Phillips, A.C., Carroll, D., Evans, P., Bosch, J.A., Clow, A., Hucklebridge, F., & Der, G. (2006)....

Post-print, not final published version. Cite this article as:Phillips, A.C., Carroll, D., Evans, P., Bosch, J.A., Clow, A.,Hucklebridge, F., & Der, G. (2006). Stressful life events areassociated with low secretion rates of immunoglobulin A in saliva in the middle-aged and elderly, Brain, Behavior and Immunity, 20, 191-197.* http://dx.doi.org/10.1016/j.bbi.2005.06.006 IF 4.91

Stressful Life Events Are Associated with Low Secretion Rates

of Immunoglobulin A in Saliva in the Middle-Aged and Elderly

Anna C. Phillips1, Douglas Carroll1, Phil Evans2, Jos A. Bosch1,

Angela Clow2, Frank Hucklebridge2, and Geoff Der3

1School of Sport and Exercise Sciences, University of

Birmingham, Birmingham, England2Psychophysiology and Stress Research Group, University of

Westminster, London, England3MRC Social and Public Health Sciences Unit, University of

Glasgow, Glasgow, Scotland

Correspondence: Anna C. Phillips, MSc, School of Sport and

Exercise Sciences, University of Birmingham, Birmingham,

England. Tel 00 44 121 414 7240; Fax 00 44 121 414 4121;

email carrolld@bham.ac.uk

Abstract

Whether chronic stress experience is related to down-

regulation of secretory immunoglobulin A (S-IgA) was tested in

two substantial cohorts, one middle-aged (N = 640) and one

elderly (N = 582), comprising similar numbers of men (N = 556)

and women (N = 666) and manual (N = 606) and non-manual (N =

602) workers. Participants indicated from a list of major

stressful life events up to six they had experienced in the

previous two years. They also rated how disruptive and

stressful the events were, at the time and now, as well as

their perceived seriousness; the products of these impact

values and event frequency were adopted as measures of stress

load. From unstimulated 2-minute saliva samples, saliva

volume and S-IgA concentration were measured, and S-IgA

secretion rate determined as their product. There was a

negative association between the stress load measures and S-

IgA secretion rate, still evident following adjustment for

such variables as smoking and saliva volume. The associations

also withstood adjustment for sex, cohort, and household

occupational status. Although these associations are small in

terms of the amount of variance explained, they nonetheless

suggest that chronic stress experience either decreases IgA

production by the local plasma cells or reduces the efficiency

with which S-IgA is transported from the glandular

interstitium into saliva. Given the importance of S-IgA in

immune defence at mucosal surfaces and the frequency with

which infections are initiated at these surfaces, S-IgA down-

regulation could be a means by which chronic stress increases

susceptibility to upper respiratory tract infection.

Keywords: Life events stress; secretory immunoglobulin A;

saliva volume; smoking; age; sex; household occupational

status.

1. Introduction

There is now convincing evidence linking measures of

chronic psychological stress, most noticeably the experience

of stressful life events, to upper respiratory tract infection

and disease (see, e.g., Cohen, Tyrell & Smith, 1991; 1993).

Up to 95% of all infections are initiated at the mucosal

surfaces (Bosch, Ring, de Geus, Veerman & Amerongen, 2002).

These surfaces are protected by the secretion of various

proteins from the exocrine glands, including the salivary

glands. Prominent among such secretory proteins are

immunoglobulins, the most predominant of which is secretory

immunoglobulin A (S-IgA) (Hood, Weissman & Wood, 1978).

Accordingly, S-IgA may be an important mediator in the link

between chronic stress and upper respiratory tract infection.

