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Evaluation of Nutritional Status and Allostatic Load in Adult Patients With Type 2 Diabetes
Can J Diabetes xxx (2019) 1e6
Contents lists available at ScienceDirect
Canadian Journal of Diabetes journal homepage: www.canadianjournalofdiabetes.com
Original Research
Evaluation of Nutritional Status and Allostatic Load in Adult Patients With Type 2 Diabetes Melahat Sedanur Macit MSc a; Nilufer Acar-Tek PhD b, * a b
Faculty of Health Sciences, Department of Nutrition and Dietetics, Ondokuz Mayıs University, Samsun, Turkey Faculty of Health Sciences, Department of Nutrition and Dietetics, Gazi University, Ankara, Turkey
Key Messages
Measurement of allostatic load may help to prevent or delay type 2 diabetes mellitus complications. Allostatic load incorporates inflammatory, metabolic and cardiovascular system parameters. Recommended consumption levels of fruits and vegetables should be encouraged in type 2 diabetes mellitus patients. Additional food consumption research is needed to understand the relationships between stress, allostatic load and level of fruit consumption.
a r t i c l e i n f o
a b s t r a c t
Article history: Received 9 January 2019 Received in revised form 9 May 2019 Accepted 24 May 2019
Objective: Diabetes is a chronic disease, affected by nutritional status, and characterized by dysregulations in several systems. Allostatic load is an index that evaluates the dysregulation of all physiological and metabolic systems. This study was conducted to determine the relationship between nutritional status and allostatic load in patients with type 2 diabetes mellitus (T2DM). Methods: The study sample consisted of 30 males and 73 females between 20 and 55 years of age. Individuals had T2DM for 7.96.17 (mean standard deviation) years. World Health Organization criteria cutoffs were used to calculate allostatic load scores. Twelve parameters were questioned and an allostatic load score between 0 and 12 was obtained; values above the cutoff levels were assigned a value of 1, and values in the normal range were assigned a value of 0. Results: Individuals with high allostatic load comprised a significant portion of the sample (79.6%) for both males and females (73.3% and 82.2%, respectively). Longer diabetes duration was associated with high allostatic load score (p<0.05). There was lower vegetable consumption and higher fruit consumption in the high-allostatic-load group compared with the low-allostatic-load group (p<0.05). However, fruit consumption was still lower than recommended levels in both groups. Conclusions: A significant number of individuals had high allostatic load scores in our study. A healthy diet plan in line with the recommendations may help to decrease the allostatic load scores by reducing body weight, waist/hip ratio, blood pressure and fasting blood glucose, and may prevent the negative effects of stress on metabolic processes in the long-term malnutrition in T2DM. Ó 2019 Canadian Diabetes Association.
Keywords: allostasis allostatic load diabetes nutrition
Mots clés: allostasie charge allostatique diabète nutrition
r é s u m é Objectif : Le diabète est une maladie chronique, influencée par l’état nutritionnel et caractérisée par des dysrégulations de nombreux systèmes. La charge allostatique est un indice qui permet d’évaluer la dysrégulation de tous les systèmes physiologiques et métaboliques. Nous avons mené la présente étude pour déterminer la relation entre l’état nutritionnel et la charge allostatique des patients atteints du diabète sucré de type 2 (DST2).
* Address for correspondence: Nilufer Acar-Tek PhD, Faculty of Health Sciences, Department of Nutrition and Dietetics, Gazi University, Muammer Yas¸ar Bostancı St, Ankara 06500, Turkey. E-mail address: [email protected] 1499-2671/Ó 2019 Canadian Diabetes Association. The Canadian Diabetes Association is the registered owner of the name Diabetes Canada. https://doi.org/10.1016/j.jcjd.2019.05.011
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Méthodes : L’échantillon de la population étudiée était composé de 30 hommes et de 73 femmes entre 20 et 55 ans. Les individus avaient le DST2 depuis 7,9 6,17 (moyenne écart type) ans. Nous avons utilisé les seuils de l’Organisation mondiale de la santé pour calculer les scores de l’indice de charge allostatique. Pour les 12 paramètres pris en compte, un score de l’indice de charge allostatique entre 0 et 12 a été obtenu; les valeurs supérieures aux seuils se sont vu attribuer une valeur de 1, et les valeurs dans la fourchette normale se sont vu attribuer une valeur de 0. Résultats : Les individus qui avaient une charge allostatique élevée comptaient pour une part importante de l’échantillon (79,6 %) d’hommes et de femmes (73,3 % et 82,2 %, respectivement). Une durée plus longue du diabète a été associée à un score élevé de l’indice de charge allostatique (p < 0,05). Le groupe qui avait une charge allostatique élevée consommait moins de légumes et plus de fruits que le groupe qui avait une faible charge allostatique (p < 0,05). Toutefois, dans les 2 groupes, la consommation de fruits était toujours inférieure aux portions recommandées. Conclusions : Dans notre étude, un nombre important d’individus avaient des scores élevés de l’indice de charge allostatique. Un régime alimentaire sain conforme aux recommandations peut aider à diminuer les scores de l’indice de charge allostatique du fait de la réduction du poids corporel, du rapport taille/ hanches, de la pression artérielle et de la glycémie à jeun, et peut prévenir les effets négatifs du stress sur les processus métaboliques de la malnutrition à long terme lors de DST2. Ó 2019 Canadian Diabetes Association.
Introduction Type 2 diabetes mellitus (T2DM) has a complex pathophysiology, with complications such as beta-cell damage and insulin resistance (1). Stress-related factors may play a role in the etiology of T2DM and can affect the inflammatory, metabolic and cardiovascular systems. Lifestyle factors may also be involved in the relationship between stress and diabetes, as well as the psychobiological factors. Allostatic load, which evaluates the dysregulation of several systems, is a model that incorporates all parameters of the inflammatory, metabolic and cardiovascular systems that are important in terms of T2DM complications. Allostatic load assessment also clarifies the effects of chronic stress on health through a comprehensive approach (2,3). Chronic stress emerges with the release of corticotrophin hormone from the hypothalamus and causes physiological changes, which result in negative health outcomes (4). If there is long-term chronic activity or inactivity in the metabolism, allostasis and allostatic load occurs, with high blood pressure, high blood lipids, high catecholamine levels, low glycemic control, increased waist circumference and abnormal levels of cortisol. This may lead to chronic diseases, such as obesity, atherosclerosis and diabetes, and may worsen the progression of current diseases (5,6). Fasting blood glucose, glycated hemoglobin (HbA1C), total cholesterol, body mass index (BMI), waist/hip ratio, body fat percentage and blood pressure are the metabolic and cardiovascular system parameters involved in the evaluation of allostatic load (7). Diabetes is a major public health problem and higher levels of blood glucose pose a long-term risk for patients. In these patients, it is useful to assess all parameters as well as blood glucose to prevent development of diabetes complications. It is necessary to monitor cardiovascular, metabolic and allostatic load-related parameters in patients with diabetes. High blood pressure may cause hypertension and unregulated blood glucose may cause microvascular complications of diabetes. Therefore, a holistic approach that includes all metabolic criteria represents a useful tool in clinical assessment. All parameters of the allostatic load are closely associated with diabetes. Accordingly, evaluation of allostatic load in patients with diabetes provides comprehensive follow up for patients in the clinic (5). Allostatic load index may provide more accurate information on mortality and physical condition as compared with evaluating the parameters separately. This model ensures assessment of primary and secondary mediators in conjunction and reveals tertiary outcomes for patients at risk (8). Nutrition is an important factor as it has major effects on allostatic load parameters. Effects of eating habits, body composition
and tertiary outcomes of allostatic load are summarized in Figure 1. Environmental factors, including diet, also have effects on allostatic load. The allostatic load may occur in response to food preferences and eating habits, and high-allostatic-load scores may be associated with abdominal obesity, cardiovascular disease, hypertension and T2DM (9). Based on this background, we conducted a study to evaluate the relationship between nutritional status and allostatic load in patients with diabetes. Our hypotheses were as follows: Nutrition has several effects on body composition and biochemical parameters, and also on allostatic load. Consumption of food groups may affect allostatic load scores independently. Unregulated blood glucose may be a determinant for high allostatic load.
