Research ArticleCardiovascular and Metabolic Consequences of Sleep and/or Circadian Disruption

Beneficial effects of a lifestyle intervention program on C-reactive protein: impact of cardiorespiratory fitness in obese adolescents with sleep disturbances

Published Online:https://doi.org/10.1152/ajpregu.00309.2018

Abstract

The objectives of this study were to assess the relationship between inflammation and obstructive sleep apnea (OSA) and determine whether the lifestyle program’s effects on inflammatory markers are associated with changes in anthropometric parameters, cardiorespiratory fitness, sleep duration, and OSA severity in severely obese adolescents. Participants were aged 14.6 (SD 1.2) yr, with a body mass index (BMI) of 40.2 (SD 6.5) kg/m2. Sleep, anthropometric parameters, glucose metabolism, inflammatory profile, and cardiorespiratory fitness [V̇o2peak relative to body weight (V̇o2peakBW) and fat-free mass (V̇o2peakFFM)] were assessed at admission and at the end of a 9-mo lifestyle intervention program (LIP). Associations between C-reactive protein (CRP) concentrations and BMI, sex, oxygen desaturation index (ODI), sleep fragmentation, total sleep time (TST), and V̇o2peak were assessed via ANCOVA. Twenty-three subjects completed the study. OSA subjects (n = 13) exhibited higher CRP concentrations and a trend for higher BMI than non-OSA subjects (P = 0.09) at admission. After intervention, OSA was normalized in six subjects, and CRP significantly decreased in the OSA group and in the whole population. In both groups, leptin levels significantly decreased, whereas adiponectin concentrations increased. At admission, BMI adjusted for sex, arousal index, ODI, TST, and V̇o2peakBW was associated with CRP levels (adjusted r2 = 0.32, P < 0.05). The decrease in CRP concentrations postintervention was associated with enhanced V̇o2peakFFM adjusted for sex, weight loss, and changed sleep parameters (adjusted r2 = 0.75, P < 0.05). Despite higher amounts of CRP in OSA subjects, obesity severity outweighs the proinflammatory effects of OSA, short sleep duration, and low cardiorespiratory fitness. However, enhanced cardiorespiratory fitness is associated with the decrease of inflammation after controlling for the same parameters.

INTRODUCTION

Prevalence rates of childhood obesity have reached alarming levels (25). This disease is closely associated with obstructive sleep apnea (OSA), which is observed in 33–61% of obese youth (34, 59, 74, 77), along with short sleep duration (8, 9, 15, 17), both known proinflammatory factors (14, 26, 37, 50, 57, 68) promoting endothelial dysfunction (6, 14, 36, 67). Indeed, breathing disorders during sleep are associated with sleep fragmentation (38) and intermittent hypoxia (10), leading to sympathetic overactivity (5, 11) and overproduction of radical oxygen species (42, 43). Independently, oxidative stress and sympathetic activity promote an inflammatory state (68, 78).

In parallel, systemic inflammation in pediatric obesity is induced by adipose tissue dysfunction (29) and mediated by a large number of cytokines (45). Indeed, high levels of leptin and reduced adiponectin concentrations (respectively pro- and anti-inflammatory adipokines) are observed in obese adolescents (23). In clinical practice, C-reactive protein (CRP) assessment is routinely performed to determine systemic inflammatory profile and cardiometabolic risk (62).

Despite conflicting results regarding the additional effects of OSA on inflammation in obese youths (19, 66, 70), this syndrome makes therapeutic approaches to pediatric obesity challenging. Although a few studies have shown the beneficial effects of a lifestyle intervention on the severity of OSA and sleep duration in obese adolescents (13, 73), only one has assessed its effects on inflammation (71). In this study, Van Hoorenbeeck et al. (71) reported positive relationships between inflammatory markers and both OSA and the severity of obesity at admission, with a 4–6 mo lifestyle program including at least 10 h of regular exercise per week. However, the reduction in inflammatory markers after the program was not associated with improvements in either sleep or anthropometric parameters, suggesting the involvement of other parameters mediating the inflammatory profile.

Studies have shown that cardiorespiratory fitness has positive effects on inflammation in adolescents (24, 47, 61). Nevertheless, no study has assessed the effects of enhanced cardiorespiratory fitness induced by exercise training as part of a lifestyle intervention program (LIP) on inflammation in obese adolescents with OSA and short sleep duration.

Therefore, we performed a 9-mo experimental, interventional study to first assess the relationship between inflammation and OSA and then study whether the LIP’s effects on inflammatory markers are associated with changes in anthropometric parameters, cardiorespiratory fitness, sleep duration, and OSA severity in severely obese adolescents. We further hypothesized that obese adolescents with OSA would exhibit higher concentrations of CRP compared with obese adolescents without OSA, and that LIP-induced reduction in CRP concentrations would be driven by concomitant weight loss, OSA normalization, and improved cardiorespiratory fitness in obese adolescents with sleep disturbances.

MATERIALS AND METHODS

Study Participants

Thirty-two adolescents (16 girls and 16 boys) with severe obesity, defined as body mass index (BMI) z-score greater than 3 (60), were recruited from a residential institution specializing in the management of adolescent obesity. Subjects spent an academic year in a specialized residential institution with the aim of body weight reduction. Experts in nutrition and physical activity and pediatricians oversaw the LIP for a period of 9 mo.

The study was approved by the medical ethics committee of the University Hospital of Besançon, France (no. 2015-A00763-46) in accordance with the Declaration of Helsinki and registered on ClinicalTrials.gov under the number NCT02588469. All participants and their parents or legal guardians were fully informed of the experimental procedures and provided written informed consent before enrollment in the study. Patient enrollment was performed in August 2015.

Experimental Procedures

Anthropometric and body composition assessment, maximal exercise testing, blood sample collection, and nocturnal recordings were performed at admission and postintervention. Pubertal developmental stages and upper airway anatomy assessments were only performed at admission.

Clinical evaluations.

Waist circumference and hip circumference were measured to the nearest 0.5 cm in a standing position with a standard nonelastic tape that was applied horizontally midway between the last rib and the superior iliac crest and from both sides of the greater trochanter, respectively. Waist-to-hip ratio was calculated as waist circumference (in cm) divided by hip circumference (in cm). BMI z-score was calculated for age and sex reference values adapted to the French pediatric population (51). Body fat mass (FM) and fat-free mass (FFM) were measured by multi-frequency bioelectrical impedance analysis (SFB7 model, Impedimed Limited, Pinkenba, Queensland, Australia) using four body surface electrodes in the supine position. Bioelectrical impedance analysis was performed in a fasting state after voiding the bladder. Pubertal developmental stages were determined according to Tanner’s method (65) by the physician of the institution at admission.

Upper airway anatomy assessments.

