Lead Exposure and Cardiovascular Disease—A Systematic Review
Publication: Environmental Health Perspectives
Volume 115, Issue 3
Pages 472 - 482
Abstract
Objective
This systematic review evaluates the evidence on the association between lead exposure and cardiovascular end points in human populations.
Methods
We reviewed all observational studies from database searches and citations regarding lead and cardiovascular end points.
Results
A positive association of lead exposure with blood pressure has been identified in numerous studies in different settings, including prospective studies and in relatively homogeneous socioeconomic status groups. Several studies have identified a dose–response relationship. Although the magnitude of this association is modest, it may be underestimated by measurement error. The hypertensive effects of lead have been confirmed in experimental models. Beyond hypertension, studies in general populations have identified a positive association of lead exposure with clinical cardiovascular outcomes (cardiovascular, coronary heart disease, and stroke mortality; and peripheral arterial disease), but the number of studies is small. In some studies these associations were observed at blood lead levels < 5 μg/dL.
Conclusions
We conclude that the evidence is sufficient to infer a causal relationship of lead exposure with hypertension. We conclude that the evidence is suggestive but not sufficient to infer a causal relationship of lead exposure with clinical cardiovascular outcomes. There is also suggestive but insufficient evidence to infer a causal relationship of lead exposure with heart rate variability.
Public Health Implications
These findings have immediate public health implications. Current occupational safety standards for blood lead must be lowered and a criterion for screening elevated lead exposure needs to be established in adults. Risk assessment and economic analyses of lead exposure impact must include the cardiovascular effects of lead. Finally, regulatory and public health interventions must be developed and implemented to further prevent and reduce lead exposure.
Background
Cardiovascular disease is the leading cause of mortality and a primary contributor to the burden of disease worldwide (Lopez et al. 2006). Environmental toxicants, including lead and other metals, are potentially preventable exposures that may explain population variation in cardiovascular disease rates (Bhatnagar 2006; Weinhold 2004). However, after more than 100 years since initial reports suggested a link between lead exposure and cardiovascular outcomes (Lancéreaux 1881; Lorimer 1886), the contribution of lead to cardiovascular disease is still incompletely understood.
Population research on the cardiovascular effects of lead has focused largely on the association with blood pressure and hypertension. Several reviews and metaanalyses combining data from more than 30 original studies and around 60,000 participants have examined the evidence relating blood lead to blood pressure or hypertension [Hertz-Picciotto and Croft 1993; Nawrot et al. 2002; Schwartz 1995; Sharp et al. 1987; Staessen et al. 1994, 1995; U.S. Environmental Protection Agency (U.S. EPA) 2006]. All these reviews concluded that there was a positive association between blood lead levels and blood pressure (Table 1). The estimated increase in systolic blood pressure associated with a 2-fold increase in blood lead levels (e.g., from 5 to 10 μg/dL) ranged across reviews from 0.6 to 1.25 mmHg. This epidemiologic relationship is also supported by a large body of experimental and mechanistic evidence (U.S. EPA 2006). Because lead exposure is widespread, even a modest effect would imply that lead exposure is an important determinant of blood pressure levels and hypertension in human populations.
The cardiovascular effects of lead, however, are not limited to increased blood pressure and hypertension. Lead exposure has also been associated with an increased incidence of clinical cardiovascular end points such as coronary heart disease, stroke, and peripheral arterial disease (Lustberg and Silbergeld 2002; Menke et al. 2006; Navas-Acien et al. 2004; Schober et al. 2006), and with other cardiovascular function abnormalities such as left ventricular hypertrophy and alterations in cardiac rhythm (Cheng et al. 1998; Schwartz 1991).
In the present article, our objective was to perform a systematic review of the epidemiologic evidence on the association of lead exposure with cardiovascular disease end points. Because previous reviews have examined the connection between lead and blood pressure in depth (Table 1), our systematic review emphasizes other clinical and intermediate cardiovascular outcomes to obtain a broader picture of the impact of lead on cardiovascular disease. Finally, we assessed the causal role of lead on blood pressure and cardiovascular disease by applying the criteria and terminology of the 2004 Surgeon General Report The Health Consequences of Smoking [U.S. Department of Health and Human Services (U.S. DHHS) 2004] to the available information.
Methods
Search strategy and data abstraction
We aimed to identify all observational studies assessing the association between lead exposure and cardiovascular end points. Using free text and key words (Appendix A), we searched PubMed (http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed), EMBASE (http://www.embase.com/), and TOXLINE (http://toxnet.nlm.nih.gov/) through August 2006 with no language restrictions. In addition we manually reviewed the reference lists from relevant original research and review articles and documents.
For lead exposure, we included studies that used biomarkers (lead levels in blood, bone, or other specimens), environmental measures (airborne lead levels), or indirect measures (job titles, job exposure matrices, living in lead-contaminated areas). For cardiovascular end points, we included studies that reported clinical cardiovascular end points (cardiovascular disease, coronary heart disease, stroke, or peripheral arterial disease) and intermediate cardiovascular end points (left ventricular mass, heart rate, heart rate variability, or electrocardiographic abnormalities) other than blood pressure levels or hypertension.
We excluded publications containing no original research, studies not carried out in humans, case reports, case series, ecologic studies, studies lacking a cardiovascular outcome, and studies lacking data on lead exposure (Figure 1). For studies with multiple publications on the same population, we selected the publication with the longest follow-up. For studies with equivalent follow-up periods, we selected the study with the largest number of cases or the most recent publication. We excluded autopsy studies measuring lead in arterial tissue and studies based on polycardiography and ballistocardiograpy, techniques no longer in use. For consistency, blood lead levels were converted to micrograms per deciliter.
We adapted the criteria used by Longnecker et al. (1988) to assess study quality for studies of clinical end points and the criteria used by Appel et al. (2002) to assess study quality for studies of intermediate end points (Appendices B and C).
Statistical methods
Measures of association (odds ratios, prevalence ratios, standardized mortality ratios, relative risks, relative hazards, comparisons of means, linear regression coefficients, correlation coefficients) and their standard errors were abstracted or derived from published data (Greenland 1987). For studies reporting measures of association for population subgroups (Cooper et al. 1985; Malcolm 1971), we pooled the measures of association using an inverse-variance weighted random-effects model (Egger et al. 2001).
Because of substantial heterogeneity and methodologic limitations of the original studies, we considered that quantitative pooling was inappropriate. We thus present a qualitative systematic review of the available evidence.
Results
Lead and clinical cardiovascular disease in general populations
Twelve studies met our inclusion criteria (Table 2). Lead was measured in blood in all the prospective cohort studies (Kromhout 1988; Lustberg and Silbergeld 2002; Menke et al. 2006; Møller and Kristensen 1992; Pocock et al. 1988) and in the only cross-sectional study available (Muntner et al. 2005). Blood lead levels were substantially lower in more recent compared with older studies. Case–control studies assessed lead exposure on the basis of lead levels in blood (Kosmala et al. 2004), plasma (Mansoor et al. 2000), and urine (Pan et al. 1993; Tsai et al. 2004), on a job exposure matrix (Gustavsson et al. 2001), and on lead levels in the air of the residential neighborhood of study participants (Dulskiene 2003). None of these studies determined lead in bone. Although cohort studies and the cross-sectional study tended to fulfill prespecified quality criteria, case–control studies failed to fulfill some important quality criteria (Appendix B).
Lead exposure was positively associated with clinical cardiovascular end points in all studies (Table 2). Among prospective studies, the relative risks for coronary heart disease ranged between 1.1 comparing blood lead levels > 24.8 μg/dL versus < 12.4 μg/dL in the British Regional Heart Study (Pocock et al. 1988) and 1.89 comparing blood lead levels ≥ 3.63 μg/dL versus < 1.93 μg/dL in the National Health and Nutrition Examination Survey (NHANES) III Mortality Follow-up Study (Menke et al. 2006). The relative risk for stroke in the NHANES III Mortality Follow-up Study was 2.51. There were no prospective studies on the association of blood lead with peripheral arterial disease. However, the relative risk for peripheral arterial disease comparing blood lead levels ≥ 2.47 μg/dL versus < 1.03 μg/dL in a cross-sectional analysis of NHANES 1999–2002 was 1.92 (Muntner et al. 2005).
