Cumulative Lead Dose and Cognitive Function in Adults : A Review of Studies That Measured Both Blood Lead and Bone Lead Objective We review empirical evidence for the relations of recent and cumulative lead dose with cognitive function in adults . In the development of the adult lead management guidelines -LRB- see Kosnett et al. 2007 -RRB- , a number of health outcomes adversely affected by lead exposure were discussed . Cognitive function was an important consideration of because of the growing number of studies in this area and increasing concern that cognitive function in adulthood may be affected by relatively low lead doses . In this article , we systematically review recent evidence concerning recent and cumulative lead dose and adult cognitive function . Measurement of lead dose In reviewing studies of the health effects of lead , it is critical to understand the available lead biomarkers in terms of how they represent external exposure -LRB- in terms of timing , duration , magnitude , and accumulation -RRB- ; how they are influenced by metabolic factors -LRB- organ distribution , compartmental dynamics , the influence of physiologic factors -RRB- ; and how the combination of these considerations affects inferences regarding the health effects of lead -LRB- Hu et al. 2007 -RRB- . We conclude from these important methodologic issues that the most informative recent epidemiologic studies of lead 's impact on health are those that were able to derive estimates of both recent and cumulative lead exposure for each study participant . To achieve this end with the greatest precision and accuracy , such studies have incorporated measurements of lead in both blood -LRB- whole blood , using standard chemical assays such as graphite furnace atomic absorption spectroscopy -RRB- and bone -LSB- using noninvasive in vivo K-shell X-ray fluorescence -LRB- KXRF -RRB- instruments -RSB- . Blood lead levels measured in epidemiologic studies with valid instruments and standardized calibration and quality control procedures have been reported in the literature for > 35 years . Bone lead levels measured by in vivo KXRF were begun in some research laboratories in the 1980s , but it was not until the mid-1990s that reports began to emerge of KXRF-measured bone lead levels in relation to potential health indicators from epidemiologic studies with sufficient sample sizes -LRB- for example , ≥ 100 subjects -RRB- to have substantial statistical power . Thus , in this review we summarize all studies to date that measure cognitive function and both blood and bone lead levels -LRB- or acceptable surrogate for cumulative lead dose -RRB- . Published reviews of relevance to this review We begin our review with a discussion of three other reviews on the topic of lead dose and cognitive function -LRB- Balbus-Kornfeld et al. 1995 ; Goodman et al. 2002 ; Meyer-Baron and Seeber 2000 -RRB- . Balbus-Kornfeld et al. -LRB- 1995 -RRB- reviewed the evidence on cumulative lead exposure and cognitive function from studies published from 1976 to 1991 . Among 21 unique studies that were identified at the time of the authors ' review , none used a biomarker of cumulative dose . Of the four longitudinal studies , all were small -LRB- mean sample size in the analysis of 47 lead-exposed subjects -RRB- , with relatively low follow-up rates and relatively short durations of follow-up . The authors thus concluded that the available literature provided inadequate evidence to conclude whether cumulative exposure or absorption of lead adversely affected cognitive function in adults . Goodman et al. -LRB- 2002 -RRB- and Meyer-Baron and Seeber -LRB- 2000 -RRB- are reviewed here because they had generally opposite conclusions , which led to considerable controversy and discussion -LRB- Goodman et al. 2001 ; Schwartz et al. 2002 ; Seeber and Meyer-Baron 2003 ; Seeber et al. 2002 -RRB- . The Goodman et al. -LRB- 2002 -RRB- article was funded by the German Battery Association , apparently in anticipation of consideration in Germany of lowering the blood lead standard in lead workers -LRB- Seeber and Meyer-Baron 2003 -RRB- . Goodman et al. -LRB- 2002 -RRB- reviewed 22 studies published between 1974 and 1999 with the expressed aim of evaluating associations between moderate blood lead levels and neurobehavioral test scores after occupational exposure to lead . Studies were included if the central tendency for blood lead levels was < 70 μg/dL , the numbers of exposed and unexposed were reported , and test score arithmetic means and measures of variability were reported for exposed and unexposed workers -LRB- Goodman et al. 2002 -RRB- . The authors concluded that none of the individual studies were conclusive or adequate in providing information on the effects of lead on cognitive function and called for prospective studies that would evaluate cognitive function before and after exposure . There was no discussion about whether examining relations of blood lead levels with cognitive function was the most relevant question if the hypothesis was that cumulative lead dose was most important to cognitive function . There was little explicit discussion of whether lead may have acute effects as a function of recent dose , and chronic effects as a function of cumulative dose , or how this could be assessed by review of epidemiologic studies . Meyer-Baron and Seeber -LRB- 2000 -RRB- performed a meta-analysis of 12 studies using selection criteria similar to Goodman et al. -LRB- 2002 -RRB- but also with the requirement for reporting means and standard deviations of dependent variables -LRB- Meyer-Baron and Seeber 2000 -RRB- . They concluded that there were obvious neurobehavioral deficits at current blood lead levels < 40 μg/dL . Again , the focus was on associations with blood lead levels , and there was little formal discussion about which lead biomarker was most relevant to hypotheses about how cumulative lead dose may influence cognitive function . Thus , this is the first review to evaluate epidemiologic studies that distinguish between the acute effects of recent dose from the chronic effects of cumulative dose . Methods Methodologic considerations for relations of lead dose and cognitive function Many methodologic issues of relevance to the epidemiologic investigation of lead and cognitive function have been addressed elsewhere in this minimonograph -LRB- Hu et al. 2007 -RRB- . When evaluating the associations of cumulative lead dose with cognitive function , it is important to acknowledge that nonoccupational sources of lead exposure were present for all members of the general population , including lead workers throughout the early part of this century until public health interventions progressively removed lead from gasoline and many consumer products during the 1970s and 1980s -LRB- Agency for Toxic Substances and Disease Registry 1999 ; Annest et al. 1983 ; Pirkle et al. 1998 -RRB- . Lead remains a low-level and ubiquitous neurotoxicant in the environment and is found in measurable levels in all individuals -LRB- Hoppin et al. 1995 -RRB- . Thus , current tibia lead levels represent a mix of occupational and environmental exposures . This review does not try to determine whether the main source of lead was occupational or environmental but rather focuses on whether lead in blood or bone is associated with adverse cognitive outcomes in adults . Identification of studies We conducted a systematic literature review of the association between blood and bone lead biomarkers and cognitive functioning in adults . Our aim was to select studies that compared markers of both recent and cumulative lead dose in their relations with cognitive function . Both occupationally and environmentally exposed adult populations were included . We searched the PubMed -LRB- National Library of Medicine 2006 -RRB- and PsycINFO databases -LRB- American Psychological Association 2006 -RRB- for epidemiologic studies using keywords such as blood , bone , lead , cumulative , cognitive , and neurobehavior . There were no date or language restrictions . From the identified publications and relevant review articles , we examined reference lists to locate additional studies that measured both recent and cumulative lead dose . This includes blood lead levels , bone lead levels , or a surrogate measure of cumulative lead dose such as integrated blood lead -LRB- IBL -RRB- , area under the curve of blood lead levels over time , or the product of blood lead level and employment time . Studies were not considered for the review if they a -RRB- contained no original research , b -RRB- were conducted on nonhuman subjects , c -RRB- were case reports , d -RRB- contained no standardized neurocognitive assessment outcomes , or e -RRB- lacked measures of both recent and cumulative lead dose . Data abstraction We abstracted data from articles meeting the selection criteria . Study quality was assessed with the following criteria : a -RRB- exposure was assessed at an individual level ; b -RRB- exposure was assessed with a biomarker ; c -RRB- cognitive outcomes were objective , standardized tests ; d -RRB- statistical adjustment for potential confounders including age , sex -LRB- in studies with both men and women -RRB- , and education ; e -RRB- data collection was similar in exposed and nonexposed participants ; f -RRB- time period of study was the same in exposed and nonexposed participants ; and g -RRB- there was a detailed description of the approach to data analysis . We decided not to try to derive a pooled estimate across studies of the associations of lead dose biomarkers with cognitive function because of differences in