Abstract
Objectives. To assess the prevalence of and the demographic factors for elevated blood lead level (EBLL; ≥ 5 µg/dL) at resettlement among newly admitted refugee children.
Methods. This cross-sectional study used data from the postresettlement refugee medical screening of 5661 children resettled in Ohio from 2009 to 2016. We computed prevalence of EBLL and adjusted prevalence ratio with modified Poisson regression modeling.
Results. Overall, 22.3% of children younger than 18 years and 27.1% of those younger than 6 years had an EBLL. Children resettled from a South Asia region including Afghanistan (EBLL prevalence = 56.2%; 95% confidence interval [95% CI] = 48.1%, 64.3%), Nepal (44.0%; 95% CI = 33.7%, 54.1%), Bhutan (32.8%; 95% CI = 30.4%, 35.9%), and Burma (31.8%; 95% CI = 27.5%, 35.9%) had the highest prevalence of EBLLs. In addition, those younger than 6 years (prevalence ratio [PR] = 2.0; 95% CI = 1.6, 2.6), male (PR = 1.3; 95% CI = 1.1, 1.4), and screened within 30 days of arrival (PR = 1.7; 95% CI = 1.1, 2.5) had significantly higher EBLL prevalence than did children aged 13 years and older, female, and screened 90 days after arrival.
Conclusions. The overall high proportion of EBLL and variation in EBLL by country of origin among resettled refugee children in the United States warrant comprehensive, yet tailored, guidelines for health professionals and resettlement and government agencies for better prevention and awareness programs targeting these high-risk children.
Childhood exposure to lead in any amount is a serious health concern.1 Lead in the body can cause damage to multiple organs and organ systems such as the heart, kidney, blood vessels, nervous system, gastrointestinal system, and reproductive system.2 Even at very low blood levels (< 5 micrograms per deciliter [μg/dL]), lead is associated with harmful effects in children including cognitive impairment3 and smaller body size.4 Because there is no safe level of lead in the body, the US Centers for Disease Control and Prevention (CDC) in 2012 changed the reference value for elevated blood lead level (EBLL) from 10 to 5 µg/dL.5
Lead exposure is a major environmental risk factor contributing to an increasing number of deaths and disabilities globally. It accounted for an estimated 674 000 deaths and 14 million disability-adjusted life years in 2010; these figures respectively represent increases of 221% and 167% from the 1990 estimates.6 Although lead exposure in US children in general has significantly declined since the late 1970s when government restricted the use of lead-based paints and leaded gasoline,7 millions of children in the country, especially African Americans,8 immigrants and resettled refugees,9 and those of a low socioeconomic status8 continue to be at high risk for environmental lead exposure. Two of the objectives of Healthy People 2020, a CDC initiative, are to reduce the mean blood lead level (BLL) in children aged 1 to 5 years from 1.8 to 1.6 µg/dL and increase the testing of homes built before 1978 for lead-based paints and lead in dust and soil in and around the homes.10 Childhood lead poisoning in the United States continues to be a salient health concern, and to achieve the lead-related Healthy People 2020 objectives, childhood lead exposure in high-risk groups, including resettled refugees, must be addressed through various federal, state, and local-level policy solutions.7
Currently, 68.5 million people globally are displaced as a result of complex emergencies and, of them, 25.4 million are classified as refugees because they crossed a national boundary to seek refuge.11 Each year, less than 1% of refugees are resettled in third countries, primarily in Western countries, as a permanent solution to their protracted refugee status (thus termed “resettled refugees”).11 Of the more than 3.5 million refugees admitted to the United States between 1983 and 2017, 59 890 have been settled in the state of Ohio12; approximately 44% of them have been children younger than 18 years.13 Exposure to environmental lead or lead-containing products is a major health concern for these children before and after resettlement in the United States.14 Before resettlement, they are often at high risk for environmental exposure to lead from sources such as poorly managed industrial wastes, leaded gasoline, lead-based paints, and improperly disposed lead-acid batteries (LABs).15–18 They may also have been exposed to lead-containing household and cosmetic products.19 After resettlement, these children and their families are often housed in older inner-city homes or apartment buildings that may contain lead-based paints, thus increasing their risk of lead exposure.16,19
Studies among various resettled refugee children in the United States have reported the prevalence of BLL of 10 µg/dL or higher from 1.0% to 40.2%,9,14,18,20–23 depending on the ethnic background, the country of origin, and the age range of the children. Previous studies have also consistently shown 4- to 5-fold higher EBLL prevalence in the resettled refugee than nonrefugee children.7,23 Two published studies that used the 2012 CDC definition of EBLL have reported a prevalence range of 13.1% to 46.0% in children from various countries of origin.22,24 These studies were limited either by the number of countries of origin represented or by the limited sample size for each country. The changing patterns of demographic, regional, and sociocultural backgrounds of the resettled refugee groups in the United States over time likely result in the evolving epidemiology of EBLL in this population. Therefore, epidemiological studies of BLL at resettlement with diverse and large sample size are necessary to understand the current state of the problem in the resettled refugee children, in general, and various subgroups, specifically.
We sought to assess the prevalence of and the demographic factors for EBLL among newly resettled refugee children in the state of Ohio. The present study, with a large sample size from diverse countries of origin, provides, to our knowledge, the most current information on the prevalence of EBLL and an associated demographic profile of this high-risk group of children.
