IJE Advance Access originally published online on January 19, 2005
International Journal of Epidemiology 2005 34(2):309-315; doi:10.1093/ije/dyh381
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Article |
Socioeconomic status and health: is parasympathetic nervous system activity an intervening mechanism?
1 Behavioral Medicine Program, Columbia University Medical Center, Box 427, 622 West 168th Street, New York, NY 10032, USA
2 Division of Behavioral Medicine, Department of Psychiatry, Columbia University, New York, NY, USA
3 New York State Psychiatric Institute, 1051 Riverside Drive, New York, NY 10032, USA
4 Division of Geriatrics, Geffen School of Medicine at UCLA, Los Angeles, CA, USA
5 Kaiser Permanente, Division of Research, Oakland, CA, USA
6 Department of Medicine, Northwestern University, Chicago, IL, USA
7 Division of Preventive Medicine, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
* Corresponding author. Richard P Sloan, Columbia University, Box 427, 622 West 168th Street, New York, NY 10032, USA. E-mail: rps7{at}columbia.edu
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Abstract |
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Background The link between socioeconomic status (SES) and health is widely recognized but the pathophysiologic mechanisms are not well understood. We tested the hypothesis that parasympathetic nervous system (PNS) regulation is one such mechanism.
Methods In a cross-sectional study, electrocardiogram-derived RR interval variability (RRV), a non-invasive index of cardiac PNS regulation, and SES, measured as educational attainment and income, were collected in 756 subjects in the CARDIA study of heart disease in young adults.
Results Relative to those with less than a high school education, those with high school to college and post-college education had 26% (ß = 0.233) and 43% (ß = 0.355) greater low frequency (LF) RRV, respectively, adjusted for age, sex, and race. For high frequency (HF) RRV, race interacted with income: relative to low income whites, intermediate and high income whites had 133 and 191% greater HF power, respectively, while intermediate and high income blacks had 32 and 44% greater HF RRV, respectively, relative to low income blacks.
Conclusions Numerous studies demonstrate that psychosocial stressors reduce cardiac parasympathetic regulation and that SES disparities are associated with increasing social stress proportional to the degree of disparity. Data from the current study suggest that PNS regulation may be a mechanism linking the stressful effects of low SES to increased morbidity and mortality.
Keywords Parasympathetic nervous system, Socioeconomic status, community study
Accepted 25 October 2004
The inverse association of socioeconomic status (SES) and health is well established. Lower SES has been related to higher prevalence and incidence of most chronic and infectious diseases as well as to greater cognitive and physical disability and higher mortality.1–4 Concerns about such health inequalities continue to grow in light of the fact that Socioeconomic differences in health appear to be increasing in the US and in other developed countries.5–7
While these associations have been consistently documented, the underlying mechanisms linking SES to adverse health outcomes have yet to be established. One candidate for such an intervening mechanism is autonomic nervous system activity. A substantial body of evidence demonstrates that RR interval variability (RRV) from the electrocardiogram provides a non-invasive index of cardiac autonomic modulation. Variability in the spectrally defined high frequency (HF) range (0.15–0.50 Hz) has been linked to cardiac parasympathetic regulation, as shown by studies employing vagal stimulation, blockade, and vagotomy. 8,9 RR interval oscillations at lower frequencies (LF) (0.04–0.15 Hz) appear to have mixed parasympathetic and sympathetic contributions,9,10 with the magnitude of the sympathetic contribution varying as a function of several factors including posture and activity.9,11
Low levels of cardiac autonomic regulation measured by RRV have been shown repeatedly to predict adverse outcomes in patients following acute myocardial infarction (MI) and heart failure12,13 and the development of heart disease of previously healthy subjects in community studies.14,15 Laboratory studies demonstrate that administration of acute stressors leads to reductions in HF and LF power16 and self-reported stress throughout the day is associated with diminished cardiac autonomic regulation.17
Because wide differences in SES, such as those that exist in the US, appear to be associated with greater social friction and psychological stress inversely related to the position on the SES hierarchy,18,19 we hypothesized that cardiac parasympathetic modulation would be directly related to SES and as such, might be a mechanism by which SES influences health. To date, only one study has examined this association and found no relationship between cardiac autonomic modulation and education.15 In this paper, we report relationships between RRV and SES in 756 young adults as part of the Coronary Artery Risk Development in Young Adults CARDIA study.
