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Constipation and Risk of Cardiovascular Disease among Postmenopausal Women

      Abstract

      Background

      Constipation is common in Western societies, accounting for 2.5 million physician visits/year in the US. Because many factors predisposing to constipation also are risk factors for cardiovascular disease, we hypothesized that constipation may be associated with increased risk of cardiovascular events.

      Methods

      We conducted a secondary analysis in 93,676 women enrolled in the observational arm of the Women's Health Initiative. Constipation was evaluated at baseline by a self-administered questionnaire. Estimates of the risk of cardiovascular events (cumulative end point including mortality from coronary heart disease, myocardial infarction, angina, coronary revascularization, stroke, and transient ischemic attack) were derived from Cox proportional hazards models adjusted for demographics, risk factors, and other clinical variables (median follow-up 6.9 years).

      Results

      The analysis included 73,047 women. Constipation was associated with increased age, African American and Hispanic descent, smoking, diabetes, high cholesterol, family history of myocardial infarction, hypertension, obesity, lower physical activity levels, lower fiber intake, and depression. Women with moderate and severe constipation experienced more cardiovascular events (14.2 and 19.1 events/1000 person-years, respectively) compared with women with no constipation (9.6/1000 person-years). After adjustment for demographics, risk factors, dietary factors, medications, frailty, and other psychological variables, constipation was no longer associated with an increased risk of cardiovascular events except for the severe constipation group, which had a 23% higher risk of cardiovascular events.

      Conclusion

      In postmenopausal women, constipation is a marker for cardiovascular risk factors and increased cardiovascular risk. Because constipation is easily assessed, it may be a helpful tool to identify women with increased cardiovascular risk.

      Keywords

      Constipation is common in Western societies, the prevalence varying between 2% and 28%, depending on the definition adopted.
      • Drossman D.
      • Li Z.
      • Andruzzi E.
      • et al.
      U.S. householder survey of functional gastrointestinal disorders Prevalence, sociodemography, and health impact.
      • Pare P.
      • Ferrazzi S.
      • Thompson W.G.
      • et al.
      An epidemiological survey of constipation in Canada: definitions, rates, demographics, and predictors of health care seeking.
      • Sandler R.S.
      • Jordan M.C.
      • Shelton B.J.
      Demographic and dietary determinants of constipation in the US population.
      • Stewart W.F.
      • Liberman J.N.
      • Sandler R.S.
      • et al.
      Epidemiology of constipation (EPOC) study in the United States: relation of clinical subtypes to socio-demographic features.
      • Talley N.J.
      • Weaver A.
      • Zinsmeister A.R.
      • Melton L.J.
      Functional constipation and outlet delay: a population-based study.
      Between 1958 and 1986, constipation accounted for 2.5 million physician visits/year in the US,
      • Sonnenberg A.
      • Koch T.R.
      Physician visits in the United States for constipation: 1958 to 1986.
      but this number has doubled over the last decade, especially in women and the elderly,
      • Shah N.
      • Chitkara D.
      • Locke G.R.
      • et al.
      Ambulatory care for constipation in the United States, 1993-2004.
      leading to considerable utilization of health care resources, with costs estimated to reach $6.9 billion. Nevertheless, constipation has received limited attention in the modern scientific literature, and its etiology and physiopathology are still poorly understood.
      • Leung F.
      Etiologic factors of chronic constipation—review of the scientific evidence.
      • Muller-Lissner S.A.
      • Kamm M.A.
      • Scarpignato C.
      • Wald A.
      Myths and misconceptions about chronic constipation.
      On the contrary, in the 19th century, constipation was considered “the disease of diseases,”
      • Whorton J.
      Civilisation and the colon: constipation as the “disease of diseases”.
      and the notion of its dangerous consequences dates back to the 16th century BC, when an Egyptian papyrus presented for the first time the notion of poisoning of the body by substances produced from decomposing waste in the intestine.
      • Ebbell B.
      The Papyrus Ebers—The Greatest Egyptian Medical Document.
      In both Ayurvedic and Chinese medicine, there is the belief that constipation may cause serious diseases,
      • Choe J.
      • Tu S.
      • Lim J.
      • et al.
      “Heat in their intestine”: colorectal cancer prevention beliefs among older Chinese Americans.
      and bowel purgation has been a mainstay of medical therapy for centuries.
      • Constipation was associated with several risk factors for cardiovascular disease and increased risk of cardiovascular events: unadjusted hazard ratio, mild vs none: 1.09 (95% confidence interval [CI], 1.02-1.17); moderate vs none: 1.49 (95% CI, 1.35-1.64); severe vs none: 2.00 (95% CI, 1.68-2.38).
      • This association was no longer present in multivariate models except for women with severe constipation, who had a 23% higher risk of cardiovascular events.
      • Because constipation is easily assessed, it may be a helpful tool to identify older women with multiple risk factors and increased cardiovascular risk.
      To date, there is limited information about the possible connection between constipation and chronic conditions, including cardiovascular disease. In cross-sectional studies, constipation has been linked with age and female sex;
      • Drossman D.
      • Li Z.
      • Andruzzi E.
      • et al.
      U.S. householder survey of functional gastrointestinal disorders Prevalence, sociodemography, and health impact.
      • Sandler R.S.
      • Jordan M.C.
      • Shelton B.J.
      Demographic and dietary determinants of constipation in the US population.
      • Stewart W.F.
      • Liberman J.N.
      • Sandler R.S.
      • et al.
      Epidemiology of constipation (EPOC) study in the United States: relation of clinical subtypes to socio-demographic features.
      • Talley N.J.
      • Jones M.
      • Nuyts G.
      • Dubois D.
      Risk factors for chronic constipation based on a general practice sample.
      • Sanjoaquin M.
      • Appleby P.
      • Spencer E.
      • Key T.
      Nutrition and lifestyle in relation to bowel movement frequency: a cross-sectional study of 20630 men and women in EPIC-Oxford.
      use of nonsteroidal anti-inflammatory drugs, aspirin, and other medications;
      • Talley N.J.
      • Jones M.
      • Nuyts G.
      • Dubois D.
      Risk factors for chronic constipation based on a general practice sample.
      • Chang J.
      • Locke G.R.
      • Schleck C.
      • Zinsmeistser A.R.
      • Talley N.J.
      Risk factors for chronic constipation and a possible role of analgesics.
      diabetes;
      • Talley N.J.
      • Jones M.
      • Nuyts G.
      • Dubois D.
      Risk factors for chronic constipation based on a general practice sample.
      lack of physical exercise;
      • Sandler R.S.
      • Jordan M.C.
      • Shelton B.J.
      Demographic and dietary determinants of constipation in the US population.
      • Dukas L.
      • Willett W.C.
      • Giovannucci E.L.
      Association between physical activity, fiber intake, and other lifestyle variables and constipation in a study of women.
      and with race, low socioeconomic status, and low education level.
      • Drossman D.
      • Li Z.
      • Andruzzi E.
      • et al.
      U.S. householder survey of functional gastrointestinal disorders Prevalence, sociodemography, and health impact.
      • Pare P.
      • Ferrazzi S.
      • Thompson W.G.
      • et al.
      An epidemiological survey of constipation in Canada: definitions, rates, demographics, and predictors of health care seeking.
      • Sandler R.S.
      • Jordan M.C.
      • Shelton B.J.
      Demographic and dietary determinants of constipation in the US population.
      • Stewart W.F.
      • Liberman J.N.
      • Sandler R.S.
      • et al.
      Epidemiology of constipation (EPOC) study in the United States: relation of clinical subtypes to socio-demographic features.
      • Higgins P.D.R.
      • Johanson J.F.
      Epidemiology of constipation in North America: a systematic review.
      Multiple studies have associated constipation with low fiber intake,
      • Sanjoaquin M.
      • Appleby P.
      • Spencer E.
      • Key T.
      Nutrition and lifestyle in relation to bowel movement frequency: a cross-sectional study of 20630 men and women in EPIC-Oxford.
      • Dukas L.
      • Willett W.C.
      • Giovannucci E.L.
      Association between physical activity, fiber intake, and other lifestyle variables and constipation in a study of women.
      • Arya L.A.
      • Novi J.M.
      • Shaunik A.
      • et al.
      Pelvic organ prolapse, constipation, and dietary fiber intake in women: a case-control study.
      • Everhart J.E.
      • Go V.L.
      • Johannes R.S.
      • et al.
      A longitudinal survey of self-reported bowel habits in the United States.
      and some trials have shown that adding fiber to specific diets improves bowel function.
      • Astrup A.
      • Vrist E.
      • Quaade F.
      Dietary fiber added to very low calorie diet reduces hunger and alleviates constipation.
      • Rigaud D.
      • Ryttig K.
      • Leeds A.
      • Bard D.
      • Apfelbaum M.
      Effects of a moderate dietary fibre supplement on hunger rating, energy input and faecal energy output in young, healthy volunteers A randomized, double-blind, cross-over trial.
      Because many of the factors that have been associated with constipation also are risk factors for cardiovascular disease, we hypothesized that women with symptoms of constipation may be at higher risk for cardiovascular events. The Women's Health Initiative (WHI) provided an ideal population to test this hypothesis, both because constipation is more frequent in older women, and because of the high quality of cardiovascular outcome ascertainment.

