| Literature DB >> 28532405 |
Geum Hee Kim1,2, Sang Won Shin3, Juneyoung Lee4, Jun Hyun Hwang5, Soon-Woo Park5, Jin Soo Moon6, Hyun Jung Kim2, Hyeong Sik Ahn7.
Abstract
BACKGROUND: The impact of meat consumption on high blood pressure (HBP) and obesity in children and adolescents is a subject of debate. The aim of this study was thus to evaluate the association between meat consumption and both HBP and obesity in this group.Entities:
Keywords: Children and adolescents; High blood pressure; Meat consumption; Obesity
Mesh:
Year: 2017 PMID: 28532405 PMCID: PMC5441095 DOI: 10.1186/s12937-017-0252-7
Source DB: PubMed Journal: Nutr J ISSN: 1475-2891 Impact factor: 3.271
Subject characteristics according to frequency of meat consumption per week
| Merged 2011-2015a | Consumption of meat per week | |||||
|---|---|---|---|---|---|---|
| Variables | <1 | 1–2 | 3–5 | >5 | ||
|
|
| |||||
| Subjects | 136,739 (100) | 4,801 (3.4) | 70,193 (51.8) | 48,538 (37.1) | 10,165 (7.7) | <0.001 |
| Girls | 64,760 (47.7) | 2,428 (3.6) | 33,992 (53.1) | 22,656 (36.2) | 4,456 (7.1) | <0.001 |
| Boys | 71,979 (52.3) | 2,373 (3.1) | 36,201 (50.7) | 25,882 (37.9) | 5,709 (8.3) | <0.001 |
| HBP | 9,918 (7.7) | 387 (8.2) | 5,190 (7.7) | 3,610 (7.8) | 731 (7.2) | <0.001 |
| Systolic HBP | 6,075 (4.8) | 259 (5.6) | 3,287 (5.0) | 2,036 (4.6) | 405 (4.3) | <0.001 |
| Diastolic HBP | 6,704 (5.3) | 245 (5.4) | 3,302 (5.2) | 2,458 (5.4) | 520 (5.1) | <0.001 |
| Obesity, | 9,528 (7.6) | 399 (9.1) | 5,337 (8.2) | 3,203 (6.9) | 589 (6.3) | <0.001 |
| 9 years | Anthropometric characteristics | |||||
|
| Height, cm | 138.80 (0.2) | 138.90 (0.1) | 138.61 (0.1) | 139.10 (0.3) | 0.007 |
| BMI, kg/m2 | 18.53 (0.1) | 18.46 (0.0) | 18.34 (0.0) | 18.29 (0.1) | <0.001 | |
| Obesity, | 138 (9.8) | 1,736 (7.9) | 694 (7.0) | 53 (6.2) | 0.001 | |
| Blood pressure | ||||||
| Systolic BP, mmHg | 99.64 (0.4) | 99.00 (0.2) | 99.13 (0.3) | 98.97 (0.6) | 0.004 | |
| Diastolic BP, mmHg | 60.48 (0.3) | 60.22 (0.2) | 60.44 (0.2) | 60.08 (0.6) | 0.114 | |
| HBP, | 106 (7.1) | 1,576 (6.9) | 657 (6.6) | 58 (6.4) | <0.001 | |
| 12 years | Anthropometric characteristics | |||||
|
| Height, cm | 156.99 (0.2) | 157.28 (0.1) | 157.51 (0.1) | 157.92 (0.2) | <0.001 |
| BMI, kg/ m2 | 20.59 (0.1) | 20.48 (0.0) | 20.14 (0.0) | 20.13 (0.1) | <0.001 | |
| Obesity, | 163 (8.5) | 2,117 (8.1) | 953 (6.0) | 128 (5.5) | 0.001 | |
| Blood pressure | ||||||
| Systolic BP, mmHg | 105.08 (0.4) | 105.22 (0.2) | 105.17 (0.2) | 105.33 (0.3) | 0.327 | |
| Diastolic BP, mmHg | 63.32 (0.2) | 63.33 (0.1) | 63.39 (0.1) | 63.20 (0.2) | 0.204 | |
| HBP, | 172 (7.9) | 2,023 (7.7) | 1,111 (7.4) | 158 (6.6) | <0.001 | |
| 15 years | Anthropometric characteristics | |||||
|
| Height, cm | 165.72 (0.4) | 166.31 (0.2) | 166.38 (0.2) | 166.71 (0.2) | 0.007 |
| BMI, kg/ m2 | 21.96 (0.1) | 21.90 (0.0) | 21.74 (0.0) | 21.64 (0.0) | <0.001 | |
| Obesity, | 98 (9.2) | 1,484 (8.6) | 1,556 (7.4) | 408 (6.6) | 0.001 | |
| Blood pressure | ||||||
| Systolic BP, mmHg | 109.21 (0.5) | 109.29 (0.2) | 109.00 (0.2) | 108.71 (0.3) | 0.004 | |
| Diastolic BP, mmHg | 65.55 (0.3) | 65.70 (0.1) | 65.55 (0.1) | 65.28 (0.2) | 0.114 | |
| HBP, | 109 (10.2) | 1,591 (8.8) | 1,842 (8.7) | 515 (7.5) | <0.001 | |
aCross-sectional data from the Korea School Health Examination Survey (2011–2015, 1761 schools)
b P-value, using chi-squared test for n (%), ANOVA for mean (standard error of the mean, SEM)
cUnweighted sample size and weighted percentage. In addition, sample sizes vary because of missing data
