Skip Navigation


American Journal of Epidemiology Advance Access originally published online on May 4, 2006
American Journal of Epidemiology 2006 163(12):1112-1117; doi:10.1093/aje/kwj148
This Article
Right arrow Abstract Freely available
Right arrow FREE Full Text (PDF) Freely available
Right arrow All Versions of this Article:
163/12/1112    most recent
kwj148v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Search for citing articles in:
ISI Web of Science (1)
Right arrowRequest Permissions
Right arrow Disclaimer
Google Scholar
Right arrow Articles by Bager, P.
Right arrow Articles by Westergaard, T.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Bager, P.
Right arrow Articles by Westergaard, T.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

American Journal of Epidemiology Copyright © 2006 by the Johns Hopkins Bloomberg School of Public Health All rights reserved; printed in U.S.A.

Original Contribution

Sibship Characteristics and Risk of Multiple Sclerosis: A Nationwide Cohort Study in Denmark

Peter Bager1, Nete Munk Nielsen1, Kristine Bihrmann1, Morten Frisch1, Jan Wohlfart1, Nils Koch-Henriksen2,3, Mads Melbye1 and Tine Westergaard1

1 Department of Epidemiology Research, Danish Epidemiology Science Centre, Statens Serum Institut, Copenhagen, Denmark
2 Department of Neurology, Aarhus University Hospital in Aalborg, Aalborg, Denmark
3 National Institute of Public Health, Copenhagen, Denmark

Correspondence to Dr. Peter Bager, Department of Epidemiology Research, Statens Serum Institute, Artillerivej 5, DK-2300 Copenhagen, Denmark (e-mail: pbg{at}ssi.dk).

Received for publication April 5, 2005. Accepted for publication January 6, 2006.


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
It has been hypothesized that age at infection with a common microbial agent may be associated with the risk of multiple sclerosis (MS). The authors addressed this hypothesis by using number of older siblings and other sibship characteristics as an approximation of age at exposure to common infections. Data on family characteristics and vital status from the Danish Civil Registration System were used to establish a cohort of all Danes whose mothers had been born in Denmark since 1935. Persons diagnosed with MS during the period 1968–1998 were identified through linkage with the Danish Multiple Sclerosis Register. The cohort of 1.9 million Danes was followed for 28.1 million person-years; during that time, 1,036 persons developed MS. Overall, there was no association between number of older siblings, number of younger siblings, total number of siblings, age distance from the nearest younger sibling, or exposure to younger siblings under 2 years of age and risk of MS later in life. There was no association of MS risk with multiple birth (vs. singleton birth) or with the age of the mother or father at birth. These results do not lend support to the hypothesis that number of older siblings or any of the other sibship characteristics studied is associated with risk of MS.

birth order; infection; maternal age; multiple sclerosis; paternal age; risk factors; siblings; twins

Abbreviations: CI, confidence interval; MS, multiple sclerosis; RR, rate ratio


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
Multiple sclerosis (MS) is believed to be an immunologic disorder caused by both genetic and environmental factors, possibly including viral infections (1Go, 2Go). In particular, several epidemiologic observations lend support to the hypothesis that MS could result from an aberrant immune response, possibly triggered by an infection acquired late in childhood or during adolescence (3Go, 4Go). Accordingly, the association between risk of MS and age at incurring one of several suggested candidate infections has been studied (5Go, 6Go). However, these studies have been carried out in small populations and with the possibility that recall of age at infection decades later could have biased the results. This may be particularly true for reinfections. In addition, subclinical infection cannot be studied in this way.

Another approach taken to address the hypothesis has been to approximate exposure to infections using sibship characteristics. Accordingly, number of siblings is believed to be associated with the risk of exposure to common infections, and birth order is believed to be inversely associated with the age at which such infections occur (7Go–12Go). According to the proposed hypothesis, children with few siblings and/or of early birth orders would be more likely to develop MS. For allergic rhinitis and atopy, the existence of an inverse association with birth order has been proven by consistency in many studies, and its existence motivated the so-called hygiene hypothesis as an explanation for the allergy epidemic in affluent countries (13Go, 14Go). Fewer and smaller studies exist on MS and birth order; results have been very inconsistent, and several of the studies have suffered from severe methodological problems (6Go, 15Go–33Go). Thus, to investigate whether age at exposure to a common microbial agent is associated with risk of developing MS, we took advantage of the high quality of information in Danish national registers and established a nationwide cohort that was followed for development of MS and assessed for number of older siblings (i.e., birth order) and other relevant sibship characteristics.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 References
 
