Type 2 diabetes mellitus (T2DM) is a disorder of glucose

Anxious Temperament and Disease Progression at Diagnosis: The Case of Type 2 Diabetes PETER A. HALL, PHD, C. PSYCH, MICHAEL J. COONS, MA, AND T. MIC...
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Anxious Temperament and Disease Progression at Diagnosis: The Case of Type 2 Diabetes PETER A. HALL, PHD, C. PSYCH, MICHAEL J. COONS, MA,



Objective: To examine the association between anxious temperament and disease progression at diagnosis for individuals with Type 2 diabetes mellitus (T2DM). Methods: A sample of 204 individuals, newly diagnosed with T2DM, completed the Behavioral Inhibition and Activation Scales (BIS/BAS) and provided an A1C reading. Regression analyses were used to predict A1C levels from individual differences in BIS and BAS. Results: Individual differences in BIS were inversely related to A1C at diagnosis in the sample as a whole, and this association remained strong after controlling for demographic variables and body mass index. Most importantly, temperamentally anxious individuals had low A1C levels at diagnosis in all age groups, in contrast to their nonanxious counterparts who showed increasing A1C at diagnosis as a function of decreasing age. BAS scores were unrelated to A1C. Conclusions: Although older age is generally associated with lower disease progression at diagnosis, high BIS individuals show uniformly lower disease progression across all age groups. High levels of temperamental anxiety may facilitate early diagnosis of T2DM, particularly among younger individuals who are not subject to routine screening. Key words: diabetes, temperament, anxiety, secondary prevention, personality. A1C ⫽ glycated hemoglobin; BAS ⫽ Behavioral Approach System; BIS ⫽ Behavioral Inhibition System; BMI ⫽ body mass index; RST ⫽ Reinforcement Sensitivity Theory; T2DM ⫽ Type 2 diabetes mellitus.

INTRODUCTION ype 2 diabetes mellitus (T2DM) is a disorder of glucose metabolism involving decreased production of insulin and/or reduced sensitivity of the body tissues to insulin. If left unmanaged, T2DM can lead to a number of serious medical complications (e.g., retinopathy, neuropathy, myocardial infarction) and eventually, death. Therefore, early detection of T2DM is imperative to prevent both morbidity and mortality (1–5). Unfortunately, signs of T2DM are difficult to detect on a subjective level because it has few obvious signs of onset. Symptoms include blurred vision, frequent urination, more frequent infections of the skin, or itchiness of the skin. These symptoms are usually mild and nonspecific; therefore, regular screening or high levels of individual vigilance are important routes to early detection (6,7). In at-risk segments of the population—particularly older adults—screening is more common because the base rate of T2DM is higher (8). Individual vigilance may be less important for early detection in older age groups for this reason. Among younger individuals, however, the situation is potentially different. Routine screening is typically not recommended for younger adults because of the relatively lower base rate of the disease and the questionable cost-effectiveness of screening in this group. As such, the likelihood of detecting the presence of T2DM is potentially more dependent on an individual’s vigilance in younger age ranges, given that primary care clinicians may be less likely to look for signs of its presence, and given that younger individuals would be likely


From the Departments of Kinesiology (P.A.H.) and Psychology (M.J.C., P.A.H.), University of Waterloo, Ontario, Canada, and the Department of Psychology and Diabetes Education Centre (T.M.V.), Queen Elizabeth II Health Sciences Centre, Halifax, NS, Canada. Address correspondence and reprint requests to Peter A. Hall, Department of Kinesiology, University of Waterloo, 200 University Avenue West, Waterloo, ON N2L 3G1, Canada. E-mail: [email protected] Received for publication June 23, 2007; revision received March 25, 2008. Funding for this study was provided by an operating grant and New Investigator Award (P.A.H.) from the Canadian Institutes of Health Research. DOI: 10.1097/PSY.0b013e31817bb8e5 Psychosomatic Medicine 70:837– 843 (2008) 0033-3174/08/7006-0837 Copyright © 2008 by the American Psychosomatic Society