The Mallampati score and tonsil size were visually scored at admission by a medical doctor. Surgical history (tonsillectomy) was also collected. The Mallampati score was obtained in the sitting position and ranged from Class 1 to 4 as follows: Class 1) faucial/tonsillar pillars, uvula, and soft palate are all visible; Class 2) partial visibility of the faucial/tonsillar pillars; Class 3) base of the uvula and soft and hard palate are visible; and Class 4) only the hard palate is visible (46). Tonsil-size grading was classified in the sitting position, using Friedman’s scale as follows: Grade 0) no tonsil tissue present; Grade 1) tonsils hidden within the faucial/tonsillar pillars; Grade 2) tonsils extending to the pillars but not beyond them; Grade 3) tonsils extending beyond the faucial/tonsillar pillars but not to the midline; and Grade 4) tonsils extending to the midline and may be touching each other (18).

Maximal exercise test.

o2peak was measured during a graded exhaustive cycling test on a fixed cycle ergometer (Ergoselect 200K, Ergoline, Bitz, Germany) with gas exchange measurement (MetaMax, Matsport, Saint Ismier, France) and was performed 2 days before nocturnal polysomnography. The initial power of 30 W was maintained for 3 min and followed by 10-W increments every minute. Adolescents were strongly encouraged by experimenters throughout the test to perform a maximal effort. V̇o2peak was measured in absolute value (l/min) and then expressed relative to the body weight, V̇o2peakBW (ml·min−1·kg−1), and to the FFM, V̇o2peakFFM (ml·min−1·kg−1).

Blood chemistry.

Blood samples were drawn via an antecubital vein after an overnight fast (12 h) for assessments of CRP, leptin, adiponectin, insulin, and glucose concentrations. Samples were centrifuged (4,000 g for 10 min at 4°C), and plasma was transferred into plastic tubes and stored at −80°C until analysis. CRP levels were measured by the immune nephelometry method (20). Plasma leptin and adiponectin concentrations were assessed by radioimmunoassay. Plasma insulin concentrations were assessed by chemiluminescence, and glucose was determined by enzymatic methods. Homeostasis model assessment of insulin resistance (HOMAIR) was calculated using the following formula: fasting insulin (mIU/l) × fasting glucose (mmol/l)/22.5, and was a marker of insulin resistance (48).

Sleep recordings.

All subjects underwent, under the same conditions and on a weekday, a standard ambulatory polysomnography (Morpheus, Micromed, Italy) in the residential institution. Sleep was assessed with standard polysomnography techniques using the 10–20 system (31). Respiratory efforts were studied by thoracic and abdominal inductance plethysmography (SleepSense, S.L.P, Elgin, IL). Airflow was measured with a thermistor and nasal pressure cannula (ThermoCan, SleepSense), and snoring was determined by filtration of the nasal pressure signal. Peripheral oxygen saturation (SpO2) and heart rate were both recorded by pulse oximetry (Nonin Medical, Plymouth, MN). The average of SpO2values (Mean SpO2) and the lowest SpO2value (Min SpO2) during sleep were determined.

Polysomnography data were recorded directly to a data acquisition, storage, and analysis system (SleepRT software; Brain RT, OSG, Rumst, Belgium). The electroencephalogram recordings were visually scored in 30-s periods (4) and respiratory events in 3-min periods for airflow (3) by an experienced, board-certified sleep physician using the American Academy of Sleep Medicine’s standard rules (3, 4) to obtain the overnight pattern of sleep stages. The following sleep parameters were retained for analyses: total sleep time (TST, min), total arousal (number of arousals) and arousal index (number of arousals/TST, %), percentage of stage 1 sleep in TST (N1, %), percentage of stage 2 sleep in TST (N2, %), percentage of stage 3 sleep in TST (N3, %), and percentage of rapid eye movement sleep in TST (REM, %). Apnea was defined as ≥ 90% reduction in airflow for the duration of at least 2 breaths associated with the presence of respiratory effort for obstructive apnea or absent respiratory effort during one portion of the event and the presence of inspiratory effort in another portion for mixed apnea. Central apnea was defined as ≥90% reduction in airflow for at least 20 s with absent inspiratory effort throughout the entire event, or for at least the duration of 2 breaths associated with ≥3% fall in oxygen saturation and/or arousal. Hypopnea was defined as ≥ 30% reduction in airflow for at least 2 breaths associated with ≥3% fall in oxygen saturation and/or arousal (3). Respiratory effort-related arousal (RERA) was defined as increasing respiratory effort for at least 2 breaths, characterized by a flattening of the inspiratory portion of the nasal pressure, and leading to arousal from sleep (3). The obstructive apnea-hypopnea index (OAHI; events per hour) was determined by dividing the number of obstructive apnea plus mixed apnea and hypopnea by hours of sleep. The apnea-hypopnea index (events per hour) was determined by dividing the number of obstructive, mixed, and central apneas plus hypopneas by hours of sleep to define the respiratory disturbance index (RDI; sum of AHI and RERA index). Oxygen desaturation index (ODI; events per hour) was determined by dividing the number of oxygen desaturations ≥3% by hours of sleep. The diagnosis of OSA was defined by the presence of an OAHI ≥ 2/h of TST (16), and subjects were thus classified as OSA group (OAHI ≥ 2) or non-OSA group (OAHI < 2). At the end of the LIP, two other groups within the OSA group were distinguished according to the change of the OAHI: normalized (OAHI < 2) and residual OSA subjects (OAHI ≥ 2).

Lifestyle Intervention Program

The 9-mo LIP was based on modified dietary habits associated with an interval training program whose intensity was dependent on the data obtained during initial incremental exercise test. This LIP has previously been described in detail elsewhere (23, 59).

Statistical Analysis

Statistical analysis was performed using Graphpad software (version 8.00, Tulsa, OK) and XLSTAT (Addinsoft, New York, NY). Data are presented as mean (SD), with a level of significance set at P < 0.05. The Kolmogorov-Smirnov test was used to test the assumption of distribution normality for quantitative parameters. Paired Student’s t-tests and Wilcoxon matched pair’s tests were used, as appropriate, to compare data in the whole population at admission and postintervention.

FM, FFM, V̇o2peakFFM, CRP, HOMAIR, OAHI, and ODI were not normally distributed and logarithmic transformations were applied as appropriate.

Two-way repeated measures ANOVA (group × time) were performed between non-OSA and OSA groups and between the normalized OSA and residual OSA groups. When an interaction was observed, paired Student’s t-tests were performed to explain the main effects. When necessary, variation rates by group were performed using the following formula: [(final value – initial value)/initial value] and subsequently compared by unpaired t-test.

