Brain Advance Access originally published online on September 15, 2004
Brain 2004 127(11):2491-2497; doi:10.1093/brain/awh283
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Brain Vol. 127 No. 11 © Guarantors of Brain 2004; all rights reserved
Childhood infections and risk of multiple sclerosis
1 Department of Epidemiology Research, Danish Epidemiology Science Centre, Statens Serum Institut, 2 The Danish Multiple Sclerosis Register and 3 National Institute of Public Health, Copenhagen, Denmark
Correspondence to: Peter Bager, Department of Epidemiology Research, Danish Epidemiology Science Centre, Statens Serum Institut, 5 Artillerivej, DK-2300 Copenhagen S, Denmark. E-mail: pbg{at}ssi.dk
Received March 18, 2004. Revised June 14, 2004. Accepted June 27, 2004.
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Summary |
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Multiple sclerosis has been hypothesized to be the result from an aberrant immune response possibly triggered by delayed exposure to a common childhood infection. Because the vast majority of previous studies testing this hypothesis have been based on a history of childhood infections recalled years to decades later in adulthood, we investigated whether age at six common childhood infections was associated with risk of multiple sclerosis, using information recalled in the childhood of a historical cohort of school children in Denmark. Cases included all individuals with multiple sclerosis in the country born between 1940 and 1975, who had attended school in the capital, Copenhagen. Controls were age- and sex-matched peers. School health records were obtained for all subjects. The records contained information on measles, pertussis, scarlet fever, birth order, sibship size, social class of the father, school years, and name of school and attended school classes for children born since 1940 (ncases = 455, ncontrols = 1801). For children born since 1950, the records also contained information on rubella, varicella and mumps (ncases = 182, ncontrols = 690). Neither age at infection with measles, rubella, varicella, mumps, pertussis and scarlet fever (upper age limit, 14 years) nor the cumulative number of these infections between the ages of 10 and 14 years was associated with the risk of multiple sclerosis. In addition, the risk of multiple sclerosis was not associated with birth order or social class. No clustering of multiple sclerosis in school classes was observed. Our findings suggest that measles, rubella, mumps, varicella, pertussis and scarlet fever, even if acquired late in childhood, are not associated with increased risk of multiple sclerosis later in life.
Key Words: multiple sclerosis; infection; social class; birth order; cluster analysis
Abbreviations: CI = confidence interval; OR = odds ratio
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Introduction |
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Multiple sclerosis is today one of the most common neurological disorders among young adults. The hypothesis that multiple sclerosis is caused by a microorganism dates back to 1884, shortly after the first scientific description of the disease, and was based on the observation that symptoms of infection coincided with acute episodes of multiple sclerosis (Marie, 1884
). Despite many years of research, the aetiology of multiple sclerosis remains unknown. It is now believed that multiple sclerosis is an immune-mediated disorder due to genetic and environmental factors, possibly including viral infections (Kurtzke, 1993; Willer et al., 2003).
The importance of environmental factors in the pathogenesis of multiple sclerosis is emphasized by studies showing that more than 80% of multiple sclerosis patients do not have affected relatives, and that around 75% of twins with an affected identical twin do not develop multiple sclerosis (Sadovnick and Macleod, 1981; Ebers et al., 1986; Willer et al., 2003). Furthermore, the world appears to be geographically divided into high-risk areas of multiple sclerosis to the north and south and low-risk areas towards the equator, a division which might reflect the influence of climatic, sanitary or socioeconomic factors in interaction with an infectious agent (Hammond et al., 1988; Lauer, 1994; Hammond et al., 1996; Kurtzke, 1993; Kurtzke and Page, 1997).
The hypothesis that multiple sclerosis could be the result from an aberrant immune response possibly triggered by delayed exposure to a common childhood infection (Poskanzer et al., 1963) is primarily based on indirect evidence from migration studies (Alter et al., 1962). Thus, the risk of multiple sclerosis has been reported to change with migration before but not after the age of 15–20 years between regions with differing occurances of multiple sclerosis (Dean and Kurtzke, 1971; Detels et al., 1978). Other indirect evidence favouring the hypothesis comes from ecological studies according to which positive antibody titres to a variety of viral diseases are more frequent early in childhood in areas where multiple sclerosis is rare compared with areas where multiple sclerosis is common (Alter et al., 1987). Finally, some studies have reported a higher risk of multiple sclerosis in persons of early birth order (Isager et al., 1980; Zilber et al., 1988; Hernan et al., 2001) and high social class (Miller et al., 1960; Beebe et al., 1967; Russell, 1971; Phadke and Downie, 1987; Gonzalez and Sotelo, 1995; Zilber and Kahana, 1996; Kurtzke and Page, 1997). Since children of early birth order and of families of high social class tend to acquire common infections at a later age in childhood (Hammon et al., 1950; Mucci et al., 2004), these findings are also compatible with the hypothesis of a link between late age at childhood infection and increased risk of multiple sclerosis (Poskanzer et al., 1963; Granieri et al., 2001).
