Preventive Medicine 67 (2014) 154–159
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Preventive Medicine journal homepage: www.elsevier.com/locate/ypmed
Gender differences in the relationship between risk of hypertension and fruit intake Hong Ji Song a, Yu Jin Paek a, Min Kyu Choi b, Hae-Jeung Lee c,⁎ a b c
Department of Family Medicine, Hallym University Sacred Heart Hospital, College of Medicine, Hallym University, Anyang-si, South Korea Department of Family Medicine, Kangnam Sacred Heart Hospital, College of Medicine, Hallym University, Seoul, South Korea Department of Food & Nutrition, Eulji University, Seongnam-si, South Korea
a r t i c l e
i n f o
Available online 18 July 2014 Keywords: Hypertension Fruit Obesity Gender differences
a b s t r a c t Objective. To investigate the relationship between hypertension and fruit intake in an Asian population. Method. This study was based on the data from 2007, 2008 and 2009 Korea National Health and Nutrition Examination Survey. In the final analysis, a total of 9791 subjects (men = 3819, women = 5972) were included. Daily energy and nutrient intakes were assessed using 24-h recall. The odds ratios (ORs) for hypertension were assessed by using logistic regression and multivariable models. Results. A total of 10.6% of individuals were classified as having hypertension. Compared with the lowest quintile of fruit intake, the fifth quintile showed the lowest likelihood of hypertension (OR 0.73; 95% confidence interval [CI], 0.61–0.88) after adjusting for age and gender. For women, the likelihood of hypertension in the 2nd, 3rd, 4th and 5th quintiles of fruit intake decreased to 0.67 (95% CI, 0.34–1.30), 0.76 (0.56–1.05), 0.90 (0.67–1.22) and 0.54 (0.38–0.77), respectively, after adjusting for confounding factors (P value for trend = 0.0011). An inverse association of fruit intake and hypertension was shown only in non-obese women. For men and obese women, there was no relationship between fruit intake and hypertension. Conclusion. Dietary fruit recommendation for hypertension should be taken into account together with ethnic background, gender as well as the presence of obesity in individuals. © 2014 Elsevier Inc. All rights reserved.
Introduction Hypertension is a leading risk factor for vascular mortality, including stroke, heart and renal diseases (Chobanian et al., 2003; James et al., 2014; Kalaitzidis and Bakris, 2010; Lewington et al., 2002). It is also a major public health concern with a global prevalence of 26% in adults (Kearney et al., 2005). A reduction in cardiovascular morbidity and mortality could be achieved through even a slight reduction in the mean blood pressure of this population (Bulpitt et al., 2006; Chobanian, et al, 2003; Richart et al., 2011). For prevention and management of hypertension, The American Heart, Lung and Blood Institute recommends adherence to the DASH (Dietary Approaches to Stop Hypertension) diet, which is a diet based on high intakes of fruits and vegetables, and low intakes of fat and sodium (Chobanian et al., 2003; James et al., 2014). The European Society of Hypertension also recommends an increase in the consumption of vegetables and fruits to lower blood pressure (Mancia et al., 2013). Based on previous research, including
⁎ Corresponding author at: Department of Food & Nutrition, Eulji University, 553 Sangseong-daero, Sujeong-gu, Seongnam-si, Gyeonggi-do, 461-713, South Korea. Fax: +82 31 740 7370. E-mail addresses: [email protected], [email protected] (H.-J. Lee).
http://dx.doi.org/10.1016/j.ypmed.2014.07.016 0091-7435/© 2014 Elsevier Inc. All rights reserved.
observational studies and intervention studies, evidence for blood pressure-lowering effects of an increased consumption of vegetables and fruits has been accepted (Boeing et al., 2012). However, one randomized controlled trial with a cross-over design could not provide strong enough evidence to support blood pressure-lowering effects due to an increase in the consumption of vegetables and fruits (Berry et al., 2010). Fresh fruits are recommended with caution in overweight patients as their high carbohydrate content may promote weight gain (Mancia et al., 2013). In some previous studies, when data for intake of fruits and vegetables were analyzed separately, reduction in prevalence of hypertension from consumption of fruits was smaller and less significant than that for vegetables (Alonso et al., 2004). When the associations between individual food groups that comprise the DASH diet components and blood pressure were examined, individual components, with the exception of low-fat milk, had no independent relationship with blood pressure (Harrington et al., 2013). In a cohort study, a significant inverse relationship between fruit and vegetable consumption and the risk of hypertension was shown only among participants with low olive oil consumption (b15 g/day), suggesting a sub-additive effect of some food items (Nunez-Cordoba et al., 2009). If there is a sub-additive effect of some food items on the protective effect of fruit consumption with respect to hypertension, then the inverse relationship between the risk of hypertension and increased in fruit intake
H.J. Song et al. / Preventive Medicine 67 (2014) 154–159
may be different in Asian populations as food items consumed on a daily basis vary between Western and Asian countries. Therefore, there are still areas of uncertainty concerning provision of advice to general Asian population to increase intakes of fruits above the usual amount. The aim of the present study was to investigate any direct, independent relationship between the prevalence of hypertension and fruit intake in Asian subjects using data from Korea National Health and Nutrition Examination Survey (KNHANES), a nationally representative survey conducted in the Republic of Korea.
Methods Study population and exclusions This study was based on the data from 2007, 2008 and 2009 KNHANES, which was the 4th KNHANES provided by Korea Centers for Disease Control and Prevention (KCDC). The 4th KNHANES database has been used for previous epidemiologic studies (Choi et al., 2013; Kim et al., 2013; Shin et al., 2013). The sample for KNHANES was selected using a stratified, multistage, cluster-sampling design with proportional allocation based on the National Census Registry. The 4th KNHANES database was comprised of 4594, 9744 and 10,533 individuals, respectively, for a total of 24,871 participants. Subjects aged 19 to 64 years were included (n = 14,334). We excluded participants using the following exclusion criteria: a) pregnant women (n = 132), b) subjects who had a diagnosis of or receiving treatment for hypertension (n = 1663) at the time of the survey, c) subjects with no blood pressure data (n = 863) and d) subjects with no energy intake data (n = 1,728). Additionally, subjects reporting unrealistic daily total energy intakes (b 500 kcal or N6000 kcal) were excluded (n = 157), as per other studies with similar study designs (Thomson et al., 2011; van der Schouw et al., 2005). As a result, a total of 9791 subjects was included in the final analysis (men = 3819, women = 5972). The study was conducted in accordance with the Ethical Principles for Medical Research Involving Human Subjects, as defined by the Helsinki Declaration. All study subjects were provided with written informed consent for the survey. Moreover, de-identified data were used in the study.
Measurements KNHANES included well-established questions to determine demographic and socioeconomic characteristics of the subjects. Questions on age, gender, education level, income, physical activity, smoking habits and alcohol consumption were incorporated. Daily energy and nutrient intakes were assessed using one 24 h recall. The height and weight of subjects were measured with participants wearing light clothing and no shoes. Body mass index (BMI) was calculated as weight (in kilograms) divided by height (in meters squared). To define obese group, BMI was categorized above 25 kg/m2 (Weisell, 2002). Moreover, well-trained observers manually measured blood pressure using a mercury sphygmomanometer (Baumanometer; Baum, Copiague, NY). Hypertension was defined as having a systolic pressure of 140 mm Hg (or higher) or a diastolic pressure of 90 mm Hg (or higher). Fruit intake was calculated considering fresh fruit and 100% fruit juice intake, and 3819 men and 5972 women were categorized into separate quintiles. Fruit intake was categorized into quartiles. Alcohol consumption was categorized into four groups: nondrinker, less than once a month, once a month (less than heavy drinker) and heavy drinker. Smoking status was categorized into non-smoker, ever-smoker and current smoker (two groups: b1 pack per day and ≥ 1 pack per day). Physical activity was categorized into four groups: no exercise with irregular walking, regular walking, regular moderatelevel activity and regular vigorous-level activity.