Lead and cardiovascular mortality in occupational populations
Eighteen studies from the United States (Cooper et al. 1985; Michaels et al. 1991; Robinson 1974; Sheffet et al. 1982; Steenland et al. 1992; Tollestrup et al. 1995), Europe (Alexieva et al. 1981; Belli et al. 1989; Carta et al. 2003; Cocco et al. 1997, 1994; Davies 1984; Dingwall-Fordyce and Lane 1963; Gerhardsson et al. 1995; Lundstrom et al. 1997; Malcolm 1971; Wilczynska et al. 1998), and Australia (McMichael and Johnson 1982) met our inclusion criteria (Table 3). Battery, ceramic, pigment, refinery, and smelter industries were studied. All studies used job titles to ascertain exposure and death certificates to identify coronary heart disease (12 studies), stroke (15 studies) and overall cardiovascular mortality (9 studies). Most were retrospective cohort studies and used external comparisons to the general population to derive standardized mortality ratios. The exceptions were the study by Dingwall-Fordyce and Lane (1963), two proportional mortality studies (Alexieva et al. 1981; McMichael and Johnson 1982) and two prospective cohort studies (Robinson 1974; Tollestrup et al. 1995). Occupational studies failed to fulfill most prespecified quality criteria (Appendix B).
Relative risk estimates across occupational studies varied widely, with positive, inverse, and null associations (Table 3). Several studies reported the associations among workers with the heaviest exposure (Dingwall-Fordyce and Lane 1963; Lundstrom et al. 1997; Malcolm and Barnett 1982; Steenland et al. 1992), by year of hire (Cooper et al. 1985; Lundstrom et al. 1997), and incorporating a latency period (Lundstrom et al. 1997). In two of the three studies that reported associations by duration of employment, coronary heart disease (Steenland et al. 1992) and stroke (Michaels et al. 1991) mortality were higher among workers with the highest number of years of employment.
Lead and intermediate cardiovascular outcomes
Five studies evaluated ventricular wall dimensional and functional parameters (Beck and Steinmetz-Beck 2005; Kasperczyk et al. 2005; Schwartz 1991; Tepper et al. 2001; Zou et al. 1995) (Table 4). Increased blood lead levels were associated with an increased prevalence of left ventricular hypertrophy in U.S. adults (Schwartz 1991) and with a nonstatistically significant increase in left ventricular mass in U.S. battery workers (Tepper et al. 2001). Similarly, Polish steel workers had higher left ventricular mass and lower ejection fraction compared to administrative workers from the same factory (Kasperczyk et al. 2005), and lead-exposed Polish workers had impaired diastolic function compared with nonexposed controls (Beck and Steinmetz-Beck 2005). Chinese refinery workers with blood lead levels > 50 μg/dL had similar interventricular septum and left ventricular wall thickness compared to workers < 50 μg/dL (Zou et al. 1995), although lead levels in the reference category are unknown.
Ten studies measured heart rate variability among lead-exposed workers (Andrzejak et al. 2004; Böckelmann et al. 2002; Gajek et al. 2004; Gennart et al. 1992; Ishida et al. 1996; Murata et al. 1995; Murata and Araki 1991; Muzi et al. 2005; Niu et al. 1998; Teruya et al. 1991), and one study measured heart rate variability in Seoul, Korea, public officials not occupationally exposed to lead (Jhun et al. 2005) (Table 4). Most of these studies had limitations in terms of sample size, methods of lead assessment, and lack of adjustment for potential confounders (Table 4; Appendix C). The conditions for electrocardiographic ascertainment and the heart rate variability indices differed widely across studies, making comparisons difficult. The coefficient of variation of the R-R interval was lower in lead-exposed workers compared with other workers in two of five studies in which the coefficient of variation was measured under normal breathing, and in one of three studies in which it was assessed during deep breathing. Among Seoul public officials (Jhun et al. 2005), increased lead levels were inversely associated with measures of low frequency, high frequency, and total power spectrum in uni-variate analyses, but adjusted results were not presented because lead exposure was dropped from the stepwise regression models used.
Fifteen studies reported the association of lead with other electrocardiographic parameters (Cheng et al. 1998; Gatagonova 1995a, 1995c; Kirkby and Gyntelberg 1985; Kosmider 1968; Kosmider and Petelenz 1961, 1962; Kosmider et al. 1965; Kromhout et al. 1985; Krotkiewski et al. 1964; Saric 1981; Shcherbak 1988; Sroczynski et al. 1990, 1985; Stozinic and Colakovic 1980) and one study with other vascular abnormalities (Aiba et al. 1999). All studies, except the Normative Aging Study (Cheng et al. 1998), were conducted in occupational populations in Europe. These types of outcome, including rhythm disorders, ischemic changes and cycle duration, varied widely across studies, and the findings were inconsistent. The Normative Aging Study measured lead in blood, tibia, and patella and identified associations between tibia lead and intraventricular conduction defects (QRS duration) and increased QT duration in subjects < 65 years of age (Cheng et al. 1998).
Finally, heart rate was evaluated using different methods in five studies, four in lead-exposed workers (Böckelmann et al. 2002; Kosmider and Petelenz 1961; Murata et al. 1995; Zou et al. 1995) and one in elderly men from the Netherlands (Kromhout et al. 1985), with inconsistent findings.
Discussion
Lead exposure and hypertension—sufficient evidence to infer a causal relationship
Chronic lead poisoning was connected to hypertension in the 19th century (Lorimer 1886). With rare exceptions (Vigdortchik 1935), a major limitation of early reports was the lack of a comparison group (Sharp et al. 1987). The hypertensive effects of lead have been extensively documented in experimental animals chronically exposed to high lead concentrations and in workers chronically exposed to high lead levels (Agency for Toxic Substances and Disease Registry 1999; U.S. EPA 2006). Generally, the development of hypertension in subjects chronically exposed to high lead levels has been interpreted as a possible consequence of lead nephropathy. At environmental levels of exposure, however, the effect of lead on blood pressure has been controversial. Numerous studies have addressed this question. All reviews have concluded that there is an association between lead and blood pressure, although the strength of this association is modest (Table 1). Substantial evidence, however, implies that this relationship is causal.
Consistency
The association between lead exposure and blood pressure has been found in populations with different geographic, ethnic, and socioeconomic background. While residual confounding by socioeconomic status is a concern, studies in homogenous samples and studies that have adjusted for a variety of socioeconomic indicators have still identified an association between lead exposure and blood pressure (Martin et al. 2006; Pocock et al. 1984).
Temporality
The association between blood lead and elevated blood pressure has been identified not only in cross-sectional but also in prospective studies that showed that new cases of hypertension and within-person elevations in blood pressure levels over follow-up were related to baseline lead exposure (Glenn et al. 2003; Møller and Kristensen 1992; Weiss et al. 1986).
Strength of the association
While the strength of the association between lead and blood pressure is modest, it may have been substantially underestimated because of measurement error in both lead and blood pressure determinations. Most studies used single blood lead measurements to assess lead exposure. When bone lead was used as a bio-marker of long-term exposure (Hu et al. 2007), lead in cortical or trabecular bone was positively associated with increased systolic blood pressure or hypertension in all prospective (Cheng et al. 2001; Glenn et al. 2003) and cross-sectional studies (Gerr et al. 2002; Hu et al. 1996; Korrick et al. 1999; Lee et al. 2001; Martin et al. 2006; Rothenberg et al. 2002; Schwartz and Stewart 2000). Furthermore, even bone lead is subject to error derived from the sampling site and from the technical difficulties of the measurement. In addition, blood pressure measurements were often conducted using nonstandardized protocols, without repeated measures, or in samples including hypertensive subjects.