      Methods

       Design and Population

      The WHI consisted of a set of randomized clinical trials and an observational study.
      The Women's Health Initiative Study Group
      Design of the Women's Health Initiative clinical trial and observational study.
      The observational study was a large prospective cohort study conducted in 93,676 postmenopausal women ineligible or unwilling to participate in the WHI clinical trials. Recruitment (1994-1998) was conducted through mailings to eligible women from large mailing lists. The duration of follow-up was between 6 and 10 years, depending on when women enrolled in the study. In order to be eligible, women had to be 50-79 years old, postmenopausal, willing to provide written informed consent, and planning to be resident in the study recruitment area for at least 3 years following enrollment. Exclusion criteria included medical conditions predictive of a survival time of <3 years; conditions inconsistent with study participation, such as alcoholism, drug dependency, mental illnesses, and dementia; and participation in another randomized controlled clinical trial.
      Participants in the observational study had a baseline visit that included physical measurements (height, weight, blood pressure, heart rate, waist and hip circumferences), collection of blood specimens, a medication/supplement inventory, and completion of questionnaires related to medical history, family history, reproductive history, lifestyle/behavioral factors, and quality of life. Routine follow-up activities consisted of mailings sent annually and a visit 3 years after enrollment to update selected baseline data and obtain additional risk-factor data. The annual mailing included a medical history update and questionnaires about lifestyle habits, demographics, hormone therapy, dietary habits, and psychosocial variables. However, except for the medical history update, such information was not collected at each year of follow-up. For internal consistency, we used only baseline variables for this analysis.
      The study outcomes were coronary heart disease, stroke, breast and colorectal cancer, osteoporotic fractures, diabetes, and total mortality. Outcomes were identified by self-report on the medical history update or by reporting directly to clinic staff in the intervals between questionnaires. Centrally trained physicians adjudicated cardiovascular and mortality outcomes.
      • Curb J.D.
      • McTiernan A.
      • Heckbert S.R.
      • et al.
      Outcomes ascertainment and adjudication methods in the Women's Health Initiative.

       Variables Definition

      Information about constipation was collected at baseline by means of a self-administered questionnaire. Constipation, defined as “difficulty having bowel movements” over the previous 4 weeks, was rated using a scale ranging from none (symptom did not occur), mild (symptom did not interfere with usual activities), moderate (symptom interfered somewhat with usual activities), or severe (symptom was so bothersome that usual activities could not be performed).
      We considered covariates that may affect constipation or cardiovascular events or both, such as age, risk factors for coronary heart disease, diet, medications, and depression. Frailty,
      • Fugate Woods N.
      • LaCroix A.Z.
      • Gray S.L.
      • et al.
      Frailty: emergence and consequences in women aged 65 and older in the Women's Health Initiative Observational Study.
      optimism,
      • Tindle H.A.
      • Chang Y.-F.
      • Kuller L.H.
      • et al.
      Optimism, cynical hostility, and incident coronary heart disease and mortality in the Women's Health Initiative.
      white blood cell count,
      • Margolis K.L.
      • Manson J.E.
      • Greenland P.
      • et al.
      Leukocyte count as a predictor of cardiovascular events and mortality in postmenopausal women: the Women's Health Initiative Observational Study.
      and resting heart rate,
      • Hsia J.
      • Larson J.C.
      • Ockene J.K.
      • et al.
      Resting heart rate as a low-tech predictor of coronary events in women: prospective cohort study.
      which have been previously associated with unfavorable mortality and cardiovascular outcomes in WHI, were included in the analysis as additional confounders.
      Demographics (race/ethnicity, age at screening, marital status, and education) and information about hypertension, diabetes, high cholesterol, previous cardiovascular events, smoking status (ever, never, current), and family history of coronary heart disease were collected at baseline by means of self-administered questionnaires. Body mass index (weight in kilograms/height in meters2) was calculated from direct measurements of height and weight performed at baseline. Because baseline cholesterol levels were not measured in the entire sample, a proxy was used (history of high cholesterol requiring pills). Because of the high percentage of missing data in the question inquiring about age of first-degree relatives at the time of the heart attack, we used a yes/no question about the occurrence of myocardial infarction in any first-degree relative. Dietary variables (water, alcohol, fiber, and total fiber intake) were derived from a self-administered food-frequency questionnaire designed for the WHI.
      • Patterson R.E.
      • Kristal A.R.
      • Tinker L.F.
      • et al.
      Measurement characteristics of the Women's Health Initiative Food Frequency Questionnaire.
      Energy expenditure (total metabolic equivalent of task hours per week, kcal/week/kg) from recreational physical activity (walking, mild, moderate, and strenuous physical activity) was computed from self-reported questionnaires. Information about ongoing medications was collected from study participants who were required to bring their medication bottles at the baseline visit. Depression was assessed using the shortened version of the Center for Epidemiological Studies Depression Scale.
      • Weissman M.
      • Sholomskas D.
      • Pottenger M.
      • et al.
      Assessing depressive symptoms in five psychiatric populations: a validation study.
      Frailty was calculated using the criteria described by LaCroix and colleagues;
      • LaCroix A.Z.
      • Gray S.L.
      • Aragaki A.
      • et al.
      Statin use and incident frailty in women aged 65 years or older: prospective findings from the Women's Health Initiative Observational Study.
      optimism was measured using the Life Orientation Test–Revised.
      • Scheier M.F.
      • Carver C.S.
      Optimism, coping, and health: assessment and implications of generalized outcome expectancies.
      Trained study staff measured the baseline resting heart rate by palpating the radial pulse for 30 seconds; white blood cell count was obtained from baseline fasting blood specimens.