Several studies have related the risk of multiple sclerosis to age at childhood infections such as measles, rubella, varicella, mumps, pertussis and scarlet fever (Panelius et al., 1973; Alter and Cendrowski, 1976; Poskanzer et al., 1980a; Andersen et al., 1981; Haile et al., 1982; Sullivan et al., 1984; Compston et al., 1986; Italian Multiple Sclerosis Study Group, 1989; Hays, 1992; Gronning et al., 1993; Casetta et al., 1994; Bansil et al., 1997; Bachmann and Kesselring, 1998; Hernan et al., 2001; Tarrats et al., 2002; Haahr et al., 2004). However, results have been inconclusive and the possible influence of bias has been emphasized (Granieri and Casetta, 1997; Casetta and Granieri, 2000; Marrie and Wolfson, 2001). Nearly all of these investigations have been hospital-based and/or based on retrospective exposure information collected in adulthood. Such methods may create bias, e.g. because it is difficult to recall exact age at infections in childhood decades later in life. Moreover, small sample size has led to low statistical power in some studies.
We took advantage of a unique collection of school health records of children with information on exposures recorded in childhood in a uniform manner and prior to multiple sclerosis onset, to study whether age at common childhood infections, birth order, and social class are factors associated with risk of multiple sclerosis. In addition, we investigated whether multiple sclerosis clustered among persons who had been classmates in childhood.
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Material and methods |
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The investigation is based on a unique historical archive containing school health records for children who attended primary schools in the capital of Denmark, Copenhagen. The children who later developed multiple sclerosis were identified in the Danish Multiple Sclerosis Register. The identification of cases and controls, described below, was made possible by the unique personal identification numbers assigned to all Danish citizens since April 1, 1968, by the Danish Civil Registration System (Malig, 1996
), which also contains updated information on vital status, residence, present and historical names, and date of birth.
Register of school health records of Copenhagen
The register of school health records is based on person-identifiable information manually computerized from the records of 325 218 children born during the period 1930 to 1975. A total of 286 533 children (88%) have been identified in the Civil Registration System with a personal identification number using information on date of birth and name of child recorded on the school health records (Ahlgren M, Wohlfahrt J, Sørensen TIA, Melbye M, unpublished observations).
Danish Multiple Sclerosis Register
The Danish Multiple Sclerosis Register was formally established in 1956, in continuation of a nationwide surveillance study in 1949. The register has since collected information on multiple sclerosis patients from all Danish departments of neurology, practising neurologists, multiple sclerosis rehabilitation centres, departments of neuropathology, death certificates, and since 1977 the National Hospital Discharge Register (Koch-Henriksen, 1999). All cases are evaluated and classified by a neurologist. Cases with onset before 1994 were evaluated using the diagnostic criteria of Allison (Allison and Millar, 1954; Millar and Allison, 1954), whereas cases with onset after 1993 are evaluated employing the Poser criteria (Poser et al., 1983). Only cases fulfilling the diagnostic criteria of Allison or Poser (including possible multiple sclerosis) are considered as multiple sclerosis cases. The completeness of the register is estimated to be more than 90% and the diagnostic validity for autopsy cases classified as definite multiple sclerosis in the register to be 94% (Koch-Henriksen et al., 2001). A total of 12 407 (85%) of the 14 622 patients in the register were alive on April 1, 1968, or later and had therefore been assigned a personal identification number, making unique linkage with other registers possible.
Identification of cases and controls
The Danish Multiple Sclerosis Register was linked with the register of school health records using the personal identification number. A total of 661 multiple sclerosis cases diagnosed after the age of 14 years were identified. For each case we initially selected seven potential controls in the register of school health records, matching the case for sex and for date of birth randomly within 1 month, and being alive and resident in Denmark in the year when the case was diagnosed with multiple sclerosis. Since information on childhood infections had not previously been computerized, we manually searched the archive of school health records and identified all cases and four of the seven corresponding controls. Records belonging to subjects born before 1940 did not have information on specific childhood infections and were excluded, leaving a total of 455 cases and 1801 controls in the study.
