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(Hypertension. 2004;43:1332.)
© 2004 American Heart Association, Inc.
Scientific Contributions |
From the Department of Epidemiology (L.Z., B.Z., Y.W., J.Y.), Fu Wai Hospital and Cardiovascular Institute, Chinese Academy of Medical Sciences, Beijing, Peoples Republic of China; Department of Health Science (H.U.), Shiga University of Medical Science, Otsu, Japan; Department of Preventive Medicine (L.Z., J.S., L.L.Y., K.L., M.L.D.), Feinberg School of Medicine, Northwestern University, Chicago, Ill; Collaborative Studies Coordinating Center (B.H.D.), Department of Biostatistics, University of North Carolina, Chapel Hill; Guangxi Medical University (L.Z.), Nanning, Peoples Republic of China; Department of Epidemiology and Public Health (P.E.), Faculty of Medicine, St Marys Campus, Imperial College, London, UK; Yu County Hospital (D.G.), Shanxi, Peoples Republic of China.
Correspondence to Dr Jeremiah Stamler, Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Suite 1102, 680 North Lake Shore Drive, Chicago, IL 60611. E-mail j-stamler{at}northwestern.edu
| Abstract |
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10%. Controlled for age and gender, nondietary variables had little effect on northsouth blood pressure differences. With inclusion in regression models of multiple dietary variables (sodium, potassium, magnesium or phosphorus, body mass index), northsouth blood pressure differences became much smaller (systolic 1.1, diastolic 1.6 mm Hg) and statistically nonsignificant. In conclusion, multiple dietary factors accounted importantly for northsouth blood pressure differences. Efforts are needed to improve nutrition in China, especially in the north, as well as in other populations including those in the United States, for prevention and control of adverse blood pressure levels and major adult cardiovascular disease.
Key Words: blood pressure diet population
| Introduction |
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In this study, we used data from the International Study on Macronutrients and Blood Pressure (INTERMAP) to examine northsouth BP differences in China and to assess nutritional factors that may be responsible.
| Methods |
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INTERMAP design, methods, and quality-control procedures have been reported in detail.1214 A brief description is given here.
Study Samples
Chinese samples were from rural populations: 2 north (Pinggu County, Beijing, and Yu County, Shanxi Province), and 1 south (Wuming County, Guangxi Zhuang Autonomous Region). In accordance with the INTERMAP Protocol,12 a population-based sample of 260 persons (1 per family) was randomly selected from each target population, stratified by gender and 10-year age group (ie, 65 persons in each of 4 10-year agegender groups).
Field work was conducted from September 1997 to January 1998. Each participant attended the local INTERMAP center on 4 occasions: 2 pairs of consecutive days
3 to 6 weeks apart. All data were collected by trained and certified staff.
Data Acquisition
Blood pressure measurement protocol was the same as in INTERSALT Study,15 ie, participant was seated quietly for at least 5 minutes and BP was measured twice with a random zero sphygmomanometer at each of the 4 visits. Height and weight without shoes or heavy clothes were measured at first and third visits. Data were collected by interviewer-administered questionnaire about age, education, occupation, work and leisure physical activity, smoking history, previous medical history, and medication use.
Two timed 24-hour urine specimens were collected. Collections were started at the research center on the first and third visits and completed at the center the next day. Urine aliquots were stored frozen at 20°C and then air-freighted frozen to the Central Laboratory (Leuven, Belgium), where urinary sodium (Na), potassium (K), urea, and other levels were measured with rigorous internal and external quality control.
Dietary data were collected at each visit by standardized 24-hour dietary recalls. All food and drink consumed in the previous 24 hours were recorded by trained and certified interviewers. Daily alcohol consumption during the previous 7 days was also recorded at the first and third visits. Interviewers coded dietary data on survey day according to the Chinese Coding Manual (China Addendum to the INTERMAP Nutrition Manual of Operations). Extensive efforts were made to obtain high-quality dietary data.1214 Nutrients were calculated from foods with use of an extensive database derived from the Chinese national food table16 and enhanced by the Nutrition Coordinating Center (NCC), University of Minnesota, working cooperatively with Chinese INTERMAP colleagues.1214
Statistical Methods
Dietary data here are expressed as nutrient densities, ie, percent total kilocalories for nutrients supplying energy (kcal from nutrient/total kcal)x100; for other nutrients per 1000 kcal (amount per day/total kcal)x1000.
Measurements for each individual were averaged across visits. Because average BP, dietary, and nondietary variables were generally similar for Beijing and Shanxi samples,17 analyses data not only were used for these 2 samples separately but also were combined as the "north" sample; the Guangxi sample was the "south" sample.
