Knowledge and practice of diabetes mellitus among Lahu and Wa populations in southwest China: a cross‑sectional study
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Abstract Background Diabetes mellitus is a major global health challenge, contributing to substantial morbidity and mortality worldwide. However, rural and ethnic minority communities often experience disparities in diabetes care outcomes compared to other regions. This study aimed to evaluate diabetes-related knowledge and practices, identify influencing factors, and assess the potential association between diabetes knowledge and self-management behaviors among the Lahu and Wa ethnic minority populations in Southwest China. Methods A cross-sectional study was conducted in Yunnan Province (2009–2010) using a multi-stage sampling design. Face-to-face interviews were performed with 2,281 Lahu and 2,876 Wa adults (aged ≥ 18 years) to collect data on socio-demographics, diabetes knowledge (symptoms, risk factors, prevention, and treatment), and practices (smoking, alcohol use, diet, physical activity, and overweight/obesity). Descriptive statistics, χ² tests, and logistic regression were used for analysis. Results Diabetes awareness was low overall (Lahu: 9.20%; Wa: 30.80%), with significant interethnic disparities. The Wa population demonstrated a higher knowledge level (72.20% vs. 62.68%, p = 0.007) and healthier behaviors (e.g., higher vegetable intake, lower female smoking/drinking rates) compared to the Lahu. No significant behavioral improvements were observed in smoking, alcohol use, physical activity, or weight management among participants with diabetes knowledge. Smoking (male: >75%; female: >30%) and alcohol use (male: >65%; female: 14.9–30.2%) remained prevalent across both groups. Female sex and literacy (Wa only) were positively associated with diabetes knowledge. Conclusions The findings highlight the poor knowledge and practice regarding diabetes among the Lahu and Wa populations, with acquired diabetes knowledge failing to translate into measurable behavioral improvements. These results underscore the need for culturally tailored interventions to improve diabetes prevention and management in these underserved communities, especially among male populations.
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However, rural and ethnic minority communities often experience disparities in diabetes care outcomes compared to other regions. This study aimed to evaluate diabetes-related knowledge and practices, identify influencing factors, and assess the potential association between diabetes knowledge and self-management behaviors among the Lahu and Wa ethnic minority populations in Southwest China. Methods A cross-sectional study was conducted in Yunnan Province (2009–2010) using a multi-stage sampling design. Face-to-face interviews were performed with 2,281 Lahu and 2,876 Wa adults (aged ≥ 18 years) to collect data on socio-demographics, diabetes knowledge (symptoms, risk factors, prevention, and treatment), and practices (smoking, alcohol use, diet, physical activity, and overweight/obesity). Descriptive statistics, χ² tests, and logistic regression were used for analysis. Results Diabetes awareness was low overall (Lahu: 9.20%; Wa: 30.80%), with significant interethnic disparities. The Wa population demonstrated a higher knowledge level (72.20% vs. 62.68%, p = 0.007) and healthier behaviors (e.g., higher vegetable intake, lower female smoking/drinking rates) compared to the Lahu. No significant behavioral improvements were observed in smoking, alcohol use, physical activity, or weight management among participants with diabetes knowledge. Smoking (male: >75%; female: >30%) and alcohol use (male: >65%; female: 14.9–30.2%) remained prevalent across both groups. Female sex and literacy (Wa only) were positively associated with diabetes knowledge. Conclusions