Associations of Metabolic Syndrome and Its Components with the Risk of Incident Knee Osteoarthritis Leading to Hospitalization: A 32-Year Follow-up Study

Abstract

Objectives

To examine whether metabolic syndrome or its individual components predict the risk of incident knee osteoarthritis (OA) in a prospective cohort study during a 32-year follow-up period.

Design

The cohort consisted of 6274 participants of the Mini-Finland Health Survey, who were free from knee OA and insulin-treated diabetes at baseline. Information on the baseline characteristics, including metabolic syndrome components, hypertension, elevated fasting glucose, elevated triglycerides, reduced high-density lipoprotein, and central obesity were collected during a health examination. We drew information on the incidence of clinical knee OA from the national Care Register for Health Care. Of the participants, 459 developed incident knee OA. In our full model, age, gender, body mass index, history of physical workload, smoking history, knee complaint, and previous injury of the knee were entered as potential confounding factors.

Results

Having metabolic syndrome at baseline was not associated with an increased risk of incident knee OA. In the full model, the hazard ratio for incident knee OA for those with metabolic syndrome was 0.76 (95% confidence interval [0.56, 1.01]). The number of metabolic syndrome components or any individual component did not predict an increased risk of knee OA. Of the components, elevated plasma fasting glucose was associated with a reduced risk of incident knee OA (hazard ratio 0.71, 95% confidence interval [0.55, 0.91]).

Conclusions

Our findings do not support the hypothesis that metabolic syndrome or its components increase the risk of incident knee OA. In fact, elevated fasting glucose levels seemed to predict a reduced risk.

Keywords

knee osteoarthritis metabolic syndrome hypertension impaired glucose tolerance

Introduction

Osteoarthritis (OA) is a chronic, progressive, and degenerative disease of the joints, also characterized by abnormal remodeling of joint tissues.^1,2 In 2 Finnish health surveys conducted among participants aged over 30 years, knee OA was diagnosed among 5% to 6% of men and 7% to 8% of women.^3,4 In the knee, local biomechanical factors such as obesity, knee malalignment, knee laxity, joint dysplasia, injuries affecting the articular surfaces, tears of menisci or ligaments, decreased proprioceptive accuracy, muscle weakness, occupational loading factors, and excessive loading during leisure time physical activities are widely accepted as predisposing factors for OA.^1,2 The role of systemic factors in the risk of knee OA has been studied with growing intensity. The evidence of the role of nutritional factors such as serum vitamin D status, dietary magnesium, and vitamin C intake, as well as hormonal status in the risk of knee OA is still controversial.^2,5-8

Metabolic syndrome is constituted by insulin resistance, visceral adiposity, dyslipidemia, and elevated blood pressure. It is a cluster of different conditions associated with an increased risk of endothelial dysfunction, prothrombotic state, proinflammatory state, nonalcoholic fatty liver disease, reproductive disorders, cardiovascular disease including coronary heart disease, and type 2 diabetes mellitus, as well as all-cause mortality.^9,10 It has been hypothesized that metabolic syndrome and its individual components affect the pathogenesis of knee OA. The methods of previous studies have been diverse in terms of the covariates and endpoints they have included, and some studies have not adjusted for body mass index (BMI).^11-20 Many studies have found that having metabolic syndrome is associated with an increased likelihood of knee OA, but this connection has attenuated after adjustment for BMI.^11-14,21 The previous results concerning individual metabolic syndrome components and their predictive ability of knee OA are controversial.^5,11-20

Given the conflicting results of previous studies, the objective of this study was to assess the association between metabolic syndrome and its individual components and incident clinical knee OA in a longitudinal setting over a 32-year follow-up period.

Materials and Methods

Study Sample and Design

The present prospective cohort study is based on the Mini-Finland Health Survey, which was carried out in Finland between 1978 and 1980.²² The nationally representative population sample was formed using a 2-stage stratified cluster sampling method, and participants were drawn from the population register of the adult population aged 30 years or over, living in mainland Finland. A more detailed description of the study population and design has been published elsewhere.^23,24

In the first stage, 40 representative areas were selected. In the second stage, a systematic sample of inhabitants was drawn from each area. The sample consisted of 8,000 people (3,637 men and 4,363 women) aged 30 years or over. Of the sample, 90% participated in the comprehensive health examination. Of all the 7,217 participants of the Mini-Finland Health Survey, 782 had knee OA at the baseline examination, 39 had been hospitalized for knee OA before the examination, 63 were on insulin medication, and 113 had missing data in any necessary determinant. A total of 943 participants met one or more of the aforementioned exclusion criteria. The cohort of the current study included 6,274 participants who were followed up until December 31, 2010.

The Mini-Finland Health Survey was carried out before the current legislation on medical research of human subjects became effective. The participants were fully informed of the use of the collected data for research purposes and participated on a voluntary basis in compliance with the principles of the World Medical Association (WMA) Declaration of Helsinki. Agreeing to participate in the baseline health examination was taken to indicate informed consent. The planning, conduct and reporting are in accordance with the International Committee of Medical Journal Editors (ICMJE) recommendations for the protection of research participants.

Baseline Health Examination

The baseline screening examination consisted of questionnaires and symptom interviews. A clinical examination including medical history, symptom history, and physical status was performed 3 to 6 months later at a mobile clinic.²³ Baseline diagnosis of knee OA was based on a standardized clinical examination. Specially trained physicians performed the physical examinations according to detailed written instructions with uniform diagnostic criteria. The examination covered medical history, symptom history, and limitations in the range of motion, tenderness, deformations, joint effusion, and stability of the knee joint. In brief, prevalent knee OA was diagnosed if some of the following conditions were fulfilled: (1) previous knee arthroplasty, even in the absence of convincing evidence of the diagnosis of knee OA; (2) typical knee OA symptoms and either of the following (even in the absence of abnormality in physical status): history of previously diagnosed knee OA (even in the absence of documentation), or documented knee OA diagnosis even in the absence of convincing evidence of the diagnosis; or (3) limitation in joint range of motion, motion tenderness, and bony deformity suggesting knee OA, but insufficiently indicative history to enable a conclusive diagnosis. The clinical examination and criteria of knee OA have been previously described in detail.^3,7,23,24 The final diagnosis of knee OA was made based on disease history, symptoms, and clinical findings. The agreement between the clinical and radiological diagnosis of knee OA was moderate.²⁵ Knee complaint was defined as difficulty in walking or limping due to discomfort or trouble in the knee during the previous month. This information was acquired via a standardized interview on musculoskeletal symptoms.³

Information on socioeconomic background, symptoms, diseases, medications, and lifestyle at baseline was collected via questionnaires and interviews. Smoking was classified into 3 groups based on self-reported information on smoking habits: (1) never smoked, (2) ex-smoker, and (3) current smoker. History of physical workload was classified into 6 categories on the basis of the questionnaire responses: (1) light sedentary work, (2) other sedentary work, (3) physically light standing work or light work involving movement, (4) fairly light or medium heavy work involving movement, (5) heavy manual work, and (6) very heavy manual work. For this study, a history of physical workload was dichotomized into physical work—classes 3 to 6—and no physical work—classes 1 and 2.

