Abstract
Objective
The aim was to examine the association between hospital-diagnosed overweight/obesity and incident CVD according to the time period of the overweight/obesity diagnosis.
Design
This is a cohort study.
Methods
From Danish national health registries, we identified all residents with a first-time hospital-based overweight/obesity diagnosis code, 1977–2018 (n = 195,221), and an age and sex-matched general population comparison cohort (n = 1,952,210). We computed adjusted hazard ratios (aHRs) with 95% confidence intervals (CIs) using Cox regression. We adjusted for comorbidities and educational level and applied 10 years of follow-up.
Results
The overall incidence rate was 10.1 (95% CI 10.0–10.1) per 1000 person-years for the comparison cohort and 25.1 (95% CI 24.8–25.4) per 1000 person-years for the overweight/obesity cohort, corresponding to an aHR of 2.5 (95% CI 2.4–2.5). The aHR was elevated for all subtypes of CVD: heart failure: 3.9 (95% CI 3.7–4.1), bradyarrhythmia: 2.9 (95% CI 2.7–3.1), angina pectoris: 2.7 (95% CI 2.7–2.8), atrial fibrillation or flutter: 2.6 (95% CI 2.5–2.6), acute myocardial infarction: 2.4 (95% CI 2.3–2.4), revascularization procedure: 2.4 (95% CI 2.2–2.5), valvular heart disease: 1.7 (95% CI 1.6–1.8), ischemic stroke: 1.6 (95% CI 1.4–1.7), transient ischemic attack: 1.6 (95% CI 1.5–1.7), and cardiovascular death: 1.6 (95% CI 1.5–1.6). The 1–10-year aHR of any CVD associated with an overweight/obesity diagnosis decreased from 2.8 (95% CI 2.7–2.9) in 1977–1987 to 1.8 (95% CI 1.8–1.9) in 2008–2018.
Conclusion
Patients with hospital-diagnosed overweight/obesity had high rates of ischemic heart disease, heart failure, structural heart disease, arrhythmia, stroke, and death, although the strength of the association decreased in recent years.
Significance statement
Obesity is linked to metabolic abnormalities that predispose individuals to an increased risk of subtypes of CVD. In this population-based nationwide 40-year cohort study, we found that of 195,221 patients with an overweight/obesity diagnosis, more than 31,000 (15.9%) were admitted to hospital within 10 years because of CVD; corresponding to a 2.5-fold greater relative risk of any CVD associated with overweight/obesity than in the general population. We observed an increased risk for most CVD subtypes, including ischemic heart disease, heart failure, structural heart disease, arrhythmia, stroke, and cardiovascular death, although the strength of the association decreased in recent years. Our study emphasizes the importance of improved clinical handling of obesity and underscores the need to prevent associated complications to alleviate the burden of obesity.
Introduction
The prevalence of obesity has greatly increased in recent decades, resulting in major public health implications (1, 2). Overweight and obesity are associated with the development of risk factors for CVD, including type 2 diabetes, hypertension, and dyslipidemia (3, 4, 5, 6). Additionally, obesity is recognized as a risk factor in the development of CVD morbidity and mortality (4, 7, 8, 9, 10, 11), owing to inflammation, effects on hemodynamics, and altered heart structure (7). Despite the increase in obesity during the past decades (1), CVD mortality has declined in European countries and in the USA (12, 13). This decrease might be attributable to improvements in other lifestyle factors, including a decrease in smoking (14, 15) and enhanced use of lipid-lowering and antihypertensive drugs (12, 16).
Knowledge regarding obesity-associated risk of CVD has primarily been based on general population-based studies, which have reported a 38–85% higher overall CVD risk in people with obesity compared with people without obesity (3, 17, 18, 19). However, no studies have examined the long-term risk of CVD among patients with hospital-diagnosed obesity. A hospital contact resulting in registration of an overweight/obesity diagnosis code indicates that the overweight/obesity status may be important for the patient’s future health. A hospital visit also provides the opportunity to assess the patient’s risk of cardio-metabolic disease and to initiate preventive interventions improving his/her long-term health.
We examined whether the association between hospital-diagnosed overweight/obesity and CVD has changed in the past decades compared with an age and sex-matched general population comparison cohort. Furthermore, we assessed associations with CVD subtypes and potential effect measure modifications according to patient characteristics.
