Elevated Risk of Osteoporosis for Vegetarian Modified by Smoking and Milk Consumption

Elevated Risk of Osteoporosis for Vegetarian Modified by Smoking and Milk Consumption | 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 Elevated Risk of Osteoporosis for Vegetarian Modified by Smoking and Milk Consumption Chen-Yang Hsu, Chiew Jan Liew, Feng-Hsi Chen, Hsuan-Chih Chen, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7952087/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 12 You are reading this latest preprint version Abstract Background Vegetarian diets are often linked to health benefits, yet concerns remain regarding potential adverse effects on bone health arising from nutrient deficiencies. Lifestyle factors that can be modified may influence this risk. Methods A cross-sectional study was conducted among adults receiving community health services in Zhunan Township, Taiwan, with a total of 610 participants enrolled. Dietary patterns and lifestyle factors were assessed using structured questionnaires, and bone mineral density was measured. Logistic regression models were applied to evaluate the association between vegetarian diet and osteoporosis, with interaction terms included to examine potential modifying effects of smoking, milk consumption, and coffee consumption. Stratified analyses were performed to further assess the roles of these modifying influences. Results After excluding participants with missing information on dietary pattern or bone mineral density, 573 subjects remained for the final analysis. Vegetarian diet was associated with a significantly higher risk of osteoporosis compared with a non-vegetarian diet with an adjusted odds ratio (aOR) of 3.03 (95% CI: 1.52–6.05). Interaction analysis indicated that smoking (P = 0.0230) and milk consumption (P = 0.0110) significantly modified this association. Among smokers, vegetarians had a substantially higher risk of osteoporosis with an aOR of 48.70 (95% CI: 6.52–363.67). Among those who did not consume milk, the vegetarians also had a greater risk with an aOR of 31.71 (95% CI: 6.72–149.59). Conclusions Vegetarian diet was independently associated with increased risk of osteoporosis, and this risk was particularly elevated among individuals who smoked or did not consume milk. These findings highlight the importance of considering lifestyle factors when evaluating bone health risks in populations adhering to vegetarian diets. Trial registration Not applicable. Vegetarian Osteoporosis Bone mineral density Smoking Milk consumption Risk modifiers Figures Figure 1 BACKGROUND Vegetarian diet has become an increasingly common dietary pattern worldwide, influenced by health consciousness, religious practices such as Buddhism and Taoism, and concerns regarding environmental sustainability. Approximately 1.5 billion individuals, representing about 18 percent of the global population, identify as vegetarians [ 1 ]. The prevalence is particularly high in India (24%), Mexico (19%), and Brazil (14%) [ 2 ]. In Taiwan, about 14% of the population follow a vegetarian diet, largely shaped by religious and cultural traditions [ 3 ]. Vegetarian diets comprise several patterns, including vegan, lacto-vegetarian, ovo-vegetarian, and lacto-ovo-vegetarian, each defined by distinct nutritional profiles and resulting differences in nutrient content and health implications [ 4 ]. Evidence suggests that vegetarian diets are associated with reduced risks of cardiovascular disease, type 2 diabetes, and some neoplastic diseases [ 5 , 6 ]. Despite these advantages, concerns persist regarding nutritional deficiencies. Inadequate intake of calcium, vitamin B12, protein, and iron, nutrients predominantly derived from animal sources, may compromise bone health [ 7 ]. These nutritional imbalances are particularly relevant when vegetarian diets are not appropriately planned or supplemented, potentially increasing susceptibility to osteoporosis. Osteoporosis is a significant public health problem, defined by reduced bone mineral density (BMD) and elevated fracture risk. It affects more than 200 million people worldwide, particularly postmenopausal women and older adults [ 8 , 9 ]. Early detection using tools such as quantitative ultrasound (QUS) and dual-energy X-ray absorptiometry (DEXA) followed by timely intervention is critical to mitigating the burden of disease [ 10 ]. Previous studies examining the association between vegetarian diet and bone health have reported heterogenous findings. Some observed lower BMD among vegetarians, especially in the lumbar spine and femoral neck [ 11 ], whereas others, including a study from Taiwan, found no significant difference between vegetarians and non-vegetarians, though a slightly higher risk of osteoporosis was noted among vegetarians [ 12 ]. Given these heterogenous findings, further research is needed to clarify the association between vegetarian diet and osteoporosis, particularly in populations with a high prevalence of vegetarian practices. This study investigated this association in a community based Taiwanese cohort and evaluated potential effect modification by smoking and milk consumption, aiming to provide evidence that may guide prevention strategies. METHODS Study Design This cross-sectional study was conducted at Daichung Hospital in Zhunan Township, Miaoli County, Taiwan. Zhunan Township has a population of about 91,000 residents, and approximately 10,000 of them are served annually through the hospital. From this population, 610 participants were enrolled in two phases as shown in Fig. 1 , with 350 individuals (121 men and 212 women) in 2019 and 260 individuals (97 men and 159 women) in 2023. Across both phases, the study included 90 vegetarians and 441 non vegetarians. Data collection involved structured questionnaires and medical examination reports. The status of BMD of participants were assessed by using DXA and QUS. Dietary habits were assessed using structured questionnaires administered in 2019 and 2023. Participants were classified according to dietary pattern into a vegetarian group (exposure group) and a non-vegetarian group (reference group). BMD was measured to determine osteoporosis status. A research database was constructed by integrating hospital electronic medical records with community service data, enabling linkage of dietary information with diabetes and osteoporosis assessments to evaluate associations and potential effect modification. Questionnaire A structured questionnaire was developed by the research team for this study to collect information on participants’ personal attributes, dietary habits, lifestyle patterns, family and medical history, health behaviors, and experiences with screening services. The instrument contains detailed items on smoking, alcohol and betel nut use, coffee intake, physical activity, and nutrition-related behaviors. It also includes items addressing chronic health conditions and women’s reproductive history. Additional modules evaluate frailty, fall risk, depressive mood, and participant feedback. Questions related to frailty screening and changes in vegetarian dietary patterns were incorporated. An English version of the questionnaire is provided in Supplementary File 1. Statistical Analysis Logistic regression models were used to assess the association between vegetarian diet and osteoporosis, adjusting for demographic characteristics (age and sex), socioeconomic status (education level), metabolic factors (body mass index (BMI), blood glucose, and lipid profile), and dietary patterns. Both univariable and multivariable analyses were conducted to evaluate the independent effect of vegetarian diet. The logistic regression model for the i th participant was specified as log \(\:\left(\frac{{P}_{i}}{1-{P}_{i}}\right)\) = β 0 + βX i , (1) where P i is the probability of osteoporosis and X i represents the covariates described above, and β denotes the corresponding regression coefficients. The intercept is given by β 0 . The regression model incorporating the main effect and confounders was specified as $$\:\text{l}\text{o}\text{g}\left(\frac{{P}_{i}}{1-{P}_{i}}\right)={\beta\:}_{0}+{\beta\:}_{Veg}\times\:\text{V}\text{e}\text{g}+{\beta\:}_{Age}\times\:\text{A}\text{g}\text{e}+{\beta\:}_{gender}\times\:\text{G}\text{e}\text{n}\text{d}\text{e}\text{r}+{\beta\:}_{Edu}\times\:\text{E}\text{d}\text{u}+{\beta\:}_{BMI}\times\:\text{B}\text{M}\text{I}+$$ \(\:{\beta\:}_{Glucose}\) ×Glucose (2) To assess effect modification, logistic regression models including interaction terms between vegetarian diet and selected risk factors (smoking, milk intake, and coffee consumption) were estimated as $$\:log\left(\frac{P(osteoporosis=1)}{1-P(osteoporosis=1)}\right)={\beta\:}_{0}+{\beta\:}_{1}\times\:\text{a}\text{g}\text{e}1+{\beta\:}_{2}\times\:\text{a}\text{g}\text{e}2+{\beta\:}_{3}\times\:\text{a}\text{g}\text{e}3+{\beta\:}_{4}\times\:\text{s}\text{e}\text{x}+$$ $$\:{\beta\:}_{5}\times\:\text{e}\text{d}\text{u}\text{c}\text{a}\text{t}\text{i}\text{o}\text{n}1+{\beta\:}_{6}\times\:\text{e}\text{d}\text{u}\text{c}\text{a}\text{t}\text{i}\text{o}\text{n}2+{\beta\:}_{7}\times\:\text{c}\text{o}\text{f}\text{f}\text{e}\text{e}+$$ $$\:{\beta\:}_{8}\times\:\text{m}\text{i}\text{l}\text{k}+{\beta\:}_{9}\times\:\text{s}\text{m}\text{o}\text{k}\text{i}\text{n}\text{g}+{\beta\:}_{10}\times\:\text{v}\text{e}\text{g}\text{e}\text{t}\text{a}\text{r}\text{i}\text{a}\text{n}+$$ $$\:{\beta\:}_{11}\times\:(\text{v}\text{e}\text{g}\text{e}\text{t}\text{a}\text{r}\text{i}\text{a}\text{n}\times\:\text{s}\text{m}\text{o}\text{k}\text{i}\text{n}\text{g})\:+{\beta\:}_{12}\times\:(\text{v}\text{e}\text{g}\text{e}\text{t}\text{a}\text{r}\text{i}\text{a}\text{n}\times\:\text{m}\text{i}\text{l}\text{k})\:+\:{\beta\:}_{13}\times\:(\text{v}\text{e}\text{g}\text{e}\text{t}\text{a}\text{r}\text{i}\text{a}\text{n}\times\:\text{c}\text{o}\text{f}\text{f}\text{e}\text{e})$$ 3 Odds ratios (ORs), adjusted odds ratios (aORs), and 95% confidence intervals (CIs) were reported for both the main effects and the interaction terms. A two-sided p-value < 0.05 was considered statistically significant. RESULTS Baseline characteristics of the study population are summarized in Table 1 . The mean age was 59.3 ± 13.3 y. Vegetarians comprised 16.9% of the cohort and were significantly older than non-vegetarians (62.3 ± 13.4 vs. 58.8 ± 13.2 y; P = 0.03). Vegetarians had higher systolic (134.1 ± 22.6 vs. 129.0 ± 20.3 mm Hg; P = 0.05) and diastolic blood pressure (85.9 ± 12.5 vs. 83.0 ± 11.3 mm Hg; P = 0.05) compared with non-vegetarians. Conversely, vegetarians exhibited significantly lower LDL-cholesterol (98.8 ± 25.4 vs. 113.8 ± 32.0 mg/dL; P < 0.001) and total cholesterol concentrations (187.9 ± 34.8 vs. 212.1 ± 43.3 mg/dL; P < 0.001). The T-scores of BMD were significantly lower among vegetarians (− 1.65 ± 1.30 vs. −1.18 ± 1.43; P < 0.001). Vegetarians had lower milk consumption (19.7% vs. 80.3%, P = 0.01) and lower smoking prevalence (7.1% vs. 92.9%, P = 0.01). No significant differences were observed for waist circumference, BMI, triglycerides, HDL