IJE Advance Access published online on December 3, 2007
International Journal of Epidemiology, doi:10.1093/ije/dym244
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
When do social inequalities in C-reactive protein start? A life course perspective from conception to adulthood in the Cardiovascular Risk in Young Finns Study
1Department of Epidemiology and Public Health, International Institute for Society and Health, UCL Medical School, London, UK.
2Department of Psychology, University of Helsinki, Helsinki, Finland.
3National Research and Development Centre of Welfare and Health (STAKES), Helsinki, Finland.
4Department of Microbiology and Immunology, Tampere University Hospital and University of Tampere Medical School, Tampere, Finland.
5Department of Clinical Chemistry, Tampere University Hospital and University of Tampere Medical School, Tampere, Finland.
6Department of Health and Functional Capacity, National Public Health Institute, Turku, Finland.
7Department of Medicine, University of Turku, Turku, Finland.
8Department of Clinical Physiology, University of Turku, Turku, Finland.
*Corresponding author. Department of Epidemiology and Public Health, International Institute for Society and Health, University College London, 1-19 Torrington Place, London WC1E 6BT, UK. E-mail: d.gimeno{at}ucl.ac.uk
 |
Abstract |
|---|
 Top Abstract IntroductionParticipantsData analysisResultsDiscussionAppendixAcknowledgementsReferences |
|---|
Background It is unclear when in the life course do social inequalities in inflammation emerge. We examined whether the association between socioeconomic position (SEP) and C-reactive protein (CRP) is determined at conception, in childhood, adolescence or adulthood in 1484 participants from the population-based Cardiovascular Risk in Young Finns Study.
Methods Five variants of the CRP gene were used to investigate whether SEP differences in CRP levels are determined at conception. SEP and serum CRP were assessed in childhood (age 3–9), adolescence (age 12–18) and in adulthood (age 24–39). SEP was measured using parental education and occupational status in childhood and adolescence, and participants’ own education and occupational status in adulthood. Participants with CRP > 10 mg/l were excluded.
Results All CRP gene variants were associated with circulating CRP concentrations in childhood, but there were no differences in the distribution of these variants by SEP. No strong evidence was found of associations between parental SEP and CRP. A graded association between higher SEP and lower CRP was observed in adulthood for education (P = 0.0005) but not for occupational status. Trajectories that led to high educational achievement both in the participants and their parents were associated with lower (P 
0.047) CRP levels in adulthood. Excluding participants with infectious diseases, pregnant or lactating women and women using oral contraceptives did not change the findings.
Conclusion In this cohort, SEP differences in CRP concentrations seen in adulthood appear not to be determined at conception or evident in childhood or adolescence.
Keywords inflammation, social class, population studies, cumulative risk
Accepted 30 October 2007
|
Introduction |
|---|
|
TopAbstractIntroductionParticipantsData analysisResultsDiscussionAppendixAcknowledgementsReferences |
|---|
Several studies have shown a graded association between lower socioeconomic position (SEP) across the life course and higher risk of coronary heart disease (CHD) in adulthood.1–3 Chronic low-grade inflammation, as indicated by C-reactive protein (CRP), may be part of the pathogenesis of cardiovascular disease,4–8 but the extent to which SEP is associated with CRP across the life course has not been extensively studied. There is some evidence to support associations of both childhood and adulthood SEP with adult CRP,9–19 but it remains unclear when social differences in CRP actually start.
A recent adoptee study using data from the biological and adoptive parents proposed genetic explanations for SEP differences in adult mortality.20 In theory, SEP differences in CRP level could also be genetically determined and, therefore, inherited at conception.20 This would occur if the genetic variants that determine higher CRP levels were more common in low than in high SEP groups, for example, because of selective mating (a tendency to select mates that are like ourselves in some respect, such as social class). It is also possible that the observed associations between SEP and CRP reflect influences in childhood, adolescence and adulthood. For example, childhood SEP strongly predicts adult SEP, which is associated with adult risk factors, such as obesity, that increase adult CRP levels.21–23
To date, no studies have examined SEP differences in CRP gene polymorphisms that determine higher CRP levels and the few existing studies on the relationship between SEP and CRP in childhood have been limited by rather narrow age ranges. They have also produced very mixed findings, with positive, negative and null associations observed in different studies.24–26 In this study, we aim to determine when social inequalities in CRP start by examining the relationship of SEP with variants in the CRP gene and serum levels of CRP in childhood, adolescence and adulthood in a sample of young Finnish women and men. Using genetic data, we test whether the SEP gradient in CRP is inherited from the previous generation and so already determined at conception. Analyses of childhood, adolescence and adulthood data are used to study when social differences in CRP levels emerge somewhere during the life course between conception and adulthood.
