Skip to main content

Influence of low birth weight on C-reactive protein in asymptomatic younger adults: the bogalusa heart study



Both low birth weight, an indicator of intrauterine growth restriction, and low grade systemic inflammation depicted by high sensitivity C-reactive protein (hs-CRP) have emerged as independent predictors of cardiovascular (CV) disease and type 2 diabetes. However, information linking low birth weight and hs-CRP in a biracial (black/white) population is scant. We assessed a cohort of 776 black and white subjects (28% black, 43% male) aged 24-43 years (mean 36.1 years) enrolled in the Bogalusa Heart Study with regard to birth weight and gestational age data were retrieved from Louisiana State Public Health Office.


Black subjects had significantly lower birth weight than white subjects (3.145 kg vs 3.441 kg, p < 0.0001) and higher hs-CRP level (3.29 mg/L vs 2.57 mg/L, p = 0.011). After adjusting for sex, age, body mass index (BMI), smoking status and race (for total sample), the hs-CRP level decreased across quartiles of increasing birth weight in white subjects (p = 0.001) and the combined sample (p = 0.002). Adjusting for sex, age, BMI, smoking status and race for the total sample in a multivariate regression model, low birth weight was retained as an independent predictor variable for higher hs-CRP levels in white subjects (p = 0.004) and the total sample (p = 0.007). Conversely, the area under the receiver operative curve (c statistic) analysis adjusted for race, sex, age, smoking status and BMI yielded a value of 0.777 with regard to the discriminating value of hs-CRP for predicting low birth weight.


The deleterious effect of low birth weight on systemic inflammation depicted by the hs-CRP levels in asymptomatic younger adults may potentially link fetal growth retardation, CV disease and diabetes, with important health implications.


The growth of an undernourished fetus results in adaptive fetal programming or metabolic imprinting, with permanent changes in structure, metabolism and physiology of fetal organs and related pathophysiologic consequences in later life [1, 2]. Studies worldwide, regardless of socio-economic background, have linked low birth weight to cardiometabolic risk factors, related cardiovascular (CV) disease, and type 2 diabetes [3, 4]. Recently, we reported the adverse relationship of low birth weight to white blood cell count and pulsatile arterial function [5, 6].

Inflammation plays an important role in the pathogenesis of atherosclerosis [79]. Risk factors, e.g. cigarette smoking, hypertension, dyslipidemia and hyperglycemia promote inflammation, are well established. Biomarkers, including as oxidized low-density lipoproteins, interleukin-6, intercellular adhesion molecule-1 and high sensitivity C-reactive protein (hs-CRP, reflect the ongoing inflammatory process [8]. Of these, hs-CRP - an acute-phase reactant secreted by the liver - has emerged as an independent predictor of CV disease and type 2 diabetes [813]. In terms of birth weight, a few studies have demonstrated an inverse association between birth weight and hs-CRP in children and adults [1416]. Consequently, the American Heart Association and Center for Disease Control recommended guidelines for the incorporation of hs-CRP into its CV disease risk stratification [8]. However, population-based data in this regard are scant. The present study examines this aspect in younger adults enrolled in the Bogalusa Heart Study, a biracial (35% black/65% white) community-based investigation of the natural history of CV disease

Materials and methods

Study Population

The study sample was derived from a cohort of 1203 subjects aged 23 to 43 examined as a part of a longitudinal follow-up survey. Of these, information on 908 singletons with hs-CRP measurement, birth weight, gestational age and body mass index (BMI) data were available. The exclusion of 132 singletons born premature (<37 weeks of gestation) and/or had conditions (with or without medication) of diabetes, hypertension and dyslipidemia left 776 eligible participants (28% black, 43% male, mean age 36.1 years). Birth weight and gestational age data were retrieved from Louisiana State Public Health Office. Tulane University Medical Center Institutional Review Board approved the study, and informed consent was obtained from all participants.


