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(Circulation. 1996;94:2417-2423.)
© 1996 American Heart Association, Inc.

Articles

Relationship to Blood Pressure of Combinations of Dietary Macronutrients

Findings of the Multiple Risk Factor Intervention Trial (MRFIT)

Jeremiah Stamler, MD; Arlene Caggiula, PhD; Greg A. Grandits, MS; Marcus Kjelsberg, PhD; Jeffrey A. Cutler, MD; for the MRFIT Research Group

the Department of Preventive Medicine (J.S.), Northwestern University Medical School, Chicago, Ill; Department of Epidemiology (A.C.), Graduate School of Public Health, University of Pittsburgh, Pa; Division of Biostatistics (G.A.G., M.K.), School of Public Health, University of Minnesota, Minneapolis; and Division of Epidemiology and Clinical Applications (J.A.C.), National Heart, Lung, and Blood Institute, Bethesda, Md.

Correspondence to Marcus Kjelsberg, Division of Biostatistics, University of Minnesota, Suite 200, 2221 University Ave SE, Minneapolis, MN 55414. E-mail marc@muskie.biostat.umn.edu.

	Abstract

Top Abstract Introduction Methods Results Discussion References

 
Background Elevated blood pressure remains a widespread major impediment to health. Obesity and specific dietary factors such as high salt and alcohol intake and low potassium intake adversely affect blood pressure. It is a reasonable hypothesis that additional dietary constituents, particularly macronutrients, may also influence blood pressure.

Methods and Results Participants were 11 342 middle-aged men from the Multiple Risk Factor Intervention Trial (MRFIT). Data from repeat 24-hour dietary recalls (four to five per person) and blood pressure measurements at six annual visits were used to assess relationships, singly and in combination, of dietary macronutrients to blood pressure, adjusted for multiple possible confounders (demographic, dietary, and biomedical). Multiple linear regression was used to assess diet–blood pressure relations in two MRFIT treatment groups (special intervention and usual care), with adjustment for confounders, pooling of coefficients from the two groups (weighted by inverse of variance), and correction of coefficients for regression-dilution bias. In multivariate regression models, dietary cholesterol (milligrams per 1000 kilocalories), saturated fatty acids (percent of kilocalories), and starch (percent of kilocalories) were positively related to blood pressure; protein and the ratio of dietary polyunsaturated to saturated fatty acids were inversely related to blood pressure. These macronutrient–blood pressure findings were obtained in analyses that controlled for body mass, dietary sodium and ratio of sodium to potassium, and alcohol intake, each positively related to blood pressure, and intake of potassium and caffeine, both inversely related to blood pressure.

Conclusions These data support the concept that multiple dietary factors influence blood pressure; hence, broad improvements in nutrition can be important in preventing and controlling high-normal and high blood pressure.

Key Words: blood pressure • diet • prevention • proteins • lipids

	Introduction

Top Abstract Introduction Methods Results Discussion References

 
Elevated blood pressure (BP) continues to be a widespread major impediment to health.^{1 2 3 4 5 6 7 8} The common pattern is for both SBP and DBP to be cumulatively higher with age from youth through middle age and beyond. As a consequence, among middle-aged and older persons, only a small minority have optimal BP levels (SBP/DBP <120/<80 mm Hg), and a majority have either high-normal or hypertensive levels (high normal: SBP 130 to 139 mm Hg with DBP <90 mm Hg, or DBP 85 to 89 mm Hg with SBP <140 mm Hg; hypertensive: SBP 140 or DBP 90 mm Hg or taking antihypertensive drug).^{1 2 3 4 5 6 7}

Above-optimal BP is a significant major risk factor for cardiovascular morbidity and mortality, all-cause mortality, and shortened life expectancy.^{1 2 3 4 5 6} This relationship is strong, continuous, graded, independent of other major risk factors (eg, smoking, serum cholesterol), and generally recognized to be etiologically significant.

A rise in BP with age during adulthood is not an inevitable consequence of the human condition, built into the genome of Homo sapiens.^{8 9 10} Five aspects of habitual lifestyle have been shown to influence BP adversely: high salt intake, high ratio of dietary sodium to potassium (Na/K), high alcohol consumption, calorie imbalance with resultant obesity, and sedentary habit.^{1 2 8 9 10 11 12 13 14 15 16 17 18 19 20} Each of these traits can influence BP sizably; hence, their prevention and control are the strategic basis for current efforts to ameliorate the population-wide BP problem by lifestyle approaches (in addition to indicated pharmacological treatment for established high BP).^{1 2 13 14 15 16 17 18 19 20}

Given the present state of knowledge, it is a reasonable hypothesis that other dietary constituents (over and above the aforementioned), including macronutrients, also influence BP. This report presents findings on this matter for the cohort of over 12 000 men randomized into MRFIT. Its focus is on the relationship to BP of several macronutrients considered together, particularly dietary protein, lipids, and simple and complex carbohydrates.

