Affiliations of authors: National Centre in HIV Epidemiology and Clinical Research, University of NSW, Sydney, Australia (AEG, CMV, JMK); School of Public Health, The University of Sydney, Sydney, Australia (AMH, AK, BKA); School of Population Health, The University of Western Australia, Perth, Australia (LF); St. Vincent's Hospital, Sydney, Australia (JJT, SM); Department of Epidemiology and Biostatistics, Monash University, Melbourne, Australia (GB)
Correspondence to: Andrew Grulich, MBBS, MSc, PhD, Head, HIV Epidemiology and Prevention Program, National Centre in HIV Epidemiology and Clinical Research, University of NSW, Level 2, 376 Victoria Street, Darlinghurst, NSW 2010, Australia (e-mail: agrulich{at}nchecr.unsw.edu.au).
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ABSTRACT |
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INTRODUCTION |
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Non-Hodgkin lymphoma (NHL) arises from cells of the immune system. Rates of NHL in people with congenital or acquired immune deficiency are at least 50 times higher than population rates (46). However, it is not known whether other forms of immune dysregulation are associated with risk of NHL. Existing evidence regarding the relationship between atopic conditions and NHL risk is inconsistent (718), although the majority of studies have found that atopy is associated with a reduced risk of NHL. Few studies have investigated the association between early-life exposure to infectious agents and risk of NHL.
To examine the association between early development of the immune system and risk of NHL, we carried out a population-based case-control study in Australia. We examined whether measures of childhood household size and structure that might indicate risk of childhood infection and history of atopic conditions were associated with risk of NHL.
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SUBJECTS AND METHODS |
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The study recruitment methods, including subject characteristics and exclusions, have been described in detail elsewhere (19). Case patients were newly diagnosed with NHL between January 2000 and August 2001, aged 20 to 74 years, and resident in New South Wales (NSW) or the Australian Capital Territory (ACT). They were identified from the population-based NSW Central Cancer Registry. Control subjects were randomly selected from NSW and ACT electoral rolls (enrollment to vote is compulsory for adult Australian citizens) and were frequency matched to case patients by age, sex, and state of residence at diagnosis. We intended to enroll equal numbers of case patients and control subjects; given the lower response rate in control subjects, extra potential control subjects were therefore identified. Written informed consent was obtained from each participant, and the study was approved by the human research ethics committee at each participating institution.
Patients with a diagnosis of chronic lymphocytic leukemia, plasma cell myeloma, precursor B or T cell lymphoblastic leukemia, and lymphomatoid granulomatosis grades 1 and 2 were excluded. Because the study was designed to examine risk factors for NHL in people without obvious clinical immune deficiency, patients were excluded if they had a history of transplantation or human immunodeficiency virus (HIV) infection. We also excluded potential case patients and control subjects who were dead, had an illness or disability that prevented a 60-minute telephone interview, or had poor English language skills. Pathology reports were reviewed by an anatomical pathologist with a particular interest in hematopathology (Dr. J. Turner, St. Vincent's Hospital, Sydney) to assess confidence in the diagnosis of NHL and to assign, where possible, a cell phenotype and WHO (ICD-03) code (19).
Data Collection
Case patients and control subjects were approached in the same manner, and the data collection procedures were identical for both groups (19). Potential participants were sent a letter and an information leaflet inviting them to participate in a research project about the effects of the environment on the development of NHL, and written informed consent was obtained from those who agreed to participate. Participants completed a self-administered mailed questionnaire and were interviewed by telephone using a computer-assisted questionnaire. Socioeconomic status was assigned to each subject based on his or her address at the time of the interview using a published index constructed from 1996 census data (20).
Data on subjects' self-reported history of medical conditions were ascertained from the telephone interview. Interviews were conducted from March 2000 through May 2002 by experienced interviewers who were blinded to the case and control status of subjects and who interviewed equal numbers of case patients and control subjects. Participants were asked to report their birth order, the total number of other children living in their household when they were a child (defined as the first 10 years of life), whether they usually shared a bed or a bedroom, and the duration (in years) of such sharing. Participants were also asked about their history of atopic conditions, including hay fever, asthma, and eczema during their childhood, teenage years, adulthood, and lifetime. Finally, participants were asked whether they had allergies to any foods or medicines and whether they had ever experienced an allergic reaction severe enough to require urgent medical attention.
