Feature Article Breastfeeding and the Risk of Childhood Leukemia A Meta-Analysis

Feature Article

Public Health Reports /November–December 2004/Volume 119?521

Breastfeeding and the Risk of

Childhood Leukemia: A Meta-Analysis

Marilyn L. Kwan, PhD a Patricia A. Buf?er, PhD,MPH a

Barbara Abrams, DrPH a Vincent A. Kiley, MD b

a

Division of Public Health Biology and Epidemiology, School of Public Health, University of California, Berkeley, CA

b

Department of Pediatric Hematology/Oncology, Kaiser Permanente, Sacramento, CA

Address correspondence to: Marilyn L. Kwan, PhD, University of California, Berkeley, Ste. 500, 2150 Shattuck Ave., Berkeley, CA 94720;tel. 510-642-6406; fax 510-643-1735; e-mail .?2004 Association of Schools of Public Health

SYNOPSIS

Objectives. The authors used a meta-analytic technique to (1) quantify the evi-dence of an association between duration of breastfeeding and risk of childhood acute lymphoblastic leukemia (ALL) or acute myeloblastic leukemia (AML), (2) assess the in?uence of socioeconomic status (SES) on any such associations, and (3)

discuss the implications of these ?ndings for the evaluation of whether breastfeeding reduces the risk of childhood leukemia.

Methods. A ?xed effects model was employed to systematically combine the results of 14 case-control studies addressing the effect of short-term (?6 months) and long-term (?6 months) breastfeed-ing on the risk of childhood ALL and/or AML. Subgroup analyses of studies that did and did not adjust for SES were also performed.Results. A signi?cant, negative association was observed between long-term breastfeeding and both ALL risk (odds ratio [OR]?0.76;95% con?dence interval [CI] 0.68, 0.84) and AML risk (OR ?0.85;95% CI 0.73, 0.98). Short-term breastfeeding was similarly protec-tive for ALL and AML. Results for studies that adjusted and did not adjust for SES were not signi?cantly different from the results for the 14 studies combined.

Conclusions. This meta-analysis showed that both short-term and long-term breastfeeding reduced the risk of childhood ALL and AML, suggesting that the protective effect of breastfeeding might not be limited to ALL as earlier hypothesized. Potential bias introduced by different participation rates for case and control samples that differed in SES can be minimized by implementing larger case-control studies with SES-matched, population-based

controls.

PHOTO: EARL DOTTER

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Leukemia is the leading cause of cancer morbidity among children younger than 15 years of age in the United States.1Data from the Surveillance, Epidemiology, and End Results (SEER) registry suggest that acute lymphoblastic leukemia (ALL) accounted for 78% of all childhood leukemia cases diagnosed in the U.S. from 1975 through 1995, while acute myeloid leukemia (AML) accounted for 16%.1 Incidence among children younger than 15 years of age showed a modest increase from 1975 through the late 1980s but de-creased slightly from 1989 to 1999.2

Currently, the causes of childhood ALL are not well known, although sex, age, race, in utero ionizing radiation,and speci?c genetic syndromes have been consistently shown to be associated with risk for ALL.1 As for childhood AML,chemotherapeutic agents and in utero and postnatal ionizing radiation are recognized risk factors, and an association has been elucidated between race and risk of childhood AML.1Because ALL encompasses a heterogeneous group of mo-lecular subtypes, independent examination of etiologic and epidemiologic factors is required for each subtype.3,4 Fur-thermore, the clinical presentation of these molecular sub-types is also quite varied.3

A possible infectious etiology for the major subtype of ALL has been suggested by Greaves,3 who hypothesized that c-ALL (common B-cell precursor ALL) arises as a conse-quence of a rare, abnormal response to a nonspeci?c com-mon infection. Two separate genetic events may lead to the presentation of c-ALL: an initial spontaneous event during the expansion of B-cell precursors pre- or perinatally and a subsequent event in the same mutant clone following anti-genic challenge early in life (e.g., exposure to a common,nonspeci?c infection and the resulting stimulation of the young child’s underdeveloped immune system). Support for this hypothesis is seen in genetic backtracking of the pre-leukemic clone TEL-AML1, a genetic determinant of c-ALL,using newborn blood spots.4