       Outcome

      The study outcome was a composite of death from coronary heart disease, nonfatal myocardial infarction, angina, coronary revascularization, stroke, and transient ischemic attack. WHI definitions for each of the cardiovascular outcomes are provided in the WHI manuals.
      • Curb D.
      • McTiernan A.
      • Heckbert S.
      Outcomes ascertainment and adjudication methods in the WHI.
      Fatal events were confirmed by death certificates, autopsy reports, hospital discharge summaries/death summaries, and coroner's report for deaths occurring out of hospital. Nonfatal events were documented by discharge summaries, hospital face sheet with International Classification of Diseases 9th revision, clinical modification codes, or physician attestation.

       Statistical Analysis

      Baseline characteristics according to different constipation categories were compared using chi-squared tests for categorical variables and Kruskal-Wallis tests for continuous variables. Survival curves were generated by the Kaplan-Meier method. Log-rank statistics were used to compare failure curves among different constipation categories. Estimates of the risk of cardiovascular events between categories of constipation relative to women reporting no symptoms (reference group) were derived from Cox proportional hazards regression models, adjusting for covariates in Table 1, Table 2. Time to event was computed in years as time from entry in the study to event, death, or last follow-up interview; and survivors were censored at the date of the last follow-up interview, or loss to follow-up. The validity of the proportional hazards assumption was confirmed by plotting log(-log[S(t)]) versus time on study, where S(t) indicates the estimated survivorship function, and noting that lines for different covariate values were parallel.
      • Lee E.
      • Wang J.
      Statistical Methods for Survival Data Analysis.
      Table 1Baseline Characteristics According to Self-reported Symptoms of Constipation
      Constipation Severity
      Total Sample 100 (73,047)None 65.3 (47,699)Mild 25.7 (18,790)Moderate 7.4 (5391)Severe 1.6 (1167)P-Value
      Chi-squared or Kruskall-Wallis.
      Characteristic, % (n)
      Age, years<.001
       50-5932.4 (23,634)31.8 (15,156)34.7 (6514)29.9 (1610)30.3 (354)
       60-6944.3 (32,377)44.8 (21,377)43.7 (8216)43.0 (2319)39.9 (465)
       70+23.3 (17,036)23.4 (11,166)21.6 (4060)27.1 (1462)29.8 (348)
      Race/ethnicity<.001
       American Indian0.4 (264)0.3 (149)0.4 (82)0.5 (26)0.6 (7)
       Asian-Pacific Islander2.8 (2054)3.0 (1406)2.8 (526)1.9 (104)1.5 (18)
       Black6.5 (4769)5.8 (2747)7.0 (1306)10.2 (548)14.4 (168)
       Hispanic3.1 (2238)2.7 (1306)3.3 (617)4.5 (245)6.0 (70)
       White86.2 (62,998)87.3 (41,631)85.6 (16,074)81.6 (4401)76.4 (892)
       Other/unknown1.0 (724)1.0 (460)1.0 (185)1.2 (67)1.0 (12)
      Education<.001
       < High school4.1 (2991)3.5 (1660)4.2 (793)7.2 (387)12.9 (151)
       High school diploma16.0 (11,690)15.2 (7262)16.7 (3136)19.3 (1039)21.7 (253)
       School after HS36.3 (26,533)35.9 (17,121)36.6 (6875)39.4 (2125)35.3 (412)
       College degree11.8 (8585)12.2 (5811)11.4 (2135)9.6 (518)10.4 (121)
       School after college31.8 (23,248)33.2 (15,845)31.1 (5851)24.5 (1322)19.7 (230)
      Marital status<.001
       Never married4.7 (3412)4.8 (2282)4.5 (838)4.4 (238)4.6 (54)
       Previously married31.8 (23,227)32.5 (15,516)29.6 (5559)32.3 (1739)35.4 (413)
       Currently married63.5 (46,408)62.7 (29,901)66.0 (12,393)63.3 (3414)60.0 (700)
      Diabetes4.0 (2882)3.5 (1653)4.3 (808)6.3 (339)7.0 (82)<.001
      BMI (kg/m2):<.001
       Normal (<25)41.5 (30,297)41.7 (19,872)42.4 (7973)37.5 (2022)36.9 (430)
       Overweight(25-29.9)34.0 (24,853)34.0 (16,200)33.9 (6366)35.4 (1906)32.7 (381)
       Obesity (30+)24.5 (17,897)24.4 (11,627)23.7 (4451)27.1 (1463)30.5 (356)
      Use of cholesterol-lowering medications14.5 (10,617)13.6 (6495)15.3 (2865)18.5 (997)22.3 (260)<.001
      Relative with MI52.7 (38,489)51.9 (24,773)53.2 (9998)56.4 (3039)58.2 (679)<.001
      Smoking.0112
       Never50.7 (37,013)50.7 (24,195)50.5 (9488)50.9 (2745)50.1 (585)
       Past43.3 (31,639)43.2 (20,626)43.8 (8228)42.7 (2299)41.7 (486)
       Current6.0 (4395)6.0 (2878)5.7 (1074)6.4 (347)8.2 (96)
      Physical activity (MET-hours/week)10.0 (3.5, 20.2)10.5 (3.8, 21.0)9.5 (3.0, 19.0)8.0 (2.3, 17.3)6.3 (1.5, 5.5)<.001
      Past history of CHD22.3 (16,291)20.6 (9817)23.6 (4442)30.0 (1615)35.7 (417)<.001
      Depression CES-D ≥0.0610.9 (7947)9.0 (4280)12.4 (2327)19.1 (1031)26.5 (309)<.001
      Optimism23.0 (21.0, 26.0)24.0 (22.0, 26.0)23.0 (21.0, 25.0)22.0 (20.0, 24.0)22.0 (19.0, 24.0)<.001
      Frailty score<.001
       056.4 (41,167)60.4 (28,810)52.7 (9899)39.4 (2122)28.8 (336)
       130.2 (22,029)28.4 (13,541)32.4 (6094)36.8 (1981)35.4 (413)
       213.5 (9851)11.2 (5348)14.9 (2797)23.9 (1288)35.8 (418)
      White blood cell count5.6 (4.7, 6.7)5.6 (4.8, 6.7)5.6 (4.7, 6.7)5.7 (4.8, 6.8)5.7 (4.8, 6.9)<.001
      Resting pulse (30 seconds)34.0 (31.0, 37.0)34.0 (31.0, 37.0)34.0 (31.0, 37.0)34.0 (31.0, 37.0)34.0 (31.0, 37.0).0306
      Calcium channel blockers9.6 (7035)8.3 (3962)10.9 (2042)14.7 (794)20.3 (237)<.001
      Diuretics7.2 (5277)6.7 (3177)7.5 (1417)9.8 (526)13.5 (157)<.001
      Abbreviations: BMI=body mass index; CES-D=Center for Epidemiological Studies Depression scale; CHD=coronary heart disease; MET=metabolic equivalent of task; MI=myocardial infarction.
      *Observations reported as % (n) or median (25th-75th percentile); observations with any missing data were omitted.
      Chi-squared or Kruskall-Wallis.
      Table 2Dietary Characteristics by Constipation Severity
      Severity of Constipation
      CharacteristicTotal SampleNoneMildModerateSevereP-Value
      Kruskal-Wallis.
      Dietary fiber (g)16.3 (12.1, 21.4)16.5 (12.2, 21.6)16.1 (12.0, 21.0)15.6 (11.5, 20.8)15.3 (11.0, 20.3)<.001
      Dietary water (g)1410.6 (1081.1, 1788.4)1425.5 (1096.6,1800.2)1392.9 (1069.2, 1769.2)1353.8 (1020.9, 1758.6)1310.0 (985.9, 1758.6)<.001
      Dietary alcohol (g)
      Drinkers only.
      5.08 (1.23, 12.79)5.50 (1.34, 13.23)4.16 (1.19, 12.45)3.65 (1.05, 12.00)2.71 (1.00, 10.54)<.001
      Total calories (kcal)1474.0 (1145.9, 1871.8)1474.2 (1148.9, 1869.4)1473.9 (1147.5, 1869.9)1472.9 (1123.2, 1896.1)1467.1 (1114.0, 1898.4).0011
      *Observations reported as median (25th-75th percentile); observations with any missing data omitted.
      Kruskal-Wallis.
      Drinkers only.
      The univariate model was adjusted for potential baseline confounders using 3 different models. The first model adjusted for demographic variables; the second model included model 1 covariates plus previous history of cardiovascular disease, coronary risk factors, and baseline heart rate. The third and final model adjusted for all previous covariates plus dietary factors, use of calcium channel blockers and diuretics, white blood cell count, depression, optimism, and frailty scores. The continuous variables age and body mass index were categorized as in Table 1, for consistency with previous WHI analyses. To handle nonlinear associations in Cox proportional hazards models, total calories and alcohol were categorized using quartiles, and white blood cell count, energy expenditure, and resting heart rate were log-transformed.
      Results are presented as unadjusted and adjusted hazard ratios with 95% confidence intervals. P values <.05 were considered significant. All statistical analyses were performed using SAS statistical software version 9.1.
      SAS Institute
      SAS Online Doc.

