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Article

Coffee and Tea Consumption and Risk of Type 2 Diabetes in Older Australians

by
Tommy Hon Ting Wong
1,
George Burlutsky
2,
Bamini Gopinath
2,
Victoria M. Flood
3,4,5,
Paul Mitchell
5 and
Jimmy Chun Yu Louie
6,*
1
Victorian Cancer Registry, Cancer Council Victoria, Melbourne, VIC 3004, Australia
2
Department of Health Sciences, Macquarie University Hearing, Macquarie University, Macquarie Park, NSW 2113, Australia
3
University Centre for Rural Health, Northern Rivers, The University of Sydney, Camperdown, NSW 2050, Australia
4
School of Health Sciences, Faculty of Medicine Health, The University of Sydney, Camperdown, NSW 2050, Australia
5
Westmead Hospital, Western Sydney Local Health District, Westmead, NSW 2145, Australia
6
Discipline of Dietetics, Department of Allied Health, School of Health Sciences, Swinburne University of Technology, 1 John St, Hawthorn, VIC 3122, Australia
*
Author to whom correspondence should be addressed.
Diabetology 2025, 6(2), 12; https://doi.org/10.3390/diabetology6020012
Submission received: 11 December 2024 / Revised: 12 January 2025 / Accepted: 8 February 2025 / Published: 11 February 2025
(This article belongs to the Special Issue Dietary Patterns and Risk of Type 2 Diabetes)
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Abstract

Background: The prospective relationship between coffee and tea consumption and the risk of developing type 2 diabetes mellitus (T2DM) is seldom assessed in older adults. This study investigated the association between coffee and tea consumption and the 10-year incidence of T2DM in older Australian adults. Method: Data were collected from participants aged 49 years or above at baseline of the Blue Mountains Eye Study (n = 1668). Coffee and tea intakes were assessed using a validated food frequency questionnaire. T2DM was ascertained by the self-reported history, fasting blood glucose ≥ 7.0 mmol/L, or self-reported use of diabetes medication. Associations were assessed using discrete-time logistic regression, adjusting for lifestyle and demographic factors. Results: Compared to no consumption, coffee intake of 1 cup/day was associated with a lower risk of developing T2DM (multivariate-adjusted HR: 0.46, 95% CI: 0.23, 0.91) in the 10-year follow-up period. However, consumption of 2–3 cups/day (HR: 0.66, 95% CI: 0.37, 1.18) or ≥4 cups/day (HR: 1.04, 95% CI: 0.52, 2.08) showed no significant association. Tea consumption at any level was not significantly associated with T2DM incidence. Results were similar after excluding participants with implausible energy intake. Conclusions: In older adults, moderate coffee intake (1 cup/day) was associated with lower T2DM incidence, while higher coffee consumption and tea intake at any level were not. The lack of a dose-dependent effect in coffee consumption warrants further investigation. These findings should be verified in larger studies, considering different coffee and tea types and potential age-related and genetic factors.

