We aimed to evaluate how the presence and severity of congenital heart disease (CHD) influence social life and lifestyle in adult patients. A random sample (n = 1,496) from the CONgenital CORvitia (n = 11,047), the Dutch national registry of adult patients with CHD, completed a questionnaire on educational attainment, employment and marital statuses, and lifestyle (response 76%). The Utrecht Health Project provided a large reference group (n = 6,810) of unaffected subjects. Logistic regression models were used for subgroup analyses and to adjust for age, gender, and socioeconomic status where appropriate. Of all patients 51.5% were men (median age 39 years, interquartile range 29 to 51) with mild (46%), moderate (44%), and severe (10%) CHD. Young (<40-year-old) patients with CHD were more likely to have achieved a lower education (adjusted odds ratios [ORs] 1.6 for men and 1.9 for women, p <0.05 for the 2 comparisons), significantly more often unemployed (adjusted ORs 5.9 and 2.0 for men and women, respectively), and less likely to be in a relationship compared to the reference group (adjusted ORs 8.5 for men and 4.5 for women). These poorer outcomes were seen in all severity groups. Overall, the CHD population smoked less (adjusted OR 0.5, p <0.05), had more sports participation (adjusted OR 1.2, p <0.05), and had less obesity (adjusted OR 0.7, p <0.05) than the reference group. In conclusion, there was a substantial social disadvantage in adult patients with CHD, which was seen in all severity groups and primarily in young men. In contrast, adults with CHD had healthier lifestyles compared to the reference group.
Conflicting findings have been documented regarding the educational and occupational performance, living situation, marital status, and offspring in adults with congenital heart disease (CHD). Deriving a complete picture of the social performance of these patients from existing studies is hampered by several factors including small samples, different age ranges, low response rates, and variations in methods across studies. Furthermore, not all studies use reference data for comparison to the general population. Studies that used reference data mostly derived their data from national registries rather than from individual patient data, which allows analyses only on group level. Another issue for the aging CHD population is that they will become more susceptible to developing coronary artery disease. Therefore, a healthy lifestyle should be advocated to minimize cardiovascular risk factors. Currently, little is known about the prevalence of cardiovascular risk factors in adult patients with CHD. Nevertheless, recent studies have shown that nearly 80% of adults with CHD have ≥1 cardiovascular risk factor and that these traditional risk factors also correlate with coronary artery disease in these patients. To evaluate the effect of CHD on social life in adults, we compared sociodemographic characteristics of adults with CHD to those of a reference group. In addition, we assessed lifestyle and determined the prevalence of cardiovascular risk factors.
Methods
The CONgenital CORvitia (CONCOR) Dutch national registry and DNA bank of adult patients with CHD has been described in detail previously. In brief, the CONCOR aims to facilitate research into the cause of CHD and on its outcome. From November 2001 through August 2009, >11,000 patients with CHD ≥18 years of age were included through their treating cardiologist or by response to advertisements in local and national media. Clinical data such as diagnosis, clinical events, and procedures—classified using the European Paediatric Cardiac Code Short List coding scheme —and patient and family histories were obtained. For multiple diagnoses in 1 patient, a prespecified hierarchical scheme founded on a consensus-based classification of severity of diagnoses was used, whereby the diagnosis with the worst prognosis was established as the main diagnosis. Currently, 107 hospitals are participating including all 8 tertiary referral centers from which approximately 67% of registered patients originate. An estimated 35% to 50% of the total adult CHD population in the Netherlands is registered in CONCOR.
From CONCOR 2,106 adult patients with CHD were randomly selected for possible participation. We excluded patients with a cognitive impairment (n = 118). The remaining 1,988 patients were invited to participate by letter to complete a Web-based questionnaire. The age range of these patients was 18 to 94 years; 52% were men. Reminders were sent to nonrespondents 6 and 12 weeks after the first invitation. The second reminder included the paper-based version of the questionnaire. Total period of data collection was 8 months (December 2009 to July 2010). Under Dutch law, ethical approval is not required for questionnaire studies. Therefore, this study was exempted from approval of the medical ethics committee of the Academic Medical Center in Amsterdam and the University Medical Center Utrecht in Utrecht.
