دردسرهای روزانه و رفتار غذایی: نقش وضعیت واکنش پذیری کورتیزول

Summary Previous research has shown high cortisol reactors to consume a greater amount of snack foods than low reactors following a laboratory stressor. The current study tested whether high cortisol reactors also consume more snacks than low reactors in response to field stressors. Fifty pre-menopausal women completed a laboratory stressor, provided saliva samples to assess cortisol reactor status and then completed daily hassles and snack intake diaries over the next fourteen days. Hierarchical multivariate linear modelling showed a significant association between daily hassles and snack intake within the overall sample, where an increased number of hassles was associated with increased snack intake. This significant positive association between number of hassles and snack intake was only observed within the high cortisol reactors and not within the low cortisol reactors. These findings suggest that high cortisol reactivity to stress promotes food intake. Furthermore, the eating style variables of restraint, emotional eating, external eating and disinhibition were more strongly associated with snack intake in high reactors than in low reactors. This suggests that cortisol reactivity may in part account for the moderating role of eating style on stress-induced eating. The results are discussed within the context of future health risk.

Introduction It is becoming more apparent that stress and negative affect not only have direct effects on health but also indirect effects through behavioural changes, including changes in the type and amount of food consumed (e.g., Macht and Simons, 2000; O’Connor et al., 2000; O’Connor and O’Connor, 2004). Laboratory and self-report studies demonstrate that individuals respond differently in their eating response to stress with gender, bodyweight and the eating style variables of restraint, emotional eating, external eating and disinhibition acting as significant moderators of the stress–eating relationship (McKenna, 1972; Herman and Polivy, 1975; Grunberg and Straub, 1992; Greeno and Wing, 1994; Conner et al., 1999; Oliver et al., 2000; Van Strien et al., 2000; O’Connor et al., 2005). Although, while research has identified a number of important moderators of stress-induced eating, relatively little is known about the underlying mechanisms. One possible mechanism for stress-induced eating concerns the activity of the hypothalamic–pituitary–adrenal axis during stress, particularly the release of glucocorticoids from the adrenal cortex. Sapolsky (1998) proposed that corticotropic releasing hormone (CRH) and glucocorticoids (GC) have opposing effects on appetite, such that food intake is inhibited by CRH and promoted by GC production. Direct manipulations of GC levels support their association with appetite and food intake. Adrenalectomised rats unable to secrete GC have been shown to consume smaller amounts of carbohydrate relative to other macronutrients (Laugero, 2001), and GC appears to protect against the hypophagic effects of leptin (Zakrzewska et al., 1997). In humans, the administration of glucocorticoids in humans has been shown to increase energy consumption, especially carbohydrates and proteins (Tataranni et al., 1996). Furthermore, the release of GC during stress has been associated with increased snack intake. In a laboratory investigation of snack intake in women after stress exposure, Epel et al. (2001) reported that during stress recovery high cortisol reactors consumed more than low reactors, especially of high fat, sweet foods. Therefore individual differences in the stress–eating response could be dependant on GC reactivity to stress, such that high cortisol reactors consume a greater amount when stressed than do low reactors. As yet, this cortisol reactivity theory of stress-induced eating has only been tested in the laboratory and not in the field. To test whether the effect is limited to the laboratory it is essential to replicate and extend Epel et al.'s (2001) findings in a more natural setting. Field studies of stress-induced eating usually require individuals to complete diary records of workload, hassles and food intake (e.g., Steptoe et al., 1998; Conner et al., 1999), allowing the researcher to measure natural eating behaviour in response to real-life stressors. Previously, diary studies of stress-induced eating have compared overall snack intake across high and low stress weeks (e.g., Steptoe et al., 1998). However, by averaging intake across days and weeks subtle daily variations in stress and intake may be lost. Multivariate linear modelling enables researchers to test between-person associations and within-person daily variations in measures (Affleck et al., 1999), and would therefore facilitate an investigation of the relationship between daily stress and snack intake. Despite this advantage, only one previous study has employed this method of analysis to examine fluctuations in intake with daily stress (O’Connor et al., 2005). The present study aimed to test whether the relationship between hassles and snacks outside the laboratory differs between high and low cortisol reactors as an extension of Epel et al.'s (2001) study and a test of whether GC release could account for variations in stress-induced eating. The study also aimed to test whether the relationship between eating style and snacking differed according to cortisol reactivity status. Following the procedure of Epel et al. (2001), pre-menopausal women were exposed to laboratory stressors to establish cortisol reactivity status and required to report daily hassles and snack intake in diaries over 2 weeks. Because of reported gender differences in cortisol reactivity to stress (e.g., Kudielka and Kirschbaum, 2005) and a greater prevalence of stress-induced food intake in females (e.g., Grunberg and Straub, 1992), only females were included in the current study. It was predicted that high cortisol reactors would show a stronger positive association between daily hassles and snack intake than low reactors.