Methods This study was planned and conducted between May 2015 and December 2015 with a total of 103 patients, including 30 males and 73 females (20 to 55 years old) with diabetes at the Endocrinology and Metabolism Outpatient Clinic of Ondokuz Mayıs University Hospital. Pregnant/breastfeeding women, those with a different endocrine disease, those using drugs that affect cortisol level (etomidate, ketoconazole, estrogens) and those doing a sport that requires intense physical activity were excluded from the study. For this study, ethics approval was obtained from Gazi University (commission dated June 5, 2014, no. 77082166-604.01.0212551). In addition, necessary permission was obtained from the Department of Health Application and Research Center at Ondokuz Mayıs University to conduct the study at the Endocrinology and Metabolism Outpatient Clinic of Ondokuz Mayis University Hospital (dated May 21, 2014, issue 2251, no. 15374210-000). Data collection General characteristics (age, gender, marital status, etc), dietary habits, smoking and alcohol consumption of the participants were obtained with a questionnaire. Consequently, food consumption records were recorded for individuals for 3 days (2 weekdays, 1 day on weekend). Daily energy and nutrient intake were calculated with a nutrition information system (BeBis) (10).
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Figure 1. Nutritional status, eating patterns and other factors affecting allostatic load. BMI, body mass index; CRP, C-reactive protein; HDL, high-density lipoprotein; HbA1C, glycated hemoglobin.
Anthropometric measurements
Assessment of allostatic load
Body weight and body fat percentage measurements were measured with a portable device (Model SC 330 ST, Tanita, Tokyo, Japan) by bioelectrical impedance (BIA). Height was measured by using a stadiometer with the patient’s head aligned in the Frankfort horizontal plane (11). Waist and hip circumferences were measured by using nonstretch tape (6,11). BMI was calculated by dividing weight (in kilograms) by height (in meters) squared (11). Waist/hip ratio was calculated by dividing waist circumference by hip circumference (12,13).
For assessment of allostatic load, we obtained the following data: systolic and diastolic blood pressure for cardiovascular function, serum fasting blood glucose, BMI, waist/hip circumference, serum total cholesterol, serum high-density lipoprotein cholesterol (HDL-C), serum HbA1C levels, body fat percentage for metabolic function, serum C-reactive protein (CRP) and albumin for the inflammatory system and serum cortisol and dehydroepiandrosterone sulfate (DHEA-S) levels for the neuroendocrine system (14‒16). Allostatic load score was obtained by
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assigning a “1” or “0” value for the parameters listed earlier for cutoff points (8,9,17,18). One point was given for parameters above cutoff and 0 point for parameters below the cutoff, except for serum albumin and HDL-C. For these, 0 point was given for parameters above the cutoff and 1 point for parameters below the cutoff. Thus, an allostatic load score of between 0 and 12 points was obtained. If the patients were using antihyperlipidemic or antihypertensive drugs, 1 point was added to the total score regardless of blood pressure and blood lipid values. Scores between 0 and 4 were defined as “low allostatic load” and scores 4 were defined as “high allostatic load” (17,19). For selection of cutoff points, World Health Organization (WHO) metabolic syndrome criteria for fasting blood glucose (>126 mg/dL), serum HDL-C (<35 mg/dL for males, <39 mg/dL for females), blood pressure (systolic blood pressure >140 mmHg, diastolic blood pressure >90 mmHg), WHO classification for BMI (>30 kg/m2), WHO references for waist/hip ratio (>0.9 for males, >0.85 for females), body fat percentage (>25% for males, >35% for females), total cholesterol (>200 mg/dL) and HbA1C (>6.5%) were used (13,20,21). Ondokuz Mayis University Central Laboratory reference values were considered in the assessment of CRP (>3 mg/dL), albumin (<3.5 mg/dL), cortisol (>19.4 mg/dL) and DHEA-S (<85 mg/dL). Statistical analyses Statistical analyses were performed using SPSS version 16.0 (IBM SPSS, Armonk, New York, United States). Descriptive analyses were calculated using mean standard deviation and median interquartile range. Nominal variables are expressed as frequency and percent. Differences between groups were assessed using the chisquare test. Differences between means and significance level were evaluated according to parametric tests (t test or Mann‒Whitney U test). Statistical significance was set at p<0.05 (2-sided). Logistic regression models were performed for associations between allostatic load scores and vegetable‒fruit consumption (adjusted by age and gender) according to HbA1C levels. Vegetable, fruit and total vegetable‒fruit consumption were selected as predictors. Results A total of 79.6% of individuals had high-allostatic-load scores (73.3% of males and 82.2% of females, respectively; data not shown). In the low-allostatic-load group (allostatic load score, 0 to 4), the mean value of allostatic load was 3.40.68 for the total group, 3.60.74 for males and 3.30.63 for females. There was no statistically difference according to gender (p¼0.268). In the highallostatic-load group (allostatic load score, 4), the mean value of allostatic load was 6.51.22 for the total group, 6.62.44 for males and 6.41.08 for females. There was no statistically difference according to gender in the high-allostatic-load group (p¼0.918) (data not shown). Assessment of parameters according to allostatic load groups are presented in Table 1. There was no statistical difference between age and allostatic load (p>0.05). However, education level was positively associated and diabetes duration negatively associated with allostatic load (p<0.05). Serum fasting blood glucose, BMI, body fat percentage, HbA1C, systolic blood pressure, CRP and cortisol were statistically significantly higher in the high-allostaticload group (p<0.05). Waist/hip ratio mean values were higher in females in the high-allostatic-load group (p>0.05). Consumption rates of the various food groups in the high- and low-allostatic-load groups are shown in Table 2. Vegetable consumption was higher in the low-allostatic-load group (341.0175.23 g/day) than in the high-allostatic-load group (216.6141.55 g/day) (p<0.05). However, mean fruit consumption
Table 1 Biomarkers according to allostatic load Biomarkers Age (year) Education level (year) Diabetes duration (year) Metabolic biomarkers Fasting blood glucose (mg/dL) Body mass index (kg/m2) Body fat (%) Waist/hip ratio Male Female Total cholesterol (mg/dL) HDL cholesterol (mg/dL) Male Female HbA1C (%) Cardiovascular biomarkers Systolic blood pressure (mmHg) Diastolic blood pressure (mmHg) Inflammatory biomarkers CRP (mg/dL) Albumin (mg/dL) Neuroendocrine biomarkers Cortisol (mg/dL) DHEA-S (mg/dL)
High allostatic load (4)
Low allostatic load (<4)
p value
47.14.34 6.84.30 8.66.46
43.89.69 10.14.88 5.33.93
0.406 0.020* 0.031*
155.550.27 35.07.45 36.88.67
126.252.13 27.83.67 27.58.02
0.001y 0.000y 0.000y
1.00.10 0.90.07 187.636.80
1.00.06 0.90.08 178.821.86
0.662 0.025* 0.203
43.99.98 49.310.62 7.71.55
46.94.13 45.712.93 6.81.64
0.420 0.327 0.000y
139.917.25 85.110.79
129.512.69 83.911.02
0.007y 0.730
7.28.22 4.50.41
4.01.61 4.60.27
0.001y 0.235
14.38.81 169.064.04
11.63.26 190.164.04
0.043* 0.469
CRP, C-reative protein; DHEA-S, dehydroepiandrosterone sulfate; HbA1C, glycated hemoglobin; HDL, high-density lipoprotein. Note: Data expressed as mean standard deviation. * p<0.05 (Mann‒Whitney U test). y p<0.01 (Mann‒Whitney U test).