1. Introduction

The number of older adults with type 2 diabetes mellitus (T2DM) is on a sharp rise globally, particularly among older adults. In 2017, individuals aged 60 or older accounted for up to 30% of adults with T2DM worldwide, a figure projected to double within 30 years [1]. By 2050, over 1.31 billion people are expected to have diabetes, with more than 10% prevalence in certain regions [2]. North Africa and the Middle East are anticipated to reach 16.8%, while Latin America and the Caribbean are projected to hit 11.3%. Additionally, nearly 44% of countries and territories (89 out of 204) are expected to see age-standardized rates exceeding 10%, reflecting the widespread and growing burden of this condition [2].
Aging is a well-known risk factor for T2DM due to insulin resistance and a decline in pancreatic beta cell function [3], commonly observed in older adults due to low-grade systemic inflammation, intermuscular adipose tissue deposition, and sarcopenia [4,5,6]. Compounded by other common comorbidities, such as frailty, physical inactivity, and malnutrition, T2DM is associated with frequent hospitalization and rapid functional decline among older adults [7,8]. It is imperative to identify ways to reduce the risk of T2DM in this vulnerable age group. Despite the significant burden of T2DM in this population, research specifically focusing on older adults remains limited, largely due to methodological challenges such as higher rates of comorbidities, medication use, and difficulties in maintaining long-term follow-up [9,10].
Both coffee and tea consumption have been related to a lower risk of T2DM. Coffee contains multiple potentially beneficial compounds, including chlorogenic acid, trigonelline, and caffeic acid, which have been shown to improve glucose metabolism by reducing glucose absorption in the intestine and improving insulin sensitivity [11,12]. Additionally, the high antioxidant content of coffee may help reduce oxidative stress and inflammation, which are implicated in T2DM development [11,12]. Similarly, tea contains polyphenols, particularly catechins in green tea and theaflavins in black tea, which may enhance insulin activity and protect pancreatic β-cells from oxidative damage [13,14]. Evidence from meta-analyses supports these potential protective effects. A meta-analysis of 30 prospective cohort and case–control studies found that the risk of developing T2DM decreased by 6% for each additional cup of coffee consumed per day, with the association remaining linear up to eight cups per day [15]. Similarly, an earlier meta-analysis of 15 cohort studies observed that a two-cup-per-day increment in tea intake was associated with a 4.6% reduction in the risk of developing T2DM among adults [16]. Nonetheless, previous studies mostly involved participants of a wide age range; thus, the results may not be specific to older adults. Data from the United States detected heterogeneity in terms of clinical manifestation in T2DM and comorbidities among people with different ages of diabetes onset [17], suggesting the need to identify protective factors against T2DM specific for different age groups.
Given the unique T2DM pathophysiology associated with older adults, exploring the association between tea and coffee intake and T2DM development in this age group is crucial. Therefore, this study aimed to assess the longitudinal associations of coffee and tea consumption with the incidence of T2DM in an older Australian population.

2. Method

2.1. Participants

The Blue Mountains Eye Study (BMES) examined vision, diet, and lifestyle factors among residents of three New South Wales towns in Australia: Katoomba, Leura, and Wentworth Falls. Details of the BMES have been previously reported [18,19]. The study recruited community-dwelling individuals aged 49 and above (born before 1 January 1943) at initial enrollment. The initial data collection phase (BMES I) occurred in 1992–1994 when participants underwent eye examinations at a community clinic and provided information about their physical measurements, lifestyle choices, and eating habits. The research team conducted two subsequent data collection waves, BMES II (1997–1999) and BMES III (2002–2004), gathering similar anthropometric, lifestyle, and dietary information. Participants were excluded from analysis if they had baseline T2DM, lacked coffee/tea consumption data, had missing covariate information, or had incomplete 10-year T2DM incidence data. The BMES was conducted in accordance with the Declaration of Helsinki guidelines, and the Human Ethics Committee of the Western Sydney Area Health Service approved all procedures. Written informed consent was obtained from all participants. As the present research constitutes a secondary analysis of anonymized data from the original BMES, no additional ethics approval was required.

2.2. Coffee and Tea Consumption Assessment

Researchers distributed a comprehensive 145-item food frequency questionnaire (FFQ) to participants before clinic appointments during each survey phase. This questionnaire, adapted from Willett et al.’s earlier version to reflect Australian dietary patterns and terminology [20], evaluated participants’ eating habits over the previous 12 months. For coffee, participants were asked about their consumption of different preparations: instant coffee, ground coffee (including espresso and other machine-brewed varieties), and decaffeinated coffee. Similarly, tea consumption was categorized as black tea (including English Breakfast and Earl Grey), green tea, and herbal/other teas. Given the data collection period (1992–1994) and the study population’s demographics, instant coffee and black tea were the predominant varieties consumed.
The FFQ, while comprehensive in measuring consumption frequency, had inherent limitations in capturing certain aspects of beverage consumption. Specifically, it did not collect detailed information about brewing methods, bean or tea leaf quality, roasting levels for coffee, or steeping times for tea, which could potentially influence the beverages’ bioactive compound content [21,22]. Additionally, the questionnaire did not gather information about the timing of consumption throughout the day, a common limitation of food frequency questionnaires [23].
Respondents indicated their consumption frequency for standard serving sizes using nine categories ranging from “never” to “four or more per day”. The questionnaire’s validity was confirmed through comparison with three separate 4-day weighed food records from a random subset of participants [24]. Both coffee and tea consumption were evaluated separately, using a standard cup size of 250 mL. The responses were later categorized into five groups: none (control group), less than daily, once daily, 2–3 times daily, and 4 or more times daily.