	Methods

Top Abstract Introduction Methods Results Discussion References

 
Published reports give detailed information about the MRFIT cohort and methods, including those for measurement of dietary variables.^{3 6 21 22 23 24 25} These are summarized here.

Cohort
From 1973 to 1975, 361 662 men aged 35 to 57 years were screened in 18 US cities for recruitment for MRFIT. Of these, 12 866 met the criteria of being at high risk of CHD and without evidence of definite CHD and were randomized into the trial. Analyses for this paper are restricted to the 11 342 men who attended the sixth annual visit, to incorporate adjustments for smoking and antihypertensive medication status at the end of the trial.

Intervention Program
MRFIT was a randomized primary prevention trial conducted at 22 US clinical centers from 1973 to 1982 to test whether reduction of elevated serum cholesterol and BP and cessation of cigarette smoking would reduce CHD mortality.^{21 22 23 24 25} Participants were monitored for 6 to 8 years. Men in the UC group were given information on risk factor levels, referred to their usual sources of medical care, and reexamined annually. Men in the SI group received group and individual counseling on a fat-modified diet; a stepped-care drug treatment program for hypertension (after an initial attempt to control BP by weight reduction, if indicated); and for cigarette smokers, counseling aimed to achieve cessation.

Data Collection, Including Nutritional Assessment
Data (demographic, behavioral, medical, hematologic, and biochemical) were collected at annual visits for both groups. BP was measured four times at each visit, twice with a standard manometer and twice with a random-zero manometer, by trained certified staff using the Hawksley random-zero manometer and a common protocol. SBP and DBP were based on the first and fifth Korotkoff sounds, respectively. The average of the two random-zero readings for each man was used to determine the end point (dependent variable) for analyses presented herein.

At the third screening visit, a 24-hour dietary recall was collected on each participant. This was repeated during the trial at five of six annual follow-up visits for men in the SI group (years 1, 2, 3, 5, and 6) and at four of six annual follow-up visits for men in the UC group (years 1, 2, 3, and 6). Staff who conducted the 24-hour recall interviews at the 22 MRFIT field centers were dietitians and nutritionists centrally trained in standardized fashion, certified, and annually recertified to perform this procedure and to adhere to study-wide quality control measures.^{22 24} Coordination of this effort came from a national facility (the NCC) established at the site of the MRFIT Coordinating Center. The NCC organized and administered the dietary data collection system and central coding of all MRFIT 24-hour recalls by specially trained and supervised coding clerks using standardized edit and quality control procedures. Coded dietary recall data were computerized by the MRFIT Coordinating Center and edited, eg, for completeness of coding, invalid codes, seemingly extreme food portion sizes, and extreme total nutrient intakes, particularly of kilocalories, fat, and alcohol. MRFIT analyses, based on the NCC's food table No. 11, yielded data on 63 nutrients for each 24-hour dietary recall.

Interviews to collect 24-hour dietary recalls did not include queries as to salt added during food preparation and at the table, nor were 24-hour urine samples collected to measure sodium. Therefore, data available on dietary sodium are for sodium in foods and thus are a "floor" of sodium intake. Recent estimates indicate that sodium added to foods by the homemaker during preparation and at the table by the consumer makes up on average only about 15% of total ingested sodium.^{12 13 26} Insofar as this percentage varied among MRFIT men, there is a potential for misclassification and bias in analyses relating sodium to BP.

Statistical Methods
To assess relationships of macronutrients to SBP and DBP, multiple linear regression analysis was used, with control for several possible confounding variables: age; ethnicity; education; serum cholesterol; smoking; antihypertensive drug use; BMI; and intake of alcohol, caffeine, sodium, and potassium. Nutrition data for individuals based on one 24-hour dietary recall are of limited reliability because of substantial intraindividual variability in day-to-day nutrient intake. As a consequence, analyses of nutrient-BP relations for individuals are biased toward zero because of misclassification (nutrient values based on one recall not accurately reflecting usual nutrient intake)—the regression-dilution bias problem.^{12 14 15 24 27 28 29 30} This measurement problem results in regression coefficients that are only a fraction of true coefficients and loss of statistical power to detect true relationships of diet to BP and other outcomes. Because of this problem, analyses here are for the six follow-up years of the trial. For each man, the average of the SBP and of the DBP at six annual follow-up visits was regressed on the average nutrient level from the four (SI) or five (UC) recalls collected per man during the trial years 1 through 6. Analyses were first performed for men in the SI and UC groups separately. Resultant regression coefficients were then pooled, with weighting by the inverse of their variances. These combined SI-UC coefficients were multivariate adjusted for regression-dilution bias,^{27 28} taking into account that the average of four or five follow-up recalls was used in the regression models. These adjusted coefficients were then used to estimate the theoretical impact on BP of putatively more favorable versus less favorable intake of macronutrients significantly related to BP, on the assumption that these relationships are etiologically significant. Levels for comparison were chosen, for the most part, on the basis of current national recommendations for more favorable levels. A z score >2.58 (nominal P<.01, two tailed, without adjustment for multiple testing) was used to guide interpretation of the results.

