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Associations of dietary phytosterols with blood lipid profiles and prevalence of obesity in Chinese adults, a cross-sectional study

Lipids in Health and Disease201817:54

https://doi.org/10.1186/s12944-018-0703-y

Received: 14 November 2017

Accepted: 8 March 2018

Published: 16 March 2018

Abstract

Background

It has been established in RCTs that high dose of phytosterols can significantly reduce blood cholesterol. However, it was uncertain whether low dose of phytosterols from daily diets was effective. In this study, we evaluated the associations between dietary phytosterols and body mass index (BMI), waist circumference (WC), blood glucose, serum lipid profiles and prevalence of overweight/obesity and abdominal obesity in healthy subjects.

Methods

Four hundred nine men and 503 women aged 18–60 years were included in this study. Dietary intakes of phytosterols were estimated using a validated food frequency questionnaire. Height, body weight, WC and blood pressure were measured, an oral glucose tolerance test was performed. Moreover, fasting serum triglyceride (TG), total cholesterol (TC), high density lipoprotein cholesterol (HDLc) and low density lipoprotein cholesterol (LDLc) were further determined.

Results

When comparing extreme quartiles of dietary phytosterols, significant differences of BMI, WC, systolic blood pressure (SBP), diastolic blood pressure (DBP), serum TC and LDLc were found. Dietary phytosterols presented a negative association with BMI, WC, SBP, DBP, serum TC and LDLc (with and without adjustment for energy). After adjustment for confounders, we found higher dietary phytosterols were linked with lower prevalence of overweight/obesity (OR highest vs. lowest quartile = 0.487; 95% CI 0.234, 0.918 for men; OR highest vs. lowest quartile = 0.277; 95% CI 0.124, 0.619 for women) and abdominal obesity (OR highest vs. lowest quartile = 0.344; 95% CI 0.144, 0.819 for men; OR highest vs. lowest quartile = 0.321; 95% CI 0.140, 0.571 for women).

Conclusions

Higher dietary phytosterols were associated with lower BMI, WC, blood pressure, serum TC and LDLc and lower prevalence of overweight/obesity and abdominal obesity in Chinese adults.

Keywords

Human, dietary phytosterolsTCLDLcObesity

Background

Obesity is an increasing challenge for public health in many countries [1], and although elevated body mass index (BMI) is a modifiable risk factor for a series of metabolic disorders and chronic diseases, including insulin resistance [2], metabolic syndrome, type 2 diabetes [3], cardiovascular diseases (CVDs) [2], hypertension [4], dyslipidemia [5], and certain cancers [6], it is difficult to maintain weight loss. Dietary habits were considered to play a vital role in development, treatment and prevention of chronic diseases, such as obesity, hyperlipidemia, diabetes and CVDs [79]. Therefore, it is important to extensively focus on the associations between daily diet and chronic diseases, and reasonable dietary recommendation should be raised.

Plant sterols and plant stanols (together they are referred as phytosterols) are a group of non-nutritive but bioactive compounds naturally present in all plant origin foods, they are 28- or 29-carbon alcohols and their structures are similar to cholesterol, a 27-carbon alcohol [10]. The dominant dietary plant sterols are β-sitosterol, campesterol, and stigmasterol, all have double bonds at the C-5 position of the ring. In certain structures, the double bond is saturated and these compounds are referred as plant stanols. Compared with plant sterols, concentrations of plant stanols, such as β-sitostanol and campestanol were generally lower in daily foods [11]. Phytosterols are structurally similar to cholesterol and can inhibit cholesterol absorption. Many randomized controlled trials (RCTs) have confirmed that phytosterols added into fat-based foods can significantly reduce serum total cholesterol (TC) and LDL cholesterol (LDLc) [1214]. A recent meta-analysis including 84 RCTs suggests that 2.15 g/d phytosterols added in fat matrices lowers LDLc concentration by 8.8% [15]. However, daily intake of capsules containing 2 g phytosterols did not reduce total- or LDL-cholesterol significantly [16], this study emphasized the importance of phytosterols from daily diets in cholesterol lowering effect.

The daily intakes of total phytosterols usually range from 200 to 400 mg in general population [17, 18] and higher daily intake of 500–1000 mg can be reached by vegetarians [19, 20]. However, in most RCTs, the health benefits are observed at a high dose of phytosterols intake (around 2 g/d), which cannot be achieved in habitual diets. In total, there are limited evidence limited evidence on the association of natural dietary intake of phytosterols and anthropometric parameters, blood glucose and serum lipid profiles. This study aims to examine the hypothesis that higher dietary phytosterols improves body weight and metabolic profile in healthy adults.