methods for subject selection , blood and bone lead measurements , neurobehavioral outcomes , approach to regression modeling , and presentation of results across studies . Pooled estimates from metaanalysis also can be highly influenced by decisions regarding how and whether to pool certain results . We thus decided to present details for each study and discuss them in turn . Results Overview of evidence We identified three main types of studies that reported cross-sectional or longitudinal associations of blood and bone lead levels with cognitive function . These were of a -RRB- environmentally exposed individuals in the general population , b -RRB- workers with current occupational exposure , and c -RRB- former lead workers without current occupational exposure to lead . We have summarized these studies in Table 1 , provided details in Table 2 , and discuss them in order below . Studies of adults without occupational lead exposure We identified six articles from three studies -LSB- i.e. , residents near a lead smelter , the Normative Aging Study -LRB- NAS -RRB- , and the Baltimore Memory Study -RSB- that evaluated subjects with mainly environmental exposure to lead -LRB- Tables 1 and 2 -RRB- . One study of young adults 19 -- 29 years of age compared 257 individuals with high childhood blood lead levels from exposure 20 years previously from a lead smelter to 276 age - and sex-matched controls . This study found impairment on many cognitive tests among the highly exposed group , but minimal association on most tests with tibia lead levels measured during young adulthood -LRB- Stokes et al. 1998 -RRB- . Four articles from the NAS reported associations of blood and bone lead levels in a cohort of older men . One of these articles -LRB- Payton et al. 1998 -RRB- was a first report that examined scores on a large battery of cognitive tests of a small sample -LRB- n = 141 -RRB- of NAS participants . This was subsequently followed up with a report on a much larger number of NAS participants -LRB- n = 1,089 with blood lead levels and n = 760 with bone lead levels , 412 -- 515 of whom took different tests twice approximately 3.5 years apart -RRB- -LRB- Weisskopf et al. 2007 -RRB- . Cross-sectional analyses in the original report found that increased blood lead levels across a relatively low range of levels -LSB- mean ± SD = 5.5 ± 3.5 μg/dL -RRB- were a stronger predictor , compared with tibia or patella lead levels , of poorer performance on tests of speed , verbal memory , vocabulary , and spatial copying skills . However , this was not confirmed in the larger , cross-sectional analysis , except possibly for scores on a vocabulary test -LRB- Weisskopf et al. 2007 -RRB- . Conversely , in longitudinal analyses , the larger study found more decline over time on almost all cognitive tests associated with both higher patella and higher tibia bone lead levels , with the associations reaching statistical significance for pattern comparison and spatial copying skills . An earlier , similar longitudinal analysis by Weisskopf et al. -LRB- 2004 -RRB- in this same population reported that patella lead levels were significantly associated with a decline in Mini-Mental State Examination -LRB- MMSE ; Folstein et al. 1975 -RRB- score over time . A slightly smaller association was observed with tibia lead levels , whereas no association was observed with blood lead levels . In cross-sectional analyses of the same population , higher blood lead levels were a stronger predictor of poorer performance on the MMSE , as were higher patella and tibia bone lead levels -LRB- Payton et al. 1998 ; Wright et al. 2003 -RRB- . In a study of almost 1,000 persons 50 -- 70 years of age randomly selected from the general population in the Baltimore Memory Study -LRB- BMS -RRB- , a cross-sectional analysis showed that relatively low current blood lead levels were not associated with cognitive domain scores . However , moderate tibia lead levels -LRB- mean ~ 19 μg/g -RRB- were significantly associated with worse performance in all seven cognitive domains -LRB- Shih et al. 2006 -RRB- . Thus , in the environmental studies of older adults , the most consistent findings across studies are associations between bone lead levels and cognitive function . The associations in the BMS were cross-sectional , whereas the predominant associations in the NAS were with change in cognitive function over time , although a significant cross-sectional association with MMSE score was also observed in this sample . Taken together , these data suggest that at environmental exposure levels , the effects of cumulative exposure are more pronounced than recent effects of current exposure . The absence of associations in the Stokes et al. -LRB- 1998 -RRB- study could be because of the younger age of studied subjects , the very low current blood and tibia lead levels , or the inadequacy of tibia lead in the third decade of life to estimate early life dose -LRB- Hoppin et al. 2000 -RRB- . Studies of occupationally exposed workers Fifteen articles were identified of workers with current or past occupational exposure to lead . Eight of these studies used a surrogate measure of cumulative lead dose -LRB- i.e. , IBL -RRB- rather than a direct measure of lead in bone . Among these studies , which compared blood and IBL lead dose , when the lead exposure was primarily current -LRB- e.g. , relatively high blood lead levels -RRB- , most studies found an association between increasing blood lead values and worse cognitive function -LRB- Barth et al. 2002 ; Bleecker et al. 1997 ; Lucchini et al. 2000 -RRB- . However , studies in which the exposure was primarily in the past demonstrated that surrogate measures of cumulative dose were a stronger predictor of worse cognitive function compared with blood lead levels -LRB- Bleecker et al. 2005 ; Chia et al. 1997 ; Lindgren et al. 1996 -RRB- . Studies that used bone lead levels as a direct indicator of retained cumulative lead dose are summarized below . One study of currently exposed lead workers in South Korea -LRB- n = 803 -RRB- found strong and consistent associations of blood lead levels with worse cognitive function after adjustment for covariates , but tibia lead levels were not as consistently associated -LRB- Schwartz et al. 2001 -RRB- . The same null findings for bone lead levels were observed in two smaller studies , one with male smelter workers -LRB- n = 57 -RRB- in whom finger bone -LRB- mixed trabecular and cortical tissue -RRB- lead levels were measured -LRB- Osterberg et al. 1997 -RRB- . The second article describes the study of a sample of 54 storage battery workers in whom tibia and calcaneus lead levels were measured -LRB- Hanninen et al. 1998 -RRB- . This is the only study published to date to report an association between IBL and cognitive outcomes in which there was a lack of an association with bone lead levels . Both these studies used early XRF techniques -LRB- e.g. , KXRF with cobalt-57 -RRB- with higher limits of detection that have not been commonly used since , and this use makes the findings more difficult to interpret . Bleecker et al. -LRB- 1997 -RRB- , in a study similar to the one by Schwartz et al. -LRB- 2001 -RRB- , reported stronger and more consistent associations of blood lead measures and neurobehavioral test performance compared to tibia lead levels . In the South Korean lead workers with current occupational exposure , a longitudinal analysis was performed to separate recent lead dose -LRB- measured as blood lead levels -RRB- from cumulative lead dose -LRB- measured as tibia lead levels -RRB- , and acute effects from chronic effects in 575 subjects with complete data across the three study visits -LRB- Schwartz et al. 2005 -RRB- . The authors reported significant cross-sectional associations of blood lead levels with lower executive ability and manual dexterity test scores , with some evidence also for a longitudinal association of changes in blood lead levels with neurobehavioral decline . Tibia lead levels were more consistently associated with longitudinal declines in manual dexterity , executive abilities , neuropsychiatric symptoms , and peripheral sensory functioning than change in blood lead levels . The authors concluded that lead was associated with worse cognitive function in two ways : an acute effect of recent dose and a chronic effect of cumulative dose . The authors also discussed that contrasting associations with blood and tibia lead levels could be due to the following : a -RRB- tibia and blood lead levels are biologically related and blood lead is in equilibrium with bone lead stores ; b -RRB- the error in measurement of tibia lead levels is larger than that for blood lead ; c -RRB- controlling for cross-sectional associations could obscure longitudinal ones ; and d -RRB- lead in blood reflects recent external exposure , and is in equilibrium with bone lead stores , possibly taking away explained variance from bone lead associations via this correlation in cross-sectional analyses . Results of a cross-sectional analysis of former organolead workers showed that higher peak tibia lead levels -LRB- range , -- 2.2 to 105.9 μg/g -RRB- were related to poorer functioning on a number of cognitive tests , including those assessing manual dexterity , executive ability , verbal intelligence , and verbal memory -LRB- Stewart et al. 1999 -RRB- . In a longitudinal analysis in this same population , among 535 lead workers exposed a mean of 16 years before , increases in peak tibia lead levels -LSB- mean ± SD = 22.6 ± 16.5 μg/g -RSB- but not in blood lead levels predicted declines over time in these same domains in