Associations of dietary patterns with kidney cancer risk, kidney cancer-specific mortality and all-cause mortality among postmenopausal women

Abstract

Background: The empirical dietary index for hyperinsulinemia (EDIH) and empirical dietary inflammatory pattern (EDIP) are novel measures of dietary quality associated with insulin hypersecretion or chronic inflammation, respectively, whereas the Healthy Eating Index (HEI-2015) measures adherence to the Dietary Guidelines for Americans (DGA). We evaluated associations of EDIH, EDIP and HEI-2015 on the risk of both kidney cancer development and mortality.

Methods: We calculated the dietary scores from baseline food frequency questionnaires among 115,830 participants aged 50-79 years in the Women's Health Initiative. Multivariable-adjusted Cox regression was used to estimate hazard ratios (HR) and 95% confidence intervals (95%CI) for kidney cancer risk, kidney cancer-specific mortality and all-cause mortality, per 1-standard deviation increment in dietary pattern scores.

Results: Higher EDIH was associated with greater risk of kidney cancer development [HR, 1.12; 95%CI, (1.01,1.23)], kidney cancer-specific death [1.22(0.99,1.48)], and all-cause mortality, [1.05(1.02,1.08)]. Higher HEI-2015 was associated with lower risk of kidney cancer development, [0.85(0.77, 0.94)], kidney cancer-specific death, [0.84(0.69,1.03)] and all-cause mortality, [0.97(0.95,1.00)]. However, EDIP was not significantly associated with outcomes. Associations did not differ by BMI categories.

Conclusions: Low-insulinemic dietary patterns and higher quality diets, are worthy of testing in dietary pattern intervention trials for kidney cancer prevention and improved survivorship.

Fig. 1. Relative risk estimates for the associations of dietary patterns (per 1 standard deviation increment) and future development of kidney cancer.

a and future kidney cancer-specific death (b). Values presented are hazard ratios (HR) and 95% confidence intervals (95% CI). Dietary score was input as a continuous variable. HRs of age-adjusted models were derived from age-adjusted Cox proportional hazards regression models stratified by age(categorical); HRs of MV-adjusted models were derived from multivariable-adjusted Cox proportional hazards regression models stratified by age at enrollment, race and ethnicity, cardiovascular diseases status, non-steroidal anti-inflammatory drug use, hormone therapy study arm (Not randomized to HRT, E-alone intervention, E-alone control, E + P intervention, E + P control), and further adjusted for the following baseline covariates: total alcohol intake, coffee/tea, physical activity, educational level, pack-years of smoking, family history of cancer, number of hormones used, comorbidity score, baseline lung disease, number of supplements used, baseline hormone therapy ever, and oral contraceptive duration.

Fig. 2. Kaplan–Meier curves of kidney cancer death and all-cause death by binary median cutoffs of baseline multivariable adjusted EDIH, EDIP, and HEI2015 scores.

Log-rank p values were calculated to test differences across median (<=median versus > median). Each dietary score was adjusted for total energy intake, age at enrollment, education, race and ethnicity, non-steroidal anti-inflammatory drug use, hormone therapy study arm (Not randomized to HRT, E-alone intervention, E-alone control, E + P intervention, E + P control), family history of cancer, baseline hormone therapy ever, total alcohol intake, tea/coffee, physical activity, pack-years of smoking, number of hormones, comorbidity score (further included baseline lung disease status and cardiovascular disease status compared with the kidney cancer risk analyses), dietary supplements, oral contraceptive duration.