There is little prospective evidence exists about whether adherence to a diabetes risk reduction diet (DRRD) is related to a significant reduction in renal cancer risk. We sought to clarify whether adherence to DRRD was associated with a reduced risk of renal cancer in a US population.
Methods
A population-based cohort of 101,755 American adults was identified from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. A DRRD score was calculated to assess adherence to this dietary pattern, where increased scores indicated greater adherence. The relationship between DRRD score and risk of renal cancer was assessed based on the hazard ratios (HRs) and 95% confidence intervals (CIs), which were both calculated using Cox regression. Non-linear association was determined through restricted cubic spline regression. Potential effect modifiers were identified through subgroup analyses.
Results
Over a mean follow-up of 8.8 years, 446 renal cancers were detected. In this analysis, the fully adjusted model depicted a notable 29% reduction in the risk of renal cancer among individuals in the highest quartile of DRRD score in comparison with the lowest quartile individuals (HRQ4 vs. Q1: 0.71; 95% CI = 0.54, 0.94; Ptrend = 0.008). This association remained consistent across a series of sensitivity analyses. A non-linear inverse dose–response association between renal cancer risk with DRRD score was observed (Pnonlinearity = 0.026). Subgroup analyses showed that this favorable link was more prominent in participants with low Healthy Eating Index-2015 (Pinteraction = 0.015). Regarding the individual components of DRRD, a decrease in the risk of renal cancer was linked to increased intake of cereal fiber and whole fruit, and lower sugar-sweetened beverage consumption (all Ptrend < 0.05).
Conclusions
Our findings indicate that individuals adhering to DRRD are associated with a reduction in the risk of renal cancer.
Ling Xiang and Yi Xiao are contributed equally to this work.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Abkürzungen
BMI
Body mass index
BQ
Baseline questionnaire
CI
Confidence interval
DHQ
Dietary history questionnaire
HR
Hazard ratio
NCI
National cancer institute
DRRD
Diabetes risk reduction diet
PLCO
Prostate lung colorectal and ovarian
Introduction
Renal cancer, with an annual incidence rate of over 330,000 cases, is regarded as the 13th most prevalent cancer globally [1]. There is significant geographic variation in the incidence of renal cancer. Europe and North America are the regions with the highest burden of renal cancer, and the low-risk countries are mainly located in Asia and Africa with an incidence of less than 2/100,000 [2]. This regional difference may be attributed to the increased prevalence of diabetes and obesity in western countries, in which western dietary patterns may play an important role [3, 4]. Several studies have linked diabetes to the incidence of renal cancer and have identified it as an independent risk factor [5]. The underlying mechanisms primarily involve insulin resistance, pro-inflammatory effect, and compensatory excess insulin production, which exhibit overlapping mechanisms with cancer [6‐8]. Recently, a specific dietary pattern was developed to prevent diabetes, namely a diabetes risk reduction diet (DRRD). This dietary pattern emphasizes the higher intakes of grain fiber, nuts, coffee, polyunsaturated fatty acids, and whole fruit, and a lesser intake of saturated and trans fatty acids, red and processed meats, sugar-sweetened beverages, and lower values of glycemic index [9]. Along with being linked to a decreased risk of developing diabetes, adherence to DRRD has been linked to a lower risk of pancreatic cancer [10], breast cancer [11], endometrial cancer [12], and lung cancer [13]. However, epidemiologic evidence regarding the association between DRRD and the risk of renal cancer is currently lacking in literature. Therefore, a large-scale prospective study was performed to investigate the impact of adherence to the DRRD on the mitigation of renal cancer risk.
Methods
Study design
The population under study was retrieved from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. Funded and designed by the United States National Cancer Institute (NCI), the PLCO is a randomized large-scale clinical trial that explores the effectiveness of screening methods in reducing fatality from various cancers in both men and women, such as prostate, lung, colorectal, and ovarian cancers [14]. The PLCO trial spanned from 1993 to 2001 across ten medical centers in the United States involving a total of 154,887 individuals (aged 55 to 74 years) being included in the trial. Following the provision of informed consent, the participants, per the PLCO trial design, were assigned randomly to equal proportions of control or intervention groups. The control group was provided the usual care, while the intervention group received screening tests. All the participating individuals were instructed to complete a self-reported questionnaire on lifestyle and recorded cancer incidence up until 2009. Specific questionnaire information included the Baseline Questionnaire (BQ) and the Dietary History Questionnaire (DHQ) [14]. The BQ was primarily employed to retrieve the baseline risk factors of participants at enrollment and the diagnosis information of cancers. The DHQ collected dietary information from participants using a 124-item Food Frequency Questionnaire (FFQ) to examine foods or nutrients intake over the past year. Previous studies have indicated the effectiveness of the DHQ in assessing diet and nutrient intake [15, 16]. Further comprehensive data about the PLCO trial can be found in the literature [14, 17].
