Behaviors and blood lead levels of children in a lead-mining area and a comparison community.

Introduction

The Centers for Disease Control and Prevention (CDC) considers lead poisoning the number-one preventable pediatric environmental health problem facing children today (1). Government agencies are currently working on lead hazard control. The U.S. Environmental Protection Agency (U.S. EPA) regulates lead in air, water, soil, and other media. The Agency for Housing and Urban Development (HUD) focuses on abatement of lead paint, and CDC focuses on the identification and treatment of children with lead poisoning. These federal programs for lead reduction are directed to only a few of the most relevant aspects of lead poisoning and are poorly coordinated (2).

To support this federal effort, communities must become active participants in an organized effort to reduce childhood lead poisoning. Because lead poisoning is so serious and so poorly reversed by treatment, it is important that communities understand how lead exposure occurs, how lead affects exposed individuals, and how to actively participate in primary and secondary prevention (3).

This article presents data on the relationships among behavior, household factors, and blood lead levels in children living in a lead-mining area. The children studied are exposed not only to the most common source of exposure, lead-based paint, but also to soil and dust from lead-mining waste.

Considerable research has indicated the sources of lead exposure for children: soil, paint, dust, and so forth (4). There has been little research, however, to indicate what steps, other than removing lead from the children's environment or removing the children from the contaminated environment, are the most likely to reduce blood lead levels (5-7).

Children's hygiene and eating and playing behaviors have not been given sufficient attention in research activities related to ingestion of lead. Childhood exposure to lead is primarily through ingestion. Surface dust and soil may be ingested by normal hand-to-mouth activity. Byers noted that hand-to-mouth behavior has been recognized as a factor in children's lead poisoning since the beginning of the century, but was disregarded until Rabin re-emphasized the importance of this behavior in lead exposure (8,9). Hand-to-mouth behavior is relevant in small children, especially in children six to 72 months of age. It is most important in children six to 24 months of age, for whom exposure is heaviest. Exposure from hand-to-mouth activity has been documented in several studies (3,10-13).

Some children may swallow nonfood items such as paint chips and soil - a condition called pica. Lead may be ingested when children playing outdoors contaminate their hands, toys, and food items with soil and put these items in their mouths. Other sources of exposure are atmospheric entry of soil into houses and soil brought indoors by animals or human beings (on bodies, clothes, and shoes). Calabrese and Stanek determined that approximately 30 percent of household dust was derived from outdoor soil and that the remaining 70 percent came from other sources such as deteriorating lead paint (14). The soil contaminates hands and other items inside the house, much as it does outdoors.

The study presented here investigates the relationship between behavioral and other modifiable factors and blood lead levels in children. The data represent a subsample of a blood lead prevalence study reported in a previous study (12). In that study, 14 percent of children living in the lead-mining area had blood lead levels greater than 10 micrograms per deciliter ([[micro]gram]/dL), a level of concern established by CDC (1). Zero percent of children living in a comparison area had blood lead levels greater than 10 [[micro]gram]/dL.

TABLE 1

Demographic Characteristics of Study and Control Groups

                                   Study Group       Control Group
Characteristic                   Number   Percent   Number   Percent

Gender
Male                              122       50.2      62       44.9
Female                            121       49.8      76       55.1

Race
White                             233       95.9     131       94.9
Black                               2        0.8       3        2.2
Asian/Pacific Islander              0        0.0       0        0.0
American Indian/Alaska Native       7        2.9       3        2.2

Income/Year
[less than]$15,000                 54       23.0      24       18.0
$15,000-$24,999                    65       27.4      34       26.2
[greater than]$25,000             117       49.6      73       55.8

Education of Head of Household
[less than]9th Grade                3        1.2       0          0
[less than] 12th Grade             34       14.2       9        6.5
High school graduate               90       37.7      62       44.9
Some college or technical         112       46.9      67       48.6

Year Home Built(*)
Before 1960                       151       62.1      42       30.8
1960-1979                          40       16.5      73       52.9
1980-present                       52       21.4      23       16.7

* p [less than] .001 (Chi square)

[TABULAR DATA FOR TABLE 2 OMITTED]

Methods

The sampling frame was determined through a census of all of the homes in the study and in the control areas to [ind children eligible for the study. From this list, children six to 71 months of age who had lived at their current residences for a least 60 days were randomly selected for the study with computer-generated numbers.

The study area was the Jasper County, Missouri, Superfund Site, which was contaminated with lead-mining waste. This area included portions of Webb City and Joplin and all of Duenweg and Carterville. The control area was chosen to be socioeconomically similar, geographically close, but physically outside the lead-mining area. It included parts of Neosho and all of Goodman, Missouri.

Participants were interviewed, and blood was collected at centrally located sites in the study and control areas. Specimen collection and analysis were performed according to specifications of the Environmental Health Laboratory Sciences Division of CDC. The division performed the blood lead analyses using the Zeeman graphic furnace atomic absorption method. Quality control was established by duplicate analysis of whole blood pools, where target values were established by thermal-ionization, isotopic-dilution mass spectroscopy.

