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Abstract
Objectives Cardiovascular disease (CVD) is a precarious complication of type 1 diabetes (T1D). Alongside glycaemic control, lipid and blood pressure (BP) management are essential for the prevention of CVD. However, age-specific differences in lipid and BP between individuals with T1D and the general population are relatively unknown.
Design Cross-sectional study.
Setting Six diabetes outpatient clinics and individuals from the Lifelines cohort, a multigenerational cohort from the Northern Netherlands.
Participants 2178 adults with T1D and 146 22 individuals without diabetes from the general population.
Primary and secondary outcome measures Total cholesterol, low-density lipoprotein cholesterol (LDL-cholesterol), systolic BP (SBP) and diastolic BP (DBP), stratified by age group, glycated haemoglobin category, medication use and sex.
Results In total, 2178 individuals with T1D and 146 822 without diabetes were included in this study. Total cholesterol and LDL-cholesterol were lower and SBP and DBP were higher in individuals with T1D in comparison to the background population. When stratified by age and medication use, total cholesterol and LDL-cholesterol were lower and SBP and DBP were higher in the T1D population. Men with T1D achieved lower LDL-cholesterol levels both with and without medication in older age groups in comparison to women. Women with T1D had up to 8 mm Hg higher SBP compared with the background population, this difference was not present in men.
Conclusions Lipid and BP measurements are not comparable between individuals with T1D and the general population and are particularly unfavourable for BP in the T1D group. There are potential sex differences in the management of LDL-cholesterol and BP.
- Blood Pressure
- DIABETES & ENDOCRINOLOGY
- Lipid disorders
- EPIDEMIOLOGY
- Risk management
Data availability statement
Data are available upon reasonable request. The data of the T1D individuals that support the findings of this study are available on request from the corresponding author (RDMV). The data are not publicly available due to privacy or ethical restrictions. The manuscript is in part based on data from the Lifelines cohort study. Lifelines adheres to standards for data availability and allows access for reproducibility of the study results. The data catalogue is publicly accessible at www.lifelines.nl. The dataset supporting the conclusions of this article is available through the Lifelines organisation, and all international researchers can apply for data access at the Lifelines research office (research@lifelines.nl). For data access, a fee is required.
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
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STRENGTHS AND LIMITATIONS OF THIS STUDY
This study uses ‘real-world’ data from outpatient clinics treating individuals with type 1 diabetes (T1D).
A large number of individuals with T1D were compared with individuals without diabetes in a representative Dutch population.
The cross-sectional design of the study does not allow conclusions to be drawn on causal relationships.
Background
Individuals with type 1 diabetes (T1D) have an increased risk of all-cause mortality, particularly cardiovascular mortality.1–6 Cardiovascular disease (CVD) prevention is therefore an essential part of T1D management. Glycaemic control plays an important role in the development of CVD.7 8 However, management of other classical risk factors such as elevated lipid and blood pressure (BP) levels further contribute to preventing CVD.9 Intervention studies with statins and BP lowering agents in T1D have demonstrated moderate effects on CVD risk in individuals with T1D.10 Consequently, current cardiovascular risk management in individuals with T1D consists of glycaemic, lipid and BP management, in addition to promoting a healthy lifestyle.9 11
Although a decrease in CVD-related hospitalisations and mortality in individuals with T1D has been described over time, there remains a significant excess incidence of CVD in comparison to controls.12 Yet, despite these differences, non-glycaemic intervention studies for CVD risk reduction in individuals with T1D are limited. Management strategies have largely been extrapolated from prevention trials conducted in individuals with type 2 diabetes (T2D) and these inferences rely on the assumption that the effects of CVD risk factors in these two populations are comparable.12 13 However, lipid profiles and BP have been shown to differ between individuals with T1D, T2D and the background population.14
T1D primarily develops in younger individuals, resulting in a longer lifetime exposure to potential CVD risk factors such as hyperglycaemia, hypoglycaemia, dyslipidaemia and hypertension.15 16 Previous studies have described lipid profiles and BPs in individuals with T1D.17 18 However, as cardiometabolic risk management and glycaemic control have improved over the years, both individuals in the general population and those with T1D have benefited from a reduction in CVD risk and CVD mortality.12 We can therefore hypothesise that the lipid levels and BPs may have become more comparable in recent years. Therefore, an updated quantitative comparison of cardiometabolic risk factors between individuals with T1D and the general population is warranted. Moreover, recent studies have identified sex differences in management of cardiometabolic risk factors in individuals with T1D.19 Further insights into the quantitative differences in the cardiometabolic risk factors between the sexes may be of interest. In this study, we report the lipid profiles and BP over different age decades and between sexes in adults with T1D and compare these to individuals without diabetes from the general population.