Statistical Methods
Continuous variables were categorized into approximate quartiles or tertiles of the exposure distribution among control subjects. The primary analyses included all case patients. The analyses were also repeated for the case patients with the two most common NHL subtypes, follicular lymphoma (n = 239) and diffuse large-B-cell lymphoma (n = 225).
Unconditional logistic regression models were adjusted for age, sex, and area of residence (i.e., NSW or ACT). Each model also included ethnicity as a covariate because fewer control subjects were born outside Australia than expected based on the 2001 Australian Census (19). To further exclude the possibility that any observed association was due to selection bias by country of birth in control subjects, we also estimated associations among Australian- and New Zealand-born subjects only. Measures of birth order and childhood crowding were included in models with and without adjustment for socioeconomic status at interview because of the known association between lower socioeconomic status and large household size in Australia (21) and because there is some (albeit inconsistent) evidence of a positive association between higher socioeconomic status and risk of NHL (18).
Variables that were statistically significantly associated with NHL risk in univariate analyses were included in a multivariable model of NHL risk. Birth order was included as a covariate in separate models with key atopy variables, i.e., lifetime history of hay fever, asthma, eczema, or food allergy. We also constructed a model containing all of these variables. Because other analyses of the subjects in this study showed that people with high sun exposure had statistically significantly lower risks of NHL (22), we also included sun exposure as a covariate. Total lifetime sun exposure was derived from measured outdoor hours on working and non-working days and vacations at 10, 20, 30, 40, 50, and 60 years of age (22). In the final model, odds ratios (ORs) were adjusted for quartile of socioeconomic status and quartile of sun exposure.
All analyses were done using STATA software (version 8.0; Stata Corporation, College Station, TX). Tests for linear trend were done by fitting ordered categories of a variable as a single ordinal variable in the logistic regression models; P values for trends were based on the Wald test. All P values presented are two-sided, and the statistical significance level for hypothesis testing was set at 0.05.
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RESULTS |
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Of the 1687 potential control subjects who were initially randomly selected for the study, five had died, 71 were too ill to participate, 74 had inadequate English, and 401 could not be contacted, leaving 1136 control subjects approached to participate. Of these, 694 were interviewed, corresponding to a response rate of 41% and a cooperation rate of 61%. Participating case patients and control subjects had a similar socioeconomic status, and similar proportions of case patients and control subjects resided in a rural locality at interview (19).
Being an only child or a first-born child of a multi-child family (hereafter referred to as an other first-born child) was strongly inversely associated with risk of NHL; the odds ratio was 0.52 (95% confidence interval [CI] = 0.32 to 0.84) for an only child compared with a fourth-born or laterbirth order child and 0.55 (95% CI = 0.40 to 0.75) for an other first-born child (Table 1). The odd ratios for second- and third-born children were 0.70 and 0.81, respectively (Ptrend<.001). The associations between birth order and risk of NHL were almost identical in men and women (data not shown). There was also a statistically significant trend of decreasing NHL risk with decreasing number of other children who lived in the household during the participant's childhood (Ptrend =.04, Table 1). However, usually sharing a bedroom or a bed as a child was not associated with risk of NHL (Table 1).
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The risk associations for birth order and the atopic conditions were very similar for follicular lymphoma and diffuse large-B-cell lymphoma (data not shown). In addition, there was little evidence of statistical interaction between history of hay fever or allergy and birth order and the risk of NHL (Table 4).
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DISCUSSION |
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Previous studies of birth order and sibship size have yielded inconsistent associations with NHL risk. A recent population-based casecontrol study in the United States found that risk of NHL increased with increasing sibship size in women and heterosexual men (13); NHL risk was also increased in nonHIV infected homosexual men with five or more siblings (12). A cohort study of male deaths from NHL in the United States (24) found a nonstatistically significant reduction in risk associated with only-child status. A large Swedish cohort study (25) found no association between birth order and the combined risk of Hodgkin lymphoma and NHL in people up to 55 years of age; however, in this age group, Hodgkin lymphoma is likely to have made up a large proportion of diagnoses. Among hospital-based casecontrol studies of NHL, an Italian study (18) found no association with sibship size, whereas a study in England (9) found a statistically significantly increased NHL risk for only children but no association with sibship size. A population-based study in Denmark found increasing risk of Hodgkin lymphoma with increasing birth order and sibship size in children younger than 15 years but the opposite pattern in young adults (1542 years of age) (26).
