Video Abstract
Elevated blood lead levels (EBLLs; ≥5 µg/dL) are more prevalent among refugee children resettled in the United States than the general US population and contribute to permanent health and neurodevelopmental problems. The Centers for Disease Control and Prevention recommends screening of refugee children aged 6 months to 16 years on arrival in the United States and retesting those aged 6 months to 6 years between 3- and 6-months postarrival.
We analyzed EBLL prevalence among refugee children aged 6 months to 16 years who received a domestic refugee medical examination between January 1, 2010 and September 30, 2014. We assessed EBLL prevalence by predeparture examination country and, among children rescreened 3 to 6 months after initial testing, we assessed EBLL changes during follow-up screening.
Twelve sites provided data on 27 284 children representing nearly 25% of refugee children resettling during the time period of this analysis. The EBLL prevalence during initial testing was 19.3%. EBLL was associated with younger age, male sex, and overseas examination country. Among 1121 children from 5 sites with available follow-up test results, EBLL prevalence was 22.7%; higher follow-up BLLs were associated with younger age and predeparture examination country.
EBLL decreased over the time period of our analysis in this population of refugee children. Refugee children may be exposed to lead before and after resettlement to the United States. Efforts to identify incoming refugee populations at high risk for EBLL can inform prevention efforts both domestically and overseas.
Refugee children have a higher risk of elevated blood lead levels (EBLLs) than the general US child population. In state-specific reports EBLL has been linked to overseas exposures, older housing, and culturally specific exposures (eg, traditional remedies or cosmetics).
Analysis of a multistate, multiyear data set permitted assessment of EBLL among refugee children by examination country to identify populations at higher risk of EBLL. Blood lead levels increases after arrival may indicate US-based lead exposures among refugee children.
Nearly 3 million refugees from around the world have resettled to the United States since 1980, with 85 000 arriving between October 2015 and September 2016.1 Among these refugees, 40.1% were children <16 years old.2 These children may be at increased risk for elevated blood lead levels (EBLLs) related to exposures before and after arrival in the United States.
Lead, a neurotoxicant, has no physiologic role in the human body; any level is potentially harmful. Exposure can cause neurologic and neurodevelopmental problems, anemia, and, at higher levels, severe brain and kidney damage leading to death.3 Children are especially at risk for lead exposure because of behaviors such as playing on the floor, which increases contact with dust and dirt potentially containing lead, and mouthing of potentially contaminated objects. Children’s bodies also absorb more lead by surface area than adult’s bodies.3 Micronutrient deficiencies (eg, iron and calcium) also can increase the body’s absorption of lead.3
Blood lead levels (BLLs) among children in the United States have declined in recent decades.4 In 2012, the Centers for Disease Control and Prevention (CDC) lowered the reference level for EBLL from 10 to 5 µg/dL on the basis of the Advisory Committee on Childhood Lead Poisoning Prevention’s5 recommendations. This value (5 µg/dL) represents the 97.5th percentile of the distribution of BLLs measured on children ages 1 to 5 years in the 2007–2010 National Health and Nutrition Examination Survey and is used by clinical and public health care providers to identify children requiring public health action.6
Previous investigations have found a higher EBLL prevalence among refugee children than in the general population of children in the United States.7,–14 Investigators identified associations between EBLL and overseas lead exposures, nutritional deficits, imported products containing lead (eg, food, cosmetics, toys), and resettlement in older housing in the United States.7,–12,15
CDC refugee screening guidelines recommend checking BLLs for all refugee children aged 6 months to 16 years16 at the time of arrival in the United States, rescreening refugees aged 6 months to 6 years 3- to 6-months postresettlement regardless of initial BLL result, and providing all children aged 6 months to 6 years with daily pediatric multivitamins with iron.16
Although authors of previous analyses have examined EBLL prevalence among refugee children living in individual states,7,–11,14 larger analyses across multiple states have not been performed. We sought to determine the prevalence over time of EBLL among newly resettled refugee children across multiple states, stratified by country of predeparture examination, and to determine changes in BLL among children rescreened within 3- to 6-months postresettlement.
Methods
State and local refugee health programs provided the CDC with BLL test results and demographic information routinely collected during the domestic refugee health examinations of children aged 6 months to 16 years resettled to the United States from January 1, 2010, to September 30, 2014. Some participating partners received funding through the CDC’s CK12-1205 Strengthening Surveillance for Diseases Among Newly-Arrived Immigrants and Refugees cooperative agreement. We preferentially included venous BLL testing results (because capillary BLLs may be subject to contamination from lead traces on fingers17) but accepted capillary or undocumented specimen results if venous results were unavailable. We defined a valid initial BLL test as a quantitative blood lead value from testing conducted ≤90 days after arrival. If a child had both capillary and venous BLL testing during the first 90 days, we preferentially selected the venous BLL if the date of collection was either before or ≤45 days after the capillary test (Fig 1). Tests administered 91 to 183 days (3–6 months) after the initial selected test were designated valid follow-up tests. Qualitative test results (ie, reported without a numeric value) and results of specimens collected outside the defined time frames were excluded. We were unable to collect data on potential lead exposures.
Selection of test results for inclusion in an analysis of BLLs among refugee children resettled in the United States.
Selection of test results for inclusion in an analysis of BLLs among refugee children resettled in the United States.
Demographic and Clinical Information
Refugee health program partners provided demographic data, including sex, age at time of BLL testing, US arrival date, and overseas examination country. When available, height, weight, and hemoglobin results from the initial domestic medical examination were also provided. If sites could not provide complete demographic information but provided a unique identification number, we used this number to extract relevant data from the CDC’s Electronic Disease Notification system.18 We categorized participants by examination country (location of the overseas immigration medical screening examination and typically where a refugee lived during the 3–6 months before US arrival), because our data on nationality were incomplete and may not reflect where a refugee was exposed to lead. Our reference country was Malaysia because it had the lowest EBLL prevalence among the 5 examination countries with the largest arrival volumes.
