The Association Between the Alternate Mediterranean Diet Index and Constipation: Evidence from the 2005-2010 NHANES

The Association Between the Alternate Mediterranean Diet Index and Constipation: Evidence from the 2005-2010 NHANES | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Association Between the Alternate Mediterranean Diet Index and Constipation: Evidence from the 2005-2010 NHANES Cuili Lin, Xiangying Lin, Kaiying He, Qihong Liu, Wenyi Fang, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6754983/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Diet plays a significant role in the develo1pment of constipation, and the alternate Mediterranean diet index (aMED) serves as an indicator of a healthy dietary pattern. However, the association between aMED and constipation has not been well studied in the general population. The aim of this study was to evaluate the relationship between the aMED and constipation. This study utilized cross-sectional data from individuals aged 20 and above who participated in the 2005–2010 National Health and Nutrition Examination Survey (NHANES). Detailed information was collected regarding constipation, aMED scores and several key covariates. Methods A total of 11397 participants were included in this study. Chronic constipation was defined using the Bristol Stool Form Scale (BSFS) as types 1 (separate hard lumps, like nuts) and 2 (sausage-like, but lumpy). aMED scores were obtained from 48-hour dietary recall questionnaires and categorized into quartiles. The relationship between aMED and constipation was assessed using weighted logistic regression and smoothed curve fitting, adjusting for potential confounders. Stratification by age, BMI, presence of hypertension diabetes, vascular disease and depression was also performed. Results The prevalence of chronic constipation in this cohort was 7.4%. The weighted logistic regression results showed that compared with individuals in the lowest aMED score category (Q1, 3 ≤ aMED < 5) those in the higher quartiles (Q2, 5 ≤ aMED < 5.5; Q3, 5.5 ≤ aMED < 6.5; Q4, 6.5 ≤ aMED ≤ 9) had adjusted ORs for constipation of 0.57 (95% CI: 0.41–0.78, P = 0.002 ), 0.64 (95% CI: 0.48–0.84, P = 0.003 ) and 0.46 (95% CI: 0.33–0.65, P = < 0.001 ), respectively. This indicates that as aMED scores increase the risk of constipation decreases. Individuals in the highest aMED category had a 54% lower risk of constipation compared to those in the lowest category. Further analysis using smoothed curve fitting confirmed a linear negative correlation between the aMED index and constipation.Stratified analyses were conducted based on sex, BMI, diabetes, hypertension, depression, and cardiovascular disease to evaluate potential modifications in the relationship between aMED scores and constipation. The findings demonstrated that the association persisted consistently across all subgroups, with no significant interaction effects detected. Conclusion Our study found that higher adherence to the aMED dietary pattern was significantly associated with a reduced risk of constipation, suggesting that promoting adherence to this diet may serve as an effective strategy for relieving constipation. Constipation alternate Mediterranean diet index NHANES cross-sectional study Figures Figure 1 Figure 2 Figure 3 Background Constipation is a prevalent functional gastrointestinal disorder, typically defined by infrequent bowel movements, hard stool consistency and straining during defecation, often accompanied by abdominal bloating and other discomforts[ 1 ]. The global prevalence of constipation is estimated at approximately 15%[ 2 ], with higher rates observed among women and older adults. Its aetiology is multifactorial, primarily influenced by dietary and lifestyle factors. Insufficient intake of dietary fibre, fluids vitamins B and E, β-carotene and niacin along with excessive consumption of caffeine has been associated with increased constipation risk[ 3 – 5 ]. Moreover unhealthy behaviours such as smoking excessive alcohol use, physical inactivity and poor sleep quality have been identified as significant contributors[ 6 , 7 ].Chronic constipation is not only linked to an elevated risk of cardiovascular and cerebrovascular events[ 8 ], but also to psychological disturbances including anxiety and depression. These mental health conditions may exacerbate constipation via neuroendocrine dysregulation perpetuating a vicious cycle of gastrointestinal dysfunction[ 9 ].From a healthcare perspective constipation poses a substantial economic burden with annual treatment costs in the United States alone exceeding $ 230 million. Importantly dietary modification remains a cornerstone of constipation management. As a first-line non-pharmacological intervention nutritional strategies are widely recommended to improve bowel function and reduce the likelihood of symptom recurrence. In recent years, the focus of nutritional research has shifted from examining individual foods or nutrients to adopting more comprehensive approaches that emphasize overall dietary patterns. This paradigm better captures the complexity of real-world eating behaviours and offers a more accurate assessment of disease risk[ 10 ].The Alternate Mediterranean Diet Score (aMED) is a widely used index to evaluate healthy dietary patterns. The aMED developed by researchers at Harvard University modifies the traditional Mediterranean Diet to suit non-Mediterranean populations. Key adaptations include replacing "total grain intake" with "whole grains ", substituting "olive oil" with the monounsaturated-to-saturated fat ratio (MUFA/SFA) excluding dairy products, redefining "wine with meals" as "moderate alcohol intake " and eliminating geographic food constraints.The aMED is characterised by high consumption of fruits, vegetables, legumes, nuts, whole grains and fish; moderate alcohol intake; a favourable ratio of monounsaturated to saturated fats; and low intake of red and processed meats. Numerous studies have demonstrated associations between higher aMED scores and a reduced risk of several chronic diseases: including cardiovascular disease[ 11 , 12 ], obesity[ 13 ], type 2 diabetes and diabetic nephropathy[ 14 ], Parkinson’s disease[ 15 ], depression[ 16 ] and gastric adenocarcinoma[ 17 ].Evidence also suggests that a diet rich in fibre, water and micronutrients such as vitamins B, E and β-carotene may reduce the risk of constipation. Given that the aMED diet is abundant in these components it may play a beneficial role in constipation prevention. However, the potential association between aMED and constipation has not yet been systematically investigated. Therefore, we conducted a cross-sectional study using data from the National Health and Nutrition Examination Survey (NHANES) to examine this relationship. We also accounted for multiple potential confounders including age, sex, household income, marital status, education level, smoking, and alcohol consumption. Our findings aim to enhance the understanding of the link between aMED and constipation and provide a basis for more effective dietary interventions in the management of chronic constipation. Materials and Methods Study Design This was a cross-sectional observational study based on a secondary analysis of data from the 2005–2010 cycles of the NHANES. The NHANES program aims to assess the health and nutritional status of non-institutionalized U.S. residents using a stratified multistage probability sampling design. Data collection includes in-home interviews screening and laboratory tests conducted in mobile examination centers (MECs) providing comprehensive demographic and health-related information. NHANES is approved by the Ethics Review Board of the National Center for Health Statistics (NCHS) and all participants provided written informed consent prior to participation. As this study involved secondary analysis of publicly available data no additional institutional review board (IRB) approval was required. Data were obtained from the NHANES website ( http://www.cdc.gov/nchs/nhanes.htm ; accessed March 1, 2022.We utilized data from the 2005–2010 NHANES cycles as they are the only cycles that include information on bowel habits and dietary intake. Participants were adults aged 20 years or older who had completed the interviews. We excluded pregnant individuals and those with missing data on aMED score, constipation status or key covariates. Alternative Mediterranean Diet Score In this study, we employed the alternative Mediterranean diet (aMED) score, a revised version of the traditional Mediterranean Diet (MED) index tailored for non-Mediterranean populations. Developed by the U.S. Food and Health Association, the aMED score encompasses nine dietary components: vegetables, fruits, legumes, nuts, whole grains, fish, the ratio of monounsaturated to saturated fats (MUFA/SFA), red and processed meats, and alcohol intake. The total score ranges from 0 to 9, based on individuals’ dietary intake patterns. Higher scores reflect greater adherence to a Mediterranean-style diet, which is characterized by higher consumption of beneficial food groups, a higher MUFA/SFA ratio, moderate alcohol consumption, and lower intake of red and processed meats[ 10 ]. Each component is assigned a score of 1 or 0 depending on whether the individual's intake is above the sex-specific median and whether higher (or lower) consumption is considered health-promoting. Dietary intake for each component over the preceding two days was assessed, and the aMED score was calculated using the “Dietaryindex” package in R. In our analysis, the aMED scores ranged from 3 to 9. Based on the distribution, participants were classified into four quartiles: Q1 (3 ≤ aMED < 5), Q2 (5 ≤ aMED < 5.5), Q3 (5.5 ≤ aMED < 6.5), and Q4 (6.5 ≤ aMED ≤ 9). This quartile-based categorization allowed for a more detailed investigation into the relationship between dietary quality and constipation.Overall, the aMED scoring system and quartile classification provided a structured and robust framework to examine the association between dietary patterns and bowel health. Definition of Constipation In previous NHANES cycles stool form has been regarded as a valid indicator for assessing constipation. Between 2005 and 2010 participants were asked about their bowel function during in-person interviews conducted at mobile examination centers. One of the questions was based on the Bristol Stool Form Scale (BSFS) a validated tool used to classify stool consistency and shape. Interviewers presented participants with a visual aid card depicting seven types of stools ranging from “separate hard lumps, like nuts” to “watery, no solid pieces.” Participants were asked to identify the stool type that best described their usual bowel movements. In this analysis constipation was defined as reporting a usual stool type corresponding to Type 1 (separate hard lumps, like nuts) or Type 2 (sausage-shaped, but lumpy) on the BSFS[ 18 ]. This definition is consistent with prior NHANES-based studies and is recognized for its reliability and clinical relevance. Covariates In accordance with previous literature[ 19 , 20 ] a comprehensive set of potential covariates was assessed including age, sex, marital status, race/ethnicity, educational, attainment household income, smoking status, alcohol consumption, physical activity time, body mass index (BMI), total energy intake, protein, carbohydrate, fat, dietary fiber, water intake, hypertension, diabetes, cardiovascular disease (CVD) and depression. Race/ethnicity was categorized as non-Hispanic White, non-Hispanic Black, Mexican American or other races. Marital status was grouped into married, cohabiting, and living alone. Education was divided into 12 years. Based on a report by the U.S. government [ 21 ], family income was classified using the poverty income ratio (PIR): low (PIR ≤ 1.3), medium (1.3 3.5).Smoking status was defined as never smokers (< 100 cigarettes), current smokers or former smokers (≥ 100 cigarettes in the past but currently not smoking). Alcohol consumption was classified as never drinkers (had < 12 drinks in their lifetime), current drinkers or former drinkers (had ≥ 12 drinks in one year but did not drink in the past year, or ≥ 12 lifetime drinks but no alcohol consumption in the past year).Prevalent diseases including hypertension, diabetes and CVD were identified based on self-reported physician diagnosis. Depression status was determined using the Patient Health Questionnaire-9 (PHQ-9) with scores of 0–4 indicating no depression and scores ≥ 5 indicating presence of depressive symptoms.BMI was calculated as weight divided by height squared (kg/m²) and classified as ≤ 25 or > 25 kg/m². Dietary intake variables including total energy, protein, carbohydrate, fat, fiber and water were obtained through 48-hour dietary recall interviews conducted prior to the MEC examination. The use of dietary supplements was determined based on responses to questions regarding supplement and medication use in the past month. Statistical Methods This study is a secondary analysis based on publicly available datasets. Categorical variables were summarized as frequencies and percentages, while continuous variables were described using means (SE) or medians and interquartile ranges (IQR) depending