METHODS
For this cross-sectional study, we requested and obtained publicly available postresettlement refugee medical screening data of newly resettled children younger than 18 years in Ohio from 2009 to 2016 from the Ohio Department of Job and Family Services. The database, which held 5716 medical screening records, contained demographic and resettlement information including date of birth, sex, country of origin, arrival year, county of resettlement, medical screening date, and BLL measurements. For the present analysis, we used 5661 records with complete information on all the variables of interest.
Of the 46 countries of origin presented in the sample, we grouped 32 with fewer than 50 children into a single category of “other countries.” The children were resettled in 1 of the following 6 Ohio counties: Cuyahoga (Cleveland metropolitan area), Franklin (Columbus metropolitan area), Hamilton (Cincinnati metropolitan area), Lucas (Toledo metropolitan area), Montgomery (Dayton metropolitan area), and Summit (Akron metropolitan area).
The US Refugee Act of 1980 requires a comprehensive postarrival medical screening for all resettled refugees within 90 days of entry into the United States.25 In addition, the Ohio Department of Health requires BLL testing for resettled refugee children. All BLL tests were performed with the capillary blood lead test (finger or heel stick) method and were analyzed in an Ohio Department of Health–approved clinical lead laboratory; all test results of 5 μg/dL or higher were confirmed by venous blood testing.26 Per the health department requirements, BLL tests performed with point-of-care methods such as LeadCare are not considered valid and not accepted even if the samples were collected by venipuncture. The BLL was measured and recorded in μg/dL and EBLL was defined as BLL of 5 μg/dL or higher.5 We calculated the time-to-postarrival medical screening (TPaMS), defined as the length of time in days from the date of arrival in the United States to the date of the postarrival medical screening, for the study. The TPaMS served as a proxy for prearrival exposure to lead in the country of origin; the earlier the screening, and thus the shorter the TPaMS, the more likely the lead exposure occurred before US resettlement. For the analysis, we categorized the TPaMS into 4 groups: within 30, 31 to 60, 61 to 90, and greater than 90 days.
We performed analyses on the overall sample and a subsample of children younger than 6 years because younger children have a higher risk of exposure and more severe adverse health effects because of their hand-to-mouth behavior and growing body.3 We summarized categorical and continuous variables by using frequency (proportion) and the measures of central tendency, respectively. We used the χ2 test, or Monte Carlo Estimate Exact Test, for frequencies less than 5 to compare the differences between categorical variables; we used the student t test to test the difference between continuous variables. We used modified Poisson regression modeling to assess the relationship between EBLL and various demographic and resettlement characteristics, and we reported associated prevalence ratios (PRs) and 95% confidence intervals (95% CIs).27 Because of their lowest observed EBLL prevalence, we selected Syrian children as the reference group for the country of origin in the Poisson regression models. We conducted all the analysis with SAS version 9.4 (SAS Institute Inc, Cary, NC).
RESULTS
Table 1 shows demographic and resettlement profiles of the children overall and stratified by 3 BLL categories (< 5, 5–10, and > 10 μg/dL). Of 5661 children, 50.7% (2871) were male, and they had a mean age of 7.3 (SD ±4.1) years. Children from Bhutan were the largest group (28.3%), followed by Somalia (17.8%) and the Democratic Republic of Congo (DRC; 10.7%). The median TPaMS was 35 days, with 98% of the children being screened within 90 days after resettlement. We observed no significant differences in age and resettlement characteristics between sexes (results not shown).
TABLE 1—
Demographic and Resettlement Profile of Resettled Refugee Children Younger Than 18 Years by Blood Lead Levels of < 5, 5–10, and > 10 µg/dL: Ohio, 2009–2016
| Blood Lead Level, No. (%) |
|||||
| Characteristic | Total, No. (%) | < 5 µg/dL | 5–10 µg/dL | > 10 µg/dL | P |