	Results

Top Abstract Introduction Methods Results Discussion References

 
Descriptive Statistics
For follow-up years 1 through 6, mean±SD values are given in Table 1 for the cohort of 5733 SI and 5609 UC men for variables of concern. Reflecting influences of the SI program, mean values for SI men compared with UC men were lower for SBP, DBP, BMI, dietary Na/K, total fat, saturated fatty acids, cholesterol, Keys score, refined and processed sucrose, and total kilocalories and higher for alcohol, fiber, protein, total polyunsaturated fatty acids, -3 polyunsaturated fatty acids, P/S, total carbohydrate, starch, and simple carbohydrates other than refined sucrose. Reported intake of total kilocalories was lower on average by 346 kcal/d (1885 versus 2231 kcal/d) for men in the SI group compared with those in the UC group. Because there was only a small difference in weight change between SI and UC groups, this calorie difference likely reflects underreporting of foods eaten by men in the SI group.^{21 22 23 24 25} Insofar as this differed in degree among participants, there is a potential consequence of misclassification and bias in analyses of nutrient-BP relations.

View this table: [in this window] [in a new window]   Table 1. Descriptive Statistics, BP, and Dietary Variables, Years 1 Through 6 of MRFIT, by Randomized Group

Reliability of Dietary Data
For each dietary variable in Table 1 except alcohol and caffeine, the ratio of intraindividual variance to interindividual variance was >1.00, reflecting the considerable within-person variability day by day in eating pattern. As a consequence, the use of dietary data from four or five recalls per person during follow-up reduced but did not eliminate the problem of regression-dilution bias. Thus, with four to five follow-up recalls, the observed regression coefficient as a percent of the true coefficient was estimated to be 52% to 57% for protein, 59% to 70% for saturated fatty acids, and 49% to 53% for cholesterol.

Relationship of Individual Dietary Variables to SBP and DBP
With control for multiple possible confounders, there was a direct relationship to BP of BMI and reported intake of alcohol, sodium, and Na/K and an inverse relationship to BP of potassium intake,²⁴ in accordance with findings from many other studies.^{1 2 8 9 10 11 12 13 14 15 16 17 18 19 20} Reported caffeine intake (milligrams per day and milligrams per 1000 kilocalories) was inversely related to SBP and DBP.²⁴ Therefore, the set of analyses of relationships of combinations of macronutrients to BP included control for these variables.

Findings from the SI-UC pooled regression analyses of SBP and DBP on macronutrients considered singly and separately are shown in Table 2. With control for multiple possible confounders (Table 2 footnote), total protein, polyunsaturated fatty acids, and P/S were inversely related to DBP. Saturated fatty acids and cholesterol were positively related to DBP. The Keys score was positively related to DBP. Analyses based on -3 fatty acids and BP yielded small z scores. Starch was positively related to SBP and DBP. Other simple carbohydrates were inversely related to DBP.

View this table: [in this window] [in a new window]   Table 2. Relationship of Individual Dietary Macronutrients to BP (SBP and DBP) for 11 342 Men, Years 1 Through 6 of MRFIT: Linear Regression Analyses

Relationship of Combinations of Macronutrients to SBP and DBP
Three separate multiple regression analyses were performed on relationships to BP of combinations of macronutrients that were significantly related to BP in the analyses shown in Table 2. Model 1 dealt with macronutrient-BP relationships without control for other specific nutrients. Models 2 and 3 dealt with macronutrient-BP relationships with control for caffeine and for sodium and potassium, first with the electrolytes entered as amounts per day (model 2) and then as the Na/K ratio (millimoles per day/millimoles per day) (model 3). As in preceding analyses (Table 2), these multiple linear regressions were controlled for several other possible confounders (Table 3 footnote).

View this table: [in this window] [in a new window]   Table 3. Relationship of Combinations of Macronutrients to BP (SBP and DBP) for 11 342 Men, Years 1 Through 6 of MRFIT: Multiple Linear Regression Analyses

Model 1
With six macronutrients in the model, there was a significant independent positive relationship of reported dietary cholesterol (milligrams per 1000 kilocalories) and saturated fatty acids (percent of kilocalories) to DBP and of starch (percent of kilocalories) to both SBP and DBP (Table 3). Total protein (percent of kilocalories) was inversely related to DBP.