on their distribution. Appropriate statistical tests were applied based on variable characteristics: one-way analysis of variance (ANOVA) for normally distributed continuous variable, Kruskal-Wallis tests for skewed data and chi-square tests for categorical variables. To examine the association between the alternative Mediterranean diet (aMED) score and constipation, multivariable logistic regression models were employed to estimate odds ratios (ORs) and 95% confidence intervals (CIs). Three models were constructed with progressive levels of covariate adjustment:Model 1 adjusted for sociodemographic factors including age, sex, race/ethnicity, marital status, educational level, and household income;Model 2 further included lifestyle and dietary factors such as smoking status, alcohol consumption, physical activity, BMI, total energy intake, protein, carbohydrates, fats, dietary fiber and water intake;Model 3 incorporated additional adjustment for chronic diseases including diabetes, hypertension, depression and cardiovascular disease. To explore potential dose–response relationships, a restricted cubic spline (RCS) regression with four knots placed at the 5th, 35th, 65th and 95th percentiles of the aMED score distribution was performed. The curve was fitted based on covariates included in Model 3 to assess linearity. Subgroup analyses were conducted to investigate effect modification by sex, BMI, diabetes, hypertension, cardiovascular disease and depression. Heterogeneity across subgroups was assessed using multivariable logistic regression and interactions were tested using likelihood ratio tests. Missing data for covariates were handled using multivariable single imputation with Bayesian ridge regression as the estimator, implemented iteratively. Robustness was assessed by comparing pre- and post-imputation datasets and performing sensitivity analyses using K-nearest neighbors imputation. Sensitivity analysis was conducted using multiple imputation to address missing covariate data and evaluate the robustness of the findings. As this study utilized existing data, no a priori sample size calculation was performed. All analyses were conducted using R software version 4.2.2 and Free Statistics Software Version 2.1.1, and A two-tailed p-value < 0.05 was considered statistically significant. Results Study Population A total of 31034 individuals completed the NHANES interviews, among whom 17132 participants were aged 20 years or older. We excluded pregnant women (n = 463), individuals with missing aMED score data (n = 3282), those lacking information on constipation (n = 997), and participants with missing covariate data (n = 993). Ultimately 11397 eligible participants from the 2005–2010 NHANES cycles were included in this cross-sectional analysis. The detailed inclusion and exclusion process is illustrated in Fig. 1 . Baseline Characteristics of the Study Population Table 1 presents the baseline characteristics of all participants categorized by aMED score quartiles. A total of 846 individuals (7.4%) reported having constipation. The average age of the participants was 47.36 years (standard deviation 0.36) with 5752 participants (51.61%) being female. Individuals with higher aMED scores tended to be older female, married or cohabiting non-Hispanic White, non-smokers, previous alcohol consumers, more highly educated, with higher household income and less physically active. Additionally these individuals had lower rates of diabetes, hypertension, depression, cardiovascular disease and constipation as well as lower calorie protein and fat intake, and higher intake of carbohydrate, dietary fiber and water intake. Table 1 Population characteristics by categories of Alternative Mediterranean Diet Index. Characteristic Alternative Mediterranean Diet Index total Q1 (3 ≤ aMED < 5) Q2 (5 ≤ aMED < 5.5) Q3 (5.5 ≤ aMED < 6.5) Q4 (6.5 ≤ aMED ≤ 9) p -value NO. 11397 1932 1735 4264 3466 Age, y, Mean (SE) 47.51 (0.36) 42.70 (0.38) 44.61 (0.55) 46.93 (0.48) 52.03 (0.64) < 0.001 Sex, n (%) < 0.001 Male 5645 (47.98) 1089 (55.72 ) 911 (51.48 ) 2115 (48.64 ) 1530 (41.58 ) Female 5752 (52.02 ) 843 (44.28 ) 824 (48.52 ) 2149 (51.36 ) 1936 (58.42 ) Race/ethnicity, n (%) < 0.001 Non-Hispanic white 5951 (73.86 ) 1034 (73.30 ) 810 (68.33 ) 2172 (72.90 ) 1935 (77.83 ) Non-Hispanic black 2224 (10.30 ) 441 (13.32 ) 392 (13.02 ) 809 (10.04 ) 582 (7.80 ) Mexican American 1916 (7.17 ) 241 (5.31 ) 319 (8.95 ) 808 (8.09 ) 548 (6.22 ) Others 1306 (8.67 ) 216 (8.07 ) 214 (9.70 ) 475 (8.97 ) 401 (8.15 ) Marital status, n (%) 0.002 Married or living with a partner 7079 (64.76 ) 1130 (60.30 ) 1034 (63.54 ) 2679 (64.27 ) 2236 (68.22 ) Living alone 4318 (35.24 ) 802 (39.70 ) 701 (36.46 ) 1585 (35.73 ) 1230 (31.78 ) Education level, y, n (%) < 0.001 12 5685 (58.89 ) 758 (46.13 ) 707 (49.63 ) 2121 (58.86 ) 2099 (69.79 ) Family income, n (%) < 0.001 Low 3261 (18.96 ) 753 (26.78 ) 609 (24.19 ) 1219 (19.03 ) 680 (12.41 ) Medium 4402 (35.61 ) 742 (37.14 ) 680 (37.63 ) 1661 (35.96 ) 1319 (33.46 ) High 3734 (45.43 ) 437 (36.08 ) 446 (38.18 ) 1384 (45.01 ) 1467 (54.12 ) Body mass index, kg/m2, Mean (SE) 28.75 (0.13) 29.65 (0.26) 29.40 (0.25) 28.95 (0.18) 27.75 (0.17) < 0.001 Physical activity time, min, Mean (SE) 180.00 (23.62 719.35) 204.28 (0.00 959.57) 180.00 (13.32 840.00) 175.00 (18.97 624.15) 203.98 (31.50 600.00) 0.013 Smoking status, n (%) < 0.001 Never 5958 (52.79 ) 797 (40.58 ) 824 (47.43 ) 2307 (54.10 ) 2030 (60.03 ) Current 3002 (25.49 ) 402 (20.62 ) 408 (23.56 ) 1124 (25.05 ) 1068 (29.42 ) Former 2437 (21.72 ) 733 (38.79 ) 503 (29.01 ) 833 (20.85 ) 368 (10.55 ) Alcoholing status, n (%) < 0.001 Never 1444 (10.45 ) 201 (7.23 ) 220 (10.69 ) 552 (10.77 ) 471 (11.62 ) Current 2323 (16.76 ) 442 (19.90 ) 401 (19.06 ) 872 (16.51 ) 608 (14.37 ) Former 7630 (72.79 ) 1289 (72.86 ) 1114 (70.25 ) 2840 (72.72 ) 2387 (74.01 ) Calorie consumption, kcal/d, Mean (SE) 2158.34 (17.26) 2267.73 (33.33) 2221.95 (37.78) 2146.40 (24.20) 2086.61 (27.86) 0.005 Protein consumption, g/d, Mean (SE) 83.79 (0.80) 88.02 (1.58) 87.25 (1.91) 83.45 (0.98) 80.41 (1.19) 0.007 Carbohydrate consumption, g/d, Mean (SE) 259.06 (1.98) 261.18 (3.96) 258.80 (4.71) 255.28 (3.39) 262.59 (2.82) 0.029 Fat consumption, g/d, Mean (SE) 82.10 (0.88) 88.39 (1.75) 85.79 (1.83) 82.70 (1.07) 76.42 (1.43) < 0.001 Dietary fiber taken, g/d, Mean (SE) 16.43 (0.24) 11.59 (0.31) 13.57 (0.33) 15.87 (0.22) 20.93 (0.36) < 0.001 Moisture taken, g/d, Mean (SE) 3086.15 (30.55) 3026.09 (65.26) 3039.27 (47.32) 3070.62 (37.56) 3157.30 (42.56) < 0.001 Diabetes 0.28 No 9380 (87.32 ) 1622 (88.30 ) 1444 (87.36 ) 3458 (86.45 ) 2856 (87.83 ) Yes 2017 (12.68 ) 310 (11.70 ) 291 (12.64 ) 806 (13.55 ) 610 (12.17 ) Hypertension 0.036 No 6534 (62.59 ) 1196 (66.69 ) 1016 (62.39 ) 2426 (61.74 ) 1896 (61.57 ) Yes 4863 (37.41 ) 736 (33.31 ) 719 (37.61 ) 1838 (38.26 ) 1570 (38.43 ) depression < 0.001 No 8006 (71.39 ) 1223 (63.59 ) 1160 (68.08 ) 3002 (71.42 ) 2621 (76.94 ) Yes 3391 (28.61 ) 709 (36.41 ) 575 (31.92 ) 1262 (28.58 ) 845 (23.06 ) CVD 0.57 No 10089 (91.51 ) 1709 (91.38 ) 1552 (92.37 ) 3794 (91.69 ) 3034 (90.98 ) Yes 1308 (8.49 ) 223 (8.62 ) 183 (7.63 ) 470 (8.31 ) 432 (9.02 ) constipation < 0.001 No 10551 (93.12 ) 1751 (89.49 ) 1606 (93.47 ) 3936 (93.04 ) 3258 (94.93 ) Yes 846 (6.88 ) 181 (10.51 ) 129 (6.53 ) 328 (6.96 ) 208 (5.07 ) Association Between aMED Score and Constipation After adjusting for potential confounders, quartile analysis revealed a clear inverse relationship between adherence to the aMED dietary pattern and the risk of constipation.Compared with individuals with lower aMED scores (3 ≤ aMED < 5), the adjusted odds ratios (OR) for constipation in the Q2 (5 ≤ aMED < 5.5), Q3 (5.5 ≤ aMED < 6.5) and Q4 (6.5 ≤ aMED ≤ 9) groups were 0.57 (95% CI: 0.41–0.78, P = 0.002 ), 0.64 (95% CI: 0.48–0.84, P = 0.003 ) ,and 0.46 (95% CI: 0.33–0.65, P = < 0.001 ), respectively (Table 2 ). This suggests that aMED scores between 6.5 and 9 are associated with a 54% reduction in the risk of constipation.Additionally, the restricted cubic splines (RCS) analysis showed a linear relationship between aMED score and constipation (linear trend, P = 0.101 ) (Fig. 2 ). Table 2 Association between Alternative Mediterranean Diet Index and constipation(the complete dataset). Quartiles OR(95% Cl) No. Crude p -Value Model 1 p -Value Model 2 p -Value Model 3 p -Value Alternative Mediterranean Diet Index Q1(3 ≤ aMED < 5) 1932 1(Ref) 1(Ref) 1(Ref) 1(Ref) Q2(5 ≤ aMED < 5.5) 1735 0.59(0.43–0.83) 0.003 0.57(0.42–0.79) 0.001 0.56(0.41–0.77) 0.001 0.57(0.41–0.78) 0.002 Q3(5.5 ≤ aMED < 6.5) 4264 0.64(0.50–0.82) < 0.001 0.64(0.50–0.82) < 0.001 0.63(0.48–0.83) 0.002 0.64(0.48–0.84) 0.003 Q4(6.5 ≤ aMED ≤ 9) 3466 0.45(0.33–0.62) < 0.001 0.47(0.34–0.65) < 0.001 0.45(0.30–0.63) < 0.001 0.46(0.33–0.65) < 0.001 Trend test 11397 < 0.001 < 0.001 < 0.001 < 0.001 Q, quartiles; OR, odds ratio; CI, confidence interval; Ref: reference. Model 1 was adjusted for sociodemographic variables (age, sex, marital status, race/ethnicity, education level, family income). Model 2 was adjusted for sociodemographic (age, sex, marital status, race/ethnicity, education level, family income), smoking status, Alcoholing status,physical activity time, body mass index,Calorie consumption,Protein consumption,Carbohydrate consumption,Fat consumption,Dietary fiber taken ,and Moisture taken. Model 3 sociodemographic (age, sex, marital status, race/ethnicity, education level, family income), smoking status, Alcoholing status,physical activity time, body mass index,Calorie consumption,Protein consumption,Carbohydrate consumption,Fat consumption,Dietary fiber taken ,and Moisture taken,diabetes,hypertension,,depression,and Cardiovascular Disease. Subgroup Analyses To explore the potential modifying effects of individual characteristics on the association between aMED scores and constipation stratified analyses were performed based on predefined variables. These included sex, BMI, diabetes, hypertension, depression, and cardiovascular disease. The association between aMED and constipation remained consistent across all subgroups and no significant interactions were observed.(Fig. 3 ). Sensitivity Analysis After multiple imputation of missing covariate data the total sample size increased to 12390 participants. The inverse association between aMED score and constipation remained robust. Compared with individuals in the lowest aMED quartile (3 ≤ aMED < 5), the adjusted odds ratios for constipation were 0.59 (95% CI: 0.43–0.81, P = 0.002) for Q2 (5 ≤ aMED < 5.5), 0.65(95% CI: 0.49–0.85, P = 0.004) for Q3 (5.5 ≤ aMED < 6.5) and 0.49 (95% CI: 0.35–0.68, P = < 0.001) for Q4 (6.5 ≤ aMED ≤ 9) as presented in Table 3 . These findings confirm the stability of the observed association after addressing missing data. Table 3 Association between Alternative Mediterranean Diet Index and constipation(multiple imputed dataset for covariate missing values). Quartiles OR(95% Cl) No. Crude p -Value Model 1 p -Value Model 2 p -Value Model 3 p -Value Alternative Mediterranean Diet Index Q1(3 ≤ aMED < 5) 2057 1(Ref) 1(Ref) 1(Ref) 1(Ref) Q2(5 ≤ aMED < 5.5) 1895 0.62(0.45–0.87) 0.006 0.59(0.43–0.81) 0.002 0.58(0.42–0.80) 0.002 0.59(0.43–0.81) 0.002 Q3(5.5 ≤ aMED < 6.5) 4643 0.66(0.52–0.85) 0.002 0.66(0.52–0.84) 0.001 0.64(0.49–0.84) 0.002 0.65(0.49–0.85) 0.004 Q4(6.5 ≤ aMED ≤ 9) 3795 0.49(0.37–0.66) < 0.001 0.49(0.36–0.67) < 0.001 0.48(0.34–0.66) < 0.001 0.49(0.35–0.68) < 0.001 Trend test 12390 < 0.001 < 0.001 < 0.001 < 0.001 Q, quartiles; OR, odds ratio; CI, confidence interval; Ref: reference. Model 1 was adjusted for sociodemographic variables (age, sex, marital status, race/ethnicity, education level, family income). Model 2 was adjusted for sociodemographic (age, sex, marital status, race/ethnicity, education level, family income), smoking status, Alcoholing status,physical activity time, body mass index,Calorie consumption,Protein consumption,Carbohydrate consumption,Fat consumption,Dietary fiber taken ,and Moisture taken. Model 3 sociodemographic (age, sex, marital status, race/ethnicity, education level, family income), smoking status, Alcoholing status,physical activity time, body mass index,Calorie consumption,Protein consumption,Carbohydrate consumption,Fat consumption,Dietary fiber taken ,and Moisture taken,diabetes,hypertension,,depression,and Cardiovascular Disease. Discussion This large cross-sectional study involving U.S. adults demonstrated a significant inverse linear relationship between the alternate Mediterranean Diet (aMED) score and the risk of constipation. Higher aMED scores were associated with a progressively lower likelihood of constipation. Stratified and sensitivity analyses confirmed the robustness of this association. Our findings suggest that adherence to the aMED dietary pattern may be associated with a reduced risk of constipation. Individuals with higher aMED scores tend to consume more fruits, vegetables, nuts, legumes, whole grains, fish, and foods rich in unsaturated fatty acids, while consuming less red and processed meats, with moderate alcohol intake. Although direct evidence linking aMED with constipation remains scarce, numerous studies have investigated the effects of its individual components on bowel function.Greater consumption of vegetables, fruits, whole grains, legumes, fish, and unsaturated fats, alongside lower intake of red meat, processed foods, and saturated fats, has been consistently associated with a lower risk of constipation. For example, higher vegetable intake is linked to a reduced risk of constipation[ 21 ], with non-starchy vegetables such as tomatoes showing particularly strong protective effects[ 22 ]. Xu et al. found that increased fruit consumption was inversely associated with constipation prevalence[ 23 ], and specific fruits such as kiwifruit, mangoes, prunes, and figs have demonstrated beneficial effects[ 24 ] [ 25 ].Whole grains, a common source of dietary fiber in Western diets, have also been shown to reduce constipation risk [ 26 ]. In a clinical study by Odes et al., patients who consumed a high-fiber cereal mixture derived from oats, corn, wheat, and soy for two weeks experienced improved bowel frequency and stool consistency, with reduced laxative use[ 27 ]. Similarly, Sander et al. reported lower legume intake in constipated individuals[ 28 ]. Liu et al.