cholesterol, fasting glucose, sex, education, coffee consumption, alcohol intake, or betel nut chewing habit. Table 1 Characteristics of study population by vegetarian status Variable Overall* Vegetarian* (N = 90) Non-Vegetarian* (N = 441) p-value Age, yrs 59.31 ± 13.27 62.28 ± 13.36 58.77 ± 13.15 0.03 Waist circumference, cm 84.35 ± 10.74 85.31 ± 10.54 84.33 ± 10.85 0.44 BMI, kg/m2 25.00 ± 4.88 24.47 ± 4.98 25.18 ± 4.99 0.23 Systolic blood pressure, mmHg 129.8 ± 20.80 134.1 ± 22.64 129.0 ± 20.32 0.05 Diastolic blood pressure, mmHg 83.42 ± 11.53 85.88 ± 12.48 83.04 ± 11.28 0.05 Triglyceride, mg/dL 134.1 ± 89.46 141.1 ± 93.10 134.2 ± 90.65 0.53 HDL-Cholesterol, mg/dL 54.68 ± 15.33 52.68 ± 15.36 54.86 ± 15.18 0.24 LDL-Cholesterol, mg/dL 111.5 ± 31.12 98.81 ± 25.40 113.8 ± 31.96 0.00 Total Cholesterol, mg/dL 208.1 ± 42.39 187.9 ± 34.83 212.1 ± 43.30 0.00 Fasting glucose, mg/dL 112.3 ± 43.56 117.3 ± 54.88 111.9 ± 41.95 0.39 BMD, (T score) -1.25 ± 1.41 -1.65 ± 1.30 -1.18 ± 1.43 0.00 Male gender 193 (36.76%) 37(19.17%) 156 (80.83%) 0.26 Education level 508 (100%) 88 (17.32%) 420 (82.68%) 0.61 Junior high school or below 207 (40.75%) 39 (18.84%) 168 (81.16%) Senior high school 147 (28.94%) 26 (17.69%) 121 (82.31%) College or above 154 (30.31%) 23 (14.94%) 131 (85.06%) Milk, Yes vs. No 375 (71.16%) 74 (19.73%) 301 (80.27%) 0.01 Coffee, Yes vs. No 303 (57.82%) 49 (16.17%) 254 (83.83%) 0.48 Alcohol drinking, Yes/Ever vs. Never 121 (23.14%) 15 (12.40%) 106 (87.60%) 0.12 Smoking, Yes vs. No 84 (15.91%) 6 (7.14%) 78 (92.86%) 0.01 Betel nuts, Yes vs. No 30 (5.68%) 3 (10.00%) 27 (90.00%) 0.30 * Values are presented as Mean ± SD or Frequency (%). Seventy-nine participants with missing information on vegetarian status were excluded from this analysis. Characteristics stratified by BMD status are presented in Table 2 . Participants with osteoporosis (T-score ≤ − 2.5) were significantly older (67.3 ± 9.7 vs. 57.3 ± 13.3 y; P < 0.001), had lower waist circumference (82.0 ± 10.2 vs. 84.7 ± 10.8 cm; P = 0.02), and lower BMI (23.5 ± 3.6 vs. 25.3 ± 5.1 kg/m²; P < 0.001) compared with those with normal BMD. They also had higher systolic blood pressure (134.0 ± 21.3 vs. 128.8 ± 20.7 mmHg, P = 0.02) and modestly higher HDL cholesterol (57.7 ± 16.7 vs. 54.1 ± 14.8 mg/dL, P = 0.05). The osteoporosis group included a smaller proportion of males (13.4% vs. 86.6%, P < 0.001) and individuals with college or higher education (9.9% vs. 90.1%, P < 0.001). No significant differences were observed for other metabolic or behavioral variables. Table 2 Characteristics of study population by Bone mineral density (BMD) levels Variables (Mean ± SD) BMD T score >-2.5* (N = 461) BMD T score ≤ -2.5* (N = 112) p-value Age, yrs 57.30 ± 13.30 67.26 ± 9.68 < 0.01 Waist circumference, cm 84.74 ± 10.80 82.03 ± 10.15 0.02 BMI, kg/m2 25.28 ± 5.11 23.52 ± 3.63 < 0.01 Systolic blood pressure, mmHg 128.8 ± 20.70 134.0 ± 21.25 0.02 Diastolic blood pressure, mmHg 83.60 ± 11.87 83.16 ± 10.32 0.69 Triglyceride, mg/dL 135.1 ± 88.70 124.6 ± 84.58 0.27 HDL-Cholesterol, mg/dL 54.07 ± 14.75 57.68 ± 16.68 0.05 LDL-Cholesterol, mg/dL 111.9 ± 31.42 111.1 ± 30.58 0.81 Total Cholesterol, mg/dL 207.4 ± 42.36 211.9 ± 43.67 0.35 Fasting glucose, mg/dL 110.3 ± 39.54 115.3 ± 44.68 0.30 BMD, (T score) -0.86 ± 1.23 -2.88 ± 0.82 < 0.01 Male gender 181 (86.60%) 28 (13.40%) < 0.01 Education 409 (81.15%) 95 (18.85%) < 0.01 Junior high school or below 146 (71.22%) 59 (28.78%) Senior high school 127 (85.81%) 21 (14.19%) College or above 136 (90.07%) 15 (9.93%) Coffee, Yes vs. No 245 (83.05%) 50 (16.95%) 0.12 Milk, Yes vs. No 303 (82.56%) 64 (17.44%) 0.13 Alcohol drinking, Quit/Yes vs. Never 105 (86.78%) 16 (13.22%) 0.06 Smoking, Yes vs. No 72 (85.71%) 12 (14.29%) 0.19 Betel nuts, Yes vs. No 23 (82.14%) 5 (17.86%) 0.86 * Values are presented as Mean ± SD or Frequency (%). Thirty-seven participants with missing information on BMD level were excluded from this analysis. Logistic regression analyses of factors associated with osteoporosis are presented in Table 3 . In univariate models, vegetarian diet was associated with higher odds of osteoporosis (OR, 1.77; 95% CI, 1.04–3.02). Older age increased risk (OR per year, 1.08; 95% CI, 1.05–1.10), whereas male sex (OR, 0.51; 95% CI, 0.32–0.81) and higher BMI (OR, 0.48; 95% CI, 0.31–0.73) were protective. Diabetes was also associated with greater odds (OR, 1.71; 95% CI, 1.10–2.67). Other factors, including hypertension, lipid profiles, alcohol use, smoking, betel nut chewing, milk intake, and coffee consumption, were not significant. In the fully adjusted model (Model 3), vegetarian diet remained independently associated with osteoporosis (aOR, 3.03; 95% CI, 1.52–6.05). Age (aOR per year, 1.12; 95% CI, 1.08–1.15), male sex (aOR, 0.14; 95% CI, 0.06–0.31), and BMI (aOR, 0.43; 95% CI, 0.24–0.78) remained significant predictors, while milk consumption was inversely associated with osteoporosis (aOR, 0.42; 95% CI, 0.23–0.77). Table 3 Estimated results on risk of osteoporosis Variables Univariable Analysis Multivariable Analysis* OR 95% C.I. aOR 95% C.I. Age, yrs 1.08 (1.05 , 1.10) 1.12 (1.08 , 1.15) Male gender, Male vs. Female 0.51 (0.32 , 0.81) 0.14 (0.06 , 0.31) Body mass index, kg/m2 0.48 (0.31 , 0.73) 0.43 (0.24 , 0.78) Hypertension, Yes vs. No 1.40 (0.92, 2.15) 1.07 (0.59, 1.95) Diabetes, Yes vs. No 1.71 (1.10 , 2.67) 1.81 (0.99, 3.31) HDL level, Low vs. High 0.68 (0.41, 1.14) 0.56 (0.29, 1.08) Alcohol drinking, Quit / Yes vs. Never 0.58 (0.33, 1.04) 1.39 (0.57, 3.40) Smoking, Yes vs. No 0.65 (0.34, 1.25) 1.58 (0.48, 5.22) Betel nuts, Yes vs. No 0.92 (0.34, 2.47) 1.74 (0.33, 9.24) Milk, Yes vs. No 0.70 (0.44, 1.11) 0.42 (0.23 , 0.77) Coffee Drinking, Yes vs. No 0.71 (0.46, 1.10) 1.14 (0.64, 2.03) Vegetarian, Yes vs. No 1.77 (1.04 , 3.02) 3.03 (1.52 , 6.05) LDL level, High vs. Normal 0.99 (0.60, 1.62) Total cholesterol, High vs. Normal 1.46 (0.94, 2.28) Triglyceride, High vs. Normal 0.76 (0.46, 1.25) * Multivariable analyses were adjusted for all covariates listed in the table. Variables with statistically significant associations are shown in bold. Low high-density lipoprotein cholesterol (HDL-C) was defined as < 40 mg/dL in men and < 50 mg/dL in women. Thirty-seven participants without information on BMD status were excluded from this analysis. Interaction analyses between vegetarian diet and lifestyle factors are shown in Table 4 . Smoking significantly modified the association of vegetarian and osteoporosis. Among smokers, vegetarians had markedly higher odds of osteoporosis (aOR, 48.70; 95% CI, 6.52-363.67), whereas among non-smokers the association was weaker but remained significant (aOR, 3.17; 95% CI, 1.45–6.90; P for interaction = 0.023). Milk consumption also acted as an effect modifier. The association between vegetarian and osteoporosis was stronger in participants without the habit of milk consumption (aOR, 31.71; 95% CI, 6.72-149.59) compared with participants with the habit of milk consumers (aOR, 4.86; 95% CI, 1.63–14.52; P for interaction = 0.011). Coffee consumption did not significantly modify the association, although effect estimates were higher among non-coffee drinkers (OR, 17.97; 95% CI, 4.61–70.03) than coffee drinkers (OR, 8.58; 95% CI, 2.36–31.22; P for interaction = 0.357). Table 4 Stratified analysis of the association between osteoporosis risk and vegetarian diet Stratification Vegetarian Vegetarian vs. non-Vagetarian P-value for interaction aOR 95% C.I. Smoking Yes 48.70 (6.52, 363.67) 0.0230 No 3.17 (1.45, 6.90) Milk Yes 4.86 (1.63, 14.52) 0.0110 No 31.71 (6.72, 149.59) Coffee Yes 8.58 (2.50, 29.42) 0.3571 No 17.97 (4.61, 70.03) *Multivariable analyses were adjusted for age, sex, educational level, smoking status, milk intake, and coffee consumption. Participants with missing information on vegetarian status (n = 79) or BMD status (n = 37) were excluded from the analysis. DISCUSSION Main findings In this cross-sectional study of a community-based population (17% vegetarians, 20% with osteoporosis), vegetarian diet was associated with a threefold higher risk of osteoporosis (aOR, 3.03; 95% CI, 1.52–6.05). Smoking significantly amplified this association, with vegetarians who smoked demonstrating substantially greater risk compared with non-smokers ( P for interaction = 0.023). In contrast, milk consumption attenuated the association, with stronger protective effects observed among participants reporting higher intake ( P for interaction = 0.011). These findings suggest that increased milk consumption and smoking cessation may help reduce osteoporosis risk in vegetarians. In line with prior research, age, sex, and educational attainment were significant predictors of osteoporosis. Older adults and women were at greater risk, with risk rising progressively with age. Women additionally experience a higher incidence of fractures, with approximately half of women over 50 sustaining a fracture compared with about one fifth of men, reflecting a 2.5-fold higher risk [ 13 ]. This disparity is largely explained by accelerated bone loss after menopause, driven by a decline in estrogen. Peak bone mass in women typically occurs between 36 and 40 years of age. Prior to menopause, women lose about 0.67% of bone mass per year, whereas postmenopausal women lose approximately 2.54% annually [ 14 ]. These findings highlight the importance of targeted bone health strategies in women, particularly after menopause, to prevent osteoporosis and related fractures. Comparison with Previous Studies Several studies have investigated the relationship between vegetarian diet and osteoporosis, yet the association remains inconclusive. A cross-sectional study in Taiwan reported no significant difference in BMD between vegetarians and non-vegetarians [ 12 ], and an Australian study found similar BMD between plant- based and meat-based diets [ 15 ]. A prospective study in Vietnam likewise observed no significant effect of a vegan diet on bone loss or fracture risk [ 16 ], and a study of Taiwanese adults published in the Tzu Chi Medical Journal found no association between vegetarian diet and age-related BMD decline [ 17 ]. In contrast, a prospective study of 258 postmenopausal Taiwanese vegetarian women showed that long term adherence to a vegan diet was associated with a higher risk of femoral neck osteopenia (OR, 3.94; 95% CI, 1.21–12.82) [ 18 ]. Similarly, a retrospective hospital-based analysis reported that vegetarian women aged 40–55 years experienced greater reductions in lumbar spine BMD ( P < 0.001) and femoral neck BMD ( P = 0.015) over three years compared with non-vegetarians, a pattern not observed in other age groups [ 19 ]. Furthermore, a meta-analysis of nine studies found that vegetarians had approximately 4% lower BMD (95% CI, 2%–7%) at both the femoral neck and lumbar spine compared with omnivores [ 20 ]. Possible Mechanisms Linking Vegetarian diet and Osteoporosis In this study, vegetarians had a higher risk of osteoporosis, likely related to imbalanced nutrient intake, such as insufficient calcium and vitamin D, which are essential for bone health. This deficiency may reflect