| Overall population | 5661 (100.0) | 4400 (77.7) | 1144 (20.2) | 117 (2.1) | |
| Age group, y | < .01 | ||||
| < 6 | 2378 (42.0) | 1735 (72.9) | 563 (23.7) | 80 (3.4) | |
| 6 to < 13 | 2673 (47.2) | 2128 (79.6) | 516 (19.3) | 29 (1.1) | |
| 13 to < 18 | 610 (10.8) | 537 (88.0) | 65 (10.7) | 8 (1.3) | |
| Sex | < .01 | ||||
| Female | 2790 (49.3) | 2239 (80.2) | 494 (17.7) | 57 (2.0) | |
| Male | 2871 (50.7) | 2161 (75.3) | 650 (22.6) | 60 (2.1) | |
| Country of origin | < .01 | ||||
| Afghanistan | 144 (2.5) | 63 (43.8) | 53 (36.8) | 28 (19.4) | |
| Bhutan | 1603 (28.3) | 1078 (67.2) | 503 (31.4) | 22 (1.4) | |
| Burma | 466 (8.2) | 318 (68.2) | 141 (30.3) | 7 (1.5) | |
| Burundi | 59 (1.0) | 53 (89.8) | 6 (10.2) | 0 (0.0) | |
| Congo | 68 (1.2) | 55 (80.9) | 11 (16.2) | 2 (2.9) | |
| Democratic Republic of Congo | 608 (10.7) | 515 (84.7) | 79 (13.0) | 14 (2.3) | |
| Eritrea | 118 (2.1) | 109 (92.4) | 8 (6.8) | 1 (0.8) | |
| Ethiopia | 65 (1.1) | 62 (95.4) | 3 (4.6) | 0 (0.0) | |
| Iraq | 821 (14.5) | 691 (84.2) | 112 (13.6) | 18 (2.2) | |
| Nepal | 91 (1.6) | 51 (56.0) | 40 (44.0) | 0 (0.0) | |
| Somalia | 1007 (17.8) | 879 (87.3) | 115 (11.4) | 13 (1.3) | |
| Sudan | 103 (1.8) | 79 (76.7) | 19 (18.4) | 5 (4.9) | |
| Syria | 258 (4.6) | 249 (96.5) | 6 (2.3) | 3 (1.2) | |
| Ukraine | 53 (0.9) | 50 (94.3) | 3 (5.7) | 0 (0.0) | |
| Other countriesa | 197 (3.5) | 148 (75.1) | 45 (22.9) | 4 (2.0) | |
| Arrival year | < .01 | ||||
| 2009 | 82 (1.4) | 53 (64.6) | 26 (31.7) | 3 (3.7) | |
| 2010 | 415 (7.3) | 285 (68.7) | 115 (27.7) | 15 (3.6) | |
| 2011 | 352 (6.2) | 253 (71.9) | 93 (26.4) | 6 (1.7) | |
| 2012 | 534 (9.4) | 385 (72.1) | 142 (26.6) | 7 (1.3) | |
| 2013 | 735 (13.1) | 532 (72.4) | 192 (26.1) | 11 (1.5) | |
| 2014 | 832 (14.7) | 686 (82.4) | 126 (15.1) | 20 (2.4) | |
| 2015 | 1097 (19.4) | 869 (79.2) | 213 (19.4) | 15 (1.4) | |
| 2016 | 1614 (28.5) | 1337 (82.8) | 237 (14.7) | 40 (2.5) | |
| County of resettlement | < .01 | ||||
| Cuyahoga | 1330 (23.5) | 997 (74.9) | 293 (22.0) | 40 (3.0) | |
| Franklin | 2527 (44.6) | 2179 (86.2) | 316 (12.5) | 32 (1.3) | |
| Hamilton | 334 (5.9) | 268 (80.2) | 61 (18.3) | 5 (1.5) | |
| Lucas | 58 (1.1) | 53 (91.4) | 4 (6.9) | 1 (1.7) | |
| Montgomery | 427 (7.5) | 358 (83.8) | 60 (14.0) | 9 (2.1) | |
| Summit | 985 (17.4) | 545 (55.3) | 410 (41.6) | 30 (3.1) | |
| Time to postarrival medical screening, d | .06 | ||||
| ≤ 30 | 2323 (41.0) | 1755 (75.5) | 513 (22.1) | 55 (2.4) | |
| 31–60 | 2445 (43.2) | 1930 (79.0) | 468 (19.1) | 47 (1.9) | |
| 61–90 | 733 (12.9) | 582 (79.4) | 138 (18.8) | 13 (1.8) | |
| > 90 | 160 (2.9) | 138 (83.1) | 25 (15.6) | 2 (1.2) | |
Other countries (n = 197) comprise Cameroon (1), Central African Republic (15), Colombia (17), Cuba (6), Ecuador (3), Egypt (3), Gabon (3), Georgia (2), Guinea (2), Haiti (1), Iran (7), Jordan (7), Kenya (8), Liberia (2), Malaysia (7), Mauritania (4), Moldova (1), Pakistan (28), Palestine (9), Russia (10), Rwanda (12), Saudi Arabia (1), South Sudan (4),Tanzania (1), Thailand (2), Togo (4), Turkey (2), Uganda (6), Uzbekistan (14), Vietnam (4), Yemen (4), and Zimbabwe (7).
Overall, 4400 (77.7%), 1144 (20.2%), and 117 (2.1%) had BLL less than 5, 5 to 10, and greater than 10 μg/dL, respectively (Table 1). Table 2 presents the prevalence of EBLL and its association with various demographic and resettlement characteristics. The children younger than 6 years had the highest prevalence among all age groups at 27.0% (95% CI = 25.2, 28.8); male children had higher prevalence than female children (24.7% vs 19.7%; P < .01); and Afghani children had the highest prevalence (56.2%; 95% CI = 48.1, 64.3) among all countries of origin. The EBLL prevalence declined from 24.4% to 16.9% with the increase in the TPaMS from 30 days to more than 90 days. In a multivariable modified Poisson regression analysis, children who were younger than 13 years, male, and from Afghanistan, Bhutan, Burma, Congo, the DRC, Iraq, Nepal, Somalia, Sudan, and “other countries” had significantly higher EBLL prevalence compared with those who were aged 13 years or older, female, and resettled from Syria. The year of resettlement was significantly associated with EBLL, with those resettled before 2015 having higher prevalence than those resettled in 2016. Those screened within 30 days had 1.7 times the prevalence of EBLL of those screened 90 days after arrival (Table 2).
