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Международный эндокринологический журнал Том 19, №5, 2023

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Зв’язок між масою тіла, рівнем серотоніну, станом психічного здоров’я, порушенням сну та обміном речовин у пацієнтів з ожирінням

Зв’язок між масою тіла, рівнем серотоніну, станом психічного здоров’я, порушенням сну та обміном речовин у пацієнтів з ожирінням

Авторы: V.I. Tkachenko, T.O. Bagro
Shupyk National Healthcare University of Ukraine, Kyiv, Ukraine

Рубрики: Эндокринология

Разделы: Клинические исследования

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Резюме

Актуальність. Значне поширення ожиріння спонукає дослідників до пошуку етіопатогенетичного лікування шляхом вивчення зв’язків і залежностей гормонального, нейрохімічного та психосоматичного компонентів. Мета: визначити кореляцію між масою тіла, рівнем серотоніну, станом психічного здоров’я, розладами сну та обміном речовин у пацієнтів з ожирінням. Матеріали та методи. У когортному проспективному дослідженні протягом шести місяців спостерігали 75 осіб з ожирінням. Пацієнти були розподілені на дві групи залежно від виявлених психосоціальних особливостей та розладів сну з відповідним лікуванням із застосуванням пацієнт-орієнтованого підходу. Обстеження включало визначення індексу маси тіла (ІМТ), окружності талії та стегон, індексів абдомінального ожиріння (BSA, WHR, ConI, ABSI, AVI), артеріального тиску, ліпідного профілю, рівнів глюкози натще, інсуліну, лептину, серотоніну, оцінку психосоціального статусу та якості сну за допомогою шкал HADS, Бека, Гамільтона, сонливості Епворта (ESS), Піттсбурзького індексу якості сну (PSQI), якості життя за опитувальником SF-36. Статистичний аналіз проводили з використанням програм IBM SPSS Statistics, Statistica 12, Excel 2010. Результати. У пацієнтів визначено ожиріння І та ІІ ступенів. Розрахункові показники абдомінального ожиріння, параметри ліпідного та вуглеводного обміну, бали за опитувальниками харчової поведінки, тривоги та депресії, якості сну, сонливості та рівень лептину перевищували рекомендовані значення, при цьому вміст серотоніну, показник шкали SF-36 мали низькі значення, що значно покращувалось у динаміці лікування. На початку дослідження виявлено сильні прямі кореляційні зв’язки між ІМТ, окружністю талії і стегон, індексами абдомінального ожиріння, артеріальним тиском, показниками ліпідного та вуглеводного обміну, рівнем лептину, оцінкою за шкалами HADS, Бека, Гамільтона, ESS, PSQI; відмічено сильну зворотну (негативну) залежність ІМТ від рівнів ліпопротеїнів високої щільності і серотоніну. Спостерігалася сильна негативна кореляція серотоніну з ІМТ, масою тіла, індексами BSA, ABSI, AVI, ConI, артеріальним тиском, показниками ліпідного та вуглеводного обміну, оцінкою за шкалами HADS, Гамільтона, Бека, PSQI (сонливість, якість, тривалість, ефективність сну) та ESS. Висновки. Високий ІМТ корелює з низьким рівнем серотоніну, підвищеним рівнем тривоги та депресії, сонливістю, погіршенням якості сну та життя, порушеннями ліпідного та вуглеводного обміну, які є взаємно обтяжливими факторами щодо розвитку ожиріння та інших неінфекційних захворювань; це необхідно враховувати при визначенні підходів до комплексного пацієнт-орієнтованого лікування ожиріння.