The study also took measurements of environmental lead in a sample of study and control homes for lead in drinking water, soil, house dust, and interior house paint. All environmental sampling and analysis was done by U.S. EPA under a standard protocol. Soil and dust were analyzed for lead using EPA SW-846, Method 3050, for digestion and EPA SW-846, Method 7420, for analysis.

Lead paint was classified as present in the home if it was detected by X-ray fluorescence (XRF) in any areas inside the home in which the child played. The soil lead value of 150 parts per million (ppm) was chosen as the background level because this value was approximately equal to the mean plus two standard errors of the mean from the control area.

Statistical analysis was performed using the Statistical Package for the Social Sciences (SPSS). Statistical significance was set at .05 with two-tailed tests of significance, but p values of .10 were considered of interest for designing a health intervention strategy. Stepwise regression used a p value of .10 to enter data and .20 to remove data.

Results

Table 1 presents demographic and socioeconomic characteristics of the study and control groups. The only characteristic that differed between groups was age of house. A higher percentage of homes in the study area were built before 1960 (p [less than] .001). A similar percentage of homes were built after 1980 in the control area. There were 243 children in the study group and 138 in the control group. Blood samples for lead were obtained from 225 study and 128 control participants. Questionnaire data on behavioral risk factors were obtained for all children. Environmental measurements were taken in 125 study and 26 control homes.

Table 2 compares environmental data and blood lead levels of the study and control [TABULAR DATA FOR TABLE 3 OMITTED] [TABULAR DATA FOR TABLE 4 OMITTED] groups. All measures of environmental lead were considerably higher in the study group, except for lead in water. Average blood lead levels were almost twice as high in study area children as in control children.

Table 3 presents a comparison of mean blood lead levels for various dichotomous behavioral and demographic factors in the study and control groups. Some factors are specific to children, and other factors relate to the households where children live.

Several behavioral variables show statistically significant differences between the blood lead levels in children practicing a behavior thought to be related to blood lead levels and the levels in children not practicing that behavior. Among children who played outdoors, those who played in areas that had grass cover had lower blood lead levels than children who played in dirt or other nonvegetated areas. Children in the mining area who took food, snacks, or other food-related items outside had higher blood lead levels than children who did not.

Several variables showed no statistically significant differences. For example, children who played outdoors were expected to have higher blood lead levels than children who played primarily indoors, especially in the mining area, where high lead levels were found in the soil. The lack of difference actually found might be due to the relatively small number of children who never played outside.

A number of factors in the control group had p values less than .10 - of interest because this pattern showed up again in the regression analysis. These factors included

* plays outdoors,

* washes before eating,

* has used pacifier, and

* sucks thumb.

Table 4 presents household characteristics that might be related to blood lead levels. Children living in homes that are rented have higher blood lead levels than children living in owner-occupied homes. The presence of copper water pipes, at least in homes in the mining area, is related to higher blood lead levels. Other factors listed in Table 4, which had been suggested as related to blood lead levels, were not statistically significant, with one exception: in the control group, if a family member repaired radiators, children living in that household had higher blood lead levels.

Table 5 presents regression coefficients of blood lead levels and behavioral and demographic factors for the study and control groups. Stepwise regression was used to select variables. Because the factors were being evaluated for inclusion in an intervention plan and because addressing these behaviors is a low-cost intervention, a liberal inclusion criteria of p of [less than].25 was used. As a result, variables were included that do not conform to the accepted significance level of .05. Those variables are, however, suggestive of behaviors that should be modified. Thirteen factors and 12 factors were related to the log of blood lead values for the control group and the study group, respectively.

Discussion

Devising low-cost, low-technology interventions for controlling lead hazards is important in reducing the risk of lead poisoning among children. According to CDC, the only way to ensure that a child will not be poisoned is to remove or cover all sources of lead such as indoor lead paint and lead-contaminated soil. CDC recognizes, however, that this is not economically feasible in the short term. Interim measures must be developed to immediately address the needs of the millions of children at risk for lead poisoning.

Health education in the home and in the community should be directed toward factors that can be modified to reduce exposure. These factors include

* keeping painted surfaces in repair;

* use of non-lead-based paint on repaired surfaces; and

* common hygiene measures such as

- frequent wet-mopping of floors, - wet-cleaning of window areas, - regular washing of children's hands, - washing of toys and pacifiers, - not taking food or drink outside, and - vegetating areas where children play.

It is of great importance that educational interventions address these factors in communities where soil is the major source of lead; of all remedial activities, the removal of lead from soil is the least likely to occur because of the high costs associated with such removals (3). On average, it costs $15,000 to remove contaminated soil from a medium-sized lot. Communities need to learn to live safely in an environment polluted with lead until a lead-free environment is achieved.

This study provides a unique perspective for looking at the relationship between some of the health behaviors listed above and blood lead levels. Two groups of children have been evaluated; one group (study) was exposed to high concentrations of lead in house dust, outdoor soil, and paint, while the other group (control) was exposed to dust levels that were on average three times lower, soil lead levels that were six times lower, and lead paint levels that were three times lower. Blood lead levels were twice as high in the study group.

