Open Access

Body mass index and musculoskeletal pain: is there a connection?

Chiropractic & Manual Therapies201321:15

DOI: 10.1186/2045-709X-21-15

Received: 14 January 2013

Accepted: 17 May 2013

Published: 20 May 2013



Back pain is one of the most common complaints that patients report to physicians and two-thirds of the population has an elevated body mass index (BMI), indicating they are either overweight or obese. It was once assumed that extra body weight would stress the low back and lead to pain, however, researchers have reported inconsistencies association between body weight and back pain. In contrast, more recent studies do indicate that an elevated BMI is associated with back pain and other musculoskeletal pain syndromes due to the presence of a chronic systemic inflammatory state, suggesting that the relationship between BMI and musculoskeletal pains be considered in more detail.


To describe how an elevated BMI can be associated with chronic systemic inflammation and pain expression. To outline measurable risk factors for chronic inflammation that can be used in clinical practice and discuss basic treatment considerations.


Adiposopathy, or “sick fat” syndrome, is a term that refers to an elevated BMI that is associated with a chronic systemic inflammatory state most commonly referred to as the metabolic syndrome. The best available evidence suggests that the presence of adiposopathy determines if an elevated BMI will contribute to musculoskeletal pain expression. It is not uncommon for physicians to fail to identify the presence of adiposopathy/metabolic syndrome.


Patients with an elevated BMI should be further examined to identify inflammatory factors associated with adiposopathy, such as the metabolic syndrome, which may be promoting back pain and other musculoskeletal pain syndromes.


Back pain Body mass index Obesity Metabolic syndrome Inflammation


An elevated BMI, due to an increase in adipose tissue mass, is rapidly becoming the norm of our modern society. In the United States, approximately sixty-five percent of adults aged 20 years or older are either overweight or obese [1]. Despite the associations between obesity and diabetes, heart disease, and other chronic diseases, adiposity or fatness, can be misinterpreted to merely represent an excess calorie storage depot due to overeating, rather than an overactive immune/endocrine organ that can generate chronic systemic inflammation [2].

Historically, studies have suggested a weak association between body weight and low back pain [3], and guidelines for the treatment of low back pain have not included diet and weight loss as recommendations [4, 5]. Updating this view appears to be in order as an elevated body mass index is considered a risk factor for low back pain chronicity [6, 7], and recent studies have indicated that overweight and obese patients are at a higher risk for musculoskeletal pain expression, as are patients with the metabolic syndrome and type 2 diabetes. For example, overweight and obese individuals are more likely to suffer from tension-type or migraine headache, fibromyalgia, abdominal pain, and chronic widespread pain [8, 9]. Studies have implicated an elevated by BMI as a promoter of low back pain [1012]. Obese subjects with hsCRP levels above 3 mg/dL are more likely to report low back pain, compared to obese subjects with normal levels [13].

Studies have demonstrated that local and widespread musculoskeletal pains are more common in patients with the metabolic syndrome [1416]. Prevalence of neck pain is higher in patients with metabolic syndrome [17]. Shoulder pain is associated with the metabolic syndrome [18]. Achilles, patella, and elbow tendinopathy are associated with the metabolic syndrome [1921]. Risk of lumbar disc herniation is increased by the metabolic syndrome [22]. Low back and radiating pain is associated with elevated serum lipids and cardiovascular disease risk factors [2331]. Osteoarthritis is also promoted by the metabolic syndrome [3235]. Patients with type 2 diabetes have reduced mobility across all joints tested compared to age/weight matched controls [36], and are more likely to develop lumbar stenosis compared to non-diabetics [37, 38]. Type 2 diabetes also increases the risk of expressing disc herniation in both the cervical and lumbar spines [39, 40].

The term “adiposopathy” has been proposed to describe a “sick fat” inflammatory state versus an overweight state without inflammation [2, 41, 42]. In other words, not all patients suffer from chronic inflammation when adipose tissue mass increases. This may be the reason for the previous inconsistent correlations between an elevated BMI and low back pain. The emerging interpretation is that adiposopathy and the related metabolic syndrome leads to pain chronicity because the associated non-resolving systemic inflammation is a pathophysiologic state that promotes nociception in injured/dysfunctional musculoskeletal tissues and prevents healing and pain resolution [10, 14, 35]. This view is consistent with the evidence that chronic non-resolving inflammation is associated with a diversity of seemingly unrelated chronic diseases, such as low back pain, arthritis, atherosclerosis, cancer, chronic obstructive pulmonary disease, asthma, inflammatory bowel disease, neurodegenerative disease, multiple sclerosis, psoriasis, and rheumatoid arthritis [4351].

Thus, understanding the nature of chronic inflammation, adiposopathy, and the metabolic syndrome is relevant to understanding and treating low back pain and other conditions commonly seen by chiropractors. The remainder of this commentary will discuss these topics.

What is chronic systemic inflammation?

Chronic systemic inflammation is a “state” of body chemistry that develops over time, which gradually leads to the expression of chronic disease. While this view of inflammation is not novel [5265], it has yet to be emphasized in the pages of physiology and pathology texts where inflammation is still typically perceived in the context of local physical injury or infection [66, 67]. In the traditional context, inflammation is viewed as a normal response to the acute injury/infection, which leads to tissue healing and the resolution of inflammation. As chronic inflammation is typically not a consideration in physiology texts (66), this can lead to a misunderstanding about the nature of common musculoskeletal diseases, of which osteoarthritis is the best example.

Osteoarthritis (OA) is still characterized as a “non-inflammatory, wear and tear” condition [35, 67], despite the evidence over the last several decades indicating that it is a chronic inflammatory condition [35, 6873]. In fact, OA joints are inflamed and express the same inflammatory chemistry as found in atherosclerotic vessels [74, 75]. And contrary to what might be expected, chondrocytes participate in cartilage degradation by releasing inflammatory mediators [76, 77]. Mounting evidence suggests that as with atherosclerosis, OA is a local manifestation of systemic inflammation [3235, 78]. Interestingly, the metabolic syndrome is associated with the expression of OA [35].

Although difficult to visualize, compared with a an injury or infection, the body responds in a similar fashion to “non-overtly injurious” homeostatic challenges. Reduced sleep, stress, sedentary living, and high glycemic index foods, promotes cellular release of inflammatory mediators, most notably are the pro-inflammatory cytokines such as interleukin-1β (IL-1), interleukin-6 (IL-6), and tumor necrosis factor-α (TNF). In other words, immune cells release the same mediators whether there is overt tissue injury or noxious homeostatic challenges, such as inadequate sleep, stress, and a high glycemic meal [62, 63, 74, 7982].

The clinical expression of the systemic pro-inflammatory state takes time to develop and varies among patients, which makes specific cause-effect relationships difficult to identify. Nonetheless, it is known that chronic inflammation, while nonspecific in terms of symptoms, is the pathophysiological state found in most chronic diseases, such as depression, asthma, atherosclerosis, rheumatoid arthritis, diabetes, osteoporosis, Alzheimer’s disease, cancer, and osteoarthritis [75, 83, 84].

While the clinical expression of the systemic pro-inflammatory state varies among patients, they commonly report poor self-rated health and a depressed affect [8591], which are risk factors for pain chronicity [6, 7]. This inflammatory “state” of ill-health and depression can be induced in many patients when they are given interferon, which causes immune cells to release pro-inflammatory cytokines [91]. The outcome can be a depressed mood, severe fatigue, lethargy, irritability, emotional lability, social withdrawal, lack of concentration and full-blown major depression in a considerable number of patients, which remits when cytokine therapy is withdrawn [91, 92]. The direct administration of IL-1 and TNF in animals acts in a dose-dependent manner to generate symptoms of sickness, depression, and pain [93].