      Results

      Of the 93,676 women initially available for the analysis, 22.0% were excluded for missing data on the exposure indicator or major confounders, leaving 73,047 women for the final analysis. Higher rates of exclusion were seen in African Americans and Hispanics compared with non-Hispanic Whites and in women with lower educational levels. Compared with women included in the analyses, women omitted due to missing data were slightly more likely to report constipation (37.8% vs 34.7%), and were slightly older, on average (64.2 vs 63.4 years). All other comparisons between groups were statistically significant because of the large number of observations, but the magnitude of the differences was small.
      Table 1 shows the baseline prevalence of selected characteristics by constipation severity. At baseline, 34.7% of women reported having constipation: 25.7% reported having mild constipation, and 7.4% and 1.6% reported moderate and severe constipation, respectively. The mean duration of follow up was 6.4±1.4 years (median, 6.9 years).

       Demographic Characteristics and Risk Factor Profile of Women with Constipation

      The population's age ranged from 50 to 79 years (median 63.0 years). Women reporting constipation tended to be older, were more likely of African American or Hispanic descent, were less educated, and had greater frailty. They also more frequently reported one or more risk factors for cardiovascular disease: being diabetic, obese, hypertensive, or current smokers; using cholesterol-lowering medications; having lower levels of physical activity; or reporting that a family relative had had a myocardial infarction. Baseline prevalence of previous cardiovascular disease was higher in women with complaints of constipation. A higher proportion of women with constipation took calcium channel blockers or diuretics. Finally, the prevalence of depression was higher in women with constipation.
      Women reporting moderate or severe constipation had a slightly lower intake of dietary fiber, alcohol, and water, while differences among caloric intake were minimal (Table 2).

