Dietary Fat Intake and Radiographic Progression of Knee Osteoarthritis: Data from the Osteoarthritis Initiative

Abstract

Objectives

Few studies have investigated the role of dietary factors on knee osteoarthritis (OA) progression. We examined the prospective association of dietary fat intake with radiographic progression of knee OA.

Methods

In the Osteoarthritis Initiative, 2092 participants with radiographic knee OA and having baseline dietary data were followed at yearly intervals up to 48 months. Dietary intakes of fatty acids were assessed with the Block Brief Food Frequency Questionnaire. To evaluate radiographic progression of knee OA, we used quantitative joint space width (JSW) between the medial femur and tibia of the knee based on fixed-flexion posterior-anterior radiographs. Linear mixed models for repeated measures were used to test the association between dietary fat and JSW loss over time.

Results

We observed significant positive relationships of total fat and saturated fatty acids (SFA) intakes with JSW loss. With increasing quartiles of total fat intake, the JSW decreases over 48 months were 0.26mm, 0.27mm, 0.31mm and 0.35 mm respectively (P trend=0.02). Similar association was observed between SFA intake and JSW loss. In contrast, higher intakes of mono- and poly-unsaturated fatty acids (MUFA, PUFA), and higher ratio of PUFA to SFA were associated with a reduced JSW loss.

Conclusion

High intakes of total fat and SFA may be associated with increased structural knee OA progression, while MUFA and PUFA may reduce radiographic progression. Replication of these novel findings in other prospective studies are needed to confirm if reduction in SFA intake and increase in unsaturated fat intake lead to delayed knee OA progression.

Introduction

Osteoarthritis (OA) is highly prevalent, costly and disabling, affecting approximately 27 million Americans aged 25 years and older.[1] [2] Increasingly, OA is recognized as involving inflammatory pathways even though the degree of inflammation is often modest.[3] In the absence of disease modifying therapy, current treatments can only moderately reduce pain and improve joint function. There is an urgent need for effective, widely available approaches to aid in the management of this common condition. Diet and nutrition play an important role in development and progression of many major chronic diseases, such as cancer, type II diabetes and cardiovascular diseases.[4–6] Dietary factors associated with inflammation, obesity and other metabolic risk factors may also play a role in OA pathogenesis.

A high fat diet has been related to weight changes and subsequent altered joint loading. Increased dietary fat has also been shown to be associated with changes in cartilage in animal models.[7] [8] [9] There is consistent evidence that polyunsaturated fatty acids (PUFA) have anti-inflammatory effects via their role as precursors for a family of compounds known as eicosanoids. Eicosanoids are mediators and regulators of inflammation. [10] Limited evidence from animal studies has linked dietary PUFA to reduced risk of cartilage loss, synovitis and bone marrow lesions.[11] [12] [13, 14] Few human studies have evaluated the role of dietary fat (or types of fatty acids) intake in knee OA progression. We therefore examined the prospective associations between dietary intakes of total fat, saturated fatty acids (SFA), mono-unsaturated (MUFA) and PUFA, and radiographic progression of knee OA using publicly available data from the Osteoarthritis Initiative (OAI).

Methods

Subjects

OAI was launched in 2002 by the National Institute of Health to develop resources for the identification of new biomarkers and treatment targets for knee OA. The OAI began enrolling people aged 45 through 79 years in 2004 and followed them annually for the development or progression of OA. The clinical sites involved were located in Baltimore, MD; Columbus, OH; Pittsburgh, PA; and Pawtucket, RI. OAI enrolled 4,796 subjects with either established symptomatic knee OA or significant risk factors for the development of knee OA and followed them over an 8-year period. The follow-up rate was >90% over the first 48 months. The detailed OAI protocol can be found elsewhere. [15]