[ 29 ] demonstrated that adherence to the HEI-2015 dietary pattern, which emphasizes fruits, vegetables, legumes, whole grains, seafood, and plant-based protein sources rich in unsaturated fats, is associated with a lower prevalence of constipation[ 29 ].Fish intake specifically appears to be protective. In a cross-sectional study in older adults in Beijing, Yang et al. reported significantly lower constipation rates among those who consumed fish regularly (P < 0.01) [ 30 ]. Conversely, Reichardt et al. found that saturated fat-rich Western diets may induce colonic neuronal death via TLR4 signaling activation, contributing to impaired motility and constipation[ 31 ].Higher DI-GM scores—indicative of lower intake of red and processed meats, refined grains, and high-fat foods—have also been linked to reduced constipation risk[ 18 ]. Conversely, adherence to a Western dietary pattern characterized by high consumption of red and processed meats, potatoes, poultry, and desserts is associated with persistent constipation symptoms[ 32 ].Collectively, these findings align with our results and support the potential benefits of aMED dietary adherence in reducing the risk of constipation. However, the mechanisms by which the aMED diet reduces the risk of constipation remain to be fully elucidated. Emerging evidence suggests that the aMED dietary pattern may exert beneficial effects by increasing the intake of dietary fiber, sorbitol, polyphenols, unsaturated fats, water, and micronutrients, thereby modulating the gut microbiota, enhancing intestinal motility, and improving stool consistency and hydration.Firstly, the aMED diet encourages the consumption of fiber-rich foods such as fruits, vegetables, legumes, whole grains, and nuts, which contain various types of dietary fiber[ 33 ]. Moderately fermentable soluble fiber forms gels that retain water in stool, improving viscosity [ 34 ], while rapidly fermentable soluble fiber acts as a prebiotic, promoting the growth of beneficial bacteria and the production of short-chain fatty acids (SCFAs) and gases, increasing osmotic load and accelerating gut transit[ 35 – 38 ]. Insoluble fiber, such as coarse wheat bran, stimulates the intestinal mucosa and induces water and mucus secretion, softening stools and facilitating defecation [ 39 , 40 ].Secondly, fruits rich in sorbitol contribute to stool softening. Sorbitol is poorly absorbed in the small intestine, retains water osmotically, and is fermented in the colon to produce SCFAs, particularly butyrate, which enhances gut motility[ 41 , 42 ].Thirdly, polyphenols found in vegetables, grains, and wine may regulate the gut microbiome. High molecular weight polyphenols reach the colon, where they promote the growth of beneficial bacteria (e.g., Bifidobacterium, Lactobacillus) and inhibit pathogenic species, thereby improving intestinal function[ 43 , 44 ] [ 45 , 46 ].The intake of unsaturated fats, especially omega-3 fatty acids from nuts and fish, also contributes. These fats lubricate the bowel, regulate microbial diversity by reducing harmful species (e.g., Faecalibacterium) and increasing beneficial ones (e.g., Bacteroides, butyrate-producing bacteria), and modulate inflammation and SCFA production, thereby promoting gut motility [ 47 – 50 ].Moreover, the aMED diet provides micronutrients such as magnesium and vitamin E through green leafy vegetables, legumes, whole grains, and nuts. Magnesium, poorly absorbed in the intestine, increases luminal osmolarity, promoting water retention and softer stools[ 51 ] [ 52 ]. Vitamin E has been inversely associated with constipation, potentially by counteracting oxidative stress and preserving intestinal barrier and neuromuscular function [ 4 ].Conversely, Western dietary patterns rich in red and processed meats, sugars, and fats may disrupt gut microbial balance, impair mucosal integrity, promote E. coli colonization, trigger inflammation, and affect GLP-1 signaling, contributing to constipation pathogenesis[ 31 ] .Collectively, aMED may alleviate constipation through both direct effects on stool consistency and indirect modulation of gut microbiota and their metabolites. Further prospective studies are warranted to validate its preventive and therapeutic potential. Nevertheless, several limitations should be considered. First, the data on constipation were only collected from the NHANES survey conducted between 2005 and 2010, which prevents further validation using data from other time periods. Second, despite conducting regression modeling, stratified analyses and sensitivity analyses residual confounding effects due to unmeasured or unknown factors cannot be completely ruled out. Third, the findings of this study are based on a survey of U.S. adults and whether these results can be generalized to other populations remains to be determined. Fourth, the food intake data for the aMED score were obtained through a 48-hour recall method, which may introduce recall bias and does not fully capture participants' long-term dietary patterns. Fifth, constipation in our study was diagnosed solely based on stool form scoring, without a more comprehensive clinical investigation of gastrointestinal diseases. Lastly, due to the cross-sectional nature of this study, causality between the aMED diet and constipation cannot be established. Longitudinal studies are needed in the future to confirm this relationship. In addition to the link between aMED and constipation, future research could also explore other potential factors influencing constipation, such as environmental exposures. Conclusion In summary, this study demonstrates a linear negative correlation between the aMED score and the incidence of constipation among U.S. adults. Specifically, as the aMED score increases the risk of constipation decreases. These findings highlight the significant association between the aMED score and the occurrence of constipation providing a theoretical foundation for further research into the potential role of the aMED dietary pattern in the prevention and management of constipation. Declarations Ethics approval and consent to participate This study was exempt from ethics review and approval as it involved secondary data analysis which does not require additional ethics committee approval.The NHANES study was authorized by the National Center for Health Statistics (NCHS) Institutional Review Board and all participants provided written informed consent prior to participation. Consent for publication Not applicable. Conflict of interest The authors declare that this study was independently conducted without any commercial or financial relationships that could be interpreted as potential conflicts of interest. Funding This research was supported by the following grants:National Natural Science Foundation of China (No. 82274282, 82174365);Central Government's Special Fund for Local Science and Technology Development (No. 2023L3013);Fujian Provincial Natural Science Foundation General Project (No. 2021J01878). Author Contribution Conceptualization: Xiao Ke, Yan Ren, Minghan Huang, Xiaofeng Huang;Data curation: Cuili Lin, Xiangying Lin;Formal analysis: Cuili Lin, Kaiying He;Funding acquisition: Xiao Ke, Yan Ren;Methodology: Cuili Lin, Qihong Liu, Wenyi Fang;Writing—original draft: Cuili Lin;Writing—review & editing: Cuili Lin, Xiangying Lin, Kaiying He, Qihong Liu Wenyi Fang,Minghan Huang, Xiaofeng Huang,Yan Ren, Xiao Ke. All authors have read and approved the final manuscript. Acknowledgments We sincerely thank Dr. Jie Liu from the Vascular and Endovascular Surgery Department at the PLA General Hospital for his contributions in statistical support research design consultation and valuable feedback on the manuscript. Data Availability The datasets generated and analyzed during the current study are available online. The name and identifier of the data repository can be accessed at: http://www.cdc.gov/nchs/nhanes.htm (accessed on March 1 2022). 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Butyrate's role in human health and the current progress towards its clinical application to treat gastrointestinal disease. Clin Nutr. 2023;42(2):61–75. Tomlin J, Read NW. Laxative properties of indigestible plastic particles. BMJ. 1988;297(6657):1175–6. Lewis SJ, Heaton KW. Roughage revisited: the effect on intestinal function of inert plastic particles of different sizes and shape. Dig Dis Sci. 1999;44(4):744–8. Koyama T, Nagata N, Nishiura K, Miura N, Kawai T, Yamamoto H. Prune Juice Containing Sorbitol, Pectin, and Polyphenol Ameliorates Subjective Complaints and Hard Feces While Normalizing Stool in Chronic Constipation: A Randomized Placebo-Controlled Trial. Am J Gastroenterol. 2022;117(10):1714–7. Lederle FA, Busch DL, Mattox KM, West MJ, Aske DM. Cost-effective treatment of constipation in the elderly: a randomized double-blind comparison of sorbitol and lactulose. Am J Med. 1990;89(5):597–601. Merken HM, Beecher GR. Measurement of food flavonoids by high-performance liquid chromatography: A review. J Agric Food Chem. 2000;48(3):577–99. Clifford MN. Diet-derived phenols in plasma and tissues and their implications for health. Planta Med. 2004;70(12):1103–14. Cardona F, Andrés-Lacueva C, Tulipani S, Tinahones FJ, Queipo-Ortuño MI. Benefits of polyphenols on gut microbiota and implications in human health. J Nutr Biochem. 2013;24(8):1415–22. Sejbuk M, Mirończuk-Chodakowska I, Karav S, Witkowska AM. Dietary Polyphenols, Food Processing and Gut Microbiome: Recent Findings on Bioavailability, Bioactivity, and Gut Microbiome Interplay. Antioxid (Basel) 2024, 13(10). Kris-Etherton PM, Harris WS, Appel LJ. Fish consumption, fish oil, omega-3 fatty acids, and cardiovascular disease. Circulation. 2002;106(21):2747–57. Watson H, Mitra S, Croden FC, Taylor M, Wood HM, Perry SL, Spencer JA, Quirke P, Toogood GJ, Lawton CL, et al. A randomised trial of the effect of omega-3 polyunsaturated fatty acid supplements on the human intestinal microbiota. Gut. 2018;67(11):1974–83. Costantini L, Molinari R, Farinon B, Merendino N. Impact of Omega-3 Fatty Acids on the Gut Microbiota. Int J Mol Sci 2017, 18(12). Fu Y, Wang Y, Gao H, Li D, Jiang R, Ge L, Tong C, Xu K. Associations among Dietary Omega-3 Polyunsaturated Fatty Acids, the Gut Microbiota, and Intestinal Immunity. Mediators Inflamm. 2021;2021:8879227. Guerrera MP, Volpe SL, Mao JJ. Therapeutic uses of magnesium. Am Fam Physician. 2009;80(2):157–62. Bellini M, Tonarelli S, Barracca F, Rettura F, Pancetti A, Ceccarelli L, Ricchiuti A, Costa F, de Bortoli N, Marchi S et al. Chronic Constipation: Is a Nutritional Approach Reasonable? Nutrients 2021, 13(10). Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6754983","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":496684277,"identity":"d923dbc9-5baa-4b6c-bfa9-e49bef2b9836","order_by":0,"name":"Cuili Lin","email":"","orcid":"","institution":"The Second Affiliated Hospital of Fujian University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Cuili","middleName":"","lastName":"Lin","suffix":""},{"id":496684278,"identity":"b1d175df-c686-41a1-89c3-b35f935af784","order_by":1,"name":"Xiangying Lin","email":"","orcid":"","institution":"Fujian University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Xiangying","middleName":"","lastName":"Lin","suffix":""},{"id":496684280,"identity":"4cb6caaa-c4d5-45d3-ab0c-d0bbaa6e29ea","order_by":2,"name":"Kaiying He","email":"","orcid":"","institution":"The Affiliated People's Hospital of Fujian University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Kaiying","middleName":"","lastName":"He","suffix":""},{"id":496684281,"identity":"57ce9ec6-ebd9-4cb1-8a7e-f5639fe2da2a","order_by":3,"name":"Qihong Liu","email":"","orcid":"","institution":"The Second Affiliated Hospital of Fujian University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Qihong","middleName":"","lastName":"Liu","suffix":""},{"id":496684283,"identity":"800efea8-861b-43a3-aeb6-dbfd87359a2d","order_by":4,"name":"Wenyi Fang","email":"","orcid":"","institution":"The Second Affiliated Hospital of Fujian University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Wenyi","middleName":"","lastName":"Fang","suffix":""},{"id":496684287,"identity":"c572aa0d-de5f-4816-beeb-2df6480673f7","order_by":5,"name":"Xiaofeng Huang","email":"","orcid":"","institution":"The Second Affiliated Hospital of Fujian University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Xiaofeng","middleName":"","lastName":"Huang","suffix":""},{"id":496684289,"identity":"97a4f1a6-b4b7-4a40-b17c-940fefcffc30","order_by":6,"name":"Minghan Huang","email":"","orcid":"","institution":"The Second Affiliated Hospital of Fujian University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Minghan","middleName":"","lastName":"Huang","suffix":""},{"id":496684290,"identity":"d365c800-0da5-4b57-ad40-a5f7c81be7c5","order_by":7,"name":"Yan Ren","email":"","orcid":"","institution":"The Second Affiliated Hospital of Fujian University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Ren","suffix":""},{"id":496684292,"identity":"f606afe8-6f76-4561-b1e8-7b7ec055fae2","order_by":8,"name":"Xiao Ke","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAqUlEQVRIiWNgGAWjYDCCA2wMjA0MNjz8/A2kaUmTkZxxgDQth20MGhKI1MF3+1ia5My28zwGDAcYP3zMIUKL5Lm0w4YbztzmMWduYJacuY0ILQZn2BsfPqi4zWPZcICNmZdILQ0HHxic4zE4kEC0FraDDzdUHCBBi+QZtmTDGWeSeSRnHGwmzi98Z9jMJHvb7Oz5+ZsPfvhIjBYkAIyeUTAKRsEoGAVUAgD2hDi8YkvPIgAAAABJRU5ErkJggg==","orcid":"","institution":"University of Traditional Chinese Medicine","correspondingAuthor":true,"prefix":"","firstName":"Xiao","middleName":"","lastName":"Ke","suffix":""}],"badges":[],"createdAt":"2025-05-27 03:38:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6754983/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6754983/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88836487,"identity":"1825e56c-5ea6-43d6-9828-e7b7c8189e42","added_by":"auto","created_at":"2025-08-12 01:14:44","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":242723,"visible":true,"origin":"","legend":"\u003cp\u003eA total of 31034 individuals completed the NHANES interviews, among whom 17132 participants were aged 20 years or older. We excluded pregnant women (n = 463), individuals with missing aMED score data (n = 3282), those lacking information on constipation (n = 997), and participants with missing covariate data (n = 993). Ultimately 11397 eligible participants from the 2005–2010 NHANES cycles were included in this cross-sectional analysis.\u003c/p\u003e","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6754983/v1/6827548f85fb7404c281dd69.png"},{"id":88836485,"identity":"7843a5be-8191-4141-920d-d3de1c297caf","added_by":"auto","created_at":"2025-08-12 01:14:44","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":112218,"visible":true,"origin":"","legend":"\u003cp\u003eThe restricted cubic splines (RCS) analysis showed a linear relationship between aMED score and constipation (linear trend, \u003cem\u003eP = 0.101\u003c/em\u003e).\u003c/p\u003e","description":"","filename":"Figure22.png","url":"https://assets-eu.researchsquare.com/files/rs-6754983/v1/df3b35a94d1cd72dd4ba597f.png"},{"id":88837164,"identity":"a638630a-a848-4390-9114-056eba97f2d5","added_by":"auto","created_at":"2025-08-12 01:22:45","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":322553,"visible":true,"origin":"","legend":"\u003cp\u003eTo explore the potential modifying effects of individual characteristics on the association between aMED scores and constipation stratified analyses were performed based on predefined variables. These included sex, BMI, diabetes, hypertension, depression, and cardiovascular disease. The association between aMED and constipation remained consistent across all subgroups and no significant interactions were observed.\u003c/p\u003e","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6754983/v1/a49743e2bc7b5065ba48cb2b.png"},{"id":91406699,"identity":"d3d8149e-9e63-4f16-a6c8-34185ea4c1f2","added_by":"auto","created_at":"2025-09-16 08:02:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1340186,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6754983/v1/c9a86594-921b-43d4-88c6-e661121f771b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Association Between the Alternate Mediterranean Diet Index and Constipation: Evidence from the 2005-2010 NHANES","fulltext":[{"header":"Background","content":"\u003cp\u003eConstipation is a prevalent functional gastrointestinal disorder, typically defined by infrequent bowel movements, hard stool consistency and straining during defecation, often accompanied by abdominal bloating and other discomforts[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The global prevalence of constipation is estimated at approximately 15%[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], with higher rates observed among women and older adults. Its aetiology is multifactorial, primarily influenced by dietary and lifestyle factors. Insufficient intake of dietary fibre, fluids vitamins B and E, β-carotene and niacin along with excessive consumption of caffeine has been associated with increased constipation risk[\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Moreover unhealthy behaviours such as smoking excessive alcohol use, physical inactivity and poor sleep quality have been identified as significant contributors[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].Chronic constipation is not only linked to an elevated risk of cardiovascular and cerebrovascular events[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], but also to psychological disturbances including anxiety and depression. These mental health conditions may exacerbate constipation via neuroendocrine dysregulation perpetuating a vicious cycle of gastrointestinal dysfunction[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].From a healthcare perspective constipation poses a substantial economic burden with annual treatment costs in the United States alone exceeding \u003cspan\u003e$\u003c/span\u003e230\u0026nbsp;million. Importantly dietary modification remains a cornerstone of constipation management. As a first-line non-pharmacological intervention nutritional strategies are widely recommended to improve bowel function and reduce the likelihood of symptom recurrence.\u003c/p\u003e\u003cp\u003eIn recent years, the focus of nutritional research has shifted from examining individual foods or nutrients to adopting more comprehensive approaches that emphasize overall dietary patterns. This paradigm better captures the complexity of real-world eating behaviours and offers a more accurate assessment of disease risk[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].The Alternate Mediterranean Diet Score (aMED) is a widely used index to evaluate healthy dietary patterns. The aMED developed by researchers at Harvard University modifies the traditional Mediterranean Diet to suit non-Mediterranean populations. Key adaptations include replacing \"total grain intake\" with \"whole grains \", substituting \"olive oil\" with the monounsaturated-to-saturated fat ratio (MUFA/SFA) excluding dairy products, redefining \"wine with meals\" as \"moderate alcohol intake \" and eliminating geographic food constraints.The aMED is characterised by high consumption of fruits, vegetables, legumes, nuts, whole grains and fish; moderate alcohol intake; a favourable ratio of monounsaturated to saturated fats; and low intake of red and processed meats. Numerous studies have demonstrated associations between higher aMED scores and a reduced risk of several chronic diseases: including cardiovascular disease[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], obesity[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], type 2 diabetes and diabetic nephropathy[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], Parkinson\u0026rsquo;s disease[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], depression[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] and gastric adenocarcinoma[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].Evidence also suggests that a diet rich in fibre, water and micronutrients such as vitamins B, E and β-carotene may reduce the risk of constipation. Given that the aMED diet is abundant in these components it may play a beneficial role in constipation prevention. However, the potential association between aMED and constipation has not yet been systematically investigated. Therefore, we conducted a cross-sectional study using data from the National Health and Nutrition Examination Survey (NHANES) to examine this relationship. We also accounted for multiple potential confounders including age, sex, household income, marital status, education level, smoking, and alcohol consumption. Our findings aim to enhance the understanding of the link between aMED and constipation and provide a basis for more effective dietary interventions in the management of chronic constipation.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design\u003c/h2\u003e\u003cp\u003eThis was a cross-sectional observational study based on a secondary analysis of data from the 2005\u0026ndash;2010 cycles of the NHANES. The NHANES program aims to assess the health and nutritional status of non-institutionalized U.S. residents using a stratified multistage probability sampling design. Data collection includes in-home interviews screening and laboratory tests conducted in mobile examination centers (MECs) providing comprehensive demographic and health-related information. NHANES is approved by the Ethics Review Board of the National Center for Health Statistics (NCHS) and all participants provided written informed consent prior to participation. As this study involved secondary analysis of publicly available data no additional institutional review board (IRB) approval was required. Data were obtained from the NHANES website (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.cdc.gov/nchs/nhanes.htm\u003c/span\u003e\u003cspan address=\"http://www.cdc.gov/nchs/nhanes.htm\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e; accessed March 1, 2022.We utilized data from the 2005\u0026ndash;2010 NHANES cycles as they are the only cycles that include information on bowel habits and dietary intake. Participants were adults aged 20 years or older who had completed the interviews. We excluded pregnant individuals and those with missing data on aMED score, constipation status or key covariates.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eAlternative Mediterranean Diet Score\u003c/h3\u003e\n\u003cp\u003eIn this study, we employed the alternative Mediterranean diet (aMED) score, a revised version of the traditional Mediterranean Diet (MED) index tailored for non-Mediterranean populations. Developed by the U.S. Food and Health Association, the aMED score encompasses nine dietary components: vegetables, fruits, legumes, nuts, whole grains, fish, the ratio of monounsaturated to saturated fats (MUFA/SFA), red and processed meats, and alcohol intake. The total score ranges from 0 to 9, based on individuals\u0026rsquo; dietary intake patterns. Higher scores reflect greater adherence to a Mediterranean-style diet, which is characterized by higher consumption of beneficial food groups, a higher MUFA/SFA ratio, moderate alcohol consumption, and lower intake of red and processed meats[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Each component is assigned a score of 1 or 0 depending on whether the individual's intake is above the sex-specific median and whether higher (or lower) consumption is considered health-promoting. Dietary intake for each component over the preceding two days was assessed, and the aMED score was calculated using the \u0026ldquo;Dietaryindex\u0026rdquo; package in R.\u003c/p\u003e\u003cp\u003eIn our analysis, the aMED scores ranged from 3 to 9. Based on the distribution, participants were classified into four quartiles: Q1 (3\u0026thinsp;\u0026le;\u0026thinsp;aMED\u0026thinsp;\u0026lt;\u0026thinsp;5), Q2 (5\u0026thinsp;\u0026le;\u0026thinsp;aMED\u0026thinsp;\u0026lt;\u0026thinsp;5.5), Q3 (5.5\u0026thinsp;\u0026le;\u0026thinsp;aMED\u0026thinsp;\u0026lt;\u0026thinsp;6.5), and Q4 (6.5\u0026thinsp;\u0026le;\u0026thinsp;aMED\u0026thinsp;\u0026le;\u0026thinsp;9). This quartile-based categorization allowed for a more detailed investigation into the relationship between dietary quality and constipation.Overall, the aMED scoring system and quartile classification provided a structured and robust framework to examine the association between dietary patterns and bowel health.\u003c/p\u003e\n\u003ch3\u003eDefinition of Constipation\u003c/h3\u003e\n\u003cp\u003eIn previous NHANES cycles stool form has been regarded as a valid indicator for assessing constipation. Between 2005 and 2010 participants were asked about their bowel function during in-person interviews conducted at mobile examination centers. One of the questions was based on the Bristol Stool Form Scale (BSFS) a validated tool used to classify stool consistency and shape. Interviewers presented participants with a visual aid card depicting seven types of stools ranging from \u0026ldquo;separate hard lumps, like nuts\u0026rdquo; to \u0026ldquo;watery, no solid pieces.\u0026rdquo; Participants were asked to identify the stool type that best described their usual bowel movements. In this analysis constipation was defined as reporting a usual stool type corresponding to Type 1 (separate hard lumps, like nuts) or Type 2 (sausage-shaped, but lumpy) on the BSFS[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. This definition is consistent with prior NHANES-based studies and is recognized for its reliability and clinical relevance.