Measurements of circulating levels of high sensitivity C-reactive protein (hsCRP) support the contention that the average patient in the United States is inflamed to moderate or high degrees [56], which may explain why depression, fatigue, poor health, and pain are such common symptoms. Levels of hsCRP of <1, 1 to 3, and >3 mg/L denote lower, moderate, and higher relative risk for future vascular events; however, on a practical basis these values should be interpreted as low, moderate, and high systemic inflammation. With this in mind, the average middle-aged American is moderately inflamed with an hsCRP level at about 1.5 mg/L; however, approximately 25% of the US population is highly inflamed with levels of hsCRP greater than 3 mg/L [56]. The recommended anti-inflammatory behavioral changes to reduce hsCRP include diet, exercise, losing weight, and cessation of smoking [56].

Adiposopathy and chronic inflammation

Multiple interrelated factors lead to weight gain and the development of obesity, the most commonly articulated is a positive caloric balance coupled with sedentary living [41, 42]. Inadequate sleep and stress also promote obesity by increasing palatable food consumption, due to increased release of ghrelin and other hormones [94100]. Less than 6 hrs of sleep per night can undermine dietary efforts to reduce obesity [101] and less than 6 hours or greater than 9 hours of sleep is associated with increased next day pain [102]. Additionally, inadequate sleep and stress independently promote systemic inflammation [103105]. Sedentary living is also associated with systemic inflammation, which can be modulated with exercise [106110]. Lees and Booth have gone so far as to call a lack of exercise the “sedentary death syndrome” [111]. A lack of exercise leads to an increase in BMI [112], poorer self-rated health [113, 114], and depression [108, 115], each of which is a risk factor for developing chronic low back pain [6, 7].

The current American diet consists largely of refined, nutrient-free foods, such as sugar, flour, and refined oils. The current American diet is approximately 20% refined sugar, 20% refined grains, 20% refined oils, 15-20% fatty meat, and 10% dairy by calories [1]. Notice that the average American eats virtually no vegetables and fruit and the vast majority of calories (40%) come from refined sugar and flour. Not well known is that high calorie meals consisting of refined carbohydrates and lipids leads to an immediate postprandial response that manifests as hypercoagulability, sympathetic hyperactivity, endothelial dysfunction and the release of inflammatory mediators, such as cytokines and C-reactive protein [62, 63]. Postprandial inflammation can occur before substantial elevations in BMI; however, eating in this fashion eventually leads to adipose tissue expansion.

As adiposity increases, there is a fundamental change in the metabolic activity of adipose tissue. In lean individuals, adipocytes exert an anti-inflammatory function by releasing adiponectin and anti-inflammatory interleukin-10, which are associated with health promotion and body repair [116, 117]. Adiponectin supports insulin sensitivity and mitochondrial biogenesis in skeletal muscle and interleukin-10 has analgesic and anti-inflammatory immune modulating properties [118121].

In contrast, as adipocytes increase in size, which is associated with an increase in BMI, a metabolic shift can occur in adipose tissue, such that a systemic chronic inflammatory state develops in certain patients. Indeed, circulating inflammatory mediators, such as hsCRP, TNF and IL-6, were measured in obese individuals and non-obese controls. In obese individuals, an increase in weight, BMI, waist circumference, hip circumference, and waist-hip ratio was correlated to increased levels of inflammatory mediators [122]. These non-invasive measurements can be readily used in clinical practice to get an impression of a patient’s potential inflammatory or pain status.

There is normally a small population of macrophages in lean adipose tissue and they exist in their “M2” or non-activated state [116, 117]. However, as adipocytes grow in size, mast cells, lymphocytes, and macrophages can actively enter adipose tissue [123, 124], which leads to the transformation of macrophages from M2 to the “M1” or activated state [116, 117]. This combination of immune cells causes adipose tissue to behave as an overactive immune organ that promotes chronic systemic inflammation [2, 42, 116, 117, 123127]. Indeed “adiposopathy” is a state in which adipose tissue immune cells are behaving in a fashion that mimics a bacterial infection and autoimmune disorders [123, 124]. Thus, it should not be a surprise that overweight individuals are more likely to suffer from pain, malaise and depression.

Adiposopathy, the metabolic syndrome, and pain expression

As an individual’s waistline continues to increase in size due to gains in adipose tissue mass, additional health/disease markers can change, such as elevations in fasting blood glucose, fasting triglycerides, and blood pressure, as well as reductions in high density lipoprotein (HDL) cholesterol. These five markers reflect the presence of adiposopathy [42], and comprise risk factors for the metabolic syndrome, of which at least three must be present to apply the diagnosis [128130]. Table 1 is an example of how predictors of the metabolic syndrome and other pro-inflammatory markers can be followed in the clinical setting.
Table 1

Markers of chronic inflammation







Metabolic syndrome

Abnormal value


1. Fasting blood glucose

≥ 100 mg/dL


2. Triglycerides

≥ 150 mg/dL


3. HDL cholesterol

< 50 for women; < 40 men


4. Blood pressure

≥ 130/85


5. Waist circumference

> 35” women; > 40” men


Pro-inflammatory markers



2-hour postprandial glucose

<140 mg/dl = normal


140–199 = prediabetes

200+ = diabetes

Fasting triglycerides

<90 mg/dl predicts controlled postprandial response


hsCRP in mg/L (marker of chronic inflammation)

<1.0 = normal


1.0-3.0 = moderate


>3.0 = high


25(OH)D (vitamin D)

32-100 ng/ml (goal >40 ng)


Body mass index (BMI)

18.5-24.9 = normal


25–29.9 = overweight

≥30 = obese

Waist/hip ratio women (risk factor for diabetes)

<0.80 = low risk


0.81-.85 = moderate risk

>0.85 = high risk

Waist/hip ratio men (risk factor for diabetes)

<0.95 = low risk


0.96-1.0 = moderate risk


>1.0 = high risk


Lack of sleep

Less than 6 hrs



Associated with systemic inflammation


Sedentary living

Associated with systemic inflammation



Associated with systemic inflammation


Self-rated health

Associated with systemic inflammation


With metabolic syndrome values in mind, the interpretation of glucose and triglyceride values can be further refined to reflect important postprandial inflammatory responses [62]. Population studies have shown that a fasting glucose as low as 90 mg/dL can be associated with a 2-hour post-prandial glucose of >200 mg/dL, which is diagnostic for type 2 diabetes. A 2 hour post-prandial blood glucose level less than 140 mg/dL suggests normal glucose handling; however, data are emerging suggesting that the ideal value may be less. While a fasting triglyceride 150 mg/dl is the cut off for metabolic syndrome, a fasting triglyceride value 90 mg/dl or less is more predictive of postprandial responses [62].

A reduced level of circulating HDL cholesterol is typically viewed as an atherosclerotic plaque risk factor. However, HDL also plays a key role in role in binding absorbed endotoxin to ensure low basal circulating levels, such that reduced HDL cholesterol levels can promote chronic endotoxemia and systemic inflammation [131]. Furthermore, when HDL is burdened by endotoxin, there are multiple pro-inflammatory atherogenic consequences including a suppression of lecithin: cholesterol acyltransferase activity and cholesterol ester transfer protein mass, and a reduced capacity to efflux cholesterol [132], which impact musculoskeletal pain. As mentioned in the introduction, several studies have found a relationship between serum lipids, cardiovascular disease risk factors, and the expression of low back and radiating pain [2331]. Vitamin D deficiency is also associated with chronic inflammation [133], the metabolic syndrome [134], and low back pain [135].