       Univariate and Multivariate Models

      Overall, women with moderate and severe constipation had a higher number of cardiovascular events (14.3 and 19.1 events/1000 person-years, respectively) compared with women with no constipation (9.6/1000 person-years). The cumulative incidence of cardiovascular events by constipation category is shown in the Figure. Constipation was associated with an increased risk of cardiovascular events (unadjusted hazard ratio, mild vs none: 1.09 [95% confidence interval (CI), 1.02-1.17]; moderate vs none, 1.49 [95% CI, 1.35-1.64]; severe vs none, 2.00 [95% CI, 1.68-2.38]; Table 3).
      Figure thumbnail gr1
      FigureCumulative incidence of cardiovascular events by baseline constipation.
      Table 3Adjusted and Unadjusted Hazard Ratios (95% CI) of Cumulative Cardiovascular Events by Constipation Severity
      Constipation Severity
      OutcomeNoneMildModerateSevere
      All cardiovascular events
      Full sample: n=72,628
      No. of events28911233467131
      Events/1000 person-years9.5910.4814.2419.13
      UnadjustedReference1.09 (1.02-1.17)1.49 (1.35-1.64)2.00 (1.68-2.38)
      Model 1Reference1.13 (1.05-1.20)1.37 (1.24-1.51)1.77 (1.48-2.11)
      Model 2Reference1.05 (0.99-1.13)1.14 (1.03-1.26)1.38 (1.15-1.64)
      Model 3Reference1.02 (0.95-1.09)1.07 (0.97-1.18)1.23 (1.03-1.47)
      Model 1: adjusted for demographics (baseline age group, race/ethnicity, education, marital status). Age categorized as 50-59, 60-69, and 70-79 years. Marital status categorized as never married, previously married (widowed, divorced, or separated), and currently married or in marriage-like relationship). Education categorized as:<high school, high school or equivalent, some college, college degree, and postgraduate.
      Model 2: adjusted for Model 1 covariates plus cardiovascular risk factors (previous history of cardiovascular disease, family history of myocardial infarction, body mass index (BMI), diabetes, high cholesterol, smoking, physical activity, hypertension) and log baseline heart rate. BMI categorized as underweight/normal (<25 kg/m2), overweight (25.0-29.9 kg/m2), and obese (≥30 kg/m2).
      Model 3: adjusted for Model 2 covariates plus dietary factors (water, fiber, alcohol, total calories), medications (calcium channel blockers, diuretics), log depression score, optimism score, frailty score, log white blood cell count. Dietary variables categorized by quartile in order to allow for nonlinear associations.
      The association of constipation with increased risk of cardiovascular events was reduced with adjustment for age, race/ethnicity, and education (Table 3, Model 1), and for risk factors and previous history of cardiovascular disease (Model 2). With further adjustment for dietary factors, use of diuretics and calcium-channel blockers, depression, optimism and frailty scores, and white blood cell count (Model 3), constipation was no longer associated with an increased risk of cardiovascular events, except for women with severe constipation, who still had a 23% higher risk of cardiovascular events compared with women with no symptoms of constipation. Results were overall consistent upon excluding women with baseline cardiovascular disease (data not shown).
      Table 4 shows the unadjusted and adjusted hazard ratios by constipation severity for each cardiovascular event composing the main study outcome. Constipation was associated with an increased risk of myocardial infarction, stroke, coronary revascularization, and angina (moderate and severe vs. none). For most cardiovascular events, the confidence interval widened compared with the cumulative outcome due to the low number of events, but the direction of the association was generally consistent with an increased risk of events in most constipation categories compared with the no-constipation group.
      Table 4Adjusted and Unadjusted Hazard Ratios (95% CI) of Each Cardiovascular Event by Constipation Severity
      Constipation Severity
      NoneMildModerateSevere
      Death, CHD

      Full sample: n=72,688
       No. events145431711
       Events/1000 person-years0.470.350.501.52
       UnadjustedReference0.76 (0.54-1.06)1.06 (0.64-1.76)3.25 (1.76-6.01)
       Model 1Reference0.81 (0.58-1.14)0.94 (0.57-1.55)2.63 (1.42-4.89)
       Model 2Reference0.73 (0.52-1.03)0.69 (0.42-1.15)1.84 (0.99-3.43)
       Model 3Reference0.65 (0.46-0.92)0.58 (0.35-0.97)1.32 (0.70-2.48)
      Death, possible CHD

      Full sample: n=72,688
       No. events9041166
       Events/1000 person-years0.290.340.470.83
       UnadjustedReference1.17 (0.81-1.69)1.62 (0.95-2.76)2.90 (1.27-6.62)
       Model 1Reference1.22 (0.85-1.77)1.34 (0.78-2.28)2.18 (0.95-5.01)
       Model 2Reference1.15 (0.79-1.66)1.11 (0.65-1.90)1.65 (0.71-3.81)
       Model 3Reference1.04 (0.72-1.51)0.93 (0.54-1.59)1.24 (0.53-2.89)
      MI

      Full sample: n=72,620
       No. events66329910331
       Events/1000 person-years2.162.493.054.34
       UnadjustedReference1.15 (1.01-1.32)1.41 (1.15-1.74)2.02 (1.41-2.89)
       Model 1Reference1.19 (1.04-1.37)1.29 (1.04-1.58)1.76 (1.22-2.52)
       Model 2Reference1.12 (0.98-1.29)1.07 (0.87-1.32)1.38 (0.96-1.98)
       Model 3Reference1.10 (0.96-1.26)1.04 (0.84-1.28)1.28 (0.89-1.99)
      Stroke

      Full sample: n=72,615
       No. events6742549627
       Events/1000 person-years2.192.112.833.77
       Unadjusted (P=.0029)Reference0.96 (0.83-1.11)1.30 (1.05-1.60)1.73 (1.18-2.54)
       Model 1Reference1.01 (0.88-1.17)1.19 (0.96-1.48)1.53 (1.04-2.26)
       Model 2Reference0.97 (0.85-1.12)1.04 (0.84-1.29)1.28 (0.87-1.88)
       Model 3Reference0.94 (0.81-1.08)0.98 (0.78-1.21)1.15 (0.78-1.70)
      TIA

      Full sample: n=72,614
       # events3871625715
       Events/1000 person-years1.261.341.682.09
       UnadjustedReference1.07 (0.89-1.29)1.34 (1.01-1.77)1.67 (0.997-2.80)
       Model 1Reference1.10 (0.92-1.32)1.25 (0.94-1.65)1.51 (0.90-2.54)
       Model 2Reference1.05 (0.88-1.26)1.10 (0.83-1.46)1.23 (0.73-2.07)
       Model 3Reference1.02 (0.85-1.22)1.01 (0.76-1.35)1.07 (0.63-1.80)
      PTCA

      Full sample: n=72,614
       # events76834412036
       Events/1000 person-years2.502.873.565.06
       UnadjustedReference1.15 (1.01-1.30)1.42 (1.17-1.72)2.03 (1.45-2.83)
       Model 1Reference1.16 (1.03-1.32)1.32 (1.09-1.60)1.84 (1.31-2.57)
       Model 2Reference1.08 (0.95-1.23)1.08 (0.89-1.31)1.39 (0.99-1.95)
       Model 3Reference1.06 (0.93-1.20)1.03 (0.84-1.25)1.27 (0.91-1.79)
      CABG