Materials and methods
Study design, setting, and data sources
The source population for this cohort study was the entire cumulative Danish population of 8.8 million residents, from January 1, 1977, through December 31, 2018. In Denmark, access to health care is universal and tax funded (20). We used civil registration numbers (a unique identifier indicating sex and date of birth) assigned to all residents since 1968 (20) and registered in the Danish Civil Registration System (CRS) (21) to access linked data from the following Danish registries.
The Danish National Patient Registry (DNPR) has recorded hospitalizations since 1977 and outpatient clinic and emergency department visits since 1995. Diagnoses were coded according to the Eighth Revision of the International Classification of Diseases (ICD-8) through 1993 and the Tenth Revision (ICD-10) thereafter (22). The DNPR contains information on the primary discharge diagnosis (i.e. the main reason for the hospital visit) and any secondary diagnoses (e.g. underlying chronic diseases) (22). The Danish Register of Causes of Death contains information from all death certificates since 1943 (23). The Integrated Database for Labour Market Research contains information on the highest level of education achieved by each resident since 1988 (24).
Overweight/obesity cohort
From the DNPR, we identified patients with a first inpatient or outpatient diagnosis code for overweight/obesity recorded at any Danish hospital during the study period (see Supplementary Tables 1 and 2 (see section on supplementary materials given at the end of this article) for codes and frequencies) (22). The overweight/obesity diagnosis codes had a positive predictive value of 87.6% when compared to in-hospital BMI measurements (25). We did not include women who were registered with overweight/obesity only in relation to pregnancy. Furthermore, we did not include patients diagnosed with CVD before an overweight/obesity diagnosis (Supplementary Table 1). We obtained the complete medical history for all patients (see Supplementary Table 3 for diagnosis codes), and from the CRS we obtained information on vital status and migration (20). For patients with a secondary diagnosis code of overweight/obesity, we tabulated the 25 most common primary diagnosis codes (Supplementary Table 4).
General population comparison cohort
Using the CRS and the DNPR (20), we obtained information on sex, birth date, and hospital discharge history. We randomly frequency-matched five individuals without previous diagnoses of overweight/obesity to each overweight/obesity patient according to sex and birth year on the date of the corresponding index patient’s first overweight/obesity diagnosis, sex and year of birth as the index patient. We performed the matching with replacement, i.e. an individual in the comparison cohort could be sampled more than once to avoid immortal time bias (26). We defined the index date as the date of diagnosis for patients with overweight/obesity and the matching day for individuals in the comparison cohort. Individuals in the comparison cohort who were subsequently diagnosed with overweight/obesity then entered the overweight/obesity cohort while remaining in the comparison cohort to avoid informative censoring (n = 56,858) (27). For each individual who after the index date also became included in the overweight/obesity cohort, five new matched individuals were selected for the comparison cohort.
Patient subgroups
Age (28), comorbidities (29), and socioeconomic status (30) may modify the association between obesity and CVD. We used data from the DNPR to summarize each patient’s comorbidity history 5 years before the index date, based on a multimorbidity index comprising 39 psychiatric and physical long-term conditions. We excluded ischemic heart disease, atrial fibrillation and flutter, heart failure, peripheral vascular disease, and stroke from the index (Supplementary Table 3) (31, 32, 33). A lookback period of 5 years has been reported to be an appropriate time period to capture relevant comorbidities and predict mortality and hospital outcomes (34).
Socioeconomic status may also modify any association between overweight/obesity and CVD (35). From the Integrated Database for Labour Market Research, we obtained information on income, employment, and the highest level of education achieved (24).
Study outcomes
Based on data from the DNPR, we identified all patients in the two cohorts with a first-time hospital diagnosis of CVD. We retrieved data on acute myocardial infarction (MI), angina pectoris, any coronary revascularization procedure (percutaneous coronary intervention or coronary artery bypass grafting, only from 1994 and onward), heart failure, valvular heart disease, aortic dissection, atrial fibrillation or flutter, bradyarrhythmia, ventricular tachycardia, cardiac arrest, ischemic stroke, transient ischemic attack, hemorrhagic stroke, cardiovascular death including sudden death, and all-cause mortality. The validity of CVD diagnosis codes in the DNPR is generally high, with positive predictive values between 76% (heart failure) and 97% (MI) when compared to a medical record review (36, 37). From the Danish Register of Causes of Death, we retrieved diagnoses for the causes of deaths (cardiovascular death including sudden death).