\u003c/p\u003e\n\u003ch3\u003eCovariates\u003c/h3\u003e\n\u003cp\u003eIn accordance with previous literature[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] a comprehensive set of potential covariates was assessed including age, sex, marital status, race/ethnicity, educational, attainment household income, smoking status, alcohol consumption, physical activity time, body mass index (BMI), total energy intake, protein, carbohydrate, fat, dietary fiber, water intake, hypertension, diabetes, cardiovascular disease (CVD) and depression. Race/ethnicity was categorized as non-Hispanic White, non-Hispanic Black, Mexican American or other races. Marital status was grouped into married, cohabiting, and living alone. Education was divided into \u0026lt;\u0026thinsp;9 years, 9\u0026ndash;12 years and \u0026gt;\u0026thinsp;12 years. Based on a report by the U.S. government [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], family income was classified using the poverty income ratio (PIR): low (PIR\u0026thinsp;\u0026le;\u0026thinsp;1.3), medium (1.3\u0026thinsp;\u0026lt;\u0026thinsp;PIR\u0026thinsp;\u0026le;\u0026thinsp;3.5), and high (PIR\u0026thinsp;\u0026gt;\u0026thinsp;3.5).Smoking status was defined as never smokers (\u0026lt;\u0026thinsp;100 cigarettes), current smokers or former smokers (\u0026ge;\u0026thinsp;100 cigarettes in the past but currently not smoking). Alcohol consumption was classified as never drinkers (had\u0026thinsp;\u0026lt;\u0026thinsp;12 drinks in their lifetime), current drinkers or former drinkers (had\u0026thinsp;\u0026ge;\u0026thinsp;12 drinks in one year but did not drink in the past year, or \u0026ge;\u0026thinsp;12 lifetime drinks but no alcohol consumption in the past year).Prevalent diseases including hypertension, diabetes and CVD were identified based on self-reported physician diagnosis. Depression status was determined using the Patient Health Questionnaire-9 (PHQ-9) with scores of 0\u0026ndash;4 indicating no depression and scores\u0026thinsp;\u0026ge;\u0026thinsp;5 indicating presence of depressive symptoms.BMI was calculated as weight divided by height squared (kg/m\u0026sup2;) and classified as \u0026le;\u0026thinsp;25 or \u0026gt;\u0026thinsp;25 kg/m\u0026sup2;. Dietary intake variables including total energy, protein, carbohydrate, fat, fiber and water were obtained through 48-hour dietary recall interviews conducted prior to the MEC examination. The use of dietary supplements was determined based on responses to questions regarding supplement and medication use in the past month.\u003c/p\u003e\n\u003ch3\u003eStatistical Methods\u003c/h3\u003e\n\u003cp\u003eThis study is a secondary analysis based on publicly available datasets. Categorical variables were summarized as frequencies and percentages, while continuous variables were described using means (SE) or medians and interquartile ranges (IQR) depending on their distribution. Appropriate statistical tests were applied based on variable characteristics: one-way analysis of variance (ANOVA) for normally distributed continuous variable, Kruskal-Wallis tests for skewed data and chi-square tests for categorical variables. To examine the association between the alternative Mediterranean diet (aMED) score and constipation, multivariable logistic regression models were employed to estimate odds ratios (ORs) and 95% confidence intervals (CIs). Three models were constructed with progressive levels of covariate adjustment:Model 1 adjusted for sociodemographic factors including age, sex, race/ethnicity, marital status, educational level, and household income;Model 2 further included lifestyle and dietary factors such as smoking status, alcohol consumption, physical activity, BMI, total energy intake, protein, carbohydrates, fats, dietary fiber and water intake;Model 3 incorporated additional adjustment for chronic diseases including diabetes, hypertension, depression and cardiovascular disease.\u003c/p\u003e\u003cp\u003eTo explore potential dose\u0026ndash;response relationships, a restricted cubic spline (RCS) regression with four knots placed at the 5th, 35th, 65th and 95th percentiles of the aMED score distribution was performed. The curve was fitted based on covariates included in Model 3 to assess linearity.\u003c/p\u003e\u003cp\u003eSubgroup analyses were conducted to investigate effect modification by sex, BMI, diabetes, hypertension, cardiovascular disease and depression. Heterogeneity across subgroups was assessed using multivariable logistic regression and interactions were tested using likelihood ratio tests.\u003c/p\u003e\u003cp\u003eMissing data for covariates were handled using multivariable single imputation with Bayesian ridge regression as the estimator, implemented iteratively. Robustness was assessed by comparing pre- and post-imputation datasets and performing sensitivity analyses using K-nearest neighbors imputation.\u003c/p\u003e\u003cp\u003eSensitivity analysis was conducted using multiple imputation to address missing covariate data and evaluate the robustness of the findings.\u003c/p\u003e\u003cp\u003eAs this study utilized existing data, no a priori sample size calculation was performed. All analyses were conducted using R software version 4.2.2 and Free Statistics Software Version 2.1.1, and A two-tailed p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003eStudy Population\u003c/h2\u003e\u003cp\u003eA total of 31034 individuals completed the NHANES interviews, among whom 17132 participants were aged 20 years or older. We excluded pregnant women (n\u0026thinsp;=\u0026thinsp;463), individuals with missing aMED score data (n\u0026thinsp;=\u0026thinsp;3282), those lacking information on constipation (n\u0026thinsp;=\u0026thinsp;997), and participants with missing covariate data (n\u0026thinsp;=\u0026thinsp;993). Ultimately 11397 eligible participants from the 2005\u0026ndash;2010 NHANES cycles were included in this cross-sectional analysis. The detailed inclusion and exclusion process is illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eBaseline Characteristics of the Study Population\u003c/h3\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the baseline characteristics of all participants categorized by aMED score quartiles. A total of 846 individuals (7.4%) reported having constipation. The average age of the participants was 47.36 years (standard deviation 0.36) with 5752 participants (51.61%) being female. Individuals with higher aMED scores tended to be older female, married or cohabiting non-Hispanic White, non-smokers, previous alcohol consumers, more highly educated, with higher household income and less physically active. Additionally these individuals had lower rates of diabetes, hypertension, depression, cardiovascular disease and constipation as well as lower calorie protein and fat intake, and higher intake of carbohydrate, dietary fiber and water intake.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePopulation characteristics by categories of Alternative Mediterranean Diet Index.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCharacteristic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e\u003cp\u003eAlternative Mediterranean Diet Index\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003etotal\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eQ1\u003c/p\u003e\u003cp\u003e(3\u0026thinsp;\u0026le;\u0026thinsp;aMED\u0026thinsp;\u0026lt;\u0026thinsp;5)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eQ2\u003c/p\u003e\u003cp\u003e(5\u0026thinsp;\u0026le;\u0026thinsp;aMED\u0026thinsp;\u0026lt;\u0026thinsp;5.5)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eQ3\u003c/p\u003e\u003cp\u003e(5.5\u0026thinsp;\u0026le;\u0026thinsp;aMED\u0026thinsp;\u0026lt;\u0026thinsp;6.5)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eQ4\u003c/p\u003e\u003cp\u003e(6.5\u0026thinsp;\u0026le;\u0026thinsp;aMED\u0026thinsp;\u0026le;\u0026thinsp;9)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNO.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11397\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1932\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1735\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4264\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3466\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge, y, Mean (SE)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47.51 (0.36)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e42.70 (0.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e44.61 (0.55)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e46.93 (0.48)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e52.03 (0.64)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5645 (47.98)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1089 (55.72 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e911 (51.48 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2115 (48.64 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1530 (41.58 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5752 (52.02 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e843 (44.28 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e824 (48.52 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2149 (51.36 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1936 (58.42 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRace/ethnicity, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNon-Hispanic white\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5951 (73.86 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1034 (73.30 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e810 (68.33 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2172 (72.90 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1935 (77.83 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNon-Hispanic black\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2224 (10.30 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e441 (13.32 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e392 (13.02 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e809 (10.04 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e582 (7.80 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMexican American\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1916 (7.17 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e241 (5.31 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e319 (8.95 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e808 (8.09 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e548 (6.22 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOthers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1306 (8.67 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e216 (8.07 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e214 (9.70 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e475 (8.97 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e401 (8.15 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarital status, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarried or living with a partner\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7079 (64.76 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1130 (60.30 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1034 (63.54 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2679 (64.27 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2236 (68.22 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLiving alone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4318 (35.24 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e802 (39.70 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e701 (36.46 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1585 (35.73 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1230 (31.78 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducation level, y, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1199 (5.07 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e216 (6.18 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e222 (6.39 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e482 (5.54 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e279 (3.32 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9\u0026ndash;12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4513 (36.04 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e958 (47.69 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e806 (43.98 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1661 (35.59 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1088 (26.89 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5685 (58.89 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e758 (46.13 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e707 (49.63 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2121 (58.86 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2099 (69.79 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFamily income, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3261 (18.96 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e753 (26.78 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e609 (24.19 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1219 (19.03 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e680 (12.41 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMedium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4402 (35.61 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e742 (37.14 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e680 (37.63 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1661 (35.96 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1319 (33.46 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3734 (45.43 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e437 (36.08 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e446 (38.18 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1384 (45.01 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1467 (54.12 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBody mass index, kg/m2, Mean (SE)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28.75 (0.13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29.65 (0.26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e29.40 (0.