Model 2
With reported dietary caffeine, sodium, and potassium included among possible confounders, saturated fatty acids and dietary cholesterol remained significantly related to DBP, and starch remained significantly related to both SBP and DBP (Table 3). Total protein remained inversely related to DBP.

Model 3
With Na/K and caffeine included among possible confounders, dietary cholesterol remained positively related to DBP, and starch remained positively related to SBP and DBP (Table 3). Protein and P/S were inversely related to DBP.

Theoretical Estimates of the Influences of More Favorable Combinations of Dietary Macronutrient Intake on SBP and DBP
Table 4 gives macronutrient-BP multiple regression coefficients from model 2 corrected for regression-dilution bias. These corrected coefficients were used to estimate the potential influence on SBP and DBP of putatively more favorable compared with less favorable cohort levels of intake of protein, cholesterol, and saturated fatty acids. The range of estimated lower SBP was from 0.5 mm Hg for saturated fatty acids to 1.9 mm Hg for dietary cholesterol (Table 4). The range of estimated lower DBP was from 1.1 mm Hg for protein to 1.4 mm Hg for dietary cholesterol. The sum of the estimated combined effects was SBP/DBP lower by 3.4/3.7 mm Hg.

View this table: [in this window] [in a new window]   Table 4. Theoretical Estimated Difference in BP (SBP and DBP) With Different Levels of Specified Dietary Macronutrient

	Discussion

Top Abstract Introduction Methods Results Discussion References

 
The main findings from these MRFIT analyses of dietary factors and BP were that several macronutrients were independently related to BP. In particular, cholesterol, saturated fatty acids, and starch were positively associated with BP, and protein was inversely associated. Extensive and convincing data are available on the independent additive relationship to BP of high salt intake, inadequate potassium intake, heavy alcohol consumption, and overweight.^{1 2 8 9 10 11 12 13 14 15 16 17 18 19 20} Current knowledge about other dietary factors and BP (limited in extent, quality, and consistency) is summarized below.

Dietary Protein and BP
A 1985 review concluded ". . . dietary protein content has little influence on BP in animals and humans."³¹ Note was taken of data indicating that increased protein ingestion—and feeding individual amino acids—induced increased renal plasma flow, glomerular filtration rate, and sodium excretion in the short term and increased renal size, renal plasma flow, and glomerular filtration rate in the long term. It was also noted that data from population-based studies on dietary protein and BP were limited. Although several surveys around the world reported lower BPs in vegetarian than in omnivorous populations,³² few reported data on nutrient intake. Nevertheless, it was widely assumed by Western researchers that this observation reflected a direct effect of dietary protein (especially animal protein) on BP,³¹ despite multiple differences in dietary and other traits between these vegetarian and meat-eating populations.

In contrast, since the 1970s, Japanese investigators have had an assessment of the protein-BP relationship different from that of Western researchers; ie, an inverse relation probably prevails between the amount of protein in the diet, particularly animal protein, and BP.^{33 34 35 36} Concordant findings have been reported from China, as well as data indicating an inverse relation between individual amino acids and BP.^{37 38 39} These studies have been limited by small sample size and reliance on urinary ratios without 24-hour excretions or without dietary data to evaluate protein intake of individuals.

In the international cooperative INTERSALT study,⁴⁰ for 10 020 men and women aged 20 to 59 years from 52 population samples in 32 countries worldwide, dietary protein (assessed by total nitrogen and urea nitrogen in 24-hour urine) was significantly inversely related to SBP and DBP with control for multiple possible confounders. A similar inverse relationship of protein to BP was reported by the 1986 to 1987 Dietary and Nutritional Survey of British Adults aged 16 to 64 years.⁴¹ In prospective analyses, the Chicago Western Electric Study reported that dietary vegetable protein was inversely related to change in BP during 9 years of annual follow-up.⁴²

The few randomized controlled trials related to this area, all short term and of limited power, showed that consumption of vegetarian diets led to BP falls in both nonhypertensive and hypertensive adults. However, no BP fall was reported in other trials with specific nutrient change from animal to vegetable protein at a fixed level of total protein. Furthermore, no BP rise was reported with an increased intake of vegetable, dairy, or meat protein.^{31 32 43 44 45}

Dietary Lipids and BP
Among several ecological studies on relations of dietary lipids to BP, most reported no significant association between average total fat intake and average BP, but several reported a significant positive association between average intake of saturated fatty acids and average BP.⁴⁶ These reports do not display data on dietary cholesterol–BP associations. Of 11 within-population cross-sectional studies on dietary lipid intake and BP of individuals, 6 reported no significant relations, and 5 had either significant positive associations (saturated fatty acids and BP) and/or inverse associations (polyunsaturated fatty acids and BP).⁴⁶ None dealt with possible dietary cholesterol–BP relations. In these studies, because of small sample sizes, most had low power to detect any but large coefficients for SBP or DBP regressed on dietary lipids. Six used only a single 24-hour dietary recall to classify lipid intake of individuals.