2.3. Ascertainment of T2DM

T2DM diagnosis was based on three criteria: self-reported diabetes history, use of diabetes medications, or fasting plasma glucose readings of 7.0 mmol/L or higher. Within one month of each interview, participants provided fasting blood samples. These samples were collected in specialized fluoride/oxalate tubes, underwent centrifugation for plasma separation, and glucose levels were determined using hexokinase methodology. New cases were identified as participants who developed T2DM during follow-up after having no diabetes at baseline.

2.4. Measurement of Potential Confounders

The study collected data on various confounding factors. Participants self-reported their smoking history, educational background, and family diabetes history. Physical activity levels were calculated using metabolic equivalents (METs) based on the International Physical Activity Questionnaire protocol [25], considering participants’ reported exercise patterns over two weeks. FFQ responses were organized into primary food categories based on their descriptions and nutrient profiles [26]. Teaspoons of table sugar added throughout the day were captured as a separate question, and in older Australian adults, this typically relates to sugars added to tea and coffee [27]. To account for overall dietary patterns and quality, the Total Diet Score (TDS) at baseline was calculated for each participant as previously described, with possible scores ranging from 0 to 20 [28,29]. Alcohol intake (in grams of alcoholic beverages) was extracted separately from FFQ responses.

2.5. Statistical Analysis

Hazard ratios were calculated using discrete-time logistic regression with a complementary log–log link, which enables the inclusion of coffee and tea intake recorded at subsequent follow-ups. The base model (Model 1) was adjusted for age and sex. Further adjustments for known confounders including smoking status (never, previous, and current), body mass index, obtained qualification after graduating from school (yes/no), family history of T2DM (yes/no), physical activity in METs, and alcohol consumption were made to the multivariate model (Model 2). Model 3 was further adjusted for TDS on top of Model 2 to examine the impact of diet quality on the observed association. The analysis with coffee intake as the exposure was also adjusted for tea intake and vice versa. Sensitivity analysis excluded participants with implausible energy intake, i.e., lower than 500 kcal or higher than 3500 kcal for females or lower than 800 kcal or higher than 4000 kcal for males [30]. All analyses were performed using R (version 4.4.1).

2.6. Declaration of Generative AI and AI-Assisted Technologies in the Writing Process

During the preparation of this work, the author used Claude 3.5 sonnet in order to improve the grammar and clarity of the text they drafted. After using this tool/service, the corresponding author reviewed and edited the content as needed and took full responsibility for the content of the publication.

3. Result

The participant flowchart is shown in Figure 1. Of the 3654 BMES participants recruited at baseline, 1668 were included in this analysis. A total of 129 (7.7%) participants developed T2DM during the follow-up period. Demographics of the included participants classified by coffee consumption groups are shown in Table 1. Those drinking the most coffee tended to be younger and had a higher proportion of current smokers than non-drinkers. Women made up a smaller percentage of the higher coffee consumption groups. Body mass index and TDS showed slight increases and decreases, respectively, with greater coffee intake. Tea consumption also differed across groups, with higher coffee drinkers less likely to consume tea regularly. The incidence of T2DM was higher among the heaviest coffee drinkers and lowest in those consuming moderate amounts of coffee.
The analysis results related to coffee consumption are shown in Table 2. No clear dose-dependent relationship (based on cups per day) between coffee consumption and the risk of developing T2DM was observed (ptrend = 0.419). In Model 3, individuals consuming one cup daily had a significantly lower risk (Hazard Ratio (HR): 0.46, 95% CI: 0.23, 0.91) than non-drinkers. However, no significant reduction in risk was observed for those drinking 2–3 cups per day (HR: 0.66, 95% CI: 0.37, 1.18) or four or more cups per day (HR: 1.04, 95% CI: 0.52, 2.08). Results of sensitivity analysis showed that excluding participants with implausible energy intake did not substantially alter the results.
Table 3 highlights key differences between tea consumption groups. Those who consumed more tea tended to be older and had a higher proportion of women. Non-smokers were more common with increased tea consumption, while current smoking was more frequent among non-tea drinkers. Those drinking the most tea had a higher rate of family history of T2DM and lower alcohol intake. Body mass index decreased slightly as tea consumption rose. Coffee intake was higher among those who drank little or no tea. T2DM incidence was similar across groups, with a slight dip in moderate tea drinkers.
The analysis results related to tea consumption are shown in Table 4. None of the tea consumption groups had a statistically significant risk reduction compared to non-drinkers, and no significant trend across increasing tea consumption levels was observed (ptrend = 0.641). Excluding participants with implausible energy intake did not materially change the results.

