Caffeinated and Decaffeinated Coffee and Risk of T2DM
The initial search identified 800 potentially relevant citations. After screening titles and abstracts, we identified 39 studies for further evaluation Fig. 1. We excluded six studies with a cross-sectional study design, three that were abstracts of conference posters, and two that were repeated in the same cohort. The results of the remaining 28 studies, comprising 1,109,272 study participants and 45,335 cases of type 2 diabetes, were included in the meta-analysis. Characteristics of all 28 studies were shown in Table 1. The duration of follow-up for incident type 2 diabetes ranged from 10 months to 20 years, with a median follow-up of 11 years. Thirteen studies were conducted in the U.S., 11 in Europe, and 4 in Asia. In nine studies, type 2 diabetes was self-reported; the outcome of six studies was assessed by means of a glucose tolerance test, and the outcome of the other studies was confirmed by either medical records or national registries. One study was a nested case-control design, and the remaining 27 were prospective cohort studies. Ten studies assessed both caffeinated and decaffeinated coffee, and only one each assessed caffeinated coffee and decaffeinated coffee. Fifteen studies did not distinguish caffeinated coffee and decaffeinated coffee, and seven assessed caffeine consumption. The mean NOS score was 7 (of a possible 9 points), suggesting a high quality of the studies included in the meta-analysis. The points were mainly lost in exposure assessment and adequacy of follow-up of cohorts: Six studies assessed coffee consumption by structured interview, and five addressed the percentage of loss to follow-up.
(Enlarge Image)
Figure 1.
Study selection process of the identified articles.
Figure 2 shows the results of different levels of total coffee consumption compared with the lowest category. Compared with the lowest category (median consumption 0 cups/day), the pooled RR for incident type 2 diabetes for individuals in the highest category of consumption (5 cups/day) was 0.70 (95% CI 0.65–0.75, I = 50%, P for heterogeneity = 0.001). The corresponding RRs were 0.80 (0.75–0.85, I = 71%, P < 0.001) for the second highest category (3.5 cups/day) and 0.91 (0.88–0.94, I = 19%, P = 0.17) for the third highest category (1 cup/day) of coffee consumption. Thus, there was evidence for substantial between-study heterogeneity in results for the highest two categories of coffee consumption.
(Enlarge Image)
Figure 2.
Forest plot of the associations between total coffee consumption and risk of type 2 diabetes. Compared with the lowest category (median consumption 0 cups/day), the pooled RR for incident type 2 diabetes was 0.70 (95% CI 0.65–0.75, I = 50%, P for heterogeneity = 0.001) for the highest category of consumption, 0.80 (0.75–0.85, I = 71%, P < 0.001) for the second highest, and 0.91 (0.88–0.94, I = 19%, P = 0.17) for the third highest category of coffee consumption.
We performed a dose-response meta-analysis in 27 studies to test for a linear trend between total coffee consumption and risk of type 2 diabetes and to estimate RRs for specific amounts of coffee consumption. One study included coffee consumption of >12 cups/day for the highest category; we treated this observation as an outlier and excluded it from the dose-response analysis. There was a strong inverse association between coffee consumption and risk of type 2 diabetes Fig. 3. A cubic spline model accounted for more variance in the outcome than did a linear model (likelihood ratio test P < 0.001), suggesting that the association was not fully linear. Compared with participants with no coffee consumption, the RR estimated directly from the cubic spline model for 1–6 cups/day was 0.92 (95% CI 0.90–0.94), 0.85 (0.82–0.88), 0.79 (0.75–0.83), 0.75 (0.71–0.80), 0.71 (0.65–0.76), and 0.67 (0.61–0.74), respectively.
(Enlarge Image)
Figure 3.
Dose-response analysis of the association between coffee consumption and risk of type 2 diabetes. For the overall association between coffee consumption and risk of diabetes, P < 0.001; for the goodness of fit of the model, P = 0.14; and for the likelihood ratio test compared with the nested linear model, P < 0.001.