In the prospective analyses of the Western Electric Study (see above), with dietary lipids considered one at a time, there was a significant positive independent relation of dietary cholesterol to SBP change during an 8-year period.^{42 47}

Randomized controlled trials also leave unclear the matter of dietary lipid–BP relations, primarily because of limitations in design. Most interventions were of short duration (4 to 6 weeks), with small sample sizes (8 to 57 people). The National Diet-Heart Study⁴⁸ published data showing no apparent BP differences across its experimental groups with double-blind modification in intake of total fat and/or saturated fatty acids, polyunsaturated fatty acids, and cholesterol. Although sample size was larger than in the foregoing trials and duration was longer, statistical power was not high for detection of 2 to 3 mm Hg differences among groups in SBP or 1 to 2 mm Hg differences in DBP. Hence, these apparently negative results cannot be regarded as definitive evidence that the several changes in dietary lipids have no effect on BP.

Dietary Carbohydrates and BP
The limited investigative attention to carbohydrate-BP relationships is reflected in the fact that except for dietary fiber and BP, this matter went unmentioned in the 1989 monograph Diet and Health: Implications for Reducing Chronic Disease.¹³ This research paucity has prevailed despite short-term studies in humans showing that ingestion of simple carbohydrates leads to salt and water retention and transient BP increases.⁴⁹ In summarizing the findings, a 1984 review stated, "There is, however, no evidence of a relationship between excessive carbohydrate ingestion and risk of developing hypertension in population groups."⁴⁹ Notable also are the assumptions of the Kempner rice-fruit diet for treatment of hypertension, ie, that low protein and high carbohydrate (starch) are beneficial. Clearly, the MRFIT finding reported here of an independent positive relationship of dietary starch to BP poses a question. However, in the Dietary and Nutritional Survey of British Adults, no relation was found of starch to BP.⁴¹ And in the prospective analyses of the Western Electric Study, there was a significant inverse relation of total carbohydrate intake to SBP change, but this was not present with inclusion of either vegetable protein, cholesterol, or Keys score in the multivariate model.⁴² The meaning of these findings remains to be clarified by further research.

Caffeine Intake and BP
It is well known that caffeine has a pressor effect in the short term. However, as reported herein, analyses of dietary-BP relationships in the MRFIT cohort showed an independent inverse association between usual caffeine intake and both SBP and DBP. Three other population-based studies reported a similar finding.⁵⁰

In summary, the MRFIT data add potentially important information to a limited, inconsistent, but growing body of knowledge suggesting that high intake of saturated fatty acids and cholesterol may have adverse effects on BP, whereas high intake of protein, high P/S, and habitual caffeine ingestion may have favorable effects. Furthermore, they pose a question, appropriate for further research, concerning the relationship of starch intake to BP. These new findings are from a data set that confirms that overweight and high intake of salt, Na/K, and alcohol have adverse effects on blood pressure and that high intake of potassium has a favorable influence. There is a need for well-designed research, observational and interventional,⁵¹ to resolve present uncertainties about macronutrient-BP relations as well as the possible influence on BP of caffeine and other dietary factors.

Despite correction for regression-dilution bias, MRFIT coefficients almost certainly underestimate the strength of relations of dietary variables to BP, both for reasons stated earlier in this article and for other reasons, including the nonprospective nature of the data.¹² This is a problem related to all estimates presented herein, if for no other reasons than the underreporting in the 24-hour dietary recalls, conspicuous for the SI men, and the likelihood that this was qualitatively and quantitatively different among men, thereby producing misclassification and likely underestimation of diet-BP relations. The important methodological difficulties leading to underestimation of the true strength of diet-BP relations make it necessary to use both large sample sizes and high-quality methods of dietary assessment in research to resolve current uncertainties.

Reflecting the above methodological problems, the estimate from the MRFIT data is a seemingly small effect of -3.4/-3.7 mm Hg (SBP/DBP) of more favorable versus less favorable level of intake of three macronutrients. However, even such an apparently modest shift downward in the average SBP/DBP level of the adult population could have favorable effects in helping to curtail the CHD/cardiovascular disease epidemic, eg, as estimated from MRFIT and other long-term prospective studies, estimated reductions in CHD rates of 6% to 7%, in stroke rates of 8% to 9%, and in all-cause death rates of 5% to 6% could be achieved.^{1 2 3 4 5 6 11 12 14 15 20 30} Moreover, the potential estimated combined impact on SBP/DBP, and hence on morbidity, mortality, and longevity, of the more favorable status for macronutrients, electrolytes, alcohol intake, and weight considered together is considerably greater.