Background. The significant spread of obesity stimulates researchers to search for etiopathogenic treatment by studying the relationships and dependencies of the hormonal, neurochemical and psychosomatic components. The purpose of the study is to determine the correlation between body weight, serotonin level, mental health status, sleep disorders and metabolism in obese patients. Materials and methods. In a cohort, prospective study, 75 patients with obesity were observed for 6 months. They were divided into 2 groups depending on the detected psychosocial characteristics and sleep disorders with the appropriate treatment using a patient-oriented approach. The examination included studying body mass index (BMI), abdominal obesity indices (body surface area, waist/hip ratio, conicity index, a body shape index, abdominal volume index), blood pressure, lipid profile, fasting glucose, insulin, leptin, serotonin, assessment of psychosocial status and sleep quality with Hospital Anxiety and Depression Scale (HADS), Beck’s Depression Inventory (BDI), Hamilton Anxiety Rating Scale (HAM-A), Epworth Sleepiness Scale (ESS), Pittsburgh Sleep Quality Index (PSQI), quality of life using the SF-36 questionnaire. Statistical analysis was performed using IBM SPSS Statistics, Statistica 12, Excel 2010. Results. At baseline, the patients had obesity class I and II. Тhe calculated indices of abdominal obesity, indicators of lipid and carbohydrate metabolism, scores of questionnaires of eating behavior, anxiety and depression, quality of sleep, sleepiness and leptin level exceeded the recommended values, while the level of serotonin, the scores of the SF-36 had low values that significantly improved in dynamics. Strong direct correlations at baseline were found between BMI, abdominal obesity indices, blood pressure, indicators of lipid and carbohydrate metabolism, leptin, HADS, BDI, HAM-A, ESS, PSQI global score; a strong inverse (negative) relationship was noted between BMI and the levels of high-density lipoprotein and serotonin. A high negative correlation was found between serotonin and BMI, abdominal obesity indices (body surface area, a body shape index, abdominal volume index, conicity index), blood pressure, indicators of lipid and carbohydrate metabolism, HADS, HAM-A, BDI, PSQI global score, sleep quality, latency, duration, efficiency and the ESS. Conclusions. The high BMI correlates with a low level of serotonin, increased level of anxiety and depression, drowsiness, deterioration of the quality of sleep and life, disorders of lipid and carbohydrate metabolism, which are mutually aggravating factors for the development of obesity and other non-infectious diseases; it must be taken into account when determining approaches to comprehensive patient-oriented treatment of obesity.


Ключевые слова

ожиріння; серотонін; порушення сну; тривога; депресія; кореляція

obesity; serotonin; sleep disorder; anxiety; depression, correlation

doi: http://dx.doi.org/10.22141/2224-0721.19.5.2023.1299

Introduction

The rapid epidemiological spread of obesity in the world increasingly provokes scientists to search for pathogene–tic treatment. Today, the pathogenetic neurochemical and hormonal mechanisms of regulation eating behavior and appetite are known [1]. Mostly, they can be provoked either by genetic predisposition, because 430 genes are known can increase body mass index (BMI) [2], or by response to exo–genous stimulation, which can be long-term stress, disruption of circadian rhythms, physical activity, profession, marital status, education, level of financial support [3].
The relationship of pathogenetic mechanisms is closed in a ring of dependencies at the level of the hypothalamus, so it is quite often difficult to determine the root cause of obesity. The centers of hunger, satiety, sleep-wake are located in the hypothalamus and are mostly mediated by the serotonergic system. Preproorexin is expressed in the lateral hypothalamus, from which orexin-A (hypocretin-1) and orexin-B (hypocretin-2) are formed. They affect areas of the brain (hypothalamus, thalamus, hippocampus, midbrain nuclei, prefrontal cortex, suture nuclei) through G-protein bound receptors OX1R and OX2R [4]. The participation of these receptors in stressor mechanisms, regulation of –eating behavior, metabolic processes, immune response has been proven [5], OX1R and OX2R are also peptides of the incretin gene, which includes glucagon-like peptide-1, the effectiveness of which in the treatment of obesity is increasing every year [6]. Insufficient concentration of orexin leads to excessive sleepiness and obesity [7]. While a decrease in serotonin leads to similar consequences, which may be due to the effect of chronic stress and increased levels of anxiety and depression. The influence of serotonin on the regulation of food consumption and body weight has been confirmed experimentally [8]. Cerebral levels of serotonin (5-HT) in animal models are inversely proportional to food intake and body weight, and some effective anti-obesity agents include serotonin transporter blockade [9].
Thus, the positive effect of serotonin agonist on the process of obesity treatment are proved [10]. Animal models showed that serotonin receptor agonists reduce the operant response to food [11]. An inverse correlation was found bet–ween the cerebral binding of the serotonin transporter and BMI [12]. Serotonin concentration was negatively associated with age, weight, BMI, fat mass [13]. Low levels of central serotonin (5-HT) found in overweight individuals lead to both increased food intake and compensatory regulation of cerebral 5-HT(2A) receptor density [14]. But these relationships remain insufficiently studied and are under study. In order to clarify this issue, it is necessary to analyze the relationship between the development of obesity and the state of physical and psycho-social health more and more carefully.
The purpose was to determine the correlation between body weight, serotonin level, mental health status, sleep disorders and metabolism in obese patients.