4. Discussion

In this population of older Australian adults with 10 years of follow-up, we observed that coffee consumption of 1 cup per day was inversely associated with the risk of developing T2DM compared to those who consumed coffee once per week or less. However, no significant association was observed for higher coffee or tea consumption levels at any level. These findings partially support the potential benefits of moderate coffee consumption for reducing the risk of T2DM among older adults. In contrast, the effect of tea consumption on T2DM in this age group requires further research.
The protective association against T2DM incidence, which we observed among participants with moderate coffee intake (1 cup per day), partially corroborates with previous research. However, our findings differ in some aspects from those of earlier studies. For instance, Nordestgaard et al. [31] observed an inverse association between coffee intake and T2DM incidence among Danish adults (mean age: 58 years old), with the protective effect extending to higher consumption levels. Similarly, Floegel et al. [32] reported an inverse association between coffee consumption and T2DM risk in a relatively younger German cohort (mean age: 49 years old), also showing benefits at higher intake levels.
Our results suggest that the protective association could be extended to populations at an older age but with some important differences. Unlike the studies above, we did not observe a significant association between high coffee intake (≥4 cups per day) and T2DM incidence. This discrepancy is primarily attributable to the limited number of BMES participants consuming coffee at this level. This substantially reduced our statistical power to detect potential associations in this consumption category. Specifically, the relatively small number of high-volume coffee consumers in our cohort made it challenging to estimate precise effect sizes and potentially masked true associations that might exist at higher consumption levels. This limitation particularly affects our ability to compare our findings with larger studies with sufficient participants across all consumption categories. Additionally, we found no significant reduction in risk for those drinking 2–3 cups per day, which contrasts with the dose-dependent relationships (defined as the association between the number of cups consumed per day and health outcomes) often reported in other studies [33,34].
Our findings reflect the intricate interplay of age-related physiological changes and lifestyle factors specific to older adults. Age-related physiological changes significantly influence how the body processes the bioactive compounds in coffee. These changes include reduced metabolic rate [35], altered drug metabolism [36], and decreased kidney function [37], potentially affecting the absorption, distribution, and elimination of compounds in coffee. In particular, older adults often experience changes in gastric acid secretion and intestinal motility [38] that may impact the absorption of polyphenols and other beneficial components in coffee and tea.
The age-related shift in gut microbiota composition presents another crucial factor [39,40]. Recent research indicates that changes in gut bacteria can substantially affect how dietary polyphenols are processed and utilized by the body [41,42], potentially altering their bioavailability and efficacy at higher doses [41,43,44]. This may explain why higher coffee consumption might not confer additional benefits in older adults, as these alterations in the gut microbiome can lead to different metabolic responses compared to younger populations, where dose-dependent effects are more commonly observed.
Lifestyle factors associated with coffee consumption in older adults introduce additional complexity. High-volume coffee consumers may be more likely to use caloric additions such as cream and sugar [45], potentially offsetting the beneficial effects of the bioactive compounds in coffee. Furthermore, older adults who consume large amounts of coffee might do so to combat fatigue or sleep issues, which are themselves risk factors for metabolic disorders [46]. While our analysis adjusted for several lifestyle factors, our models may not fully capture the intricate relationship between coffee consumption patterns and other health behaviors in older populations.
Nonetheless, several mechanisms could potentially explain the lack of a dose-dependent effect in our study. First, dietary factors may significantly influence the bioavailability of the beneficial compounds in coffee. The consumption of proteins, particularly dairy products commonly added to coffee, can bind to polyphenols and reduce their absorption [47,48]. Similarly, dietary fats may delay the absorption of chlorogenic acids and other bioactive compounds by delaying gastric emptying [49]. Second, while moderate coffee consumption may be protective, higher intake levels could introduce competing mechanisms that negate these benefits. For instance, higher caffeine intake might induce glucose intolerance acutely in some individuals [50], potentially offsetting the positive effects of other coffee components. Third, it is possible that the beneficial components in coffee, such as chlorogenic acids and other polyphenols, exert their maximal effect at relatively low doses. Once this threshold is reached (potentially at around one cup per day in our population), additional intake may not confer further benefits [11,12]. However, our limited ability to detect effects at higher consumption levels due to small sample sizes makes it difficult to establish or rule out dose–response relationships.
The mechanisms by which coffee intake might be protective against T2DM remain to be fully elucidated. Although coffee consumption induced glucose intolerance acutely [50], this adverse effect no longer persisted in individuals who consumed coffee every day for as short as two months in randomized controlled trials [51,52,53]. A previous study conducted by our group also found that coffee consumption of up to one cup per day was inversely associated with metabolic syndrome in BMES participants, which supported a protective effect of coffee on the metabolic health of older adults [54]. The main components in coffee, e.g., caffeine and chlorogenic acids, have been associated with benefits for glycaemic homeostasis. Caffeine could enhance thermogenesis and lipolysis [55], thus possibly combating the adiposity-induced insulin resistance commonly observed in older people [56]. Chlorogenic acids, a polyphenol, were found to stimulate the secretion of incretin hormones in human volunteers [57], promote glucose uptake in skeletal muscle, and inhibit intestinal glucose reabsorption in animal models [58,59].
Contrary to previous studies, we did not observe a significant association between tea intake and T2DM risk. This contrasts with a recent cohort study involving 0.5 million Chinese adults, which detected a modest reduction in the risk of T2DM associated with tea consumption [60]. A meta-analysis involving 15 earlier cohort studies also observed a modest inverse association between tea consumption and T2DM risk [16].