was higher in the high-allostatic-load group (131.7106.63 g/day) than in the low-allostatic-load group (73.464.34 g/day) (p<0.05). There was no statistically significant difference between allostatic load and consumption of milk and dairy products; meat, fish and alternatives; legumes and oilseeds; and grains (p>0.05). Vegetable and fruit consumption have found to be associated with allostatic load scores (Table 2). Therefore, a logistic regression model was used to assess the effects of fruit and vegetable consumption on allostatic load for the groups with regulated and unregulated blood glucose (Table 3). Vegetable consumption (odds ratio [OR], 0.986; 95% confidence interval [CI], 0.976 to 0.997) and total vegetable‒fruit consumption (OR, 0.992; 95% CI, 0.976 to 0.997), but not fruit consumption (1.008; 95% CI, 0.996 to 1.019), demonstrated lowering effects on allostatic load in individuals with HbA1C values <6.5%. However, there was no statistically significant effect for vegetable, fruit and total vegetable‒fruit consumption in individuals with HbA1C values >6.5%. Discussion Allostatic load is a multisystem assessment that includes metabolic, anthropometric, cardiovascular, inflammatory and neuroendocrine parameters. Diabetes is a major chronic disease with a number of complications, which includes the parameters above. Nutritional status may affect allostatic load and disease duration due to their influences on these parameters (21). According to the present findings, 79.6% of participants had high-allostatic-load scores and 20.4% had low-allostatic-load scores, with mean values of 3.40.68 and 6.51.22. Seeman et al reported that having an allostatic load score >3 was associated with cardiovascular disease (22). In another study, high-allostaticload scores were found to be related to mortality (23). In a study of T2DM patients, it was found that the allostatic load mean value was 3.8 (5). Mattei et al showed that diabetes increased the risk of high allostatic load by 4.19-fold (24). In the present study, allostatic load
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Table 2 Daily consumption of food groups Food groups (g)
Allostatic load score
p
Male (n¼30)
Milk and dairy products Meat, fish and alternatives Legumes and oilseeds Grains Total fruit and vegetables Fruit Vegetables Fat
p
High allostatic load
Low allostatic load
259.4108.59 72.649.44 41.921.84 154.382.20 339.0217.14 148.1108.03 189.9160.43 25.88.38
289.4224.10 98.469.56 31.316.14 189.5114.06 411.814.12 82.567.60 329.3173.18 25.4120.20
Female (n¼73)
0.142 0.475 0.256 0.555 0.142 0.202 0.013* 0.256
p
High allostatic load
Low allostatic load
193.0141.89 60.744.58 31.918.77 151.981.62 352.4141.35 125.7106.39 226.7134.08 23.28.35
161.5106.56 53.050.48 32.919.06 159.9105.76 415.9160.03 67.864.38 348.2183.21 27.411.49
0.145 0.618 0.756 0.762 0.145 0.069 0.015* 0.914
Total (n¼103) High allostatic load
Low allostatic load
210.9136.37 63.845.93 34.520.00 152.581.27 348.5163.77 131.7106.63 216.6141.55 23.98.39
203.6171.61 70.361.09 32.315.60 171.2107.14 414.3150.46 73.464.34 341.0175.23 25.412.02
0.534 0.880 0.809 0.803 0.147 0.020* 0.010* 0.640
Note: Data expressed as mean standard deviation. * p<0.05 (Mann‒Whitney U test).
mean values were high, similar to previous studies, which may be related to the different health risks (5,24). In a study examining the relationship between allostatic load and socioeconomic status in men, it was found that participants with higher education level had low-allostatic-load scores (16). Seeman et al noted that low educational level and low income were associated with higher allostatic load scores (23). In our study, participants with the lower education also had higher allostatic load scores, as seen in previous studies (p<0.05; Table 1). We found that participants’ diabetes duration was 8.06.17 years. Diabetes duration may have effects on diabetic complications. The difference between diabetes duration and allostatic load was statistically significant and longer diabetes duration was associated with higher allostatic load scores (p<0.05). Diabetic complications occur unless the disease progression cannot be controlled. Accordingly, diabetes duration may affect allostatic load scores negatively. Inflammation-induced long-term allostasis adaptation in glucose and lipid homeostasis may result in impaired glucose metabolism and atherogenic dyslipidemia. These parameters are also components of metabolic syndrome. Furthermore, they have effects on energy metabolism and the immune system in the short term. Allostatic load is a risk factor with other lifestyle factors for metabolic syndrome (25). Nutrition is 1 of these lifestyle factors and nutritional status effects anthropometric measurements, biochemical parameters and allostatic load scores. In this study, in the high-allostatic-load group, fasting blood glucose, HbA1C, systolic blood pressure, CRP, cortisol levels, BMI, body fat percentage and waist/hip ratio Table 3 Logistic regression analysis showing relationship between fruit, vegetable and total fruit‒vegetable consumption and high-allostatic-load risk according to HbA1C Allostatic load
Regulated blood glucose (HbA1C <6.5%) Model I Fruit consumption (g) Model II Vegetable consumption (g) Model III Total fruit‒vegetable consumption (g) Unregulated blood glucose (HbA1C 6.5%) Model I Fruit consumption (g) Model II Vegetable consumption (g) Model III Total fruit‒vegetable consumption (g)
OR
95% CI
1.008
0.996‒1.019
Beta
0.008
0.986
0.976‒0.997
*
0.004
0.992
0.984‒1.000*
0.002
1.004
0.994‒1.014
0.004
0.996
0.992‒1.001
0.014
0.998
0.994‒1.002
0.008
CI, confidence interval; HbA1C, glycated hemoglobin; OR, odds ratio. * Adjusted by age and gender.