Speculation has focused recently on the role of breast-feeding in protecting children from disease.3,5,6 Human milk has long been recognized as providing numerous antimicro-bial, anti-in?ammatory, and immunomodulating agents.Many studies have shown conclusively that breastfeeding protects against acute gastrointestinal infections through transmission of maternal antibodies, macrophages, and lym-phocytes.7,8 In contrast, the evidence for the protective ef-fect of breastfeeding with regard to acute respiratory infec-tion is still under debate.8,9 Therefore, since breast milk contains many bene?cial biological factors, the Greaves hy-pothesis implies that breastfeeding mediates the occurrence of childhood ALL as a result of a rare, abnormal response to a common infection.1 To date, no similar mechanism has been suggested for the association of breastfeeding and child-hood AML.

The scienti?c evidence has been mixed regarding the association of breastfeeding with childhood leukemia. A number of studies have shown no association between breast-feeding and leukemia risk.10–23 Five recent case-control stud-ies, however, have suggested that breastfeeding protects chil-dren from developing childhood ALL.6,24–27 The largest of these studies 24 included more than 1,700 ALL cases, while the smallest study 27 included only 69 cases. In addition to varying samples sizes, these ?ve studies differed on methods

of case ascertainment and selection of controls, and in mea-surement of breastfeeding duration. More important, two out of the ?ve studies 25,27 did not adjust for any marker of socioeconomic status (SES). This lack of adjustment in the statistical analysis is unusual since measures of SES, particu-larly maternal education, have been shown to be highly associated with breastfeeding.28 As for the association of SES with risk of childhood leukemia, results have varied. E arly ecologic and descriptive studies in the United States sug-gested that higher SES was a possible risk factor for child-hood leukemia, but in contrast, case-control studies have reported lower SE S in childhood leukemia patients com-pared to control subjects.29

The above issues prompt the need for a thorough review of the current literature on breastfeeding and childhood leukemia. For this study, we used a meta-analytic approach to evaluate the association of maternal breastfeeding with the risk of childhood leukemia. To our knowledge, this is the ?rst report to systematically review epidemiologic data on this topic and to present risk estimates for childhood ALL and AML associated with breastfeeding. Our goals were (1) to quantify any association between duration of breast-feeding and risk of childhood ALL or AML, (2) to assess the in?uence of SES on any such associations, and (3) to discuss the implications of these ?ndings for the evaluation of whether breastfeeding reduces the risk of childhood leukemia.

METHODS

We searched MEDLINE and CancerLit for original research and review articles on childhood leukemia and breastfeeding.In addition, we reviewed the bibliographies in these publica-tions as well as master’s theses and PhD dissertations ?led electronically that addressed breastfeeding and childhood leukemia. Keyword combinations for the online searches consisted of “breastfeeding and childhood cancer,” “breast-feeding and childhood leukemia,” “infant feeding and child-hood leukemia,” “infant feeding and childhood cancer,”“infant feeding and cancer,” and the names of three promi-nent investigators in the ?eld of maternal and child health whose names were encountered in the initial literature search.Thirty articles were initially identi?ed. Studies that pre-sented data on any type of leukemia in children 15 years or younger in terms of an odds ratio (OR) and con?dence interval (CI) and analyzed duration of breastfeeding in months were selected for the analysis. Seventeen studies were excluded, leaving 14 for the analysis.6,10–13,15,17,19–21,24–26,30Three of these studies were not peer-reviewed.10,11,21 Of the 17 excluded articles, two reported no ORs,31,32 one reported no CIs or p -values,33 two reported ORs only for all cancers combined,34,35 three were duplicate reports,36–38 two were topi-cal reviews on breastfeeding,9,39 one was a literature review,5and four did not analyze breastfeeding duration.14,16,18,27 Fi-nally, two cohort studies did not satisfy the selection criteria:one did not report any quantitative results 22 while the other did not analyze breastfeeding duration.23