To test whether the inverse association between coffee consumption and risk of type 2 diabetes was different for unadjusted and adjusted RRs, we performed a dose-response meta-analysis of the unadjusted data in 27 studies Supplementary Fig. 1. The spline curve of the unadjusted data was similar to that of the multivariable-adjusted data, indicating that adjustment for potential confounders minimally affected effect estimates for the association between coffee consumption and a lower risk of diabetes.
Both caffeinated and decaffeinated coffee consumption was inversely associated with risk of type 2 diabetes Supplementary Fig. 2. Compared with participants with the lowest level of caffeinated coffee consumption, the RR for incident type 2 diabetes was 0.74 (95% CI 0.67–0.81, I = 56%, P for heterogeneity = 0.005) for the highest category (median consumption 5 cups/day), 0.82 (0.75–0.91, I = 74%, P < 0.001) for the second highest category (3.5 cups/day), and 0.92 (0.89–0.96, I = 6.6%, P = 0.38) for the third highest category (1 cup/day). Compared with those with the lowest level of decaffeinated coffee consumption, the combined RR for incident type 2 diabetes was 0.80 (0.70–0.91, I = 62%, P = 0.001) for the highest category (4 cups/day), 0.95 (0.88–1.02, I = 53%, P = 0.02) for the second highest category (2 cups/day), and 0.98 (0.92–1.05, I = 62%, P = 0.003) for the third highest category (0.5 cups/day). Heterogeneity was shown for five of the six subgroups. Seven of 12 studies adjusted for caffeinated and decaffeinated coffee consumption simultaneously. The association was slightly stronger for caffeinated coffee consumption than for decaffeinated coffee consumption (P = 0.03 for the second highest group, P = 0.07 for the highest group) Supplementary Table 1.
We conducted a linear dose-response analysis for caffeinated and decaffeinated coffee consumption separately (11 studies). For a 1 cup/day increase in caffeinated coffee consumption, the RR for type 2 diabetes was 0.91 (95% CI 0.89–0.94), and for a 1 cup/day increase in decaffeinated coffee consumption, the RR was 0.94 (0.91–0.98, P for difference = 0.17). We performed a dose-response analysis between caffeine consumption and type 2 diabetes risk based on seven of the included studies and found that for every 140 mg/day (~1 cup/day coffee) higher caffeine consumption, the RR for type 2 diabetes was 0.92 (0.90–0.94). Of note, none of the included studies controlled for coffee intake when modeling caffeine intake and diabetes.
In stratified analyses, the inverse associations between coffee consumption and risk of diabetes were similar by geographical region (U.S., Europe, and Asia), sex, and diabetes assessment method (P for interaction > 0.05 for all groups) Supplementary Table 1.
For the dose-response analysis of total coffee consumption with diabetes, after we included the observation with extremely high coffee consumption, the results did not change. Significant heterogeneity was found for the highest and second highest total coffee consumption, which might be attributable to the heterogeneous amount of coffee consumption in these categories. The dose-response analysis accounted for the heterogeneous consumption amount of individual studies and showed an appropriate goodness of fit (P = 0.14).
Heterogeneity was also found in separate analyses of caffeinated and decaffeinated coffee consumption. In addition to considering different consumption amounts, we stratified the analyses by whether the studies included caffeinated and decaffeinated coffee consumption simultaneously in the same model. In these analyses, the heterogeneity at each level of caffeinated and decaffeinated coffee consumption decreased significantly, with even more inverse results for both caffeinated and decaffeinated coffee consumption Supplementary Fig. 3.
The Egger test provided no evidence of publication bias at any levels of total coffee, caffeinated coffee, and decaffeinated coffee consumption Supplementary Table 2.