Materials and methods

A cohort, prospective study was conducted among 75 obese patients (BMI 30–40 kg/m2), aged 39.03 ± 0.93 years, women (n = 39) and men (n = 36), within 6 months. Inclusion criteria were: age from 25 to 54 years, BMI 25.0–39.9 kg/m2.
Exclusion criteria: presence of excess body weight, age under 25 years and above 54 years, pregnancy, breastfee–ding, pronounced allergic reactions in history (angioedema, bronchial asthma, generalized urticaria), chronic disea–ses (polycystic ovary syndrome, hypothyroidism, Cushing’s syndrome, diabetes, resistant arterial hypertension, chronic kidney disease stage 2–5), refusal of the patient to participate in the study.
Patients with obesity were divided into 2 groups: I (37 people) and II (38 people) depending on the detected psychosocial characteristics and sleep disorders (shift work disorder). Sleep disorder was defined according to criteria of Diagnostic and Statistical Manual of Mental Disorders, 5th edition and International Classification of Sleep Disorders, 3rd edition (compliance with criteria A-D) [15, 16].
Treatment of obesity in patients included motivatio–nal counseling with a patient-oriented approach regarding healthy diet and lifestyle, physical activity, sleep hygiene, correction of risk factors in accordance with current clinical protocols. Patients with detected shift work sleep disorder additionally received armodafinil in a dose of 150 mg in accordance with the clinical guidelines American Academy of Sleep Medicine (2021) [17] and FDA recommendations [18].
All patients who participated in the study signed the informed consent Information for research subjects and informed consent form, which was approved by the Ethics Commission at Shupyk National Healthcare University of Ukraine (protocol No. 10 dated 12.23.2019).
The health status of the patients was assessed at the baseline and in the dynamics after 1, 3 and 6 months of treatment using Hospital Anxiety and Depression Scale (HADS), Beck’s Depression Inventory (BDI), the Hami–lton Scale (HAM-A), Epworth Sleepiness Scale (ESS), Pittsburgh Sleep Quality Index (PSQI), quality of life SF-36 questionnaire; anthropometric indicators — height, weight, waist circumference (WC), hip circumference (HC), calculated indices of abdominal obesity (body surface area (BSA), waist-to-hip ratio (WHR), conicity index (ConI), a body shape index (ABSI), abdominal volume index (AVI)), systolic (SBP) and diastolic (DBP) blood pressure, laboratory indicators (lipidogram, fasting glucose, insulin, leptin, serotonin).
Statistical analysis of the obtained data was carried out using Student’s and Pearson’s tests using IBM SPSS Statitics, Statistica 12, descriptive statistics Excel 2010.