to have fewer routine contacts with healthcare providers. Given the lower rate of routine screening in younger age ranges, it is possible that personality traits that predispose individuals toward symptom perception, magnification, or reporting may facilitate disease detection at an earlier stage of disease progression (9,10). Anxious temperament may be one such personality trait, and to date several studies have documented an inverse association between anxious temperament and glycated hemoglobin (A1C) (11–14). Neural Basis of Anxious Temperament To provide a theoretical framework for understanding the interplay of emotion and behavior in the context of anxious temperament, Gray and McNaughton (15,16) posited the existence of two separate motivational systems rooted in central nervous system function: the Behavioral Inhibition System (BIS) and the Behavioral Approach System (BAS). The BAS comprises a neural system that activates approach behaviors in the presence of stimuli indicating the presence of potential rewards; individuals with a strong BAS system would tend to be sensitive on a behavioral and emotional level to available rewards in the environment (i.e., impulsive in temperament). The BIS, on the other hand, comprises neural structures that control avoidance behaviors that terminate aversive emotional states; individuals with a highly active BIS system would be particularly responsive both behaviorally and emotionally to stimuli signaling the presence of potential threats in the environment (i.e., anxious in temperament). The interplay of the BAS and BIS is thought to form the basis of individual differences in personality, according to Reinforcement Sensitivity Theory (RST) (15,16), and it could be argued that either system might have important health implications for those living with diabetes. For example, the hyperresponsivity of the BAS in some individuals might leave them more sensitive to the availability of appetitive but unhealthy high fat and high sugar foods (17–19), rendering dietary regimen adherence more difficult. Likewise, it could be argued that a strong BIS may be protective to the extent that it motivates individuals to avoid feared negative consequences of unhealthy choices later in the life span (i.e., retinopathy, amputation, myocardial infarction). However, to date, few studies have explored the significance of individual 837

P. A. HALL et al. differences in BAS for diabetes, and BIS (i.e., anxious temperament) has only been explored in a few studies. Moreover, the relevance of anxiety for diabetes management has been explored less comprehensively than other forms of negative emotionality (e.g., depression, stress) and important distinctions among disease progression and glycemic control have not been consistently considered. Anxiety, Age, and Disease Progression at Diagnosis T2DM is a slowly evolving physiological process with a gradual onset, despite the use of discrete criteria for diagnosis (i.e., categorical cut-off criteria). For this reason, A1C can gradually increase over many years before a diagnosis is made. A diagnosis may not be rendered until long after glycemic control has surpassed the threshold for diagnosis; a situation that is particularly likely if the individual is not being regularly screened by his/her own volition or by a primary care clinician. Although historically very few people ⬍60 years old would have been expected to be at risk for T2DM, diagnoses among younger age groups are increasingly common (20). Many younger individuals do not know that they are at risk, and it is relatively unlikely that they will be referred for screening unless they initiate it themselves. As such, screening—and resultant diagnosis—is less likely to occur in younger adults unless they are sensitive to subtle cues of disease onset and initiate contact with a primary healthcare provider. Although there is increasing awareness of importance of diagnosing preclinical states associated with diabetes (e.g., impaired glucose tolerance, metabolic syndrome), screening is likely to be applied selectively more so to older than younger adults, as they would be considered to be more at-risk relatively speaking. There is considerable variability in disease progression at diagnosis for T2DM, and this has implications for management. The earlier that diabetes is diagnosed, the earlier that self-management efforts can begin to bring blood glucose under control and thereby offset the risk of early diseaserelated complications (8). As such, earlier diagnosis of T2DM is better than later diagnosis, all other factors being equal. However, little is known about what factors predispose individuals to superior (i.e., earlier) disease detection. Given the apparent significance of dispositional anxiety in disease management, we hypothesized that it may also facilitate initial disease detection. Further, given the lack of routine screening in younger individuals, we hypothesize that individual differences in anxious temperament would be particularly important determinants of disease detection in younger people. Finally, based on RST, we hypothesized that anxious temperament would be positively associated with deliberativeness about contingencies for self-management behaviors (e.g., exercise, dietary behavior, glucose monitoring), especially potential negative contingencies (e.g., costs) associated with the uptake of these behaviors. We hypothesized, based on RST, that BAS scores would also be associated with total deliberativeness, especially about positive contingencies (e.g., rewards) for self-care behaviors. 838