The findings highlight the poor knowledge and practice regarding diabetes among the Lahu and Wa populations, with acquired diabetes knowledge failing to translate into measurable behavioral improvements. These results underscore the need for culturally tailored interventions to improve diabetes prevention and management in these underserved communities, especially among male populations. Diabetes mellitus Knowledge Practice Ethnic minorities Lahu population Wa population Figures Figure 1 Figure 2 Figure 3 Introduction Diabetes mellitus (DM) is a metabolic disorder characterized by hyperglycemia resulting from insufficient insulin secretion and/or impaired insulin action(1). It has been ranked among the top ten global causes of mortality and disability(2). The prevalence of diabetes has shown a significant upward trend over the past three decades, and the global number of people with diabetes will reach 783 million by 2045, imposing tremendous pressure on healthcare systems worldwide and driving continuous increases in medical expenditures(3, 4). Notably, approximately 81% of people with diabetes reside in low- and middle-income countries(4). In China, rapid urbanization and economic growth have further exacerbated the diabetes epidemic, with particularly prominent disease burdens observed in rural areas and ethnic minority populations(5). Behavioral and lifestyle factors play a pivotal role in the prevention and management of diabetes and its complications. Evidence-based medical research demonstrates that modifiable risk factors primarily include unhealthy diet, physical inactivity, smoking, and excessive alcohol consumption(6). Multiple large-scale cohort studies have confirmed that lifestyle interventions—such as weight management, balanced nutrition, and regular physical activity—can significantly reduce the incidence of diabetes(7, 8). However, clinical practice reveals that adherence to recommended interventions remains suboptimal, even with clear evidence of benefits, particularly in regions with limited healthcare resources(5, 9)China’s chronic disease surveillance data indicate significant disparities in health behaviors between urban and rural populations(10). Notably, central obesity rates and physical inactivity continue to rise among ethnic minority groups and populations with low socioeconomic status(11), underscoring the necessity for targeted, precision interventions in these high-risk groups. Health literacy serves as a critical determinant in facilitating effective self-management behaviors. Evidence suggests that acquiring diabetes-related knowledge significantly enhances individuals' disease awareness and self-efficacy, thereby increasing their likelihood of adopting standardized self-management practices(12). Although China has made substantial progress in improving population health literacy through initiatives such as the National Basic Public Health Services (NBPHS)(13)and the "Healthy China 2030" development plan(14), regional disparities remain pronounced. Rural and ethnic minority regions continue to lag behind the national average in health literacy(13, 15)This knowledge gap is particularly severe among "direct transition" ethnic groups (e.g., Lahu and Wa) in Southwest China, who exhibit markedly insufficient health literacy and health-related skills(16, 17). However, systematic research on diabetes awareness and behavioral practices in these underserved populations remains lacking. To address this gap, this study conducts the first comprehensive investigation of diabetes knowledge and practices among the Lahu and Wa populations in Southwest China. Methods Study design This cross-sectional investigation employed a multi-stage sampling design to recruit participants between August 2009 and September 2010 in Yunnan Province, China. The sampling framework involved: (1) stratified random selection of two