Approximately 25% of individuals age 40–49, 35% of those age 50–59, and 45% of those over 60 year of age may have the pro-inflammatory metabolic syndrome [136]. In other words, 25-40% of the adult population is chronically inflamed in the fasted state, which is further augmented by repeated consumption of meals that leads to the acute postprandial inflammatory state that was described earlier. When the metabolic syndrome is identified in a patient, the interpretation should be that the patient has transformed into a state of chronic inflammation as evidenced by a host of inflammatory changes [125, 137, 138] (see Table 2).
Table 2

Pro-inflammatory chemistry of the metabolic syndrome


↑ NF-κB






↑ IL-6


↑ Increased white blood cell count

↓ protein synthesis

↑ plasminogen activator inhibitor

↑ protein catabolism

↑ Fibrinogen

↑ gluconeogenesis

↑ Leptin

↑ serum amyloid A

↑ Resistin

↑ angiotensinogen

↓ adiponectin

The pro-inflammatory metabolic syndrome chemistry is known to promote the expression of multiple diseases including type 2 diabetes, cancer, cardiovascular disease, stroke, hypertension, polycystic ovarian syndrome, nonalcoholic fatty liver disease, gallstones, sleep apnea, acne, myopia, male vertex balding, and a reduced age of menarche [138141]. With such a diverse expression of disease associated with the metabolic syndrome, it is not a surprise that higher postprandial glycemia is considered to be “a universal mechanism for disease progression” [142].

Despite its obvious pervasiveness and associated health risks, it is not uncommon for primary care physicians to fail to identify the presence of the metabolic syndrome [129]. It is important that practitioners of manual therapy avoid this pitfall. As described earlier, the metabolic syndrome and type 2 diabetes are associated with an increased expression of common painful musculoskeletal conditions seen everyday by manual therapists. Additionally, the presence of the metabolic syndrome is directly related to the expression of depression and poor self-rated health [143147], which are known risk factors for chronic low back pain [6, 7].

Knowledge of the metabolic syndrome-pain relationship may be very important, for without it, manual therapists can be led astray to believe that painful conditions not responding to manual care represent “central sensitization syndromes” because it is often assumed that peripheral system is no longer injured or inflamed if manual care is unsuccessful [148]. In contrast, as stated earlier, the emerging impression is that inflammatory chemistry of the metabolic syndrome becomes superimposed over areas of strain or a previous injury and reduces tissue healing and/or leads to ongoing nociception [10, 14, 35].

As the pro-inflammatory metabolic syndrome is a predecessor of type 2 diabetes, it should not be a surprise that type 2 diabetes is an inflammatory state. At least as early as 2002, review articles outlined how chronic inflammation is the cause of insulin resistance and type 2 diabetes [149]. When studies demonstrate that type 2 diabetics have significantly more complications from lumbar fusion surgery [150], the view should not merely be that this is because they have diabetes and do not heal well. While this is true, the correct view is that diabetes is a non-healing state because it is a chronic inflammatory state.

In addition to the pro-inflammatory chemistry outlined in Table 2, patients with type 2 diabetes also have increased circulating painful pro-inflammatory prostaglandins compared to controls [151]. Not surprisingly, these patients are more likely to experience a host of musculoskeletal pain syndromes. Of interest to note is that patients with type II diabetes are known to have altered proteoglycan metabolism in their intervertbral discs, which may promote weakening of the annular fibers and disc herniation [152]. The implication to consider is that the microanatomy of the musculoskeletal system may change in the presence of chronic inflammatory states, such as adiposopathy, the metabolic syndrome, and type 2 diabetes. Recent tendinopathy research supports this contention.

While a waist girth of over 40 inches for men is a risk factor for the metabolic syndrome, it should not be assumed measurements below 40 inches are not associated with inflammation and adiposopathy. A recent study identified that asymptomatic men aged 40 years and older, with a waist girth of more than 33 inches, had the greatest prevalence of Achilles tendinopathy based on ultrasound examination [153]. An earlier study with elite volleyball players also indicated that a waistline measure above 33 inches was associated with an increased risk of tendon pathology; in this case, patella tendinopathy [20]. While a traditional conclusion would be that mechanical loading would be the cause of tendinopathy in such athletes, the authors provided additional insights:

“Waist girth is a good measure of abdominal adipose tissue, and this tissue releases free fatty acids into the circulation during adipocyte lipolysis, as well as pro-inflammatory cytokines. Free fatty acids and cytokines have been linked to disorders such as heart disease and diabetes. These biochemical substances may also adversely affect tendon function and metabolism and predispose to pathology and abnormal imaging. Therefore, waist girth may have a biochemical as well as a mechanical influence on the development of patellar tendon pathology” [20].

While central accumulation of adipose tissue is known to be harmful to tendons (21), it is unlikely that increased loading adequately explains the development of tendinopathy [19]. It is more likely that tendons are compromised by pro-inflammatory metabolic factors associated with an elevated BMI, such that, “lipid deposition is known to occur in tendons, high cholesterol levels have been observed among individuals with Achilles tendon rupture, and the esterified fraction of cholesterol is elevated in biopsies from Achilles tendinopathy subjects” [19]. In other words, the anatomy, and thus, the integrity of the musculoskeletal system is known to be changed by adiposity, perhaps rendering it more susceptible to injury during mechanical loading. These studies support the suggestion that, “it may be appropriate to redefine our concept of tendinopathy to that of a cardiovascular disease (CVD),” and that “perhaps treating CVD risk factors will improve the treatment of tendinopathy” [19].

Treatment considerations

While the intent of this commentary is not to provide detailed or specific treatments, as this can vary among patients, general management considerations are appropriate to mention. A growing body of evidence clearly implicates pro-inflammatory body chemistry as an initiator and/or perpetuator of musculoskeletal pain syndromes, and thus, the potential for altered chemistry should be considered during patient assessment, especially when an elevated BMI is identified.

While not all patients with an elevated BMI suffer from a chronic inflammatory state, an elevated BMI should be viewed as a potential initiator/promoter of musculoskeletal pain. The risk factors listed in Table 1 can be used to help determine which patients are systemically inflamed. Some are direct markers, including glucose, triglycerides, HDL cholesterol, hsCRP, and vitamin D, while the remainder are surrogate markers of inflammation.

The treatment approach to reduce adiposopathy and the metabolic syndrome can involve multiple anti-inflammatory lifestyle modifications including dietary changes, nutritional supplements, stress management, exercise, and ensuring adequate sleep. Depending on a practitioner’s training, practice scope, and the potential need for pharmacologic interventions, co-management of certain patients will be likely.


Historically, an elevated BMI was viewed as a storage depot of excess energy due to overeating and/or a lack of exercise. The systemic pro-inflammatory metabolic consequences of an elevated BMI were unknown until recently, which demands that clinicians modify their views about the influence that weight gain can have on human health.

An elevated BMI may or may not be associated with low back pain and other musculoskeletal pain syndromes. However, as the metabolic syndrome is a universal driver of disease expression, including musculoskeletal pain syndromes, it is incumbent upon the chiropractic profession to identify patients at risk. Identifying adiposopathy and the metabolic syndrome can have a substantial public health impact as patients may only present with musculoskeletal pain and yet have the chronic inflammatory chemistry that promotes heart disease, cancer, and other chronic diseases.