We found that the risk of NHL was reduced by identical proportions in those who were only or other first-born children and that the risk increased linearly with the number of older siblings. There was no evidence, however, that close proximity to siblings and household members by sharing a bed or a bedroom was associated with NHL risk. These data suggest that it is events related to contact with other children in infancy (which should be identical in only and other first-born children), rather than events later in childhood (which are likely to differ between only and other first-born children), that contribute to NHL risk. Because the case patients and control subjects in our study were frequency matched by age, and age was controlled for in the analyses, these associations are unlikely to be confounded by time trends in household size.
Why should being an only child or other first-born child be associated with a reduced risk of NHL? One possibility is that early infection is a risk factor for NHL and that being an only or other first-born child is a surrogate marker of protection from early infection. It is unclear which infectious agents might be involved. The best-studied candidate for an early-life infection that may be related to NHL, Epstein-Barr virus, is believed to be associated with only a small minority of NHL cases, mainly in individuals with severe immune deficiency (27), who were excluded from this study. However, it is possible that early-life infection in general or its immunologic consequences may increase NHL risk through indirect pathways. It is also possible that other, unmeasured correlates of being first born contribute to NHL risk.
Several previous studies have examined the relationship between atopy and risk of NHL, but the methods by which atopy was measured varied widely and few studies reported on individual atopic conditions. Studies that have measured atopy or allergic conditions overall have generally not found either to be statistically significantly associated with NHL risk (9,11,1517), but in all of these studies the odds ratios were 1.0 or less. Nonstatistically significant reductions in NHL risk have also been reported for asthma (9,13,16) and hay fever (7,10,18); no studies have reported increased NHL risk associated with these conditions. Among those with eczema, a wide range of associations with NHL risk have been observed, including statistically significantly decreased risk (7), statistically significantly increased risk (9), and no statistically significant association (10,18). Among those with allergies to specific substances (i.e., plants, animals, drugs, and foods), both nonstatistically significantly (9,16) and statistically significantly (14) reduced risks have been reported, as well as odds ratios around 1.0 (7,8). No study has reported a statistically significant increase in NHL risk associated with allergies to specific substances. One study in the United States that found a reduced NHL risk in people with atopic conditions also found a reduced risk associated with antihistamine use (12). When these findings are taken together with our findings, a reasonably consistent picture of reduced risk associated with atopic disease appears to be emerging for NHL. Two recently reported population-based casecontrol studies of childhood acute lymphoblastic leukemia, another neoplasm of B lymphocytes, have reported a similar reduced risk in association with atopic disease in childhood (2829).
The two factors that were statistically significantly associated with a decreased risk of NHL in our study, early birth order and having a history of atopic disease, have been consistently shown to be related to each other in epidemiologic studies (1). A possible mechanism for this relationship, consistent with the hygiene hypothesis, is that less exposure to infection in early life may lead to later-than-normal colonization of the gut by bacteria, thereby reducing the strong stimulus for a change to a Th1-dominant response that is seen with early-life exposure to infection (30). Evidence in support of this possible mechanism comes from the finding that populations with a higher prevalence of organisms transmitted by the fecaloral route have a lower incidence of atopic diseases (31). In this context, it is interesting to note that the greatest risk reduction we found was for allergies to substances presented to the gut (i.e., for food allergies).
If the association between a Th2-dominant immune response and decreased NHL risk is causal, the mechanism is uncertain. On its face, the relationship between a Th2-dominant response and decreased NHL risk could be interpreted as the opposite of the well-described association between immune deficiency and increased NHL risk. However, in people with HIV-related immune deficiency, markers of a Th2 immune response, including increased levels of total immunoglobulin and B-cell stimulatory cytokines, are associated with increased rather than decreased NHL risk (32,33). Genetic polymorphisms associated with high expression of the B-cell stimulatory cytokine interleukin-10 are also associated with NHL risk in HIV-positive people (34). It may be that, in immune-deficient individuals, the absence of effective Th1 function to control the Th2 response explains the positive association with risk of NHL. In our study of nonimmune deficient people, we documented an opposite relationship of NHL risk with markers of Th2 function.