Methods

Internet-based FFQ

In large population, food frequency questionnaires (FFQs) were universally used by researchers [21]. However, impossibility of conducting traditional face-to-face FFQs during a short period make it inconvenient in researches due to time-consuming [22]. Therefore, a portable tool named Internet-based dietary questionnaire for Chinese (IDQC) has been designed and validated at Harbin Medical University by experts of nutrition, epidemiology and bio-statistics [23, 24]. In IDQC, commonly eaten foods were divided into 16 categories (i.e., grains, potatoes, legumes, vegetables, fungus, fruits, seeds and nuts, livestock, poultry, dairy, eggs, fish, snacks, sugar, condiments, and beverages). Reference images of each food item’s weight/volume were exhibited as references to assist the participants in making accurate estimation of food portions. Each participant had to choose the frequency and amount of each subtype of food groups. Finally, the questionnaires were uploaded to a secure website, which is free of access at http://www.yyjy365.org/diet.

Study population

To restrict the cost of the biochemical measurements and the length of the study, we randomly selected 912 participants from the database of previously published literature [25] (Additional file 1: Figure S1.). This sample size is sufficient to detect differences of the primary outcome between quartiles, at 95% power and 5% level of significance (0.24 mmol/l in TC and 0.24 mmol/l in LDLc). Online questionnaires including age, gender, occupation, education background, income, physical exercise, smoking, drinking and dietary habits during the past 6 months were completed by all participants as previously described [25]. Daily nutrients intakes were then calculated by using the computerized China food composition tables of 2009 [26].

In this study, the following exclusion criteria were applied: (1) missing data of dietary intake; (2) reported extremely low or high energy intake (i.e. < 800 kcal (3349 kJ) or > 5000 kcal (20,934 kJ) for males; < 600 kcal (2512 kJ) or > 4000 kcal (16,747 kJ) for females); (3) Diabetes diagnosis in routine physical examination; (4) Being on a diet in the past 6 months. The study complied with the Declaration of Helsinki and was approved by the Human Research Ethics Committee of the Harbin Medical University (approval code [2015] 006). Online informed consent was obtained from all participants.

Estimation of phytosterols intake

On the basis of dietary habits of Chinese residents, more than 160 types of food items (including vegetable oils, cereal and its products, beans and its products, vegetables, fruits, nuts and potatoes) in the Chinese food composition table were chosen for measurement. The contents of β-sitosterol, campesterol, stigmasterol, β-sitostanol and campestanol in food were analyzed at Institute of Nutrition and Food Safety, Chinese Centre for Disease Control and Prevention, Beijing, China, using gas chromatograph methods by Han et al. [27, 28]. The database of phytosterols concentrations were established and were linked to the questionnaire data, intake of phytosterols were then estimated using the IDQC. A supplementary table outlining the phytosterols contents of typical foods in Chinese was provided (Additional file 2: Table S1).

Anthropometric measurements, cut-off points of overweight/obesity and definition of abdominal obesity

Height, bodyweight and waist circumference (WC) were measured by well-trained medical students. Body mass index (BMI) was calculated as body weight in kilograms divided by the square of the height in meters (kg/m2). Participants were asked to wear light, thin clothing and no shoes. Body weight and height were measured to the nearest 0.1 kg and 0.1 cm. WC was measured midway between the lowest rib and the iliac crest with a flexible anthropometric tape on the horizontal plane with the participant in standing position, to the nearest of 0.1 cm. After a 10 min rest in a sitting position, systolic blood pressure (SBP) and diastolic blood pressure (DBP) of participants were gauged using a standard mercury sphygmomanometer by nurses of the health examination center, mean values of three times were recorded. The BMI cut-off points in Chinese subjects for overweight (24 ≤ BMI < 28 kg/m2) and obesity (BMI ≥ 28 kg/m2) were used in our study to define these states [29]. According to the 2006 Guidelines on Preservation and Control Overweight and Obesity in Chinese Adults classification [30], abdominal obesity was defined as WC ≥ 85 cm in men and WC ≥ 80 cm in women.

Serum collection and laboratory measurements

Fasting blood samples were collected between 8:00 and 9:00 a.m. after fasting overnight. Then, each participant was asked to take 75 g glucose and postprandial blood samples were drawn 2 h later. FBG and 2 h-PG were measured with a hand-held glucometer (ACCU-CHEK, Roche, Shanghai, China). Blood samples were centrifuged at 3000 rpm for 15 min and the serum was used for laboratory measurements immediately. Serum triglyceride (TG), total cholesterol (TC), high density lipoprotein cholesterol (HDLc) and low density lipoprotein cholesterol (LDLc) were determined using a Roche Modular P800 Automatic Biochemical Analyzer (Roche Diagnostics, Mannheim, Germany). Coefficients of variations of lab measurements were presented in supplemental materials.