In conclusion, MRFIT data indicating additive independent relationships of macronutrient intake to BP, independent of dietary sodium, potassium, alcohol, and calorie balance, lend further support to the concept that broadly based population-wide improvements in diet can contribute importantly to prevention and control of high-normal and high BP and major cardiovascular diseases.

	Selected Abbreviations and Acronyms

 

BMI = body mass index BP = blood pressure CHD = coronary heart disease DBP = diastolic blood pressure MRFIT = Multiple Risk Factor Intervention Trial Na/K = ratio of sodium to potassium NCC = Nutrition Coding Center (later, the Nutrition Coordinating Center) P/S = ratio of polyunsaturated to saturated fatty acids SBP = systolic blood pressure SI = special intervention UC = usual care

Received January 31, 1996; revision received May 31, 1996; accepted June 10, 1996.

	References

Top Abstract Introduction Methods Results Discussion References

 
1. National High Blood Pressure Education Program. The fifth report of the Joint National Committee on Detection, Evaluation, and Treatment of High Blood Pressure (JNC V). Arch Intern Med. 1993;153:154-183.[Abstract/Free Full Text]

2. National High Blood Pressure Education Program Working Group. 1993 National High Blood Pressure Education Program Working Group report on primary prevention of hypertension. Arch Intern Med. 1993;153:186-208.[Abstract/Free Full Text]

3. Stamler J, Vaccaro O, Neaton JD. Diabetes, other risk factors, and 12-yr cardiovascular mortality for men screened in the Multiple Risk Factor Intervention Trial. Diabetes Care. 1993;16:434-444.[Abstract]

4. Stamler J, Stamler R, Neaton JD. Blood pressure, systolic and diastolic, and cardiovascular risks: US population data. Arch Intern Med. 1993;153:598-615.[Abstract/Free Full Text]

5. Stamler J, Dyer AR, Shekelle RB, Neaton J, Stamler R. Relationship of baseline major risk factors to coronary and all-cause mortality, and to longevity: findings from long-term follow-up of Chicago cohorts. Cardiology. 1993;82:191-222.[Medline] [Order article via Infotrieve]

6. Neaton JD, Kuller L, Stamler J, Wentworth DN. Impact of systolic and diastolic blood pressure on cardiovascular mortality. In: Laragh JH, Brenner BM, eds. Hypertension: Physiology, Diagnosis, and Management. 2nd ed. New York, NY: Raven Press; 1995:chap 9.

7. Burt VL, Whelton P, Roccella EJ, Brown C, Cutler JA, Higgins M, Horan MJ, Labarthe D. Prevalence of hypertension in the US adult population: results from the third National Health and Nutrition Examination Survey 1988-1991. Hypertension. 1995;25:305-313.[Abstract/Free Full Text]

8. INTERSALT Cooperative Research Group. INTERSALT: an international study of electrolyte excretion and blood pressure—results for 24 hour urinary sodium and potassium excretion. BMJ. 1988;297:319-328.

9. Mancilha-Carvalho JJ, Baruzzi RG, Howard PF, Poulter N, Alpers MP, Franco LJ, Marcopito LF, Spooner VJ, Dyer AR, Elliott P, Stamler J, Stamler R. Blood pressure in four remote populations in the INTERSALT Study. Hypertension. 1989;14:238-246.[Abstract/Free Full Text]

10. Shaper AG. Communities without hypertension. In: Shaper AG, Hutt MSR, Fejfar Z, eds. Cardiovascular Disease in the Tropics. London, England: British Medical Association; 1974:77-83.

11. Stamler J. Epidemiologic findings on body mass and blood pressure in adults. Ann Epidemiol. 1991;1:347-362.[Medline] [Order article via Infotrieve]

12. Stamler J. Dietary salt and blood pressure. Ann N Y Acad Sci. 1993;676:122-156.[Medline] [Order article via Infotrieve]

13. National Research Council, Committee on Diet and Health, Food and Nutrition Board, Commission on Life Sciences. Diet and Health: Implications for Reducing Chronic Disease. Washington, DC: National Academy Press; 1989.

14. Cutler JA, Kotchen TA, Obarzanek E, eds. The National Heart, Lung, and Blood Institute Workshop on Salt and Blood Pressure. Hypertension. 1991;17(suppl I):I-1-I-221.