Anzeige
In this experiment, participants meeting the following criteria were excluded: (1) failing to return BQ (n = 4918); (2) failing to complete a DHQ (n = 33,241); (3) having an invalid DHQ (the DHQ had to meet certain requirements, including having a specific completion date, having a death date that was not prior to the completion date, having fewer than 8 missing frequency responses, and having an energy intake without extremes (i.e., not in the top 1% or bottom 1% of intake) (n = 5221); (4) being diagnosed with cancer prior to DHQ entry (n = 9705); and (5) developing outcome events such as renal cancer, died, or were lost to follow-up between randomization and completion of the DHQ were excluded (n = 63). Ultimately, 101,755 participants in total met the eligibility criteria (Fig. 1). Approval for this research was granted by the NCI (Project ID: PLCO-1063).
Fig. 1
The flow chart of identifying eligible subjects. PLCO, Prostate, Lung, Colorectal, and Ovarian; BQ, baseline questionnaire; DHQ, diet history questionnaire
×
DRRD score calculation
Based on the latest published research [18, 19], the DRRD score was quantified to assess the adherence of participants to a type 2 diabetes prevention diet. The individuals were classified into five strata per the quintile of their dietary intakes for each of the nine DRRD components and given points based on their strata (Additional file 1: Table S1). Participants with the highest intake of favorable components (highest stratum), such as coffee, cereal fiber, whole fruits, and polyunsaturated to saturated fatty acids ratio, and nuts, receive 5 points, whereas those with the lowest intake (lowest stratum) receive 1 point. In addition, the trend was the opposite for the “unfavorable” DRRD components, including glycemic index, trans fatty acids, sugar-sweetened beverages, and red and processed meats. The scores for the nine components were then summed, resulting in a total DRRD score ranging from 9 to 45 for each individual. A higher score indicates greater adherence to the DRRD.
This research utilized the aforementioned DHQ to extract the nutrient variables used for the purpose of calculating the DRRD score. The cereal fiber refers to insoluble fiber collected in DHQ, and sugar-sweetened beverages are the sum of fruit drinks and soft drinks assessed by DHQ. The glycemic index was derived using the DHQ data according to the method described in previous literature [20]. It is reliable and reproducible to assess nutrition-related indicators via the DHQ [21].
Covariates data collection
The personal baseline information of participants was available in the completed self-administered BQ. In this study, the following factors: level of education, race/ethnicity, age, marital status, sex, body mass index (BMI), weight change, arm (intervention or control), pack-years of smoking, smoking status, ibuprofen use, family history of renal cancer, history of diabetes and hypertension were included. BMI was derived as weight (kg) divided by height squared (m2) at baseline. Weight change was termed as the baseline weight of the participant minus weight at age 20 (pounds). DHQ was utilized to retrieve dietary data, such as alcohol consumption, total energy intake from diet, Healthy Eating Index (HEI)-2015 score, and individual dietary components of DRRD. It is worth noting that HEI-2015 was utilized to assess personal diet quality, and the specific calculation method can be checked in prior research [22].
Anzeige
Renal cancer ascertainment
The PLCO trial used a method of identifying cases of renal cancer based on reports extracted from the annual study update form, which included self-reports, reports from family members, and death certificates, among other sources. After the identification of potential cases, the medical records were reviewed to confirm the diagnoses using ICD-O-2 codes, and data were extracted using standardized tables. The endpoint of this study was defined as malignant neoplasm of renal parenchyma and renal pelvis (C649 and C659).
Statistical analysis
In this study, all missing data were less than 5%. Hence, the missing data of categorical covariates, which included educational degree, marital status, family history of renal cancer, ibuprofen use, and smoking status as well as a history of hypertension, and diabetes were imputed using the modal value. The missing data of continuous covariates, including those such as pack-years of smoking, BMI, and weight change, were imputed with median value. The detailed imputation information was depicted in tabular form (Additional file 1: Table S2).
A Cox proportional hazards regression model was employed to determine the 95% confidence intervals (CIs) and hazard ratios (HRs) for assessing the correlation between DRRD score and renal cancer incidence, with the follow-up period as the time metric. In particular, this research defined the follow-up period as the time from the completion of DHQ to the incidence of renal cancer, fatality, the loss of follow-up, or the end of follow-up (i.e., December 31, 2009), whichever was the first to occur (Fig. 2). In the Cox regression model, the DRRD score was classified into quartiles, with the reference group defined as the lowest quartile. Based on the follow-up period, the person-years of each quartile were quantified. Schoenfeld residuals approach was used to determine whether the DRRD score is a time-varying variable. The Cox regression model was utilized to conduct a trend test across the quartiles of DRRD scores for the risk assessment of renal cancer risk. This analysis involved assigning the median value of each quartile to all individuals within that quartile and treating it as a continuous variable. Afterward, covariates were screened and adjustments were made for confounders in multivariate regression models as per the review of the literature [23, 24] and clinical judgment. Adjustment of model 1 with race, sex, marital status, age, and education levels was done, and model 2 was further adjusted with smoking status, intake of alcohol, pack-years of smoking, BMI, trail arm, ibuprofen usage, family history of renal cancer, history of hypertension and diabetes, and energy intake from the diet. The study applied a restricted cubic spline model with three knots at the 10th, 50th, and 90th to evaluate the risk of renal cancer across the full spectrum of the DRRD score [25].