Exposure data
The archive of school health records contains records of regular, mostly annual, health examinations of children attending schools in the municipality of Copenhagen, as described elsewhere (Andersen et al., 1981). Included is information on history of measles, pertussis, and scarlet fever for children born since 1940 and, for children born since 1950, of rubella, varicella and mumps. The information is obtained from parents by the school physician at school entry (average age, 7 years) and during school years (ages 7–14 years). Time of childhood infection was recorded either as the exact date (2%), the month and year (10%), the year (56%), or as prior to school entry (32%). For children born since 1940, the records also contain information on birth order, sibship size, father's occupation, school years, name of the school, attended grades, and identity of the attended classes. Social class in childhood was derived from the father's occupation recorded when starting school (Enevoldsen et al., 1980). Vaccination against pertussis was introduced in Denmark in 1961; vaccinations against the other studied infections had not been administered (Plesner and Ronne, 1994) during the exposure period.
Statistical analyses
All risk ratios were estimated as odds ratios (ORs) using conditional logistic regression to take the matched design into account. We assessed the independent effect on risk of multiple sclerosis of each childhood infection acquired at any age (yes, no, missing) and at different ages within the age span 0–14 years, with and without adjustment for possible confounding by birth order (1, 2, 3, 4, 5+, missing) and social class (I, II, III, IV, V, missing). Similarly, we assessed the effect on risk of multiple sclerosis of the cumulative number of the six infections acquired at ages 0–14, 10–14 and 7–14 years; in the two latter analyses estimates were further adjusted for cumulative number of infections before age 10 and 7 years, respectively. We also assessed the effect on risk of multiple sclerosis of birth order, sibship size and social class. Finally, we assessed whether multiple sclerosis clustered in school classes by investigating whether classmates of multiple sclerosis cases were at increased risk of multiple sclerosis. A person was defined as ‘having a multiple sclerosis case as a classmate’ if the multiple sclerosis case was diagnosed before that person. To avoid bias, controls were assigned a pseudo-date of diagnosis, which was the date of diagnosis of their corresponding case. P values were based on likelihood ratio tests and 95% confidence intervals (CIs) were based on Wald's tests. The statistical software program SAS version 8.2 was used for the analyses (SAS Institute, Cary, NC, USA).
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Results |
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Cases had been diagnosed with multiple sclerosis between the age of 15 and 56 years (mean age 35.0 years) and the ratio of males to females was 1:1.9. The prevalence of reported childhood infections before the age of 15 years among cases and controls was, respectively, 78 and 80% for measles, 45 and 45% for rubella, 68 and 67% for varicella, 35 and 41% for mumps, 50 and 52% for pertussis, and 8 and 10% for scarlet fever.
Table 1 shows the risk of multiple sclerosis according to history of infection with measles, pertussis and scarlet fever among 455 cases and 1801 controls, and of rubella, varicella and mumps among 182 cases and 690 controls. Overall, no specific childhood infection before the age of 15 years was associated with risk of multiple sclerosis.
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Table 2 shows the risk of multiple sclerosis according to age at infection. Overall, age at measles, rubella, mumps, varicella, pertussis and scarlet fever was not significantly associated with risk of multiple sclerosis. These findings did not change materially when grouping together subjects in intervals of ages at infection between 10 and 14 years, 7 and 9 years, and 0 and 6 years, the last group including also those subjects who had a positive history of infection before age 7 years but for whom age at infection had not been specified (data not shown). A total of 164 cases and 585 controls born in 1950 or later had complete information on the history of all six studied infections. Among these subjects, the risk of multiple sclerosis did not vary by number of infections between the ages of 10 and 14 years (Table 3), between the ages of 7 and 14 years, or before the age of 15 years (data not shown).
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The risk estimates presented in Tables 1, 2 and 3 were similar with and without adjustment for social class and birth order, or social class and sibship size. Estimates for pertussis did not change materially when excluding from the analyses subjects born after pertussis vaccination was introduced (57 cases) (Plesner and Ronne, 1994
). Table 4 shows the risk of multiple sclerosis among the 455 cases and 1801 controls according to birth order, sibship size and social class of the father on starting school. Being a firstborn or having no siblings did not constitute risk factors for multiple sclerosis. Table 4 also shows that risk of multiple sclerosis was not associated with social class in childhood. Neither of the above comparisons (birth order, sibship size, social class) changed materially when mutually adjusted (data not shown).