|
Participants |
|---|
|
TopAbstractIntroductionParticipantsData analysisResultsDiscussionAppendixAcknowledgementsReferences |
|---|
Participants were from the population-based Cardiovascular Risk in Young Finns Study.27,28 In order to select participants who were broadly representative of Finnish children and adolescents, in terms of living conditions and socioeconomic and demographic background, Finland was divided into five areas according to the location of the university cities with a medical school (Helsinki, Kuopio, Oulu, Tampere and Turku). In each area, urban and rural boys and girls were randomly selected on the basis of their personal social security number from the Social Insurance Institution's population register, which covers the whole Finnish population. The baseline survey was conducted in six age cohorts of children (aged 3, 6 and 9) and adolescents (aged 12, 15 and 18) in 1980, with a participation rate of 83%, i.e. 3596 of those invited. Participants were re-examined every 3 years between 1980 and 1992 and again in 2001, when they had reached adulthood (aged 24–39).29 Data on at least one SEP measure (either education or occupational status) and one measure of CRP (either in 1980 or 2001) were available for 3576 participants. We excluded those participants who had high CRP values (i.e. >10 mg/l, n = 46 at baseline, n = 73 at follow-up), indicating acute inflammation and immune activation due to current illness, as this is likely to reflect short term rather than chronic inflammation.30 The number of participants for whom data on CRP and SEP measures were available for analysis varied between the childhood, adolescence and adulthood analyses (see Tables 2–5
for detailed samples). The most restrictive sample included those participants (n = 1484) with complete data, that is, two SEP measures, CRP levels from childhood or adolescence and adulthood and all covariates. Comparison of the SEP distributions between the initial 3576 participants and this restricted sample showed a maximum of 1% difference in each SEP category. The study was conducted according to the guidelines of the Declaration of Helsinki, and the protocol was approved by local ethics committees. Own/parental consent was obtained for all participants.
Genotyping
DNA was extracted from whole blood in 2001 using a commercially available kit (Qiagen Inc., Hilden, Germany). Participants were genotyped for the –286 C > T > A (rs3091244), –717 A > G (rs2794521), +1059 G > C (rs1800947), +1444 C > T (rs1130864) and +1846 G > A (rs1205) single-nucleotide polymorphisms (SNPs) of the CRP gene. These five genetic variants of the CRP gene were chosen because of their confirmed associations with circulating CRP levels in previous studies31–35 as well as in this cohort.36 Genotyping was performed using the ABI Prism 7900HT Sequence Detection System for both polymerase chain reaction (PCR) and allelic discrimination (Applied Biosystems, Foster City, CA, USA). For SNP +1059, a commercial kit from Applied Biosystems was used (Assay On Demand, C_177490_10 CRP). The other SNPs were genotyped using Assays By Design from Applied Biosystems under standard conditions, with the exception of the tri-allelic tag SNP (–286 C > T > A). This was genotyped as previously described,33 except for the genotype calling that was done manually from the PCR run component tab. Of the five variants, two are promoter region polymorphisms (–286 C > T > A and –717 A > G), one is exonic (+1059 G > C) and two are in the 3'-untranslated region (+1444 C > T and +1846 G > A). The observed genotype distributions of the variants did not deviate from the expected Hardy–Weinberg distributions.