There is now fairly convincing evidence that acute

psychological stress whether naturalistic or contrived in the

laboratory is associated with increases in S-IgA concentration

and/or secretion rate (e.g., (Bosch, de Geus, Kelder, Veerman,

Hoogstraten & Amerongen, 2001; Carroll, Ring, Shrimpton,

Evans, Willemsen & Hucklebridge, 1996; Kugler, Reintjes, Tewes

& Schedlowski, 1996; Ring, Drayson, Walkey, Dale & Carroll,

2002; Willemsen, Ring, Carroll, Evans, Clow & Hucklebridge,

1998; Willemsen, Ring, McKeever & Carroll, 2000; Zeier,

Brauchli & Joller-Jemelka, 1996). Further, the inconsistent

findings from the numerous studies of examination stress

become well reconciled to the model above when the distinction

is drawn on temporal grounds between test or examination

stress - the acute stress of an imminent or ongoing

examination, and academic stress - more chronic exposure to an

extended examination period (Bosch, de Geus, Ring, Nieuw

Amerongen & Stowell, 2004; Bosch et al., 2002). All six

studies of the former report increases in S-IgA concentration

or secretion rate (Bosch, Brand, Ligtenberg, Bermond,

Hoogstraten & Nieuw Amerongen, 1998; Bristow, Hucklebridge,

Clow & Evans, 1997; Evans, Bristow, Hucklebridge, Clow & Pang,

1994; Huwe, Hennig & Netter, 1998; McClelland, Ross & Patel,

1985; Spangler, 1997). In sharp contrast, of the seven

studies that have investigated the latter, five (Deinzer and

Schuller, 1998; Jemmott, Borysenko, Borysenko, McClelland,

Chapman, Meyer & Benson, 1983; Jemmott and Magloire, 1988; Li,

Ziu, Qian & Tang, 1997; Mouton, Fillion, Tawadros & Tessier,

1989) have found decreases in S-IgA.

Academic stress aside, the rest of the evidence

linking chronic stress and S-IgA down regulation is less than

compelling. Most of the studies have examined minor events or

daily hassles in small samples of students or female nurses.

Of the six studies that have been published to date, only

three report negative associations between hassle frequency or

change in frequency and S-IgA concentration or secretion rate.

The problems with these studies have been enumerated elsewhere

(Bosch et al., 2002). Aside from modest sample size, some

have used instruments for measuring stress that have little

psychometric pedigree and all failed to control for health

behaviours, particularly smoking, now known to be related to

both S-IgA (Evans, Der, Ford, Hucklebridge, Hunt & Lambert,

2000) and chronic stress (Heslop, Davey Smith, Carroll,

Macleod, Hyland & Hart, 2001). Thus, although the balance of

evidence tends to favour the hypothesis that chronic stress

exposures down-regulate S-IgA, numerous methodological

problems counsel caution.

Data from the West of Scotland Twenty-07 Study

on a large adult community sample, in which both S-IgA ((Evans

et al., 2000) and major life events were measured, permitted a

more convincing test of the hypothesis that chronic stress

experience is related to down-regulation of S-IgA. In

addition, any putative associations between stress and S-IgA

could be adjusted for smoking, as well as for age, sex, and

household occupational status.

2. Method

2.1. Participants

Data are derived from the middle and eldest of the three

age cohorts of the West of Scotland Twenty-07 Study.

Individuals were all from the Glasgow area and have been

followed up at regular intervals since the baseline survey in

1987 (Ford, Ecob, Hunt, Macintyre & West, 1994). Members of

the middle cohort were all around 44 years old and members of

the older cohort were all around 63 years old at the third

follow-up when data on life events were collected and a saliva

sample taken. The optimum sample size was 1477. However,

missing data and improperly collected saliva reduced the

sample with full data to 1222, comprising 640 from the middle

cohort and 582 from the eldest cohort. The mean age of the

middle cohort was 44.6 (SD = 0.84) years and 63.6 (SD = 0.61)

years for the eldest cohort. Overall, there were 556 (45%)

men and 666 (55%) women, and 606 (50%) of the participants

came from manual and 602 (50%) from non-manual occupational

households. The sex ratios for the two cohorts were virtually

identical: 285 (45%) men and 355 (55%) women for the middle

cohort and 271 (47%) men and 311 (53%) women for the older

cohort. However, the distribution of participants from

manual and non-manual occupational households differed

significantly between cohorts (χ2 (1) = 21.81, p < 001); in the

middle cohort, 275 (44%) came from manual and 354 (56%) from

non-manual occupational households, whereas for the elder

cohort the figures were 331 (43%) and 248 (57%), respectively.

