Lowering Drugs for Type 2 Diabetes: A Retrospective Cohort Study Using Health Insurance Claims in Japan . Diabetes Ther . 2023 Jul ; 14 ( 7 ): 1175 – 92 . OpenUrl PubMed 28. ↵ Heikkala E , Mikkola I , Jokelainen J , Timonen M , Hagnäs M . Multimorbidity and achievement of treatment goals among patients with type 2 diabetes: a primary care, real-world study . BMC Health Serv Res . 2021 Sep 14 ; 21 ( 1 ): 964 . OpenUrl PubMed 29. ↵ TODAY Study Group , Bjornstad P , Drews KL , Caprio S , Gubitosi-Klug R , Nathan DM , et al. Long-Term Complications in Youth-Onset Type 2 Diabetes . N Engl J Med . 2021 Jul 29 ; 385 ( 5 ): 416 – 26 . OpenUrl CrossRef PubMed 30. ↵ Groop PH , Thomas MC , Moran JL , Wadèn J , Thorn LM , Mäkinen VP , et al. The presence and severity of chronic kidney disease predicts all-cause mortality in type 1 diabetes . Diabetes . 2009 Jul ; 58 ( 7 ): 1651 – 8 . OpenUrl Abstract / FREE Full Text 31. Rawshani A , Rawshani A , Franzén S , Eliasson B , Svensson AM , Miftaraj M , et al. Mortality and Cardiovascular Disease in Type 1 and Type 2 Diabetes . N Engl J Med . 2017 Apr 13 ; 376 ( 15 ): 1407 – 18 . OpenUrl CrossRef PubMed 32. ↵ Forssas E , Arffman M , Manderbacka K , Keskimäki I , Ruuth I , Sund R . Multiple complications among people with diabetes from Finland: an 18-year follow-up in 1994-2011 . BMJ Open Diabetes Res Care . 2016 ; 4 ( 1 ): e000254 . OpenUrl Abstract / FREE Full Text 33. ↵ Samuelsson J , Bertilsson R , Bülow E , Carlsson S , Åkesson S , Eliasson B , et al. Autoimmune comorbidity in type 1 diabetes and its association with metabolic control and mortality risk in young people: a population-based study . Diabetologia . 2024 Apr ; 67 ( 4 ): 679 – 89 . OpenUrl PubMed 34. ↵ Willadsen TG , Bebe A , Køster-Rasmussen R , Jarbøl DE , Guassora AD , Waldorff FB , et al. The role of diseases, risk factors and symptoms in the definition of multimorbidity - a systematic review . Scand J Prim Health Care . 2016 Jun ; 34 ( 2 ): 112 – 21 . OpenUrl CrossRef PubMed View the discussion thread. Back to top Previous Next Posted September 08, 2025. Download PDF Supplementary Material Data/Code Email Thank you for your interest in spreading the word about medRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following Multimorbidity in type 1 diabetes is common and associated with increased mortality Message Subject (Your Name) has forwarded a page to you from medRxiv Message Body (Your Name) thought you would like to see this page from the medRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share Multimorbidity in type 1 diabetes is common and associated with increased mortality Anni Ylinen , Stefan Mutter , Stefanie Hägg-Holmberg , Susanna Satuli-Autere , Valma Harjutsalo , Per-Henrik Groop , Lena M Thorn medRxiv 2025.09.07.25334819; doi: https://doi.org/10.1101/2025.09.07.25334819 Share This Article: Copy Citation Tools Multimorbidity in type 1 diabetes is common and associated with increased mortality Anni Ylinen , Stefan Mutter , Stefanie Hägg-Holmberg , Susanna Satuli-Autere , Valma Harjutsalo , Per-Henrik Groop , Lena M Thorn medRxiv 2025.09.07.25334819; doi: https://doi.org/10.1101/2025.09.07.25334819 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Endocrinology (including Diabetes Mellitus and Metabolic Disease) Subject Areas All Articles Addiction Medicine (568) Allergy and Immunology (863) Anesthesia (299) Cardiovascular Medicine (4425) Dentistry and Oral Medicine (443) Dermatology (382) Emergency Medicine (607) Endocrinology (including Diabetes Mellitus and Metabolic Disease) (1507) Epidemiology (15221) Forensic Medicine (30) Gastroenterology (1123) Genetic and Genomic Medicine (6588) Geriatric Medicine (667) Health Economics (997) Health Informatics (4524) Health Policy (1368) Health Systems and Quality Improvement (1612) Hematology (540) HIV/AIDS (1264) Infectious Diseases (except HIV/AIDS) (15910) Intensive Care and Critical Care Medicine (1103) Medical Education (623) Medical Ethics (145) Nephrology (667) Neurology (6588) Nursing (346) Nutrition (998) Obstetrics and Gynecology (1143) Occupational and Environmental Health (956) Oncology (3331) Ophthalmology (970) Orthopedics (369) Otolaryngology (420) Pain Medicine (435) Palliative Medicine (129) Pathology (663) Pediatrics (1690) Pharmacology and Therapeutics (691) Primary Care Research (710) Psychiatry and Clinical Psychology (5440) Public and Global Health (9219) Radiology and Imaging (2195) Rehabilitation Medicine and Physical Therapy (1369) Respiratory Medicine (1196) Rheumatology (593) Sexual and Reproductive Health (710) Sports Medicine (529) Surgery (710) Toxicology (99) Transplantation (289) Urology (265) (function(){function c(){var b=a.contentDocument||a.contentWindow.document;if(b){var d=b.createElement('script');d.innerHTML="window.__CF$cv$params={r:'9ffc96b27a14ad07',t:'MTc3OTQ2MDk1OQ=='};var a=document.createElement('script');a.src='/cdn-cgi/challenge-platform/scripts/jsd/main.js';document.getElementsByTagName('head')[0].appendChild(a);";b.getElementsByTagName('head')[0].appendChild(d)}}if(document.body){var a=document.createElement('iframe');a.height=1;a.width=1;a.style.position='absolute';a.style.top=0;a.style.left=0;a.style.border='none';a.style.visibility='hidden';document.body.appendChild(a);if('loading'!==document.readyState)c();else if(window.addEventListener)document.addEventListener('DOMContentLoaded',c);else{var e=document.onreadystatechange||function(){};document.onreadystatechange=function(b){e(b);'loading'!==document.readyState&&(document.onreadystatechange=e,c())}}}})();