Authors’ Affiliations

National University of Health Sciences, SPC-Health Education Center


  1. Cordain L, Eaton SB, Sebastian A, Mann N, Lindeberg S, Watkins BA, O’Keefe JH, Brand-Miller J: Origins and evolution of the Western diet: health implications for the 21st century. Am J Clin Nutr. 2005, 81: 341-354.PubMed
  2. Bays HE, Gonzalez-Campoy M, Henry RR, Bergman DA, Kitabchi AE, Schorr AB, Rodbard HW: Is adiposopathy (sick fat) an endocrine disease?. Int J Clin Pract. 2008, 62: 1474-1483. 10.1111/j.1742-1241.2008.01848.x.PubMed CentralPubMed
  3. Leboeuf-Yde C: Body weight and low back pain. A systematic literature review of 56 journal articles reporting on 65 epidemiologic studies. Spine. 2000, 25: 226-237. 10.1097/00007632-200001150-00015.PubMed
  4. Chou R, Qaseem A, Snow V, Casey D, Cross JT, Shekelle P, Owens DK: Diagnosis and treatment of low back pain: a joint clinical practice guideline from the American College of Physicians and the American Pain Society. Ann Intern Med. 2007, 147: 478-491. 10.7326/0003-4819-147-7-200710020-00006.PubMed
  5. Bouwmeester W, van Enst A, van Tulder M: Quality of low back pain guidelines improved. Spine. 2009, 34: 2562-2567. 10.1097/BRS.0b013e3181b4d50d.PubMed
  6. Rubin DI: Epidemiology and risk factors for spine pain. Neurol Clin. 2007, 25: 353-371. 10.1016/j.ncl.2007.01.004.PubMed
  7. Lebovits A, Hainline B, Stone LS, Seminowicz DA, Brunz JT, Rosenquist RW, Cowan P: Struck from behind: maintaining quality of life with chronic low back pain. J Pain. 2009, 10: 927-931. 10.1016/j.jpain.2009.06.011.PubMed
  8. Stone AA, Broderick JE: Obesity and pain are associated in the United States. Obesity. 2012, 20: 1491-1495. 10.1038/oby.2011.397.PubMed
  9. Wright LJ, Schur E, Noonan C, Ahumada S, Buchwald D, Afari N: Chronic pain, overweight, and obesity: findings from a community-based twin registry. J Pain. 2010, 11: 628-635. 10.1016/j.jpain.2009.10.004.PubMed CentralPubMed
  10. Shiri R, Karppinen J, Leino-Arjas P, Solovieva S, Viikari-Juntura E: The association between obesity and low back pain: a meta-analysis. Am J Epidemiol. 2010, 171: 135-154. 10.1093/aje/kwp356.PubMed
  11. Heuch I, Hagen K, Heuch I, Nygaard Ø, Zwart JA: The impact of body mass index on the prevalence of low back pain: the HUNT study. Spine. 2010, 35: 764-768.PubMed
  12. Heuch I, Heuch I, Hagen K, Zwart JA: Body mass index as a risk factor for developing chronic low back pain: A Follow-up in the Nord-Trøndelag Health Study. Spine. 2012, [Epub ahead of print]
  13. Briggs MS, Givens DL, Schmitt LC, Taylor CA: The relationships of C-reactive protein and obesity to the prevalence and odds of reporting low back pain. Arch Phys Med Rehabil. 2012, S0003-9993 (12): 01187-09993. 10.1016/j.apmr.2012.11.026. Epub ahead of print]
  14. Mantyselka P, Miettola J, Niskanen L, Kumpusalo E: Persistent pain at multiple sites-connection to glucose derangement. Diabetes Res Clin Pract. 2009, 84 (2): e30-e32. 10.1016/j.diabres.2009.01.018.PubMed
  15. Mantyselka P, Miettola J, Niskanen L, Kumpusalo E: Glucose regulation and chronic pain at multiple sites. Rheumatology. 2008, 47: 1235-1238. 10.1093/rheumatology/ken220.PubMed
  16. Mantyselka P, Miettola J, Niskanen L, Kumpusalo E: Chronic pain, impaired glucose tolerance and diabetes: a community-based study. Pain. 2008, 137: 34-40. 10.1016/j.pain.2007.08.007.PubMed
  17. Mantyselka P, Kautianen H, Vanhala M: Prevalence of neck pain in subjects with metabolic syndrome - a cross-sectional population-based study. BMC Musculoskelet Disord. 2010, 11: 171-10.1186/1471-2474-11-171.PubMed CentralPubMed
  18. Rechardt M, Shiri R, Karppinen J, Jula A, Heliövaara M, Viikari-Juntura E: Lifestyle and metabolic factors in relation to shoulder pain and rotator cuff tendinitis: A population-based study. BMC Musculoskelet Disord. 2010, 11: 165-10.1186/1471-2474-11-165.PubMed CentralPubMed
  19. Gaida JE, Alfredson L, Kiss ZS, Wilson AM, Alfredson H, Cook JL: Dyslipidemia in Achilles tendinopathy is characteristic of insulin resistance. Med Sci Sports Exerc. 2009, 41: 1194-1197. 10.1249/MSS.0b013e31819794c3.PubMed
  20. Malliaras P, Cook JL, Kent PM: Anthropometric risk factors for patellar tendon injury among volleyball players. Br J Sports Med. 2007, 41: 259-263. 10.1136/bjsm.2006.030049.PubMed CentralPubMed
  21. Shiri R, Viikari-Juntura E, Varonen H, Heliovaara M: Prevalence and determinants of lateral and medial epicondylitis: a population study. Am J Epidemiol. 2006, 164: 1065-1074. 10.1093/aje/kwj325.PubMed
  22. Jhawar BS, Fuchs CS, Colditz GA, Stampfer MJ: Cardiovascular risk factors for physician-diagnosed lumbar disc herniation. Spine J. 2006, 6: 684-691. 10.1016/j.spinee.2006.04.016.PubMed
  23. Kauppila LI, McAlindon T, Evans S, Wilson PW, Kiel D, Felson DT: Disc degeneration/back pain and calcification of the abdominal aorta: a 25-year follow-up study in Framingham. Spine. 1997, 22: 1642-1647. 10.1097/00007632-199707150-00023.PubMed
  24. Kurunlahti M, Tervonen O, Vanharanta H, Ilkko E, Suramo I: Association of atherosclerosis with low back pain and the degree of disc degeneration. Spine. 1999, 24: 2080-2084. 10.1097/00007632-199910150-00003.PubMed
  25. Kauppila LI, Mikkonen R, Mankinen P, Pelto-Vasenius K, Mäenpää I: MR aortography and serum cholesterol levels in patients with long-term non-specific lower back pain. Spine. 2004, 29: 2347-2352.
  26. Leino-Arjas P, Kaila-Kangas L, Solovieva S, Riihimäki H, Kirjonen J, Reunanen A: Serum lipids and low back pain: an association? A follow-up study of a working population sample. Spine. 2006, 31: 1032-1037. 10.1097/01.brs.0000214889.31505.08.PubMed
  27. Leino-Arjas P, Solovieva S, Kirjonen J, Reunanen A, Riihimäki H: Cardiovascular risk factors and low-back pain in a long-term follow-up of industrial employees. Scand J Work Environ Health. 2006, 32: 12-19. 10.5271/sjweh.971.PubMed
  28. Shiri R, Karppinen J, Leino-Arjas P, Solovieva S, Varonen H, Kalso E, Ukkola O, Viikari-Juntura E: Cardiovascular and lifestyle risk factors in lumbar radicular pain or clinically defined sciatica: a systematic review. Eur Spine J. 2007, 16: 2043-2054. 10.1007/s00586-007-0362-6.PubMed CentralPubMed