Changes (∆) in anthropometric parameters, body composition, cardiorespiratory fitness, sleep parameters, and inflammatory markers were calculated using the following formula: [final value – initial value]. Spearman’s correlation coefficients were used to assess the association between ∆ FM (kg) and ∆ leptin concentrations in the whole population, in the OSA and non-OSA groups, and in the normalized and residual OSA groups.

ANCOVA adjusted for sex was performed to examine associations between inflammatory markers and anthropometric, sleep, and cardiorespiratory fitness parameters at admission and postintervention.

RESULTS

Characteristics of the Whole Population

Nine subjects (6 boys, 3 girls) were excluded from the study; 2 boys were treated by continuous positive airway pressure, 1 boy did not undergo blood sample collections and maximal exercise test, 1 boy presented poor quality polysomnographic data, and 3 girls and 2 boys failed to complete the 9-mo LIP. In total, 23 subjects (10 boys, 13 girls) with severe obesity were considered for analysis. According to Tanner’s method, pubertal development stages of the subjects ranged between 4 and 5. Anthropometric, biological, and sleep parameters and cardiorespiratory fitness are reported in Table 1. Mallampati scores, tonsil sizes, and history of tonsillectomy are reported in Table 2.

Table 1. Anthropometric and body composition assessments and biological, sleep, and cardiorespiratory parameters at admission and at 9 mo postintervention in the whole population and between OSA and non-OSA subjects

Whole Population
OSA Group, n = 13
Non-OSA Group, n = 10
At admissionAt 9 moAt admissionAt 9 moAt admissionAt 9 moGroup EffectTime EffectInter-action
Girls/boys, n (%)13/10 (57/43)7/6 (54/46)6/4 (60/40)
Anthropometric and body composition assessments
Age, yr14.71 (1.30)15.37 (1.32)***14.62 (1.51)15.26 (1.56)14.84 (1.04)15.50 (0.99)NS†††NS
Height, cm166.70 (6.84)168.40 (7.04)***164.92 (4.37)166.54 (5.00)169.05 (8.85)170.76 (8.76)NS†††NS
Weight, kg111.50 (20.38)100.60 (16.84)***115.17 (23.44)102.01 (19.78)106.81 (15.43)98.79 (12.85)NS†††NS
BMI, kg/m240.12 (6.93)35.33 (5.68)***42.27 (8.01)36.44 (6.75)37.32 (4.05)33.88 (3.76)NS†††NS
BMI z-score4.68 (0.95)3.97 (1.06)***4.94 (1.13)4.17 (1.29)4.34 (0.52)3.71 (0.61)NS†††NS
WC, cm121.10 (16.01)98.42 (12.55)***123.54 (17.84)98.75 (12.41)117.90 (13.51)98.00 (13.39)NS†††NS
HC, cm126.70 (10.98)114.80 (9.81)***127.92 (12.80)115.00 (11.54)125.00 (8.42)114.70 (7.60)NS†††NS
WHR0.95 (0.07)0.86 (0.08)***0.96 (0.08)0.86 (0.07)0.94 (0.05)0.85 (0.09)NS†††NS
FM, %39.36 (4.86)33.35 (5.84)***40.00 (5.87)34.06 (4.61)38.53 (3.23)32.41 (7.30)NSNS
FFM, %60.64 (4.86)66.65 (5.84)***60.00 (5.87)65.94 (4.61)61.47 (3.23)67.59 (7.30)NS†††NS
Biological parameters
CRP, mg/l8.46 (6.50)6.11 (4.07)*10.98 (7.57)6.78 (4.08)5.19 (2.41)5.25 (4.11)NS
Leptin, ng/ml65.54 (28.65)43.88 (19.74)***64.56 (20.31)42.16 (17.52)66.82 (38.19)46.11 (23.09)NS†††NS
Adiponectin, µg/ml7.55 (2.25)9.24 (3.20)*7.06 (2.26)9.28 (3.05)8.19 (2.17)9.18 (3.54)NSNS
Glucose, g/l0.78 (0.06)0.79 (0.06)NS0.79 (0.05)0.78 (0.06)0.78 (0.07)0.81 (0.05)NSNSNS
Insulin, µIU/ml19.98 (9.52)18.99 (12.40)NS23.00 (10.42)19.73 (15.01)16.06 (6.82)18.03 (8.58)NSNSNS
HOMAIR3.86 (1.91)3.80 (2.26)NS4.45 (2.09)3.98 (2.68)NS3.10 (1.38)3.57 (1.68)NSNSNS
Sleep parameters
TST, min451.50 (31.05)483.60 (45.37)*443.20 (23.43)491.80 (44.37)462.30 (37.33)473.00 (46.73)NSNS
N1, %TST4.94 (2.83)7.08 (2.49)*5.70 (3.28)6.17 (2.77)NS3.96 (1.83)8.30 (2.36)§§§NS††
N2, %TST53.67 (4.39)52.36 (6.25)NS52.75 (4.13)51.56 (6.61)54.87 (4.64)53.43 (5.92)NSNSNS
N3, %TST21.32 (4.77)18.42 (4.32)*21.78 (5.37)19.88 (3.08)20.72 (4.04)16.48 (5.12)NS††NS
REM, %TST20.03 (3.20)22.13 (4.29)*19.74 (3.31)22.40 (5.42)20.42 (3.17)21.77 (2.36)NSNSNS
Total arousal, nb58.52 (19.50)85.05 (40.99)*61.92 (15.75)88.25 (43.45)54.1 (23.68)80.78 (39.62)NSNS
Arousal index, nb/h7.76 (2.50)10.89 (4.93)*8.37 (2.08)11.30 (5.43)6.97 (2.87)10.35 (4.78)NSNS
RDI, nb/h)8.46 (4.62)9.99 (6.53)NS11.46 (3.17)11.52 (7.85)NS4.55 (2.97)7.77 (3.16)§§††NS
OAHI, nb/h2.37 (2.49)2.48 (2.59)NS3.68 (2.62)2.91 (2.95)§0.66 (0.51)1.93 (2.05)NS††NS††
ODI, nb/h3.92 (4.05)3.95 (3.29)NS5.48 (4.77)4.53 (4.22)1.89 (1.32)3.19 (1.26)NSNSNS
Mean SpO2, %95.03 (1.66)95.19 (2.21)NS95.08 (2.10)95.53 (2.35)94.96 (0.90)94.74 (2.05)NSNSNS
Min SpO2, %83.66 (5.83)85.52 (6.16)NS83.19 (6.93)84.46 (6.06)84.26 (4.28)86.89 (6.32)NSNSNS
Cardiorespiratory fitness
o2peak, l/min2.50 (0.46)2.74 (0.55)***2.54 (0.52)2.71 (0.57)2.49 (0.43)2.78 (0.57)NS†††NS
o2peakBW, ml·min−1·kg−122.91 (3.05)27.89 (4.92)***22.50 (2.39)27.50 (3.90)23.44 (3.89)28.40 (6.19)NS†††NS
o2peakFFM, ml·min−1·kg−137.47 (5.39)41.60 (5.44)*38.40 (6.48)41.36 (4.67)37.20 (3.64)41.98 (6.73)NSNS