Methods
Population
T1D population: Diabeter/University Medical Centre Groningen (UMCG) study
Data from individuals with T1D visiting Diabeter, a specialised T1D outpatient clinic with five separate locations in The Netherlands, and the UMCG were used in this study. Cross-sectional data were collected in 2018 from electronic medical files, as described earlier.20 Individuals were included if they were diagnosed with T1D, were ≥18 years of age and had been using insulin for ≥1 year.
Control population: Lifelines cohort study
Data obtained in individuals without diabetes mellitus from the general population, who participated in the Lifelines cohort study, were used as an age-matched comparison. Lifelines is a multidisciplinary prospective population-based cohort study examining in a unique three-generation design the health and health-related behaviours of 167 729 persons living in the North of the Netherlands. It employs a broad range of investigative procedures in assessing the biomedical, sociodemographic, behavioural, physical and psychological factors which contribute to the health and disease of the general population, with a special focus on multimorbidity and complex genetics. Individuals who were measured at baseline between 2007 and 2014 and were ≥18 years of age without a diagnosis of T1D or T2D were included for analysis.21 22
Variables and definition
Data extracted included age, sex, ethnicity, body mass index (BMI), smoking behaviour, BP, total cholesterol, low-density lipoprotein cholesterol (LDL-cholesterol), lipid lowering medication (LLM) use, antihypertensive medication (AHM) use and the presence of CVD. The latter was defined as the presence of coronary artery disease, or an earlier cerebrovascular accident or transient ischaemic attack. The presence of peripheral arterial disease was excluded, as this information was not available in the Lifelines cohort study.
Total cholesterol and LDL-cholesterol were measured in a routine outpatient clinical setting for the T1D population and were generally non-fasting measurements. In the Lifelines cohort study, total cholesterol and LDL-cholesterol were collected the morning after an overnight fast. For both populations, serum total cholesterol was measured using an enzymatic colorimetric method and the LDL-cholesterol using an enzymatic method on the Roche Modular P chemistry analyser (Roche, Basel, Switzerland).
In the Lifelines cohort, the BP measurements were conducted during the first study visit. Individuals were measured every minute for 10 min, and the mean of the last three measurements is reported. The BP measurements from the T1D cohort were performed during an outpatient clinic visit and extracted from the electronic medical files.
Medication use was derived from electronic medical records in the T1D population. In the Lifelines cohort, medication was self-reported. The presence of coronary artery disease, cerebrovascular accident or transient ischaemic attack for the individuals in the T1D population was based on registration in the electronic medical file. In the Lifelines cohort, medical history was self-reported.
Statistical analysis
All statistical analyses were conducted using R Statistical Software, R Studio Software and R packages.23–27 Descriptive data of the populations are presented where appropriate as means with SD, medians with IQR or counts with frequencies.
For each population, the mean and 95% CIs for total cholesterol, LDL-cholesterol, systolic BP (SBP) and diastolic BP (DBP) were calculated stratified by medication use and for the following age categories: ‘18 to <30’, ‘30 to <40’, ‘40 to <50’, ‘50 to <60’, ‘60 to <70’ and ‘70+’. In individuals with T1D, the measurements were further stratified by glycaemic control. Glycaemic control was considered excellent if glycated haemoglobin (HbA1c) was ≤6.5% (48 mmol/mol), good if HbA1c was >6.5% and ≤8% (64 mmol/mol) and poor if HbA1c was >8%. Additionally, LDL-cholesterol and SBP means, and 95% CIs, were calculated stratified by sex. Finally, CVD prevalence, LLM and AHM use were calculated for the age categories specified above.
Patient and public involvement
Patients were not involved in the design and conduct of this research.
Results
From a total of 2287 individuals with T1D from the Diabeter/UMCG study, 2178 individuals had complete data on total cholesterol, LDL-cholesterol, SBP and DBP. From the Lifelines cohort, 146 822 individuals without diabetes and complete data were included in the analysis. Table 1 presents the characteristics of these two study populations.