Data Analysis
We defined EBLL as a BLL of ≥5 µg/dL.6 The comparison group for all analyses was children with BLL values <5 µg/dL. We used the month of testing, grouped by quarter (eg, January to March), to evaluate the potential association between the time of year and BLL. We defined moderate to severe anemia as hemoglobin <10 g/dL, regardless of age or sex.19 We used height and weight measurements to calculate anthropometric z scores using the World Health Organization’s Child Growth Standards SAS igrowup macro package (SAS version 9.4; SAS Institute, Inc, Cary, NC). Stunting was defined as <−2 SD from median height-for-age z score for reference population and wasting as <−2 SD from median weight-for-height or BMI z score for reference population.20
We assessed the relationship between EBLL on the initial screening test and demographic characteristics and other covariates in our data set by calculating prevalence ratios (PRs) and 95% confidence intervals (CIs) using generalized estimating equations to account for state-level clustering and both with and without age stratification (comparing children aged <7 years with children aged 7–16 years). We included variables in the adjusted model if they were significantly associated with EBLL in the bivariate model at the .05 α level. In our age-stratified analysis, sex was the only variable with significantly different BLLs, so we included an interaction term for age and sex in our model. We also analyzed the association between nutritional status (ie, stunting, wasting, or severe anemia) and EBLL using the same modeling approach on the subset of our population with available nutritional indicator data. We used the Cochran-Armitage test to assess for trends in EBLL prevalence over the time period covered by our data set. To evaluate changes in BLL after arrival, we calculated the prevalence of a ≥2 µg/dL increase in BLL using a generalized estimating equation and used the sign test to compare the change in median BLL from the initial and follow-up tests among children who had EBLL on both tests. We evaluated the relationship between EBLL on the follow-up test and multiple covariates using the same modeling approach described for the initial testing. All data analysis was performed using SAS 9.4 software. This analysis was determined to be nonresearch surveillance by a CDC human subjects advisor; institutional review board review was not required.
Results
We received valid BLL results for 27 284 resettled refugee children aged 6 months to 16 years old at the time of initial domestic medical examination from 12 sites: 11 states (CO, ID, IL, KY, MA, MN, NC, NY [excluding New York City], TX, UT, and WA) and 1 county health department (Marion County Public Health Department of IN); these data represent nearly a quarter (24.0%) of all refugee arrivals <17 years old to the United States over the time period.20 Girls comprised 49% (n = 13 355) of our data set, and the mean age was 95.6 months (8 years; median: 92 months; interquartile range: 46–142 months) (Table 1). The top 5 overseas examination countries by arrivals were Thailand (n = 5574; 20.7%), Nepal (n = 4117; 15.2%), Malaysia (n = 3431; 12.8%), Iraq (n = 2360; 8.8%), and Kenya (n = 1962; 7.3%). Demographics of children in our data set did not differ from those of the overall population of refugee child arrivals to the United States during the same period by age, sex, arrival year, or country of examination.20
Overall, 5275 (19.3%) children had EBLL on initial testing; children <7 years old had the highest prevalence (n = 2836; 22.8%) (Supplemental Table 5). Children ≥7 years old had an EBLL prevalence of 16.5%. There were 579 (2.1%) children with BLL over 10 µg/dL and 6 (0.02%) children with BLL ≥45 µg/dL. The mean time elapsed between arrival in the United States and the initial BLL test was 29.8 days (SD = 20.2 days), and 72.1% of initial tests were venous (Table 1).
Characteristics of Refugee Children (Aged 6 Months to 16 Years) in 12 US Sites by Initial BLL Results (January 1, 2010, to September 30, 2014)
Characteristic . | Total . | Initial BLL . | χ2 . | ||
---|---|---|---|---|---|
<5 µg/dL . | 5–9.9 µg/dL . | ≥10 µg/dL . | |||
Total, N (%) | 27 284 (100) | 22 009 (80.7) | 4693 (17.2) | 582 (2.1) | — |
Age at US arrival, y | <.001 | ||||
Mean ± SD | 8.0 ± 4.7 | 8.2 ± 4.7 | 7.2 ± 4.4 | 6.8 ± 4.4 | — |
<2, n (%) | 3019 (11.1) | 2342 (77.6) | 580 (19.2) | 97 (3.2) | — |
2–6, n (%) | 9446 (34.6) | 7287 (77.1) | 1935 (20.5) | 224 (2.4) | — |
7–11, n (%) | 9608 (35.2) | 7897 (82.2) | 1515 (15.8) | 196 (2) | — |
12–16, n (%) | 5211 (19.1) | 4483 3 (86) | 663 (12.7) | 65 (1.2) | — |
Sex, n (%) | <.001 | ||||
Girls | 13 372 (49.0) | 11 272 (84.3) | 1871 (14) | 229 (1.7) | — |
Boys | 13 907 (51.0) | 10 732 (77.2) | 2822 (20.3) | 353 (2.5) | — |
Year of US arrival, n (%) | <.001 | ||||
2010 | 6005 (22.0) | 4533 (75.5) | 1311 (21.8) | 161 (2.7) | — |
2011 | 4896 (17.9) | 3738 (76.3) | 1041 (21.3) | 117 (2.4) | — |
2012 | 5692 (20.9) | 4625 (81.3) | 950 (16.7) | 117 (2.1) | — |