Traumatic knee injury was defined as a previous distension of the knee, meniscal tear or rupture of the cruciate ligament, or a femoral or tibial fracture of the knee region. A physician classified the injuries after the baseline examination according to the International Classification of Diseases 8th revision based on all information available in the medical history, symptoms, and physical findings of the clinical examination. The injuries were only accounted for if they had led to permanent damage or to any continuing impairment or complaint.

At the baseline examination, height and weight were measured and BMI (kg/m²) was calculated. We classified the participants into 3 groups by BMI: (1) normal or below normal weight, <25.0 kg/m²; (2) overweight, 25.0 to 29.9 kg/m²; and (3) obese, >30 kg/m².

Overnight (minimum 11 hours) fasting blood samples were taken and stored at −20°C. These samples were analyzed and serum total cholesterol concentrations were determined a few weeks after the samples were taken, using a modified version of the direct Liebermann-Burchard method without serum-blank subtraction (Boehringer, Mannheim, Germany). Fasting serum samples taken during the baseline health examination were kept frozen at −0°C until 2003, when 25(OH)D levels were determined by radioimmunoassay (DiaSorin, Inc., Stillwater, MN). Serum insulin was measured from the stored samples between 2002 and 2003, using a modified version of Herbert’s immunoassay method (microparticle enzyme immunoassay; Insulin kit (REAGENT): Abbott Laboratories, Dainabot, Tokyo, Japan; Analyzer: ABBOT, IMX 20238). Insulin resistance was evaluated by the Homeostatic Model Assessment of Insulin Resistance.²⁶

Baseline Data of Metabolic Syndrome and Its Components

Our definition of the metabolic syndrome was based on the harmonized definition of the metabolic syndrome.⁹ The criterion for metabolic syndrome was the presence of any 3 or more of the following 5 components: central obesity, elevated mean blood pressure (systolic blood pressure ≥130 mmHg or diastolic blood pressure ≥85 mmHg or antihypertensive medication), elevated serum triglycerides (≥1.7 mmol/L), reduced serum high-density lipoprotein (HDL) level (<1.3 mmol/L among women and <1.0 mmol/L among men), and elevated plasma fasting glucose (≥5.6 mmol/L, or diagnosed type 2 diabetes without insulin therapy). For the purposes of this study, we excluded diabetics with insulin therapy at baseline.

Since the present data did not include information on waist circumference, we used the ratio of subscapular to triceps skinfold as an indicator of central versus peripheral distribution of body fat.²⁷ Trained technicians measured skinfold thicknesses on the right side of the body using a Harpenden skinfold caliper (British Indicators Ltd, John Bull). The subscapular skinfold was measured at the inferior angle of the scapula. The triceps skinfold was measured posteriorly at the halfway point between the outer edge of the acromion process and the olecranon process of the ulna. The highest quintile of the ratio (>1.23) was considered to represent truncal adiposity in the present study. This cutoff was chosen on the basis of the knowledge on the prevalence of central obesity in Finland in 1987.²⁸

We measured casual blood pressure twice at 90-second intervals using the auscultatory method. As described above, overnight fasting blood samples were taken and stored at −20°C. These samples were analyzed and serum HDL cholesterol, plasma fasting glucose, and serum triglycerides concentrations were determined a few weeks after the samples were taken. We analyzed serum HDL level using Mg-dextrane sulfate precipitation and determined serum triglyceride concentration using the fully enzymatic method (Boehringer, Mannheim, Germany). Plasma fasting glucose was determined using a glucose oxidase method (Boehringer, Mannheim, Germany).

Follow-up Information on Incident Knee OA

We drew the follow-up information on the incidence of knee OA from the national Care Register for Health Care. Patients treated in hospital with a diagnosis of knee OA were identified using the International Classification of Diseases, until 1986 with code 713.01 of the 8th revision, from 1987 until 1995 with code 7151F or 7152F of the 9th revision, and from 1996 onwards with code M17 of the 10th revision. Prior to 1995, the register contained data on patients discharged from inpatient care in hospitals only. From 1995 onwards, diagnoses given in day surgery and specialized outpatient care were also recorded. The follow-up period started from the baseline examination in 1978 to 1980 and continued until the first hospitalization for knee OA, death, or the end of 2010, whichever came first. The register data on all the participants of the study was retrieved from the Care Register for Health Care using their social security number. Record linkage of national health registers to the survey data was approved by the register authorities.

Statistical Analysis

We used Cox’s proportional hazards model to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for incident knee OA according to the categories of the variables of interest: the presence of metabolic syndrome, the 5 components of metabolic syndrome (elevated blood pressure, elevated fasting glucose, elevated triglycerides, reduced HDL cholesterol, and central obesity, the cutoff values of which are described above), and the number of present components of the metabolic syndrome. We first estimated HRs adjusted for age and gender only. Then, we constructed 3 main models: a basic model adjusted for age, gender, and BMI with each variable of interest entered one by one; a full model in which the histories of physical workload and smoking, and difficulty walking due to disorders or complaints in the knees, and previous injury of the knee were also entered as potential confounding factors; and a full model from which the first 15 years of the follow-up was excluded to examine the effect of the possible preclinical disease phase. We selected the potential confounding factors in the full model from those available on the basis of prior assumptions of determinants of knee OA and metabolic syndrome and its components, of which age, gender, BMI, history of physical workload, and knee injuries are major risk factors for knee OA.^2,29,30 We studied the effect modification by entering all the multiplicative first-degree interaction terms of the potential risk determinants, one by one, into the full model. Likelihood ratio statistics were used to test the statistical significance of the interactions. We used the SAS System for Windows, version 9.1 (SAS Institute, Inc., Cary, NC) for all the analyses.