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e28.95 (0.18)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e27.75 (0.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhysical activity time, min, Mean (SE)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e180.00 (23.62 719.35)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e204.28 (0.00 959.57)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e180.00 (13.32 840.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e175.00 (18.97 624.15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e203.98 (31.50 600.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.013\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoking status, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNever\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5958 (52.79 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e797 (40.58 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e824 (47.43 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2307 (54.10 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2030 (60.03 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCurrent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3002 (25.49 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e402 (20.62 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e408 (23.56 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1124 (25.05 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1068 (29.42 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFormer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2437 (21.72 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e733 (38.79 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e503 (29.01 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e833 (20.85 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e368 (10.55 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAlcoholing status, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNever\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1444 (10.45 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e201 (7.23 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e220 (10.69 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e552 (10.77 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e471 (11.62 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCurrent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2323 (16.76 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e442 (19.90 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e401 (19.06 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e872 (16.51 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e608 (14.37 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFormer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7630 (72.79 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1289 (72.86 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1114 (70.25 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2840 (72.72 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2387 (74.01 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCalorie consumption, kcal/d, Mean (SE)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2158.34 (17.26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2267.73 (33.33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2221.95 (37.78)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2146.40 (24.20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2086.61 (27.86)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.005\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProtein consumption, g/d, Mean (SE)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e83.79 (0.80)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e88.02 (1.58)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e87.25 (1.91)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e83.45 (0.98)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e80.41 (1.19)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.007\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCarbohydrate consumption, g/d, Mean (SE)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e259.06 (1.98)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e261.18 (3.96)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e258.80 (4.71)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e255.28 (3.39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e262.59 (2.82)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.029\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFat consumption, g/d, Mean (SE)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e82.10 (0.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e88.39 (1.75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e85.79 (1.83)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e82.70 (1.07)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e76.42 (1.43)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDietary fiber taken, g/d, Mean (SE)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16.43 (0.24)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11.59 (0.31)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13.57 (0.33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e15.87 (0.22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e20.93 (0.36)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMoisture taken, g/d, Mean (SE)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3086.15 (30.55)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3026.09 (65.26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3039.27 (47.32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3070.62 (37.56)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3157.30 (42.56)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiabetes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.28\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9380 (87.32 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1622 (88.30 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1444 (87.36 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3458 (86.45 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2856 (87.83 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2017 (12.68 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e310 (11.70 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e291 (12.64 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e806 (13.55 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e610 (12.17 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.036\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6534 (62.59 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1196 (66.69 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1016 (62.39 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2426 (61.74 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1896 (61.57 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4863 (37.41 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e736 (33.31 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e719 (37.61 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1838 (38.26 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1570 (38.43 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003edepression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8006 (71.39 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1223 (63.59 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1160 (68.08 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3002 (71.42 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2621 (76.94 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3391 (28.61 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e709 (36.41 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e575 (31.92 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1262 (28.58 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e845 (23.06 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCVD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.57\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10089 (91.51 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1709 (91.38 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1552 (92.37 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3794 (91.69 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3034 (90.98 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1308 (8.49 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e223 (8.62 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e183 (7.63 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e470 (8.31 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e432 (9.02 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003econstipation\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10551 (93.12 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1751 (89.49 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1606 (93.47 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3936 (93.04 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3258 (94.93 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e846 (6.88 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e181 (10.51 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e129 (6.53 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e328 (6.96 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e208 (5.07 )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eAssociation Between aMED Score and Constipation\u003c/h2\u003e\u003cp\u003eAfter adjusting for potential confounders, quartile analysis revealed a clear inverse relationship between adherence to the aMED dietary pattern and the risk of constipation.Compared with individuals with lower aMED scores (3\u0026thinsp;\u0026le;\u0026thinsp;aMED\u0026thinsp;\u0026lt;\u0026thinsp;5), the adjusted odds ratios (OR) for constipation in the Q2 (5\u0026thinsp;\u0026le;\u0026thinsp;aMED\u0026thinsp;\u0026lt;\u0026thinsp;5.5), Q3 (5.5\u0026thinsp;\u0026le;\u0026thinsp;aMED\u0026thinsp;\u0026lt;\u0026thinsp;6.5) and Q4 (6.5\u0026thinsp;\u0026le;\u0026thinsp;aMED\u0026thinsp;\u0026le;\u0026thinsp;9) groups were 0.57 (95% CI: 0.41\u0026ndash;0.78, \u003cem\u003eP\u0026thinsp;=\u0026thinsp;0.002\u003c/em\u003e), 0.64 (95% CI: 0.48\u0026ndash;0.84, \u003cem\u003eP\u0026thinsp;=\u0026thinsp;0.003\u003c/em\u003e) ,and 0.46 (95% CI: 0.33\u0026ndash;0.65, \u003cem\u003eP\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/em\u003e), respectively (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). This suggests that aMED scores between 6.5 and 9 are associated with a 54% reduction in the risk of constipation.Additionally, the restricted cubic splines (RCS) analysis showed a linear relationship between aMED score and constipation (linear trend, \u003cem\u003eP\u0026thinsp;=\u0026thinsp;0.101\u003c/em\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAssociation between Alternative Mediterranean Diet Index and constipation(the complete dataset).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"10\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eQuartiles\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"9\" nameend=\"c10\" namest=\"c2\"\u003e\u003cp\u003eOR(95% Cl)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo.\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCrude\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e-Value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eModel 1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e-Value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eModel 2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e-Value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eModel 3\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e-Value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAlternative Mediterranean Diet Index\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ1(3\u0026thinsp;\u0026le;\u0026thinsp;aMED\u0026thinsp;\u0026lt;\u0026thinsp;5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1932\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1(Ref)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1(Ref)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1(Ref)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1(Ref)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ2(5\u0026thinsp;\u0026le;\u0026thinsp;aMED\u0026thinsp;\u0026lt;\u0026thinsp;5.