Table 1 outlines important characteristics of the studies included in the meta-analysis. First, eight of the 14 studies excluded cases of leukemia in infants (usually children younger than 1 year of age) to avoid possible biases associ-

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ated with premature cessation of breastfeeding in children with cancer and also because most leukemias occurring dur-ing infancy are known to have different etiologies from childhood leukemias.40 We divided the 14 studies into sub-groups based on the leukemia classi ?cations used. The ALL classi ?cation was generally straightforward, with only one study specifying “leukemia ” instead of “ALL.”25 Since the majority of childhood leukemia is ALL,1 we included this study in the ALL group. Four studies 6,12,13,30 used the classi ?-cations “other leukemias ” or acute non-lymphoblastic leuke-mia (ANLL) instead of AML. Nevertheless, we included these studies in the AML group since the majority of such cases are AML cases.1 Finally, for purposes of this meta-analysis,we classi ?ed breastfeeding for six months or less as short-term breastfeeding, and breastfeeding for more than six months as long-term breastfeeding.

For each of the 14 articles reviewed, an OR and its 95%CI were extracted. When available, ORs adjusted for SE S were selected since SES was the most widely used potential confounder in these studies. A ?xed effects model based on the general principles of Greenland 41 was utilized since this model maintains a direct relationship between sample size and relative weight among smaller studies, unlike a random effects model.42 In addition, a ?xed effects model, in con-trast to a random effects model, assumes no heterogeneity between studies.41

Each OR was assigned a weight (W i ) equal to the inverse square of its standard error (SE ): W i ?1/(SE)2. SE s were calculated by dividing the natural log of the ratio of the upper and lower 95% con ?dence limits (CLs) by 3.92:SE ?ln(CL upper /CL lower )/3.92. For each study, the weight was multiplied by the natural log of the risk ratio (b i ) to give a summary measure (W i b i ). A combined summary was calcu-lated by adding the summary measures and dividing by the sum of the weights: b ?S W i b i /S W i . A summary OR was pro-duced by taking the exponential of the combined summary:OR sum ?exp b .

Heterogeneity among study results was assessed using the Chi-square statistic: x 2?S W i (b –b i )2. When evidence of het-erogeneity was present, the 95% CI of the summary OR was readjusted using new weights based on a random effects model that incorporated between-study heterogeneity.43

Finally, publication bias, the tendency of journals to pub-lish only those studies reporting signi ?cant associations, was evaluated visually by using the traditional funnel graph method to display the distribution of all included studies by their point estimates and SEs.44 Smaller studies will naturally be less precise (have larger SEs), and therefore, by chance,the risk estimates will vary around the true point estimate to a greater extent than in larger studies. As demonstrated by Light and Pillemer, a symmetric funnel shape is formed when study results and sample sizes are plotted if no publica-tion bias is present.44 If bias is present, the shape of the graph is skewed, indicating a correlation between point esti-mates and their SEs. In addition, as recommended by Begg and Mazumdar, we performed rank correlation tests to test for a signi ?cant relationship between the sample sizes and effect sizes of the studies.45 If a signi ?cant correlation does exist between these two factors, then publication bias is considered to be present.

RESULTS

The 14 articles on breastfeeding and childhood leukemia contributed 6,835 ALL cases and 1,216 AML cases. No evi-dence of publication bias was apparent for studies reporting results on the association between long-term breastfeeding and risk of ALL since the data points for these studies were fairly randomly distributed around the combined OR esti-mate (Figure 1) and the p -value for the rank correlation tests was nonsigni ?cant (p ?0.58). Similarly, we found no evidence of publication bias for studies exploring the asso-ciation between long-term breastfeeding and risk of AML (not shown, p ?0.46).