For descriptive statistics, means and standard deviations or percentages are given for each sample and for the north sample, with t tests or
2 tests for northsouth comparisons. Tests were also performed between the 2 north samples. Based on significant northsouth differences for nondietary and dietary variables, multiple linear regression models were used to examine relations of dietary factors with northsouth differences in SBP and DBP with control for nondietary variables. The basic model (model 1) included age, gender, and an indicator for north to obtain the agegender-adjusted coefficient for northsouth SBP and DBP differences. Then each factor was added to model 1 separately, and percentage reduction from the model 1 coefficient was calculated to assess influence of the added variable on northsouth BP differences. In addition to age and gender, model 2 also included nondietary factors. Finally, dietary variables were included in combinations to assess their joint impact on northsouth BP differences. Three groups of nutrients were added to model 2: 24-hour urinary Na and K,18 and electrolytes plus magnesium or phosphorus (magnesium and phosphorus were highly correlated, r=0.88; hence, these 2 were added separately). These models were computed without or with inclusion of body mass index (BMI), because nutrientBP relations may be overadjusted with BMI in the models because of associations of nutrient intake with body mass and body mass with BP;19 also, BMI, a variable measured with high intraindividual reproducibility, may distort coefficients for nutrientBP relations because nutrients are measured with lower reproducibility.20 Interactions between BMI and single nutrients in influencing BP were also assessed. Analyses were also repeated with exclusion of participants using antihypertensive medication.
| Results |
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140, DBP
90, or using medication) prevalence was higher for the north (22.3%) than south (7.2%).
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Average age and years of education were similar for north and south (Table 1). Mean BMI was 23.8 kg/m2 for the north, which was 2 U higher than for the South (P<0.001). Southern participants engaged, on average, in 4 hours of heavy physical activity per day. Northern participants performed <1 hour of heavy physical activity per day (P<0.001). Percentage reporting consumption of a special diet was higher for north than south, as was the proportion with history of cardiovascular disease/diabetes. Percent of current drinkers was lower for north, especially in Shanxi, as was alcohol intake.
For most nutrient variables, mean intakes by Beijing and Shanxi participants were similar, and different from Guangxi (Table 1). With absolute differences in most nutrient variables between Beijing and Shanxi being small, it was deemed valid to combine Beijing and Shanxi as the "north" sample. Southern participants reported slightly lower average total energy intakes, higher total and animal protein (%kcal) intakes, higher total fat, saturated fat, and monounsaturated fat intakes, higher Keys dietary lipid score, lower polyunsaturated/saturated fatty acids ratio (PFA/SFA), and relatively less carbohydrate, starch, and dietary fiber intake than northern participants. Southern intakes of vitamin A, retinol, beta-carotene, vitamin C, calcium, magnesium, and phosphorus were higher; vitamin E and selenium intakes were lower. Na and Na/K intakes were
50% lower, and K excretion was higher for the south.
Relation of Single Dietary Variables to NorthSouth SBP/DBP Differences
With adjustment for age and gender in multiple regression analyses, north SBPs/DBPs were higher than those for south by 7.6/6.9 mm Hg (P<0.001; Table 2; model 1). These coefficients were altered only slightly by inclusion in the model separately (one at a time) of 4 nonnutrient variables (data not shown). In contrast, with BMI in the model, northsouth BP differences were reduced 36.2% (SBP) and 26.5% (DBP) (row B, Table 2). Among nutrients, urinary Na/K ratio produced the largest reduction in SBP coefficient (56.3%), then phosphorus (49.0%) (rows D and G, Table 2). Several other nutrients reduced site SBP coefficients by 10% or more, eg, urinary Na, dietary calcium, and magnesium. Northsouth DBP differences were sizably reduced by phosphorus (43.7%), magnesium (28.4%), urinary Na/K (25.9%), and urinary Na (20.2%)
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Results were similar with exclusion of participants using antihypertensive medication (data not shown). In analyses of BMInutrient interactions in relation to SBP and DBP, no significant interaction was found (data not shown).
Relation of Combinations of Dietary Variables to NorthSouth SBP/DBP Differences
Compared with model 1, additional adjustment for cardiovascular disease/diabetes diagnosis, special diet, and hours of heavy physical activity together had little effect on northsouth SBP/DBP differences (Table 3). Inclusion of BMI reduced the coefficients sizably (eg, in model 2, by 30% and 21%).
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Urinary Na and K greatly reduced northsouth SBP difference by 66.3% without BMI and 77.7% with BMI to statistically nonsignificant levels (model 3, Table 3). The combinations of urinary Na, K, magnesium, or phosphorus (models 4 and 5) further reduced northsouth SBP difference to 2 mm Hg or less (statistically nonsignificant). Results for DBP were similar but quantitatively less. In these 3-nutrient models, effect of adding BMI was modest compared with its large effect without the nutrients (models 1 and 2). With exclusion of participants on antihypertensive medication, results were similar (data not shown).
| Discussion |
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Differences in BP levels and prevalence of hypertension between northern and southern Chinese have been reported.17 Few studies explored reasons for these differences. In the PRC-USA Collaborative Study,8 BP levels were markedly higher in northern than southern participants, for men and women, and for urban and rural. Differences in BMI (higher for north), alcohol intake, and other (nondietary) factors only partially explained BP differences. Nutrient influences were not reported.