  29. Leino-Arjas P, Kauppila L, Kaila-Kangas L, Shiri R, Heistaro S, Heliövaara M: Serum lipids in relation to sciatica among Finns. Atherosclerosis. 2008, 197: 43-49. 10.1016/j.atherosclerosis.2007.07.035.PubMed
  30. Kauppila LI: Atherosclerosis and disc degeneration/low back pain – a systematic review. Eur J Vasc Endovasc Surg. 2009, 37: 661-670. 10.1016/j.ejvs.2009.02.006.PubMed
  31. Heuch I, Heuch I, Hagen K, Zwart JA: Associations between serum lipid levels and chronic low back pain. Epidemiology. 2010, 21: 837-841. 10.1097/EDE.0b013e3181f20808.PubMed
  32. Conaghan PG, Vanharanta H, Dieppe PA: Is progressive osteoarthritis an atheromatous vascular disease?. Ann Rheum Dis. 2005, 64: 1539-1541. 10.1136/ard.2005.039263.PubMed CentralPubMed
  33. Masuko K, Murata M, Suematsu N, Okamoto K, Yudoh K, Nakamura H, Kato T: A metabolic aspect of osteoarthritis: lipid as a possible contributor to the pathogenesis of cartilage degradation. Clin Exp Rheumatol. 2009, 27: 347-353.PubMed
  34. Gkretsi V, Simopoulou T, Tsezou A: Lipid metabolism and osteoarthritis: lessons from atherosclerosis. Prog Lipid Res. 2011, 50: 133-140. 10.1016/j.plipres.2010.11.001.PubMed
  35. Berenbaum F: Osteoarthritis as an inflammatory disease (osteoarthritis is not osteoarthrosis). Osteoarthr Cartil. 2013, 21: 16-21. 10.1016/j.joca.2012.11.012.PubMed
  36. Abate M, Schiavone C, Pelotti P, Salini V: Limited joint mobility (LJM) in elderly subjects with type II diabetes mellitus. Arch Gerontol Geriatrics. 2011, 53: 135-140. 10.1016/j.archger.2010.09.011.
  37. Lotan R, Oron A, Anekstein Y, Shalmon E, Mirovsky Y: Lumbar stenosis and systemic diseases: is there any relevance. J Spinal Disord Tech. 2008, 21: 247-251. 10.1097/BSD.0b013e31813707af.PubMed
  38. Anekstein Y, Smorgick Y, Lotan R, Agar G, Shalmon E, Floman Y, Mirovsky Y: Diabetes mellitus as a risk factor for the development of lumbar spinal stenosis. Isr Med Assoc J. 2010, 12: 16-20.PubMed
  39. Sakellaridis N: The influence of diabetes mellitus on lumbar intervertebral disk herniation. Surg Neurol. 2006, 66: 152-154. 10.1016/j.surneu.2006.01.019.PubMed
  40. Sakellaridis N, Androulis A: Influence of diabetes mellitus on cervical intervertebral disc herniation. Clin Neurol Neurosurg. 2008, 110: 810-812. 10.1016/j.clineuro.2008.05.007.PubMed
  41. Bays HE: Adiposopathy: is sick fat a cardiovascular disease?. J Am Coll Cardiol. 2011, 57: 2461-2473. 10.1016/j.jacc.2011.02.038.PubMed
  42. Bays H: Adiposopathy, diabetes mellitus, and primary prevention of atherosclerotic coronary artery disease: treating “sick fat” through improving fat function with antidiabetes therapies. Am J Cardiol. 2012, 110 (suppl): 4B-12B.PubMed
  43. Sommer C, Birklein F: Resolvins and inflammatory pain. F1000 Med Rep. 2011, 3: 19-10.3410/M3-19.PubMed CentralPubMed
  44. Sommer C, Birklein F: Fighting off pain with resolvins. Nat Med. 2010, 16 (5): 518-520. 10.1038/nm0510-518.PubMed
  45. Ji RR, Xu ZZ, Strichartz G, Serhan CN: Emerging roles of resolvins in the resolution of inflammation and pain. Trends Neurosci. 2011, 34: 599-609. 10.1016/j.tins.2011.08.005.PubMed CentralPubMed
  46. Xu ZZ, Zhang L, Liu T, Park JY, Berta T, Yang R, Serhan CN, Ji RR: Resolvins RvE1 and RvD1 attenuate inflammatory pain via central and peripheral actions. Nat Med. 2010, 16: 592-597. 10.1038/nm.2123.PubMed CentralPubMed
  47. Nathan C, Ding A: Nonresolving inflammation. Cell. 2010, 140: 871-882. 10.1016/j.cell.2010.02.029.PubMed
  48. Serhan CN, Brain SD, Buckley CD, Gilroy DW, Haslett C, O’Neill LA, Perretti M, Rossi AG, Wallace JL: Resolution of inflammation: state of the art, definitions and terms. FASEB J. 2007, 21: 325-332. 10.1096/fj.06-7227rev.PubMed CentralPubMed
  49. Zhang MJ, Spite M: Resolvins: anti-inflammatory and proresolving mediators derived from omega-3 polyunsaturated fatty acids. Annu Rev Nutr. 2012, 32: 203-227. 10.1146/annurev-nutr-071811-150726.PubMed
  50. Campbell EL, Serhan CN, Colgan SP: Antimicrobial aspects of inflammatory resolution in the mucosa: a role for proresolving mediators. J Immunol. 2011, 187: 3475-3481. 10.4049/jimmunol.1100150.PubMed CentralPubMed
  51. Das UN: Is multiple sclerosis a proresolution deficiency disorder?. Nutrition. 2012, 28: 951-958. 10.1016/j.nut.2011.12.016.PubMed
  52. Ross R: Atherosclerosis–an inflammatory disease. N Engl J Med. 1999, 340: 115-126. 10.1056/NEJM199901143400207.PubMed
  53. Biasucci LM, Colizzi C, Rizzello V, Vitrella G, Crea F, Liuzzo G: Role of inflammation in the pathogenesis of unstable coronary artery diseases. Scand J Clin Lab Invest Suppl. 1999, 230: 12-22.PubMed
  54. Das UN: Is obesity and inflammatory condition?. Nutrition. 2001, 17: 953-966. 10.1016/S0899-9007(01)00672-4.PubMed
  55. Seaman DR: The diet-induced pro-inflammatory state: a cause of chronic pain and other degenerative diseases?. J Manip Physiol Ther. 2002, 25: 168-179. 10.1067/mmt.2002.122324.
  56. Ridker PM: C-reactive protein: a simple test to help predict risk of heart attack and stroke. Circulation. 2003, 108: 81-85. 10.1161/01.CIR.0000093381.57779.67.
  57. Nicklas BJ, You T, Pahor M: Behavioural treatments for chronic systemic inflammation: effects of dietary weight loss and exercise training. CMAJ. 2005, 172: 1199-1209. 10.1503/cmaj.1040769.PubMed CentralPubMed
  58. Esposito K, Marfella R, Ciotola M, Di Palo C, Giugliano F, Giugliano G, D’Armiento M, D’Andrea F, Giugliano D: Effect of a mediterranean-style diet on endothelial dysfunction and markers of vascular inflammation in the metabolic syndrome: a randomized trial. JAMA. 2004, 292: 1440-1446. 10.1001/jama.292.12.1440.PubMed
  59. Esposito K, Giugliano D: Diet and inflammation: a link to metabolic and cardiovascular diseases. Eur Heart J. 2006, 27: 15-20.PubMed
  60. Giugliano D, Ceriello A, Esposito K: The effects of diet on inflammation: emphasis on the metabolic syndrome. J Am Coll Cardiol. 2006, 48: 677-685. 10.1016/j.jacc.2006.03.052.PubMed
  61. Basu A, Devaraj S, Jialol I: Dietary factors that promote or retard inflammation. Arterioscler Thromb Vasc Biol. 2006, 26: 995-1001. 10.1161/01.ATV.0000214295.86079.d1.PubMed