were above the reference values for biochemical parameters. In an earlier study, it was found that waist/hip ratio, fasting plasma glucose, cortisol and systolic blood pressure were also higher than the reference values and contributed to allostatic load (5). In another study, increased waist circumference, fasting blood glucose, cortisol and systolic blood pressure contributed to allostatic load scores (26). These parameters were found to be high in earlier studies and contributed to allostatic load, as in our study. Nutrition can also affect these parameters. We found that there were differences with regard to vegetable and fruit consumption. The beneficial effects of vegetables and fruits on biochemical parameters and anthropometric measurements have been reported previously (27). It is important to highlight the recommended consumption amounts for the various food groups to maintain healthy eating patterns and improve blood glucose and antioxidant capacity, which is important in prevention of oxidative stress and complications in diabetes (28). There have been few studies examining allostatic load and nutritional status, but 1 of them showed that increased fat consumption was associated with high-allostatic-load scores (9). In our study, according to food group consumption levels, the only statistically significant difference was seen in the dairy group, with men having higher consumption levels of dairy products (p<0.05). In addition, patients with higher vegetable and lower fruit consumption had lower allostatic load scores (p<0.05). The WHO states that fruit and vegetable consumption helps to maintain body weight; decreases the risk of T2DM, ischemic heart disease and stroke; and recommends at least 400 g (5 portions) of fruits and vegetables per day (29,30). However, consumption of vegetables and fruits, especially in the high-allostatic-load group, were lower (339.0217.14) than WHO recommendations. This relationship remained significant after regression analyses according to HbA1C levels, and lower vegetable and total fruit‒vegetable consumption increased the risk of high allostatic load in the regulated blood glucose group (OR, 0.992; 95% CI, 0.984 to 1.000; beta ¼ 0.002; Table 3). However, no statistical association was found for the unregulated blood glucose group. In a prospective study, the relationship between vegetable and fruit consumption was assessed, and there was no association with total consumption and risk of T2DM development; however, women who consumed green and yellow vegetables had a lower risk of T2DM development (31). In another study, allostatic load was significantly and negatively associated with self-reported dietary intakes of green/yellow vegetables (32). These results and the WHO recommendations highlight the importance of appropriate vegetable and fruit consumption levels for good health. Briefly, exposure to adverse experiences increases cumulative stress or allostasis. Stress increases inflammatory processes and induces behavioural maladaptations, such as overeating, binge
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eating, feelings of hunger or disinhibited eating and uncontrolled eating, which may contribute to development of T2DM (33). Other recent studies have addressed allostatic load with regard to psychiatric and neurologic complications (34,35). Thus, in this study we examined allostatic load in terms of T2DM. Conclusions To our knowledge, there has been no previous study evaluating the relationships between nutrition, T2DM and allostatic load. Our recommendations include: In T2DM patients with unregulated blood glucose, there are fluctuations in several parameters as well as HbA1C. Allostatic load provides an assessment that incorporates all these parameters. This measure may help to prevent or delay complications. In T2DM patients, vegetable and total fruit‒vegetable consumption have positive effects. Consumption of fruits and vegetables in the recommended amounts should be encouraged in these patients. In T2DM patients, further studies about food consumption are needed to assess the mechanisms between stress, allostatic load and level of fruit consumption. Limitations and strengths This study has both limitations and strengths. The limited number of studies investigating dietary habits and allostatic load makes it difficult to make comparisons. There are a limited number of studies on allostatic load and nutrition in the literature. For this reason, our study may offer a novel perspective. Author Disclosures Conflicts of interests: None. Author Contributions N.A.T. designed the study, M.S.M. collected the data, M.S.M. and N.A.T. drafted the results and the final manuscript and N.A.T. provided critical assessment and review. All authors had critical analysis input. References 1. Steptoea A, Hacketta RA, Lazzarinoa AI, et al. Disruption of multisystem responses to stress in type 2. Proc Natl Acad Sci 2014;111:15693e8. 2. Mori T, Karlamangla AS, Merkin SS, et al. Multisystem dysregulation and bone strength: Findings from the study of midlife in the United States. J Clin Endocrinol Metab 2014;99:1843e51. 3. Gallo LC, Jimenez JA. Allostatic load and the assessment of cumulative biological risk in biobehavioral medicine: Challenges and opportunities. Psychosom Med 2014;6:478e80. 4. Danese A, McEwen BS. Adverse childhood experiences, allostasis, allostatic load, and age-related disease. Physiol Behav 2012;106:29e39. 5. Carlsson AC, Andreasson N, Wandell PE. Poor self-rated health is not associated with a high total allostatic load in type 2 diabetic patientsdbut high blood pressure is. Diabetes Metabol 2011;37:446e51. lık Bakanlıg ı, 2008. 6. Pekcan G. Beslenme durumunun saptanmasi. Ankara: TC Sag 7. Logan JG, Barksdale DJ. Allostasis and allostatic load: Expanding the discourse on stress and cardiovascular disease. J Clin Nurs 2008;17:201e8. 8. Juster RP, McEwen BS, Lupien SJ. Allostatic load biomarkers of chronic stress and impact on health and cognition. Neurosci Biobehav Rev 2010;35:2e16.
9. Kim JY. Relationships between dietary habits and allostatic load index in metabolic syndrome patients. Korean J Fam Med 2013;34. 10. Erhardt J. Entwickelt an der Universität Hohenheim. The Nutritional Information Systems package program (BeBiS) 7.1. Stuttgart: Universität Hohenheim, 2010. lu Yayınevi, 2008:69e78. 11. Baysal A, Aksoy M, Besler HT, et al. Ankara: Hatipog 12. World Health Organization. BMI classification. http://appswhoint/bmi/ indexjsp?introPage¼intro_3html. Accessed May 15, 2017. 13. World Health Organization. Waist circumference and waist-hip ratio report of a WHO expert consultation. Geneva: WHO, 2008. 14. Mechanick JI. Metabolic mechanisms of stress hyperglycemia. Parenter Enteral Nutr 2006;30:157e63. 15. Rainisch BK, Upchurch DM. Sociodemographic correlates of allostatic load among a national sample of adolescents: Findings from the National Health and Nutrition Examination Survey, 1999-2008. J Adolesc Health 2013;53: 506e11. 16. Lipowicz A, Szklarska A, Malina RM. Allostatic load and socioeconomic status in Polish adult men. J Biosoc Sci 2014;46:155e67. 17. Geronimus AT, Hicken M, Keene D, Bound J. "Weathering" and age patterns of allostatic load scores among blacks and whites in the United States. Am J Clin Nutr 2006;96:826e33. 18. Juster RP, Sindi S, Marin MF, et al. clinical allostatic load index is associated with burnout symptoms and hypocortisolemic profiles in healthy workers. Psychoneuroendocrinology 2011;36:797e805. 19. Mattei J, Noel SE, Tucker KL. A meat, processed meat, and French fries dietary pattern is associated with high allostatic load in Puerto Rican older adults. J Am Diet Assoc 2011;111:1498e506. 20. World Health Organization. World Health Organization guidelines for the management of dyslipidaemia in patients with diabetes mellitus. Geneva: WHO, 2006. 21. Alberti KG, Zimmet PZ. Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: Diagnosis and classification of diabetes mellitus provisional report of a WHO consultation. Diabetic Med 1998;15. 22. Seeman T, Epel E, Gruenewald T, Karlamangla A, McEwen BS. Socio-economic differentials in peripheral biology: Cumulative allostatic load. Ann NY Acad Sci 2010;1186:223e39. 