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. Author manuscript; available in PMC: 2017 Sep 15.
Published in final edited form as: Cancer. 2016 Jun 28;122(18):2867–2875. doi: 10.1002/cncr.30129

Childhood Leukemia Incidence in California: High and Rising in the Hispanic Population

Brenda M Giddings 1, Todd P Whitehead 2,3, Catherine Metayer 3,4, Mark D Miller 3,5
PMCID: PMC5542672  NIHMSID: NIHMS872801  PMID: 27351365

Abstract

Background

High rates of childhood leukemia incidence have been reported in Latin America and among Hispanic children in the United States. California’s large Hispanic population affords an important opportunity to perform a detailed analysis of the leukemia burden among Hispanic children.

Methods

Leukemias diagnosed among non-Hispanic white (NHW), Hispanic, African American (AA), and Asian/Pacific Islander (API) children, aged 0 to 19 years, between January 1, 1990 and December 31, 2012 were obtained from the California Cancer Registry (n=11,084). Age-adjusted incidence rates (AAIR), standardized rate ratios (SRR), and secular trends in incidence (annual percent change [APC]) were analyzed by subtype, race/ethnicity, sex, and age.

Results

Compared to NHWs, acute lymphoblastic leukemia (ALL) incidence was higher among Hispanics (SRR=1.32) and lower among AAs (SRR=0.55) and APIs (SRR=0.91). From 1990 to 2012, ALL incidence increased overall (APC=1.1%), among males (APC=1.0%), females (APC=1.3%), Hispanics (APC=1.1%), AAs (APC=1.9%), AA males (APC=2.8%), API males (APC=1.9%), and Hispanic females (APC=1.5%). ALL increased among Hispanic males aged 15 to 19 years (APC=2.5%) and Hispanic females aged 0 to 4 and 15 to 19 years (APC=2.2% and 1.9%, respectively). Acute myeloid leukemia (AML) incidence did not differ among racial/ethnic groups. From 1990 to 2012, overall AML incidence remained stable but increased among Hispanics (APC=1.2%), females (APC=1.0%), Hispanic females (APC=2.3%), and Hispanic females aged 15 to 19 years (APC=3.4%).

Conclusions

Notable differences in childhood leukemia incidence among four racial/ethnic groups in California were observed. Factors which may contribute to these differences include differential exposure to carcinogens and/or genetic susceptibility.

Keywords: leukemia, children, Hispanic, incidence, trends, epidemiology

INTRODUCTION

Worldwide, leukemia is the most common cancer diagnosed among children with acute lymphoblastic leukemia (ALL) occurring most frequently followed by acute myeloid leukemia (AML).1, 2 Childhood leukemia incidence differs with respect to subtype, race/ethnicity, sex, age, and geographic region.19 Males have a higher risk of developing ALL than females and children aged 0 to 4 years have a higher risk than children aged 5 to 19 years. For AML, males have a slightly higher risk of developing the disease than females and incidence peaks in infancy. The highest incidence rates of childhood ALL have been observed in Costa Rica, Ecuador, Mexico City, and among Hispanics in the United States, and the lowest incidence rates observed in Africa and among African Americans in the United States. The highest incidence rates of childhood AML have been observed in the Philippines and Korea, and the lowest incidence rates observed in Africa.2, 6, 7, 1013

In the United States, approximately 3,800 children are diagnosed with ALL or AML each year.14 From 1975 to 2012, the incidence of ALL and AML among children aged 0 to 19 years increased significantly by 0.8% per year and 1.1% per year, respectively. During this time period, the percent change in the age-adjusted incidence rate was 54.9% for ALL and 55.9% for AML.15

Our study examined incidence rates and trends of leukemia among children aged 0 to 19 years in California by subtype, race/ethnicity, sex, and age. Given that high rates of childhood leukemia have been reported among Hispanics in the United States and internationally, California’s large Hispanic population affords an important opportunity to examine the leukemia burden among Hispanic children.

MATERIALS & METHODS

Cases were identified using the California Cancer Registry (CCR). The CCR is a population-based registry which has been collecting information on new cancers diagnosed among California residents since 1988. The CCR follows standardized data collection and quality control procedures and has consistently met the standards for data quality and completeness set by the North American Association of Central Cancer Registries.1623

Cases of leukemia diagnosed among non-Hispanic white (NHW), Hispanic, non-Hispanic black (hereafter referred to as African American [AA]), and Asian/Pacific Islander (API) children aged 0 to 19 years during the time period January 1, 1990 to December 31, 2012 were included in this study. Subtypes of leukemia were defined according to the Surveillance, Epidemiology, and End Results program’s International Classification of Childhood Cancer (ICCC) Recode ICD-O-3/WHO 2008 definition.15 This definition groups acute lymphoblastic leukemia (ALL) into a single group with other lymphoid leukemias; however, ALL makes up the vast majority (approximately 99 percent) of lymphoid leukemias diagnosed in children.4 Therefore, the term ALL is used throughout this paper. Cases that were not microscopically confirmed (n=68, 0.6%) or were not the first primary tumor (n=161, 1.4%) were excluded.

Information on the race/ethnicity of patients in the CCR is based primarily on information obtained from the medical record. This information may be based on self-report or by assumptions made by medical personnel. Additionally, the CCR utilizes various methods to enhance the identification of a patient’s race/ethnicity and may infer this information based on birthplace, maiden name, surname, or the parents’ race/ethnicity.16 If more than one race was reported for a patient, only the primary race was used. In this study, patients with Hispanic ethnicity were not further categorized by race, whereas non-Hispanic patients were categorized as white, African American, or Asian/Pacific Islander.

The distribution of leukemia cases by subtype, sex, and age among the four racial/ethnic groups was compared by use of chi-square tests. SEER*Stat software from the National Cancer Institute was used to calculate incidence rates and rate ratios.24 Population estimates for California by race/ethnicity, sex, and age were obtained from the National Center for Health Statistics.2527 All rates were age-adjusted to the 2000 U.S. Standard Population using the direct method of standardization and were calculated per 1,000,000 persons.