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The risk of multiple sclerosis was not significantly associated with having been classmates with a case (OR 1.1; 95% CI, 0.7–1.6); thus 36/449 (8.0%) cases and 130/1761 (7.4%) controls were classmates with a case for 1 year or more, and no cases were classmates with more than one case (six cases with no information on class identity were excluded from the analyses).
None of the results presented above and in the tables changed materially when cases diagnosed before (n = 238) and after (n = 217) the age of 35 years were grouped separately in the analysis (scarlet fever was not analysed due to small numbers). None of the results presented changed materially when excluding from the analyses the 55 cases with a diagnosis of possible multiple sclerosis.
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Discussion |
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According to the present case–control study, childhood infection with measles, rubella, mumps, varicella, pertussis or scarlet fever, whether acquired at a late age or cumulatively, is not associated with the risk of multiple sclerosis. The overall interpretation (Casetta and Granieri, 2000
) of previous (Panelius et al., 1973; Alter and Cendrowski, 1976; Poskanzer et al., 1980a; Andersen et al., 1981; Haile et al., 1982; Sullivan et al., 1984; Compston et al., 1986; Italian Multiple Sclerosis Study Group, 1989; Hays, 1992; Gronning et al., 1993; Casetta et al., 1994; Bansil et al., 1997; Bachmann and Kesselring, 1998) and, in some cases, more recent studies (Hernan et al., 2001; Tarrats et al., 2002; Haahr et al., 2004) is that the frequency of each of these infections is not different between multiple sclerosis patients and controls or reference populations, but that cases generally report a later age at infections. Most studies relating multiple sclerosis to age at infection have, however, been criticized (Granieri and Casetta, 1997; Casetta and Granieri, 2000; Marrie and Wolfson, 2001). Specifically, only a small study has avoided the potential bias from recalling age at childhood infections during adulthood or after multiple sclerosis development (Andersen et al., 1981). In addition, few studies have enrolled cases and controls from the general population (Poskanzer et al., 1980a; Andersen et al., 1981; Sullivan et al., 1984; Casetta et al., 1994) or with a shared childhood environment (Poskanzer et al., 1980a; Andersen et al., 1981; Sullivan et al., 1984; Hays, 1992; Hernan et al., 2001; Tarrats et al., 2002; Haahr et al., 2004). Avoiding all of these potential sources of bias, our results do not support the belief that patients with multiple sclerosis are older at childhood infection than control populations with respect to measles (Panelius et al., 1973; Alter and Cendrowski, 1976; Haile et al., 1982; Sullivan et al., 1984; Compston et al., 1986; Gronning et al., 1993; Bachmann and Kesselring, 1998), rubella (Compston et al., 1986; Bachmann and Kesselring, 1998), mumps (Hays, 1992; Bachmann and Kesselring, 1998; Hernan et al., 2001), varicella (Bachmann and Kesselring, 1998), pertussis (Poskanzer et al., 1980a) or scarlet fever (Bachmann and Kesselring, 1998).
In our analyses we did not find any association between risk of multiple sclerosis and delayed exposure to common childhood infections as approximated by birth order. The lack of an association with early birth order is in agreement with reports from most other case–control studies (Antonovsky et al., 1965; Alter and Cendrowski, 1976; Visscher et al., 1982; Berr et al., 1989; Koch-Henriksen, 1989; Operskalski et al., 1989; Matias-Guiu et al., 1994; Gaudet et al., 1995), although not all (Isager et al., 1980; Zilber et al., 1988; Hernan et al., 2001). Isager and colleagues studied 46 Danish multiple sclerosis patients and controls and reported a decreased risk of multiple sclerosis among persons with three or more older siblings (Isager et al., 1980). The authors used a design and material similar to those of the present study but they did not describe the diagnostic inclusion criteria of multiple sclerosis, and we could not reproduce their significant result among 66 patients identified using the same years of multiple sclerosis diagnosis and births (OR 0.6; 95% CI, 0.3–1.2; birth order 3 or more versus 1 and 2). Zilber and colleagues found the mean birth order number among 97 Israeli multiple sclerosis patients to be significantly lower when compared with controls, but the authors themselves were concerned about selection bias (Zilber et al., 1988). Hernan and colleagues studied 301 female cases and reported firstborns in large sibships (
4) to be at increased risk of multiple sclerosis, but trend analyses were less convincing (Hernan et al., 2001).