Data from the Civil Registration System were used to generate a complete sibship database for persons born to Danish women. Since April 1, 1968, all residents of Denmark have been recorded in the Civil Registration System and assigned a unique personal identification number. Individual information is kept under this identification number in all national registers, ensuring precise and secure linkage of person-identifiable information between registers. The Civil Registration System also includes person-identifiable information on date of birth, sex, place of birth, vital status, and, for most persons born since the beginning of the 1950s, information on parents and offspring (34Go). We established a population-based sibship database by extracting data on all women born in Denmark since 1935 and all of their offspring who were alive on April 1, 1968, or born between that date and December 31, 1988. The offspring constituted the study cohort.

Information about MS in cohort members and their parents was obtained through linkage with the Danish Multiple Sclerosis Register. The Danish Multiple Sclerosis Register was formally established in 1956, in continuation of a nationwide MS surveillance study that began in 1949. Since then, the register has collected clinical information on all MS patients in Denmark (35Go). It is the longest-running nationwide MS register in the world (36Go). Cases have been classified by only three neurologists since the register's inception. The cases fulfill the diagnostic criteria of Allison or Poser (including possible MS) (37Go–39Go), and the diagnoses are consistent over time. The register has been estimated to be more than 90 percent complete (36Go).

The possible impacts of sibship characteristics on MS risk, measured by incidence rate ratios, were investigated in a follow-up study using log-linear Poisson regression models (40Go). The studied sibship characteristics at age 10 years were: number of older siblings, number of younger siblings, total number of siblings, age distance from the nearest younger sibling (<2, 2–<6, or ≥6 years), and number of years exposed to younger siblings under 2 years of age (<1, 1–<3, 3–<5, or ≥5 years). We also studied whether being a member of a multiple birth versus being a singleton was associated with MS and whether the age of the mother or father at birth was associated with MS. Children born on the same day or an adjacent day as a sibling were considered members of a multiple birth.

Overall, the study cohort consisted of 1,903,625 persons who were followed for MS from their 10th birthday or April 1, 1968, whichever came last, until MS diagnosis, death, emigration, or December 31, 1998, whichever came first. The results were adjusted for the potential interaction between sex and calendar period and the potential interaction between sex and age using quadratic restricted splines, where quadratic functions were connected at 15, 20, 25, 30, and 35 years (41Go, 42Go). All analyses were also adjusted for parental MS (yes, no). Parents were considered to have MS if one or both had ever been diagnosed with MS. Additional adjustments were carried out for age of the mother at birth (<20, 20–24, 25–29, or ≥30 years), number of older siblings (0, 1, 2, or ≥3), and number of younger siblings (0, 1, 2, or ≥3).

Maximum likelihood estimation was performed using the GENMOD procedure in SAS (version 8.02; SAS Institute, Inc., Cary, North Carolina). Two-sided p values were based on likelihood ratio tests, and 95 percent confidence intervals were based on Wald's tests. Trend slopes were estimated by treating categorical variables of interest as quantitative variables. Trends for ages of the mother and father at birth were estimated using 1-year categories. Effect modification by year of birth (1950–1959, 1960–1969, or 1970 onward) and age was evaluated by including interaction terms in the model.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 References
 
Overall, 1,036 persons aged 10 years or more were diagnosed with MS during the 28.1 million person-years of follow-up. Table 1 shows the distribution of MS cases by gender, age, year of birth, and family history of MS.


View this table:
[in this window]
[in a new window]
  		TABLE 1. Characteristics of 1,036 multiple sclerosis patients aged 10 years or more who were born in Denmark in 1950 or later and whose cases were diagnosed during the period 1968–1998

 
Table 2 shows rate ratios for MS according to number of older siblings, number of younger siblings, total number of siblings, being a member of a multiple birth, and ages of the mother and father at birth. Overall, there was no significant association between the MS rate ratio and number of older siblings or total number of siblings. There was a tendency for the MS rate ratio to increase with decreasing number of younger siblings; however, the trend was not significant (p = 0.08). The trend estimate for the MS rate ratio for each of these exposures was not modified by year of birth. Neither was there an association with being a member of a multiple birth as compared with being a singleton or with the age of the mother or father at birth.