Statistical analysis

For descriptive statistics, means and SDs (or frequencies and percentages) were calculated across quartiles of dietary phytosterols and compared using one-way analysis of variance or chi-square test, as appropriate. Bivariate correlation analysis (without variants adjusted) and partial correlation analysis (with adjustment for energy intake) was performed to assess the association of dietary phytosterols and BMI, WC, SBP, DBP, FBG, 2 h-PG, serum TG, TC, HDLc and LDLc. To estimate the odds ratio (OR) and 95% confidence interval (CI) of overweight/obesity and abdominal obesity between quartiles of dietary phytosterols, logistic regression model was used. Age, education, income, labor, exercise status, smoking habits, drinking habits, dietary carbohydrate, fat, protein, cholesterol and fiber intake were adjusted in three models. The statistical analyses were carried out using SAS software (version 9.1; SAS Institute, Cary, NC, USA) and P < 0.05 was considered statistically significant.

Results

Characteristics and dietary intakes of the study population

The characteristics and dietary intakes of participants were summarized in Table 1. Participants of the 3rd quartile of dietary phytosterols were youngest. Participants of the 4th quartile of dietary phytosterols had a higher percentage of low income and low education level versus the first quartile. For dietary intakes, energy, protein, fat, fiber and cholesterol intake increased through quartiles of dietary phytosterols. Finally, among individuals with higher intake of phytosterols, lower prevalence of overweight/obesity and abdominal obesity were observed.
Table 1

Characteristics and dietary nutrients intake of participants by quartiles (Q) of total phytosterols intake

 

Quartiles based on total phytosterols intake

 

Characteristics

Q1

Q2

Q3

Q4

P

Total, n

228

228

228

228

 

Age, y

32.4 ± 12.2a

33.5 ± 13.1a

29.4 ± 11.4b

33.2 ± 12.6a

0.002

Gender, M/W

109/119

88/140

106/122

106/122

0.179

Income per month

    

0.027

 < 2000 yuan, n (%)

133 (58.3)

133 (58.3)

154 (67.5)

158 (69.3)

 

 2000–5000 yuan, n (%)

86 (37.7)

92 (40.4)

70 (30.7)

64 (28.1)

 

 ≥ 5000 yuan, n (%)

9 (3.9)

3 (1.3)

4 (1.8)

6 (2.6)

 

Education

    

< 0.001

 Under college, n (%)

46 (20.2)

52 (22.8)

54 (23.7)

72 (31.6)

 

 Bachelor, n (%)

162 (71.1)

166 (72.8)

170 (74.5)

152 (66.7)

 

 Master or doctor, n (%)

20 (8.8)

10 (4.4)

4 (1.8)

4 (1.8)

 

PAL

    

0.145

 Light, n (%)

58 (25.4)

58 (25.4)

58 (25.4)

70 (32.5)

 

 Medium, n (%)

160 (70.2)

161 (70.6)

168 (73.7)

154 (67.5)

 

 Heavy, n (%)

10 (4.4)

9 (3.9)

2 (0.9)

4 (1.8)

 

Exercise

    

0.949

 < 10 h/week, n (%)

101 (44.3)

94 (41.2)

88 (38.6)

92 (40.4)

 

 10–20 h/week, n (%)

98 (43.0)

104 (45.6)

108 (47.4)

106 (46.5)

 

 ≥ 20 h/week, n (%)

29 (12.7)

30 (13.2)

32 (14.0)

30 (13.2)

 

Smokinga

    

0.072

 Non-smoker, n (%)

206 (90.4)

207 (90.8)

210 (92.1)

194 (85.1)

 

 Current smoker, n (%)

22 (9.6)

21 (9.2)

18 (7.9)

34 (14.9)

 

Drinkinga

    

0.636

 Non-drinker, n (%)

182 (79.8)

184 (80.7)

184 (80.7)

192 (84.2)

 

 Current drinker, n (%)

46 (20.2)

44 (19.3)

44 (19.3)

36 (15.8)

 

Overweight/obesity, n (%)

100 (43.9)

90 (39.5)

82 (36.0)

74 (32.5)

0.075

Abdominal obesity, n (%)

77 (33.8)

62 (27.2)

59 (25.9)

54 (23.7)