Biologic gradient (dose response)
Some studies have demonstrated a progressive dose–response relationship between lead exposure and blood pressure (Pocock et al. 1984; Schwartz 1988; Weiss et al. 1986). However, the shape of the dose–response relationship is not completely characterized, particularly at low levels of exposure. It is not known what is the lowest level of lead exposure not associated with blood pressure, although in the available studies there seems to be no evidence of a threshold effect (Hertz-Picciotto and Croft 1993; Schwartz et al. 2001).
Biologic plausibility and experimental data
Numerous experimental studies in animals have shown irrefutable evidence that chronic exposure to low lead levels results in arterial hypertension that persists long after the cessation of lead exposure (U.S. EPA 2006). The precise mechanisms explaining a hypertensive effect of low chronic exposure to environmental lead are unknown. An inverse association between estimated glomerular filtration rate and blood lead has been observed at blood lead levels < 5 μg/dL in general population studies (Ekong et al. 2006; Muntner et al. 2005), indicating that lead-induced reductions in renal function could play a major role in hypertension. Other potential mechanisms include enhanced oxidative stress (Stohs and Bagchi 1995; Vaziri et al. 2001), stimulation of the renin-angiotensin system (Carmignani et al. 1999; Rodriguez-Iturbe et al. 2005), and down-regulation of nitric oxide (Ding et al. 1998; Dursun et al. 2005) and soluble guanylate cyclase (Farmand et al. 2005). These mechanisms could result in increased vascular tone and peripheral vascular resistance (U.S. EPA 2006).
Causal inference
We conclude that the evidence is sufficient to infer a causal relationship between lead exposure and high blood pressure. Further research is still needed to determine the precise dose–response relationship, the relative importance of short-term versus chronic lead effects, the relevant mechanisms at environmental levels of exposure, and whether the magnitude of the association is different in children or in other vulnerable population subgroups.
Clinical cardiovascular end points in general populations
Consistency and temporality
Few cohort studies have evaluated the prospective association of lead with clinical cardiovascular outcomes in general population settings. The findings of the NHANES II and NHANES III Mortality Follow-up studies are remarkable. NHANES are periodic, standardized surveys designed to provide representative health data from the U.S. noninstitutionalized population. Despite a marked decline in lead levels in U.S. adults, both surveys showed statistically significant increases in cardiovascular mortality with increasing blood lead (Lustberg and Silbergeld 2002; Schober et al. 2006). In addition a cross-sectional analysis of NHANES 1999–2002 data identified an association of blood lead with the prevalence of peripheral arterial disease (Muntner et al. 2005; Navas-Acien et al. 2004). The British Regional Heart Study (Pocock et al. 1988) and two other small cohort studies (Kromhout 1988; Møller and Kristensen 1992) showed positive but nonstatistically significant associations of coronary heart disease or stroke incidence with higher lead levels. The confidence intervals from these studies were wide but included the point estimates of the NHANES studies. Additional studies are needed to determine the consistency of the evidence in diverse populations.
Strength of the association and dose response
The associations of blood lead with clinical cardiovascular end points in the NHANES studies were moderately strong, with a clear dose–response gradient. An unresolved issue is the impact of uncontrolled confounding and measurement error on the relative risk estimates in studies of lead and clinical cardiovascular end points. NHANES studies adjusted for race, education, income, and urban versus rural location, which reduces potential confounding by socioeconomic status. Studies with more detailed information on the determinants of lead exposure may contribute to a better understanding of this issue. Similarly, evaluating lead effects using a single blood lead measure may result in measurement error with substantial underestimation of the magnitude of the association. This is particularly problematic when there are marked temporal trends in lead levels, as this source of error adds to within-person variability in blood lead levels to increase regression-dilution bias.
Biologic plausibility and experimental data
Lead levels of 0.8 ppm (Revis et al. 1981) and 0.1 ppm (Minaii et al. 2002) in drinking water induced atherosclerosis in animal models, and lead levels of 0.5–10 μM induced the proliferation of vascular smooth cells and fibroblasts in in vitro models (Fujiwara et al. 1995). Lead-related atherosclerosis could be explained by several mechanisms, including increases in blood pressure, impairment of renal function (Ekong et al. 2006), and induction of oxidative stress (Stohs and Bagchi 1995; Vaziri et al. 2001), inflammation (Heo et al. 1996), and endothelial dysfunction (Vaziri et al. 2001).
Causal inference
Because of the scarce number of prospective studies and the lack of information on incident nonfatal events, we conclude that the evidence is suggestive but not sufficient to infer a causal relationship with clinical cardiovascular end points. Prospective studies are required to characterize fully the impact of lead on cardiovascular morbidity and mortality. These studies need detailed and repeated assessment of lead exposure and its determinants, standardized assessment of traditional cardiovascular risk factors, and long-term follow-up to identify incident cardiovascular events and trends in subclinical markers of atherosclerosis. Although elevated blood pressure and impaired renal function are proposed mechanisms that mediate the effects of lead on clinical cardiovascular outcomes, other mechanisms are likely to be involved. Future epidemiologic studies should explore in detail the magnitude of the contribution of specific mediators of clinical cardiovascular lead effects.
Cardiovascular mortality in occupational populations
Adequacy of the evidence
The validity of occupational studies of lead and cardiovascular mortality is limited by several methodologic problems. A major limitation is the healthy worker effect (Arrighi and Hertz-Picciotto 1994). The comparison of exposed workers with the general population is particularly inappropriate for cardiovascular mortality because workers are healthier and their lifestyles and cardiovascular risk factors are likely to differ widely from those of the general population (Choi 1992). In addition, cardiovascular diseases are associated with prolonged disability and changes in employment status. Even in studies based on comparisons with unexposed workers, the selection of healthier individuals at time of hire or for specific jobs within an industry may have resulted in biased estimates of the association. Correcting the bias introduced by the healthy worker survivor effect is extremely challenging, and stratifying by duration of employment or time since hire is unlikely to completely account for this source of bias (Arrighi and Hertz-Picciotto 1994; Howe et al. 1988).
Additional limitations include the assignment of lead exposure based on job titles and of cardiovascular deaths based on death certificates. Misclassification of exposure and outcome may have resulted in further underestimation of the association of lead and cardiovascular end points. Finally, the lack of determinations of established cardiovascular risk factors and of other occupational exposures may have contributed to uncontrolled confounding.
Causal inference
As a result of these methodologic limitations, and despite many occupational cohort studies published in the literature (Table 3), available information on occupational lead exposure and cardiovascular mortality is inadequate to infer the presence or absence of a causal relationship. Because studies of environmental lead exposure provide evidence of an association between lead and cardiovascular mortality at lower exposures than those experienced by occupationally exposed workers, we expect the impact of lead in exposed workers to be at least as important as in environmentally exposed subjects.
Lead exposure and heart rate variability
Consistency, temporality, and strength of the association
Several studies, mostly cross-sectional, found an association between increased lead exposure and decreased heart rate variability. The diversity in the methods and conditions used for measuring heart rate variability makes it difficult to compare the association of lead exposure and heart rate variability across studies. In addition, the validity and precision of these studies are often limited by small sample sizes, limitations in the assessment of lead exposure, and lack of control for established cardiovascular risk factors and other confounders.
Biologic plausibility and experimental data
Lead, a well-established neurotoxicant, could affect heart rate variability by interfering in autonomic nervous control of the heart (Chang et al. 2005). Heart rate variability measures the fluctuation of the heart rate around the mean heart rate (Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology 1996). Because the basis of normal cardiac autonomic functioning is the shift from parasympathetic to sympathetic modulation, decreased heart rate variability is a marker of cardiac autonomic dysfunction. Indeed, decreased heart rate variability in supine position and in response to postural change has been associated with increased incident coronary heart disease and all-cause mortality in large prospective cohort studies in populations free of cardiovascular disease (Liao et al. 1997; Tsuji et al. 1996).