2.2 Apparatus and procedure

Participants were tested in a quiet room in their own

homes by trained nurses. Demographic information was obtained

by interview. Household socioeconomic position was classified

as manual and non-manual from the occupational status of the

head of household, using the Registrar General’s (1980)

classification system of occupations. Head of household was

either the participant or his/her partner, depending on which

of the two held or had held the highest status occupation.

Major life events over the past two years and their

initial and current impact were assessed by presenting

participants with eight cards each of which listed a number of

major life events in one particular domain. The domains were

as follows: health (e.g. serious illness diagnosed), marriage

(e.g. living apart or divorce), relationships (e.g. serious

disagreement within family), deaths (e.g. spouse died), work

(e.g. unemployment), housing (e.g. problem with landlord),

finance (e.g. problems paying bills), and general (e.g.

burglary or theft). Participants were asked to indicate up to

six events which had happened either to them or to someone

they cared about. The present analyses focussed on those

events that had happened directly to the participant.

Following identification of the events, participants were

asked to specify, for each event, how much the event disrupted

or changed their life and how stressful it was at the time of

occurrence, as well as how disruptive and stressful it was

now. All of these responses were scored on a 5-point scale,

where 1 = a very great deal and 5 = not at all; for the

analyses, the values were reversed so that the greater the

impact the higher the score. In addition, participants were

asked for each event to indicate how serious the event was on

a 10-point scale, where 1 = ‘something really small and

unimportant’ and 10 = ‘the worst thing that could happen to

you’. The present assessment method is based on the well-

established Life Events and Difficulties Schedule (Brown and

Harris, 1989) and included the same domains of personal

experience. As concern lay with the overall stress load on

participants, four measures were derived from the sums of the

product of each life event experienced and its disruptiveness

and stressfulness, both at the time of its occurrence and now.

In addition, a similar measure was derived from the number of

events times their rated seriousness.

Smoking behaviour was determined by responses to the

question, ‘Do you ever smoke tobacco now? I am thinking of a

pipe, cigars and your own roll ups as well as cigarettes you

might buy.’ If the answer was ‘No’, participants were asked,

‘Did you ever used to smoke any kind of tobacco?’ On this

basis, participants were characterised as ‘never smokers’, ex

smokers’, or ‘current smokers’.

Saliva samples were taken at the end of the interview,

using standard salivettes (Sarstedt Ltd, Leicester, UK).

Participants were instructed to swallow hard to dry out the

mouth and then immediately to place the swab under the tongue.

They were asked to hold the swab as still as possible for 2

minutes, timed precisely by the nurse interviewers using

portable digital timers. After exactly 2 minutes,

participants removed the swab, returning it to the salivette

case. It should be conceded that the use of absorbent cotton

materials to collect saliva has been observed to produce lower

S-IgA concentrations (Shirtcliff, Granger, Schwartz & Curran,

2001); however, it is reasonable to consider that any such

reduction would be a constant error. All samples were frozen

within 2 hours of collection and remained frozen at -20

degrees C until assay. Samples were dispatched from Glasgow

to London by air for assay in four batches and recovered after

thawing by centrifugation at 1000g for 10 minutes. Double

antibody sandwich ELISA, described in detail elsewhere

(Carroll et al., 1996), was used to determine S-IgA

concentration. Intra-assay % coefficient of variation was 3.8

and inter-assay % coefficient of variation was 7.6. Prior to

assay, saliva volume was determined gravimetrically. Saliva

sample collection and volume determination for S-IgA analysis

conformed to a procedure described previously (Zeier et al.,

1996). The focus of analysis was S-IgA secretion rates

(μg/2min), which were calculated as the product of saliva

volume (ml) and S-IgA concentration (μg/ml). Given the

distribution of S-IgA secretion rate values in this sample

(Evans et al., 2000), a natural log transformation was applied

prior to statistical analyses.

2.3 Data analyses

Analysis was undertaken using SPSS version 12.

