Atherosclerotic coronary artery disease (CAD) is the leading cause of mortality worldwide.1 In this context, the burden of CAD shows considerable regional heterogeneity at the national level. For example, age-standardized mortality rates varied between 106 and 178 deaths per 100 000 at the level of German federal states in 2019.2 The regional heterogeneity of cardiovascular mortality suggests that the residential environment should be considered as an important determinant for successful secondary prevention. Environmental features that were frequently drawn upon to explain regional inequalities of cardiovascular outcomes are spatial socioeconomic deprivation (SSD) and rurality.3 Rurality may impact cardiovascular health due to impaired access to healthcare services. Socioeconomically deprived neighbourhoods, on the other hand, exhibit restricted opportunities to eat healthy, exercise regularly, utilize health care, and avoid environmental hazards such as air pollution.3
Repeated activation of compensatory mechanisms to counter these harmful exposures may lead to dysregulation of the immune and metabolic system, chronic inflammation, and oxidative stress.4 An emerging body of research suggests that chronic systemic oxidative stress and inflammation are accompanied by high levels of dysfunctional high-density lipoprotein (HDL), and that dysfunctional HDL is associated with worse outcomes among cardiovascular patients.5,6 Hence, we investigated the association of SSD and rurality with dysfunctional HDL to explore spatial inequalities of oxidative stress and inflammation among patients with CAD. In this study, we used a cell-free fluorometric method based on the Amplex Red reaction that we developed to measure HDL-associated lipid peroxidation (HDLox) indicating HDL dysfunction.7
We conducted a cross-sectional study among adult patients with a coronary stenosis of at least 50%. The study was approved by the local ethics committees of the medical association of Brandenburg [AS69(bB)/2016] and the Ruhr University of Bochum (Nr. 15-5279). Patients admitted electively for coronary angiography at the University Hospital Brandenburg an der Havel of Brandenburg Medical School and at the University Hospital of the Ruhr University of Bochum were recruited between 2016 and 2019 if they provided informed consent. Both hospitals are located in cities that rank in the highest quintile of SSD in Germany.8 Brandenburg an der Havel and its surroundings show a rural settlement structure while Bochum is located in a highly urbanized area. HDL-associated lipid peroxidation was measured in serum blood samples of 812 patients.7 Clinical data were collected in personal interviews. Data on rurality and SSD were linked to individual cases using five-digit postcodes. The community population density (scale of 1000 inhabitants/km2) was used to define rurality9 and the German Index of Socioeconomic Deprivationwas used to define SSD (0 indicating low and 1 indicating high deprivation).8 We conducted multivariable linear regression to estimate adjusted associations of continuous scores of SSD and rurality with the level of HDLox. Values of HDLox have no unit and were logarithmized to yield normally distributed data. Residuals of logarithmized HDLox were distributed normally and there was no heteroscedasticity. Multilevel analysis was not performed, since no clustering of HDLox was detected at the level of postcode areas.
Among all included patients, 76.1% were male and the majority of the study population were over 70 years old (Table 1). HDL-associated lipid peroxidation showed a coefficient of variability of 0.55 and there were higher levels of HDLox in regions with high compared with regions with low SSD (Figure 1). In linear regression, we found good evidence for an association of SSD with HDLox when adjusting for age group, sex, and hospital (β = 0.444, P = 0.02). This result corresponds to an increase of HDLox by 5.6% with an increase of the SSD index by 0.1. There was no association of rurality with levels of HDLox after adjustment for confounders (β = 0.040, P = 0.19). Moreover, when mutually adjusting for SSD and rurality, deprivation was still associated with HDLox (β = 0.404, P = 0.05). Further adjustment for current smoking (yes/no), arterial hypertension (yes/no), obesity (BMI > 30 kg/m2), total cholesterol (mg/dL), LDL (mg/dL), triglycerides (mg/dL), and current statin use (yes/no) did not change the results. However, adjustment for diabetes mellitus reduced the regression coefficient for SSD (β = 0.330, P = 0.09). Finally, the association of SSD with HDLox was only present in the 50% of postcodes with the lowest population density (β = 0.610, P = 0.01), but not in the 50% with the highest population density (β = −0.051, P = 0.90). There was weak evidence for the interaction of SSD with the binary indicator for rurality (P = 0.16).
Table 1.