Characteristics of participants with type 1 diabetes and individuals without diabetes from the Lifelines cohort study
Individuals with T1D were younger, had a comparable BMI, had a higher average BP, with lower total cholesterol and LDL-cholesterol in comparison to the background population. Moreover, individuals with T1D were less often current smokers in comparison to the background population, but more frequently had a positive medical history for CVD and were using more LLM and AHM (table 1).
Figure 1 shows total cholesterol and LDL-cholesterol levels per age group for both populations, stratified by medication use. In general, individuals with T1D had lower levels of LDL-cholesterol and total cholesterol in comparison to the background population. In those not using LLM, total cholesterol and LDL-cholesterol gradually increased with higher age in the background population, whereas in the T1D population they remained relatively stable with increasing age. This observation was similar when stratified for glycaemic control (online supplemental figures S1 and S2). Among the individuals using LLM, LDL-cholesterol and total cholesterol levels decreased in the older age groups, and the differences between those with and without T1D were less pronounced. Again, these findings were comparable when T1D was stratified for glycaemic control (online supplemental figures S1 and S2).
Supplemental material
Supplemental material
Mean and 95% CI of low-density lipoprotein cholesterol (LDL-cholesterol) (A) and total cholesterol (B) in populations with and without type 1 diabetes, stratified by lipid lowering medication use. Black diamond=individuals with type 1 diabetes; open diamond=individuals without diabetes.
When LDL-cholesterol levels are further stratified by sex, we still observed higher levels of LDL-cholesterol in the background population using LLM compared with those with T1D (figure 2). In men, the differences were more pronounced in the younger age groups. Moreover, there was a slight increase in LDL-cholesterol among older women with T1D, in comparison to men. However, men using LLM appeared to have higher LDL-cholesterol values in the younger age groups in comparison to older age groups. Additionally, women using LLM appeared to have a less pronounced decline in LDL-cholesterol levels as age increased.
Mean and 95% CI of low-density lipoprotein cholesterol (LDL-cholesterol) stratified by lipid lowering medication use in individuals with and without type 1 diabetes. (A) In women. (B) In men. Filled circles and boxes=individuals with type 1 diabetes; open circles and boxes=individuals without type 1 diabetes.
In contrast to the pattern observed for total cholesterol and LDL-cholesterol, individuals with T1D had higher SBP compared with those without diabetes (figure 3). In the younger age groups not using AHM, the difference amounted up to 10 mm Hg. In all cases, SBP levels increased with ageing. In those using AHM, the differences showed a similar pattern; however, there was more variation in the SBP in individuals with T1D. DBP was also higher among the younger age groups with T1D (18–30, 30–40, 40–50) while in the older age groups, these differences disappeared. Similar observations were made when T1D was stratified by glycaemic control and individuals in the poor glycaemic control group appeared to have the highest systolic pressures (online supplemental figures S3 and S4).
Supplemental material
Supplemental material
Mean and 95% CI of systolic (A) and diastolic (B) blood pressure in individuals with and without type 1 diabetes, stratified by antihypertensive medication use. Black diamond=individuals with type 1 diabetes; open diamond=individuals without diabetes.
When the SBP is stratified by sex, we observed that the discrepancies in SBP between those with and without diabetes were most pronounced among young women, in comparison to men (figure 4). Young women with T1D both with and without AHM use had higher SBP in comparison to the background population. In men, although the mean SBP was higher than in women, the SBP between those with and without diabetes was not as discrepant as observed among women. Moreover, older women with T1D using AHM had higher SBP in comparison to men with T1D, with many age groups reaching SBPs considered hypertensive.
Mean and 95% CI of systolic blood pressure in individuals with and without type 1 diabetes, stratified by antihypertensive medication use. (A) In women. (B) In men. Filled circles and boxes=individuals with type 1 diabetes; open circles and boxes=individuals without type 1 diabetes.
Online supplemental figure S5 shows the prevalence of CVD in the T1D and background population per age group. The prevalence of CVD was higher in the T1D population. Similar to the CVD prevalence, both AHM and LLM use was higher among the T1D population in comparison to the background population. The prevalence of medication use is further illustrated in online supplemental file S6.
Supplemental material
Supplemental material
Discussion
In this study, we have shown that concentrations of cholesterol and levels of BP differ between individuals with T1D and people from the general population when compared across age decades and stratified for medication use. In particular, LDL-cholesterol values were lower in T1D, while SBP measurements were higher in almost all age groups irrespective of medication use. Furthermore, sex differences were present when comparing mean LDL and SBP between those with and without T1D. Despite a higher frequency of cardioprotective medication use among individuals with T1D, their prevalence of CVD was higher.