Participants from the Utrecht Health Project (UHP) formed our reference group. The UHP is a prospective dynamic population study in a new suburb west of the city Utrecht, the Netherlands, which started in 2000. New inhabitants are invited to participate in this study. At baseline, an individual health profile is made using an extended intake procedure including a physical examination, blood sample, and a self-report questionnaire. The questionnaire includes demographic factors, lifestyle factors, current health status, quality of life, psychopathology, and disability. The UHP population is considered a general population sample. Reference data were collected during 7 years (March 2000 to May 2007) and were available for all items but only partly for assessment of offspring. Our reference group consisted of 6,810 subjects whose age range was 19 to 91 years, and 45% were men.
The questions used in this questionnaire ( Supplementary data , available online) were partly derived from the validated health questionnaire used for the UHP at baseline. The following subjects were covered: (1) medical history, gender, age, height, weight, chronic diseases, and functional status; (2) substance use and exercise; and (3) educational, marital, and occupational statuses, offspring, and living conditions.
Severity of defect was categorized as mild, moderate, or severe using a consensus-based classification scheme. Educational attainment was categorized as high or low, with low educational attainment being defined as having achieved secondary education or lower. Unemployment was defined as having no paid job or having a paid job for <12 hours a week. Income was defined as annual gross income and divided in 2 categories (cutoff was set at the lowest tertile) with low income being defined as <€20,000/year. Sports participation was defined as ≥1 hour/week participation in sports (walking/bicycling not included). The activity score provided an indication of the activity level per subject per week and was derived from the validated Dutch Short Questionnaire to Assess Health Enhancing Physical Activity. This score takes into account a subject’s age, MET score for exercise, self-reported intensity of exercise, and duration of exercise per week in minutes. Soft drugs were defined as cannabis; all other drugs were classified as hard drugs.
For sociodemographic characteristics, substance use, cardiovascular risk factors, and proportions of patients are presented in percentages. Age is presented as median (interquartile range). For comparison between patients with CHD and the reference group, we used chi-square test for categorical variables and independent-samples t test for continuous variables or Mann–Whitney test when appropriate. Outcomes of interest were low educational attainment, unemployment, low income, no relationship, alcohol use, current smoking, sports participation, obesity, diabetes mellitus, and having ≥1 cardiovascular risk factor. To examine the effect of having a CHD on the different outcomes, multivariable logistic regression analyses were performed with adjustment for age for sociodemographic characteristics and adjustment for age, gender, and socioeconomic status (educational attainment was used as a proxy for socioeconomic status) for assessment of lifestyle. Furthermore, the same analyses were used to examine the effect of the severity of the defect on the outcomes described earlier, with severity of defect included as categorical variable. We tested for modification by including interaction terms in the model. Modification was considered present when the p value of the interaction term was ≤0.05. Age and gender proved to be effect modifiers in the associations between the CHD and sociodemographic outcomes (p ≤0.05 for interaction terms); therefore, we performed stratified analyses in subgroups defined by age (no older than vs older than median age) and gender (man vs woman) for these associations. Presented outcome measurements were odds ratios (ORs) with 95% confidence intervals (CIs). The association was considered significant if the 95% CI did not cover the value 1.
Nonresponse analyses concerning age, gender, severity of defect, and type of treating hospital were also performed using chi-square test and Mann–Whitney test. Level of significance was set at a p value ≤0.05 (2-sided). Statistical analysis was performed with SPSS 17.0.1 (SPSS, Inc., Chicago, Illinois).
Results
Of the eligible 1,988 patients, 32 refused to participate and 1,496 patients agreed to complete the Web-based (anonymously, n = 1,104) or paper-based (anonymously, n = 392) questionnaire. Eleven patients were lost to follow-up and did not receive our invitation; the other 449 patients did not respond to our call for participation. The overall response rate, corrected for deceased patients and subjects lost to follow-up, was 76% ( Figure 1 ) .