2013 | 6094 (22.3) | 5179 (85.0) | 813 (13.3) | 102 (1.7) | — |
2014 | 4597 (16.8) | 3934 (85.6) | 578 (12.6) | 85 (1.8) | — |
Overseas examination country, n (%) | <.001 | ||||
Iraq | 2362 (8.7) | 1873 (79.3) | 428 (18.1) | 61 (2.6) | — |
Kenya | 1972 (7.2) | 1590 (80.6) | 314 (15.9) | 68 (3.4) | — |
Malaysia | 3434 (12.6) | 2915 (84.9) | 493 (14.4) | 26 (0.8) | — |
Nepal | 4100 (15) | 2972 (72.5) | 1036 (25.3) | 92 (2.2) | — |
Thailand | 5627 (20.6) | 4446 (79) | 1079 (19.2) | 102 (1.8) | — |
Othera | 9789 (35.9) | 8213 (83.9) | 1343 (13.7) | 233 (2.4) | — |
Duration from US arrival to initial test, d | <.001 | ||||
Mean ± SD | 29.8 (20.2) | 30.3 (20.4) | 27.6 (19.0) | 29.5 (19.7) | — |
<30, n (%) | 16 107 (59) | 12 802 (79.5) | 2964 (18.4) | 341 (2.1) | — |
≥30, n (%) | 11 177 (41) | 9207 (82.4) | 1729 (15.5) | 241 (2.2) | — |
Month of initial test, n (%) | <.001 | ||||
January to March | 6141 (22.5) | 5086 (82.8) | 951 (15.5) | 104 (1.7) | — |
April to June | 6707 (24.6) | 5427 (80.9) | 1141 (17) | 139 (2.1) | — |
July to September | 8298 (30.4) | 6534 (78.7) | 1551 (18.7) | 213 (2.6) | — |
October to December | 6138 (22.5) | 4962 (80.8) | 1050 (17.1) | 126 (2.1) | |
Test type, n (%) | <.001 | ||||
Venous | 19 668 (72.1) | 16 010 (81.4) | 3235 (16.4) | 423 (2.2) | — |
Capillary | 3304 (12.1) | 2692 (81.5) | 530 (16) | 82 (2.5) | — |
Unknown | 4312 (15.8) | 3307 (76.7) | 928 (21.5) | 77 (1.8) | — |
Nutritional status total,b n (%) | 8951 (100) | 7254 (81) | 1541 (17.2) | 156 (1.7) | — |
Anemia, hemoglobin <10 g/dL, n (%) | .02 | ||||
Yes | 327 (3.7) | 245 (74.9) | 68 (20.8) | 14 (4.3) | — |
No | 8624 (96.3) | 7009 (81.3) | 1473 (17.1) | 142 (1.6) | — |
Wasting,c n (%) | .05 | ||||
Yes | 423 (4.7) | 329 (77.8) | 90 (21.3) | 4 (0.9) | — |
No | 8528 (95.3) | 6925 (81.2) | 1451 (17) | 152 (1.8) | — |
Stunting,d n (%) | <.001 | ||||
Yes | 1865 (20.8) | 1460 (78.3) | 361 (19.4) | 44 (2.4) | — |
No | 7086 (79.2) | 5794 (81.8) | 1180 (16.7) | 111 (1.6) | — |
Characteristic . | Total . | Initial BLL . | χ2 . | ||
---|---|---|---|---|---|
<5 µg/dL . | 5–9.9 µg/dL . | ≥10 µg/dL . | |||
Total, N (%) | 27 284 (100) | 22 009 (80.7) | 4693 (17.2) | 582 (2.1) | — |
Age at US arrival, y | <.001 | ||||
Mean ± SD | 8.0 ± 4.7 | 8.2 ± 4.7 | 7.2 ± 4.4 | 6.8 ± 4.4 | — |
<2, n (%) | 3019 (11.1) | 2342 (77.6) | 580 (19.2) | 97 (3.2) | — |
2–6, n (%) | 9446 (34.6) | 7287 (77.1) | 1935 (20.5) | 224 (2.4) | — |
7–11, n (%) | 9608 (35.2) | 7897 (82.2) | 1515 (15.8) | 196 (2) | — |
12–16, n (%) | 5211 (19.1) | 4483 3 (86) | 663 (12.7) | 65 (1.2) | — |
Sex, n (%) | <.001 | ||||
Girls | 13 372 (49.0) | 11 272 (84.3) | 1871 (14) | 229 (1.7) | — |
Boys | 13 907 (51.0) | 10 732 (77.2) | 2822 (20.3) | 353 (2.5) | — |
Year of US arrival, n (%) | <.001 | ||||
2010 | 6005 (22.0) | 4533 (75.5) | 1311 (21.8) | 161 (2.7) | — |
2011 | 4896 (17.9) | 3738 (76.3) | 1041 (21.3) | 117 (2.4) | — |
2012 | 5692 (20.9) | 4625 (81.3) | 950 (16.7) | 117 (2.1) | — |
2013 | 6094 (22.3) | 5179 (85.0) | 813 (13.3) | 102 (1.7) | — |
2014 | 4597 (16.8) | 3934 (85.6) | 578 (12.6) | 85 (1.8) | — |
Overseas examination country, n (%) | <.001 | ||||
Iraq | 2362 (8.7) | 1873 (79.3) | 428 (18.1) | 61 (2.6) | — |
Kenya | 1972 (7.2) | 1590 (80.6) | 314 (15.9) | 68 (3.4) | — |
Malaysia | 3434 (12.6) | 2915 (84.9) | 493 (14.4) | 26 (0.8) | — |
Nepal | 4100 (15) | 2972 (72.5) | 1036 (25.3) | 92 (2.2) | — |
Thailand | 5627 (20.6) | 4446 (79) | 1079 (19.2) | 102 (1.8) | — |
Othera | 9789 (35.9) | 8213 (83.9) | 1343 (13.7) | 233 (2.4) | — |
Duration from US arrival to initial test, d | <.001 | ||||
Mean ± SD | 29.8 (20.2) | 30.3 (20.4) | 27.6 (19.0) | 29.5 (19.7) | — |
<30, n (%) | 16 107 (59) | 12 802 (79.5) | 2964 (18.4) | 341 (2.1) | — |
≥30, n (%) | 11 177 (41) | 9207 (82.4) | 1729 (15.5) | 241 (2.2) | — |
Month of initial test, n (%) | <.001 | ||||
January to March | 6141 (22.5) | 5086 (82.8) | 951 (15.5) | 104 (1.7) | — |
April to June | 6707 (24.6) | 5427 (80.9) | 1141 (17) | 139 (2.1) | — |
July to September | 8298 (30.4) | 6534 (78.7) | 1551 (18.7) | 213 (2.6) | — |
October to December | 6138 (22.5) | 4962 (80.8) | 1050 (17.1) | 126 (2.1) | |
Test type, n (%) | <.001 | ||||
Venous | 19 668 (72.1) | 16 010 (81.4) | 3235 (16.4) | 423 (2.2) | — |
Capillary | 3304 (12.1) | 2692 (81.5) | 530 (16) | 82 (2.5) | — |
Unknown | 4312 (15.8) | 3307 (76.7) | 928 (21.5) | 77 (1.8) | — |
Nutritional status total,b n (%) | 8951 (100) | 7254 (81) | 1541 (17.2) | 156 (1.7) | — |
Anemia, hemoglobin <10 g/dL, n (%) | .02 | ||||
Yes | 327 (3.7) | 245 (74.9) | 68 (20.8) | 14 (4.3) | — |
No | 8624 (96.3) | 7009 (81.3) | 1473 (17.1) | 142 (1.6) | — |
Wasting,c n (%) | .05 | ||||
Yes | 423 (4.7) | 329 (77.8) | 90 (21.3) | 4 (0.9) | — |
No | 8528 (95.3) | 6925 (81.2) | 1451 (17) | 152 (1.8) | — |
Stunting,d n (%) | <.001 | ||||
Yes | 1865 (20.8) | 1460 (78.3) | 361 (19.4) | 44 (2.4) | — |
No | 7086 (79.2) | 5794 (81.8) | 1180 (16.7) | 111 (1.6) | — |
Initial BLL testing was performed within 90 d after arrival. —, not applicable.