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Study population
The CARDIA study is a bi-ethnic, prospective, multicentre epidemiological study of the evolution of cardiovascular risk development in young adulthood. In 1985–1986, 5155 black and white men and women, aged 18–30 years, were recruited at Birmingham, AL; Chicago, IL; Minneapolis, MN; and Oakland, CA, to achieve a balance at each site by race (black, white), gender, education (high school degree or less, more than high school), and age (18–24 years, 25–30 years).20 Participants were examined at study entry and at years 2, 5, 7, 10, and 15 with re-examination rates among surviving cohort members of 90.5, 85.7, 80.6, 78.5, and 73.5%, respectively. Comparisons of CARDIA subjects who participated in the Year 15 examination with those who did not indicated that the latter participants were more likely to be African American, younger, less educated, and smokers (data not shown). Approval and informed consent were obtained for each examination from the site institutional review committee.
At the Year 15 examination, subjects seen at the Oakland, CA and Chicago, IL sites (and living within 50 miles of the clinic; n = 721 and 615, respectively) were asked to participate in the RRV substudy of SES and development of biological risk, including assessments of RRV. Of the 1336 subjects who were eligible for the substudy, 789 (59%) agreed to participate. Comparisons of those who did and did not participate in the substudy revealed that participants tended to be of somewhat lower education and income and had somewhat higher body-mass index BMI, diastolic and systolic blood pressure (SBP).
Data collection
SES
For SES, we used both total years of education completed as of the Year 15 examination and current household income, with education in three categories: those who completed high school or less, those who completed at least some college (i.e. 13–16 years), and those with at least some post-graduate education. Income was classified into approximate tertiles: <$42 500, $42 500 to <$87 500, and 
$87 500.
Covariates
Measurements of SBP, BMI, physical activity, and smoking from the Year 15 examination were examined. Selection of these covariates was based on their known associations with both SES and RRV. SBP was measured during seated rest, the average of three measurements with a random zero sphygmomanometer. Physical activity was measured as self-reported participation in heavy and moderate intensity activities and quantified as previously described.21 Smoking was measured as self-reported current smoking (non-smoker, ex-smoker, and current smoker). Analyses examined these factors as potential mediators of the relationship between SES and RRV.
Substudy assessments
Participants arrived at the laboratory having eaten a light breakfast and having abstained from caffeinated beverages that morning. Study protocols were explained and written consent was obtained. The RRV protocol was then explained and ECG electrodes were attached. Subjects then rested quietly in the seated position for a 2-min period after which data were collected for 10 min. Subjects were asked to sit quietly without moving or talking.
Acquisition and processing of ECG signals
ECG data were collected continuously throughout the protocol. ECG electrodes were placed on the right shoulder, on the left anterior axillary line at the 10th intercostal space and in the right lower quadrant. Analog ECG signals were digitized at 500 Hz by a National Instruments A/D board and stored on a microcomputer. The ECG waveform was submitted to a specially written R-wave detection routine, resulting in a time series of RR intervals (RRIs). Errors in marking of R-waves were corrected interactively.
Heart rate (HR) and RRV
The mean HR was computed for all subjects. Spectral analysis to compute RRV was conducted on 5-min epochs using an interval method for computing Fourier transforms similar to that described by DeBoer, Karemaker, and Strackee.22 Although the term ‘heart rate variability’ is more common, we refer to RRV because spectral analyses were conducted on time series of RRIs, not HRs. Prior to the Fourier analysis, the mean of the RRI series was subtracted from each value in the series and the residual series then was filtered using a Hanning window23 and the power, i.e. variance (in ms2), over each of the low (0.04–0.15 Hz (LF)) and high (0.15–0.50 Hz (HF)) frequency bands was summed. Estimates of spectral power were adjusted to account for attenuation produced by this filter.23 Global RRV, computed as the standard deviation of RR intervals (SDRR), also was measured.
In cases in which 5-min epochs of data were compromised by electronic artifact or subject movement, identification of all R-waves was impossible. RRIs associated with these artifacts were fixed using established procedures if possible. If not, the epoch was excluded from spectral analysis.
For each subject, RRV was computed as the mean of the two 5-min epochs. Prior to statistical analysis, estimates of RRV were log transformed to correct for skewness.