Trends in the age-adjusted incidence rates (AAIR) were analyzed using JoinPoint Regression Program software from the National Cancer Institute.28 The JoinPoint regression model fits a series of joined straight lines (i.e., trends) to the AAIR on a logarithmic scale. The slope of each line segment describes the annual percentage change (APC) in the AAIR (and 95% confidence interval [CI]), and line segments are connected by “joinpoints” that denote a statistically significant change in trend (p < 0.05).15 We allowed a minimum of zero joinpoints for each model. The maximum number of joinpoints for each model was based on the Joinpoint software’s algorithmic recommendations based on the number of data points. If the model had 23 data points the maximum number of joinpoints allowed was four. If the model had 11 data points the maximum number of joinpoints allowed was one. In most instances, the optimal model had zero joinpoints. Due to the small number of AML cases in race/ethnicity, sex, and age strata, APCs were calculated by combining cases diagnosed in two-year periods (except for the three-year period from 1990 to 1992) in order to provide stable estimates.

RESULTS

From 1990 to 2012, a total of 11,084 incident cases of leukemia were diagnosed among NHW (n=3,699), Hispanic (n=5,803), AA (n=497) and API (n=1,085) children. In each racial/ethnic group, ALL was the most frequent. However, AA children had a larger proportion of AML cases (27.0%) compared to the other groups. Overall, each racial/ethnic group had a larger proportion of cases diagnosed among males and, with the exception of AAs, cases were more frequently diagnosed among 0 to 4 year olds (Table 1).

Table 1.

Characteristics of childhood leukemia cases by race/ethnicity, California, 1990–2012 (n=11,084)

Variable NHW Hispanic AA API
(n=3,699) (n=5,803) (n=497) (n=1,085)

n % n % n % n %
Subtype*
  ALL 2,861 77.3 4,711 81.2 324 65.2 780 71.9
  AML 657 17.8 852 14.7 134 27.0 227 20.9
  Other 181 4.9 240 4.1 39 7.8 78 7.2
Sex
  Male 2,110 57.0 3,269 56.3 280 56.3 620 57.1
  Female 1,589 43.0 2,534 43.7 217 43.7 465 42.9
Age at Diagnosis*
  0 to 4 years 1,707 46.1 2,574 44.4 172 34.6 516 47.6
  5 to 9 years 861 23.3 1,325 22.8 128 25.8 236 21.8
  10 to 14 years 560 15.1 971 16.7 116 23.3 165 15.2
  15 to 19 years 571 15.4 933 16.1 81 16.3 168 15.5
*

p is ≤ 0.01

Compared to NHW children, the annual average age-adjusted incidence rate (AAIR) of all leukemias combined was significantly higher among Hispanic children (43.5 and 55.0, respectively; SRR=1.26, p≤0.01) and significantly lower among AA children (43.5 and 28.5 respectively; SRR=0.65, p≤0.01) (Table 2). The incidence among API children was close to that of NHW children. Similarly, compared to NHWs, childhood ALL was higher among Hispanics (33.7 and 44.5, respectively; SRR=1.32, p≤0.01) and lower among AAs (33.7 and 18.5, respectively; SRR=0.55, p≤0.01) and APIs (33.7 and 30.6, respectively; SRR=0.91, p=0.02). Results for all leukemias combined and ALL were similar for males and females (Table 2).

Table 2.

AAIRs and SRRs for leukemias diagnosed among Hispanic, AA, and API children compared to NHW children, California, 1990 to 2012

Subtype and
Racial/Ethnic
Group
Both Sexes
Male
Female
AAIR SRR (95% CI) Ratio
P-Value
AAIR SRR (95% CI) Ratio
P-Value
AAIR SRR (95% CI) Ratio
P-Value



Leukemias (all combined)
  NHW 43.5 48.3 38.5
  Hispanic 55.0 1.26 (1.21 – 1.32) ≤ 0.01 60.6 1.25 (1.19 – 1.32) ≤ 0.01 49.1 1.28 (1.20 – 1.36) ≤ 0.01
  AA 28.5 0.65 (0.60 – 0.72) ≤ 0.01 31.5 0.65 (0.57 – 0.74) ≤ 0.01 25.4 0.66 (0.57 – 0.76) ≤ 0.01
  API 42.4 0.97 (0.91 – 1.04) 0.46 47.1 0.97 (0.89 – 1.07) 0.59 37.5 0.97 (0.88 – 1.08) 0.64
ALL
  NHW 33.7 38.0 29.1
  Hispanic 44.5 1.32 (1.26 – 1.39) ≤ 0.01 49.5 1.30 (1.23 – 1.39) ≤ 0.01 39.2 1.35 (1.25 – 1.45) ≤ 0.01
  AA 18.5 0.55 (0.49 – 0.62) ≤ 0.01 20.7 0.54 (0.46 – 0.63) ≤ 0.01 16.4 0.56 (0.47 – 0.67) ≤ 0.01
  API 30.6 0.91 (0.84 – 0.98) 0.02 34.2 0.90 (0.81 – 1.00) 0.05 26.7 0.92 (0.81 – 1.04) 0.17
AML
  NHW 7.7 8.0 7.4
  Hispanic 8.2 1.06 (0.95 – 1.17) 0.29 8.5 1.06 (0.92 – 1.22) 0.43 7.9 1.05 (0.91 – 1.23) 0.51
  AA 7.7 1.00 (0.82 – 1.20) > 0.99 7.8 0.97 (0.74 – 1.26) 0.89 7.7 1.03 (0.77 – 1.35) 0.89
  API 8.8 1.14 (0.98 – 1.33) 0.10 8.8 1.10 (0.89 – 1.36) 0.39 8.8 1.18 (0.94 – 1.48) 0.14
Other Subtypes
  NHW 2.1 2.4 1.9
  Hispanic 2.3 1.08 (0.89 – 1.32) 0.46 2.6 1.09 (0.84 – 1.42) 0.55 2.0 1.07 (0.79 – 1.45) 0.72
  AA 2.3 1.06 (0.73 – 1.50) 0.81 3.1 1.29 (0.81 – 1.99) 0.28 1.4 0.75 (0.37 – 1.38) 0.43
  API 3.0 1.42 (1.07 – 1.86) ≤ 0.01 4.1 1.72 ( 1.21 – 2.41) ≤ 0.01 1.9 1.02 (0.62 – 1.64) > 0.99

Rates are per 1,000,000 and age-adjusted to the 2000 U.S. Standard Population.

