Whole grain and high fiber cereals and multimorbidity: A longitudinal study in 146,329 adults aged 45 years and over

Whole grain and high fiber cereals and multimorbidity: A longitudinal study in 146,329 adults aged 45 years and over | 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 Whole grain and high fiber cereals and multimorbidity: A longitudinal study in 146,329 adults aged 45 years and over Xiaoyue Xu, Ling Zeng, Yang Li, Margo Barr, Sara Grafenauer, Aletta E Schutte This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9182393/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 Purpose This study aimed to examine the associations between whole grain and high fiber cereal intake and the risks of heart disease, multimorbidity and complex multimorbidity over 15 years. Methods We retrospectively analysed data from the 45 and Up Study, spanning the period from 2005 to 2020, with 146,329 individuals aged ≥ 45 years followed two follow-up waves across a 15-year period. Whole grain and high fiber cereals and wholemeal bread intake were assessed using a short food frequency questionnaire, and its’ association with heart disease, multimorbidity, and complex multimorbidity were examined using Generalized Estimating Equation models. Results Females who consumed whole grain and high fibre cereals had a 12% lower relative risk (RR) of heart disease (RR = 0.88; 95% CI: 0.78; 0.99) and a 13% lower risk of complex multimorbidity (RR = 0.87; 95% CI: 0.77; 0.97) than non-consumers. Oat cereal consumption was consistently associated with higher disease risk, whereas muesli consumption with lower risk across all outcomes. Participants consuming more than 12 slices of wholemeal bread per week had 13%, 18%, and 17% lower risks of heart disease, multimorbidity, and complex multimorbidity, respectively, compared with those consuming fewer than five slices. Conclusion Whole grain and high fiber cereals were associated with lower risks of heart disease, multimorbidity and complex multimorbidity. Promoting their inclusion in healthy diets may help prevent heart disease and the development of multiple chronic conditions in midlife. whole grain high fiber cereals multimorbidity complex multimorbidity longitudinal study Figures Figure 1 Figure 2 Figure 3 Introduction Multimorbidity, commonly defined as the presence of at least two chronic diseases in the same individual, has become increasingly common and affects more than one-third of the global adult population [ 1 , 2 ]. Regionally, the prevalence in South America is 45.7%, followed by North America (43.1%), Europe (39.2%) and Asia (35%) [ 2 ]. In Australia, 38% of Australians were diagnosed with multimorbidity in 2022 [ 3 ]. The prevalence of complex multimorbidity, referred to as three or more chronic conditions affecting different body systems, was 17% among people aged 45 and over in Australia [ 4 ]. Multimorbidity is expanding on a global scale due to increased life expectancy, which often leads to reduced quality of life, higher hospital admissions, higher mortality risk and greater healthcare costs [ 4 – 12 ]. Diet is a key risk factor for the development of multimorbidity [ 6 , 7 , 13 ]. A growing body of epidemiological evidence has demonstrated that whole grains, which are often high in fiber, offers protective effects against several chronic diseases, including cardiovascular disease, cancer, obesity and diabetes [ 14 – 19 ]. These effects are attributed to the abundance of cereal fiber content, vitamins, minerals, lignans, and phytochemicals concentrated in the bran and germ of whole grains [ 14 , 19 ]. Collectively, these bioactive components of whole grains are known to lower inflammation, a key contributor to the pathogenesis of cardiovascular and metabolic diseases [ 16 , 20 , 21 ]. Much of this benefit is mediated by dietary fiber, which is metabolized by the colonic microbiota into short-chain fatty acids such as acetate, propionate, and butyrate [ 22 ]. Although whole grain and fiber-rich foods have been extensively studied in relation to single disease states, studies linking whole grains and fiber-rich foods with multimorbidity, particularly complex multimorbidity, remain scarce and inconclusive. One study of 1,020 participants in China reported that higher whole grain intake was associated with a lower risk of developing multimorbidity compared with diets high in refined grains such as rice and wheat [ 23 ]. In contrast, a cross-sectional study conducted in Brazil found that higher whole grain consumption was associated with a 64% increased risk of multimorbidity among men [ 24 ]. Previous studies have mostly employed cross-sectional designs that measure whole grain and fiber-rich foods consumption at a single time point, overlooking the dynamic nature of long-term dietary habits and their influence on the development of multimorbidity [ 6 ]. Longitudinal studies are therefore needed to clarify the cumulative effects of whole grain and high fiber cereal consumption on the development of multimorbidity and complex multimorbidity. Accordingly, this study examined the associations between whole grain and high fiber cereal intake and the risks of heart disease, multimorbidity and complex multimorbidity over 15 years. Methods Data sources This research used the established Central and Eastern Sydney Primary and Community Health Cohort/Linkage Resource (CES-P&CH) based on the Sax Institute’s 45 and Up Study [25]. The 45 and Up Study is a large-scale Australian cohort study including 267,357 men and women aged 45 and over across New South Wales (NSW), Australia. The baseline participants gave written informed consent and were surveyed between 2005 and 2009. The first follow-up survey data were collected between 2012 and 2015, and the second follow-up survey data was collected between 2018 and 2020. At these three time points, socioeconomic, health behaviour and health-related information were collected via a comprehensive questionnaire [26]. About 19% of those invited participated and participants included about 11% of the NSW population aged 45 years and over. Details of the 45 and Up Study, including sampling strategy and methods are described elsewhere [27]. Ethics Ethical approval was granted for this research by the XX Research Ethics Committee (Reference Number: XX) and from the XX Human Research Ethics Committee. Participant cohort We included 146,329 participants who had no self-reported heart disease, multimorbidity, or complex multimorbidity at baseline (2005–2009) and followed through two waves until 2020. Only participants who completed dietary questionnaires in follow-up waves were included in the analysis ( Figure 1 ). Whole grain and high fiber cereals and wholemeal bread In the 45 and Up Study questionnaire, dietary consumption was assessed using short food frequency questions, which have been described in our previous studies [28, 29]. Each of the questions on diet was previously validated in the Million Women Study [30]. Whole grain and high fiber cereals consumption was defined based on participants’ responses to a question about the types of breakfast cereals they usually ate. Participants who reported consuming bran cereals (e.g., All-Bran, Bran Flakes), biscuit cereals (e.g., Weet-Bix, Shredded Wheat), oat cereals (e.g., porridge), or muesli were classified as whole grain and high-fiber cereals consumers. Participants were also asked whether they consumed brown or wholemeal bread, and if so, how many slices or pieces they typically ate per week. Based on their responses, we identified wholemeal bread consumers and further categorised them into tertiles (low, medium, and high) according to the number of slices consumed weekly. Outcomes: heart disease, multimorbidity and complex multimorbidity Heart disease was defined based on self-reported responses of a diagnosis, indicated by a ‘yes’ response to the question, ‘Has a doctor ever told you that you have heart disease?’ or by reporting treatment for heart conditions in response to the question, ‘In the last month, have you been treated for a heart attack, angina, or other heart disease?’ Multimorbidity was defined as the presence of two or more chronic conditions out of a total of 12, including cancer, heart disease, diabetes, Parkinson’s disease, stroke, depression or anxiety, asthma, allergic rhinitis, hypertension, thrombosis, musculoskeletal conditions, and thyroid disorders. Complex multimorbidity was defined as the presence of three or more conditions affecting different body systems, selected from a total of 9 categories: cardiovascular, musculoskeletal, neurological, psychological, respiratory, skin, endocrine/metabolic, female genital, and male genital systems. The definitions of multimorbidity and complex multimorbidity were determined based on our previous publication and consultation with clinicians [31]. Definitions for each individual disease, along with the corresponding questionnaire items, are provided in Supplementary Table 1 . Covariates We included socio-demographic factors, health behavioural factors, and other food group consumption as covariates in the statistical analysis. Socio-demographic variables included age, marital status (married/partner, single/divorced/separated, and widowed), education (Low, Median, High). Socioeconomic levels were assessed by Socio-Economic Indexes For Areas (SEIFA), which is based on three tertiles (Low, Medium, High) of Index of Relative Socio-economic Advantage and Disadvantage [32]. Health behaviours included smoking, alcohol drinking and physical activity levels. Smoking was identified as never smoked, previous smoker, and current smoker, based on two questions: “Have you ever been a regular smoker?”, and “Are you a regular smoker now?”. The frequency of alcohol consumption was identified by a question of “about how many alcoholic drinks do you have each week?” Physical activity was measured using the Active Australia Survey, asking the total time spent on walking, and on moderate-intensity and vigorous-intensity physical activity in the previous week. Adequate physical activity was identified if people spent 150 minutes of moderate intensity physical activity, or 75 minutes of vigorous intensity physical activity per week [33]. Body Mass Index was also included and calculated based on the weight and height that was identified by the questions “about how much do you weight?” and “how tall are you without shoes?” Based on the Australian Guide to Healthy Eating [34] other food components were also included as covariates, namely 1) vegetables, 2) fruit, 3) lean meat and poultry, and 4) dairy or dairy alternatives [28]. The frequency of consuming these food groups was reported in the 45 and Up dietary questionnaire. The details have been described in our previous publications [28, 29]. Statistical analysis Number and percentage for categorical variables and mean (SD) for continuous variables were used to present baseline characteristics by whole grain and high-fiber cereals and wholemeal bread intake. Chi-squire and ANOVA were applied to present statistical differences between groups. The statistical differences in the trends of grain consumption and the prevalence of heart disease, multimorbidity, and complex multimorbidity were assessed using ANOVA. Generalized Estimating Equation (GEE) models were used to assess the longitudinal effects of consumption of whole grain and high-fiber cereals and wholemeal bread on disease outcomes. We presented results from GEE models in the forest plots as crude and adjusted models, with Relative Risk (RR) and 95% Confidence Interval (CI). The latter model was adjusted for socioeconomic factors (age, marital status, education, and socioeconomic level), health behaviours (smoking, alcohol drinking, physical activity levels), and consumption of other foods (vegetables, fruit dairy or alternatives, lean meat and poultry), given that these variables were commonly reported as related to heart disease. All analyses were stratified by sex and conducted in Stata/SE 17 (StataCorp, College Station, TX). Results A total of 146,329 participants without heart disease, multimorbidity, or complex multimorbidity at baseline, and with available dietary data, were included in the study and followed for up to 15 years. By the first follow-up, 7,417 participants had developed heart disease, 25,173 had developed multimorbidity, and 5,312 had developed complex multimorbidity. By the second follow-up, there are 8,002 had heart disease, 24,847 had multimorbidity, and 6,831 had complex multimorbidity (Fig. 1 ). The distribution of chronic conditions and body system morbidities is presented in Supplementary Table 2 . The prevalence of each chronic condition and body system morbidity increased across waves. Hypertension was the most common single condition (rising from 23.8% to 38.5%), followed by musculoskeletal conditions (from 2.9% to 21%) and cancer (from 6.5% to 19.9%). Among body system morbidities, cardiovascular diseases were the most prevalent (increasing from 25.9% to 46.4%), followed by musculoskeletal (from 2.9% to 21%) and respiratory conditions (from 8.8% to 15.9%). Baseline characteristics by whole grain high-fiber cereals and brown/wholemeal bread intake are presented in Table 1 . Females reported higher consumption of grain cereals compared to males, whereas males tended to consume more brown/wholemeal bread than females (p < 0.001). Participants who were married, had a medium level of education, or identified as Australian were more likely to consume both grain cereals and brown/wholemeal bread than those in other respective categories (p < 0.001). Non-smokers and those with adequate physical activity levels reported higher intake of whole grain high-fiber cereals and brown/wholemeal bread (p < 0.001). Table 1 Baseline characteristics by whole grain and high fiber cereals and wholemeal bread intake (N = 146,329) Whole grain