Results

Table 1 shows the baseline characteristics of the participants with and without incident knee OA leading to hospitalization. During the follow-up of 157,987 person-years, 459 participants developed clinical knee OA. Of the incident knee OA cases, significantly more were female, overweight or obese, nonsmokers, and had a history of heavy physical work and knee injuries, current knee complaints, metabolic syndrome, and higher serum 25(OH)D concentrations. The mean age of the group that did not develop incident knee OA during follow-up was higher. The mean levels of serum total cholesterol, plasma fasting glucose, and systolic blood pressure were lower among the participants who developed incident knee OA. Mean triceps skinfold thickness, subscapular skinfold thickness, and subscapular per triceps skinfold ratio were higher among those who developed incident knee OA than among those who did not.

Table 1.

Baseline Characteristics of Participants Free from Knee OA at Follow-up and Incident Knee OA Cases, Mini-Finland Health Survey, 1978 to 1980.

Factor	Participants Free from Knee OA at Follow-up	Incident Knee OA Cases
Number of participants	5,815	459
Age, years
30-44	41.4%	52.7%
45-54	22.9%	30.1%
55-98	35.7%	17.2%
Gender
Male	49.9%	37.9%
Female	50.1%	62.1%
BMI, kg/m²
<25.0	49.6%	33.8%
25.0-29.9	37.9%	46.2%
≥30.0	12.5%	20.0%
Smoking
Never	52.4%	62.5%
Ex-smoker	21.8%	20.3%
Current	25.7%	17.2%
Physical work	51.4%	68.2%
Knee complaints	7.5%	12.4%
Knee injury	1.7%	4.4%
Diabetes (without insulin therapy)	4.1%	1.5%
Antihypertensive medication	12.3%	9.6%
Treatment for dyslipidemia	1.3%	0.4%
Metabolic syndrome	19.2%	12.0%
Number of metabolic syndrome components
0	13.5%	17.2%
1	37.6%	41.4%
2	30.1%	29.4%
3	14.4%	10.5%
4	4.1%	1.5%
5	0.3%	0%
Age, years, mean	49.9 (± SD 13.8)	44.8 (± SD 10.0)
BMI, kg/m², mean	25.5 (± SD 3.86)	26.9 (± SD 3.86)
Fasting serum 25(OH)D, nmol/L, mean	43.4 (± SD 19.7)	46.3 (± SD 20.0)
Fasting serum total cholesterol, mmol/L, mean	6.92 (± SD 1.38)	6.73 (± SD 1.15)
Fasting serum HDL, mmol/L, mean	1.70 (± SD 0.41)	1.72 (± SD 0.38)
Fasting plasma glucose, mmol/L, mean	5.35 (± SD 1.11)	5.14 (± SD 0.54)
Fasting serum triglycerides, mmol/L, mean	1.50 (± SD 1.06)	1.33 (± SD 0.64)
HOMA-IR, mean	2.09 (± SD 2.09)	1.97 (± SD 1.10)
Systolic blood pressure, mmHg, mean	145 (± SD 23.5)	139 (± SD 18.6)
Diastolic blood pressure, mmHg, mean	87.0 (± SD 11.8)	86.1 (± SD 10.2)
Triceps skinfold, mm, mean	16.5 (± SD 6.95)	19.4 (± SD 7.38)
Subscapular skinfold, mm, mean	15.4 (± SD 7.01)	17.6 (± SD 7.47)
Subscapular per triceps skinfold ratio, mean	0.99 (± SD 0.39)	0.96 (± SD 0.33)

OA = osteoarthritis; BMI = body mass index; SD = standard deviation; 25(OH)D = 25-hydroxyvitamin D; HDL = high-density lipoprotein; HOMA-IR = Homeostatic Model Assessment of Insulin Resistance.

Table 2 shows the HRs and their 95% CIs for incident knee OA leading to hospitalization, according to age, gender, presence of metabolic syndrome, number of metabolic syndrome components, and individual components, as both unadjusted and adjusted for age and gender. Elevated plasma fasting glucose levels predicted a reduced risk of knee OA: the HR (95% CI) for knee OA was 0.75 (0.58-0.97) for those with elevated plasma fasting glucose concentrations in comparison to those without. The HRs for metabolic syndrome and its other components remained nonsignificant.

Table 2.

Hazard Ratios and Their 95% Confidence Intervals for Incident Knee OA Leading to Hospitalization in Categories of Metabolic Syndrome, Each of Its Individual Components, and Number of Metabolic Syndrome Components as Unadjusted and Adjusted for Age and Gender.

	N	n	Unadjusted, HR (95% CI)	Adjusted for Age and Gender, HR (95% CI)
Age, years
30-44	2,651	242	1	1
45-54	1,468	138	1.29 (1.04-1.59)	1.27 (1.03-1.57)
55-98	2,155	79	1.16 (0.89-1.50)	1.11 (0.86-1.45)
Gender
Male	3,074	174	1	1
Female	3,200	285	1.37 (1.13-1.66)	1.36 (1.13-1.64)
Central obesity^a
No	5,028	372	1	1
Yes	1,246	87	0.99 (0.78-1.24)	1.17 (0.91-1.51)
Elevated mean blood pressure^b
No	1,296	105	1	1
Yes	4,978	354	1.22 (0.98-1.52)	1.22 (0.97-1.53)
Elevated plasma fasting glucose^c
No	4,708	388	1	1
Yes	1,566	71	0.75 (0.58-0.97)	0.75 (0.58-0.97)
Elevated serum triglycerides^d
No	4,554	359	1	1
Yes	1,720	100	1.03 (0.82-1.28)	1.05 (0.84-1.32)
Reduced serum HDL cholesterol^e
No	5,909	439	1	1
Yes	365	20	1.02 (0.65-1.59)	0.96 (0.61-1.51)
Metabolic syndrome^f
No	5,125	404	1	1
Yes	1,149	55	0.92 (0.69-1.22)	0.97 (0.73-1.29)
Number of metabolic syndrome^f components
0	863	79	1	1
1	2,379	190	1.10 (0.85-1.43)	1.11 (0.85-1.45)
2	1,883	135	1.14 (0.86-1.50)	1.19 (0.89-1.60)
3	886	48	1.08 (0.75-1.54)	1.18 (0.81-1.72)
4	243	7	0.74 (0.34-1.60)	0.80 (0.37-1.76)
5	20	0
Number of metabolic syndrome^f components
Increment by one component			1.00 (0.91-1.10)	1.02 (0.93-1.13)

OA = osteoarthritis; N = number of participants in respective category; n = number of disease cases in respective category; HR = hazard ratio; CI = confidence interval; HDL = high-density lipoprotein.

Subscapular to triceps skinfold ratio >1.23.