Other higher volume (>300 arrivals over time period) overseas examination countries include Ethiopia, Jordan, Turkey, Syria, Uganda, Tanzania, Egypt, Cuba, South Africa, and Rwanda.
Total (N = 8951) represents the available data set for nutritional assessment.
Wasting is <−2 SD from median weight-for-height or BMI z score for reference population based on the World Health Organization’s AnthroPlus SAS Macro anthropometric calculator.
Stunting is <−2 SD from median height-for-age z score for reference population based on the World Health Organization’s AnthroPlus SAS Macro anthropometric calculator.
Of the 5 examination countries with the largest volume of arrivals, children from Nepal had the highest EBLL prevalence (n = 1128; 27.5%) followed by Thailand (n = 1181; 21.0%) and Iraq (n = 489, 20.7%); Kenya had the highest prevalence of BLL ≥10 µg/dL (3.4%) (Table 1). Independent of arrival volume, EBLL prevalence was highest among refugees from India (57.9%) and Afghanistan (55.1%) (Table 2); the examination country with the highest prevalence of BLL >10 µg/dL was Afghanistan (16.7%). Boys had a higher prevalence of EBLL (22.8%) than that of girls (15.7%; P < .001) (Table 1), but the geometric mean EBLL did not differ between sexes (6.5 µg/dL [95% CI = 6.4–6.6] for both). EBLL prevalence did not differ between sexes for children aged <2 years; in all other age groups, girls had a significantly lower prevalence of EBLL than did boys, and the sex disparity increased with age. EBLL was significantly associated with the time of year during initial testing (highest during July through September; 21.2%; P < .001). EBLL prevalence declined by arrival year, dropping from 24.4% of arrivals in 2010 to 14.4% of arrivals in 2014 (P < .001; Fig 2) (Supplemental Table 5).
Prevalence of Initial BLLs Among Refugee Children in 12 US Sites by Country of Overseas Examination (January 1, 2010, to September 30, 2014)
Country of Examination . | Initial BLL . | ||||
---|---|---|---|---|---|
<5 µg/dL, n (%) . | 5–9.9 µg/dL, n (%) . | ≥5 µg/dL, n (%) . | ≥10 µg/dL, n (%) . | Total . | |
Thailand | 4446 (79) | 1079 (19.2) | 1181 (21) | 102 (1.8) | 5627 |
Nepal | 2972 (72.5) | 1036 (25.3) | 1128 (27.5) | 92 (2.2) | 4100 |
Malaysia | 2915 (84.9) | 493 (14.4) | 519 (15.1) | 26 (0.8) | 3434 |
Iraq | 1873 (79.3) | 428 (18.1) | 489 (20.7) | 61 (2.6) | 2362 |
Kenya | 1590 (80.6) | 314 (15.9) | 382 (19.4) | 68 (3.4) | 1972 |
Ethiopia | 1155 (85.9) | 166 (12.3) | 190 (14.1) | 24 (1.8) | 1345 |
Jordan | 1002 (93.5) | 62 (5.8) | 70 (6.5) | 8 (0.8) | 1072 |
Turkey | 771 (93.1) | 51 (6.2) | 57 (6.9) | 6 (0.7) | 828 |
Syria | 556 (77.3) | 153 (21.3) | 163 (22.7) | 10 (1.4) | 719 |
Uganda | 469 (78.7) | 107 (18) | 127 (21.3) | 20 (3.4) | 596 |
Tanzania | 494 (92.9) | 33 (6.2) | 38 (7.1) | 5 (0.9) | 532 |
Egypt | 380 (84.6) | 62 (13.8) | 69 (15.4) | 7 (1.6) | 449 |
Cuba | 320 (84.2) | 56 (14.7) | 60 (15.8) | 4 (1.1) | 380 |
South Africa | 353 (93.9) | 22 (5.9) | 23 (6.1) | 1 (0.3) | 376 |
Rwanda | 349 (96.7) | 12 (3.3) | 12 (3.3) | — | 361 |
Burma | 177 (62.8) | 89 (31.6) | 105 (37.2) | 16 (5.7) | 282 |
Djibouti | 144 (81.8) | 26 (14.8) | 32 (18.2) | 6 (3.4) | 176 |
Zambia | 151 (86.8) | 19 (10.9) | 23 (13.2) | 4 (2.3) | 174 |
Lebanon | 126 (89.4) | 14 (9.9) | 15 (10.6) | 1 (0.7) | 141 |
Afghanistan | 62 (44.9) | 53 (38.4) | 76 (55.1) | 23 (16.7) | 138 |
India | 56 (42.1) | 67 (50.4) | 77 (57.9) | 10 (7.5) | 133 |
Austria | 109 (92.4) | 9 (7.6) | 9 (7.6) | — | 118 |
Ukraine | 99 (99) | 1 (1) | 1 (1) | — | 100 |
Othera | 1440 (77.1) | 341 (18.2) | 429 (22.9) | 88 (4.7) | 1869 |
Total | 22 009 (80.7) | 4693 (17.2) | 5275 (19.3) | 582 (2.1) | 27 284 |
Country of Examination . | Initial BLL . | ||||
---|---|---|---|---|---|