Causal inference
We conclude that the evidence is suggestive of but not sufficient to infer a causal relationship of lead exposure with heart rate variability. Large studies with adequate measures of lead exposure and of heart rate variability are needed to better characterize the association between lead exposure and autonomic cardiac control.
Public health implications
The evidence in this systematic review is sufficient to infer a causal relationship of lead exposure with elevated blood pressure, and it is suggestive of but not sufficient to infer a causal relationship of lead with clinical cardiovascular outcomes and cardiovascular function tests. These associations have been observed at blood lead levels well below 5 μg/dL (Menke et al. 2006; Nawrot and Staessen 2006). Indeed, no lower threshold has been established for any lead-cardiovascular association.
Although future research will contribute to characterize fully the impact of lead exposure on cardiovascular health, these findings have several important public health implications. First, there is an immediate need to lower the current safety standard of the World Health Organization and the U.S. Occupational Safety and Health Administration for blood lead in workers (currently established at 40 μg/dL). Second, a criterion for elevated blood lead levels in adults needs to be established and screened for in preventive services. In fact, the cardiovascular end points described above plus the substantial evidence that chronic lead exposure affects cognitive function (Shih et al. 2007) and renal function (Ekong et al. 2006) at levels < 5 μg/dL indicate that the U.S. Centers for Disease Control and Prevention criterion for elevated blood levels in children (10 μg/dL) is too high for adults. Third, the hypertensive effects of lead exposure and its impact on cardiovascular mortality need to be included in risk assessment and in economic analyses of lead exposure impact. Finally, regulatory and public health interventions must be developed and implemented to prevent and reduce lead exposure beyond current levels in adults.
| First author, year | Typea | No. of studies included | Year of publication of studies (range) | Language of literature search | Total no. of subjects | Age range of participants (years) | Comparison | Outcome | Pooled estimate [change in mmHg (95% CI)] | Median of estimates [change in mmHg (range)] | Conclusions as reported by authors |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Sharp et al. 1987 | Review | 4 | 1982–1986 | English, French | 8,406 | 24–59 | Per 2-fold ↑b | SBP | — | 1.9 (0.7 to 2.3) | Evidence consistent with causation |
| Hertz-Picciotto and Croft 1993 | Review | 13 | 1980–1992 | English | 22,923 | 12–80 | ≠ for each study | SBP DBP Hypertension | — — — | 2.0 (−5.9 to 8.0) 1.7 (−1.6 to 4.0) RR: 1.4 (1.2 to 1.7) | Evidence strongly supports causal association |
| Staessen et al. 1994, 1995 | SR, MA | 23 | 1980–1993 | English, French, German | 33,141 | 10–88 | Per 2-fold ↑ | SBP DBP | 1.0 (0.4–1.6) 0.6 (0.2–1.0) | 1.0 (−3.0 to 14.0) 1.0 (−2.0 to 13.0) | MA suggests a weak association |
| Schwartz 1995 | SR, MA | 15 | 1985–1993 | English | NR Men only | 18–76 | Per 2-fold ↑b | SBP | 1.25 (0.87–1.63) | 1.45 (0.2 to 3.2) | MA consistent with causal association |
| ATSDR 1999 | SR | 24 | 1980–1996 | No language restriction | NR | All ages | ≠ for each study | SBP DBP Hypertension | — — — | NR NR NR | Suggestion of ↑ blood pressure, but evidence is inconclusive |
| Nawrot et al. 2002 | SR, MA | 31 | 1980–2001 | English, French, German | 58,518 | 10–90 | Per 2-fold ↑ | SBP DBP | 1.0 (0.5–1.4) 0.6 (0.4–0.8) | 1.0 (−5.0 to 14.0) 1.0 (−2.0 to 14.0) | MA suggests a weak association |
| U.S. EPA 2006 | SR, MA | 9 10 | 1990–2003 | English | 27,424 34,740 | 14–93 | Per 2-fold ↑ | SBP DBP | 0.81 (0.46–1.16)c — | 1.0 (−3.9 to 11) 1.0 (−1.3 to 7.3) | MA suggests an effect of blood lead on SBP |
Abbreviations: ≠, different; ↑, increase; CI, confidence interval; DBP, diastolic blood pressure; MA, meta-analysis; NHANES, National Health and Nutrition Examination Survey; NR, not reported; RR, relative risk; SBP, systolic blood pressure; SR, systematic review; U.S. DHHS, U.S. Department of Health and Human Services; U.S. EPA, U.S. Environmental Protection Agency.
a
Systematic review: a search strategy and criteria for manuscript selection are specified. Meta-analysis: a pooled analysis using meta-analysis techniques are presented.
b
In the study by Sharp et al. (1987), we divided by 3 the change per 15 μg/dL (equivalent to comparing 10 μg/dL vs. 5 μg/dL). The study by Schwartz et al. (1995) reports the change in mmHg comparing 10 μg/dL vs. 5 μg/dL.
c
Pooled estimate using an inverse variance weighted random-effects model (Egger et al. 2001) of two pooled estimates for linear and log-linear estimates, respectively.
| First author, year | Country | Population | Men (%) | Age range (years) | Lead assessment | Range of lead levels | End point ascertainment | Outcome | No. of cases/noncases | Measure ofb association | Comparison | Adjusted forc |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Prospective cohort studies | ||||||||||||
| Pocock et al. 1988 | U.K. | British Regional Heart Study | 100 | 40–49 | Blood (AAS) | < 6.2 to > 35.2 μg/dL | Death certificate or chest pain, enzyme, ECGa | CHD, F + NF | 316/7,063 | OR 1.1 (0.4–1.8) | > 24.8 vs. < 12.4 μg/dL | Age, smoking, location |
| Death certificate, medical record | Stroke, F + NF | 66/7,313 | Mean 16.7 μg/dL Mean 15.3 μg/dL | Cases vs. noncases | Age, smoking, location | |||||||
| Kromhout 1988 | Netherlands | Elderly men in Zutphen | 100 | 57–76 | Blood (AAS) | < 10.8 (10th p) > 28.0 (90th p) μg/dL | Death certificate or chest pain, enzyme, ECGa | CHD, F + NF | 26/115 | HR 1.34 (0.46–3.94) | > 23.8 vs. < 13.0 μg/dL | Age, smoking, BMI, BP, cholesterol |
| Møller and Kristensen 1992 | Denmark | Survey repondents 4 municipalities | 48 | 40 | Blood (AAS) | 2 to 60 μg/dL | Death certificate, hospital admissions | CHD, F + NF CVD, F + NF | 40/1,005 54/991 | HR 1.58 (0.85–2.95) HR 1.10 (0.63–1.93) | Per log unit change | Sex, smoking, alcohol, BP, cholesterol, exercise |
| Lustberg and Silbergeld 2002 | U.S. | NHANES II | 47 | 30–74 | Blood (AAS) | < 10 to 29 μg/dL | Death certificate | CVD, F | 424/3,766 | HR 1.39 (1.01–1.91) | 20–29 vs. < 10 μg/dL | Age, sex, race, educ., income, smoking, BMI, exercise, location |
| Menke et al. 2006 | U.S. | NHANES III | 47 | ≥ 17 | Blood (AAS) | < 1 to 10 μg/dL | Death certificate | CVD, F CHD, F Stroke, F | 766/13,198 367/13,597 141/13,823 | HR 1.55 (1.08–2.24) HR 1.89 (1.04–3.43) HR 2.51 (1.20–5.26) | < 1.93 vs. ≥ 3.63 μg/dL | Age, sex, race, educ., income, smoking, alcohol, BMI, exercise, cholesterol, CRP, urban residence, menopause, hypertension, kidney function |
| Case–control and cross-sectional studies | ||||||||||||
| Pan et al. 1993 | Taiwan | Clinic-based | 69 | NR | Urine (DPASV) | 7.9 to 138.4 μg/L | NR | BFD prev. | 16/16 | 30.8 (30.1) μg/L 17.4 (5.4) μg/L | Cases vs. noncases | Age, sex |