      Full sample: n=72,616
       # events4612118023
       Events/1000 person-years1.501.752.363.22
       UnadjustedReference1.17 (0.994-1.38)1.58 (1.24-2.00)2.15 (1.41-3.27)
       Model 1Reference1.20 (1.02-1.42)1.46 (1.15-1.85)1.95 (1.28-2.97)
       Model 2Reference1.11 (0.94-1.31)1.15 (0.91-1.46)1.43 (0.94-2.19)
       Model 3Reference1.08 (0.92-1.28)1.12 (0.88-1.43)1.34 (0.88-2.05)
      Angina

      Full sample: n=72,616
       # events107046720660
       Events/1000 person-years3.503.916.178.61
       UnadjustedReference1.12 (1.00-1.24)1.76 (1.51-2.04)2.45 (1.89-3.17)
       Model 1Reference1.13 (1.02-1.27)1.62 (1.39-1.88)2.16 (1.67-2.81)
       Model 2Reference1.04 (0.93-1.16)1.29 (1.11-1.50)1.60 (1.23-2.07)
       Model 3Reference1.00 (0.90-1.12)1.20 (1.03-1.40)1.39 (1.07-1.82)
      Abbreviations: CABG=coronary artery bypass grafting; CHD=coronary heart disease; CI=confidence interval; MI=myocardial infarction; PTCA=percutaneous coronary angioplasty; TIA=transient ischemic attack.
      Model 1: adjusted for demographics (baseline age group, race/ethnicity, education, marital status). Age categorized as 50-59, 60-69, and 70-79 years. Marital status categorized as never married, previously married (widowed, divorced, or separated), and currently married or in marriage-like relationship). Education categorized as:<high school, high school or equivalent, some college, college degree, and postgraduate.
      Model 2: adjusted for Model 1 covariates plus cardiovascular risk factors (previous history of cardiovascular disease, family history of myocardial infarction, body mass index (BMI), diabetes, high cholesterol, smoking, physical activity, hypertension) and log baseline heart rate. BMI categorized as underweight/normal (<25 kg/m2), overweight (25.0-29.9 kg/m2), and obese (≥30 kg/m2).
      Model 3: adjusted for Model 2 covariates plus dietary factors (water, fiber, alcohol, total calories), medications (calcium channel blockers, diuretics), log depression score, optimism score, frailty score, log white blood cell count. Dietary variables categorized by quartile in order to allow for nonlinear associations.

      Discussion

      In this analysis of a prospective cohort of community-dwelling, postmenopausal women, constipation was associated significantly with all the major risk factors for cardiovascular disease and with an increased risk of cardiovascular events. However, constipation was not an independent predictor of cardiovascular risk.
      At baseline, the prevalence of all major cardiovascular risk factors was higher in women with more severe self-reported constipation. Consequently, the finding of an association between constipation and increased incidence of cardiovascular events was not surprising, and confirmed our hypothesis that constipation is a marker for cardiovascular risk in women who are postmenopausal. When cardiovascular risk factors were added into the multivariate model (Model 2), they reduced the strength of the associations between constipation and cardiovascular events. Further adjustment for diet, constipation-causing medications, depression, optimism and frailty scores, and leukocyte count had a more modest impact on the association. In the final model, women with severe constipation still had a 23% higher risk of cardiovascular events compared with women who did not describe constipation. Our first hypothesis is that this independent association is due to residual confounding. Because information about risk factors and previous medical history in the observational arm of the WHI was self-reported, residual confounding could result if women had under-reported coronary risk factors such as high cholesterol levels that were not measured at baseline. Second, it has been suggested that food frequency questionnaires may underestimate fiber intake, thus resulting in inadequate adjustment for fiber consumption.
      • Hudson T.S.
      • Forman M.R.
      • Cantwell M.M.
      • et al.
      Dietary fiber intake: assessing the degree of agreement between food frequency questionnaires and 4-day food records.
      However, fiber intake is more likely to be under-reported in men than in women,
      • Hudson T.S.
      • Forman M.R.
      • Cantwell M.M.
      • et al.
      Dietary fiber intake: assessing the degree of agreement between food frequency questionnaires and 4-day food records.
      and the instrument used in the WHI showed good correlations with dietary recalls.
      • Patterson R.E.
      • Kristal A.R.
      • Tinker L.F.
      • et al.
      Measurement characteristics of the Women's Health Initiative Food Frequency Questionnaire.
      A purely speculative explanation is that severe constipation might trigger an inflammatory process that in turn accelerates the development of atherosclerosis and cardiovascular events. Inflammation, with release of cytokines by activated macrophages, could be caused by excessive or abnormal bacterial proliferation. Bacterial overgrowth with movement of gut bacteria from the lumen across the intestinal mucosa and immune activation has been described in patients with irritable bowel syndrome,
      • Lin H.C.
      Small intestinal bacterial overgrowth: a framework for understanding irritable bowel syndrome.
      and there is preliminary evidence of an association between infections and coronary heart disease.
      • Saikku P.
      • Leinonen M.
      • Tenkanen L.
      • et al.
      Chronic Chlamydia pneumoniae infection as a risk factor for coronary heart disease in the Helsinki Heart Study.
      • Patel P.
      • Mendall M.
      • Carrington D.
      • et al.
      Association of Helicobacter pylori and Chlamydia pneumoniae infections with coronary heart disease and cardiovascular risk factors.
      This study presents some limitations. First, information about constipation was self-reported and limited to the previous 4 weeks. It has been suggested that self-reported constipation is not as specific and sensitive as symptom-based criteria
      • Stewart W.F.
      • Liberman J.N.
      • Sandler R.S.
      • et al.
      Epidemiology of constipation (EPOC) study in the United States: relation of clinical subtypes to socio-demographic features.
      such as the number of bowel movements or the Rome II criteria.
      • Thompson W.
      • Longstreth G.
      • Drossman D.
      • et al.
      Functional bowel disorders and functional abdominal pain.
      The prevalence of constipation in our population was in fact higher (34%) than that reported in studies using objective criteria. If women in our study reported constipation that would not otherwise be confirmed by objective criteria, this would result in an underestimation of the associations between constipation and cardiovascular risk. Furthermore, the definition used in the WHI—“difficulty having bowel movements”—is similar to how primary care providers ask their patients about constipation.
      Second, because of the particular population studied, including women who are postmenopausal, mostly white, and educated beyond high school, these results may not be generalizable to younger age groups and less educated women and men. The limitations, however, should not detract from the strengths of the study; that is, a large cohort of community-dwelling, older women who were prospectively followed for outcomes over 6-10 years.
      In conclusion, in postmenopausal women, constipation is a marker for the major risk factors for cardiovascular disease and for increased cardiovascular risk. We did not find evidence for an independent association or for a causal association between constipation and cardiovascular disease. Because constipation is easily assessed in a primary care setting, it may be a helpful tool to identify women who may present several risk factors for cardiovascular disease and who may be at increased cardiovascular risk. Considering the prevalence of constipation, further research is needed to confirm whether it may be a marker of cardiovascular risk in both men and women and in younger age groups.