Systolic blood pressure ≥130 mmHg or diastolic blood pressure ≥85 mmHg or antihypertensive medication.

Concentration ≥5.6 mmol/L or diagnosed type 2 diabetes without insulin therapy.

Concentration ≥1.7 mmol/L.

Concentration <1.3 mmol/L in women and <1.0 mmol/L in men.

Defined as presence of any 3 or more of following 5 components: systolic blood pressure ≥130 mmHg or diastolic blood pressure ≥85 mmHg or antihypertensive drug treatment, serum triglycerides ≥1.7 mmol/L, serum HDL cholesterol <1.3 mmol/L among women and <1.0 mmol/L among men, plasma fasting glucose ≥5.6 mmol/L, and subscapular to triceps skinfold ratio >1.23.

Table 3 shows the adjusted HRs and their 95% CIs for incident knee OA leading to hospitalization. After adjustment for age, gender, and BMI, the HR for incident knee OA was 0.83 (95% CI [0.59, 1.15]) for those with baseline metabolic syndrome. After adjustment for all covariates, the HR for incident knee OA was 0.76 (95% CI [0.56, 1.01]) for those with metabolic syndrome at baseline.

Table 3.

Adjusted Hazard Ratios and Their 95% Confidence Intervals for Incident Knee OA Leading to Hospitalization in Categories of Its Major Risk Factors, Potential Confounding Factors, Metabolic Syndrome, Each of Its Individual Components, and Number of Metabolic Syndrome Components.

	N	n	Basic Model,^a HR (95% CI)	Full Model,^b HR (95% CI)	Full Model,^b First 15 Years of Follow-up Excluded
	N	n	Basic Model,^a HR (95% CI)	Full Model,^b HR (95% CI)	N	n	HR (95% CI)
Age, years
30-44	2,651	242	1	1	2,504	206	1
45-54	1,468	138	1.08 (0.87-1.34)	1.07 (0.86-1.33)	1,262	108	1.02 (0.80-1.30)
55-98	2,155	79	0.89 (0.68-1.16)	0.91 (0.69-1.21)	1,099	40	0.69 (0.48-0.99)
Gender
Male	3,074	174	1	1	2,253	137	1
Female	3,200	285	1.45 (1.20-1.76)	1.32 (1.05-1.66)	2,612	217	1.29 (1.00-1.67)
BMI, kg/m²
<25.0	3,041	155	1	1	2,412	126	1
25-29.9	2,417	212	2.06 (1.67-2.55)	2.04 (1.64-2.54)	1,876	158	1.98 (1.55-2.53)
≥30.0	816	92	3.07 (2.36-3.99)	3.14 (2.37-4.17)	577	70	3.32 (2.44-4.56)
Smoking
Never	3,336	287	1	1	2,671	219	1
Ex-smoker	1,362	93	0.92 (0.69-1.22)	0.89 (0.69-1.15)	1,023	72	0.90 (0.68-1.20)
Current	1,576	79	0.76 (0.57-1.02)	0.76 (0.58-0.99)	1,171	63	0.78 (0.58-1.05)
Physical work
No	2,971	146	1	1	1,929	104	1
Yes	3,303	313	1.31 (1.06-1.68)	1.29 (1.05-1.57)	2,936	250	1.31 (1.04-1.66)
Knee complaints
No	5,781	402	1	1	4,537	320	1
Yes	493	57	1.49 (1.04-2.13)	1.68 (1.24-2.27)	328	34	1.34 (0.91-1.96)
Knee injury
No	6,158	439	1	1	4,790	341	1
Yes	116	20	2.76 (1.57-4.84)	2.21 (1.36-3.61)	75	13	2.28 (1.25-4.17)
Central obesity^c
No	5,028	372	1	1	3,904	286	1
Yes	1,246	87	0.95 (0.71-1.27)	0.94 (0.72-1.21)	961	68	0.93 (0.70-1.25)
Elevated mean blood pressure^d
No	1,296	105	1	1	1,169	82	1
Yes	4,978	354	1.09 (0.84-1.41)	1.02 (0.80-1.28)	3,696	272	1.11 (0.85-1.44)
Elevated plasma fasting glucose^e
No	4,708	388	1	1	3,811	301	1
Yes	1,566	71	0.74 (0.55-0.99)	0.71 (0.55-0.91)	1,054	53	0.73 (0.54-0.98)
Elevated serum triglycerides^f
No	4,554	359	1	1	3,720	284	1
Yes	1,720	100	0.78 (0.59-1.02)	0.86 (0.68-1.09)	1,145	70	0.82 (0.62-1.08)
Reduced serum HDL cholesterol^g
No	5,909	439	1	1	4,635	339	1
Yes	365	20	0.81 (0.48-1.38)	0.90 (0.57-1.42)	230	15	0.93 (0.55-1.58)
Metabolic syndrome^h
No	5,125	404	1	1	4,147	311	1
Yes	1,149	55	0.83 (0.59-1.15)	0.76 (0.56-1.01)	718	43	0.85 (0.61-1.18)
Number of metabolic syndrome^h components
0	863	79	1	1	802	63	1
1	2,379	190	1.01 (0.74-1.36)	0.90 (0.69-1.19)	1,915	153	0.98 (0.72-1.33)
2	1,883	135	0.84 (0.59-1.19)	0.83 (0.61-1.13)	1,430	95	0.82 (0.58-1.16)
3	886	48	0.81 (0.52-1.27)	0.72 (0.49-1.07)	575	37	0.81 (0.52-1.27)
4	243	7	0.63 (0.26-1.48)	0.47 (0.21-1.05)	129	6	0.63 (0.27-1.49)
5	20	0			14	0
Number of metabolic syndrome^h components
Increment by one component			0.90 (0.79-1.01)	0.88 (0.79-0.98)			0.90 (0.79-1.01)

OA = osteoarthritis; N = number of participants in respective category; n = number of disease cases in respective category; HR = hazard ratio; CI = confidence interval; BMI = body mass index; HDL = high-density lipoprotein.

Adjusted for age, gender, and BMI.

Adjusted for age, gender, BMI, history of physical workload, smoking history, difficulty walking due to disorder or complaint in the knees, and previous knee injury. For individual metabolic syndrome components: plasma fasting glucose, serum triglycerides, serum HDL, mean blood pressure, and central obesity, analysis was adjusted for other metabolic syndrome components. For combined variables: metabolic syndrome and number of metabolic syndrome components, no adjustment for individual metabolic syndrome components were performed.

Subscapular to triceps skinfold ratio >1.23.