ethnically diverse counties based on Lahu and Wa demographic representation; (2) economic stratification of counties into tertiles (high, medium, low) using per capita GDP criteria; (3) random selection of one township per stratum with subsequent probability-proportional-to-size sampling of two villages per township. Study population The study enrolled adult participants (age ≥18 years) who self-identified as either Lahu or Wa ethnicity and maintained uninterrupted local residency for ≥5 years. Exclusion criteria comprised: (1) clinically significant cognitive impairment (precluding reliable survey responses), and (2) language barriers sufficient to compromise informed consent or questionnaire comprehension. Research instruments The study utilized a structured, pretested questionnaire for systematic data collection (see supplementary file 1 for details). Socio-demographic characteristics included educational attainment (with literate defined as ≥6 completed years of formal schooling) and income level (Low income was classified according to China National Bureau of Statistics thresholds: ≤1,196 yuan [2009] and ≤1,274 yuan [2010] annual per capita). Diabetes-related awareness and knowledge were evaluated using 15 items selected from the questionnaire, beginning with a screening question (“Have you ever heard of diabetes?”). Participants responding affirmatively were asked subsequent questions examining information sources (5 items), symptom knowledge (4 items), risk factor knowledge (5 items), prevention knowledge (3 items, in which diet control includes eating more fiber-rich foods, eating more whole grains and reducing intake of high-fat and high-sugar foods). One additional item assessed treatment awareness (“Do you know how diabetes is treated?”). Knowledge items employed categorical responses (“yes” or “no”). Domain-specific scores were calculated by summing correct responses, with total knowledge scores dichotomized (0 = no knowledge; ≥1 = some knowledge). Behavioral assessments included tobacco use (defined as ≥1 cigarette daily for >6 consecutive months), alcohol consumption (weekly intake of traditional beverages including Baijiu, beer, wine, or rice wine), dietary vegetable proportion (dichotomized at 50% of total consumption), and physical activity intensity. Physical activity was classified as heavy (manual farming causing significant cardiorespiratory strain), moderate (household chores involving moderate exertion), or light (sedentary occupations with less than 25% active movement or mental work). Data collection Trained research staff conducted standardized face-to-face interviews using the questionnaire to collect data. Anthropometric measurements (height and weight) were collected after an 8-12 hour fasting period, with body mass index (BMI) calculated as weight (kg)/height² (m²). Overweight and obesity were defined according to Chinese criteria as BMI ≥24.0 kg/m² and ≥28.0 kg/m², respectively(18). Statistical analysis Data were analyzed using SPSS (version 27.0). Categorical variables were presented as frequencies (percentages) with between-group comparisons performed using χ² tests. Non-normally distributed continuous variables were expressed as median values (interquartile range [IQR]) and analyzed with Mann-Whitney U tests. For diabetes knowledge assessment, the analytical framework incorporated three dimensions: (1) cross-ethnic comparisons (Lahu vs. Wa populations); (2) intra-ethnic stratification by sex, age categories (<45 vs. ≥45 years), education (illiterate vs. literate), and income levels (Low income vs. Non-low income); and (3) cross-stratification analyses of ethnic differences across demographic subgroups. Multivariable logistic regression models identified determinants of: (1) heard of diabetes and (2) knowledge retention, with results reported as adjusted odds ratios (ORs) and 95% confidence intervals (CIs). Statistical significance was determined at α=0.05 (two-tailed). Results Socio-demographic characteristics The study included 2,281 Lahu (996 males; 1,285 females) and 2,876 Wa (1,107 males; 1,769 females) participants. The Lahu population had a median age of 40 years, with around 61% aged <45 years (no sex difference, p=0.944). In contrast, Wa males were significantly older (median 45 years; 49.2% <45 years) than Wa females (58.6% <45 years, p<0.001). Wa participants showed substantially higher literate rates (males: 67.3% vs 19.0%; females: 59.2% vs 23.0%; all p<0.001) compared to Lahu. Low-income prevalence was significantly higher in Wa females (65.2%) than males (59.3%, p=0.001), but did not differ between Lahu sexes (p=0.207) (Table 1). Table 1. Socio-demographic Characteristics of Lahu and Wa Populations by Sex. Characteristics Lahu (n=2281) Wa (n=2876) p male p female Male Female p lahu Male Female p wa Age (years) 40(28.75,50) 40(28,51) 0.794 45(35,55) 41(32,51) <0.001 <0.001 0.002 <45 607(60.90%) 785(61.10%) 0.944 545(49.20%) 1036(58.60%) <0.001 =45 389(39.10%) 500(38.90%) 562(50.80%) 733(41.40%) Annual income per capita (Yuan) 1250(1147,1667) 1250(1147,1600) 0.008 1250(1250,1600) 1250(1250,1500) 0.001 0.002 <0.001 Low income No 379(38.10%) 456(35.50%) 0.207 451(40.70%) 615(34.80%) 0.001 0.208 0.680 Yes 617(61.90%) 829(64.50%) 656(59.30%) 1154(65.20%) Literate No 807(81.00%) 989(77.00%) 0.019 362(32.70%) 722(40.80%) <0.001 <0.001 <0.001 Yes 189(19.00%) 296(23.00%) 745(67.30%) 1047(59.20%) Note: p lahu = p for Lahu male vs. female; p Wa = p for Wa male vs. female; p male = p for Lahu male vs. Wa male; p female = p for Lahu female vs. Wa female. Knowledge towards diabetes mellitus Only 9.2% of Lahu participants reported having heard of diabetes, compared to 30.8% of Wa (p<0.001). Both groups primarily obtained diabetes information from television and physicians, with minimal use of print media (<2%). Lahu utilized educational materials more frequently (8.6% vs 2.5%, p<0.001). Wa participants demonstrated higher overall diabetes knowledge level (some knowledge: 72.2% vs 62.7%, p=0.007),though both ethnic groups displayed severely right-skewed total knowledge score distributions (median=1, IQR=0-2), with only 18.7% of Lahu and 16.2% of Wa participants achieving scores ≥3. Similar right-skewed distributions were observed across all knowledge domains (symptoms, risk factors, prevention, and treatment), with scores predominantly clustered at 0-1. Lahu participants were less likely to recognize overeating as a diabetes risk factor than Wa (10.5% vs. 19.8%, p=0.002) but more frequently identified family history (6.2% vs. 2.5%, p=0.006). No other significant interethnic differences were observed in diabetes knowledge (Table 2, Figure 1). Table 2. Knowledge of Diabetes Among Lahu and Wa Population Diabetes Knowledge Lahu Wa χ 2 p Heard of diabetes No 2072(90.80%) 1991(69.20%) 355.408 <0.001 Yes 209(9.20%) 885(30.80%) Sources of diabetes-related information Television No 162(77.50%) 720(81.40%) 1.599 0.206 Yes 47(22.50%) 165(18.60%) Physician No 173(82.80%) 686(77.50%) 2.774 0.096 Yes 36(17.20%) 199(22.50%) Newspapers/Magazines No 206(98.60%) 870(98.30%) 0.07 0.791 Yes 3(1.40%) 15(1.70%) Educational Materials No 191(91.40%) 863(97.50%) 18.015 <0.001 Yes 18(8.60%) 22(2.50%) Other No 73(34.90%) 349(39.40%) 1.449 0.229 Yes 136(65.10%) 536(60.60%) Number of Sources 1 192(91.90%) 849(95.90%) 23.754 <0.001 2 5(2.40%) 27(3.10%) 3 10(4.80%) 2(0.20%) 4 2(1.00%) 7(0.80%) Knowledge of diabetes symptoms Polyuria No 157(75.10%) 634(71.60%) 1.023 0.312 Yes 52(24.90%) 251(28.40%) Polydipsia No 184(88.00%) 770(87.00%) 0.162 0.688 Yes 25(12.00%) 115(13.00%) Polyphagia No 186(89.00%) 799(90.30%) 0.312 0.576 Yes 23(11.00%) 86(9.70%) Weight loss No 180(86.10%) 787(88.90%) 1.294 0.255 Yes 29(13.90%) 98(11.10%) Knowledge of diabetes risk factors Obesity No 