Descriptive characteristics of included patients with coronary artery disease
| Female (n = 194) | Male (n = 618) | |
|---|---|---|
| Age group | ||
| Under 50 | 8 (4.1%) | 24 (3.9%) |
| 50–59 | 19 (9.8%) | 115 (18.6%) |
| 60–69 | 55 (28.4%) | 176 (28.5%) |
| 70–79 | 72 (37.1%) | 215 (34.8%) |
| Over 79 | 40 (20.6%) | 86 (13.9%) |
| Missing | 0 (0%) | 2 (0.3%) |
| Hospital | ||
| Brandenburg an der Havel | 115 (59.3%) | 328 (53.1%) |
| Bochum | 79 (40.7%) | 290 (46.9%) |
| Spatial socioeconomic deprivation | ||
| Median (min, max) | 0.815 (0.611, 0.869) | 0.813 (0.454, 0.908) |
| Missing | 0 (0%) | 5 (0.8%) |
| Rurality (1000 inhabitants/km2) | ||
| Median (min, max) | 0.309 (0.017, 3.860) | 0.310 (0.017, 3.890) |
| Missing | 0 (0%) | 5 (0.8%) |
| HDLox level (no unit) | ||
| Median (min, max) | 0.659 (0.217, 5.270) | 0.822 (0.135, 5.850) |
| Current smoking | ||
| No | 137 (70.6%) | 388 (62.8%) |
| Yes | 54 (27.8%) | 217 (35.1%) |
| Missing | 3 (1.5%) | 13 (2.1%) |
| Arterial hypertension | ||
| No | 14 (7.2%) | 69 (11.2%) |
| Yes | 179 (92.3%) | 547 (88.5%) |
| Missing | 1 (0.5%) | 2 (0.3%) |
| Obesity (BMI >30 kg/m2) | ||
| No | 115 (59.3%) | 396 (64.1%) |
| Yes | 77 (39.7%) | 220 (35.6%) |
| Missing | 2 (1.0%) | 2 (0.3%) |
| Diabetes mellitus | ||
| No | 117 (60.3%) | 390 (63.8%) |
| Yes | 76 (39.2%) | 219 (35.8%) |
| Missing | 1 (0.5%) | 2 (0.3%) |
| Cholesterol level (mg/dL) | ||
| Median (min, max) | 184.0 (94.0, 374.0) | 168.0 (80.4, 412.0) |
| Missing | 2 (1.0%) | 14 (2.3%) |
| LDL level (mg/dL) | ||
| Median (min, max) | 109.0 (32.0, 295.0) | 100.0 (19.3, 227.0) |
| Missing | 1 (0.5%) | 17 (2.8%) |
| Triglyceride level (mg/dL) | ||
| Median (min, max) | 76.5 (22.8, 396.0) | 85.0 (12.0, 2100.0) |
| Missing | 1 (0.5%) | 17 (2.8%) |
| Current statin use | ||
| No | 114 (18.4%) | 46 (23.7%) |
| Yes | 502 (81.2%) | 147 (75.8%) |
| Missing | 2 (0.3%) | 1 (0.5%) |
HDLox, high-density lipoprotein lipid peroxidation; BMI, body mass index.
Figure 1.
Scatterplot of high-density lipoprotein lipid peroxidation levels according to spatial socioeconomic deprivation.
Our study showed higher levels of HDLox among CAD patients from neighbourhoods with high SSD compared with patients from moderately deprived areas. Since high HDLox mirrors the result of exposure to chronic oxidative stress and inflammation, these mechanisms may be promising starting points for further research on spatial disparities of cardiovascular health outcomes.5 Concerning behavioural risk factors, recent studies suggested that diabetes mellitus, reduced physical activity, and chronic inflammatory diseases are associated with impaired HDL function.5,10 Our finding that diabetes mellitus partially explained the association of SSD with HDLox is in line with these results. The lack of an association of rurality with HDLox suggests that socioeconomic conditions of neighbourhoods may play a more important role than rurality for oxidative stress and inflammation among cardiovascular patients in Germany. Moreover, moderation of the association of SSD with HDLox by rurality indicates effect modification.
Areas included in this study represent medium and highly deprived regions and are not representative for the socioeconomic environment of Germany. Furthermore, we were not able to disentangle compositional from contextual effects, since no data on the individual socioeconomic position were available. The strength of our study lies in the valid assessment of rurality and SSD in combination with an innovative technique to measure HDLox.7 Furthermore, analysing the association on the level of small areas probably allowed us to minimize bias due to the modifiable area unit problem.
In conclusion, our findings highlight that knowledge about socioeconomic characteristics of cardiovascular patients’ neighbourhoods might be crucial when evaluating strategies for secondary prevention. In addition, inflammation and oxidative stress depict important mechanisms that may explain spatial socioeconomic inequalities among patients with CAD. Since we employed a cross-sectional exploratory study, our results need confirmation in future research.
Acknowledgements
We would like to thank all participants of this study.
Funding
N.P. received an internal grant from Brandenburg Medical School Theodor Fontane.
Footnotes
Conflict of interest: none declared.
Data availability
The data of this study cannot be made publicly available because current data protection regulations in Germany prohibit publication of health-related data, as anonymized information could still be used in combination and/or with other data to identify study participants. However, data can be made available for researchers who meet the criteria for access to confidential data upon reasonable request to the corresponding author.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data of this study cannot be made publicly available because current data protection regulations in Germany prohibit publication of health-related data, as anonymized information could still be used in combination and/or with other data to identify study participants. However, data can be made available for researchers who meet the criteria for access to confidential data upon reasonable request to the corresponding author.