Results

At baseline the patients had obesity of the I and II degrees, the waist volumes of the patients exceeded the re–commended values, calculated indices of abdominal obesity, indicators of lipid and carbohydrate metabolism, scores of questionnaires of eating behavior, anxiety and depression, quality of sleep, sleepiness and leptin level exceeded the re–ference values, while the level of serotonin, the scores of the quality of life questionnaire and the level of physical activity had low values, more detailed results are presented in Table 1 and previous publications of Tkachenko V.I., Bagro T.O. (2022–2023) [19].
The indicators of anxiety, depression, sleep quality and sleepiness differed between groups (Table 1), which formed the basis for the use of different patient-centered treatment approaches.
The correlation analysis at baseline (Table 2) showed strong direct correlations between BMI and WC (r = 0.78), HC (r = 0.80), ConI (r = 0.58), AVI (r = 0.79), ABSI (r = 0.43), SBP (r = 0.71), DBP (r = 0.66), as well as levels of glucose (r = 0.75), insulin (r = 0.43), HOMA (r = 0.63), cholesterol (r = 0.65), LDL (r = 0.65), VLDL (r = 0.64), atherogenic index (r = 0.83), leptin (r = 0.75), HADS depression (r = 0.61) and anxiety (r = 0.51), Beck’s (r = 0.61), Hamilton (r = 0.45), sleepiness Epworth (r = 0.64), PSQI global score (r = 0.60); a strong inverse (negative) relationship of BMI with the level of HDL (r = –0.78) and serotonin (r = –0.55). After 1 month of treatment (Table 2), when a moderate decrease in body weight (pI > 0.05; pII > 0.05) and BMI (pI > 0.05; pII > 0.05) was noted in in both groups, the correlations changed somewhat. Thus, the strength of the correlation moderately weakened between BMI and WC (r = 0.76), HC (r = 0.79), ConI (r = 0.43), AVI (r = 0.77), SBP (r = 0.68), DBP (r = 0.56), glucose levels (r = 0.69), insulin (r = 0.45), HOMA (r = 0.61), cholesterol (r = 0.57), LDL (r = 0.59), VLDL (r = 0.67), atherogenic index (r = 0.77), leptin (r = 0.73), PSQI global score (r = 0.48).
In contrast, there was a stronger correlation between BMI and ABSI (r = 0.21), HADS depression (r = –0.14) and anxiety (r = –0.20), Beck’s (r = –0.05), Hamilton (r = 0.46) and Epworth sleepiness (r = 0.67). In the 3rd month of treatment, correlations between BMI and the studied indicators were characterized by a similar situation (Table 2). At the 6-month follow-up BMI significantly decreased in both groups relative to baseline (p < 0.001), anxiety and depression levels decreased from subclinical to normal values. The level of sleepiness and quality of sleep from excessive values were normalized.
A strong correlation remained between BMI and indicators: WC (r = 0.73), HC (r = 0.73), AVI (r = 0.74), glucose levels (r = 0.68), leptin (r = 0.66), LDL (r = 0.58), VLDL (r = 0.67), atherogenic index (r = 0.67), Epworth sleepiness scores (r = 0.59), ConI (r = 0.41), SBP (r = 0.58), DBP (r = 0.47), cholesterol (r = 0.56), insulin (r = 0.43), HOMA (r = 0.58), points of the Hamilton scale (r = 0.49). Correlations lost strength between BMI and ABSI indicators (r = 0.21), PSQI global score (r = 0.29), HADS depression (r = 0.16), anxiety (r = 0.03), Beck’s (r = 0.17).
When analyzing the correlations in each group separately, similar regularities were determined. The determined high strength of the inverse correlation of serotonin with BMI motivated a detailed consideration of serotonergic mechanisms of obesity development, namely the influence of psychosocial factors and circadian rhythm disruption.