      Acknowledgements

      Women's Health Initiative investigators:
      Program Office (National Heart, Lung, and Blood Institute, Bethesda, MD): Jacques Rossouw, Shari Ludlam, Joan McGowan, Leslie Ford, and Nancy Geller.
      Clinical Coordinating Center (Fred Hutchinson Cancer Research Center, Seattle, WA): Ross Prentice, Garnet Anderson, Andrea LaCroix, Charles Kooperberg; (Medical Research Labs, Highland Heights, KY) Evan Stein; (University of California at San Francisco, San Francisco, CA) Steven Cummings.
      Clinical Centers: (Albert Einstein College of Medicine, Bronx, NY) Sylvia Wassertheil-Smoller; (Baylor College of Medicine, Houston, TX) Haleh Sangi-Haghpeykar; (Brigham and Women's Hospital, Harvard Medical School, Boston, MA) JoAnn E. Manson; (Brown University, Providence, RI) Charles B. Eaton; (Emory University, Atlanta, GA) Lawrence S. Phillips; (Fred Hutchinson Cancer Research Center, Seattle, WA) Shirley Beresford; (George Washington University Medical Center, Washington, DC) Lisa Martin; (Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA) Rowan Chlebowski; (Kaiser Permanente Center for Health Research, Portland, OR) Erin LeBlanc; (Kaiser Permanente Division of Research, Oakland, CA) Bette Caan; (Medical College of Wisconsin, Milwaukee, WI) Jane Morley Kotchen; (MedStar Research Institute/Howard University, Washington, DC) Barbara V. Howard; (Northwestern University, Chicago/Evanston, IL) Linda Van Horn; (Rush Medical Center, Chicago, IL) Henry Black; (Stanford Prevention Research Center, Stanford, CA) Marcia L. Stefanick; (State University of New York at Stony Brook, Stony Brook, NY) Dorothy Lane; (The Ohio State University, Columbus, OH) Rebecca Jackson; (University of Alabama at Birmingham, Birmingham, AL) Cora E. Lewis; (University of Arizona, Tucson/Phoenix, AZ) Cynthia A. Thomson; (University at Buffalo, Buffalo, NY) Jean Wactawski-Wende; (University of California at Davis, Sacramento, CA) John Robbins; (University of California at Irvine, CA) F. Allan Hubbell; (University of California at Los Angeles, Los Angeles, CA) Lauren Nathan; (University of California at San Diego, LaJolla/Chula Vista, CA) Robert D. Langer; (University of Cincinnati, Cincinnati, OH) Margery Gass; (University of Florida, Gainesville/Jacksonville, FL) Marian Limacher; (University of Hawaii, Honolulu, HI) J. David Curb; (University of Iowa, Iowa City/Davenport, IA) Robert Wallace; (University of Massachusetts/Fallon Clinic, Worcester, MA) Judith Ockene; (University of Medicine and Dentistry of New Jersey, Newark, NJ) Norman Lasser; (University of Miami, Miami, FL) Mary Jo O'Sullivan; (University of Minnesota, Minneapolis, MN) Karen Margolis; (University of Nevada, Reno, NV) Robert Brunner; (University of North Carolina, Chapel Hill, NC) Gerardo Heiss; (University of Pittsburgh, Pittsburgh, PA) Lewis Kuller; (University of Tennessee Health Science Center, Memphis, TN) Karen C. Johnson; (University of Texas Health Science Center, San Antonio, TX) Robert Brzyski; (University of Wisconsin, Madison, WI) Gloria E. Sarto; (Wake Forest University School of Medicine, Winston-Salem, NC) Mara Vitolins; (Wayne State University School of Medicine/Hutzel Hospital, Detroit, MI) Michael S. Simon.
      Women's Health Initiative Memory Study: (Wake Forest University School of Medicine, Winston-Salem, NC) Sally Shumaker.