Fig. 1Prevalence of high blood pressure according to the frequency of meat consumption. By age (9, 12, and 15 years), the weighted percentage of systolic and diastolic high blood pressure (HBP) in subjects with no excess weight (Panel a: systolic HBP, Panel b: diastolic HBP, n = 116,475) and with obesity (Panel c: systolic HBP, Panel d: diastolic HBP, n = 9,746) according to the frequency of meat consumption (serving/wk) after adjustment for sex and height. Overall trends are estimated using chi-squared tests. Korea School Health Examination Survey, 2011–2015
Adjusted coefficients of regression parameters for BMI in relation to meat consumption
| Merged 2011-2015a
| Body Mass Index, kg/m2 | |||||||
|---|---|---|---|---|---|---|---|---|
| Girlsb | Boysb | |||||||
|
| SEM |
|
|
| SEM |
|
| |
| Adjusted R2 | 0.231 | 0.191 | ||||||
| Age (years) | ||||||||
| 12 y | 0.442 | 0.06 | <0.001 | −0.665 | 0.07 | <0.001 | ||
| 15 y | 1.557 | 0.08 | <0.001 | −0.847 | 0.10 | <0.001 | ||
| Height (cm) | 0.099 | 0.01 | <0.001 | 0.121 | 0.01 | <0.001 | ||
| Areas | ||||||||
| Rural | −0.084 | 0.05 | 0.095 | −0.071 | 0.04 | 0.130 | ||
| Blood pressure (mmHg) | 0.795 | 0.01 | <0.001 | 0.116 | 0.01 | <0.001 | ||
| Systolic hypertension | 1.878 | 0.11 | <0.001 | 2.599 | 0.10 | <0.001 | ||
| Diastolic hypertension | 0.728 | 0.11 | <0.001 | 1.314 | 0.11 | <0.001 | ||
| Dietary patterns (<3/wk) | ||||||||
| Meat | 0.441 | 0.05 | <0.001 | 0.176 | 0.06 | 0.004 | ||
| Milk | −0.296 | 0.04 | <0.001 | −0.302 | 0.04 | <0.001 | ||
| Fruits | 0.434 | 0.04 | <0.001 | 0.222 | 0.04 | <0.001 | ||
| Vegetable | −0.100 | 0.04 | 0.018 | −0.208 | 0.04 | <0.001 | ||
| Breakfast | 0.327 | 0.05 | <0.001 | 0.148 | 0.06 | 0.021 | ||
| Physical and leisure activities | ||||||||
| Exercise (<3/wk) | −0.329 | 0.04 | <0.001 | 0.056 | 0.03 | 0.097 | ||
| Internet or games (≥2 hr/d) | 0.271 | 0.04 | <0.001 | 0.263 | 0.04 | <0.001 | ||
aCross-sectional data from the Korea School Health Examination Survey (2011–2015, 1761 schools)
bOutcome variables: Body mass index (BMI)
c P-value of Wald’s test; β, coefficient of regression parameters; SEM, standard error of the mean; R 2, coefficient of determination
dAll variables in the left column of the table are explanatory variables, and their associations (including place of residence, 17 cities and provinces in South Korea) with BMI were simultaneously adjusted using multiple linear regression
eReference group: Aged 9 y = 0; Urban areas = 0; Dietary patterns, food intake > 5 servings/wk = 0; Exercise ≥ 5/wk = 0; Internet or games < 2 hr/d = 0
Adjusted coefficients of regression parameters for blood pressure in relation to meat consumption
| Merged 2011-2015a
| Blood pressure (BP), mmHg | |||||||
|---|---|---|---|---|---|---|---|---|
| Systolic BPb | Diastolic BPb | |||||||
|
| SEM |
|
|
| SEM |
|
| |
| Adjusted R2 | 0.260 | 0.162 | ||||||
| Sex | ||||||||
| Boys | 1.137 | 0.11 | <0.001 | 0.467 | 0.07 | <0.001 | ||
| Age (years) | ||||||||
| 12 y | 1.339 | 0.29 | <0.001 | 0.896 | 0.20 | <0.001 | ||
| 15 y | 2.964 | 0.33 | <0.001 | 2.111 | 0.22 | <0.001 | ||
| Height (cm) | 0.260 | 0.01 | <0.001 | 0.103 | 0.01 | <0.001 | ||
| Areas | ||||||||
| Rural | −0.089 | 0.28 | 0.757 | −0.003 | 0.19 | 0.987 | ||
| BMI (kg/m2) | 0.795 | 0.01 | <0.001 | 0.116 | 0.01 | <0.001 | ||
| Overweight | 4.452 | 0.13 | <0.001 | 2.265 | 0.09 | <0.001 | ||
| Obesity | 7.497 | 0.16 | <0.001 | 4.123 | 0.10 | <0.001 | ||
| Dietary patterns (<3/wk) | ||||||||