Several factors might explain this divergence from previous findings. First, the type of tea consumed likely plays a crucial role. While our study population predominantly consumed black tea, reflecting typical Australian dietary patterns of the 1990s, many previous studies showing protective effects were conducted in Asian populations where green tea consumption is more prevalent [61,62]. This distinction is important because green tea typically contains more catechins and other bioactive compounds than black tea [14]. The fermentation process used in black tea production alters the chemical composition of these compounds, potentially affecting their biological activity and health benefits [63]. Second, cultural differences in tea preparation and consumption patterns might contribute to these disparate findings. Australian tea-drinking customs often include adding milk and sugar, which could modify the bioavailability and effectiveness of the beneficial compounds of tea [64]. Furthermore, the timing and context of tea consumption (with or between meals) may differ across cultures, potentially affecting its metabolic impact. A previous meta-analysis of 27 randomized controlled trials supports this cultural variation, finding that the inverse associations between tea consumption and fasting glucose and insulin were significant only among Asian but not Caucasian populations [65]. Third, the age of our study population might interact with the potential benefits of tea in ways not observed in younger cohorts. Similar to coffee, age-related changes in metabolism, gut microbiota composition, and absorption efficiency could affect how the body processes and utilizes the bioactive compounds in tea. These physiological changes might be particularly relevant for tea consumption, as the absorption and metabolism of tea polyphenols depend on various factors that can be altered with ageing as discussed above.
One strength of this work is the inclusion of coffee and tea intake at both baseline and follow-ups, thus enabling a more accurate estimation of the associations. Another strength is using a validated FFQ in BMES, which yielded accurate dietary intake data for this analysis. This study is also one of the few to simultaneously assess the longitudinal associations between coffee, tea, and T2DM among older adults. This enabled the reporting of novel associations between either tea or coffee intake and T2DM incidence independent of the other.
Nonetheless, we caution the readers with several limitations when interpreting the findings. First, reliance on self-reported dietary intake through FFQs introduces potential measurement errors and recall bias, which are common challenges in nutritional epidemiology [66]. While our FFQ was validated against weighed food records in a subset of participants [24], the retrospective nature of dietary reporting over one year may have led to imprecise estimates of coffee and tea consumption. Participants might have had difficulty accurately recalling their average consumption patterns, particularly for beverages consumed irregularly or in varying amounts [23]. Additionally, social desirability bias might have influenced reporting [67], potentially leading to under-reporting high consumption levels or over-reporting moderate consumption patterns perceived as healthier. Second, our study focused on a white, Caucasian population, reflecting the demographic composition of the Blue Mountains region during the study period. While focusing on a single ethnic group is common in nutritional epidemiological studies, we acknowledge that this limits the generalizability of our findings to populations of other ethnicities. Future research could examine these associations in diverse ethnic groups to provide a broader understanding of these relationships. Third, while the BMES represents one of the few cohort studies focusing on elderly populations, the relatively small sample size may limit statistical power and generalizability. Fourth, residual confounding remains a significant concern despite our extensive adjustment for potential confounders. The FFQ did not capture specific information about coffee preparation methods (such as brewing time and temperature), coffee bean types and roasting levels, or tea varieties and steeping durations, all of which could affect the concentration of bioactive compounds. Furthermore, while we adjusted for added sugars in the diet, we lacked precise data on the type and amount of additives (such as milk, cream, or sugar) specifically used in coffee and tea, which could independently influence T2DM risk. The absence of this detailed dietary information may have affected our ability to detect true associations between beverage consumption and T2DM risk. Fifth, we did not assess heterogeneity due to different types of coffee and tea consumed due to low consumption of decaffeinated coffee and herbal tea. These limitations in capturing detailed beverage consumption patterns highlight the need for more comprehensive dietary assessment methods in future studies examining the relationship between coffee and tea consumption and T2DM risk in older adults.
Despite these limitations, our findings have important implications. From a public health perspective, our observation that moderate coffee consumption (one cup daily) may help prevent T2DM in older adults provides a practical and achievable intervention strategy. For clinical practice, healthcare providers should consider discussing moderate coffee consumption as part of T2DM prevention counseling while accounting for individual factors like sleep quality, anxiety, and medical conditions that caffeine might affect. The absence of additional benefits at higher consumption levels suggests that recommending increased intake beyond one cup daily may be unnecessary. These recommendations must be tailored to individual health profiles because older adults may have altered caffeine sensitivity and potential medication interactions. The inconclusive findings regarding tea consumption indicate the need for further research before making specific recommendations about tea for T2DM prevention in older Caucasian populations. Future research priorities should include investigating coffee preparation methods, bioactive compounds, and age-specific mechanisms while incorporating diverse populations of larger sample sizes and detailed dietary assessments to develop more targeted recommendations for T2DM prevention.
To conclude, we found that moderate coffee intake (one cup per day) could benefit T2DM risk reduction in older adults. In contrast, higher coffee consumption and tea intake at any level were not associated with T2DM risk in this population. The lack of a dose-dependent effect in coffee consumption warrants further investigation into the complex interplay of coffee constituents, individual physiology, and lifestyle factors. These findings should be verified in future studies with more participants and cases, particularly focusing on potential dose–response relationships, the effects of different types of coffee and tea, and the role of age-related factors in modifying these associations.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/diabetology6020012/s1, File S1: R script used to conduct the analyses.