Standardized techniques and protocols were used by trained examiners. Height and weight were measured twice and the mean values were used to calculate BMI as a measure of adiposity. Information on smoking status was obtained by questionnaires. Those who had smoked at least one cigarette per week during the past one year or more were identified as current smokers, and the remainder as non-smokers. Plasma high sensitivity hs-CRP levels were measured by latex particle-enhanced immunoturbidemetric assay on a Hitachi 902 Automatic Analyzer (Roche Diagnostics, Indianapolis, IN, USA). The reproducibility of hs-CRP measurement checked with 10% of randomly assigned pairs of blind duplicate analysis, which gave an intraclass correlation coefficient of 0.99.

Statistical Methods

Statistical analyses were done with SAS software, version 9.1 (SAS, Carey, NC). As the hs-CRP level was not normally distributed, log transformation was used to approach normality. Analyses were performed where appropriate on transformed data. Analysis of variance for race difference in mean values of continuous variables and chi-square test for categorical variables were used. Because of a strong association between gestational age and birth weight, the latter was adjusted by regression analysis models to the mean values of the former in each race-sex group. For categorical analysis, quartiles of gestational age-adjusted birth weight were defined by using cut-off points in race-sex groups. Covariates adjusted mean values of hs-CRP were calculated by general linear models and used for analysis of birth weight by quartiles. Multiple regression analysis was used to determine the independent association of birth weight with hs-CRP in relation to the measured covariates. Two steps were followed in the regression model: the logarithm of hs-CRP was used in both cases as a dependent variable to determine the association between birth weight and hs-CRP. Model 1 was adjusted for age, sex, smoking and race (for the total sample) and the model 2 was adjusted for the above variables along with the potential confounding variable, BMI. In addition, a multivariate c-statistic model was used to determine the ability of hs-CRP to predict low birth weight (defined as <2500 gm). The area under the receiver-operating characteristic curve (c-statistic) was evaluated after adjusting for the covariates race, sex, age, smoking status and BMI. C-statistic of >0.5 indicated increased predictive ability.


Table 1 shows the mean values of hs-CRP, birth weight, and other study variables of younger adults by race. Black subjects had significantly lower gestational age and birth weight, but higher BMI and hs-CRP levels, than white subjects.

Table 1 Birth Weight, hs-CRP and other study variables of young adults by race

Figure 1 illustrates the relation of covariates-adjusted mean levels of hs-CRP to race- and sex-specific quartiles of gestational age-adjusted birth weight. The covariates included race (for the total sample), sex, age, BMI and smoking status. The hs-CRP level significantly decreased with increasing quartiles of birth weight among white subjects (p = 0.001) and the total sample (p = 0.002). Black subjects showed no such significant trend.

Figure 1

Covariates-adjusted mean values of hs-CRP by race and sex-specific quartiles of gestational age-adjusted birth weight: The Bogalusa Heart Study. Quartile I represents the lowest birth weight, and quartile IV represents the highest birth weight. Covariates included race (for the total sample), sex, age, body mass index and smoking status.

Table 2 presents the multivariate linear regression analysis of hs-CRP on gestational age-adjusted birth weight and other covariates in white subjects, black subjects and the total sample. Birth weight was independently and inversely associated with hs-CRP in white subjects in models without or with BMI as a covariate. In the total sample, such independent inverse association was noted only in model 2 that included BMI as a covariate. Also, sex (females > males), BMI (positive association), and smoking (positive association) were independently correlated with hs-CRP in white subjects and the total sample in model 2.

Table 2 Predictors of hs-CRP in young adults by race.

Figure 2 shows the discriminative value of hs-CRP for associating with low birth weight, after adjusting for race, sex, age, smoking status and BMI. The c-value for hs-CRP was 0.777.

Figure 2

The area under the receiver-operating curve of hs-CRP for predicting low birth weight, adjusted for race, sex, age, smoking status and body mass index. The c-statistic was 0.777.