limited animal protein and calcium sources in vegetarian diets. Although some studies have suggested a protective effect of plant-based diets, our findings highlight potential nutritional challenges for vegetarians in maintaining bone health. Low consumption of soy products and dairy was associated with greater osteoporosis risk. This observation is consistent with previous reports showing that strict vegans, who typically have lower calcium intake, are at higher fracture risk [ 21 ]. Soy and dairy provide calcium, protein, and isoflavones [ 11 ], all of which contribute to BMD [ 22 ]. Adequate calcium intake is therefore critical to osteoporosis prevention. Our analysis further demonstrated that vegetarian diet remained an independent predictor of osteoporosis after multivariable adjustment. These results align with prior research in southern Taiwan among postmenopausal Buddhist nuns and practitioners, where long term vegan diets were associated with increased risk of lumbar spine fractures and osteoporosis classification [ 18 ]. Together, these findings support a potential link between vegetarian dietary patterns and bone health. In addition to diet, age, sex, and education were significant predictors of osteoporosis. Consistent with prior studies, older adults and women were at higher risk, with women experiencing approximately 2.5 times more fractures than men after the age of 50 [ 13 ]. This disparity is largely explained by accelerated bone loss after menopause due to estrogen deficiency. Women reach peak bone mass between 36 and 40 years of age, losing about 0.67% of bone mass annually before menopause, compared with 2.54% per year afterward [ 14 ]. These results underscore the importance of targeted bone health strategies in women, particularly after menopause, to prevent osteoporosis and related fractures. Effect modification of the association between vegetarian diet and osteoporosis by lifestyle factors The influence of vegetarian diet on osteoporosis risk may be modified by individual characteristics and lifestyle factors. In this study, interaction analyses revealed significant effect modification by milk consumption, coffee consumption, and smoking. Stratified analyses showed that vegetarians without the habit of milk consumption had a substantially higher risk of osteoporosis (aOR, 31.71), and those who did not consume coffee also faced elevated risk (aOR, 17.97). Smoking had the strongest interaction, with vegetarian smokers exhibiting a substantial increased risk of osteoporosis (aOR, 48.70). These results highlight the complex interplay between diet and lifestyle in shaping bone health. Prior studies support these findings. Nicotine and cigarette smoke have been shown to impair bone remodeling and repair, establishing smoking as a major risk factor for low BMD [ 23 ]. Milk provides proteins, minerals, and vitamins critical for bone health, and low intake during childhood has been linked to a twofold increase in fracture risk [ 24 ]. National data from Korea further demonstrated that frequent milk consumption may reduce osteoporosis incidence in adults [ 25 ]. Coffee, through its antioxidant properties, has been reported to inhibit osteoclast formation and lower osteoporosis risk [ 26 ]. Together, these mechanisms suggest that milk and coffee may exert protective effects on bone metabolism, whereas smoking accelerates bone deterioration. Strengths and Limitations This study has several strengths. First, it included both vegetarians and non- vegetarians from a community setting, enhancing representativeness and external validity. The inclusion of a diverse participant pool supports broader generalizability of the findings. Second, multiple health related factors, including age, sex, smoking, and alcohol use, were comprehensively considered in the analysis, which minimized potential confounding and improved the robustness of the results. Several limitations should also be acknowledged. The cross-sectional design precludes causal inference, and the associations observed may be affected by unmeasured factors or reverse causation, such as individuals with preexisting health conditions adopting vegetarian diets. Prospective longitudinal studies with repeated measurements of BMD, diet, and lifestyle factors are needed to clarify causal pathways. Recall bias may also have influenced self-reported dietary information. The relatively small number of vegetarians limits statistical power and may reduce the stability and generalizability of the results. Furthermore, although the study provided preliminary insights into the relationship between vegetarian diet and osteoporosis, it did not address other health outcomes of vegetarian diets, and further research is warranted, particularly in subgroups such as individuals with diabetes. CONCLUSION This study demonstrated that vegetarian diet was positively associated with osteoporosis risk, and this relationship was further modified by smoking, milk consumption, and coffee consumption. Abbreviations BMD Bone Mineral Density aOR Adjusted odds ratio BMI Body mass index CI Confidence interval DEXA Dual-energy X-ray absorptiometry HDL High-density lipoprotein LDL Low-density lipoprotein OR Odds ratio Declarations Ethics approval and consent to participate This study was approved by the Joint Institutional Review Board of Taipei Medical University (TMU-JIRB No. N202103060) and Daichung Hospital, Miaoli, Taiwan. Written informed consent was obtained from all participants prior to study enrollment, and all procedures were conducted in accordance with Good Clinical Practice (GCP) guidelines and the principles of the Declaration of Helsinki. Consent for publication Not applicable. Availability of data and materials The datasets generated and/or analyzed during the current study are not publicly available due to institutional regulations but are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding No specific funding was received for this research. Authors’ contributions C-J Liew, C-Y Hsu, and S-Y Chuang contributed to data collection, analysis, and drafting the manuscript. F-H Chen, H-C Chen, A M-F Yen conceived the study, C-Y Hsu and S-Y Chuang supervised the research process, and is the guarantor of the work. All authors read and approved the final manuscript. Acknowledgements The authors would like to express their gratitude to Mrs Hui-Lan Chen, Daichung hospital, for her support and encouragement, and to Mr Kuang-Chun Ku, Daichung hospital, for his valuable assistance with administrative coordination and data collection. Authors’ information 1 Daichung Hospital, Miaoli, Taiwan. 2 Master of Public Health Program, College of Public Health, National Taiwan University, Taipei, Taiwan. 3 Institute of Population Health Sciences, National Health Research Institutes, Miaoli, Taiwan. 4 School of Oral Hygiene, College of Oral Medicine, Taipei Medical University, Taipei, Taiwan. 5 Taiwan Association of Medical Screening, Taipei, Taiwan. References Leahy E, Lyons S, Tol RSJ. An estimate of the number of vegetarians in the world. ESRI Working Paper No. 340. 2010. World Population Review. Vegetarianism by country 2024. https://worldpopulationreview.com/country-rankings/vegetarianism-by-country/ . Accessed May 2024. 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Br Med Bull. 2020;133(1):105–17. 10.1093/bmb/ldaa005 . Cotts KG, Cifu AS. Treatment of osteoporosis. JAMA. 2018;319(10):1040–1. 10.1001/jama.2018.0001 . Sözen T, Özışık L, Başaran NÇ. An overview and management of osteoporosis. Eur J Rheumatol. 2017;4(1):46–56. 10.5152/eurjrheum.2016.048 . Iguacel I, Miguel-Berges ML, Gómez-Bruton A, Moreno LA, Julián C. Veganism, vegetarianism, bone mineral density, and fracture risk: a systematic review and meta-analysis. Nutr Rev. 2019;77(1):1–18. 10.1093/nutrit/nuy045 . Wang YF, Chiu JS, Chuang MH, Hsieh YJ, Huang YC, Lin CC, et al. Bone mineral density of vegetarian and non-vegetarian adults in Taiwan. Asia Pac J Clin Nutr. 2008;17(1):101–6. Guggenbuhl P. Osteoporosis in males and females: is there really a difference? Joint Bone Spine. 2009;76(6):595–601. 10.1016/j.jbspin.2009.08.002 . Yang TS, Chen CH, Chen RM, Lin KC, Chao TY, Chen HS, et al. Osteoporosis: prevalence in Taiwanese women. Osteoporos Int. 2004;15(5):345–7. 10.1007/s00198-003-1554-8 . Austin G, Ferguson JJA, Eslick S, Nisa M, Manson J, Eslick EM, et al. Bone mineral density and body composition in Australians following plant-based diets vs regular meat diets. Front Nutr. 2024;11:1411003. 10.3389/fnut.2024.1411003 . Ho-Pham LT, Vu BQ, Lai TQ, Nguyen ND, Nguyen TV. Vegetarianism, bone loss, fracture and vitamin D: a longitudinal study in Asian vegans and non-vegans. Eur J Clin Nutr. 2012;66(1):75–82. 10.1038/ejcn.2011.165 . Chuang TL, Lin CH, Wang YF. Effects of vegetarian diet on bone mineral density. Tzu Chi Med J. 2020;33(2):128–34. 10.4103/tcmj.tcmj_84_20 . Chiu JF, Lan SJ, Yang CY, Chen CJ, Sung FC, Lin RS, et al. Long-term vegetarian diet and bone mineral density in postmenopausal Taiwanese women. Calcif Tissue Int. 1997;60(3):245–9. 10.1007/PL00005812 . Chuang TL, Lin YL, Wu CH, Chen YC, Lin YC, Lin YT, et al. Association between vegetarian diets and bone mineral density: a retrospective study from a teaching hospital in Taiwan. Int J Environ Res Public Health. 2022;19(4):2361. 10.3390/ijerph19042361 . Ho-Pham LT, Nguyen ND, Nguyen TV. Effect of vegetarian diets on bone mineral density: a Bayesian meta-analysis. Am J Clin Nutr. 2009;90(4):943–50. 10.3945/ajcn.2009.27521 . Appleby P, Roddam A, Allen N, Key T. Comparative fracture risk in vegetarians and nonvegetarians in EPIC-Oxford. Eur J Clin Nutr. 2007;61(12):1400–6. 10.1038/sj.ejcn.1602659 . Zhu K, Prince RL. Calcium and bone. Clin Biochem. 2012;45(12):936–42. 10.1016/j.clinbiochem.2012.05.006 . Yoon V, Maalouf NM, Sakhaee K. The effects of smoking on bone metabolism. Osteoporos Int. 2012;23(8):2081–92. 10.1007/s00198-011-1814-z . Ratajczak AE, Rychter AM, Zawada A, Dobrowolska A, Krela-Kaźmierczak I. Milk and dairy products: good or bad for human bone? Nutrients. 2021;13(4):1329. 10.3390/nu13041329 . Kim JS, Oh SW, Kim J, Lee CM, Chung JO, Kwon H, et al. Milk consumption and bone mineral density in adults: using data from the Korea National Health and Nutrition Examination Survey 2008–2011. Korean J Fam Med. 2021;42(3):327–33. 10.4082/kjfm.20.0182 . Choi E, Park SM, Cho MH, Lee JS, Lee J. The benefit of bone health by drinking coffee among Korean postmenopausal women: a cross-sectional analysis of the fourth and fifth Korea National Health and Nutrition Examination Surveys. PLoS ONE. 2016;11(1):e0147762. 10.1371/journal.pone.0147762 . Additional Declarations No competing interests reported. 