For the current study, we included individuals with medial radiographic knee OA in at least one knee based on OAI central X-ray reading at baseline (Kellgren and Lawrence [KL] grade of 2 or 3). We excluded knees with severe radiographic OA defined as the baseline KL of 4 (less likely to progress any further due to the absence of medial joint space) or those with primarily lateral joint space narrowing, and knees in which the difference of rim distance (from tibial plateau to tibial rim closest to femoral condyle) between any follow-up visit and the baseline visit were ≥2mm to minimize possible effects of knee positioning changes on measurement error of joint space width (JSW). We further excluded 74 participants who did not report dietary data, or had > 50 % of incomplete Food Frequency Questionnaire (FFQ) responses, and those with implausible total calories intake (daily calories intake < 500 or > 3500 Kcal). [16, 17] Compared to our included participants, the excluded sample were more likely to be male and less educated, and less likely to be whites. Finally, 2092 participants (2980 knees) with KL grade of 2 or 3 constituted the study sample (Figure 1). Follow-up at 12, 24, 36 and 48 months were included in this analysis. Over the study period, 84% of our sample had one or more follow-up visits and the loss to follow up did not vary by baseline characteristics.

Figure 1.

Osteoarthritis Initiative Participants Included in the Current Study at Baseline

Radiographic progression of OA

A quantitative approach on plain radiographs was used to provide a precise measure of JSW in millimeters between the adjacent bones of the knee. [18, 19] Multiple JSWs were measured at fixed locations along the joint in medial compartment, denoted as JSW(x), at 0.025 intervals for x = 0.15 – 0.30. The reproducibility of this technique and the responsiveness to change have been documented elsewhere,[18] [20] including one study using OAI data which demonstrated a responsiveness that compared favorably to magnetic resonance imaging.[20] We used medial JSW at x=0.25 because it is the location with the best responsiveness of change to quantify the progression of OA. [20] We define the repeated measures of the changes of JSW from baseline to 12, 24, 36 and 48 months as the outcome variable. In the semi-quantitative approach, we defined the radiographic OA progression for a specific knee as at least one full score increase of KL grade characterized by both joint space narrowing and osteophytes from baseline to 48 months. The adjudicated KL grade was done through longitudinal readings of serial knee X-rays for tibiofemoral radiographic OA.

Dietary assessment

Usual dietary intakes of foods and nutrients were assessed at baseline with a Block Brief FFQ including 60 food items.[21] The self-administered brief FFQ was mailed to the participants and reviewed by study nurses for completion. For each food, a commonly used unit or portion size was specified, and participants were asked how often they had consumed the food items on average, during the previous year (coded as: never, a few times per year, once per month, 2–3 times per month, once per week, twice per week, 3–4 times per week, 5–6 times per week, and every day). Daily intakes of total fat, saturated fatty acids (SFA), mono-unsaturated fatty acids (MUFA) and PUFA were calculated by multiplying the frequency of consumption of each food item by its nutrient content and summing the nutrient contributions of all foods on the basis of US Department of Agriculture food composition data through NutritionQuest (www.nutritionquest.com). In this analysis, we grouped men and women into 4 groups using gender-specific quartiles of dietary fat intake. This brief FFQ has been validated against three four-day records in a group of middle-aged women, and against two seven-day records in a group of older men. The absolute value of macronutrients estimated by the Block Brief FFQ was a slightly lower than food-record estimates, but most micronutrients were not underestimated. [21, 22] The total fat intake estimated by the brief FFQ was 11.6% lower than dietary records administered by interview.[21]

Information on covariates

Baseline demographic and socioeconomic factors include age, sex, race/ethnicity, marital status, education level, employment status, annual income and social support. Individuals were classified as African American, white, or other racial/ethnic group based on self report. Education level was categorized as high school or less, college and above college. General clinical parameters include current smoking, depressed mood defined as the CES-D 20 item scale >16 [23], history of traumatic knee injury and knee surgery, baseline JSW, alcohol use, body mass index (BMI), weight changes, physical activity, NSAIDs use, and other nutrients intake (quartiles) (total calories, protein, dietary and supplement calcium). Body weight was measured in the clinic without shoes and in light clothing using a balance beam scale calibrated daily, and height was measured without shoes with a stadiometer. BMI defined as the individual's body mass divided by the square of his or her height (kg/m²) was categorized into <25.0, 25.0–29.9, and ≥30 kg/m² using World Health Organization criterion. Weight changes were measured repeatedly from baseline to each follow up time point. Physical activity was assessed by using the Physical Activity Scale for the Elderly (PASE), an established questionnaire for measuring physical activity in older individuals that has also been validated in younger subjects.[24, 25] Alcohol consumption was assessed at baseline including separate items for beer, wine, and liquor in OAI (none or less than 5 grams /day, 5–10 grams/day, >10 grams/day). We also adjusted for changes of the beam angles and rim distances (from tibial plateau to tibial rim closest to femoral condyle between follow-up visits and baseline), which indicate knee-positioning consistency for x-ray exam.

