Interaction of Stress, Lead Burden, and Age on Cognition in Older Men: The VA Normative Aging Study

Junenette L. Peters; Marc G. Weisskopf; Avron Spiro III; Joel Schwartz; David Sparrow; Huiling Nie; Howard Hu; Robert O. Wright; Rosalind J. Wright


Environ Health Perspect. 2010;118(4):505-510. 

In This Article

Materials and Methods

Study Population

The NAS cohort is a longitudinal study on aging that was established in 1963 by the Veterans Administration (now the Department of Veterans Affairs); the subgroup of participants used in our analyses have been previously described (Cheng et al. 2001; Hu et al. 1996). Briefly, the NAS is a closed cohort of 2,280 male volunteers from the Greater Boston, Massachusetts, area. Men were screened at entry and enrolled if they had no chronic medical condition. Participants have been reevaluated every 3–5 years using questionnaires and detailed onsite physical examinations.

Cognitive testing was performed on 1,031 of the men still participating in the NAS between 1993 and 1997. Of these, 1,011 had a blood lead measure, 717 a bone lead measure, 838 a perceived stress measure, and 615 a stress appraisal measure, which is described below. Lead and questionnaire measurements were matched to the same year as the MMSE; however, if no questionnaire measurement was available for that year, the questionnaire data collected in the preceding evaluation cycle (within 3 years) were used. We used data reported up to 3 years before the MMSE test for 28 subjects. If no bone lead measure was available for the year of the participant's MMSE score, we used the closest measure, within 2 years.

The present study was approved by the Human Research Committees of Brigham and Women's Hospital and the Department of Veterans Affairs Boston Healthcare System, and written informed consent was obtained from subjects prior to participation.

Cognitive Assessment

The MMSE is a brief global examination of cognition that covers several domains including orientation to place and time, memory, attention, language, and ability to copy a design (Dufouil et al. 2000). We excluded the question on county ("What county are we in?"), as counties have little political significance in Massachusetts and are generally unknown to residents and thus of little diagnostic value. In this study, the maximum MMSE score was 29.

Stress Measures

Two measures of stress were available in the NAS. Using a health and social behavior questionnaire (Aldwin et al. 1996; Peters et al. 2007; Yancura et al. 2006), participants were asked to think of, list, and describe the most stressful thing that occurred to them in the past month. They were then asked, "Compared to other problems you might have had in the past, how stressful was this problem to you? (By stressful we mean how much it bothered or troubled you)"; participants rated this question on a 7-point scale. To facilitate the interpretability of interactive effects, the stress levels were dichotomized as low self-report of stress (≤ 5) and as high self-report of stress (> 5), as we had done in previous analyses (Peters et al. 2007). In other research, this measure was positively associated with a sense of threat and negative affect and negatively associated with a sense of challenge and positive affect supporting its construct validity (Yancura et al. 2006). In our subgroup, the measure correlated with a global distress index of the Brief Symptom Inventory (r = 0.21; p < 0.01) (Derogatis 1993) as well as with the Perceived Stress Scale (PSS) (r = 0.23; p < 0.01) (Peters et al. 2007).

The 14-item PSS (Cohen et al. 1995), a validated measure of stress appraisal, was also used to ascertain the degree to which respondents felt their lives were unpredictable, uncontrollable, and overwhelming to their coping resources in the month before the PSS was administered. Each item is scored on a 5-point scale that ranges from "never" (0) to "very often" (4); scores are obtained by summing the items. The PSS is the most widely used stress appraisal measure (Pizzagalli et al. 2007) with documented reliability and validity; it correlates with life events scores and depressive and physical symptomatology and has been shown to be a better predictor of a number of health outcomes compared with life-event measures of stress (Cohen et al. 1983, 1995). To facilitate interpretability of the interaction term, we dichotomized PSS by the median such that PSS ≤ 18 was characterized as low PSS and > 18 as high PSS; these values are consistent with prior studies (e.g., Kuiper et al. 1986; Pizzagalli et al. 2007).

Lead Measurement

Blood lead was analyzed using Zeeman background-corrected graphite furnace atomic absorption (ESA Laboratories, Chelmsford, MA, USA). The instrument was calibrated with Standard Reference Material 955a, lead in blood (National Institute of Standard and Technology, Gaithersburg, MD). Ten percent of the samples were run in duplicate, at least 10% as controls and 10% as blanks. When these samples were compared with reference samples from the Centers for Disease Control and Prevention, we found that the precision ranged from 8% for concentrations < 30 µg/dL to 1% for higher concentrations.

Bone lead was measured for 30 min each at the midtibia shaft and patella using a K-shell X-ray fluorescence instrument (ABIOMED, Inc, Danvers, MA). The tibia and patella have been used for bone lead research because they consist primarily of cortical and trabecular bone, respectively, with differing toxicity potential for each. Technical specifications and validity of this instrument are described in detail elsewhere (Burger et al. 1990; Hu et al. 1990, 1994). We excluded tibia and patella bone measures with estimated uncertainties > 10 µg/g and 15 µg/g of bone, respectively, because these measures usually reflect excessive patient movement during measurement (Hu et al. 1996).


We first assessed the relationship between each of the stress measures and the MMSE. We next considered the modifying effect of stress on age by fitting a model that included the main effects of stress and age plus an interaction term of stress times age predicting the MMSE score.

We then assessed the interactive relationship between lead and stress by testing a model that included the main effects of lead and stress plus an interaction term of lead times stress to predict MMSE score. We log-transformed the lead measures to address the influence of extreme values. We modeled the association by interquartile range (IQR) of log lead concentrations (approximately a 2-fold increase): blood lead (0.69 log units), patella lead (0.78 log units), and tibia lead (0.77 log units). We also checked our results by modeling untransformed lead values after using the extreme studentized deviation (ESD) many-outlier method to remove extreme outliers (Rosner 1983). Finally, we assessed the relationship of lead–stress combinations as modifiers of the relationship between age and MMSE score. For these analyses, we dichotomized lead measures by their median: 5 µg/dL for blood lead, 26 µg/g for patella lead, and 19 µg/g for tibia lead; and created the following four groups: high stress and high lead, high stress and low lead, low stress and high lead, and low stress and low lead. We then ran the analyses with the main effects of lead–stress groups and age and interaction terms of lead–stress group times age to predict MMSE score.

We ran the analyses using generalized linear models with SAS software (SAS Institute Inc., Cary, NC). The analyses were performed separately for the interaction of each lead measure (tibia lead, patella lead, and blood lead) and for each stress measure (self-report of stress appraisal and the PSS score). All analyses were adjusted for age (years), education (< 12 years, 12 years, 13–15 years, ≥ 16 years), smoking (never, former, current), alcohol intake (grams/day), computer experience (yes/no), and English as a first language (yes/no).


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