. Results 3.1. Stress ratings The stressfulness ratings of the stress procedure ranged from 1 (not at all stressful) to 7 (extremely stressful) on the 7 point scale, with a mean of 4.78 (SD=1.43), indicating that the stressor was moderately, but not extremely, stressful. The mean state anxiety level was 13.94 (SD=3.32) before the stress manipulation, and 16.76 (3.68) after the manipulation. A repeated measures t-test indicated that this difference was significant (t(49)=4.96, p<0.001), indicating that the stress manipulation was successful in increasing anxiety. 3.2. Cortisol reactivity Cortisol reactivity was measured by taking the difference between the average of the two baseline samples and the peak response (between 10 and 40 min following the start of the stress protocol). There was an average cortisol increase of 1.36 nmol/l (SD=3.77). A previous study has shown an average cortisol increase of ∼7.00 nmol/l in women after 40 min (Kirschbaum et al., 1992), therefore average reactivity was lower in the current study. Reactivity ranged from –3.39 to +13.43 nmol/l, indicating that some participants showed a decline in cortisol levels following baseline. Twenty-six women showed an increase in cortisol levels, and were classified as high reactors (mean reactivity=3.69 nmol/l). Twenty-three women who showed a decrease in levels and one participant who showed no change were classified as low reactors (mean reactivity=−1.18 nmol/l). Fig. 1 shows the cortisol reactivity profiles for high and low reactors. High and low reactors significantly differed in reactivity from baseline (t(48)=−6.18, p<0.001), but not in average baseline values (t(48)=0.08, n.s.). There was no difference in stress ratings of the manipulation between the reactor groups (t(48)=−0.93, n.s.), but there was a significant difference in state anxiety post-manipulation (t(48)=−3.11, p<0.01), indicating that high reactors had a greater anxiety rating following the stress manipulation than did low reactors. Cortisol reactivity profiles of high and low reactors during the laboratory ... Figure 1. Cortisol reactivity profiles of high and low reactors during the laboratory session. Figure options 3.3. Relationship between daily hassles and snack intake The number of reported daily hassles ranged from zero to five, with a mode of one. The number of daily hassles was positively skewed so this variable was dichotomised: No hassles or one hassle experienced per day was coded as low, and 2 or more coded as high, to provide the most even division of low and high numbers of hassles (65.7% days coded as low hassle days, and 34.3% coded as high hassle days). The rated intensities of each hassle were summed for each day to give a total daily hassle intensity score. These hassle intensity scores ranged from 0 to 16 and were also positively skewed. The variable was dichotomised into high and low hassle intensity days, with intensity scores of 0 to 2 coded as low, and 3 to 16 as high (47.1% days were coded as low intensity and 52.9% as high intensity). Because the number and intensity of hassles were dichotomised, both these variables were entered as uncentred variables in the multivariate models. The number of daily snacks consumed ranged from 0 to 6, with a mean of 1.84 snacks per day. The effect of the number and intensity of daily hassles on overall snack intake was tested using a level one model, with the number and intensity of hassles as predictors. This model is expressed as Yi=β0+β1+εi,Yi=β0+β1+εi, Turn MathJax on where Yi is the outcome variable of the number of daily snacks, β0 the intercept, β1 the slope for the level one predictor variable and εi the random error term. Each level one predictor variable (number of hassles, intensity of hassles, negative affect and positive affect) was entered individually into the equation, rather than all being entered simultaneously. Table 1 shows the association between each predictor variable and snack intake. Table 1. Associations between daily stress and snack intake in the overall sample and within high and low reactor groups separately. Predictor Overall sample