RESEARCH DESIGN AND METHODS Participants and Procedures Participants were 204 individuals newly diagnosed with T2DM. All participants were recruited from consecutive referrals to a hospital-based self-management education program between January 2005 and October 2006 at Royal University Hospital in Saskatchewan, Canada. The average time since diagnosis for the group was 3 months (standard deviation (SD) ⫽ 1.76). Participants did not receive any formalized diabetes behavioral intervention during the interval between diagnosis and enrollment in the current study, and they had received only initial information about self-management. None of the participants were suffering from major psychiatric disorder and all had contact with a healthcare professional via the self-management clinic. Only participants with corrected-to-normal vision and acceptable English language comprehension were included in the study. This study received ethical clearance through the relevant Institutional Review Board procedures; all participants provided their informed consent before participating in the study.

Measures Anxiety Anxious temperament was measured by self-report using the BIS/BAS Scale (21). This scale consists of 20 items with responses given on a 4-point Likert scale with “1” indicating strong agreement and “4” indicating strong disagreement. In early studies, Carver and White examined the psychometric properties of the BIS/BAS in a sample of university undergraduates, using both correlational and experimental methods. Exploratory factor analysis suggested the existence of four factors among the scale items, together accounting for 49% of the total variance: a) BIS, the tendency to experience anxious emotionality in response to impending punishment; b) BAS Drive (BAS-D), the tendency to pursue appetitive goals; c) BAS Fun Seeking (BAS-FS), the tendency to gravitate toward excitement and act with spontaneity; and d) BAS Reward Responsiveness (BAS-RR), the tendency to experience positive affective responsiveness to rewards. Internal consistency reliabilities for each subscale were moderate (Cronbach’s ␣ values ranged from 0.66 for BAS-FS to 0.76 for BAS-D). Scores on the BIS subscale were moderately correlated with other conceptually related constructs (e.g., r ⫽ .60 for other behavioral inhibition measures) and uncorrelated with conceptually distinct constructs (e.g., r ⫽ ⫺.06 for positive affectivity) (21). Consistent with their conceptual understanding of the BIS/BAS subscales, Carver and White (21) found that BIS uniquely predicted nervousness in response to impending punishment in the laboratory setting, and BAS uniquely predicted happiness in response to impending reward. Other independent studies have confirmed the factor structure of the BIS/BAS in translations into other languages (22,23), and for both community (24) and clinical samples (25). Finally, the BIS and BAS demonstrated good test-retest reliability over an 8-week period (21), consistent with the notion that these measures assess temporally stable dimensions of personality. In the current sample, the Cronbach’s ␣ for BIS, BAS-D, BAS-FS, and BAS-RR were 0.72, 0.79, 0.62, and 0.69, respectively.

Body Mass Index (BMI) BMI was computed using a standard formula reflecting self-reported weight in kilograms divided by self-reported height in meters squared.