| Mansoor et al. 2000 | Sweden | Clinic-based | 53 | Mean 46 | Plasma (TRXFS) | Mean 3.3 ng/g plasma | Angiograms | PAD prev. | 65/65 | 3.3 (0.4) ng/g plasma 3.2 (0.3) ng/g plasma | Cases vs. noncases | Age, sex |
| Gustavsson et al. 2001 | Sweden | SHEEP Study | 68 | 45–70 | JEM | NM | Chest pain, ECG enzymea | AMI inc., NF | 1,335/1,658 | OR 1.03 (0.64–1.65) | ≥ 0.04 mg/m3 vs. unexp. | Age, sex, smoking, alcohol, BP, BMI, exercise, location |
| Dulskiene 2003 | Lithuania | Clinic-based | 100 | 25–64 | Airborne | NM | Medical records | AMI | 579/1,777 | OR 1.12 (0.76–1.40) | > 0.225 vs. ≤ 0.225 μg/m3 | Age, sex, smoking, BP |
| Tsai et al. 2004 | Taiwan | Clinic-based | 57 | NR | Urine (AAS) | 5.3 to 123.6 μg/L | NR | BFD prev. | 68/68 | 33.7 (24.3) μg/L 22.2 (11.8) μg/L | Cases vs. noncases | Age, sex |
| Kosmala et al. 2004 | Poland | Clinic-based | 53 | Mean 62 | Blood (AAS) | Mean 3.9 μg/dL | Coronariography, treadmill exercise text | Effort angina | 33/18 | 3.9 (1.4) μg/dL 3.7 (1.2) μg/dL | Cases vs. noncases | Crude |
| Muntner et al. 2005 | U.S. | NHANES 1999–2002 | 47 | ≥ 40 | Blood (AAS) | < 0.3 to > 10 (98th p) μg/dL | Ankle-brachial BP index | PAD prev. | NR | OR 1.92 (1.02–3.61) | ≥ 2.47 vs. < 1.06 μg/dL | Age, sex, race, educ., insurance, smoking, alcohol, BMI, diabetes |
Abbreviations: AAS, atomic absorption spectrometry; AMI, acute myocardial infarction; BFD, black foot disease, a form of peripheral arterial disease endemic in the arseniasis areas of southwestern Taiwan; BMI, body mass index; BP, blood pressure levels or hypertension; CHD, coronary heart disease; CI, confidence interval; CVD, cardiovascular disease; DPASV, differential pulse anodic stripping voltammetry; ECG, electrocardiogram; educ., education; F, fatal; F+NF, fatal and nonfatal; HR, hazard ratio; inc., incidence; JEM, job exposure matrix; NF, nonfatal; NHANES, National Health and Nutrition Examination Survey; NM, not measured; NR, not reported; OR, odds ratio; PAD, peripheral arterial disease; p, percentile; prev, prevalence; SHEEP, Stockholm Heart Epidemiology Study; TRXFS, total-reflection X-ray fluorescence spectrometry; unexp., unexposed.
a
Standard World Health Organization criteria for myocardial infarction.
b
For studies that categorized lead exposure, we report the HR or OR (with 95% CI in parentheses) comparing the highest with the lowest lead category. Otherwise, we present the mean (SD) lead levels for cases and noncases.
c
Blood pressure–unadjusted relative risk is as follows: a) Menke (2006): cardiovascular mortality 1.64, coronary heart disease mortality 2.01, stroke mortality 2.61; b) Gustavsson( 2001): acute myocardial infarction 1.17.
| First author, year | Country | Population | Men (%) | Age range (years) | Outcome | Follow-up (years) | No. of deathsa | RR (95% CI)b | Comparison | Adjusted for | Corrected for healthy worker effect |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Prospective cohort studies | |||||||||||
| Robinson 1974 | U.S. | Tetraethyl lead production workers | 100 | 20–58 | CVD | 20 | 57 n = 1,252 | 0.64 (0.54–0.75) | Production vs. maintenance workers | Crude | No |
| Tollestrup et al. 1995 | U.S. | Orchard workers (lead arsenate) | 66 | 8 to ≥ 55 | CHD Stroke | 45 | NR NR n = 1,097 | 1.27 (0.72–2.23) 0.82 (0.31–2.12) | Workers vs. general population | Age, sex | No |
| Retrospective cohort studies | |||||||||||
| Dingwall-Fordyce and Lane 1963 | U.K. | Lead pensioners and workers | 100 | ≥ 65 Mean 55 | Stroke | 35 | 51 | 2.73 (1.31–5.71)c | Assembly, plumbers, plate cutting, etc. vs. office, chemist, etc. | Age, period | No |
| Malcolm 1971, Malcolm and Barnett 1982 | U.K. | Lead battery and smelter pensioners and workers | 99 | < 65 to ≥ 65 at death | CHD Stroke | 10 51 | 99 103 | 1.00 (0.82–1.22) 1.31 (0.66–1.91) | Workers vs. general population High exposed vs. no exposed | Age | No |
| Sheffet et al. 1982 | U.S. | Pigment plant workers | 100 | Mean 27.8 | CVDd | 31 | 139 | 0.62 (0.52–0.73) | Workers vs. general population | ||
| Davies 1984 | U.K. | Pigment plant workers Pigment plant workers + lead poisoning | 100 100 | 18–59 18–59 | Stroke Stroke | 30 30 | 31 9 | 0.94 (0.66–1.33) 4.10 (2.12–7.86) | Workers vs. general population Workers vs. general population | Age, period Age, period | No No |
| Cooper et al. 1985 | U.S. | Lead battery and producing workers | 100 | < 25–74 | CVD CHD Stroke | 24 | 984 715 172 | 0.97 (0.99–1.06) 0.85 (0.69–1.05) 1.06 (0.76–1.48) | Workers vs. general population | Age (~ findings by year of hire and employment duration) | Partiallye |
| Belli et al. 1989 | Italy | Lead miners | 100 | NR | CVD | 36 | 82 | 0.95 (0.76–1.10) | Workers vs. general population | Age | No |
| Michaels et al. 1991 | U.S. | Newspaper print workers | 100 | 19–83 | CHD Stroke | 23 | 186 43 | 0.63 (0.54–0.73) 1.35 (0.98–1.82) | Workers vs. general population | Age (for stroke, analysis by employment durationf) | Partially |
| Steenland et al. 1992 | U.S. | Smelter workers | 100 | NR | CHD Stroke CHD Stroke | 39 39 | 320 74 239 53 | 0.94 (0.84–1.05) 1.05 (0.82–1.32) 0.99 (0.87–1.12) 1.05 (0.79–1.37) | Workers vs. general population High exposed vs. general population | Age, period (+ analyses by employment durationg) Age, period | Partially |
| Cocco et al. 1994 | Italy | Lead miners | 100 | Mean 27.7 | CVD | 28 | 258 | 0.63 (0.56–0.72) | Workers vs. general population | Age, period (~ findings for surface and underground workers) | No |
| Gerhardsson et al. 1995 | Sweden | Smelter workers | 100 | NR | CHD Stroke | 20 | 34 0 | 1.72 (1.20–2.42) 0 (0.00–1.23) | Workers vs. general population | Age, period (~ findings by year of hire) | No |
| Lundström et al. 1997 | Sweden | Smelter workers | 100 | 15 to ≥ 75 at death | CVD CHD Stroke | 32 | 234 152 36 | 0.90 (0.80–1.00) 0.80 (0.70–1.00) 0.80 (0.60–1.20) | Workers vs. general population | Age, period (~ findings for highest exposure group and adding a latency period) | No |
| Cocco et al. 1997 | Italy | Smelter workers | 100 | Mean 30.4 | CVD CHD Stroke | 48 | 251 49 105 | 0.70 (0.62–0.80) 0.34 (0.25–0.45) 0.95 (0.77–1.15) | Workers vs. general population | Age, period | No |
| Wilczynksa et al. 1998 | Poland | Workers compensated for lead poisoning | 100 | < 29 to ≥ 50 at 1st episode | CVD CHD Stroke | 22 | 231 98 33 | 0.91 (0.80–1.04) 0.96 (0.78–1.17) 1.03 (0.71–1.45) | Workers vs. general population | Age (~ findings by number of lead poisoning episodes) | No |
| Carta et al. 2003 | Italy | Smelter workers | 100 | NR | CVD | 29 | 28 | 0.80 (0.56–1.16) | Workers vs. general population | Age | No |
| Proportional mortality study | |||||||||||
| Alexieva et al. 1981 | Bulgaria | Smelter workers | 100 | Mean at death 61 | CHD Stroke | 10 | 26 47 | 5.60 (1.68–18.6) 0.17 (0.08–0.36) | Workers vs. general population | Age | No |
| McMichael and Johnson 1982 | Australia | Smelter workers | 100 | 30 to > 60 at death | CHD Stroke | 40 | 231 53 | 0.95 (0.67–1.35) 1.45 (0.76–2.76) | Exposed workers vs. staff workers | Age | No |
Abbreviations: CHD, coronary heart disease; CI, confidence interval; CVD, cardiovascular; RR, relative risk; SMR, standard mortality ratio.