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Statistical analyses Means and standard errors (SEs) of continuous variables were calculated in the hypertension and non-hypertension groups. Proportions of each covariate in categorical variables were calculated for each group. The odds ratios for hypertension of dependent variables were assessed by using logistic regression after adjusting for age and gender. The mean or proportion of BMI, fasting glucose, triglycerides, LDL-C, HDLC, energy, sodium intake, smoking, alcohol consumption, physical activity, education, income, education for hypertension and survey year (for men and women) and menopause (for women only) were different in the hypertension and non-hypertension groups (P b 0.05). Therefore, the multivariable model was additionally adjusted for these factors. For subgroup analysis, we conducted a stratified analysis by obesity or smoking status. We conducted a further stratified analysis by gender, obesity, and smoking status. All analyses were performed using SAS statistical software (version 9.2; SAS Institute Inc., Cary, NC). Results Out of 9791 participants, 10.6% were classified as having hypertension. There was a significant difference in the distribution of prevalence of hypertension and fruit intake between men and women. Obesity has been considered as one of the important risk factors for hypertension (Eckel et al., 2014). Therefore, we analyzed the data in subgroups by gender and obesity (Table 1). The first and second quintiles for men reported a daily fruit intake of 0, and the fifth quintile for men had about 502.08 g of fruit intake per day. In the first and the fifth quintiles for women, the daily fruit intake was 0 and 613.23 g/day, respectively. In the whole population, compared to the lowest quintile for fruit intake, the fifth quintile showed the lowest likelihood of developing hypertension, with an odds ratio (OR) of 0.73 (95% confidence interval [CI], 0.61–0.88) after adjusting for age and gender. In multivariable models, odds ratios (ORs) for the likelihood of developing hypertension in the third, fourth and fifth quintiles for fruit intake decreased to 0.83 (95% CI, 0.68–1.03), 0.85 (95% CI, 0.69–1.03) and 0.76 (95% CI, 0.62–0.94), respectively. Although the confidence intervals of the odds ratio for the third and fourth quintiles were not significant, there was a significant trend (P value for trend = 0.0068). For women, the likelihood of developing hypertension in the second, third, fourth and fifth quintiles for fruit intake decreased to 0.67, 0.76, 0.90 and 0.54, respectively. Although the confidence intervals of odds ratio for the second, third and fourth quintiles were not significant, there was a significant positive trend (P value for trend = 0.0011). However, for men, there was no relationship between fruit intake and the likelihood of developing hypertension (Table 2). Subgroup analysis according to BMI (b25, ≥25) revealed that, for non-obese women, the likelihood for hypertension in the second, third and fourth quintiles for fruit intake decreased to 0.70, 0.75 and 0.48, respectively. Although the confidence intervals of odds ratio for the second and third quintiles were not significant, there was a significant positive trend (P value for trend = 0.0011) (Table 3). However, for obese women, there was no relationship between fruit intake and the likelihood of hypertension (Table 3). For both obese and nonobese men, no relationship between fruit intake and the likelihood of hypertension was found (data not shown). Subgroup analysis for smoking status showed that the likelihood of hypertension in the second, third and fourth quintiles for fruit intake in the non-smoker group decreased to 0.88, 0.81 and 0.73, respectively. Although the confidence intervals of odds ratio for the second and third quintiles were not significant, there was a significant positive trend (P value for trend = 0.0214) (Table 4). However, after subgroup analysis according to gender, obesity and smoking, there was no association between fruit intake and the likelihood of hypertension for men and obese women (data not shown). Since more than 88% of women were non-
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Table 1 Baseline characteristics of participants. Men, BMI b 25
Men, BMI ≥ 25
Women, BMI b 25
Women, BMI ≥ 25
P value
Hypertension (n = 321)
Nonhypertension (n = 1013)
P value
Hypertension (n = 214)
Nonhypertension (n = 4419)
P value
Hypertension (n = 183)
Nonhypertension (n = 1156)
P value
46.2 ± 0.6 123.7 ± 0.9 82.0 ± 0.6 22.8 ± 0.1 100.2 ± 1.2 169.7 ± 7.6 115.2 ± 1.9 48.7 ± 0.7 2248.9 ± 45.2 6044.2 ± 194.9 150.2 ± 16.5
40.8 ± 0.3 111.7 ± 0.2 74.1 ± 0.1 22.2 ± 0.0 94.4 ± 0.5 131.9 ± 2.3 108.1 ± 0.7 46.9 ± 0.2 2288.1 ± 17.7 5917.0 ± 67.4 166.4 ± 6.8
b0.0001 b0.0001 b0.0001 b0.0001 b0.0001 b0.0001 0.0005 0.0112 0.4288 0.538 0.3642
43.9 ± 0.6 123.5 ± 0.8 84.0 ± 0.6 27.6 ± 0.1 103.4 ± 1.6 214.1 ± 9.1 116.8 ± 2.1 43.4 ± 0.5 2364.4 ± 48.3 6204.6 ± 185.6 158.3 ± 16.6
41.2 ± 0.4 113.4 ± 0.3 75.7 ± 0.2 27.2 ± 0.1 99.0 ± 0.7 183.1 ± 4.2 116.1 ± 1.0 42.3 ± 0.3 2318.3 ± 27.2 6259.0 ± 100.2 154.8 ± 9.1
b0.0001 b0.0001 b0.0001 0.0016 0.011 0.002 0.7655 0.0571 0.4062 0.7919 0.8522
49.4 ± 0.7 127.0 ± 1.1 83.1 ± 0.6 22.4 ± 0.1 100.2 ± 2.2 124.8 ± 5.6 124.0 ± 2.3 51.5 ± 0.8 1572.3 ± 44.7 3982.4 ± 175.1 148.8 ± 15.1
39.7 ± 0.2 107.5 ± 0.1 71.2 ± 0.1 21.5 ± 0 90.9 ± 0.2 92.9 ± 1.0 108.3 ± 0.4 52.2 ± 0.2 1677.9 ± 9.2 4279.4 ± 38.3 221.7 ± 5.0
b0.0001 b0.0001 b0.0001 b0.0001 b0.0001 b0.0001 b0.0001 0.3307 0.0142 0.0954 0.0014