Statistical analyses
We followed all individuals in both cohorts from the index date until appearance of the first diagnosis code in any CVD disease category, death, emigration, or December 31, 2018, whichever came first. We characterized both cohorts in terms of sex, age, and other covariates and computed the median age with interquartile range at inclusion and median follow-up time.
We then computed the incidence rates (IRs) of any first-time acute admission due to CVD per 1000 person-years in the two cohorts, following all individuals for 10 years. We conducted a Cox proportional-hazards regression analysis to compute the hazard ratios (HRs) of any CVD with 95% CIs, comparing patients with overweight/obesity with individuals in the comparison cohort. For all Cox models, we used log–log plots to assess the proportionality of hazards visually and found that the assumptions were not violated. In the regression model, we adjusted for the individual comorbidities listed in Supplementary Table 5, cohabitation status, and educational level. We calculated the absolute risk of CVD, treating death as a competing risk (38).
We repeated the adjusted HR (aHR) analyses within 10 years of follow-up stratified by age (<30, 30–49, 50–69, and ≥70 years), sex (female/male), period of diagnosis (1977–1987, 1988–1997, 1998–2007, and 2008–2018), number of comorbidities at index date (0/1/2/3/≥4), type of diagnosis code (primary vs secondary and overweight vs obesity), prior diabetes (yes/no), chronic obstructive pulmonary disease (yes/no), alcoholism-related disorders (yes/no), kidney disease (yes/no), income (low/intermediate/high/very high), and educational level (basic education/youth education/higher education).
We graphically illustrated short-term and long-term cumulative risk for patients with overweight/obesity within 1 year, 10 years, and 20 years of follow-up. For each period of diagnosis, we further computed IRs and crude HR and aHRs for 1–364 days, 1–10 years, 11–20 years, 21–30 years, 31–40 years, and 1–40 years after the index date. Finally, we computed the IRs and crude and aHRs for the most frequent CVDs and compared the rates of subtypes of CVD in the two cohorts within 10 years of follow-up.
The study was registered with the Danish Data Protection Agency (registration number: 2016-051-000001, 605). According to Danish legislation, registry-based studies do not require separate approval from the Danish Research Ethics Committee. We conducted all statistical analyses in SAS version 9.4 (SAS Institute, Cary, NC).
Results
Characteristics
In the overweight/obesity cohort (n = 195,221 patients, 1,239,504 person-years) and the comparison cohort (n = 1,952,210 individuals, 13,850,648 person-years), 72.1% were women, and the median age was 40 years at the index date (Fig. 1 and Supplementary Table 5). More individuals in the overweight/obesity cohort than in the comparison cohort had hospital-recorded comorbidity at the index date (comorbidity score = 0 in 64.8% vs 80.9%, respectively), including diabetes (14.6% vs 0.8%).
Adjusted hazard ratios of cardiovascular disease among patients with overweight/obesity and individuals in the comparison cohort, overall and by subgroup, within 10 years of follow-up. The aHRs are adjusted for type 2 diabetes, chronic obstructive pulmonary disease, alcoholism-related disease, kidney disease, cohabitation status, and educational level, except for the variable in concern in the stratified analyses.
Citation: Endocrine Connections 13, 4; 10.1530/EC-23-0452
Among patients with overweight/obesity, overweight/obesity was a secondary diagnosis code for 158,090 (81.0%) of them (Fig. 1 and Supplementary Table 5). The number of patients with newly diagnosed overweight/obesity increased largely during the study period, with 101,740 (52.1%) of the patients being diagnosed in the final 10 years. Among patients with overweight/obesity 38.4% had basic education as the highest educational level vs 26.2% among the individuals in the comparison cohort (Fig. 1 and Supplementary Table 5).
Association between overweight/obesity and overall CVD
The IRs and the aHRs for any CVD were markedly higher for the overweight/obesity cohort than for the comparison cohort during the entire study period (Fig. 2 and Supplementary Table 6). The overall IR was 10.1 (95% CI 10.0–10.1) per 1000 person-years for the comparison cohort and 25.1 (95% CI 24.8–25.4) per 1000 person-years for the overweight/obesity cohort (Supplementary Table 5). The overall aHR was 2.5 (95% CI 2.4–2.5) within 10 years of follow-up.