Statistical analysis

In descriptive analysis, all baseline characteristics of participants were compared among the levels of total dietary fat intake by Analysis of Variance, Chi-square tests or non-parametric tests when applicable. The primary analysis was to assess the influence of total dietary fat intake and types of fatty acids on the decrease in JSW over the study period. The primary outcomes were repeated measures of quantitative JSW loss from baseline to 12, 24, 36 and 48 months respectively. The primary exposures were quartiles of daily intake of total fat, SFA, MUFA, and PUFA. Due to high correlation between SFA and MUFA or PUFA (Pearson correlation coefficients from 0.7 to 0.8), we adjusted total calories intake and included SFA-adjusted MUFA and PUFA using residual methods in the models.[26] Additionally, we calculated the ratio of PUFA to SFA (P:S ratio) and evaluated the association between relative composition of dietary fat and JSW loss. The initial analyses compared mean decreases in JSW among quartiles of energy adjusted dietary fat intakes. Multivariable models for repeated measures were used to adjust for baseline disease severity, BMI, weight changes, total calories intake, other dietary factors and other potential confounding factors described above. The final parsimonious model was developed using a backward selection procedure by eliminating covariates at a significant level of 0.10. Due to the hierarchical structure of the data (three levels: participant- knee - measures over time), we used linear mixed models to account for within subject correlation and the correlation of repeated measures in knee level. To assess the possible differential effect of each exposure across the follow-up time points, we included dietary fat by follow-up time interaction in the model. The final covariance models were evaluated using Akaike's information criterion (AIC) and Bayesian information criterion (BIC). To test for linear trends across quartiles of dietary fat intake, the median value of each fat intake quartile was used as a continuous variable to calculate the p-value for trend. Missing covariate information was minimal. Only < 1% of our final sample had missing BMI and physical activity scale. We replaced missing values using the gender-specific sample median. We considered that being overweight or obese may be both a confounder and an effect-modifier. We included interactions between each dietary fat exposure and BMI categories (<25, 25–30, >30 kg/m²). We also included interaction terms in the models to evaluate whether or not important covariates (sex, age, race, physical activity) modified the association of dietary fat with JSW loss. The significance of interactions was evaluated using likelihood ratio tests.

To test the robustness of our results, we also used the first full grade increase of the KL grade as the endpoint for OA progression. We developed a Cox proportional hazards model to assess the association between each exposure and the time to KL grade increase after controlling for other covariates. For each participant, the time of follow-up was calculated from the baseline date to the date of the first increase of KL grade, death, or end of the study, whichever came first. The discrete likelihood method was used to handle ties of the failure times in the models. We used a robust sandwich covariance estimate to account for the intra-class dependence between two knees within individual patients. [27] Adjusted hazard ratios (HR) with 95% confidence intervals (95% CI) were used to evaluate the strength of the associations. The proportional hazard assumption was tested based on the smoothed plots of the scaled Schoenfeld residuals.[28] The statistical significance was determined by two-sided α level of 0.05. Data analyses were performed using SAS 9.4 (SAS Institute, Cary, NC).

Results

The baseline characteristics of participants are shown in table 1 according to quartiles of total fat intake. Compared to the participants in the bottom quartile of total fat intake, those in the highest quartile of dietary fat intake were more likely to be younger, non-Hispanic black, less educated, depressed, and smokers, and have higher BMI, higher intakes of Calcium, protein, and total calories intake at baseline.

Table 1.