49.0 ± 0.7 126.4 ± 1.2 82.1 ± 0.7 28.0 ± 0.2 100.4 ± 2.1 149.7 ± 5.8 127.7 ± 2.7 48.1 ± 0.8 1588.3 ± 48.0 4106.6 ± 176.0 180.3 ± 20.2
44.3 ± 0.3 112.1 ± 0.3 73.8 ± 0.2 27.4 ± 0.1 97.7 ± 0.7 127.4 ± 2.6 119.5 ± 0.9 47.2 ± 0.3 1624.6 ± 18.0 4379.8 ± 104.1 217.4 ± 10.0
b0.0001 b0.0001 b0.0001 0.0029 0.1471 0.0005 0.0046 0.2076 0.4589 0.3133 0.1008
56.8 12.4 15.9 14.9
52.1 15.2 16.6 16.1
0.4028 49.8 17.8 15.0 17.5
51.8 16.2 16.0 16.0
0.794
45.3 16.4 25.7 12.6
33.9 20.4 22.8 22.9
0.0002 43.2 16.4 18.0 22.4
40.4 15.9 21.0 22.7
0.7991
17.6 36.9 22.1 23.4
20.6 30.2 26.2 23.1
0.0786 20.2 33.8 21.8 24.3
18.5 31.1 23.3 27.1
0.5999 89.1 2.4 6.6 1.9
88.2 5.8 5.3 0.7
0.0334 92.9 3.3 3.3 0.6
88.9 5.8 4.2 1.1
0.4047
2.6 10.3 55.8 31.4
4.0 21.5 54.8 19.7
b0.0001 3.5 16.5 48.3 31.8
4.4 20.8 50.6 24.3
0.0441 19.9 37.0 31.8 11.4
12.6 41.0 41.6 4.8
b0.0001 17.6 34.6 37.9 9.9
14.6 42.5 38.2 4.8
0.0133
42.0
39.3
0.1383 41.5
41.9
0.2392 43.8
46.6
0.6185 37.8
42.3
0.2786
27.9 7.1 23.1
30.4 10.4 19.9
24.6 6.7 27.2
28.5 7.5 22.1
29.5 11.4 15.2
29.5 8.9 15.0
26.7 14.4 21.1
29.2 11.0 17.4
17.3 15.7 32.7 34.3
9.9 10.9 30.6 48.6
b0.0001 13.0 10.8 27.9 48.3
9.3 10.2 30.3 50.2
0.2662 30.3 16.6 43.6 9.5
11.5 9.4 36.3 42.9
b0.0001 39.6 18.7 29.7 12.1
24.5 16.3 35.4 23.9
b0.0001
31.4 21.4 27.5 19.7 1.3
24.5 24.4 25.7 25.4 0.3
0.0198 27.9 29.2 22.6 20.4 0.009 1.3
22.4 27.1 23.8 26.7 0.5
0.0589 31.3 25.6 23.7 19.4 0.1482 1.0
22.3 23.2 27.5 27.0 0.1
0.0047 28.0 29.7 21.4 20.9 b0.0001 1.7
28.8 27.5 21.6 22.2 0.1
0.9344
12.7 25.1 62.2
18.3 40.4 41.2
b0.0001 14.6 29.9 55.5
17.4 40.3 42.4
0.0002 9.4 32.7 57.9
17.7 40.5 41.8
b0.0001 10.4 26.8 62.8
18.0 40.1 41.9
b0.0001
All data represent mean ± standard error or number (%) of participants. a Hypertension was defined as having a systolic pressure of 140 mm Hg (or higher) or diastolic pressure of 90 mm Hg (or higher). b Heavy drinker was defined as consuming alcohol twice or more per week and having at least 7 drinks/occasion for men and 5 drinks/occasion for women.
0.0003
H.J. Song et al. / Preventive Medicine 67 (2014) 154–159
Nonhypertension (n = 2170)
Hypertension (n = 315) Age, years Systolic blood pressure Diastolic blood pressure Body mass index (kg/m2) Fasting glucose (mg/dL) Triglycerides LDL-cholesterol (mg/dL) HDL-cholesterol (mg/dL) Energy (kcal/day) Sodium (mg/day) Fruits intake (g/day) Fruit intake (%) 1st (Lowest) 2nd 3rd 4th (Highest) Smoking (%) Non-smoker Ever-smoker Current smoker, b1 pack per day Current smoker, ≥1 pack per day Alcohol intake (%) Non-drinker Less than once a month Once a month — less than heavy drinker Heavy drinkerb Physical activity (%) No regular exercise with irregular walking Regular walking Regular, moderate-level activity Regular, vigorous-level activity Education (%) Elementary school Middle school High school College or higher degree Income (%) 1st (lowest) 2nd 3rd 4th (highest) Received hypertension education (%) Survey year (%) 2007 2008 2009
a
H.J. Song et al. / Preventive Medicine 67 (2014) 154–159
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Table 2 Odds ratio (95% confidence interval) of risk of hypertensiona according to fruit intake. Category
Total number
Range of Category (g/day)
Median of total fruit intake (g/day)
No. of cases
Age and gender adjusted ORs (95% CI)
Multivariate-adjusted ORsb (95% CI)
Total Q1 and Q2
4134
0
0
515
Reference
Reference
Q3 Q4 Q5
1740 1959 1958
0 b –129.9 130.0–345.2 345.5–6523.3
58.0 212.3 577.4 P value for trendc
161 186 171
0.82 (0.68–1.00) 0.84 (0.70–1.00) 0.73 (0.61–0.88) 0.0007
0.83 (0.68–1.03) 0.85 (0.69–1.03) 0.76 (0.62–0.94) 0.0068
Men Q1 and Q2
1995
0
0
339
Reference
Reference
298 762 764
0 b –52.3 52.7–278.8 280.7–3108.8
11.4 156.1 502.1 P value for trendc
41 121 135
0.82 (0.57–1.16) 0.90 (0.71–1.13) 1.01 (0.81–1.26) 0.9758
0.83 (0.57–1.21) 0.90 (0.70–1.16) 1.08 (0.84–1.34) 0.6117
2139 248 1196 1198 1191
0 0 b –14.3 14.4–176.0 176.3–393.2 393.2–6523.3
0 3.6 100.0 258.7 613.2 P value for trendc
176 11 73 84 53
reference 0.58 (0.31–1.09) 0.68 (0.51–0.91) 0.77 (0.59–1.02) 0.45 (0.32–0.61) b0.0001
reference 0.67 (0.34–1.30) 0.76 (0.56–1.05) 0.90 (0.67–1.22) 0.54 (0.38–0.77) 0.0011
Q3 Q4 Q5
Women Q1 Q2 Q3 Q4 Q5
Abbreviations: CI, confidence interval; ORs, odds ratios; Q, quintile. a Hypertension was defined as having a systolic pressure of 140 mm Hg (or higher) or diastolic pressure of 90 mm Hg (or higher). b Multivariate-adjusted models were adjusted for age, body mass index, fasting glucose, triglycerides, LDL-C, HDL-C, energy, sodium intake, smoking, alcohol consumption, physical activity, education, income, education for hypertension, survey year (for men and women), and menopause (for women only). c Tests for linear trends across categories were conducted by treating the median of each category as a continuous variable.
smokers, subgroup analysis for ever-smoker and smoker women could not be performed. The significant association between fruit intake and the likelihood of hypertension was consistent only in the non-smoker and non-obese women (data not shown).
Discussion The present study documents the association between fruit consumption and the prevalence of hypertension in an Asian context. Previous studies reported that increasing consumption of vegetables and fruits reduced the risk for developing hypertension (Appel et al., 2006; Ascherio et al., 1996; Berkow and Barnard, 2005; Miura et al., 2004; Sacks et al., 2001). However, fruits and vegetables have different nutritional compositions, and the reduction of hypertension prevalence was not significant for fruit intake in a sub-analysis (Alonso et al., 2004).
