| Literature DB >> 35348601 |
Qingqing Cai1,2, Ming-Jie Duan1, Louise H Dekker1, Juan Jesús Carrero3, Carla Maria Avesani4, Stephan J L Bakker1, Martin H de Borst1, Gerjan J Navis1.
Abstract
BACKGROUND: Ultraprocessing makes food products more convenient, appealing, and profitable. Recent studies show that high ultraprocessed food (UPF) intake is associated with cardiometabolic diseases.Entities:
Keywords: chronic kidney disease; eGFR change; Lifelines; kidney function decline; ultraprocessed foods
Mesh:
Year: 2022 PMID: 35348601 PMCID: PMC9257475 DOI: 10.1093/ajcn/nqac073
Source DB: PubMed Journal: Am J Clin Nutr ISSN: 0002-9165 Impact factor: 8.472
Baseline characteristics of participants according to the sex-specific quartiles of UPF consumption in the Lifelines cohort[1]
| Quartiles of UPF consumption | ||||||
|---|---|---|---|---|---|---|
| Total ( | Q1 ( | Q2 ( | Q3 ( | Q4 ( |
| |
| Demographics | ||||||
| Age, years | 45.8 ± 12.6 | 52.0 ± 11.5 | 48.4 ± 11.6 | 44.7 ± 11.4 | 38.3 ± 11.8 | <0.001 |
| Sex, %, female | 58.4 | 58.4 | 58.4 | 58.4 | 58.4 | — |
| Food intake | ||||||
| Proportion of UPF in the diet, % of grams/day | 37.7 ± 12.3 | 23.9 ± 4.8 | 32.7 ± 3.2 | 40.2 ± 3.4 | 54.1 ± 8.5 | <0.001 |
| Range of UPF proportion in the diet, % | ||||||
| Female | 0.1–99.9 | 0.1–27.0 | 27.0–34.2 | 34.2–42.9 | 42.9–99.9 | <0.001 |
| Male | 0.1–94.5 | 0.1–32.1 | 32.1–39.2 | 39.2–47.3 | 47.3–94.5 | <0.001 |
| Mediterranean diet score | 4.2 ± 1.7 | 4.8 ± 1.6 | 4.3 ± 1.6 | 4.0 ± 1.6 | 3.6 ± 1.5 | <0.001 |
| Total energy intake, kcal/day | 2075.6 ± 606.8 | 1825.4 ± 520.4 | 2050.3 ± 552.9 | 2165.2 ± 592.2 | 2261.8 ± 663.0 | <0.001 |
| Total protein intake, g/day | 75.9 ± 20.3 | 71.1 ± 18.8 | 76.5 ± 19.2 | 78.4 ± 20.2 | 77.8 ± 22.1 | <0.001 |
| Total fat intake, g/day | 82.4 ± 29.3 | 70.2 ± 24.6 | 81.4 ± 26.7 | 87.2 ± 28.9 | 90.7 ± 32.2 | <0.001 |
| Total carbohydrate intake, g/day | 232.7 ± 72.9 | 201.6 ± 63.8 | 227.5 ± 66.0 | 242.0 ± 69.9 | 259.6 ± 78.5 | <0.001 |
| Total alcohol intake, g/day | 4.0 (0.9–10.4) | 5.8 (1.2–11.7) | 5.2 (1.2–10.8) | 3.9 (0.9–10.1) | 3.2 (0.7–9.7) | <0.001 |
| Clinical factors | ||||||
| eGFR, mL/min/1.73 m2 | 95.9 ± 14.3 | 92.0 ± 13.3 | 94.0 ± 13.5 | 96.4 ± 14.0 | 101.2 ± 14.7 | <0.001 |
| BMI, kg/m2 | 26.0 ± 4.2 | 26.0 ± 3.9 | 26.0 ± 3.9 | 26.0 ± 4.2 | 26.0 ± 4.6 | 0.224 |
| Cholesterol, mmol/L | 5.12 ± 1.00 | 5.27 ± 1.01 | 5.20 ± 1.00 | 5.10 ± 0.99 | 4.91 ± 0.97 | <0.001 |
| Triglycerides, mmol/L | 1.17 ± 0.78 | 1.14 ± 0.75 | 1.16 ± 0.75 | 1.17 ± 0.77 | 1.20 ± 0.86 | <0.001 |
| Diabetes, % | 3.1 | 3.9 | 3.2 | 3.0 | 2.3 | <0.001 |
| Hypertension, % | 22.0 | 26.7 | 23.1 | 21.1 | 17.2 | <0.001 |
| Cardiovascular disease, % | 2.6 | 4.0 | 2.7 | 2.3 | 1.6 | <0.001 |
| Health-related behaviors | ||||||
| Physical activity, minutes/week | 190 (60–365) | 240 (90–420) | 210 (80–375) | 180 (60–360) | 170 (60–345) | <0.001 |
| Smoker, % | 16.6 | 13.9 | 15.1 | 16.7 | 20.5 | <0.001 |
| Education, % | ||||||
| Low | 28.7 | 29.8 | 29.1 | 28.4 | 27.4 | <0.001 |
| Middle | 39.9 | 34.4 | 38.0 | 40.8 | 46.5 | — |
| High | 31.0 | 35.2 | 32.4 | 30.5 | 25.8 | — |
| Unknown/no answer | 0.4 | 0.6 | 0.5 | 0.4 | 0.3 | — |
Data are presented as mean ± SD, median (IQR) or percentage, as appropriate. Mediterranean diet scores vary between 0 and 9. eGFR, estimated glomerular filtration rate; Q, quartile; UPF, ultraprocessed food.