Baseline Characteristics of Participants With Osteoarthritis According to Total Dietary Fat Intake

		Quartiles of total fat intake (median, grams/day)
Variables	Total N=2092	Q1 (26.9)	Q2 (42.0)	Q3 (56.9)	Q4 (84.4)	P value
Age in years, mean (SD)	62.4(9.0)	64.2(8.7)	62.8(9.0)	62.3(9.1)	60.8(8.8)	<0.01
Men, %	41.2	40.0	43.1	41.0	40.7	0.98
Race, %
Non-hisp White	76.8	73.3	78.4	81.8	73.1	0.02
Non-hisp Black	20.0	21.1	18.6	16.4	24.2
Others	3.2	5.6	3.0	1.8	2.7
Education, %
≤high school	18.2	15.9	14.9	18.2	23.1	<0.01
College	45.6	44.5	47.4	46.2	44.3
Above college	36.2	39.6	37.7	35.6	32.6
Family income, %
<25k	15.1	14.7	12.2	14.8	18.2	0.25
25k-49k	27.7	30.5	26.1	27.0	27.5
50k-99k	36.2	35.5	37.1	37.9	34.4
100k+	21.0	19.3	24.6	20.3	19.9
Depressed, %	8.7	6.7	7.9	7.7	12.0	<0.01
Smoke, %
Never	54.1	58.7	53.6	53.4	51.3	<0.01
Current	6.2	2.8	5.5	6.6	9.1
Past	39.8	38.5	40.9	40.0	39.6
Alcohol, g/d
0-<5	65.7	69.0	64.9	64.2	65.1	0.19
5-<10	11.0	10.3	11.9	10.1	11.6
10+	23.3	20.7	23.2	25.7	23.3
PASE a, mean (SD)	157.5(82.0)	151.3(82.7)	159.6(81.4)	155.9(80.4)	162.6(83.6)	0.07
BMI b (kg/m2), %
<25	16.0	22.4	15.7	16.1	10.7	<0.01
25–29	38.8	41.1	41.2	37.7	35.9
30+	45.2	36.5	43.1	46.2	53.4
K-L grade c (index knee), %
2	63.7	63.4	62.9	65.3	62.9	0.94
3	36.3	36.6	37.1	34.7	37.1
NSAIDsd use, %	21.9	21.1	20.4	20.6	25.1	0.12
Dietary Calcium, mg/d, mean (SD)	676.5(343.3)	504.3(279.1)	587.8(286.3)	695.6(308.4)	883.6(365.1)	<0.01
Supplement Calcium, mg/d, mean (SD)	469.3(473.1)	493.6(482.6)	487.1(483.0)	466.5(472.1)	435.2(455.6)	0.04
Protein (g/d), mean (SD)	60.8(25.3)	38.7(13.0)	50.9(14.3)	63.1(18.1)	86.3(24.8)	<0.01
Total calories (Kcal/d), mean (SD)	1425(553)	888.9(247.9)	1188.2(270.0)	1462(321.3)	2059.6(489.6)	<0.01

^a. Physical Activity Scale for the Elderly (PASE) score.

^b. Body mass index.

^c. Kellgren-Lawrence Scale.

^dNon-steroidal anti-inflammatory drugs (including Aspirin, Ibuprofen, etc) use for joint pain or arthritis in past 30 days.

Results of multivariable analyses are shown in table 2. We observed a significant dose-response relationship between total fat and SFA intakes and JSW loss. With increasing levels of total fat intake, the JSW decreases over 48 months were 0.26mm, 0.27mm, 0.31mm and 0.35 mm respectively (P trend 0.02). Similarly, the JSW decreases for quartiles of dietary SFA intake were 0.25mm, 0.26mm, 0.33mm and 0.37mm (P trend <0.01). In contrast, we found significant inverse associations of JSW loss with PUFA intake (p trend 0.02) and P:S ratio (P trend <0.01). Although, participants with higher MUFA intake tended to have less JSW loss than those with lower MUFA intake, no significant linear trend was observed (P trend 0.19). No significant interactions were found between follow-up time and kinds of dietary fat intake (P=0.73 for SFA, P=0.20 for PUFA, P=0.55 for MUFA). We also did not observe the significant interactions between kinds of dietary fats and age, sex, BMI and smoking status.

Table 2.