Interestingly, there was a clear difference between men and women for the relationship between fruit intake and the prevalence of hypertension in this study. Gender-specific differences have been found in chronic non-communicable diseases, including metabolic and cardiovascular diseases, and cancer (Song et al., 2008; Vlassoff, 2007). Different findings for men and women may result from the complex influence of genetic differences, hormonal differences, health behaviors, responses to social and environmental factors, and due to interactions between all of these factors. The renin–angiotensin system is a wellknown regulator of blood pressure and plays an important role in the gender-specific pathogenesis of cardiovascular disease (Bauer et al., 2011). In animal models of hypertension, a female-specific blood pressure quantitative trait loci region was detected (Herrera et al., 2006). Recent animal studies have suggested that there are gender-specific hypertension genes and different mechanisms for response to treatment between the two genders (Fava et al., 2012; Herrera et al., 2012;
Table 3 Odds ratio (95% confidence interval) of risk of hypertensiona according to fruit intake in obese and non-obese women. Category
Total number
Range of Category (g/day)
Median of Category (g/day)
No. of cases
Age adjusted ORs (95% CI)
Multivariate-adjusted ORsb (95% CI)
BMI b 25 Q1 Q2 Q3 Q4
1593 723 1156 1161
0 0 b–103.1 103.8–310.7 310.9–6523.3
0 44.7 204.0 524.5 P value for trendc
97 29 54 34
Reference 0.65 (0.42–1.01) 0.68 (0.48–0.97) 0.40 (0.27–0.60) b.0001
Reference 0.70 (0.44–1.12) 0.75 (0.51–1.10) 0.48 (0.31–0.75) 0.0011
BMI ≥ 25 Q1 Q2 Q3 Q4
546 123 336 334
0 0 b–68.2 70.2–310.9 310.9–2478.5
0 28.5 187.3 527.1 P value for trendc
79 19 44 41
Reference 1.04 (0.60–1.80) 0.83 (0.56–1.24) 0.74 (0.49–1.11) 0.1376
Reference 1.05 (0.58–1.91) 0.88 (0.56–1.37) 0.77 (0.48–1.24) 0.2765
Abbreviations: CI, confidence interval; ORs, odds ratios; Q, quartile. a Hypertension was defined as systolic pressure of 140 mm Hg (or higher) or diastolic pressure of 90 mm Hg (or higher). b Multivariate-adjusted models were adjusted for age, body mass index, fasting glucose, triglycerides, LDL-C, HDL-C, energy, sodium intake, smoking, alcohol consumption, physical activity, education, income, education for hypertension, survey year, and menopause. c Tests for linear trends across categories were conducted by treating the median of each category as a continuous variable.
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Table 4 Odds ratio (95% confidence interval) of risk of hypertensiona according to fruit intake in non-, ever- and current smokers. Category
Total number
Range of Category (g/day)
Median of Category (g/day)
No. of cases
Age and gender adjusted ORs (95% CI)
Multivariate-adjusted ORsb (95% CI)
Non-smoker Q1 Q2 Q3 Q4
2092 919 1497 1502
0 0 b–104.5 104.6–323.5 324.2–6523.3 P value for trendc
0 50.8 205.2 545.6
197 68 112 99
reference 0.83 (0.61–1.11) 0.75 (0.58–0.96) 0.62 (0.48–0.81) 0.0002
reference 0.88 (0.64–1.21) 0.81 (0.62–1.06) 0.73 (0.55–0.97) 0.0214
Ever-smoker Q1 Q2 Q3 Q4
688 72 380 381
0 0 b–14.4 15.1–235.0 235.6–2478.5 P value for trendc
0 4.7 116.9 468.9
111 10 51 61
reference 0.89 (0.60–1.80) 0.77 (0.54–1.12) 0.93 (0.66–1.32) 0.1376
reference 1.01 (0.46–2.26) 0.71 (0.47–1.07) 1.02 (0.68–1.52) 0.9831
0
201
reference
reference
52.0 334.1
38 74
0.79 (0.54–1.15) 0.88 (0.66–1.17) 0.3654
0.72 (0.47–1.09) 0.93 (0.68–1.29) 0.6656
Current smoker Q1 1329 Q2 Q3 327 Q4 552
0 0 b–137.2 139.1–2733.0 P value for trendc
Abbreviations: CI, confidence interval; ORs, odds ratios; Q, quartile. a Hypertension was defined as having a systolic pressure of 140 mm Hg (or higher) or diastolic pressure of 90 mm Hg (or higher). b Multivariate-adjusted models were adjusted for age, gender, body mass index, fasting glucose, triglycerides, LDL-C, HDL-C, energy, sodium intake, alcohol consumption, physical activity, education, income, education for hypertension, survey year and menopause (for women only). c Tests for linear trends across categories were conducted by treating the median of each category as a continuous variable.
Hoffman et al., 2013; Park et al., 2012). Although the epigenetic mechanism that results in gender-specific gene expression has yet to be discovered, there is accumulating evidence that demonstrates gender-specific relationships between diverse environmental influences on placental functions and the risk of disease later in life (Gabory et al., 2013). Low potassium and high sodium intakes (He et al., 2013; Sacks et al., 2001; Zhang et al., 2013) and sodium-to-potassium intake ratio (Castro and Raij, 2013) have been reported to be associated with high blood pressure. In a previous study, daily sodium intake of men was much higher than that of women, and there was a clear independent relationship between high sodium intake and an increased likelihood of being overweight in men but not in women (Song et al., 2013). However, after adjusting for sodium intake, there was no change in the difference between men and women in our study. In a previous study carried out in an Asian population, former smokers with abdominal obesity had a higher risk for subsequent hypertension than current smokers (Onat et al., 2009). Therefore, we analyzed the data using the smoking status of subjects and the significant association between fruit intake and the likelihood of hypertension was consistent only in the non-smoker and non-obese women. The inverse association between higher levels of potassium intake and blood pressure was attenuated after adjusting for major lifestyle and dietary factors (Shin et al., 2013). Therefore, the mechanism for the inverse association of fruits for high blood pressure cannot be explained by the high potassium intakes alone and instead, must be due to both high potassium intakes and other gender-specific different factors and obesity. Women are generally more prone to proinflammatory status and autoimmune activation. Fruit intake might be of highest benefit through preventing enhanced low-grade inflammation (Onat and Can, 2014). Our study had several limitations. Fruit intake was estimated by using one 24-h dietary recall. Ideally, at least three 24-h recalls would be done, one on a day-off and two on working days. However, this could not be easily applied to a large population. To minimize this bias, 79% of 2007–2009 KNHANES were performed on week days and 21% on weekends. The other limitation was the cross-sectional study design using dietary recall. A randomized controlled trial design can provide better evidence. However, a randomized controlled trial could not be easily applied to a large number of participants in a general population. Considering the reliability of questionnaire-derived dietary
information and the stability of food habits over time for adults (Jensen et al., 1984), 24-h recall can serve as one of the most costeffective and feasible replacements for a randomized controlled trial for research using a large number of human subjects. Causal relationships cannot be confirmed from such cross-sectional design. To minimize this limitation, we excluded data from people who were diagnosed with hypertension or had received treatment for hypertension. Conclusions Even though longitudinal studies and randomized controlled trials are needed to confirm the relationship between fruit intake and the reduction in hypertension risk, there is a potential opportunity to prevent hypertension and improve the prognosis of hypertension, in individuals who have it, through optimal management of dietary fruit intake. The present study suggested that dietary fruit recommendations for hypertension should consider ethnic and gender-specific differences and obesity. Additional studies are needed to clarify the mechanism by which dietary fruit intake helps to lower hypertension risk. Conflict of interest statement The authors have no conflicts of interest.