Values are presented as means (SD). BMI, body mass index; CRP, C-reactive protein; FFM, fat-free mass; FM, fat mass; HC, hip circumference; HOMAIR, homeostasis model assessment of insulin resistance; N1, stage N1 sleep; N2, stage N2 sleep; N3, stage N3 sleep; OAHI, obstructive apnea-hypopnea index; ODI, oxygen desaturation index; OSA, obstructive sleep apnea; RDI, respiratory disturbance index; REM, rapid eye movement sleep; SpO2, peripheral oxygen saturation; TST, total sleep time; V̇o2peak, absolute peak oxygen uptake (l/min); V̇o2peakBW, peak oxygen uptake expressed relative to body weight (ml·min−1·kg−1); V̇o2peakFFM, peak oxygen uptake expressed relative to fat-free mass (ml·min−1·kg−1); WC, waist circumference; WHR, waist-to-hip ratio. Paired Student’s t-test for parametric data and Wilcoxon matched pairs test for nonparametric data for comparison in the whole population between admission and post intervention; NS, not significant;

*P < 0.05;

***P < 0.001. Two-way repeated measures ANOVA; nonparametric data are log transformed; NS, not significant;

P < 0.05;

††P < 0.01;

†††P < 0.001. Paired Student’s t-test for comparison by groups between admission and postintervention; NS, not significant;

§P < 0.05;

§§P < 0.01;

§§§P < 0.001.

Table 2. Mallampati Score, tonsil size, and tonsillectomy in the whole population and by group

Whole PopulationNon-OSANormalized OSAResidual OSA
n20956
Mallampati score
    110 (50%)4 (4.4%)2 (40%)4 (66.6%)
    24 (20%)2 (22.2%)2 (40%)0 (0%)
    34 (20%)3 (33.3%)0 (0%)1 (16.7%)
    42 (20%)0 (0%)1 (20%)1 (16.7%)
Tonsil size
    06 (30%)3 (33.3%)2 (40%)1 (16.7%)
    13 (15%)1 (11.1%)2 (40%)0 (0%)
    26 (30%)4 (44.4%)0 (0%)2 (33.3%)
    35 (25%)1 (11.1%)1 (20%)3 (50%)
    40 (0%)0 (0%)0 (0%)0 (0%)
Tonsillectomy, n4211

Results: n (%). One missing value for each group and each outcome. OSA, obstructive sleep apnea.

Postintervention.

The LIP significantly reduced body weight, BMI, BMI z-score, and FM (P < 0.05) and significantly increased FFM (P < 0.05; Table 1).

CRP and leptin concentrations decreased (P < 0.05 and P < 0.001, respectively) and adiponectin levels significantly increased (P < 0.05), whereas no changes were found in glycemia, insulin concentrations, or HOMAIR. A significant correlation between ∆ FMkg and ∆ leptin was found (r = 0.52, P < 0.01).

TST, N1, and REM sleep were increased (P < 0.05) while N3 was decreased (P < 0.05). N2 was not modified by the intervention. Total arousal and arousal index were increased (P < 0.05) while RDI, OAHI, ODI, Mean SpO2, and Min SpO2were not improved following LIP (Table 1). Furthermore, LIP increased the absolute V̇o2peak, relative V̇o2peakBW (P < 0.001), and V̇o2peakFFM (P < 0.05; Table 1).

OSA and Non-OSA Groups

Anthropometric and body composition assessments.

No anthropometric or body composition differences were found between OSA and non-OSA groups, and the LIP significantly reduced body weight, BMI, BMI z-score (time effect: P < 0.001), and FM (time effect: P < 0.05) and significantly increased FFM in both groups (time effect: P < 0.001; Table 1).

Upper airway assessments.

Three subjects (2 OSA subjects, 1 non-OSA subject) did not undergo the upper airway assessments. Regarding the Mallampati scores in the OSA group, six subjects exhibited Class 1, two exhibited Class 2, one exhibited Class 3, and two exhibited Class 4 scores. In the non-OSA group, Class 1 was found in four subjects, Class 2 in two subjects, and Class 3 in three subjects. No subject exhibited a Class 4 score (Table 2).

Regarding tonsil sizes in the OSA group, three subjects were Grade 0, two were Grade 1, two were Grade 2, and four were Grade 3. None presented a Grade 4 size. In the non-OSA group, three subjects were Grade 0, one was Grade 1, four were Grade 2, and one was Grade 3. In both groups, two subjects had a history of tonsillectomy (Table 2).

Biological and sleep parameters.

OSA subjects presented higher levels of CRP compared with non-OSA subjects (group effect: P < 0.05), and the LIP significantly reduced CRP concentrations (time effect: P < 0.05; Table 1).

Leptin and adiponectin concentrations were similar between groups and were decreased and increased by the LIP (time effect: P < 0.001 and P < 0.05, respectively, Table 1). In the OSA and non-OSA groups, trends for a correlation between ∆FMkg and ∆ leptin were found, albeit they did not reach statistical significance (r = 0.54, P = 0.058; r = 0.62, P = 0.054, respectively).

Glucose and insulin concentrations were similar between groups and were not modified by the LIP. A time × group interaction was observed for HOMAIR. Variation rates in the OSA and non-OSA groups (−0.12 ± 0.33% and 0.21 ± 0.35%, respectively) were significantly different (P < 0.05), reflecting decreased HOMAIR in the OSA group with LIP.

TST was not different between groups and was increased by the LIP (time effect: P < 0.05). N2, N3, and REM sleep were not different between groups. N1 was increased by the LIP (time effect: P < 0.001, interaction: P < 0.05). Paired Student’s t-tests showed a significant increase of N1 in the non-OSA group (P < 0.001) and no change in the OSA group. N3 was decreased by the LIP (time effect: P < 0.05), and REM sleep was not modified despite a trend for a time effect (P = 0.06). N2 was not changed by the intervention, whereas total arousal and arousal index were increased (time effect: P < 0.05). ODI, Mean SpO2, and Min SpO2were not different between groups and were not modified by the intervention.

A group effect and a time × group interaction were observed for OAHI (group effect: P < 0.001, interaction: P < 0.05) and RDI (group effect: P < 0.001, interaction: P < 0.01). Paired Student’s t-test showed a significant decrease of OAHI in the OSA group (P < 0.05), whereas no changes were observed in the non-OSA group. By contrast, RDI was increased in the non-OSA group (P < 0.01) but was not modified in the OSA group (Table 1).

Cardiorespiratory fitness.