and high fiber P value Number of brown/whole grain bread P value No Yes Low Median High Age (mean, SD) 59.6 (10.5) 60.3 (10.4) < 0.001 58.1 (9.5) 59.8 (10.2) 61.9 (10.6) < 0.001 Sex (N, %) Males 20,075 (49.8) 50,275 (47.4) < 0.001 21,351 (46.7) 19,812 (42.9) 24,526 (54.6) < 0.001 Females 20,265 (50.2) 55,712 (52.6) 24,338 (53.3) 26,409 (57.1) 20,365 (45.4) Marital status (N, %) Married/partner 30,539 (76.3) 83,655 (79.4) < 0.001 36,026 (79.4) 36,337 (79.1) 35,181 (78.8) < 0.001 Single/divorce/separated 7,100 (17.8) 15,317 (14.5) 7,254 (16.0) 6,917 (15.1) 6,531 (14.6) widowed 2,371 (5.93) 6,370 (6.05) 2,115 (4.7) 2,667 (5.8) 2,925 (6.6) Education (N, %) Low 13,332 (33.7) 31,035 (29.7) < 0.001 14,053 (31.2) 13,052 (28.6) 13,415 (30.3) < 0.001 Medium 17,003 (43.0) 45,111 (43.2) 19,400 (43.0) 19,565 (42.9) 19,522 (44.1) High 9,214 (23.3) 28,351 (27.1) 11,627 (25.8) 12,964 (28.4) 11,340 (25.6) SEIFA* (N, %) Low 15,159 (38.6) 34,325 (33.3) < 0.001 15,595 (35.1) 14,587 (32.5) 15,338 (35.1) < 0.001 Medium 12,803 (32.6) 34,609 (33.6) 14,838 (33.4) 14,839 (33.0) 14,829 (34.0 High 11,298 (28.8) 34,113 (33.1) 13,975 (31.5) 15,526 (34.5) 13,497 (30.9) Ethnicity (N, %) Australian 19,409 (47.2) 54,367 (51.3) < 0.001 22,609 (49.5) 22,938 (49.6) 23,104 (51.5) < 0.001 English 8,708 (21.6) 26,954 (25.4) 10,370 (22.7) 11,576 (25.0) 11,633 (25.9) Irish 2,030 (5.0) 5,602 (5.3) 2,337 (5.1) 2,443 (5.3) 2,347 (5.2) Others 10,533 (26.2) 19,064 (18.0) 10,373 (22.7) 9,264 (20.0) 7,807 (17.4) Smoke (N, %) No 34,613 (86.4) 99,445 (94.2) < 0.001 40,783 (89.7) 42,899 (93.2) 41,895 (93.8) < 0.001 Yes 5,460 (13.6) 6,094 (5.8) 4,682 (10.3) 3,130 (6.8) 2,784 (6.2) Physical activity** (N, %) Inadequate 10,162 (26.5) 19,990 (19.4) < 0.001 10,761 (24.4) 9,020 (20.1) 7,840 (18.0) < 0.001 Adequate 28,231 (73.5) 82,846 (80.6) 33,433 (75.6) 35,828 (79.9) 35,759 (82.0) Body Mass Index (mean, SD) 26.6 (4.8) 26.2 (4.4) < 0.001 26.4 (4.6) 26.3 (4.4) 26.3 (4.4) < 0.001 Vegetables (serves, mean, SD) 3.6 (2.9) 4.0 (2.8) < 0.001 3.6 (2.6) 3.9 (2.7) 4.0 (2.7) < 0.001 Protein (times, mean, SD) 5.8 (4.6) 6.5 (3.8) < 0.001 6.5 (3.8) 6.4 (3.7) 6.6 (3.7) < 0.001 Fruit (serves, mean, SD) 1.8 (1.5) 2.0 (1.4) < 0.001 3.6 (2.6) 3.9 (2.7) 4.0 (2.7) < 0.001 Dairy (N, %) No 1,632 (4.1) 2,492 (2.4) < 0.001 1,551 (3.4) 1,169 (2.5) 1,175 (2.6) < 0.001 Yes 38,708 (95.9) 103,495 (97.6) 44,138 (96.6) 45,052 (97.5) 43,716 (97.4) At baseline, 105,987 participants (72.4%) reported consuming whole grain and high fiber cereals, decreasing to 53.9% at the first follow-up and 59.6% at the second follow-up. Across all three waves, females consistently reported higher whole grain and high fiber cereals consumption than males. Wholemeal bread consumption declined over time, with an average intake of 10.2 slices per week at baseline, decreasing to 8.4 slices by the second follow-up; males reported higher consumption than females. During the follow-up period, more males developed heart disease, whereas females had higher rates of multimorbidity and complex multimorbidity ( Table 2 ). Table 2 Trends in whole grain and high fiber cereals intake and prevalence of disease outcomes over time Whole grain and high fiber cereals (N, %) Baseline (N = 146,329) First follow-up (N = 83,032) Second follow-up (N = 60,211) P value All 105,987 (72.4) 32,891 (53.9) 27,330 (59.6) < 0.001 Males 50,275 (71.5) 13,216 (45.9) 11,316 (51.5) < 0.001 Females 55,712 (73.3) 19,675 (61.0) 16,014 (67.0) < 0.001 Number of slides – wholemeal bread per week (mean/SD) All 10.2 (8.9) 9.0 (7.7) 8.4 (7.3) < 0.001 Males 11.4 (10.4) 10.5 (8.9) 9.9 (8.5) < 0.001 Females 9.0 (7.1) 7.6 (6.2) 7.2 (5.8) < 0.001 Heart disease (N, %) All - 7,417 (8.9) 8,002 (13.3) < 0.001 Males - 4,538 (11.7) 4,964 (17.6) < 0.001 Females - 2,879 (6.5) 3,038 (9.5) < 0.001 Multimorbidity (N, %) All - 25,173 (30.3) 24,847 (41.3) < 0.001 Males - 11,460 (29.5) 11,478 (40.6) < 0.001 Females - 13,713 (31.0) 13,369 (41.8) < 0.001 Complex multimorbidity (N, %) All - 5,312 (6.4) 6,831 (11.4) < 0.001 Males - 2,179 (5.6) 2,845 (10.1) < 0.001 Females - 3,142 (7.1) 3,986 (12.5) < 0.001 * Red indicates the significant association. * Red indicates the significant association. The relationship between long-term consumption of whole grain and high fiber cereals and disease outcomes are shown in Fig. 2 A. In the unadjusted model, those who consumed whole grain and high fiber cereals had lower risk of heart disease, multimorbidity and complex multimorbidity. After adjustment for covariates, females who consumed whole grain and high fibre cereals had a 12% lower relative risk of heart disease (RR = 0.88; 95% CI: 0.78; 0.99) and a 13% lower risk of complex multimorbidity (RR = 0.87; 95% CI: 0.77; 0.97) compared with those who did not consume grain cereals. In contrast, males who consumed whole grain and high fibre cereals had a 14% higher risk of complex multimorbidity (RR = 1.14; 95% CI: 1.01; 1.29). After adjusting for covariates of socio-demographic factors, health behavioural factors, and other food group consumption, participants who consumed more than 12 slices of wholemeal bread per week had a 13% lower risk of heart disease (RR = 0.87; 95% CI: 0.83; 0.92), a 18% lower risk of multimorbidity (RR = 0.82; 95% CI: 0.80; 0.85), and an 17% lower risk of complex multimorbidity (RR = 0.83; 95% CI: 0.78; 0.87), compared to those who consumed fewer than 5 slices per week. Sex-specific analyses further indicated that females who consumed more than 12 slices of wholemeal bread per week experienced greater risk reduction than males across all disease outcomes. For heart disease, the relative risk was 0.79 (95% CI: 0.72; 0.85) in females and 0.94 (0.88; 0.99) in males. For multimorbidity, the relative risk was 0.74 (0.71; 0.77) in females and 0.92 (0.88; 0.95) in males. For complex multimorbidity, it was 0.77 (0.71; 0.83) in females and 0.90 (0.82; 0.98) in males (Fig. 2 B). We further examined the associations between different types of whole grain and high-fibre cereals (bran cereals, biscuit cereals, oat cereals, and muesli) and disease outcomes (Fig. 3 ). Oat cereal and muesli consumption showed consistent associations with all disease outcomes (Figs. 3 C & 3 D). Oat cereal consumption associated with 16% higher risk for heart disease (RR = 1.16; 95% CI: 1.11; 1.22), 15% higher risk for multimorbidity (RR = 1.15; 95% CI: 1.11; 1.18) and 13% higher risk for complex multimorbidity (RR = 1.13; 95% CI: 1.07; 1.19). These associations were consistent in both males and females, with higher oat cereal intake linked to increased relative risks across all outcomes (Fig. 3 C). In the contrast, muesli consumption was associated with a lower risk of heart disease (RR = 0.88; 95% CI: 0.84; 0.93), multimorbidity (RR = 0.92; 95% CI: 0.89; 0.95), and complex multimorbidity (RR = 0.88; 95% CI: 0.84; 0.94). Consistent associations were observed in both sexes, with greater risk reductions observed in females than males across all disease outcomes (Fig. 3 D). Discussion To the best of our knowledge, this is the first investigation on the association between long-term consumption of whole grain and high fiber cereals and risk of developing multimorbidity and complex multimorbidity. Over 15 years, intake of whole grain and high fiber cereals and wholemeal bread declined. Females with sustained intake of whole grain and high fibre cereals experienced significantly lower risks of heart disease and complex multimorbidity, while associations were not consistent in males. Notably, cereal subtypes showed divergent associations, with oat cereals associated with higher risks and muesli and wholemeal bread demonstrating consistent protective effects. In this study, hypertension was the most common chronic condition, and cardiovascular disease the most prevalent morbidity among middle-aged and older adults, both showing a significant increase with age as expected. This is consistent with recent Global Burden of Disease analyses [ 35 ] indicating that cardiovascular disease remains the primary cause of death and hypertension was the leading risk factor of disease burden in older adults. The number of people who survive and live with cardiovascular disease continues to rise with global population aging [ 36 ]. Thus, it is important to implement effective, evidence-based dietary risk reduction strategies for blood pressure control and cardiovascular disease prevention across the life-course. The clear decline in the intake of whole grain and high fiber cereals and wholemeal bread across the 15 year follow-up may reflect the increased availability, affordability, and variety of refined grains on the market, making it easier for individuals to shift away from whole grain and high-fiber cereals consumption [ 37 ]. Additionally, aging-related factors such as reduced sensory appeal, difficulty chewing and swallowing and decreased appetite may influence food choices, such as grain products with harder textures [ 38 ]. Although we are not able to make a direct comparison with the Australian Dietary Guidelines due to the limitations of the questionnaire, whole grain and high fiber intake in the Australian population is generally much lower than recommended, suggesting that the benefits of these foods have not yet been widely realised [ 39 ]. Consistent with established evidence [ 14 , 15 , 17 ], higher consumption of wholemeal bread was associated with a lower risk of heart disease. Unlike previous studies that primarily assessed whole grain consumption at a single time point [ 14 , 15 ], the present study captured the dynamic nature of long-term dietary patterns, thereby strengthening the evidence linking sustained wholemeal bread consumption to a reduced risk of heart disease. This observed inverse association aligns with current national dietary guidelines [ 40 – 42 ], which consistently recommend increasing whole grain intake. The cardioprotective effects of wholemeal bread are largely attributed to its provision of dietary fiber and its beneficial modulation of the gut microbiota [ 22 ], as well as its content of antioxidants and minerals, which together contribute to lower low-density lipoprotein cholesterol levels, improved blood pressure regulation, and overall cardiovascular health [ 43 ]. In addition, we observed a reduced risk of multimorbidity and complex multimorbidity associated with higher wholemeal bread consumption, further supporting its broader benefits for overall health. Evidence examining the associations between whole grain and high fiber cereal consumption and multimorbidity, particularly complex multimorbidity, remains limited. Given population ageing and the rising prevalence of multimorbidity and complex multimorbidity among middle-aged and older adults [ 4 , 10 ], it is no longer sufficient to assess dietary exposures solely in relation to individual diseases. Our cohort, 41% of participants developed multimorbidity and 11% developed complex multimorbidity, highlighting the importance of investigating the role of diet in the prevention of multiple co-occurring chronic conditions for the middle-aged and older population. Among different types of cereal consumption, long-term muesli intake was associated with clear benefits for heart disease, multimorbidity, and complex multimorbidity. Similar to wholemeal bread, the cardioprotective effects of muesli may be partly explained by its high fiber content and its favorable modulation of the gut microbiota, leading to the production of cardioprotective metabolites [ 22 ]. Additional benefits may stem from the common inclusion of nuts and dried fruits, which supply a range of macro- and micronutrients known to support cardiovascular health [ 44 ]. Surprisingly, we observed positive association between oat cereal consumption and heart disease, multimorbidity and complex multimorbidity. This finding should be interpreted with caution, as oat cereals represent a heterogeneous group of products that vary widely in processing level, which can alter the molecular properties and viscosity of oat β-glucans - key determinants of their cardioprotective effects. Highly processed oat cereals may also contain added sugars or refined components that could further attenuate these benefits [ 45 , 46 ], However, because the dietary questionnaire did not differentiate between specific types of oat cereals, it is not possible to determine whether this association reflects product heterogeneity rather than a true adverse effect. In addition, reverse causation may contribute to this association, as oat cereals are often recommended to people with heart disease, leading higher-risk people to preferentially consume them. Further longitudinal studies with more detailed dietary assessment are needed to clarify the health impacts of different forms of oat cereal consumption. Our study identified clear sex-specific differences in whole grain and high fiber cereal consumption and associated disease outcomes. Females reported higher long-term consumption of whole grain and high fiber cereals, whereas males tended to consume more wholemeal bread. Notably, females appeared to experience greater risk reductions for heart disease and complex multimorbidity associated with higher intake of whole grain and high fiber cereals, as well as with high consumption of wholemeal bread, compared with males. The mechanisms underlying these associations are not yet fully understood. However, our findings were consistent with previous epidemiological evidence indicating that dietary behaviours and food preferences differ by sex. For example, an Italian population-based study examining gender differences in food preferences reported that females were more inclined to consume whole grains than males [ 47 ]. This may reflect sex differences in taste preferences, health awareness, and health-related behaviours that influence food choices. Our findings emphasise the importance of considering sex-specific dietary patterns