Joint Space Width Loss (ΔJSW, mm) (SE) During Follow-up by Dietary Fat Intake

	Quartiles of dietary fat intake (median)				P for trend
	Q 1	Q 2	Q 3	Q 4
Total Fat, g/d	(26.9)	(42.0)	(56.9)	(84.4)
Energy-adjusted	0.30(0.03)	0.31(0.02)	0.32(0.02)	0.34(0.03)	0.30
P value	Referent	0.80	0.48	0.31
Fully-Adjusted ┼	0.26(0.03)	0.27(0.02)	0.31(0.02)	0.35(0.03)
P value	Referent	0.78	0.12	0.05	0.02
SFA, g/d	(9.0)	(14.2)	(19.8)	(29.4)
Energy-adjusted	0.28(0.03)	0.29(0.02)	0.34(0.02)	0.36(0.03)	0.03
P value	Referent	0.83	0.07	0.07
Fully-Adjusted ┼	0.25(0.03)	0.26(0.02)	0.33(0.02)	0.37(0.03)
P value	Referent	0.76	0.02	0.02	<0.01
MUFA, g/d	(9.7)	(15.3)	(21.1)	(31.9)
Energy-adjusted	0.37(0.02)	0.29(0.02)	0.32(0.02)	0.29(0.02)
P value	Referent	<0.01	0.09	0.01	0.03
Fully-Adjusted ┼‡	0.36(0.02)	0.29(0.02)	0.32(0.02)	0.32(0.02)
P value	Referent	0.01	0.13	0.10	0.19
PUFA, g/d	(5.2)	(8.3)	(11.7)	(17.1)
Energy-adjusted	0.37(0.02)	0.33(0.02)	0.28(0.02)	0.30(0.02)
P value	Referent	0.24	<0.01	0.02	<0.01
Fully-Adjusted ┼‡	0.34(0.02)	0.31(0.02)	0.26(0.02)	0.28(0.02)
P value	Referent	0.34	0<0.01	0.06	0.02
P:S ratio	(0.41)	(0.53)	(0.64)	(0.83)
Energy-adjusted	0.36(0.02)	0.34(0.02)	0.27(0.02)	0.29(0.02)
P value	Referent	0.54	<0.01	0.02	<0.01
Fully-Adjusted ┼	0.34(0.02)	0.33(0.02)	0.25(0.02)	0.28(0.02)
P value	Referent	0.67	<0.01	0.05	<0.01

^┼Adjusted for age, sex, race, follow-up time, physical activity, body mass index, weight change, NSAIDs use, baseline JSW, the changes of rim distance and beam angle, protein, and total calories intake. SFA: Saturated fatty acids, MUFA: monounsaturated fatty acids, PUFA: polyunsaturated fatty acids, P:S ratio: the ratio of PUFA to SFA.

^‡Adjusted for dietary SFA using residual method.

Table 3 shows the multivariable adjusted HR of OA progression evaluated by time to the first increase of KL grade. Consistent with JSW analysis, after adjustment for covariates, we found a significant positive association between SFA intake and risk of OA progression. With increasing quartiles of SFA intake, the HRs (95% CI) were 1.32 (0.95,1.82), 1.59 (1.11,2.27) and 1.60 (1.02,2.51) compared to the bottom quartile (P trend 0.03). Total fat intake tended to be positively related to OA progression, although the relationship was not statistically significant (P trend 0.29). Participants in the top quartile of MUFA intake had 25% reduced risk of OA progression compared to those in the bottom quartile (P trend 0.05). There was a significant association between higher PUFA intake and reduced risk of OA progression. With increasing quartiles of PUFA intake, the HRs (95% CI) were 1.01 (0.79,1.30), 0.67 (0.51,0.89) and 0.70 (0.53,0.93) compared to the bottom quartile (P trend <0.01). A consistent inverse relationship was also found between the P:S ratio and risk of knee OA progression (P trend 0.01).

Table 3.