  62. O’Keefe JH, Bell DS: Postprandial hyperglycemia/hyperlipidemia (postprandial dysmetabolism) is a cardiovascular risk factor. Am J Cardiol. 2007, 100: 899-904. 10.1016/j.amjcard.2007.03.107.PubMed
  63. O’Keefe JH, Gheewala NM, O’Keefe JO: Dietary strategies for improving post-prandial glucose, lipids, inflammation, and cardiovascular health. J Am Coll Cardiol. 2008, 51: 249-255. 10.1016/j.jacc.2007.10.016.PubMed
  64. Frassetto LA, Schloetter M, Mietus-Synder M, Morris RC, Sebastian A: Metabolic and physiologic improvements from consuming a paleolithic, hunter-gatherer type diet. Eur J Clin Nutr. 2009, 63: 947-955. 10.1038/ejcn.2009.4.PubMed
  65. Egger G, Dixon J: Inflammatory effects of nutritional stimuli: further support for the need for a big picture approach to tackling obesity and chronic disease. Obes Rev. 2010, 11: 137-149. 10.1111/j.1467-789X.2009.00644.x.PubMed
  66. Guyton AC, Hall JE: Textbook of medical physiology. 2011, Philadelphia: Saunders
  67. Robbins & Cotran Pathologic Basis of Disease. Edited by: Kumar V, Abbas AK, Fausto N, Aster J. 2010, Philadelphia: Saunders, 8
  68. Bonner WM, Jonsson H, Malanos C, Bryant M: Changes in lipids of human articular cartilage with age. Arthritis Rheum. 1975, 18: 461-473. 10.1002/art.1780180505.PubMed
  69. Goldenberg DL, Egan MS, Cohen AS: Inflammatory synovitis in degenerative joint disease. J Rheumatol. 1982, 9: 204-209.PubMed
  70. Adkisson HD, Risener FS, Zarrinkar PP, Walla MD, Christie WW, Wuthier RE: Unique fatty acid composition of normal cartilage: discovery of high levels of n-9 eicosatrienoic acid and low levels of n-6 polyunsaturated fatty acids. FASEB J. 1991, 5: 344-353.PubMed
  71. Nakamura H, Yoshino S, Kato T, Tsuruha J, Nishioka K: T-cell mediated inflammatory pathway in osteoarthritis. Osteoarthritis Cart. 1999, 7: 401-402. 10.1053/joca.1998.0224.
  72. Nishioka K: Autoimmune response in cartilage-derived peptides in a patient with osteoarthritis. Arth Res Ther. 2003, 6: 6-7.
  73. Kato T, Xiang Y, Nakamura H, Nishioka K: Neoantigens in osteoarthritic cartilage. Curr Opin Rheumatol. 2004, 16: 604-608. 10.1097/
  74. Lamon BD, Hajjar DP: Inflammation at the molecular interface of atherogenesis: an anthropological journey. Am J Pathol. 2008, 173: 1253-1264. 10.2353/ajpath.2008.080442.PubMed CentralPubMed
  75. Bonnet CS, Walsh DA: Osteoarthritis, angiogenesis and inflammation. Rheumatology. 2005, 44: 7-16. 10.1093/rheumatology/keh344.PubMed
  76. Tiku ML, Shah R, Allison GT: Evidence link chondrocyte lipid peroxidation to cartilage matrix protein degradation: possible role in cartilage aging and the pathogenesis of osteoarthritis. J Biol Chem. 2000, 275: 20069-20076. 10.1074/jbc.M907604199.PubMed
  77. Tiku ML, Allison GT, Naik K, Karry SK: Malondialdehyde oxidation of cartilage collagen by chondrocytes. Osteoarthr Cartil. 2003, 11: 159-166. 10.1016/S1063-4584(02)00348-5.PubMed
  78. Sturmer T, Sun Y, Sauerland S, Zeissig I, Gunther KP, Puhl W, Brenner H: Serum cholesterol and osteoarthritis. The baseline examination of the Ulm Osteoarthritis Study. J Rheumatol. 1998, 25: 1827-1832.PubMed
  79. Maes M, Song C, Lin A, Van Gastel A, Kenis G, Bosmans E, De Meester I, Benoy I, Neels H, Demedts P, Janca A, Scharpé S, Smith RS: The effects of psychological stress on humans: increased production of pro-inflammatory cytokines and TH-1 like response in stress-induced anxiety. Cytokine. 1998, 10: 313-318. 10.1006/cyto.1997.0290.PubMed
  80. Bierhaus A, Humpert PM, Nawroth PP: Linking stress to inflammation. Anesthesiol Clin N Am. 2006, 24: 325-340. 10.1016/j.atc.2006.01.001.
  81. Simpson N, Dinges DF: Sleep and inflammation. Nutr Rev. 2007, 65: S244-S252. 10.1301/nr.2007.dec.S244-S252.PubMed
  82. Irwin MR, Carrillo C, Omstead R: Sleep loss activates cellular markers of inflammation: sex differences. Brain Behav Immunity. 2010, 24: 54-57. 10.1016/j.bbi.2009.06.001.
  83. Baker RG, Hayden MS, Ghosh S: NF-κB, inflammation, metabolic disease. Cell Metab. 2011, 13: 11-22. 10.1016/j.cmet.2010.12.008.PubMed CentralPubMed
  84. Ahn KS, Aggarwal BB: Transcription factor NF-κB: a sensor for smoke and stress signals. Ann NY Acad Sci. 2005, 1056: 218-233. 10.1196/annals.1352.026.PubMed
  85. Lekander M, Elofsson S, Neve IM, Hansson LO, Undén AL: Self-rated health is related to levels of circulating cytokines. Psychosom Med. 2004, 66: 559-563. 10.1097/01.psy.0000130491.95823.94.PubMed
  86. Christian LM, Glaser R, Porter K, Malarkey WB, Beversdorf D, Kiecolt-Glaser JK: Poorer self-rated health is associated with elevated inflammatory markers among older adults. Psychoneuroendocrinology. 2011, 36: 1495-1504. 10.1016/j.psyneuen.2011.04.003.PubMed CentralPubMed
  87. Wium-Andersen MK, Orsted DD, Nielsen SF, Nordestgaard BG: Elevated C-reactive protein levels, psychological distress, and depression in 73,131 individuals. JAMA Psychiatry. 2013, 70: 176-184. 10.1001/2013.jamapsychiatry.102.PubMed
  88. Khairova RA, Machado-Vieira R, Du J, Manji HK: A potential role for pro-inflammatory cytokines in regulating synaptic plasticity in major depressive disorder. Int J Neuropsychopharmacol. 2009, 12: 561-578. 10.1017/S1461145709009924.PubMed CentralPubMed
  89. Miller AH, Maletic V, Raison CL: Inflammation and its discontents: the role of cytokines in the pathophysiology of major depression. Biol Psychiatry. 2009, 65: 732-741. 10.1016/j.biopsych.2008.11.029.PubMed CentralPubMed
  90. Krishnadas R, Cavanagh J: Depression: an inflammatory illness?. J Neurol Neurosurg Psychiatry. 2012, 83: 495-502. 10.1136/jnnp-2011-301779.PubMed
  91. Irwin MR: Inflammation at the intersection of behavior and somatic symptoms. Psychiatr Clin N Am. 2011, 34: 605-620. 10.1016/j.psc.2011.05.005.
  92. Bonaccorso S, Meltzer HY, Maes M: Psychological and behavioral effects of interferons. Curr Opin Psychiatry. 2000, 13: 673-677. 10.1097/00001504-200011000-00034.
  93. Dantzer R, O’Connor JC, Freund GG, Johnson RW, Kelley KW: From inflammation to sickness and depression: when the immune system subjugates the brain. Nat Rev Neurosci. 2008, 9: 46-56. 10.1038/nrn2297.PubMed CentralPubMed