Nonresponse analysis between respondents and nonrespondents (the latter includes patients refusing to participate) showed that respondents were more often women (p = 0.06), were older (median age 40 vs 32 years, respectively, p <0.001), were less often treated in a tertiary referral center (p <0.001), and had less often severe defects (p = 0.01). However, when comparing respondents to the total CONCOR population, no significant differences were seen in gender, age, type of treating hospital, and severity of defect (absolute difference of proportions <5%).
The proportional distribution of the main diagnoses in the study population is displayed in Figure 2 . Ventricular septal defect, atrial septal defect, tetralogy of Fallot, aortic coarctation, and aortic stenosis collectively accounted for 54% of all diagnoses, similar to the total CONCOR population. Nearly 72% of patients were treated in a tertiary referral center. Main sociodemographic characteristics of the study population are listed in Table 1 .
| Sociodemographic Characteristics | CHD | Total Patients ⁎ (n = 1,496) | Reference Group (n = 6,810) | p Value † | ||
|---|---|---|---|---|---|---|
| Mild (n = 682, 45.6%) | Moderate (n = 656, 43.9%) | Severe (n = 157, 10.5%) | ||||
| Age (years), median (interquartile range) | 44 (31–56) | 38 (28–48) | 30 (25–37) | 39 (29–51) | 35 (30–45) | 0.006 |
| Male gender | 50.90% | 51.10% | 56.10% | 51.50% | 44.80% | <0.001 |
| Educational attainment | ||||||
| No education | 2.80% | 2.30% | 4.50% | 2.70% | 3.40% | |
| Lower | 31.40% | 26.60% | 26.10% | 28.80% | 26.90% | <0.001 |
| Average | 34.90% | 38.40% | 47.10% | 37.80% | 30.10% | |
| Higher | 30.80% | 32.60% | 22.30% | 30.70% | 39.70% | |
| Daily life | ||||||
| Employed | ||||||
| Paid job ≥12 hours | 59.80% | 67.60% | 65.60% | 63.80% | 77.70% | <0.001 |
| Hours of work/week, median (interquartile range) | 37.5 (28–40) | 37 (30–40) | 36 (27–40) | 36 (28–40) | 38 (32–40) | |
| Paid job <12 hours | 2.10% | 2.90% | 0% | 2.20% | 0.80% | |
| Unpaid volunteer work | 0.90% | 0.90% | 0.60% | 0.90% | 0% | |
| Unemployed | ||||||
| Household | 7.80% | 5.60% | 7.00% | 6.80% | 8.00% | |
| Job seeking/disabled | 9.70% | 11.30% | 17.20% | 11.20% | 6.80% | |
| Retired | 14.40% | 5.00% | 0% | 8.80% | 5.40% | |
| Student | 5.4 | 6.6 | 9.6 | 6.4 | 1.4 | |
| Annual income ‡ | ||||||
| <€20,000 | 37.60% | 36.50% | 54.50% | 38.90% | 28.90% | |
| €20,000–€30,000 | 24.40% | 22.80% | 24.50% | 23.70% | 16.90% | <0.001 |
| €30,000–€40,000 | 17.80% | 20.70% | 14.50% | 18.80% | 25.80% | |
| >€40,000 | 20.20% | 19.90% | 6.40% | 18.70% | 28.40% | |
| Living situation § | ||||||
| Relationship ‖ | ||||||
| Yes | 72.10% | 68.60% | 57.40% | 69.00% | 89.00% | <0.001 |
| No | ||||||
| Divorced | 3.10% | 3.10% | 0% | 2.80% | 1.90% | |
| Single | 13.20% | 17.40% | 21.30% | 15.90% | 6.20% | |
| Widow(er) | 3.40% | 1.20% | 0.60% | 2.20% | 1.00% | |
| Other ¶ | 8.10% | 9.70% | 20.60% | 10.10% | 1.90% | |
| No offspring | 38.40% | 50.90% | 74.40% | 47.60% | Unknown | |
| Offspring # | ||||||
| 1 child | 19.30% | 25.20% | 57.50% | 23.90% | 39.70% | <0.001 |
| 2 children | 53.50% | 50.80% | 27.50% | 50.90% | 43.90% | |
| ≥3 children | 27.30% | 24.00% | 15.00% | 25.20% | 16.40% | |
⁎ Defect unknown in 1 patient.