OSA subjects exhibited similar absolute V̇o2peak, relative V̇o2peakBW, and V̇o2peakFFM to those measured in non-OSA subjects, which improved in both groups at the end of the program (time effect: P < 0.001, P < 0.001 and P < 0.05, respectively; Table 1).

According to the change in OAHI between admission and postintervention in the OSA group, two subgroups were then distinguished; normalized (OAHI < 2, 6 subjects, 46%) and residual OSA subjects (OAHI ≥ 2, 7 subjects, 54%).

Normalized and Residual OSA Groups

At the end of the intervention, OSA changes were equally distributed between boys and girls; OSA was normalized in three girls and three boys (“normalized OSA group”) and OSA was residual in four girls and three boys (“residual OSA group”).

Regarding Mallampati scores, two normalized OSA subjects were Class 1, two were Class 2, zero were Class 3, and one was Class 4. In the residual OSA group, four subjects were Class 1, zero were Class 2, one was Class 3, and one was Class 4 (Table 2).

Regarding Tonsil sizes, Grade 0 was observed in two normalized OSA subjects and Grade 1 was observed in two subjects. Zero subjects were Grade 2, and one was Grade 3. Finally, one was Grade 4. In the residual OSA group, one subject was Grade 0, zero were Grade 1, two were Grade 2, three were Grade 3, and zero were Grade 4. A history of tonsillectomy was reported for one normalized OSA subject and one residual OSA subject (Table 2).

Except for OAHI and ODI, which were higher in the residual OSA group compared with the normalized OSA group (group effect: P < 0.05), similar values in anthropometric, body composition, inflammatory, sleep duration, and cardiorespiratory parameters were observed between these two groups (Table 3).

Table 3. Anthropometric and body composition assessments, biological and sleep parameters and cardiorespiratory fitness between subjects with normalized and residual OSA

Normalized OSA, n = 6; 46%
Residual OSA, n = 7; 54%
At admissionAt 9 moΔAt admissionAt 9 moGroup EffectTime EffectInter-action
Girls/boys, n3/34/3Δ
Anthropometric and body composition assessments
Weight, kg119.80 (29.85)106.10 (21.16)−13.70 (11.45)111.20 (17.80)98.50 (19.44)−12.70 (7.92)NSNS***NS
BMI, kg/m242.40 (10.06)36.69 (7.23)−5.75 (4.25)42.15 (6.64)36.22 (6.90)−5.92 (3.26)NSNS***NS
BMI z-score4.89 (1.28)4.18 (1.22)−0.71 (0.42)4.98 (1.09)4.16 (1.44)−0.82 (0.53)NSNS***NS
WC, cm122.50 (21.23)97.67 (13.71)−24.83 (13.67)124.43 (16.09)101.29 (12.80)−23.14 (12.28)NSNS***NS
FM, %39.60 (6.24)34.24 (6.15)−5.36 (6.05)40.24 (6.01)33.84 (3.30)−6.40 (7.33)NSNS**NS
Biological parameters
CRP, mg/l10.45 (8.76)6.10 (2.71)−4.35 (7.65)11.49 (7.11)7.45 (5.12)−4.04 (3.71)NSNS*NS
Leptin, ng/ml53.93 (18.19)38.27 (13.11)−15.66 (19.78)73.89 (18.95)46.06 (20.97)−27.83 (25.38)NSNS**NS
Adiponectin, µg/ml7.38 (1.49)7.86 (2.06)0.47 (1.12)6.77 (2.86)10.70 (3.32)3.93 (3.90)NSNS*NS
HOMAIR4.08 (1.92)2.47 (0.88)§§§−1.61 (1.12)4.75 (2.34)4.83 (3.09)NS0.08 (1.38)NSNS*
Sleep parameters
OAHI, nb/h2.57 (0.53)0.68 (0.34)−1.88 (0.81)4.63 (3.35)4.81 (2.84)0.19 (3.49)NS*NSNS
ODI, nb/h3.75 (1.44)1.62 (0.92)−2.13 (1.89)6.96 (6.19)7.03 (4.38)0.07 (7.11)NS*NSNS
TST, min453.33 (23.40)496.50 (36.22)44.17 (36.22)435.29 (22.04)474.67 (57.12)39.38 (56.13)NSNS**NS
N1, %TST3.02 (1.79)6.62 (2.18)§3.60 (2.97)8.00 (2.33)5.78 (3.32)NS−2.22 (4.52)*NS*
N2, %TST53.03 (4.11)50.97 (7.39)−2.07 (6.52)52.50 (4.45)52.07 (6.43)−0.43 (7.45)NSNSNSNS
N3, %TST23.00 (3.13)19.53 (3.11)−3.47 (2.15)20.74 (6.84)20.18 (3.27)−0.56 (7.34)NSNSNSNS
REM, %TST20.95 (2.63)22.88 (4.39)1.93 (4.79)18.70 (3.67)21.99 (6.49)3.29 (6.63)NSNSNSNS
Cardiorespiratory fitness
o2peak, l/min2.73 (0.64)2.98 (0.63)0.23 (0.35)2.39 (0.36)2.50 (0.45)0.11 (0.26)NSNSNSNS
o2peakBW, ml·min−1·kg−123.50 (2.88)29.00 (1.90)5.50 (2.43)21.50 (1.26)26.50 (4.99)5.00 (4.11)NSNS***NS
o2peak FFM, ml·min−1·kg−140.68 (8.83)45.47 (6.73)4.79 (4.46)36.55 (2.88)40.51 (5.90)3.95 (3.27)NSNS**NS

Values are presented as means (SD). BMI, body mass index; CRP, C-reactive protein; FM, fat mass; HOMAIR, homeostasis model assessment of insulin resistance; N1, stage N1 sleep; N2, stage N2 sleep; N3, stage N3 sleep; OAHI, obstructive apnea-hypopnea index; ODI, oxygen desaturation index; OSA, obstructive sleep apnea; REM, rapid eye movement sleep; TST, total sleep time; V̇o2peak, absolute peak oxygen uptake (l/min); V̇o2peakBW, peak oxygen uptake expressed relative to body weight (ml·min−1·kg−1); V̇o2peakFFM, peak oxygen uptake expressed relative to fat-free mass (ml·min−1·kg−1); WC, waist circumference; Δ, change in values between admission and postintervention. Unpaired Student’s t-test for parametric data and Mann-Whitney test for nonparametric data for comparison of delta values between normalized OSA and residual OSA groups; Two-way repeated measures ANOVA for comparison per group; nonparametric data are log transformed; NS, not significant;

P < 0.05.

*P < 0.05;

**P < 0.01;

***P < 0.001.

Paired Student’s t-test for comparison by groups between admission and post intervention; NS, not significant;

§P < 0.05;

§§§P < 0.001.

