J Endocrinol Invest DOI 10.1007/s40618-014-0102-9

ORIGINAL ARTICLE

Low-grade inflammation in overweight and obese adults is affected by weight loss program ˇ ernelicˇ-Bizjak • Ana Petelin • Mojca Bizjak • Masˇa C Mihaela Jurdana • Tadeja Jakus • Zala Jenko-Prazˇnikar

Received: 31 March 2014 / Accepted: 21 May 2014 Ó Italian Society of Endocrinology (SIE) 2014

Abstract Purpose Low-grade systemic inflammation due to obesity is considered to be the key link between obesity and obesity-related disorders. The hypothesis was tested that significant alterations in inflammatory markers and adipokines would occur over a multidisciplinary intervention and that these changes might also be important for improvement of cardiovascular risk factors. Methods Thirty-tree overweight adults completed a 6-month multidisciplinary intervention program to evaluate the effects of a personalized dietary program based on the individual’s resting metabolic rate (RMR) on anthropometric parameters, aerobic and anaerobic capabilities, metabolic profile, inflammation, and body image satisfaction. Body composition, physical activity, anaerobic capabilities, RMR, metabolic profile, and low-grade inflammation were measured. Diet composition and body image dissatisfaction were also assessed. Results After 6 months of multidisciplinary intervention the participants showed significantly decreased body weight, waist circumference (WC), and the inflammatory markers tumor necrosis factor-a, C-reactive protein, and visfatin. They also showed increased anti-inflammatory adiponectin and consequently decreased serum insulin, HOMA-IR, and total cholesterol. The important findings of the study were that reduction of sugars and saturated fatty acids in the diet, coupled with an increase in exercise, significantly correlated with reduction of WC and body mass index. In addition, positive correlations between D

A. Petelin
M. Bizjak
M. Cˇernelicˇ-Bizjak
M. Jurdana
T. Jakus
Z. Jenko-Prazˇnikar (&) Faculty of Health Sciences, University of Primorska, Polje 42, SI-6310 Izola, Slovenia e-mail: [email protected]

BMI, D WC, D trunk fat, inflammation, and cardiovascular risk factors were demonstrated. Conclusions Weight loss in combination with increased physical activity, a negative energy balance, and diet adjustment was associated with lower inflammation and consequently with lower cardiovascular risk factors. Keywords Interdisciplinary intervention
Obesity
Weight loss
Adipokines
Inflammation

Introduction The obese state is associated with low-grade inflammation and adipocytes themselves play an important role in this process by releasing many pro-inflammatory cytokines, such as tumor necrosis factor-a (TNF-a), visfatin, interleukin-6 (IL-6), and anti-inflammatory adiponectin [1]. Indeed, the higher concentrations of pro-inflammatory mediators in obese people are now believed to have a potential role in the pathogenesis of disorders ranging from insulin resistance, type 2 diabetes mellitus, fatty liver disease, to cardiovascular diseases (CVD) [2, 3]. Much research has been performed in recent years to identify the most effective treatment for adult overweight and obesity with the intention of restoring the inflammatory state in obese subjects. As obesity is a multifactorial disease, for an effective weight loss intervention, a multidisciplinary team is required [4]. Moreover, individual interventions are significantly more effective than weight loss group programs [5]. The first step in weight loss intervention is to achieve a negative energy balance. Very low-energy diets (3,360 kJ/800 kcal or less) are not successful because they are frequently followed by weight regain [6]. However, Casazza et al. [7] have highlighted the

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J Endocrinol Invest Fig. 1 Flow diagram for participant’s recruitment and attrition rate

controversy regarding the certainty with which very lowcalorie diets are followed by weight gain. Key factors in the problem of weight regain are adaptation of energy metabolism, especially resting metabolic rate (RMR), nonexercise thermogenesis, and diet-induced thermogenesis [8]. Therefore, measurement of an individual’s RMR is crucial to determine his or her energy needs before and during the weight loss program [9, 10]. In addition, a negative energy balance can also be achieved by increasing regular physical activity. Most studies reported significant reduction in body mass, body fat, and abdominal adiposity and blood lipids after physical exercise [11, 12]. Moreover, regular physical activity also improves glucose homeostasis and insulin sensitivity, coronary blood flow and cardiac function, enhances endothelial function, and reduces blood pressure [13]. Besides diet and physical activity, psychological factors may also play an important role in a weight loss program. Recently, it has been shown that long-term interdisciplinary therapy is effective in controlling the physiological aspects and psychological well-being in obese patients [14]. However, despite these promising results, few studies have addressed the effects of long-term multidisciplinary intervention on pro- and anti-inflammatory cytokine levels [15, 16]. In the light of the above, the aim of the study was to discover the effect of a 6-month multidisciplinary intervention, including an individual dietary program based on the person’s RMR, on physical aspects, inflammation, metabolic profile, and body image dissatisfaction in overweight and obese subjects. The hypothesis was put forward that significant alterations in inflammatory markers and adipokines would occur over the course of the multidisciplinary intervention and

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that these changes might also be important for improvement of cardiovascular risk factors.