The correlation analysis between the level of serum serotonin and the studied parameters at baseline (Table 3) showed a high negative relationship between body weight (r = –0.64), WC (r = –0.64), HC (r = –0.60), BMI (r = –0.55), BSA (r = –0.54), AVI (r = –0.63), ConI (r = –0.45), SBP (r = –0.48), DBP (r = –0.40), glucose (r = –0.59), insulin (r = –0.30), HOMA (r = –0.45), HDL (r = 0.56), LDL (r = –0.45), VLDL (r = –0.53), atheroge–nic index (r = –0.49), HADS scales of anxiety (r = –0.54), depression (r = –0.56), Hamilton (r = –0.58), Beck’s depression (r = –0.63), PSQI global score (r = –0.66), PSQI: sleep quality (r = –0.42), sleep latency (r = –0.51), sleep duration (r = –0.48), habitual sleep efficiency (r = –0.49) and the Epworth sleepiness scale (r = –0.66).
Correlation of medium strength was noted with sleep disturbance (r = –0.31), use of sleeping medication (r = –0.06), daytime dysfunction (r = –0.31) of the PSQI scale, total cholesterol (r = –0.35), ABSI (r = –0.38) and leptin (r = –0.36). After 1 month of treatment (Table 3), the concentration of serotonin in groups I (pІ > 0.05) and II (pII > 0.05) increased moderately, the mental state and sleep indicators tended to normalize, although not pronounced. Against this background, the relationship between serotonin and the studied indicators also changed, although not significantly. A high strength correlation remained between serotonin level and body weight (r = –0.55), BMI (r = –0.77), WC (r = –0.66), HC (r = –0.70), AVI (r = –0.66), ConI (r = –0.41), total cholesterol (r = –0.58), HDL (r = 0.66), LDL (r = –0.50), VLDL (r = –0.72), atherogenic index (r = –0.70), glucose (r = –0.72), insulin (r = –0.55), HOMA (r = –0.67), leptin (r = –0.56), Epworth sleepiness scale (r = –0.72), PSQI global score (r = –0.50), sleep latency (r = –0.36), sleep duration (r = –0.41).
Loss of correlation strength occurred between the le–vel of serotonin and scores of the Beck’s depression scale (r = –0.04), components of the sleep quality questionnaire, in particular, sleep quality (r = 0.09), habitual sleep efficiency (r = –0.21), sleep disturbance (r = –0.19), use of sleeping medication (r = –0.04), daytime dysfunction (r = –0.13).
After 3 months of therapeutic measures (Table 3), the level of serum serotonin in the II group increased significantly (p < 0.001), while in the I group, its increase was not reliable (p > 0.05) and the strength of correlation dependences for all indicators remained at the same level. At the 6th month of observation, the indicators were respectively body weight (r = –0.51), BMI (r = –0.75), WC (r = –0.74), HC (r = –0.70), ABSI (r = –0.42), ConI (r = –0.55), AVI (r = –0.72), HDL (r = 0.62), VLDL (r = –0.64), HOMA (r = –0.57), glucose (r = –0.69), atherogenic index (r = –0.60), insulin (r = –0.47), LDL (r = –0.51), choleste–rol (r = –0.45), leptin (r = –0.48), Beck’s scale (r = –0.28), PSQI global score (r = –0.38), sleep quality (r = 0.02), sleep latency (r = –0.14), sleep duration (r = –0.18), habitual sleep efficiency (r = –0.15), sleep disturbance (r = –0.05), use of sleeping medication (r = –0.07), daytime dysfunction (r = –0.32), Epworth scale (r = –0.59), taking into account the significant increase in serum serotonin in the II group (p < 0.001) and moderate in the 1st group (p < 0.05).