Author Contributions

Conceptualization, T.H.T.W., V.M.F. and J.C.Y.L.; methodology, T.H.T.W., G.B., V.M.F. and J.C.Y.L.; formal analysis, T.H.T.W. and J.C.Y.L.; investigation, T.H.T.W. and J.C.Y.L.; resources, V.M.F. and P.M.; data curation, T.H.T.W. and G.B.; writing—original draft preparation, T.H.T.W.; writing—review and editing, T.H.T.W., B.G., V.M.F. and J.C.Y.L.; supervision, V.M.F. and J.C.Y.L.; project administration, V.M.F. and J.C.Y.L.; funding acquisition, V.M.F. and P.M. All authors have read and agreed to the published version of the manuscript.

Funding

The Blue Mountains Eye Study was funded by the Australian National Health and Medical Research Council, Canberra, Australia. No funding has been provided to support this secondary analysis.

Institutional Review Board Statement

The Blue Mountains Eye Study was conducted in accordance with the Declaration of Helsinki guidelines, and the Human Ethics Committee of the Western Sydney Area Health Service approved all procedures. As the present research constitutes a secondary analysis of anonymized data from the original BMES, no additional ethics approval was required.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the original Blue Mountains Eye Study.

Data Availability Statement

The data used in this study could be made available upon request and approval. Interested parties should contact Vicki Flood (vicki.flood@sydney.edu.au) to discuss. The R code used in this analysis is available as Supplementary File S1.

Acknowledgments

The authors would like to thank Joanna Russell of the University of Wollongong for providing data related to the Total Diet Score.

Conflicts of Interest

All authors have no conflicts of interest to disclose.