Methods and materials Study design This retrospective study was conducted in 2012 at the Faculty of Health Sciences, University of Primorska, Izola, Slovenia. Subjects who fulfilled the following inclusion criteria and passed the baseline physical examination were included in the intervention group (Fig. 1): (1) body mass index (BMI) higher than 25 and lower than 35; (2) aged 25–49; (3) healthy with no metabolic, cardiovascular, endocrine, and acute or chronic inflammatory diseases; (4) not taking medication for lipid metabolism; (5) women in fertility period; (6) reporting a stable weight within the previous 3 months. The participants were evaluated at baseline and after the 6-month multidisciplinary intervention. The protocols and procedures of this study were in agreement with the ethical guidelines on biomedical research on human subjects and the study was approved by the national ethical committee. Informed consent was obtained from all subjects. Measurements Resting metabolic rate A hand-held indirect calorimeter (MedGemÒ Microlife) from Medical Home Solutions, Inc., Golden, CO, was used for measuring RMR. All RMR measurements were

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performed between 7 a.m. and 8 a.m., after 8 h of sleep. Measurements were carried out after auto calibration of the device in a quiet thermo-neutral environment (20–22 °C). Anthropometric measurements All measurements were performed between 7 a.m. and 9 a.m. in standardized conditions by the same examiner after fasting overnight. At the study site height, weight, and waist circumference were measured using a standardized protocol. Subject height was measured to the nearest 0.1 cm in a standing position, without shoes, using leicester height measure (Invicta Plastics Limited, Oadby, England). Body weight of the participants wearing usual light indoor clothing without shoes was measured with a 0.1-kg precision. Waist was measured in standing position halfway between costal edge and iliac crest, whereas hip was measured as the greatest circumference around the buttocks. BMI was calculated using the following formula: weight (kg)/height (m2). Body composition [total percentage body fat (% BF) and percentage trunk fat (% TF)] were assessed by using bioelectrical impedance analysis (BIA) Tanita BC 418MA (Tanita Corporation, Arlington Heights, IL) and data analyzed with the software provided by the same producer. Aerobic and anaerobic capabilities To assess muscle capabilities subjects performed the extensor and flexor endurance test as previously described [17]. Briefly, to measure back extensor endurance, participants laid prone with the lower body fixed to the test bed and the upper body extended in a cantilevered fashion over the edge of the test bench. Participants maintained their position at 0° of lumbar flexion. The flexor endurance test required participants to sit on the test table and place the upper body at an angle of 60° from the table. The trial was initiated with a 2-min resting baseline, and the endurance time was manually recorded in seconds. Physical activity was estimated using information based on a questionnaire which included types and durations of activities for every day. Physical activity in metabolic equivalent tasks (METs) per week was computed from the data on specific activities within the corresponding categories in a physical activity compendium [18]. MET was defined as the ratio of work metabolic rate to a standard resting metabolic rate of 1 kcal/kg/h. Body image evaluation or (dis)satisfaction Body satisfaction (a subjective parameter of body image) was assessed as a cognitive aspect of a person’s concept about his/her body. We used three items that focused on the

most relevant aspects for the particular appearance concerns of obese individuals, and that have been used in previous studies [19, 20]. Participants answered questions on satisfaction, which were to be answered according to a 5-point response scale ranging from 1 (completely satisfied) to 5 (not at all), such that higher scores indicated greater dissatisfaction. Serum analyses Venous blood samples for biochemical and hormonal determinations were collected in the fasting state in the morning between 7 a.m. and 9 a.m. (in standardized conditions) in 4 mL vacuum test tubes (Beckton-Dickinson, Rutherford, USA). Serum was immediately separated, frozen, and stored at -20 °C until subsequent analysis. The biochemical analyses have already been described [17, 21]. Serum concentrations of adiponectin, resistin, visfatin, IL6, and TNF-a were performed in duplicate on a microplate reader (Tecan, Ma¨nnedorf, Switzerland) using human ELISA Kits for adiponectin and resistin (BioVendor, Lab. Med. Inc., Brno, Czech Republic), visfatin (BioVision, Mountain View, CA, USA), IL-6, and TNF-a (both Thermo Fischer Scientific Inc., Rockford, USA). Assay sensitivity was 30 pg/mL for visfatin, 10 pg/mL for adiponectin, 33 pg/mL for resistin, \1 pg/mL for IL-6 and \2 pg/mL for TNF-a. Serum concentrations of glucose, triglycerides (TG), total cholesterol, low-density lipoprotein (LDL cholesterol), high-density lipoprotein (HDL cholesterol), and C-reactive protein (CRP) were measured using Olympus reagents and performed on an AU 680 analyzer (Beckman Coulter). Serum insulin concentrations were measured using Abbott reagents and performed on a 2000 iSR analyzer (Abbott Architect). The homeostasis model assessment (HOMA) was used as a measure of insulin resistance (HOMA-IR) and b cell function (HOMA-b). HOMA-IR was calculated as [insulin (mU/L) 9 glucose (mmol/L)]/22.5, and HOMA-b as [20 9 insulin (mU/L)/(glucose (mmol/L) - 3.5)] [22]. Food record The week before blood samples were taken for biochemical analyses, subjects were asked to record their food intake for three consecutive days (2 weekdays and 1 day during the weekend). Where possible, subjects were asked to include food labels and recipes for mixed dishes and were encouraged to avoid any alterations to their normal diet. All food records (FR) were checked and completed by dieticians if unclear descriptions or a lack of data became evident. Nutrient composition was analyzed using the open platform for clinical nutrition (OPEN) program that is accessible through the website http://opkp.si/. Data from

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J Endocrinol Invest Table 1 Examples of breakfast containing 1,440 kJ (343 kcal), which is part of a 6,300 kJ (1,500 kcal) individual diet plan

Intervention

Meal

Food group

Food

Quantity

Diet plan intervention in small groups, in-person training, and individual diet plan intervention

Breakfast

Milk and fermented milk

Semi-skimmed milk (1.3–1.6 % of milk fat), yogurt, fermented milk (1.3–1.6 % milk fat), kefir with less fat, soured milk with less fat

2 dl

Buttermilk, soya drink Skimmed-milk powder

2.5 dl 20 g

Melons, strawberries, quinces, raspberries, blackberries, cranberries, watermelon (without rind), redcurrants

250 g

Mandarins, oranges Pineapple (peeled), gages, pears, apples, kiwis, mulberries, medlars (flesh only), plums, peaches