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1","display":"","copyAsset":false,"role":"figure","size":109394,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlowchart of participant recruitment and study design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003csup\u003e* \u003c/sup\u003eThirty-seven subjects without BMD information\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7952087/v1/1ee22abf6a17611a868ccc36.jpg"},{"id":97370265,"identity":"d59e27a9-d4c2-426a-92ac-7959e72625c9","added_by":"auto","created_at":"2025-12-03 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common dietary pattern worldwide, influenced by health consciousness, religious practices such as Buddhism and Taoism, and concerns regarding environmental sustainability. Approximately 1.5\u0026nbsp;billion individuals, representing about 18 percent of the global population, identify as vegetarians [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The prevalence is particularly high in India (24%), Mexico (19%), and Brazil (14%) [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In Taiwan, about 14% of the population follow a vegetarian diet, largely shaped by religious and cultural traditions [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Vegetarian diets comprise several patterns, including vegan, lacto-vegetarian, ovo-vegetarian, and lacto-ovo-vegetarian, each defined by distinct nutritional profiles and resulting differences in nutrient content and health implications [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eEvidence suggests that vegetarian diets are associated with reduced risks of cardiovascular disease, type 2 diabetes, and some neoplastic diseases [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Despite these advantages, concerns persist regarding nutritional deficiencies. Inadequate intake of calcium, vitamin B12, protein, and iron, nutrients predominantly derived from animal sources, may compromise bone health [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. These nutritional imbalances are particularly relevant when vegetarian diets are not appropriately planned or supplemented, potentially increasing susceptibility to osteoporosis.\u003c/p\u003e\u003cp\u003eOsteoporosis is a significant public health problem, defined by reduced bone mineral density (BMD) and elevated fracture risk. It affects more than 200\u0026nbsp;million people worldwide, particularly postmenopausal women and older adults [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Early detection using tools such as quantitative ultrasound (QUS) and dual-energy X-ray absorptiometry (DEXA) followed by timely intervention is critical to mitigating the burden of disease [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Previous studies examining the association between vegetarian diet and bone health have reported heterogenous findings. Some observed lower BMD among vegetarians, especially in the lumbar spine and femoral neck [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], whereas others, including a study from Taiwan, found no significant difference between vegetarians and non-vegetarians, though a slightly higher risk of osteoporosis was noted among vegetarians [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eGiven these heterogenous findings, further research is needed to clarify the association between vegetarian diet and osteoporosis, particularly in populations with a high prevalence of vegetarian practices. This study investigated this association in a community based Taiwanese cohort and evaluated potential effect modification by smoking and milk consumption, aiming to provide evidence that may guide prevention strategies.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design\u003c/h2\u003e\u003cp\u003eThis cross-sectional study was conducted at Daichung Hospital in Zhunan Township, Miaoli County, Taiwan. Zhunan Township has a population of about 91,000 residents, and approximately 10,000 of them are served annually through the hospital. From this population, 610 participants were enrolled in two phases as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, with 350 individuals (121 men and 212 women) in 2019 and 260 individuals (97 men and 159 women) in 2023. Across both phases, the study included 90 vegetarians and 441 non vegetarians. Data collection involved structured questionnaires and medical examination reports. The status of BMD of participants were assessed by using DXA and QUS.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eDietary habits were assessed using structured questionnaires administered in 2019 and 2023. Participants were classified according to dietary pattern into a vegetarian group (exposure group) and a non-vegetarian group (reference group). BMD was measured to determine osteoporosis status. A research database was constructed by integrating hospital electronic medical records with community service data, enabling linkage of dietary information with diabetes and osteoporosis assessments to evaluate associations and potential effect modification.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eQuestionnaire\u003c/h3\u003e\n\u003cp\u003eA structured questionnaire was developed by the research team for this study to collect information on participants\u0026rsquo; personal attributes, dietary habits, lifestyle patterns, family and medical history, health behaviors, and experiences with screening services. The instrument contains detailed items on smoking, alcohol and betel nut use, coffee intake, physical activity, and nutrition-related behaviors. It also includes items addressing chronic health conditions and women\u0026rsquo;s reproductive history. Additional modules evaluate frailty, fall risk, depressive mood, and participant feedback. Questions related to frailty screening and changes in vegetarian dietary patterns were incorporated. An English version of the questionnaire is provided in Supplementary File 1.\u003c/p\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eLogistic regression models were used to assess the association between vegetarian diet and osteoporosis, adjusting for demographic characteristics (age and sex), socioeconomic status (education level), metabolic factors (body mass index (BMI), blood glucose, and lipid profile), and dietary patterns. Both univariable and multivariable analyses were conducted to evaluate the independent effect of vegetarian diet. The logistic regression model for the \u003cem\u003ei\u003c/em\u003eth participant was specified as\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003elog\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\left(\\frac{{P}_{i}}{1-{P}_{i}}\\right)\\)\u003c/span\u003e\u003c/span\u003e\u0026thinsp;=\u0026thinsp;β\u003csub\u003e0\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;\u003cb\u003eβX\u003c/b\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e, (1)\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ewhere \u003cem\u003eP\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e is the probability of osteoporosis and \u003cb\u003eX\u003c/b\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e represents the covariates described above, and \u003cb\u003eβ\u003c/b\u003e denotes the corresponding regression coefficients. The intercept is given by β\u003csub\u003e0\u003c/sub\u003e.\u003c/p\u003e\u003cp\u003eThe regression model incorporating the main effect and confounders was specified as\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:\\text{l}\\text{o}\\text{g}\\left(\\frac{{P}_{i}}{1-{P}_{i}}\\right)={\\beta\\:}_{0}+{\\beta\\:}_{Veg}\\times\\:\\text{V}\\text{e}\\text{g}+{\\beta\\:}_{Age}\\times\\:\\text{A}\\text{g}\\text{e}+{\\beta\\:}_{gender}\\times\\:\\text{G}\\text{e}\\text{n}\\text{d}\\text{e}\\text{r}+{\\beta\\:}_{Edu}\\times\\:\\text{E}\\text{d}\\text{u}+{\\beta\\:}_{BMI}\\times\\:\\text{B}\\text{M}\\text{I}+$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\beta\\:}_{Glucose}\\)\u003c/span\u003e\u003c/span\u003e\u0026times;Glucose (2)\u003c/p\u003e\u003cp\u003eTo assess effect modification, logistic regression models including interaction terms between vegetarian diet and selected risk factors (smoking, milk intake, and coffee consumption) were estimated as\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:log\\left(\\frac{P(osteoporosis=1)}{1-P(osteoporosis=1)}\\right)={\\beta\\:}_{0}+{\\beta\\:}_{1}\\times\\:\\text{a}\\text{g}\\text{e}1+{\\beta\\:}_{2}\\times\\:\\text{a}\\text{g}\\text{e}2+{\\beta\\:}_{3}\\times\\:\\text{a}\\text{g}\\text{e}3+{\\beta\\:}_{4}\\times\\:\\text{s}\\text{e}\\text{x}+$$\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equc\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equc\" name=\"EquationSource\"\u003e\n$$\\:{\\beta\\:}_{5}\\times\\:\\text{e}\\text{d}\\text{u}\\text{c}\\text{a}\\text{t}\\text{i}\\text{o}\\text{n}1+{\\beta\\:}_{6}\\times\\:\\text{e}\\text{d}\\text{u}\\text{c}\\text{a}\\text{t}\\text{i}\\text{o}\\text{n}2+{\\beta\\:}_{7}\\times\\:\\text{c}\\text{o}\\text{f}\\text{f}\\text{e}\\text{e}+$$\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equd\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equd\" name=\"EquationSource\"\u003e\n$$\\:{\\beta\\:}_{8}\\times\\:\\text{m}\\text{i}\\text{l}\\text{k}+{\\beta\\:}_{9}\\times\\:\\text{s}\\text{m}\\text{o}\\text{k}\\text{i}\\text{n}\\text{g}+{\\beta\\:}_{10}\\times\\:\\text{v}\\text{e}\\text{g}\\text{e}\\text{t}\\text{a}\\text{r}\\text{i}\\text{a}\\text{n}+$$\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:{\\beta\\:}_{11}\\times\\:(\\text{v}\\text{e}\\text{g}\\text{e}\\text{t}\\text{a}\\text{r}\\text{i}\\text{a}\\text{n}\\times\\:\\text{s}\\text{m}\\text{o}\\text{k}\\text{i}\\text{n}\\text{g})\\:+{\\beta\\:}_{12}\\times\\:(\\text{v}\\text{e}\\text{g}\\text{e}\\text{t}\\text{a}\\text{r}\\text{i}\\text{a}\\text{n}\\times\\:\\text{m}\\text{i}\\text{l}\\text{k})\\:+\\:{\\beta\\:}_{13}\\times\\:(\\text{v}\\text{e}\\text{g}\\text{e}\\text{t}\\text{a}\\text{r}\\text{i}\\text{a}\\text{n}\\times\\:\\text{c}\\text{o}\\text{f}\\text{f}\\text{e}\\text{e})$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e3\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eOdds ratios (ORs), adjusted odds ratios (aORs), and 95% confidence intervals (CIs) were reported for both the main effects and the interaction terms. A two-sided p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eBaseline characteristics of the study population are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The mean age was 59.3\u0026thinsp;\u0026plusmn;\u0026thinsp;13.3 y. Vegetarians comprised 16.9% of the cohort and were significantly older than non-vegetarians (62.3\u0026thinsp;\u0026plusmn;\u0026thinsp;13.4 vs. 58.8\u0026thinsp;\u0026plusmn;\u0026thinsp;13.2 y; P\u0026thinsp;=\u0026thinsp;0.03). Vegetarians had higher systolic (134.1\u0026thinsp;\u0026plusmn;\u0026thinsp;22.6 vs. 129.0\u0026thinsp;\u0026plusmn;\u0026thinsp;20.3 mm Hg; P\u0026thinsp;=\u0026thinsp;0.05) and diastolic blood pressure (85.9\u0026thinsp;\u0026plusmn;\u0026thinsp;12.5 vs. 83.0\u0026thinsp;\u0026plusmn;\u0026thinsp;11.3 mm Hg; P\u0026thinsp;=\u0026thinsp;0.05) compared with non-vegetarians. Conversely, vegetarians exhibited significantly lower LDL-cholesterol (98.8\u0026thinsp;\u0026plusmn;\u0026thinsp;25.4 vs. 113.8\u0026thinsp;\u0026plusmn;\u0026thinsp;32.0 mg/dL; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and total cholesterol concentrations (187.9\u0026thinsp;\u0026plusmn;\u0026thinsp;34.8 vs. 212.1\u0026thinsp;\u0026plusmn;\u0026thinsp;43.3 mg/dL; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The T-scores of BMD were significantly lower among vegetarians (\u0026minus;\u0026thinsp;1.65\u0026thinsp;\u0026plusmn;\u0026thinsp;1.30 vs. \u0026minus;1.18\u0026thinsp;\u0026plusmn;\u0026thinsp;1.43; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Vegetarians had lower milk consumption (19.7% vs. 80.3%, P\u0026thinsp;=\u0026thinsp;0.01) and lower smoking prevalence (7.1% vs. 92.9%, P\u0026thinsp;=\u0026thinsp;0.01). No significant differences were observed for waist circumference, BMI, triglycerides, HDL cholesterol, fasting glucose, sex, education, coffee consumption, alcohol intake, or betel nut chewing habit.