15. Law MR, Frost CD, Wald NJ. By how much does salt restriction lower blood pressure? I, analysis of observational data among populations; II, analysis of observational data within populations; III, analysis of data from trials of salt reduction. Br Med J. 1991;302:811-815,815-818,819-824.

16. Marmot MG, Elliott P, Dyer AR, Shipley MJ, Ueshima H, Beevers DG, Stamler R, Kesteloot H, Rose G, Stamler J. Alcohol and blood pressure: the INTERSALT Study. Br Med J. 1994;308:1263-1267.[Abstract/Free Full Text]

17. Elliott P, Stamler J, Nichols R, Dyer AR, Stamler J, Kesteloot H, Marmot M, for the INTERSALT Cooperative Research Group. INTERSALT revisited: further analyses of 24-hour sodium excretion and blood pressure within and across populations. Br Med J. 1996;312:1249-1253.[Abstract/Free Full Text]

18. Denton D, Weisinger R, Mundy NI, Wickings EJ, Dixson A, Moisson P, Pingard AM, Shade R, Carey D, Ardaillou R, Paillard F, Chapman J, Thillet J, Michel JB. The effect of increased salt intake on blood pressure of chimpanzees. Nat Med. 1995;I:1009-1016.

19. Cardiovascular Review Group, Committee on Medical Aspects of Food Policy. Nutritional Aspects of Cardiovascular Disease. London, England: Department of Health; HMSO Report on Health and Social Subjects No. 46; Her Majesty's Stationery Office; 1994:1-186.

20. Stamler J. Potential for prevention of major adult cardiovascular diseases. In: Toshima H, Koga Y, Blackburn HJ, Keys A, eds. Lessons for Science from the Seven Countries Study: A 35-Year Collaborative Experience in Cardiovascular Disease Epidemiology. Tokyo, Japan: Springer-Verlag; 1995:195-235.

21. Benfari RC, Sherwin R, co-eds. The Multiple Risk Factor Intervention Trial (MRFIT): the methods and impacts of intervention over four years. Prev Med. 1981;10:387-553.

22. Morgan J, Kjelsberg MO, eds. The Multiple Risk Factor Intervention Trial: quality control of technical procedures and data acquisition. Control Clin Trials. 1986;7:1S-202S.

23. Multiple Risk Factor Intervention Trial Research Group. Multiple Risk Factor Intervention Trial: risk factor changes and mortality results. JAMA. 1982;248:1465-1477.[Abstract/Free Full Text]

24. Stamler J, Caggiula AW, Cutler JA, Dolecek TA, Grandits GA, Kjelsberg MO, Tillotson JL, guest editors. Dietary-nutritional methods and findings: the Multiple Risk Factor Intervention Trial (MRFIT). Am J Clin Nutr. In press.

25. MRFIT Research Group. Mortality after 16 years for participants randomized to the Multiple Risk Factor Intervention Trial (MRFIT). Circulation. 1996;94:946-951.[Abstract/Free Full Text]

26. Dennis BH. Public health policy and salt: doing the right thing. Perspect Appl Nutr. 1995;3:121-123.

27. Dyer AR, Shipley M, Elliott P, for the INTERSALT Cooperative Research Group. Urinary electrolyte excretion in 24 hours and blood pressure in the INTERSALT study, I: estimates of reliability. Am J Epidemiol. 1994;139:927-939.[Abstract/Free Full Text]

28. Dyer AR, Shipley M, Elliott P, for the INTERSALT Cooperative Research Group. Urinary electrolyte excretion in 24 hours and blood pressure in the INTERSALT study, II: estimates of electrolyte-blood pressure associations corrected for regression dilution bias. Am J Epidemiol. 1994;139:940-951.[Abstract/Free Full Text]

29. Liu K, Stamler J, Dyer A, McKeever J, McKeever P. Statistical methods to assess and minimize the role of intra-individual variability in obscuring the relationship between dietary lipids and serum cholesterol. J Chronic Dis. 1978;31:399-418.[Medline] [Order article via Infotrieve]

30. Stamler J. Assessing diets to improve world health: nutritional research on disease causation in populations. Am J Clin Nutr. 1994;59:146S-156S.[Abstract/Free Full Text]

31. Meyer TW, Anderson S, Brenner BM. Dietary protein intake and the course of renal disease: the role of capillary hypertension and hyperperfusion in the pathogenesis of progressive glomerular sclerosis. In: Horan MJ, Blaustein M, Dunbar JB, Kachadorian W, Kaplan NM, Simopoulos AP, eds. NIH Workshop on Nutrition and Hypertension. New York, NY: Biomedical Information Corp; 1985:217-229.