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Contents lists available at ScienceDirect
Preventive Medicine journal homepage: www.elsevier.com/locate/ypmed
Gender differences in the relationship between risk of hypertension and fruit intake Hong Ji Song a, Yu Jin Paek a, Min Kyu Choi b, Hae-Jeung Lee c,⁎ a b c
Department of Family Medicine, Hallym University Sacred Heart Hospital, College of Medicine, Hallym University, Anyang-si, South Korea Department of Family Medicine, Kangnam Sacred Heart Hospital, College of Medicine, Hallym University, Seoul, South Korea Department of Food & Nutrition, Eulji University, Seongnam-si, South Korea
a r t i c l e
i n f o
Available online 18 July 2014 Keywords: Hypertension Fruit Obesity Gender differences
a b s t r a c t Objective. To investigate the relationship between hypertension and fruit intake in an Asian population. Method. This study was based on the data from 2007, 2008 and 2009 Korea National Health and Nutrition Examination Survey. In the final analysis, a total of 9791 subjects (men = 3819, women = 5972) were included. Daily energy and nutrient intakes were assessed using 24-h recall. The odds ratios (ORs) for hypertension were assessed by using logistic regression and multivariable models. Results. A total of 10.6% of individuals were classified as having hypertension. Compared with the lowest quintile of fruit intake, the fifth quintile showed the lowest likelihood of hypertension (OR 0.73; 95% confidence interval [CI], 0.61–0.88) after adjusting for age and gender. For women, the likelihood of hypertension in the 2nd, 3rd, 4th and 5th quintiles of fruit intake decreased to 0.67 (95% CI, 0.34–1.30), 0.76 (0.56–1.05), 0.90 (0.67–1.22) and 0.54 (0.38–0.77), respectively, after adjusting for confounding factors (P value for trend = 0.0011). An inverse association of fruit intake and hypertension was shown only in non-obese women. For men and obese women, there was no relationship between fruit intake and hypertension. Conclusion. Dietary fruit recommendation for hypertension should be taken into account together with ethnic background, gender as well as the presence of obesity in individuals. © 2014 Elsevier Inc. All rights reserved.
Introduction Hypertension is a leading risk factor for vascular mortality, including stroke, heart and renal diseases (Chobanian et al., 2003; James et al., 2014; Kalaitzidis and Bakris, 2010; Lewington et al., 2002). It is also a major public health concern with a global prevalence of 26% in adults (Kearney et al., 2005). A reduction in cardiovascular morbidity and mortality could be achieved through even a slight reduction in the mean blood pressure of this population (Bulpitt et al., 2006; Chobanian, et al, 2003; Richart et al., 2011). For prevention and management of hypertension, The American Heart, Lung and Blood Institute recommends adherence to the DASH (Dietary Approaches to Stop Hypertension) diet, which is a diet based on high intakes of fruits and vegetables, and low intakes of fat and sodium (Chobanian et al., 2003; James et al., 2014). The European Society of Hypertension also recommends an increase in the consumption of vegetables and fruits to lower blood pressure (Mancia et al., 2013). Based on previous research, including
⁎ Corresponding author at: Department of Food & Nutrition, Eulji University, 553 Sangseong-daero, Sujeong-gu, Seongnam-si, Gyeonggi-do, 461-713, South Korea. Fax: +82 31 740 7370. E-mail addresses: [email protected], [email protected] (H.-J. Lee).
http://dx.doi.org/10.1016/j.ypmed.2014.07.016 0091-7435/© 2014 Elsevier Inc. All rights reserved.
observational studies and intervention studies, evidence for blood pressure-lowering effects of an increased consumption of vegetables and fruits has been accepted (Boeing et al., 2012). However, one randomized controlled trial with a cross-over design could not provide strong enough evidence to support blood pressure-lowering effects due to an increase in the consumption of vegetables and fruits (Berry et al., 2010). Fresh fruits are recommended with caution in overweight patients as their high carbohydrate content may promote weight gain (Mancia et al., 2013). In some previous studies, when data for intake of fruits and vegetables were analyzed separately, reduction in prevalence of hypertension from consumption of fruits was smaller and less significant than that for vegetables (Alonso et al., 2004). When the associations between individual food groups that comprise the DASH diet components and blood pressure were examined, individual components, with the exception of low-fat milk, had no independent relationship with blood pressure (Harrington et al., 2013). In a cohort study, a significant inverse relationship between fruit and vegetable consumption and the risk of hypertension was shown only among participants with low olive oil consumption (b15 g/day), suggesting a sub-additive effect of some food items (Nunez-Cordoba et al., 2009). If there is a sub-additive effect of some food items on the protective effect of fruit consumption with respect to hypertension, then the inverse relationship between the risk of hypertension and increased in fruit intake
H.J. Song et al. / Preventive Medicine 67 (2014) 154–159
may be different in Asian populations as food items consumed on a daily basis vary between Western and Asian countries. Therefore, there are still areas of uncertainty concerning provision of advice to general Asian population to increase intakes of fruits above the usual amount. The aim of the present study was to investigate any direct, independent relationship between the prevalence of hypertension and fruit intake in Asian subjects using data from Korea National Health and Nutrition Examination Survey (KNHANES), a nationally representative survey conducted in the Republic of Korea.
Methods Study population and exclusions This study was based on the data from 2007, 2008 and 2009 KNHANES, which was the 4th KNHANES provided by Korea Centers for Disease Control and Prevention (KCDC). The 4th KNHANES database has been used for previous epidemiologic studies (Choi et al., 2013; Kim et al., 2013; Shin et al., 2013). The sample for KNHANES was selected using a stratified, multistage, cluster-sampling design with proportional allocation based on the National Census Registry. The 4th KNHANES database was comprised of 4594, 9744 and 10,533 individuals, respectively, for a total of 24,871 participants. Subjects aged 19 to 64 years were included (n = 14,334). We excluded participants using the following exclusion criteria: a) pregnant women (n = 132), b) subjects who had a diagnosis of or receiving treatment for hypertension (n = 1663) at the time of the survey, c) subjects with no blood pressure data (n = 863) and d) subjects with no energy intake data (n = 1,728). Additionally, subjects reporting unrealistic daily total energy intakes (b 500 kcal or N6000 kcal) were excluded (n = 157), as per other studies with similar study designs (Thomson et al., 2011; van der Schouw et al., 2005). As a result, a total of 9791 subjects was included in the final analysis (men = 3819, women = 5972). The study was conducted in accordance with the Ethical Principles for Medical Research Involving Human Subjects, as defined by the Helsinki Declaration. All study subjects were provided with written informed consent for the survey. Moreover, de-identified data were used in the study.
Measurements KNHANES included well-established questions to determine demographic and socioeconomic characteristics of the subjects. Questions on age, gender, education level, income, physical activity, smoking habits and alcohol consumption were incorporated. Daily energy and nutrient intakes were assessed using one 24 h recall. The height and weight of subjects were measured with participants wearing light clothing and no shoes. Body mass index (BMI) was calculated as weight (in kilograms) divided by height (in meters squared). To define obese group, BMI was categorized above 25 kg/m2 (Weisell, 2002). Moreover, well-trained observers manually measured blood pressure using a mercury sphygmomanometer (Baumanometer; Baum, Copiague, NY). Hypertension was defined as having a systolic pressure of 140 mm Hg (or higher) or a diastolic pressure of 90 mm Hg (or higher). Fruit intake was calculated considering fresh fruit and 100% fruit juice intake, and 3819 men and 5972 women were categorized into separate quintiles. Fruit intake was categorized into quartiles. Alcohol consumption was categorized into four groups: nondrinker, less than once a month, once a month (less than heavy drinker) and heavy drinker. Smoking status was categorized into non-smoker, ever-smoker and current smoker (two groups: b1 pack per day and ≥ 1 pack per day). Physical activity was categorized into four groups: no exercise with irregular walking, regular walking, regular moderatelevel activity and regular vigorous-level activity.