Association of dietary fat intakes with rate of OA progression measured by the increase of Kellgren-Lawrence (K-L) grade (Hazard ratio and 95% confident interval)^*

Dietary fat	Quartiles of dietary fat intake (median)				P for trend
	Q1	Q2	Q3	Q4
Total Fat	(26.9)	(42.0)	(56.9)	(84.4)
Energy-adjusted	Referent	1.03(0.77,1.38)	1.11(0.81,1.51)	1.27(0.84,1.91)	0.27
Fully-Adjusted	Referent	1.12(0.81,1.51)	1.24(0.86,1.78)	1.25(0.78,2.01)	0.29
SFA	(9.0)	(14.2)	(19.8)	(29.4)
Energy-adjusted	Referent	1.19(0.89,1.60)	1.41(1.04,1.92)	1.60(1.08,2.36)	0.01
Fully-Adjusted	Referent	1.32(0.95,1.82)	1.59(1.11,2.27)	1.60(1.02,2.51)	0.03
MUFA┼	(9.7)	(15.3)	(21.1)	(31.9)
Energy-adjusted	Referent	0.79(0.61,1.02)	0.81(0.63,1.04)	0.64(0.50,0.84)	<0.01
Fully-Adjusted	Referent	0.84(0.64,1.10)	0.89(0.69,1.16)	0.75(0.57,0.98)	0.05
PUFA┼	(5.2)	(8.3)	(11.7)	(17.1)
Energy-adjusted	Referent	1.03(0.81,1.31)	0.64(0.49,0.84)	0.66(0.50,0.86)	<0.01
Fully-Adjusted	Referent	1.01(0.79,1.30)	0.67(0.51,0.89)	0.70(0.53,0.93)	<0.01
P:S ratio	(0.41)	(0.53)	(0.64)	(0.83)
Energy-adjusted	Referent	1.15(0.89,1.49)	0.57(0.42,0.76)	0.75(0.56,1.00)	<0.01
Fully-Adjusted	Referent	1.15(0.88,1.49)	0.60(0.44,0.82)	0.82(0.61,1.12)	0.01

^*Hazard ratios and 95% confident intervals were calculated using Cox proportional hazards model with the discrete likelihood method handling ties in failure times. The fully-adjusted models adjusted for age, sex, race, body mass index, NSAIDs use, baseline K-L grade, dietary protein, and total calories intake. SFA: Saturated fatty acids, MUFA: monounsaturated fatty acids, PUFA: polyunsaturated fatty acids, P:S ratio: the ratio of PUFA to SFA.

^┼Adjusted for dietary SFA intake using residual method.

Discussion

In this 48-month follow-up study of people with radiographic knee OA, we observed significant associations of dietary fat with structural progression of knee OA. Higher total dietary fat or SFA intake was associated with increased radiographic progression of knee OA, and higher PUFA and MUFA intakes appeared to be associated with reduced progression.

The association between a high fat diet and early-onset OA in a mouse model has been known since 1950.[8] The effects of dietary fats (especially SFA) may be related to weight gain and subsequent altered joint loading. Increased dietary fat has been associated with changes in rabbit cartilage in vivo.[7] Among mice, a very high fat diet increased levels of serum leptin, adiponectin, IL-8, and IL-1α, and also induced symptomatic characteristics of OA including hyperalgesia and anxiety-like behaviors.[29, 30] However, very few human studies have evaluated the role of high fat diet in knee OA progression. A cohort study with 251 subjects found that increased consumption of SFA was associated with an increased incidence of bone marrow lesions, which may predict knee OA progression.[31]

Although the potential mechanisms linking dietary PUFA and OA are unknown, there is consistent evidence that PUFAs are directly linked to inflammation via their role as precursors for a family of compounds known as eicosanoids. In multiple trials treatment with n-3 PUFA, such as eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) resulted in lower levels of proinflammatory markers and higher levels of anti-inflammatory markers [32, 33] and better outcomes in numerous diseases including cardiovascular diseases.[34, 35] The pathophysiology of OA is now recognized to involve much more than simple mechanical “wear and tear” of articular cartilage. It involves a complex interplay between articular pro- versus anti-inflammatory mediators as well as anabolic versus catabolic signaling within cartilaginous matrix, chondrocytes, synovium, bone, and synovial fluid.[36, 37] Results from in vitro and animal investigations of OA confirmed that cytokines, in addition to local and systemic factors, such as oxidative stress due to decreased articular antioxidant capacity, play important roles in OA pathobiology and cartilage metabolism.[38–40] Consistent with our study, an inverse relation between total n-3 PUFAs with patellofemoral cartilage loss was reported in a cohort study with 472 subjects.[11] A supplement rich in fish oil was shown to improve function and pain in OA patients.[41] Also in cartilage cell cultures n-3 PUFAs have been shown to cause a reduction in the mRNA levels for major enzymes and cytokines tied to matrix degradation. [14] Regarding MUFA, a recent animal study reported a beneficial effect of an extra-virgin olive oil diet on the articular cartilage. The effects of anterior cruciate ligament transection decrease drastically the expression of lubricin and increase the expression of IL-1 in rats, while after extra-virgin olive oil supplemented diet and physical activity, the values returned to a normal level compared to the control group.[42] No previous human study indicated a possible benefit effect of higher MUFA intake on knee OA progression.