  94. Spiegel K, Tasali E, Penev P, Van Cauter E: Sleep curtailment in healthy young men is associated with decreased leptin levels, elevated ghrelin levels and increased hunger and appetite. Ann Intern Med. 2004, 141: 846-850. 10.7326/0003-4819-141-11-200412070-00008.PubMed
  95. Knutson KL, Spiegel K, Penev P, van Cauter E: The metabolic consequences of sleep deprivation. Sleep Med Rev. 2007, 11: 163-178. 10.1016/j.smrv.2007.01.002.PubMed CentralPubMed
  96. Morselli L, Leproult R, Balbo M, Spiegel K: Role of sleep duration in the regulation of glucose metabolism and appetite. Best Prac Res Clin Endocrinol Metab. 2010, 24: 687-702. 10.1016/j.beem.2010.07.005.
  97. Lucassen EA, Rother KI, Cizza G: Interacting epidemics? Sleep curtailment, insulin resistance, and obesity. Ann NY Acad Sci. 2012, 1264: 110-134. 10.1111/j.1749-6632.2012.06655.x.PubMed CentralPubMed
  98. Dallman MF, Pecoraro NC, la Fleur SE: Chronic stress and comfort foods: self-medication and abdominal obesity. Brain Behav Immun. 2005, 19: 275-280. 10.1016/j.bbi.2004.11.004.PubMed
  99. Adam TC, Epe ES: Stress, eating and the reward system. Physiol Behav. 2007, 91: 449-458. 10.1016/j.physbeh.2007.04.011.PubMed
  100. Maniam J, Morris MJ: The link between stress and feeding behaviour. Neuropharmacol. 2012, 63: 97-110. 10.1016/j.neuropharm.2012.04.017.
  101. Nedeltcheva AV, Kilkus JM, Imperial J, Schoeller DA, Penev PD: Insufficient sleep undermines dietary efforts to reduce obesity. Ann Int Med. 2010, 153: 435-441. 10.7326/0003-4819-153-7-201010050-00006.PubMed CentralPubMed
  102. Edwards R, Almeida DM, Klick B, Haythornthwaite JA, Smith MT: Duration of sleep contributes to next-day pain report in the general population. Pain. 2008, 137: 202-207. 10.1016/j.pain.2008.01.025.PubMed CentralPubMed
  103. Mullington JM, Simpson NS, Meier-Ewert HK, Haak M: Sleep loss and inflammation. Best Prac Res Clin Endocrinol Metab. 2010, 24: 775-784. 10.1016/j.beem.2010.08.014.
  104. Motivala SJ: Sleep and inflammation. psychoneuroimmunology in the context of cardiovascular disease. Ann Behav Med. 2011, 42: 141-152. 10.1007/s12160-011-9280-2.PubMed
  105. Black PH: The inflammatory consequences of psychologic stress: relationship to insulin resistance, obesity, atherosclerosis and diabetes mellitus, type II. Med Hypoth. 2006, 67: 879-891. 10.1016/j.mehy.2006.04.008.
  106. Petersen AM, Pedersen BK: The anti-inflammatory effects of exercise. J Appl Physiol. 2005, 98: 1154-1162. 10.1152/japplphysiol.00164.2004.PubMed
  107. Mathur N, Pedersen BK: Exercise as a means to control low-grade systemic inflammation. Mediators Inflamm. 2008, 2008: 109502-PubMed CentralPubMed
  108. Rethorst CD, Toups MS, Greer TL, Nakonezny PA, Carmody TJ, Brannermann BD, Huebinger RM, Barber RC, Trivedi MH: Pro-inflammatory cytokines as predictors of antidepressant effects of exercise in major depressive disorder. Mol Psychiatry. 2012, 10.1038/mp.2012.125. [Epub ahead of print]
  109. Santos RV, Viana VA, Boscolo RA, Marques VG, Santana MG, Lira FS, Tufik S, de Mello MT: Moderate exercise training modulates cytokine profile and sleep in elderly people. Cytokine. 2012, [Epub ahead of print]
  110. Oliveira J, Páscoa Pinheiro J, Reis F, Teixeira de Lemos E: Regular physical exercise as a strategy to improve antioxidant and anti-inflammatory status: benefits in type 2 diabetes mellitus. Oxid Med Cell Longev. 2012, 2012: 741545-PubMed CentralPubMed
  111. Lees SJ, Booth FW: Sedentary death syndrome. Can J Appl Physiol. 2004, 29: 447-460. 10.1139/h04-029.PubMed
  112. Norman A, Bellocco R, Vaida F, Wolk A: Total physical activity in relation to age, body mass, health and other factors in a cohort of Swedish men. Int J Obesity. 2002, 26: 670-675. 10.1038/sj.ijo.0801955.
  113. Sodergren M, Sundquist J, Johansson SE, Sundquist K: Physical activity, exercise and self-rated health: a population-based study from Sweden. BMC Publ Health. 2008, 8: 352-10.1186/1471-2458-8-352.
  114. Darviri C, Fouka G, Gnardellis C, Artemiadis AK, Tigani X, Alexopoulos EC: Determinants of self-rated health in a representative sample of a rural population: a cross-sectional study in Greece. Int J Environ Res Public Health. 2012, 9: 943-954. 10.3390/ijerph9030943.PubMed CentralPubMed
  115. Babyak M, Blumenthal JA, Herman S, Khatri P, Doraiswamy M, Moore K, Craighead E, Baldewicz TT, Krishnan R: Exercise treatment for major depression: maintenance of therapeutic benefit at 10 months. Psychosom Med. 2000, 62: 633-638.PubMed
  116. Galic S, Oakhill JS, Steinberg GR: Adipose tissue as an endocrine organ. Mol Cell Endocrinol. 2010, 316: 129-139. 10.1016/j.mce.2009.08.018.PubMed
  117. Sell H, Eckel J: Adipose tissue inflammation: novel insight into the role of macrophages and lymphocytes. Curr Opin Clin Nutr Metab Care. 2010, 13: 366-370. 10.1097/MCO.0b013e32833aab7f.PubMed
  118. Chandran M, Phillips SA, Ciaraldi T, Henry RR: Adiponectin: more than just another fat cell hormone?. Diabetes Care. 2003, 26: 2442-2450. 10.2337/diacare.26.8.2442.PubMed
  119. Lustig Y, Hemi R, Kanety H: Regulation and function of adiponectin receptors in skeletal muscle. Vitam Horm. 2012, 90: 95-123.PubMed
  120. Uceyler N, Valenza R, Stock M, Schedel R, Sprotte G, Sommer C: Reduced levels of antiinflammatory cytokines in patients with chronic widespread pain. Arthritis Rheum. 2006, 54: 2656-2664. 10.1002/art.22026.PubMed
  121. Saraiva M, O’Garra A: The regulation of IL-10 production by immune cells. Nat Rev Immunol. 2010, 10: 170-181. 10.1038/nri2711.PubMed
  122. Park HS, Park LY, Yu R: Relationship of obesity and visceral adiposity with serum concentrations of CRP, TNF-alpha and IL-6. Diabetes Res Clin Pract. 2005, 69: 29-35. 10.1016/j.diabres.2004.11.007.PubMed
  123. Harford KA, Reynolds CM, McGillicuddy FC, Roche HM: Fats, inflammation and insulin resistance: insights to the role of macrophage and T-cell accumulation in adipose tissue. Proc Nutr Soc. 2011, 70: 408-417. 10.1017/S0029665111000565.PubMed
  124. Schipper HS, Prakken B, Kalkhoven E, Boes M: Adipose tissue-resident immune cells: key players in immunometabolism. Trends Endocrinol Metab. 2012, 23: 407-415. 10.1016/j.tem.2012.05.011.PubMed