200 g 150 g

Blueberries, grapes, mango (without rind), cherries, nectarines, figs

100 g

Banana (peeled), pomegranate (flesh only), persimmons

80 g

Fruit

Starchy food

Fat and fatty foods

Plums dry-without stone

35 g

Dates, dried figs, apple slices, raisins, dried apricots-pitted

25 g

Juice pressed from fresh fruit with no added sugar

1.5 dl

Black, white, semi-white, graham, corn, rye, whole wheat, buckwheat, oatmeal bread

60 g

Rusks, crackers, oat flakes, barley flakes, corn flakes, millet flakes, wheat flakes, muesli, bran, wheat middlings, rye flakes, corn meal, millet porridge

40 g

Sweet flakes

30 g

Butter, margarine Peanuts, hazelnuts, almonds, walnuts, sesame seeds, sunflower pits, pumpkin seeds, flax seeds, and various vegetable spreads for bread

6g 10 g

Avocado, sour cream

25 g

Olives

40 g

Exercise regime Within the intervention, subjects were invited to a guided exercise program which included exercises for improvement of muscle function and strength and a Nordic walking course. The subjects also received a brochure with detailed instructions and recommendations for daily training. Psychological assistance

The subjects were advised to choose one food from each food group to create their own menu. For example, breakfast can include 2 dl of yogurt with 1.3 % of fat, 100 g of figs, 40 g of corn flakes, and 10 g of almonds

FRs were automatically converted into energy intake and nutrients, namely protein, carbohydrates, fiber, total fatty acid, saturated fatty acid (SFA), monounsaturated fatty acid (MUFA), and polyunsaturated fatty acid (PUFA).

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After data collection at baseline, all subjects attended two educational sessions (2 h) about healthy diet, nutritional composition; correct timing of eating and about the beneficial effects of daily vegetable and fruit eating. Each group included 6–7 subjects. In addition, all subjects attended two sessions of individual education about their prescribed individual diet plan (each subject was given a personalized diet plan). To estimate total energy needs, individual RMR (person’s RMR) measured from indirect calorimeter was multiplied by the appropriate activity factor (from 1.3 to 1.6), and then the reduction of 500 kcal for all participants was made, except for two female participants who had very low RMR. In those two subjects the restriction of 250 kcal per day was made. Planned macronutrients were 15–17 % of energy from proteins, 25–30 % of energy from fat, and more than 50 % of energy from carbohydrates. Dietary fat composition was \10 % of SFA, at least 10 % of MUFA and 5 % of PUFA. They received a list of foods for each meal and the quantity of food in grams to choose from (Table 1). No drugs or antioxidants were recommended. All subjects had three weight checking and RMR measurements during intervention when the diet plan was adjusted. Throughout the intervention, subjects had the opportunity to attend extra in person, telephone or e-mail consultations, if they needed them.

In addition, an individual appointment with a psychologist was offered to all subjects. The purpose of this assistance was to give nondirective support and information (education) about any question in relation to emotions, emotional eating, overeating, and negative thoughts relating to coping with dieting. Statistical analysis All analyses were carried out using the SPSS statistics version 20.0 (IBM, Chicago, IL). First, data were checked for

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normality; data not normally distributed were transformed using log conversions. Means and standard deviation of the mean were determined at both baseline and after 6 months of intervention for all parameters. Analysis of the effect of intervention on the variables was conducted using Student’s paired t test. These analyses were performed on 6-month outcomes of body composition, dietary intake, physical capabilities, body satisfaction, metabolic profile, and Table 2 Baseline characteristics of 33 subjects

Characteristics

Mean ± SD

Gender (n)

F, female; M, male; n, number of subjects Table 3 Anthropometric, psychological, biochemical, and physical characteristics of the participants, before and after 6 month of intervention

F

20

M

13

adipokines. Associations among the variables were examined using Pearson correlations. Statistical significance was defined as p \ 0.05. Furthermore, hierarchical approach was performed. At the first step reduction of energy intake and increase in physical activity were entered. In the second step some variables (reduction in sugars, SFA) were entered to see if any of these variables make an additional contribution to the prediction of reduction of TF and/or inflammation. At last step improvement of anaerobic capabilities was entered. Two hierarchical multiple regression analyses were performed to examine the effects of study variables on the level of reduction of TF and inflammation biomarker, measured with CRP.

Age (years)

38.9 ± 6.5

Overweight/ obese (n)

20/13

Results

Metabolic syndrome (n)

9

The baseline descriptive characteristics of all subjects who participated in the 6-month intervention program are

Variable

Before/after intervention (M) Mean ± SD

Before/after intervention (F) %

Mean ± SD

%

Anthropometric parameters Weight (kg)

96.4 ± 8.1/92.3 ± 8.1**

-4

80.1 ± 9.1/77.0 ± 8.9**

-4

BMI (kg/m2) WC (cm)

29.8 ± 2.8/28.5 ± 2.6** 100.7 ± 6.7/95.2 ± 7.7***

-4 -5

29.1 ± 2.7/28.2 ± 2.6** 91.7 ± 7.3/88.2 ± 7.6*

-3 -4

HC (cm)

106.4 ± 4.4/102.5 ± 5.3***

-4

106.9 ± 9.6/103.7 ± 7.9*

-3

Fat mass (%)

24.2 ± 3.5/22.8 ± 4.8*

-6

38.2 ± 3.1/36.9 ± 3.6**

-3

SBP (mmHg)

139.2 ± 14.4/121.9 ± 12.7***

-12

122.9 ± 16.6/110.5 ± 15.3**

-10

Aerobic and anaerobic capabilities MET/day

2.4 ± 2.2/3.5 ± 2.1*

?46

2.9 ± 2.1/3.3 ± 2.3*

?14

LPET (s)

87.5 ± 24.6/110.0 ± 11.5***

?26

66.6 ± 37.4/95.3 ± 32.2**

?43

TMET (s)

47.6 ± 34.7/89.9 ± 26.0***

?89

26.0 ± 26.8/49.1 ± 31.1**

?89

3.6 ± 0.9/3.2 ± 0.8

-11

4.1 ± 1.0/3.4 ± 1.4*

-17

Glucose (mmol/L)