Measurement of CRP
Serum samples were taken in 1980 (childhood and adolescence) and 2001 (adulthood). Childhood and adolescence samples were stored at –20°C and analysed in 2005, and adulthood samples were analysed in 2001. During the storage, the samples were not thawed or refrozen. Serum high-sensitive CRP was analysed using an automated analyser (Olympus AU400, Olympus, USA) and a highly sensitive turbidimetric immunoassay kit (CRP-UL-assay, Wako Chemicals, Neuss, Germany). Detection limit was 0.02 mg/l, since in our laboratory we have been able to measure reproducibly CRP concentrations between 0.02 and 0.06 mg/l (the detection limit suggested by the manufacturer of the assay). Inter-assay coefficients of variation were 3.33% at the mean level of 1.52 mg/l (n = 116) and 2.65% at the mean level of 2.51 mg/l (n = 168), so similar precision of the assay was observed at different CRP levels.
Socioeconomic position
SEP in childhood and adolescence was assessed in 1980 by parental occupational status (manual; lower-grade non-manual and higher-grade non-manual) and in 1983 by parental education [comprehensive school; non-academic secondary education (i.e. high school or vocational school) and academic].34 Where SEP differed between parents, data on the parent with the higher occupational status/education were used. The participants’ own adult SEP, educational attainment and occupational status were measured in 2001 and categorized as for parental SEP. The categorization of SEP used for the present study was chosen to be consistent with previous work in the same population.22,27,34,37,38 In addition, for occupational status and education, we constructed two life course SEP indicators by combining parental and adult own SEP categories: one indicator of trajectories of exposure to SEP, and, a second indicator of cumulative measures to SEP. Due to sample limitations, some categories had to be combined for the analyses of trajectories (i.e. parental lower and higher non-manual groups were collapsed into a non-manual category, and non-academic secondary education and academic education were collapsed, see Table 4). For the analyses of parental and adult own SEP combined (Table 5), we coded manual = 1, lower non-manual = 2 and higher non-manual = 3. Similarly, we coded comprehensive school = 1, non-academic secondary education = 2 and academic = 3. The sum of parental and adult own SEP scores resulted in a scale from 2 (both manual/comprehensive school) to 6 (both higher non-manual/academic education).
|
Data analysis |
|---|
|
TopAbstractIntroductionParticipantsData analysisResultsDiscussionAppendixAcknowledgementsReferences |
|---|
Associations between SEP categorical indicators and genetic variants in the CRP gene were examined using the
2-test. We used regression analysis to study associations between SEP indicators and CRP. The distribution of CRP is skewed and thus the regression models were fitted with the natural logarithm of CRP as the dependent variable. Findings are illustrated with back-transformed geometric means and the standard error (SE) of CRP levels by SEP category. Linear trends in the associations were tested by entering SEP indicators as continuous variables in the models. Data on men and women were combined as there was no strong evidence of sex differences in the associations between SEP and CRP (all P-values for interaction between sex and SEP were >0.15). All regression models were adjusted by age and sex. Additionally, we explored the associations between SEP and levels of CRP excluding participants with self-reported infectious disease, pregnant or lactating women and women using oral contraceptives.
Sample size varied between childhood, adolescence and adulthood analyses. Since smaller numbers reduce the power to detect SEP differences in CRP levels, we conducted post hoc power analyses to estimate the required sample size to achieve an 
-level of P = 0.05 assuming that estimates and their SE remain unchanged. Finally, to inform a life course approach, CRP levels in adulthood were analysed in relation to trajectories of exposure to parental and own adult SEP categories as well as cumulative measures of parental and own adult SEP indicators.
|
Results |
|---|
|
TopAbstractIntroductionParticipantsData analysisResultsDiscussionAppendixAcknowledgementsReferences |
|---|
CRP concentration increased by age in both sexes (P < 0.0001) and was higher (P < 0.0008) among women (0.29 mg/l in childhood/adolescence and 0.85 mg/l in adulthood) than among men (0.25 mg/l in childhood/adolescence and 0.64 mg/l in adulthood). Table 1 shows the age- and sex-adjusted levels of CRP in childhood by CRP gene polymorphisms. All the CRP gene variants were found to be associated with circulating CRP levels in childhood (all P
0.025) supporting the status of these variants as early determinants of circulating CRP levels. However, the distribution of CRP gene polymorphisms by parental SEP indicators (Appendix Table A1) showed no SEP differences in any of the CRP gene polymorphisms examined, neither when parental occupation nor parental education was used as the SEP indicator.