Lipid profile
Lipid metabolism is dependent on glycaemic control and serum insulin concentrations. The peripheral hyperinsulinaemia that accompanies exogenous insulin therapy in T1D leads to a reduction in very LDL (VLDL) production and an increase in LDL, leading to normal or lower concentrations of LDL-cholesterol among individuals with optimal glycaemic control.28 Analyses of individuals from the Diabetes Control and Complications trial (DCCT) comparing T1D to healthy controls showed no differences in LDL-cholesterol concentrations between young adults with and without T1D; however HbA1c levels were 8.9% in men and 9.3% in women.17 Previous studies have demonstrated that better glycaemic control results in lower total cholesterol and LDL-cholesterol levels.29 We therefore expected that LDL-cholesterol may be comparable or lower in the T1D population in comparison to the background population. However, this likely only explains part of the low LDL-cholesterol concentrations we observed in the T1D population using LLM in our study.
Indication bias most likely contributed to the lower levels of LDL-cholesterol found in our T1D population. Individuals with T1D are more readily screened for dyslipidaemia and started on LLM. The lower levels of LDL-cholesterol observed in the age groups above 40 without LLM use is likely a result of the individuals with an indication for LLM being prescribed it, thereby leaving the ‘healthiest’ individuals in this group. What may support this is that the use of LLM was much higher in the population with T1D in comparison to the background population.
Additionally, the lower levels of LDL-cholesterol achieved in the T1D population using LLM could be a result of both treatment and better adherence driven by differences in motivation. Physicians prescribing LLM in individuals with T1D may do so more stringently by virtue of knowing the greater implication of cardiovascular risk for this population. Individuals with T1D may also be more motivated than the background population to protect themselves from cardiovascular complications. Studies have shown that individuals with more risk factors are more likely to be adherent to prescribed medications.30 31 However, there is also likely a component of survival bias, whereby individuals with T1D and severe dyslipidaemia are lost earlier than individuals in the background population.
Blood pressure
Previous studies have established the presence of accelerated vascular ageing and increased arterial stiffness in youth and young adults with T1D.32 33 Early vascular or endothelial damage can lead to an increased vascular resistance, requiring greater systolic pressures to perfuse tissue.34 Additionally, this increased resistance leads to further renal dysfunction, which contributes further to an increased BP.34 These mechanisms may explain the increased SBPs measured across all age groups in our study. Our findings are similar to a study in Finland, in which individuals with T1D were found to have higher SBP in comparison to controls.18 Moreover, the higher SBP measures in combination with lower DBP measured in the older age groups suggests that pulse pressure, an important marker of vascular stiffness and risk factor for CVD, also increases substantially.35
Sex differences
Sex differences for both LDL-cholesterol and SBP were observed in this study. Young women with T1D, not using LLM, had comparable to lower LDL concentrations to the general population. This may be explained by the effects of oestrogens on the lipid and lipoprotein metabolism.36 Premenopausal women have lower circulating LDL-cholesterol, explained by the enhanced clearance of VLDL and LDL-cholesterol.37 The LDL-cholesterol in older women, not using LLM, continued to increase in our study. This may in part be due to the postmenopausal changes in LDL-cholesterol, however, may also be due to differences in LLM prescription practices. Previous studies have described lower use of cardioprotective medications despite guideline recommendations in women with T1D.19 38 This finding may point to potential differences in the management of lipid profiles between men and women. This is of importance as in contrast to the general population, women with T1D have a higher risk of vascular events in comparison to men.39
Although the SBPs are lower in women compared with men not using AHM, the discrepancy between individuals with T1D and the background population was largest among the women. In particular, the SBP measurements in women using AHM is much higher than men and are in the hypertensive range (>140 mm Hg). This not only suggests a difference in management practices between men and women, but also could suggest that women are more therapy resistant. But most importantly, these results suggest women are less protected for CVD in comparison to men. In the EURODIAB study, a collaboration of European childhood diabetes registers, SBP was found to be a significant risk factor for coronary heart disease in women, with an HR of 1.3 for every 1 mm Hg increase in SBP.40 In men, SBP was not a significant predictor for CVD.40 Poor systolic control in these women is therefore undesirable and suggests an area for future improvement.