\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\u003eCharacteristics of study population by vegetarian status\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=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOverall*\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eVegetarian*\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;90)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon-Vegetarian*\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;441)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge, yrs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e59.31\u0026thinsp;\u0026plusmn;\u0026thinsp;13.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e62.28\u0026thinsp;\u0026plusmn;\u0026thinsp;13.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e58.77\u0026thinsp;\u0026plusmn;\u0026thinsp;13.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWaist circumference, cm\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e84.35\u0026thinsp;\u0026plusmn;\u0026thinsp;10.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e85.31\u0026thinsp;\u0026plusmn;\u0026thinsp;10.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e84.33\u0026thinsp;\u0026plusmn;\u0026thinsp;10.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.44\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI, kg/m2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25.00\u0026thinsp;\u0026plusmn;\u0026thinsp;4.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24.47\u0026thinsp;\u0026plusmn;\u0026thinsp;4.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e25.18\u0026thinsp;\u0026plusmn;\u0026thinsp;4.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.23\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSystolic blood pressure, mmHg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e129.8\u0026thinsp;\u0026plusmn;\u0026thinsp;20.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134.1\u0026thinsp;\u0026plusmn;\u0026thinsp;22.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e129.0\u0026thinsp;\u0026plusmn;\u0026thinsp;20.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiastolic blood pressure, mmHg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e83.42\u0026thinsp;\u0026plusmn;\u0026thinsp;11.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e85.88\u0026thinsp;\u0026plusmn;\u0026thinsp;12.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e83.04\u0026thinsp;\u0026plusmn;\u0026thinsp;11.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTriglyceride, mg/dL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e134.1\u0026thinsp;\u0026plusmn;\u0026thinsp;89.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e141.1\u0026thinsp;\u0026plusmn;\u0026thinsp;93.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e134.2\u0026thinsp;\u0026plusmn;\u0026thinsp;90.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.53\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHDL-Cholesterol, mg/dL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e54.68\u0026thinsp;\u0026plusmn;\u0026thinsp;15.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52.68\u0026thinsp;\u0026plusmn;\u0026thinsp;15.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e54.86\u0026thinsp;\u0026plusmn;\u0026thinsp;15.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.24\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLDL-Cholesterol, mg/dL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e111.5\u0026thinsp;\u0026plusmn;\u0026thinsp;31.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e98.81\u0026thinsp;\u0026plusmn;\u0026thinsp;25.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e113.8\u0026thinsp;\u0026plusmn;\u0026thinsp;31.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal Cholesterol, mg/dL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e208.1\u0026thinsp;\u0026plusmn;\u0026thinsp;42.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e187.9\u0026thinsp;\u0026plusmn;\u0026thinsp;34.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e212.1\u0026thinsp;\u0026plusmn;\u0026thinsp;43.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFasting glucose, mg/dL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e112.3\u0026thinsp;\u0026plusmn;\u0026thinsp;43.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e117.3\u0026thinsp;\u0026plusmn;\u0026thinsp;54.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e111.9\u0026thinsp;\u0026plusmn;\u0026thinsp;41.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.39\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMD, (T score)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-1.25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1.65\u0026thinsp;\u0026plusmn;\u0026thinsp;1.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-1.18\u0026thinsp;\u0026plusmn;\u0026thinsp;1.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale gender\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e193 (36.76%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e37(19.17%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e156 (80.83%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.26\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducation level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e508 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e88 (17.32%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e420 (82.68%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.61\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJunior high school or below\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e207 (40.75%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e39 (18.84%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e168 (81.16%)\u003c/p\u003e\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\u003eSenior high school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147 (28.94%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26 (17.69%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e121 (82.31%)\u003c/p\u003e\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\u003eCollege or above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e154 (30.31%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23 (14.94%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e131 (85.06%)\u003c/p\u003e\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\u003eMilk, Yes vs. No\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e375 (71.16%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e74 (19.73%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e301 (80.27%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCoffee, Yes vs. No\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e303 (57.82%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e49 (16.17%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e254 (83.83%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.48\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAlcohol drinking, Yes/Ever vs. Never\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e121 (23.14%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15 (12.40%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e106 (87.60%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoking, Yes vs. No\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e84 (15.91%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6 (7.14%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e78 (92.86%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBetel nuts, Yes vs. No\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30 (5.68%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (10.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27 (90.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.30\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e* Values are presented as Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or Frequency (%). Seventy-nine participants with missing information on vegetarian status were excluded from this analysis.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eCharacteristics stratified by BMD status are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Participants with osteoporosis (T-score\u0026thinsp;\u0026le;\u0026thinsp;\u0026minus;\u0026thinsp;2.5) were significantly older (67.3\u0026thinsp;\u0026plusmn;\u0026thinsp;9.7 vs. 57.3\u0026thinsp;\u0026plusmn;\u0026thinsp;13.3 y; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), had lower waist circumference (82.0\u0026thinsp;\u0026plusmn;\u0026thinsp;10.2 vs. 84.7\u0026thinsp;\u0026plusmn;\u0026thinsp;10.8 cm; P\u0026thinsp;=\u0026thinsp;0.02), and lower BMI (23.5\u0026thinsp;\u0026plusmn;\u0026thinsp;3.6 vs. 25.3\u0026thinsp;\u0026plusmn;\u0026thinsp;5.1 kg/m\u0026sup2;; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared with those with normal BMD. They also had higher systolic blood pressure (134.0\u0026thinsp;\u0026plusmn;\u0026thinsp;21.3 vs. 128.8\u0026thinsp;\u0026plusmn;\u0026thinsp;20.7 mmHg, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02) and modestly higher HDL cholesterol (57.7\u0026thinsp;\u0026plusmn;\u0026thinsp;16.7 vs. 54.1\u0026thinsp;\u0026plusmn;\u0026thinsp;14.8 mg/dL, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.05). The osteoporosis group included a smaller proportion of males (13.4% vs. 86.6%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and individuals with college or higher education (9.9% vs. 90.1%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). No significant differences were observed for other metabolic or behavioral variables.\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\u003eCharacteristics of study population by Bone mineral density (BMD) levels\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=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBMD\u003c/p\u003e\u003cp\u003eT score \u0026gt;-2.5*\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;461)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBMD\u003c/p\u003e\u003cp\u003eT score \u0026le; -2.5*\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;112)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge, yrs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e57.30\u0026thinsp;\u0026plusmn;\u0026thinsp;13.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e67.26\u0026thinsp;\u0026plusmn;\u0026thinsp;9.