Note: Boldface indicates statistical significance (p < 0.05).

For AML, the AAIR did not significantly differ by race/ethnicity and sex. For other leukemia subtypes, API children had a significantly higher incidence compared to NHW children (3.0 versus 2.1; SRR=1.42, p≤0.01), especially for males (4.1 versus 2.4; SRR=1.72, p≤0.01; see Table 2).

Trends in ALL

From 1990 to 2012, the incidence of childhood ALL increased significantly overall (APC=1.1%, p≤0.01), among males (APC=1.0%, p≤0.01) and females (APC=1.3%, p≤0.01), as well as among Hispanics (APC=1.1%, p≤0.01) and AAs (APC=1.9%, p=0.03). ALL also increased significantly from 1990 to 2012 among AA males (APC=2.8%, p≤0.01), API males (APC=1.9%, p=0.04), and Hispanic females (APC=1.5%, p≤0.01) (Table 3).

Table 3.

Trend (APC) in the AAIR of childhood leukemia by subtype, race/ethnicity, and sex, California, 1990–2012

Sex Race/Ethnicity Time Period APC 95% CI P-Value
ALL
Both Sexes All Racial/Ethnic Groups* 1990–2012 1.1 0.8 – 1.5 ≤ 0.01
NHW 1990–2012 0.5 −0.1 – 1.1 0.10
Hispanic 1990–2012 1.1 0.5 – 1.7 ≤ 0.01
AA 1990–2012 1.9 0.2 – 3.7 0.03
API 1990–2012 1.2 −0.2 – 2.7 0.09
Male All Racial/Ethnic Groups* 1990–2012 1.0 0.5 – 1.5 ≤ 0.01
NHW 1990–2012 0.5 −0.4 – 1.4 0.26
Hispanic 1990–1992 25.0 −2.7 – 60.5 0.08
1992–2012 0.1 −0.6 – 0.8 0.72
AA 1990–2012 2.8 0.8 – 5.0 ≤ 0.01
API 1990–2012 1.9 0.1 – 3.7 0.04
Female All Racial/Ethnic Groups* 1990–2012 1.3 0.7 – 1.8 ≤ 0.01
NHW 1990–2012 0.5 −0.5 – 1.5 0.30
Hispanic 1990–2012 1.5 0.9 – 2.2 ≤ 0.01
AA 1990–2012 1.1 −2.1 – 4.4 0.48
API 1990–2012 0.5 −1.6 – 2.7 0.61
AML
Both Sexes All Racial/Ethnic Groups* 1990–2012 0.6 −0.1 – 1.3 0.09
NHW 1990–2012 0.5 −1.1 – 2.1 0.51
Hispanic 1990–2012 1.2 0.6 – 1.8 ≤ 0.01
AA 1990–2012 −0.7 −3.1 – 1.8 0.55
API 1990–2012 −1.0 −3.2 – 1.2 0.31
Male All Racial/Ethnic Groups* 1990–2012 0.2 −0.9 – 1.2 0.71
NHW 1990–2012 0.4 −1.4 – 2.3 0.62
Hispanic 1990–2012 0.3 −1.1 – 1.8 0.64
AA 1990–2012 −0.5 −3.3 – 2.4 0.71
API 1990–1996 −11.7 −23.4 – 1.7 0.07
1996–2012 0.2 −2.1 – 2.5 0.84
Female All Racial/Ethnic Groups* 1990–2012 1.0 0.3 – 1.8 ≤ 0.01
NHW 1990–2012 0.6 −1.6 – 2.9 0.55
Hispanic 1990–2012 2.3 0.9 – 3.8 ≤ 0.01
AA 1990–2012 −0.7 −5.7 – 4.5 0.75
API 1990–2012 0.1 −4.3 – 4.6 0.98
*

Includes children of other and unknown races.

Note: Boldface indicates statistical significance (p < 0.05).

In analyses further stratified by age, ALL incidence increased significantly from 1990 to 2012 among Hispanic males aged 15 to 19 years (APC=2.5%, p≤0.01) as well as among Hispanic females aged 0 to 4 years (APC=2.2%, p≤0.01) and 15 to 19 years (APC=1.9%, p=0.05). On the contrary, ALL incidence remained stable among NHW males and females in all age groups except for NHW females aged 15 to 19 years for whom ALL incidence decreased significantly from 2007 to 2012 (APC= −27.3%, p=0.02) (Table 4). Sex- and age- stratified trends could not be calculated for AA and API children due to small sample size.

Table 4.

Trend (APC) in the AAIR of childhood leukemia by subtype, race/ethnicity, sex, and age, California, 1990–2012