Systolic blood pressure ≥130 mmHg or diastolic blood pressure ≥85 mmHg or antihypertensive medication.

Concentration ≥5.6 mmol/L or diagnosed type 2 diabetes without insulin therapy.

Concentration ≥1.7 mmol/L.

Concentration <1.3 mmol/L in women and <1.0 mmol/L in men.

The number of metabolic syndrome components at baseline was inversely associated with the risk of incident knee OA. In the full model, HR per increment by one component was 0.88 (95% CI [0.79, 0.98]) and the P value for the linear trend was 0.02 ( Table 3 ).

Of the individual metabolic syndrome components, none were associated with a significantly increased risk of incident knee OA. Elevated plasma fasting glucose level at baseline predicted significantly lower incidence of knee OA both when adjusted for age, gender, and BMI, and when adjusted for all the covariates (HR 0.71, 95% CI [0.55, 0.91]). After excluding the first 15 years of follow-up, risk reduction persisted as significant ( Table 3 ).

We observed some statistically significant interactions between metabolic syndrome, its components, and the covariates. Among women, central obesity predicted a significantly lower risk of incident knee OA (HR 0.53, 95% CI [0.30, 0.94], P = 0.016) but this was not the case among men (HR 1.17, 95% CI [0.86, 1.59], P value for interaction, 0.016). Among those with BMI in the range of 25.0 to 29.9 kg/m², elevated serum triglycerides showed a significantly lower risk of incident knee OA, unlike among those with higher or lower BMI (BMI < 25.0 kg/m²: HR 1.32, 95% CI [0.81, 2.15]; BMI 25.0-29.9 kg/m²: HR 0.55, 95% CI [0.38, 0.79]; BMI > 30.0 kg/m²: HR 1.20, 95% CI [0.78, 1.86], P value for interaction, 0.004). Knee complaints at baseline significantly modified the associations of metabolic syndrome, elevated mean blood pressure, and elevated triglycerides with the risk of developing knee OA ( Table 4 ). These factors predicted significantly reduced risks among the participants with knee complaints only.

Table 4.

Hazard Ratios with 95% Confidence Intervals for Incident Knee OA According to Certain Covariates among Those with and without Knee Complaints^a at Baseline.

	No Knee Complaints^a			Knee Complaints^a			P Value for Interaction^b
	N	n	HR (95% CI)	N	n	HR (95% CI)	P Value for Interaction^b
Metabolic syndrome^c	1,035	51	0.86 (0.63-1.18)	114	4	0.28 (0.10-0.80)	0.031
Elevated serum triglycerides^d	1,546	91	0.97 (0.76-1.25)	174	9	0.39 (0.18-0.83)	0.023
Elevated mean blood pressure^e	4,551	311	1.09 (0.85-1.40)	427	43	0.59 (0.31-1.12)	0.039

OA = osteoarthritis; N = number of participants in respective category; n = number of incident knee OA cases in respective category; HR = hazard ratio; CI = confidence interval.

Self-reported difficulty walking or limping due to discomfort or trouble in knee during preceding month.

Tested using likelihood ratio statistics.

Defined as presence of any 3 or more of following 5 components: systolic blood pressure ≥130 mmHg or diastolic blood pressure ≥85 mmHg or antihypertensive medication, serum triglycerides ≥1.7 mmol/L, serum HDL cholesterol <1.3 mmol/L in women and <1.0 mmol/L in men, and plasma fasting glucose ≥5.6 mmol/L, and subscapular to triceps skinfold ratio >1.23.

Concentration ≥1.7 mmol/L.

Systolic blood pressure ≥130 mmHg or diastolic blood pressure ≥85 mmHg or antihypertensive medication.

Discussion

In our prospective cohort study, the presence of metabolic syndrome at baseline did not predict incident knee OA leading to hospitalization. On the contrary, even after adjustment for a comprehensive set of potential confounding factors, the number of metabolic syndrome components and fasting plasma glucose concentration were inversely proportional to the risk of developing knee OA.

The current study found no significant association between having metabolic syndrome and the risk of incident clinical knee OA. The results of most previous studies^11,13-16,21 are in line with our results, although in one study²⁰ the accumulation of metabolic syndrome components predicted the risk of total knee replacement due to knee OA even when adjusted for BMI. A recent systematic review³¹ also concluded that current data suggest that metabolic syndrome is not associated with knee OA, which is in line with our results.

Central obesity is strongly associated with BMI, a known risk factor for knee OA.^32,33 In several previous studies,^{12-15,20,21,34-36} central obesity has predicted an increased risk of knee OA or total knee replacement due to OA in adjusted analyses, but in most of these studies, this association attenuated after adjustment for BMI. In 2 of these studies, the association of waist circumference and knee OA persisted after adjustment for BMI.^11,20 In a recent study, increased waist circumference was associated with a higher risk of total knee replacement due to OA among those aged under 70 years but not among those aged 70 years or over.¹⁶ Our study is in line with the majority of these studies, as the results suggest no significant association between central obesity and the risk of incident knee OA. A recent review³⁷ discussed how systemic and local adipose tissue might play different roles in knee OA pathogenesis, but the mechanisms behind this and its relevance remain unclear.

Although cartilage is avascular, it has been suggested that vascular pathology might play a role in OA pathogenesis.^38,39 This may be due to changes in the microvasculature of the subchondral bone or other joint tissues rather than direct effects on cartilage. Even in early knee OA, subchondral bone marrow lesions have been detected, which has led to a suggestion that the site of OA onset might be the subchondral bone rather than the cartilage tissue itself. The potential association between hypertension, low serum HDL concentrations, and high serum triglyceride concentrations has been hypothesized as originating from vascular pathology.^38,39

Several previous studies have focused on the association of hypertension and the risk of knee OA, but the results are controversial,^11-20,40,41 and in some, hypertension has been related to an increased risk of knee OA.^{12,13,17-20,40} In some studies,^13,40 after adjustments for BMI this association has attenuated, but in others^12,17,19,20 it has persisted. In yet other studies, hypertension was not associated with an increased risk of knee OA or total knee arthroplasty, even without adjustment for BMI.^11,14,15 In one study, hypertension was related to the risk of bilateral radiographic knee OA independent of BMI, but was not related to unilateral knee OA.⁴¹ A recent study found hypertension to be significantly associated with a risk of total knee replacement among participants aged under 50 years, but there was no significant association in older age groups.¹⁶ A recent meta-analysis⁴² showed an association between hypertension and knee OA. However, the findings of all studies, except for one,¹⁹ which was included in the meta-analysis, were attenuated after adjustment for BMI. Therefore, confounding by BMI is possible, and these results may not indicate that hypertension is an independent risk factor for knee OA. The current study suggests that hypertension does not significantly increase the risk of incident clinical knee OA.