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Statistical analyses Means and standard errors (SEs) of continuous variables were calculated in the hypertension and non-hypertension groups. Proportions of each covariate in categorical variables were calculated for each group. The odds ratios for hypertension of dependent variables were assessed by using logistic regression after adjusting for age and gender. The mean or proportion of BMI, fasting glucose, triglycerides, LDL-C, HDLC, energy, sodium intake, smoking, alcohol consumption, physical activity, education, income, education for hypertension and survey year (for men and women) and menopause (for women only) were different in the hypertension and non-hypertension groups (P b 0.05). Therefore, the multivariable model was additionally adjusted for these factors. For subgroup analysis, we conducted a stratified analysis by obesity or smoking status. We conducted a further stratified analysis by gender, obesity, and smoking status. All analyses were performed using SAS statistical software (version 9.2; SAS Institute Inc., Cary, NC). Results Out of 9791 participants, 10.6% were classified as having hypertension. There was a significant difference in the distribution of prevalence of hypertension and fruit intake between men and women. Obesity has been considered as one of the important risk factors for hypertension (Eckel et al., 2014). Therefore, we analyzed the data in subgroups by gender and obesity (Table 1). The first and second quintiles for men reported a daily fruit intake of 0, and the fifth quintile for men had about 502.08 g of fruit intake per day. In the first and the fifth quintiles for women, the daily fruit intake was 0 and 613.23 g/day, respectively. In the whole population, compared to the lowest quintile for fruit intake, the fifth quintile showed the lowest likelihood of developing hypertension, with an odds ratio (OR) of 0.73 (95% confidence interval [CI], 0.61–0.88) after adjusting for age and gender. In multivariable models, odds ratios (ORs) for the likelihood of developing hypertension in the third, fourth and fifth quintiles for fruit intake decreased to 0.83 (95% CI, 0.68–1.03), 0.85 (95% CI, 0.69–1.03) and 0.76 (95% CI, 0.62–0.94), respectively. Although the confidence intervals of the odds ratio for the third and fourth quintiles were not significant, there was a significant trend (P value for trend = 0.0068). For women, the likelihood of developing hypertension in the second, third, fourth and fifth quintiles for fruit intake decreased to 0.67, 0.76, 0.90 and 0.54, respectively. Although the confidence intervals of odds ratio for the second, third and fourth quintiles were not significant, there was a significant positive trend (P value for trend = 0.0011). However, for men, there was no relationship between fruit intake and the likelihood of developing hypertension (Table 2). Subgroup analysis according to BMI (b25, ≥25) revealed that, for non-obese women, the likelihood for hypertension in the second, third and fourth quintiles for fruit intake decreased to 0.70, 0.75 and 0.48, respectively. Although the confidence intervals of odds ratio for the second and third quintiles were not significant, there was a significant positive trend (P value for trend = 0.0011) (Table 3). However, for obese women, there was no relationship between fruit intake and the likelihood of hypertension (Table 3). For both obese and nonobese men, no relationship between fruit intake and the likelihood of hypertension was found (data not shown). Subgroup analysis for smoking status showed that the likelihood of hypertension in the second, third and fourth quintiles for fruit intake in the non-smoker group decreased to 0.88, 0.81 and 0.73, respectively. Although the confidence intervals of odds ratio for the second and third quintiles were not significant, there was a significant positive trend (P value for trend = 0.0214) (Table 4). However, after subgroup analysis according to gender, obesity and smoking, there was no association between fruit intake and the likelihood of hypertension for men and obese women (data not shown). Since more than 88% of women were non-
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Table 1 Baseline characteristics of participants. Men, BMI b 25
Men, BMI ≥ 25
Women, BMI b 25
Women, BMI ≥ 25
P value
Hypertension (n = 321)
Nonhypertension (n = 1013)
P value
Hypertension (n = 214)
Nonhypertension (n = 4419)
P value
Hypertension (n = 183)
Nonhypertension (n = 1156)
P value
46.2 ± 0.6 123.7 ± 0.9 82.0 ± 0.6 22.8 ± 0.1 100.2 ± 1.2 169.7 ± 7.6 115.2 ± 1.9 48.7 ± 0.7 2248.9 ± 45.2 6044.2 ± 194.9 150.2 ± 16.5
40.8 ± 0.3 111.7 ± 0.2 74.1 ± 0.1 22.2 ± 0.0 94.4 ± 0.5 131.9 ± 2.3 108.1 ± 0.7 46.9 ± 0.2 2288.1 ± 17.7 5917.0 ± 67.4 166.4 ± 6.8
b0.0001 b0.0001 b0.0001 b0.0001 b0.0001 b0.0001 0.0005 0.0112 0.4288 0.538 0.3642
43.9 ± 0.6 123.5 ± 0.8 84.0 ± 0.6 27.6 ± 0.1 103.4 ± 1.6 214.1 ± 9.1 116.8 ± 2.1 43.4 ± 0.5 2364.4 ± 48.3 6204.6 ± 185.6 158.3 ± 16.6
41.2 ± 0.4 113.4 ± 0.3 75.7 ± 0.2 27.2 ± 0.1 99.0 ± 0.7 183.1 ± 4.2 116.1 ± 1.0 42.3 ± 0.3 2318.3 ± 27.2 6259.0 ± 100.2 154.8 ± 9.1
b0.0001 b0.0001 b0.0001 0.0016 0.011 0.002 0.7655 0.0571 0.4062 0.7919 0.8522
49.4 ± 0.7 127.0 ± 1.1 83.1 ± 0.6 22.4 ± 0.1 100.2 ± 2.2 124.8 ± 5.6 124.0 ± 2.3 51.5 ± 0.8 1572.3 ± 44.7 3982.4 ± 175.1 148.8 ± 15.1
39.7 ± 0.2 107.5 ± 0.1 71.2 ± 0.1 21.5 ± 0 90.9 ± 0.2 92.9 ± 1.0 108.3 ± 0.4 52.2 ± 0.2 1677.9 ± 9.2 4279.4 ± 38.3 221.7 ± 5.0
b0.0001 b0.0001 b0.0001 b0.0001 b0.0001 b0.0001 b0.0001 0.3307 0.0142 0.0954 0.0014