Statistical Analyses
Data were analysed in two stages. First, linear regression models examined the effect of SES, adjusted simultaneously for age, race, gender, and the SES–race interaction. A second regression model then was estimated adding all of the following to the model: physical activity, BMI, smoking, and SBP. Separate analyses were conducted for education and income as they were only modestly correlated (r = 0.46). In each case, a pair of dummy variables was used to model the effects of each of the two higher levels of either education or income relative to a reference group (the lowest category of education and income, respectively). Analyses were run on RRV (HF, LF, SDRR) and HR. All analyses were conducted using SAS version 8.02 (SAS Institute Inc, Cary, NC).
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Results |
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Of the 789 subjects who participated in the study, 756 subjects (96%) had technically adequate data. 44% were white and 42% were men. Table 1 presents general characteristics of the cohort. As expected, all indices of RRV were significantly correlated with each other, with rs ranging from 0.67 to 0.83 (all Ps < 0.0001). Table 2 shows that in model 1, all indices of RRV and HR were significantly associated with educational attainment as an index of SES. This SES–LF power relationship is depicted in Figure 1a. Relative to those with less than a high school education, those with high school to college and post-college education had 26% (ß = 0.233) and 43% (ß = 0.355) greater LF RRV respectively. After adding risk factor covariates of SBP, physical activity, BMI, and smoking, variables that plausibly could be in the causal pathway between SES and cardiac autonomic regulation, to the model, only LF power remained significant and the effect was attenuated by
25%.
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As shown in Table 2, for SES measured as income, the race–income interaction was significant for LF power, SDRR, and HR and marginally significant for HF power. To illustrate the interaction, race-stratified analyses were run. Figure 1b presents HF power by income separately for black and white subjects. As the figure demonstrates, the effect of income on HF power was seen in both groups, although after control for model 1 covariates, the effect of income on HF power was significant in whites and marginally significant in blacks. Relative to low income whites, intermediate and high income whites had 133 and 191% greater HF power, respectively, while intermediate and high income blacks had 32 and 44% greater HF RRV, respectively, than low income blacks, adjusted for age and sex. As shown in Table 2, addition of model 2 covariates did not alter these race–income interactions.
We repeated these analyses excluding subjects who reported that they had been diagnosed with heart disease, hypertension, or diabetes or reported taking medications for any of these conditions. The results of these analyses did not differ from those conducted on the entire sample (analyses available on request).
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Discussion |
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The association between low levels of SES and increased morbidity and mortality is well established, even if the intervening pathophysiologic mechanisms are not clear. Analysis of data from 756 participants in the CARDIA study of young adults suggests that autonomic nervous system regulation may be one such mechanism. Even after adjustment for stratification variables of age, gender, and race and potential mediating risk factors of physical activity, BMI, SBP, and smoking, lower SES was strongly associated with reduced cardiac vagal modulation as measured by HF power, generally in a dose–response fashion. This was largely true whether SES was assessed either as education or income, although the effects were stronger for income, especially in white subjects. The same effect was seen for LF power.
Of course, the suggestion that cardiac parasympathetic regulation is a mechanism linking SES to health outcomes rests on the evidence that RRV reflects parasympathetic activity. Abundant data supports HF power as such an index. These data include studies of pharmacologic blockade that demonstrate that in both the supine and upright positions, the cholinergic antagonist atropine eliminates HF power.9,11 The physiological significance of LF power is less clear, although the best evidence suggests that it reflects both parasympathetic and sympathetic contributions with the latter varying depending upon several factors including posture. In the supine position, atropine eliminates virtually all LF power, indicating that in this position, LF power also principally reflects parasympathetic activity.9,11 Correspondingly, the sympathetic antagonist propranolol had no significant effect on LF power measured in the supine position. In the upright position, however, atropine alone and propranolol alone eliminated ~70% of LF power, suggesting that in this position, LF power also may reflect a contribution from the sympathetic system.9 This finding is consistent with the underlying physiology of positional change from the supine to the upright position, in which sympathetic activity increases to compensate for gravitationally induced pooling of blood in the lower limbs.24–26
We know of no studies that show the impact of pharmacologic blockade in the seated position. However, using pharmacological blockade, Taylor et al. have demonstrated that atropine eliminated LF power in the 408 tilted position, intermediate between the supine and standing positions.11 They also showed that change from the supine to the 408 upright position did not lead to an increase in LF power, as would be expected if LF power reflected the sympathetic contribution to this positional change. These data suggest much greater similarity in the autonomic profile of the seated and supine positions than the standing one.