|
Table 2 shows the age- and sex-adjusted levels of CRP in childhood, adolescent and adulthood by parental SEP indicators. No SEP gradient in CRP levels was found in childhood or in adolescents. Based on post hoc power analyses, the required number of adolescents needed to observe an effect would be between 1.3 and 1.8 times greater than the current sample. For adult CRP, there was only indication of an inverse gradient in adult CRP by parental occupation (P = 0.064, n = 2151). This would have reached
-level P = 0.05 with only 12.2% additional participants. No association was seen between parental education and adult CRP (P = 0.522, n = 1905). Regarding the participants’ own SEP, there was strong evidence of an inverse association between education and adult CRP (P = 0.0005, n = 2198), but no strong evidence of an association with occupational status (Table 3).
|
|
Table 4 shows age- and sex-adjusted levels of CRP in adulthood by SEP trajectory characterized by exposure to parental and adult own SEP indicators. There was no difference by trajectory of occupational status from childhood to adulthood (P = 0.417), but there was an association between educational trajectory and CRP (P = 0.015). Participants who did not achieve an academic level of education as adults had the highest levels of CRP, while those who did had the lowest levels irrespective of parental education.
|
Table 5 shows age- and sex-adjusted levels of CRP in adulthood by cumulative exposure to parental and adult own SEP indicators. No SEP gradient in CRP levels was found for parental and participant's occupational status combined (P = 0.197), but such a gradient was observed for parental and participant's education combined (P = 0.047). The lowest levels of CRP were seen among participants with own and parental education at the non-academic secondary level or with at least one at the academic level had the lowest levels of CRP. Other combinations were associated with higher CRP levels.
|
The exclusion of participants with infectious diseases, pregnant or lactating women, and women using oral contraceptives, had little effect on the previously observed associations between SEP and CRP: a gradient in adult CRP was still seen with own education (P < 0.0001, n = 1697); educational trajectory (P = 0.021, n = 1452) and, cumulative exposure of parental and adult own education (P = 0.048, n = 1452).
|
Discussion |
|---|
|
TopAbstractIntroductionParticipantsData analysisResultsDiscussionAppendixAcknowledgementsReferences |
|---|
The present study based on the well-defined sample population-based Cardiovascular Risk in Young Finns Study is probably the first to explore the association between SEP and CRP from a life course perspective that extends from pre-natal genetic influences through childhood and adolescence to adulthood. In this cohort, SEP differences in serum CRP concentrations were seen in early adulthood, age 24–39 years, but such differences were not evident in childhood or adolescence. There was no evidence of SEP differences in the five genetic variants studied, suggesting that SEP differences are not pre-determined at conception. The association between adult SEP and CRP levels was evident only for participants’ own education, and not with occupational status. Educational trajectories from childhood to adulthood as well as the combination of parental and adult own educational levels also showed an association with CRP levels.
Inter-individual variation in CRP plasma levels may be explained by genetic factors, but our findings suggest that such variation is unlikely to explain the SEP gradients in CRP observed in later life. Thus, our results provide no evidence of assortative mating by SEP that could explain social inequalities in CRP. In contrast, cumulative exposure to environmental risk factors is a more plausible explanation to SEP differences that become apparent in adulthood. This is also consistent with prior research on SEP gradients in adult CRP levels. Exposure to adverse psychosocial, behavioural, material and other health-related risk factors are hypothesized mechanisms through which SEP may influence levels of CRP.39
SEP trajectories and cumulative SEP experiences were associated with CRP levels, but the association between SEP and CRP levels became only evident with adult own education. Therefore, both the trajectory and the cumulative effect of SEP would be mostly explained by exposure to adult SEP, an interpretation that is consistent with the missing cross-sectional associations between SEP and CRP in childhood and adolescence. In addition, we found that the association between SEP and CRP levels was only evident for participants’ education, and not with participants’ occupational status. This may be because of the age range (24–39 years) of our sample. Adults in this age range have a relatively short exposure to work life. Our findings indicating stronger effects of adult vs childhood SEP and of education vs occupation on adulthood levels of CRP are in agreement with one recent study evaluating SEP in childhood (age 10 years) and adulthood (age 45 and more years).40
We did not find statistically significant SEP differences in serum CRP levels in childhood or adolescence. Similarly, differences in childhood CRP levels by parental social class were not observed in a sample of 10- to 11-year-old British children.24 However, among a rural sample of 2- to 15-year olds in Bolivia, low household economic resources were associated with greater CRP levels.26 In contrast, a sample of British children aged 12–13 years attending high-SEP school had greater CRP levels than children attending a low-SEP school.25 This unexpected direct gradient disappeared when high (>10 mg/l) CRP levels were excluded. The Bolivian study did not report results using this cut off, so positive findings that were due to the inclusion of high values cannot be ruled out.26 We excluded participants with CRP levels exceeding 10 mg/l because such high CRP levels have been defined as suggestive of acute inflammation and immune activation due to current illness, and are thus likely to reflect short-term responses. As expected, in our data, the inclusion of participants with these high-CRP values strengthened slightly the magnitude of the association between SEP and CRP levels,27 although overall results were unaffected. The mechanism through which SEP and CRP are related in childhood may be that children living in deprived environments have greater prevalence of acute infectious illnesses that raises inflammation.