23. Seeman TE, McEwen BS, Rowe JW, Singer BH. Allostatic load as a marker of cumulative biological risk: MacArthur studies of successful aging. Proc Natl Acad Sci 2001;98:4770e5. 24. Mattei J, Demissie S, Falcon LM, Ordovas JM, Tucker K. Allostatic load is associated with chronic conditions in the Boston Puerto Rican Health Study. Soc Sci Med 2010;70. 25. Ruiz-Núñez B, Dijck-Brouwer DAJ, Muskiet FAJ. The relation of saturated fatty acids with low-grade inflammation and cardiovascular disease. J Nutr Biochem 2016;36:1e20. 26. Allsworth JE, Weitzen S, Boardman LA. Early age at menarche and allostatic load: data from the Third National Health and Nutrition Examination Survey. Ann Epidemiol 2005;15:438e44. 27. Oguntibeju OO, Truter EJ, Esterhuyse AJ. The role of fruit and vegetable consumption in human health and disease prevention. In: Ogintibeju OO, ed. Diabetes mellitus—insights and perspectives. Rijeka: InTech, 2013: 117e30. 28. Dierckx N, Horvath G, van Gils C, et al. Oxidative stress status in patients with diabetes mellitus: Relationship to diet. Eur J Clin Nutr 2003;57: 999e1008. 29. Fruit and vegetables for health: Report of a joint FAO/WHO workshop, 1-3 September, 2004, Kobe, Japan. Geneva: World Health Organization and Food and Agriculture Organization of the United Nations; 2005. Available at https://apps.who.int/iris/bitstream/handle/10665/43143/9241592818_eng. pdf?sequence=1&isAllowed=y. Accessed August 8, 2019. 30. World Health Organization. Healthy diet fact sheet. 2015. http://www.who. int/mediacentre/factsheets/fs394/en. Accessed May 15, 2019. 31. Liu S, Serdula M, Janket SJ, et al. A prospective study of fruit and vegetable intake and the risk of type 2 diabetes in women. Diabetes Care 2004;27. 32. Kusano Y, Crews DE, Iwamoto A, et al. Allostatic load differs by sex and diet, but not age in older Japanese from the Goto Islands. Ann Hum Biol 2016;43: 34e41. 33. Smith BE, Miles TP, Elkins J, Barkin JL, Ebell MH. The impact of stressful life events on the incidence of type 2 diabetes in U.S. adults from the Health and Retirement Study. J Gerontol B Psychol Sci Soc Sci (in press). 34. Bergera M, Justerd RP, Westhale S, et al. Allostatic load is associated with psychotic symptoms and decreases with antipsychotic treatment in patients with schizophrenia and first-episode psychosis. Psychoneuroendocrinology 2018;90:35e42. 35. Misiaka B, Kotowiczb K, Loskac O, et al. Decreased use of active coping styles contributes to elevated allostatic load index in first-episode psychosis. Psychoneuroendocrinology 2018;96:166e72.
Contents lists available at ScienceDirect
Canadian Journal of Diabetes journal homepage: www.canadianjournalofdiabetes.com
Original Research
Evaluation of Nutritional Status and Allostatic Load in Adult Patients With Type 2 Diabetes Melahat Sedanur Macit MSc a; Nilufer Acar-Tek PhD b, * a b
Faculty of Health Sciences, Department of Nutrition and Dietetics, Ondokuz Mayıs University, Samsun, Turkey Faculty of Health Sciences, Department of Nutrition and Dietetics, Gazi University, Ankara, Turkey
Key Messages
Measurement of allostatic load may help to prevent or delay type 2 diabetes mellitus complications. Allostatic load incorporates inflammatory, metabolic and cardiovascular system parameters. Recommended consumption levels of fruits and vegetables should be encouraged in type 2 diabetes mellitus patients. Additional food consumption research is needed to understand the relationships between stress, allostatic load and level of fruit consumption.
a r t i c l e i n f o
a b s t r a c t
Article history: Received 9 January 2019 Received in revised form 9 May 2019 Accepted 24 May 2019
Objective: Diabetes is a chronic disease, affected by nutritional status, and characterized by dysregulations in several systems. Allostatic load is an index that evaluates the dysregulation of all physiological and metabolic systems. This study was conducted to determine the relationship between nutritional status and allostatic load in patients with type 2 diabetes mellitus (T2DM). Methods: The study sample consisted of 30 males and 73 females between 20 and 55 years of age. Individuals had T2DM for 7.96.17 (mean standard deviation) years. World Health Organization criteria cutoffs were used to calculate allostatic load scores. Twelve parameters were questioned and an allostatic load score between 0 and 12 was obtained; values above the cutoff levels were assigned a value of 1, and values in the normal range were assigned a value of 0. Results: Individuals with high allostatic load comprised a significant portion of the sample (79.6%) for both males and females (73.3% and 82.2%, respectively). Longer diabetes duration was associated with high allostatic load score (p<0.05). There was lower vegetable consumption and higher fruit consumption in the high-allostatic-load group compared with the low-allostatic-load group (p<0.05). However, fruit consumption was still lower than recommended levels in both groups. Conclusions: A significant number of individuals had high allostatic load scores in our study. A healthy diet plan in line with the recommendations may help to decrease the allostatic load scores by reducing body weight, waist/hip ratio, blood pressure and fasting blood glucose, and may prevent the negative effects of stress on metabolic processes in the long-term malnutrition in T2DM. Ó 2019 Canadian Diabetes Association.
Keywords: allostasis allostatic load diabetes nutrition
Mots clés: allostasie charge allostatique diabète nutrition
r é s u m é Objectif : Le diabète est une maladie chronique, influencée par l’état nutritionnel et caractérisée par des dysrégulations de nombreux systèmes. La charge allostatique est un indice qui permet d’évaluer la dysrégulation de tous les systèmes physiologiques et métaboliques. Nous avons mené la présente étude pour déterminer la relation entre l’état nutritionnel et la charge allostatique des patients atteints du diabète sucré de type 2 (DST2).
* Address for correspondence: Nilufer Acar-Tek PhD, Faculty of Health Sciences, Department of Nutrition and Dietetics, Gazi University, Muammer Yas¸ar Bostancı St, Ankara 06500, Turkey. E-mail address: [email protected] 1499-2671/Ó 2019 Canadian Diabetes Association. The Canadian Diabetes Association is the registered owner of the name Diabetes Canada. https://doi.org/10.1016/j.jcjd.2019.05.011
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Méthodes : L’échantillon de la population étudiée était composé de 30 hommes et de 73 femmes entre 20 et 55 ans. Les individus avaient le DST2 depuis 7,9 6,17 (moyenne écart type) ans. Nous avons utilisé les seuils de l’Organisation mondiale de la santé pour calculer les scores de l’indice de charge allostatique. Pour les 12 paramètres pris en compte, un score de l’indice de charge allostatique entre 0 et 12 a été obtenu; les valeurs supérieures aux seuils se sont vu attribuer une valeur de 1, et les valeurs dans la fourchette normale se sont vu attribuer une valeur de 0. Résultats : Les individus qui avaient une charge allostatique élevée comptaient pour une part importante de l’échantillon (79,6 %) d’hommes et de femmes (73,3 % et 82,2 %, respectivement). Une durée plus longue du diabète a été associée à un score élevé de l’indice de charge allostatique (p < 0,05). Le groupe qui avait une charge allostatique élevée consommait moins de légumes et plus de fruits que le groupe qui avait une faible charge allostatique (p < 0,05). Toutefois, dans les 2 groupes, la consommation de fruits était toujours inférieure aux portions recommandées. Conclusions : Dans notre étude, un nombre important d’individus avaient des scores élevés de l’indice de charge allostatique. Un régime alimentaire sain conforme aux recommandations peut aider à diminuer les scores de l’indice de charge allostatique du fait de la réduction du poids corporel, du rapport taille/ hanches, de la pression artérielle et de la glycémie à jeun, et peut prévenir les effets négatifs du stress sur les processus métaboliques de la malnutrition à long terme lors de DST2. Ó 2019 Canadian Diabetes Association.