This community-based study demonstrates an inverse and independent association between birth weight and hs-CRP, a widely used biomarker of systemic inflammation. In addition, female sex, BMI and smoking were independent adverse correlates of hs-CRP. It is noteworthy that these findings support the emerging concept of intrauterine imprinting and its pathophysiologic consequences later in life by linking low birth weight to excess hs-CRP [1, 2].

Although previous study in children has failed to find significant association between birth weight and hs-CRP [16], our epidemiologic study is consistent with the MIDSPAN family study and Northern Finland 1966 birth cohort study in adults [14, 15]. However, this inverse relationship was not observed in black subjects in our analysis. Of note, black subjects had significantly lower birth weights and related higher hs-CRP levels than white subjects [17, 18].

Although observational studies like this cannot address the issue of causality, several putative mechanisms might link low birth weight to underlying perturbation in inflammatory pathways in utero. Undernutrition in utero causes permanent impairment in growth, structure, and function of muscle [19, 20], fat [21, 22], liver [23] and renal nephrons [9, 24] inter alia due to adaptive programming, resulting in cardiometabolic syndrome and related disorders in later life [3, 25]. Interestingly, in utero muscle growth is retarded in low-birth weight babies [25]; and since there is little muscle cell replication after birth [26], these individuals will develop a disproportionately high fat mass and related state of chronic low-grade inflammation induced by adipose tissue cells including monocytes in a nutritionally-rich environment of postnatal life [25, 27]. Acute-phase reactants secreted by the liver, including hs-CRP, are upregulated by interleukin-6, a proinflammatory cytokine synthesized by adipose tissue and cleared mainly by the kidneys. Hence, adaptive programming of any of these tissues may result in heightened inflammatory states later in life. Of note, Barker et al. [28] demonstrated an inverse relationship between birth weight and acute-phase reactant fibrinogen in adults. Furthermore, studies including our own have shown an inverse relationship between birth weight and the number of circulating leukocytes [5, 29], the cellular effectors of inflammation. However, a caveat relating to causality, is that the observed elevation in hs-CRP levels among low birth weight adults may be a reverse causation phenomenon secondary to underlying excess atherosclerosis [30, 31].

As in previous studies [18, 32], obesity measured as BMI has been identified as an independent correlate of hs-CRP in our cohort. As discussed above, this is consistent with the pathophysiological role of adipose tissue in regulating inflammation. Furthermore, sex, but not race, was retained as an independent correlate of hs-CRP in our subjects. The excess in hs-CRP in females, also noted in previous study [18], may be due to an estrogen effect [33]. Based on exogenous estrogen administration studies in women, this hormone has been implicated in the transcriptional control, clearance, or cytokine regulation of several acute-phase reactants produced by the liver, including hs-CRP [34], but the role of endogenous estrogen in this regard is unknown. The current observations on white and total subjects also support the known adverse influence of smoking behavior on hs-CRP levels [35]. The lack of adverse effect of smoking among black subjects may be due to differences in intensity and duration of smoking.

In conclusion, low birth weight for gestational age is characterized by increased hs-CRP levels. In conjunction with earlier studies, these findings support the view that low birth weight, albeit a crude surrogate indicator of adaptive fetal programming, is a potential early risk factor for the emergence of disorders related to the activation of inflammatory pathways. As stated by Barker [1], primary prevention lies in protecting fetal development.



high sensitivity C-reactive protein


body mass index.


  1. 1.

    Barker DJ: Fetal Origins of Cardiovascular and Lung Disease. 2001, New York, NY: Marcel Dekker, Inc, 97-197.

    Google Scholar 

  2. 2.

    Waterland RA, Garza C: Potential mechanisms of metabolic imprinting that lead to chronic disease. Am J Clin Nutr. 1999, 69: 179-197.

    PubMed  CAS  Google Scholar 

  3. 3.