Anthropometric parameters (time effect: P < 0.05) and FM% (time effect: P < 0.01) decreases were observed. CRP and leptin concentrations decreased (time effect: P < 0.01 and P < 0.05, respectively) while adiponectin concentrations increased (time effect: P < 0.01) with the LIP. In the normalized OSA group, a correlation between ∆FMkg and ∆ leptin was found (r = 0.89, P < 0.05), although it was not observed in the residual OSA subjects (r = 0.43, P = 0.36).

As for HOMAIR, a time × group interaction was observed (P < 0.05). Paired Student’s t-tests revealed a decrease of HOMAIR in the normalized OSA group (P < 0.001), whereas no changes were observed in the residual OSA group.

TST was improved by the LIP (time effect: P < 0.001). N2, N3, and REM sleep were not modified by the LIP, whereas a group effect (P < 0.05) and a time × group interaction (P < 0.05) were observed for N1. Paired Student’s t-tests showed an increase of N1 in the normalized OSA group (P < 0.05) and no change in the residual OSA group. OAHI and ODI were not significantly modified by the intervention.

Finally, LIP significantly improved relative V̇o2peakBW and V̇o2peakFFM in both groups (time effect: P < 0.05), whereas absolute V̇o2peak was not modified (Table 3).

Associations of Pro- and Anti-Inflammatory Markers with Sex, Weight Status, Sleep, and Cardiorespiratory Parameters

At admission.

A significant association between CRPlog, sex, and waist circumference was found (adjusted r2 = 0.18, P < 0.05), whereas no significant associations were found with BMI z-score, FMlog and FFMlog, and relative V̇o2peak or V̇o2peakFFM log.

ANCOVA showed a significant association between CRPlog, sex, and BMI (model 1; adjusted r2 = 0.24, P = 0.02). This association persisted after adjusting for ODIlog, arousal index (model 2; adjusted r2 = 0.30, P = 0.03), TST (model 3; adjusted r2 = 0.31, P = 0.04), and V̇o2peakBW (model 4; adjusted r2 = 0.32, P < 0.05). After an adjustment for V̇o2peakFFM, the model was no longer significant (model 4bis; adjusted r2 = 0.27, P = 0.07). These data are reported in Table 4.

Table 4. BMI is associated with basal CRP levels after controlling for sex, ODI, arousal index, sleep duration, and V̇o2peakBW (models 1, 2, 3, and 4)

Factor
Model
βtPr2Adjusted r2P
Model 1
    Sex0.080.410.690.310.24<0.05
    BMI0.512.550.02
Model 2
    Sex−0.10−0.450.660.420.30<0.05
    BMI0.642.950.008
    ODIlog0.120.560.58
    Arousal index−0.42−1.860.08
Model 3
    Sex−0.10−0.690.500.460.31<0.05
    BMI0.703.170.005
    ODIlog0.090.390.70
    Arousal index−0.42−1.890.08
    TST−0.21−1.180.26
Model 4
    Sex−0.18−0.810.430.500.32<0.05
    BMI0.622.690.015
    ODIlog0.100.450.66
    Arousal index−0.45−2.020.06
    TST−0.21−1.160.26
    V̇o2peakBW−0.221.130.27
Model 4bis
    Sex−0.15−0.660.520.460.270.07
    BMI0.703.080.01
    ODIlog0.090.400.69
    Arousal index−0.43−1.850.08
    TST−0.21−1.140.27
    V̇o2peakFFM−0.04−0.210.84

BMI, body mass index; CRP,  C-reactive protein; ODI, oxygen desaturation index; TST, total sleep time; V̇o2peakBW, peak oxygen uptake expressed relative to body weight (ml·min−1·kg−1); V̇o2peakFFM, peak oxygen uptake expressed relative to fat-free mass (ml·min−1·kg−1); Bold values are significant values; n = 23 subjects.

At admission, positive significant relationships between leptin concentrations and FMlog (adjusted r2 = 0.27, P = 0.01) and a negative association with FFMlog (adjusted r2 = 0.25, P = 0.02) were found after adjustment for sex. Adiponectin levels were negatively associated with waist circumference after controlling for sex (adjusted r2 = 0.19, P < 0.05).

LIP-induced changes.

A negative association between ΔCRP and ΔV̇o2peakBW after adjusting for sex (adjusted r2 = 0.53, P < 0.001) was found. Similarly, a relationship between ΔCRP and ΔV̇o2peakFFM was also observed despite a sex effect (adjusted r2 = 0.70, P < 0.01). No relationship was observed with Δ waist circumference, ΔBMI z-score, ΔFM, and ΔFFM.

A significant association was found between ΔCRP and ΔBMI after adjusting for sex (model 1; adjusted r2 = 0.33, P = 0.02), ΔODI, and Δ arousal index (model 2; adjusted r2 = 0.38, P < 0.05). This relationship was not significant after adjusting for ΔTST (model 3; adjusted r2 = 0.34, P = 0.08). Nevertheless, when adjusting for ΔV̇o2peakBW, a significant relationship between ΔCRP concentrations and ΔV̇o2peakBW appeared (model 4; adjusted r2 = 0.77, P < 0.001). A similar association was found between ΔCRP levels and ΔV̇o2peakFFM after adjusting for sex, ΔBMI, ΔODI, Δ arousal index, and ΔTST (model 4bis; adjusted r2 = 0.75, P < 0.05). These data are reported in Table 5.

Table 5. ΔV̇o2peak is associated with ΔCRP after controlling for sex, ΔODI, Δ arousal, and ΔTST

Factor
Model
βtPr2Adjusted r2P
Model 1
    Sex0.180.070.950.410.33<0.05
    ΔBMI1.232.930.01
Model 2
    Sex0.000.010.990.540.38<0.05
    ΔBMI0.722.630.022
    ΔODI−0.05−0.180.86
    Δ Arousal index0.321.130.28
Model 3
    Sex0.600.150.880.550.340.08
    ΔBMI1.502.570.026
    ΔODI−0.05−0.120.91
    Δ Arousal index0.331.120.29
    ΔTST−0.01−0.550.59
Model 4
    Sex−1.24−0.410.690.870.77<0.001
    ΔBMI−0.17−0.290.78
    ΔODI0.822.300.05
    Δ Arousal index−0.27−1.000.35
    ΔTST−0.01−0.640.54
    ΔV̇o2peakBW−1.97−4.100.003
Model 4bis
    Sex−1.25−0.320.760.890.75<0.05
    ΔBMI0.570.980.37
    ΔODI0.801.640.16
    Δ Arousal index−0.33−0.910.40
    ΔTST−0.02−1.130.31
    ΔV̇o2peakFFM−1.08−3.250.023

ΔBMI is associated with ΔCRP after controlling for sex, ΔODI, and Δ arousal index (models 1 and 2). ΔV̇o2peakBW and ΔV̇o2peakFFM are associated with ΔCRP after controlling for sex, ΔODI, Δ arousal, and ΔTST (models 4 and 4bis). BMI, body mass index; CRP, C-reactive protein; ODI, oxygen desaturation index; TST, total sleep time; V̇o2peakBW, peak oxygen uptake expressed relative to body weight (ml·min−1·kg−1); V̇o2peakFFM = peak oxygen uptake expressed relative to fat-free mass (ml·min−1·kg−1); Δ, change in values between admission and postintervention. Bold values are significant values; n = 23 subjects.