Methodological issues
Relatively small samples may have influenced the power of our study to detect SEP differences. Post hoc power analyses suggested that a small increase in sample size might have provided evidence of an effect of parental SEP on adult CRP. Regarding the skewness of the CRP data, most parametric statistical procedures are not substantially affected if the assumption of data being normally distributed is not exactly satisfied. Further, the central limit theorem ensures that sample means would be normally distributed for large enough samples, regardless of the degree of skewness in the data. Sample sizes as small as 75–100 per group are usually sufficient to produce valid results, even from highly skewed distributions.41 Although log transformation of the CRP data did not totally normalize the distribution, limiting the analyses of CRP data to values under 10 mg/l reduces problems related to non-normality.
Measurement error also has the potential to affect our findings. Childhood CRP was analysed from serum samples stored for 25 years since 1980 at –20°C, as commercial high-sensitive CRP methods have been available for less than a decade.42 Protein levels may be reduced during long-term storage as a result of proteolysis and aggregation. Thus, a possibility exists that the levels of childhood CRP values analysed from stored samples may have been inaccurate and erroneously low. However, that would have mostly mattered if the level of deterioration of the samples differed by SEP. Additionally, although the long-term stability of high-sensitive CRP is unknown,43–45 a preliminary study of the stability of CRP frozen at –20°C indicated that it remained remarkably stable over a 5-year storage period.46
Selection bias might be present, given that 36% of the baseline participants were lost to follow-up. However, because participants included in the analyses were largely similar to those lost to follow-up, generalizability should not be substantially affected. Since no interaction between SEP and sex was observed our findings probably apply equally to both women and men. As the study was conducted among a sample of white participants, which represented the Finnish population in 1980, our results may not be generalizable to other groups. Nevertheless, our findings are in agreement with recent research examining a large sample of African-American and white US adults40 and thus generalizability could be higher than initially assumed.
Our findings on the distribution of the genetic polymorphisms by SEP in Finnish data may have limited generalizability to other populations. However, the selected CRP gene polymorphisms for this study are common genetic variants of CRP covering the CRP gene and have known functional effects (e.g. increasing or decreasing) over concentrations of plasma CRP or cardiovascular disease risk across the life course.31–33 Several studies have shown that variants in the CRP gene indeed are involved in the regulation of circulating levels of CRP both in childhood and adulthood,8,34,36,47 and in non-Finnish populations (i.e. British).47 Nevertheless, the identification of human genes is not yet completed (see International HapMap Project at http://www.hapmap.org/index.html.en) and we cannot exclude the possibility that other CRP polymorphisms differ by SEP.
In summary, evidence from a prospective population-based study suggests that SEP differences in CRP seen in adult life appear not to be determined at conception or to be the outcome of a trajectory starting early in life and tracking to adulthood. Rather, SEP gradients in CRP levels seem to become apparent only in adulthood, in our sample around the age of 24–39 years.