ANOVA was used to compare life events scores between cohorts,

sexes, household occupational groups, and smoking status

groups. Eta-squared (η2) was derived as the ratio of the

independent variable sums of squares and the total sums of

squares, and used as an indicator of effect size. Similar

analyses were applied to the log n transformed S-IgA secretion

rate values. To test the main hypothesis, linear regression

was conducted, with log n transformed S-IgA secretion rate

values as the dependent variable. Initially, simple linear

regression was used to establish whether there were

indications of an association between stressful life events

exposure and secretion rate. In subsequent hierarchical

regression analyses, assay batch, saliva volume, and smoking

behaviour were entered at step 1. Since the batch variable

reflected inter-assay variation, it could be a potential

confounder. Adjustment for saliva volume would help establish

whether any associations between S-IgA secretion rates and

stressful life events exposure were driven by variations in

saliva volume or reflected a link with actual variations in S-

IgA production and/or transport (Willemsen et al., 1998). The

importance of controlling for smoking behaviour when examining

possible relationships between psychosocial variables and S-

IgA has already been demonstrated (Evans et al., 2000). In

these analyses, the life events measures were entered at step

2. In subsequent analyses, batch, smoking, and saliva volume

were again entered at step 1, with possible moderating

variables, sex, age cohort, and household occupational status,

entered at step 2, and the life events variables being

relegated to step 3. The main results of these regressions

are presented in Tables.

3. Results

3.1 Life Events

The median number of major stressful life events

happening to the participants over the last two years was 1

(interquartile range = 2). Although very few events were

experienced, they were clearly regarded as serious; the

average seriousness score was 7.12 (SD = 9.21) on a scale of

1-10. With regard to the stress load, the mean total

disruption scores at the time of the event and now were 3.65

(SD = 4.85) and 2.52 (SD = 3.61) respectively, and the mean

total stressfulness scores then and now were 4.10 (SD = 5.22)

and 2.53 (SD = 3.62).

The middle cohort identified more stressful life

events than the elder cohort, F (1,1220) = 8.81, p = .003, η2 =

.007, and their total stress load at the time of exposure was

higher, in terms of disruption, F (1,1220) = 7.79, p = .005, η2

= .006, stress, F (1,1220) = 8.75, p = .003, η2 = .007, and

seriousness, F (1,1220) = 4.89, p = .03, η2 = .004. Men and

women did not differ in the number of events exposed to or in

terms of the total contemporary and present stress load

arising from such exposures, nor did manual and non-manual

occupational household groups. The summary data are

presented in Table 1.

There were 420 (34%) current smokers in the sample,

330 (27%) ex smokers, and 472 (39%) never smokers. The life

events data for smokers, ex smokers, and never smokers are

presented in Table 2. Smokers had been exposed to more life

events than current non smokers, F (2,1219) = 5.21, p = .006,

η2 = .008, rated them as more serious, F (2,1219) = 7.73, p

< .001, η2 = .013, , experienced more disruption then, F

(2,1219) = 5.99, p = .003, η2 = .010, and now, F (2,1219) =

5.24, p = .005, η2 = .009, and experienced more stress at the

time, F (2,1219) = 5.78, p = .003, η2 = .009, and now, F

(2,1219) = 3.40, p = .03, η2 = .006.

3.2 Secretory Immunoglobulin A

Logn S-IgA secretion rates were significantly higher in

the middle than the older cohort, F (1,1220) = 12.04, p = .001,

η2 = .010; this would appear to be driven largely by cohort

differences in saliva volume, F (1,1220) = 23.82, p < .001, η2

= .019. Men had higher logn S-IgA secretion rates than women,

F (1,1220) = 18.45, p < .001, η2 = .015, again with

significantly higher saliva volumes, F (1,1220) = 6.27, p

= .01, η2 = .005. Non-manual occupational household groups had

higher secretion rates than manual occupational household

groups, F (1,1206) = 5.38, p = .02, η2 = .004, which again

appeared to be driven by differences in saliva volume, F

(1,1206) = 6.21, p = .01, η2 = .005. The summary data are

presented in Table 3. Finally, logn S-IgA secretion rates were

attenuated, F (2,1219) = 8.73, p < .001, η2 = .014, in current

smokers (M = 3.32, SD = 1.70) compared to ex smokers (M =

3.61, SD = 1.55) and never smokers (M = 3.62, SD = 1.46), and

assay batch also affected logn S-IgA secretion rate, F (3,1218)