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1735\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.59(0.43\u0026ndash;0.83)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.57(0.42\u0026ndash;0.79)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.56(0.41\u0026ndash;0.77)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.57(0.41\u0026ndash;0.78)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ3(5.5\u0026thinsp;\u0026le;\u0026thinsp;aMED\u0026thinsp;\u0026lt;\u0026thinsp;6.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4264\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.64(0.50\u0026ndash;0.82)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.64(0.50\u0026ndash;0.82)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.63(0.48\u0026ndash;0.83)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.64(0.48\u0026ndash;0.84)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ4(6.5\u0026thinsp;\u0026le;\u0026thinsp;aMED\u0026thinsp;\u0026le;\u0026thinsp;9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3466\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.45(0.33\u0026ndash;0.62)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.47(0.34\u0026ndash;0.65)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.45(0.30\u0026ndash;0.63)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.46(0.33\u0026ndash;0.65)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTrend test\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e11397\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"10\"\u003eQ, quartiles; OR, odds ratio; CI, confidence interval; Ref: reference.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"10\"\u003eModel 1 was adjusted for sociodemographic variables (age, sex, marital status, race/ethnicity, education level, family income).\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"10\"\u003eModel 2 was adjusted for sociodemographic (age, sex, marital status, race/ethnicity, education level, family income), smoking status, Alcoholing status,physical activity time, body mass index,Calorie consumption,Protein consumption,Carbohydrate consumption,Fat consumption,Dietary fiber taken ,and Moisture taken.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"10\"\u003eModel 3 sociodemographic (age, sex, marital status, race/ethnicity, education level, family income), smoking status, Alcoholing status,physical activity time, body mass index,Calorie consumption,Protein consumption,Carbohydrate consumption,Fat consumption,Dietary fiber taken ,and Moisture taken,diabetes,hypertension,,depression,and Cardiovascular Disease.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eSubgroup Analyses\u003c/h2\u003e\u003cp\u003eTo explore the potential modifying effects of individual characteristics on the association between\u003c/p\u003e\u003cp\u003eaMED scores and constipation stratified analyses were performed based on predefined variables. These\u003c/p\u003e\u003cp\u003eincluded sex, BMI, diabetes, hypertension, depression, and cardiovascular disease. The association between\u003c/p\u003e\u003cp\u003eaMED and constipation remained consistent across all subgroups and no significant interactions were\u003c/p\u003e\u003cp\u003eobserved.(Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eSensitivity Analysis\u003c/h2\u003e\u003cp\u003eAfter multiple imputation of missing covariate data the total sample size increased to 12390\u003c/p\u003e\u003cp\u003eparticipants. The inverse association between aMED score and constipation remained robust. Compared\u003c/p\u003e\u003cp\u003ewith individuals in the lowest aMED quartile (3\u0026thinsp;\u0026le;\u0026thinsp;aMED\u0026thinsp;\u0026lt;\u0026thinsp;5), the adjusted odds ratios for constipation were\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e0.59 (95% CI: 0.43\u0026ndash;0.81, P\u0026thinsp;=\u0026thinsp;0.002) for Q2 (5\u0026thinsp;\u0026le;\u0026thinsp;aMED\u0026thinsp;\u0026lt;\u0026thinsp;5.5), 0.65(95% CI: 0.49\u0026ndash;0.85, P\u0026thinsp;=\u0026thinsp;0.004) for Q3\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e(5.5\u0026thinsp;\u0026le;\u0026thinsp;aMED\u0026thinsp;\u0026lt;\u0026thinsp;6.5) and 0.49 (95% CI: 0.35\u0026ndash;0.68, P\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.001) for Q4 (6.5\u0026thinsp;\u0026le;\u0026thinsp;aMED\u0026thinsp;\u0026le;\u0026thinsp;9) as presented in\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. These findings confirm the stability of the observed association after addressing missing data.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAssociation between Alternative Mediterranean Diet Index and constipation(multiple imputed dataset for covariate missing values).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"10\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eQuartiles\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"9\" nameend=\"c10\" namest=\"c2\"\u003e\u003cp\u003eOR(95% Cl)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo.\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCrude\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e-Value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eModel 1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e-Value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eModel 2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e-Value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eModel 3\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e-Value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAlternative Mediterranean Diet Index\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ1(3\u0026thinsp;\u0026le;\u0026thinsp;aMED\u0026thinsp;\u0026lt;\u0026thinsp;5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2057\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1(Ref)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1(Ref)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1(Ref)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1(Ref)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ2(5\u0026thinsp;\u0026le;\u0026thinsp;aMED\u0026thinsp;\u0026lt;\u0026thinsp;5.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1895\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.62(0.45\u0026ndash;0.87)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.59(0.43\u0026ndash;0.81)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.58(0.42\u0026ndash;0.80)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.59(0.43\u0026ndash;0.81)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ3(5.5\u0026thinsp;\u0026le;\u0026thinsp;aMED\u0026thinsp;\u0026lt;\u0026thinsp;6.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4643\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.66(0.52\u0026ndash;0.85)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.66(0.52\u0026ndash;0.84)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.64(0.49\u0026ndash;0.84)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.65(0.49\u0026ndash;0.85)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ4(6.5\u0026thinsp;\u0026le;\u0026thinsp;aMED\u0026thinsp;\u0026le;\u0026thinsp;9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3795\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.49(0.37\u0026ndash;0.66)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.49(0.36\u0026ndash;0.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.48(0.34\u0026ndash;0.66)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.49(0.35\u0026ndash;0.68)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTrend test\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e12390\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"10\"\u003eQ, quartiles; OR, odds ratio; CI, confidence interval; Ref: reference.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"10\"\u003eModel 1 was adjusted for sociodemographic variables (age, sex, marital status, race/ethnicity, education level, family income).\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"10\"\u003eModel 2 was adjusted for sociodemographic (age, sex, marital status, race/ethnicity, education level, family income), smoking status, Alcoholing status,physical activity time, body mass index,Calorie consumption,Protein consumption,Carbohydrate consumption,Fat consumption,Dietary fiber taken ,and Moisture taken.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"10\"\u003eModel 3 sociodemographic (age, sex, marital status, race/ethnicity, education level, family income), smoking status, Alcoholing status,physical activity time, body mass index,Calorie consumption,Protein consumption,Carbohydrate consumption,Fat consumption,Dietary fiber taken ,and Moisture taken,diabetes,hypertension,,depression,and Cardiovascular Disease.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis large cross-sectional study involving U.S. adults demonstrated a significant inverse linear relationship between the alternate Mediterranean Diet (aMED) score and the risk of constipation. Higher aMED scores were associated with a progressively lower likelihood of constipation. Stratified and sensitivity analyses confirmed the robustness of this association.\u003c/p\u003e\u003cp\u003eOur findings suggest that adherence to the aMED dietary pattern may be associated with a reduced risk of constipation. Individuals with higher aMED scores tend to consume more fruits, vegetables, nuts, legumes, whole grains, fish, and foods rich in unsaturated fatty acids, while consuming less red and processed meats, with moderate alcohol intake. Although direct evidence linking aMED with constipation remains scarce, numerous studies have investigated the effects of its individual components on bowel function.Greater consumption of vegetables, fruits, whole grains, legumes, fish, and unsaturated fats, alongside lower intake of red meat, processed foods, and saturated fats, has been consistently associated with a lower risk of constipation. For example, higher vegetable intake is linked to a reduced risk of constipation[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], with non-starchy vegetables such as tomatoes showing particularly strong protective effects[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Xu et al. found that increased fruit consumption was inversely associated with constipation prevalence[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], and specific fruits such as kiwifruit, mangoes, prunes, and figs have demonstrated beneficial effects[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].Whole grains, a common source of dietary fiber in Western diets, have also been shown to reduce constipation risk [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In a clinical study by Odes et al., patients who consumed a high-fiber cereal mixture derived from oats, corn, wheat, and soy for two weeks experienced improved bowel frequency and stool consistency, with reduced laxative use[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Similarly, Sander et al. reported lower legume intake in constipated individuals[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Liu et al.[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] demonstrated that adherence to the HEI-2015 dietary pattern, which emphasizes fruits, vegetables, legumes, whole grains, seafood, and plant-based protein sources rich in unsaturated fats, is associated with a lower prevalence of constipation[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].Fish intake specifically appears to be protective. In a cross-sectional study in older adults in Beijing, Yang et al. reported significantly lower constipation rates among those who consumed fish regularly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01) [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Conversely, Reichardt et al. found that saturated fat-rich Western diets may induce colonic neuronal death via TLR4 signaling activation, contributing to impaired motility and constipation[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].Higher DI-GM scores\u0026mdash;indicative of lower intake of red and processed meats, refined grains, and high-fat foods\u0026mdash;have also been linked to reduced constipation risk[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Conversely, adherence to a Western dietary pattern characterized by high consumption of red and processed meats, potatoes, poultry, and desserts is associated with persistent constipation symptoms[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].Collectively, these findings align with our results and support the potential benefits of aMED dietary adherence in reducing the risk of constipation.