| Literature DB >> 34200398 |
Salwa Ali Albar1, Merfat Abdulrahman Almaghrabi1, Rawabi Ahmed Bukhari1, Rawan Hussein Alghanmi1, Maha Ali Althaiban1, Khaled A Yaghmour2.
Abstract
Information regarding the spread and effect of coffee and caffeine intake by individuals with type II diabetes remains unclear. This study aims to identify the amount and sources of habitual caffeine intake by individuals with type II diabetes and to investigate its association with other health outcomes, especially HbA1c. This is a cross-sectional survey involving 100 people medically defined as having type II diabetes comprising both genders, recruited from a care centre. All participants completed a caffeine semi-quantitative food frequency questionnaire (C-FFQ) to estimate their caffeine consumption, a two day 24-h recall, and a detailed questionnaire. The average caffeine intake was calculated from all sources and the differences in mean by gender were tested using a regression model (adjusted to important confounders). Regression models were used to verify the association between average caffeine intake on HbA1c and other health outcomes with adjustment for important confounders. A p value < 0.05 represented statistical significance. Arabic coffee (gahwa) and tea were the most common sources of caffeine among Saudi adults living with diabetes. Average caffeine intake for the whole sample was 194 ± 165 mg/day, which is 2.3 ± 2 mg/kg. There was an inverse association between caffeine intake and age: difference in mean -3.26 mg/year (95%CI: -5.34, -1.18; p = 0.003). Males had significantly higher consumption of caffeine compared to females: difference in mean 90.7 mg/day (95%CI: 13.8, 167.6; p = 0.021). No association was found between average caffeine intake and HbA1C or any other cardiovascular risk factors. This information can help public health practitioners and policy makers when assessing the risk of caffeine consumption among this vulnerable group.Entities:
Keywords: HbA1c; Saudi adults; caffeine consumption; cardiovascular risk factors; coffee; type II diabetes
Year: 2021 PMID: 34200398 PMCID: PMC8226783 DOI: 10.3390/nu13061960
Source DB: PubMed Journal: Nutrients ISSN: 2072-6643 Impact factor: 5.717
General characteristics of study participants by gender.
| General Characteristics | All Participants ( | Females | Males | ||||
|---|---|---|---|---|---|---|---|
| Mean | SD | Mean | SD | Mean | SD | ||
| Age * (years) | 56.2 | 14.0 | 57.1 | 14.4 | 55.3 | 13.7 | 0.650 |
| Height * (cm) | 161.9 | 8.1 | 157.4 | 7.0 | 166.5 | 6.3 | 0.001 |
| Weight * (kg) | 89.2 | 14.5 | 88.5 | 20.8 | 89.8 | 15.9 | 0.708 |
| BMI * (kg/m2) | 33.7 | 6.5 | 35.0 | 7.1 | 32.3 | 5.7 | 0.035 |
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| Normal weight | 6 | 6% | 3 | 6% | 3 | 6% | |
| Overweight | 26 | 26% | 10 | 20% | 16 | 32% | 0.038 |
| Obese | 68 | 68% | 37 | 74% | 31 | 62% | |
| Waist circumference * (cm) | 98 | 15 | 99 | 17 | 97 | 13 | 0.444 |
|
| 36 | 36% | 18 | 36% | 18 | 36% | 1.000 |
| Diabetes Diet (self-assessment of balanced diet) | 30 | 83% | 14 | 78% | 16 | 89% | 0.212 |
| Diabetes Diet and other diet e.g., low fat diet or low salt diet or for losing weight | 6 | 17% | 4 | 22% | 2 | 11% | |
| Duration of having diabetes (year) | 14 | 10 | 13 | 8 | 15 | 11 | 0.305 |
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| Oral antidiabetic drugs only | 37 | 37% | 21 | 42% | 16 | 32% | |
| Insulin | 22 | 22% | 9 | 18% | 13 | 26% | 0.490 |
| Oral antidiabetic drugs and Insulin | 41 | 41% | 20 | 40% | 21 | 42% | |
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| Total energy (Kcal) | 2392 | 610 | 2194 | 614 | 2589 | 544 | 0.001 |
| Protein (g) | 102 | 46 | 80 | 34 | 123 | 46 | 0.001 |
| Fat (g) | 77 | 34 | 70 | 34 | 83 | 34 | 0.053 |
| Energy from fat (Kcal) | 708 | 349 | 746 | 387 | 746 | 305 | 0.273 |
| Carbohydrate (g) | 318 | 95 | 303 | 106 | 333 | 81 | 0.121 |
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| Blood pressure (yes) | 60 | 60% | 33 | 66% | 27 | 54% | 0.221 |
| Cholesterol (yes) | 74 | 74% | 38 | 76% | 36 | 72% | 0.648 |
| Other disease (yes) | 28 | 28% | 16 | 32% | 12 | 24% | 0.373 |
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| Yes | 17 | 17% | 5 | 10% | 12 | 24% | 0.001 |
| I have given up | 23 | 23% | 1 | 2% | 22 | 44% | |
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| Never | 28 | 28% | 17 | 34% | 11 | 22% | 0.119 |
| Once a week | 21 | 21% | 14 | 28% | 7 | 14% | |
| Twice a week | 12 | 12% | 5 | 10% | 7 | 14% | |
| More than four times week | 39 | 39% | 14 | 28% | 25 | 50% | |
* Differences between genders were assessed by using an independent sample t-test. † Differences between the proportion of males and females in the categorical variables were assessed by using a Chi2 test.