KEY MESSAGES
|
|
Appendix |
|---|
|
TopAbstractIntroductionParticipantsData analysisResultsDiscussionAppendixAcknowledgementsReferences |
|---|
|
|
Acknowledgements |
|---|
|
TopAbstractIntroductionParticipantsData analysisResultsDiscussionAppendixAcknowledgementsReferences |
|---|
The Cardiovascular Risk in Young Finns Study has been supported by the Academy of Finland (grants 77841 and 210283), the Social Insurance Institution of Finland, the Finnish Work Environment Foundation, Turku University Foundation, Juho Vainio Foundation, the Yrjö Jahnsson Foundation, the Finnish Foundation of Cardiovascular Research, the Finnish Cultural Foundation and Turku University Central Hospital Research Funds in Finland. M.K. was supported by the Academy of Finland (grants 105195 and 117604) and T.L. by the Emil Aaltonen Foundation. L.K-J. was supported by the Academy of Finland (grants 209514 and 209518).
Conflict of interest: None declared.
|
References |
|---|
|
TopAbstractIntroductionParticipantsData analysisResultsDiscussionAppendixAcknowledgementsReferences |
|---|
1 Rose G, Marmot MG. Social class and coronary heart disease. Br Heart J (1981) 45:13–19.
2 Marmot M, Shipley M, Brunner E, Hemingway H. Relative contribution of early life and adult socioeconomic factors to adult morbidity in the Whitehall II study. J Epidemiol Commun H (2001) 55:301–7.
3 Langenberg C, Shipley MJ, Batty GD, Marmot MG. Adult socioeconomic position and the association between height and coronary heart disease mortality: findings from 33 years of follow-up in the Whitehall Study. Am J Public Health (2005) 95:628–32.
4 Ross R. Atherosclerosis–an inflammatory disease. N Engl J Med (1999) 340:115–26.
5 Davey Smith G, Timpson N, Lawlor DA. C-reactive protein and cardiovascular disease risk: still an unknown quantity? Ann Intern Med (2006) 145:70–72.
6 Danesh J, Wheeler JG, Hirschfield GM, et al. C-reactive protein and other circulating markers of inflammation in the prediction of coronary heart disease. N Engl J Med (2004) 350:1387–97.
7 Lowe GD, Rumley A, McMahon AD, Ford I, O’Reilly DS, Packard CJ. Interleukin-6, fibrin D-dimer, and coagulation factors VII and XIIa in prediction of coronary heart disease. Arterioscler Thromb Vasc Biol (2004) 24:1529–34.
8 Lange LA, Carlson CS, Hindorff LA, et al. Association of polymorphisms in the CRP gene with circulating C-reactive protein levels and cardiovascular events. JAMA (2006) 296:2703–11.
9 Mendall MA, Patel P, Asante M, et al. Relation of serum cytokine concentrations to cardiovascular risk factors and coronary heart disease. Heart (1997) 78:273–77.
10 Woodward M, Rumley A, Tunstall-Pedoe H, Lowe GD. Associations of blood rheology and interleukin-6 with cardiovascular risk factors and prevalent cardiovascular disease. Br J Haematol (1999) 104:246–57.[CrossRef][Web of Science][Medline]
11 Hemingway H, Shipley M, Mullen MJ, et al. Social and psychosocial influences on inflammatory markers and vascular function in civil servants (the Whitehall II study). Am J Cardiol (2003) 92:984–87.[CrossRef][Web of Science][Medline]
12 Woodward M, Rumley A, Lowe GD, Tunstall-Pedoe H. C-reactive protein: associations with haematological variables, cardiovascular risk factors and prevalent cardiovascular disease. Br J Haematol (2003) 122:135–41.[CrossRef][Web of Science][Medline]
13 Jousilahti P, Salomaa V, Rasi V, Vahtera E, Palosuo T. Association of markers of systemic inflammation, C reactive protein, serum amyloid A, and fibrinogen, with socioeconomic status. J Epidemiol Commun H (2003) 57:730–33.