Results
Characteristics of Studies
The initial search identified 800 potentially relevant citations. After screening titles and abstracts, we identified 39 studies for further evaluation Fig. 1. We excluded six studies with a cross-sectional study design, three that were abstracts of conference posters, and two that were repeated in the same cohort. The results of the remaining 28 studies, comprising 1,109,272 study participants and 45,335 cases of type 2 diabetes, were included in the meta-analysis. Characteristics of all 28 studies were shown in Table 1. The duration of follow-up for incident type 2 diabetes ranged from 10 months to 20 years, with a median follow-up of 11 years. Thirteen studies were conducted in the U.S., 11 in Europe, and 4 in Asia. In nine studies, type 2 diabetes was self-reported; the outcome of six studies was assessed by means of a glucose tolerance test, and the outcome of the other studies was confirmed by either medical records or national registries. One study was a nested case-control design, and the remaining 27 were prospective cohort studies. Ten studies assessed both caffeinated and decaffeinated coffee, and only one each assessed caffeinated coffee and decaffeinated coffee. Fifteen studies did not distinguish caffeinated coffee and decaffeinated coffee, and seven assessed caffeine consumption. The mean NOS score was 7 (of a possible 9 points), suggesting a high quality of the studies included in the meta-analysis. The points were mainly lost in exposure assessment and adequacy of follow-up of cohorts: Six studies assessed coffee consumption by structured interview, and five addressed the percentage of loss to follow-up.
(Enlarge Image)
Figure 1.
Study selection process of the identified articles.
Total Coffee Consumption and Risk of Type 2 Diabetes
Figure 2 shows the results of different levels of total coffee consumption compared with the lowest category. Compared with the lowest category (median consumption 0 cups/day), the pooled RR for incident type 2 diabetes for individuals in the highest category of consumption (5 cups/day) was 0.70 (95% CI 0.65–0.75, I = 50%, P for heterogeneity = 0.001). The corresponding RRs were 0.80 (0.75–0.85, I = 71%, P < 0.001) for the second highest category (3.5 cups/day) and 0.91 (0.88–0.94, I = 19%, P = 0.17) for the third highest category (1 cup/day) of coffee consumption. Thus, there was evidence for substantial between-study heterogeneity in results for the highest two categories of coffee consumption.
(Enlarge Image)
Figure 2.
Forest plot of the associations between total coffee consumption and risk of type 2 diabetes. Compared with the lowest category (median consumption 0 cups/day), the pooled RR for incident type 2 diabetes was 0.70 (95% CI 0.65–0.75, I = 50%, P for heterogeneity = 0.001) for the highest category of consumption, 0.80 (0.75–0.85, I = 71%, P < 0.001) for the second highest, and 0.91 (0.88–0.94, I = 19%, P = 0.17) for the third highest category of coffee consumption.
Dose-response Analyses of Total Coffee Consumption and Risk of Diabetes
We performed a dose-response meta-analysis in 27 studies to test for a linear trend between total coffee consumption and risk of type 2 diabetes and to estimate RRs for specific amounts of coffee consumption. One study included coffee consumption of >12 cups/day for the highest category; we treated this observation as an outlier and excluded it from the dose-response analysis. There was a strong inverse association between coffee consumption and risk of type 2 diabetes Fig. 3. A cubic spline model accounted for more variance in the outcome than did a linear model (likelihood ratio test P < 0.001), suggesting that the association was not fully linear. Compared with participants with no coffee consumption, the RR estimated directly from the cubic spline model for 1–6 cups/day was 0.92 (95% CI 0.90–0.94), 0.85 (0.82–0.88), 0.79 (0.75–0.83), 0.75 (0.71–0.80), 0.71 (0.65–0.76), and 0.67 (0.61–0.74), respectively.
(Enlarge Image)
Figure 3.
Dose-response analysis of the association between coffee consumption and risk of type 2 diabetes. For the overall association between coffee consumption and risk of diabetes, P < 0.001; for the goodness of fit of the model, P = 0.14; and for the likelihood ratio test compared with the nested linear model, P < 0.001.