As shown in Tables 2 and 3, a signi ?cant, negative associa-tion was observed between short-term breastfeeding and ALL (OR ?0.88; 95% CI 0.80, 0.96), but the AML results (OR ?0.90; 95% CI 0.80, 1.02) were not signi ?cant. Tables 2and 3 and Figures 2 and 3 show a signi ?cant, negative asso-ciation between long-term breastfeeding and ALL based on 14 studies (OR ?0.76; 95% CI 0.68, 0.84) and a signi ?cant,negative association between long-term breastfeeding and AML based on eight studies (OR ?0.85; 95% CI 0.73, 0.98).Heterogeneity statistics for leukemia types and duration of breastfeeding were not signi ?cant (p -values ranged from 0.13 to 0.28) except for the ALL analysis addressing short-term breastfeeding (p ?0.03). For this point estimate, the adjusted 95% CI (0.80, 0.97) was almost exactly the same as the unadjusted 95% CI (0.80, 0.96). Therefore, use of the ?xed effects model, which assumes no heterogeneity among studies, was appropriate. A random effects model yielded similar ORs and heterogeneity statistics (not shown). Over-all, the combined ORs for all 14 studies supported a protec-tive role for breastfeeding with regard to the risk of child-hood leukemia.

Separate analyses were also conducted that addressed the association of breastfeeding duration with risk of ALL or AML using data adjusted and not adjusted for SES (Tables 2and 3). The ORs for short-term breastfeeding and risk of ALL based on adjusted and unadjusted data were both in the protective direction, analogous to the OR for the 14studies combined. For long-term breastfeeding and ALL,the ORs based on adjusted and unadjusted data were similar to the OR for the combined studies, although breastfeeding was no longer signi ?cantly protective in the unadjusted data (OR unadjusted ?0.78; 95% CI 0.55, 1.10). For the AML studies,the ORs for short-term breastfeeding based on adjusted and unadjusted data were both suggestive of a protective effect,similar to the OR for the combined studies. For long-term breastfeeding and risk of AML, the ORs for adjusted and unadjusted data were comparable to the OR for combined data, although breastfeeding was no longer signi ?cantly pro-tective in the unadjusted data (OR unadjusted ?0.89, 95% CI 0.29, 2.71). The estimates for the unadjusted AML data should be interpreted with caution since only two studies were available for comparison. Table 4 shows the ORs for SE S-adjusted data from the meta-analysis, as well as sepa-rately for the United Kingdom Childhood Cancer Study (UKCCS) and the Children ’s Cancer Group (CCG) study.19,24Overall, SES as a potential confounder appeared to play no substantial role in the ?ndings of either the short-term or long-term breastfeeding studies.

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Tables 2 and 3 also display the weights applied to each study result in the meta-analysis. An important point to note is that the weights are directly related to the SE for each study (see Methods), but the SE does not always correlate with sample size —the SE depends on both the number of individuals in the study and the distribution of these indi-viduals across exposure and disease categories. For ALL, no study contributed more than 34% of the total weight for long-term breastfeeding or more than 32% of the total weight for short-term breastfeeding. For AML, the UKCCS 19 con-tributed 74% of the total weight for long-term breastfeeding and 70% of the total weight for short-term breastfeeding.Removal of this study from the AML analysis resulted in an OR of 0.73 (95% CI 0.55, 0.97) for long-term breastfeeding and an OR of 0.91 (95% CI 0.73, 1.15) for short-term breast-feeding. Thus, exclusion of this study produced a moderate decrease in the combined OR and a wider CI for long-term breastfeeding, and essentially no change in the combined OR and a wider CI for short-term breastfeeding.

