| Literature DB >> 22666334 |
Geertruida J van Woudenbergh, Anneleen Kuijsten, Dagmar Drogan, Daphne L van der A, Dora Romaguera, Eva Ardanaz, Pilar Amiano, Aurelio Barricarte, Joline W J Beulens, Heiner Boeing, H Bas Bueno-de-Mesquita, Christina C Dahm, M-Doleres Chirlaque, Francoise Clavel, Francesca L Crowe, Piia-Piret Eomois, Guy Fagherazzi, Paul W Franks, Jytte Halkjaer, Kay T Khaw, Giovanna Masala, Amalia Mattiello, Peter Nilsson, Kim Overvad, J Ramón Quirós, Olov Rolandsson, Isabelle Romieu, Carlotta Sacerdote, María-José Sánchez, Matthias B Schulze, Nadia Slimani, Ivonne Sluijs, Annemieke M W Spijkerman, Giovanna Tagliabue, Anne Tjønneland, Rosario Tumino, Nita G Forouhi, Stephen Sharp, Claudia Langenberg, Edith J M Feskens, Elio Riboli, Nicholas J Wareham.
Abstract
BACKGROUND: In previous meta-analyses, tea consumption has been associated with lower incidence of type 2 diabetes. It is unclear, however, if tea is associated inversely over the entire range of intake. Therefore, we investigated the association between tea consumption and incidence of type 2 diabetes in a European population. METHODOLOGY/PRINCIPALEntities:
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Year: 2012 PMID: 22666334 PMCID: PMC3364250 DOI: 10.1371/journal.pone.0036910
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Figure 1Tea consumption based on data from a food frequency questionnaire in the sub-cohort of the EPIC-InterAct project by country (n = 15,227).
Bar represents median (p25–p75); error line represents p5 till p95.
Characteristics of the sub-cohort of the EPIC-InterAct project by categories of tea consumption (n = 15,227).
| None | >0-<1 | 1-<4 | ≥4 | |
| (cups/day) | (cups/day) | (cups/day) | ||
| (n = 5,458) | (n = 4,032) | (n = 3,444) | (n = 2,293) | |
| Age (years) | 51.7 (8.6) | 51.4 (9.1) | 53.0 (9.7) | 54.7 (8.8) |
| Body mass index (kg/m | 27.0 (4.3) | 25.8 (4.0) | 25.5 (4.0) | 25.0 (3.8) |
| Male (%) | 40.5 | 41.3 | 32.7 | 33.6 |
| Country (%) | ||||
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| 83.0 | 7.5 | 9.5 | 0 |
|
| 43.1 | 44.2 | 12.8 | 0 |
|
| 33.6 | 30.5 | 28.2 | 7.7 |
|
| 36.7 | 21.1 | 27.4 | 15.1 |
|
| 17.3 | 38.8 | 9.8 | 34.1 |
|
| 6.1 | 39.6 | 36.5 | 17.8 |
|
| 8.3 | 18.7 | 42.1 | 31.0 |
|
| 5.2 | 8.9 | 39.0 | 46.9 |
| Smoking (% current) | 31.9 | 27.5 | 19.6 | 18.8 |
| Education level (% high) | 13.7 | 21.7 | 25.3 | 28.8 |
| Physical activity (% inactive) | 31.6 | 20.1 | 20.4 | 15.6 |
| Hypertension (%) | 17.5 | 19.1 | 20.3 | 17.4 |
| Hyperlipidaemia (%) | 17.9 | 15.8 | 17.0 | 10.3 |
| Family history of diabetes (%) | 13.9 | 17.1 | 16.9 | 17.9 |
| Stroke (%) | 0.7 | 0.9 | 1.1 | 0.7 |
| Angina Pectoris (%) | 1.3 | 2.4 | 3.1 | 2.4 |
| Myocardial infarct (%) | 1.1 | 1.4 | 1.6 | 1.7 |
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| Total energy (kcal/d) | 2188 (662) | 2140 (645) | 2067 (591) | 2124 (603) |
| Protein (energy%) | 18.0 (3.2) | 16.4 (2.8) | 16.5 (3.1) | 16.6 (2.9) |
| Fat (energy%) | 35.4 (6.1) | 34.6 (5.7) | 34.6 (5.8) | 34.0 (5.6) |
| Saturated fatty acids | 12.4 (3.6) | 13.6 (3.3) | 13.7 (3.3) | 13.8 (3.1) |
| Mono-unsaturated fatty acids | 14.6 (3.7) | 13.0 (3.1) | 12.3 (3.0) | 11.3 (2.2) |
| Poly-unsaturated fatty acids | 5.6 (2.1) | 5.2 (1.6) | 5.8 (1.8) | 5.9 (1.8) |
| Carbohydrate (energy%) | 42.2 (7.2) | 44.7 (6.9) | 45.1 (6.8) | 45.5 (6.7) |
| Fiber (g/d) | 22.7 (8.1) | 22.1 (7.4) | 22.4 (7.2) | 24.6 (8.0) |
| Alcohol (%>24 g/d) | 22.6 | 19.9 | 15.1 | 15.5 |
| Coffee (g/d) | 154 (60–400) | 400 (130–700) | 363 (125–525) | 375 (86–500) |
| Soft drinks (g/d) | 0 (0–29) | 16 (0–86) | 14 (0–90) | 16 (0–90) |
| Juices (g/d) | 1 (0–25) | 22 (3–94) | 40 (4–120) | 29 (3–100) |
| Milk (g/d) | 180 (61–300) | 138 (25–271) | 150 (25–295) | 193 (36–387) |
Values are expressed as Mean (Standard Deviation), Median (p25–p75), or percentage.