addition to visual memory -LRB- Schwartz et al. 2000 -RRB- . This finding indicates that even many years after high lead exposure , and in the absence of high current lead exposure , cumulative lead dose may exert progressive effects on cognitive functioning -LRB- Links et al. 2001 -RRB- . Lead exposure and psychiatric symptoms Several lines of evidence suggest that increased blood lead levels are associated with psychiatric symptoms in adults , such as depression , anxiety , irritability , and anger . For example , a cross-sectional analysis of 107 occupationally exposed individuals showed increased rates of depression , confusion , anger , fatigue , and tension as measured by the Profile of Mood States -LRB- POMS ; McNair et al. 1971 -RRB- among those with blood levels > 40 μg/dL -LRB- Baker et al. 1983 -RRB- . Maizlish et al. -LRB- 1995 -RRB- found that current and cumulative measures of blood lead levels in currently exposed lead workers were associated with tension , anxiety , hostility , and depression measured by the POMS questionnaire . Lindgren et al. -LRB- 1996 -RRB- examined the POMS ' factor structure in retired lead smelter workers and showed that the resulting `` general distress '' factor was significantly related to IBL but not to current blood lead level . In occupationally exposed South Korean lead workers , tibia lead levels were significantly associated with more depressive symptoms measured by the Center for Epidemiologic Studies Depression scale -LRB- CES-D ; Radloff 1977 -RRB- after adjusting for age , sex , education , job duration , and blood lead level -LRB- Schwartz et al. 2001 -RRB- . However , only one recent study has examined a direct measure of cumulative dose with bone measurements in a community sample -LRB- Rhodes et al. 2003 -RRB- . These authors used the Brief Symptom Inventory -LRB- BSI ; Derogatis and Melisaratos 1983 -RRB- to show that patella bone lead levels were associated with an increased risk of anxiety and depression sub-scale scores . The logistic regression estimate for the phobic anxiety subscale was statistically significant -LRB- p < 0.05 -RRB- , as well as for the combined measure of all three BSI subscales -LRB- anxiety , depression , and phobic anxiety -RRB- . Psychiatric symptoms , specifically symptoms of depression , potentially share the same neural substrates with components of cognition , and thus may be important to late-life cognitive functioning . Compared with nondepressed elderly individuals , depressed elderly perform more poorly on tests involving attention , memory encoding , and retrieval . However , intelligence tests are more resistant to these effects of depression -LRB- Arnett et al. 1999 ; Naismith et al. 2003 ; Weingartner et al. 1981 -RRB- . Depressive symptoms -LRB- as measured by the CES-D -RRB- are positively associated with both the risk of Alzheimer disease and a steeper rate of cognitive decline -LRB- Wilson et al. 2002 -RRB- . Because late-life symptoms of depression are closely associated with dementia , investigators have put forth a number of hypotheses that suggest depression a -RRB- may be a risk factor for cognitive decline , b -RRB- has risk factors in common with dementia , c -RRB- is an early reaction to declining cognition , and d -RRB- influences the threshold at which dementia emerges -LSB- for review see Jorm -LRB- 2000 -RRB- -RSB- . The exact temporal and mechanistic relation remains unclear . Regardless of the exact relation between depressive symptoms and cognitive function , however , the assessment of the impact of lead exposure on these outcomes is not compromised . Whatever the associations with these outcomes , they would still be attributed to lead -- that is , even if depressive symptoms lead to worse cognitive performance , and lead leads to symptoms of depression , the cognitive impairment as a result of that depression could still be considered part of the total effect of lead . Lead -- gene interactions In the former organolead worker studies discussed above , possessing at least one apolipoprotein E -LRB- APOE -RRB- ɛ 4 allele magnified the negative cross-sectional association of tibia lead levels with performance on the cognitive domains of executive ability , manual dexterity , and psychomotor skills -LRB- Stewart et al. 2002 -RRB- . No direct effects of the APOE ɛ 4 allele were observed on cognitive function in this study , presumably because of the sample 's younger age -LRB- range , 41 -- 73 years -RRB- . Other studies have found that APOE ɛ 4 modifies dementia outcome in individuals with previous traumatic head injury , suggesting that APOE ɛ 4 plays a role in recovery from brain insults -LRB- Mayeux et al. 1995 -RRB- , which may be extended to include insult from lead exposure . Discussion Summary of evidence for a causal relationship The literature on associations of recent and cumulative dose biomarkers with cognitive function has grown impressively since the 1995 review -LRB- Balbus-Kornfeld et al. 1995 -RRB- . We believe sufficient evidence exists to conclude that there is an association between lead dose and decrements in cognitive function in adults . Overall , while the association between blood lead levels and cognitive function is more pronounced in occupational groups with high current lead exposures , associations between bone lead levels and cognitive function are more evident in studies of older subjects with lower current blood lead levels , particularly in longitudinal studies of cognitive decline . Consistency of associations Following is a summary of the findings from each of the three types of populations . First , cross-sectional studies of currently exposed lead workers showed that associations of blood lead levels and cognitive function were clearer than the associations for tibia , patella , or calcaneus lead levels , perhaps because the acute effects of recent dose in an occupational setting masked the chronic effects of cumulative lead dose . Second , previously exposed occupational populations demonstrated a stronger association between cumulative lead dose measured in tibia bone with cognitive deficits compared with blood lead levels . The two studies that deviated from these otherwise consistent findings may not have had sufficient power to detect any associations -LRB- n < 60 -RRB- . Last , studies of environmentally exposed adults who had notably higher exposures in the past suggest that bone lead level is more consistently associated with performance on cognitive tests than is blood lead level . The domains associated with lead dose do not differ in general by lead biomarker -LRB- blood , tibia , patella -RRB- . The cognitive domains consistently associated with each biomarker in both environmental and occupational studies on adults include verbal and visual memory , visuospatial ability , motor and psychomotor speed , manual dexterity , attention , executive functioning , and peripheral motor strength . Comparisons of lead and psychiatric symptom associations in previously and currently exposed samples lend credence , although perhaps at higher thresholds than for cognitive outcomes , that neurobehavioral functioning is consistently associated with blood lead when exposure is currently high -LRB- e.g. , occupational -RRB- and bone lead when exposure is primarily from past chronic exposure . These associations exist in multiple settings , including both occupational and non-occupational , in men and women , and in populations with diversity by socioeconomic status and race/ethnicity . This reduces the likelihood of associations by statistical chance or due to unmeasured confounding . However , this consistency can not completely rule out the possibility of uncontrolled confounding or effect modification -LRB- Martin et al. 2006 ; Shih et al. 2006 -RRB- . In addition , in studies of general populations with diversity by socioeconomic status and race/ethnicity , the ability to disentangle social , cultural , and biological factors from the `` independent '' influence of lead dose may be a futile exercise -LRB- Weiss and Bellinger 2006 -RRB- . Strength of association The strength of associations between lead and cognitive function is strong and can be compared to the influence of age on cognitive function . The comparative magnitude of these effects has been reported in several studies . In currently exposed lead workers , cross-sectional associations showed that a 5-μg/dL increase in blood lead was equivalent to an increase of 1.05 years in age -LRB- Schwartz et al. 2001 -RRB- . The magnitude of cross-sectional associations with tibia lead levels in the BMS was moderate to large . A proportion comparison of the direct effect of age and the direct effect of tibia lead levels on cognitive outcomes demonstrated that the magnitude of the association with tibia lead levels was moderate to large , equivalent to 22 -- 60 % of the magnitude of the age effect in its relations with cognitive domain scores . Specifically , an interquartile range increase in tibia lead levels was equivalent to 2 -- 6 more years of age at baseline across all seven domains -LRB- Shih et al. 2006 -RRB- . Longitudinal analyses in the NAS observed that an interquartile range higher patella lead level was approximately equivalent to that of aging 5 years in relation to the baseline MMSE score -LRB- Weisskopf et al. 2004 -RRB- and an interquartile range higher bone -LRB- patella or tibia , depending on the specific cognitive outcome -RRB- lead level was approximately equivalent to that of aging 1 year in relation to the baseline test scores on a battery of cognitive tests -LRB- Weisskopf et al. 2007 -RRB- . Specificity