49.0 ± 0.7 126.4 ± 1.2 82.1 ± 0.7 28.0 ± 0.2 100.4 ± 2.1 149.7 ± 5.8 127.7 ± 2.7 48.1 ± 0.8 1588.3 ± 48.0 4106.6 ± 176.0 180.3 ± 20.2
44.3 ± 0.3 112.1 ± 0.3 73.8 ± 0.2 27.4 ± 0.1 97.7 ± 0.7 127.4 ± 2.6 119.5 ± 0.9 47.2 ± 0.3 1624.6 ± 18.0 4379.8 ± 104.1 217.4 ± 10.0
b0.0001 b0.0001 b0.0001 0.0029 0.1471 0.0005 0.0046 0.2076 0.4589 0.3133 0.1008
56.8 12.4 15.9 14.9
52.1 15.2 16.6 16.1
0.4028 49.8 17.8 15.0 17.5
51.8 16.2 16.0 16.0
0.794
45.3 16.4 25.7 12.6
33.9 20.4 22.8 22.9
0.0002 43.2 16.4 18.0 22.4
40.4 15.9 21.0 22.7
0.7991
17.6 36.9 22.1 23.4
20.6 30.2 26.2 23.1
0.0786 20.2 33.8 21.8 24.3
18.5 31.1 23.3 27.1
0.5999 89.1 2.4 6.6 1.9
88.2 5.8 5.3 0.7
0.0334 92.9 3.3 3.3 0.6
88.9 5.8 4.2 1.1
0.4047
2.6 10.3 55.8 31.4
4.0 21.5 54.8 19.7
b0.0001 3.5 16.5 48.3 31.8
4.4 20.8 50.6 24.3
0.0441 19.9 37.0 31.8 11.4
12.6 41.0 41.6 4.8
b0.0001 17.6 34.6 37.9 9.9
14.6 42.5 38.2 4.8
0.0133
42.0
39.3
0.1383 41.5
41.9
0.2392 43.8
46.6
0.6185 37.8
42.3
0.2786
27.9 7.1 23.1
30.4 10.4 19.9
24.6 6.7 27.2
28.5 7.5 22.1
29.5 11.4 15.2
29.5 8.9 15.0
26.7 14.4 21.1
29.2 11.0 17.4
17.3 15.7 32.7 34.3
9.9 10.9 30.6 48.6
b0.0001 13.0 10.8 27.9 48.3
9.3 10.2 30.3 50.2
0.2662 30.3 16.6 43.6 9.5
11.5 9.4 36.3 42.9
b0.0001 39.6 18.7 29.7 12.1
24.5 16.3 35.4 23.9
b0.0001
31.4 21.4 27.5 19.7 1.3
24.5 24.4 25.7 25.4 0.3
0.0198 27.9 29.2 22.6 20.4 0.009 1.3
22.4 27.1 23.8 26.7 0.5
0.0589 31.3 25.6 23.7 19.4 0.1482 1.0
22.3 23.2 27.5 27.0 0.1
0.0047 28.0 29.7 21.4 20.9 b0.0001 1.7
28.8 27.5 21.6 22.2 0.1
0.9344
12.7 25.1 62.2
18.3 40.4 41.2
b0.0001 14.6 29.9 55.5
17.4 40.3 42.4
0.0002 9.4 32.7 57.9
17.7 40.5 41.8
b0.0001 10.4 26.8 62.8
18.0 40.1 41.9
b0.0001
All data represent mean ± standard error or number (%) of participants. a Hypertension was defined as having a systolic pressure of 140 mm Hg (or higher) or diastolic pressure of 90 mm Hg (or higher). b Heavy drinker was defined as consuming alcohol twice or more per week and having at least 7 drinks/occasion for men and 5 drinks/occasion for women.
0.0003
H.J. Song et al. / Preventive Medicine 67 (2014) 154–159
Nonhypertension (n = 2170)
Hypertension (n = 315) Age, years Systolic blood pressure Diastolic blood pressure Body mass index (kg/m2) Fasting glucose (mg/dL) Triglycerides LDL-cholesterol (mg/dL) HDL-cholesterol (mg/dL) Energy (kcal/day) Sodium (mg/day) Fruits intake (g/day) Fruit intake (%) 1st (Lowest) 2nd 3rd 4th (Highest) Smoking (%) Non-smoker Ever-smoker Current smoker, b1 pack per day Current smoker, ≥1 pack per day Alcohol intake (%) Non-drinker Less than once a month Once a month — less than heavy drinker Heavy drinkerb Physical activity (%) No regular exercise with irregular walking Regular walking Regular, moderate-level activity Regular, vigorous-level activity Education (%) Elementary school Middle school High school College or higher degree Income (%) 1st (lowest) 2nd 3rd 4th (highest) Received hypertension education (%) Survey year (%) 2007 2008 2009
a
H.J. Song et al. / Preventive Medicine 67 (2014) 154–159
157
Table 2 Odds ratio (95% confidence interval) of risk of hypertensiona according to fruit intake. Category
Total number
Range of Category (g/day)
Median of total fruit intake (g/day)
No. of cases
Age and gender adjusted ORs (95% CI)
Multivariate-adjusted ORsb (95% CI)
Total Q1 and Q2
4134
0
0
515
Reference
Reference
Q3 Q4 Q5
1740 1959 1958
0 b –129.9 130.0–345.2 345.5–6523.3
58.0 212.3 577.4 P value for trendc
161 186 171
0.82 (0.68–1.00) 0.84 (0.70–1.00) 0.73 (0.61–0.88) 0.0007
0.83 (0.68–1.03) 0.85 (0.69–1.03) 0.76 (0.62–0.94) 0.0068
Men Q1 and Q2
1995
0
0
339
Reference
Reference
298 762 764
0 b –52.3 52.7–278.8 280.7–3108.8
11.4 156.1 502.1 P value for trendc
41 121 135
0.82 (0.57–1.16) 0.90 (0.71–1.13) 1.01 (0.81–1.26) 0.9758
0.83 (0.57–1.21) 0.90 (0.70–1.16) 1.08 (0.84–1.34) 0.6117
2139 248 1196 1198 1191
0 0 b –14.3 14.4–176.0 176.3–393.2 393.2–6523.3
0 3.6 100.0 258.7 613.2 P value for trendc
176 11 73 84 53
reference 0.58 (0.31–1.09) 0.68 (0.51–0.91) 0.77 (0.59–1.02) 0.45 (0.32–0.61) b0.0001
reference 0.67 (0.34–1.30) 0.76 (0.56–1.05) 0.90 (0.67–1.22) 0.54 (0.38–0.77) 0.0011
Q3 Q4 Q5
Women Q1 Q2 Q3 Q4 Q5
Abbreviations: CI, confidence interval; ORs, odds ratios; Q, quintile. a Hypertension was defined as having a systolic pressure of 140 mm Hg (or higher) or diastolic pressure of 90 mm Hg (or higher). b Multivariate-adjusted models were adjusted for age, body mass index, fasting glucose, triglycerides, LDL-C, HDL-C, energy, sodium intake, smoking, alcohol consumption, physical activity, education, income, education for hypertension, survey year (for men and women), and menopause (for women only). c Tests for linear trends across categories were conducted by treating the median of each category as a continuous variable.
smokers, subgroup analysis for ever-smoker and smoker women could not be performed. The significant association between fruit intake and the likelihood of hypertension was consistent only in the non-smoker and non-obese women (data not shown).
Discussion The present study documents the association between fruit consumption and the prevalence of hypertension in an Asian context. Previous studies reported that increasing consumption of vegetables and fruits reduced the risk for developing hypertension (Appel et al., 2006; Ascherio et al., 1996; Berkow and Barnard, 2005; Miura et al., 2004; Sacks et al., 2001). However, fruits and vegetables have different nutritional compositions, and the reduction of hypertension prevalence was not significant for fruit intake in a sub-analysis (Alonso et al., 2004).