5.6 ± 0.3/4.4 ± 1.1**

-21

5.1 ± 0.4/4.6 ± 0.7*

-10

Insulin (mU/L)

11.0 ± 5.2/8.2 ± 3.4**

-25

8.2 ± 3.2/7.6 ± 2.8*

-7

HOMA-IR

2.7 ± 1.4/1.6 ± 0.8**

-41

1.9 ± 0.8/1.5 ± 0.6*

-21

TG (mmol/L)

1.7 ± 0.9/1.7 ± 1.2

1.3 ± 0.7/1.4 ± 1.2

?8

TG (mmol/L)a TC (mmol/L)

1.6(0.6–4.1)/1.1(0.6–4.5) 5.7 ± 1.0/5.2 ± 1.0*

Psychological factors Body dissatisfaction Metabolic profile

BMI body mass index, CRP C-reactive protein, F female, HOMA-IR homeostasis model assessment of insulin resistance, IL-6 interleukin-6, LPET lumbar paraspinal endurance time, M men, MET metabolic equivalent task, SBP systolic blood pressure, TC total cholesterol, TG triglycerides, TMET trunk muscle endurance time, TNF-a tumor necrosis factor-alpha *** p \ 0.001, ** p \ 0.01, * p \ 0.05 a

The data for TG is shown as median and range

HDL-C (mmol/L) LDL-C (mmol/L)

1.2 ± 0.2/1.2 ± 0.2 3.7 ± 0.9/3.4 ± 0.8*

0

1.1(0.5–3.6)/1.1(0.4–4.1) 5.9 ± 1.1/5.5 ± 0.9**

-7

0

1.4 ± 0.3/1.3 ± 0.3*

-7

-8

3.9 ± 0.9/3.6 ± 0.7*

-8

-14

3.6 ± 1.8/2.4 ± 1.7**

-33

-49

-9

Adipokines and inflammation markers CRP (mg/L)

2.2 ± 1.8/1.9 ± 1.9*

TNF-a (pg/mL)

5.1 ± 3.4/2.6 ± 3.5**

5.4 ± 4.2/3.6 ± 3.4***

-33

IL-6 (pg/mL)

2.7 ± 1.3/5.6 ± 3.7

?107

3.2 ± 1.3/3.7 ± 2.3

?16

Adiponectin (lg/mL)

3.9 ± 2.1/4.4 ± 1.3

?13

5.0 ± 2.9/5.9 ± 2.2*

?18

Visfatin (pg/mL)

3.1 ± 1.1/1.1 ± 0.7**

-64

3.9 ± 1.2/1.6 ± 1.0*

-59

Resistin (lg/mL)

7.9 ± 2.2/7.7 ± 2.1

-3

7.9 ± 2.9/7.5 ± 2.7

-5

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J Endocrinol Invest Table 4 Diet characteristics of the participants, before and after 6 months of intervention

Variable

Before/after intervention (M) Mean ± SD

Before/after intervention (F) %

Mean ± SD

%

5,865 ± 1,067/5,458 ± 1,088*

-7

Health related behaviors RMR kJ

7,924 ± 1,050/7,116 ± 799*

kcal

1,893 ± 251/1,700 ± 191*

-10

1,401 ± 255/1,304 ± 260*

Energy intake kJ

9,879 ± 3,311/8,791 ± 3,797*

kcal

2,360 ± 791/2,100 ± 907*

-11

8,020 ± 2,386/6,049 ± 2,089**

-25

1,916 ± 570/1,445 ± 499**

Protein intake g/day

112 ± 40/92 ± 44*

-18

68 ± 19/60 ± 15

-12

% Energy

19 ± 7/17 ± 8

-11

14 ± 4/17 ± 4

?21

Total fat intake g/day 95 ± 13/77 ± 36*

-19

66 ± 21/54 ± 21*

-18

36 ± 5/33 ± 15

-8

31 ± 10/34 ± 13

?10

g/day

35 ± 14/28 ± 15*

-20

23 ± 9/17 ± 8**

-26

% Energy

13 ± 5/12 ± 6

-8

11 ± 4/10 ± 8

-9

% Energy SFA

MUFA g/day

23 ± 11/18 ± 10

-22

19 ± 8/16 ± 7

-16

% Energy

9 ± 4/8 ± 4

-11

9 ± 4/10 ± 4

?11

g/day

14 ± 6/11 ± 5

-21

9 ± 5/9 ± 5

0

% Energy

5 ± 2/5 ± 2

0

4 ± 2/6 ± 3

?50

PUFA

Carbohydrate intake

MUFA monounsaturated fatty acid, n subject’s number, ns not significant, PUFA polyunsaturated fatty acid, RMR resting metabolic rate, SFA saturated fatty acid ** p \ 0.01; * p \ 0.05

g/day

250 ± 85/242 ± 89

-3

253 ± 103/175 ± 68**

-31

% Energy

42 ± 14/46 ± 17

?10

53 ± 21/48 ± 19

-9

20 ± 12/19 ± 7

-5

24 ± 19/20 ± 8

-17

g/day

85 ± 41/74 ± 39*

-13

101 ± 52/60 ± 28**

-41

% Energy

15 ± 7/14 ± 7

-7

21 ± 11/17 ± 8

219

Fibre g/day Sugars

presented in Table 2. Thirty-three individuals (20 women and 13 men), aged 38.9 ± 6.5 years, completed the whole intervention program. Twenty of them were overweight and the other 13 obese. Nine participants were classified as having the metabolic syndrome. Table 3 summarizes the anthropometric characteristics, aerobic and anaerobic capabilities, physiological factors, metabolic profile, inflammatory markers, and adipokines of subjects at baseline and after 6 months of multidisciplinary intervention program. As shown in Table 3, after 6 months of multidisciplinary intervention, both men and women displayed statistically significantly reduced body weight, BMI, WC, systolic blood pressure (SBP), hip circumference (HC), and percentage of fat mass. On the other hand, lumbar paraspinal and trunk muscle endurance time and physical activity in METs per day statistically significantly increased after 6 months of intervention in male and female subjects. In addition, women displayed also