Introduction Type 2 diabetes mellitus (T2DM) has a complex pathophysiology, with complications such as beta-cell damage and insulin resistance (1). Stress-related factors may play a role in the etiology of T2DM and can affect the inflammatory, metabolic and cardiovascular systems. Lifestyle factors may also be involved in the relationship between stress and diabetes, as well as the psychobiological factors. Allostatic load, which evaluates the dysregulation of several systems, is a model that incorporates all parameters of the inflammatory, metabolic and cardiovascular systems that are important in terms of T2DM complications. Allostatic load assessment also clarifies the effects of chronic stress on health through a comprehensive approach (2,3). Chronic stress emerges with the release of corticotrophin hormone from the hypothalamus and causes physiological changes, which result in negative health outcomes (4). If there is long-term chronic activity or inactivity in the metabolism, allostasis and allostatic load occurs, with high blood pressure, high blood lipids, high catecholamine levels, low glycemic control, increased waist circumference and abnormal levels of cortisol. This may lead to chronic diseases, such as obesity, atherosclerosis and diabetes, and may worsen the progression of current diseases (5,6). Fasting blood glucose, glycated hemoglobin (HbA1C), total cholesterol, body mass index (BMI), waist/hip ratio, body fat percentage and blood pressure are the metabolic and cardiovascular system parameters involved in the evaluation of allostatic load (7). Diabetes is a major public health problem and higher levels of blood glucose pose a long-term risk for patients. In these patients, it is useful to assess all parameters as well as blood glucose to prevent development of diabetes complications. It is necessary to monitor cardiovascular, metabolic and allostatic load-related parameters in patients with diabetes. High blood pressure may cause hypertension and unregulated blood glucose may cause microvascular complications of diabetes. Therefore, a holistic approach that includes all metabolic criteria represents a useful tool in clinical assessment. All parameters of the allostatic load are closely associated with diabetes. Accordingly, evaluation of allostatic load in patients with diabetes provides comprehensive follow up for patients in the clinic (5). Allostatic load index may provide more accurate information on mortality and physical condition as compared with evaluating the parameters separately. This model ensures assessment of primary and secondary mediators in conjunction and reveals tertiary outcomes for patients at risk (8). Nutrition is an important factor as it has major effects on allostatic load parameters. Effects of eating habits, body composition
and tertiary outcomes of allostatic load are summarized in Figure 1. Environmental factors, including diet, also have effects on allostatic load. The allostatic load may occur in response to food preferences and eating habits, and high-allostatic-load scores may be associated with abdominal obesity, cardiovascular disease, hypertension and T2DM (9). Based on this background, we conducted a study to evaluate the relationship between nutritional status and allostatic load in patients with diabetes. Our hypotheses were as follows: Nutrition has several effects on body composition and biochemical parameters, and also on allostatic load. Consumption of food groups may affect allostatic load scores independently. Unregulated blood glucose may be a determinant for high allostatic load.
Methods This study was planned and conducted between May 2015 and December 2015 with a total of 103 patients, including 30 males and 73 females (20 to 55 years old) with diabetes at the Endocrinology and Metabolism Outpatient Clinic of Ondokuz Mayıs University Hospital. Pregnant/breastfeeding women, those with a different endocrine disease, those using drugs that affect cortisol level (etomidate, ketoconazole, estrogens) and those doing a sport that requires intense physical activity were excluded from the study. For this study, ethics approval was obtained from Gazi University (commission dated June 5, 2014, no. 77082166-604.01.0212551). In addition, necessary permission was obtained from the Department of Health Application and Research Center at Ondokuz Mayıs University to conduct the study at the Endocrinology and Metabolism Outpatient Clinic of Ondokuz Mayis University Hospital (dated May 21, 2014, issue 2251, no. 15374210-000). Data collection General characteristics (age, gender, marital status, etc), dietary habits, smoking and alcohol consumption of the participants were obtained with a questionnaire. Consequently, food consumption records were recorded for individuals for 3 days (2 weekdays, 1 day on weekend). Daily energy and nutrient intake were calculated with a nutrition information system (BeBis) (10).
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Figure 1. Nutritional status, eating patterns and other factors affecting allostatic load. BMI, body mass index; CRP, C-reactive protein; HDL, high-density lipoprotein; HbA1C, glycated hemoglobin.
Anthropometric measurements
Assessment of allostatic load
Body weight and body fat percentage measurements were measured with a portable device (Model SC 330 ST, Tanita, Tokyo, Japan) by bioelectrical impedance (BIA). Height was measured by using a stadiometer with the patient’s head aligned in the Frankfort horizontal plane (11). Waist and hip circumferences were measured by using nonstretch tape (6,11). BMI was calculated by dividing weight (in kilograms) by height (in meters) squared (11). Waist/hip ratio was calculated by dividing waist circumference by hip circumference (12,13).