Discussion

A widely used indicator of obesity status in the world is BMI due to its easy use, in particular, in primary care [20]. The dependence between BMI with a significant number of indicators and indices on it was proved. The results of our study confirmed the highly correlated positive dependence of BMI and WC, HC, calculated indices of abdominal obesity BSA, WHR, ConI, ABSI, AVI in patients with obesity of the first and second degree, which coincides with the data of M. Gažarová et al. [21] and Y. Ou et al. [22], who also observed a similar dependence.
Indicators of carbohydrate metabolism — the level of glucose, insulin, the HOMA also depended on the degree of obesity and BMI, which was confirmed by the research of T.C. Adam et al. [23], A. Bahadur et al. [24], W. Boyer et al. [25].
Blood pressure levels and lipid metabolism indicators correlated with BMI, which confirms the data K. Foti et al. [26], W. Zhang [27], A. Arias et al. [28], who noted the pre–sence of such connections in their research. Although this dependence is controversial in the general population, given the research by D. Højland Ipsen et al. [29], there is the pre––sence of lipid metabolism disorders in patients with normal BMI as well.
The relationship between metabolic disorders underlines the need for a comprehensive approach to the treatment of obesity and the prevention of diabetes and other non-infectious diseases, emphasizing the features of diet therapy and lifestyle correction of patients.
Taking into account the increase of scientific interest in the impact of circadian rhythm and sleep disorders, the influence of psycho-emotional factors on the development of obesity, it is necessary to provide a more in-depth study of this problem and search for new approaches to the treatment and management of patients. A study of sleep quality in patients with obesity is recommended by the European Guidelines for Obesity Management in Adults [30], however, without specifying the methodology. Considering the unavailability of polysomnography in the primary care, the widely used questionnaires of Epworth and PSQI [31, 32] which have shown their effectiveness, can serve as preliminary tools for the study of such disorders.
Our study determined the presence of sleep disorders in some patients in the form of excessive sleepiness, shift work disorder and reduced sleep quality. We found correlations between sleep disorder, assessed using the Epworth and PSQI questionnaires, with BMI, which confirms the influence of sleep disturbance on the development of obesity. Similar assumptions about the relationship were made by R.P. Ogilvie and S.R. Patel [33], C. Antza et al. [34]. Studies by S. Jehan et al. [35] noted the development of obesity in patients with chronic sleep deprivation, namely shift work disorder. A number of other authors also testified to a strong relationship between sleep disturbance and the level of obesity. The most reliable confirmation of the effect of sleep disorders on obesity was obtained by conducting polysomnography in the studies of J.H. Jung et al. [36] and C. Primack [37]. A sleep study for evaluating patients with obesity is recommended by the European Guidelines for Obesity Management in Adults [30] and American Academy of Sleep Medicine [38].
It is known that the psycho-emotional state affects the quality of sleep and eating behavior of patients [39]. Our research focused on correlations between the level of anxiety, depression and the level of serotonin, as a hormone of “happiness” that affects the centers of hunger, satiety, sleep-vigor in the pathogenesis of obesity [40, 41]. We have proven the relationship of low serotonin with poor sleep quality, drow–siness, anxiety and depression, low physical functioning and quality of life in obese patients, as well as with impaired indicators of lipid and carbohydrate metabolism.
The correlation between BMI and leptin level that we found is logically significant, given that it is a hormone of adipocytes, this dependence has been proven for a long time and is annually confirmed by researchers of the obesity problem [42].
The strong correlation between the level of anxiety, depression and BMI that we established emphasizes the need to examine patients for depression and other mood disorders and the importance of first-line treatment of depression before obesity correction [43].
The quality of life of patients at the initial level according to the indicators of mental and physical health in our study was below the average and average level, but in the dynamics of the patient-oriented integrated approach to treatment, it statistically significantly improved after 6 months, which was accompanied by an improvement in the quality of sleep, indicators of lipid-carbohydrate metabolism and reducing body weight.

Conclusions

The correlation analysis proved the correlation between the degree of obesity, body weight, serotonin level, mental health, sleep and metabolism disorders. In obese patients, a high BMI correlates with a low level of serotonin, increased level of anxiety and depression, drowsiness, deterioration of the quality of sleep and life, disorders of lipid and carbohydrate metabolism, which are mutually aggravating factors for the development of obesity and other non-infectious diseases. Diagnosis of sleep disorders, determination of the level of anxiety and depression, as well as the level of serotonin, indicators of carbohydrate and lipid metabolism must be taken into account when determining approaches to comprehensive patient-oriented treatment of obese patients.
Limitations. This article represents the part of results of 6 months follow-up study of patients with obesity treated by complex therapy with patient-oriented approach, other results are represented in previous publication of Tkachenko V.I., Bagro T.O. [19].
 
Received 02.06.2023
Revised 25.07.2023
Accepted 01.08.2023

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