Race/Ethnicity Sex Age (years) Time Period APC 95% CI P-Value
ALL
Overall* Both 0 to 19 1990–2012 1.1 0.8 – 1.5 ≤ 0.01
NHW Male 0 to 4 1990–2012 1.2 −0.2 – 2.7 0.09
5 to 9 1990–2012 0.9 −1.0 – 2.9 0.35
10 to 14 1990–2012 −1.9 −4.0 – 0.2 0.07
15 to 19 1990–2012 −0.6 −3.1 – 2.0 0.62
Female 0 to 4 1990–2012 0.8 −0.5 – 2.1 0.23
5 to 9 1990–2012 0.9 −1.0 – 2.9 0.35
10 to 14 1990–2012 0.1 −2.9 – 3.1 0.96
15 to 19 1990–2007 0.2 −3.9 – 4.5 0.92
2007–2012 −27.3 −44.4 – −5.0 0.02
Hispanic Male 0 to 4 1990–2012 −0.1 −0.9 – 0.7 0.87
5 to 9 1990–2012 0.7 −0.3 – 1.7 0.15
10 to 14 1990–1992 109.8 −2.7 – 352.6 0.06
1992–2012 −0.2 −2.3 – 1.9 0.85
15 to 19 1990–2012 2.5 0.7 – 4.2 ≤ 0.01
Female 0 to 4 1990–2012 2.2 1.3 – 3.1 ≤ 0.01
5 to 9 1990–2012 0.6 −1.0 – 2.1 0.46
10 to 14 1990–2012 1.4 −0.2 – 3.0 0.09
15 to 19 1990–2012 1.9 0.03 – 3.8 0.05
AML
Overall* Both 0 to 19 1990–2012 0.6 −0.1 – 1.3 0.09
NHW Male 0 to 4 1990–2012 2.1 −1.4 – 5.8 0.21
5 to 9 1990–2012 ~ ~ ~
10 to 14 1990–2012 −1.1 −5.2 – 3.1 0.56
15 to 19 1990–2012 0.1 −2.5 – 2.8 0.91
Female 0 to 4 1990–1998 −8.7 −22.0 – 6.9 0.21
1998–2012 6.3 0.8 – 12.1 0.03
5 to 9 1990–2012 1.0 −6.5 – 9.0 0.78
10 to 14 1990–2012 ~ ~ ~
15 to 19 1990–2012 0.1 −4.1 – 4.5 0.94
Hispanic Male 0 to 4 1990–2012 1.9 −0.4 – 4.2 0.10
5 to 9 1990–2012 −3.1 −7.4 – 1.5 0.16
10 to 14 1990–2012 2.1 −2.2 – 6.5 0.30
15 to 19 1990–2012 −0.8 −3.2 – 1.7 0.50
Female 0 to 4 1990–2004 7.0 3.4 – 10.7 ≤ 0.01
2004–2012 −2.9 −9.3 – 4.0 0.33
5 to 9 1990–2012 0.8 −5.0 – 6.8 0.78
10 to 14 1990–1996 24.8 −6.0 – 65.7 0.10
1996–2012 −1.7 −6.2 – 2.9 0.39
15 to 19 1990–2012 3.4 0.3 – 6.6 0.03
*

Includes children of all racial/ethnic groups including unknown.

Note: Boldface indicates statistical significance (p < 0.05).

~

The APC could not be calculated due to zero counts in one or more cell.

Trends in AML

From 1990 to 2012, the overall incidence of AML remained stable (APC=0.6%, p=0.09). However, AML incidence increased significantly among females (APC=1.0%, p≤0.01) and Hispanics (APC=1.2%, p≤0.01), particularly among Hispanic females (APC=2.3%, p≤0.01).

In analyses further stratified by age, AML incidence among Hispanic female children aged 0 to 4 years increased significantly between 1990 and 2004 (APC=7.0%, p≤0.01) and then decreased between 2004 and 2012 (APC= −2.9%, p=0.33). However, this decrease was not statistically significant. From 1990 to 2012, AML incidence significantly increased among Hispanic female children aged 15 to 19 years (APC=3.4%, p=0.03) and also increased among NHW females aged 0 to 4 years from 1998 to 2012 (APC=6.3%, p=0.03) (Table 4).

DISCUSSION

In this study, Hispanic children had significantly higher incidence of ALL than NHW children, whereas AA and API children had significantly lower incidence. These findings are consistent with previously published studies of children in the United States.8, 9, 2932 The observed differences in childhood ALL incidence by race/ethnicity may reflect underlying differences in genetic susceptibility by race/ethnicity. Genome-wide association studies have identified several single nucleotide polymorphisms associated with ALL, which have higher risk allele frequencies in Hispanics compared to NHWs and AAs, partially explaining the higher risk of ALL in Hispanic children.33, 34 Similarly, candidate gene studies have identified ethnic differences in risk associated with gene variants in several pathways.3538 However, only a handful of genetic risk factors for childhood ALL have been discovered, and the proportion of leukemia risk attributable to these known genetic variants is low.34, 3943 Moreover, while risk allele frequencies could change within the Hispanic population over long periods of time, genetic susceptibility is unlikely to explain the upward trends in childhood leukemia we observed over an evolutionarily short time period. A recent analysis of California Cancer Registry records from 1988 to 2012 found higher rates of leukemia in children of Hispanic mothers born in the U.S. (and mostly from Mexican descent), compared to children of non-U.S. born Hispanic mothers or children of NHW mothers.44 While this finding suggests a role for environmental factors in the observed elevated rates of leukemia for Hispanic children in California, characterizing the relative contribution of environmental, sociodemographic, and genetic factors to the racial/ethnic differences in childhood leukemia rates is complex and requires studies with detailed information on these factors.

A growing body of literature has linked numerous environmental hazards to an increased risk of developing childhood leukemia.1, 4551 For example, investigators from the California Childhood Leukemia Study (CCLS) have reported that dust concentrations of certain persistent organic pollutants (POPs), including congeners of polybrominated diphenyl ethers (PBDEs) and polychlorinated biphenyls (PCBs), were associated with an increased risk of ALL.52, 53 At the same time, the CCLS found that dust levels of certain POPs, including PBDEs, were higher in the homes of Hispanic children than in the homes of NHW children.52, 54 Interestingly, time trends in PBDE body burdens roughly parallel the observed increases in childhood leukemia incidence rates during the study period (1990–2012), as longitudinal studies suggest that levels of BDEs 47, 99, and 153 in blood from U.S. adults increased from the 1970s to the early 2000s, plateauing in the mid-2000s.55, 56

Investigators from the CCLS have also observed ethnic disparities in occupational exposures to putative childhood ALL risk factors, including pesticides and organic solvents. For example, among the fathers participating in the CCLS who were exposed to pesticides at the workplace, the vast majority was Hispanic (87%). Moreover, fathers occupationally exposed to pesticides were more likely to have a child diagnosed with ALL.57 Similarly, associations were observed between paternal exposure to organic solvents and childhood ALL for Hispanic fathers, but not for NHW fathers.58 Ethnic disparities in children’s exposure to chemicals at home, as well as ethnic disparities in their parents’ exposures to chemicals at work, may contribute to the higher burden of childhood leukemia in Hispanic children. A more complete evaluation of the role of specific environmental factors that disproportionally affect the Hispanic community in the increased risk of leukemia in Hispanic children is warranted.