The only demographic and socioeconomic difference between the two groups was that the age of the homes of the study group was older. This difference is reflected in the higher average paint lead concentrations in the study group.

In both groups, income was related to blood lead levels. Children from homes with lower family incomes have higher blood lead levels than children coming from higher-income homes. Families that have the lowest incomes are least likely to remove lead hazards from the home because of economic barriers. The children of these families are also at the highest risk for lead poisoning because of poorer nutritional status. This is consistent with the history of lead poisoning in the United States (3,13,15). The data suggest that priority in primary lead prevention should be given to low-income children, particularly those living in older homes.

Interventions that are directed toward low-income families must be sensitive to what strategies it is realistic to ask this group to perform. Suggesting full abatement of the home without providing resources for this abatement is not only doomed to failure, it is also insensitive. Parents want to protect their children but are limited by scarcity of resources. Other strategies, such as those suggested in this paper, should be tried immediately, until more expensive measures can be implemented.

The situation is further complicated if the home is rented. Children living in rental properties have higher blood lead levels than those living in owner-occupied homes. Renters are frequently fearful of being forced out of the home if they complain about lead exposure and are hesitant to perform expensive remedial work to a house to which they are only temporarily attached. When possible, intervention strategies should endeavor to work with landlords to help reduce the risk of exposure; however, until this can be brought about, low-cost interim measures must be implemented.

Children from homes where the head of the household had a lower level of education had higher blood lead levels. Although education was only significantly related to blood lead levels in the study group, education level should be considered in the design of any intervention, independently of the source of lead exposure. Interventions must be appropriate for all education levels and informational material should be written with this in mind.

Although different factors entered the regression model for the study and control groups, all factors should be considered when designing an educational intervention program (Table 5). Children should be encouraged to play in grassy areas and should be particularly discouraged from playing in dirt. Children who put nonfood items in their mouths have higher blood lead levels, and children should be encouraged not to do so. All toys and other play items that might be placed in the mouth should be washed on a regular basis. The regression coefficient for baths per week is positive, indicating that children who take more baths have higher blood lead levels. It is probably the case that the dirtier a child gets, the more often the child is given a bath. Children who wash after playing in dirt and wash before eating, however, have lower blood lead levels.

As expected, the more time a child spends playing outdoors in a mining area, the higher the blood lead levels. Some studies have indicated that children who eat vegetables from local gardens in mining areas have higher blood lead levels. This was not confirmed in this study. Children from homes with vegetable gardens had lower blood lead levels. This result might be an effect of better nutrition.

Some herbal medicines contain lead. Control children who took herbal medicines had [TABULAR DATA FOR TABLE 5 OMITTED] lower blood lead levels. Only in the study group was the direction of the coefficient as expected.

A few children were reported to have put paint chips in their mouths. This practice, as expected, resulted in higher blood lead levels. Children who sucked their thumbs had lower blood lead levels. Sucking thumbs is a powerful comforting habit, especially for younger children, and sucking a hand or a thumb may be more hygienic for a child than putting anything else in the mouth (16).

The regression factors explained only 29 percent of the variation in blood lead levels in the study group, compared with 48 percent of the variance in the control group. These results suggest that in lead-mining areas, where more sources of lead exist, behavioral factors may explain less of the increased blood lead levels than they do in areas of less exposure. But even in lead-mining and waste areas, interim measures should help reduce the lead risk to children. If the control group represents average blood lead levels when there is no exposure to lead-mining waste, then approximately half the average blood lead levels in the lead-mining area result from lead-based paint and hall from mining waste. Measures that reduce exposure either to lead paint or to mining waste should result in lower blood lead levels.

Our study suggests important points for primary prevention (i.e., preventing lead exposure from ever occurring). While federal programs are directed mostly to secondary prevention (i.e., paint removal in a dwelling after children have tested positive for lead) or tertiary prevention (i.e., treatment to alleviate neurological sequelae), primary prevention is left to the localities because education is historically provided by the local community.

Conclusion

Areas where high lead level exposure occurs represent a challenge and an opportunity for health education, public policy, and disease prevention. Lead intervention strategies thai include education to modify behavior may be less effective in areas of high lead exposure around lead-mining and smelting operations. Interventions that combine education with remedial activities are taking the right steps toward prevention of lead exposure. The use of multiple strategies in pursuit of aggregate results has real promise for health promotion in poorer segments of the community (17). Complete abatement has been virtually impossible to attain. Well-coordinated, combined approaches that include community participation through education, public policy, and health promotion and disease prevention represent a viable alternative.

Over the long term, lead education alone cannot be relied on to substantially lower blood lead levels in mining and smelting areas and possibly in other areas of high lead exposure. Measures such as removing and covering sources of lead exposure must eventually be implemented. Interim education and behavioral modification, however, are tools that can be of immediate benefit in reducing childhood lead poisoning.

Acknowledgements

This study was supported by a grant from the Agency for Toxic Substances and Disease Registry. U.S. Public Health Service, Department of Health and Human Services.

Corresponding Author: Dr. Ana Maria Murgueytio, School of Public Health, Saint Louis University, 3663 Lindell Bldv., St. Louis, MO 63108.

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