In all studies, lead exposure was determined through job titles, and mortality outcomes were assigned through information in death certificates.
a
Sample size not available in most studies.
b
Relative risk estimates came from SMRs except Robinson (1974) (RR), Tollestrup (1995) (HR), Alexieva (1981) (proportional mortality rate), and McMichael (1982) (proportional mortality rate).
c
The within-cohort relative risk was estimated by comparing standardized mortality ratios in the highest versus the lowest category of exposure.
d
A total of 15% of subjects with unknown cause of death in death certificate.
e
Partial adjustment indicates that authors conducted additional analyses by employment duration.
f
For Michaels et al. (1991), SMRs (95%CI) for stroke by number of years of employment are < 10 years, 2.52 (0.06–13,93); 10–19 years, 0.32 (0.01–1.74); 20–29 years, 0.65 (0.18–1.68); ≥ 30 years, 1.68 (1.18–2.31).
g
For Steenland et al. (1992), SMRs by numbers of years of employment are as follows: a) CHD: 1–5 years, 1.02; 5–20 years, 0.92; ≥ 20 years, 0.86. b) Stroke: 1–5 years, 0.83; 5–20 years, 1.01; ≥ 20 years, 1.41.
| First author, year | Country | Population | Sample size (no.) | Men (%) | Age range (years) | Lead assessment | Range levels (μg/dL) | Comparison | End point ascertainment | Main findings |
|---|---|---|---|---|---|---|---|---|---|---|
| Studies of ventricular mass and function | ||||||||||
| Schwartz 1991 | U.S. | NHANES II | < 9,932 | ~ 50 | 25–74 | Blood | NR | Per 1 μg/dL | ECG (Minnesota code) | ↑ prevalence left ventricular hypertrophy OR adjusted for age, sex, race = 1.33 (95% CI, 1.09–1.61) |
| Zou et al. 1995 | China | Refinery workers | 41 | 81 | 24–45 | Blood | Mean 42.5 | > 50 vs. < 50 μg/dL | US (dimensional and functional parameters) | ~ end-diastolic, systolic internal dimension, wall thickness ~ ejection fraction (%), cardiac output (mL/sec), index (mL/sec × m2 ~ heart rate |
| Tepper et al. 2001 | U.S. | Battery workers | 108 | 51 | 36–73 | Blood | 12–50 | 34–50 vs. 12–25 μg/dL | US and ECG | ↑ left ventricular mass (g/m2) but NS (p = 0.20) |
| Kasperczyk et al. 2005 | Poland | Steel workers | 143 | NR | Mean 44 | Blood | Mean 23.4 | Administrative workers | US (dimensional and functional parameters) | ↑ left ventricular mass (g and g/m2) ↑ left, ~ right end-diastolic internal dimensions ~ wall thickness (interventricular septum, posterior wall, others) ↓ ejection fraction (%) |
| Beck and Steinmetz-Beck 2005 | Poland | Lead workers | 104 | 100 | 32–56 | Blood | 19.3–79.8 | Lead exposed vs. control | Echo-doppler | ↓ early mitral inflow peak velocity, ↑ late mitral inflow peak velocity ↓ time velocity integral of early vs. late diastolic inflow ~ time velocity integral of early vs. total diastolic inflow ↑ time velocity integral of late vs. total diastolic inflow ~ Isovolumetric relaxation time of left ventricle |
| Studies of heart rate variability | ||||||||||
| Murata and Araki 1991 | Japan | Gun workers | 32 | 100 | 23–58 | Job title | < 16–60 | Other workers no lead exp. | ECG: 100 R-R intervals, normal breath | ↓ CV of R-R interval; ~ CV of LF component, ↓ CV of HF component |
| Teruya et al. 1991 | Japan | Battery, refinery workers | 172 | 100 | 18–57 | Blood | 5–76 | Correlation, > 50 vs. < 20 μg/dL | ECG: 1 min, normal, deep breath | ~, ↓ mean; ~, ↓ SD; and ~, ↓ CV of R-R interval ~, ↓ maximal variation ratio (min/max R-R interval) ~, ↓ maximal variation rate ([min/max R-R interval]/mean) |
| Gennart et al. 1992 | Belgium | Battery workers | 183 | 100 | 22–55 | Blood | 4.4–75 | Other workers (finishing, maintenance, etc.) | ECG: normal, deep breath | ~ CV of R-R interval, ~ CV of mean square of successive differences, and ~ CV of mean ratio of shortest to longest R-R |
| Murata et al. 1995 | Japan | Glass workers | 51 | 0 | 21–35 | Job title | NR | Textile workers | ECG: 100 R-R intervals, normal breath | ~ heart rate ↓ CV of R-R interval, ↓ CV of LF and ↓ HF components ↓ LF/HF ratio |
| Ishida et al. 1996 | Japan | Ceramic painters | 128 | 45 | 29–75 | Blood | 2.1–69.5 | > 30 vs. < 10 μg/dL | ECG: 100 R-R intervals, normal, deep breath Doppler: finger blood flow | ~ CV of R-R interval ↓ flow between supine and standing/supine ~ flow drop velocity (supine flow/time to the nadir after standing) |
| Niu et al. 1998 | China | Lead-exposed workers | 302 | NR | 20–59 | Job title | NM | Healthy controls | ECG: deep breath, valsalva, stand up | ~ R-R interval |
| Böckelmann et al. 2002 | Germany | Lead, iron, steel workers | 136 | 100 | Mean 43 | Blood | Mean lead workers 31.2 | Iron steel workers | ECG: 90 min, 10-step battery test | ↓ heart rate at rest ↑ sinus arrhythmia at rest Lack of recovery of LF and HF after test |
| Gajek et al. 2004 | Poland | Foundry workers | 35 | 100 | Mean 42 | Blood | < 3.6 to > 41.0 | Healthy controls | ECG: 24 hr, long- and short-term | ~ mean R-R, SDNN, SDNN index, SDANN, rMSSD, pNN50 Short-term only: ~ TP, VLF, LF, HF, LF/HF, HF night / HF day |
| Andrzejak et al. 2004 | Poland | Copper smelter workers | 86 | 100 | Mean 43 | Blood | Mean lead workers,br>46.8 | Healthy controls matched on age, sex, smoking, lipids, BMI | ECG: 24 hr | ~ heart rate Long-term: ↓ pNN50, ~ mean R-R, SDNN, SDNN index, SDANN, rMSSD Short-term: all parameters ↓ included LF and HF, except mean R-R and LF:HF |
| Muzi et al. 2005 | Italy | Battery workers | 78 | 96 | Mean 38 | Blood | < 3.5 to > 31.6 | Other workers | ECG: battery tests | ↓ R-R interval ratios for lying-standing, lying-standing-lying, deep breaths, and valsalva |