DISCUSSION

This meta-analysis supports the hypothesis that short- and long-term breastfeeding play a protective role with regard to the risk for ALL. In addition —and not anticipated on bio-logical grounds —the results show that long-term breast-feeding is also protective against AML. However, while the

Figure 1. Funnel graph to assess publication bias in studies of association between breastfeeding >6 months and risk of childhood ALL (n =14 studies)

ALL ? acute lymphoblastic leukemia

Standard error of odds ratio

1.5

1.0

0.5

Odds ratio

0.2

0.4

classi ?cation of ALL was fairly uniform across studies, the AML category was more variable. The variability in AML classi ?cation could lead to misclassi ?cation of the outcome and subsequent spurious associations. Furthermore, inclu-sion of SE S as a potential confounder had minimal in ?u-ence on the risk estimates for both short-term and long-term breastfeeding for ALL and AML. Before any general conclu-sions can be drawn, several issues must be considered: the results of the two largest case-control studies in the meta-analysis,19,24 the results of the two cohort studies,22,23 current knowledge regarding the etiology of ALL and AML, the relationship between SES and breastfeeding, and the effect of differential participation rates for case and control samples that differed in SES.

The UKCCS 19 and CCG study 24 were the two largest and/or most in ?uential studies in the meta-analysis. The UKCCS included 1,401 (87%) ALL and 214 (13%) AML case pa-tients recruited from health programs that enrolled 98% of the total UK population; control subjects were selected from population-based health rosters. In contrast, the CCG study included 1,744 (79%) ALL and 456 (21%) AML case pa-tients enrolled from speci ?c CCG centers, and control sub-jects were selected via random-digit-dialing (RDD). The use of RDD in control recruitment introduces a concern regard-ing unknown and possibly stronger SE S differentials be-tween cases and controls, a major issue when conducting a case-control study. Both studies found that long-term breast-

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feeding was protective for ALL, but the CI for the risk esti-mate from the UKCCS did not exclude unity (1.00), whereas the CI for the risk estimate reported by the CCG study clearly excluded unity (1.00), indicating statistical signi ?-cance. The UKCCS, however, found no association between short- or long-term breastfeeding and risk of AML, while the CCG study found a signi ?cant protective effect of long-term breastfeeding for AML. The UKCCS investigators were cautious in drawing conclusions due to a concern about systematic bias resulting from documented differences in participation between cases and controls. The CCG study investigators were less tenuous in their conclusion that the Table 2. Selected characteristics of 14 case-control studies included in the meta-analysis examining the association between breastfeeding and risk of childhood ALL, by duration of breastfeeding

Study

SES-adjusted

Number of cases (n )

OR 95% CI W i (%)Breastfeeding ?6 months van Duijn et al. 198810Yes 492 1.150.80, 1.6728.4 (6)Magnani et al. 198811Yes 142 1.100.74, 1.6424.3 (5)Davis et al. 198812No 520.510.23, 1.16 5.9 (1)Shu et al. 199513Yes 108 1.100.50, 2.50 5.9 (1)Schuz et al. 199915Yes 6820.830.63, 1.1147.9 (10)CCG study 199924

Yes 1,7440.860.73, 1.01145.8 (32)Dockerty et al. 199917Yes 97 1.240.47, 3.23 4.1 (1)Smulevich et al. 199925

No 1090.520.32, 0.8615.7 (3)Infante-Rivard et al. 200026Yes 4910.680.49, 0.9535.1 (8)UKCCS 200119

Yes 14010.850.60, 1.2032.0 (7)Hardell et al. 200120No 204 1.000.50, 2.008.0 (2)Perrillat et al. 20026Yes 218 1.100.70, 1.7019.5 (4)Kwan 200221

Yes 1470.870.43, 1.777.4 (2)Lancashire et al. 200330

Yes 9480.960.77, 1.2078.1 (17)Combined OR: SES-adjusted —6,4700.900.82, 0.99—Combined OR: not SES-adjusted —3650.620.43, 0.89—

Combined OR: all studies —6,8350.880.80, 0.97458.27 (100)Breastfeeding ?6 months van Duijn et al. 198810Yes 4920.830.48, 1.4312.9 (4)Magnani et al. 198811Yes 142 1.060.54, 2.088.4 (3)Davis et al. 198812No 520.680.32, 1.47 6.6 (2)Shu et al. 199513Yes 108 1.120.60, 2.209.1 (3)Schuz et al. 199915Yes 6820.770.59, 1.0055.2 (17)CCG study 199924