Fig. 2
The timeline and follow-up scheme of our study
×
The study conducted several pre-selected subgroup analyses to determine whether the relationship between DRRD score and renal cancer incidence was influenced by certain factors. These included sex (male vs. female), age (≤ 65 vs. > 65 years old), BMI (≤ 30 vs. > 30 kg/m2), smoking status (non-smokers vs. current/former smoker), pack-years of smoking (≤ medium vs. > medium), family history of renal cancer (no vs. yes/possible), history of hypertension (no vs. yes), history of diabetes (no vs. yes) and HEI-2015 (≤ medium vs. > medium). The P value for interaction was calculated to indicate the intrinsic statistical interaction in these subgroup analyses.
To ensure the reliability of the obtained data, multiple sensitivity analyses were conducted. These measures included (1) exclusion of individuals with a family history of renal cancer due to their higher predisposition to develop renal malignancy; (2) exclusion of individuals with a diabetic history as they may have a greater tendency to adhere to a diabetes risk reduction diet; (3) exclusion of 32 cases with renal pelvis cancer, to clarify the association of DRRD score with the renal parenchyma cancer risk; (4) exclusion of observed cases within the initial years of follow-up (first two and three years) to eliminate the issue of reverse causality; (5) additional adjustment in model 2 for HEI-2015 to verify whether the determined correlation was influenced by the quality of the diet; and (6) adjustment for weight change in model 2 rather than BMI to examine the impact of body weight on the correlation.
The association of each dietary component of DRRD with renal cancer risk was assessed. Individual components of DRRD were categorized into quartiles, with the lowest quartile as the reference group. Subsequent analyses were similar to the above-mentioned methods for assessing the link of DRRD score with renal cancer risk. The descriptive statistics are expressed as mean ± standard deviation and number (percentage) for continuous and categorical variables. The statistical analyses were conducted utilizing the R software (version 4.0.5). A two-tailed p-value less than 0.05 was considered significant.
Results
Participant baseline features
In this research, the number of participants reached 101,755 as per the above-mentioned exclusion criteria (Fig. 1). The mean (standard deviation) for DRRD score, age, and follow-up time of participants were 26.8 (5.3) points, 65.5 (5.7) years, and 8.8 (1.9) years, respectively. The individuals were classified into quartiles by DRRD score [Quartile 1 (DRRD score, 9–23), n = 27,890; Quartile 2 (DRRD score, 24–27), n = 28,970; Quartile 3 (DRRD score, 28–30), n = 19,784; Quartile 4 (DRRD score, 31–45), n = 25,111]. Participants in higher quartiles indicated better adherence to a diabetes risk-reduction diet. Compared to the individuals in the lowest quartile group, those in the highest quartile were observed to have certain characteristics, such as were being older, female, non-smokers, and drinkers, as well as having higher education levels, alcohol consumption, and HEI-2015 score. Conversely, the likelihood of higher BMI, a history of diabetes or hypertension, and higher energy was low. More detailed information was also examined (Table 1).
Table 1
Baseline characteristics of study population according to overall diabetes risk reduction diet score
Characteristics
Overall
Quartiles of overall Diabetes Risk Reduction Diet score
Quartile 1 (9–23)
Quartile 2 (24–27)
Quartile 3 (28–30)
Quartile 4 (31–45)
Number of participants
101,755
27,890
28,970
19,784
25,111
Diabetes risk reduction diet score
26.8 ± 5.3
20.4 ± 2.4
25.5 ± 1.1
28.9 ± 0.8
33.8 ± 2.6
Age
65.5 ± 5.7
64.7 ± 5.6
65.5 ± 5.7
65.9 ± 5.8
66.2 ± 5.7
Sex
Male
49,496 (48.6%)
16,282 (58.4%)
14,856 (51.3%)
8839 (44.7%)
9519 (37.9%)
Female
52,259 (51.4%)
11,608 (41.6%)
14,114 (48.7%)
10,945 (55.3%)
15,592 (62.1%)
Race
White
94,066 (92.4%)
26,077 (93.5%)
26,890 (92.8%)
18,295 (92.5%)
22,804 (90.8%)
Non-white
7689 (7.6%)
1813 (6.5%)
2080 (7.2%)
1489 (7.5%)
2307 (9.2%)
Marital status
Married or living as married
79,826 (78.4%)
22,143 (79.4%)
23,066 (79.6%)
15,509 (78.4%)
19,108 (76.1%)
No
21,929 (21.6%)