Lead has adverse effects on many other health outcomes in addition to cognitive function . This is not surprising given lead 's numerous biologic effects , including calcium agnonism and antagonism -LRB- Ferguson et al. 2000 -RRB- , binding to sulfhydryl and carboxyl groups on proteins , and activation of nuclear transcription factors -LRB- Ramesh et al. 2001 -RRB- , for example . It is thus not surprising that lead 's toxicity is not specific to the brain and we do not believe this lack of target organ specificity diminishes the inference for a causal relationship between lead and cognitive dysfunction . Temporal relationship Associations between lead biomarkers and cognitive outcomes have been demonstrated in both cross-sectional and longitudinal studies . In several of the longitudinal studies , change in cognitive function was explicitly modeled in relation to preceding lead dose or in relation to change in lead dose . In either case , the temporality condition is met . In addition , as bone lead is a measure that ascertains prior dose , even in cross-sectional analyses , analysis of bone lead with cognitive test scores evaluates lead dose that preceded current cognitive performance ; thus , while cognitive assessment is cross-sectional , dose assessment is retrospective and cumulative . This again would minimize concerns about incorrect temporal relations . Biological gradient -LRB- dose -- effect relations -RRB- Nearly all reviewed studies found a dose -- effect relation for blood lead , bone lead , or both . Existing studies do not allow determination of a threshold dose for either blood lead or bone lead or the shape of the dose -- effect relationship at low dose levels . Associations have been observed in populations with mean blood lead levels as low as 4.5 μg/dL -LRB- Wright et al. 2003 -RRB- and mean tibia lead levels as low as 18.7 μg/g -LRB- Shih et al. 2006 -RRB- . Biologic plausibility and experimental data Lead adversely affects the brain in a variety of ways . Lead is thought to increase oxidative stress , induce neural apoptosis , influence neurotransmitter storage and release , and damage mitochondria . The ability of lead to substitute for calcium allows it to affect calcium-mediated processes and pass through the blood -- brain barrier . It may also interfere with zinc-dependent transcription factors , altering the regulation of genetic transcription -LRB- Zawia et al. 2000 -RRB- . Animal studies indicate that the accumulation of lead in the brain is generally uniform -LRB- Widzowski and Cory-Slechta 1994 -RRB- , although the hippocampus and limbic system , prefrontal cerebral cortex , and cerebellum are clearly principal sites of the effects of lead -LRB- Finkelstein et al. 1998 -RRB- . Low lead levels in rats produce structural changes in the hippocampus -LRB- Cory-Slechta 1995 -RRB- , a brain region critical for learning and memory -LRB- Eichenbaum 2001 -RRB- , which is consistent with the finding of learning and memory deficits in lead-exposed individuals . Blood lead level is a measure of current biologically active lead burden and is therefore a better marker of the acute effects of recent lead dose . These are likely to be effects on neurotransmission and calcium enzyme-dependent processes such as synaptic plasticity . This could lead to circulating blood lead impairing , for example , information storage and retrieval mechanisms or processing speed , which have been suggested to impair performance on cognitive tests -LRB- Salthouse 1996a , 1996b -RRB- . Lead levels in bone are a measure of cumulative dose over decades as well as a source of lead in the body that is available for mobilization into blood , especially during periods of increased bone turnover -LRB- e.g. , pregnancy , puberty -RRB- . Although lead stored in bone is not directly harmful to the brain , the cumulative effects of chronic lead exposure are likely to be related to oxidative stress and neuronal death and could impair cognitive function , for example , by reducing the capacity of specific regions to process information , or by impairing diffuse ascending projection systems such as the midbrain cholinergic and dopaminergic cells . Lead may also influence cognitive function indirectly through its effects on blood pressure , hypertension , or homocysteine levels . Increased homocysteine levels , a well-known risk factor for cardiovascular disease , have also been associated with risk for poorer cognitive functioning -LRB- Dufouil et al. 2003 ; Schafer et al. 2005a -RRB- and risk for dementia -LRB- Hogervorst et al. 2002 ; McCaddon et al. 2003 ; Selley 2003 -RRB- . Homocysteine is neurotoxic to the central nervous system by influencing neurotransmitter synthesis , and causing excitotoxicity and cell death -LRB- McCaddon and Kelly 1992 ; Parnetti et al. 1997 -RRB- . Blood lead levels were associated with homocysteine levels as well , although the direction of causality has yet to be determined -LRB- Guallar et al. 2006 ; Schafer et al. 2005b -RRB- . Both blood and bone lead levels have been linked with blood pressure and hypertension in community-based samples of older adults -LRB- Martin et al. 2006 ; Nash et al. 2003 -RRB- and occupationally exposed populations -LRB- Glenn et al. 2003 , 2006 -RRB- . Hypertension has also been identified as a potential risk factor for dementia -LRB- Birkenhager and Staessen 2006 ; Hayden et al. 2006 ; Skoog and Gustafson 2006 -RRB- . Thus , lead may indirectly play a role in cognitive declines by way of poor vascular health . We believe the effect modification by APOE genotype offers strong biologic plausibility to the inference that lead causes cognitive dysfunction -LRB- Stewart et al. 2002 -RRB- . The APOE ɛ 4 allele is a risk factor for lateonset Alzheimier disease -LRB- Corder et al. 1993 ; Meyer et al. 1998 ; Saunders et al. 1993 -RRB- , hippocampal atrophy -LRB- Moffat et al. 2000 -RRB- , and senile plaques -LRB- Zubenko et al. 1994 -RRB- . It appears that the APOE ɛ 4 allele lowers the age of onset of the disease and accelerates age-related cognitive decline -LRB- Meyer et al. 1998 -RRB- . Mechanistically , APOE ɛ 4 is involved in the recovery response of injured nerve tissue -LRB- Poirier and Sevigny 1998 -RRB- , with the APOE ɛ 4 allele having reduced ability to promote growth and reduced antioxidant properties -LRB- Miyata and Smith 1996 ; Teter et al. 1999 ; Yankner 1996 -RRB- . The interaction of APOE genotype with tibia lead level may be related to an impaired ability to counteract injury from lead exposure among APOE ɛ 4 carriers . Another recent study also offers biologic plausibility . In the former organolead workers , tibia lead level was associated with the prevalence and severity of white matter lesions on brain MRI , using the Cardiovascular Health Study white matter grading system -LRB- Stewart et al. 2006 -RRB- . Tibia lead level was also associated with smaller volumes on several regions of interest ranging from large -LRB- e.g. , total brain volume , lobar gray and white matter volumes -RRB- to small -LRB- e.g. , cingulate gyrus , insula , corpus callosum -RRB- . As volume can decline because of changes in cell number , synaptic number or density , or other changes in cellular architecture , these findings reinforce evidence that lead may cause a persistent change in the brain that is associated with progressive declines in cognitive function . Public health implications The removal of lead from gasoline , paint , and most other commercial products has succeeded in dramatically reducing environmental sources of lead exposure , and this has been reflected by the parallel declines in mean blood lead levels in Americans over the same time frame . However , lead has accumulated in the bones of older individuals , and especially those of lead workers exposed at the continued higher levels encountered in lead-using workplaces . Thus , past use of lead will continue to cause adverse health effects even when current exposures to lead are much lower than in the past . Lead in bone is not directly harmful to the central nervous system , and most of the structural and neurochemical damage is likely to have occurred decades ago . Nevertheless , lead in bone might serve as a source from which lead can be mobilized into blood , and potentially cross the blood -- brain barrier . The chronic effects of lead may account for a proportion of cognitive aging ; future research will be able to determine whether the chronic effects of cumulative lead dose alter the trajectory of normal cognitive aging . Research efforts should be directed to development of preventive interventions for both lead-associated cognitive decline with aging from past exposures , as well as the mobilization of current bone lead stores into the circulatory system leading to new health effects . Cognitive aging occurs in conjunction with the normal biological aging process . It remains to be determined whether lead affects cognitive aging in adults by permanently reducing brain circuitry capacity thereby lowering baseline cognitive functioning , or by inducing steeper declines in cognitive functioning , leading to abnormal cognitive aging . It may be that lead influences cognitive health through its relationship with depressive symptoms , hypertension , or homocysteine levels , all of which influence cognitive impairment and risk of dementia . Future investigations should explicitly account for these complex causal pathways , and also determine whether chronic effects of cumulative lead dose increases the risk for such clinically relevant syndromes as mild cognitive impairment -LRB- Petersen et al. 1999 -RRB- .