<5 µg/dL, n (%) . | 5–9.9 µg/dL, n (%) . | ≥5 µg/dL, n (%) . | ≥10 µg/dL, n (%) . | Total . | |
Thailand | 4446 (79) | 1079 (19.2) | 1181 (21) | 102 (1.8) | 5627 |
Nepal | 2972 (72.5) | 1036 (25.3) | 1128 (27.5) | 92 (2.2) | 4100 |
Malaysia | 2915 (84.9) | 493 (14.4) | 519 (15.1) | 26 (0.8) | 3434 |
Iraq | 1873 (79.3) | 428 (18.1) | 489 (20.7) | 61 (2.6) | 2362 |
Kenya | 1590 (80.6) | 314 (15.9) | 382 (19.4) | 68 (3.4) | 1972 |
Ethiopia | 1155 (85.9) | 166 (12.3) | 190 (14.1) | 24 (1.8) | 1345 |
Jordan | 1002 (93.5) | 62 (5.8) | 70 (6.5) | 8 (0.8) | 1072 |
Turkey | 771 (93.1) | 51 (6.2) | 57 (6.9) | 6 (0.7) | 828 |
Syria | 556 (77.3) | 153 (21.3) | 163 (22.7) | 10 (1.4) | 719 |
Uganda | 469 (78.7) | 107 (18) | 127 (21.3) | 20 (3.4) | 596 |
Tanzania | 494 (92.9) | 33 (6.2) | 38 (7.1) | 5 (0.9) | 532 |
Egypt | 380 (84.6) | 62 (13.8) | 69 (15.4) | 7 (1.6) | 449 |
Cuba | 320 (84.2) | 56 (14.7) | 60 (15.8) | 4 (1.1) | 380 |
South Africa | 353 (93.9) | 22 (5.9) | 23 (6.1) | 1 (0.3) | 376 |
Rwanda | 349 (96.7) | 12 (3.3) | 12 (3.3) | — | 361 |
Burma | 177 (62.8) | 89 (31.6) | 105 (37.2) | 16 (5.7) | 282 |
Djibouti | 144 (81.8) | 26 (14.8) | 32 (18.2) | 6 (3.4) | 176 |
Zambia | 151 (86.8) | 19 (10.9) | 23 (13.2) | 4 (2.3) | 174 |
Lebanon | 126 (89.4) | 14 (9.9) | 15 (10.6) | 1 (0.7) | 141 |
Afghanistan | 62 (44.9) | 53 (38.4) | 76 (55.1) | 23 (16.7) | 138 |
India | 56 (42.1) | 67 (50.4) | 77 (57.9) | 10 (7.5) | 133 |
Austria | 109 (92.4) | 9 (7.6) | 9 (7.6) | — | 118 |
Ukraine | 99 (99) | 1 (1) | 1 (1) | — | 100 |
Othera | 1440 (77.1) | 341 (18.2) | 429 (22.9) | 88 (4.7) | 1869 |
Total | 22 009 (80.7) | 4693 (17.2) | 5275 (19.3) | 582 (2.1) | 27 284 |
—, not applicable.
Other includes Zimbabwe, Russia, Yemen, Chad, United Arab Emirates, Sudan, Cameroon, Burundi, Tunisia, Malawi, Somalia, Mozambique, Malta, Pakistan, Ghana, Vietnam, Gabon, Belarus, Botswana, Guinea, Senegal, Slovak Republic, Philippines, Democratic Republic of Congo, Kuwait, Central African Republic, Ecuador, Côte d’Ivoire, Sri Lanka, Kyrgyzstan, Nigeria, China, Azerbaijan, Republic of Congo, Indonesia, Mali, Romania, Georgia, Bahrain, The Gambia, Kazakhstan, Namibia, Oman, Iran, Libya, Republic of Moldova, Bangladesh, Bhutan, Colombia, Saudi Arabia, Tajikistan, Canada, Liberia, Eritrea, Slovakia, Algeria, Benin, Cambodia, Costa Rica, Macau, Australia, France, Israel, Kiribati, Morocco, South Georgia and/or South Sandwich Island, Sierra Leone, Tonga, unknown, Uruguay, Uzbekistan, and Western Sahara.
EBLL prevalence by arrival year and country of examination for Iraq, Kenya, Malaysia, Nepal, Thailand, and all other countries combined, 2010–2014.
EBLL prevalence by arrival year and country of examination for Iraq, Kenya, Malaysia, Nepal, Thailand, and all other countries combined, 2010–2014.
The nutritional analysis subset included 8951 children from 8 sites with complete hemoglobin results and height (or length) and weight information; 1697 (19.0%) of these children had EBLL. In unadjusted analyses, EBLL was associated with moderate to severe anemia (PR = 1.4; 95% CI 1.2–1.7; P = .001) and stunting (PR = 1.2; 95% CI 1.1–1.3; P = .001) but not wasting (PR = 1.2; 95% CI 1.0–1.4; P = .09). However, none of these variables remained associated with EBLL after adjustment for age, sex, and time of year.
In the adjusted model (Table 3), prevalence of EBLL among boys and girls was not significantly different in children <2 years of age. In children ages 2 years and older, boys were more likely to have EBLL than girls of the same age, and the disparity increased with age. No other covariates differed by age in age-stratified analysis. Children examined in Nepal, Iraq, Kenya, and Thailand were more likely to have EBLL on follow-up testing than children examined in Malaysia.