when developing targeted dietary interventions for disease prevention and dietary guidelines. The strengths of our study are that it involved large sample size and followed over 15 years that allow us to understand long-term associations of whole grain and high fibre cereal consumption and health outcomes by different sexes. More importantly, we provide new evidence, previously lacking in the literature, demonstrating the association between long-term whole grain and high fibre consumption and the risk of multimorbidity and complex multimorbidity, conditions that are highly prevalent among middle-aged and older adults. The generalizability needs to be noted in that the 45 and Up Study sample skews toward higher income groups, as well as oversampling of people aged ≥ 80 years and residents of rural and remote areas [ 48 ]. The study has several limitations. First, it relied on self-reported data, which may introduce measurement bias and does not allow assessment of the quality of whole grain consumption. The questionnaire provides a limited range of example foods and captured only the commonly consumed whole grain and high fiber cereals by participants, without collecting information on exact quantities and types (e.g., oat cereals), which limited a more detailed assessment of intake. In addition, although examples of whole grain and high fiber cereal were provided in the questionnaire, there remains the potential for misclassification if participants selected incorrect categories, which may have contributed to measurement bias. There was substantial loss to follow-up during the first and second follow-up waves, resulting in missing dietary and health information, which may have introduced selection bias and thereby influenced the observed associations. Nonetheless, such attrition is a common challenge in long-term longitudinal epidemiological studies. While the analysis adjusted for major food groups, some dietary confounders, such as consumption of fast or processed foods, may not have been fully accounted for. Finally, our results are clearly observational, and relationships do not necessarily reflect cause-and-effect. Conclusion Long-term dietary behaviour of whole grain and high fiber cereal intake associated with a lower risk of developing heart disease by 12%, and complex multimorbidity by 13% for females. Across different cereal types, oat cereal consumption was consistently associated with higher risk across all disease outcomes, whereas muesli consumption was consistently associated with lower risk across all disease outcomes. Long-term consumption of wholemeal bread was associated with a 13% lower risk of heart disease, an 18% lower risk of multimorbidity, and a 17% lower risk of complex multimorbidity. Our findings suggest that guidelines could more confidently promote the inclusion of whole grains and high fiber cereals, in particular muesli and wholemeal bread as part of a life-long healthy diet to help prevent not only heart disease but also multiple chronic conditions for middle-aged and older adults. Declarations Competing Interests AES has received speaker honoraria from Servier, Abbott, Sanofi, AstraZeneca, Medtronic, Omron, Novo Nordisk and Aktiia and serves on scientific advisory boards for Medtronic, Roche/Alnylam, AstraZeneca, Servier, SiSU Health, Biozen and Sky Labs. No other disclosures declared. Funding This research was funded through X.X.’s Scientia Program at the University of New South Wales, Australia. AES is funded by an Investigator Grant from the National Health and Medical Research Council of Australia (APP2017504). Competing Interests AES has received speaker honoraria from Servier, Abbott, Sanofi, AstraZeneca, Medtronic, Omron, Novo Nordisk and Aktiia and serves on scientific advisory boards for Medtronic, Roche/Alnylam, AstraZeneca, Servier, SiSU Health, Biozen and Sky Labs. No other disclosures declared. Author Contribution X.X.: Conceptualization, Methodology, Formal analysis, Data curation, Writing- Original draft preparation, Funding acquisition; L.Z: Writing - original draft; S.G: Conceptualization, Methodology, Writing - review & editing; A.E.S: Methodology, Writing - review & editing; M.B.: Data curation, Writing - review & editing; Y.L.: Writing - review & editing. Acknowledgement The 45 and Up Study is managed by the Sax Institute in collaboration with major partner Cancer Council NSW and the NSW Ministry of Health. We thank the many thousands of people participating in the 45 and Up Study AES is funded by an Investigator Grant from the National Health and Medical Research Council of Australia (APP2017504). Data Availability This research was completed using data collected through the 45 and Up Study (www.saxinstitute.org.au). References Nguyen H, Manolova G, Daskalopoulou C, Vitoratou S, Prince M, Prina AM (2019) Prevalence of multimorbidity in community settings: A systematic review and meta-analysis of observational studies, Journal of Comorbidity , vol. 9, pp. 2235042X19870934-2235042X19870934. 10.1177/2235042X19870934 Chowdhury SR, Chandra Das D, Sunna TC, Beyene J, Hossain A (2023) Global and regional prevalence of multimorbidity in the adult population in community settings: a systematic review and meta-analysis, EClinicalMedicine , vol. 57, pp. 101860–101860. 10.1016/j.eclinm.2023.101860 Australian Institute of Health and Welfare (2024) Multimorbidity . [Online] Available: https://www.aihw.gov.au/reports/australias-health/multimorbidity A. I. o. H. a. Welfare;, Chronic condition multimorbidity 2021, (2021) [Online]. Available: https://www.aihw.gov.au/reports/chronic-disease/chronic-condition-multimorbidity-2021/contents/what-are-the-types-of-multimorbidity-and-how-commo Valderas JMMDPMPH, Starfield BMDMPH, Sibbald BMP (2009) B. C. M. F. Salisbury, and M. C. B. E. D. M. F. F. F. Roland, Defining Comorbidity: Implications for Understanding Health and Health Services. Ann Fam Med 7(4):357–363. 10.1370/afm.983 Skou ST et al (2022) Multimorbidity. Nat reviews Disease primers 8(1):48–48. 10.1038/s41572-022-00376-4 Tazzeo C et al (2023) Risk factors for multimorbidity in adulthood: A systematic review. Ageing Res Rev 91:102039–102039. 10.1016/j.arr.2023.102039 Sugiyama Y, Mutai R, Aoki T, Matsushima M (2022) Multimorbidity and complex multimorbidity, their prevalence, and associated factors on a remote island in Japan: a cross-sectional study. BMC Prim Care 23(1):258. 10.1186/s12875-022-01860-2 . /10/03 2022 Harrison C, Henderson J, Miller G, Britt H (2016) The prevalence of complex multimorbidity in Australia. Aust N Z J Public Health 40(3):239–244 2016/06/01/. https://doi.org/10.1111/1753-6405.12509 Rizzuto D, Melis RJF, Angleman S, Qiu C, Marengoni A (2017) Effect of Chronic Diseases and Multimorbidity on Survival and Functioning in Elderly Adults. J Am Geriatr Soc (JAGS) 65(5):1056–1060. 10.1111/jgs.14868 Makovski TT, Schmitz S, Zeegers MP, Stranges S, van den Akker M (2019) Multimorbidity and quality of life: Systematic literature review and meta-analysis. Ageing Res Rev 53:100903–100903. 10.1016/j.arr.2019.04.005 Kabir A, Conway DP, Ansari S, Tran A, Rhee JJ, Barr M (2024) Impact of multimorbidity and complex multimorbidity on healthcare utilisation in older Australian adults aged 45 years or more: a large population-based cross-sectional data linkage study. BMJ Open 14(1):e078762. 10.1136/bmjopen-2023-078762 Indu PS (2023) Escalating Burden of Noncommunicable Diseases and Multimorbidity: Can Dietary Interventions Make a Difference? Indian J Clin Med 13(2):73–74. 10.1177/26339447231223564 McRae MP (Mar 2017) Health Benefits of Dietary Whole Grains: An Umbrella Review of Meta-analyses, (in eng). J Chiropr Med 16(1):10–18. 10.1016/j.jcm.2016.08.008 Zhang B, Zhao Q, Guo W, Bao W, Wang X (2018) Association of whole grain intake with all-cause, cardiovascular, and cancer mortality: a systematic review and dose–response meta-analysis from prospective cohort studies. Eur J Clin Nutr 72(1):57–65. 10.1038/ejcn.2017.149 Schacht SR, Olsen A, Dragsted LO, Overvad K, Tjønneland A, Kyrø C (2021) Whole-Grain Intake and Pancreatic Cancer Risk—The Danish, Diet, Cancer and Health Cohort. J Nutr 151(3):666–674. 10.1093/jn/nxaa385 Hu Y, Willett WC, Manson JAE, Rosner B, Hu FB, Sun Q (2022) Intake of whole grain foods and risk of coronary heart disease in US men and women. BMC Med 20(1):192–192. 10.1186/s12916-022-02396-z Hu H et al (2023) Consumption of whole grains and refined grains and associated risk of cardiovascular disease events and all-cause mortality: a systematic review and dose-response meta-analysis of prospective cohort studies. Am J Clin Nutr 117(1):149–159. 10.1016/j.ajcnut.2022.10.010 Wang Y, Feng J, Liu T, Gong Z, Zhuo Q (2024) Association between Whole-Grain Intake and Obesity Defined by Different Anthropometric Indicators and Dose-Response Relationship Analysis among U.S. Adults: A Population-Based Study, Nutrients , vol. 16, no. 14, p. 2373. 10.3390/nu16142373 Xu Y, Wan Q, Feng J, Du L, Li K, Zhou Y (2018) Whole grain diet reduces systemic inflammation: A meta-analysis of 9 randomized trials. Med (Baltim) 97(43):e12995–e. 10.1097/MD.0000000000012995 Roager HM et al (2019) Whole grain-rich diet reduces body weight and systemic low-grade inflammation without inducing major changes of the gut microbiome: a randomised cross-over trial, Gut , vol. 68, no. 1, pp. 83–93. 10.1136/gutjnl-2017-314786 Xu C, Marques FZ (2022) How dietary fibre, acting via the gut microbiome, lowers blood pressure. Curr Hypertens Rep 24(11):509–521 Ruel G et al (2014) Association between nutrition and the evolution of multimorbidity: The importance of fruits and vegetables and whole grain products. Clinical Nutr Article vol 33(3):513–520. 10.1016/j.clnu.2013.07.009 Pereira BP et al (2020) Food consumption and multimorbidity among noninstitutionalized elderly people in Pelotas, 2014: A cross-sectional study, Epidemiologia e Servicos de Saude , Article vol. 29, no. 3, Art no. e2019050. 10.5123/S1679-49742020000300015 Sax Institute (2016) 45 and Up Study https://www.saxinstitute.org.au/our-work/45-up-study/ (accessed 2/1/16 Bleicher K et al (2023) Cohort profile update: the 45 and up study. Int J Epidemiol 52(1):e92–e101 Banks E et al (2007) Cohort profile: the 45 and up study. Int J Epidemiol 37(5):941–947 Xu X et al (2021) The Joint Effects of Diet and Dietary Supplements in Relation to Obesity and Cardiovascular Disease over a 10-Year Follow-Up: A Longitudinal Study of 69,990 Participants. 13(3):944in Australia, vol Xu X, Ling M, Inglis SC, Hickman L (2020) and D. J. I. j. o. p. h. Parker, Eating and healthy ageing: a longitudinal study on the association between food consumption, memory loss and its comorbidities, pp. 1–12 Astell-Burt T, Feng X, Croteau K, Kolt GSJSS, Medicine (2013) Influence of neighbourhood ethnic density, diet and physical activity on ethnic differences in weight status: a study of 214,807 adults in Australia. 93:70–77 Kabir A, Tran A, Ansari S, Conway DP, Barr M (2022) Impact of multimorbidity and complex multimorbidity on mortality among older Australians aged 45 years and over: a large population-based record linkage study. BMJ open 12(7):e060001 Australian Bureau of Statistics Socio-Economic Indexes for Areas. http://www.abs.gov.au/websitedbs/censushome.nsf/home/seifa (accessed Ding D, Rogers K, van der Ploeg H, Stamatakis E (2015) J. P. m. Bauman, Traditional and emerging lifestyle risk behaviors and all-cause mortality in middle-aged and older adults: evidence from a large population-based Australian cohort. 12(12):e1001917 Australian Government (2013) Eat for Health: Australian Dietary Guidelines Providing the Scientific Evidence for Healthier Australian Diets, ed: Commonwealth of Australia. National Health and Medical Research Council Canberra, Australia Chen Q-F et al Global burden of disease and its risk factors for adults aged 70 and older across 204 countries and territories: a comprehensive analysis of the Global Burden of Disease Study 2021, BMC Geriatrics , vol. 25, no. 1, p. 462, 2025/07/02 2025. 10.1186/s12877-025-06095-1 Zhou M, Zhao G, Zeng Y, Zhu J, Cheng F, Liang W (2022) Aging and Cardiovascular Disease: Current Status and Challenges, (in eng), Rev Cardiovasc Med , vol. 23, no. 4, p. 135, Apr 10.31083/j.rcm2304135 Dunford EK, Miles DR, Popkin B, Ng SW Whole Grain and Refined Grains: An Examination of US Household Grocery Store Purchases, (in eng), J Nutr , vol. 152, no. 2, pp. 550–558, Feb 8 2022. 10.1093/jn/nxab382 Liu F, Yin J, Wang J, Xu X (2022) Food for the elderly based on sensory perception: A review, (in eng). Curr Res Food Sci 5:1550–1558. 10.1016/j.crfs.2022.09.014 Grains & Legumes Nutrition Council (2014) [Online]. Available: https://www.glnc.org.au/wp-content/uploads/2015/04/Australians-at-Risk-2014-Grains-Legumes-Consumption-Attitudinal-Study.pdf The (2013) Australian dietary guidelines and recommendations for older Australians, Australian Journal of General Practice , vol. 44, pp. 311–315, 04/22 2015. [Online]. Available: https://www.racgp.org.au/afp/2015/may/the-2013-australian-dietary-guidelines-and-recomme Snetselaar LG, de Jesus JM, DeSilva DM, Stoody EE (2021) Dietary Guidelines for Americans, 2020–2025: Understanding the Scientific Process, Guidelines, and Key Recommendations, (in eng), Nutr Today , vol. 56, no. 6, pp. 287–295, Nov-Dec 10.1097/nt.0000000000000512 (2019) Canada’s Dietary Guidelines . [Online] Available: https://food-guide.canada.ca/en/guidelines/ Aune D et al (2016) Whole grain consumption and risk of cardiovascular disease, cancer, and all cause and cause specific mortality: systematic review and dose-response meta-analysis of prospective studies, bmj , vol. 353 Xu X, Parker D, Inglis SC, Byles J (2019) Can regular long-term breakfast cereals consumption benefits lower cardiovascular diseases and diabetes risk? A longitudinal population-based study, Annals of epidemiology , vol. 37, pp. 43–50. e3 Grundy MM-L, Fardet A, Tosh SM, Rich GT, Wilde PJ (2018) Processing of oat: the impact on oat's cholesterol lowering effect. Food Funct 9(3):1328–1343 Decker EA, Rose DJ, Stewart D (2014) Processing of oats and the impact of processing operations on nutrition and health benefits. Br J Nutr, 112, S2, pp. S58-S64 Feraco A et al (2024) Assessing gender differences in food preferences and physical activity: a population-based survey. (in eng) Front Nutr 11:1348456. 