O B O O B I O B O O O O O O O O B B O B B O O O O O O O O O O O O B O O B I O B O O O O O O O B O O O O O O O O O O O O O O O O O O B O O O O B I O O O O O O O O O O O O O O O O O O O B I O O O O O O O O B O O O O O O O O O O O O O O O B O O O B I O O O B O O O O O O O O O B O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O B O O B O O B O O O O O O O O O O O O O O B O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O B O B B O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O B I O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O B O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O B I O O O O O O O O B I O O O O O O O O O O O O O O B B O O B I O O O O O O O O O O O B O O O O O B I O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O B B O O O O O O O O O O B O O O O O O O O O B O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O B I O O O O O O O O O O B O B I O O O O O O O O O O O O O O O O O O O O B O O B I O O O O O O O O O O B O O O O O O O O O O O O B O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O B O B O B O O O O O O O B O O O O O O O O O O O O O O B O B B O O O O O B O O O O O O O O O O O O O O O B O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O B O B O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O B B O O B B O O O O O O O O B O O O O B B O O O O O O O O O B B O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O B I O O O O O O O O O B O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O B B O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B O O B O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O B O O O O O O O O O O O O B B O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O B O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O B B O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O B B O O B I O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O B O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O B O O O O O O O O O O O O B O B O O O O O O O B O O B O O O O B O O O O O O O O O B B O O O O O O O O O O B B O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O B B O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O B O O O O O O O O O O B O O O O O O O O O O O O O O O B B O O O B I O O O O O O O B O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O B O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O B O O O O O O B O O O O O O O O O O O O O O B O O O O B B O O O O B O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O B O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O B O O B O O O O O O O O O O O O B B O O O O O B B O O O O B B O O O O O O O O O O B O O O O O O B B O O O O O O O O O O O O O O O B O B O O O O O O O O O O B B O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O B O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O B O O O B O O O O O O O O O O O O O O O B O O O O O O O O O O O B B O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O B O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O B O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O B I O B O O O O O O O B B O O B I O O O O O O O O O B O O O O B B O O B I O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O B B O O B I O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O B O O O O B O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O B B O O O O O O O O O O O O B B O O O O O O B O O O O O O O B O O B O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O B O B I O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O B O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O B I O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O B O O O O O O O B O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O B B O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O B B O O O O O O O O O O O O O O O O B B O B B O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O B O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O B O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O B O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O B O O O O O O O O O O O O O O B O O O O O O O O O B O O O O O O B O O O O O O O O O O B O O B O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O B I O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O B B O O O O O B O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B I O O O O O O O B O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O B B O O O O O O O O O O O B O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O B O O O O O O O O B O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O B O O O O O O O B O O O O B O O O O O B O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O

adults
blood
bone
cognitive function
lead
neurobehavior


The effect of birth-weight with genetic susceptibility on depressive symptoms in childhood and adolescence Low birth-weight has been associated with depression and related outcomes in adults , and with problem behaviours in children . This study aimed to examine the association between low birth-weight for gestation and depressive symptoms in children and adolescents and to examine whether the relationship is moderated by genetic risk for depression . An epidemiological , genetically sensitive design was used including 2,046 twins aged 8 -- 17 years -LRB- 1,023 families -RRB- . Data were obtained by parental report and analysed using regression analysis . A small but significant association between birth-weight for gestation and early depressive symptoms was observed . The unit increase in depressive symptoms per unit decrease in birth-weight for gestation was greater for individuals at genetic or familial risk for depression . For low birth-weight children , genetic risk for depression moderated the influence of birth-weight for gestation in predicting early depressive symptoms . Birth-weight for gestation is moderated by genetic and familial risk for depression in influencing early depression symptoms . These observations have clinical implications in that the impact of being small for gestational age on depressive symptoms is greater in children at familial/genetic risk although the association between birth weight and depression does not imply causality . Introduction Several cohort studies have shown associations between indexes of foetal nutrition such as pre-natal famine -LSB- 6 -RSB- and low birth-weight -LRB- LBW -RRB- with depression and related phenomena in adults -LSB- 3 , 7 , 49 -RSB- . However , the association between birth-weight for gestation and depressive symptoms in childhood has not been well examined . Instead , studies of the association between birth-weight and difficulties in childhood have focused on total behavioural problems or externalising problems -LSB- 20 , 52 , 56 -RSB- . Follow-up studies of children who were LBW at birth have reported that these children show a number of difficulties , in particular disruptive behavioural problems and reduced IQ in comparison to children who were born with normal weight at term -LSB- 4 , 20 -RSB- . Although there have been relatively few studies that have examined the prevalence of depression in LBW children , there are now a growing number of reports illustrating that LBW children also show elevated rates of depressive symptoms -LSB- 5 , 17 -RSB- . In addition , one recent nested case -- control study of adolescent depression found increased rates of depressive disorder in adolescents who were either premature or LBW -LSB- 32 -RSB- . Preliminary evidence suggests that early adversity may modify the link between birth weight and depression in adults , with one study finding a stronger association in those adults exposed to more adverse socio-economic conditions during childhood -LSB- 15 -RSB- . One other factor that may potentially modify the relationship between birth weight and depressive symptoms is familial or genetic risk for depression . Genetic factors are known to be important in the aetiology of depression -LSB- 29 , 37 -RSB- . To our knowledge , no study has examined the impact of genetic risk for depression on the association between birth-weight and depression in early life . We used a population-based twin register to first examine the association between birth-weight and depressive symptoms and then to test whether this effect was moderated by familial and genetic risk for depression . Methods Participants A total of 1,581 families , a sub-sample from a systematically ascertained , population-based register of all twin births between 1980 and 1991 , the Cardiff Study of All-Wales and North-west England Twins -LRB- CASTANET -RRB- were invited to participate . Twins on this register were identified through child health databases and the characteristics of the sample have been described in detail elsewhere -LSB- 38 , 47 -RSB- but are representative of the local population in terms of social class and ethnicity . The percentages of families from social class groups I , II , III , IV and V were 11.4 % , 29.3 % , 30.1 % , 4.9 % and 1.4 % , respectively , with the remainder classified as at-home or unemployed . These figures