Association between composite kidney outcome and UPF consumption by logistic regression analysis[1]
| Per 10% increment of UPF consumption OR (95% CI) | |||||||
|---|---|---|---|---|---|---|---|
| Sex-specific quartiles of UPF consumption, OR (95% CI) | |||||||
| Q1 | Q2 | Q3 | Q4 |
|
| ||
| Events, | 864 (4.4%) | 653 (3.3%) | 560 (2.9%) | 393 (2.0%) | <0.001 | — | — |
| Model 1 | 1.00 | 0.99 (0.90–1.11) | 1.19 (1.06–1.33) | 1.41 (1.23–1.60) | <0.001 | 1.15 (1.11–1.20) | <0.001 |
| Model 2 | 1.00 | 0.99 (0.88–1.11) | 1.12 (0.99–1.27) | 1.35 (1.17–1.55) | <0.001 | 1.13 (1.08–1.19) | <0.001 |
| Model 3 | 1.00 | 0.98 (0.88–1.10) | 1.11 (0.98–1.26) | 1.33 (1.15–1.53) | <0.001 | 1.13 (1.08–1.18) | <0.001 |
| Model 4 | 1.00 | 0.97 (0.86–1.08) | 1.07 (0.95–1.22) | 1.27 (1.09–1.47) | 0.003 | 1.11 (1.06–1.17) | <0.001 |
Model 1 was adjusted for age and sex. Model 2 was adjusted for the variables in model 1 plus baseline eGFR, diabetes, hypertension, cardiovascular disease, physical activity, smoking, total energy intake, and education level. Model 3 was adjusted for the variables in model 2 plus Mediterranean diet score. Model 4 was adjusted for the variables in model 3 plus energy-adjusted protein intake, energy-adjusted carbohydrate intake, and energy-adjusted fat intake. eGFR, estimated glomerular filtration rate; Q, quartile; UPF, ultraprocessed food.
Association between annual change in eGFR and UPF consumption by linear regression analysis[1]
| Per 10% increment of UPF consumption β (95% CI) | |||||||
|---|---|---|---|---|---|---|---|
| Sex-specific quartiles of UPF consumption, β (95% CI) | |||||||
| Q1 | Q2 | Q3 | Q4 |
|
| ||
| Annual change in eGFR, mL/min/1.73 m2 | −2.07 (−3.74 to −0.72) | −2.15 (−3.83 to −0.74) | −2.25 (−3.99 to −0.81) | −2.46 (−4.30 to −0.93) | <0.001 | — | — |
| Model 1 | 1.00 | −0.03 (−0.08 to 0.03) | −0.09 (−0.14 to −0.03) | −0.23 (−0.28 to −0.17) | <0.001 | −0.08 (−0.10 to −0.06) | <0.001 |
| Model 2 | 1.00 | −0.08 (−0.13 to −0.02) | −0.16 (−0.21 to −0.10) | −0.29 (−0.34 to −0.23) | <0.001 | −0.10 (−0.12 to −0.08) | <0.001 |
| Model 3 | 1.00 | −0.06 (−0.12 to −0.01) | −0.14 (−0.19 to −0.08) | −0.26 (−0.31 to −0.20) | <0.001 | −0.09 (−0.11 to −0.07) | <0.001 |
| Model 4 | 1.00 | −0.04 (−0.09 to 0.02) | −0.09 (−0.14 to −0.03) | −0.17 (−0.23 to −0.11) | <0.001 | −0.06 (−0.08 to −0.04) | <0.001 |
Model 1 was adjusted for age and sex. Model 2 was adjusted for the variables in model 1 plus baseline eGFR, diabetes, hypertension, cardiovascular disease, physical activity, smoking, total energy intake, and education level. Model 3 was adjusted for the variables in model 2 plus Mediterranean diet score. Model 4 was adjusted for the variables in model 3 plus energy-adjusted protein intake, energy-adjusted carbohydrate intake, and energy-adjusted fat intake. eGFR, estimated glomerular filtration rate; Q, quartile; UPF, ultraprocessed food.
FIGURE 1Subgroup analyses of the associations between UPF consumption and composite kidney outcomes. ORs are for participants who reached incident CKD or an eGFR decline ≥ 30%, per 10% increment of UPF consumption. The multivariable logistic regression model adjusted for age, sex, baseline eGFR, diabetes, hypertension, cardiovascular disease, physical activity, smoking, total energy intake, education level, energy-adjusted protein intake, energy-adjusted carbohydrate intake, energy-adjusted fat intake, and MDS. CKD, chronic kidney disease; eGFR, estimated glomerular filtration rate; MDS, Mediterranean diet score; UPF, ultraprocessed food.
FIGURE 2Subgroup analyses of the association between UPF consumption and annual change in eGFR. Regression coefficient (β) represents the annual change in eGFR per 10% increment of UPF consumption. Linear regression model adjusted for age, sex, baseline eGFR, diabetes, hypertension, cardiovascular disease, physical activity, smoking, total energy intake, education level, energy-adjusted protein intake, energy-adjusted carbohydrate intake, energy-adjusted fat intake, and MDS. eGFR, estimated glomerular filtration rate; MDS, Mediterranean diet score; UPF, ultraprocessed food.