5747 (20.6%)
5904 (20.4%)
4275 (21.6%)
6003 (23.9%)
Education level
College below
64,953 (63.8%)
19,955 (71.5%)
19,034 (65.7%)
12,053 (60.9%)
13,911 (55.4%)
College graduate
17,848 (17.5%)
4210 (15.1%)
4973 (17.2%)
3687 (18.6%)
4978 (19.8%)
Postgraduate
18,954 (18.6%)
3725 (13.4%)
4963 (17.1%)
4044 (20.4%)
6222 (24.8%)
Body mass index (kg/m2)
27.2 ± 4.8
28.2 ± 5.0
27.5 ± 4.7
26.9 ± 4.6
26.0 ± 4.4
Weight changea (pounds)
33.0 ± 27.2
38.5 ± 28.8
34.6 ± 26.9
31.5 ± 26.4
26.4 ± 24.8
Arm
Intervention
51,817 (50.9%)
14,077 (50.5%)
14,663 (50.6%)
10,063 (50.9%)
13,014 (51.8%)
Control
49,938 (49.1%)
13,813 (49.5%)
14,307 (49.4%)
9721 (49.1%)
12,097 (48.2%)
Smoking status
Never
48,580 (47.7%)
12,409 (44.5%)
13,572 (46.8%)
9700 (49.0%)
12,899 (51.4%)
Current
9401 (9.2%)
3772 (13.5%)
2841 (9.8%)
1488 (7.5%)
1300 (5.2%)
Former
43,774 (43.0%)
11,709 (42.0%)
12,557 (43.3%)
8596 (43.4%)
10,912 (43.5%)
Smoking pack-years
17.7 ± 26.6
21.7 ± 30.0
18.4 ± 27.0
16.1 ± 25.0
13.5 ± 22.2
Drinking status
No
27,757 (27.3%)
8654 (31.0%)
7780 (26.9%)
5006 (25.3%)
6317 (25.2%)
Yes
73,998 (72.7%)
19,236 (69.0%)
21,190 (73.1%)
14,778 (74.7%)
18,794 (74.8%)
Alcohol consumption (g/day)
9.5 ± 25.3
8.4 ± 23.5
9.7 ± 24.4
10.7 ± 28.1
9.7 ± 25.7
Ibuprofen use
No
73,349 (72.1%)
19,784 (70.9%)
20,817 (71.9%)
14,243 (72.0%)
18,505 (73.7%)
Yes
28,406 (27.9%)
8106 (29.1%)
8153 (28.1%)
5541 (28.0%)
6606 (26.3%)
Family history of renal cancer
No
97,569 (95.9%)
26,624 (95.5%)
27,766 (95.8%)
19,007 (96.1%)
24,172 (96.3%)
Yes
1543 (1.5%)
406 (1.5%)
423 (1.5%)
310 (1.6%)
404 (1.6%)
Possibly
2643 (2.6%)
860 (3.1%)
781 (2.7%)
467 (2.4%)
535 (2.1%)
History of diabetes
No
94,949 (93.3%)
25,675 (92.1%)
26,957 (93.1%)
18,531 (93.7%)
23,786 (94.7%)
Yes
6806 (6.7%)
2215 (7.9%)
2013 (6.9%)
1253 (6.3%)
1325 (5.3%)
History of hypertension
No
68,707 (67.5%)
18,002 (64.5%)
19,251 (66.5%)
13,558 (68.5%)
17,896 (71.3%)
Yes
33,048 (32.5%)
9888 (35.5%)
9719 (33.5%)
6226 (31.5%)
7215 (28.7%)
Energy intake from diet (kcal/day)
1738.6 ± 736.4
1797.0 ± 740.6
1739.3 ± 782.4
1715.3 ± 763.7
1691.5 ± 645.2
Healthy Eating Index-2015
66.5 ± 9.7
57.5 ± 7.9
65.2 ± 7.0
69.9 ± 6.5
75.5 ± 6.2
DRRD and other nutrients intakes
Cereal fiber (g/day)
11.9 ± 5.7
9.3 ± 4.2
11.1 ± 5.2
12.5 ± 5.6
15.1 ± 6.2
Nuts (g/day)
6.7 ± 14.5
2.7 ± 5.7
4.9 ± 9.9
7.4 ± 14.8
12.7 ± 21.8
Coffee (g/day)
846.4 ± 794.5
730.2 ± 788.9
869.6 ± 802.6
892.7 ± 790.5
912.2 ± 780.6
Polyunsaturated/saturated fatty acids
0.8 ± 0.3
0.6 ± 0.2
0.7 ± 0.2
0.8 ± 0.2
0.9 ± 0.3
Whole fruit (Servings/day)
2.7 ± 2.0
1.7 ± 1.3
2.4 ± 1.7
3.0 ± 2.0
4.0 ± 2.4
Glycemic index of diet
53.6 ± 3.3
55.6 ± 3.0
53.9 ± 3.0
52.8 ± 2.9
51.4 ± 2.7
Trans fat acid (g/day)
4.0 ± 2.4
4.9 ± 2.5
4.2 ± 2.5
3.7 ± 2.2
2.9 ± 1.6
Sugar-sweetened beverage (g/day)
264.5 ± 433.3
449.6 ± 565.5
264.4 ± 407.3
191.5 ± 329.2
116.6 ± 254.4
Red and processed meat (g/day)
12.4 ± 15.3
19.5 ± 19.3
13.4 ± 15.0
9.8 ± 11.8
5.5 ± 7.6
Descriptive statistics are presented as (mean ± standard deviation) and number (percentage) for continuous and categorical. DRRD, diabetes risk reduction diet
aWeight change was defined as the participant's baseline weight minus weight at age 20
Association between DRRD score and the incidence of renal cancer
During 899,337.5 person-years of follow-up, 446 renal cancer cases were observed, with an overall incidence rate of 0.496 cases per 1000 person-years. In the unadjusted model, in contrast with the lowest quartile of the DRRD score, the highest quartile individuals depicted a notably decreased incidence of renal cancer (HRQ4 vs. Q1: 0.52; 95% CI 0.40, 0.68; P < 0.001 for trend) (Table 2). In the multivariate Cox regression model 1 and model 2 with adjustment for possible confounders, the DRRD score and the renal cancer incidence were depicted to have an inverse association [(model 1: HR Quartile 4 vs. Quartile1: 0.61; 95% CI 0.46, 0.80; P < 0.001 for trend) and (model 2: HRQ4 vs. Q1: 0.71; 95% CI 0.54, 0.94; P = 0.008 for trend)] (Table 2). It is important to note that this inverse association was similar when repeated analyses were executed in a population of 97,486 participants with the complete data, after excluding all missing data (HRQ4 vs. Q1: 0.74; 95% CI 0.55, 0.98; P = 0.019 for trend) (Additional file 1: Table S3).