Yes 1,7440.720.60, 0.87111.3 (34)Dockerty et al. 199917Yes 970.620.28, 1.38 6.0 (2)Smulevich et al. 199925

No 1090.760.47, 1.2216.9 (5)Infante-Rivard et al. 200026Yes 4910.670.47, 0.9432.0 (10)UKCCS 200119

Yes 1,4010.650.43, 1.0021.6 (7)Hardell et al. 200120No 2040.900.50, 1.809.4 (3)Perrillat et al. 20026Yes 2180.500.20, 1.10 5.3 (2)Kwan 200221

Yes 147 1.030.51, 2.087.3 (2)Lancashire et al. 200330

Yes 9480.900.60, 1.3423.8 (7)Combined OR: SES-adjusted —6,4700.750.67, 0.85—Combined OR: not SES-adjusted —3650.780.55, 1.10—

Combined OR: all studies

—

6,835

0.76

0.68, 0.84

326.27 (100)

ALL = acute lymphoblastic leukemia SES = socioeconomic status OR = odds ratio CI = con ?dence interval

W i = weight assigned to each odds ratio, de ?ned as the inverse square of its standard error

results of their study demonstrated lower risk of ALL and AML for breastfed infants, particularly those breastfed for more than six months.

Two large cohort studies have been published, one evalu-ating the association between breastfeeding and risk of child-hood cancer 22 and the other evaluating the association be-tween breastfeeding and risk of childhood ALL.23 The major advantage of cohort studies is that they are not subject to the same biases as case-control studies and can better assess the temporal relationship between exposure and disease. Murray et al. conducted a historical cohort study of 434,933 single-ton live births in Northern Ireland from 1971 through 1986.23

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Cases of ALL were identi ?ed through the Northern Ireland Child Health System and Northern Ireland Cancer Registry ’s Register of Childhood Cancers. No statistically signi ?cant difference was found for ever vs. never breastfeeding (OR=0.98; 95% CI 0.68, 1.42) for ALL. Golding et al. conducted a national cohort study of 16,193 infants delivered in one week of April 1970 in Great Britain, following them until 1980.22 Thirty-three cancer cases, nine of which were leuke-mia cases, were identi ?ed from death certi ?cates, through the Cancer Registration system, or from follow-up interviews conducted at ages 5 and 10 years. No childhood cancer data are presented by the investigators, but breastfeeding was reported to not be protective for childhood cancer. Although the Golding et al. study is not as informative as the study by Murray et al., these cohort studies indicate the lack of a protective effect of breastfeeding on risk of childhood ALL or childhood cancer.

The observation of a protective effect of breastfeeding for both ALL and AML in our analyses raises questions about the classi ?cation of leukemia cases in the two sub-groups as well as the underlying biological mechanism involved. First, four studies included in this meta-analysis speci ?ed ANLL or “other leukemias ” rather than AML ex-Table 3. Selected characteristics of 8 case-control studies included in the meta-analysis examining association between breastfeeding and risk of childhood AML, by duration of breastfeeding

Study

SES-adjusted

Number of cases (n )

OR 95% CI W i (%)Breastfeeding ?6 months Davis et al. 198812No 11 1.120.25, 5.00 1.7 (1)Shu et al. 199513Yes 51 1.650.50, 5.60 2.6 (1)CCG study 199924Yes 4560.950.68, 1.3334.1 (14)UKCCS 200119

Yes 2140.900.77, 1.04170.1 (70)Hardell et al. 200120No 260.200.10, 2.00 1.7 (1)Perrillat et al. 20026Yes 28 1.300.50, 3.60 3.9 (2)Kwan 200221

Yes 360.290.06, 1.54 1.5 (1)Lancashire et al. 200330

Yes 3940.900.62, 1.3127.5 (11)Combined OR: SES-adjusted —1,1790.910.80, 1.04—Combined OR: not SES-adjusted —370.470.16, 1.36—