Our results suggest that elevated serum triglyceride concentrations do not predict incident knee OA. Serum hypertriglyceridemia was not associated with knee OA in the majority of previous studies.^11-16,41

A low level of serum HDL was not associated with knee OA in most studies,^{11,13-16,20,41} but in one Japanese study it was.¹⁹ In another study, low HDL level was related to both radiographic and symptomatic knee OA among men, but not among women.¹² The results of the current study suggest no correlation between low serum HDL and increased incidence of knee OA.

Our results do not suggest that elevated plasma fasting glucose levels or diagnosed diabetes without insulin therapy predict higher incidence of knee OA. Instead, our study observed that elevated plasma fasting glucose levels are related to a reduced risk of incident knee OA. Impaired fasting glycemia was associated with knee OA in some studies.^5,11,20 A recent systematic review found little evidence that impaired glucose metabolism was an independent risk factor for knee OA.⁴³ Another recent review on the association between type 2 diabetes mellitus and OA discussed the effect of hyperglycemia on chondrocytes as being potentially mediating through oxidative stress and possibly even glucose toxicity during OA.⁴⁴ However, another study found that supraphysiological glucose concentrations preserve glucose uptake, hyaluronan synthesis, and matrix integrity, and induce anti-inflammatory actions, thereby promoting cartilage repair in equine chondrocytes studied in vitro.⁴⁵

As expected, female gender, higher BMI, heavy physical workload, previous knee injuries, and knee complaints predicted an increased incidence of knee OA, as reported previously.^7,30 In the current study, baseline knee complaints significantly modified the associations of metabolic syndrome, elevated mean blood pressure, and elevated serum triglycerides with the risk of developing knee OA: these factors predicted a reduced risk among those with knee complaints only. Possible explanations for this interaction are speculative. Knee complaints might, for example, lead to a reduced exercise rate and therefore affect the lipid profile and blood pressure levels, which is a possible explanation for the interaction. The finding suggesting that elevated serum triglycerides have a protective effect against developing knee OA among overweight individuals, but not among those with normal or below normal weight or obesity, does not seem rational at all. That central obesity among women, but not among men, is a predictor of lower knee OA risk, is plausible through different adiposity patterns and the possibly different predictive value of central obesity for knee OA among women compared with men. In all, the authors believe that the great number of interactions tested has led to significant findings by chance. The findings need therefore replication in further studies to confirm an interaction. It is also noteworthy that we had no a priori hypothesis on effect modification.

Smoking was associated with a reduced risk of incident knee OA. Some previous studies^8,12 as well as a meta-analysis⁴⁶ observed that smoking had a protective effect on incident knee OA.

The current study had many strengths, but also some limitations. The main strengths of our study were its prospective design and the large, nationally representative and well-characterized population sample. The long follow-up period of 32 years was a major strength of this study. The reliability of knee OA diagnosis at baseline and the agreement between clinical and radiological diagnoses proved to be acceptable in quality estimations carried out as part of field examinations.²⁵ Another strength of the study was its access to information on the major risk factors of knee OA at baseline. Although the detailed data on multiple knee OA risk factors allowed adjustment for potential confounders, the possibility of residual confounding cannot be ruled out.

One limitation of the current study was that the present data did not include information on waist circumference. Waist circumference and body fat distribution are better predictors of metabolic syndrome than BMI.^47,48 The available data on the subscapular to triceps skinfold ratio were used as a proxy for central obesity. There is, however, no clear limit as to what ratio threshold would correspond to the waist circumference threshold generally used⁹ for central obesity. Among the Finnish adult population, the prevalence of central obesity, defined as waist circumference over 100 cm among men and 90 cm among women, was 23.2% (age standardized 22.4%) among men and 18.3% (age standardized 17.6%) among women in 1987.²⁸ Therefore, we decided to use the highest quintile of subscapular to triceps skinfold ratio to approximate abdominal obesity. Another limitation of our study was that the follow-up covered knee OA cases admitted to hospital, but only a part of all patients suffering from knee OA are ever hospitalized. The hospitalized patients may not be representative of all the people who develop knee OA. The incidence of knee OA in this study was 6% among men and 9% among women. In the Health 2000 survey, conducted in a similar nationally representative study population, the prevalence of knee OA in the Finnish population aged over 30 years was 5% among men and 7% among women.⁴ This supports the assumption that the amount of missed knee OA cases over follow-up is low. The criteria for hospitalization may also have changed over time. For example, the rate of arthroscopy procedures of osteoarthritic knees has declined. However, this may not have led to many missed cases in our study, as these patients still need specialist consultation in secondary health care, and would therefore mostly be recorded in the register. Furthermore, we cannot rule out that some early knee OA cases were missed by the physicians during the baseline examination. Some of the incident knee OA cases may also have been induced by a traumatic injury during follow-up. Furthermore, the participants’ way of life might have changed during the follow-up and this may have led to alterations in the covariates. The duration of fasting before blood sampling probably varied among the participants. This might have changed the estimates, but the direction of this change is conservative.

In conclusion, our findings do not support the hypothesis that metabolic syndrome or its individual components increase the risk of clinical knee OA. In fact, the number of metabolic syndrome components seemed inversely proportional to this risk. Whether elevated plasma fasting glucose levels predict a reduced risk of knee OA merits testing in further studies.

Footnotes

Author Contributions

All authors made substantial contributions to the conception and designs of the study or analysis and interpretation of the data, to drafting the article or critically revising it for important intellectual content, and all have approved the final version of the submitted manuscript. Each individual named as an author meets the ICMJE Uniform Requirements for Manuscripts Submitted to Biomedical Journals criteria for authorship.

Acknowledgments and Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethical Approval

Ethical approval was not sought for the present study because at the time of the baseline health examination between 1978 and 1980, ethics committees or review boards did not exist in Finland. More detailed information of the field examination phase of the study can be found from the Mini-Finland Health Survey webpages, reference 22. Finnish Institute for Health and Welfare. Mini-Finland Health Survey. Available from: .

Informed Consent

Verbal informed consent was obtained from all subjects before the study.

ORCID iD

Sanna Konstari

References

Loeser

Goldring

Scanzello

Goldring

MB.