Table 2
Hazard ratios of the association of diabetes risk reduction diet score with the risk of renal cancer
Quartiles of DRRD score
Number of cases
Person-years
Incidence rate per 1000 person-years (95% confidence interval)
Hazard ratio (95% confidence interval)
Unadjusted
Model 1a
Model 2b
Quartile 1 (9–23)
162
243,233.1
0.67 (0.57, 0.78)
1.00 (reference)
1.00 (reference)
1.00 (reference)
Quartile 2 (24–27)
133
256,240.4
0.52 (0.44, 0.62)
0.78 (0.62, 0.98)
0.81 (0.64, 1.02)
0.85 (0.68, 1.08)
Quartile 3 (28–30)
73
175,613.0
0.42 (0.33, 0.52)
0.62 (0.47, 0.82)
0.68 (0.52, 0.90)
0.75 (0.57, 1.00)
Quartile 4 (31–45)
78
224,251.0
0.35 (0.28, 0.43)
0.52 (0.40, 0.68)
0.61 (0.46, 0.80)
0.71 (0.54, 0.94)
Ptrend
< 0.001
< 0.001
0.008
DRRD, diabetes risk reduction diet
aModel 1: Adjusted for age (years), sex (male, female), race (white, non-white), marital status (married or living as married, no), educational level (college below, college graduate, postgraduate)
bModel2: Adjusted for model 1 plus body mass index (kg/m2), smoking status (never, current, former), smoking pack-years (continuous), alcohol consumption (g/day), ibuprofen use (no, yes), arm (intervention, control), family history of renal cancer (no, yes), history of diabetes (no, yes), history of hypertension (no, yes) and energy intake from diet (kcal/day)
Anzeige
Additional analyses
A restricted cubic spline model was utilized to analyze the renal cancer risk across the full range of DRRD scores. The findings demonstrated that the association between DRRD score and renal cancer risk followed a nonlinear dose–response pattern and was an inverse association (P = 0.026 for nonlinearity) (Fig. 3). The analysis of the subgroups did not reveal any remarkable interaction between DRRD score and smoking status, age, consumption of alcohol, BMI, sex, family history of renal cancer, or history of diabetes and hypertension in relation to the occurrence of renal cancer (all P > 0.05 for interaction). The results, however, depicted that the inverse association between the DRRD score and renal cancer incidence was more prominent in individuals with lower Healthy Eating Index-2015 [≤ medium (67)] (HRQ4 vs. Q1: 0.29; 95% CI 0.11, 0.80; P = 0.015 for interaction) (Table 3). In sensitivity analyses, the primary associations were still similar in the case of exclusion of cases with a family history of renal cancer (HRQ4 vs. Q1 = 0.69, 95% CI 0.52–0.92, P = 0.006 for trend) and exclusion of individuals with a history of diabetes (HRQ4 vs. Q1 = 0.74, 95% CI 0.55–0.99, P = 0.024 for trend) at baseline, exclusion of cases with renal pelvis cancer (HRQ4 vs. Q1 = 0.72, 95% CI 0.54–0.97, P = 0.020 for trend), exclusion of renal cancer cases during 2-year follow-up (HRQ4 vs. Q1 = 0.69, 95% CI 0.50–0.93, P = 0.005 for trend) or 3-year follow-up (HRQ4 vs. Q1 = 0.68, 95% CI 0.49–0.94, P = 0.008 for trend) baseline, further adjustment for Healthy Eating Index-2015 (HRQ4 vs. Q1 = 0.69, 95% CI 0.48–0.99, P = 0.035 for trend) and further adjustment for weight change (HRQ4 vs. Q1 = 0.71, 95% CI 0.53–0.93, P = 0.007 for trend) at baseline, implying the reliability of the inverse association between DRRD score and renal cancer risk (Table 4).