View this table:
[in this window]
[in a new window]
  		TABLE 2. Rate ratios for multiple sclerosis according to sibship characteristics in a cohort of 1.9 million persons, Denmark, 1968–1998*

 
For number of older siblings and total number of siblings, the effect on the MS rate ratio was the same for subjects under age 30 years and subjects aged 30 years or more. For number of younger siblings, the rate ratio increased with decreasing number of younger siblings among subjects below age 30 years (rate ratio (RR) for trend = 0.87, 95 percent confidence interval (CI): 0.79, 0.96) but not among subjects aged 30 years or more (RR for trend = 1.04, 95 percent CI: 0.92, 1.18). When the effect of younger siblings was stratified by year of birth, ages <25 and ≥25 years, ages <30 and ≥30 years, and year of birth and ages <30 and ≥30 years yielded the same results.

To conform the analyses of younger siblings with those of a recent study (23Go) (see Discussion), we also analyzed the rate ratio for MS according to cumulative years of having younger siblings under 2 years of age. Overall, there was no association; the trend estimate for the rate ratio was 0.98 (95 percent CI: 0.91, 1.06) after adjustment for sex x calendar period, sex x age, parental MS, age of the mother at birth, and number of older siblings. Stratifying by year of birth and age <30 years/≥30 years yielded the same result, although for births occurring after 1970, the trend estimate for MS diagnosed at ages below 30 years was 0.87 (95 percent CI: 0.71, 1.07), and no cases were aged 30 years or more. Furthermore, the rate ratio for MS was not associated with age distance to the nearest younger sibling (p = 0.44).

Table 3 shows rate ratios for MS according to combinations of number of older siblings and total number of siblings. Compared with only children, there was no evidence of an increased MS rate ratio with decreasing number of older siblings when the total number of subjects' siblings was one, two, three, or four or more. In fact, second-born children in families with two children had an increased MS rate ratio in comparison with only children (RR = 1.32, 95 percent CI: 1.01, 1.70). Overall, there was no effect of interaction between total number of siblings and number of older siblings on the rate ratio for MS (p = 0.70).


View this table:
[in this window]
[in a new window]
  		TABLE 3. Rate ratios* for multiple sclerosis according to combinations of number of older siblings and total number of siblings at age 10 years in a cohort of 1.9 million persons, Denmark, 1968–1998{dagger}

 
The results presented did not change materially when subjects with a diagnosis of possible MS (n = 131) were not considered MS cases in the analysis; neither did the results change materially without adjustment for sex.


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
References
 
The present population-based cohort study was based on detailed information on MS and family characteristics for a large nationwide cohort of Danes. The results do not support an increased risk of MS with decreasing number of older siblings as previously suggested (15Go, 31Go, 32Go), nor do they suggest an overall association with number of younger siblings, total number of siblings, age distance to the nearest younger sibling, years of exposure to younger siblings under 2 years of age, being a member of a multiple birth versus being a singleton, or age of the mother or father at birth. Selection bias, which may have hampered previous studies, was considered minimal here, because we used information from nationwide registries of high quality. Furthermore, we took variations in population family size over time into account by adjusting for a possible calendar effect on sibship characteristics.

The majority (76 percent) of the studied MS patients were born before the 1970s, the era when day-care attendance began to increase in Denmark. Among children aged ≤2 years, 16 percent attended day care in 1973, 41 percent in 1983, and 49 percent in 1992 (43Go). Therefore, the lack of support for the hypothesis that firstborn children tend to be infected at a late age and consequently are at increased risk of MS was not likely to be explained by many firstborns' attending day care, thereby being exposed earlier to infections. In fact, there was no association between the rate ratio for MS and number of siblings in any stratum of birth year (1950–1959, 1960–1969, and 1970 or later).