To test whether the inverse association between coffee consumption and risk of type 2 diabetes was different for unadjusted and adjusted RRs, we performed a dose-response meta-analysis of the unadjusted data in 27 studies Supplementary Fig. 1. The spline curve of the unadjusted data was similar to that of the multivariable-adjusted data, indicating that adjustment for potential confounders minimally affected effect estimates for the association between coffee consumption and a lower risk of diabetes.
Comparison of Associations for Caffeinated and Decaffeinated Coffee
Both caffeinated and decaffeinated coffee consumption was inversely associated with risk of type 2 diabetes Supplementary Fig. 2. Compared with participants with the lowest level of caffeinated coffee consumption, the RR for incident type 2 diabetes was 0.74 (95% CI 0.67–0.81, I = 56%, P for heterogeneity = 0.005) for the highest category (median consumption 5 cups/day), 0.82 (0.75–0.91, I = 74%, P < 0.001) for the second highest category (3.5 cups/day), and 0.92 (0.89–0.96, I = 6.6%, P = 0.38) for the third highest category (1 cup/day). Compared with those with the lowest level of decaffeinated coffee consumption, the combined RR for incident type 2 diabetes was 0.80 (0.70–0.91, I = 62%, P = 0.001) for the highest category (4 cups/day), 0.95 (0.88–1.02, I = 53%, P = 0.02) for the second highest category (2 cups/day), and 0.98 (0.92–1.05, I = 62%, P = 0.003) for the third highest category (0.5 cups/day). Heterogeneity was shown for five of the six subgroups. Seven of 12 studies adjusted for caffeinated and decaffeinated coffee consumption simultaneously. The association was slightly stronger for caffeinated coffee consumption than for decaffeinated coffee consumption (P = 0.03 for the second highest group, P = 0.07 for the highest group) Supplementary Table 1.
We conducted a linear dose-response analysis for caffeinated and decaffeinated coffee consumption separately (11 studies). For a 1 cup/day increase in caffeinated coffee consumption, the RR for type 2 diabetes was 0.91 (95% CI 0.89–0.94), and for a 1 cup/day increase in decaffeinated coffee consumption, the RR was 0.94 (0.91–0.98, P for difference = 0.17). We performed a dose-response analysis between caffeine consumption and type 2 diabetes risk based on seven of the included studies and found that for every 140 mg/day (~1 cup/day coffee) higher caffeine consumption, the RR for type 2 diabetes was 0.92 (0.90–0.94). Of note, none of the included studies controlled for coffee intake when modeling caffeine intake and diabetes.
Stratified Analysis
In stratified analyses, the inverse associations between coffee consumption and risk of diabetes were similar by geographical region (U.S., Europe, and Asia), sex, and diabetes assessment method (P for interaction > 0.05 for all groups) Supplementary Table 1.
Sensitivity Analysis
For the dose-response analysis of total coffee consumption with diabetes, after we included the observation with extremely high coffee consumption, the results did not change. Significant heterogeneity was found for the highest and second highest total coffee consumption, which might be attributable to the heterogeneous amount of coffee consumption in these categories. The dose-response analysis accounted for the heterogeneous consumption amount of individual studies and showed an appropriate goodness of fit (P = 0.14).
Heterogeneity was also found in separate analyses of caffeinated and decaffeinated coffee consumption. In addition to considering different consumption amounts, we stratified the analyses by whether the studies included caffeinated and decaffeinated coffee consumption simultaneously in the same model. In these analyses, the heterogeneity at each level of caffeinated and decaffeinated coffee consumption decreased significantly, with even more inverse results for both caffeinated and decaffeinated coffee consumption Supplementary Fig. 3.
Publication Bias
The Egger test provided no evidence of publication bias at any levels of total coffee, caffeinated coffee, and decaffeinated coffee consumption Supplementary Table 2.
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