Fig. 3
Nonlinear Dose–response analysis on the association of DRRD score with the risk of renal cancer. Hazard ratio was adjusted for age, sex, race, marital status, education levels, drinking status, alcohol consumption, smoking status, pack-years of smoking, body mass index, ibuprofen use, history of hypertension, history of diabetes, family history of renal cancer, and energy intake from diet (P = 0.026 for nonlinear nonlinearity)
Table 3
Subgroup analyses on the association of diabetes risk reduction diet score with the risk of renal cancer
Subgroup variable
Number of participates
Number of cases
HR Quartile 4 vs. Quartile 1 (95% CI) a
P-interaction
Age (years)
0.135
≤ 65
28,171
114
0.75 (0.39, 1.42)
> 65
24,830
126
0.84 (0.48, 1.47)
Sex
0.585
Male
25,801
156
0.74 (0.44, 1.27)
Female
27,200
84
0.94 (0.47, 1.87)
Body mass index (kg/m2)
0.455
≤ 30
40,972
161
0.93 (0.56, 1.53)
> 30
12,029
79
0.55 (0.26, 1.18)
Smoking status
0.289
Never
25,308
80
0.48 (0.24, 0.99)
Current/former
27,693
160
1.05 (0.63, 1.75)
Smoking pack-years
0.214
≤ Medium
26,872
85
0.45 (0.22, 0.91)
> Medium
26,129
155
1.13 (0.67, 1.89)
Family history of renal cancer
0.661
No
50,796
228
0.79 (0.52, 1.22)
Yes/possibly
2205
12
1.34 (0.2, 8.81)
History of hypertension
0.792
No
35,898
137
1.35 (0.77, 2.36)
Yes
17,103
103
0.43 (0.23, 0.80)
History of diabetes
0.394
No
49,461
219
0.87 (0.56, 1.34)
Yes
3540
21
0.42 (0.10, 1.77)
Healthy eating index-2015
0.015
≤ Medium
27,000
154
0.29 (0.11, 0.80)
> Medium
26,001
86
1.12 (0.57, 2.20)
HR, hazard ratio; CI, confidence interval
aHRs were adjusted for age (years), sex (male, female), race (white, non-white), marital status (married or living as married, no), educational level (college below, college graduate, postgraduate), body mass index (kg/m2), smoking status (never, current, former), smoking pack-years (continuous), alcohol consumption (g/day), ibuprofen use (no, yes), arm (intervention, control), family history of renal cancer (no, yes), history of diabetes (no, yes), history of hypertension (no, yes), Healthy Eating Index-2015 (continuous) and energy intake from diet (kcal/day)
Table 4
Sensitivity analyses on the association of diabetes risk reduction diet score with the risk of renal cancer
Categories
HR Quartile 4 vs. Quartile 1 (95% CI)a
P-trend
Excluded participants with a family history of renal cancerb
0.69 (0.52, 0.92)
0.006
Excluded participants with a history of diabetesc
0.74 (0.55, 0.99)
0.024
Exclude 32 cases with renal pelvis cancer
0.72 (0.54, 0.97)
0.020
Excluded cases observed within the first 2 years of follow-up
0.69 (0.50, 0.93)
0.005
Excluded cases observed within the first 3 years of follow-up
0.68 (0.49, 0.94)
0.008
Further adjusted for Healthy Eating Index-2015d
0.69 (0.48, 0.99)
0.035
Further adjusted for weight changee
0.71 (0.53, 0.93)
0.007
HR, hazard ratio; CI, confidence interval
aHRs were adjusted for age (years), sex (male, female), race (white, non-white), marital status (married or living as married, no), educational level (college below, college graduate, postgraduate), body mass index (kg/m2), smoking status (never, current, former), smoking pack-years (continuous), alcohol consumption (g/day), ibuprofen use (no, yes), arm (intervention, control), family history of renal cancer (no, yes), history of diabetes (no, yes), history of hypertension (no, yes) and energy intake from diet (kcal/day)
bHR was not adjusted for history of renal comorbidity
cHR was not adjusted for history of diabetes
dThis covariate was treated as the continuous variable in multivariable Cox regression
eWeight change, defined as the participant's baseline weight minus weight at age 20, which was used as a proxy for BMI to be included in the analysis in the COX regression
×
Dietary components of DRRD and the risk of renal cancer
Regarding the “favorable” DRRD components, less risk of renal cancer was depicted in individuals in the highest quartile of cereal fiber and whole fruit consumption in contrast to the lowest quartile [(cereal fiber: HRQ4 vs. Q1: 0.68; 95% CI 0.48, 0.97; P = 0.025 for trend) (Additional file 1: Table S4) and (whole fruit: HRQ4 vs. Q1: 0.69; 95% CI 0.52, 0.92; P = 0.008 for trend) (Additional file 1: Table S5)]. Among “unfavorable” DRRD components, individuals in the highest quartile of sugar-sweetened beverage intake had an elevated risk of renal cancer than those in the lowest quartile (HRQ4 vs. Q1: 1.46; 95% CI 1.10, 1.93; P = 0.004 for trend; Additional file 1: Table S6). There was a lack of any remarkable association between the risk of renal cancer and remaining DRRD components, including nuts (Additional file 1: Table S7), coffee (Additional file 1: Table S8), polyunsaturated/saturated fatty acids (Additional file 1: Table S9), glycemic index (Additional file 1: Table S10), trans fatty acids (Additional file 1: Table S11), and red meat and processed meat (Additional file 1: Table S12).