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statistically significantly decreased body dissatisfaction. Moreover, a statistically significant decrease in serum glucose, serum insulin, HOMA-IR, total cholesterol, and LDL was observed after 6 months of multidisciplinary intervention, in both men and women. Among the selected adipokines and inflammatory markers, TNF-a, visfatin, and CRP statistically significantly decrease, in men and women, whereas adiponectin statistically significantly increases after the same period, but only in female subjects. Moreover, Table 4 summarizes the dietary composition and nutrient intake before and after the 6 months of multidisciplinary intervention. Consistent with the research design, participants changed their nutrition pattern and an improvement in the composition of diet was observed. After dietary alteration, male subjects consumed less energy from total dietary fat, SFA, and sugars. On the other hand, female subjects consumed less energy from SFA and sugars, but not from total dietary fat. However, female

J Endocrinol Invest Table 5 Associations between aerobic/anaerobic capabilities, diet, anthropometric parameters and biochemical parameters Variable and range

2

3

4

5

6

7

8

9

10

11

12

Male

-0.247

-0.446

-0.255

-0.431

-0.514*

-0.414*

-0.511*

-0.299

-0.533*

0.211

0.215

Female

-0.447*

-0.129

-0.216

-0.236

-0.454*

-0.166

-0.319

-0.422*

-0.229

0.284

0.273*

1D METs/day

2D kcal/day Male

0.403*

0.470*

0.252

0.124

0.359

0.312

0.179

0.189

-0.423

-0.137

Female

0.679**

0.780**

0.236

0.541*

0.251

0.271

0.159

0.110

-0.254

-0.120

3D Sugars Male

0.321

0.312*

0.437*

0.116

0.391*

0.365*

0.396

-0.107

-0.202

0.616**

0.428*

0.567**

0.167

0.342*

0.379*

0.191

-0.165

-0.217

Male

0.126

0.109

0.165

0.257

0.189

0.195

-0.359*

-0.275

Female

0.233

0.179

0.188

0.215

0.424*

0.116

-0.227*

-0.160

Female 4D SFA

5D BMI Male

0.850**

0.641*

0.321*

0.316

0.290

-0.488*

-0.252

Female

0.857**

0.396

0.357*

0.527**

0.140

-0.310*

-0.569**

Male

0.648*

0.258

0.288

0.366*

-0.278*

-0.162

Female

0.313

0.195

0.456*

0.272

-0.272*

-0.386

6D TF

7D TC Male

0.373*

0.117

0.037

-0.561*

-0.119

Female

0.411*

0.308

0.280

-0.280*

-0.120

0.312*

0.183

-0.116

-0.273

0.276*

0.151

-0.192

-0.189

8D HOMA-IR Male Female 9D CRP Male

0.371*

-0.253

-0.366

Female

0.306*

-0.296*

-0.155

10D TNF-a Male

-0.298*

-0.203

Female

-0.251

-0.114

11D Adiponectin Male

0.138

Female

0.157

12D Anaerobic capabilities All associations are presented as Pearson’s correlation coefficients (r) BMI body mass index, CRP C-reactive protein, HOMA-IR homeostasis model assessment of insulin resistance, MET metabolic equivalent task, SFA saturated fatty acids, TC total cholesterol, TF trunk fat, TNF-a tumor necrosis factor-alpha ** p \ 0.01, * p \ 0.05

subjects consumed more energy from MUFA and PUFA. In addition the reduction of the subject’s RMR after 6 months of intervention was observed, in both men and women. Pearson’s correlation analysis was performed to investigate the associations between relative changes in aerobic/ anaerobic capabilities, diet, anthropometric and biochemical parameters. Reduction in TF was significantly and directly associated with a reduction in kcal/day, sugars, and with increase in physical activity in METs per day. In

addition, reduction in BMI, TF, HOMA-IR, and CRP was significantly and directly associated with a reduction in sugars in both genders. Moreover, increase in physical activity in METs per day was significantly associated with reduction in total cholesterol, HOMA-IR, and TNF-a in male subject, but with reduction in CRP and increase of anaerobic capabilities in female subjects. Moreover, reduction in BMI and TF was significantly and directly associated not only with a reduction in inflammatory

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J Endocrinol Invest Table 6 Results of hierarchical multiple regression analysis for variables predicting changes in TF Predictors

D TF, dependent variable DR2 (M/F)

Step 1

0.28*/0.35*

D kcal/day D METs/day Step 2

F (M/F) 4.9/7.5

0.25*/0.42* -0.53*/-0.37* 0.25/0.35**

D Sugars

2.7/8.7 0.15/0.25**

D SFA Step 3

B (M/F)

0.31*/0.37* 0.01/0.03

D Anaerobic capabilities

1.6/4.5 -0.12/-0.19

Total R2

0.54*/0.73**

N

13/20

F female, M male, MET metabolic equivalent task, SFA saturated fatty acids, TF trunk fat ** p \ 0.01, * p \ 0.05

Table 7 Results of hierarchical multiple regression analysis for variables predicting changes in serum CRP Predictors

D CRP, dependent variable DR2 (M/F)

Step 1

0.17*/0.24**

D BMI D TF Step 2

B (M/F)

2.9/3.8 0.41*/0.38* 0.15/0.27**

0.13*/0.16

2.3/3.3

D kcal/day

0.23*/0.27*

D METs/day

-0.42**/-0.23*

Step 3

0.09/0.12*

D Sugars

1.9/2.3 0.11/0.41*

D SFA Step 3

F (M/F)