Osteoarthritis: a disease of the joint as an organ. Arthritis Rheum. 2012;64(6):1697-707. doi:10.1002/art.34453

Felson

Lawrence

Dieppe

Hirsch

Helmick

Jordan

, et al. Osteoarthritis: new insights. Part 1: the disease and its risk factors. Ann Intern Med. 2000;133(8):635-46.

Heliövaara

Mäkelä

Sievers

Melkas

Aromaa

Knekt

, et al. Musculoskeletal diseases in Finland (in Finnish with English Summary). Helsinki: Social Insurance Institution; 1993. p. AL35.

Kaila-Kangas

Musculoskeletal disorders and diseases in Finland: results of the health 2000 survey. Helsinki: Social Insurance Institution; 2007. p. B25.

Hart

Doyle

Spector

TD.

Incidence and risk factors for radiographic knee osteoarthritis in middle-aged women: the Chingford Study. Arthritis Rheum. 1999;42(1_suppl):17-24. doi:10.1002/1529-0131(199901)42:1<17::AID-ANR2>3.0.CO;2-E

Konstari

Paananen

Heliövaara

Knekt

Marniemi

Impivaara

, et al. Association of 25-hydroxyvitamin D with the incidence of knee and hip osteoarthritis: a 22-year follow-up study. Scand J Rheumatol. 2012;41(2):124-31. doi:10.3109/03009742.2011.617314

Konstari

Kaila-Kangas

Jääskeläinen

Heliövaara

Rissanen

Marniemi

, et al. Serum 25-hydroxyvitamin D and the risk of knee and hip osteoarthritis leading to hospitalization: a cohort study of 5274 Finns. Rheumatology (Oxford). 2014;53(10):1778-82. doi:10.1093/rheumatology/keu178

Felson

Zhang

Hannan

Naimark

Weissman

Aliabadi

, et al. Risk factors for incident radiographic knee osteoarthritis in the elderly. The Framingham study. Arthritis Rheum. 1997;40(4):728-33. doi:10.1002/art.1780400420

Alberti

KGMM

Eckel

Grundy

Zimmet

Cleeman

Donato

, et al. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation. 2009;120(16):1640-5. doi:10.1161/CIRCULATIONAHA.109.192644

10.

Kaur

A comprehensive review on metabolic syndrome. Cardiol Res Pract. 2014;2014:943162. doi:10.1155/2014/943162

11.

Engström

Gerhardsson

Verdier

Rollof

Nilsson

Lohmander

LS.

C-reactive protein, metabolic syndrome and incidence of severe hip and knee osteoarthritis. A population-based cohort study. Osteoarthritis Cartilage. 2009;17(2):168-73. doi:10.1016/j.joca.2008.07.003

12.

Niu

Clancy

Aliabadi

Vasan

Felson

DT.

Metabolic syndrome, its components, and knee osteoarthritis: the Framingham Osteoarthritis Study. Arthritis Rheumatol. 2017;69(6):1194-203. doi:10.1002/art.40087

13.

Shin

Association between metabolic syndrome, radiographic knee osteoarthritis, and intensity of knee pain: results of a national survey. J Clin Endocrinol Metab. 2014;99(9):3177-83. doi:10.1210/jc.2014-1043

14.

Sanchez-Santos

Judge

Gulati

Spector

Hart

Newton

, et al. Association of metabolic syndrome with knee and hand osteoarthritis: a community-based study of women. Semin Arthritis Rheum. 2019;48:791-8. doi:10.1016/j.semarthrit.2018.07.007

15.

Han

Yang

Lee

Park

KK.

Correlation between metabolic syndrome and knee osteoarthritis: data from the Korean National Health and Nutrition Examination Survey (KNHANES). BMC Public Health. 2013;13:603. doi:10.1186/1471-2458-13-603

16.

Hellevik

Johnsen

Langhammer

Baste

Furnes

Storheim

, et al. Metabolic syndrome as a risk factor for total hip or knee replacement due to primary osteoarthritis: a prospective cohort study (the HUNT study and the Norwegian Arthroplasty Register). Clin Epidemiol. 2018;10:83-96. doi:10.2147/CLEP.S145823

17.

McAlindon

Katz

Driban

Price

Eaton

, et al. Systolic and pulse pressure associate with incident knee osteoarthritis: data from the osteoarthritis initiative. Clin Rheumatol. 2017;36(9):2121-28. doi:10.1007/s10067-017-3656-z

18.

Xie

Wei

Zeng

Yang

Wang

, et al. Association between metabolic syndrome and knee osteoarthritis: a cross-sectional study. BMC Musculoskelet Disord. 2017;18(1_suppl):533. doi:10.1186/s12891-017-1890-9

19.

Yoshimura

Muraki

Oka

Tanaka

Kawaguchi

Nakamura

, et al. Accumulation of metabolic risk factors such as overweight, hypertension, dyslipidaemia, and impaired glucose tolerance raises the risk of occurrence and progression of knee osteoarthritis: a 3-year follow-up of the ROAD study. Osteoarthritis Cartilage. 2012;20(11):1217-26. doi:10.1016/j.joca.2012.06.006

20.

Hussain

Wang

Cicuttini

Simpson

Giles

Graves

, et al. Incidence of total knee and hip replacement for osteoarthritis in relation to the metabolic syndrome and its components: a prospective cohort study. Semin Arthritis Rheum. 2014;43(4):429-36. doi:10.1016/j.semarthrit.2013.07.013

21.

Visser

de Mutsert

le Cessie

den Heijer

Rosendaal

Kloppenburg

, et al. The relative contribution of mechanical stress and systemic processes in different types of osteoarthritis: the NEO study. Ann Rheum Dis. 2015;74(10):1842-7. doi:10.1136/annrheumdis-2013-205012

22.

Finnish Institute for Health and Welfare. Mini-Finland Health Survey. Available from: https://thl.fi/en/web/thlfi-en/research-and-expertwork/population-studies/finnish-mobile-clinic/mini-finland-health-survey

23.

Aromaa

Heliövaara

Impivaara

Knekt

Maatela

Aims, methods and study population. Part 1. In: Aromaa

Heliövaara

Impivaara

Knekt

Maatela

, editors. The execution of the Mini-Finland Health Survey (in Finnish with English summary). Helsinki, Finland: National Public Health Institute; 1989. p. ML88.

24.

Sievers

Melkas

Heliövaara

; The Study Group for Musculoskeletal Diseases. Survey methods for musculoskeletal diseases. Part 3. In: Aromaa

Heliövaara

Impivaara

Knekt

Maatela

, editors. The execution of the Mini-Finland Health Survey (in Finnish with English summary). Helsinki, Finland: National Public Health Institute; 1989. p. ML88.