Discussion
The PLCO Cancer Screening Trial provided the prospective data, which were utilized in this research to investigate the potential link between DRRD and renal cancer risk. Our result demonstrated that the DRRD score is associated with the incidence of renal cancer inversely, even after adjusting for established and suspected confounders. The restricted cubic spline model also presented a declining nonlinear trend of the incidence of renal cancer with increasing DRRD score, suggesting that the incidence of renal cancer is lower in individuals who adhered better to a diabetes risk reduction diet. Additionally, a series of sensitivity analyses were conducted, and the data depicted that the inverse association of the DRRD score with the renal cancer risk remained robust.
Previous studies have demonstrated that several single dietary or nutrient components are associated with renal cancer risk [26‐28]. However, these studies have considerable limitations as they only consider the influence of single dietary component on cancer risk but ignore the possible antagonistic or synergistic effects between different dietary components. In the present study, a higher DRRD score, reflecting better adherence to the DRRD, is calculated by a series of dietary and nutrient factors, including a higher intake of coffee, nuts, cereal fiber, whole fruits, and higher values of the ratio of polyunsaturated to saturated fatty acids, and lower glycemic index, and lesser intake of trans fatty acids, sugar-sweetened beverage, and red and processed meats [18]. Given the intercorrelation and interaction between individual dietary components in influencing disease incidence, the application of certain dietary patterns to predict disease risk is appropriate and valuable [29, 30]. Currently, epidemiological studies have increasingly confirmed the potential correlation of DRRD patterns with reduced cancer risk, such as pancreatic, breast, endometrial, and lung cancers [10‐13]. Although these results were consistent with these studies, the favorable impact of adherence to DRRD in preventing renal cancer has not been investigated in detail before, which may be a valuable contribution to the field of nutritional epidemiology of renal cancer.
Anzeige
The HEI-2015 is a diet quality indicator established by the United States Department of Agriculture, based on the Dietary Guidelines for Americans and the Food Pyramid. It consists of 13 food and nutrient components, including whole fruits, total fruits, whole grains, total vegetables, total protein foods, beans and greens, dairy, fatty acids, refined grains, sodium, seafood, plant proteins, added sugars, and saturated fats [31]. Notably, some overlapping dietary components were included in the dietary pattern of HEI-2015 and DRRD, such as whole fruits, fatty acids, and sugars. In this sensitivity analysis with further adjustment for HEI-2015, the inverse correlation between DRRD score and renal cancer risk did not change materially (HRQ4 vs. Q1: 0.69; 95% CI 0.48, 0.99; P = 0.035 for trend), suggesting that adherence to DRRD for reducing renal cancer risk is independent of diet quality. It has been shown that higher HEI-2015, indicating a better quality of diet, is associated with a lower incidence of cancers such as breast, oral, and pharyngeal cancers [31‐33], but the evidence for the association of HEI-2015 and renal cancer risk was limited. In the subgroup analyses, the inverse association of DRRD scores with the risk of renal cancer was more prominent in individuals with a lower HEI-2015 [≤ medium (67)] (HRQ4 vs. Q1: 0.29; 95% CI 0.11, 0.80; P = 0.015 for interaction). This means that the potential benefit of adherence to DRRD in preventing renal cancer is greater for participants with poor diet quality.
An in-depth analysis to investigate the association of individual components of DRRD with renal cancer risk was conducted. The results suggested that renal cancer risk was negatively linked to cereal fiber and whole fruit intake, and positively linked to sugar-sweetened beverage intake. However, other components of DRRD did not depict any notable association with renal cancer risk. This means that cereal fiber, whole fruit, and sugar-sweetened beverage may be the main contributing components to the detected inverse association of DRRD with renal cancer incidence. Notably, in a meta-analysis designed to examine the relationship between dietary fiber and renal cancer risk, the researchers documented a strong correlation between the risk of renal cancer and vegetable and legume fiber intake, but not to the intake of cereal fiber [34]. The resulting data of this research provided valuable and additional evidence for the association of renal cancer risk with cereal fiber. Cereal fiber increases the chewing action and enhances the feeling of satiety after eating, which leads to weight loss [35] and thus plays a role in reducing cancer risk [36]. In addition, studies have demonstrated that whole fruit [37] and sugar-sweetened beverage consumption [38] are significantly associated with renal cancer risk, which is consistent with the results obtained. Accordingly, in specific dietary patterns (DRRD), the impact of individual components and potential synergies between different components on renal cancer risk deserves more attention.
The inverse association between DRRD and renal cancer risk in the study may be explained by the following mechanisms. It is known that diabetes is a metabolic disease characterized by chronic hyperglycemia, and the development of diabetes mainly includes the following three aspects: insulin resistance, pro-inflammatory effect, and compensatory excessive insulin production [39], which exhibits overlapping mechanisms with renal cancer [4]. First, insulin can directly or indirectly regulate the production of hepatic IGF-1 [40], and relevant clinical research has confirmed that elevated serum IGF-I levels are linked to a greater risk of renal cancer [6, 7] and that insulin resistance further enhances the above effects [8]. The role of chronic inflammation in promoting the occurrence and progression of cancer had also been affirmed [41]. Therefore, a possible explanation for the inverse correlation between DRRD scores and renal cancer risk is that individuals who adhere to the DRRD pattern are less likely to develop chronic inflammation, hyperinsulinemia, and insulin resistance, thus reducing the incidence of renal cancer. It is important to note that diabetes has been depicted as important concerning the etiology of renal cancer [42], and there is already established evidence of the association between DRRD and diabetes risk [9]. These findings imply that the association of the DRRD pattern with renal cancer risk observed in this study may be mediated by diabetes. However, after excluding patients with a history of diabetes in the sensitivity analysis, the initial correlation did not vary significantly (HRQ4 vs. Q1: 0.74; 95% CI 0.55, 0.99; P = 0.024 for trend), suggesting that the influence of this dietary pattern on renal cancer prevention is independent of the presence of diabetes. Further research is needed on the mechanism of the process to clarify these findings.