Adjusted PRs for EBLL Results on Initial Testing Among Refugee Children 6 Months to 16 Years Screened in 12 US Sites (January 1, 2010, to September 30, 2014)
Characteristic . | aPRa (95% CI) . |
---|---|
Age and sex at US arrival | |
<2 y | |
Boy | 1.1 (1.0–1.2) |
Girl | Reference |
2–6 y | |
Boy | 1.2 (1.2–1.3) |
Girl | Reference |
7–11 y | |
Boy | 1.5 (1.4–1.7) |
Girl | Reference |
12–16 y | |
Boy | 3.0 (2.5–3.7) |
Girl | Reference |
Year of arrival | |
2014 | Reference |
2013 | 1.0 (0.9–1.2) |
2012 | 1.3 (1.1–1.5) |
2011 | 1.6 (1.2–2.1) |
2010 | 1.7 (1.5–2.0) |
Overseas examination country | |
Malaysia | Reference |
Nepal | 1.8 (1.6–2.1) |
Iraq | 1.5 (1.3–1.6) |
Kenya | 1.3 (1.1–1.6) |
Thailand | 1.4 (1.1–1.7) |
Other | 1.1 (1.0–1.3) |
Duration from US arrival to initial test, d | |
<30 | 1.2 (1.0–1.3) |
≥30 | Reference |
Month of initial test | |
January to March | Reference |
April to June | 1.1 (1.0–1.3) |
July to September | 1.2 (1.1–1.3) |
October to December | 1.1 (1.0–1.1) |
Characteristic . | aPRa (95% CI) . |
---|---|
Age and sex at US arrival | |
<2 y | |
Boy | 1.1 (1.0–1.2) |
Girl | Reference |
2–6 y | |
Boy | 1.2 (1.2–1.3) |
Girl | Reference |
7–11 y | |
Boy | 1.5 (1.4–1.7) |
Girl | Reference |
12–16 y | |
Boy | 3.0 (2.5–3.7) |
Girl | Reference |
Year of arrival | |
2014 | Reference |
2013 | 1.0 (0.9–1.2) |
2012 | 1.3 (1.1–1.5) |
2011 | 1.6 (1.2–2.1) |
2010 | 1.7 (1.5–2.0) |
Overseas examination country | |
Malaysia | Reference |
Nepal | 1.8 (1.6–2.1) |
Iraq | 1.5 (1.3–1.6) |
Kenya | 1.3 (1.1–1.6) |
Thailand | 1.4 (1.1–1.7) |
Other | 1.1 (1.0–1.3) |
Duration from US arrival to initial test, d | |
<30 | 1.2 (1.0–1.3) |
≥30 | Reference |
Month of initial test | |
January to March | Reference |
April to June | 1.1 (1.0–1.3) |
July to September | 1.2 (1.1–1.3) |
October to December | 1.1 (1.0–1.1) |
aPR, adjusted prevalence ratio.
Adjusted for variables in the table as well as site reporting data.
Five sites (CO, IL, IN, MN, and NY) provided follow-up testing results on 3532 (13.0%) children. Among children with multiple BLL results, 1121 (31.7%) had valid follow-up tests (Fig 2) of which 76.3% were venous tests. The proportion of children with a valid follow-up test was 5.0% among children <7 years old (22.8% EBLL prevalence) and 3.4% among children ≥7 years old (16.5% EBLL prevalence).
Among 1121 children with valid follow-up BLLs, 183 (16.3%) had EBLL on both initial and follow-up tests, and 71 (6.3%) did not have EBLL initially but had EBLL at follow-up (Fig 3). In total, 117 (10.4%) children experienced a ≥2 µg/dL increase in BLL on the follow-up test. Increases in BLL were most common among children <2 years (20.8% of retested children <2 years), but 5.2% of children 7 years and older experienced a ≥2 µg/dL increase in BLL. Overall, the median BLL declined significantly between initial and follow-up testing (8.0 µg/dL [95% CI = 8.0–8.7] and 7.0 µg/dL; [95% CI = 6.2–7.1], respectively; sign test P < .0001) for children with EBLL on both tests.
Comparison of initial and follow-up BLLs 3 to 6 months after initial testing among refugee children (N = 1121) aged 6 months to 16 years in 5 US sites, January 1, 2010, to September 30, 2014. a Includes 7 individuals who dropped <5 μg/dL; 46 remained >5 μg/dL. b Includes 43 individuals who dropped <5 μg/dL but had a <2 μg/dL decline in BLL.
Comparison of initial and follow-up BLLs 3 to 6 months after initial testing among refugee children (N = 1121) aged 6 months to 16 years in 5 US sites, January 1, 2010, to September 30, 2014. a Includes 7 individuals who dropped <5 μg/dL; 46 remained >5 μg/dL. b Includes 43 individuals who dropped <5 μg/dL but had a <2 μg/dL decline in BLL.
A ≥2 µg/dL rise in BLL on the follow-up test was associated with younger age, particularly <2 years old, testing time of year (April through June), and examination country (adjusted model, Table 4). An EBLL result on the follow-up test was associated with younger age (<7 years), earlier arrival years (2010–2011), country of examination (Iraq and Kenya), and time of year (July through September) (adjusted model; data not shown) .
Prevalence and Adjusted PR of a ≥2 µg/dL BLL Increase 3–6 Months After Initial Testing Among Refugee Children Aged 6 Months to 16 Years Arriving in 5 US Sites, January 1, 2010, to September 30, 2014 (N = 1121)
Characteristic . | >2 µg/dL Increase in BLL, % . | aPRa (95% CI) . |
---|---|---|
Age, y | ||
<2 | 20.8 | 4.5 (2.6–7.6) |
2–6 | 11.6 | 2.4 (2.0–2.9) |
7–11 | 5.6 | 1.2 (1.11.4) |
12+ | 4.3 | Reference |
Boy | 11.0 | 1.1 (0.8–1.5) |
Girl | 9.9 | Reference |
Year of arrival | ||
2014 | 8.0 | Reference |
2013 | 10.2 | 1.3 (1.1–1.5) |
2012 | 5.8 | 0.7 (0.5–0.8) |
2011 | 12.3 | 1.3 (0.9–1.9) |
2010 | 14.7 | 1.5 (1.2–1.9) |
Country of examination | ||
Iraq | 6.1 | 1.2 (0.5–2.5) |
Kenya | 13.9 | 2.3 (1.2–4.5) |
Malaysia | 9.5 | Reference |
Nepal | 8.8 | 1.6 (0.7–3.7) |
Thailand | 6.3 | 2.6 (1.3–5.3) |
Other | 16.0 | 1.2 (0.6–2.23) |
Month of follow-up test | ||
January to March | 13.8 | Reference |
April to June | 10.2 | 1.6 (1.1–2.3) |
July to September | 11.6 | 1.4 (0.9–2.0) |
October to December | 5.9 | 1.4 (1.0–2.0) |
Characteristic . | >2 µg/dL Increase in BLL, % . | aPRa (95% CI) . |
---|---|---|
Age, y | ||
<2 | 20.8 | 4.5 (2.6–7.6) |
2–6 | 11.6 | 2.4 (2.0–2.9) |
7–11 | 5.6 | 1.2 (1.11.4) |
12+ | 4.3 | Reference |
Boy | 11.0 | 1.1 (0.8–1.5) |
Girl | 9.9 | Reference |
Year of arrival | ||
2014 | 8.0 | Reference |
2013 | 10.2 | 1.3 (1.1–1.5) |
2012 | 5.8 | 0.7 (0.5–0.8) |
2011 | 12.3 | 1.3 (0.9–1.9) |
2010 | 14.7 | 1.5 (1.2–1.9) |
Country of examination | ||
Iraq | 6.1 | 1.2 (0.5–2.5) |
Kenya | 13.9 | 2.3 (1.2–4.5) |
Malaysia | 9.5 | Reference |
Nepal | 8.8 | 1.6 (0.7–3.7) |
Thailand | 6.3 | 2.6 (1.3–5.3) |
Other | 16.0 | 1.2 (0.6–2.23) |
Month of follow-up test | ||
January to March | 13.8 | Reference |
April to June | 10.2 | 1.6 (1.1–2.3) |
July to September | 11.6 | 1.4 (0.9–2.0) |
October to December | 5.9 | 1.4 (1.0–2.0) |
aPR, adjusted prevalence ratio.