Associations between overweight/obesity and cardiovascular disease, by time period and duration of follow-up. The aHRs are adjusted for type 2 diabetes, chronic obstructive pulmonary disease, alcoholism-related disease, kidney disease, cohabitation status, and educational level.
Citation: Endocrine Connections 13, 4; 10.1530/EC-23-0452
The absolute CVD risks within 10 years of follow-up were 17.5% (95% CI 17.3–17.8%) in the overweight/obesity cohort and 9.1% (95% CI 9.1–9.2%) in the comparison cohort (Supplementary Table 6).
Association between overweight/obesity and 1-year CVD risk
During the first year of follow-up, the absolute risk of any CVD was 4.6% (95% CI 4.50–4.7%) in the overweight/obesity cohort and 0.9% (95% CI 0.8–0.9%) in the comparison cohort (Supplementary Table 6). Looking at the entire study period, the aHR was 5.2 (95% CI 5.0–5.3) during the first year after a diagnosis of overweight/obesity (Fig. 2 and Supplementary Table 6). Patients diagnosed with overweight/obesity in 1977–1987 had an aHR of 5.9 (95% CI 5.5–6.3) and an IR of 69.9 (95% CI 66.7–73.1) within the first year of follow-up, while patients diagnosed in 2008–2018 had an aHR of 3.4 (95% CI 3.2–3.5) and an IR of 29.3 (95% CI 28.2–30.4) within the first year of follow-up (Fig. 2 and Supplementary Table 7).
Association between overweight/obesity and CVD rate beyond 1 year
The aHRs remained elevated approximately two-fold during the entire study period for the overweight/obesity cohort compared with the comparison cohort (Figs. 2, 3 and Supplementary Table 7). The 1–10-year aHR clearly decreased over time, from 2.8 (95% CI 2.7–2.9) in 1977–1987 to 1.8 (95% CI 1.8–1.9) in 2008–2018 (Figs. 2, 3 and Supplementary Table 7).
Cumulative incidence of cardiovascular disease in the overweight/obesity cohort 1, 10, and 20 years after the first diagnosis of overweight or obesity.
Citation: Endocrine Connections 13, 4; 10.1530/EC-23-0452
CVD subtypes
Compared with individuals in the comparison cohort, patients with obesity/overweight had markedly higher 10-year aHRs for all subtypes of CVD (Fig. 4 and Supplementary Table 8). Overweight/obesity was associated with a four-fold higher risk of heart failure and a three-fold higher risk of angina pectoris. Furthermore, patients with overweight/obesity had an approximately two-fold higher rate of MI, atrial fibrillation or flutter, bradyarrhythmia, cardiac arrest, ventricular tachycardia, ischemic stroke, transient ischemic attack, any revascularization procedure, valvular heart disease, aortic dissection, cardiovascular death, and all-cause mortality. Finally, the risk of hemorrhagic stroke associated with overweight/obesity was 1.4-fold higher, though the estimates varied from 0.9 to 2.2 depending on the time period of diagnosis (Supplementary Table 8).
(A and B) Associations between overweight/obesity and cardiovascular disease among patients with overweight/obesity compared with individuals in the comparison cohort within 10 years of follow-up. The aHRs are adjusted for type 2 diabetes, chronic obstructive pulmonary disease, alcoholism-related disease, kidney disease, cohabitation status, and educational level. *Percutaneous coronary intervention or coronary artery bypass graft.
Citation: Endocrine Connections 13, 4; 10.1530/EC-23-0452
Stratified analyses
The association between overweight/obesity and CVD decreased with age (age 18–29 years: aHR = 3.4 (95% CI 3.0–3.8); age 70+ years: aHR = 1.9 (95% CI 1.9–2.0)) (Fig. 1 and Supplementary Table 5). The aHR was higher among patients with overweight/obesity with no comorbidities (aHR = 2.3 (95% CI 2.3–2.3)) than in those with ≥4 comorbidities at baseline (aHR = 1.3 (95% CI 0.9–1.9)). Similarly, patients with overweight/obesity and diabetes had an aHR of 1.5 (95% CI 1.1–2.0), whereas patients without diabetes had an aHR of 2.1 (95% CI 2.1–2.1) (Fig. 1 and Supplementary Table 5). The aHR was 1.9 (95% CI 1.8–1.9) for women and 2.5 (95% CI 2.4–2.5) for men.