Contingency Deliberativeness Deliberativeness about self-management behaviors (exercise behavior, dietary behavior, and glucose monitoring) was assessed by self-report by asking participants to indicate on a 7-point scale (where 1 ⫽ “not at all” and 7 ⫽ “very much”) how much they currently think about a variety of potential contingencies, using the general form “How much do you think about [outcome X] (as a result of performing behavior Y)?” Both negative (i.e., costs) and positive (i.e., benefits) outcomes for each self-management behavior were represented (e.g., “How often do you think about preventing complications (as a result of daily glucose monitoring)?”; “How often do you think about losing time out of your day (as a result of daily glucose monitoring)?”). Each scale consisted of multiple items (13 for exercise behavior; 10 for dietary behavior; and 10 for glucose monitoring) derived from a survey of existing measures of outcome expectancies for each behavior in question, and via consultations Psychosomatic Medicine 70:837– 843 (2008)

ANXIETY AND DISEASE PROGRESSION with experts (dieticians, diabetes nurse educators, and health psychologists) (26). Scale reliabilities were satisfactory for exercise behavior, dietary behavior, and glucose monitoring deliberativeness (␣ values were 0.82, 0.75, and 0.73, respectively). An aggregate of the three domain measures was formed to produce an index of total deliberativeness about contingencies for self-management behavior. Higher scores on this aggregate measure, therefore, reflected greater degrees of self-reported deliberativeness about self-management contingencies in general. Two additional index variables were constructed reflecting deliberations about costs and benefits, respectively, by standardizing and aggregating scores across all three behaviors.

Dietary Choice Dietary choice was assessed using the National Institutes of Health Fruit and Vegetable Screener (27). This self-report scale has been validated in adult samples, and assesses the frequency of fruit and vegetable consumption over the previous 7 days.

Disease Progression A1C, a measure of glycohemoglobin, served as our measure of disease progression at diagnosis. Over the 120-day life span of red blood cells, glucose molecules join hemoglobin, forming glycohemoglobin. A build-up of glycohemoglobin in the red blood cells reflects the average level of glucose that the cell has been exposed to during its life span. It is frequently measured by analyzing a blood sample in the laboratory and is expressed as a percentage; in the current study, we used the Bayer DCA 2000 for on-site testing of A1C. Normal A1C values are ⬍6%, although this number can vary slightly depending on the laboratory tests used. Clinically, the A1C is used to index control of diabetes over a 4-month period of time, but it is better conceptualized as an index of the degree of disease progression when it is assessed at the time of diagnosis. A difference of 0.5% to 1.0% in A1C is considered clinically significant.


Demographic Characteristics of the Sample

Age, mean (SD), y Gender % Male Female Ethnicity % Caucasian Aboriginal/Metis Other Education % Elementary school (some or completed) High school (some or completed) College/university (some or completed) Graduate studies (Master’s or PhD) Household income % $0–19,999 $20,000–39,999 $40,000–59,999 $60,000–79,999 $80,000–99,999 $100,000⫹ BMI % ⬍25 25–29.9 30–34.9 ⱖ35 Months since diagnosis

57.87 (10.59) 40.8 59.2 90.0 7.5 2.5 10.4 35.6 50.0 4.0 10.5 25.7 21.5 19.9 10.5 12.0 10.1 33.3 24.2 31.3 3.05 (1.76)

N ⫽ 204; BMI ⫽ body mass index. TABLE 2.

BIS and BAS Scores as Predictors of A1C at Diagnosis

Physical Activity Physical activity was assessed by self-report using the Physical Activity Scale for the Elderly (PASE) (28). This measure has been validated for use with older adults within the age range of the current sample and has demonstrated good test-retest reliability over a 3- to 7-week period (28). Habitual physical activity was measured by a single self-report item, “How physically active are you normally?” with responses indicated on a 7-point scale where 1 ⫽ “not at all” and 7 ⫽ “extremely.”

Statistical Analyses Statistical analyses were conducted using SPSS. To test the main hypothesis that personality measures would be associated with A1C at diagnosis, regression analyses were employed entering any covariates on the first block, followed by the personality predictor variable of interest on the second block. In the primary set of predictive analyses, three models were tested, including an unadjusted model (Model 1), a model adjusting for age and gender alone (Model 2), and a model adjusting for age, gender, and BMI (Model 3). Additional moderational analyses were conducted in accordance with the conventions established by Aiken and West (29) for moderated multiple regression. High and low groups in dichotomous analyses or descriptive presentations were formed based on the recommended convention of mean ⫾ 1 SD. Moderational analyses were adjusted for gender, education, and BMI.

