| Literature DB >> 27544676 |
Caroline Nordenvall1,2, Viktor Oskarsson3, Alicja Wolk3.
Abstract
PURPOSE: Epidemiologic data on whether consumption of fruit and vegetables (FVs) decreases the risk of gallstone disease are sparse. Therefore, we examined the association between FV consumption and the 14-year risk of symptomatic gallstone disease (defined as occurrence of cholecystectomy) in a large group of middle-aged and elderly persons.Entities:
Keywords: Cohort study; Fruit consumption; Gallbladder disease; Vegetable consumption
Mesh:
Year: 2016 PMID: 27544676 PMCID: PMC5847035 DOI: 10.1007/s00394-016-1298-6
Source DB: PubMed Journal: Eur J Nutr ISSN: 1436-6207 Impact factor: 5.614
Hazard ratios of cholecystectomy by sex-specific quartiles of fruit and vegetable consumption
| Quartile of consumptiona |
| ||||
|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | ||
| No. of participants | 18,644 | 18,658 | 18,622 | 18,630 | – |
| No. of cases/person-years | 532/227,763 | 534/235,426 | 535/237,903 | 519/238,624 | – |
| Hazard ratio (95 % CI) | |||||
| Age- and sex-adjusted | 1.00 (ref) | 0.94 (0.83–1.06) | 0.92 (0.82–1.04) | 0.88 (0.78–0.99) | 0.036 |
| Multivariable-adjustedc | 1.00 (ref) | 0.96 (0.85–1.09) | 0.96 (0.85–1.09) | 0.95 (0.83–1.08) | 0.43 |
aSee Table 1 for range (servings/day) of sex-specific quartiles of fruit and vegetable consumption in men and women
bTest for trend was calculated by modeling the sex-specific quartiles of FV consumption as a continuous variable
cDerived from a Cox regression model that was adjusted for attained age during follow-up (time-axis), sex, education (≤12, >12 years), smoking status (never, past, current), alcohol drinking [never, past, current in < or ≥ the sex-specific median intake (g/day)], physical activity (<20, 20–40, >40 min of walking/day, corresponding to approximate tertiles), use of aspirin (no, yes), energy intake [sex-specific quartiles (kcal/day)], and coffee consumption (<2, 2–3, 4–5, ≥6 cups/day)
Age-standardized baseline characteristics by sex-specific quartiles of fruit and vegetable consumption
| Characteristicsa | Quartiles of consumption (servings/day) (median) | |||||||
|---|---|---|---|---|---|---|---|---|
| Men ( | Women ( | |||||||
| <2.4 (1.7) | 2.4–3.5 (3.0) | 3.6–5.1 (4.3) | >5.1 (6.5) | <3.3 (2.4) | 3.3–4.7 (4.0) | 4.8–6.6 (5.6) | >6.6 (8.3) | |
| No. of participants | 10,631 | 10,650 | 10,613 | 10,622 | 8013 | 8008 | 8009 | 8008 |
| Age (years) (mean) | 61.0 | 59.7 | 59.3 | 59.7 | 63.6 | 61.6 | 61.0 | 60.2 |
| Education >12 years (%) | 9.2 | 14.4 | 18.0 | 23.2 | 12.4 | 19.0 | 23.5 | 27.1 |
| Current smoker (%) | 33.7 | 24.4 | 21.4 | 18.3 | 27.7 | 19.8 | 17.0 | 14.0 |
| BMI (kg/m2) (mean) | 26.0 | 25.8 | 25.6 | 25.6 | 25.0 | 24.9 | 24.8 | 24.8 |
| Physical activity >40 min of walking/day (%) | 27.8 | 32.0 | 34.2 | 37.3 | 30.0 | 33.3 | 36.8 | 42.0 |
| Use of aspirin (%) | 35.7 | 38.2 | 38.0 | 38.0 | 50.2 | 51.9 | 51.4 | 50.8 |
| History of diabetes (%) | 10.4 | 9.7 | 8.5 | 9.9 | 4.3 | 4.2 | 4.1 | 4.7 |
| History of hyperlipidemia (%) | 16.6 | 16.5 | 17.0 | 16.2 | 8.6 | 8.2 | 8.9 | 9.1 |
| Ever used oral contraceptives (%) | – | – | – | – | 58.1 | 59.4 | 60.9 | 60.2 |
| Parity (mean) | – | – | – | – | 2.1 | 2.1 | 2.1 | 2.2 |
| Ever used HRT (%)b | – | – | – | – | 50.6 | 54.6 | 56.2 | 58.1 |
| Daily intake (mean) | ||||||||
| Alcohol (g)c | 15.4 | 15.0 | 15.0 | 14.9 | 6.4 | 6.7 | 6.7 | 6.9 |
| Coffee (cups) | 3.7 | 3.5 | 3.4 | 3.3 | 3.2 | 3.1 | 3.0 | 3.0 |
| Energy (kcal) | 2390 | 2586 | 2714 | 2992 | 1513 | 1680 | 1790 | 2026 |
BMI body mass index, HRT hormone replacement therapy
aMeans and percentages were calculated for men and women with complete data. The percentage of missingness was 0.3 % for education, 1.5 % for smoking status, 3.5 % for BMI, 8.6 % for physical activity, 9.9 % for use of aspirin, 1.0 % for use of oral contraceptives, 5.8 % for use of HRT, 2.4 % for alcohol intake, and 4.9 % for coffee consumption
bCalculated for postmenopausal women
cCalculated for current drinkers
Fig. 1Time-varying hazard ratios of cholecystectomy for the highest compared with the lowest quartile of fruit and vegetable consumption in women, according to attained age during follow-up (time-axis). The figure illustrates time-varying hazard ratios and 95 % CI for the highest compared with the lowest quartile of fruit and vegetable consumption (Y-axis) according to attained age (X-axis). Data were derived from a Cox regression model that included an interaction term between fruit and vegetable consumption (in quartiles) and attained age (as a continuous variable, modeled using 3-knot restricted cubic splines). Estimates were adjusted for the same co-variables as those in Table 2