Mean (SD) and median (IQR) of total caffeine intake (mg/day) by source and gender, and the tested mean differences between genders.
| Source of Caffeine | All Participants | Females | Males | Adjusted Difference in Means (95%CI) * | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| N | Mean | Median | N | Mean | Median | N | Mean | Median | |||
| Caffeine-FFQ (mg/day) | 100 | 194 (165) | 151 (81, 233) | 50 | 127 (107) | 99 (52, 181) | 50 | 261 (185.0) | 218(121, 345) | 90.70 (13.8, 167.6) | 0.021 |
| Caffeine/body weight (mg/kg) | 2.3 (2.0) | 1.8 (0.9, 2.8) | 50 | 1.5 (1.4) | 1.2 (0.7, 1.9) | 50 | 3.0 (2.4) | 2.3 (1.5, 3.4) | 1.29 (2.27, 0.35) | 0.011 | |
| Tea | 95 | 116(108) | 76 (44, 180) | 46 | 79 (75) | 72 (31, 103) | 49 | 150 (123) | 110(72, 187) | 31.51(21.77,84.80) | 0.243 |
| ratio of the geometric means (95%CI) † | |||||||||||
| Coffee | 52 | 94 (128) | 56 (10, 102) | 22 | 66 (77) | 47 (9, 94) | 30 | 114 (154) | 56 (18, 130) | 0.53 (0.22, 1.24) | 0.139 |
| Arabic coffee (Gahwa) | 95 | 8 (12) | 3 (1, 8) | 48 | 9 (12) | 4 (2, 9) | 47 | 7 (12) | 2 (1, 8) | 1.5 (0.67, 3.20) | 0.338 |
| Energy drink | 12 | 31(45) | 8 (5, 52) | 5 | 29 (47) | 8 (7, 11) | 7 | 33.5 (34) | 8 (3, 89) | 0.89 (0.01, 61.9) | 0.947 |
| Soft drink | 56 | 19 (31) | 8 (5, 13) | 28 | 14.5(20) | 8 (5, 13) | 28 | 24 (39) | 8 (5, 19) | 0.74 (0.36, 1.5) | 0.406 |
| Chocolate | 90 | 6 (11) | 2.3 (1, 5) | 45 | 6 (12) | 3 (1, 5) | 45 | 6 (11) | 2 (1, 5) | 1.9 (0.89, 4.1) | 0.654 |
N = number of consumers. * Differences between gender in mean caffeine consumption by sources were assessed by using regression model-1 with adjusting for BMI, age, smoking, and total energy intake (EI); † Transformed data, the difference was assessed using regression model-1 and after back-transformation the difference was the ratio of the sample geometric mean (female to male ratio).
Association between caffeine intake (100 mg/day) and HbA1C, cholesterol, triglyceride, and blood pressure for all participants and clustering by gender.
| Health Outcome | All Participants † | Female ‡ | Male ‡ | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| N | Mean (SD) | Change in Health Outcome/100 mg Caffeine * (95%CI) | N | Mean (SD) | Change in | N | Mean | Change in | ||||
| HbA1c | 100 | 8.5 (2.1) | 0.3 (−0.3, 0.3) | 0.866 | 50 | 8.5 (2.3) | 0.3 (−0.4, 1.0) | 0.348 | 50 | 8.6 (2.01) | −0.1 (−0.4, 0.3) | 0.661 |
| Cholesterol (mmol/L) | 85 | 172.6 (53.0) | 3.4 (−4.7, 11.7) | 0.400 | 40 | 172.5 (58.2) | 4.3 (−16.2, 24.8) | 0.672 | 45 | 172.8 (48.66) | 4.1(−4.8, 13.1) | 0.358 |
| HDL (mg/dL) | 81 | 47.7 (21.8) | 1.5 (−1.97, 5.02) | 0.389 | 39 | 50.6 (24.3) | 3.2 (−5.6, 11.9) | 0.464 | 42 | 44.9 (19.03) | 1.1 (−2.5, 4.9) | 0.519 |
| LDL (mg/dL) | 75 | 100.9 (45.6) | 0.72 (−6.4, 8.1) | 0.844 | 34 | 102.3 (48.3) | 9.9 (−7.5, 27.4) | 0.252 | 41 | 99.7(43.80) | −1.6 (−10.1, 6.9) | 0.706 |
| Triglyceride (mg/dL) | 87 | 137.5 (100.2) | 2.0 (−13.1, 17.1) | 0.791 | 42 | 141.9 (116.1) | −6.7 (−45.4, 31.8) | 0.724 | 45 | 133.4 (84.01) | 3.5 (−11.9, 19.1) | 0.645 |
| Blood pressure (mmHg) | ||||||||||||
| Diastolic | 96 | 71.0 (10.6) | −1.1 (−2.4, 0.33) | 0.135 | 48 | 68.4 (9.5) | −0.9 (−3.8, 2.0) | 0.529 | 48 | 73.5 (11.06) | −1.1 (−2.7, 0.6) | 0.194 |
| Systolic | 96 | 140.8(21.9) | −0.7 (−3.9, 2.4) | 0.646 | 48 | 139.7 (20.5) | −1.5 (−7.8, 4.7) | 0.624 | 48 | 141.9 (23.33) | −0.4 (−4.3, 3.64) | 0.855 |
N = number of participants’ complete information; * approximately 8-ounce cup of coffee closer to 80 to 100 mg caffeine. † The associations were assessed by using regression model-2 with adjusting for BMI, age, gender, smoking, and EI. ‡ The associations were assessed by using regression model-3 with adjusting for BMI, age, smoking, and EI.