Previous studies documented much higher salt and Na/K intake for north than south.57,10,21 High Na and Na/K intake adversely influence BP levels.5,6 In the INTERSALT Study, compared with 45 other samples worldwide, the Chinese mean BMI was lower and heavy drinking was less, but Chinese Na and Na/K intakes were higher, and upward slope of BP with age was greater than for other samples.11 These findings suggest that dietary Na and Na/K are important in explaining regional BP differences in China, but no previous studies have quantified this relation. Our findings support this inference; northern Na and Na/K intakes were significantly and substantially higher and accounted sizably for higher northern BP levels.
Our findings also confirm that even modest BMI differences within the nonoverweight range influence BP, per extensive data on the BMIBP relation.22 They further indicate that other dietary factors account importantly for northsouth BP differences, particularly higher southern intake of magnesium and phosphorus. The importance of dietary factors in explaining intergroup BP differences has been demonstrated in other studies. Among 2195 US INTERMAP participants, there was a significant inverse relation between years of education and BP, reduced to statistically nonsignificant levels with inclusion in linear regression models of Na, K, alcohol, vegetable protein, Keys dietary lipid score, magnesium, calcium, phosphorus, and iron.23
The importance of dietary influences on BP is also supported by data from clinical trials. The Dietary Approaches to Stop Hypertension (DASH) trial showed that feeding a "combination" diet high in fruits, vegetables, legumes, nuts, low-fat dairy products, and reduced in fatty meats, fats, and sweets lowered BP levels in prehypertensive and hypertensive individuals.24 In a subsequent trial, reduction in Na intake augmented this effect of the DASH diet on BP.25 The DASH trials were not designed to evaluate impact of specific nutrients on BP, but it is noteworthy that the DASH diet is higher in potassium, calcium, magnesium, phosphorus, vitamins, fiber, PFA/SFA, protein, and lower in Na, Na/K, total fat, saturated fat, cholesterol, and sugar.
Geographic variations in BP are also apparent in other countries. For example, in the southern US BP levels and prevalence of hypertension are higher than in the north.26,27 The southeast region of the US also has higher stroke mortality ("stroke belt").28 Dietary differences between the south and north could partially account for such differences. The National Health and Nutritional Examination Survey III showed that the southern region had higher consumption of Na, cholesterol, monounsaturated fat, and lower consumption of K, calcium, phosphorus, magnesium, copper, fiber, and vitamins than other regions.27
Main strengths of the present study are: (1) population-based samples; (2) standardized collection of high-quality BP and nutrition data; (3) use of improved nutrient database; and (4) multiple quality-control procedures. The study is limited by small sample size (3 rural samples) and its cross-sectional design. Nevertheless, significant dietary differences between north and south were observed that accounted for northsouth BP differences. The findings may or may not be generalizable to all northern and southern Chinese and to other populations. However, their concordance with other research findings, especially extensive data on adverse influences on BP of higher Na and Na/K intakes and higher BMI, is consistent with the possibility that they are generalizable.
In conclusion, INTERMAP data from middle-aged Chinese participants from the north and the south showed that southerners had much lower BP levels and generally more favorable lifestyles, especially lower BMI, Na intake, Na/K ratio, and higher intake of magnesium and phosphorus (also other micronutrients). These largely accounted for their lower BP levels. Compared with northern Chinese, the nutrient intake of southern Chinese more closely resembles the DASHsodium combination diet, demonstrated to reduce BP levels significantly in prehypertensive and hypertensive individuals.
Perspectives
Substantial increases in SBP/DBP from youth through middle age, high prevalence rates of prehypertension and hypertension, and low prevalence rates of normotension are common phenomena worldwide. Hence, adverse BP level, which is an established major risk factor for epidemic adult cardiovascular disease, is a virtually population-wide problem, but southern Chinese are significantly less affected. Geographic variations in BP are present in many countries, including the United States. The data here show that dietary differences account substantially for lower BP in southern Chinese. These findings may well have important public health implications, not only for China but also for other countries. In addition to the known importance of maintaining an optimal body weight and lower salt intake, higher intake of specific micronutrients may be valuable to improve population BP levels and prevent cardiovascular disease.
| Acknowledgments |
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Received March 1, 2004; first decision March 12, 2004; accepted April 5, 2004.
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