In contrast to our results, in a recent large case-control study of 4,443 Swedish MS patients, Montgomery et al. (15Go) reported an inverse association between MS risk and number of siblings, both older and younger, and a decreased risk of MS among twins. The Swedish findings also contrasted with the lack of association reported in most previous case-control studies for number of older siblings (6Go, 16Go–24Go) and total number of siblings (6Go, 16Go, 22Go, 33Go). Although the authors did not rule out the possibility that the associations they found, including a greater age distance to the nearest sibling among MS patients, could be explained by late exposure to infections, they were more inclined toward the interpretation that increased risk of MS could be associated with reduced fertility among parents of MS patients. To support this, they also reported that the age of the father was associated with risk of MS (15Go). We found no association with the age of the father. However, Montgomery et al.'s population was missing up to half of all deceased persons, and 25 percent of cases and 15 percent of controls were excluded because of incomplete information on siblings (15Go). The possibility that this could have affected their results cannot be excluded.

The analyses presented by Ahlgren and Andersen (30Go) from another Swedish study of 258 MS patients illustrated how serious bias could have been introduced into the earliest studies of MS and birth order because the birth order distributions of MS patients were compared with a theoretical distribution based on the erroneous assumption that the population family size remains stable through time (24Go–29Go, 31Go). Investigators in later studies avoided this bias by using a case-control design matching the data on time of birth (6Go, 16Go–24Go, 31Go–33Go), but only a few of the studies, based on relatively small and selected case materials, observed an association between low birth order and increased risk of MS (31Go–33Go). Among the larger of these case-control studies, Bager et al. (6Go) reported no association in a study of 455 MS patients, and in another study of 301 female MS patients, Hernan et al. (33Go) reported an increased risk of MS among firstborn siblings in large sibships (≥4), although the trend analysis was less convincing.

In a recent case-control study of 136 MS patients in Tasmania, Australia, Ponsonby et al. (23Go) reported risk of MS to be associated with a decreasing number of younger siblings but not older siblings. In particular analyses, the authors showed that patients were diagnosed at a young age less often if they had lived in the same house with younger siblings under 2 years of age during the first 6 years of life (23). Their focus on that exposure, and not exclusively the number of younger siblings, was based on their assumption that it is a specific marker of reinfections transmitted from younger siblings of very low age. We did not reproduce their result using comparable analyses of MS among two million Danes. We observed that patients were diagnosed at a young age less often when they had younger siblings, but this could not be attributed to the number of years exposed to younger siblings of very low age. In addition, being closer in age to the nearest younger sibling was not associated with fewer diagnoses of MS. When the findings are analyzed together, our results are not compatible with the Tasmania study or its basic hypothesis (23Go).

Finally, it has been hypothesized that children who are members of a multiple birth may tend to have increased exposure to infections early in life from close contact between multiple siblings (44Go). However, we found no association between being a member of a multiple birth and the rate ratio for MS. In a case-control study of 241 MS patients, Antonovsky et al. (22Go) reported that a significantly higher percentage of MS patients than of controls were born to mothers aged 40 years or more but not to mothers aged 30 years or more, although numbers were small. As in the larger Swedish study (15Go), we found no association between MS and the age of the mother.

In conclusion, these results do not lend support to the hypothesis that age at infection with a common microbial agent, as approximated by number of older siblings or any of the other sibship characteristics studied, is associated with risk of MS.


   ACKNOWLEDGMENTS
 
Conflict of interest: none declared.