We also assessed the possible association between risk of multiple sclerosis and social class. It has been proposed that age at common infections in childhood is inversely associated with social class in childhood, reflecting sanitary conditions and hygienic standards. Accordingly, high socio-economic status should confer an increased risk of multiple sclerosis (Poskanzer et al., 1963). We found no association using social class derived from the father's occupation at school start, a finding compatible with most previous studies using similar socio-economic status in childhood (Antonovsky et al., 1965; Alter and Speer, 1968; Poskanzer et al., 1980b; Berr et al., 1989; Koch-Henriksen, 1989; Operskalski et al., 1989). With respect to socio-economic status later in life, several studies, notably two large population-based studies from the USA and Australia, have reported an association with high socio-economic status in adolescence, adulthood, or at multiple sclerosis onset (i.e. educational level or social class), but these findings are not easily interpreted in the context of exposure to infections in childhood (Miller et al., 1960; Beebe et al., 1967; Russell, 1971; Visscher et al., 1981; Phadke and Downie, 1987; Italian Multiple Sclerosis Study Group, 1989; Casetta et al., 1994; Gonzalez and Sotelo, 1995; Hammond et al., 1996; Zilber and Kahana, 1996; Kurtzke and Page, 1997). There are, however, also exceptions to these findings (Antonovsky et al., 1967; Alter and Speer, 1968; Panelius, 1969; Poskanzer et al., 1980b; Berr et al., 1989; Koch-Henriksen, 1989; Operskalski et al., 1989; Ghadirian et al., 2001; Tarrats et al., 2002).
Finally, a possible infectious aetiology of multiple sclerosis has also been suggested on the basis of observations of space–time clusters of multiple sclerosis (Riise, 1997). More recently, Haahr and colleagues reported a cluster of eight multiple sclerosis patients in a Danish community who, during a 13-year period, attended the same elementary school from the age of 7 to 14 years and were also scouts together (Haahr et al., 1997). However, we found no evidence that multiple sclerosis clustered among persons who had been classmates during that period of childhood.
In a supplementary analysis we explored whether delayed exposure to a childhood infection might specifically be a cause of multiple sclerosis developed at a relatively old age. The hypothesis was invoked by studies reporting that the risk of presumably genetically determined multiple sclerosis that may accumulate in families increases with decreasing age at onset in the affected relative (Sadovnick et al., 1998). Grouping multiple sclerosis diagnosed before and after the age of 35 years separately and repeating all analyses showed no significant variation in risk estimates.
Overall, we did not find any association between risk of multiple sclerosis and exposure to childhood infections. It is, however, interesting, although not systematically reported, that the records of three cases and three controls had recorded information on infectious mononucleosis, corresponding to a 4-fold increase in the risk of multiple sclerosis (95% CI, 0.8–20.0). Previously, a 2- to 3-fold significantly increased risk of multiple sclerosis after infectious mononucleosis has been reported and Epstein–Barr virus has therefore been suggested to be involved in the development of multiple sclerosis (Operskalski et al., 1989; Lindberg et al., 1991; Hernan et al., 2001; Haahr et al., 1995, 2004).
In conclusion, our findings suggest that measles, rubella, mumps, varicella, pertussis and scarlet fever, even if acquired late in childhood, are not associated with increased risk of multiple sclerosis later in life.
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Acknowledgements |
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We wish to thank Statistician Claus Holst for electronic identification of cases and matching of controls using the register of school health records and the Danish Multiple Sclerosis Register. The present study was supported by the Danish Medical Research Council, the Augustinus Foundation, the Lundbeck Foundation and Danish Multiple Sclerosis Society.
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References |
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TopSummaryIntroductionMaterial and methodsResultsDiscussionReferences |
|---|
Allison RS, Millar JH. Prevalence of disseminated sclerosis in Northern Ireland. Ulster Med J 1954; 23 Suppl 2: 1–27.[Medline]
Alter M, Cendrowski W. Multiple sclerosis and childhood infections. Neurology 1976; 26: 201–4.
Alter M, Speer J. Clinical evaluation of possible etiologic factors in multiple sclerosis. Neurology 1968; 18: 109–16.[Web of Science][Medline]
Alter M, Halpern L, Kurland LT, Bornstein B, Leibowitz U, Silberstein J. Multiple sclerosis in Israel. Prevalence among immigrants and native inhabitants. Arch Neurol 1962; 7: 253–63.
Alter M, Zhen-Xin Z, Davanipour Z, Sobel E, Min LS, LaRue L. Does delay in acquiring childhood infection increase risk of multiple sclerosis? Ital J Neurol Sci 1987; Suppl 6: 11–6.