TABLE 2—
Association Between Demographic and Resettlement Characteristics and Elevated Blood Lead Level Among Resettled Refugee Children Younger Than 18 Years: Ohio, 2009–2016
| EBLL (≥ 5 µg/dL) |
||||
| % (95% CI) | Prevalence, % (95% CI) | Unadjusted PR (95% CI) | Adjusteda PR (95% CI) | |
| Overall (n = 5661) | 100.0 | 22.3 (21.2, 23.3) | . . . | . . . |
| Age group, y | ||||
| < 6 | 42.0 (40.7, 43.3) | 27.0 (25.2, 28.8) | 2.2 (1.8, 2.8) | 2.0 (1.6, 2.6) |
| 6 to < 13 | 47.2 (45.9, 48.5) | 20.4 (18.9, 21.9) | 1.7 (1.3, 2.1) | 1.6 (1.2, 2.0) |
| 13 to < 18 | 10.8 (9.9, 11.6) | 11.9 (9.4, 14.5) | 1 (Ref) | 1 (Ref) |
| Sex | ||||
| Male | 50.7 (49.4, 52.0) | 19.7 (18.3, 21.1) | 1.2 (1.1, 1.4) | 1.3 (1.1, 1.4) |
| Female | 49.3 (47.9, 52.0) | 24.7 (23.1, 26.3) | 1 (Ref) | 1 (Ref) |
| Country of origin | ||||
| Afghanistan | 2.5 (2.1, 2.9) | 56.2 (48.1, 64.3) | 16.1 (8.3, 31.1) | 12.8 (6.3, 26.0) |
| Bhutan | 28.3 (27.1, 29.5) | 32.7 (30.4, 35.9) | 9.4 (4.9, 17.9) | 6.8 (3.4, 13.5) |
| Burma | 8.2 (7.5, 8.9) | 31.8 (27.5, 35.9) | 9.1 (4.7, 17.5) | 5.6 (2.8, 11.5) |
| Burundi | 1.0 (0.8, 1.3) | 10.2 (2.4, 17.9) | 2.9 (1.1, 7.9) | 2.1 (0.7, 5.9) |
| Congo | 1.2 (0.9, 1.5) | 19.1 (9.8, 28.5) | 5.5 (2.4, 12.3) | 5.6 (2.3, 13.8) |
| Democratic Republic of Congo | 10.7 (9.9, 11.5) | 15.3 (12.4, 18.1) | 4.4 (2.2, 8.5) | 4.0 (1.9, 8.2) |
| Eritrea | 2.1 (1.7, 2.4) | 7.6 (2.8, 12.4) | 2.2 (0.9, 5.4) | 2.1 (0.8, 5.5) |
| Ethiopia | 1.1 (0.9, 1.4) | 4.6 (0.0, 9.7) | 1.3 (0.4, 4.7) | 1.4 (0.4, 5.4) |
| Iraq | 14.5 (13.6, 15.4) | 15.8 (13.3, 18.3) | 4.5 (2.3, 8.8) | 3.8 (1.9, 7.6) |
| Nepal | 1.6 (1.3, 1.9) | 43.9 (33.7, 54.1) | 12.6 (6.4, 24.9) | 9.7 (4.5, 20.8) |
| Somalia | 17.8 (16.8, 18.8) | 12.7 (10.6, 14.8) | 3.6 (1.9, 7.1) | 4.2 (2.1, 8.6) |
| Sudan | 1.8 (1.5, 2.2) | 23.3 (15.1, 31.5) | 6.7 (3.2, 13.9) | 5.5 (2.5, 12.1) |
| Ukraine | 0.9 (0.7, 1.2) | 5.7 (0.0, 11.9) | 1.6 (0.4, 5.8) | 1.1 (0.3, 4.3) |
| Other countriesb | 3.5 (3.0, 3.9) | 24.9 (18.8, 30.9) | 7.1 (3.6, 14.2) | 5.9 (2.8, 12.4) |
| Syria | 4.5 (4.0, 5.1) | 3.5 (1.2, 5.7) | 1 (Ref) | 1 (Ref) |
| Arrival year | ||||
| 2009 | 1.4 (1.1, 1.7) | 35.4 (25.0, 45.7) | 2.1 (1.5, 2.8) | 2.3 (1.5, 1.4) |
| 2010 | 7.3 (6.6, 8.0) | 31.3 (26.9, 35.8) | 1.8 (1.5, 2.2) | 1.7 (1.3, 2.1) |
| 2011 | 6.2 (5.6, 6.8) | 28.1 (23.4, 32.8) | 1.6 (1.3, 1.9) | 1.4 (1.1, 1.8) |
| 2012 | 9.4 (8.7, 10.2) | 27.6 (24.4, 30.8) | 1.6 (1.4, 1.9) | 1.4 (1.1, 1.7) |
| 2013 | 12.9 (12.1, 13.8) | 27.6 (24.4, 30.8) | 1.6 (1.4, 1.9) | 1.7 (1.4, 2.1) |
| 2014 | 14.7 (13.8, 15.6) | 17.5 (14.9, 20.1) | 1.0 (0.8, 1.2) | 1.0 (0.8, 1.2) |
| 2015 | 19.4 (18.3, 20.4) | 20.8 (18.4, 23.2) | 1.2 (1.0, 1.4) | 1.2 (1.0, 1.5) |
| 2016 | 28.5 (27.3, 29.7) | 17.2 (15.3, 19.0) | 1 (Ref) | 1 (Ref) |
| County of resettlement | ||||
| Cuyahoga | 23.5 (22.4, 24.6) | 25.0 (22.7, 27.4) | 2.9 (1.2, 6.7) | 1.3 (0.5, 3.3) |
| Franklin | 44.6 (43.3, 45.9) | 13.8 (12.4, 15.1) | 1.6 (0.7, 3.7) | 0.7 (0.3, 1.7) |
| Hamilton | 5.9 (5.3, 6.5) | 19.8 (15.5, 24.0) | 2.3 (0.9, 5.4) | 0.9 (0.3, 2.3) |
| Montgomery | 7.5 (6.8, 8.2) | 16.1 (12.7, 19.6) | 1.9 (0.8, 4.4) | 1.0 (0.4, 2.6) |
| Summit | 17.4 (16.4, 18.4) | 44.7 (41.6, 47.8) | 5.2 (2.2, 12.0) | 1.7 (0.7, 4.4) |
| Lucas | 1.0 (0.8, 1.3) | 8.6 (1.4, 15.8) | 1 (Ref) | 1 (Ref) |
| Time to postarrival medical screening, d | ||||
| ≤ 30 | 41.0 (39.7, 42.3) | 24.4 (22.7, 26.2) | 1.4 (1.0, 2.0) | 1.7 (1.1, 2.5) |
| 31–60 | 43.2 (41.9, 44.5) | 21.1 (19.4, 22.7) | 1.2 (0.9, 1.8) | 1.4 (0.9, 2.1) |
| 61 to 90 | 12.9 (12.1, 13.8) | 20.6 (17.7, 23.5) | 1.2 (0.8, 1.8) | 1.3 (0.9, 2.0) |
| > 90 | 2.8 (2.4, 3.2) | 16.9 (11.1, 22.7) | 1 (Ref) | 1 (Ref) |
Note. CI = confidence interval; EBLL = elevated blood lead level; PR = prevalence ratio.