For assessment of allostatic load, we obtained the following data: systolic and diastolic blood pressure for cardiovascular function, serum fasting blood glucose, BMI, waist/hip circumference, serum total cholesterol, serum high-density lipoprotein cholesterol (HDL-C), serum HbA1C levels, body fat percentage for metabolic function, serum C-reactive protein (CRP) and albumin for the inflammatory system and serum cortisol and dehydroepiandrosterone sulfate (DHEA-S) levels for the neuroendocrine system (14‒16). Allostatic load score was obtained by
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assigning a “1” or “0” value for the parameters listed earlier for cutoff points (8,9,17,18). One point was given for parameters above cutoff and 0 point for parameters below the cutoff, except for serum albumin and HDL-C. For these, 0 point was given for parameters above the cutoff and 1 point for parameters below the cutoff. Thus, an allostatic load score of between 0 and 12 points was obtained. If the patients were using antihyperlipidemic or antihypertensive drugs, 1 point was added to the total score regardless of blood pressure and blood lipid values. Scores between 0 and 4 were defined as “low allostatic load” and scores 4 were defined as “high allostatic load” (17,19). For selection of cutoff points, World Health Organization (WHO) metabolic syndrome criteria for fasting blood glucose (>126 mg/dL), serum HDL-C (<35 mg/dL for males, <39 mg/dL for females), blood pressure (systolic blood pressure >140 mmHg, diastolic blood pressure >90 mmHg), WHO classification for BMI (>30 kg/m2), WHO references for waist/hip ratio (>0.9 for males, >0.85 for females), body fat percentage (>25% for males, >35% for females), total cholesterol (>200 mg/dL) and HbA1C (>6.5%) were used (13,20,21). Ondokuz Mayis University Central Laboratory reference values were considered in the assessment of CRP (>3 mg/dL), albumin (<3.5 mg/dL), cortisol (>19.4 mg/dL) and DHEA-S (<85 mg/dL). Statistical analyses Statistical analyses were performed using SPSS version 16.0 (IBM SPSS, Armonk, New York, United States). Descriptive analyses were calculated using mean standard deviation and median interquartile range. Nominal variables are expressed as frequency and percent. Differences between groups were assessed using the chisquare test. Differences between means and significance level were evaluated according to parametric tests (t test or Mann‒Whitney U test). Statistical significance was set at p<0.05 (2-sided). Logistic regression models were performed for associations between allostatic load scores and vegetable‒fruit consumption (adjusted by age and gender) according to HbA1C levels. Vegetable, fruit and total vegetable‒fruit consumption were selected as predictors. Results A total of 79.6% of individuals had high-allostatic-load scores (73.3% of males and 82.2% of females, respectively; data not shown). In the low-allostatic-load group (allostatic load score, 0 to 4), the mean value of allostatic load was 3.40.68 for the total group, 3.60.74 for males and 3.30.63 for females. There was no statistically difference according to gender (p¼0.268). In the highallostatic-load group (allostatic load score, 4), the mean value of allostatic load was 6.51.22 for the total group, 6.62.44 for males and 6.41.08 for females. There was no statistically difference according to gender in the high-allostatic-load group (p¼0.918) (data not shown). Assessment of parameters according to allostatic load groups are presented in Table 1. There was no statistical difference between age and allostatic load (p>0.05). However, education level was positively associated and diabetes duration negatively associated with allostatic load (p<0.05). Serum fasting blood glucose, BMI, body fat percentage, HbA1C, systolic blood pressure, CRP and cortisol were statistically significantly higher in the high-allostaticload group (p<0.05). Waist/hip ratio mean values were higher in females in the high-allostatic-load group (p>0.05). Consumption rates of the various food groups in the high- and low-allostatic-load groups are shown in Table 2. Vegetable consumption was higher in the low-allostatic-load group (341.0175.23 g/day) than in the high-allostatic-load group (216.6141.55 g/day) (p<0.05). However, mean fruit consumption
Table 1 Biomarkers according to allostatic load Biomarkers Age (year) Education level (year) Diabetes duration (year) Metabolic biomarkers Fasting blood glucose (mg/dL) Body mass index (kg/m2) Body fat (%) Waist/hip ratio Male Female Total cholesterol (mg/dL) HDL cholesterol (mg/dL) Male Female HbA1C (%) Cardiovascular biomarkers Systolic blood pressure (mmHg) Diastolic blood pressure (mmHg) Inflammatory biomarkers CRP (mg/dL) Albumin (mg/dL) Neuroendocrine biomarkers Cortisol (mg/dL) DHEA-S (mg/dL)
High allostatic load (4)
Low allostatic load (<4)
p value
47.14.34 6.84.30 8.66.46
43.89.69 10.14.88 5.33.93
0.406 0.020* 0.031*
155.550.27 35.07.45 36.88.67
126.252.13 27.83.67 27.58.02
0.001y 0.000y 0.000y
1.00.10 0.90.07 187.636.80
1.00.06 0.90.08 178.821.86
0.662 0.025* 0.203
43.99.98 49.310.62 7.71.55
46.94.13 45.712.93 6.81.64
0.420 0.327 0.000y
139.917.25 85.110.79
129.512.69 83.911.02
0.007y 0.730
7.28.22 4.50.41
4.01.61 4.60.27
0.001y 0.235
14.38.81 169.064.04
11.63.26 190.164.04
0.043* 0.469
CRP, C-reative protein; DHEA-S, dehydroepiandrosterone sulfate; HbA1C, glycated hemoglobin; HDL, high-density lipoprotein. Note: Data expressed as mean standard deviation. * p<0.05 (Mann‒Whitney U test). y p<0.01 (Mann‒Whitney U test).
was higher in the high-allostatic-load group (131.7106.63 g/day) than in the low-allostatic-load group (73.464.34 g/day) (p<0.05). There was no statistically significant difference between allostatic load and consumption of milk and dairy products; meat, fish and alternatives; legumes and oilseeds; and grains (p>0.05). Vegetable and fruit consumption have found to be associated with allostatic load scores (Table 2). Therefore, a logistic regression model was used to assess the effects of fruit and vegetable consumption on allostatic load for the groups with regulated and unregulated blood glucose (Table 3). Vegetable consumption (odds ratio [OR], 0.986; 95% confidence interval [CI], 0.976 to 0.997) and total vegetable‒fruit consumption (OR, 0.992; 95% CI, 0.976 to 0.997), but not fruit consumption (1.008; 95% CI, 0.996 to 1.019), demonstrated lowering effects on allostatic load in individuals with HbA1C values <6.5%. However, there was no statistically significant effect for vegetable, fruit and total vegetable‒fruit consumption in individuals with HbA1C values >6.5%. Discussion Allostatic load is a multisystem assessment that includes metabolic, anthropometric, cardiovascular, inflammatory and neuroendocrine parameters. Diabetes is a major chronic disease with a number of complications, which includes the parameters above. Nutritional status may affect allostatic load and disease duration due to their influences on these parameters (21). According to the present findings, 79.6% of participants had high-allostatic-load scores and 20.4% had low-allostatic-load scores, with mean values of 3.40.68 and 6.51.22. Seeman et al reported that having an allostatic load score >3 was associated with cardiovascular disease (22). In another study, high-allostaticload scores were found to be related to mortality (23). In a study of T2DM patients, it was found that the allostatic load mean value was 3.8 (5). Mattei et al showed that diabetes increased the risk of high allostatic load by 4.19-fold (24). In the present study, allostatic load
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Table 2 Daily consumption of food groups Food groups (g)
Allostatic load score
p
Male (n¼30)
Milk and dairy products Meat, fish and alternatives Legumes and oilseeds Grains Total fruit and vegetables Fruit Vegetables Fat
p
High allostatic load
Low allostatic load
259.4108.59 72.649.44 41.921.84 154.382.20 339.0217.14 148.1108.03 189.9160.43 25.88.38
289.4224.10 98.469.56 31.316.14 189.5114.06 411.814.12 82.567.60 329.3173.18 25.4120.20
Female (n¼73)
0.142 0.475 0.256 0.555 0.142 0.202 0.013* 0.256
p
High allostatic load
Low allostatic load
193.0141.89 60.744.58 31.918.77 151.981.62 352.4141.35 125.7106.39 226.7134.08 23.28.35
161.5106.56 53.050.48 32.919.06 159.9105.76 415.9160.03 67.864.38 348.2183.21 27.411.49
0.145 0.618 0.756 0.762 0.145 0.069 0.015* 0.914
Total (n¼103) High allostatic load
Low allostatic load
210.9136.37 63.845.93 34.520.00 152.581.27 348.5163.77 131.7106.63 216.6141.55 23.98.39
203.6171.61 70.361.09 32.315.60 171.2107.14 414.3150.46 73.464.34 341.0175.23 25.412.02
0.534 0.880 0.809 0.803 0.147 0.020* 0.010* 0.640
Note: Data expressed as mean standard deviation. * p<0.05 (Mann‒Whitney U test).