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWaist circumference, cm\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e84.74\u0026thinsp;\u0026plusmn;\u0026thinsp;10.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e82.03\u0026thinsp;\u0026plusmn;\u0026thinsp;10.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI, kg/m2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25.28\u0026thinsp;\u0026plusmn;\u0026thinsp;5.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23.52\u0026thinsp;\u0026plusmn;\u0026thinsp;3.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSystolic blood pressure, mmHg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e128.8\u0026thinsp;\u0026plusmn;\u0026thinsp;20.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e134.0\u0026thinsp;\u0026plusmn;\u0026thinsp;21.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiastolic blood pressure, mmHg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e83.60\u0026thinsp;\u0026plusmn;\u0026thinsp;11.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e83.16\u0026thinsp;\u0026plusmn;\u0026thinsp;10.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.69\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTriglyceride, mg/dL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e135.1\u0026thinsp;\u0026plusmn;\u0026thinsp;88.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e124.6 \u0026plusmn; 84.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHDL-Cholesterol, mg/dL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e54.07\u0026thinsp;\u0026plusmn;\u0026thinsp;14.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e57.68\u0026thinsp;\u0026plusmn;\u0026thinsp;16.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLDL-Cholesterol, mg/dL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e111.9\u0026thinsp;\u0026plusmn;\u0026thinsp;31.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e111.1\u0026thinsp;\u0026plusmn;\u0026thinsp;30.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.81\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal Cholesterol, mg/dL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e207.4\u0026thinsp;\u0026plusmn;\u0026thinsp;42.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e211.9\u0026thinsp;\u0026plusmn;\u0026thinsp;43.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.35\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFasting glucose, mg/dL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e110.3\u0026thinsp;\u0026plusmn;\u0026thinsp;39.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e115.3\u0026thinsp;\u0026plusmn;\u0026thinsp;44.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.30\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMD, (T score)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.86\u0026thinsp;\u0026plusmn;\u0026thinsp;1.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-2.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale gender\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e181 (86.60%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e28 (13.40%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e409 (81.15%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e95 (18.85%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJunior high school or below\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e146 (71.22%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e59 (28.78%)\u003c/p\u003e\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\u003eSenior high school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e127 (85.81%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e21 (14.19%)\u003c/p\u003e\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\u003eCollege or above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e136 (90.07%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15 (9.93%)\u003c/p\u003e\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\u003eCoffee, Yes vs. No\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e245 (83.05%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e50 (16.95%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMilk, Yes vs. No\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e303 (82.56%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e64 (17.44%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.13\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAlcohol drinking, Quit/Yes vs. Never\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e105 (86.78%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16 (13.22%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoking, Yes vs. No\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e72 (85.71%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12 (14.29%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBetel nuts, Yes vs. No\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23 (82.14%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5 (17.86%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.86\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e* Values are presented as Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or Frequency (%). Thirty-seven participants with missing information on BMD level were excluded from this analysis.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eLogistic regression analyses of factors associated with osteoporosis are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. In univariate models, vegetarian diet was associated with higher odds of osteoporosis (OR, 1.77; 95% CI, 1.04\u0026ndash;3.02). Older age increased risk (OR per year, 1.08; 95% CI, 1.05\u0026ndash;1.10), whereas male sex (OR, 0.51; 95% CI, 0.32\u0026ndash;0.81) and higher BMI (OR, 0.48; 95% CI, 0.31\u0026ndash;0.73) were protective. Diabetes was also associated with greater odds (OR, 1.71; 95% CI, 1.10\u0026ndash;2.67). Other factors, including hypertension, lipid profiles, alcohol use, smoking, betel nut chewing, milk intake, and coffee consumption, were not significant. In the fully adjusted model (Model 3), vegetarian diet remained independently associated with osteoporosis (aOR, 3.03; 95% CI, 1.52\u0026ndash;6.05). Age (aOR per year, 1.12; 95% CI, 1.08\u0026ndash;1.15), male sex (aOR, 0.14; 95% CI, 0.06\u0026ndash;0.31), and BMI (aOR, 0.43; 95% CI, 0.24\u0026ndash;0.78) remained significant predictors, while milk consumption was inversely associated with osteoporosis (aOR, 0.42; 95% CI, 0.23\u0026ndash;0.77).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eEstimated results on risk of osteoporosis\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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"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\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eUnivariable Analysis\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003eMultivariable Analysis*\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e95% C.I.\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eaOR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e95% C.I.\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge, yrs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e1.08\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e(1.05\u003c/b\u003e,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e1.10)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e1.12\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e(1.08\u003c/b\u003e,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e1.15)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale gender, Male vs. Female\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e0.51\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e(0.32\u003c/b\u003e,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.81)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.14\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e(0.06\u003c/b\u003e,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.31)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBody mass index, kg/m2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e0.48\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e(0.31\u003c/b\u003e,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.73)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.43\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e(0.24\u003c/b\u003e,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.78)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertension, Yes vs. No\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e(0.92,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e(0.59,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.95)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiabetes, Yes vs. No\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e1.71\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e(1.10\u003c/b\u003e,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e2.67)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e(0.99,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e3.31)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHDL level, Low vs. High\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e(0.41,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e(0.29,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.08)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAlcohol drinking, Quit / Yes vs. Never\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e(0.33,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.04)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e(0.57,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e3.40)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoking, Yes vs. No\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e(0.34,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e(0.48,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e5.22)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBetel nuts, Yes vs. No\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e(0.34,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.47)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e(0.33,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e9.24)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMilk, Yes vs. No\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e(0.44,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.42\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e(0.23\u003c/b\u003e,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.77)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCoffee Drinking, Yes vs. No\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e(0.46,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e(0.64,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2.03)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVegetarian, Yes vs. No\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e1.77\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e(1.04\u003c/b\u003e,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e3.02)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e3.03\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e(1.52\u003c/b\u003e,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e6.05)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLDL level, High vs. Normal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e(0.60,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.62)\u003c/p\u003e\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\u003eTotal cholesterol, High vs. Normal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e(0.94,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.28)\u003c/p\u003e\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\u003eTriglyceride, High vs. Normal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e(0.46,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.25)\u003c/p\u003e\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\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003e* Multivariable analyses were adjusted for all covariates listed in the table. Variables with statistically significant associations are shown in bold. Low high-density lipoprotein cholesterol (HDL-C) was defined as \u0026lt;\u0026thinsp;40 mg/dL in men and \u0026lt;\u0026thinsp;50 mg/dL in women. Thirty-seven participants without information on BMD status were excluded from this analysis.