RESULTS Demographic characteristics of the sample are presented in Table 1. Hierarchical regression analyses were conducted to test the hypothesis that BIS (but not BAS) would predict disease progression at the time of diagnosis. As predicted, BIS was inversely associated with A1C at the time of diagnosis in all models tested; BAS was unrelated to A1C in any of the models (Table 2). Adjusting for time since diagnosis did not affect the significance of the BIS-A1C effect (␤ ⫽ ⫺0.203, t ⫽ ⫺2.822, p ⫽ .005). Psychosomatic Medicine 70:837– 843 (2008)

A1C at Diagnosis


Model 1

Model 2

Model 3

⫺0.170 0.055 0.002 ⫺0.031

⫺0.173 0.089 0.041 ⫺0.008

⫺0.189c 0.094 0.038 0.000



All coefficients are standardized ␤ weights; Model 1 ⫽ unadjusted regression coefficient; Model 2 ⫽ regression coefficient adjusted for age and gender; Model 3 ⫽ regression coefficient adjusted for age, gender and BMI; BIS ⫽ Behavioral Inhibition; BAS-D ⫽ Behavioral Approach (Drive subscale); BAS-RR ⫽ Behavioral Approach (Reward Responsiveness subscale); BASFS ⫽ Behavioral Approach (Fun Seeking subscale). a p ⱕ .05; b p ⱕ .01; c p ⱕ .001.

In a second set of analyses, we tested whether or not the association between BIS and A1C could be accounted for by differential levels of self-management behaviors over the previous number of weeks. In three separate regression analyses, we force-entered each of three behavior measures on Step 2 along with BIS scores (with demographics and BMI on Step 1). We found that the association between BIS and A1C was not better accounted for by recent dietary behavior (␤ ⫽ ⫺0.050, t ⫽ ⫺0.695, p ⫽ .488), recent physical activity as measured by PASE scores (␤ ⫽ 0.073, t ⫽ 1.02, p ⫽ .311), or habitual physical activity (␤ ⫽ ⫺0.009, t ⫽ ⫺0.129, p ⫽ .897). As such, early self-management efforts around the time of diagnosis do not explain the association between BIS and A1C. 839

P. A. HALL et al. TABLE 3.

Summary of Hierarchical Multiple Regression Model Predicting A1C at Diagnosis

Step 1 BMI Gender Education Step 2 Age BIS Step 3 BIS ⫻ Age



Significance of R2 Change











0.143 ⫺0.111 ⫺0.076 ⫺0.187 ⫺0.188 0.190

R2 ⫽ 0.134.

Moderation Analyses To determine whether BIS moderates the association between age and disease progression at diagnosis, a moderational analysis was conducted in accordance with Aiken and West (29), using the group mean ⫾ 1 SD to define “High” and “Low” groups on attributes of interest. As predicted, age was a significant predictor of A1C at diagnosis, suggesting that younger individuals tended to have higher A1C levels at the time of diagnosis (reflecting greater disease progression) than older individuals (␤ ⫽ ⫺0.189, t ⫽ ⫺2.536, p ⫽ .012). Further, both BIS scores (␤ ⫽ ⫺0.188, t ⫽ ⫺2.665, p ⫽ .008) and age (␤ ⫽ ⫺0.187, t ⫽ ⫺2.534, p ⫽ .012) were unique predictors of A1C. Most importantly, the interaction term for BIS and age was also significant (␤ ⫽ 0.190, t ⫽ 2.782, p ⫽ .006), suggesting that the relationship between age and A1C was different for different levels of BIS (Table 3). Specifically, there was stronger evidence of age bias in diagnosis for those low in BIS than among those high in BIS; as depicted in Figure 1, BIS seems to moderate age bias in the diagnosis of T2DM.