0.092

Dietary intakes

 Energy, kcal

2179.3 ± 528.7a

2271.9 ± 551.5b

2368.9 ± 548.6c

2498.2 ± 494.1d

< 0.001

 Protein, g/d

76.1 ± 21.2a

82.9 ± 23.9b

86.9 ± 24.9b

95.2 ± 22.1c

< 0.001

 Fat, g/d

60.2 ± 23.0a

69.5 ± 23.7b

74.3 ± 24.7c

86.4 ± 21.7d

< 0.001

 Carbohydrate, g/d

344.9 ± 93.6

343.6 ± 89.9

353.0 ± 91.7

355.8 ± 89.8

0.399

 Fiber, g/d

14.4 ± 3.9a

17.3 ± 4.4b

19.5 ± 4.9c

23.1 ± 5.2d

< 0.001

 Cholesterol, mg/d

382.9 ± 230.5a

461.1 ± 266.9b

445.8 ± 275.0b

504.2 ± 260.4c

< 0.001

 Total plant sterols, mg/d

161.9 ± 23.0

231.3 ± 20.1

294.0 ± 18.8

383.0 ± 54.4

< 0.001

 β-sitosterol, mg/d

96.4 ± 16.8a

139.9 ± 22.2b

187.9 ± 27.9c

255.7 ± 47.3d

< 0.001

 campesterol, mg/d

32.5 ± 13.4a

48.8 ± 20.4b

51.4 ± 26.9b

57.9 ± 29.2c

< 0.001

 stigmasterol, mg/d

12.5 ± 5.4a

15.0 ± 5.9b

17.8 ± 7.5c

19.0 ± 7.3d

< 0.001

 β-sitostanol, mg/d

9.2 ± 4.4a

13.3 ± 5.6b

18.5 ± 6.6c

27.2 ± 7.5d

< 0.001

 campestanol, mg/d

11.3 ± 3.3a

14.4 ± 4.0b

18.3 ± 4.2c

23.2 ± 4.8d

< 0.001

P values are for differences across quartiles of total plant sterols intake; Data are mean ± SD or frequency (percentage), a, b, c, d, mean values with unlike letters were significantly different (P < 0.05)

Abbreviations: PAL physical activity level

a There is no report of quitting smoking or quitting drinking in our population

Anthropometric parameters, blood glucose and serum lipid profiles of participants

BMI, WC, blood glucose and serum lipid profiles of participants among quartiles of dietary phytosterols were showed in Table 2. Compared with those in the first quartile of dietary phytosterols, participants of the 4th quartile had lower BMI, WC, SBP, DBP, TC and LDLc (P < 0.01 for BMI and TC, P < 0.05 for WC, SBP, DBP and LDLc). After stratified by gender, similar results were observed in men and women (all P < 0.05). There is no significant difference of FBG, 2 h-PG, TG and HDLc among quartiles of dietary phytosterols.
Table 2

Anthropometric parameters, blood glucose and serum lipid profiles of participants by quartiles (Q) of total phytosterols intake

 

Quartiles based on total phytosterols intake

 
 

Q1

Q2

Q3

Q4

P

Overall, n

228

228

228

228

 

 BMI, kg/m2

23.85 ± 3.17

23.53 ± 3.44

23.05 ± 3.71*

22.67 ± 2.76**

0.001

 WC, cm

80.31 ± 10.21

78.76 ± 8.74

78.45 ± 9.67*

78.12 ± 7.91*

0.044

 SBP, mm Hg

119.51 ± 11.16

117.13 ± 12.42

116.45 ± 11.33

115.04 ± 10.14*

0.034

 DBP, mm Hg

78.74 ± 8.92

77.32 ± 8.41

76.72 ± 8.93

76.27 ± 7.22*

0.046

 FBG, mmol/l

4.71 ± 0.81

4.68 ± 0.73

4.59 ± 0.82

4.62 ± 0.78

0.282

 2 h-PG, mmol/l

6.42 ± 0.97

6.35 ± 0.81

6.33 ± 0.87

6.27 ± 0.96

0.361

 TG, mmol/l

1.68 ± 1.24

1.73 ± 1.31

1.71 ± 1.28

1.75 ± 1.38

0.916

 TC, mmol/l

5.25 ± 0.87

5.17 ± 0.78

5.09 ± 0.86

5.01 ± 0.90**

0.004

 HDLc, mmol/l

1.26 ± 0.33

1.25 ± 0.34

1.29 ± 0.29

1.25 ± 0.36

0.289

 LDLc, mmol/l

2.55 ± 0.83

2.42 ± 0.86

2.39 ± 0.79

2.31 ± 0.90*

0.042

Men, n

102

102

102

103

 