    Barker DJ, Hales CN, Fall CH, Osmond C, Phipps K, Clark PM: Type 2 (non-insulin-dependent) diabetes mellitus, hypertension and hyperlipidaemia(syndrome X): relation to reduced fetal growth. Diabetologia. 1993, 36: 62-67. 10.1007/BF00399095.

    PubMed  CAS  Article  Google Scholar 

  4. 4.

    Leon DA, Lithell HO, Vâgerö D, Koupilová I, Mohsen R, Berglund L, Lithell UB, McKeigue PM: Reduced fetal growth rate and increased risk of death from ischaemic heart disease: cohort study of 15 000 Swedish men and women born 1915-29. BMJ. 1998, 317: 241-245.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  5. 5.

    Chen W, Srinivasan SR, Berenson GS: Influence of birth weight on white blood cell count in biracial (black-white) children, adolescents, and young adults: the Bogalusa Heart Study. Am J Epidemiol. 2009, 169: 214-218. 10.1093/aje/kwn341.

    PubMed  PubMed Central  Article  Google Scholar 

  6. 6.

    Bhuiyan AR, Chen W, Srinivasan SR, Azevedo MJ, Berenson GS: Relationship of low birth weight to pulsatile arterial function in asymptomatic younger adults: the Bogalusa Heart Study. Am J Hypertens. 2010, 23: 168-173. 10.1038/ajh.2009.218.

    PubMed  Article  Google Scholar 

  7. 7.

    Ross R: Atherosclerosis: an inflammatory disease. N Engl J Med. 1999, 340: 115-125. 10.1056/NEJM199901143400207.

    PubMed  CAS  Article  Google Scholar 

  8. 8.

    Pearson TA, Mensah GA, Alexander RW: Markers of inflammation and cardiovascular disease. Application to clinical and public health practice: a statement for healthcare professionals from the Centers for Disease Control and Prevention and the American Heart Association. Circulation. 2003, 107: 499-511. 10.1161/01.CIR.0000052939.59093.45.

    PubMed  Article  Google Scholar 

  9. 9.

    Grundy SM: Inflammation, hypertension, and the metabolic syndrome. JAMA. 2003, 290: 3000-3002. 10.1001/jama.290.22.3000.

    PubMed  CAS  Article  Google Scholar 

  10. 10.

    Rawson ES, Freedson PS, Osganian SK, Matthews CE, Reed G, Ockene IS: Body mass index, but not physical activity, is associated with C-reactive protein. Med Sci Sports Exerc. 2003, 35: 1160-1166. 10.1249/01.MSS.0000074565.79230.AB.

    PubMed  CAS  Article  Google Scholar 

  11. 11.

    Wong ND, Pio J, Valencia R, Thakal G: Distribution of C-reactive protein and its relation to risk factors and coronary heart disease risk estimation in the National Health and Nutrition Examination Survey (NHANES) III. Prev Cardiol. 2001, 4: 109-114. 10.1111/j.1520-037X.2001.00570.x.

    PubMed  Article  Google Scholar 

  12. 12.

    Freeman DJ, Norrie J, Caslake MJ, Gaw A, Ford I, Lowe GD, O'Reilly DS, Packard CJ, Sattar N: C-reactive protein is an independent predictor of risk for the development of diabetes in the West of Scotland Coronary Prevention Study. Diabetes. 2002, 51: 1596-1600. 10.2337/diabetes.51.5.1596.

    PubMed  CAS  Article  Google Scholar 

  13. 13.

    Pradhan AD, Manson JE, Rifai N, Buring JE, Ridker PM: C-reactive protein, interleukin 6, and risk of developing type 2 diabetes mellitus. JAMA. 2001, 286: 327-334. 10.1001/jama.286.3.327.

    PubMed  CAS  Article  Google Scholar 

  14. 14.

    Sattar N, McConnachie A, O'Reilly D, Upton MN, Greer IA, Davey Smith G, Watt G: Inverse association between birth weight and C-reactive protein concentrations in the MIDSPAN Family Study. Arterioscler Thromb Vasc Biol. 2004, 24: 583-587. 10.1161/01.ATV.0000118277.41584.63.