0.29*/0.29* 0.04/0.01

D Anaerobic capabilities

1.6/0.4 -0.24/-0.12

Total R2

0.43*/0.53*

N

13/20

BMI body mass index, CRP C-reactive protein, F female, M male, MET metabolic equivalent task, SFA saturated fatty acids ** p \ 0.01, * p \ 0.05

markers and with production of adiponectin, but also with reduction in serum total cholesterol and HOMA-IR, differently by gender. Specifically, in male subjects, reduction in BMI or TF was significantly associated with a reduction in total-cholesterol, HOMA-IR, TNF-a and with production of adiponectin. On the other hand, in female subjects reduction in BMI or TF was significantly associated with a reduction in

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total-cholesterol, HOMA-IR, CRP and with production of adiponectin. In addition, reduction of CRP and production of anti-inflammatory adiponectin was directly associated with reduction in total cholesterol and HOMA-IR, in both men and women. However, production of adiponectin was significantly and directly associated also with reduction in SFA (Table 5). Two hierarchical multiple regression were performed to investigate the effects of the relative role of METs/day and kcal/day on improvement of the TF and the inflammatory marker CRP. In the first step of the first hierarchical multiple regression analysis, two predictors were entered: kcal/day and MET/day. This step was statistically significant and explained 28 and 35 % of variance in the relative reduction of TF for men and women, respectively (Table 6). Also the relative changes in sugars and SFA intake at step 2 contributed significantly and explained additional 25 and 35 % of the variation in the relative reduction of TF for men and women, respectively. Together, the adjusted R squared value was 0.54 for men and 0.73 for women. This indicates that 54 % of the variance for men and 73 % of the variance for women in the relative changes in TF were explained by the present model (Table 6). The second hierarchical multiple regression analysis was performed to examine the effects of the relative role of METs/day and kcal/day on improvement of the inflammatory marker CRP (Table 7). The relative changes of BMI and TF were entered as variables at step 1, followed by the relative changes in kcal/day and METs/day (step 2), and by the relative changes in sugars and SFA intake (step 3). In the last step (step 4) the relative changes in anaerobic capabilities were also entered. The hierarchical multiple regressions revealed that at stage one, the relative changes in BMI and TF contributed significantly to the regression model and accounted for 17 % for men and 24 % for women of the variation in the reduction of CRP. Introducing the relative changes of the kcal/day and METs/day in the stage two of the regression model explained additional 13 % for men and 16 % for women of the variation in reduction of CRP. Adding the relative changes in sugars and SFA in the regression model explained additional 9 % in men and 12 % in women of the variation in reduction of CRP. Together, the adjusted R squared value was 0.43 for men and 0.53 for women. This indicates that 43 % of the variance for men and 53 % of the variance for women in the relative changes in the inflammatory marker CRP were explained by the model (Table 7).

Discussion The purpose of this study was to evaluate the effect of a nutrient-balanced, moderate energy-restricted diet based on

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the individual’s RMR measurement and a moderate exercise program on weight and body fat loss in respect to health parameters. Specifically, we tested the hypothesis that multidisciplinary intervention may induce changes in serum adiponectin, resistin, visfatin, and TNF-a levels. We clearly demonstrated that weight loss was accompanied by decreased concentrations of circulating mediators of inflammation and an increased concentration of serum adiponectin. In addition, these effects were in line with reduction of cardiovascular risk factors. Moreover, the finding of the present study was that reduction in kcal/day, sugars and SFA in diet and, on the other hand, increase in exercise had major effects on WC, TF, BMI, and SBP. Although some results provide no justification for the exclusion of added sucrose in weightreducing diets [23], our results are in agreement with studies indicating that sucrose promotes obesity-associated comorbidities [24, 25]. Different authors in the past decade observed that excess of sugar in the diet may be stored as TF [26, 27]. We indicated that reverse also holds less sugar consumed demonstrated statistically significant reduction of TF (see Table 5). In addition, Summers et al. [28] demonstrated that a diet rich in PUFA compared with a diet rich in SFA resulted in a decrease in abdominal subcutaneous fat area and in an improvement of insulin sensitivity and plasma LDL cholesterol concentrations. Similarly, our study demonstrated that simple changes of the type of dietary fat consumed (reduction of SFA and increase in PUFA) had beneficial effects in preventing excessive weight gain. The health benefits of physical activity in intervention programs for weight control are well recognized [13, 29]. In accordance with previous interventional studies [11, 12], we found that significant improvement of daily exercise, especially aerobics, resulted in a reduced TF mass (see Table 5). Although increasing physical activity is effective therapy for weight loss, higher physical fitness may also emerge as a promising treatment for reducing overall inflammation and contributing to clinical benefits [29]. Given that physical activity and obesity are inversely related, it is not clear whether the anti-inflammatory health benefits of a physically active lifestyle are due to exercise per se, or result from favorable changes in body composition [30]. However, our results (Tables 6, 7) demonstrated that both, changes in body composition and exercise per se, contributed to improvement in low-grade inflammation. Moreover, the present findings, in accordance with previous studies, showed that moderate weight loss was effective in reducing glucose, insulin and HOMA-IR, and total cholesterol [31]. However, lipid metabolism was not significantly altered, although we observed a reduction in total cholesterol, LDL cholesterol, and TG. Our results are in agreement with previous reports where lipid metabolism was