Furthermore, the aHR associated with overweight/obesity was 2.0 (95% CI 1.9–2.1) among patients with higher education, compared with 1.9 (95% CI 1.8–1.9) among patients with basic education (Supplementary Table 5). For patients with very high income, the aHR was 2.5 (95% CI 2.4–2.6) compared with 1.7 (95% CI 1.7–1.8) for patients with low income (Fig. 1 and Supplementary Table 5).
Discussion
In this population-based follow-up study, we found that more than 31,000 of 195,221 patients with overweight/obesity were hospitalized due to CVD within 10 years after being diagnosed with overweight/obesity. These findings corresponded to a 2.5-fold higher aHR of any CVD in patients with overweight/obesity compared with the general population. From 1977 to 2018, we observed a decrease in the association between overweight/obesity and the risk of CVD in patients with hospital-diagnosed overweight/obesity. We showed that findings from general population studies of an association between overweight/obesity and all subtypes of CVD also apply to a hospital setting.
Overall CVD risk increased – but declined in recent years
Our findings of a higher long-term CVD risk associated with hospital-diagnosed overweight/obesity are comparable to those from general population studies. However, direct comparisons are difficult, considering that comorbidities, lifestyle, and other confounding factors affecting CVD risk may be more frequent in hospitalized people (33, 39). Our study supports that obesity is associated with an elevated risk of several types of CVD (17, 40). In the absence of broad evidence of the overall burden of CVDs in people with hospital-diagnosed overweight/obesity, we analyzed associations between overweight/obesity and overall CVD as well as CVD subtypes. Throughout the study period, we found a consistently elevated 1-year risk of any CVD, indicating that obesity-related pathophysiological mechanisms may be central in the development of CVD.
The decline in CVD risk associated with overweight/obesity over time may be attributable to earlier and better primary prevention (e.g. lipid-lowering and antihypertensive drugs) of CVD risk factors and decreased tobacco use (15, 41). These preventive measures may have more impact in people with obesity than in normal weight people due to the a priori higher CVD risk among people with obesity. For most CVD subtypes, the obesity-associated risk declined from 1988–1997 to 1998–2007, which coincided with the shift in the use of ICD-8 to ICD-10 diagnosis codes in 1994 as well as inclusion of outpatient diagnosis codes.
Subtypes of CVD
We provided an overview of associations between overweight/obesity and subtypes of CVD and found that overweight/obesity is associated with an elevated risk of heart failure (40, 42, 43, 44, 45), angina pectoris (17, 45), atrial fibrillation (46), MI (47, 48), heart valve disease (40, 49), ischemic stroke (48, 50), transient ischemic attack (48, 51), cardiovascular death (52), aortic dissection (53), and hemorrhagic stroke (48, 54).
Sex differences, age, comorbidities, and socioeconomic factors
Our results support previous findings indicating that overweight/obesity may be associated with CVD in both women and men (55, 56). Also in support of existing research, we found a stronger association between overweight/obesity and CVD in men than in women (56). We found no large differences in CVD risk according to age at the time of receiving the overweight/obesity diagnosis.
The presence of baseline comorbidities may dilute the association between overweight/obesity and CVD. People with, rather than without, diabetes are disproportionately affected by CVD, possibly because of diabetes-associated risk factors such as lifestyle factors, hypertension, and dyslipidemia (5, 57). Diabetes reduces life expectancy, with CVD being the leading cause of death among people with diabetes (5, 57).
The association between adverse socioeconomic factors and higher CVD risk is well established (30). In patients with high rather than low socioeconomic status, other lifestyle risk factors may be less frequent, leading to higher isolated effects of obesity.