The simple slope regressing age on A1C was significantly different from zero for low (␤ ⫽ ⫺0.388, t ⫽ ⫺3.791, p ⬍ .001) and moderate BIS groups (␤ ⫽ ⫺0.187, t ⫽ ⫺2.588, p ⫽ .010); however, as hypothesized, the simple slope for the high BIS group was not significantly different from zero (␤ ⫽ 0.014, t ⫽ 0.133, p ⫽ .894), suggesting essentially complete attenuation of age bias in diagnosis in this latter group. BIS/BAS and Self-Care Deliberativeness To test the hypothesis that high BIS would be associated with higher levels of deliberativeness about self-care behaviors, we conducted separate regressions predicting self-care deliberativeness scores (for diet, exercise, and glucose monitoring) from BIS scores. As expected, BIS was positively associated with deliberativeness about all three behaviors in unadjusted and adjusted analyses (Table 4; Figure 2). To test the hypothesis that BIS would be selectively associated with deliberativeness about costs of self-management behaviors and BAS would be associated with deliberativeness about benefits, we formed separate costs and benefits deliberation measures by collapsing across all three self-care behaviors. As predicted, BIS scores were positively and selectively associated with deliberativeness about potential costs associated with self-care behaviors, whereas BAS-RR scores were positively and selectively associated with deliberativeness about potential benefits associated with self-care behaviors; other BAS subscales were not significantly related to deliberativeness about self-care contingencies, although regression coefficients for BAS-FS scales showed a trend toward statistical significance in all three models. Results for adjusted and unadjusted models are presented in Table 5. DISCUSSION Early detection is fundamentally important for secondary prevention, and this is particularly true for T2DM. Continued dis-

BIS Moderation Analyses 6.9 6.8 6.7 A1C at Diagnosis

6.6 6.5




6.3 6.2 6.1 6 5.9 Younger



Age Category

Figure 1. 840

Vertical axis depicts A1C at the time of diagnosis. BIS ⫽ Behavioral Inhibition System; A1C ⫽ glycated hemoglobin. Psychosomatic Medicine 70:837– 843 (2008)

ANXIETY AND DISEASE PROGRESSION TABLE 4. BIS Scores as Predictors of Deliberativeness About Exercise, Dietary Behavior, and Glucose Monitoring Model 1

Model 2

Model 3

0.279b 0.251b 0.329b

0.270b 0.224a 0.346b

0.256b 0.209a 0.339b

Exercise Dietary behavior Glucose monitoring

All coefficients are standardized ␤ weights; Predictor ⫽ BIS score; Model 1 ⫽ unadjusted regression coefficient; Model 2 ⫽ regression coefficient adjusted for age and gender; Model 3 ⫽ regression coefficient adjusted for age, gender, and body mass index. a p ⱕ .01; b p ⱕ .001.

ease progression in the absence of treatment and self-management can result in significant medical complications and even death in extreme cases. Our findings suggest that younger individuals are prone to later-stage disease detection than older adults, but this age bias in detection is almost completely compensated for by anxious temperament. That is anxious temperament seems to eliminate the usual age bias in detection and diagnosis of diabetes. As such, anxious temperament

may be an adaptive trait when it comes to the early detection of T2DM. Consistent with predictions derived from RST, anxious temperament was also associated with deliberativeness about costs associated with self-care behaviors (e.g., exercise, dietary behaviors, and glucose monitoring) after diagnosis. These findings highlight important nuances in the relationship between anxiety and diabetes. Past research has shown that individual differences in anxious temperament are associated A1C ⱖ6 months after diagnosis, suggesting on the surface that anxious temperament may facilitate self-management. However, the data in most of these studies also reveal baseline associations between anxiety and A1C, and the relevance of anxiety for early diagnosis is unclear without a newly diagnosed cohort. The current findings, using a newly diagnosed cohort, suggest that anxious temperament is inversely associated with disease progression at diagnosis among individuals who are not subject to routine screening. With respect to self-management behaviors, our findings seem to suggest that anxiety is associated with cognitive tendencies

Deliberativeness by BIS group 6








Be haviora l Doma in

Figure 2. Vertical axis depicts level of overall deliberativeness (collapsed across costs and benefits) associated with each self-care behavior. BIS ⫽ Behavioral Inhibition System. TABLE 5.

