The association between caffeine intake and mortality among patients with chronic kidney disease: A population-based study

doi:10.21203/rs.3.rs-4963935/v1

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The association between caffeine intake and mortality among patients with chronic kidney disease: A population-based study

https://doi.org/10.21203/rs.3.rs-4963935/v1

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Background

The benefits of caffeine to human health have been widely reported, but the association between caffeine intake and mortality among patients with chronic kidney disease (CKD) has been rarely studied in large epidemiologic studies. Thus, we aimed to investigate the association between caffeine intake and mortality among CKD patients.

Methods

Our study was based on non-dialysis CKD patients in 2003–2016 National Health and Nutrition Examination Survey (NHANES). Weighted COX regression analysis was applied to explore the linear relationship between caffeine intake and mortality (including all-cause mortality, cardiovascular mortality, cancer mortality, cerebrovascular mortality, nephropathy mortality and influenza and pneumonia mortality). Restricted cubic spline analysis was performed to explore the nonlinear relationship. Finally, threshold effects were analyzed with two-piecewise linear regression.

Results

In the fully adjusted model, there was no significant linear association between caffeine intake and mortality. However, a U-shaped nonlinear association between caffeine intake and all-cause mortality (inflection point = 277mg) was identified. Moreover, there was a J-shaped association between caffeine intake and cardiovascular mortality (inflection point = 252mg) and cancer mortality (inflection point = 79mg).

Conclusion

Moderate caffeine intake shows a protective effect on the prognosis of CKD patients. However, excessive caffeine intake was associated with increased all-cause mortality, cardiovascular mortality and cancer mortality.

Health sciences/Diseases

Health sciences/Nephrology

Health sciences/Health care/Nutrition

Health sciences/Health care/Prognosis

chronic kidney disease

caffeine

mortality

prognosis

NHANES

population-based study

Over 850 million individuals globally suffer from chronic kidney disease (CKD), and the incidence of CKD is still growing(1). Most CKD patients may not finally progress to renal failure, but CKD can still lead to higher mortality through complicating the treatment of other diseases, especially cardiovascular disease, cancer and infection (2–4).Currently, CKD ranks tenth among the leading causes of death worldwide and is predicted to rise to fifth by 2040(5). Thus, improving the prognosis of CKD has become an urgent issue globally.

As the most characteristic natural component of coffee, caffeine (1,3,7-trimethylxanthine) has been widely used as psychoactive substance worldwide(6, 7). Daily sources of caffeine mainly include coffee, tea and cocoa products(8). For adults from North America and European countries, about 75% of the daily caffeine intake comes from coffee(9). Recently, it has been demonstrated in multiple studies that caffeine can affect human health through different physiological mechanisms(10–12).

The results of several studies suggested that daily coffee intake is associated with a reduced risk of CKD(13–16). Moreover, a study based on the National Health and Nutrition Examination Survey (NHANES) database showed that caffeine intake was negatively associated with all-cause mortality, but not significantly associated with cardiovascular mortality or cancer mortality among CKD patients(12). However, the optimal caffeine intake for CKD patients remains unclear. Therefore, our study was aimed to analyze the association between caffeine intake and prognosis of CKD patients and further explore the optimal caffeine intake for CKD patients.

Data sources and participants

All of the data in our research were obtained from the NHANES database, which is a national cross-sectional study conducted by the National Center for Health Statistics (NCHS) to assess the nutrition and health status of the U.S. population. Demographic data, dietary data, examination data, laboratory data and questionnaire data were provided by NHANES. The data mentioned above were all collected through complex stratified, multistage probability cluster sampling(17).

Research Ethics Review Board of NCHS approved the protocols for NHANES research. All of the survey participants (including legal guardians) wrote informed consent. We confirm that all methods were performed in accordance with the relevant guidelines and regulations. All of the NHANES data are publicly available at https://www.cdc.gov/nchs/nhanes/.

Seven NHANES cycles from 2003 to 2016 (n = 37662) were selected to assess the association between caffeine intake and mortality among CKD patients since only these survey cycles include complete variables needed in our study. Inclusion criteria of our study were as follows: 1) diagnosed with CKD [estimated glomerular filtration rate (eGFR) < 60ml/min/1.73m²(18) or urine albumin-to-creatinine ratio (UACR) > 30 mg/g)]; 2) age > = 18. Exclusion criteria were as follows: 1) receiving dialysis; 2) missing data on caffeine intake, mortality data or covariates; 3) missing data on weights, primary sampling unit or stratification.