Adjusted for age group, sex, year of arrival, country of origin, county of resettlement, and time to postarrival medical screening.
EBLL among other countries (no. of children with EBLL/total no. of children): Cameroon (0/1), Central African Republic (5/15), Colombia (5/17), Cuba (1/6), Ecuador (1/3), Egypt (0/3), Gabon (2/3), Georgia (2/2), Guinea (1/2), Haiti (1/1), Iran (0/7), Jordan (0/7), Kenya (3/8), Liberia (2/2), Malaysia (0/7), Mauritania (3/4), Moldova (0/1), Pakistan (9/28), Palestine (4/9), Russia (0/10), Rwanda (3/12), Saudi Arabia (0/1), South Sudan (0/4), Tanzania (0/1), Thailand (1/2), Togo (1/4), Turkey (0/2), Uganda (3/6), Uzbekistan (0/14), Vietnam (2/4), Yemen (0/4), and Zimbabwe (0/7).
Table 3 presents demographics and resettlement characteristics of children younger than 6 years. The EBLL prevalence in the subsample was 27.1% (95% CI = 25.2, 28.8). Children aged 12 to 23 months had the highest EBLL prevalence at 32.4% (Figure 1). Afghani and Bhutanese children had the highest prevalence of EBLL at 75.7% (95% CI = 65.7, 85.8) and 39.9% (95% CI = 35.9, 43.4), respectively. In a multivariable modified Poisson regression analysis, children aged 12 to 23 months, and those from Afghanistan, Bhutan, Burma, the DRC, Nepal, Somalia, and “other countries” were significantly more likely to have a higher EBLL prevalence than children aged 60 to less than 72 months and from Syria, respectively. The TPaMS was inversely associated with EBLL prevalence (Table 3).
TABLE 3—
Association Between Demographic and Resettlement Profile and Elevated Blood Lead Level Among Resettled Refugee Children Younger Than 6 Years: Ohio, 2009–2016
| EBLL (≥ 5 µg/dL) |
||||
| % (95% CI) | Prevalence, % (95% CI) | Unadjusted PR (95% CI) | Adjusteda PR (95% CI) | |
| Overall (n = 2378) | 100.0 | 27.1 (25.2, 28.8) | . . . | . . . |
| Age group, mo | ||||
| < 12 | 6.7 (5.7, 7.7) | 23.3 (16.7, 29.8) | 1 (Ref) | 1 (Ref) |
| 12 to < 24 | 19.6 (17.9, 21.2) | 32.4 (28.1, 36.6) | 1.4 (1.0, 1.9) | 1.4 (1.0, 2.1) |
| 24 to < 36 | 19.0 (17.5, 20.6) | 25.6 (21.6, 29.6) | 1.1 (0.8, 1.5) | 1.2 (0.9, 1.8) |
| 36 to < 48 | 17.1 (15.6, 18.6) | 25.8 (21.5, 30.0) | 1.1 (0.8, 1.5) | 1.2 (0.8, 1.8) |
| 48 to < 60 | 19.2 (17.7, 20.8) | 24.9 (20.9, 28.8) | 1.1 (0.8, 1.5) | 1.2 (0.8, 1.8) |
| 60 to < 72 | 18.3 (16.7, 19.8) | 27.6 (23.4, 31.8) | 1.2 (0.9, 1.0) | 1.2 (0.8, 1.8) |
| Sex | ||||
| Male | 49.2 (47.2, 51.2) | 25.9 (23.4, 28.4) | 1.1 (0.9, 1.2) | 1.1 (0.9, 1.3) |
| Female | 50.8 (48.8, 52.8) | 28.2 (25.6, 30.8) | 1 (Ref) | 1 (Ref) |
| Country of origin | ||||
| Afghanistan | 2.9 (2.3, 3.6) | 75.7 (65.7, 85.8) | 8.6 (4.5, 16.2) | 8.0 (3.9, 16.5) |
| Bhutan | 28.5 (26.7, 30.3) | 39.7 (35.9, 43.4) | 4.5 (2.4, 8.4) | 3.6 (1.8, 7.4) |
| Burma | 10.3 (9.1, 11.6) | 30.9 (25.1, 36.7) | 3.5 (1.8, 6.7) | 2.6 (1.2, 5.5) |