  125. Antuna-Puente B, Feve B, Fellahi S, Bastard AP: Adipokines: the missing link between insulin resistance and obesity. Diabetes Metab. 2008, 34: 2-11. 10.1016/j.diabet.2007.09.004.PubMed
  126. Suganami T, Ogawa Y: Adipose tissue macrophages: their role in adipose tissue remodeling. J Leukoc Biol. 2010, 88: 33-39. 10.1189/jlb.0210072.PubMed
  127. Fain JN: Release of inflammatory mediators by human adipose tissue is enhanced in obesity and primarily by the nonfat cells: a review. Mediators Inflamm. 2010, Article ID: 513948
  128. Wilson PW, Grundy SM: The metabolic syndrome: practical guide to origins and treatment: Part I. Circulation. 2003, 108: 1422-1424. 10.1161/01.CIR.0000089505.34741.E5.PubMed
  129. Helminen EE, Mäntyselkä P, Nykänen I, Kumpusalo E: Far from easy and accurate - detection of metabolic syndrome by general practitioners. BMC Fam Pract. 2009, 10: 76-10.1186/1471-2296-10-76.PubMed CentralPubMed
  130. Golbidi S, Mesdaghinia A, Laher I: Exercise in the metabolic syndrome. Oxid Med Cell Longev. 2012, 2012: 349710-PubMed CentralPubMed
  131. Pussinen PJ, Havulinna AS, Lehto M, Sundvall J, Salomaa V: Endotoxemia is associated with an increased risk of incident diabetes. Diabetes Care. 2011, 34: 392-397. 10.2337/dc10-1676.PubMed CentralPubMed
  132. de la Llera MM, McGillicuddy FC, Hinkle CC, Byrne M, Joshi MR, Nguyen V, Tabita-Martinez J, Wolfe ML, Badellino K, Pruscino L, Mehta NN, Asztalos BF, Reilly MP: Inflammation modulates human HDL composition and function in vivo. Atherosclerosis. 2012, 222: 390-394. 10.1016/j.atherosclerosis.2012.02.032.
  133. Guillot X, Semerano L, Saidenberg-Kermanac’h N, Falgarone G, Boissier MC: Vitamin D and inflammation. Joint Bone Spine. 2010, 77: 552-557. 10.1016/j.jbspin.2010.09.018.PubMed
  134. Hypponen E, Boucher BJ, Berry DJ, Power C: 25-hydroxyvitamin D, IGF-1, and the metabolic syndrome at 45 years of age. A cross-sectional study in the 1958 British Birth Cohort. Diabetes. 2008, 57: 298-305.PubMed
  135. Schwalfenberg G: Improvement of chronic back pain or failed back surgery with vitamin D repletion: a case series. J Am Board Fam Med. 2009, 22: 69-74. 10.3122/jabfm.2009.01.080026.PubMed
  136. Ford ES, Giles WH, Dietz WH: Prevalence of the metabolic syndrome among US adults: findings from the Third National Health and Nutrition Examination Survey. JAMA. 2002, 287: 356-359. 10.1001/jama.287.3.356.PubMed
  137. Dandona P, Aljada A, Chaudhuri A, Mohanty P, Garg R: Metabolic Syndrome - a comprehensive perspective based on interactions between obesity, diabetes, and inflammation. Circulation. 2005, 111: 1448-1454. 10.1161/01.CIR.0000158483.13093.9D.PubMed
  138. Blaha M, Elasy TA: Clinical use of the metabolic syndrome: why the confusion?. Clin Diabetes. 2006, 24: 125-131. 10.2337/diaclin.24.3.125.
  139. Facchini FS, Hua N, Abbasi F, Reaven GM: Insulin resistance as a predictor of age-related disease. J Clin Endocrinol Metab. 2001, 86: 3574-3578. 10.1210/jc.86.8.3574.PubMed
  140. Cordain L, Eades MR, Eades MD: Hyperinsulinemic diseases of civilization: more than just syndrome X. Compar Biochem Physiol. 2003, 136: 95-112. 10.1016/S1095-6433(03)00011-4.
  141. Cowy S, Hardy RW: The metabolic syndrome: A high-risk state for cancer?. Am J Pathol. 2006, 169: 1505-1522. 10.2353/ajpath.2006.051090.
  142. Barclay AW, Petocz P, McMillan-Price J, Flood VM, Prvan T, Mitchell P, Brand-Miller JC: Glycemic index, glycemic load, and chronic disease risk–a meta-analysis of observational studies. Am J Clin Nutr. 2008, 87: 627-637.PubMed
  143. Heiskanen TH, Niskanen LK, Hintikka JJ, Koivumaa-Honkanen HT, Honkalampi KM, Haatainen KM, Viinamäki HT: Metabolic syndrome and depression: a cross-sectional analysis. J Clin Psychiatry. 2006, 67: 1422-1427. 10.4088/JCP.v67n0913.PubMed
  144. Koponen H, Jokelainen J, Keinänen-Kiukaanniemi S, Kumpusalo E, Vanhala M: Metabolic syndrome predisposes to depressive symptoms: a population-based 7-year follow-up study. J Clin Psychiatry. 2008, 69: 178-182. 10.4088/JCP.v69n0202.PubMed
  145. Miettola J, Niskanen LK, Viinamäki H, Kumpusalo E: Metabolic syndrome is associated with self-perceived depression. Scand J Prim Health Care. 2008, 26: 203-210. 10.1080/02813430802117624.PubMed CentralPubMed
  146. Akbaraly TN, Ancelin ML, Jaussent I, Ritchie C, Barberger-Gateau P, Dufouil C, Kivimaki M, Berr C, Ritchie K: Metabolic syndrome and onset of depressive symptoms in the elderly: findings from the three-city study. Diabetes Care. 2011, 34: 904-909. 10.2337/dc10-1644.PubMed CentralPubMed
  147. Saudny H, Cao Z, Egeland GM: Poor self-reported health and its association with biomarkers among Canadian Inuit. Int J Circumpolar Health. 2012, 71: 18589-,
  148. Nijs J, Van Houdenhove B, Oostendorp RA: Recognition of central sensitization in patients with musculoskeletal pain: Application of pain neurophysiology in manual therapy practice. Manual Ther. 2010, 15: 135-141. 10.1016/j.math.2009.12.001.
  149. Grimble RF: Inflammatory status and insulin resistance. Curr Opin Clin Nutr Metab Care. 2002, 5: 551-559. 10.1097/00075197-200209000-00015.PubMed
  150. Glassman SD, Alegre G, Carreon L, Dimar JR, Johnson JR: Perioperative complications of lumbar instrumentation and fusion in patients with diabetes mellitus. Spine J. 2003, 3: 496-501. 10.1016/S1529-9430(03)00426-1.PubMed
  151. Helmersson J, Vessby B, Larsson A, Basu S: Association of type 2 diabetes with cylcooxygenase-mediated inflammation and oxidative stress in an elderly population. Circulation. 2004, 109: 1729-1734. 10.1161/01.CIR.0000124718.99562.91.PubMed
  152. Robinson D, Mirovsky Y, Halperin N, Evron Z, Nevo Z: Changes in proteoglycans of intervertebral disc in diabetic patients: a possible cause of increased back pain. Spine. 1998, 23: 849-856. 10.1097/00007632-199804150-00001.PubMed
  153. Gaida JE, Alfredson H, Kiss ZS, Bass SL, Cook JL: Asymptomatic Achilles tendon pathology is associated with a central fat distribution in men and a peripheral fat distribution in women: a cross sectional study of 298 individuals. BMC Musculoskelet Disord. 2010, 11: 41-10.1186/1471-2474-11-41.PubMed CentralPubMed


© Seaman; licensee BioMed Central Ltd. 2013

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.