| Jhun et al. 2005 | Korea | Public officials and family | 331 | 55 | Mean 38 | Blood | < 1.39 to > 3.45 | Per natural-log unit | ECG: 3 min, seated position | ↓ LF, HF, and total power spectrum |
| Studies of other cardiac function abnormalities | ||||||||||
| Kosmider and Petelenz 1961 | Poland | Lead-poisoned workers | 140 | 100 | 18–45 | Job title symptoms | NM | Healthy controls | ECG | ↓ heart rate, ↓ P-Q interval ↑ heart muscle lesions and vegetative disorders |
| Kosmider and Petelenz 1962 | Poland | Lead-poisoned workers | 76 | 100 | 46–65 | Job title symptoms | NM | Healthy controls | ECG | ↑ heart muscle lesions and vegetative disorders |
| Krotkiewski et al. 1964 | Poland | Lead-poisoned workers | 591 | 78 | 20–68 | Job title symptoms | NM | Other workers | ECG | ↑ prevalence of ischemic changes: 32% vs. 13% |
| Kosmider et al. 1965 | Poland | Lead-poisoned workers | 100 | 100 | 20–45 | Job title symptoms | NM | Healthy controls | ECG | ↑ heart muscle lesions and vegetative disorders |
| Kosmider 1968 | Poland | Lead-poisoned workers | 216 | 100 | 18–65 | Job title symptoms | NM | Healthy controls | ECG | ↑ heart muscle lesions and vegetative disorders |
| Stozinic and Colakovic 1980 | Yugoslavia | Lead-poisoned workers | 1,000 | 100 | NR | Job title symptoms | NM | Healthy controls | ECG questionnaire | ↑ electrocardiographic abnormalities (including ↑ S-T segment) ↑ self-reported coronary heart disease and intermittent claudication |
| Saric 1981 | Croatia | Residents near to and far from a smelter | 502 | 50 | 26–70 | Area of residency | NM | Residents far from smelter | ECG | ~ electrocardiographic abnormalities |
| Kromhout et al. 1985 | Netherlands | Elderly men in Zutphen | 152 | 100 | 57–76 | Blood | < 10.8 > 28.0 | Correlation | ECG | ~ resting heart rate |
| Kirkby and Gyntelberg 1985 | Denmark | Lead smelter workers | 190 | 89 | 30–60 | Job title | Mean 31 | Healthy controls residents in Glostrup | ECG (Minnesota code) | ↑ prevalence of ischemic changes: 20% vs. 6% |
| Sroczynski et al. 1985 | Poland | Lead workers | 250 | 100 | Mean 41 | Job title | NM | Other workers | ECG (Minnesota code) | ↑ prevalence of ischemic changes: 10.0% vs. 5.3% ↑ prevalence of rhythm disorders: 14% vs. 2.7% |
| Shcherbak 1988 | Russia | Lead workers | 320 | 100 | 20–59 | Job title | NM | Other workers | ECG | ↑ prevalence of ischemic changes: 11.6% vs. 6.7% |
| Sroczynski et al. 1990 | Poland | Lead workers | 711 | 100 | 20–60 | Job title | NM | Other workers | ECG (Minnesota code) | ↑ prevalence systolic murmur and rhythm disorders ↑ prevalence ventricular repolarization ~ prevalence of ischemic changes |
| Gatagonova 1995a,b,d | Russia | Lead workers | 500 | 78 | 20–60 | Job title | Mean 67 | Other workers | Integral rehography ECG | Changes of intracardial and peripheral hemodynamics Disorders of myocardial bioelectric activity and contractility ↑ P wave and QT, QRS interval; ~ P–Q interval |
| Gatagonova 1995c | Russia | Lead workers | 68 | 100 | NR | Job title | NM | Other workers | Exercise stress test | ↑ prevalence of ischemic changes (↑ S-T segment > 1 mm 15.9 vs. 4.2%) |
| Cheng et al. 1998 | U.S. | NormativeAging Study | 775 | 100 | 48–93 | Blood Tibia Patella | Mean 5.79 Mean 22 μg/g Mean 31 μg/g | Per 10 unit ↑ | ECG | Subjects < 65 years: ↑ QT, ↑ QRS interval for tibia and patella, ~ for blood Subjects ≥ 65 years: ~ QT, ~ QRS interval for all biomarkers ~ conduction defects and arrhythmia for all biomarkers, indices and age groups, except ↑ intraventricular conduction defect for tibia lead in < 65 years |
| Studies of other vascular function abnormalities | ||||||||||
| Aiba et al. 1999 | Japan | Refinery workers | 48 | 100 | 18–69 | Job title | Mean 43.2 | Correlation | Acceleration plethysmography | ↓ amplitude ratio of the second/first systolic wave (age adjusted) ~ amplitude ratio of the third/first and third/first waves (age adjusted) |
Abbreviations: ↑, ↓ – indicate increase or decrease (statistically significant at p < 0.05, unless otherwise specified). BMI, body mass index; CI, confidence interval; CV, coefficient of variation; DB, deep breathe; ECG, electrocardiogram; exp., exposed; HF, high frequency; HRV, heart rate variability; LF, low frequency; NM, not measured; NR, not reported; NS, not significant; OR, odds ratio; pNN50, proportion of interval differences of successive normal-to-normal intervals > 50 msec; RMSSD, square root of the mean-squared differences of successive NN intervals; SD, standard deviation; SDANN, SD of the average normal-to-normal interval. SDNN, SD of the normal-to-normal interval; TP, total power; US ultrasound; V, ventricular; VLF, very low frequency.
Article Notes
We thank J.M. Samet for his comments to a previous version of this manuscript.
Databases: PubMed (http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed); EMBASE (http://www.embase.com/); TOXLINE (http://toxnet.nlm.nih.gov/).
This article is part of the mini-monograph “Lead Exposure and Health Effects in Adults: Evidence, Management, and Implications for Policy.”
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Appendix A. Search strategy
Free text and key word
Lead, lead poisoning, heavy metals, mortality, atherosclerosis, cardiovascular disease, peripheral arterial disease, peripheral vascular disease, hypertension, blood pressure, heart rate, electrocardiogram, left ventricular hypertrophy.