Exposure and outcomes

All of the NHANES participants were engaged in two 24-hour dietary recall interviews. The first dietary recall interview took place at a mobile testing center while the second was carried out via telephone 3–10 days later. Daily total intake of nutrients/food components were measured based on the criterion provided by USDA Dietary Study Food and Nutrition Database. Almost all caffeinated beverages and foods, including approximately 50 coffee/coffee beverages and 30 teas, were taken into account to estimate the daily caffeine intake. The average caffeine intake from two 24-hour recall interviews was calculated and chosen as exposure(19).

Information of vital status and cause-of-death of participants in NHANES was investigated by NCHS. The follow-up time was calculated from the beginning of interview to the date of death or December 31, 2019. Cause-of-death was determined according to ICD-10. All-cause mortality, cardiovascular mortality, cancer mortality, cerebrovascular mortality, nephropathy mortality, influenza and pneumonia mortality were selected as outcomes.

Covariates

Potential factors that could influence the association between caffeine intake and mortality were considered in our study and included as covariates, containing age (year), gender (male/female), race (Mexican American/other Hispanic/non-Hispanic White/non-Hispanic Black/other races), marital status (married/widowed/divorced/separated/never married/living with partner), body mass index (BMI) (kg/m2), ratio of family income to poverty (PIR), eGFR (ml/min/1.73m2), UACR (mg/g), frequency of drinking, smoked more than 100 cigarettes in life (Y/N), hypertension (Y/N), diabetes (Y/N). All detailed processes of the measurement of these variables are publicly available at www.cdc.gov/nchs/nhanes/.

Statistical analysis

All statistical analyses were performed following the guidelines of Centers for Disease Control and Prevention (CDC). Appropriate NHANES sampling weights were applied and complex multistage cluster survey was taken into account. Continuous variables with normal distributions were presented as mean ± standard deviation while those with skewed distributions were presented as median and interquartile range. Categorical parameters were summarized as proportions. CKD patients were divided into four groups based on the quartiles of caffeine intake. The baseline characteristics of different groups were compared via various statistical analysis approaches, including weighted analysis of variance (for normally distributed continuous variables), Kruskal-Wallis H test (for skewedly distributed continuous variables) and chi-square test (for categorical variables).

Then, weighted COX proportional hazard regression was utilized to evaluate the association between caffeine intake and all-cause mortality, cardiovascular mortality, cancer mortality, cerebrovascular mortality, nephropathy mortality and influenza and pneumonia mortality. Three different COX regression models were calculated. Model 1 was the crude mode. Model 2 was adjusted for age, sex and race. Model 3 included the covariates of model 2 with additional adjustment for marital status, BMI, PIR, eGFR, UACR, alcohol intake, smoking status, hypertension and diabetes. Results were described as hazard ratio (HR) and 95% confidence interval (95%CI).

Adjusting for all covariates, restricted cubic spline (RCS) model (4 knots) based on COX regression was constructed to test the nonlinear relationship between caffeine intake and all-cause mortality, cardiovascular mortality, cancer mortality, cerebrovascular mortality, nephropathy mortality and influenza mortality and pneumonia mortality. Finally, a two-piecewise linear regression model was applied to explore the threshold effects. All analyses were conducted with R version 4.3.2. A value of P < 0.05 was considered statistically significant.

Baseline characteristics of participants

A total of 5815 CKD patients were enrolled according to our criterion(Fig. 1), of whom 49.22% were male and 50.78% were female, with a weighted median age of 48 years. The weighted median caffeine intake of all CKD patients was 133.5mg. Due to the skewed distribution of caffeine intake, we used log(x + 1) transformed data for all further analyses. Participants were grouped according to the quartiles of caffeine intake, whose characteristics are shown in Table 1. There were significant differences in age, sex, race, marital status, PIR, alcohol intake and smoking status among the four groups.