To our knowledge, our study demonstrated for the first time that increasing trends in ALL and AML incidence among female children overall and among Hispanic children specifically, were primarily due to significant increases in Hispanic female incidence. There is not current literature to explain the trends for Hispanic female children identified here. In fact, though gender difference for childhood leukemia incidence has long been noted, with predominance among males, the basis for this remains largely unexplained.

When analyses were further stratified by age, significant increases in ALL incidence were observed among Hispanic males and females in the highest age group of 15 to 19 years. This could be due in part to prolonged and cumulative exposure to environmental carcinogens.

Despite having lower incidence, a significant increase in ALL was observed among AA children, particularly among males. The published literature regarding trends in ALL incidence among AA children in the United States provides inconsistent findings. A recent study by Siegel et al. reported an APC of 2.0% for lymphoid leukemia among non-Hispanic black children aged 0 to 19 years in the United States during the time period from 2001 to 2009, but this increase was not statistically significant.59 Similarly, Xie et al. reported a statistically significant APC of 2.2% for black males and a non-significant APC of 1.8% for black females, aged 0 to 19 years, from 1973 to 1998 in the SEER 9 regions of the United States.60 On the contrary, Linabery and Ross reported an APC of −2.1% for ALL among black children aged 0 to 19 years in the SEER 13 regions of the United States from 1992–2004 but this decrease was not statistically significant.61 Given the small number of cases of ALL diagnosed among AA children in California each year, our finding of an increasing trend in this population should be interpreted with caution, especially in the context of the inconsistent findings reported in the literature. Future studies should evaluate the trend of ALL incidence among AA children to see if a significant increase is replicated.

This study has some limitations that should be considered. Although California has a very large Hispanic population, mostly from Mexican origin (83%), Hispanics residing in California may not be representative of those living throughout the United States and thus our findings are not generalizable to all Hispanics.

Race/ethnicity of patients in the CCR is based primarily on information contained in the medical record. This information may be based on self-report by the patient (or the patient’s family), by assumptions made by medical personnel, or inferred by cancer registry personnel based on the patient’s birthplace or the race/ethnicity of the patient’s parents. How often race/ethnicity in the CCR is determined by self-report versus other means is unknown. As such, misclassification of race/ethnicity is known to exist in the CCR and can impact the accuracy of incidence rates.62 Several studies evaluating the quality of race and ethnicity in cancer registry data indicate high agreement for race and moderate agreement for Hispanic ethnicity between cancer registry and self-reported data.62, 63 Overall, the effect of such misclassification in this study was likely an underreporting of Hispanic ethnicity in the cancer registry, suggesting an underestimation of incidence rates among Hispanic children.

Imprecise population estimates also impact the accuracy of incidence rates. The Census strives to count every person living in the United States, regardless of immigration status; however, the estimated undercount of Hispanic children aged less than 18 years was 5.0% in 1990 and 2.1% in 2010.64, 65 An undercount of the Hispanic population would result in artificially high incidence rates for this group. However, given that the incidence of childhood leukemia among Hispanics has increased while the undercount of Hispanic children by the Census has decreased, it is unlikely that the observed increase in incidence among Hispanics can be explained by the undercount in the population estimates.

Socioeconomic status (SES) is associated with both childhood leukemia incidence and race/ethnicity. This study did not include information on SES because population estimates by SES are only available for Census years. Future studies should include information on SES to evaluate the effect modification on risk factors for childhood leukemia, particularly race/ethnicity.

In conclusion, ALL incidence was significantly higher among Hispanic children and significantly lower among AA and API children compared to NHWs. Furthermore, ALL and AML incidence significantly increased among Hispanic children, predominantly among Hispanic females, and remained stable among NHW children. There is some evidence to suggest that racial/ethnic differences in childhood ALL incidence reflect differences in genetic susceptibility as well as differences in patterns of carcinogenic exposure between populations. However, more research on the underlying causes (environmental or others) of the disproportionate burden of leukemia in Hispanic children is warranted.

Acknowledgments

The collection of cancer incidence data used in this study was supported by the California Department of Public Health as part of the statewide cancer reporting program mandated by the California Health and Safety Code Section 103885; the National Cancer Institute’s Surveillance, Epidemiology and End Results Program under contracts awarded to the Cancer Prevention Institute of California, the University of Southern California, and the Public Health Institute; and the Centers for Disease Control and Prevention’s National Program of Cancer Registries, under agreement awarded to the California Department of Public Health. The ideas and opinions expressed herein are those of the author(s) and endorsement by the State of California, Department of Public Health, the National Cancer Institute, the Centers for Disease Control and Prevention, or their Contractors and Subcontractors is not intended nor should be inferred.

This publication was supported in part by the cooperative agreement award number 1 U61TS000237-01 from the Agency for Toxic Substances and Disease Registry (ATSDR). Its contents are the responsibility of the authors and do not necessarily represent the official views of ATSDR. The U.S. Environmental Protection Agency (EPA) supports the Pediatric Environmental Health Specialty Units (PEHSU) by providing partial funding to ATSDR under Inter-Agency Agreement number DW-75-95877701. Neither EPA nor ATSDR endorse the purchase of any commercial products or services mentioned in PEHSU publications.

This work was also supported in part by the National Institute of Environmental Health Sciences (NIEHS), USA (P01 ES018172 and P50ES018172) and the Environmental Protection Agency, USA (USEPA, RD83451101 and RD83615901), as part of the Center for Integrative Research on Childhood Leukemia and the Environment (CIRCLE). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIEHS or USEPA.

Footnotes

Brenda M. Giddings contributed to the design of the study, conducted the data analysis, interpreted the results, and wrote key sections of the manuscript. Ms. Giddings is the guarantor and is responsible for the overall content of the manuscript.