are in keeping with those expected from a population from Greater Manchester -LSB- 36 -RSB- . The present wave of data collection took place in 2000 including twins from the register aged less than 17 years -LRB- range 8 -- 17 -RRB- and in full-time education born in Greater Manchester . The mean age of participating twins was 11.17 -LRB- standard error = 0.068 -RRB- . Completed questionnaires were received from 1,023 families , giving an overall response rate of 65 % -LRB- 1,023 / 1,581 -RRB- . Data on birth-weight , antenatal and perinatal factors and social class had been collected 3 years previously . There were 934/1 ,545 twin pairs who took part at both assessment points -LRB- 60 % -RRB- . -LRB- Note : There were 934 pairs who took part in both waves of the study but missing computed scores for some variables meant that they were not included in regression analyses -RRB- . There were no significant differences between those individuals who had complete data available and those who did not take part at Time 2 in terms of birth weight -LRB- t = 0.545 , SE = 0.15 , P = 0.586 -RRB- or those who did not take part at time 1 in terms of depressive symptoms -LRB- t = 0.730 , SE = 0.06 , P = 0.465 -RRB- . In addition , information on emotional symptoms as assessed by parental report on the Rutter questionnaire -LRB- 40 -RRB- at Time 1 did not reveal any significant differences between those with complete data and those who did not participate at Time 2 -LRB- t = 1.114 , SE = 0.06 , P = 0.465 -RRB- . Multi-centre ethical approval was obtained . The study was described to participants and informed consent was obtained following return of the completed questionnaire package . Complete data on birth weight , gestation and depressive symptoms were available for 370 monozygotic -LRB- MZ -RRB- and 495 dizygotic -LRB- DZ -RRB- pairs . Zygosity was assigned according to parent responses to the twin similarity questionnaire , which has been found to be over 90 % accurate in distinguishing MZ and DZ twins . An algorithm based on previous work was used -LSB- 8 , 47 -RSB- . Measures Mothers of the twins reported information on antenatal and obstetric factors using a questionnaire adapted from Lewis & Murray -LSB- 27 -RSB- , which included the twins ' birth-weights , number of weeks of gestation at birth , maternal age at birth and maternal smoking during pregnancy -LRB- yes/no -RRB- . Mother reports of birth weight and gestation have been found to be very accurate in comparison to antenatal records with correlations of over 0.90 on average -LSB- 16 , 51 -RSB- . Social class information was also collected and classified according to Standard Occupational Classification -LSB- 31 -RSB- . Depression in the children and mothers was assessed 3 years later in the year 2000 . Child depressive symptoms were assessed using the Mood and Feelings Questionnaire -LRB- MFQ -RRB- -LSB- 11 -RSB- . The MFQ is a 34-item scale based on DSM-III-R symptoms of depression that is a reliable quantitative measure of depression and a useful screening questionnaire for clinical depression in children in the community -LSB- 11 , 48 -RSB- as well as in clinical populations -LSB- 57 -RSB- . Parent reports of children 's depression symptoms were used as child reports are only reliably obtained for those over the age of 11 years . The mean depression score for the sample was 9.15 -LRB- range 0 -- 60 -RRB- . Boys ' scores -LRB- mean = 8.63 ; range 0 -- 43 -RRB- were lower than those of girls -LRB- mean = 9.59 ; range = 0 -- 60 -RRB- although this difference was not significant -LRB- t = − 1.45 , SE = 0.05 , P = 0.15 -RRB- . Given that there was no significant gender difference in mean symptom counts for the sample , and no evidence for gender differences in the magnitude of the genetic influence on parent-rated depressive symptoms in a previous analysis of this sample -LSB- 38 -RSB- , the primary analyses were conducted using the combined sample rather than separately for each gender . Parents also completed the depression sub-scale of the Hospital Anxiety and Depression Scale -LRB- HADS -RRB- -LSB- 59 -RSB- about their own depression symptoms in the past week . The mean depression score for parents was 4.46 -LRB- range 0 -- 21 -RRB- . The majority of analyses were based on total symptom scores given that there are strong arguments for regarding depression as a continuous dimension of risk rather than as a categorical disorder -LRB- affected/unaffected -RRB- both in adults and in children . Firstly , studies of adults and children show that depressive symptoms behave as a continuum with no evidence of increased morbidity once clinical diagnostic criteria are met -LSB- 23 , 51 -RSB- . For example , Pickles & colleagues -LSB- 33 -RSB- found that number of depressive symptoms but not functional impairment predicted future depressive episodes . Second , sub-clinical depressive symptoms are associated with impairment -LSB- 2 , 26 -RSB- -- one of the main criteria for fulfilment of disorder . Third , sub-clinical symptoms are associated with service use and significantly increase the risk for depressive disorder in adulthood -LSB- 21 , 34 -RSB- . Moreover , it appears that a continuous measure of depression is more indicative of genetic risk in children and adolescents . Several studies have found that the aetiology of very high levels of depressive symptoms is less influenced by genetic factors than depressive symptoms across the normal range -LSB- 13 , 14 , 38 -RSB- . Thus , at least in children , symptoms of depression may give a better indicator of genetic risk than categorical diagnoses . Nonetheless , because of the suggestion of aetiological heterogeneity , depressive symptoms were analysed both as a continuous and a categorical measure in this report . Birth weight was examined both as a dimensional measure and as a category since both birth weight across the continuum and LBW have been reported to be associated with depression in adults -LSB- 7 , 15 , 32 -RSB- . Statistical analysis Data were analysed using STATA -LSB- 45 -RSB- and SPSS -LSB- 46 -RSB- . We adopted two approaches for testing the effect of birth-weight for gestation and genetic/familial risk . First , genetic regression analysis -LSB- 22 , 56 -RSB- was used to test for genetic effects and for interaction of genetic risk and birth-weight . We made use of the twin design that relies on the observation that identical -LRB- monozygotic ; MZ -RRB- twins share all of their genes in common -LRB- coefficient of relationship = 1 -RRB- , while on average , non-identical -LRB- dizygotic ; DZ twins -RRB- share only half of their genes in common -LRB- coefficient of relationship = 0.5 -RRB- . Genetic regression analysis is undertaken using standard forced entry linear regression analysis with one twin 's depression symptom scores being the dependent variable . The twin 's depression score was predicted using the formula T = B0 + B1 C+B 2 R+B 3 I+B 4 M+B 5 G where T = the twin depression score , B0 = the regression constant , C = the co-twin depression score , R = a coefficient of genetic relatedness -LRB- 0.5 for DZ twins ; 1 for MZ twins -RRB- , I is the interaction term -LRB- C * R * birth-weight corrected for gestation -RRB- , M = the main effect of birth-weight -LRB- with the length of gestation regressed out -RRB- and G = twin gender . One twin 's depression score was entered as the dependent variable , with co-twin depression , genetic relatedness and the interaction term as independent variables . Regression analyses were carried out using both continuous and categorical measures of birth-weight corrected for gestational age . Low birth-weight for gestation was classified as ≤ 10th centile since standard published cut points were not available for birth weights of twins . Next , linear regression analysis was used to test for a main effect of birth-weight on depressive symptoms . The survey commands in STATA were used to take account of clustering within twin pairs by likening the twin data to a two-stage cluster design with the twin pairs as the primary sampling unit . A robust variance matrix calculation is utilised that relaxes the assumption of independence within groups . Birth-weight was corrected for number of weeks gestation at birth by regressing out the effect of length of gestation and using the unstandardized residuals for further analysis . As boys tended to be heavier at birth than girls , and the association between birth-weight and depressive symptoms may differ by gender . The effect of sex was controlled for by including sex as a predictor variable in the regression model . A number of factors have been reported to be associated with LBW -LSB- 12 -RSB- . Information on three potential influences was available -- maternal smoking during pregnancy , social class and maternal age at birth . Social class was not associated with birth weight for gestation -LRB- b = − 4.20 , SE = 3.32 , P = 0.206 -RRB- or depressive symptoms -LRB- b = 0.147 , SE = 0.107 , P = 0.169 -RRB- in the present sample . Maternal pre-natal smoking -LRB- yes/no -RRB- was inversely associated birth weight for gestation -LRB- b = − 141.62 , SE = 18.32 , P = 0.001 -RRB- and positively associated with depressive symptoms in the offspring -LRB- b = 2.16 , SE = 0.618 , P = 0.001 -RRB- . Maternal age at birth of child was negatively associated with child depressive symptoms -LRB- b = − .143 , SE = 0.053 , P = 0.007 -RRB- and positively associated with twin birth weight -LRB- b = 6.68 , SE = 1.65 , P = 0.001 -RRB- . These three variables were entered as predictor variables in regression models in addition to child gender . The second approach to test the effects of birth-weight and genetic/familial risk was to use standard regression analysis but this time defining -LRB- 1 -RRB- genetic and -LRB- 2 -RRB- familial risk according to cut points on the depression questionnaires for -LRB- 1 -RRB- the co-twin and -LRB- 2 -RRB- the mother . Regression analysis was used to estimate the unit increase in depressive symptoms per unit decrease in birth weight for those individuals at genetic risk or family risk of depression and those not at risk . Both familial risk and genetic risk for depression was used for this analysis because to estimate the unit increase in symptoms by genetic risk meant restricting the analysis to MZ twins and thus a substantial reduction in sample size . Using familial risk allowed results to be replicated using the much larger full sample . Furthermore , using mother 's depression to index familial risk rather than the DZ twins allowed the entire sample to be double entered i.e. each twin to be entered as an individual in the analysis . This is because maternal depressive symptoms is a variable that is obligatory shared for each member of a twin pair . Appropriate correction for the non-independence of twins was undertaken using the survey commands in STATA as described above . For genetic risk , birth-weight and gestation were entered as independent variables to predict MZ twin depressive symptoms for MZ twins individuals without an affected co-twin -LRB- MZ co-twin depressive symptoms < 90th centile -RRB- and those with an affected co-twin -LRB- MZ co-twin depressive symptoms ≥ 90th centile -RRB- . This analysis was then repeated for the whole sample using parent depression symptoms as the cut point -LRB- parental depression score ≥ 90th centile -RRB- as a measure of familial risk . Dummy coded groups -LSB- 9 -RSB- were then analysed to assess whether there was an interaction between genetic or familial risk for depression and birth weight in predicting early depressive symptoms . These dummy variables allow the difference between the beta coefficients for the low-risk and high-risk groups to be tested . Results Descriptives Parent-rated MZ mean depression symptoms were lower than those of DZ twins but this was not significant -LRB- MZ mean = 8.97 , standard deviation = 9.49 ; DZ mean = 9.14 , standard deviation = 8.92 ; t = 0.980 , df = 967 , P = 0.327 -RRB- . There were no significant differences on the ante-natal and labour complications assessed according to zygosity -LRB- admission to hospital for high blood pressure χ2 = 0.328 , P = 0.609 , vaginal bleeding χ2 = 0.088 , P = 0.800 , labour less than 3 h χ2 = 1.035 , P = 0.345 , emergency Caesarean , χ2 = 2.270 , P = 0.151 , maternal smoking during pregnancy , χ2 = 0.192 , P = 0.697 , forceps or ventouse delivery ? χ2 = 1.398 , P = 0.237 -RRB- . Descriptive statistics for the birth-weight and weeks gestation of twins are shown in Table 1 . It can be seen that second-born twins were lighter at birth than first-born twins . MZ twins were lighter than DZ twins although they also tended to be born earlier in pregnancy . The average birth-weight for the entire sample was 2469.81 g -LRB- standard deviation = 553.38 -RRB- and the average length of gestation was 36.36 weeks -LRB- standard deviation = 2.87 -RRB- . Table 1Birth-weight in grams and gestation in weeks by zygosity , gender and birth order for twins with complete data pointsNMeanStandard deviationFirst-born twin birth-weight8892484.55544 .03 Second-born twin birth-weight8892457.62562 .17 MZ first-born birth-weight3812404.32531 .55 MZ second-born birth-weight3812392.41545 .44 DZ first-born birth-weight5082544.65546 .01 DZ second-born birth-weight5082506.10570 .11 Girl first-born birth-weight4892445.43544 .59 Girl second-born birth-weight4892426.00560 .75 Boy first-born birth-weight4002532.18540 .06 Boy second-born birth-weight4002494.76562 .45 MZ duration of gestation -LRB- weeks -RRB- 37136.443.00 DZ duration of gestation -LRB- weeks -RRB- 49735.992.75 Girls weeks gestation48336 .312.87 Boys weeks gestation38536 .182.87 Main effect of birth-weight for gestation -- standard regression analysis Linear regression showed that birth-weight for gestation significantly predicted parent-rated child depression symptoms when controlling for child gender -LRB- b = − 0.001 , SE = 0.001 , P = 0.003 , 95 % CI − 0.003 , − 0.0006 -RRB- -LRB- n = 1,740 -RRB- . This remained significant when child gender , maternal age at birth , pre-natal smoking and social class were also included in the regression model -LRB- b = − 0.001 , SE = 0.001 , P = 0.015 , 95 % CI = − 0.003 , − 0.0003 -RRB- . This illustrates that children who were small for gestation had higher depressive symptoms in childhood and adolescence . Genetic regression analysis The results of genetic regression analyses with depression as a continuous variable are shown in Table 2 . It can be seen from Table 2 that birth-weight for gestation , genetic risk and maternal smoking during pregnancy showed main effects on depressive symptoms . When birth-weight for gestation was included as a continuous variable there was no birth-weight by genetic risk interaction effect although there was a slight trend -LRB- β = − 0.048 , P = 0.096 -RRB- -LRB- n = 861 -RRB- . Data were also analysed using LBW as a categorical variable . Significant main effects of birth-weight for gestation , genetic risk , pre-natal smoking and a significant genetic risk by LBW interaction were found -LRB- β = 0.394 , P = 0.001 -RRB- -LRB- n = 861 -RRB- . This relationship is illustrated graphically in Fig. 1 and shows a stronger relationship between genetic risk -LRB- C * R -RRB- and depressive symtpoms for those individuals who were small for gestational age at birth -LRB- ≤ 10th centile -RRB- . This suggests that it is LBW for gestational age that interacts with genetic risk for depression when depression is assessed as a continuous variable . Table 2Genetic risk for depression and birth-weightBeta -LRB- birth-weight as a continuous variable -RRB- P valueBeta -LRB- low birth-weight for gestation as a categorical variable -RRB- P valueInteraction between birth-weight corrected for gestation & genetic risk − 0.048 a0 .0960.394 * 0.001 Birth-weight for gestation − 0.081 * 0.006 − 0.075 * 0.032Co-twin depressive symptoms0 .541 * 0.001 0.212 * 0.002 Twin gender0 .044 a0 .1300.049 a0 .080 Zygosity0 .0270.349 − 0.096 * 0.010 Maternal pre-natal smoking -LRB- yes/no -RRB- 0.063 * 0.0330.067 * 0.021 Social class0 .0110.7050.0110.700 Maternal age at birth − 0.0240.411 − 0.0180.529 aP < 0.1 * P < 0.05 Fig. 1Genetic risk and depressive symptoms by birth-weight for gestation Analyses of depression as a categorical variable -- standard regression analysis When twins were classified at genetic risk of depression if they had an affected MZ co-twin , the coefficients derived showed that for those twins at genetic risk for depression -LRB- N = 32 -RRB- , for each 1 kg decrease in birth weight corrected for gestation , gender , social class , maternal age at birth and pre-natal smoking there was an increase of 2 depressive symptoms . As birth weight was measured in grams , this was calculated by the regression coefficent multiplied by 1000 -LRB- − 0.002 × 1,000 = − 2 -RRB- . For those identical twins -LRB- N = 338 -RRB- not at genetic risk , the increase in depressive symptoms for each 1 kg decrease in birth weight was 1 symptom -LRB- − 0.001 × 1,000 = − 1 -RRB- . Thus , there was a two fold increase in the number of depressive symptoms for each 1 kg decrease in birth-weight for twins at genetic risk -LRB- 2 vs. 1 symptom -RRB- when controlling for covariates . Similarly , for each decrease in birth-weight of 1 kg there was an increase of 7 depressive symptoms for those at familial risk of depression -LRB- N = 196 -RRB- -LRB- − 0.007 × 1,000 = − 7 -RRB- and an increase of 1 depressive symptoms for those not at familial risk of depression -LRB- N = 1478 -RRB- -LRB- − 0.001 × 1,000 = − 1 -RRB- representing a seven-fold increase in number of symptoms . Regression with dummy coded variables showed that the effect of birth-weight on depressive symptoms was not significantly different for those at high genetic risk of depression compared to those not at genetic risk of depression -LRB- for interaction term , β = 0.009 , P = 0.853 -RRB- . It should be noted that regression with dummy coded variables for genetic risk of depression