Table 1

Baseline characteristics of CKD patients stratified by daily caffeine intake levels
Variables	Quantiles of the caffeine (mg) log(x + 1) transform				P value
	Q1(< 3.85)	Q2(3.85–4.90)	Q3(4.90–5.55)	Q4(≥ 5.55)
Number of participants (%)	1757(30.21)	1618(27.82)	1362(23.42)	1078(18.54)
Age, years, median (IQR)	47.00(35.00)	46.00 (31.00)	48.00(26.00)	49.00(21.00)	< 0.001
Female, n (%)	935(55.9)	828(53.1)	648(51.5)	426(42.6)	< 0.001
Race, n (%)					< 0.001
Mexican American	309(9.4)	299(10.4)	202(5.8)	110(2.7)
Other Hispanic	82(4.1)	106(5.0)	67(2.9)	31(1.4)
Non-Hispanic White	727(63.0)	732(66.6)	841(81.5)	823(89.8)
Non-Hispanic Black	555(19.1)	411(13.9)	200(6.3)	70(2.1)
Other Race	84(4.4)	70(4.2)	52(3.5)	44(4.0)
Marital status, n (%)					< 0.001
Married	906(54.8)	839(56.6)	782(62.0)	652(64.2)
Widowed	226(9.2)	240(10.3)	170(6.7)	104(6.0)
Divorced	174(9.3)	172(8.0)	164(11.3)	154(14.0)
Separated	64(2.3)	59(2.8)	31(2.2)	30(1.7)
Never married	286(18.4)	206(15.2)	134(11.8)	77(7.9)
Living with partner	101(6.1)	102(7.1)	81(6.2)	61(6.2)
BMI, kg/m2, mean (SD)	28.76 (7.09)	28.86(6.55)	28.35(6.46)	28.94 (6.29)	0.489
PIR, median(IQR)	2.49 (2.83)	2.72(3.06)	3.36(3.18)	3.31(3.08)	< 0.001
eGFR, ml/min/1.73m², median (IQR)	95.66(38.76)	94.40(33.64)	94.24(30.95)	94.87(29.13)	0.294
Urinary albumin: creatinine ratio, median (IQR)	104.00(125.91)	101.65(120.17)	100.00(123.08)	98.00(118.00)	0.243
Frequency of drinking, median (IQR)	1.00(3.00)	2.00(2.00)	2.00(3.00)	2.00(2.31)	0.008
Smoked more than 100 cigarettes in life, n (%)	835(46.7)	782(45)	825(58.3)	786(68.5)	< 0.001
Hypertension, n (%)	857(39.3)	801(37.7)	658(34.6)	489(34.3)	0.165
Diabetes, n (%)	344(12.5)	322(9.9)	283(11.3)	226(11.8)	0.279

During a median follow-up of 142 months, 1628 all-cause deaths were documented, including 473 (29.05%) cardiovascular mortality, 351 (21.56%) cancer deaths, 83 (5.10%) cerebrovascular deaths, 40 (2.46%) nephropathy deaths and 36 (2.21%) influenza and pneumonia death.

Linear association between caffeine intake and mortality

Adjusting for all covariates, no significant linear association was found between caffeine intake and all-cause mortality (p = 0.76), cardiovascular mortality (p = 0.21), cancer mortality (p = 0.34), cerebrovascular mortality (p = 0.32), nephropathy mortality (p = 0.46) and influenza and pneumonia mortality (p = 0.97). Detailed results are shown in Table 2.

Table 2

Cox regression models for the linear association between caffeine intake and mortality among CKD patients.
	Quantiles of the caffeine (mg) log(x + 1) transform
	Q1	Q2	Q3	Q4	P for trend
All-cause mortality
Deaths, n (%)	511(29)	435(27)	373(27)	309(29)
Model 1 HR	-	0.81(0.68–0.97)	0.76(0.61–0.96)	0.82(0.65–1.04)	0.09
Model 2 HR	-	0.89(0.77–1.03)	0.86(0.70–1.05)	1.03(0.85–1.26)	0.98
Model 3 HR	-	0.90(0.76–1.06)	0.85(0.69–1.05)	0.99(0.79–1.24)	0.76
Cardiovascular mortality
Deaths, n (%)	143(8)	136(8)	102(7)	92(9)
Model 1 HR	-	0.87(0.63–1.19)	0.82(0.55–1.21)	0.92(0.65–1.29)	0.57
Model 2 HR	-	0.97(0.71–1.33)	0.96(0.69–1.35)	1.24(0.88–1.75)	0.28
Model 3 HR	-	0.98(0.69–1.41)	1.01(0.68–1.50)	1.26(0.88–1.80)	0.21
Cancer mortality
Deaths, n (%)	109(6)	74(5)	88(6)	80(7)
Model 1 HR	-	0.78(0.57–1.05)	0.84(0.60–1.17)	1.08(0.79–1.48)	0.58
Model 2 HR	-	0.84(0.62–1.14)	0.93(0.65–1.33)	1.30(0.89–1.89)	0.22
Model 3 HR	-	0.87(0.64–1.17)	0.92(0.64–1.31)	1.23(0.84–1.81)	0.34
Cerebrovascular mortality
Deaths, n (%)	30(2)	24(1)	17(1)	12(1)
Model 1 HR	-	0.71(0.40–1.26)	0.42(0.22–0.80)	0.47(0.21–1.06)	0.03
Model 2 HR	-	0.76(0.42–1.38)	0.52(0.28–0.99)	0.80(0.35–1.82)	0.33
Model 3 HR	-	0.77(0.40–1.51)	0.53(0.28–0.99)	0.79(0.34–1.83)	0.32
Nephropathy mortality
Deaths, n (%)	11(1)	11(1)	12(1)	6(1)
Model 1 HR	-	1.03(0.34–3.09)	2.10(0.69–6.37)	0.59(0.16–2.21)	0.92
Model 2 HR	-	1.19(0.41–3.48)	2.87(0.90–9.07)	0.98(0.26–3.63)	0.38
Model 3 HR	-	0.81(0.34–1.94)	2.68(1.09–6.62)	0.83(0.22–3.17)	0.46
Influenza and pneumonia mortality
Deaths, n (%)	12(1)	8(0)	11(1)	5(0)
Model 1 HR	-	0.53(0.16–1.65)	0.94(0.33–2.71)	0.59(0.19–1.89)	0.59
Model 2 HR	-	0.61(0.18–2.07)	1.22(0.41–3.59)	0.92(0.27–3.18)	0.87
Model 3 HR	-	0.68(0.21–2.22)	1.11(0.37–3.33)	0.85(0.24–3.06)	0.97