10.3389/fnut.2024.1348456 Johar M, Jones G, Savage E (2012) Healthcare expenditure profile of older Australians: evidence from linked survey and health administrative data. Economic Papers: J Appl Econ policy 31(4):451–463 Additional Declarations Competing interest reported. AES has received speaker honoraria from Servier, Abbott, Sanofi, AstraZeneca, Medtronic, Omron, Novo Nordisk and Aktiia and serves on scientific advisory boards for Medtronic, Roche/Alnylam, AstraZeneca, Servier, SiSU Health, Biozen and Sky Labs. No other disclosures declared. Supplementary Files SupplementaryTables.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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2","display":"","copyAsset":false,"role":"figure","size":96689,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAssociations between whole grain and high fibre cereals intake and heart disease, multimorbidity, and complex multimorbidity by sex\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9182393/v1/617c53dcf6cc35749a7ac2ae.png"},{"id":105983243,"identity":"885bcd29-626e-4b3e-ba2d-d34a992b7796","added_by":"auto","created_at":"2026-04-02 07:08:00","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":98479,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAssociations between types of whole grain and high fibre cereals intake and heart disease, multimorbidity, and complex multimorbidity by sex\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9182393/v1/1ef2354de6f63ea2b2b67f63.png"},{"id":106096744,"identity":"360ca548-26c9-4570-bf1d-f7865843cca4","added_by":"auto","created_at":"2026-04-03 11:56:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1490782,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9182393/v1/3a1e4234-2842-413f-ad80-e22d4e00d155.pdf"},{"id":105983241,"identity":"8f4b662b-2fef-4186-863c-932da2e2ef24","added_by":"auto","created_at":"2026-04-02 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AES has received speaker honoraria from Servier, Abbott, Sanofi, AstraZeneca, Medtronic, Omron, Novo Nordisk and Aktiia and serves on scientific advisory boards for Medtronic, Roche/Alnylam, AstraZeneca, Servier, SiSU Health, Biozen and Sky Labs. No other disclosures declared.","formattedTitle":"Whole grain and high fiber cereals and multimorbidity: A longitudinal study in 146,329 adults aged 45 years and over","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMultimorbidity, commonly defined as the presence of at least two chronic diseases in the same individual, has become increasingly common and affects more than one-third of the global adult population [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Regionally, the prevalence in South America is 45.7%, followed by North America (43.1%), Europe (39.2%) and Asia (35%) [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In Australia, 38% of Australians were diagnosed with multimorbidity in 2022 [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The prevalence of complex multimorbidity, referred to as three or more chronic conditions affecting different body systems, was 17% among people aged 45 and over in Australia [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Multimorbidity is expanding on a global scale due to increased life expectancy, which often leads to reduced quality of life, higher hospital admissions, higher mortality risk and greater healthcare costs [\u003cspan additionalcitationids=\"CR5 CR6 CR7 CR8 CR9 CR10 CR11\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDiet is a key risk factor for the development of multimorbidity [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. A growing body of epidemiological evidence has demonstrated that whole grains, which are often high in fiber, offers protective effects against several chronic diseases, including cardiovascular disease, cancer, obesity and diabetes [\u003cspan additionalcitationids=\"CR15 CR16 CR17 CR18\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. These effects are attributed to the abundance of cereal fiber content, vitamins, minerals, lignans, and phytochemicals concentrated in the bran and germ of whole grains [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Collectively, these bioactive components of whole grains are known to lower inflammation, a key contributor to the pathogenesis of cardiovascular and metabolic diseases [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Much of this benefit is mediated by dietary fiber, which is metabolized by the colonic microbiota into short-chain fatty acids such as acetate, propionate, and butyrate [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough whole grain and fiber-rich foods have been extensively studied in relation to single disease states, studies linking whole grains and fiber-rich foods with multimorbidity, particularly complex multimorbidity, remain scarce and inconclusive. One study of 1,020 participants in China reported that higher whole grain intake was associated with a lower risk of developing multimorbidity compared with diets high in refined grains such as rice and wheat [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. In contrast, a cross-sectional study conducted in Brazil found that higher whole grain consumption was associated with a 64% increased risk of multimorbidity among men [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePrevious studies have mostly employed cross-sectional designs that measure whole grain and fiber-rich foods consumption at a single time point, overlooking the dynamic nature of long-term dietary habits and their influence on the development of multimorbidity [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Longitudinal studies are therefore needed to clarify the cumulative effects of whole grain and high fiber cereal consumption on the development of multimorbidity and complex multimorbidity. Accordingly, this study examined the associations between whole grain and high fiber cereal intake and the risks of heart disease, multimorbidity and complex multimorbidity over 15 years.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData sources\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research used the established Central and Eastern Sydney Primary and Community Health Cohort/Linkage Resource (CES-P\u0026amp;CH) based on the Sax Institute’s 45 and Up Study [25]. The 45 and Up Study is a large-scale Australian cohort study including 267,357 men and women aged 45 and over across New South Wales (NSW), Australia. The baseline participants gave written informed consent and were surveyed between 2005 and 2009. The first follow-up survey data were collected between 2012 and 2015, and the second follow-up survey data was collected between 2018 and 2020. At these three time points, socioeconomic, health behaviour and health-related information were collected via a comprehensive questionnaire [26]. About 19% of those invited participated and participants included about 11% of the NSW population aged 45 years and over. Details of the 45 and Up Study, including sampling strategy and methods are described elsewhere [27].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was granted for this research by the XX Research Ethics Committee (Reference Number: XX) and from the XX Human Research Ethics Committee.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eParticipant cohort\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe included 146,329 participants who had no self-reported heart disease, multimorbidity, or complex multimorbidity at baseline (2005–2009) and followed through two waves until 2020. Only participants who completed dietary questionnaires in follow-up waves were included in the analysis (\u003cstrong\u003eFigure 1\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eWhole grain and high fiber cereals and wholemeal bread\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;In the 45 and Up Study questionnaire, dietary consumption was assessed using short food frequency questions, which have been described in our previous studies [28, 29]. Each of the questions on diet was previously validated in the Million Women Study [30]. Whole grain and high fiber cereals consumption was defined based on participants’ responses to a question about the types of breakfast cereals they usually ate. Participants who reported consuming bran cereals (e.g., All-Bran, Bran Flakes), biscuit cereals (e.g., Weet-Bix, Shredded Wheat), oat cereals (e.g., porridge), or muesli were classified as whole grain and high-fiber cereals consumers. Participants were also asked whether they consumed brown or wholemeal bread, and if so, how many slices or pieces they typically ate per week. Based on their responses, we identified wholemeal bread consumers and further categorised them into tertiles (low, medium, and high) according to the number of slices consumed weekly.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eOutcomes: heart disease, multimorbidity and complex multimorbidity\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHeart disease was defined based on self-reported responses of a diagnosis, indicated by a ‘yes’ response to the question, ‘Has a doctor ever told you that you have heart disease?’ or by reporting treatment for heart conditions in response to the question, ‘In the last month, have you been treated for a heart attack, angina, or other heart disease?’\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMultimorbidity was defined as the presence of two or more chronic conditions out of a total of 12, including cancer, heart disease, diabetes, Parkinson’s disease, stroke, depression or anxiety, asthma, allergic rhinitis, hypertension, thrombosis, musculoskeletal conditions, and thyroid disorders. Complex multimorbidity was defined as the presence of three or more conditions affecting different body systems, selected from a total of 9 categories: cardiovascular, musculoskeletal, neurological, psychological, respiratory, skin, endocrine/metabolic, female genital, and male genital systems. The definitions of multimorbidity and complex multimorbidity were determined based on our previous publication and consultation with clinicians [31]. Definitions for each individual disease, along with the corresponding questionnaire items, are provided in \u003cstrong\u003eSupplementary Table 1\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCovariates\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe included socio-demographic factors, health behavioural factors, and other food group consumption as covariates in the statistical analysis. Socio-demographic variables included age, marital status (married/partner, single/divorced/separated, and widowed), education (Low, Median, High). Socioeconomic levels were assessed by Socio-Economic Indexes For Areas (SEIFA), which is based on three tertiles (Low, Medium, High) of Index of Relative Socio-economic Advantage and Disadvantage [32]. Health behaviours included smoking, alcohol drinking and physical activity levels. Smoking was identified as never smoked, previous smoker, and current smoker, based on two questions: “Have you ever been a regular smoker?”, and “Are you a regular smoker now?”. The frequency of alcohol consumption was identified by a question of “about how many alcoholic drinks do you have each week?” Physical activity was measured using the Active Australia Survey, asking the total time spent on walking, and on moderate-intensity and vigorous-intensity physical activity in the previous week. Adequate physical activity was identified if people spent 150 minutes of moderate intensity physical activity, or 75 minutes of vigorous intensity physical activity per week [33]. Body Mass Index was also included and calculated based on the weight and height that was identified by the questions “about how much do you weight?” and “how tall are you without shoes?”\u003c/p\u003e\n\u003cp\u003eBased on the Australian Guide to Healthy Eating [34] other food components were also included as covariates, namely 1) vegetables, 2) fruit, 3) lean meat and poultry, and 4) dairy or dairy alternatives [28]. The frequency of consuming these food groups was reported in the 45 and Up dietary questionnaire. The details have been described in our previous publications [28, 29].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStatistical analysis\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNumber and percentage for categorical variables and mean (SD) for continuous variables were used to present baseline characteristics by whole grain and high-fiber cereals and wholemeal bread intake. Chi-squire and ANOVA were applied to present statistical differences between groups. The statistical differences in the trends of grain consumption and the prevalence of heart disease, multimorbidity, and complex multimorbidity were assessed using ANOVA.\u003c/p\u003e\n\u003cp\u003eGeneralized Estimating Equation (GEE) models were used to assess the longitudinal effects of consumption of whole grain and high-fiber cereals and wholemeal bread on disease outcomes. We presented results from GEE models in the forest plots as crude and adjusted models, with Relative Risk (RR) and 95% Confidence Interval (CI). The latter model was adjusted for socioeconomic factors (age, marital status, education, and socioeconomic level), health behaviours (smoking, alcohol drinking, physical activity levels), and consumption of other foods (vegetables, fruit dairy or alternatives, lean meat and poultry), given that these variables were commonly reported as related to heart disease. All analyses were stratified by sex and conducted in Stata/SE 17 (StataCorp, College Station, TX).