Based on n = 13,345, because information about hyperlipidemia was not collected in one center of Sweden.
Based on n = 8,802, because information about family history of diabetes was not collected in Italy, Spain, one center of Germany, and one center of the United Kingdom.
Based on n = 14,262, because information about a history of stroke was not collected in one center of Sweden.
Based on n = 10,168, because information about a history of angina was not collected in Sweden, The Netherlands, and one center of Germany.
Hazard Ratios (HR) and 95% confidence intervals (95%CI) for incident type 2 diabetes by categories of tea consumption in cups per day (n = 26,039).
| Crude | Model 1 | Model 2 | Model 3 | Model 4 | |||||||||
| N total | Cases | Median | HR | (95% CI) | HR | (95% CI) | HR | (95% CI) | HR | (95% CI) | HR | (95% CI) | |
| 0 | 9,499 | 4,389 | 0 | 1 | 1 | 1 | 1 | 1 | |||||
| >0-<1 | 7,060 | 3,197 | 0.23 | 0.89 | (0.80, 0.99) | 0.93 | (0.81, 1.07) | 0.96 | (0.84, 1.10) | 0.97 | (0.85, 1.10) | 1.03 | (0.91, 1.16) |
| 1-<4 | 5,751 | 2,437 | 2.00 | 0.77 | (0.66, 0.90) | 0.83 | (0.69, 0.99) | 0.85 | (0.71, 1.01) | 0.84 | (0.72, 0.98) | 0.93 | (0.81, 1.05) |
| ≥4 | 3,729 | 1,518 | 6.84 | 0.63 | (0.50, 0.80) | 0.68 | (0.52, 0.90) | 0.72 | (0.53, 0.96) | 0.70 | (0.54, 0.90) | 0.84 | (0.71, 1.00) |
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HR and 95%CI were derived from the modified Cox proportional hazard model by age at baseline and are based on pooled estimates from country specific analyses using a random effects meta-analysis.
Model 1: sex, smoking status, physical activity level, and education level.
Model 2: additional to model 1: intake of energy, protein, carbohydrates, saturated fatty acids, mono-unsaturated fatty acids, poly-unsaturated fatty acids, alcohol, and fiber.
Model 3: additional to model 2: intake of coffee, juices, soft-drinks, and milk.
Model 4: additional to model 3: body mass index.
Figure 2Association between tea consumption as a categorical variable (>0-<1 vs. 0, 1-<4 vs. 0, ≥4 vs. 0 cups/d) based on data from a food frequency questionnaire and risk of type 2 diabetes (n = 26,039).
Country-specific Hazard Ratios (HR) and 95% Confidence Intervals (95%CI) were pooled using random effects meta-analyses. HR were adjusted for sex, smoking status, physical activity level, education level, intake of energy, protein, carbohydrates, saturated fatty acids, mono-unsaturated fatty acids, poly-unsaturated fatty acids, alcohol, fiber, coffee, juices, soft-drinks, milk, and body mass index.
Figure 3Association between tea consumption based on data from a food frequency questionnaire and risk of type 2 diabetes obtained by spline regression with 3 knots (1, 4, 7 cups per day) and 0 cups per day as reference (n = 26,039).
Dotted lines represent 95% confidence intervals (95%CI). P non-linearity = 0.20. Hazard ratios were adjusted for sex, smoking status, physical activity level, education level, intake of energy, protein, carbohydrates, saturated fatty acids, mono-unsaturated fatty acids, poly-unsaturated fatty acids, alcohol, fiber, coffee, juices, soft-drinks, milk, and body mass index.