195(93.30%) 842(95.10%) 1.159 0.282 Yes 14(6.70%) 43(4.90%) Drink alcohol No 187(89.50%) 793(89.60%) 0.003 0.956 Yes 22(10.50%) 92(10.40%) Tobacco use No 197(94.30%) 858(96.90%) 3.561 0.059 Yes 12(5.70%) 27(3.10%) Overeating No 187(89.50%) 710(80.20%) 9.793 0.002 Yes 22(10.50%) 175(19.80%) Family History No 196(93.80%) 863(97.50%) 7.613 0.006 Yes 13(6.20%) 22(2.50%) Knowledge of diabetes prevention Exercise No 185(88.50%) 780(88.10%) 0.024 0.878 Yes 24(11.50%) 105(11.90%) Diet Control No 171(81.80%) 671(75.80%) 3.432 0.064 Yes 38(18.20%) 214(24.20%) Weight Management No 192(91.90%) 841(95.00%) 3.211 0.073 Yes 17(8.10%) 44(5.00%) Knowledge of diabetes treatment No 205(98.10%) 870(98.30%) 0.047 0.827 Yes 4(1.90%) 15(1.70%) Total diabetes knowledge level No knowledge 78(37.32%) 246(27.80%) 7.357 0.007 Some knowledge 131(62.68%) 639(72.20%) Factors associated with participant’s knowledge towards diabetes mellitus Consistent ethnic disparities were observed across all demographic strata (gender, age, education, and income levels), with Wa participants demonstrating significantly higher diabetes awareness rates than their Lahu counterparts (p<0.001 for all comparisons). Additionally, the Wa exhibited significantly higher overall diabetes knowledge levels than the Lahu in male, ≥45-year-old, and low-income subgroups (all p<0.05) (Figure 2). Multivariate logistic regression analysis identified distinct ethnic-specific patterns in both diabetes awareness and knowledge (Figure 3). Gender differences were particularly notable, with female sex demonstrating significantly lower diabetes awareness in both populations - more strongly in Lahu women (OR = 2.16, 95% CI: 1.57-2.96) than in Wa women (OR = 1.21, 95% CI: 1.03-1.44). No other demographic factors (age, income status, or literate) showed statistically significant associations with diabetes awareness in either group (all p>0.05). Regarding diabetes knowledge, literacy status emerged as the only significant predictor among Wa participants (OR=1.46, 95% CI: 1.00-2.11), whereas no significant predictors were identified in the Lahu population. Practices towards diabetes mellitus Males in both ethnic groups exhibited significantly higher rates of tobacco use (Lahu: 77.6% vs 38.3%; Wa: 79.8% vs 33.6%) and alcohol consumption (Lahu: 66.9% vs 30.2%; Wa: 66.0% vs 14.9%) compared to their female counterparts (all p<0.001). Lahu females demonstrated higher smoking (38.3% vs 33.6%) and drinking rates (30.2% vs 14.9%) than Wa females, along with greater overweight/obesity prevalence (16.2% vs 7.9%) and lower heavy physical activity participation (43.3% vs 61.7%) compared to Lahu males (all p<0.01). Wa participants showed more balanced sex distribution in physical activity levels (67.0% males vs 64.4% females, p=0.086) and significantly higher vegetable consumption rates than Lahu participants in both sexes (both p<0.001). Obesity prevalence remained consistently low across all subgroups (<3.5%) (Table 3). Table 3. Diabetes Practices Stratified by sex in Southwest China's Lahu and Wa Populations Practices Lahu Wa p male p female Male Female p lahu Male Female p wa Tobacco use No 223(22.40%) 793(61.70%) <0.001 224(20.20%) 1174(66.40%) <0.001 0.228 0.008 Yes 773(77.60%) 492(38.30%) 883(79.80%) 595(33.60%) Drink alcohol No 330(33.10%) 897(69.80%) <0.001 376(34.00%) 1505(85.10%) <0.001 0.686 <0.001 Yes 666(66.90%) 388(30.20%) 731(66.00%) 264(14.90%) Physical activity intensity Heavy 615(61.70%) 557(43.30%) <0.001 742(67.00%) 1139(64.40%) 0.086 0.041 <0.001 Moderate 293(29.40%) 540(42.00%) 282(25.50%) 456(25.80%) Light 88(8.80%) 188(14.60%) 83(7.50%) 174(9.80%) Dietary vegetable proportion <=50% 701(70.40%) 827(64.40%) 0.002 398(36.00%) 666(37.60%) 0.360 <0.001 50% 295(29.60%) 458(35.60%) 709(64.00%) 1103(62.40%) BMI Group Normal 917(92.10%) 1077(83.80%) <0.001 913(82.50%) 1422(80.40%) 0.375 <0.001 0.052 overweight 