\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 146,329 participants without heart disease, multimorbidity, or complex multimorbidity at baseline, and with available dietary data, were included in the study and followed for up to 15 years. By the first follow-up, 7,417 participants had developed heart disease, 25,173 had developed multimorbidity, and 5,312 had developed complex multimorbidity. By the second follow-up, there are 8,002 had heart disease, 24,847 had multimorbidity, and 6,831 had complex multimorbidity (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe distribution of chronic conditions and body system morbidities is presented in \u003cb\u003eSupplementary Table\u0026nbsp;2\u003c/b\u003e. The prevalence of each chronic condition and body system morbidity increased across waves. Hypertension was the most common single condition (rising from 23.8% to 38.5%), followed by musculoskeletal conditions (from 2.9% to 21%) and cancer (from 6.5% to 19.9%). Among body system morbidities, cardiovascular diseases were the most prevalent (increasing from 25.9% to 46.4%), followed by musculoskeletal (from 2.9% to 21%) and respiratory conditions (from 8.8% to 15.9%).\u003c/p\u003e \u003cp\u003eBaseline characteristics by whole grain high-fiber cereals and brown/wholemeal bread intake are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Females reported higher consumption of grain cereals compared to males, whereas males tended to consume more brown/wholemeal bread than females (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Participants who were married, had a medium level of education, or identified as Australian were more likely to consume both grain cereals and brown/wholemeal bread than those in other respective categories (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Non-smokers and those with adequate physical activity levels reported higher intake of whole grain high-fiber cereals and brown/wholemeal bread (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\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\u003eBaseline characteristics by whole grain and high fiber cereals and wholemeal bread intake (N\u0026thinsp;=\u0026thinsp;146,329)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\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=\"char\" char=\".\" 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=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eWhole grain and high fiber\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eNumber of brown/whole grain bread\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eP value\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\u003eYes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e (mean, SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e59.6 (10.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60.3 (10.4)\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=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e58.1 (9.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e59.8 (10.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e61.9 (10.6)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e (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=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20,075 (49.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50,275 (47.4)\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=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e21,351 (46.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e19,812 (42.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e24,526 (54.6)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20,265 (50.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55,712 (52.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24,338 (53.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e26,409 (57.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e20,365 (45.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e (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=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried/partner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30,539 (76.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e83,655 (79.4)\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=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e36,026 (79.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e36,337 (79.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e35,181 (78.8)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle/divorce/separated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7,100 (17.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15,317 (14.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7,254 (16.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6,917 (15.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e6,531 (14.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ewidowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,371 (5.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6,370 (6.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2,115 (4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2,667 (5.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2,925 (6.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e (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=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13,332 (33.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31,035 (29.7)\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=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14,053 (31.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e13,052 (28.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e13,415 (30.3)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17,003 (43.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45,111 (43.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e19,400 (43.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e19,565 (42.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e19,522 (44.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\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=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9,214 (23.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28,351 (27.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11,627 (25.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12,964 (28.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e11,340 (25.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSEIFA*\u003c/b\u003e (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=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15,159 (38.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34,325 (33.3)\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=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e15,595 (35.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e14,587 (32.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e15,338 (35.1)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12,803 (32.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34,609 (33.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14,838 (33.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e14,839 (33.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e14,829 (34.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\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=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11,298 (28.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34,113 (33.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13,975 (31.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e15,526 (34.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e13,497 (30.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEthnicity (N, %)\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAustralian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19,409 (47.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e54,367 (51.3)\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=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e22,609 (49.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e22,938 (49.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e23,104 (51.5)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnglish\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8,708 (21.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26,954 (25.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10,370 (22.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11,576 (25.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e11,633 (25.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIrish\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,030 (5.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5,602 (5.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2,337 (5.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2,443 (5.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2,347 (5.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\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=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10,533 (26.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19,064 (18.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10,373 (22.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9,264 (20.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e7,807 (17.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoke\u003c/b\u003e (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=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e34,613 (86.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e99,445 (94.2)\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=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e40,783 (89.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e42,899 (93.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e41,895 (93.8)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5,460 (13.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6,094 (5.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4,682 (10.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3,130 (6.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2,784 (6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePhysical activity**\u003c/b\u003e (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=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInadequate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10,162 (26.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19,990 (19.4)\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=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10,761 (24.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9,020 (20.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e7,840 (18.0)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdequate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28,231 (73.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e82,846 (80.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e33,433 (75.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e35,828 (79.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e35,759 (82.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBody Mass Index\u003c/b\u003e (mean, SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26.6 (4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.2 (4.4)\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=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26.4 (4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e26.3 (4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e26.3 (4.4)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVegetables\u003c/b\u003e (serves, mean, SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.6 (2.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.0 (2.8)\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=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.6 (2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.9 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.0 (2.7)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eProtein\u003c/b\u003e (times, mean, SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.8 (4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.5 (3.8)\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=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.5 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.4 (3.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e6.6 (3.7)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFruit\u003c/b\u003e (serves, mean, SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.8 (1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.0 (1.4)\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=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.6 (2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.9 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.0 (2.7)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDairy\u003c/b\u003e (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=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,632 (4.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2,492 (2.4)\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=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1,551 (3.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,169 (2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1,175 (2.6)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38,708 (95.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e103,495 (97.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e44,138 (96.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e45,052 (97.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e43,716 (97.