Andersen E, Isager H, Hyllested K. Risk factors in multiple sclerosis: tuberculin reactivity, age at measles infection, tonsillectomy and appendectomy. Acta Neurol Scand 1981; 63: 131–5.[Web of Science][Medline]
Antonovsky A, Leibowitz U, Smith HA, Medalie JM, Balogh M, Kats R, et al. Epidemiologic study of multiple sclerosis in Israel. Arch Neurol 1965; 13: 183–93.
Antonovsky A, Leibowitz U, Medalie JM, Smith HA, Halpern L, Alter M. Epidemiologic study of multiple sclerosis in Israel. Part III: multiple sclerosis and socioeconomic status. J Neurol Neurosurg Psychiatry 1967; 30: 1–6.
Bachmann S, Kesselring J. Multiple sclerosis and infectious childhood diseases. Neuroepidemiology 1998; 17: 154–60.[CrossRef][Web of Science][Medline]
Bansil S, Singhal BS, Ahuja GK, Riise T, Ladiwala U, Behari M, et al. Multiple sclerosis in India: a case–control study of environmental exposures. Acta Neurol Scand 1997; 95: 90–5.[Web of Science][Medline]
Beebe GW, Kurtzke JF, Kurland LT, Auth TL, Nagler B. Studies on the natural history of multiple sclerosis. 3. Epidemiologic analysis of the army experience in World War II. Neurology 1967; 17: 1–17.
Berr C, Puel J, Clanet M, Ruidavets JB, Mas JL, Alperovitch A. Risk factors in multiple sclerosis: a population-based case–control study in Hautes-Pyrenees, France. Acta Neurol Scand 1989; 80: 46–50.[Web of Science][Medline]
Casetta I, Granieri E. Clinical infections and multiple sclerosis: contribution from analytical epidemiology. J Neurovirol 2000; 6 Suppl 2: S147–S151.
Casetta I, Granieri E, Malagu S, Tola MR, Paolino E, Caniatti LM, et al. Environmental risk factors and multiple sclerosis: a community-based, case–control study in the province of Ferrara, Italy. Neuroepidemiology 1994; 13: 120–8.[CrossRef][Web of Science][Medline]
Compston DA, Vakarelis BN, Paul E, McDonald WI, Batchelor JR, Mims CA. Viral infection in patients with multiple sclerosis and HLA-DR matched controls. Brain 1986; 109: 325–44.
Dean G, Kurtzke JF. On the risk of multiple sclerosis according to age at immigration to South Africa. Br Med J 1971; 3: 725–9.
Detels R, Visscher BR, Haile RW, Malmgren RM, Dudley JP, Coulson AH. Multiple sclerosis and age at migration. Am J Epidemiol 1978; 108: 386–93.
Ebers GC, Bulman DE, Sadovnick AD, Paty DW, Warren S, Hader W, et al. A population-based study of multiple sclerosis in twins. N Engl J Med 1986; 315: 1638–42.[Abstract]
Enevoldsen B, Michelsen N, Friis-Hasche E, Kamper-Jorgensen F. Social classification. II. Stalastoga's subdivision according to social status rank and the social grouping employed by the Institute for Social Research. [Danish]. Ugeskr Laeger 1980; 142: 544–50.[Medline]
Gaudet JP, Hashimoto L, Sadovnick AD, Ebers GC. 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.[Web of Science][Medline]
Ghadirian P, Dadgostar B, Azani R, Maisonneuve P. A case–control study of the association between socio-demographic, lifestyle and medical history factors and multiple sclerosis. Can J Public Health 2001; 92: 281–5.[Web of Science][Medline]
Gonzalez O, Sotelo J. Is the frequency of multiple sclerosis increasing in Mexico? J Neurol Neurosurg Psychiatry 1995; 59: 528–30.