The contribution of PNS activity to morbidity and mortality is well established in some areas and more speculative in others. By enhancing myocardial electrical stability, the PNS reduces the risk of sudden cardiac death. Animal experiments confirm the capacity of higher levels of cardiac vagal regulation to protect against sudden death after experimentally induced MI27 and RRV was a powerful predictor of sudden death in heart failure patients13 and in patients at elevated risk for sudden death.28 This effect may account for the repeated finding that low levels of RRV confer elevated risk of adverse events after MI.12,29 According to a recent review, risk of arrhythmias was positively associated with social and psychosocial factors in 88 of the 96 published studies,30 consistent with the proposal that PNS activity is a mechanism linking SES and health.
However, low levels of RRV also predict the development of new onset coronary disease in initially healthy subjects participating in community studies,14,31 suggesting that in addition to enhancing myocardial electrical stability, the PNS has an antiatherogenic and other effects that may operate through the regulation of inflammation32,33 and fat metabolism and insulin resistance.34 Borovikova et al. have demonstrated that vagal nerve stimulation inhibits synthesis of tumour-necrosis factor a (a mediator of local and systemic inflammation) in response to endotoxin.32 Kreier et al. have shown that parasympathetic innervation of adipose tissue modulates its insulin sensitivity and glucose and free fatty acid metabolism.34 These data provide other pathways through which PNS activity could contribute to the SES effect on morbidity and mortality.
To complete the elaboration of the proposed causal pathway, laboratory studies have repeatedly demonstrated that short-term stressors, e.g. arithmetic tasks or the Stroop color word matching task, reduce parasympathetic modulation of the heart, as indicated by reductions in RRV.16,35–37 Wide differences in SES appear to be associated with greater social friction and psychological stress inversely related to the position on the SES hierarchy18,19 and as such should be considered as chronic stressors or repeated acute stressors, either of which should have the effect of stressors introduced in the laboratory: reduction of PNS regulation. Thus, the stressfulness of low SES reduces parasympathetic activity which in turn elevates the risk of sudden cardiac death, the development of coronary artery disease, and sources of morbidity and mortality related to inflammation, insulin sensitivity, and fat metabolism.
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A principal limitation of this study is its cross-sectional nature, which makes inferences about causal direction of the RRV–SES relationship impossible. Although it is unlikely that low levels of RRV are responsible for low SES, it is conceivable that the relationship between RRV and SES is the product of some third factor. For example, because CAD is associated with lower levels of RRV,38,39 it is possible that subclinical cardiovascular disease could account for low levels of RRV. Such an association would explain the capacity of low RRV to predict the development of heart disease in community studies. However, it is not clear how subclinical disease would also be responsible for low SES.
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Conclusion |
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Although the relationship between SES and health is well established, the mechanisms responsible for this association remain mysterious. Using data from a population sample of young healthy adults, we found that after controlling for the effects of stratification variables of age, gender, and race, and risk factors including physical activity, BMI, SBP, and smoking, SES had a positive and linear association with the PNS regulation of the heart. While the effect was greater for white subjects compared with black subjects with SES measured as income, the linear increase in HF and LF power as a function of income was seen for both groups. Since lower levels of parasympathetic activity predict the development of adverse cardiac outcomes, diminished inhibition of inflammation, and insulin sensitivity and fat metabolism, these data suggest that PNS regulation may be a mechanism through which lower SES confers increased health risks.
KEY MESSAGES
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Acknowledgments |
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Work on this manuscript was supported (or partially supported) by contracts N01-HC-48047, N01-HC-48048, N01-HC-48049, N01-HC-48050 and N01-HC-95095 from the National Heart, Lung and Blood Institute, the MacArthur Research Network on SES and Health through grants from the John D. and Catherine T. MacArthur Foundation, by Independent Scientist Award K02 MH01491 (Sloan) from the National Institute of Mental Health, and the Nathaniel Wharton Fund. The authors are indebted to Maria-Paola Pacifici for her expert technical contributions to this article.
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