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eInteraction analyses between vegetarian diet and lifestyle factors are shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Smoking significantly modified the association of vegetarian and osteoporosis. Among smokers, vegetarians had markedly higher odds of osteoporosis (aOR, 48.70; 95% CI, 6.52-363.67), whereas among non-smokers the association was weaker but remained significant (aOR, 3.17; 95% CI, 1.45\u0026ndash;6.90; P for interaction\u0026thinsp;=\u0026thinsp;0.023). Milk consumption also acted as an effect modifier. The association between vegetarian and osteoporosis was stronger in participants without the habit of milk consumption (aOR, 31.71; 95% CI, 6.72-149.59) compared with participants with the habit of milk consumers (aOR, 4.86; 95% CI, 1.63\u0026ndash;14.52; P for interaction\u0026thinsp;=\u0026thinsp;0.011). Coffee consumption did not significantly modify the association, although effect estimates were higher among non-coffee drinkers (OR, 17.97; 95% CI, 4.61\u0026ndash;70.03) than coffee drinkers (OR, 8.58; 95% CI, 2.36\u0026ndash;31.22; P for interaction\u0026thinsp;=\u0026thinsp;0.357).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eStratified analysis of the association between osteoporosis risk and vegetarian diet\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eStratification\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVegetarian\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e\u003cp\u003eVegetarian vs. non-Vagetarian\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eP-value for interaction\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eaOR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e95% C.I.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eSmoking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e48.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(6.52,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e363.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.0230\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(1.45,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.90)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eMilk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(1.63,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e14.52)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.0110\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e31.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(6.72,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e149.59)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCoffee\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(2.50,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e29.42)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.3571\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(4.61,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e70.03)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e*Multivariable analyses were adjusted for age, sex, educational level, smoking status, milk intake, and coffee consumption. Participants with missing information on vegetarian status (n\u0026thinsp;=\u0026thinsp;79) or BMD status (n\u0026thinsp;=\u0026thinsp;37) were excluded from the analysis.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eMain findings\u003c/h2\u003e\u003cp\u003eIn this cross-sectional study of a community-based population (17% vegetarians, 20% with osteoporosis), vegetarian diet was associated with a threefold higher risk of osteoporosis (aOR, 3.03; 95% CI, 1.52\u0026ndash;6.05). Smoking significantly amplified this association, with vegetarians who smoked demonstrating substantially greater risk compared with non-smokers (\u003cem\u003eP\u003c/em\u003e for interaction\u0026thinsp;=\u0026thinsp;0.023). In contrast, milk consumption attenuated the association, with stronger protective effects observed among participants reporting higher intake (\u003cem\u003eP\u003c/em\u003e for interaction\u0026thinsp;=\u0026thinsp;0.011). These findings suggest that increased milk consumption and smoking cessation may help reduce osteoporosis risk in vegetarians.\u003c/p\u003e\u003cp\u003eIn line with prior research, age, sex, and educational attainment were significant predictors of osteoporosis. Older adults and women were at greater risk, with risk rising progressively with age. Women additionally experience a higher incidence of fractures, with approximately half of women over 50 sustaining a fracture compared with about one fifth of men, reflecting a 2.5-fold higher risk [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. This disparity is largely explained by accelerated bone loss after menopause, driven by a decline in estrogen. Peak bone mass in women typically occurs between 36 and 40 years of age. Prior to menopause, women lose about 0.67% of bone mass per year, whereas postmenopausal women lose approximately 2.54% annually [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. These findings highlight the importance of targeted bone health strategies in women, particularly after menopause, to prevent osteoporosis and related fractures.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eComparison with Previous Studies\u003c/h3\u003e\n\u003cp\u003eSeveral studies have investigated the relationship between vegetarian diet and osteoporosis, yet the association remains inconclusive. A cross-sectional study in Taiwan reported no significant difference in BMD between vegetarians and non-vegetarians [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], and an Australian study found similar BMD between plant- based and meat-based diets [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. A prospective study in Vietnam likewise observed no significant effect of a vegan diet on bone loss or fracture risk [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], and a study of Taiwanese adults published in the \u003cem\u003eTzu Chi Medical Journal\u003c/em\u003e found no association between vegetarian diet and age-related BMD decline [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn contrast, a prospective study of 258 postmenopausal Taiwanese vegetarian women showed that long term adherence to a vegan diet was associated with a higher risk of femoral neck osteopenia (OR, 3.94; 95% CI, 1.21\u0026ndash;12.82) [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Similarly, a retrospective hospital-based analysis reported that vegetarian women aged 40\u0026ndash;55 years experienced greater reductions in lumbar spine BMD (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and femoral neck BMD (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.015) over three years compared with non-vegetarians, a pattern not observed in other age groups [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Furthermore, a meta-analysis of nine studies found that vegetarians had approximately 4% lower BMD (95% CI, 2%\u0026ndash;7%) at both the femoral neck and lumbar spine compared with omnivores [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003ePossible Mechanisms Linking Vegetarian diet and Osteoporosis\u003c/h3\u003e\n\u003cp\u003eIn this study, vegetarians had a higher risk of osteoporosis, likely related to imbalanced nutrient intake, such as insufficient calcium and vitamin D, which are essential for bone health. This deficiency may reflect limited animal protein and calcium sources in vegetarian diets. Although some studies have suggested a protective effect of plant-based diets, our findings highlight potential nutritional challenges for vegetarians in maintaining bone health.\u003c/p\u003e\u003cp\u003eLow consumption of soy products and dairy was associated with greater osteoporosis risk. This observation is consistent with previous reports showing that strict vegans, who typically have lower calcium intake, are at higher fracture risk [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Soy and dairy provide calcium, protein, and isoflavones [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], all of which contribute to BMD [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Adequate calcium intake is therefore critical to osteoporosis prevention.\u003c/p\u003e\u003cp\u003eOur analysis further demonstrated that vegetarian diet remained an independent predictor of osteoporosis after multivariable adjustment. These results align with prior research in southern Taiwan among postmenopausal Buddhist nuns and practitioners, where long term vegan diets were associated with increased risk of lumbar spine fractures and osteoporosis classification [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Together, these findings support a potential link between vegetarian dietary patterns and bone health.\u003c/p\u003e\u003cp\u003eIn addition to diet, age, sex, and education were significant predictors of osteoporosis. Consistent with prior studies, older adults and women were at higher risk, with women experiencing approximately 2.5 times more fractures than men after the age of 50 [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. This disparity is largely explained by accelerated bone loss after menopause due to estrogen deficiency. Women reach peak bone mass between 36 and 40 years of age, losing about 0.67% of bone mass annually before menopause, compared with 2.54% per year afterward [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. These results underscore the importance of targeted bone health strategies in women, particularly after menopause, to prevent osteoporosis and related fractures.