Nonlinear association between caffeine intake and mortality

By constructing the RCS model with full adjustment for covariates, a U-shaped nonlinear association between caffeine intake and all-cause mortality was found. Moreover, caffeine intake displayed a J-shaped association with cardiovascular mortality and cancer mortality. However, there was no significant nonlinear association between caffeine intake and cerebrovascular mortality, nephropathy mortality and influenza and pneumonia mortality (Fig. 2).

Threshold effects analysis

Threshold effects analysis was performed through fitting a two-piecewise linear regression model (Table 3). When caffeine intake was lower than 277mg, caffeine intake was negatively associated with all-cause mortality in CKD patients, but when caffeine intake was higher than 277mg, caffeine intake was positively associated with all-cause mortality. When caffeine intake was above 252mg, caffeine intake was positively associated with cardiovascular mortality. When caffeine intake was above 79mg, caffeine intake was positively associated with cancer mortality. The trends described above are basically consistent with the RCS analysis, which proves the robustness of our results.

Table 3

Threshold effects analysis using two-piecewise regression models
Outcome	the effect size, 95%CI, P value
All-cause mortality
Model 1	0.986(0.957–1.016)0.356
Model 2
Inflection point	5.628 (277mg)
< 5.628	0.968(0.938-1.000)0.048
> 5.628	1.512(1.171–1.952)0.002
P for likelihood ratio test	0.002
Cardiovascular mortality
Model 1	1.015(0.958–1.074)0.619
Model 2
Inflection point	5.533 (252mg)
< 5.533	0.987(0.929–1.048)0.663
> 5.533	1.722(1.132–2.617)0.011
P for likelihood ratio test	0.019
Cancer mortality
Model 1	1.025(0.958–1.096)0.474
Model 2
Inflection point	4.382 (79mg)
< 4.382	0.923(0.839–1.015)0.097
> 4.382	1.355(1.11–1.655)0.003
P for likelihood ratio test	0.004

Several studies have revealed the benefits of moderate caffeine intake to healthy adults by reducing the risk of cardiovascular disease, obesity, diabetes and cancer(20). However, the dietary patterns of healthy people do not apply to CKD patients(21). Currently, there is limited research on the impact of caffeine intake on the prognosis of CKD patients. A previous study showed that caffeine intake in CKD patients was linearly and negatively correlated with all-cause mortality, and had no significant association with cardiovascular mortality and cancer mortality(12). Nevertheless, nonlinear association between caffeine intake and mortality among CKD patients has not been explored and the optimal caffeine intake for CKD patients remains unknown. Thus, our study aimed to select updated NHANES datasets to analyze the linear and nonlinear relationship between caffeine intake and mortality in CKD patients and explore the optimal caffeine intake for CKD patients.

In our study, the results of linear analysis suggested that caffeine intake was not significantly associated with all-cause mortality, cardiovascular mortality, cancer mortality, cerebrovascular mortality, nephropathy mortality and influenza and pneumonia mortality among CKD patients. Our results are not consistent with the previous study mentioned above. The reason may be that updated NHANES datasets were selected in our research so that our included population tended to consume more caffeine. This may account for the failure of fitting the relationship between caffeine intake and prognosis among CKD patients with linear model.