32. Sacks FM, Rosner B, Kass E. Blood pressure in vegetarians. Am J Epidemiol. 1974;100:390-398.[Abstract/Free Full Text]

33. Kimura N. Atherosclerosis in Japan: epidemiology. In: Paoletti R, Gotto AM, eds. Atherosclerosis Reviews. New York, NY: Raven Press; 1977:209-221.

34. Yamori Y, Horie R, Nara Y, Kihara M, Ikeda K, Mano M, Fujiwara K. Dietary prevention of hypertension in animal models and its applicability to humans. Ann Clin Res. 1984;16(suppl 43):28-31.

35. Yamori Y, Kihara M, Nara Y, Ohtaka M, Horie R, Tsunematsu T, Note S, Fukase M. Hypertension and diet: multiple regression analysis in a Japanese farming community. Lancet. 1981;1:1204-1205.

36. Kihara M, Fujikawa J, Ohtaka M, Mano M, Nara Y, Horie R, Tsunematsu T, Note S, Fukase M, Yamori Y. Interrelationships between blood pressure, sodium, potassium, serum cholesterol, and protein intake in Japanese. Hypertension. 1984;6:736-742.[Abstract/Free Full Text]

37. Zhou BF, Wu XG, Tao SC, Yang J, Cao TX, Zheng RP, Tian XZ, Liu CQ, Miao HY, Ye FM, Zhu LG, Zhu C, Jiang JP, He HQ, Ma F, Du FC, Wang B. Dietary patterns in 10 groups and the relationship with blood pressure. Chin Med J. 1988;102:257-261.

38. Zhang X, Cai R, Zhou B. The relationships of dietary protein, serum and urine free amino acids and blood pressure in three Chinese populations. Abstract book of the 3rd International Conference on Preventive Cardiology; June 27-July 1, 1993; Oslo, Norway. Abstract 5.

39. Zhou B, Zhang X, Zhu A, Zhao L, Zhu S, Ruan L, Zhu L, Liang S. The relationship of dietary animal protein and electrolytes to blood pressure: a study on three Chinese populations. Int J Epidemiol. 1994;23:716-722.[Abstract/Free Full Text]

40. Stamler J, Elliott P, Kesteloot H, Nichols R, Claeys G, Dyer AR, Stamler R, for the INTERSALT Cooperative Research Group. Inverse relationship between dietary protein markers and blood pressure of individuals: findings for 10 020 men and women—the INTERSALT study. Circulation. 1996;94:1629-1733.[Abstract/Free Full Text]

41. Elliott P, Freeman J, Pryer J, Brunner E, Marmot M. Dietary protein and blood pressure: a report from the Dietary and Nutritional Survey of British adults. J Hypertens. 1992;109(suppl):S141. Abstract.

42. Liu K, Ruth KJ, Shekelle RB, Stamler J. Macronutrients and long-term change in systolic blood pressure. Circulation. 1993;87:679. Abstract.

43. Sacks FM, Kass EH. Low blood pressure in vegetarians: effects of specific foods and nutrients. Am J Clin Nutr. 1988;48:795-800.[Abstract/Free Full Text]

44. Dwyer JT. Health aspects of vegetarian diets. Am J Clin Nutr. 1988;48:712-738.[Abstract/Free Full Text]

45. Burke V, Beilin LJ. Vegetarian diets and high blood pressure: an update. Nutr Metab Cardiovasc Dis. 1994;4:103-112.

46. Sacks FM. Dietary fats and blood pressure: a critical review of the evidence. Nutr Rev. 1989;47:291-300.[Medline] [Order article via Infotrieve]

47. Stamler J, Ruth KJ, Liu K, Shekelle RB. Dietary anti-oxidants and blood pressure change in the Western Electric study 1958-66. Circulation. 1994;89:932. Abstract.

48. National Diet-Heart Study Research Group. The National Diet-Heart Study final report. Circulation. 1968;37(suppl I):I-1-I-428.

49. Hodges RE, Rebello T. Relationships between carbohydrates and blood pressure. In: Horan MJ, Blaustein M, Dunbar JB, Kachadorian W, Simopoulos AP, eds. NIH Workshop on Nutrition and Hypertension. New York, NY: Biomed Information Corp; 1984:249-253.

50. Myers MG. Effects of caffeine on blood pressure. Arch Intern Med. 1988;148:1189-1193.[Abstract/Free Full Text]

51. Sacks FM, Obarzanek E, Windhauser MM, Svetkey LP, Vollmer WM, McCullough M, Karanja N, Lin PH, Steele P, Proschan MA, Evans MA, Appel LJ, Bray GA, Vogt TM, Moore TJ. Rationale and design of the Dietary Approaches to Stop Hypertension trial (DASH): a multicenter controlled-feeding study of dietary patterns to lower blood pressure. Ann Epidemiol. 1995;5:108-118.[Medline] [Order article via Infotrieve]

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