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eEffect modification of the association between vegetarian diet and osteoporosis by lifestyle factors\u003c/h2\u003e\u003cp\u003eThe influence of vegetarian diet on osteoporosis risk may be modified by individual characteristics and lifestyle factors. In this study, interaction analyses revealed significant effect modification by milk consumption, coffee consumption, and smoking. Stratified analyses showed that vegetarians without the habit of milk consumption had a substantially higher risk of osteoporosis (aOR, 31.71), and those who did not consume coffee also faced elevated risk (aOR, 17.97). Smoking had the strongest interaction, with vegetarian smokers exhibiting a substantial increased risk of osteoporosis (aOR, 48.70). These results highlight the complex interplay between diet and lifestyle in shaping bone health.\u003c/p\u003e\u003cp\u003ePrior studies support these findings. Nicotine and cigarette smoke have been shown to impair bone remodeling and repair, establishing smoking as a major risk factor for low BMD [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Milk provides proteins, minerals, and vitamins critical for bone health, and low intake during childhood has been linked to a twofold increase in fracture risk [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. National data from Korea further demonstrated that frequent milk consumption may reduce osteoporosis incidence in adults [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Coffee, through its antioxidant properties, has been reported to inhibit osteoclast formation and lower osteoporosis risk [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Together, these mechanisms suggest that milk and coffee may exert protective effects on bone metabolism, whereas smoking accelerates bone deterioration.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eStrengths and Limitations\u003c/h2\u003e\u003cp\u003eThis study has several strengths. First, it included both vegetarians and non- vegetarians from a community setting, enhancing representativeness and external validity. The inclusion of a diverse participant pool supports broader generalizability of the findings. Second, multiple health related factors, including age, sex, smoking, and alcohol use, were comprehensively considered in the analysis, which minimized potential confounding and improved the robustness of the results.\u003c/p\u003e\u003cp\u003eSeveral limitations should also be acknowledged. The cross-sectional design precludes causal inference, and the associations observed may be affected by unmeasured factors or reverse causation, such as individuals with preexisting health conditions adopting vegetarian diets. Prospective longitudinal studies with repeated measurements of BMD, diet, and lifestyle factors are needed to clarify causal pathways. Recall bias may also have influenced self-reported dietary information. The relatively small number of vegetarians limits statistical power and may reduce the stability and generalizability of the results. Furthermore, although the study provided preliminary insights into the relationship between vegetarian diet and osteoporosis, it did not address other health outcomes of vegetarian diets, and further research is warranted, particularly in subgroups such as individuals with diabetes.\u003c/p\u003e\u003c/div\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis study demonstrated that vegetarian diet was positively associated with osteoporosis risk, and this relationship was further modified by smoking, milk consumption, and coffee consumption.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eBMD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eBone Mineral Density\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eaOR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAdjusted odds ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eBMI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eBody mass index\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eConfidence interval\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eDEXA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eDual-energy X-ray absorptiometry\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHDL\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eHigh-density lipoprotein\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eLDL\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eLow-density lipoprotein\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eOR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eOdds ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Joint Institutional Review Board of Taipei Medical University (TMU-JIRB No. N202103060) and Daichung Hospital, Miaoli, Taiwan. Written informed consent was obtained from all participants prior to study enrollment, and all procedures were conducted in accordance with Good Clinical Practice (GCP) guidelines and the principles of the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are not publicly available due to institutional regulations but are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo specific funding was received for this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eC-J Liew, C-Y Hsu, and S-Y Chuang contributed to data collection, analysis, and drafting the manuscript. F-H Chen, H-C Chen, A M-F Yen conceived the study, C-Y Hsu and S-Y Chuang supervised the research process, and is the guarantor of the work. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to express their gratitude to Mrs Hui-Lan Chen, Daichung hospital, for her support and encouragement, and to Mr Kuang-Chun Ku, Daichung hospital, for his valuable assistance with administrative coordination and data collection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u0026nbsp;\u003c/sup\u003eDaichung Hospital, Miaoli, Taiwan.\u0026nbsp;\u003csup\u003e2\u0026nbsp;\u003c/sup\u003eMaster of Public Health Program, College of Public Health, National Taiwan University, Taipei, Taiwan.\u003csup\u003e3\u0026nbsp;\u003c/sup\u003eInstitute of Population Health Sciences, National Health Research Institutes, Miaoli, Taiwan.\u0026nbsp;\u003csup\u003e4\u003c/sup\u003e School of Oral Hygiene, College of Oral Medicine, Taipei Medical University, Taipei, Taiwan.\u0026nbsp;\u003csup\u003e5\u0026nbsp;\u003c/sup\u003eTaiwan Association of Medical Screening, Taipei, Taiwan.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLeahy E, Lyons S, Tol RSJ. 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PLoS ONE. 2016;11(1):e0147762. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0147762\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0147762\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"bmc-nutrition","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nutn","sideBox":"Learn more about [BMC Nutrition](http://bmcnutr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/nutn/default.aspx","title":"BMC Nutrition","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Vegetarian, Osteoporosis, Bone mineral density, Smoking, Milk consumption, Risk modifiers","lastPublishedDoi":"10.21203/rs.3.rs-7952087/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7952087/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eVegetarian diets are often linked to health benefits, yet concerns remain regarding potential adverse effects on bone health arising from nutrient deficiencies. Lifestyle factors that can be modified may influence this risk.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003e A cross-sectional study was conducted among adults receiving community health services in Zhunan Township, Taiwan, with a total of 610 participants enrolled. Dietary patterns and lifestyle factors were assessed using structured questionnaires, and bone mineral density was measured. Logistic regression models were applied to evaluate the association between vegetarian diet and osteoporosis, with interaction terms included to examine potential modifying effects of smoking, milk consumption, and coffee consumption. Stratified analyses were performed to further assess the roles of these modifying influences.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eAfter excluding participants with missing information on dietary pattern or bone mineral density, 573 subjects remained for the final analysis. Vegetarian diet was associated with a significantly higher risk of osteoporosis compared with a non-vegetarian diet with an adjusted odds ratio (aOR) of 3.03 (95% CI: 1.52\u0026ndash;6.05). Interaction analysis indicated that smoking (P\u0026thinsp;=\u0026thinsp;0.0230) and milk consumption (P\u0026thinsp;=\u0026thinsp;0.0110) significantly modified this association. Among smokers, vegetarians had a substantially higher risk of osteoporosis with an aOR of 48.70 (95% CI: 6.52\u0026ndash;363.67). Among those who did not consume milk, the vegetarians also had a greater risk with an aOR of 31.71 (95% CI: 6.72\u0026ndash;149.59).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eVegetarian diet was independently associated with increased risk of osteoporosis, and this risk was particularly elevated among individuals who smoked or did not consume milk. These findings highlight the importance of considering lifestyle factors when evaluating bone health risks in populations adhering to vegetarian diets.\u003c/p\u003e\u003ch2\u003eTrial registration\u003c/h2\u003e\u003cp\u003eNot applicable.\u003c/p\u003e","manuscriptTitle":"Elevated Risk of Osteoporosis for Vegetarian Modified by Smoking and Milk Consumption","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-03 11:39:32","doi":"10.21203/rs.3.rs-7952087/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-04T09:44:29+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-04T08:17:38+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-09T06:52:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"165042367757836309642986699148380259773","date":"2025-12-09T04:45:51+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-08T17:22:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"145780267251541240871885253265884635026","date":"2025-12-08T15:42:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"4256181945256069256270015260873059229","date":"2025-12-02T06:20:03+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-01T12:02:23+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-25T09:55:11+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-11-07T09:04:55+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-07T02:02:38+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Nutrition","date":"2025-11-07T01:59:48+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-nutrition","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nutn","sideBox":"Learn more about [BMC Nutrition](http://bmcnutr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/nutn/default.aspx","title":"BMC Nutrition","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"805931f6-9c73-45a9-b131-1ccbf9203557","owner":[],"postedDate":"December 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-08T10:43:47+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-03 11:39:32","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7952087","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7952087","identity":"rs-7952087","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}