Dr. Todd Whitehead contributed to the design of the study, wrote key sections of the manuscript, and revised the manuscript for important intellectual content.

Dr. Catherine Metayer contributed to the design of the study and revised the manuscript for important intellectual content.

Dr. Mark Miller contributed to the conception and design of the study and revised the manuscript for important intellectual content.

This research project had no specific funding. There are no conflict of interest disclosures from any authors.

References

  • 1.Ross JA, Spector LG. Cancers in Children. In: Schottenfeld D, Fraumeni JF, editors. Cancer Epidemiology and Prevention. New York: Oxford University Press, Inc; 2006. pp. 1251–68. [Google Scholar]
  • 2.Parkin DM, Stiller CA, Draper GJ, Bieber CA. The international incidence of childhood cancer. Int J Cancer. 1988;42(4):511–20. doi: 10.1002/ijc.2910420408. [DOI] [PubMed] [Google Scholar]
  • 3.Eden T. Aetiology of childhood leukaemia. Cancer Treat Rev. 2010;36(4):286–97. doi: 10.1016/j.ctrv.2010.02.004. [DOI] [PubMed] [Google Scholar]
  • 4.Ries LAG, Smith MA, Gurney JG, et al. Cancer Incidence and Survival among Children and Adolescents: United States SEER Program 1975-1995. Bethesda, MD: National Cancer Institute; 1999. [Google Scholar]
  • 5.McNeil DE, Cote TR, Clegg L, Mauer A. SEER update of incidence and trends in pediatric malignancies: acute lymphoblastic leukemia. Med Pediatr Oncol. 2002;39(6):554–7. doi: 10.1002/mpo.10161. discussion 52-3. [DOI] [PubMed] [Google Scholar]
  • 6.Stiller CA, Parkin DM. Geographic and ethnic variations in the incidence of childhood cancer. Br Med Bull. 1996;52(4):682–703. doi: 10.1093/oxfordjournals.bmb.a011577. [DOI] [PubMed] [Google Scholar]
  • 7.Linet MS, Brown LM, Mbulaiteye SM, et al. International long-term trends and recent patterns in the incidence of leukemias and lymphomas among children and adolescents ages 0-19 years. Int J Cancer. 2016;138(8):1862–74. doi: 10.1002/ijc.29924. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Glazer ER, Perkins CI, Young JL, Schlag RD, Campleman SL, Wright WE. Cancer among Hispanic children in California, 1988-1994 - Comparison with non-Hispanic white children. Cancer. 1999;86(6):1070–79. [PubMed] [Google Scholar]
  • 9.Wilkinson JD, Fleming LE, MacKinnon J, et al. Lymphoma and lymphoid leukemia incidence in Florida children - Ethnic and racial distribution. Cancer. 2001;91(7):1402–08. doi: 10.1002/1097-0142(20010401)91:7<1402::aid-cncr1145>3.0.co;2-6. [DOI] [PubMed] [Google Scholar]
  • 10.Monge P, Wesseling C, Rodriguez AC, et al. Childhood leukaemia in Costa Rica, 1981-96. Paediatr Perinat Epidemiol. 2002;16(3):210–8. doi: 10.1046/j.1365-3016.2002.00422.x. [DOI] [PubMed] [Google Scholar]
  • 11.Perez-Saldivar ML, Fajardo-Gutierrez A, Bernaldez-Rios R, et al. Childhood acute leukemias are frequent in Mexico City: descriptive epidemiology. BMC Cancer. 2011:11. doi: 10.1186/1471-2407-11-355. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Fajardo-Gutierrez A, Juarez-Ocana S, Gonzalez-Miranda G, et al. Incidence of cancer in children residing in ten jurisdictions of the Mexican Republic: importance of the Cancer registry (a population-based study) BMC Cancer. 2007;7:68. doi: 10.1186/1471-2407-7-68. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Barrington-Trimis JL, Cockburn M, Metayer C, Gauderman WJ, Wiemels J, McKean-Cowdin R. Rising rates of acute lymphoblastic leukemia in Hispanic children: trends in incidence from 1992 to 2011. Blood. 2015;125(19):3033–4. doi: 10.1182/blood-2015-03-634006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Cancer Facts & Figures 2014. Atlanta, GA: American Cancer Society; 2014. [Google Scholar]
  • 15.Howlader N, Noone A, Krapcho M, et al. SEER Cancer Statistics Review, 1975-2012. Bethesda, MD: National Cancer Institute; 2015. [Google Scholar]
  • 16.California Cancer Reporting System Standards, Volume I: Abstracting and Coding Procedures for Hospitals. Fourteenth. Sacramento, CA: California Department of Public Health, Chronic Disease Surveillance and Research Branch; Feb, 2014. [Google Scholar]
  • 17.California Cancer Reporting System Standards for 2014, Volume II: Standards for Automated Reporting. Sacramento, CA: California Department of Public Health, Chronic Disease Surveillance and Research Branch; Dec, 2013. [Google Scholar]
  • 18.California Cancer Reporting System Standards, Volume III: Data Standards for Regional Registries and California Cancer Registry. Sacramento, CA: California Department of Public Health, Chronic Disease Surveillance and Research Branch; 2014. [Google Scholar]
  • 19.California Cancer Reporting System Standards, Volume IV: Physician Requirements for Cancer Reporting in California. Sacramento, CA: California Department of Public Health, Chronic Disease Surviellance and Research Branch; 2013. [Google Scholar]
  • 20.Havener LA. Standards for Cancer Registries, Volume I: Data Exchange Standards and Record Descriptions, Version 14. Springfield, IL: North American Association of Central Cancer Registries, Inc; 2013. [Google Scholar]
  • 21.Thornton ML. Standards for Cancer Registries Volume II: Data Standards and Data Dictionary, Record Layout Version 14. 18. Springfield, IL: North American Association of Central Cancer Registries, Inc; 2013. [Google Scholar]
  • 22.Hofferkamp J. Standards for Cancer Registries Volume III: Standards for Completeness, Quality, Analysis, Management, Security and Confidentiality of Data. Springfield, IL: North American Association of Central Cancer Registries, Inc; 2008. [Google Scholar]