Adjusted for variables reported in table as well as site reporting data.
Discussion
This report expands our knowledge of the prevalence of EBLL among resettled refugee children, using data from a representative sample of children resettled to multiple states. The EBLL prevalence in this population of recently arrived refugee children (23.7% among 1–5-year-olds) was 10-fold higher than the NHANES-estimated prevalence of 2.3% among all 1- to 5-year-old children in the United States from 1999 to 2010.21 In addition, up to 10% of children had increases in BLL 3 to 6 months after the initial test, including 5% of children who were >6 years old.
Initial EBLL results likely indicate overseas lead exposures, because testing was conducted within 3 months of arrival. Among 5 overseas sites with the largest arrival volume, EBLL prevalence was highest among children with overseas medical examinations in Nepal (generally children of Bhutanese origin or nationality), Thailand (Burma origin), and Iraq (Iraq origin). Children examined in India, Afghanistan, Burma, and Nepal had the highest overall prevalence of EBLL, and children examined in Afghanistan had the highest prevalence of BLL ≥10 µg/dL, although the relatively small numbers of refugee arrivals from these countries limited our ability to draw definitive conclusions, and EBLL risk may vary by subnational factors such as city or refugee camp of residence, which we were unable to analyze. Our findings may warrant further investigation of EBLL as a common health concern for children from these countries.
Younger age and male sex (regardless of age) were also associated with EBLL at arrival. Although the oldest children (age 12–16 years) had a lower EBLL prevalence (14%) than children aged 2 to 4 (24%), they had a higher prevalence of EBLL than has been reported among the general US adolescent population,22,23 supporting the CDC’s current recommendations for testing refugee children through age 16. As previously noted,9,12 initial EBLL prevalence was highest among children tested between July and September.
EBLL prevalence among refugee arrivals declined over the period of our analysis, which could have resulted from many factors, including improved conditions overseas, such as the introduction of electricity in some refugee camps24; phasing out of leaded gasoline in multiple countries in the years leading up to this analysis25; and changes in the countries of origin of resettlement populations. For example, refugees resettling from Thailand may have been exposed to lead poisoning prevention messaging as part of an overseas educational campaign on lead early in the analysis period, although our analysis was unable to evaluate the effect of this education. Although EBLL declined overall, we noted upward trends in Thailand and Kenya in 2014; further investigation would be needed to identify contributors.
We identified an overall decline in median BLL among children who received a follow-up test, although a minority experienced postresettlement BLL increases, which may indicate domestic lead exposures. We had no information on specific lead exposures, but other investigations of EBLL among refugee children have identified associations between postresettlement increases in BLL and anemia, parasitic infections, pre-1950s housing,9 and imported infant remedies and cosmetics,7 for example.
There were limitations to this analysis. First, reporting differences between sites lead to the exclusion of some data from analysis (eg, qualitative results). Some sites did not provide height, weight, and hemoglobin data. Most sites were unable to provide the laboratory limit of detection data, so we could not calculate mean BLLs for children with results <5 µg/dL. Most sites were unable to provide follow-up BLL data, usually because refugee health programs only have access to initial postarrival screening data, and follow-up testing is performed outside the refugee health program. Accordingly, children in our follow-up data set had a higher initial prevalence of EBLL (30.8%) than children in our overall data set (19.3%), which may explain why some children >6 years were retested. A majority (89.4%) of our follow-up test results were collected from 2 sites; therefore, related findings cannot be generalized to the broader data set. We were unable to ascertain whether follow-up tests had taken place after settlement in permanent housing; therefore, we chose to use a narrow definition for follow-up testing, which excluded a number (2411) of follow-up tests not meeting the retesting time period we specified. Finally, we were not always able to determine which BLL testing method was used in each site. On the basis of a May 2017 Food and Drug Administration advisory, use of LeadCare analyzers for venous BLL testing may produce falsely low BLL results.26 If participating sites used this method, it could have underestimated EBLL prevalence.
Efforts to reduce EBLL among foreign-born children, including refugee children, are an important part of the Healthy People 2020 strategy of achieving BLLs <5.2 µg/dL for ≥97.5% of the population aged 1 to 5 years.27 Although EBLL prevalence in resettled refugee children declined over the period of this analysis, it remains far higher than the general US prevalence. EBLL prevalence varied by examination country, and refugee children remain susceptible to both overseas and domestic exposures, as illustrated by postarrival increases in BLL for some children. Refugee children with potential lead exposure can arrive in any state, so it remains important to improve linkages between federal, state, and local lead and refugee health programs to facilitate collaboration, ensure appropriate screening and follow-up for refugee children, and share best practices. We encourage states to notify the CDC of specific lead exposures or refugee populations with unusually high EBLL prevalence rates, which can help facilitate overseas and domestic interventions. Finally, we suggest that states develop and share translated resources for lead education and encourage lead poisoning prevention education for refugee families early and often. Because refugee children are a subset of all immigrant children who may have similar exposures, such resources may also benefit other children migrating to the United States.