 BMI, kg/m2

23.91 ± 3.09

23.77 ± 3.25

23.41 ± 3.36

22.75 ± 2.68*

0.016

 WC, cm

83.45 ± 9.26

81.19 ± 9.62

79.63 ± 9.18*

78.58 ± 7.26*

0.024

 SBP, mm Hg

120.12 ± 12.01

118.03 ± 11.45

117.17 ± 11.45

115.03 ± 9.98*

0.047

 DBP, mm Hg

79.11 ± 7.92

78.23 ± 8.63

77.87 ± 8.95

77.03 ± 7.15*

0.045

 FBG, mmol/l

4.75 ± 0.86

4.81 ± 0.78

4.79 ± 0.81

4.72 ± 0.91

0.442

 2 h-PG, mmol/l

6.51 ± 0.92

6.66 ± 0.98

6.35 ± 0.78

6.24 ± 0.86

0.296

 TG, mmol/l

1.79 ± 1.14

1.73 ± 1.21

1.78 ± 1.24

1.76 ± 1.41

0.855

 TC, mmol/l

5.17 ± 0.91

5.06 ± 0.89

5.01 ± 0.81

4.95 ± 0.88*

0.028

 HDLc, mmol/l

1.27 ± 0.35

1.26 ± 0.38

1.24 ± 0.32

1.23 ± 0.37

0.354

 LDLc, mmol/l

2.44 ± 0.86

2.31 ± 0.91

2.25 ± 0.77

2.19 ± 0.86*

0.034

Women, n

125

126

126

126

 

 BMI, kg/m2

23.72 ± 3.24

23.41 ± 3.31

22.78 ± 3.74*

22.45 ± 2.66*

0.021

 WC, cm

76.02 ± 8.17

74.28 ± 8.21

73.20 ± 9.12*

72.89 ± 7.31*

0.047

 SBP, mm Hg

118.23 ± 10.93

116.34 ± 12.78

114.96 ± 11.61

113.82 ± 10.21*

0.038

 DBP, mm Hg

77.71 ± 8.86

76.25 ± 8.52

75.12 ± 8.61

74.78 ± 7.31*

0.032

 FBG, mmol/l

4.68 ± 0.82

4.59 ± 0.71

4.41 ± 0.78

4.44 ± 0.98

0.341

 2 h-PG, mmol/l

6.31 ± 0.91

6.26 ± 0.95

6.31 ± 0.82

6.33 ± 0.91

0.458

 TG, mmol/l

1.58 ± 1.31

1.72 ± 1.34

1.66 ± 1.22

1.74 ± 1.33

0.545

 TC, mmol/l

5.34 ± 0.76

5.29 ± 0.76

5.18 ± 0.92

5.06 ± 0.93*

0.013

 HDLc, mmol/l

1.24 ± 0.32

1.24 ± 0.31

1.33 ± 0.29

1.27 ± 0.36

0.128

 LDLc, mmol/l

2.67 ± 0.81

2.52 ± 0.83

2.46 ± 0.81

2.41 ± 0.85*

0.044

Abbreviations: BMI body mass index, WC waist circumference, SBP systolic blood pressure, DBP diastolic blood pressure, FBG fasting blood glucose, 2 h-PG 2 h-postprandial glucose, TG triglyceridel, TC total cholesterol, HDLc high destiny lipoprotein cholesterol, LDLc low destiny lipoprotein cholesterol

* P < 0.05; ** P < 0.01 compared with the 1st quartile

Correlations between dietary phytosterols and anthropometric parameters, blood glucose and serum lipid profiles

As shown in Table 3, we found negative correlations between total phytosterols and BMI, WC, SBP, DBP, TC and LDLc (all P < 0.05). The associations were stronger with adjustment of total energy intake. After stratified by gender, similar trends were observed in male and female (all P < 0.05). However, no significant associations between dietary phytosterols and FBG, 2 h-PG, TG and HDLc were observed.
Table 3

Correlation analysis of dietary total phytosterols versus anthropometric parameters, blood glucose and serum lipid profiles

 

