In this study of older adults, dietary patterns were associated with specific indicators of insulin sensitivity and inflammation. Several previous studies also linked dietary patterns to insulin sensitivity. In a study of adults aged 50-69 years, a ‘prudent’ diet was related to higher insulin sensitivity (Villegas et al., 2004
). Additionally, among women aged 40–60 years, a ‘healthy’ dietary pattern was inversely associated and a ‘Western’ pattern positively associated with insulin resistance (Esmaillzadeh et al., 2007b
). Furthermore, among men aged 40-75 years, Fung et al. (2001)
found an inverse association between a ‘prudent’ pattern and fasting insulin and a positive association between a ‘Western’ pattern and fasting insulin.
Previous research has also linked dietary patterns to markers of systemic inflammation. In a study of women aged 40-60 years, Esmaillzadeh et al. (2007a)
showed an inverse association between a ‘healthy’ dietary pattern and plasma CRP, and a positive association between a ‘western’ pattern and plasma CRP and IL-6. Similarly, in a study of adults aged 45–84 years, Nettleton et al. (2006)
found a positive association between a ‘fats and processed meats’ pattern and CRP and IL-6, an inverse association between a ‘whole grains and fruit’ pattern and CRP and IL-6, and an inverse association between a ‘vegetables and fish’ pattern and IL-6. Furthermore, in a study of women aged 43-69 years, a ‘prudent’ pattern was inversely associated with plasma CRP, while a ‘Western’ pattern was positively related to CRP and IL-6 (Lopez-Garcia et al., 2004
). In a study of men aged 40-75 years, a “Western” pattern was also positively associated with CRP (Fung et al., 2001
). Additionally, in a study of adults aged 50-74 years, a “healthy” dietary pattern was inversely associated with CRP (Nanri et al., 2008
It is difficult to compare results of dietary pattern studies, as derived patterns are unique to each study population. However, dietary patterns associated with insulin resistance and inflammation have consistently included certain food groups. A dietary pattern high in whole grains, vegetables, fruit, poultry, fish and lowfat dairy products, and low in refined grains, red meat, sweetened beverages, added fats, sweets, and high-fat dairy products, has been associated with higher insulin sensitivity. With respect to inflammation, a dietary pattern high in vegetables, fruit, whole grains, fish, poultry and legumes, and low in refined grains, red and processed meat, sweets, sweetened beverages, and fried potatoes, has been linked to lower systemic inflammation. These dietary patterns may contribute to lower metabolic risk because they are high in specific protective nutrients, some perhaps not yet identified, but the current study was not intended to investigate the effects of individual nutrients.
While this study showed significant differences among clusters in IL-6, but not in CRP or TNF-α, all inflammatory markers displayed similar patterns. This would be expected, as inflammation involves a cascade in which tissue injury stimulates cells to produce pro-inflammatory cytokines, which in turn stimulate hepatocytes to produce acute-phase proteins. TNF-α and IL-6 thereby promote increased production of CRP by the liver. One unexpected finding was that the ‘Meat and alcohol’ cluster did not exhibit significantly higher metabolic risk than the ‘Healthy foods’ cluster. Because the ‘Meat and alcohol’ cluster had a substantially smaller sample size than the other clusters, however, these findings may not be highly meaningful.
The mechanisms to explain associations of diet with inflammation and insulin resistance have not been fully elucidated, though several theories have been suggested. Excess body fat has been linked to both insulin resistance and a state of chronic low-grade systemic inflammation, and inflammation may contribute to insulin resistance. Adipose tissue expresses cytokines such as TNF-α and IL-6, which may induce insulin resistance by impairing insulin signaling (Qatanani and Lazar, 2007
). When the current analyses were adjusted for BMI, differences in several indicators of insulin sensitivity among clusters were no longer significant. This could support an intermediate role of excess body fat in a causal pathway between diet and insulin sensitivity. Due to the cross-sectional nature of this study, however, it is not possible to determine if a variable such as BMI is in a causal pathway, or if it is a confounding variable.
This study did not show an interaction between dietary pattern and PPAR-γ
genotype in relation to insulin sensitivity or inflammation. Several studies have associated the common Pro12Ala polymorphism in the PPAR-γ
gene with insulin sensitivity and inflammation, and some have suggested that its effects may depend on the diet (Heikkinen et al., 2009
; Soriguer et al., 2006
). It is possible that the dietary patterns in this study did not differ sufficiently in the main dietary ligands of PPAR-γ, which may include derivatives of monounsaturated and polyunsaturated fatty acids, to show an interaction with PPAR-γ
genotype. In addition, some studies have indicated that effects of the PPAR-γ
Pro12Ala genotype may vary according to BMI, gender, and other genetic polymorphisms, and these potential influences on the interaction between diet and PPAR-γ
genotype were not investigated in this study (Razquin et al., 2009
Strengths of this study include its focus on adults aged 70 and older, a little-studied population, and simultaneous examination of multiple measures of insulin sensitivity and systemic inflammation. In addition, analyses were controlled for numerous potential confounders, and a genetic interaction was considered. A limitation of this study is that the cross-sectional design does not allow inference of a causal relationship between diet and metabolic risk factors. Furthermore, this study population consisted of relatively well-functioning older adults at presumably lower metabolic risk, and it is possible that associations between diet and insulin sensitivity and inflammation would be stronger in a study population of less healthy older adults.
In conclusion, the current and previous studies suggest that a ‘healthy’ dietary pattern, high in whole grains, vegetables, fruit, poultry, and fish, and low in refined grains, red and processed meat, high-fat dairy products, sweets and desserts, and sweetened beverages, is associated with both greater insulin sensitivity and a lower level of systemic inflammation when compared to other dietary patterns. Because indicators of insulin sensitivity and systemic inflammation have been linked to risk of multiple chronic diseases, diets that promote higher insulin sensitivity and lower systemic inflammation should be encouraged in older adults. Dietary interventions to lower metabolic risk in older adults could be targeted to groups according to their current dietary patterns.