Granieri E, Casetta I. The epidemiologic study of exogenous factors in the etiology of multiple sclerosis: part Iii: selected reviews: common childhood and adolescent infections and multiple sclerosis. Neurology 1997; 49: S42–S54.[Web of Science][Medline]
Granieri E, Casetta I, Tola MR, Ferrante P. Multiple sclerosis: infectious hypothesis. Neurol Sci 2001; 22: 179–85.[CrossRef][Web of Science][Medline]
Gronning M, Riise T, Kvale G, Albrektsen G, Midgard R, Nyland H. Infections in childhood and adolescence in multiple sclerosis. A case–control study. Neuroepidemiology 1993; 12: 61–9.[CrossRef][Web of Science][Medline]
Haahr S, Koch-Henriksen N, Moller-Larsen A, Eriksen LS, Andersen HM. Increased risk of multiple sclerosis after late Epstein–Barr virus infection: a historical prospective study. Mult Scler 1995; 1: 73–7.[Medline]
Haahr S, Munch M, Christensen T, Moller-Larsen A, Hvas J. Cluster of multiple sclerosis patients from Danish community. Lancet 1997; 349: 923.[CrossRef][Web of Science][Medline]
Haahr S, Plesner AM, Vestergaard BF, Hollsberg P. A role of late Epstein–Barr virus infection in multiple sclerosis. Acta Neurol Scand 2004; 109: 270–5.[CrossRef][Web of Science][Medline]
Haile R, Smith P, Read D, Nassim D, Warlow C, Russell WC. A study of measles virus and canine distemper virus antibodies, and of childhood infections in multiple sclerosis patients and controls. J Neurol Sci 1982; 56: 1–10.[CrossRef][Web of Science][Medline]
Hammon W, Sather GE, Hollinger N. Preliminary report of epidemiological studies on poliomyelitis and streptococcal infections. Am J Public Health 1950; 40: 306.
Hammond SR, McLeod JG, Millingen KS, Stewart-Wynne EG, English D, Holland JT, et al. The epidemiology of multiple sclerosis in three Australian cities: Perth, Newcastle and Hobart. Brain 1988; 111: 1–25.
Hammond SR, McLeod JG, Macaskill P, English DR. Multiple sclerosis in Australia: socioeconomic factors. J Neurol Neurosurg Psychiatry 1996; 61: 311–3.
Hays P. Multiple sclerosis and delayed mumps. Acta Neurol Scand 1992; 85: 200–3.[Web of Science][Medline]
Hernan MA, Zhang SM, Lipworth L, Olek MJ, Ascherio A. Multiple sclerosis and age at infection with common viruses. Epidemiology 2001; 12: 301–6.[CrossRef][Web of Science][Medline]
Isager H, Andersen E, Hyllested K. Risk of multiple sclerosis inversely associated with birth order position. Acta Neurol Scand 1980; 61: 393–6.[Web of Science][Medline]
Italian Multiple Sclerosis Study Group. Migration and infectious diseases in the etiology of multiple sclerosis: a case–control study. In: Battaglia MA, editor. Multiple sclerosis research. Amsterdam: Excerpta Medica; 1989. p. 147–56.
Koch-Henriksen N. An epidemiological study of multiple sclerosis. Familial aggregation, social determinants, and exogenic factors. Acta Neurol Scand 1989; 80: 1–121.[Web of Science][Medline]
Koch-Henriksen N. The Danish Multiple Sclerosis Registry: a 50-year follow-up. Mult Scler 1999; 5: 293–6.
Koch-Henriksen N, Rasmussen S, Stenager E, Madsen M. The Danish Multiple Sclerosis Registry. History, data collection and validity. Dan Med Bull 2001; 48: 91–4.[Web of Science][Medline]
Kurtzke JF. Epidemiologic evidence for multiple sclerosis as an infection. Clin Microbiol Rev 1993; 6: 382–427.
Kurtzke JF, Page WF. Epidemiology of multiple sclerosis in US veterans: VII. Risk factors for MS. Neurology 1997; 48: 204–13.
Lauer K. The risk of multiple sclerosis in the U.S.A. in relation to sociogeographic features: a factor-analytic study. J Clin Epidemiol 1994; 47: 43–8.[CrossRef][Web of Science][Medline]
Lindberg C, Andersen O, Vahlne A, Dalton M, Runmarker B. Epidemiological investigation of the association between infectious mononucleosis and multiple sclerosis. Neuroepidemiology 1991; 10: 62–5.[Web of Science][Medline]
Malig C. The civil registration system in Denmark. Bethesda (MD): International Institute for Vital Registration and Statistics; 1996. p. 1–6.
Marie P. Sclérose en plaques et maladies infectueuses. Prog Med 1884; 12: 287–9.
Marrie RA, Wolfson C. Multiple sclerosis and varicella zoster virus infection: a review. Epidemiol Infect 2001; 127: 315–25.[Medline]
Matias-Guiu J, Ferri L, Falip R, Galiano L, Martin R. Birth order in multiple sclerosis: a population-based case–control study in Alcoi, Spain. Neuroepidemiology 1994; 13: 129–30.[Web of Science][Medline]
Millar JH, Allison RS. Familial incidence of disseminated sclerosis in Northern Ireland. Ulster Med J 1954; 23 Suppl 2: 29–92.[Medline]
Miller H, Ridley A, Schapira K. Multiple sclerosis. A note on social incidence. Br Med J 1960; 2: 343–5.