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Diabetology 06 00012 g001
Figure 1. Participant exclusion flowchart. Since some participants had missing data for more than one confounder, the number of participants with missing data is greater than the difference between participants present in at least one follow-up and the number of participants included in the analysis. BMI, body mass index. FFQ, food frequency questionnaire. METs, metabolic equivalents. T2DM, type 2 diabetes mellitus.
Figure 1. Participant exclusion flowchart. Since some participants had missing data for more than one confounder, the number of participants with missing data is greater than the difference between participants present in at least one follow-up and the number of participants included in the analysis. BMI, body mass index. FFQ, food frequency questionnaire. METs, metabolic equivalents. T2DM, type 2 diabetes mellitus.
Diabetology 06 00012 g001
Table 1. Lifestyle and demographic characteristics of included participants stratified by coffee consumption groups (n = 1668).
Table 1. Lifestyle and demographic characteristics of included participants stratified by coffee consumption groups (n = 1668).
VariablesCoffee Consumption Groups
Never<1 Cup/Day1 Cup/Day2–3 Cups/Day≥4 Cups/Day
n237449311488183
Age, years64.0 (8.5)64.3 (8.2)64.7 (8.4)62.8 (7.8)60.5 (7.2)
Female, %69.260.654.057.048.6
Smoking status, %
Never57.056.854.051.635.5
Previous32.535.237.337.933.3
Current10.58.08.710.531.1
Obtained qualification after high school, %44.738.829.935.540.4
Family history of T2DM, %19.820.923.223.420.8
Alcoholic beverages intake, g/day100.5 (263.9)167.1 (349.7)185.1 (307.6)182.2 (315.5)181.6 (339.9)
BMI, kg/m225.6 (4.2)26.0 (4.1)26.2 (4.2)26.4 (4.3)26.5 (4.4)
Total diet score (TDS)9.8 (2.1)9.5 (2.3)9.4 (2.2)9.4 (2.1)8.8 (1.9)
Tea consumption group, %
Never16.04.95.814.127.9
Up to 1 cup/week5.512.04.58.219.7
2–6 cups/week3.06.52.95.38.2
1 cup/day6.829.815.113.513.1
2–3 cups/day27.046.845.341.419.7
>4 cups/day41.88.926.417.411.5
T2DM incidence, %9.74.94.27.010.4
All values are mean (SD) for continuous variables and % for categorical variables. BMI, body mass index. T2DM, type 2 diabetes mellitus.
Table 2. Hazard ratio (95% CI) of type 2 diabetes mellitus development for different coffee consumption groups when compared with no consumption.
Table 2. Hazard ratio (95% CI) of type 2 diabetes mellitus development for different coffee consumption groups when compared with no consumption.
Coffee Consumption Groupptrend
Never<1 Cup/Day1 Cup/Day2–3 Cups/Day≥4 Cups/Day
ncase/ntotal22/23740/44913/31134/48819/183-
Model 11 (Ref)0.87 (0.50, 1.51)0.50 (0.25, 1.00)0.76 (0.43, 1.33)1.25 (0.65, 2.44)0.769
Model 21 (Ref)0.83 (0.48, 1.44)0.46 (0.23, 0.92)0.67 (0.37, 1.19)1.06 (0.53, 2.12)0.448
Model 31 (Ref)0.82 (0.47, 1.43)0.46 (0.23, 0.91)0.66 (0.37, 1.18)1.04 (0.52, 2.08)0.419
Sensitivity analysis *
ncase/ntotal22/23539/44613/31134/48619/183-
Model 11 (Ref)0.89 (0.51, 1.56)0.53 (0.26, 1.05)0.80 (0.45, 1.41)1.31 (0.67, 2.57)0.928
Model 21 (Ref)0.85 (0.48, 1.49)0.49 (0.24, 0.98)0.71 (0.39, 1.27)1.11 (0.55, 2.24)0.578
Model 31 (Ref)0.84 (0.48, 1.49)0.48 (0.24, 0.98)0.70 (0.39, 1.26)1.09 (0.54, 2.21)0.552
Model 1 adjusted for age and sex. Model 2 further adjusted for smoking status, physical activity, obtained qualification after graduation, family history of T2D, alcohol, and coffee intake. Model 3 was further adjusted for the total diet score on top of Model 2. * Participants with implausible energy intake were excluded from the sensitivity analysis.
Table 3. Lifestyle and demographic characteristics of included participants stratified by tea consumption groups (n = 1668).