Total phytosterols intake, mg/d

Unadjusted

Adjusteda

r

P

r

P

Overall

 BMI, kg/m2

−0.181

< 0.001

− 0.226

< 0.001

 WC, cm

− 0.106

0.001

− 0.167

< 0.001

 SBP, mm Hg

− 0.112

< 0.001

− 0.132

< 0.001

 DBP, mm Hg

− 0.109

0.002

−0.134

< 0.001

 FBG, mmol/l

−0.024

NS

−0.033

NS

 2 h-PG, mmol/l

−0.019

NS

−0.023

NS

 TG, mmol/l

−0.033

NS

−0.041

NS

 TC, mmol/l

−0.144

< 0.001

−0.183

< 0.001

 HDLc, mmol/l

−0.023

NS

−0.029

NS

 LDLc, mmol/l

−0.138

< 0.001

−0.167

< 0.001

Men

 BMI, kg/m2

−0.212

< 0.001

−0.243

< 0.001

 WC, cm

−0.164

< 0.001

−0.206

< 0.001

 SBP, mm Hg

−0.117

0.024

−0.136

0.011

 DBP, mm Hg

−0.112

0.031

−0.140

0.023

 FBG, mmol/l

−0.028

NS

−0.037

NS

 2 h-PG, mmol/l

−0.023

NS

−0.029

NS

 TG, mmol/l

−0.034

NS

−0.044

NS

 TC, mmol/l

−0.147

0.003

−0.191

< 0.001

 HDLc, mmol/l

−0.021

NS

−0.023

NS

 LDLc, mmol/l

−0.133

0.006

−0.185

< 0.001

Women

 BMI, kg/m2

−0.158

< 0.001

−0.210

< 0.001

 WC, cm

−0.087

0.047

−0.122

0.006

 SBP, mm Hg

−0.106

0.028

−0.129

0.011

 DBP, mm Hg

−0.105

0.042

−0.119

0.033

 FBG, mmol/l

−0.019

NS

−0.024

NS

 2 h-PG, mmol/l

−0.014

NS

−0.018

NS

 TG, mmol/l

−0.029

NS

−0.031

NS

 TC, mmol/l

−0.137

0.011

−0.179

< 0.001

 HDLc, mmol/l

−0.027

NS

−0.033

NS

 LDLc, mmol/l

−0.121

0.021

−0.145

0.006

Abbreviations: BMI body mass index, WC waist circumference, SBP systolic blood pressure, DBP diastolic blood pressure, FBG fasting blood glucose, 2 h-PG 2 h-postprandial glucose, TG triglyceride, TC total cholesterol, HDLc high destiny lipoprotein cholesterol, LDLc low destiny lipoprotein cholesterol, NS no significance

a Adjusting for total energy intake

Correlations between dietary plant sterols and prevalence of obesity

With adjustment for potential dietary and non-dietary cofounders (age, education, income, PAL, physical exercise, smoking and drinking status, dietary carbohydrate, fat, protein, fiber and cholesterol intake), we found higher dietary total phytosterols intake was linked with lower prevalence of overweight/obesity. Data was illustrated in Table 4, compared with the 1st quartile, the multivariable-adjusted ORs of overweight/obesity of the 4th quartile were 0.440 (0.254, 0.763) in overall population, 0.487 (0.234, 0.918) in men and 0.277 (0.124, 0.619) in women. (All P < 0.05).
Table 4

Association between total phytosterols intake and prevalence of overweight/obesity

Overall

Q1

Q2

Q3

Q4

 Participants, n

228

228

228

228

 No. of cases, n

100

90

82

74

 Intake, mg/d

161.9

231.3

294

383

Crude

1

0.835 (0.575, 1.212)

0.719 (0.493, 1.047)

0.615 (0.420, 0.900)*

 Model 1

1

0.746 (0.496, 1.122)

0.762 (0.504, 1.151)

0.496 (0.324, 0.761)**

 Model 2

1

0.708 (0.462, 1.085)

0.711 (0.445, 1.136)

0.440 (0.254, 0.763)**

Men

Q1

Q2

Q3

Q4

 Participants, n

102

102

102

103

 No. of cases, n

49

44

34

32

 Intake, mg/d

157.3

233

381.4

301

 Crude

1

0.835 (0.480, 1.451)

0.541 (0.307, 0.952)*

0.481 (0.272, 0.850)*

 Model 1

1

0.752 (0.412, 1.373)

0.552 (0.294, 1.035)

0.509 (0.274, 0.946)*

 Model 2

1

0.778 (0.403, 1.501)

0.559 (0.244, 1.183)

0.487 (0.234, 0.918)*

Women

Q1

Q2

Q3

Q4

 Participants, n

125

126

126

126

 No. of cases, n

52

51

42

42

 Intake, mg/d

165.6

229.3

287.6

384.2

 Crude

 

0.955 (0.577, 1.579)

0.702 (0.420, 1.173)

0.702 (0.420, 1.173)

 Model 1

 

0.927 (0.527, 1.631)

0.790 (0.441, 1.414)

0.501 (0.275, 0.911)*

 Model 2

1

0.758 (0.416, 1.380)

0.537 (0.275, 1.048)

0.277 (0.124, 0.619)**

Model 1: adjusting for age, education, income, PAL, exercise status, smoking and drinking habits

Model 2: Model 1 + dietary carbohydrate, fat, protein, fiber and cholesterol intake were adjusted