14 Lawlor DA, Smith GD, Rumley A, Lowe GD, Ebrahim S. Associations of fibrinogen and C-reactive protein with prevalent and incident coronary heart disease are attenuated by adjustment for confounding factors. British Women's Heart and Health Study. Thromb Haemost (2005) 93:955–63.[Web of Science][Medline]
15 Panagiotakos DB, Pitsavos C, Manios Y, Polychronopoulos E, Chrysohoou CA, Stefanadis C. Socio-economic status in relation to risk factors associated with cardiovascular disease, in healthy individuals from the ATTICA study. Eur J Cardiovasc Prev Rehabil (2005) 12:68–74.[CrossRef][Web of Science][Medline]
16 Loucks EB, Sullivan LM, Hayes LJ, et al. Association of educational level with inflammatory markers in the Framingham Offspring Study. Am J Epidemiol (2006) 163:622–28.
17 Koster A, Bosma H, Penninx BW, et al. Association of inflammatory markers with socioeconomic status. J Gerontol A Biol Sci Med Sci (2006) 61:284–90.
18 O’Reilly DS, Upton MN, Caslake MJ, et al. Plasma C reactive protein concentration indicates a direct relation between systemic inflammation and social deprivation. Heart (2006) 92:533–35.
19 Alley DE, Seeman TE, Ki Kim J, Karlamangla A, Hu P, Crimmins EM. Socioeconomic status and C-reactive protein levels in the US population: NHANES IV. Brain Behav Immun (2006) 20:498–504.[CrossRef][Web of Science][Medline]
20 Osler M, Petersen L, Prescott E, Teasdale TW, Sorensen TI. Genetic and environmental influences on the relation between parental social class and mortality. Int J Epidemiol (2006) 35:1272–77.
21 Power C, Matthews S. Origins of health inequalities in a national population sample. Lancet (1997) 350:1584–89.[CrossRef][Web of Science][Medline]
22 Kivimaki M, Smith GD, Juonala M, et al. Socioeconomic position in childhood and adult cardiovascular risk factors, vascular structure, and function: cardiovascular risk in young Finns study. Heart (2006) 92:474–80.
23 Brunner E, Shipley MJ, Blane D, Smith GD, Marmot MG. When does cardiovascular risk start? Past and present socioeconomic circumstances and risk factors in adulthood. J Epidemiol Commun H (1999) 53:757–64.[Abstract]
24 Cook DG, Mendall MA, Whincup PH, et al. C-reactive protein concentration in children: relationship to adiposity and other cardiovascular risk factors. Atherosclerosis (2000) 149:139–50.[CrossRef][Web of Science][Medline]
25 Thomas NE, Cooper SM, Williams SR, Baker JS, Davies B. Fibrinogen, homocyst(e)ine, and C-reactive protein concentrations relative to sex and socioeconomic status in British young people. Am J Hum Biol (2005) 17:809–13.[CrossRef][Web of Science][Medline]
26 McDade TW, Leonard WR, Burhop J, et al. Predictors of C-reactive protein in Tsimane' 2 to 15 year-olds in lowland Bolivia. Am J Phys Anthropol (2005) 128:906–13.[CrossRef][Web of Science][Medline]
27 Kivimaki M, Lawlor DA, Juonala M, et al. Lifecourse socioeconomic position, C-reactive protein, and carotid intima-media thickness in young adults: the cardiovascular risk in Young Finns Study. Arterioscler Thromb Vasc Biol (2005) 25:2197–202.
28 Porkka KV, Raitakari OT, Leino A, et al. Trends in serum lipid levels during 1980–1992 in children and young adults. The cardiovascular risk in Young Finns Study. Am J Epidemiol (1997) 146:64–77.
29 Raitakari OT, Juonala M, Kahonen M, et al. Cardiovascular risk factors in childhood and carotid artery intima-media thickness in adulthood: the cardiovascular risk in Young Finns Study. JAMA (2003) 290:2277–83.
30 Myers GL, Rifai N, Tracy RP, et al. CDC/AHA Workshop on markers of inflammation and cardiovascular disease: application to clinical and public health practice: report from the laboratory science discussion group. Circulation (2004) 110:e545–49.
31 Kushner I, Rzewnicki D, Samols D. What does minor elevation of C-reactive protein signify? Am J Med (2006) 119:166.e17–166.e28.