  • 23.Klein WT, Havener LA. Standard for Cancer Registries, Volume V: Pathology Laboratory Electronic Reporting, Version 4.0. Springfield, IL: North American Association of Central Cancer Registries, Inc; 2011. [Google Scholar]
  • 24.Surveillance Research Program, National Cancer Institute. SEER*Stat Software, Version 8.2.1. Apr 7, 2015. [Google Scholar]
  • 25.National Center for Health Statistics. Bridged-race intercensal estimates of the July 1, 1990 - July 1, 1999, United States resident population by county, single-year of age, sex, race, and Hispanic origin. Prepared by the US Census Bureau with support from the National Cancer Institute. 2004 Jul 26; Available at: http://www.cdc.gov/nchs/nvss/bridged_race.htm.
  • 26.National Center for Health Statistics. Intercensal estimates of the resident population of the United States for July 1, 2000 - July 1, 2009, by year, county, single-year of age, bridged race, Hispanic origin, and sex. Prepared under a collaborative arrangement with the U.S. Census Bureau. 2012 Oct 26; Available from : http://www.cdc.gov/nchs/nvss/bridged_race.htm.
  • 27.National Center for Health Statistics. Postcensal estimates of the resident population of the United States for July 1, 2010 - July 1, 2012 by year, county, single-year of age, bridged race, Hispanic origin, and sex (Vintage 2012) Prepared under a collaborative arrangement with the U.S. Census Bureau. 2013 Jun 13; Available from http://www.cdc.gov/nchs/nvss/bridged_race.htm.
  • 28.Statistical Methodology and Applications Branch, National Cancer Institute. Joinpoint Regression Program software, Version 4.1.1. Aug, 2014. [Google Scholar]
  • 29.Matasar MJ, Ritchie EK, Consedine N, Magai C, Neugut AI. Incidence rates of the major leukemia subtypes among US Hispanics, Blacks, and non-Hispanic Whites. Leuk Lymphoma. 2006;47(11):2365–70. doi: 10.1080/10428190600799888. [DOI] [PubMed] [Google Scholar]
  • 30.Oksuzyan S, Crespi CM, Cockburn M, Mezei G, Vergara X, Kheifets L. Race/ethnicity and the risk of childhood leukaemia: a case-control study in California. J Epidemiol Community Health. 2015;69(8):795–802. doi: 10.1136/jech-2014-204975. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Okcu MF, Goodman KJ, Carozza SE, et al. Birth weight, ethnicity, and occurrence of cancer in children: a population-based, incident case-control study in the State of Texas, USA. Cancer Causes Control. 2002;13(7):595–602. doi: 10.1023/a:1019555912243. [DOI] [PubMed] [Google Scholar]
  • 32.Dores GM, Devesa SS, Curtis RE, Linet MS, Morton LM. Acute leukemia incidence and patient survival among children and adults in the United States, 2001-2007. Blood. 2012;119(1):34–43. doi: 10.1182/blood-2011-04-347872. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Walsh KM, Chokkalingam AP, Hsu LI, et al. Associations between genome-wide Native American ancestry, known risk alleles and B-cell ALL risk in Hispanic children. Leukemia. 2013;27(12):2416–19. doi: 10.1038/leu.2013.130. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Xu H, Yang WJ, Perez-Andreu V, et al. Novel Susceptibility Variants at 10p12.31-12.2 for Childhood Acute Lymphoblastic Leukemia in Ethnically Diverse Populations. J Natl Cancer Inst. 2013;105(10):733–42. doi: 10.1093/jnci/djt042. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Chokkalingam AP, Bartley K, Wiemels JL, et al. Haplotypes of DNA repair and cell cycle control genes, X-ray exposure, and risk of childhood acute lymphoblastic leukemia. Cancer Causes Control. 2011;22(12):1721–30. doi: 10.1007/s10552-011-9848-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Chokkalingam AP, Metayer C, Scelo G, et al. Fetal growth and body size genes and risk of childhood acute lymphoblastic leukemia. Cancer Causes Control. 2012;23(9):1577–85. doi: 10.1007/s10552-012-0035-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Chokkalingam AP, Metayer C, Scelo GA, et al. Variation in xenobiotic transport and metabolism genes, household chemical exposures, and risk of childhood acute lymphoblastic leukemia. Cancer Causes Control. 2012;23(8):1367–75. doi: 10.1007/s10552-012-9947-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Metayer C, Scelo G, Chokkalingam AP, et al. Genetic variants in the folate pathway and risk of childhood acute lymphoblastic leukemia. Cancer Causes Control. 2011;22(9):1243–58. doi: 10.1007/s10552-011-9795-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Migliorini G, Fiege B, Hosking FJ, et al. Variation at 10p12.2 and 10p14 influences risk of childhood B-cell acute lymphoblastic leukemia and phenotype. Blood. 2013;122(19):3298–307. doi: 10.1182/blood-2013-03-491316. [DOI] [PubMed] [Google Scholar]
  • 40.Papaemmanuil E, Hosking FJ, Vijayakrishnan J, et al. Loci on 7p12.2, 10q21.2 and 14q11.2 are associated with risk of childhood acute lymphoblastic leukemia. Nature Genetics. 2009;41(9):1006-U73. doi: 10.1038/ng.430. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Trevino LR, Yang WJ, French D, et al. Germline genomic variants associated with childhood acute lymphoblastic leukemia. Nature Genetics. 2009;41(9):1001-U67. doi: 10.1038/ng.432. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Perez-Andreu V, Roberts KG, Harvey RC, et al. Inherited GATA3 variants are associated with Ph-like childhood acute lymphoblastic leukemia and risk of relapse. Nature Genetics. 2013;45(12):1494-U127. doi: 10.1038/ng.2803. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Sherborne AL, Hosking FJ, Prasad RB, et al. Variation in CDKN2A at 9p21.3 influences childhood acute lymphoblastic leukemia risk. Nature Genetics. 2010;42(6):492–94. doi: 10.1038/ng.585. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Heck JE, Park AS, Contreras ZA, et al. Risk of Childhood Cancer by Maternal Birthplace: A Test of the Hispanic Paradox. JAMA Pediatr. 2016 Apr 25; doi: 10.1001/jamapediatrics.2016.0097. Advance online publication. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Bailey HD, Fritschi L, Infante-Rivard C, et al. Parental occupational pesticide exposure and the risk of childhood leukemia in the offspring: findings from the childhood leukemia international consortium. Int J Cancer. 2014;135(9):2157–72. doi: 10.1002/ijc.28854. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Milne E, Greenop KR, Scott RJ, et al. Parental prenatal smoking and risk of childhood acute lymphoblastic leukemia. Am J Epidemiol. 2012;175(1):43–53. doi: 10.1093/aje/kwr275. [DOI] [PubMed] [Google Scholar]