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAt baseline, 105,987 participants (72.4%) reported consuming whole grain and high fiber cereals, decreasing to 53.9% at the first follow-up and 59.6% at the second follow-up. Across all three waves, females consistently reported higher whole grain and high fiber cereals consumption than males. Wholemeal bread consumption declined over time, with an average intake of 10.2 slices per week at baseline, decreasing to 8.4 slices by the second follow-up; males reported higher consumption than females. During the follow-up period, more males developed heart disease, whereas females had higher rates of multimorbidity and complex multimorbidity \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" 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\u003eTrends in whole grain and high fiber cereals intake and prevalence of disease outcomes over time\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWhole grain and high fiber cereals (N, %)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline (N\u0026thinsp;=\u0026thinsp;146,329)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFirst follow-up (N\u0026thinsp;=\u0026thinsp;83,032)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSecond follow-up (N\u0026thinsp;=\u0026thinsp;60,211)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAll\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e105,987 (72.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32,891 (53.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27,330 (59.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eMales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50,275 (71.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13,216 (45.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11,316 (51.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eFemales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55,712 (73.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19,675 (61.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16,014 (67.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003cb\u003eNumber of slides \u0026ndash; wholemeal bread per week (mean/SD)\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAll\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.2 (8.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.0 (7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.4 (7.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eMales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.4 (10.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.5 (8.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.9 (8.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eFemales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.0 (7.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.6 (6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.2 (5.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003cb\u003eHeart disease (N, %)\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAll\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7,417 (8.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8,002 (13.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eMales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4,538 (11.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4,964 (17.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eFemales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2,879 (6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3,038 (9.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003cb\u003eMultimorbidity (N, %)\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAll\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25,173 (30.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24,847 (41.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eMales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11,460 (29.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11,478 (40.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eFemales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13,713 (31.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13,369 (41.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003cb\u003eComplex multimorbidity (N, %)\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAll\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5,312 (6.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6,831 (11.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eMales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2,179 (5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2,845 (10.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eFemales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3,142 (7.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3,986 (12.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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=\"5\"\u003e* \u003cem\u003eRed indicates the significant association.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e* \u003cem\u003eRed indicates the significant association.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe relationship between long-term consumption of whole grain and high fiber cereals and disease outcomes are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA. In the unadjusted model, those who consumed whole grain and high fiber cereals had lower risk of heart disease, multimorbidity and complex multimorbidity. After adjustment for covariates, females who consumed whole grain and high fibre cereals had a 12% lower relative risk of heart disease (RR\u0026thinsp;=\u0026thinsp;0.88; 95% CI: 0.78; 0.99) and a 13% lower risk of complex multimorbidity (RR\u0026thinsp;=\u0026thinsp;0.87; 95% CI: 0.77; 0.97) compared with those who did not consume grain cereals. In contrast, males who consumed whole grain and high fibre cereals had a 14% higher risk of complex multimorbidity (RR\u0026thinsp;=\u0026thinsp;1.14; 95% CI: 1.01; 1.29).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAfter adjusting for covariates of socio-demographic factors, health behavioural factors, and other food group consumption, participants who consumed more than 12 slices of wholemeal bread per week had a 13% lower risk of heart disease (RR\u0026thinsp;=\u0026thinsp;0.87; 95% CI: 0.83; 0.92), a 18% lower risk of multimorbidity (RR\u0026thinsp;=\u0026thinsp;0.82; 95% CI: 0.80; 0.85), and an 17% lower risk of complex multimorbidity (RR\u0026thinsp;=\u0026thinsp;0.83; 95% CI: 0.78; 0.87), compared to those who consumed fewer than 5 slices per week.\u003c/p\u003e \u003cp\u003eSex-specific analyses further indicated that females who consumed more than 12 slices of wholemeal bread per week experienced greater risk reduction than males across all disease outcomes. For heart disease, the relative risk was 0.79 (95% CI: 0.72; 0.85) in females and 0.94 (0.88; 0.99) in males. For multimorbidity, the relative risk was 0.74 (0.71; 0.77) in females and 0.92 (0.88; 0.95) in males. For complex multimorbidity, it was 0.77 (0.71; 0.83) in females and 0.90 (0.82; 0.98) in males (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003eWe further examined the associations between different types of whole grain and high-fibre cereals (bran cereals, biscuit cereals, oat cereals, and muesli) and disease outcomes (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Oat cereal and muesli consumption showed consistent associations with all disease outcomes (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC \u0026amp; \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). Oat cereal consumption associated with 16% higher risk for heart disease (RR\u0026thinsp;=\u0026thinsp;1.16; 95% CI: 1.11; 1.22), 15% higher risk for multimorbidity (RR\u0026thinsp;=\u0026thinsp;1.15; 95% CI: 1.11; 1.18) and 13% higher risk for complex multimorbidity (RR\u0026thinsp;=\u0026thinsp;1.13; 95% CI: 1.07; 1.19). These associations were consistent in both males and females, with higher oat cereal intake linked to increased relative risks across all outcomes (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). In the contrast, muesli consumption was associated with a lower risk of heart disease (RR\u0026thinsp;=\u0026thinsp;0.88; 95% CI: 0.84; 0.93), multimorbidity (RR\u0026thinsp;=\u0026thinsp;0.92; 95% CI: 0.89; 0.95), and complex multimorbidity (RR\u0026thinsp;=\u0026thinsp;0.88; 95% CI: 0.84; 0.94). Consistent associations were observed in both sexes, with greater risk reductions observed in females than males across all disease outcomes (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eTo the best of our knowledge, this is the first investigation on the association between long-term consumption of whole grain and high fiber cereals and risk of developing multimorbidity and complex multimorbidity. Over 15 years, intake of whole grain and high fiber cereals and wholemeal bread declined. Females with sustained intake of whole grain and high fibre cereals experienced significantly lower risks of heart disease and complex multimorbidity, while associations were not consistent in males. Notably, cereal subtypes showed divergent associations, with oat cereals associated with higher risks and muesli and wholemeal bread demonstrating consistent protective effects.\u003c/p\u003e \u003cp\u003eIn this study, hypertension was the most common chronic condition, and cardiovascular disease the most prevalent morbidity among middle-aged and older adults, both showing a significant increase with age as expected. This is consistent with recent Global Burden of Disease analyses [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] indicating that cardiovascular disease remains the primary cause of death and hypertension was the leading risk factor of disease burden in older adults. The number of people who survive and live with cardiovascular disease continues to rise with global population aging [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Thus, it is important to implement effective, evidence-based dietary risk reduction strategies for blood pressure control and cardiovascular disease prevention across the life-course.\u003c/p\u003e \u003cp\u003eThe clear decline in the intake of whole grain and high fiber cereals and wholemeal bread across the 15 year follow-up may reflect the increased availability, affordability, and variety of refined grains on the market, making it easier for individuals to shift away from whole grain and high-fiber cereals consumption [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Additionally, aging-related factors such as reduced sensory appeal, difficulty chewing and swallowing and decreased appetite may influence food choices, such as grain products with harder textures [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Although we are not able to make a direct comparison with the Australian Dietary Guidelines due to the limitations of the questionnaire, whole grain and high fiber intake in the Australian population is generally much lower than recommended, suggesting that the benefits of these foods have not yet been widely realised [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eConsistent with established evidence [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], higher consumption of wholemeal bread was associated with a lower risk of heart disease. Unlike previous studies that primarily assessed whole grain consumption at a single time point [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], the present study captured the dynamic nature of long-term dietary patterns, thereby strengthening the evidence linking sustained wholemeal bread consumption to a reduced risk of heart disease. This observed inverse association aligns with current national dietary guidelines [\u003cspan additionalcitationids=\"CR41\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], which consistently recommend increasing whole grain intake. The cardioprotective effects of wholemeal bread are largely attributed to its provision of dietary fiber and its beneficial modulation of the gut microbiota [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], as well as its content of antioxidants and minerals, which together contribute to lower low-density lipoprotein cholesterol levels, improved blood pressure regulation, and overall cardiovascular health [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. In addition, we observed a reduced risk of multimorbidity and complex multimorbidity associated with higher wholemeal bread consumption, further supporting its broader benefits for overall health.\u003c/p\u003e \u003cp\u003eEvidence examining the associations between whole grain and high fiber cereal consumption and multimorbidity, particularly complex multimorbidity, remains limited. Given population ageing and the rising prevalence of multimorbidity and complex multimorbidity among middle-aged and older adults [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], it is no longer sufficient to assess dietary exposures solely in relation to individual diseases. Our cohort, 41% of participants developed multimorbidity and 11% developed complex multimorbidity, highlighting the importance of investigating the role of diet in the prevention of multiple co-occurring chronic conditions for the middle-aged and older population.