* P < 0.05; ** P < 0.01 compared with the 1st quartile

Correlations between dietary plant sterols and prevalence of abdominal obesity

In this study, we have observed the reverse relationship between dietary phytosterols and abdominal obesity. As shown in Table 5, compared with the 1st quartile, the multivariable-adjusted ORs of abdominal obesity of the 4th quartile were 0.239 (0.127, 0.450); 0.344 (0.144, 0.819) and 0.321 (0.140, 0.571) in overall population, men and women, respectively (All P < 0.05). Potential dietary and non-dietary cofounders (age, education, income, PAL, physical exercise, smoking and drinking status, dietary carbohydrate, fat, protein, fiber and cholesterol intake) were rectified.
Table 5

Association between total phytosterols intake and prevalence of abdominal obesity

Overall

Q1

Q2

Q3

Q4

 Participants, n

228

228

228

228

 No. of cases, n

77

62

59

54

 Intake, mg/d

161.9

231.3

294

383

 Crude

1

0.732 (0.491, 1.093)

0.685 (0.457, 1.025)

0.609 (0.404, 0.918)*

 Model 1

1

0.806 (0.513, 1.266)

0.566 (0.360, 0.891)*

0.490 (0.305, 0.785)**

 Model 2

1

0.512 (0.302, 0.868)*

0.423 (0.259, 0.691)**

0.239 (0.127, 0.450)**

Men

Q1

Q2

Q3

Q4

 Participants, n

102

102

102

103

 No. of cases, n

51

43

36

36

 Intake, mg/d

157.3

233

381.4

301

 Crude

1

0.741 (0.426, 1.289)

0.529 (0.302, 0.927)*

0.545 (0.311, 0.957)*

 Model 1

1

0.657 (0.355, 1.215)

0.520 (0.303, 0.955)*

0.510 (0.293, 0.951)*

 Model 2

1

0.462 (0.233, 0.918)*

0.407 (0.191, 0.864)*

0.344 (0.144, 0.819)*

Women

Q1

Q2

Q3

Q4

 Participants, n

125

126

126

126

 No. of cases, n

25

23

20

18

 Intake, mg/d

165.6

229.3

287.6

384.2

 Crude

1

0.893 (0.476, 1.676)

0.755 (0.395, 1.443)

0.667 (0.343, 1.295)

 Model 1

1

0.738 (0.354, 1.539)

0.672 (0.305, 1.480)

0.341 (0.151, 0.770)*

 Model 2

1

0.525 (0.216, 1.276)

0.497 (0.221, 1.118)

0.321 (0.140, 0.571)**

Model 1: adjusting for age, education, income, PAL, exercise status, smoking and drinking habits

Model 2: Model 1 + dietary carbohydrate, fat, protein, fiber and cholesterol intake were adjusted

* P < 0.05; ** P < 0.01 compared with the 1st quartile

Discussion

To our knowledge, this is the first Internet-based cross-sectional study to investigate associations between dietary phytosterols and anthropometric parameters, blood glucose, serum lipid profiles and prevalence of overweight/obesity and abdominal obesity among healthy subjects. The major finding of this study is that higher dietary phytosterols intake was associated with lower BMI, WC, blood pressure, serum TC and LDLc and lower prevalence of overweight/obesity and abdominal obesity in northern Chinese adults. A moderate dietary intake of total plant sterols was found (267.5 mg/d) in our population. Therefore, this sample can represent the general population.

Lifestyle, including dietary habits and physical exercises, could present a distinct effect on management of bodyweight and lipid/lipoprotein. Here, we generally found a dose-dependent inverse association between phytosterols intake from natural diet and BMI, WC, blood pressure, TC and LDLc in northern Chinese adults. Our findings suggest that higher intake of phytosterols in natural diet may be favorable in the prevention of overweight/obesity and improve cholesterol metabolism. Therefore, reasonable advice of consuming more phytosterol-rich foods may be useful for these patients.

It has been established that high dose of phytosterols can significantly reduce blood cholesterol in RCTs [31]. However, it was still undecided whether low doses of phytosterols from natural diets were effective in management of serum cholesterol. In our reserch, we found that higher dietary phytosterols were related with lower serum TC and LDLc after adjustment for total energy intake. Similar results were observed in two large cross-sectional studies. In the European Prospective Investigation into Cancer and Nutrition (EPIC-Norfolk) study, a 289 mg/d or 281 mg/d (in men/women) increase of phytosterols intake was correlated to 4.1%/2.4% decrease in serum TC and 3.5%/3.0% decrease in LDLc, respectively [32]. Another study including 37,150 men and 40,502 women presents 2.6%/3.5% lower TC and 3.1%/3.2% lower LDLc in highest quintile in comparison with the lowest quintile of plant sterols in men and women, respectively [33].