Physiological mechanisms
Obesity adversely influences CVD risk factors such as insulin resistance, blood pressure, and lipid profiles (58). Furthermore, obesity may promote disease progression in the cardiovascular system, mediated by changes in volume status, cardiac loading, oxidative stress, endothelial dysfunction, and systemic low-grade inflammation (10, 43). In case of heart failure, high body mass causes hemodynamic perturbations, thus altering the heart structure and increasing inflammatory and hormonal stress on the heart and vasculature (42, 43).
Limitations
A main limitation of our study is the use of overweight/obesity diagnosis codes without information on exact BMI values. The completeness of overweight/obesity registration in the DNPR is low with only 11% of patients with a BMI ≥25 kg/m2 receiving an overweight/obesity diagnosis (25), which may raise concerns about information bias. However, the positive predictive value of an overweight/obesity diagnosis is 87.6%, which is high (25). Our risk estimates associated with hospital-diagnosed overweight/obesity might be conservative, due to low sensitivity of the overweight/obesity diagnosis code despite a high specificity, as well as an increasing prevalence of overweight and obesity in Denmark; more than half of Danes have overweight (34%) or obesity (19%) (59). We included patients with inpatient (43.5%) and outpatient (56.5%) clinic contacts. Obesity is likely underdiagnosed. However, this is not a major limitation as we studied prognosis and not incidence. Still, an inpatient diagnosis could reflect more severe obesity than an outpatient diagnosis. We therefore also stratified by contact type and found that the aHR for any CVD was 2.5 (95% CI 2.4–2.5) for inpatients and 1.5 (95% CI 1.5–1.5) for outpatients (Fig. 1), supporting the assumption of a registration of more severe or comorbid obesity in inpatients. The most common primary diagnosis codes among patients with a secondary overweight/obesity diagnosis code included diabetes, arthrosis, and menstrual disturbances, all of which may be associated with overweight/obesity. Thus, we might have included patients who already developed obesity-related comorbidities.
For some covariates and outcomes, changes in diagnostic criteria may have occurred during the study period (60). However, this can hardly explain the general trend observed for cardiovascular diseases. Onset of overweight and obesity is likely to occur years before a hospital visit, meaning that prevalent and incident obesity cases might have been mixed, particularly for the first years of our study period due to left censoring in the DNPR (61).
The number of patients with hospital diagnoses of overweight/obesity has increased in recent years, potentially reflecting an increased prevalence of overweight/obesity in the population, an increased use of the diagnosis codes by clinicians, an increasing number of hospital admissions in general, and/or increased awareness of overweight/obesity. We speculate that this increased awareness and the inclusion of outpatient clinic patients from 1995 onward might have led to the inclusion of more healthy patients diagnosed with overweight/obesity in the later years of the study period.
Finally, we had no information on life style factors including physical activity level (11, 62).
Conclusion
Patients with overweight/obesity had a substantially elevated long-term risk of CVD. The associated increased risk was observed for most individual CVD subtypes, thus emphasizing the importance of overweight/obesity as a risk factor for ischemic heart disease, heart failure, structural heart disease, arrhythmia, stroke, and death. Still, in the past, we observed decreases in obesity-associated risk of CVD among patients with hospital-diagnosed overweight/obesity. Our study highlights the need to improve the clinical handling of obesity and emphasizes that prevention of obesity and associated complications is crucial to alleviate the burden of obesity.
Supplementary materials
This is linked to the online version of the paper at https://doi.org/10.1530/EC-23-0452.
Declaration of interest
SBG has received speaking fees from Novo Nordisk A/S. All other authors declare they have no conflicts of interest.
Funding
This research was supported by Department of Clinical Epidemiology at Aarhus University Hospital, the Independent Research Fund Denmark (grant 490-63-2618), the Novo Nordisk Foundation (grant NNF18OC0052917), and the Central Denmark Region. MS is supported by the Novo Nordisk Foundation (grant NNF19OC0054908) outside of this work. The funding sources had no involvement in the study design; in the collection, analysis and interpretation of data; in the writing of the article; or in the decision to submit the article for publication.
Data availability statement
Data are available as presented in the paper. According to Danish legislation, our own approvals to use the Danish data sources for the current study do not allow us to distribute or make patient data directly available to other parties. Interested researchers may apply for data access through the Research Service at the Danish Health Data Authority. Up-to-date information on data access is available online (http://sundhedsdatastyrelsen.dk/da/forskerservice). The authors do not have special access privileges to these data.
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