Search in PubMed
(Lead [MH] OR Lead poisoning [MH] OR (Metals, heavy [MH] NOT (Actinium OR Americium OR Antimony OR Barium OR Berkelium OR Bismuth OR Californium OR Cesium OR Chromium OR Cobalt OR Copper OR Curium OR Einsteinium OR Fermium OR Francium OR Gallium OR Germanium Gold OR Hafnium OR Indium OR Iridium OR Iron OR Lawrencium OR Manganese OR Molybdenum OR Neptunium OR Nickel OR Niobium OR Nobelium OR Osmium OR Palladium OR Platinum OR Plutonium OR Protactinium OR Radium OR Rhenium OR Rhodium OR Rubidium OR Ruthenium OR Silver OR Strontium OR Tantalum OR Technetium OR Thallium OR Thorium OR Tin OR Tungsten OR Uranium OR Vanadium OR Zinc OR Zirconium))) AND (Cardiovascular Disease [MH] OR Mortality OR Myocardial Infarction OR Stroke OR Peripheral Arterial Disease OR Peripheral Vascular Disease OR Hypertension OR Blood pressure OR Systolic OR Diastolic OR Atherosclerosis OR Arteriosclerosis OR Electrocardiography OR Heart Rate OR Ventricular Hypertrophy OR heart failure)
Search in EMBASE
(Lead:de OR (Lead poisoning:de)) AND ((cardiovascular disease:de) OR mortality:ti,ab OR (Myocardial Infarction:ti,ab) OR Stroke:ti,ab OR (Peripheral Arterial Disease:ti,ab) OR (Peripheral Vascular Disease:ti,ab) OR Hypertension:ti,ab OR (Blood pressure:ti,ab) OR Systolic:ti,ab OR Diastolic:ti,ab OR Atherosclerosis:ti,ab OR Arteriosclerosis:ti,ab OR Electrocardiography:ti,ab OR (Heart Rate:ti,ab) OR (Ventricular Hypertrophy:ti,ab) OR (heart failure:ti,ab))
Search in TOXLINE
(Lead [MH] OR Lead poisoning [MH]) AND (Cardiovascular Disease [MH] OR Mortality OR Myocardial Infarction OR Stroke OR Peripheral Arterial Disease OR Peripheral Vascular Disease OR Hypertension OR Blood pressure OR Systolic OR Diastolic OR Atherosclerosis OR Arteriosclerosis OR Electrocardiography OR Heart Rate OR Ventricular Hypertrophy OR heart failure)
Appendix
| General populations | Occupational populations | |||||||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Cohort studies | CC and CS studies | Prosp. | Retrospective cohort studies | PMS | ||||||||||||||||||||||||||
| Pocock et al. 1988 | Kromhout 1988 | Møller and Kristensen 1992 | Lustberg and Silbergeld 2002 | Menke et al. 2006 | Pan et al. 1993 | Mansoor et al. 2000 | Gustavsson et al. 2001 | Dulskiene 2003 | Tsai et al. 2004 | Kosmala et al. 2004 | Muntner et al. 2005 | Robinson 1974 | Tollestrup et al. 1995 | Dingwall-Fordyce and Lane 1963 | Malcolm 1971, Malcolm and Barnett 1982 | Sheffet et al. 1982 | Davies 1984 | Cooper et al. 1985 | Belli et al. 1989 | Michaels 1991 | Steenland et al. 1992 | Cocco et al. 1994 | Gerhardsson et al. 1995 | Lundstrom et al. 1997 | Cocco et al. 1997 | Wilczynksa et al. 1998 | Carta et al. 2003 | Alexieva et al. 1981 | McMichael and Johnson 1982 | |
| All studies | ||||||||||||||||||||||||||||||
| Lead exposure was assessed at the individual level | Y | Y | Y | Y | Y | Y | Y | Y | N | Y | Y | Y | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | Y |
| Exposure was assessed measuring lead levels in blood or bone | Y | Y | Y | Y | Y | N | N | N | N | N | Y | Y | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N |
| Outcomes were based on objective tests/standard criteria in ≥ 90% of study participants | Y | Y | N | N | N | N | Y | Y | N | N | Y | Y | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N |
| Authors presented internal comparisons within study participants | Y | Y | Y | Y | Y | Y | Y | Y | Y | Y | Y | Y | Y | Y | Y | N | N | N | N | N | N | N | N | N | N | N | N | N | Y | Y |
| Authors controlled for relevant confounding factors in addition to age and sexb | Y | N | Y | Y | Y | N | N | N | Y | N | N | Y | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N |
| Cohort studies | ||||||||||||||||||||||||||||||
| Loss to follow-up was independent of lead exposure | Y | Y | Y | Y | Y | — | — | — | — | — | — | — | Y | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | — | — |
| Intensity of search of disease was independent of lead exposure | Y | Y | Y | Y | Y | — | — | — | — | — | — | — | Y | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | — | — |
| Case–control and cross-sectional studies | ||||||||||||||||||||||||||||||
| Response rate among noncases was at least 70% | — | — | — | — | — | N | U | Y | U | N | U | Y | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — |
| Exclusion criteria and data collection were similar for all participants | — | — | — | — | — | U | Y | Y | U | U | Y | Y | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | Y | Y |
| Non cases would have been cases if they had developed cardiovascular disease | — | — | — | — | — | U | N | Y | U | U | Y | Y | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | N | N |
| Interviewer was blinded with respect to the participant case or exposure status | — | — | — | — | — | U | U | U | U | U | U | Y | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | N | N |
Abbreviations: —, not applicable; CC, case–control study; CS, cross-sectional study; N, no; PMS, proportional mortality study, Prosp., prospective; U, unclear; Y, yes.
a
Criteria modified from Longnecker et al. (1988).
b
In occupational studies, relevant factors included the healthy worker survivor effect. Studies that adjusted for blood pressure levels were considered not to fulfill this criterion.
Appendix
| Ventricular mass and function | Heart rate variability | Other cardiac abnormalities | Other vasc. | |||||||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Schwartz 1991 | Zou et al. 1995 | Tepper et al. 2001 | Kasperczyk et al. 2005 | Beck and Steinmetz-Beck 2005 | Murata and Araki 1991 | Teruya et al. 1991 | Gennart et al. 1992 | Murata et al. 1995 | Ishida et al. 1996 | Niu and Abbritti 1998 | Böckelmann et al. 2002 | Gajek et al. 2004 | Andrzejak et al. 2004 | Muzi et al. 2005 | Jhun et al. 2005 | Kosmider and Petelenz 1961 | Kosmider 1962 | Krotkiewski et al. 1964 | Kosmider et al. 1965 | Kosmider 1968 | Stozinic and Colakovic 1980 | Saric 1981 | Kromhout et al. 1985 | Kirkby and Gyntelberg 1985 | Sroczynski et al. 1985 | Shcherbak1988 | Sroczynski et al. 1990 | Gatagonova 1995 a,b,d | Gatagonova 1995 c | Cheng et al. 1998 | Aiba et al. 1999 | |
| Association estimates based on lead assessed at the individual level | Y | Y | Y | N | N | N | Y | N | N | Y | N | N | N | N | N | Y | N | N | N | N | N | N | N | Y | N | N | N | N | N | N | Y | Y |
| Association estimates based on blood or bone lead measures | Y | Y | Y | N | N | N | Y | Y | N | Y | N | N | N | N | N | Y | N | N | N | N | N | N | N | Y | N | N | N | N | N | N | Y | Y |
| Cardiovascular tests were based on a standardized protocol | Y | Y | Y | Y | Y | Y | Y | Y | Y | Y | U | Y | Y | Y | Y | Y | N | N | Y | N | N | N | N | Y | Y | Y | U | Y | N | N | Y | N |
| Authors indicate that examiners received training to conduct cardiovascular tests | Y | N | Y | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | Y | Y | N | N | N | N | N | Y | U |
| Inclusion and exclusion criteria were similar for all participants | Y | U | Y | U | Y | Y | Y | N | Y | Y | U | Y | N | Y | U | Y | U | U | U | U | U | U | N | Y | Y | U | Y | U | U | U | Y | U |
| Recruitment procedures were similar for all participants | Y | U | Y | U | U | Y | Y | Y | N | Y | U | U | N | Y | U | Y | U | U | U | U | U | U | N | Y | Y | U | Y | U | U | U | Y | U |
| Response rate was at least 70% | Y | U | N | U | U | U | U | Y | U | U | U | U | U | U | U | U | U | U | U | U | U | U | U | Y | Y | U | U | U | U | U | Y | U |
| Examiner was blinded with respect to the participant exposure status | Y | U | U | U | U | U | Y | U | U | Y | U | U | U | U | U | Y | U | U | U | U | U | U | U | Y | N | U | U | U | U | U | Y | U |
| Authors controlled for relevant confounding factors in addition to age, sex | Y | Y | Y | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | Y | N | N | N | N | N | N | Y | N |
Abbreviations: N, no; U, unclear; vasc., vascular; Y, yes;.
a
Criteria modified from Appel et al. (2002).
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Received: 3 October 2006
Accepted: 20 December 2006
Published online: 22 December 2006
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