25.

Toivanen

Arokoski

JPA

Manninen

PSH

Heliövaara

Haara

Tyrväinen

, et al. Agreement between clinical and radiological methods of diagnosing knee osteoarthritis. Scand J Rheumatol. 2007;36(1_suppl):58-63. doi:10.1080/03009740600759886

26.

Matthews

Hosker

Rudenski

Naylor

Treacher

Turner

RC.

Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985;28(7):412-9.

27.

Miller

Biller

BMK

Lipman

Bradwin

Rifai

Klibanski

Truncal adiposity, relative growth hormone deficiency, and cardiovascular risk. J Clin Endocrinol Metab. 2005;90(2):768-74. doi:10.1210/jc.2004-0894

28.

Lahti-Koski

Harald

Männistö

Laatikainen

Jousilahti

Fifteen-year changes in body mass index and waist circumference in Finnish adults. Eur J Cardiovasc Prev Rehabil. 2007;14(3):398-404. doi:10.1097/HJR.0b013e32800fef1f

29.

Blagojevic

Jinks

Jeffery

Jordan

KP.

Risk factors for onset of osteoarthritis of the knee in older adults: a systematic review and meta-analysis. Osteoarthritis Cartilage. 2010;18(1_suppl):24-33. doi:10.1016/j.joca.2009.08.010

30.

Toivanen

Heliövaara

Impivaara

Arokoski

JPA

Knekt

Lauren

, et al. Obesity, physically demanding work and traumatic knee injury are major risk factors for knee osteoarthritis—a population-based study with a follow-up of 22 years. Rheumatology (Oxford). 2010;49(2):308-14. doi:10.1093/rheumatology/kep388

31.

Felson

DT.

What is the evidence to support the association between metabolic syndrome and osteoarthritis? A systematic review. Arthritis Care Res (Hoboken). 2019;71(7):875-84. doi:10.1002/acr.23698

32.

Jiang

Tian

Wang

Rong

Bao

Liu

, et al. Body mass index and susceptibility to knee osteoarthritis: a systematic review and meta-analysis. Joint Bone Spine. 2012;79(3):291-7. doi:10.1016/j.jbspin.2011.05.015

33.

Sowers

Karvonen-Gutierrez

CA.

The evolving role of obesity in knee osteoarthritis. Curr Opin Rheumatol. 2010;22(5):533-7. doi:10.1097/BOR.0b013e32833b4682

34.

Abbate

Stevens

Schwartz

Renner

Helmick

Jordan

JM.

Anthropometric measures, body composition, body fat distribution, and knee osteoarthritis in women. Obesity (Silver Spring). 2006;14(7):1274-81. doi:10.1038/oby.2006.145

35.

Davis

Neuhaus

Ettinger

Mueller

WH.

Body fat distribution and osteoarthritis. Am J Epidemiol. 1990;132(4):701-7.

36.

Hochberg

Lethbridge-Cejku

Scott

Reichle

Plato

Tobin

JD.

The association of body weight, body fatness and body fat distribution with osteoarthritis of the knee: data from the Baltimore Longitudinal Study of Aging. J Rheumatol. 1995;22(3):488-93.

37.

Chang

Liao

Meng

Han

Ding

Systemic and local adipose tissue in knee osteoarthritis. Osteoarthritis Cartilage. 2018;26(7):864-71. doi:10.1016/j.joca.2018.03.004

38.

Findlay

DM.

Vascular pathology and osteoarthritis. Rheumatology (Oxford). 2007;46(12):1763-8. doi:10.1093/rheumatology/kem191

39.

Lajeunesse

Massicotte

Pelletier

Martel-Pelletier

Subchondral bone sclerosis in osteoarthritis: not just an innocent bystander. Mod Rheumatol. 2003;13(1_suppl):7-14. doi:10.3109/s101650300001

40.

Yoshimura

Muraki

Oka

Kawaguchi

Nakamura

Akune

Association of knee osteoarthritis with the accumulation of metabolic risk factors such as overweight, hypertension, dyslipidemia, and impaired glucose tolerance in Japanese men and women: the ROAD study. J Rheumatol. 2011;38(5):921-30. doi:10.3899/jrheum.100569

41.

Hart

Doyle

Spector

TD.

Association between metabolic factors and knee osteoarthritis in women: the Chingford Study. J Rheumatol. 1995;22(6):1118-23.

42.

Zhang

Wang

Liu

XG.

Association between hypertension and risk of knee osteoarthritis: a meta-analysis of observational studies. Medicine (Baltimore). 2017;96(32):e7584. doi:10.1097/MD.0000000000007584

43.

Dawson

Fairley

Papandony

Hussain

Cicuttini

Wluka

AE.

Is abnormal glucose tolerance or diabetes a risk factor for knee, hip, or hand osteoarthritis? A systematic review. Semin Arthritis Rheum. 2018;48(2):176-89. doi:10.1016/j.semarthrit.2018.02.008

44.

Veronese

Cooper

Reginster

Hochberg

Branco

Bruyère

, et al. Type 2 diabetes mellitus and osteoarthritis. Semin Arthritis Rheum. 2019;49(1_suppl):9-19. doi:10.1016/j.semarthrit.2019.01.005

45.

Sopasakis

Wickelgren

Sukonina

Brantsing

Svala

Hansson

, et al. Elevated glucose levels preserve glucose uptake, hyaluronan production, and low glutamate release following interleukin-1β stimulation of differentiated chondrocytes. Cartilage. 2019;10(4):491-503. doi:10.1177/1947603518770256

46.

Kong

Wang

Meng

Cao

Shen

Association between smoking and risk of knee osteoarthritis: a systematic review and meta-analysis. Osteoarthritis Cartilage. 2017;25(6):809-16. doi:10.1016/j.joca.2016.12.020

47.

Bener

Yousafzai

Darwish

Al-Hamaq

AOAA

Nasralla

Abdul-Ghani

Obesity index that better predict metabolic syndrome: body mass index, waist circumference, waist hip ratio, or waist height ratio. J Obes. 2013;2013:269038. doi:10.1155/2013/269038

48.

Ketel

IJG

Volman

MNM

Seidell

Stehouwer

CDA

Twisk

Lambalk

. Superiority of skinfold measurements and waist over waist-to-hip ratio for determination of body fat distribution in a population-based cohort of Caucasian Dutch adults. Eur J Endocrinol. 2007;156(6):655-61. doi:10.1530/EJE-06-0730