required restriction to MZ twins only and thus a substantial reduction in sample size . There was , however , a significant interaction according to familial risk -LRB- β = − 0.086 , t = − 2.381 , P = 0.017 -RRB- . Discussion Depressive symptoms in young people show strong similarities with depression in adulthood -LSB- 18 , 19 -RSB- and are associated with a number of deleterious health outcomes including increased risk for depressive disorder in adulthood ; impaired educational and social functioning ; increased service use and deliberate self-harm -LSB- 2 , 18 , 21 , 26 , 34 -RSB- . We find that genetic risk interacts with LBW for gestation in influencing depression . Standard regression analysis treating birth-weight for gestation as a continuous variable also showed that familial risk but not genetic risk interacts with birth-weight . These results suggest that being at genetic or familial risk for depression increases the influence that being small for gestational age has on depression . This result suggests that there may be public health implications for the future mental health of infants who are small for gestational age if there is also a family history of depression . Results from genetic and standard regression analysis showed broadly similar results . However , results from genetic regression analysis suggested that LBW for gestation has the strongest effect on depressive symptoms in the context of genetic risk , rather than birth-weight for gestation across the continuum . It is possible that defining genetic risk according to cut points on the depression questionnaire may not be as robust an approach as examining depression as a continuum . Many studies of childhood depressive symptoms have reported estimates of genetic aetiology substantially lower for high depression scores than for scores within the normal range -LSB- 13 , 14 , 38 -RSB- . The results of studies reviewed earlier which suggest that depression may be viewed as a continuum -LSB- 2 , 21 , 22 , 26 , 33 , 34 , 51 -RSB- suggest that in the present study , results from analyses where depression is included as a continuous variable may therefore be more robust . It is unclear whether birth-weight is a ` causal ' risk factor for depression in children and adolescents , although some studies suggest that LBW is an important environmental risk factor for behavioural and cognitive problems -LSB- 25 , 52 , 56 -RSB- . However , the purpose of this paper was not to assess causality , but rather , to examine the association between birth-weight and depression and whether it was modified by genetic and familial risk for depression . Birth-weight has several properties that make it a useful risk factor for examining potential gene-environment interaction effects -LSB- 25 , 42 -RSB- . First , birth-weight is primarily influenced by environmental rather than genetic factors . For example , in this sample , examination of the MZ and DZ correlations for birth-weight showed that birth-weight was influenced primarily by shared environmental rather than genetic factors as the MZ and DZ correlation coefficients are similar -LRB- rMZ = 0.781 ; rDZ = 0.697 -RRB- -LRB- full model fitting results available from first author -RRB- . Moreover , there was little evidence that there were common genes influencing both depressive symptoms and LBW as the cross-twin cross-trait correlations in this sample were near zero for both MZ and DZ twins . This is not true of other risk variables , indeed , there is consistent evidence that many important environmental risk factors -LRB- e.g. smoking in pregnancy -RRB- are not independent of genetic predisposition -LSB- 42 -RSB- . As many risk factors or indicators are influenced by genetic factors this can cause difficulty in detecting and interpreting gene by environment interactions -LSB- 41 , 44 -RSB- . Second , LBW for gestation does not appear to be associated with maternal depression during pregnancy in developed countries -LSB- 1 , 35 , 43 , 58 -RSB- . Indeed , there was no association between current maternal depressive symptoms and birth-weight corrected for gestation in this sample -LRB- rtwin 1 birth-weight = 0.021 , P = 0.540 ; rtwin 2 birth-weight = 0.001 , P = 0.975 -RRB- . This observation reduces the possibility that the influence of birth-weight on depressive symptoms observed in the present study is due to an association with maternal depression although it does not rule out the possibility . Birth weight is influenced by a number of psychosocial and maternal health characteristics including social class , pre-natal smoking , maternal height , weight , age and parity . There were three such factors that have previously been found to influence birth weight , for which data were available in this study -LRB- social class , pre-natal smoking , maternal age at birth of child -RRB- . These were included as predictor variables in regression models in addition to child gender , thus effects for birth weight adjusted for gestation in the present study are independent of these variables although we were not able to control for all variables that have previously been associated with birth weight -LRB- e.g. maternal weight at birth -RRB- . In the present study , depression was assessed according to current symptoms . It is likely that this will underestimate the genetic risk for depression as life time ever rates of depression are significantly higher than point prevalence estimates -LSB- 10 , 24 , 39 -RSB- . We also relied on symptoms rather than diagnoses of depression . However , there is compelling evidence that depression appears as a continuum . Moreover , in particular for tests of interaction , statistical power is low -LSB- 9 , 42 -RSB- and thus power is substantially increased with the inclusion of continuous rather than categorical measures . The reliance upon parental reports of birth-weight and antenatal risk factors in the present study is not ideal -- information from antenatal records would have been preferable . However , the retrospective recollection of birth-weight of children by parents has been found to be accurate in comparison to medical records with correlations of over 0.90 between the two data sources reported -LSB- 16 , 54 -RSB- . In addition , retrospective recall of pregnancy related events has been shown to be reliable -LSB- 50 -RSB- . The reliance on parental reports of the twins ' emotional state may have influenced results . Maternal reports of child psychopathology have been reported to be influenced by the mother 's own mental state . For the most part , it has been found that this results in inflated levels of emotional problems in children being reported by mothers who have emotional difficulties themselves . This is consistent with evidence that depression runs in families , but also raises the possibility that familial risk for children may be partly attributable to rater effects . However , there is some evidence that depressed mothers can be more sensitive to depression in their children -LSB- 55 -RSB- . In addition , maternal reports of anxiety and depression are predictive of outcome in young adulthood , which lends some predictive validity to maternal reports of emotional problems in children -LSB- 53 -RSB- . Assortative mating has been reported for depression , though reported spousal correlations for depression have been relatively small -LSB- 28 -RSB- . Information on the father 's mental state was not available in this study . Assortative mating for depression would result in an inflated DZ twin correlation and thus reduced evidence for genetic influences -LSB- 30 -RSB- and we have previously found a genetic influence for depressive symptoms in this sample -LSB- 38 -RSB- . One final potential criticism is that birth-weight in twins may not mean the same as in singletons . However , the twin design was necessary to allow for the effects of genetic influences and until susceptibility genes for depression are identified , molecular genetic indicators of risk for depression are not feasible . In summary , the present results suggest that LBW for gestation and genetic/familial factors co-act and interact in influencing early parent-rated depressive symptoms . These observations suggest that it may be useful to monitor children in cases where there is a family history of depression and the child was small for gestational age .

O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O B O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O B O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O B O O O O O O B O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O B O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O B O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O B O O B O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O B O O O 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B O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O B O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O B O O O O O O

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