altered only after massive weight loss [32] or after weight loss in combination with intensive physical activity [33]. Obese individuals often experience chronic inflammation. Increase of adipose tissue mass is associated with low serum adiponectin and elevated TNF-a and visfatin in obesity [1]. It is expected that changes in these adipocytokines would be reversed with fat loss. Consistent with this, in agreement with other observations [34, 35], one important finding was that the adiponectin concentration significantly increased after weight loss. We found that serum D adiponectin in overweight subjects had a statistically negative correlation with D total cholesterol, in both male and female subjects. Decreased serum total cholesterol levels may further decrease the risk of CVD and chronic inflammation. A possible explanation for production of adiponectin on weight loss is probably activation of the peroxisome proliferator-activated receptor gamma (PPAR-c), a pathway which is activated by a negative energy balance and weight loss [36]. Therefore, we suggest that weight loss is more important in activation of PPAR-c than a negative energy balance. However, our results pointed out the possible, additional mechanism for improvement of anti-inflammatory status, because statistically significant and direct association between production of adiponectin and reduction of SFA was found. Moreover, increased adiponectin and decreased visfatin, TNF-a, and CRP in a weight loss-dependent manner suggest that an anti-inflammatory state is obtained after weight loss. This represents a BMI reduction of 4 %. Considering the metabolic parameters, the results demonstrated the effectiveness of weight loss in improvement of cardiovascular risk factors in overweight adults. This is evident from the positive correlation of D BMI and D TF with D total cholesterol and D HOMA-IR (see Table 5). Additionally, D total cholesterol and D HOMA-IR negatively correlated with D adiponectin and positively with D inflammatory markers (Table 5). Although it remains unclear whether the adipokines investigated to date are responsible for the beneficial effects on health-associated weight loss, it is clear that there are important associations between weight loss, adipokines, and cardiovascular risk factors. Additionally, the present study showed that body image dissatisfaction significantly improved during the intervention, especially in female subjects. Therefore, our results suggest that cognitive and affective changes might occur during the weight loss program, thus supporting the proposition that weight reduction may directly benefit more positive psychosocial outcomes [37]. However, body dissatisfaction may also be associated with inflammation, as reported by Sabiston et al. [38] who claimed that stress related to body image and body dissatisfaction is a possible correlate of elevated CRP. This should be further investigated.

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Finally, we should point out that our participants were mostly overweight and in this state it is probably easier to improve obesity-related biomarkers. Lang et al. [39] proposed that subjects with a BMI of 30 kg/m2 or greater may develop hyperplastic obesity, which results in greater difficulty in losing weight and increases the concentrations of the obesity-related biomarkers. Therefore, if we consider overweight as a pre-disease state, it is important to ameliorate low-grade inflammation already at this stage, before the occurrence of obesity and obesity-related diseases. In conclusion, our data showed that the inflammatory state improved after moderate weight loss. This finding may be important for controlling obesity-related co-morbidities. It would appear that the moderate weight loss observed in our study resulted in significant improvements in circulating levels of adipokines. Changes in adipokines possibly resulted in improvements in the fasting glucose and lipid profile. However, it is difficult to distinguish whether these effects are due to the weight loss per se, the nature of the diet used to induce weight loss, energy restriction itself, in part also to physical activity or maybe in part also due to body image satisfaction. But our results pointed out that all of these components significantly contributed to the improvement in health benefits. This study is not without limitations. To comprehensively explain what is happening within carefully planned diet intervention with observation of metabolic changes in overweight individuals it would be very beneficial to enlarge the number of participants and include additional control group in more extended time frame. Acknowledgments The authors would like to thank all the subjects for their participation. The authors would also like to thank the nurses (Sabina Licˇen and Tamara Sˇtemberger Kolnik) of the Faculty of Health Sciences for taking blood samples, Vanja Pahor and the Izola General Hospital biochemical laboratory staff, and colleague Tamara Poklar Vatovec from the Faculty of Health Sciences for her technical support. The authors sincerely thank Nadja Plazar for supporting this study. They are also grateful to Peter Raspor and Anthony R. Byrne for proof reading the manuscript. The study was funded by the University of Primorska, Faculty of Health Sciences, for the project entitled ‘‘A multidisciplinary approach in the treatment of obesity’’, by the Slovenian Research Agency (Programme P1-0386), and by the European Regional Development Fund, Cross-Border Cooperation Italy–Slovenia Programme 2007–2013 (EU strategic Project TRANS2CARE). Conflict of interest of interest.

The authors declare that there are no conflicts

References 1. Wang Z, Nakayama T (2010) Inflammation, a link between obesity and cardiovascular disease. Mediators Inflamm. doi:10. 155/2010/535918

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2. Shoelson SE, Goldfine AB (2009) Getting away from glucose: fanning the flames of obesity-induced inflammation. Nat Med 15:373–374 3. Fuentes E, Fuentes F, Vilahur G et al (2013) Mechanisms of chronic state of inflammation as mediators that link obese adipose tissue and metabolic syndrome. Mediators Inflamm. doi:10.1155/ 2013/136584 4. Seagle HM, Strain GW, Makris A et al (2009) Position of the American dietetic association: weight management. J Am Diet Assoc 109:330–346 5. Gagnon C, Brown C, Couture C et al (2011) A cost-effective moderate-intensity interdisciplinary weight-management programme for individuals with prediabetes. Diabetes Metab 37:410–418 6. Franz MJ, VanWormer JJ, Crain AL et al (2011) Weight-loss outcomes: a systematic review and meta-analysis of weight-loss clinical trials with a minimum 1-year follow-up. J Am Diet Assoc 107:1755–1767 7. Casazza K, Fontaine KR, Astrup A et al (2013) Myths, presumptions, and facts about obesity. N Engl J Med 368:446–454 8. Weck M, Bornstein SR, Barthel A, Blu¨her M (2012) Strategies for successful weight reduction-focus on energy balance. Dtsch Med Wochenschr 137:2223–2228 9. Dulloo AG, Jacquet J, Montani JP, Schutz Y (2012) Adaptive thermogenesis in human body weight regulation: more of a concept than a measurable entity? Obes Rev 13(Suppl 2):105–121 10. Se´ne´chal M, Arguin H, Bouchard DR et al (2012) Effects of rapid or slow weight loss on body composition and metabolic risk factors in obese postmenopausal women. A pilot study. Appetite 58:831–834 11. Caranti DA, de Mello MT, Prado WL et al (2007) Short- and long-term beneficial effects of a multidisciplinary therapy for the control of metabolic syndrome in obese adolescents. Metabolism 56:1293–1300 12. Greene NP, Martin SE, Crouse SF (2012) Acute exercise and training alter blood lipid and lipoprotein profiles differently in overweight and obese men and women. Obesity (Silver Spring) 20:1618–1627 13. Murphy MH, Blair SN, Murtagh EM (2009) Accumulated versus continuous exercise for health benefit: a review of empirical studies. Sports Med 39:29–43 14. Carnier J, Lofrano MC, Prado WL et al (2008) Hormonal alteration in obese adolescents with eating disorder: effects of multidisciplinary therapy. Horm Res 70:79–84 15. Lira FS, Rosa JC, Dos Santos RV et al (2011) Visceral fat decreased by long-term interdisciplinary lifestyle therapy correlated positively with interleukin-6 and tumor necrosis factor-a and negatively with adiponectin levels in obese adolescents. Metabolism 60:359–365 16. Chae JS, Paik JK, Kang R et al (2013) Mild weight loss reduces inflammatory cytokines, leukocyte count, and oxidative stress in overweight and moderately obese participants treated for 3 years with dietary modification. Nutr Res 33:195–203 17. Jurdana M, Petelin A, Cˇernelicˇ Bizjak M et al (2013) Increased visfatin levels in obesity and its association with anthropometric/ biochemical parameters, physical activity and nutrition. e-SPEN J 8:e59–e67 18. Ainsworth BE, Haskell WL, Herrmann SD et al (2011) Compendium of physical activities: a second update of codes and MET values. Med Sci Sports Exerc 43:1575–1581 19. Wardle J, Johnson F (2002) Weight and dieting: examining levels of weight concern in British adults. Int J Obes Relat Metab Disord 26:1144–1149