    PubMed  CAS  Article  Google Scholar 

  15. 15.

    Tzoulaki I, Jarvelin MR, Hartikainen AL, Leinonen M, Pouta A, Paldanius M, Ruokonen A, Canoy D, Sovio U, Saikku P, Elliott P: Size at birth, weight gain over the life course, and low-grade inflammation in young adulthood: northern Finland 1966 Birth Cohort study. Eur Heart J. 2008, 29: 1049-56. 10.1093/eurheartj/ehn105.

    PubMed  Article  Google Scholar 

  16. 16.

    Gillum RF: Association of serum C-reactive protein and indices of body fat distribution and overweight in Mexican American children. J Natl Med Assoc. 2003, 95: 545-552.

    PubMed  CAS  PubMed Central  Google Scholar 

  17. 17.

    Frerichs RR, Srinivasan SR, Webber LS, Rieth MC, Berenson GS: Serum lipids and lipoproteins at birth in a biracial population: the Bogalusa heart study. Pediatr Res. 1978, 12: 858-863. 10.1203/00006450-197808000-00011.

    PubMed  CAS  Article  Google Scholar 

  18. 18.

    Patel DA, Srinivasan SR, Xu JH, Li S, Chen W, Berenson GS: Distribution and metabolic syndrome correlates of plasma C-reactive protein in biracial (black-white) younger adults: the Bogalusa Heart Study. Metabolism. 2006, 55: 699-705. 10.1016/j.metabol.2005.07.015.

    PubMed  CAS  Article  Google Scholar 

  19. 19.

    Phillips DI: Insulin resistance as a programmed response to fetal undernutrition. Diabetologia. 1996, 39: 1119-22. 10.1007/BF00400663.

    PubMed  CAS  Article  Google Scholar 

  20. 20.

    Taylor DJ, Thompson CH, Kemp GJ, Barnes PR, Sanderson AL, Radda GK, Phillips DI: A relationship between impaired fetal growth and reduced muscle glycolysis revealed by 31P magnetic resonance spectroscopy. Diabetologia. 1995, 38: 1205-1212. 10.1007/BF00422370.

    PubMed  CAS  Article  Google Scholar 

  21. 21.

    Lapillonne A, Braillon P, Claris O, Chatelain PG, Delmas PD, Salle BL: Body composition in appropriate and in small for gestational age infants. Acta Paediatr. 1997, 86: 196-200. 10.1111/j.1651-2227.1997.tb08868.x.

    PubMed  CAS  Article  Google Scholar 

  22. 22.

    Jaquet D, Gaboriau A, Czernichow P, Levy-Marchal C: Insulin resistance early in adulthood in subjects born with intrauterine growth retardation. J Clin Endocrinol Metab. 2000, 85: 1401-1406. 10.1210/jc.85.4.1401.

    PubMed  CAS  Google Scholar 

  23. 23.

    Barker DJ, Martyn CN, Osmond C, Wield GA: Abnormal liver growth in utero and death from coronary heart disease. BMJ. 1995, 310: 703-704.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  24. 24.

    Hinchliffe SA, Lynch MR, Sargent PH, Howard CV, Van Velzen D: The effect of intrauterine growth retardation on the development of renal nephrons. Br J Obstet Gynaecol. 1992, 99: 296-301. 10.1111/j.1471-0528.1992.tb13726.x.

    PubMed  CAS  Article  Google Scholar 

  25. 25.

    Eriksson JG: Growth and coronary heart disease in adult life. CVR & R. 2002, 23: 557-560.

    Google Scholar 

  26. 26.

    Widdowson EM, Crabb DE, Milner RD: Cellular Development of Some Human Organs Before Birth. Arch Dis Child. 1972, 4 (7): 652-655. 10.1136/adc.47.254.652.

    Article  Google Scholar 

  27. 27.