Table 3. Lifestyle and demographic characteristics of included participants stratified by tea consumption groups (n = 1668).
VariablesTea Consumption Group
Never<1 Cup per Day1 Cup/Day2–3 Cups/Day≥4 Cups/Day
n198214182577497
Age, years61.9 (7.8)61.2 (7.5)63.2 (8.1)64.7 (8.6)63.9 (7.9)
Female, %51.555.655.557.264.2
Smoking status, %
Never45.552.350.552.555.9
Previous35.433.234.639.033.8
Current19.214.514.88.510.3
Obtained qualification after high school, %42.936.039.633.838.4
Family history of T2DM, %16.220.123.120.326.4
Alcoholic beverage intake, g/day211.6 (403.5)173.4 (327.5)255.1 (404.6)165.6 (307.2)115.9 (243.1)
BMI, kg/m226.9 (4.7)26.5 (4.1)26.2 (4.1)26.1 (4.3)25.8 (4.0)
Total diet score (TDS)9.2 (2.2)9.2 (2.0)9.3 (2.4)9.5 (2.1)9.6 (2.2)
Coffee consumption group, %
Never19.29.38.811.119.9
Up to 1 cup/week5.625.28.812.327.4
2–6 cups/week5.610.77.110.914.9
1 cup/day9.130.825.824.416.5
2–3 cups/day34.823.836.335.017.1
>4 cups/day25.89.813.26.24.2
T2DM incidence, %6.69.38.85.79.3
All values are mean (SD) for continuous variables and % for categorical variables. BMI, body mass index. T2DM, type 2 diabetes mellitus.
Table 4. Hazard ratio (95% CI) of type 2 diabetes mellitus development for different tea consumption groups compared with no consumption.
Table 4. Hazard ratio (95% CI) of type 2 diabetes mellitus development for different tea consumption groups compared with no consumption.
Tea Consumption Groupptrend
Never<1 Cup/Day1 Cup/Day2–3 Cups/Day≥4 Cups/Day
ncase/ntotal13/19821/21416/18233/57746/497-
Model 11 (Ref)1.43 (0.67, 3.02)1.43 (0.66, 3.13)1.00 (0.51, 1.99)1.36 (0.69, 2.66)0.670
Model 21 (Ref)1.53 (0.72, 3.25)1.69 (0.77, 3.71)1.18 (0.59, 2.37)1.51 (0.75, 3.02)0.645
Model 31 (Ref)1.53 (0.72, 3.26)1.70 (0.77, 3.72)1.18 (0.59, 2.37)1.50 (0.75, 3.02)0.641
Sensitivity analysis *
ncase/ntotal13/19821/21415/18033/57545/494-
Model 11 (Ref)1.43 (0.67, 3.02)1.35 (0.61, 2.97)1.01 (0.51, 1.99)1.33 (0.68, 2.61)0.698
Model 21 (Ref)1.52 (0.72, 3.23)1.59 (0.72, 3.53)1.18 (0.59, 2.38)1.50 (0.74, 3.01)0.654
Model 31 (Ref)1.53 (0.72, 3.24)1.60 (0.72, 3.55)1.19 (0.59, 2.38)1.49 (0.74, 3.00)0.651
Model 1 adjusted for age and sex. Model 2 further adjusted for smoking status, physical activity, obtained qualification after graduation, family history of T2D, alcohol, and coffee intake. Model 3 was further adjusted for the total diet score on top of Model 2. * Participants with implausible energy intake were excluded from the sensitivity analysis.
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Wong, T.H.T.; Burlutsky, G.; Gopinath, B.; Flood, V.M.; Mitchell, P.; Louie, J.C.Y. Coffee and Tea Consumption and Risk of Type 2 Diabetes in Older Australians. Diabetology 2025, 6, 12. https://doi.org/10.3390/diabetology6020012

AMA Style

Wong THT, Burlutsky G, Gopinath B, Flood VM, Mitchell P, Louie JCY. Coffee and Tea Consumption and Risk of Type 2 Diabetes in Older Australians. Diabetology. 2025; 6(2):12. https://doi.org/10.3390/diabetology6020012

Chicago/Turabian Style

Wong, Tommy Hon Ting, George Burlutsky, Bamini Gopinath, Victoria M. Flood, Paul Mitchell, and Jimmy Chun Yu Louie. 2025. "Coffee and Tea Consumption and Risk of Type 2 Diabetes in Older Australians" Diabetology 6, no. 2: 12. https://doi.org/10.3390/diabetology6020012

APA Style

Wong, T. H. T., Burlutsky, G., Gopinath, B., Flood, V. M., Mitchell, P., & Louie, J. C. Y. (2025). Coffee and Tea Consumption and Risk of Type 2 Diabetes in Older Australians. Diabetology, 6(2), 12. https://doi.org/10.3390/diabetology6020012

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