Interestingly, there was a clear difference between men and women for the relationship between fruit intake and the prevalence of hypertension in this study. Gender-specific differences have been found in chronic non-communicable diseases, including metabolic and cardiovascular diseases, and cancer (Song et al., 2008; Vlassoff, 2007). Different findings for men and women may result from the complex influence of genetic differences, hormonal differences, health behaviors, responses to social and environmental factors, and due to interactions between all of these factors. The renin–angiotensin system is a wellknown regulator of blood pressure and plays an important role in the gender-specific pathogenesis of cardiovascular disease (Bauer et al., 2011). In animal models of hypertension, a female-specific blood pressure quantitative trait loci region was detected (Herrera et al., 2006). Recent animal studies have suggested that there are gender-specific hypertension genes and different mechanisms for response to treatment between the two genders (Fava et al., 2012; Herrera et al., 2012;
Table 3 Odds ratio (95% confidence interval) of risk of hypertensiona according to fruit intake in obese and non-obese women. Category
Total number
Range of Category (g/day)
Median of Category (g/day)
No. of cases
Age adjusted ORs (95% CI)
Multivariate-adjusted ORsb (95% CI)
BMI b 25 Q1 Q2 Q3 Q4
1593 723 1156 1161
0 0 b–103.1 103.8–310.7 310.9–6523.3
0 44.7 204.0 524.5 P value for trendc
97 29 54 34
Reference 0.65 (0.42–1.01) 0.68 (0.48–0.97) 0.40 (0.27–0.60) b.0001
Reference 0.70 (0.44–1.12) 0.75 (0.51–1.10) 0.48 (0.31–0.75) 0.0011
BMI ≥ 25 Q1 Q2 Q3 Q4
546 123 336 334
0 0 b–68.2 70.2–310.9 310.9–2478.5
0 28.5 187.3 527.1 P value for trendc
79 19 44 41
Reference 1.04 (0.60–1.80) 0.83 (0.56–1.24) 0.74 (0.49–1.11) 0.1376
Reference 1.05 (0.58–1.91) 0.88 (0.56–1.37) 0.77 (0.48–1.24) 0.2765
Abbreviations: CI, confidence interval; ORs, odds ratios; Q, quartile. a Hypertension was defined as systolic pressure of 140 mm Hg (or higher) or diastolic pressure of 90 mm Hg (or higher). b Multivariate-adjusted models were adjusted for age, body mass index, fasting glucose, triglycerides, LDL-C, HDL-C, energy, sodium intake, smoking, alcohol consumption, physical activity, education, income, education for hypertension, survey year, and menopause. c Tests for linear trends across categories were conducted by treating the median of each category as a continuous variable.
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Table 4 Odds ratio (95% confidence interval) of risk of hypertensiona according to fruit intake in non-, ever- and current smokers. Category
Total number
Range of Category (g/day)
Median of Category (g/day)
No. of cases
Age and gender adjusted ORs (95% CI)
Multivariate-adjusted ORsb (95% CI)
Non-smoker Q1 Q2 Q3 Q4
2092 919 1497 1502
0 0 b–104.5 104.6–323.5 324.2–6523.3 P value for trendc
0 50.8 205.2 545.6
197 68 112 99
reference 0.83 (0.61–1.11) 0.75 (0.58–0.96) 0.62 (0.48–0.81) 0.0002
reference 0.88 (0.64–1.21) 0.81 (0.62–1.06) 0.73 (0.55–0.97) 0.0214
Ever-smoker Q1 Q2 Q3 Q4
688 72 380 381
0 0 b–14.4 15.1–235.0 235.6–2478.5 P value for trendc
0 4.7 116.9 468.9
111 10 51 61
reference 0.89 (0.60–1.80) 0.77 (0.54–1.12) 0.93 (0.66–1.32) 0.1376
reference 1.01 (0.46–2.26) 0.71 (0.47–1.07) 1.02 (0.68–1.52) 0.9831
0
201
reference
reference
52.0 334.1
38 74
0.79 (0.54–1.15) 0.88 (0.66–1.17) 0.3654
0.72 (0.47–1.09) 0.93 (0.68–1.29) 0.6656
Current smoker Q1 1329 Q2 Q3 327 Q4 552
0 0 b–137.2 139.1–2733.0 P value for trendc
Abbreviations: CI, confidence interval; ORs, odds ratios; Q, quartile. a Hypertension was defined as having a systolic pressure of 140 mm Hg (or higher) or diastolic pressure of 90 mm Hg (or higher). b Multivariate-adjusted models were adjusted for age, gender, body mass index, fasting glucose, triglycerides, LDL-C, HDL-C, energy, sodium intake, alcohol consumption, physical activity, education, income, education for hypertension, survey year and menopause (for women only). c Tests for linear trends across categories were conducted by treating the median of each category as a continuous variable.
Hoffman et al., 2013; Park et al., 2012). Although the epigenetic mechanism that results in gender-specific gene expression has yet to be discovered, there is accumulating evidence that demonstrates gender-specific relationships between diverse environmental influences on placental functions and the risk of disease later in life (Gabory et al., 2013). Low potassium and high sodium intakes (He et al., 2013; Sacks et al., 2001; Zhang et al., 2013) and sodium-to-potassium intake ratio (Castro and Raij, 2013) have been reported to be associated with high blood pressure. In a previous study, daily sodium intake of men was much higher than that of women, and there was a clear independent relationship between high sodium intake and an increased likelihood of being overweight in men but not in women (Song et al., 2013). However, after adjusting for sodium intake, there was no change in the difference between men and women in our study. In a previous study carried out in an Asian population, former smokers with abdominal obesity had a higher risk for subsequent hypertension than current smokers (Onat et al., 2009). Therefore, we analyzed the data using the smoking status of subjects and the significant association between fruit intake and the likelihood of hypertension was consistent only in the non-smoker and non-obese women. The inverse association between higher levels of potassium intake and blood pressure was attenuated after adjusting for major lifestyle and dietary factors (Shin et al., 2013). Therefore, the mechanism for the inverse association of fruits for high blood pressure cannot be explained by the high potassium intakes alone and instead, must be due to both high potassium intakes and other gender-specific different factors and obesity. Women are generally more prone to proinflammatory status and autoimmune activation. Fruit intake might be of highest benefit through preventing enhanced low-grade inflammation (Onat and Can, 2014). Our study had several limitations. Fruit intake was estimated by using one 24-h dietary recall. Ideally, at least three 24-h recalls would be done, one on a day-off and two on working days. However, this could not be easily applied to a large population. To minimize this bias, 79% of 2007–2009 KNHANES were performed on week days and 21% on weekends. The other limitation was the cross-sectional study design using dietary recall. A randomized controlled trial design can provide better evidence. However, a randomized controlled trial could not be easily applied to a large number of participants in a general population. Considering the reliability of questionnaire-derived dietary
information and the stability of food habits over time for adults (Jensen et al., 1984), 24-h recall can serve as one of the most costeffective and feasible replacements for a randomized controlled trial for research using a large number of human subjects. Causal relationships cannot be confirmed from such cross-sectional design. To minimize this limitation, we excluded data from people who were diagnosed with hypertension or had received treatment for hypertension. Conclusions Even though longitudinal studies and randomized controlled trials are needed to confirm the relationship between fruit intake and the reduction in hypertension risk, there is a potential opportunity to prevent hypertension and improve the prognosis of hypertension, in individuals who have it, through optimal management of dietary fruit intake. The present study suggested that dietary fruit recommendations for hypertension should consider ethnic and gender-specific differences and obesity. Additional studies are needed to clarify the mechanism by which dietary fruit intake helps to lower hypertension risk. Conflict of interest statement The authors have no conflicts of interest.
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