   References
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 

  1. Kurtzke JF. Epidemiologic evidence for multiple sclerosis as an infection. Clin Microbiol Rev 1993;6:382–427.[Abstract/Free Full Text]
  2. Willer CJ, Dyment DA, Risch NJ, et al. Twin concordance and sibling recurrence rates in multiple sclerosis. Proc Natl Acad Sci U S A 2003;100:12877–82.[Abstract/Free Full Text]
  3. Poskanzer DC, Schapira K, Miller H. Multiple sclerosis and poliomyelitis. Lancet 1963;186:917–21.[CrossRef][Medline]
  4. Granieri E, Casetta I, Tola MR, et al. Multiple sclerosis: infectious hypothesis. Neurol Sci 2001;22:179–85.[CrossRef][ISI][Medline]
  5. Casetta I, Granieri E. Clinical infections and multiple sclerosis: contribution from analytical epidemiology. J Neurovirol 2000;6(suppl 2):S147–51.
  6. Bager P, Nielsen NM, Bihrmann K, et al. Childhood infections and risk of multiple sclerosis. Brain 2004;127:2491–7.[Abstract/Free Full Text]
  7. Taylor I, Knowelden J. Family size. In: Principles of epidemiology. London, United Kingdom: J & A Churchill Ltd, 1964:304–7.
  8. MacMahon B. Is acute lymphoblastic leukemia in children virus-related? Am J Epidemiol 1992;136:916–24.[Abstract/Free Full Text]
  9. Hammon W, Sather GE, Hollinger N. Preliminary report of epidemiological studies on poliomyelitis and streptococcal infections; Lansing neutralizing antibody and antistreptolysin O surveys of California cities, Texas, North Carolina, Mexico, Pacific Islands, and Japan. Am J Public Health 1950;40:293–306.[Free Full Text]
  10. Goodman KJ, Correa P. Transmission of Helicobacter pylori among siblings. Lancet 2000;355:358–62.[CrossRef][ISI][Medline]
  11. Valeur-Jensen AK, Pedersen CB, Westergaard T, et al. Risk factors for parvovirus B19 infection in pregnancy. JAMA 1999;281:1099–105.[Abstract/Free Full Text]
  12. Lanari M, Giovannini M, Giuffre L, et al. Prevalence of respiratory syncytial virus infection in Italian infants hospitalized for acute lower respiratory tract infections, and association between respiratory syncytial virus infection risk factors and disease severity. Pediatr Pulmonol 2002;33:458–65.[CrossRef][ISI][Medline]
  13. Strachan DP. Family size, infection and atopy: the first decade of the "hygiene hypothesis." Thorax 2000;55(suppl 1):S2–10.[CrossRef][Medline]
  14. Karmaus W, Botezan C. Does a higher number of siblings protect against the development of allergy and asthma? A review. J Epidemiol Community Health 2002;56:209–17.[Abstract/Free Full Text]
  15. Montgomery SM, Lambe M, Olsson T, et al. Parental age, family size, and risk of multiple sclerosis. Epidemiology 2004;15:717–23.[CrossRef][ISI][Medline]
  16. Gaudet JP, Hashimoto L, Sadovnick AD, et al. Is sporadic MS caused by an infection of adolescence and early adulthood? A case-control study of birth order position. Acta Neurol Scand 1995;91:19–21.[ISI][Medline]
  17. Koch-Henriksen N. An epidemiological study of multiple sclerosis. Familial aggregation, social determinants, and exogenic factors. Acta Neurol Scand Suppl 1989;124:1–123.[Medline]
  18. Matias-Guiu J, Ferri L, Falip R, et al. Birth order in multiple sclerosis: a population-based case-control study in Alcoi, Spain. Neuroepidemiology 1994;13:129–30.[ISI][Medline]
  19. Operskalski EA, Visscher BR, Malmgren RM, et al. A case-control study of multiple sclerosis. Neurology 1989;39:825–9.[Abstract/Free Full Text]
  20. Alter M, Cendrowski W. Multiple sclerosis and childhood infections. Neurology 1976;26:201–4.[Abstract/Free Full Text]
  21. Berr C, Puel J, Clanet M, et al. Risk factors in multiple sclerosis: a population-based case-control study in Hautes-Pyrenees, France. Acta Neurol Scand 1989;80:46–50.[ISI][Medline]
  22. Antonovsky A, Leibowitz U, Smith HA, et al. Epidemiologic study of multiple sclerosis in Israel. I. An overall review of methods and findings. Arch Neurol 1965;13:183–93.[ISI][Medline]
  23. Ponsonby AL, van der Mei I, Dwyer T, et al. Exposure to infant siblings during early life and risk of multiple sclerosis. JAMA 2005;293:463–9.[Abstract/Free Full Text]