Combined OR: all studies —1,2160.900.80, 1.02243.14 (100)Breastfeeding ?6 months Davis et al. 198812No 11 1.920.45, 8.33 1.8 (1)Shu et al. 199513Yes 51 1.210.50, 3.30 4.3 (2)CCG study 199924Yes 4560.570.39, 0.8426.1 (14)UKCCS 200119

Yes 2140.890.75, 1.05135.7 (74)Hardell et al. 200120No 260.300.10, 3.20 1.3 (1)Perrillat et al. 20026Yes 280.600.10, 2.90 1.4 (1)Kwan 200221

Yes 360.380.08, 1.93 1.5 (1)Lancashire et al. 200330

Yes 3940.850.73, 0.9810.8 (6)Combined OR: SES-adjusted —1,1790.850.73, 0.98—Combined OR: not SES-adjusted —370.890.29, 2.71—

Combined OR: all studies

—

1,216

0.85

0.73, 0.98

182.90 (100)

AML = acute myeloblastic leukemia SES = socioeconomic status OR = odds ratio CI = con ?dence interval

W i = weight assigned to each odds ratio, de ?ned as the inverse square of its standard error

plicitly.6,12,13,30 Therefore, this group of leukemias might not be as homogeneous as the ALL group, thus constraining inferences regarding AML and breastfeeding. Second,Greaves ’s hypothesis of an abnormal immunological response leading to presentation with childhood leukemia is speci ?c for the natural history of c-ALL. ALL and AML have differ-ent cell origins: childhood ALL arises from lymphoid stem cells while childhood AML arises from myeloid stem cells.46If breastfeeding modulates the immune response via B-cell precursors, as the Greaves hypothesis suggests, then the pro-tective effect observed for AML is unexpected. Our results imply that a separate immunological mechanism is operat-ing via myeloid precursors along with the mechanism sug-gested by Greaves.

It is recognized that higher SE S mothers have higher rates of breastfeeding than lower SE S mothers, and this pattern has been stable over the past two decades.47,48 Higher SES mothers tend to retrospectively recall longer periods of breastfeeding than lower SES mothers.49 Variations in breast-feeding practices may re ?ect differences in education, a measure of SES. If the mother is better educated about the bene ?ts of breast milk, she may be more inclined to breastfeed her child.28 In addition, lower SES mothers may

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qualify for government food support programs that can help pay for infant formula, and the availability of food assistance for the family may deter the mother from breastfeeding her infant children.50

Finally, the roles of SE S and participation bias can be assessed in this body of literature. In both the UKCCS 19 and CCG study,24 the control subjects were of higher SES than the case patients. Even though SES was adjusted for in both of these studies (the UKCCS adjusted for a deprivation in-dex, and the CCG study adjusted for maternal education and family annual income), this factor could have intro-duced some residual bias. The most important consider-ation is the representativeness of the controls relative to the base population from which the cases arise. This can best be assessed with the population-based design of studies such as the UKCCS.

The effect of differential participation rates between cases and controls on the overall results is important to consider.For example, when the UKCCS analysis was published,19 the authors cited a meta-analysis that demonstrated a protective role of breastfeeding with respect to risk of diabetes melli-tus; however, the controls had higher participation rates than the cases.51 In the current meta-analysis, participation rates 52 could be calculated for only six of the 14 included studies.10,15,19–21,26 For ?ve of these six studies,10,15,19,21,26 the participation rates for cases were higher than those for con-trols, and in most of these studies, the controls were of

Figure 2. Odds ratios (ORs) and 95% con?dence intervals (CIs) in studies of association between breastfeeding >6 months and risk of childhood ALL (n =14 studies)

ALL ? acute lymphoblastic leukemia

van Duijn 198810Magnami 198811

Davis 198812Shu 199513Schuz 199915

CCG study 199924

Dockerty 199917Smulevich 199925Infante-Rivard 200026

UKCCS 200219Hardell 200120Perrillat 20026Kwan 200221

Lancashire 200330

Combined

0.1

1.010.0

Combined OR ?0.76(95% CI 0.68. 0.84)