| Meat | 0.574 | 0.16 | <0.001 | 0.376 | 0.12 | 0.003 | ||
| Milk | −0.129 | 0.17 | 0.264 | 0.023 | 0.07 | 0.767 | ||
| Fruits | 0.143 | 0.10 | 0.189 | −0.128 | 0.07 | 0.098 | ||
| Vegetable | 0.044 | 0.09 | 0.661 | 0.016 | 0.07 | 0.817 | ||
| Breakfast | 0.240 | 0.13 | 0.065 | 0.202 | 0.09 | 0.035 | ||
| Physical and leisure activities | ||||||||
| Exercise (<3/wk) | 0.058 | 0.10 | 0.567 | 0.134 | 0.06 | 0.047 | ||
| Internet or games (≥2 hr/d) | 0.077 | 0.11 | 0.490 | 0.006 | 0.07 | 0.930 | ||
aCross-sectional data from the Korea School Health Examination Survey (2011–2015, 1761 schools)
bOutcome variables: SBP or DBP
c P-value of Wald’s test; β, coefficient of regression parameters; SEM, standard error of the mean; R 2, coefficient of determination
dAll variables in the left column of the table were explanatory variables, and their associations (including place of residence, 17 cities and provinces in South Korea) with SBP or DBP were simultaneously adjusted using multiple linear regression
eReference group: Girls = 0; Aged 9 y = 0; Body mass index (BMI), No excess weight = 0; Urban areas = 0; Dietary patterns, food intake > 5 servings/wk = 0; Exercise ≥ 5/wk = 0; Internet or games < 2 hr/d = 0
Association between meat consumption and both obesity and high blood pressure in South Korean children and adolescents
|
| Consumption of meat (servings/wk)c | |||
|---|---|---|---|---|
| <1 | 1–2 | 3–5 | >5 | |
| Obesitya, ORs (95% CI)b | ||||
| Model 1, multivariabled | 1.62*** (1.39–1.91) | 1.42*** (1.28–1.59) | 1.16** (1.04–1.29) | Reference |
| Model 2, model 1 plus BPe | 1.50*** (1.27–1.76) | 1.36*** (1.21–1.52) | 1.13* (1.01–1.26) | Reference |
| Model 3, model 2 plus dietary patternsf | 1.43*** (1.21–1.69) | 1.30*** (1.16–1.46) | 1.12* (1.00–1.25) | Reference |
| Model 4, model 3 plus activitiesg | 1.44*** (1.21–1.70) | 1.30*** (1.16–1.46) | 1.12* (1.00–1.25) | Reference |
| Systolic HBPa, ORs (95% CI)b | ||||
| Model 1, multivariabled | 1.43*** (1.16–1.75) | 1.23** (1.08–1.41) | 1.10 (0.96–1.26) | Reference |
| Model 2, model 1 plus BMIe | 1.29** (1.04–1.60) | 1.14 (0.99–1.31) | 1.06 (0.92–1.22) | Reference |
| Model 3, model 2 plus dietary patternsf | 1.31** (1.06–1.62) | 1.15* (1.00–1.32) | 1.06 (0.92–1.22) | Reference |
| Model 4, model 3 plus activitiesg | 1.30** (1.05–1.62) | 1.15* (1.00–1.31) | 1.05 (0.92–1.21) | Reference |
| Diastolic HBPa, ORs (95% CI)b | ||||
| Model 1, multivariabled | 1.37** (1.11–1.69) | 1.27*** (1.11–1.45) | 1.19** (1.04–1.36) | Reference |
| Model 2, model 1 plus BMIe | 1.28* (1.03–1.59) | 1.20* (1.04–1.38) | 1.16* (1.16–1.33) | Reference |
| Model 3, model 2 plus dietary patternsf | 1.26* (1.02–1.55) | 1.20** (1.04–1.38) | 1.17* (1.02–1.33) | Reference |
| Model 4, model 3 plus activitiesg | 1.25* (1.02–1.54) | 1.19** (1.04–1.37) | 1.16* (1.01–1.33) | Reference |
aOutcome variables: High blood pressure (HBP) or Obesity
b*P < 0.05; **P ≤ 0.01; ***P ≤ 0.001, using binary multiple logistic regression analysis for adjusted odds ratios (ORs) and 95% confidence interval (CI)
cExplanatory variable: meat consumption (servings per wk)
dAdjusted for sex, age, height, and regions (17 cities and provinces in South Korea)
eAdditional adjustment for BP (mm Hg) when modelling obesity and for BMI (kg/m2) when modelling HBP
fAdditional adjustment for milk (quartiles), fruit (quartiles), vegetable (quartiles), and breakfast (quartiles)
gAdditional adjustment for physical activities and internet/games use