Concerning leptin and adiponectin concentrations, associations were no longer observed between Δ leptin, ΔFM, and ΔFFM, or between Δ adiponectin and Δ waist circumference.

DISCUSSION

Lifestyle modification is the first line of treatment for pediatric obesity in Europe, but its effects on inflammation in an adolescent obese population at risk for OSA are not elucidated. In the present study, we aimed to assess the relationship between inflammation and OSA and to study whether the LIP’s effects on inflammatory markers were associated with changes in anthropometric parameters, cardiorespiratory fitness, short sleep, and OSA severity in severely obese adolescents. We reported that although CRP was greater in OSA subjects at baseline, LIP-induced, decreased CRP levels were driven by reduction in those with OSA. Additionally, the decrease in CRP concentrations postintervention in the whole population was associated with enhanced cardiorespiratory fitness after controlling for sex, weight loss, and changed sleep parameters.

At admission, CRP levels in the OSA and non-OSA groups were respectively 11 and 5 times higher than normal levels (63). The CRP levels in this population reflect systemic low-grade inflammation and are associated with the degree of obesity and cardiovascular risk (64). On the other hand, OSA is also recognized as a proinflammatory factor, despite conflicting results in the obese pediatric population (33, 66, 70). In the present study, the CRP concentrations in the OSA group were twice as high at admission as those in the non-OSA subjects. These results are in contradiction with those of Van Eyck et al. (70), who did not find any difference in CRP levels between obese individuals without OSA, those with mild OSA, and those with moderate-to-severe OSA. When we compare the OSA and non-OSA subjects in our population, no significant differences in anthropometric parameters or body composition were found. However, a greater degree of obesity in the OSA group was clinically observed and might explain the higher levels of CRP compared with the non-OSA subjects.

Leptin is known to regulate energy balance and satiety signaling (79) and is also implicated in breath control (56). Elevated leptin concentrations reflect the adipose tissue dysfunction observed in obese individuals and contribute to systemic inflammation. Independently, leptin resistance is also associated with OSA (58). Unexpectedly, similar levels of leptin were observed in both groups. In our population, leptin levels were higher than those reported in previous studies (12, 22), and it may be hypothesized that the morbid degree of obesity in our population outweighs the potential effects of OSA and altered sleep on the release of proinflammatory adipokines.

When considering sleep parameters, we found similar short sleep duration, intermittent hypoxia, and sleep fragmentation between OSA and non-OSA subjects. These factors are all known to promote systemic inflammation through sympathetic overactivation and oxidative stress independently of obesity (5, 11, 43) and may explain the high concentrations of CRP in the whole population. The multiple factors contributing to systemic inflammation and their potentiation led us to investigate their specific impact on its etiology. ANCOVA analyses allowed us to determine that the degree of obesity alone was associated with systemic inflammation, even after controlling for sex, chronic intermittent hypoxia, sleep fragmentation, short sleep duration, and low cardiorespiratory fitness. Although discordant with the findings of other authors (66, 71), this finding reinforces the hypothesis that the morbid degree of obesity outweighs the additional effects of sleep disorders, independently of sex, and is associated with the very high levels of leptin and low concentrations of adiponectin in the individuals regardless of group.

Overall, in accordance with other authors, the LIP induced positive changes regarding inflammation in our whole population, with decreased CRP and increased adiponectin levels (12, 71). As expected, the decrease in leptin concentration was associated with FM lowering (44). Specifically, CRP levels only decreased in the OSA group. Indeed, CRP profiles were improved with similar values to the non-OSA group in postintervention, suggesting that the LIP-lowered CRP was driven by reduction in those with OSA, although these concentrations remained alarming.

Thus, despite the small sample size, it was relevant to observe the impact of LIP on OSA, namely normalized (n = 6) and residual (n = 7) OSA subjects. First, these subjects exhibited similar clinical phenotypes at admission, except for OAHI and ODI, which were higher in residual OSA and remained unchanged in postintervention. Nevertheless, leptin concentrations appeared clinically higher in the residual OSA group, but the sample size may have blunt potential significance. Regarding the influence of the LIP, residual and normalized OSA subjects exhibited identical changes in body weight, fat mass, CRP levels, and cardiorespiratory fitness. Interestingly, a positive association was observed between leptin decrease and FM loss in normalized OSA subjects, while such a relationship was not confirmed in the residual OSA subjects. The small sample size and the important interindividual variability require considering results with caution. It is therefore difficult to explain why some subjects responded to the program and others did not in terms of OSA. However, residual OSA subjects exhibited higher Mallampati scores and tonsil sizes by comparison with normalized OSA subjects. These results might explain the failure of the LIP to normalize OSA in these subjects because upper airway abnormalities represent a risk factor for OSA in children and adolescents (40, 75). Additionally, a recent study provided new insights by showing that respiratory allergies were a predictive factor for residual OSA after a lifestyle intervention in obese adolescents (69).

Second, subjects with normalized OSA exhibited increased sleep duration and decreased insulin resistance. It has previously been shown that both OSA (7, 76) and short sleep duration (32, 39) independently induce insulin resistance, and treating OSA thus appears to be a valuable strategy to improve insulin sensitivity. The small sample size obliges us to consider these results with caution, but nonetheless provides new perspectives in terms of OSA management in the obese adolescent population.

On the other hand, arousals were unexpectedly increased in the whole population and in each group at the end of the program, and RDI was increased in the non-OSA group. In addition to a longer TST, we have also observed an increase in the proportion of REM sleep (%) and N1 sleep stage (%) and a decrease of the N3 sleep stage (%) in our subjects at the end of the LIP. REM sleep is a stage during which respiratory events occur more frequently by comparison to N3 sleep (52), and some authors reported that 55% of respiratory events in youths occur during REM sleep (80). This phenomenon was visually observed during sleep analyses in the present study and the modifications in sleep architecture may therefore explain the increase of the proportion of arousals because respiratory events are frequently associated with oxygen desaturation and arousals, leading to sleep fragmentation expressed by increased N1 (53). In 2000, Goh et al. (80) also reported a higher arousal index during REM in youths.

Finally, the decreased inflammation in the overall population, driven by reduction in OSA subjects, led us to investigate which factors could be associated with this improvement.