| Burundi | 1.0 (0.6, 1.4) | 20.8 (4.6, 37.1) | 2.4 (0.9, 6.4) | 1.7 (0.5, 5.3) |
| Congo | 0.9 (0.5, 1.3) | 22.7 (5.2, 40.2) | 2.6 (0.9, 6.9) | 2.8 (0.8, 8.1) |
| Democratic Republic of Congo | 8.8 (7.6, 9.9) | 25.0 (19.1, 30.9) | 2.8 (1.4, 5.5) | 2.6 (1.2, 5.3) |
| Eritrea | 1.9 (1.4, 2.5) | 13.0 (3.3, 22.8) | 1.5 (0.5, 3.9) | 1.7 (0.6, 4.9) |
| Ethiopia | 1.2 (0.8, 1.7) | 6.9 (0.0, 16.1) | 0.8 (0.2, 3.4) | 0.9 (0.2, 4.3) |
| Iraq | 16.1 (14.7, 17.6) | 16.1 (12.5, 19.8) | 1.8 (0.9, 3.5) | 1.7 (0.8, 3.6) |
| Nepal | 1.6 (1.1, 2.1) | 43.6 (28.0, 59.1) | 4.9 (2.4, 10.1) | 4.4 (1.8, 10.4) |
| Somalia | 16.3 (14.8, 17.8) | 12.9 (9.5, 16.2) | 1.5 (0.7, 2.9) | 1.9 (0.9, 3.9) |
| Sudan | 1.9 (1.3, 2.4) | 26.7 (13.7, 39.6) | 3.0 (1.4, 6.6) | 2.9 (1.2, 7.3) |
| Ukraine | 1.0 (0.6, 1.5) | 12.0 (0.0, 24.7) | 1.4 (0.4, 4.6) | 1.1 (0.3, 4.1) |
| Other countriesb | 3.0 (2.3, 3.7) | 30.5 (19.9, 41.2) | 3.5 (1.7, 7.1) | 3.2 (1.4, 7.2) |
| Syria | 4.3 (3.4, 5.1) | 8.8 (3.3, 14.3) | 1 (Ref) | 1 (Ref) |
| Arrival year | ||||
| 2009 | 2.1 (1.6, 2.7) | 29.4 (16.9, 41.9) | 1.1 (0.7, 1.8) | 1.7 (1.0, 3.0) |
| 2010 | 10.3 (9.1, 11.5) | 33.1 (27.2, 38.9) | 1.3 (1.0, 1.6) | 1.6 (1.2, 2.1) |
| 2011 | 7.6 (6.5, 8.6) | 28.3 (21.7, 34.9) | 1.1 (0.8, 1.4) | 1.2 (0.8, 1.7) |
| 2012 | 10.9 (9.6, 12.1) | 30.5 (24.9, 35.5) | 1.2 (0.9, 1.5) | 1.2 (0.9, 1.7) |
| 2013 | 12.1 (10.8, 13.4) | 30.2 (24.9, 35.5) | 1.2 (0.9, 1.5) | 1.4 (1.1, 1.9) |
| 2014 | 14.3 (12.9, 15.7) | 21.4 (17.0, 25.8) | 0.8 (0.6, 1.1) | 0.8 (0.6, 1.1) |
| 2015 | 17.3 (15.8, 18.8) | 24.7 (20.6, 28.9) | 0.9 (0.8, 1.2) | 1.1 (0.8, 1.4) |
| 2016 | 25.3 (23.6, 27.1) | 25.7 (22.2, 29.2) | 1 (Ref) | 1 (Ref) |
| County of resettlement | ||||
| Cuyahoga | 23.4 (21.7, 25.1) | 33.0 (29.1, 36.9) | 2.4 (0.8, 6.9) | 1.6 (0.5, 5.4) |
| Franklin | 45.4 (43.4, 47.5) | 15.4 (13.3, 17.6) | 1.1 (0.4, 3.3) | 0.8 (0.2, 2.6) |
| Hamilton | 5.3 (4.4, 6.2) | 21.4 (14.2, 28.6) | 1.6 (0.5, 4.7) | 0.9 (0.3, 3.2) |
| Montgomery | 6.8 (5.7, 7.8) | 22.4 (15.9, 28.8) | 1.6 (0.5, 4.9) | 1.3 (0.4, 4.5) |
| Summit | 18.1 (16.6, 19.7) | 52.4 (47.7, 57.1) | 3.8 (1.3, 11.0) | 2.0 (0.6, 6.6) |
| Lucas | 0.9 (0.5, 1.3) | 13.6 (0.0, 27.9) | 1 (Ref) | 1 (Ref) |
| Time to postarrival medical screening, d | ||||
| ≤ 30 | 39.4 (37.5, 41.4) | 30.2 (27.2, 33.1) | 2.0 (1.2, 3.5) | 2.3 (1.3, 4.2) |
| 31–60 | 43.2 (41.2, 45.2) | 26.2 (23.5, 28.8) | 1.8 (1.0, 3.0) | 1.9 (1.1, 3.5) |
| 61 to 90 | 13.9 (12.5, 15.3) | 23.9 (19.3, 28.5) | 1.6 (0.9, 2.8) | 1.7 (0.9, 3.2) |
| > 90 | 3.4 (2.7, 4.1) | 14.8 (7.1, 22.5) | 1 (Ref) | 1 (Ref) |
Note. CI = confidence interval; EBLL = elevated blood lead level; PR = prevalence ratio.
Adjusted for age group, sex, year of arrival, country of origin, county of resettlement, and time to postarrival medical screening.