Table 4. SES-adjusted risk of ALL and AML,by duration of breastfeeding: meta-analysis,UKCCS,19 and CCG study 24

OR (95%CI)

Duration of breastfeeding ALL AML Meta-analysis n ?6,470 (85%)n ?1,179 (15%)?6 months 0.90 (0.82, 0.99)0.91 (0.80, 1.04)?6 months 0.75 (0.67, 0.85)0.85 (0.73, 0.98)UKCCS 200119

n ?1,401 (87%)n ?214 (13%)?6 months 0.85 (0.60, 1.20)0.90 (0.77, 1.04)?6 months 0.65 (0.43, 1.00)0.89 (0.75, 1.05)CCG study 199924

n ?1,744 (79%)n ?456 (21%)?6 months 0.86 (0.73, 1.01)0.95 (0.68, 1.33)?6 months

0.72 (0.60, 0.87)

0.57 (0.39, 0.84)

SES = socioeconomic status ALL = acute lymphoblastic leukemia AML = acute myeloblastic leukemia

UKCCS = United Kingdom Childhood Cancer Study CCG = Children ’s Cancer Group OR = odds ratio CI = con ?dence interval

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higher SE S than the cases. Therefore, the association of breastfeeding with SES in combination with differential par-ticipation rates by SES could have biased the OR toward a protective effect.

This meta-analysis demonstrated a protective association between breastfeeding and risk of childhood ALL and possi-bly AML. Three alternative explanations must be consid-ered. First, a systematic bias may be present in case-control studies of childhood leukemia arising from differential par-ticipation rates for case and control samples that differed in SE S. Second, the effect on ALL risk may be spurious, as suggested by the results of the two cohort studies;22,23 unfor-tunately, these studies provided no information regarding AML. Third, the protective effect of breastfeeding may not be limited to ALL, as predicted by the Greaves hypothesis;however, support for a different underlying mechanism for AML would rely on an accurate and homogeneous category of AML cases. Further evaluation of the biological mecha-nisms while taking into consideration potential biases can be feasibly achieved with more large-scale case-control stud-ies utilizing population-based, SES-matched controls.

In conclusion, the potential protective effect of breast-feeding on risk of childhood ALL may be more complicated than the current literature suggests. Nevertheless, the avail-able evidence suggests that such a protective effect exists for both ALL and AML, with the caveats noted.

Figure 3. Odds ratios (ORs) and 95% con ?dence intervals (CIs) in studies of association between breastfeeding >6 months and risk of childhood AML (n =8 studies)

AML ? acute myeloblastic leukemia

0.1

1.010.0

Davis 198812Shu 199513CCG 199924UKCCS 200119Hardell 200120Perrillat 20026Kwan 200221

Lancashire 200330

Combined

Combined OR ?0.85(95% CI 0.73. 0.98)

This study was supported by research grants from the National Institute of Environmental Health Sciences (PS42 ES04705 and R01 ES09137). The authors thank Craig Steinmaus, MD, MPH,for his guidance on the conduct of meta-analyses.

Author note: This meta-analysis does not include the study by Jourdan-Da Silva et al. (Jourdan-Da Silva, N., et al. Infectious diseases in the first year of life, perinatal characteristics and childhood acute leukaemia. Br J Cancer 2004;90:139-45) since their study was released after this manuscript ’s original submission in 2003.The authors re-calculated the combined ORs with the Jourdan-Da Silva paper, and these results were virtually the same as the results cited in the meta-analysis: combined OR for ALL and breastfeeding ?6 months ?0.89; 95% CI 0.82, 0.97; combined OR for ALL and breastfeeding ?6 months ?0.76; 95% CI 0.69,0.85; combined OR for AML and breastfeeding ?6 months ?0.91;95% CI 0.80, 1.03; combined OR for AML and breastfeeding ?6 months ?0.85; 95% CI 0.73, 0.98.

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