  • 47.Liu R, Zhang L, McHale CM, Hammond SK. Paternal smoking and risk of childhood acute lymphoblastic leukemia: systematic review and meta-analysis. J Oncol. 2011;2011:854584. doi: 10.1155/2011/854584. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Chang JS, Selvin S, Metayer C, Crouse V, Golembesky A, Buffler PA. Parental smoking and the risk of childhood leukemia. Am J Epidemiol. 2006;163(12):1091–100. doi: 10.1093/aje/kwj143. [DOI] [PubMed] [Google Scholar]
  • 49.Metayer C, Zhang L, Wiemels JL, et al. Tobacco smoke exposure and the risk of childhood acute lymphoblastic and myeloid leukemias by cytogenetic subtype. Cancer Epidemiol Biomarkers Prev. 2013;22(9):1600–11. doi: 10.1158/1055-9965.EPI-13-0350. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Boothe VL, Boehmer TK, Wendel AM, Yip FY. Residential traffic exposure and childhood leukemia: a systematic review and meta-analysis. Am J Prev Med. 2014;46(4):413–22. doi: 10.1016/j.amepre.2013.11.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51.Ekanayake R, Miller M, Marty M. Report to the Legislature, Children's Environmental Health Program. Sacramento, CA: Office of Environmental Health Hazard Assessment, California Environmental Protection Agency; 2014. [Google Scholar]
  • 52.Ward MH, Colt JS, Metayer C, et al. Residential exposure to polychlorinated biphenyls and organochlorine pesticides and risk of childhood leukemia. Environ Health Perspect. 2009;117(6):1007–13. doi: 10.1289/ehp.0900583. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53.Ward MH, Colt JS, Deziel NC, et al. Residential Levels of Polybrominated Diphenyl Ethers and Risk of Childhood Acute Lymphoblastic Leukemia in California. Environ Health Perspect. 2014;122(10):1110–16. doi: 10.1289/ehp.1307602. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54.Whitehead TP, Brown FR, Metayer C, et al. Polybrominated diphenyl ethers in residential dust: sources of variability. Environ Int. 2013:57–58. 11–24. doi: 10.1016/j.envint.2013.03.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55.Sjodin A, Jones RS, Focant JF, et al. Retrospective time-trend study of polybrominated diphenyl ether and polybrominated and polychlorinated biphenyl levels in human serum from the United States. Environ Health Perspect. 2004;112(6):654–58. doi: 10.1289/ehp.112-1241957. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56.Turyk ME, Anderson HA, Steenport D, Buelow C, Imm P, Knobeloch L. Longitudinal biomonitoring for polybrominated diphenyl ethers (PBDEs) in residents of the Great Lakes basin. Chemosphere. 2010;81(4):517–22. doi: 10.1016/j.chemosphere.2010.07.037. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 57.Gunier RB, Kang AY, Hammond SK, et al. Parental Occupational Pesticide Exposure and Childhood Acute Lymphoblastic Leukemia; International Society for Environmental Epidemiology Conference; Seattle, WA. 2014. [Google Scholar]
  • 58.Metayer C, Scélo G, Kang AY, et al. A Task-based Assessment of Parental Occupational Exposure to Organic Solvents and Other Compounds and Risk of Acute Lymphoblastic Leukemia in the Offspring; International Society for Environmental Epidemiology Conference; Seattle, WA. 2014. [Google Scholar]
  • 59.Siegel DA, King J, Tai E, Buchanan N, Ajani UA, Li J. Cancer Incidence Rates and Trends Among Children and Adoslescents in the United States, 2001-2009. Pediatrics. 2014;134(4) doi: 10.1542/peds.2013-3926. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 60.Xie Y, Davies SM, Xiang Y, Robison LL, Ross JA. Trends in leukemia incidence and survival in the United States (1973-1998) Cancer. 2003;97(9):2229–35. doi: 10.1002/cncr.11316. [DOI] [PubMed] [Google Scholar]
  • 61.Linabery AM, Ross JA. Trends in childhood cancer incidence in the U.S. (1992-2004) Cancer. 2008;112(2):416–32. doi: 10.1002/cncr.23169. [DOI] [PubMed] [Google Scholar]
  • 62.Gomez SL, Glaser SL. Misclassification of race/ethnicity in a population-based cancer registry (United States) Cancer Causes Control. 2006;17(6):771–81. doi: 10.1007/s10552-006-0013-y. [DOI] [PubMed] [Google Scholar]
  • 63.Clegg LX, Reichman ME, Hankey BF, et al. Quality of race, Hispanic ethnicity, and immigrant status in population-based cancer registry data: implications for health disparity studies. Cancer Causes Control. 2007;18(2):177–87. doi: 10.1007/s10552-006-0089-4. [DOI] [PubMed] [Google Scholar]
  • 64.U.S. Census Bureau. Post-Enumeration Survey, 1990 Census. Net Undercount and Undercount Rate fro U.S. and States (1990) Retreived April 11, 2016, from http://www.census.gov/dmd/www/pdf/understate.pdf.
  • 65.O'Hare W. The Changing Child Population of the United States: Analysis of Data from the 2010 Census. Baltimore, MD: The Annie E Casey Foundation; 2011. [Google Scholar]

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