= 10.81, p <.001, η2 = .026, with higher values being recorded

for the earlier batches. Finally, as would be expected, logn

S-IgA secretion rate and logn S-IgA concentration, r(1220)

= .66, p < .001, and logn S-IgA secretion rate and saliva

volume, r(1220) = .68, p < .001, were strongly correlated. The

positive correlation between logn S-IgA concentration and

saliva volume was more modest, but still statistically

significant, r(1220) = .07, p = .01.

[Insert Tables 1, 2, and 3 about here]

3.3 Life events and Secretory Immunoglobulin A Secretion Rate

Simple linear regression revealed statistically

significant negative associations between the five stressful

life events variables and log n S-IgA secretion rate: for

disruption then, β = -.06, t = 1.99, p = .05, R2 = .003; stress

then, β = -.06, t = 2.24, p = .03, R2 = .004; disruption now, β =

-.06, t = 2.17, p = .03, R2 = .004; stress now, β = -.06, t =

2.14, p = .03, R2 = .004; and seriousness, β = -.07, t = 2.30, p

= .02, R2 = .004.

In multiple hierarchical regressions models in

which assay batch, saliva volume, and smoking was entered at

step 1 and the life events variables at step 2, the negative

associations between stressful life events experience and S-

IgA secretion rate were attenuated, but all bar one remained

statistically significant. As might be expected from the

analyses above, the step 1 variables were all significantly

associated with log n S-IgA secretion rate: for batch, β =

-.14, t = 6.78, p < .001; for saliva volume, β = .67, t =

32.87, p < .001; for smoking β = -.09, t = 4.13, p <.001. The

step 1 model, incorporating all three variables accounted for

almost half the variance in log n S-IgA secretion rate, ΔR2

= .487. The associations between log n S-IgA secretion rate

and the life events variables emerging at step 2 in these

models are summarised in Table 4. Although for the most part,

remaining statistically significant, it is important to note

that the residual associations like the original bivariate

associations are small in terms of the amount of variance they

explain. In the next set of multiple hierarchical regression

models, batch, saliva volume and smoking were entered at step

1. In these models, though, the major demographic variables,

age cohort, sex, and household occupational status, were

entered at step 2, with the life events variables entered at

step 3. Only sex emerged from step 2 entry as a significant

predictor of log n S-IgA secretion rate, β = -.10, t = 3.70, p

< .001. The full step 2 model accounted for around %1, ΔR2

= .012, of additional variance in log n S-IgA secretion rate.

The associations between log n S-IgA secretion rate and the

life events variables emerging at step 3 in these models are

also summarised in Table 4; the associations are virtually

unchanged from those that emerged from the previous two-step

hierarchical models.

[Insert Table 4 about here]

4. Discussion

The present analyses testify to a negative association

between the experience of stressful life events and S-IgA

secretion rate. As such, they support the contention (Bosch

et al., 2002) that in contrast to the S-IgA enhancing effects

of acute psychological stress (Bosch et al., 2001; Carroll et

al., 1996; Kugler et al., 1996; Ring et al., 2002; Willemsen

et al., 1998; Willemsen et al., 2000; Zeier et al., 1996),

chronic stress might effect a down-regulation of S-IgA. Aside

from the evidence from the specific chronic exposure of

academic stress (Bosch et al., 2002), support for down-

regulation has largely relied on studies reporting a negative

relationship between S-IgA and university students’ experience

of daily hassles and fairly minor irritants (Evans, Bristow,

Hucklebridge, Clow & Walters, 1993; Farne, Boni, Corallo,

Gnugnoli & Sacco, 1992; Martin and Dobbin, 1988). To our

knowledge, the present study is the first to show that the

experience of serious and major life events over a protracted

period in substantial cohorts of middle aged and elderly men

and women is negatively related to S-IgA secretion rates. In

addition, it is clear from these analyses that these

associations embrace impact both currently and at the time of

exposure.