\u003c/p\u003e \u003cp\u003eAmong different types of cereal consumption, long-term muesli intake was associated with clear benefits for heart disease, multimorbidity, and complex multimorbidity. Similar to wholemeal bread, the cardioprotective effects of muesli may be partly explained by its high fiber content and its favorable modulation of the gut microbiota, leading to the production of cardioprotective metabolites [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Additional benefits may stem from the common inclusion of nuts and dried fruits, which supply a range of macro- and micronutrients known to support cardiovascular health [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSurprisingly, we observed positive association between oat cereal consumption and heart disease, multimorbidity and complex multimorbidity. This finding should be interpreted with caution, as oat cereals represent a heterogeneous group of products that vary widely in processing level, which can alter the molecular properties and viscosity of oat β-glucans - key determinants of their cardioprotective effects. Highly processed oat cereals may also contain added sugars or refined components that could further attenuate these benefits [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e], However, because the dietary questionnaire did not differentiate between specific types of oat cereals, it is not possible to determine whether this association reflects product heterogeneity rather than a true adverse effect. In addition, reverse causation may contribute to this association, as oat cereals are often recommended to people with heart disease, leading higher-risk people to preferentially consume them. Further longitudinal studies with more detailed dietary assessment are needed to clarify the health impacts of different forms of oat cereal consumption.\u003c/p\u003e \u003cp\u003eOur study identified clear sex-specific differences in whole grain and high fiber cereal consumption and associated disease outcomes. Females reported higher long-term consumption of whole grain and high fiber cereals, whereas males tended to consume more wholemeal bread. Notably, females appeared to experience greater risk reductions for heart disease and complex multimorbidity associated with higher intake of whole grain and high fiber cereals, as well as with high consumption of wholemeal bread, compared with males. The mechanisms underlying these associations are not yet fully understood. However, our findings were consistent with previous epidemiological evidence indicating that dietary behaviours and food preferences differ by sex. For example, an Italian population-based study examining gender differences in food preferences reported that females were more inclined to consume whole grains than males [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. This may reflect sex differences in taste preferences, health awareness, and health-related behaviours that influence food choices. Our findings emphasise the importance of considering sex-specific dietary patterns when developing targeted dietary interventions for disease prevention and dietary guidelines.\u003c/p\u003e \u003cp\u003eThe strengths of our study are that it involved large sample size and followed over 15 years that allow us to understand long-term associations of whole grain and high fibre cereal consumption and health outcomes by different sexes. More importantly, we provide new evidence, previously lacking in the literature, demonstrating the association between long-term whole grain and high fibre consumption and the risk of multimorbidity and complex multimorbidity, conditions that are highly prevalent among middle-aged and older adults. The generalizability needs to be noted in that the 45 and Up Study sample skews toward higher income groups, as well as oversampling of people aged\u0026thinsp;\u0026ge;\u0026thinsp;80 years and residents of rural and remote areas [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. The study has several limitations. First, it relied on self-reported data, which may introduce measurement bias and does not allow assessment of the quality of whole grain consumption. The questionnaire provides a limited range of example foods and captured only the commonly consumed whole grain and high fiber cereals by participants, without collecting information on exact quantities and types (e.g., oat cereals), which limited a more detailed assessment of intake. In addition, although examples of whole grain and high fiber cereal were provided in the questionnaire, there remains the potential for misclassification if participants selected incorrect categories, which may have contributed to measurement bias. There was substantial loss to follow-up during the first and second follow-up waves, resulting in missing dietary and health information, which may have introduced selection bias and thereby influenced the observed associations. Nonetheless, such attrition is a common challenge in long-term longitudinal epidemiological studies. While the analysis adjusted for major food groups, some dietary confounders, such as consumption of fast or processed foods, may not have been fully accounted for. Finally, our results are clearly observational, and relationships do not necessarily reflect cause-and-effect.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eLong-term dietary behaviour of whole grain and high fiber cereal intake associated with a lower risk of developing heart disease by 12%, and complex multimorbidity by 13% for females. Across different cereal types, oat cereal consumption was consistently associated with higher risk across all disease outcomes, whereas muesli consumption was consistently associated with lower risk across all disease outcomes. Long-term consumption of wholemeal bread was associated with a 13% lower risk of heart disease, an 18% lower risk of multimorbidity, and a 17% lower risk of complex multimorbidity. Our findings suggest that guidelines could more confidently promote the inclusion of whole grains and high fiber cereals, in particular muesli and wholemeal bread as part of a life-long healthy diet to help prevent not only heart disease but also multiple chronic conditions for middle-aged and older adults.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003cp\u003e AES has received speaker honoraria from Servier, Abbott, Sanofi, AstraZeneca, Medtronic, Omron, Novo Nordisk and Aktiia and serves on scientific advisory boards for Medtronic, Roche/Alnylam, AstraZeneca, Servier, SiSU Health, Biozen and Sky Labs. No other disclosures declared.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis research was funded through X.X.\u0026rsquo;s Scientia Program at the University of New South Wales, Australia. AES is funded by an Investigator Grant from the National Health and Medical Research Council of Australia (APP2017504).\u003c/p\u003e \u003cp\u003eCompeting Interests\u003c/p\u003e \u003cp\u003eAES has received speaker honoraria from Servier, Abbott, Sanofi, AstraZeneca, Medtronic, Omron, Novo Nordisk and Aktiia and serves on scientific advisory boards for Medtronic, Roche/Alnylam, AstraZeneca, Servier, SiSU Health, Biozen and Sky Labs. No other disclosures declared.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eX.X.: Conceptualization, Methodology, Formal analysis, Data curation, Writing- Original draft preparation, Funding acquisition; L.Z: Writing - original draft; S.G: Conceptualization, Methodology, Writing - review \u0026amp; editing; A.E.S: Methodology, Writing - review \u0026amp; editing; M.B.: Data curation, Writing - review \u0026amp; editing; Y.L.: Writing - review \u0026amp; editing.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe 45 and Up Study is managed by the Sax Institute in collaboration with major partner Cancer Council NSW and the NSW Ministry of Health. We thank the many thousands of people participating in the 45 and Up Study AES is funded by an Investigator Grant from the National Health and Medical Research Council of Australia (APP2017504).\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThis research was completed using data collected through the 45 and Up Study (www.saxinstitute.org.au).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eNguyen H, Manolova G, Daskalopoulou C, Vitoratou S, Prince M, Prina AM (2019) Prevalence of multimorbidity in community settings: A systematic review and meta-analysis of observational studies, \u003cem\u003eJournal of Comorbidity\u003c/em\u003e, vol. 9, pp. 2235042X19870934-2235042X19870934. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/2235042X19870934\u003c/span\u003e\u003cspan address=\"10.1177/2235042X19870934\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChowdhury SR, Chandra Das D, Sunna TC, Beyene J, Hossain A (2023) Global and regional prevalence of multimorbidity in the adult population in community settings: a systematic review and meta-analysis, \u003cem\u003eEClinicalMedicine\u003c/em\u003e, vol. 57, pp. 101860\u0026ndash;101860. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.eclinm.2023.101860\u003c/span\u003e\u003cspan address=\"10.1016/j.eclinm.2023.101860\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAustralian Institute of Health and Welfare (2024) \u003cem\u003eMultimorbidity\u003c/em\u003e. [Online] Available: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.aihw.gov.au/reports/australias-health/multimorbidity\u003c/span\u003e\u003cspan address=\"https://www.aihw.gov.au/reports/australias-health/multimorbidity\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eA. I. o. H. a. Welfare;, Chronic condition multimorbidity 2021, (2021) [Online]. Available: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.aihw.gov.au/reports/chronic-disease/chronic-condition-multimorbidity-2021/contents/what-are-the-types-of-multimorbidity-and-how-commo\u003c/span\u003e\u003cspan address=\"https://www.aihw.gov.au/reports/chronic-disease/chronic-condition-multimorbidity-2021/contents/what-are-the-types-of-multimorbidity-and-how-commo\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eValderas JMMDPMPH, Starfield BMDMPH, Sibbald BMP (2009) B. C. M. F. Salisbury, and M. C. B. E. D. M. F. F. F. Roland, Defining Comorbidity: Implications for Understanding Health and Health Services. Ann Fam Med 7(4):357\u0026ndash;363. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1370/afm.983\u003c/span\u003e\u003cspan address=\"10.1370/afm.983\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSkou ST et al (2022) Multimorbidity. Nat reviews Disease primers 8(1):48\u0026ndash;48. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41572-022-00376-4\u003c/span\u003e\u003cspan address=\"10.1038/s41572-022-00376-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTazzeo C et al (2023) Risk factors for multimorbidity in adulthood: A systematic review. Ageing Res Rev 91:102039\u0026ndash;102039. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.arr.2023.102039\u003c/span\u003e\u003cspan address=\"10.1016/j.arr.2023.102039\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSugiyama Y, Mutai R, Aoki T, Matsushima M (2022) Multimorbidity and complex multimorbidity, their prevalence, and associated factors on a remote island in Japan: a cross-sectional study. BMC Prim Care 23(1):258. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12875-022-01860-2\u003c/span\u003e\u003cspan address=\"10.1186/s12875-022-01860-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. /10/03 2022\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHarrison C, Henderson J, Miller G, Britt H (2016) The prevalence of complex multimorbidity in Australia. Aust N Z J Public Health 40(3):239\u0026ndash;244 2016/06/01/. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/1753-6405.12509\u003c/span\u003e\u003cspan address=\"10.1111/1753-6405.12509\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRizzuto D, Melis RJF, Angleman S, Qiu C, Marengoni A (2017) Effect of Chronic Diseases and Multimorbidity on Survival and Functioning in Elderly Adults. J Am Geriatr Soc (JAGS) 65(5):1056\u0026ndash;1060. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/jgs.14868\u003c/span\u003e\u003cspan address=\"10.1111/jgs.14868\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMakovski TT, Schmitz S, Zeegers MP, Stranges S, van den Akker M (2019) Multimorbidity and quality of life: Systematic literature review and meta-analysis. Ageing Res Rev 53:100903\u0026ndash;100903. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.arr.2019.04.005\u003c/span\u003e\u003cspan address=\"10.1016/j.arr.2019.04.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKabir A, Conway DP, Ansari S, Tran A, Rhee JJ, Barr M (2024) Impact of multimorbidity and complex multimorbidity on healthcare utilisation in older Australian adults aged 45 years or more: a large population-based cross-sectional data linkage study. BMJ Open 14(1):e078762. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bmjopen-2023-078762\u003c/span\u003e\u003cspan address=\"10.1136/bmjopen-2023-078762\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIndu PS (2023) Escalating Burden of Noncommunicable Diseases and Multimorbidity: Can Dietary Interventions Make a Difference? Indian J Clin Med 13(2):73\u0026ndash;74. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/26339447231223564\u003c/span\u003e\u003cspan address=\"10.1177/26339447231223564\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcRae MP (Mar 2017) Health Benefits of Dietary Whole Grains: An Umbrella Review of Meta-analyses, (in eng). J Chiropr Med 16(1):10\u0026ndash;18. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jcm.2016.08.008\u003c/span\u003e\u003cspan address=\"10.1016/j.jcm.2016.08.008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang B, Zhao Q, Guo W, Bao W, Wang X (2018) Association of whole grain intake with all-cause, cardiovascular, and cancer mortality: a systematic review and dose\u0026ndash;response meta-analysis from prospective cohort studies. Eur J Clin Nutr 72(1):57\u0026ndash;65. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/ejcn.2017.149\u003c/span\u003e\u003cspan address=\"10.1038/ejcn.2017.149\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchacht SR, Olsen A, Dragsted LO, Overvad K, Tj\u0026oslash;nneland A, Kyr\u0026oslash; C (2021) Whole-Grain Intake and Pancreatic Cancer Risk\u0026mdash;The Danish, Diet, Cancer and Health Cohort. J Nutr 151(3):666\u0026ndash;674. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/jn/nxaa385\u003c/span\u003e\u003cspan address=\"10.1093/jn/nxaa385\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHu Y, Willett WC, Manson JAE, Rosner B, Hu FB, Sun Q (2022) Intake of whole grain foods and risk of coronary heart disease in US men and women. BMC Med 20(1):192\u0026ndash;192. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12916-022-02396-z\u003c/span\u003e\u003cspan address=\"10.1186/s12916-022-02396-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHu H et al (2023) Consumption of whole grains and refined grains and associated risk of cardiovascular disease events and all-cause mortality: a systematic review and dose-response meta-analysis of prospective cohort studies. Am J Clin Nutr 117(1):149\u0026ndash;159. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ajcnut.2022.10.010\u003c/span\u003e\u003cspan address=\"10.1016/j.ajcnut.2022.10.010\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang Y, Feng J, Liu T, Gong Z, Zhuo Q (2024) Association between Whole-Grain Intake and Obesity Defined by Different Anthropometric Indicators and Dose-Response Relationship Analysis among U.S. Adults: A Population-Based Study, \u003cem\u003eNutrients\u003c/em\u003e, vol. 16, no. 14, p. 2373. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/nu16142373\u003c/span\u003e\u003cspan address=\"10.3390/nu16142373\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu Y, Wan Q, Feng J, Du L, Li K, Zhou Y (2018) Whole grain diet reduces systemic inflammation: A meta-analysis of 9 randomized trials. Med (Baltim) 97(43):e12995\u0026ndash;e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/MD.0000000000012995\u003c/span\u003e\u003cspan address=\"10.1097/MD.0000000000012995\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRoager HM et al (2019) Whole grain-rich diet reduces body weight and systemic low-grade inflammation without inducing major changes of the gut microbiome: a randomised cross-over trial, \u003cem\u003eGut\u003c/em\u003e, vol. 68, no. 1, pp. 83\u0026ndash;93. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/gutjnl-2017-314786\u003c/span\u003e\u003cspan address=\"10.1136/gutjnl-2017-314786\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu C, Marques FZ (2022) How dietary fibre, acting via the gut microbiome, lowers blood pressure. Curr Hypertens Rep 24(11):509\u0026ndash;521\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRuel G et al (2014) Association between nutrition and the evolution of multimorbidity: The importance of fruits and vegetables and whole grain products. Clinical Nutr Article vol 33(3):513\u0026ndash;520. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.clnu.2013.07.009\u003c/span\u003e\u003cspan address=\"10.1016/j.clnu.2013.07.009\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePereira BP et al (2020) Food consumption and multimorbidity among noninstitutionalized elderly people in Pelotas, 2014: A cross-sectional study, \u003cem\u003eEpidemiologia e Servicos de Saude\u003c/em\u003e, Article vol. 29, no. 3, Art no. e2019050. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.5123/S1679-49742020000300015\u003c/span\u003e\u003cspan address=\"10.5123/S1679-49742020000300015\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSax Institute (2016) 45 and Up Study \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.saxinstitute.org.au/our-work/45-up-study/\u003c/span\u003e\u003cspan address=\"https://www.saxinstitute.org.au/our-work/45-up-study/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (accessed 2/1/16\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBleicher K et al (2023) Cohort profile update: the 45 and up study. Int J Epidemiol 52(1):e92\u0026ndash;e101\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBanks E et al (2007) Cohort profile: the 45 and up study. Int J Epidemiol 37(5):941\u0026ndash;947\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu X et al (2021) The Joint Effects of Diet and Dietary Supplements in Relation to Obesity and Cardiovascular Disease over a 10-Year Follow-Up: A Longitudinal Study of 69,990 Participants. 13(3):944in Australia, vol\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu X, Ling M, Inglis SC, Hickman L (2020) and D. J. I. j. o. p. h. Parker, Eating and healthy ageing: a longitudinal study on the association between food consumption, memory loss and its comorbidities, pp. 1\u0026ndash;12\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAstell-Burt T, Feng X, Croteau K, Kolt GSJSS, Medicine (2013) Influence of neighbourhood ethnic density, diet and physical activity on ethnic differences in weight status: a study of 214,807 adults in Australia. 93:70\u0026ndash;77\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKabir A, Tran A, Ansari S, Conway DP, Barr M (2022) Impact of multimorbidity and complex multimorbidity on mortality among older Australians aged 45 years and over: a large population-based record linkage study. BMJ open 12(7):e060001\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAustralian Bureau of Statistics Socio-Economic Indexes for Areas. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.abs.gov.au/websitedbs/censushome.nsf/home/seifa\u003c/span\u003e\u003cspan address=\"http://www.abs.gov.au/websitedbs/censushome.nsf/home/seifa\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (accessed\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDing D, Rogers K, van der Ploeg H, Stamatakis E (2015) J. P. m. Bauman, Traditional and emerging lifestyle risk behaviors and all-cause mortality in middle-aged and older adults: evidence from a large population-based Australian cohort. 12(12):e1001917\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAustralian Government (2013) Eat for Health: Australian Dietary Guidelines Providing the Scientific Evidence for Healthier Australian Diets, ed: Commonwealth of Australia. National Health and Medical Research Council Canberra, Australia\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen Q-F et al Global burden of disease and its risk factors for adults aged 70 and older across 204 countries and territories: a comprehensive analysis of the Global Burden of Disease Study 2021, \u003cem\u003eBMC Geriatrics\u003c/em\u003e, vol. 25, no. 1, p. 462, 2025/07/02 2025. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12877-025-06095-1\u003c/span\u003e\u003cspan address=\"10.1186/s12877-025-06095-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhou M, Zhao G, Zeng Y, Zhu J, Cheng F, Liang W (2022) Aging and Cardiovascular Disease: Current Status and Challenges, (in eng), \u003cem\u003eRev Cardiovasc Med\u003c/em\u003e, vol. 23, no. 4, p. 135, Apr \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.31083/j.rcm2304135\u003c/span\u003e\u003cspan address=\"10.31083/j.rcm2304135\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDunford EK, Miles DR, Popkin B, Ng SW Whole Grain and Refined Grains: An Examination of US Household Grocery Store Purchases, (in eng), \u003cem\u003eJ Nutr\u003c/em\u003e, vol. 152, no. 2, pp. 550\u0026ndash;558, Feb 8 2022. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/jn/nxab382\u003c/span\u003e\u003cspan address=\"10.1093/jn/nxab382\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu F, Yin J, Wang J, Xu X (2022) Food for the elderly based on sensory perception: A review, (in eng). Curr Res Food Sci 5:1550\u0026ndash;1558. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.crfs.2022.09.014\u003c/span\u003e\u003cspan address=\"10.1016/j.crfs.2022.09.014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrains \u0026amp; Legumes Nutrition Council (2014) [Online]. Available: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.glnc.org.au/wp-content/uploads/2015/04/Australians-at-Risk-2014-Grains-Legumes-Consumption-Attitudinal-Study.pdf\u003c/span\u003e\u003cspan address=\"https://www.glnc.org.au/wp-content/uploads/2015/04/Australians-at-Risk-2014-Grains-Legumes-Consumption-Attitudinal-Study.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThe (2013) Australian dietary guidelines and recommendations for older Australians, \u003cem\u003eAustralian Journal of General Practice\u003c/em\u003e, vol. 44, pp. 311\u0026ndash;315, 04/22 2015. [Online]. Available: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.racgp.org.au/afp/2015/may/the-2013-australian-dietary-guidelines-and-recomme\u003c/span\u003e\u003cspan address=\"https://www.racgp.org.au/afp/2015/may/the-2013-australian-dietary-guidelines-and-recomme\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSnetselaar LG, de Jesus JM, DeSilva DM, Stoody EE (2021) Dietary Guidelines for Americans, 2020\u0026ndash;2025: Understanding the Scientific Process, Guidelines, and Key Recommendations, (in eng), \u003cem\u003eNutr Today\u003c/em\u003e, vol. 56, no. 6, pp. 287\u0026ndash;295, Nov-Dec \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/nt.0000000000000512\u003c/span\u003e\u003cspan address=\"10.1097/nt.0000000000000512\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e(2019) \u003cem\u003eCanada\u0026rsquo;s Dietary Guidelines\u003c/em\u003e. [Online] Available: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://food-guide.canada.ca/en/guidelines/\u003c/span\u003e\u003cspan address=\"https://food-guide.canada.ca/en/guidelines/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAune D et al (2016) Whole grain consumption and risk of cardiovascular disease, cancer, and all cause and cause specific mortality: systematic review and dose-response meta-analysis of prospective studies, \u003cem\u003ebmj\u003c/em\u003e, vol. 353\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu X, Parker D, Inglis SC, Byles J (2019) Can regular long-term breakfast cereals consumption benefits lower cardiovascular diseases and diabetes risk? A longitudinal population-based study, \u003cem\u003eAnnals of epidemiology\u003c/em\u003e, vol. 37, pp. 43\u0026ndash;50. e3\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrundy MM-L, Fardet A, Tosh SM, Rich GT, Wilde PJ (2018) Processing of oat: the impact on oat's cholesterol lowering effect. Food Funct 9(3):1328\u0026ndash;1343\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDecker EA, Rose DJ, Stewart D (2014) Processing of oats and the impact of processing operations on nutrition and health benefits. Br J Nutr, 112, S2, pp. S58-S64\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFeraco A et al (2024) Assessing gender differences in food preferences and physical activity: a population-based survey. (in eng) Front Nutr 11:1348456. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fnut.2024.1348456\u003c/span\u003e\u003cspan address=\"10.3389/fnut.2024.1348456\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJohar M, Jones G, Savage E (2012) Healthcare expenditure profile of older Australians: evidence from linked survey and health administrative data. Economic Papers: J Appl Econ policy 31(4):451\u0026ndash;463\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":"whole grain, high fiber cereals, multimorbidity, complex multimorbidity, longitudinal study","lastPublishedDoi":"10.21203/rs.3.rs-9182393/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9182393/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eThis study aimed to examine the associations between whole grain and high fiber cereal intake and the risks of heart disease, multimorbidity and complex multimorbidity over 15 years.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe retrospectively analysed data from the 45 and Up Study, spanning the period from 2005 to 2020, with 146,329 individuals aged\u0026thinsp;\u0026ge;\u0026thinsp;45 years followed two follow-up waves across a 15-year period. Whole grain and high fiber cereals and wholemeal bread intake were assessed using a short food frequency questionnaire, and its\u0026rsquo; association with heart disease, multimorbidity, and complex multimorbidity were examined using Generalized Estimating Equation models.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eFemales who consumed whole grain and high fibre cereals had a 12% lower relative risk (RR) of heart disease (RR\u0026thinsp;=\u0026thinsp;0.88; 95% CI: 0.78; 0.99) and a 13% lower risk of complex multimorbidity (RR\u0026thinsp;=\u0026thinsp;0.87; 95% CI: 0.77; 0.97) than non-consumers. Oat cereal consumption was consistently associated with higher disease risk, whereas muesli consumption with lower risk across all outcomes. Participants consuming more than 12 slices of wholemeal bread per week had 13%, 18%, and 17% lower risks of heart disease, multimorbidity, and complex multimorbidity, respectively, compared with those consuming fewer than five slices.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eWhole grain and high fiber cereals were associated with lower risks of heart disease, multimorbidity and complex multimorbidity. Promoting their inclusion in healthy diets may help prevent heart disease and the development of multiple chronic conditions in midlife.\u003c/p\u003e","manuscriptTitle":"Whole grain and high fiber cereals and multimorbidity: A longitudinal study in 146,329 adults aged 45 years and over","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-02 07:07:55","doi":"10.21203/rs.3.rs-9182393/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":"512b73b0-f8ef-48c0-9544-36a75b3fcfc9","owner":[],"postedDate":"April 2nd, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"334179073768228858213421890486842912477","date":"2026-05-11T09:50:43+00:00","index":52,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-02T07:07:55+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-02 07:07:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9182393","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9182393","identity":"rs-9182393","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}