Regarding the whole population, and as expected, weight loss was associated with the decrease in low-grade inflammation after adjusting for change in sleep fragmentation and intermittent hypoxia. However, this association disappeared after controlling for enhanced cardiorespiratory fitness relative to body weight. Surprisingly, improved cardiorespiratory fitness, when adjusted for all the parameters set out above, was associated with the decrease in inflammation among 77%. These results might, in part, explain those of Van Hoorenbeeck et al. (71). As such, while inflammatory markers were associated with both OSA and the severity of obesity in adolescents at entrance to the LIP, the lowering of the inflammatory profile postintervention was not related to improvements in either sleep or anthropometric parameters. The authors concluded that the lowering of the inflammatory profile was possibly due to the concomitant effects of weight loss and the normalization of sleep parameters (71). The program included at least 10 h/wk of regular exercise, but changes in cardiorespiratory fitness were not assessed and might have played a pivotal role in the decrease of the inflammatory markers.

Indeed, it is well known that cardiorespiratory fitness has a favorable impact on inflammation (47, 49, 61), but its effects as a component of a LIP remain controversial (21, 41, 54). However, in the present study, cardiorespiratory fitness was objectively assessed and allows us to confirm that improved fitness decreased inflammation in obese adolescents. On the other hand, other studies (2, 28) have discussed whether enhanced fitness might be explained by fatness. The use of V̇o2peak relative to body weight is open to criticism because it is strongly related to adiposity and may alter the independent effect of fitness. As suggested by other authors (2, 28), V̇o2peakFFM may be the best indirect estimate of the metabolic capacity of the muscle. In the present study, when adjusted for sex, weight loss, and change in sleep parameters, the decrease of inflammation is associated among 75% with cardiorespiratory fitness related to FFM.

Fatness and fitness are two factors independently involved in inflammation state (27, 47). Despite a significant decrease in body weight and adiposity, the present population remained drastically fat postintervention. In the context of severe obesity, enhanced fitness modified the impact of excess body weight on inflammation. Fitness is thus protective against obesity-induced inflammation, and a LIP involving exercise training appears to be a valuable health strategy for this population. Although the anti-inflammatory effect of exercise could be explained by the increased adiponectin levels, further studies are warranted to better understand these mechanisms.

This study has some limitations that deserve to be underlined. The sample size is small, especially when considering normalized OSA and residual OSA subgroups, and the heterogeneity of the population requires considering results with caution. Additionally, it would have been relevant to determine the menstrual cycle’s phase in girls, as this outcome may influence leptin concentrations (1). Mostly, it would have been interesting to assess some proinflammatory cytokine profiles (e.g., interleukin-6, tumor necrosis factor-α) to complete the systemic inflammation profile.

In our study, subjects underwent ambulatory polysomnography, but it would have been useful to have one adaptation night before the recording used for study purposes. However, the logistic conditions of this study, plus the drawbacks of polysomnography, e.g., high cost and time-consuming process, were limitations on the feasibility of allowing one night of adaptation. Furthermore, the measurement of carbon dioxide concentrations by capnometry during the night would have been interesting for the assessment of the obesity hypoventilation syndrome, as often found in obese subjects. However, because of the planning of the protocol, this measurement could not be achieved. In addition to bio-impedance analyses, it would also have been interesting to perform a direct measure of fat (e.g., dual X-ray absorptiometry).

Perspectives and Significance

Chronic exercising in part of a LIP represents an inexpensive and effective tool for the improvement of fitness and cardiometabolic health in adolescents with severe obesity and sleep disturbances, independently of weight loss and fatness. Additionally, exercise is known to normalize OSA (30). In France, 190,000 youths are obese (72) and approximatively a half of them suffer from OSA (59), despite this syndrome being underdiagnosed. Systemic inflammation, promoted by both obesity and sleep disorders, represents a main risk factor for cardiometabolic diseases and warrants particular attention (14, 68). As such, it would be relevant to assess, in further studies, the effects of exercise training modalities on markers of systemic inflammation and immune function and OSA severity in obese adolescents. If continuous moderate chronic exercise has shown beneficial effects on immune function in healthy and obese subjects (35, 55), other modalities of exercise training, such as high intensity interval training or concurrent training, are worth assessing in this population of obese adolescents with OSA and sleep disturbances.

In conclusion, this study shows that despite higher amounts of CRP in adolescents with OSA, obesity outweighs the proinflammatory effects of short sleep duration, sleep fragmentation, intermittent hypoxia, and low cardiorespiratory fitness and is associated with the systemic inflammation at admission to a LIP. Although the program was not effective in normalizing OSA in all subjects, the levels of CRP and adipokine profiles were improved at the end of the study in the overall population, even though concentrations remained alarming. Overall, we show that the decrease in inflammation in this severely obese adolescent population is associated with enhanced cardiorespiratory fitness related to FFM after controlling for sex, weight loss, and changes in sleep duration, intermittent hypoxia, and sleep fragmentation. It is worth noting that the decreased CRP levels are driven by reduction in OSA subjects. To the best of our knowledge, this is the first study to assess this relationship in this population independently of fatness.

In view of the long-term health implications of obesity and OSA and the challenging management of these two diseases in an adolescent population, these results provide new insights, and further studies in larger samples of subjects are warranted to better explore the relationship between fitness and inflammation in obese adolescents with sleep disturbances.

GRANTS

This work was supported by a grant from Le Don Du Souffle (Besançon, France).

DISCLOSURES

No conflicts of interest, financial or otherwise, are declared by the authors.

AUTHOR CONTRIBUTIONS

J.R., L.I., V.G., and F.M. conceived and designed research; J.R., F.P., and V.G. performed experiments; J.R., L.I., F.P., G.D., V.G., and F.M. analyzed data; J.R., L.I., F.P., G.D., V.G., and F.M. interpreted results of experiments; J.R. prepared figures; J.R. and L.I. drafted manuscript; J.R., L.I., F.P., G.D., V.G., and F.M. edited and revised manuscript; J.R., L.I., F.P., G.D., V.G., and F.M. approved final version of manuscript.

ACKNOWLEDGMENTS

The authors thank “Le Don Du Souffle” for financial support, the Sleep Medicine Center “Ellipse” for technical support, and Fiona Ecarnot for editorial assistance. The authors address special thanks to Fanny Capellier for precious help in sleep scoring and advice and thank Jocelyne Gototte and Barbara Dehecq for the blood sample analyses. The authors are grateful to Olivier Marlot, Solène Martin, and the staff of “La Beline” for technical assistance. The authors address particular words of thanks to the study participants and their parents.

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AUTHOR NOTES

  • Address for reprint requests and other correspondence: J. Roche, Sports Science Faculty, University of Bourgogne Franche-Comté, 31 Chemin de l’Epitaphe, 25000 Besançon, France (e-mail: ).