The underlying mechanism of hypocholesterolemic activity of phytosterols was summarized in a recent review [34]. It is well accepted that phytosterols inhibit the intestinal absorption of dietary cholesterol due to their greater affinity for micelles [35]. Therefore, more cholesterol and its metabolites were excreted by feces. Recent studies also suggest that phytosterols might lower LDLc by upregulating intestinal cholesterol efflux transporters and receptor-mediated lipoprotein cholesterol uptake in response to the reduced supply of exogenous cholesterol [34]. Moreover, in high fat diet feeding hamsters, phytosterols supplementation leads to a remarkable increase in the biliary bile acid:cholesterol ratio, induces the expression of CYP7A1, which governs the synthesis of bile acid and controls its activity at the transcriptional level [36], and normalizes the expression of HNF4A, a key controller of bale acid metabolism [37, 38], indicating that phytosterols enhance bile acid synthesis.

Another important finding of this study was the lower SBP and DBP of the 4th quartile of dietary phytosterols than in the 1st quartile. The lower SBP was most likely interpreted by the lower body weight. The benefits of the decrease in blood pressure are apparent, because lower blood pressure has been shown to lower risk of cardiovascular morbidity [39]. Coker et al. reported that dietary supplementation of essential amino acids and phytosterols may reduce risk for metabolic syndrome and cardiovascular diseases by promoting the reductions of blood lipids and improving insulin resistance in overweight individuals with hypertriglyceridemia [40]. In our work, we did not observe significant correlations in FBG or 2 h-PG because, at least in part, diabetic patients were excluded from the study, and both FBG and 2 h-PG were in normal ranges at baseline.

The major limitation of this study is the cross-sectional and retrospective design which might have limitations in the confirmation of causal relationship. Therefore, long term cohort studies for verification of this issue are needed. Secondly, we included only those subjects who lived in Harbin, in consideration of the large population and vast territory of China, we should be rigorous to extrapolate this result to the general population.

In spite of those defects, this is the first web-based FFQ study that has investigated this issue. In our previous study, there were significantly positive correlations in the dietary intakes of 9 food groups and 23 nutrients between the IDQC and 3-day diet records [24], these data suggested that the intake of phytosterols assessed by using IDQC might reflect a long-term and stable habitual intake of phytosterols from habitual diets in this population. We firstly reported that higher dietary phytosterols were associated with lower BMI, WC, blood pressure, serum TC and LDLc and lower prevalence of overweight/obesity and abdominal obesity, which provided practical significances in nutritional counseling as the importance for prevention of dyslipidemia, obesity and cardiovascular diseases. For overweight/obese and hypercholesterolemia clients, advice of consuming more plant sterols-rich foods may be useful.

Conclusions

Overall, our study firstly reported that dietary phytosterols were negatively associated with BMI, WC, SBP, DBP, serum TC and LDLc. Higher dietary phytosterols were also associated with lower prevalence of overweight/obesity and abdominal obesity. Further studies are needed to verify the causal association and explore the potential mechanism.

Abbreviations

2 h-PG: 

2 h-postprandial glucose

BMI: 

Body mass index

CI: 

Confidence interval

CVDs: 

Cardiovascular diseases

DBP: 

Diastolic blood pressure

FBG: 

Fasting blood glucose

FFQ: 

Food frequency questionnaire

HDLc: 

High density lipoprotein cholesterol

IDQC: 

Internet-based dietary questionnaire for Chinese

LDLc: 

Low density lipoprotein cholesterol

OR: 

Odds ratio

RCTs: 

Randomized controlled trials

SBP: 

Systolic blood pressure

TC: 

Total cholesterol

TG: 

Triglycerides

WC: 

Waist circumference

Declarations

Acknowledgements

We would like to thank the respondents who voluntarily took part in this study.

Funding

This study was supported by the National Natural Science Fund of China (No. 81573133) and Nature Science Fund of Heilongjiang provience (No. H2016018).

Availability of data and materials

Data and all materials supporting this research are available from the corresponding author on reasonable request.

Authors’ contributions

R-NF and C-HS were responsible for the study concept and design; Y-CL, P-PG, and MZ performed the experiment and collected the data; Y-CL carried out the analysis and interpretation of data; Y-CL and C-LL wrote the paper; RL, X-NJ contributed to the critical revision of the manuscript; R-NF and C-HS were responsible for obtaining funds and supervision. All authors read and approved the final manuscript.

Ethics approval and consent to participate

The study complies with the Declaration of Helsinki and was approved by the Human Research Ethics Committee of the Harbin Medical University (approval code [2015] 006). Online informed consent was obtained from all participants.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

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Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, People’s Republic of China
(2)
Department of General Surgery, the Second Affiliated Hospital of Harbin Medical University, Harbin, People’s Republic of China
(3)
Department of Food and School Hygiene, Dalian Center for Disease Control and Prevention, Dalian, People’s Republic of China

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© The Author(s). 2018

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