It should be emphasized that this study is the first to reveal the inverse association between DRRD score and renal cancer incidence in a large-scale population. Further sensitivity analyses confirmed the robustness of this inverse correlation. Additionally, subgroup analyses depicted that this association was more prominent in participants with lower HEI-2015 (≤ 67), suggesting that adherence to DRRD was more beneficial in decreasing the risk of renal cancer in those with lower diet quality. Furthermore, the role of each specific component of DRRD was examined concerning the reduction of the risk of developing renal cancer. In addition to determining that whole fruit and SSB are significantly related to renal cancer risk, the data also depicted a considerable effect of cereal fiber on reducing the risk of renal cancer, which is the first time that the relationship between cereal fiber and the risk of renal cancer was depicted. This may provide more accurate guidance for people to adhere to DRRD, that is, consuming higher whole fruit and cereal fiber and lower SSB in the diet pattern of DRRD may be more beneficial in reducing renal cancer risk.
Anzeige
Objectively, this study is limited in several aspects. First, the food consumption of DRRD was only examined once with DHQ instead of long-term cumulative averages, which may lead to nondifferential bias as dietary habits are subject to alterations during the follow-up period. However, related studies of adults have pointed out that their dietary habits are not always subject to major alterations in the short term [43]. Moreover, the current evidence did not fully support the suggestion that using cumulative averages tends to produce stronger associations than using baseline dietary data [44, 45]. Second, there is a possibility of misclassification bias in the dietary data obtained from the self-reported food frequency questionnaire. Third, although these results were fully and extensively adjusted for relevant covariates, residual confounding is still difficult to completely avoid. For example, metformin use is protective against renal cancer risk in patients with diabetes [46], but it is unclear whether the diabetic population in this study was taking metformin. Fourth, the population in the study was older Americans with an average age of 65.5 years, it remains uncertain, whether the close association of DRRD with renal cancer risk can be applied to other age groups or non-U.S. populations. Future research should be performed in other populations to validate the reliability of these findings.
Conclusion
In conclusion, this research depicted an inverse association of DRRD score with renal cancer risk. Adherence to the dietary pattern of DRRD may be an effective approach for preventing renal cancer. To enhance the reliability and scope of our findings, future research should aim to replicate our analysis in ethnically and geographically diverse cohorts, ensuring robust cross-national validation. Furthermore, conducting large-scale prospective cohort studies with extended follow-up periods will be pivotal in assessing the long-term effectiveness of adhering to the DRRD in preventing the onset and progression of renal cancer. By elucidating the generalizability and temporal sequence of this dietary pattern-disease association through rigorous longitudinal studies, we can further promote DRRD as a recommended and healthy dietary pattern for mitigating the increasing incidence of renal cancer worldwide.
Acknowledgements
We sincerely appreciate the PLCO study group and PLCO participants. This research has been conducted using the PLCO resource (https://cdas.cancer.gov/plco/) under application number PLCO-1063.
Declarations
Ethics approval and consent to participate
The study is in line with the Helsinki Declaration. The PLCO Cancer Screening Trial design was approved by the Institutional Review Board of the National Cancer Institute and each of the screening centers. Participants provided written informed consent prior to participation in this study.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
In einer Studie aus New York wirkte sich Ärger kurzfristig deutlich negativ auf die Endothelfunktion gesunder Probanden aus. Möglicherweise hat dies Einfluss auf die kardiovaskuläre Gesundheit.
Die Nahrungsaufnahme auf wenige Stunden am Tag zu beschränken, hat möglicherweise einen günstigen Einfluss auf die Prognose nach akutem ST-Hebungsinfarkt. Darauf deutet eine Studie an der Uniklinik in Halle an der Saale hin.
Auch kleine Entscheidungen im Alltag einer Praxis können einen großen Beitrag zum Klimaschutz leisten. Die neue Leitlinie zur "klimabewussten Verordnung von Inhalativa" geht mit gutem Beispiel voran, denn der Wechsel vom klimaschädlichen Dosieraerosol zum Pulverinhalator spart viele Tonnen CO2. Leitlinienautor PD Dr. Guido Schmiemann erklärt, warum nicht nur die Umwelt, sondern auch Patientinnen und Patienten davon profitieren.
Menschen mit Typ-2-Diabetes sind überdurchschnittlich gefährdet, in den nächsten Jahren auch noch eine Depression zu entwickeln – und umgekehrt. Besonders ausgeprägt ist die Wechselbeziehung laut GKV-Daten bei jüngeren Erwachsenen.
Update Innere Medizin
Bestellen Sie unseren Fach-Newsletter und bleiben Sie gut informiert.