In comparison to the simple and intuitive interpretation ability provided by linear regression, nonlinear regression is more suitable for fitting complicated data patterns. Therefore, RCS analysis was performed to further explore the nonlinear association between caffeine intake and mortality among CKD patients. The results showed a U-shaped relationship (inflection point = 277mg) between caffeine intake and all-cause mortality. A tall of Americano typically contains about 150mg caffeine. For healthy adults, the recommended daily caffeine intake is less than 400mg(22). Thus, CKD patients may be suitable to consume less caffeine than healthy adults. It is recommended that CKD patients intake moderate amount of caffeine daily (about 1.85 talls of Americano) to reduce the risk of all-cause death. In addition, the results showed a J-shaped relationship between caffeine intake and cardiovascular (inflection point = 252mg, about 1.68 talls of Americano) and cancer mortality (inflection point = 79mg, about 0.53 talls of Americano).

The association between coffee consumption and the risk of CKD is controversial. Three relevant meta-analyses were retrieved, two of which supported the role of coffee consumption in reducing the risk of developing CKD(16, 23), while the other did not find a statistical association(24). The molecular mechanism by which caffeine affects the kidney is unclear. The protective effect of caffeine on the kidney may be attributed to the antioxidant ability of caffeine. Oxidant-antioxidant system imbalance always occurs in CKD patients, which can result in kidney damage and progression of CKD by inducing inflammatory responses and renal interstitial fibrosis(25). Reactive oxygen species production can be reduced and oxidative stress can be inhibited by caffeine and its methylxanthine metabolites through antagonizing adenosine receptor(26). However, adenosine also acts as an endogenous anti-inflammatory agent in humans. The antagonistic effects of caffeine on adenosine receptors may also exacerbate glomerular and interstitial inflammation(27). It has been demonstrated in animal studies that caffeine does not cause pathological effects on the kidneys with normal function and structure, but aggravates adverse effects on the kidneys with preexisting diseases(28–31). Thus, combined with the results in our research, we speculated that caffeine may play a dual role on the kidneys. Moderate caffeine intake may protect the kidney through antioxidants, but excessive caffeine intake may cause kidney damage through pro-inflammatory effects.

The effects of caffeine intake on the occurrence of cardiovascular events have been extensively studied. The results of a large prospective cohort study based on the general population showed that moderate caffeine intake from coffee (121-180mg/ day) had the highest protective effect against coronary heart disease(32). However, our research did not find the protective effect of caffeine against cardiovascular mortality in CKD patients and suggested that excessive caffeine intake may increase cardiovascular mortality. It has been reported in a recent study that low density lipoprotein (LDL) levels in the blood can be reduced by caffeine through inducing the expression of LDL receptors on liver cells(33). The reduced LDL levels may account for the protection effect of caffeine on coronary heart disease. However, excessive caffeine intake can lead to a sharp increase in blood pressure, which may explain the increased cardiovascular risk caused by excessive caffeine consumption(34).

Caffeine has the potential to prevent and control various types of cancer(35–37). It may play a role in inhibiting proliferation, promoting apoptosis, preventing metastasis, enhancing immune response(36, 38–40). However, it was suggested in our study that excessive caffeine consumption may increase the cancer mortality in CKD patients. There is few research on the cancer risk of caffeine, which deserves further research.

Our research has several advantages. First, CKD patients, a special population, were selected as our research objects. It is the first time to investigate the nonlinear relationship between caffeine intake and mortality and explore the optimal daily caffeine intake in CKD patients. Second, our study was based on the NHANES database, which adopts the method of sampling weights to make the data representative. All of our analyses took appropriate weights into account. Anyway, there are some limitations in our study. Although some potential covariates were adjusted in this study, the influence of other possible confounding factors could not be completely excluded.

In summary, moderate caffeine intake (277mg) is recommended for CKD patients. However, CKD patients have to avoid excessive caffeine intake since the risk of increasing all-cause mortality, cardiovascular mortality and cancer mortality. This study may provide new insights into improving the prognosis of CKD patients.

Conflicts of Interest:

The authors declare no conflicts of interest.

Funding:

This work was supported by grants from the National Natural Science Foundation of China (No. 81770736).

Author Contribution

WC and JX conceived and designed the study. WC and JZ collected data and analyzed the results. WC wrote the manuscript. JX provided the financial support and reviewed the manuscript. All authors contributed to the article and approved the submitted version.

Data Availability

All of the data used in this study are publicly available at https://www.cdc.gov/nchs/nhanes/.

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The association between caffeine intake and mortality among patients with chronic kidney disease: A population-based study

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