J Endocrinol Invest 20. Millstein RA, Carlson SA, Fulton JE et al (2008) Relationships between body size satisfaction and weight control practices among US adults. Medscape J Med 10:119 21. Jenko-Prazˇnikar Z, Petelin A, Jurdana M, Zˇiberna L (2013) Serum bilirubin levels are lower in overweight asymptomatic middle-aged adults: an early indicator of metabolic syndrome? Metabolism 62:976–985 22. Matthews DR, Hosker JP, Rudenski AS et al (1985) Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 28:412–419 23. West JA, De Looy AE (2001) Weight loss in overweight subjects following low-sucrose or sucrose-containing diets. Int J Obes Relat Metab Disord 25:1122–1128 24. Parks EJ, Hellerstein MK (2000) Carbohydrate-induced hypertriacylglycerolemia: historical perspective and review of biological mechanisms. Am J Clin Nutr 71:412–433 25. Krauss RM, Blanche PJ, Rawlings RS et al (2006) Separate effects of reduced carbohydrate intake and weight loss on atherogenic dyslipidemia. Am J Clin Nutr 83:1025–1031 26. Minehira K, Bettschart V, Vidal H et al (2003) Effect of carbohydrate overfeeding on whole body and adipose tissue metabolism in humans. Obes Res 11:1096–1103 27. Collison KS, Zaidi MZ, Subhani SN et al (2010) Sugar-sweetened carbonated beverage consumption correlates with BMI, waist circumference, and poor dietary choices in school children. BMC Public Health 10:234 28. Summers LKM, Fielding BA, Bradshaw HA et al (2002) Substituting dietary saturated fat with polyunsaturated fat changes abdominal fat distribution and improves insulin sensitivity. Diabetologia 45:369–377 29. Beavers KM, Brinkley TE, Nicklas BJ (2010) Effect of exercise training on chronic inflammation. Clin Chim Acta 411:785–793 30. Calder PC, Ahluwalia N, Brouns F et al (2011) Dietary factors and low-grade inflammation in relation to overweight and obesity. Br J Nutr 106(Suppl. 3):S5–S78

31. Grulich-Henn J, Lichtenstein S, Ho¨rster F et al (2011) Moderate weight reduction in an outpatient obesity intervention program significantly reduces insulin resistance and risk factors for cardiovascular disease in severely obese adolescents. Int J Endocrinol. doi:10.1155/2011/541021 32. Masquio DC, de Piano A, Sanches PL et al (2012) The effect of weight loss magnitude on pro-/anti-inflammatory adipokines and carotid intima-media thickness in obese adolescents engaged in interdisciplinary weight loss therapy. Clin Endocrinol 79:55–64 33. Varady KA, Jones PJH (2005) Combination diet and exercise interventions for the treatment of dyslipidemia: an effective preliminary strategy to lower cholesterol levels? J Nutr 135:1829–1835 34. Cnop M, Havel PJ, Utzschneider KM et al (2003) Relationship of adiponectin to body fat distribution, insulin sensitivity and plasma lipoproteins: evidence for independent roles of age and sex. Diabetologia 46:459–469 35. Chan DC, Watts GF, Ng TW et al (2008) Effect of weight loss on markers of triglyceride-rich lipoprotein metabolism in the metabolic syndrome. Eur J Clin Invest 38:743–751 36. Verreth W, Ganame J, Mertens A et al (2006) Peroxisome proliferator-activated receptor-alpha, gamma-agonist improves insulin sensitivity and prevents loss of left ventricular function in obese dyslipidemic mice. Arterioscler Thromb Vasc Biol 26:922–928 37. Blaine BE, Rodman J, Newman JM (2007) Weight loss treatment and psychological well-being a review and meta-analysis. J Health Psychol 12:66–82 38. Sabiston C, Castonguay A, Barnett T et al (2009) Body image and C-reactive protein in adolescents. Int J Obes 33:597–600 39. Lang HF, Chou CY, Sheu WH, Lin JY (2011) Weight loss increased serum adiponectin but decreased lipid levels in obese subjects whose body mass index was lower than 30 kg/m2. Nutr Res 31:378–386

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