mean values were high, similar to previous studies, which may be related to the different health risks (5,24). In a study examining the relationship between allostatic load and socioeconomic status in men, it was found that participants with higher education level had low-allostatic-load scores (16). Seeman et al noted that low educational level and low income were associated with higher allostatic load scores (23). In our study, participants with the lower education also had higher allostatic load scores, as seen in previous studies (p<0.05; Table 1). We found that participants’ diabetes duration was 8.06.17 years. Diabetes duration may have effects on diabetic complications. The difference between diabetes duration and allostatic load was statistically significant and longer diabetes duration was associated with higher allostatic load scores (p<0.05). Diabetic complications occur unless the disease progression cannot be controlled. Accordingly, diabetes duration may affect allostatic load scores negatively. Inflammation-induced long-term allostasis adaptation in glucose and lipid homeostasis may result in impaired glucose metabolism and atherogenic dyslipidemia. These parameters are also components of metabolic syndrome. Furthermore, they have effects on energy metabolism and the immune system in the short term. Allostatic load is a risk factor with other lifestyle factors for metabolic syndrome (25). Nutrition is 1 of these lifestyle factors and nutritional status effects anthropometric measurements, biochemical parameters and allostatic load scores. In this study, in the high-allostatic-load group, fasting blood glucose, HbA1C, systolic blood pressure, CRP, cortisol levels, BMI, body fat percentage and waist/hip ratio Table 3 Logistic regression analysis showing relationship between fruit, vegetable and total fruit‒vegetable consumption and high-allostatic-load risk according to HbA1C Allostatic load
Regulated blood glucose (HbA1C <6.5%) Model I Fruit consumption (g) Model II Vegetable consumption (g) Model III Total fruit‒vegetable consumption (g) Unregulated blood glucose (HbA1C 6.5%) Model I Fruit consumption (g) Model II Vegetable consumption (g) Model III Total fruit‒vegetable consumption (g)
OR
95% CI
1.008
0.996‒1.019
Beta
0.008
0.986
0.976‒0.997
*
0.004
0.992
0.984‒1.000*
0.002
1.004
0.994‒1.014
0.004
0.996
0.992‒1.001
0.014
0.998
0.994‒1.002
0.008
CI, confidence interval; HbA1C, glycated hemoglobin; OR, odds ratio. * Adjusted by age and gender.
were above the reference values for biochemical parameters. In an earlier study, it was found that waist/hip ratio, fasting plasma glucose, cortisol and systolic blood pressure were also higher than the reference values and contributed to allostatic load (5). In another study, increased waist circumference, fasting blood glucose, cortisol and systolic blood pressure contributed to allostatic load scores (26). These parameters were found to be high in earlier studies and contributed to allostatic load, as in our study. Nutrition can also affect these parameters. We found that there were differences with regard to vegetable and fruit consumption. The beneficial effects of vegetables and fruits on biochemical parameters and anthropometric measurements have been reported previously (27). It is important to highlight the recommended consumption amounts for the various food groups to maintain healthy eating patterns and improve blood glucose and antioxidant capacity, which is important in prevention of oxidative stress and complications in diabetes (28). There have been few studies examining allostatic load and nutritional status, but 1 of them showed that increased fat consumption was associated with high-allostatic-load scores (9). In our study, according to food group consumption levels, the only statistically significant difference was seen in the dairy group, with men having higher consumption levels of dairy products (p<0.05). In addition, patients with higher vegetable and lower fruit consumption had lower allostatic load scores (p<0.05). The WHO states that fruit and vegetable consumption helps to maintain body weight; decreases the risk of T2DM, ischemic heart disease and stroke; and recommends at least 400 g (5 portions) of fruits and vegetables per day (29,30). However, consumption of vegetables and fruits, especially in the high-allostatic-load group, were lower (339.0217.14) than WHO recommendations. This relationship remained significant after regression analyses according to HbA1C levels, and lower vegetable and total fruit‒vegetable consumption increased the risk of high allostatic load in the regulated blood glucose group (OR, 0.992; 95% CI, 0.984 to 1.000; beta ¼ 0.002; Table 3). However, no statistical association was found for the unregulated blood glucose group. In a prospective study, the relationship between vegetable and fruit consumption was assessed, and there was no association with total consumption and risk of T2DM development; however, women who consumed green and yellow vegetables had a lower risk of T2DM development (31). In another study, allostatic load was significantly and negatively associated with self-reported dietary intakes of green/yellow vegetables (32). These results and the WHO recommendations highlight the importance of appropriate vegetable and fruit consumption levels for good health. Briefly, exposure to adverse experiences increases cumulative stress or allostasis. Stress increases inflammatory processes and induces behavioural maladaptations, such as overeating, binge
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eating, feelings of hunger or disinhibited eating and uncontrolled eating, which may contribute to development of T2DM (33). Other recent studies have addressed allostatic load with regard to psychiatric and neurologic complications (34,35). Thus, in this study we examined allostatic load in terms of T2DM. Conclusions To our knowledge, there has been no previous study evaluating the relationships between nutrition, T2DM and allostatic load. Our recommendations include: In T2DM patients with unregulated blood glucose, there are fluctuations in several parameters as well as HbA1C. Allostatic load provides an assessment that incorporates all these parameters. This measure may help to prevent or delay complications. In T2DM patients, vegetable and total fruit‒vegetable consumption have positive effects. Consumption of fruits and vegetables in the recommended amounts should be encouraged in these patients. In T2DM patients, further studies about food consumption are needed to assess the mechanisms between stress, allostatic load and level of fruit consumption. Limitations and strengths This study has both limitations and strengths. The limited number of studies investigating dietary habits and allostatic load makes it difficult to make comparisons. There are a limited number of studies on allostatic load and nutrition in the literature. For this reason, our study may offer a novel perspective. Author Disclosures Conflicts of interests: None. Author Contributions N.A.T. designed the study, M.S.M. collected the data, M.S.M. and N.A.T. drafted the results and the final manuscript and N.A.T. provided critical assessment and review. All authors had critical analysis input. References 1. Steptoea A, Hacketta RA, Lazzarinoa AI, et al. Disruption of multisystem responses to stress in type 2. Proc Natl Acad Sci 2014;111:15693e8. 2. Mori T, Karlamangla AS, Merkin SS, et al. Multisystem dysregulation and bone strength: Findings from the study of midlife in the United States. J Clin Endocrinol Metab 2014;99:1843e51. 3. Gallo LC, Jimenez JA. Allostatic load and the assessment of cumulative biological risk in biobehavioral medicine: Challenges and opportunities. Psychosom Med 2014;6:478e80. 4. Danese A, McEwen BS. Adverse childhood experiences, allostasis, allostatic load, and age-related disease. Physiol Behav 2012;106:29e39. 5. Carlsson AC, Andreasson N, Wandell PE. Poor self-rated health is not associated with a high total allostatic load in type 2 diabetic patientsdbut high blood pressure is. Diabetes Metabol 2011;37:446e51. lık Bakanlıg ı, 2008. 6. Pekcan G. Beslenme durumunun saptanmasi. Ankara: TC Sag 7. Logan JG, Barksdale DJ. Allostasis and allostatic load: Expanding the discourse on stress and cardiovascular disease. J Clin Nurs 2008;17:201e8. 8. Juster RP, McEwen BS, Lupien SJ. Allostatic load biomarkers of chronic stress and impact on health and cognition. Neurosci Biobehav Rev 2010;35:2e16.
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