EBLL among other countries (no. of children with EBLL/total no. of children): Central African Republic (2/3), Colombia (4/7), Cuba (0/2), Ecuador (1/3), Gabon (1/2), Guinea (1/1), Haiti (1/1), Iran (0/1), Jordan (0/3), Kenya (0/2), Malaysia (0/6), Mauritania (2/2), Moldova (0/1), Pakistan (4/10), Palestine (2/3), Russia (0/4), Rwanda (1/2), South Sudan (0/1), Thailand (1/2), Turkey (0/2), Uganda (1/3), Uzbekistan (0/3), Vietnam (1/2), Yemen (0/1), and Zimbabwe (0/5).
FIGURE 1—
Prevalence of Blood Lead Level (BLL) 5–10 µg/dL and > 10 µg/dL Among Resettled Refugee Children Younger Than 6 Years: Ohio, 2009–2016
Note. Whiskers indicate 95% confidence intervals.
DISCUSSION
In this study conducted among refugee children resettled in Ohio from 2009 to 2016, 22.3% and 27.1% of children younger than 18 years and younger than 6 years, respectively, had an EBLL. The 22.3% EBLL prevalence observed in the overall sample was twice the 11.2% prevalence reported in a sample of resettled refugee children younger than 15 years in Kentucky by Kotey et al.24 The observed differences may be explained by the difference in the countries of origin in the 2 samples. The study by Kotey et al., with a sample size of 1950, predominantly included children from countries of origin in sub-Saharan Africa and the Middle East. Our study, with a sample size of 5661, included a greater diversity of countries of origin, and the majority of the children were from South Asia including Bhutan, Burma, and Afghanistan. The observed EBLL prevalence difference in the 2 studies highlights the differing risk of EBLL among various resettled refugee populations in the United States. Public health professionals, clinicians, and resettlement and social service agency personnel need to be aware of these differences in providing clinical, preventive, educational, and social services to address the lead risks and hazards.
The observed EBLL prevalence in our study was almost 4- to 7-fold higher than the US national prevalence (4.7%) and the Ohio state prevalence (6.7%) in children younger than 6 years.28 Our results are consistent with previous reports of about 5-fold-higher EBLL levels among US resettled refugee children than nonrefugee children.14 While the countries of origin change over time, refugee children continue to be a high-risk group for EBLL at resettlement in the United States. Addressing the issue of EBLL in these high-risk children at resettlement and after resettlement is critical not only for their health and well-being but also for achieving the Healthy People 2020 goals.
With 46 countries of origin, this study is reporting EBLL prevalence in one of the most diverse group of resettled refugee children in the United States. Our results are consistent with previously reported EBLL prevalence among several refugee groups, while providing new estimates among previously unreported groups. A multistate study published in 2016 by Yun et al. reported EBLL prevalence ranging from 13.1% for Ethiopian to 26.8% for Bhutanese children younger than 8 years.22 In our study, the EBLL prevalence ranged from 8.8% for Syrian children to 75.7% for Afghani children younger than 6 years. The prevalence of 56.2% among Afghani children younger than 18 years and 75.7% for children younger than 6 years are the highest EBLL prevalence ever reported in a US resettled population. The Afghani children not only had a high prevalence of BLL of 5 µg/dL or higher but also had a high prevalence of BLL greater than 10 µg/dL (19.4%). Burmese and Bhutanese children also exhibited high EBLL prevalence at 32.7% and 31.8%, respectively.
The high EBLL prevalence observed in Afghani, Nepali, Bhutanese, and Burmese children in our study is likely associated with lead exposures related to cultural and environmental factors in their countries of origin.18,19,29,30 In Afghani, Nepali, and Bhutanese customs, the use of an eye cosmetic, called kajal or surma, in infants and young children is a common practice, and these products have been found to contain high levels of lead.18,19,29 A 2013 case series published in Morbidity and Mortality Weekly Report involving 2 Afghani refugee siblings with BLL of greater than 25 µg/dL found that the kajal brought from Afghanistan and used by the family contained 54% lead.18 A study of lead content in eye cosmetic products from Afghanistan reported 70% of the sample with lead content of 35% to 83%.29
Bhutanese refugees are ethnic Nepali and lived in refugee camps in Nepal before US resettlement. Therefore, the children from the Nepali and Bhutanese groups share common environmental and social-cultural sources of potential lead exposures in Nepal. A study of environmental lead in Kathmandu Valley in Nepal found that 64.4% of children aged 6 to 36 months had an EBLL, and children who played outside had 4.5 times the odds of EBLL than those who did not.30 Moreover, lead-based paints are still commonly used in Nepal for painting dwellings and in other consumer products.31 A case–control study conducted in Burmese refugee camps in Thailand reported exposure to automotive batteries and the use of traditional remedies such as wonotsay (a digestive aid commonly given to children) and cosmetics contaminated with lead and arsenic as potential sources.15 The results of our study, along with the host country studies on the sources of socio-cultural environmental lead exposures, support the observation of EBLL at the postarrival medical screening as a result of the prearrival exposures.