† Comparison of total patient group to reference group.
‡ Annual income per subject, known only for a CONgenital CORvitia subgroup (n = 1,144) and for 1-subject households in the reference group (n = 532).
§ Known only for a subgroup of the reference group (n = 1,872).
‖ Married, living together with partner, or long distance relationship.
¶ Living with parents, living with roommates, or living under guidance.
# Known only for a subgroup of women in the reference group (n = 665).
Stratified multivariable logistic regression showed that having a CHD significantly increased the probability of low educational attainment for men (adjusted OR 1.6, 95% CI 1.3 to 3.0) and women <40 years old (adjusted OR 1.9, 95% CI 1.5 to 2.5; Figure 3 ) . These risks were higher in all severity groups, even in the mild group, but were most pronounced in the severe group. Young (<40-year-old) patients with CHD were also more often unemployed (adjusted OR 5.9, 95% CI 3.9 to 9.1 for men and 2.0, 95% CI 1.5 to 2.6 for women) and were less likely to be in a relationship compared to the reference group (adjusted OR 8.5, 95% CI 5.7 to 12.5 for men, 4.5 95% CI 3.2 to 6.3 for women). Furthermore, young patients with CHD more often had a low income compared to the reference group, although this difference disappeared after additional adjustment for educational attainment and hours of work.
Table 2 presents substance use and cardiovascular risk factors. The patient sample had a significantly lower lifetime prevalence of drug use and smoked less than the reference group. No differences were seen in sports participation. This was also the case when intensive sports participation (≥5 hours/week) was compared. Multivariable logistic regression showed an overall healthier lifestyle in adults with CHD ( Table 3 ). No differences were seen in lifestyle between women and men with CHD, except for sports participation. Overall higher sports participation in the CHD group ( Table 3 ) was mainly owing to the contribution of women (OR 1.4, 95% CI 1.2 to 1.7 vs OR 1.1, 95% CI 0.9 to 1.2 for men).
| Substance Use and Cardiovascular Risk Factors | CHD | Total Patients ⁎ (n = 1,496) | Reference Group (n = 6,810) | p Value † | ||
|---|---|---|---|---|---|---|
| Mild (n = 682, 45.6%) | Moderate (n = 656, 43.9%) | Severe (n = 157, 10.5%) | ||||
| Currents in alcohol use | 82.60% | 81.00% | 75.20% | 81.10% | 82.60% | 0.17 |
| Drinks/week, mean ± SD | 5.1 ± 5.7 | 4.5 ± 5.2 | 4.3 ± 5.0 | 4.7 ± 5.4 | 8.7 ± 11.1 | <0.001 |
| Drugs (life-time use) ‡ | ||||||
| Soft drugs | 13.10% | 13.30% | 12.80% | 13.10% | 25.70% | <0.001 |
| Hard drugs | 4.30% | 6.20% | 7.70% | 5.50% | 7.70% | 0.01 |
| Current smoker | 14.30% | 13.10% | 5.70% | 12.90% | 20.50% | <0.001 |
| Pack-years, mean ± SD | 11.2 ± 9.3 | 10.9 ± 10.2 | 6.6 ± 9.9 | 10.9 ± 9.8 | 16.4 ± 14.1 | <0.001 |
| Physical activity | ||||||
| Participation in sports | 52.50% | 51.40% | 48.70% | 51.60% | 49.60% | 0.16 |
| Activity score, mean ± SD | 622.0 ± 1,025.8 | 582.9 ± 885.3 | 595.5 ± 1,153.1 | 601.9 ± 980.4 | 583.5 ± 1,045.8 | 0.54 |
| Body mass index (kg/m 2 ) | ||||||
| Normal (<25) | 54.20% | 63.50% | 69.90% | 59.90% | 51.40% | <0.001 |
| Overweight (25–30) | 34.30% | 27.50% | 22.90% | 30.20% | 36.10% | |
| Obesity (>30) | 11.40% | 9.00% | 7.20% | 9.90% | 12.50% | |
| Diabetes mellitus | 3.10% | 4.10% | 1.90% | 3.40% | 2.30% | 0.02 |
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