The importance of controlling for smoking

behaviour in this context has been emphasised elsewhere (Bosch

et al., 2002; Evans et al., 2000). In the present sample,

current smokers had lower S-IgA secretion rates than ex

smokers and never smokers. Smoking would also in turn seem to

vary with variations in psychological stress (Heslop et al.,

2001). In the present study, smokers had higher life events

scores than non smokers. Thus any relationship between

chronic stress and S-IgA may be confounded by variations in

smoking behaviour. However, the negative associations between

our life events measures and S-IgA largely withstood

adjustment for smoking, as well as for assay batch and saliva

volume. That assay batch has a substantial effect on S-IgA

secretion rate has been reported in prior aggregate analyses

of all three cohorts from this study (Evans et al., 2000).

The current analyses confirm the importance of controlling for

inter-assay variability in large scale epidemiological studies

of immune parameters.

By statistical adjustment we were able to establish

that the observed relationships between life events and S-IgA

secretion rate were not, for the most part, driven by

variations in saliva volume. This is important because it

permits us to eliminate one fairly parsimonious but less

interesting explanation that for those participants with a

high stress load the glands simply release less saliva into

mouth. The earlier analyses of all three cohorts from this

study indicated that the positive association between S-IgA

secretion rates and household occupational status were

essentially the result of lower salivary flow in the lower

household occupational status groups (Evans et al., 2000).

That this was not the case in the present analyses indicates

that life events stress either decreases IgA production by the

local plasma cells or reduces the efficiency with which S-IgA

is transported from the glandular interstitium into saliva.

The value of measuring total S-IgA levels, as opposed to

antigen-specific S-IgA, has been the subject of considerable

debate (Jemmott and McClelland, 1989; Stone, Cox,

Valdimarsdottir, Jandorf & Neale, 1987). This debate stems

from the common misconception that S-IgA is a measure of

adaptive immune responses, i.e., responses that are driven by

exposure to a previously encountered antigen. If this were

indeed the case then only the levels of S-IgA molecules that

are specifically directed against particular antigens would

matter for host protection rendering the measurement of total

S-IgA levels less meaningful. However, total S-IgA consists,

for the most part, of so-called ‘natural antibodies’ (Bos,

Cebra & Kroese, 2000). These natural antibodies have a

broader specificity to recognize many different types of

antigen, and their levels are independent of re-exposure to

specific antigens (Stoel, Jiang, van Diemen, Bun, Dammers,

Thurnheer, Kroese, Cebra & Bos, 2005). Hence, total

immunoglobulin levels are the key to monitoring this aspect of

immunity. This perspective is consistent with evidence

showing that total S-IgA levels are predictive of

susceptibility to respiratory, oral, and aural infections

(Evans, Hucklebridge, Clow & Doyle, 1995; Jemmott and

McClelland, 1989; Kuby, 1997). Thus, measuring total S-IgA

levels is an immunologically meaningful measure of mucosal

host resistance.

The present study suffers from a number of limitations.

First, although the present life events scale has a sound

pedigree and a paper using it has been published elsewhere

(Carroll, Phillips, Ring, Der & Hunt, 2005), the manner of its

administration could have imposed an arbitrary cap on the

total stress load scores derived. Participants were permitted

to select up to six life events only, rather than being free

to nominate as many events as had occurred. However,

participants on average selected only a small number of events

and only nine (1%) reported having experienced six events,

whereas 1061 (87%) reported between zero and two events, which

strongly suggests that the methodology was not unduly

constraining. Second, only one measure of S-IgA was taken, a

concern given circadian variation (Hucklebridge, Clow & Evans,

1998). However, in a large cohort study, more comprehensive

monitoring was not practicable. Further, S-IgA would appear

to reasonably stable from around three hours after wakening

(Hucklebridge et al., 1998), and early morning testing was

rare. In addition, individual differences in S-IgA has been

found to show good test-retest reliability across two to four

days (Ring et al., 2002), one to two weeks (Bosch et al.,

2001), and four weeks (Willemsen et al., 1998). Third, it

should be conceded that the associations that emerged from the

present analyses are small in terms of the amount of variance

explained. However, they are consistent and remain

significant in four out of five cases following adjustment for

assay batch, saliva volume, and smoking that account for

around half the variance in S-IgA secretion rate. Further,

they are of the same order of magnitude as the effect sizes

reported in a recent meta-analysis of life events and

immunoglobulins (Segerstrom and Miller, 2004); it would appear

that samples of the current size are needed for such

associations to achieve statistical significance.