For children from Africa, Asia and the Pacific region, and Latin America and the Caribbean—3 regions of origin for most of the US resettled refugees—the continued use of lead in paint and the increasing production, use, and improper disposal of LABs are likely the major sources of lead exposure.32–34 A study of enamel-based paint samples from several Asian countries found extremely high levels of lead including 76% and 25% with concentrations greater than 90 parts per million and greater than 10 000 parts per million, respectively.35 Only 11.1%, 20.5%, and 33.0% of the countries in Africa, Asia and the Pacific region, and Latin America and the Caribbean, respectively, have lead laws limiting the production, import, and sale of lead-based paints.31 Even in countries with restrictions on lead paint, enforcement remains problematic as evident from high lead levels in paints sold in many countries with such laws.31,35
This highlights the complexities and challenges in addressing the problem of the use of lead in consumer products. In fact, in the past 2 decades, the production of LABs has dramatically increased in countries such as China for widespread use in many products including automobiles, electric bikes, and photovoltaic systems worldwide.34 The production processes, as well as improper recycling and disposal of LABs, is a growing source of environmental lead contamination, imperiling the health and lives of populations in low- and middle-income countries where 97% of LABs are recycled or disposed.33
The greater than 5% prevalence of EBLL in children from 13 of 14 countries in the study highlights the continued risk of lead exposure faced by children from many parts of the world. While the formation of the Global Alliance to Eliminate Lead Paint in 2011 is a positive step toward addressing this salient global public health problem,32 addressing the issue of improper handling, recycling, and disposal of LABs must also be a global priority.
In our study, 97% of the postarrival medical screenings were conducted within 90 days of resettlement and the observed BLLs are likely a proxy for the children’s lead exposure before their US resettlement. This is supported by the observation of declining prevalence of EBLL with the increasing TPaMS. However, this does not mean that these children are not at risk for exposure to lead in the United States. Many of the socio-cultural sources of lead exposure such as the use of eye cosmetics, traditional herbs, and costume jewelries containing lead may persist in the United States. In addition, most of the refugees are resettled in older houses where their exposure to environmental lead is likely at a higher rate than that of the general US population.
In Ohio, most refugees are resettled in counties with large metropolitan areas such as Columbus, Cleveland, and Akron. Children in the inner-city neighborhoods in these metropolitan areas in Ohio have higher rates of childhood exposure to lead than children from other neighborhoods because of the higher proportion of older houses with lead-based paints.36,37 The 2016 Summit County Ohio Community Health Assessment Report estimated that 73% of houses in the county, which includes the Akron Metropolitan Area, were built before 1978.38 The majority of Afghani, Bhutanese, and Burmese children were resettled in Cuyahoga and Summit counties in Ohio, which puts them at increased risk for lead exposure after resettlement. As an example, after 7 months of living in the west side of Cleveland, a 3-year-old Iraqi resettled refugee child was hospitalized for lead poisoning with a BLL of 125 µg/dL as a result of environmental lead exposure at home.37 Because resettled refugee children are at higher risk for exposure to lead before and after arrival in the United States, the need for comprehensive guidelines for public health and resettlement agency personnel to address the risk of lead exposure and prevention strategies in these communities is urgent and critical.
Strengths and Limitations
Our study, with 46 countries of origin and a substantially large sample size for 14 countries, presents EBLLs from the most diverse group of resettled refugee children in the United States since the 2012 CDC definition change for elevated levels. These results from diverse subgroups of children provide important baseline prevalence of EBLL at the time of resettlement. Although we cannot be fully certain that observed lead levels in these children are exclusively attributable to prearrival exposures, thus a limitation of the study, the facts that 97.1% of the children had their medical screening within 3 months of arrival and declining EBLL with increasing TPaMS suggest that the likely sources of exposure are in the country of origin. The decline in prevalence of EBLL among the children with increasing TPaMS also suggests that the level of exposure in the United States is likely lower than that in the host countries. To delineate the pre- and postarrival exposure, longitudinal studies in the US-resettled refugees are needed.
While the sample only includes Ohio-resettled children, thus potentially limiting the generalizabity of the findings to the entire population of US-resettled refugees, a large sample size, diverse countries of origin, and 8 years of resettlement data provide a sound basis for estimating the EBLL prevalence in children from 14 countries of origin. This study also provides some indication of EBLLs among children in the countries of origin represented in the sample. Future studies in the countries of origin in Asia and Africa should be conducted to assess the risk of lead exposure among children and potential short- and long-term effects in these children.
Conclusions
The increasing risk of lead exposure in children globally and the continually changing profile of resettled refugee groups in the United States necessitates epidemiological studies with the most up-to-date demographic and BLL data to understand the current situation related to lead exposure among these new and vulnerable children. While overall the observed EBLLs in the resettled refugee children are substantially higher than those reported in US-born children, a wide disparity in BLL exists within the refugee subgroups. Clinical, public health, and social services professionals must be aware of the disparity and, thus, the varying needs by refugee groups when providing clinical, preventive, and social services related to lead exposure.
These findings also highlight the need for comprehensive,7 but tailored, guidelines for these groups for prevention and awareness programs. The resettlement agency personnel also must be cognizant of the lead risk in the housing where they settle newly arriving refugees and should provide educational and informational materials related to lead during the initial phases of the resettlement process to create awareness of the issue in these high-risk groups. Exposure to any level of lead is harmful for children, and mitigation of potential exposure after arrival in the United States will prevent further adverse effects in many of these already exposed children.
ACKNOWLEDGMENTS
The authors would like to thank the Ohio Department of Job and Family Services for providing the data for this study.
Note. The contents of this article are solely the responsibility of the authors and do not necessarily represent the official views of the Ohio Department of Job and Family Services.
CONFLICTS OF INTEREST
The authors have no conflicts of interest to disclose.
HUMAN PARTICIPANT PROTECTION
This study was approved by the institutional review board at Kent State University as a level I (exempt) review.
Footnotes
See also Jacobs, p. 830.
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