  24. Visscher BR, Liu KS, Sullivan CB, et al. Birth order and multiple sclerosis. Acta Neurol Scand 1982;66:209–15.[ISI][Medline]
  25. Alperovitch A, Le Canuet P, Marteau R. Birth order and risk of multiple sclerosis: are they associated and how? Acta Neurol Scand 1981;63:136–8.[ISI][Medline]
  26. Cendrowski W. Birth order of multiple sclerotic subjects. Psychiatr Neurol Basel 1966;151:161–7.
  27. Cripps J, Rudd A, Ebers GC. Birth order and multiple sclerosis. Acta Neurol Scand 1982;66:342–6.[ISI][Medline]
  28. Sadovnick AD, Yee IM, Ebers GC. Multiple sclerosis and birth order: a longitudinal cohort study. Lancet Neurol 2005;4:611–17.[CrossRef][ISI][Medline]
  29. Pratt RTC. The familial occurrence of disseminated sclerosis. Ann Eugen 1951;16:45–59.
  30. Ahlgren C, Andersen O. No major birth order effect on the risk of multiple sclerosis. Neuroepidemiology 2005;24:38–41.[CrossRef][ISI][Medline]
  31. Zilber N, Kutai-Berman M, Kahana E, et al. Multiple sclerosis and birth order. Acta Neurol Scand 1988;78:313–17.[ISI][Medline]
  32. Isager H, Andersen E, Hyllested K. Risk of multiple sclerosis inversely associated with birth order position. Acta Neurol Scand 1980;61:393–6.[ISI][Medline]
  33. Hernan MA, Zang SM, Lipworth L, et al. Multiple sclerosis and age at infection with common viruses. Epidemiology 2001;12:301–6.[CrossRef][ISI][Medline]
  34. Westergaard T. Birth order and cancer risk. (PhD thesis). Copenhagen, Denmark: University of Copenhagen, 1997.
  35. Koch-Henriksen N. The Danish Multiple Sclerosis Registry: a 50-year follow-up. Mult Scler 1999;5:293–6.[Abstract/Free Full Text]
  36. Koch-Henriksen N, Rasmussen S, Stenager E, et al. The Danish Multiple Sclerosis Registry. History, data collection and validity. Dan Med Bull 2001;48:91–4.[ISI][Medline]
  37. Allison RS, Millar JH. Prevalence of disseminated sclerosis in Northern Ireland. Ulster Med J 1954;23:1–27.[Medline]
  38. Millar JH, Allison RS. Familial incidence of disseminated sclerosis in Northern Ireland. Ulster Med J 1954;23:29–92.[Medline]
  39. Poser CM, Paty DW, Scheinberg L, et al. New diagnostic criteria for multiple sclerosis: guidelines for research protocols. Ann Neurol 1983;13:227–31.[CrossRef][ISI][Medline]
  40. Breslow NE, Day NE, eds. Statistical methods in cancer research. Vol 2. The design and analysis of cohort studies. (IARC Scientific Publication no. 82). Lyon, France: International Agency for Research on Cancer, 1987.
  41. Wohlfahrt J, Mouridsen H, Andersen PK, et al. Reproductive risk factors for breast cancer by receptor status, histology, laterality and location. Int J Cancer 1999;81:49–55.[CrossRef][ISI][Medline]
  42. Stenager E, Moller R, Brønnum-Hansen H, et al. Multiple sclerosis: its change in prevalence in Denmark, 1950–1996, and its total prevalence in Danish counties in 1996. (In Danish). Ugeskr Laeger 2005;167:1500–2.[Medline]
  43. Westergaard T, Andersen PK, Pedersen JB, et al. Birth characteristics, sibling patterns, and acute leukemia risk in childhood: a population-based cohort study. J Natl Cancer Inst 1997;89:939–47.[Abstract/Free Full Text]
  44. McKeever TM, Lewis SA, Smith C, et al. Siblings, multiple births, and the incidence of allergic disease: a birth cohort study using the West Midlands general practice research database. Thorax 2001;56:758–62.[Abstract/Free Full Text]

Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?



This Article
Right arrow Abstract Freely available
Right arrow FREE Full Text (PDF) Freely available
Right arrow All Versions of this Article:
163/12/1112    most recent
kwj148v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Search for citing articles in:
ISI Web of Science (1)
Right arrowRequest Permissions
Right arrow Disclaimer
Google Scholar
Right arrow Articles by Bager, P.
Right arrow Articles by Westergaard, T.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Bager, P.
Right arrow Articles by Westergaard, T.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?