\u003c/p\u003e\u003cp\u003eHowever, the mechanisms by which the aMED diet reduces the risk of constipation remain to be fully elucidated. Emerging evidence suggests that the aMED dietary pattern may exert beneficial effects by increasing the intake of dietary fiber, sorbitol, polyphenols, unsaturated fats, water, and micronutrients, thereby modulating the gut microbiota, enhancing intestinal motility, and improving stool consistency and hydration.Firstly, the aMED diet encourages the consumption of fiber-rich foods such as fruits, vegetables, legumes, whole grains, and nuts, which contain various types of dietary fiber[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Moderately fermentable soluble fiber forms gels that retain water in stool, improving viscosity [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], while rapidly fermentable soluble fiber acts as a prebiotic, promoting the growth of beneficial bacteria and the production of short-chain fatty acids (SCFAs) and gases, increasing osmotic load and accelerating gut transit[\u003cspan additionalcitationids=\"CR36 CR37\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Insoluble fiber, such as coarse wheat bran, stimulates the intestinal mucosa and induces water and mucus secretion, softening stools and facilitating defecation [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].Secondly, fruits rich in sorbitol contribute to stool softening. Sorbitol is poorly absorbed in the small intestine, retains water osmotically, and is fermented in the colon to produce SCFAs, particularly butyrate, which enhances gut motility[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].Thirdly, polyphenols found in vegetables, grains, and wine may regulate the gut microbiome. High molecular weight polyphenols reach the colon, where they promote the growth of beneficial bacteria (e.g., Bifidobacterium, Lactobacillus) and inhibit pathogenic species, thereby improving intestinal function[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e].The intake of unsaturated fats, especially omega-3 fatty acids from nuts and fish, also contributes. These fats lubricate the bowel, regulate microbial diversity by reducing harmful species (e.g., Faecalibacterium) and increasing beneficial ones (e.g., Bacteroides, butyrate-producing bacteria), and modulate inflammation and SCFA production, thereby promoting gut motility [\u003cspan additionalcitationids=\"CR48 CR49\" citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e].Moreover, the aMED diet provides micronutrients such as magnesium and vitamin E through green leafy vegetables, legumes, whole grains, and nuts. Magnesium, poorly absorbed in the intestine, increases luminal osmolarity, promoting water retention and softer stools[\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e] [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Vitamin E has been inversely associated with constipation, potentially by counteracting oxidative stress and preserving intestinal barrier and neuromuscular function [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].Conversely, Western dietary patterns rich in red and processed meats, sugars, and fats may disrupt gut microbial balance, impair mucosal integrity, promote E. coli colonization, trigger inflammation, and affect GLP-1 signaling, contributing to constipation pathogenesis[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] .Collectively, aMED may alleviate constipation through both direct effects on stool consistency and indirect modulation of gut microbiota and their metabolites. Further prospective studies are warranted to validate its preventive and therapeutic potential.\u003c/p\u003e\u003cp\u003eNevertheless, several limitations should be considered. First, the data on constipation were only collected from the NHANES survey conducted between 2005 and 2010, which prevents further validation using data from other time periods. Second, despite conducting regression modeling, stratified analyses and sensitivity analyses residual confounding effects due to unmeasured or unknown factors cannot be completely ruled out. Third, the findings of this study are based on a survey of U.S. adults and whether these results can be generalized to other populations remains to be determined. Fourth, the food intake data for the aMED score were obtained through a 48-hour recall method, which may introduce recall bias and does not fully capture participants' long-term dietary patterns. Fifth, constipation in our study was diagnosed solely based on stool form scoring, without a more comprehensive clinical investigation of gastrointestinal diseases. Lastly, due to the cross-sectional nature of this study, causality between the aMED diet and constipation cannot be established. Longitudinal studies are needed in the future to confirm this relationship. In addition to the link between aMED and constipation, future research could also explore other potential factors influencing constipation, such as environmental exposures.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, this study demonstrates a linear negative correlation between the aMED score and the incidence of constipation among U.S. adults. Specifically, as the aMED score increases the risk of constipation decreases. These findings highlight the significant association between the aMED score and the occurrence of constipation providing a theoretical foundation for further research into the potential role of the aMED dietary pattern in the prevention and management of constipation.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003cp\u003e This study was exempt from ethics review and approval as it involved secondary data analysis which does not require additional ethics committee approval.The NHANES study was authorized by the National Center for Health Statistics (NCHS) Institutional Review Board and all participants provided written informed consent prior to participation.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003cp\u003eThe authors declare that this study was independently conducted without any commercial or financial relationships that could be interpreted as potential conflicts of interest.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis research was supported by the following grants:National Natural Science Foundation of China (No. 82274282, 82174365);Central Government's Special Fund for Local Science and Technology Development (No. 2023L3013);Fujian Provincial Natural Science Foundation General Project (No. 2021J01878).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization: Xiao Ke, Yan Ren, Minghan Huang, Xiaofeng Huang;Data curation: Cuili Lin, Xiangying Lin;Formal analysis: Cuili Lin, Kaiying He;Funding acquisition: Xiao Ke, Yan Ren;Methodology: Cuili Lin, Qihong Liu, Wenyi Fang;Writing\u0026mdash;original draft: Cuili Lin;Writing\u0026mdash;review \u0026amp; editing: Cuili Lin, Xiangying Lin, Kaiying He, Qihong Liu Wenyi Fang,Minghan Huang, Xiaofeng Huang,Yan Ren, Xiao Ke. All authors have read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e\u003cp\u003eWe sincerely thank Dr. Jie Liu from the Vascular and Endovascular Surgery Department at the PLA General Hospital for his contributions in statistical support research design consultation and valuable feedback on the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and analyzed during the current study are available online. The name and identifier of the data repository can be accessed at: http://www.cdc.gov/nchs/nhanes.htm (accessed on March 1 2022).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAlavi K, Thorsen AJ, Fang SH, Burgess PL, Trevisani G, Lightner AL, Feingold DL, Paquette IM. The American Society of Colon and Rectal Surgeons Clinical Practice Guidelines for the Evaluation and Management of Chronic Constipation. 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J Nutr Biochem. 2013;24(8):1415\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSejbuk M, Mirończuk-Chodakowska I, Karav S, Witkowska AM. Dietary Polyphenols, Food Processing and Gut Microbiome: Recent Findings on Bioavailability, Bioactivity, and Gut Microbiome Interplay. Antioxid (Basel) 2024, 13(10).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKris-Etherton PM, Harris WS, Appel LJ. Fish consumption, fish oil, omega-3 fatty acids, and cardiovascular disease. Circulation. 2002;106(21):2747\u0026ndash;57.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWatson H, Mitra S, Croden FC, Taylor M, Wood HM, Perry SL, Spencer JA, Quirke P, Toogood GJ, Lawton CL, et al. A randomised trial of the effect of omega-3 polyunsaturated fatty acid supplements on the human intestinal microbiota. Gut. 2018;67(11):1974\u0026ndash;83.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCostantini L, Molinari R, Farinon B, Merendino N. Impact of Omega-3 Fatty Acids on the Gut Microbiota. Int J Mol Sci 2017, 18(12).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFu Y, Wang Y, Gao H, Li D, Jiang R, Ge L, Tong C, Xu K. Associations among Dietary Omega-3 Polyunsaturated Fatty Acids, the Gut Microbiota, and Intestinal Immunity. Mediators Inflamm. 2021;2021:8879227.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGuerrera MP, Volpe SL, Mao JJ. Therapeutic uses of magnesium. Am Fam Physician. 2009;80(2):157\u0026ndash;62.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBellini M, Tonarelli S, Barracca F, Rettura F, Pancetti A, Ceccarelli L, Ricchiuti A, Costa F, de Bortoli N, Marchi S et al. Chronic Constipation: Is a Nutritional Approach Reasonable? \u003cem\u003eNutrients\u003c/em\u003e 2021, 13(10).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Constipation, alternate Mediterranean diet index, NHANES, cross-sectional study","lastPublishedDoi":"10.21203/rs.3.rs-6754983/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6754983/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e Diet plays a significant role in the develo1pment of constipation, and the alternate Mediterranean diet index (aMED) serves as an indicator of a healthy dietary pattern. However, the association between aMED and constipation has not been well studied in the general population. The aim of this study was to evaluate the relationship between the aMED and constipation. This study utilized cross-sectional data from individuals aged 20 and above who participated in the 2005\u0026ndash;2010 National Health and Nutrition Examination Survey (NHANES). Detailed information was collected regarding constipation, aMED scores and several key covariates.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e A total of 11397 participants were included in this study. Chronic constipation was defined using the Bristol Stool Form Scale (BSFS) as types 1 (separate hard lumps, like nuts) and 2 (sausage-like, but lumpy). aMED scores were obtained from 48-hour dietary recall questionnaires and categorized into quartiles. The relationship between aMED and constipation was assessed using weighted logistic regression and smoothed curve fitting, adjusting for potential confounders. Stratification by age, BMI, presence of hypertension diabetes, vascular disease and depression was also performed.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e The prevalence of chronic constipation in this cohort was 7.4%. The weighted logistic regression results showed that compared with individuals in the lowest aMED score category (Q1, 3\u0026thinsp;\u0026le;\u0026thinsp;aMED\u0026thinsp;\u0026lt;\u0026thinsp;5) those in the higher quartiles (Q2, 5\u0026thinsp;\u0026le;\u0026thinsp;aMED\u0026thinsp;\u0026lt;\u0026thinsp;5.5; Q3, 5.5\u0026thinsp;\u0026le;\u0026thinsp;aMED\u0026thinsp;\u0026lt;\u0026thinsp;6.5; Q4, 6.5\u0026thinsp;\u0026le;\u0026thinsp;aMED\u0026thinsp;\u0026le;\u0026thinsp;9) had adjusted ORs for constipation of 0.57 (95% CI: 0.41\u0026ndash;0.78, \u003cem\u003eP\u0026thinsp;=\u0026thinsp;0.002\u003c/em\u003e), 0.64 (95% CI: 0.48\u0026ndash;0.84, \u003cem\u003eP\u0026thinsp;=\u0026thinsp;0.003\u003c/em\u003e) and 0.46 (95% CI: 0.33\u0026ndash;0.65, \u003cem\u003eP\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/em\u003e), respectively. This indicates that as aMED scores increase the risk of constipation decreases. Individuals in the highest aMED category had a 54% lower risk of constipation compared to those in the lowest category. Further analysis using smoothed curve fitting confirmed a linear negative correlation between the aMED index and constipation.Stratified analyses were conducted based on sex, BMI, diabetes, hypertension, depression, and cardiovascular disease to evaluate potential modifications in the relationship between aMED scores and constipation. The findings demonstrated that the association persisted consistently across all subgroups, with no significant interaction effects detected.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e Our study found that higher adherence to the aMED dietary pattern was significantly associated with a reduced risk of constipation, suggesting that promoting adherence to this diet may serve as an effective strategy for relieving constipation.\u003c/p\u003e","manuscriptTitle":"The Association Between the Alternate Mediterranean Diet Index and Constipation: Evidence from the 2005-2010 NHANES","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-12 01:14:40","doi":"10.21203/rs.3.rs-6754983/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4dbe1335-a009-489f-89d4-0ae8bc5995ba","owner":[],"postedDate":"August 12th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-16T07:53:41+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-12 01:14:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6754983","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6754983","identity":"rs-6754983","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}