    Rajala MW, Scherer PE: Minireview: The adipocyte--at the crossroads of energy homeostasis, inflammation, and atherosclerosis. Endocrinology. 2003, 144: 3765-3773. 10.1210/en.2003-0580.

    PubMed  CAS  Article  Google Scholar 

  28. 28.

    Barker DJ, Meade TW, Fall CH, Lee A, Osmond C, Phipps K, Stirling Y: Relation of fetal and infant growth to plasma fibrinogen and factor VII concentrations in adult life. BMJ. 1992, 304: 148-152. 10.1136/bmj.304.6820.148.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  29. 29.

    Canoy D, Pouta A, Ruokonen A, Hartikainen AL, Saikku P, Järvelin MR: Weight at birth and infancy in relation to adult leukocyte count: a population-based study of 5619 men and women followed from the fetal period to adulthood. J Clin Endocrinol Metab. 2009, 94: 1916-1922. 10.1210/jc.2008-2545.

    PubMed  CAS  Article  Google Scholar 

  30. 30.

    Schunkert H, Samani NJ: Elevated C-reactive protein in atherosclerosis--chicken or egg?. N Engl J Med. 2008, 359: 1953-1955. 10.1056/NEJMe0807235.

    PubMed  CAS  Article  Google Scholar 

  31. 31.

    Shah SH, de Lemos JA: Biomarkers and cardiovascular disease: determining causality and quantifying contribution to risk assessment. JAMA. 2009, 302: 92-93. 10.1001/jama.2009.949.

    PubMed  CAS  Article  Google Scholar 

  32. 32.

    Tracy RP: Is visceral adiposity the "enemy within"?. Arterioscler Thromb Vasc Biol. 2001, 21: 881-883.

    PubMed  CAS  Article  Google Scholar 

  33. 33.

    Rifai N, Ridker PM: Population distributions of C-reactive protein in apparently healthy men and women in the United States: implication for clinical interpretation. Clin Chem. 2003, 49: 666-669. 10.1373/49.4.666.

    PubMed  CAS  Article  Google Scholar 

  34. 34.

    Ridker PM, Hennekens CH, Rifai N, Buring JE, Manson JE: Hormone replacement therapy and increased plasma concentration of C-reactive protein. Circulation. 1999, 100: 713-716.

    PubMed  CAS  Article  Google Scholar 

  35. 35.

    Bazzano LA, He J, Muntner P, Vupputuri S, Whelton PK: Relationship between cigarette smoking and novel risk factors for cardiovascular disease in the United States. Ann Intern Med. 2003, 138: 891-897.

    PubMed  Article  Google Scholar 

Download references


Supported by grants 546145G1 from Tulane University, 0855082E from the American Heart Association, AG-16592 from the National Institute on Aging, HL-38844 from the National Heart, Lung and Blood Institute.

The authors have no conflict of interest.

The Bogalusa Heart Study is a joint effort of many individuals whose cooperation is gratefully acknowledged. We are especially grateful to the study participants.

Author information



Corresponding author

Correspondence to Gerald S Berenson.

Additional information

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

ARB participated in study design, data analysis and manuscript preparation. SRB, WC and GSB contributed to study concept and design, data collection, acquisition of funding and manuscript preparation. MJA involved in manuscript preparation. All authors listed have made substantial contributions on this article

Authors’ original submitted files for images

Below are the links to the authors’ original submitted files for images.

Authors’ original file for figure 1

Authors’ original file for figure 2

Rights and permissions

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, providedthe original work is properly cited.

Reprints and Permissions

About this article

Cite this article

Bhuiyan, A.R., Srinivasan, S.R., Chen, W. et al. Influence of low birth weight on C-reactive protein in asymptomatic younger adults: the bogalusa heart study. BMC Res Notes 4, 71 (2011).

Download citation


  • Body Mass Index
  • Birth Weight
  • White Subject
  • Black Subject
  • Bogalusa Heart Study