32 Chen J, Zhao J, Huang J, Su S, Qiang B, Gu D. –717A>G polymorphism of human C-reactive protein gene associated with coronary heart disease in ethnic Han Chinese: the Beijing atherosclerosis study. J Mol Med (2005) 83:72–78.[CrossRef][Web of Science][Medline]
33 Carlson CS, Aldred SF, Lee PK, et al. Polymorphisms within the C-reactive protein (CRP) promoter region are associated with plasma CRP levels. Am J Hum Genet (2005) 77:64–77.[CrossRef][Web of Science][Medline]
34 Kivimaki M, Lawlor DA, Eklund C, et al. Mendelian randomization suggests no causal association between C-reactive protein and carotid intima-media thickness in the young Finns study. Arterioscler Thromb Vasc Biol (2007) 27:978–79.
35 Kathiresan S, Larson MG, Vasan RS, et al. Contribution of clinical correlates and 13 C-reactive protein gene polymorphisms to interindividual variability in serum C-reactive protein level. Circulation (2006) 113:1415–23.
36 Kivimaki M, Lawlor DA, Smith GD, et al. Variants in the CRP gene as a measure of lifelong differences in average C-reactive protein levels: the cardiovascular risk in Young Finns Study, 1980, 2001. Am J Epidemiol (2007) 166:760–64.
37 Pulkki L, Kivimaki M, Elovainio M, Viikari J, Keltikangas-Jarvinen L. Contribution of socioeconomic status to the association between hostility and cardiovascular risk behaviors: a prospective cohort study. Am J Epidemiol (2003) 158:736–42.
38 Pulkki L, Kivimaki M, Keltikangas-Jarvinen L, Elovainio M, Leino M, Viikari J. Contribution of adolescent and early adult personality to the inverse association between education and cardiovascular risk behaviours: prospective population-based cohort study. Int J Epidemiol (2003) 32:968–75.
39 McDade TW, Hawkley LC, Cacioppo JT. Psychosocial and behavioral predictors of inflammation in middle-aged and older adults: the Chicago health, aging, and social relations study. Psychosom Med (2006) 68:376–81.
40 Pollitt RA, Kaufman JS, Rose KM, Diez-Roux AV, Zeng D, Heiss G. Early-life and adult socioeconomic status and inflammatory risk markers in adulthood. Eur J Epidemiol (2007) 22:55–66.[CrossRef][Web of Science][Medline]
41 Kingman A, Zion G. Some power considerations when deciding to use transformations. Stat Med (1994) 13:769–83.[Web of Science][Medline]
42 Rifai N, Tracy RP, Ridker PM. Clinical efficacy of an automated high-sensitivity C-reactive protein assay. Clin Chem (1999) 45:2136–41.
43 Wilkins J, Gallimore JR, Moore EG, Pepys MB. Rapid automated high sensitivity enzyme immunoassay of C-reactive protein. Clin Chem (1998) 44:1358–61.
44 Roberts WL. CDC/AHA workshop on markers of inflammation and cardiovascular disease: application to clinical and public health practice: laboratory tests available to assess inflammation–performance and standardization: a background paper. Circulation (2004) 110:e572–76.
45 Nilsson TK, Boman K, Jansson JH, et al. Comparison of soluble thrombomodulin, von Willebrand factor, tPA/PAI-1 complex, and high-sensitivity CRP concentrations in serum, EDTA plasma, citrated plasma, and acidified citrated plasma (Stabilyte) stored at –70 degrees C for 8-11 years. Thromb Res (2005) 116:249–54.[CrossRef][Web of Science][Medline]
46 Juonala M, Viikari JS, Ronnemaa T, Taittonen L, Marniemi J, Raitakari OT. Childhood C-reactive protein in predicting CRP and carotid intima-media thickness in adulthood: the cardiovascular risk in Young Finns Study. Arterioscler Thromb Vasc Biol (2006) 26:1883–88.
47 Timpson NJ, Lawlor DA, Harbord RM, et al. C-reactive protein and its role in metabolic syndrome: mendelian randomisation study. Lancet (2005) 366:1954–59.[CrossRef][Web of Science][Medline]
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  J. P Casas Commentary: Social class, C-reactive protein and coronary heart disease Int. J. Epidemiol., April 1, 2008; 37(2): 299 - 300. [Full Text] [PDF]
|
|
|
|
|
|
S. Ebrahim The riches of cohorts Int. J. Epidemiol., April 1, 2008; 37(2): 223 - 224. [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||