BIS and BAS Scores as Predictors of Deliberativeness About Costs and Benefits of Self-Care Behaviors Costs



Model 1

Model 2

Model 3




0.393 ⫺0.038 0.103 ⫺0.003

0.390 ⫺0.041 0.086 ⫺0.016

0.374 ⫺0.032 0.072 0.001

Model 1 0.097 0.081 0.294* 0.127†

Model 2 0.087 0.102 0.289* 0.128†

Total Model 3 0.077 0.103 0.281* 0.136†

Model 1 *

0.309 0.052 0.299* 0.102

Model 2 *

0.302 0.067 0.294* 0.102

Model 3 0.290* 0.077 0.280* 0.120

All coefficients are standardized ␤ weights; Model 1 ⫽ unadjusted regression coefficient; Model 2 ⫽ regression coefficient adjusted for age and gender; Model 3 ⫽ regression coefficient adjusted for age, gender, and body mass index; BIS ⫽ Behavioral Inhibition; BAS-D ⫽ Behavioral Approach (Drive subscale); BAS-RR ⫽ Behavioral Approach (Reward Responsiveness subscale); BAS-FS ⫽ Behavioral Approach (Fun Seeking subscale). * p ⱕ .001. † p ⱕ .10. Psychosomatic Medicine 70:837– 843 (2008)


P. A. HALL et al. that may not be conducive to good uptake of self-management behaviors after diagnosis; specifically, higher scores on our measure of BIS were associated with more deliberativeness over potential negative contingencies for these behaviors. Several studies have found that the presence of clinically significant anxiety disorders—as assessed by diagnostic interviewing—results in significantly poorer glycemic control (30). There are a number of ways to interpret these seemingly inconsistent findings. The relationship between anxiety and A1C could be understood as an inverted U relationship such that moderate levels of experienced anxiety in relation to a disease generate approach-related self-management behaviors, whereas exceptionally high levels of anxiety (i.e., clinically significant anxiety disorders) generate avoidance behaviors that preclude effective management. For example, individuals who are only temperamentally anxious may worry about and be motivated to avoid serious complications of T2DM by engaging in self-management efforts; those who are phobically avoidant of all reminders of the disease may fail to take corrective action at all, thereby predisposing them to early experience of disease-related complications. Ultimately, this is an empirical question, and future studies might establish whether anxiety in its most extreme variants—perhaps more easily measured through psychophysical assessments—is associated with A1C in a nonlinear fashion. A secondary finding was that increased reward responsiveness is associated with increased deliberativeness about selfcare behaviors in general, and selectively so with deliberations about potential benefits. The relevance of such cognitions for uptake of self-management behaviors is unclear but could be disentangled with a prospective analysis. Nonetheless, the form of this relationship is consistent with what would be hypothesized based on Gray’s theoretical framework. Finally, at least ten published studies to date have demonstrated that depression and anxiety measured at baseline can prospectively predict diagnosis of T2DM at follow-up (31– 40). This could be taken as evidence that anxiety and depression are somehow linked to the development of T2DM via behavioral, hormonal, and neuroendoncrine pathways. These are all possibilities; however, the current findings suggest that anxious individuals may also be more likely to be diagnosed early in the stage of disease progression; this on its own could account for why more depressed and anxious individuals might receive a diagnosis during any given follow-up interval, regardless of differential incidence of the disorder in depressed/anxious groups versus controls. The mechanism by which individuals come to be diagnosed earlier in disease progression is presently unclear but could involve increased salience of symptoms to the individual/clinician, increased helpseeking behavior among anxious individuals, or other unknown mechanisms. Ultimately, these are questions to be addressed by future research. Strengths and Limitations Strengths of this study include the use of an objective measure of disease progression (A1C) and recruitment of a 842