Mucci LA, Hsieh CC, Williams PL, Dickman PW, Bjorkman L, Pedersen NL. Birth order, sibship size, and housing density in relation to tooth loss and periodontal disease: a cohort study among Swedish twins. Am J Epidemiol 2004; 159: 499–506.
Operskalski EA, Visscher BR, Malmgren RM, Detels R. A case–control study of multiple sclerosis. Neurology 1989; 39: 825–9.
Panelius M. Studies on epidemiological, clinical and etiological aspects of multiple sclerosis. Acta Neurol Scand 1969; Suppl 39: 1–82.
Panelius M, Salmi A, Halonen PE, Kivalo E, Rinne UK, Penttinen K. Virus antibodies in serum specimens from patients with multiple sclerosis, from siblings, and matched controls. A final report. Acta Neurol Scand 1973; 49: 85–107.[Web of Science][Medline]
Phadke JG, Downie AW. Epidemiology of multiple sclerosis in the north-east (Grampian region) of Scotland—an update. J Epidemiol Community Health 1987; 41: 5–13.
Plesner AM, Ronne T. The childhood vaccination program. Background, status and future. Ugeskr Laeger 1994; 156: 7497–503.[Medline]
Poser CM, Paty DW, Scheinberg L, McDonald WI, Davis FA, Ebers GC, et al. New diagnostic criteria for multiple sclerosis: guidelines for research protocols. Ann Neurol 1983; 13: 227–31.[CrossRef][Web of Science][Medline]
Poskanzer DC, Schapira K, Miller H. Multiple sclerosis and poliomyelitis. Lancet 1963; 186: 917–21.[CrossRef][Medline]
Poskanzer DC, Sever JL, Sheridan JL, Prenney LB. Multiple sclerosis in the Orkney and Shetland Islands. IV: viral antibody titres and viral infections. J Epidemiol Community Health 1980a; 34: 258–64.
Poskanzer DC, Sheridan JL, Prenney LB, Walker AM. Multiple sclerosis in the Orkney and Shetland Islands. II: the search for an exogenous aetiology. J Epidemiol Community Health 1980b; 34: 240–52.
Riise T. Cluster studies in multiple sclerosis. Neurology 1997; 49 (2 Suppl 2): S27–S32.
Russell WR. Multiple sclerosis: occupation and social group at onset. Lancet 1971; 2: 832–34.[Web of Science][Medline]
Sadovnick AD, Macleod PM. The familial nature of multiple sclerosis: empiric recurrence risks for first, second-, and third-degree relatives of patients. Neurology 1981; 31: 1039–41.
Sadovnick AD, Yee IM, Ebers GC, Risch NJ. Effect of age at onset and parental disease status on sibling risks for MS. Neurology 1998; 50: 719–23.
Sullivan CB, Visscher BR, Detels R. Multiple sclerosis and age at exposure to childhood diseases and animals: cases and their friends. Neurology 1984; 34: 1144–8.
Tarrats R, Ordonez G, Rios C, Sotelo J. Varicella, ephemeral breastfeeding and eczema as risk factors for multiple sclerosis in Mexicans. Acta Neurol Scand 2002; 105: 88–94.[CrossRef][Web of Science][Medline]
Visscher BR, Clark VA, Detels R, Malmgren RM, Valdiviezo NL, Dudley JP. Two populations with multiple sclerosis. Clinical and demographic characteristics. J Neurol 1981; 225: 237–49.[CrossRef][Web of Science][Medline]
Visscher BR, Liu KS, Sullivan CB, Valdiviezo NL, Detels R. Birth order and multiple sclerosis. Acta Neurol Scand 1982; 66: 209–15.[Web of Science][Medline]
Willer CJ, Dyment DA, Risch NJ, Sadovnick AD, Ebers GC. Twin concordance and sibling recurrence rates in multiple sclerosis. Proc Natl Acad Sci USA 2003; 100: 12877–82.
Zilber N, Kahana E. Risk factors for multiple sclerosis: a case–control study in Israel. Acta Neurol Scand 1996; 94: 395–403.[Web of Science][Medline]
Zilber N, Kutai-Berman M, Kahana E, Korczyn AD. Multiple sclerosis and birth order. Acta Neurol Scand 1988; 78: 313–7.[Web of Science][Medline]
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