Strengths and limitations
A major strength of this study includes the use of outpatient clinic data in a ‘real-world’ setting and the comparison to individuals without diabetes in the Lifelines cohort, a representative background population .34
Although this study reflects the ‘real-world’ setting, individuals at the extremes of lipid profiles and BP measurements may be under-represented. Individuals who historically have had good lipid profiles and BP measurements may be screened less often. While individuals who have lower drive for self-care may present less often in the outpatient clinic. Furthermore, individuals with severe complications such as renal failure are not captured in this population, as they are managed by nephrologists. This can contribute to an underestimation of the lipid and BP measurements. Survival bias is also difficult to eliminate due to the cross-sectional nature of this study, therefore individuals with extreme measurements may already be lost at the time of measurement.
A further potential limitation is the quality and the completeness of the data extracted from electronic medical records.41 Nevertheless, only 4% of the T1D population were excluded in this study due to incomplete data. Moreover, data were collected at different time points, with up to 8 years difference between the measurements in the Lifelines cohort and the T1D cohort. Although guidelines for cardiovascular risk management have changed over time, they have not changed to such an extent to influence the results. Newer guidelines have primarily focused on better risk stratifications, and treatment changes are primarily in groups that are not included in our control population (individuals with T2D or renal disease).
Lastly, the use of outpatient clinic BP measurements may lead to an overestimation in the measurements.42 Although guidelines recommend the use of two measurements when assessing BP, this practice cannot be assured to the same degree as a study visit. Finally, there were differences in lipid measurements, non-fasted versus fasted state, between those with T1D and the general population. However, studies have shown that total cholesterol and LDL-cholesterol remain stable in the fasted and non-fasted state.43
Conclusion
Individuals with T1D continue to have an increased prevalence of CVD when compared with a background population even in an era with improved treatment options for glycaemic and non-glycaemic risk factors. LDL-cholesterol and BP are not comparable between individuals with T1D and the background population in most age groups. Although treated LDL-cholesterol levels appear to be better in individuals with T1D, the same cannot be said for BP. Differences in the BP means between individuals with T1D and the background population appear to be highest among young women, potentially implying underlying sex differences in the management of LDL-cholesterol and BP.
Data availability statement
Data are available upon reasonable request. The data of the T1D individuals that support the findings of this study are available on request from the corresponding author (RDMV). The data are not publicly available due to privacy or ethical restrictions. The manuscript is in part based on data from the Lifelines cohort study. Lifelines adheres to standards for data availability and allows access for reproducibility of the study results. The data catalogue is publicly accessible at www.lifelines.nl. The dataset supporting the conclusions of this article is available through the Lifelines organisation, and all international researchers can apply for data access at the Lifelines research office (research@lifelines.nl). For data access, a fee is required.
Ethics statements
Patient consent for publication
Ethics approval
This study involves human participants. Diabeter/UMCG cohort: The Medical Ethical Review Board of the UMCG, Groningen, the Netherlands, declared that the study was not subject to the Dutch ‘Medical Research Involving Human Subjects Act’ (WMO) and a waiver was granted. The institutional review board approved the study protocol (202000883). Lifelines cohort: The study protocol was approved by the medical ethical review committee of the University Medical Center Groningen, Groningen, the Netherlands. Participants gave informed consent to participate in the study before taking part.
Acknowledgments
The authors acknowledge the services of the Lifelines cohort study, the contributing research centres delivering data to Lifelines and all the study participants. This study was supported by Dutch Diabetes Research Foundation grant no. 2015.16.1856, for which we are very grateful. The Lifelines Biobank initiative has been made possible by subsidy from the Dutch Ministry of Health, Welfare and Sport, the Dutch Ministry of Economic Affairs, the University Medical Center Groningen (UMCG the Netherlands), University Groningen and the Northern Provinces of the Netherlands.
References
Supplementary materials
Supplementary Data
This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.
Footnotes
Contributors RDMV contributed to the design, analysis, interpretation and authored the manuscript. DM and H-JA contributed to the design, acquisition of the data and gave feedback on the manuscript. BHRW and MMvdK contributed to the acquisition of the data and supervised the project and are guarantors of this study.
Funding This study was funded by Dutch Diabetes Research Foundation grant no. 2015.16.1856.
Competing interests DM and H-JA are employed at Diabeter Netherlands, an independent clinic (owned by Medtronic), with brand-agnostic prescription under EU/Dutch healthcare laws. The research presented here was independently performed.
Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Provenance and peer review Not commissioned; externally peer reviewed.
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.