Nevertheless, their size does raise the question as to whether

associations of this magnitude are of idiopathic clinical

significance.

. In conclusion, the experience of major life events

both at the time and now was negatively associated with S-IgA

secretion rate. This association would not appear to be

driven by variations in saliva volume. As such, a high life

stress load would seem to compromise either production or

transport. Given the prominent role of S-IgA in immune

defence at mucosal surfaces and the frequency with which

infections are initiated at these surfaces, it is plausible

that S-IgA affords a pathway by which chronic stress increases

susceptibility to upper respiratory tract infection.

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Table 1

Life Events Descriptive Statistics by Age Cohort, Sex and

Household Occupational Status

Middle Eldest Men Women Manual

manual

Number of

events

(1.37)

(1.15)*

(1.27)

(1.28)

(1.23)

(1.31)Disruption

(5.22)

(4.37)*

(4.75)

(4.93)

(4.61)

(5.03)Stressful

(5.61)

(4.71)*

(4.96)

(5.42)

(5.10)

(5.29)Disruption

(3.71)

(3.50)

(3.68)

(3.56)

(3.63)

(3.58)Stressful

(3.66)

(3.56)

(3.59)

(3.64)

(3.70)

(3.49)Seriousness 7.68

(9.82)

(8.45)*

(8.92)

(9.45)

(8.89)

(9.40)

* p < .05

Table 2

Life Events Scores according to Smoking Status

Current

Smoker Ex Smoker Never Smoker

Mean (SD) Mean (SD) Mean (SD)

Number of

events1.22 (1.34) 0.98 (1.21)

0.97 (1.24)

Disruption

then4.31 (5.11) 3.30 (4.66)

3.31 (4.68)

Stressful

then4.80 (5.52) 3.74 (5.05)

3.74 (4.99)

Disruption

now 2.97 (3.88) 2.22 (3.17)

2.31 (3.63)

Stressful now 2.90 (3.78) 2.28 (3.28) 2.38 (3.67)Seriousness 8.54

(10.04)6.43 (8.63)

6.34 (8.68)

Table 3

Salivary Descriptive Statistics by Age Cohort, Sex and

Household Occupational Status

Middle Eldest Men Women Manual

manual

Saliva volume

(0.59)

(0.52)*

(0.57)

(0.55)*

(0.55)

(0.57)*

S-IgA secretion rate (μg/2min)

102(384)

84 (162) 100(163)

88 (377) 83 (148) 105(399)

log n S-IgA secretion rate

3.63(1.49)

3.32(1.66)*

3.70(1.53)

3.31(1.60)*

3.38(1.63)

3.59(1.53)*

* p < .05

Table 4

Associations between Secretory Immunoglobulin A Secretion Rate

and Life Experience following Adjustment for Potential

Confounding Variables

Step β t ΔR2

Step 1: Assay Batch,

Saliva Volume, and SmokingStep 2: Disruption

-.04 2.10* .002

Stressful

-.04 1.99* .002

Disruption

-.04 2.04* .002

Stressful

-.04 1.76# .001

Seriousness -.04 2.02* .002

Step 2: Age Cohort, Sex,

and Household Occupational

StatusStep 3: Disruption

-.05 2.21* .002

Stressful -.04 2.03* .002

thenDisruption

-.05 2.17* .002

Stressful

-.04 1.84# .001

Seriousness -.04 2.08* .002

* p < .05# p < .08

Phillips, A.C., Carroll, D., Evans, P., Bosch, J.A., Clow, A., Hucklebridge, F., & Der, G. (2006)....

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