Our findings add to the literature, showing a positive association of dietary saturated fat with knee OA progression, and potential protective effects of dietary PUFA and MUFA against knee OA progression. Recently, the Dietary Guidelines for Americans (2015) encourages the low consumption of SFA (< 10% total calories per day). Sources of SFA should be replaced with unsaturated fat, particularly PUFA, and solid animal fats should be replaced with non-tropical vegetable oils and nuts.[43] In the absence of disease modifying therapy, following a healthy diet may be an effective strategy for knee OA management, and clearly more attractive than medications in terms of risk/benefit and more likely to be implementable.

The strengths of this study include the prospective design, the large number of participants with knee OA, and the state-of-the-art quantitative measures of structural change from sophisticated image processing technology. The quantitative software–based assessment provided a more precise measure of JSW in millimeters and permitted the assessor to document appreciable change in JSW in the tibiofemoral compartment.[18] To confirm our findings, we also used the increases of semiquantitative KL grade as the endpoint to represent the disease progressions in both joint space narrowing and osteophytes. To minimize the possible measurement error of radiographic data, we excluded knees in which the difference of rim distance between follow-up and baseline visits was ≥2 mm and adjusted for changes of rim distance and beam angle in the multivariate models. Additionally, the analysis of P:S ratio incorporating both MUFA and SFA further eliminated the possible collinearity between them and confirmed our findings. Because of the observational nature of the study, patients were not randomly assigned to each dietary exposure groups. The excluded 74 participants who did not have reliable dietary data were more likely to be male and less educated, and less likely to be white. We cannot prove that the observed associations are causal because residual confounding and possible selection bias could theoretically affect the observed associations. However, we controlled for potential confounding by most known risk factors that are plausibly associated with diet and knee OA progression. Obesity and weight change may be intermediate factors linking fat intake and OA outcomes. However, the association remains after controlling for weight changes and BMI. We did not control for treatments except baseline NSAIDs use,[44] but no other treatments have been proven to reduce radiographic OA progression, and related to dietary fat intake. Misclassification of exposures may result from the self-reported Block brief FFQ at only baseline. It is also possible that dietary fat intake is associated with both knee OA development and progression, which may result in the index event bias (or collider stratification bias) in case-only studies.[45] However, index event bias may bias the effect towards the null. Our significant findings in associations of dietary fats with knee OA progression persisted after controlling for major established risk factors of incident OA (e.g. sex, BMI, knee injury). In addition, detailed information for the consumption of n-3 and n-6 PUFA was not available in OAI. We cannot separate the potential contrary associations of these two fatty acids, and therefore the preferable association of n-3 PUFA on knee OA progression may be stronger than our current findings of total PUFA.

In conclusion, our study suggested that high intake of total fat and saturated fat may be associated with increased structural progression of knee OA, while high intake of mono- and poly-unsaturated fats may be associated with a reduced knee OA progression. Our study indicated a healthy diet may be beneficial to knee OA. Replication of these novel findings in other prospective studies is warranted.

Significance and Innovations.

• Few studies have examined the possible role of diet on OA progression. This large cohort study investigated the prospective association of dietary fat intake with radiographic knee OA progression.

• High intakes of total fat and saturated fatty acids were associated with increased structural knee OA progression, and high intakes of unsaturated fatty acids reduced radiographic progression.

• Following a healthy diet may be important in the management of knee OA.