treatment-naı¨ve T2DM sample. Along these lines, the fact that we used only newly diagnosed T2DM participants provides a stringent test of our hypotheses. Past studies have been limited by mixed samples including patients with both Type 1 and Type 2 diabetes, those undergoing active behavior change intervention (as part of standard care), and those with earlyand late-stage disease progression. In this sample, restriction to newly diagnosed T2DM participants is a strength that eliminates many potential confounds. Likewise, our use of A1C, rather than daily glucose readings, represents a more stringent test of the disease progression hypothesis. Several limitations are important to consider. First, due to the cross-sectional nature of the study, it is not possible to make statements about meditational processes, although we suspect that they may involve any combination of increased detection, amplification, or reporting of somatic symptoms among individuals who are higher in anxious temperament. It is also possible, however, that dysfunction of the hypothalamic pituitary axis concurrent with anxious temperament may be responsible for the development of diabetes itself, as suggested by Engum (31). The cross-sectional nature of the data may also lead some to question the directionality of the effects (i.e., to what extent is anxiety symptomatic of low circulating glucose?). The initial onset of episodes of acute hypoglycemia are known to mimic the symptoms of acute anxiety states (41). There are three lines of defense to this argument—all of which are potentially applicable here. First, our measure of BIS is a trait measure—not a state measure; scores therefore reflect general dispositional tendencies that transcend acute emotional states. Second, A1C does not reflect state fluctuation in blood glucose. By definition, the majority of the study sample are above average in blood sugar concentrations and none were currently taking insulin, which is the primary cause of acute states of hypoglycemia in diabetic samples (via overcorrection); a full 98% of our sample had A1C levels of ⬎5.0 at the time of assessment, and most of these were ⬎6.0. Although representative of the geographic region from which the sample was drawn, the present sample may or may not be representative of a more ethnically diverse population. Finally, reliance on self-reported BMI is a limitation of this study. Implications and Future Directions Clinically significant anxiety disorders seem to influence glycemic control through perpetuation of avoidance of necessary self-care behaviors (e.g., needle/injection/blood phobias). Based on this literature, one might conclude that the propensity to be anxious is associated with poor glycemic control, but our data suggest that a dispositional variety of anxious temperament—i.e., behavioral inhibition—may actually be useful for facilitating timely disease detection, especially among younger individuals who are not subject to routine screening. The present findings could be understood within the larger literature of psychopathology and diabetes, which suggests that anxiety in the clinical range (as opposed to everyday anxious temperament, as measured here) may actually be detrimental for self-management after diagnosis. This is a complex issue and it may be that, although a little anxiety may Psychosomatic Medicine 70:837– 843 (2008)

ANXIETY AND DISEASE PROGRESSION be helpful before diagnosis, postdiagnosis anxiety may be decidedly unhelpful, particularly if it is strong enough to motivate defensive denial about the consequences of nonmanagement or avoidance of cues as to the presence of the disease. Understanding these dynamics could have important screening and intervention implications. What is the practical significance of knowing that anxious temperament is associated with earlier diagnosis? Given that early diagnosis is generally understood as a positive state of affairs with respect to T2DM, the present study suggests that we may be able to learn something about disease detection from temperamentally anxious individuals that could be of use among the larger population of at-risk individuals. If future studies can determine how those with anxious temperament come to be diagnosed earlier, e.g., via hypervigilance to subtle physical signs, via less delayed reporting of symptoms, and/or via more frequent contact with a physician over somatic complaints, we may be able to encourage behaviors that facilitate early diagnosis among nonanxious individuals as well. We thank Lynette Epp, Judy Whiting and the staff at the Diabetes Education Centre, Royal University Hospital for their assistance with data collection.

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