      References

        • Drossman D.
        • Li Z.
        • Andruzzi E.
        • et al.
        U.S. householder survey of functional gastrointestinal disorders.
        Dig Dis Sci. 1993; 38: 1569-1580
        • Pare P.
        • Ferrazzi S.
        • Thompson W.G.
        • et al.
        An epidemiological survey of constipation in Canada: definitions, rates, demographics, and predictors of health care seeking.
        Am J Gastroenterol. 2001; 96: 3130-3137
        • Sandler R.S.
        • Jordan M.C.
        • Shelton B.J.
        Demographic and dietary determinants of constipation in the US population.
        Am J Public Health. 1990; 80: 185-189
        • Stewart W.F.
        • Liberman J.N.
        • Sandler R.S.
        • et al.
        Epidemiology of constipation (EPOC) study in the United States: relation of clinical subtypes to socio-demographic features.
        Am J Gastroenterol. 1999; 94: 3530-3540
        • Talley N.J.
        • Weaver A.
        • Zinsmeister A.R.
        • Melton L.J.
        Functional constipation and outlet delay: a population-based study.
        Gastroenterology. 1993; 105: 781-790
        • Sonnenberg A.
        • Koch T.R.
        Physician visits in the United States for constipation: 1958 to 1986.
        Dig Dis Sci. 1989; 34: 606-611
        • Shah N.
        • Chitkara D.
        • Locke G.R.
        • et al.
        Ambulatory care for constipation in the United States, 1993-2004.
        Am J Gastroenterol. 2008; 103: 1746-1753
        • Leung F.
        Etiologic factors of chronic constipation—review of the scientific evidence.
        Dig Dis Sci. 2007; 52: 313-316
        • Muller-Lissner S.A.
        • Kamm M.A.
        • Scarpignato C.
        • Wald A.
        Myths and misconceptions about chronic constipation.
        Am J Gastroenterol. 2005; 100: 232-242
        • Whorton J.
        Civilisation and the colon: constipation as the “disease of diseases”.
        BMJ. 2000; 321: 1586-1589
        • Ebbell B.
        The Papyrus Ebers—The Greatest Egyptian Medical Document.
        Levin & Munksgaard, Copenhagen1937
        • Choe J.
        • Tu S.
        • Lim J.
        • et al.
        “Heat in their intestine”: colorectal cancer prevention beliefs among older Chinese Americans.
        Ethnic Dis. 2006; 16: 248-254
        • Talley N.J.
        • Jones M.
        • Nuyts G.
        • Dubois D.
        Risk factors for chronic constipation based on a general practice sample.
        Am J Gastroenterol. 2003; 98: 1107-1111
        • Sanjoaquin M.
        • Appleby P.
        • Spencer E.
        • Key T.
        Nutrition and lifestyle in relation to bowel movement frequency: a cross-sectional study of 20630 men and women in EPIC-Oxford.
        Public Health Nutr. 2004; 7: 77-83
        • Chang J.
        • Locke G.R.
        • Schleck C.
        • Zinsmeistser A.R.
        • Talley N.J.
        Risk factors for chronic constipation and a possible role of analgesics.
        Neurogastroenterol Motil. 2007; 19: 905-911
        • Dukas L.
        • Willett W.C.
        • Giovannucci E.L.
        Association between physical activity, fiber intake, and other lifestyle variables and constipation in a study of women.
        Am J Gastroenterol. 2003; 98: 1790-1796
        • Higgins P.D.R.
        • Johanson J.F.
        Epidemiology of constipation in North America: a systematic review.
        Am J Gastroenterol. 2004; 99: 750-759
        • Arya L.A.
        • Novi J.M.
        • Shaunik A.
        • et al.
        Pelvic organ prolapse, constipation, and dietary fiber intake in women: a case-control study.
        Am J Obstet Gynecol. 2005; 192: 1687-1691
        • Everhart J.E.
        • Go V.L.
        • Johannes R.S.
        • et al.
        A longitudinal survey of self-reported bowel habits in the United States.
        Dig Dis Sci. 1989; 34: 1153-1162
        • Astrup A.
        • Vrist E.
        • Quaade F.
        Dietary fiber added to very low calorie diet reduces hunger and alleviates constipation.
        Int J Obesity. 1990; 14: 105-112
        • Rigaud D.
        • Ryttig K.
        • Leeds A.
        • Bard D.
        • Apfelbaum M.
        Effects of a moderate dietary fibre supplement on hunger rating, energy input and faecal energy output in young, healthy volunteers.
        Int J Obesity. 1987; 11: 73-78
        • The Women's Health Initiative Study Group
        Design of the Women's Health Initiative clinical trial and observational study.
        Control Clin Trials. 1998; 19: 61-109
        • Curb J.D.
        • McTiernan A.
        • Heckbert S.R.
        • et al.
        Outcomes ascertainment and adjudication methods in the Women's Health Initiative.
        Ann Epidemiol. 2003; 13: S122-S128
        • Fugate Woods N.
        • LaCroix A.Z.
        • Gray S.L.
        • et al.
        Frailty: emergence and consequences in women aged 65 and older in the Women's Health Initiative Observational Study.
        J Am Geriatr Soc. 2005; 53: 1321-1330
        • Tindle H.A.
        • Chang Y.-F.
        • Kuller L.H.
        • et al.
        Optimism, cynical hostility, and incident coronary heart disease and mortality in the Women's Health Initiative.
        Circulation. 2009; 120: 656-662
        • Margolis K.L.
        • Manson J.E.
        • Greenland P.
        • et al.
        Leukocyte count as a predictor of cardiovascular events and mortality in postmenopausal women: the Women's Health Initiative Observational Study.
        Arch Intern Med. 2005; 165: 500-508
        • Hsia J.
        • Larson J.C.
        • Ockene J.K.
        • et al.
        Resting heart rate as a low-tech predictor of coronary events in women: prospective cohort study.
        BMJ. 2009; 338: b219
        • Patterson R.E.
        • Kristal A.R.
        • Tinker L.F.
        • et al.
        Measurement characteristics of the Women's Health Initiative Food Frequency Questionnaire.
        Ann Epidemiol. 1999; 9: 178-187
        • Weissman M.
        • Sholomskas D.
        • Pottenger M.
        • et al.
        Assessing depressive symptoms in five psychiatric populations: a validation study.
        Am J Epidemiol. 1977; 106: 203-214
        • LaCroix A.Z.
        • Gray S.L.
        • Aragaki A.
        • et al.
        Statin use and incident frailty in women aged 65 years or older: prospective findings from the Women's Health Initiative Observational Study.
        J Gerontol A Biol Sci Med Sci. 2008; 63: 369-375
        • Scheier M.F.
        • Carver C.S.
        Optimism, coping, and health: assessment and implications of generalized outcome expectancies.
        Health Psychol. 1985; 4: 219-247
        • Curb D.
        • McTiernan A.
        • Heckbert S.
        Outcomes ascertainment and adjudication methods in the WHI.
        Ann Epidemiol. 2003; 13: S122-S128
        • Lee E.
        • Wang J.
        Statistical Methods for Survival Data Analysis.
        3rd edition. Wiley, New York2003
        • SAS Institute
        SAS Online Doc.
        (Version 9.1) SAS Institute, Inc. Publishers, Cary, NC1999
        • Hudson T.S.
        • Forman M.R.
        • Cantwell M.M.
        • et al.
        Dietary fiber intake: assessing the degree of agreement between food frequency questionnaires and 4-day food records.
        J Am Coll Nutr. 2006; 25: 370-381
        • Lin H.C.
        Small intestinal bacterial overgrowth: a framework for understanding irritable bowel syndrome.
        JAMA. 2004; 292: 852-858
        • Saikku P.
        • Leinonen M.
        • Tenkanen L.
        • et al.
        Chronic Chlamydia pneumoniae infection as a risk factor for coronary heart disease in the Helsinki Heart Study.
        Ann Intern Med. 1992; 116: 273-278
        • Patel P.
        • Mendall M.
        • Carrington D.
        • et al.
        Association of Helicobacter pylori and Chlamydia pneumoniae infections with coronary heart disease and cardiovascular risk factors.
        BMJ. 1996; 311: 711-714
        • Thompson W.
        • Longstreth G.
        • Drossman D.
        • et al.
        Functional bowel disorders and functional abdominal pain.
        Gut. 1999; 45: II43-II47

      Linked Article

      • Postmenopausal Women with Constipation and Cardiovascular Disease
        The American Journal of MedicineVol. 125Issue 2
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          The secondary analysis of the Women's Health Initiative's observational arm by Salmoirago-Blotcher et al1 offers a novel approach to the risk factors associated with this disease. This study clearly documents the distribution of the many cardiovascular risk factors, such as smoking and diabetes. Although the study does document the use of symptomatic medications such as diuretics and calcium channel blockers, it would be helpful to know the distribution of mortality-reducing medications in post-cardiovascular injury, such as angiotensin-converting enzyme inhibitors,2 beta-blockers,3 and aspirin.
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