High reactors Low reactors β SE t β SE t β SE t Number of hassles 0.324 0.086 3.76⁎⁎ 0.387 0.098 3.96⁎⁎ 0.012 0.089 0.14 Intensity of hassles 0.240 0.079 3.06⁎⁎ 0.506 0.080 6.30⁎⁎ −0.143 0.078 −1.84 Negative affect 0.043 0.014 3.15⁎⁎ 0.027 0.014 1.95 0.043 0.016 2.75⁎ Positive affect 0.001 0.010 0.12 0.016 0.011 1.52 −0.028 0.011 −2.61⁎ Note: β coefficients are unstandardised. ⁎ p<0.05. ⁎⁎ p<0.01. Table options Table 1 shows that across the sample snack intake was significantly associated with the number of hassles, intensity of hassles and negative affect. An increase in hassle intensity, number and negative affect was associated with increased snack intake. Daily positive affect score was unrelated to snack intake. 3.4. Daily hassles and intake in high and low cortisol reactors To test whether the relationship between hassles and snack intake differed between the low and high peak cortisol reactors, the same hierarchical modelling was also conducted separately for the two groups (shown in Table 1). Within the low reactors, snack intake was not significantly associated with the number of daily hassles (β=0.01, t=0.14, n.s.) or the intensity of hassles (β=−0.14, t=−1.84, n.s.). In high peak reactors, there were significant positive associations between hassle number and snack intake (β=0.39, t=3.96, p<0.01), and hassle intensity and snack number (β=0.51, t=6.30, p<0.001), indicating that snack intake increased with a greater number and intensity of hassles in the high reactor group. Beta coefficients were significantly different between the high and low reactor groups for number of hassles (t(46)=2.83, p<0.01) and numbers of hassles (t(46)=5.81, p<0.01). With regards to daily mood, snack intake was significantly positively associated with negative affect (β=0.04, t=2.75, p<0.05) and negatively associated with positive affect (β=−0.01, t=−2.61, p<0.05) in the low reactors only indicating that snack intake increased with negative mood and decreased with positive mood in low and not in high peak reactors. 3.5. Effect of eating style on snack consumption To test whether snack consumption was predicted by the eating style variables and if this relationship differed according to cortisol reactivity status, each eating style variable was added individually to Yi=β0+β1+εij,Yi=β0+β1+εij, Turn MathJax on where Yi is the outcome variable of the number of daily snacks, β0 the intercept, β1 the slope for the level two eating style predictor variable and εij the random error term. Table 2 shows the relationship between each of the eating style measures and daily snack intake in the overall sample and within the high and low cortisol reactor groups separately. Table 2. Main effects of eating style on snack intake in the overall sample and within high and low reactor groups separately. Eating style predictor Overall sample High reactors Low reactors β SE t β SE t β SE T Restraint 0.075 0.011 6.83⁎⁎ 0.089 0.011 7.85⁎⁎ 0.030 0.010 3.12⁎⁎ Emotional eating 0.041 0.010 4.16⁎⁎ 0.055 0.012 4.62⁎⁎ 0.025 0.007 3.61⁎⁎ External eating 0.041 0.017 2.47⁎ 0.046 0.021 2.19⁎ 0.026 0.012 2.21⁎ Disinhibition 0.101 0.025 4.08⁎⁎ 0.127 0.030 4.23⁎⁎ 0.041 0.019 2.19⁎ Note: β coefficients are unstandardised. ⁎ p<0.05. ⁎⁎ p<0.01. Table options Snack intake was significantly associated with dietary restraint (β=0.08, t=6.83, p<0.01), emotional eating (β=0.04, t=4.16, p<0.01), disinhibition (β=0.10, t=4.08, p<0.01) and external eating (β=0.04, t=2.47, p<0.01) in the overall sample. In each case, an increase in the eating style variable was associated with an increase in the number of snacks consumed. Table 2 also shows that all the eating style variables were significantly associated with snack intake in both the high and low cortisol reactors, but that the associations were stronger within the high reactors. A comparison of the beta coefficients between the groups showed that associations were significantly stronger within the high reactors for restraint (t(46)=3.97, p<0.01), emotional eating (t(46)=2.16, p<0.01) and disinhibition (t(46)=2.42, p<0.01), but not external eating style (t(46)=0.83, n.s.).