This study has several strengths. It was population based and had a low refusal rate among case patients. The most common reasons for case patients not participating were death prior to interview or illness preventing an interview; consequently, patients with the most severe disease may have been underrepresented (19). However, there is no reason to believe that severity of illness would be related to family size or atopic disease. The study also has limitations. As is seen with most population-based case-control studies, the participation rate among control subjects was less than that among case patients, raising the possibility that selection bias may have influenced our results. However, of two important factors known to influence family size, ethnicity and socioeconomic status, neither adjustment for both factors in a multivariable model nor restriction of analyses to those born in Australia and New Zealand materially altered the associations. Although this result weighs against bias caused by major known social determinants of family size, we cannot exclude the possibility that other, unmeasured determinants of family size or of history of atopy influenced study participation. We specifically excluded case patients who had HIV infection or were receiving immune-suppressive therapy after organ transplantation. Therefore, the results may be generalizable only to NHL patients without obvious severe immune deficiency. Control subjects were not asked specifically about their HIV status because of privacy concerns, but because the prevalence of HIV in Australian adults aged 1549 years is estimated to be 0.1% (35) the presence of HIV-infected control subjects is unlikely to have caused bias.
Another possible limitation is that the data were provided by self-reporting. It seems reasonable to expect that self-report data on birth order and household size should be accurate. The data on atopic conditions were also self-reported and were not confirmed using medical records. However, for relatively mild conditions such as hay fever and eczema, self-report data may be more accurate than medical records because participants may not have sought medical attention. Recall bias is also possible, but it is difficult to conceive of a reason why control subjects should be more likely than case patients to recall these mild conditions, especially given that recall bias usually acts in the opposite direction. If the error in recall of atopic diseases were nondifferential between case patients and control subjects, then it is likely that we have underestimated the strength of association with atopic conditions.
In the multivariable models, associations with the main risk variablesbirth order, hay fever, and food allergywere attenuated only slightly after mutual adjustment for birth order and each atopic condition. In addition, there was little evidence of interactions between atopic conditions and birth order. Thus, it appears that the pathways by which atopy and birth order might mediate decreased NHL risk, assuming that they are causal, are at least partially independent.
Taken together, our findings suggest that reduced exposure to infection in early life and its immunological consequence of a Th2-dominated immune response are associated with a reduced risk of NHL. It should be noted, however, that our findings cannot explain the increasing incidence of NHL seen in industrialized countries (36), in which household size is decreasing and the incidence of atopic conditions is increasing (1). One possible explanation for this observation is that early-life exposure to infection may have increased recently despite decreasing household size, due to the increasing use of day care for children. The incidence of Th1 diseases such as multiple sclerosis and type I diabetes is also increasing (3). It may be that all diseases that are associated with immune dysregulation are increasing in incidence and that NHL is another such condition.
Further epidemiologic studies are needed to confirm the link between birth order (or more specific measures of exposure to infection in early life), atopy, and reduced risk of NHL. Such studies, in addition to measuring other early-life environmental exposures relating to crowding and potential for infection, should measure biomarkers of Th2 response and T-cell regulation. Although data from casecontrol studies of genetic determinants of immune regulation may provide some information, data from cohort studies will also be required because the origin of NHL in the immune system will almost certainly frustrate retrospective assessment of these biomarkers in casecontrol studies.
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NOTES |
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We gratefully acknowledge the individuals who participated in the research, the clinicians who gave permission for us to approach their patients, and staff at the NSW Central Cancer Registry and the Hunter Valley Research Foundation. Special thanks to Melissa Litchfield, Maria Agaliotis, and Chris Goumas for data collection and data entry and to Jackie Turner for telephone follow-up. We also thank Sean Riminton and Michael Boyle, who made important comments on an earlier draft of the manuscript.
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Manuscript received July 19, 2004; revised January 20, 2005; accepted February 14, 2005.
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