Conclusions
Refugee children remain at risk for EBLL, despite declines in prevalence over time. With our findings, we underscore the importance of screening all arriving refugee children aged 6 months to 16 years for EBLL, followed by rescreening of refugee children aged 6 months to 6 years 3- to 6-months postresettlement. Although domestic BLL increases were more likely to occur in younger children, our data suggest that older children and adolescents also experience increases in BLL after arrival. Because our follow-up data were limited to 5 sites, further work is necessary to determine if this pattern is consistent across sites and its implications for the recommended age limits for follow-up testing.
Ms Pezzi conceptualized and designed the project, conducted the initial analyses, and drafted the initial manuscript; Ms Lee conceptualized and designed the project, drafted the initial manuscript, and reviewed the final manuscript; Drs Mitchell and Brown conceptualized and designed the project and reviewed the final manuscript; Ms Kennedy, Ms Aguirre, Ms Titus, Ms Ford, Ms Cochran, Ms Smock, Ms Mamo, Ms Urban, Ms Morillo, Dr Hughes, Dr Payton, Dr Scott, Ms Montour, and Ms Matheson collected data and reviewed the final manuscript; and all authors revised the manuscript, approved the final manuscript as submitted, and agree to be accountable for all aspects of the work.
The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.
FUNDING: Nine sites (CO; IL; Marion County, IN; MA; Catholic Charities, KY; MN; NY; TX; and Thomas Jefferson University) were supported by the CK12-1205 Strengthening Surveillance for Diseases Among Newly-Arrived Immigrants and Refugees federally funded cooperative agreement from the Centers for Disease Control and Prevention.
COMPANION PAPER: A companion to this article can be found online at www.pediatrics.org/cgi/doi/10.1542/peds.2018-3567.
Acknowledgments
We thank Collin Elias (ID), Kenneth Mulanya (Marion County, IN), Shandy Dearth (Marion County, IN), P. Joseph Gibson (Marion County, IN), and Amelia Self (UT) for the use of their data and their assistance. We also thank Adrienne Ettinger (CDC Division of Environmental Health Science and Practice) for providing lead subject matter expertise and Yecai Liu, Christina Phares, and Emily Jentes (CDC Division of Global Migration and Quarantine) for their guidance and support during data analysis and article preparation.
References
Competing Interests
POTENTIAL CONFLICT OF INTEREST: Dr Brown has received consultant fees from Meridian Bioscience, Inc; the other authors have indicated they have no potential conflicts of interest to disclose.
FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.
Comments
Physiological contributors of persistently elevated blood lead levels
This large, population-based study highlights that 19.3% of refugee children have elevated blood lead levels (EBLL) in initial testing that persists on repeat testing in a subset of these children (1). With a half-life of about 5 weeks, the blood lead levels (BLL) should decrease with time. However, about 22% of the children retested 3-6 months later had EBLL, particularly if they were retested between July and September.
We have previously described EBLL in pregnant women within 3 months of emigration. The majority of whom were from Mexico or the Indian subcontinent. (2), like Pezzi et.al. (1), we also found the initial EBLL reflected cumulative lead exposure in their home countries. Their neonates had EBLL, with mean values of 8.51 µg/dl. Although it decreased with time, the BLL in the infants remained high on repeat testing, with mean levels of 7.35 µg/dl at 1 month, and 5.90 µg/dl at 1 year of age. If these infants had been tested for the first time at 1 year of age, EBLL would likely have been attributed to environmental exposures, leading to repeat testing with increased healthcare visits and costs associated with lead-abatement efforts in their living spaces.
EBLL during pregnancy is due to increased bone turnover which results in release of lead stored in the bone into the blood (3). A similar relationship of EBLL with somatic growth is observed among adolescents, especially those that had EBLL prior to growth, indicating that bone turnover related to somatic growth resulted in further increase in BLL (4; Figure1). We therefore speculate that bone turnover may be another contributing factor to persistently EBLL in the population studied by Pezzi et.al (1). Infants and adolescents, the age groups associated with higher growth velocity, were the ones observed to have EBLL in repeat testing. Since some of these children had wasting and stunting (1), catch-up growth and associated bone turnover after improved nutrition in the US could contribute to EBLL in these children as compared to those who emigrated with a better baseline nutritional and growth status.
Furthermore, all cases of EBLL in repeat testing independently correlated with summer-time testing. (1) July to September represent a period of maximum sun exposure in the US. Sun exposure is associated with vitamin D formation, which causes increased bone growth and turnover, and again may contribute to release of stored lead from bone to the blood (5).
We highlight these physiologic mechanisms to be considered in addition to the potential of post-arrival exposure to lead in the US among the resettled refugee children due to substandard housing or cultural practices, as proposed by Green and Saia(6). Awareness of these potential mechanisms for EBLL may avoid repeat extensive workup and environmental intervention of the child’s living spaces and provide an alternative explanation in cases where no overt exposure to lead has been identified.
References:
1. Pezzi C, Lee D, Kennedy L et.al. Blood lead levels among resettled refugee children in selected sates, 201-2014. Pediatr 2019 ;143(5): e20182591
2. Rastogi S, Nandlike K, Fenester M. Elevated lead levels in pregnant women: identification of high-risk population and interventions. J Perinat Med. 2007;36:492-496
3. Manton WI, Angle CR, Stanek KL, Kuntzelman D, Reese YR, Kuehnemann TJ. Release of lead from bone in pregnancy and lactation. Environ Res. 2003 Jun; 92(2):139-51
4. Burns J, Williams PL, Leed MM, et.al. Peripubertal blood lead levels and growth among Russian boys. Environ Int. 2017;106:53-59
5. Kemp FW, Neti PVSV, Howell RW, Wegner P, Louria DB, Bogden JD. Elevated blood lead concentrations and vitamin D deficiency in winter and summer in young urban children. Environ Health Perpect. 2007;115(4):630-635
6. Green A Saia M. Preventing harm on arrival: lead prevention in newly resettled pediatric refugees. Pediatr 2019;143(5): e20183567