71(7.10%) 173(13.50%) 162(14.60%) 291(16.40%) obesity 8(0.80%) 35(2.70%) 32(2.90%) 56(3.20%) Note: p lahu = p for Lahu male vs. female; p Wa = p for Wa male vs. female; p male = p for Lahu male vs. Wa male; p female = p for Lahu female vs. Wa female. Association Between Diabetes Knowledge and Practices Among Lahu participants who had heard of diabetes, tobacco use was significantly lower (46.4% vs 56.4%, p=0.006) and overweight/obesity prevalence higher (26.3% vs 11.2%, p0.05). For those with some diabetes knowledge, Lahu participants demonstrated significantly lower heavy physical activity among the knowledgeable group (45.0% vs 62.8%, p=0.033), while Wa participants with knowledge reported lower vegetable consumption (>50% intake: 60.7% vs 67.9% in knowledgeable vs less knowledgeable, p=0.048). No significant associations were found between knowledge levels and alcohol consumption patterns in either group (all p>0.05) (Table 4). Table 4. Diabetes Practices Stratified by Awareness and Knowledge Status in Southwest China's Lahu and Wa Populations Goup Practices Lahu Wa No Yes p lahu No Yes p wa Heard of Diabetes Tobacco use No 904(43.63%) 112(53.59%) 0.006 963(48.37%) 435(49.15%) 0.697 Yes 1168(56.37%) 97(46.41%) 1028(51.63%) 450(50.85%) Drink alcohol No 1106(53.38%) 121(57.89%) 0.212 1280(64.29%) 601(67.91%) 0.060 Yes 966(46.62%) 88(42.11%) 711(35.71%) 284(32.09%) Physical activity intensity Heavy 1064(51.35%) 108(51.67%) 0.536 1310(65.8%) 571(64.52%) 0.303 Moderate 751(36.25%) 82(39.23%) 514(25.82%) 224(25.31%) Light 257(12.4%) 19(9.09%) 0.335 167(8.39%) 90(10.17%) Dietary vegetable proportion 50% 680(32.82%) 73(34.93%) 1257(63.13%) 555(62.71%) BMI Group Normal 1840(88.8%) 154(73.68%) <0.001 1612(80.96%) 723(81.69%) 0.325 overweight 198(9.56%) 46(22.01%) 323(16.22%) 130(14.69%) obesity 34(1.64%) 9(4.31%) 56(2.81%) 32(3.62%) Some Diabetes knowledge Tobacco use No 41(52.56%) 71(54.20%) 0.819 109(44.31%) 326(51.02%) 0.074 Yes 37(47.44%) 60(45.80%) 137(55.69%) 313(48.98%) Drink alcohol No 47(60.26%) 74(56.49%) 0.594 169(68.70%) 432(67.61%) 0.755 Yes 31(39.74%) 57(43.51%) 77(31.30%) 207(32.39%) Physical activity intensity Heavy 49(62.82%) 59(45.04%) 0.033 162(65.85%) 409(64.01%) 0.741 Moderate 22(28.21%) 60(45.80%) 62(25.20%) 162(25.35%) Light 7(8.97%) 12(9.16%) 22(8.94%) 68(10.64%) Dietary vegetable proportion 50% 25(32.05%) 48(36.64%) 167(67.89%) 388(60.72%) BMI Group Normal 56(71.79%) 98(74.81%) 0.852 197(80.08%) 526(82.32%) 0.255 Overweight 18(23.08%) 28(21.37%) 36(14.63%) 94(14.71%) Obesity 4(5.13%) 5(3.82%) 13(5.28%) 19(2.97%) Discussion Our survey revealed strikingly low awareness of diabetes among the studied ethnic minorities. Only 9.20% of Lahu and 30.80% of Wa respondents reported having heard of diabetes, rates significantly lower than those reported in contemporaneous studies from rural Northeast India (91%) (19), urban South India (75.5%)(20), and rural Bangladesh (93%)(21). The knowledge assessment demonstrated even more concerning results. In a 13-item diabetes knowledge test, fewer than 20% of respondents from either ethnic group could correctly answer three or more questions, indicating severe knowledge deficiencies. This overall level of diabetes knowledge was substantially inferior to data reported from Middle Eastern countries such as Saudi Arabia(22)and Jordan(23). Notably, the Wa population exhibited higher diabetes awareness and knowledge than the Lahu, potentially attributable to their higher educational attainment, which may facilitate more active health information-seeking behaviors(24). This difference was partially evidenced by their distinct health knowledge acquisition patterns: Wa respondents predominantly relied on active channels (newspapers/magazines, physician consultations), while Lahu respondents primarily depended on passive information sources (television broadcasts, educational materials). Only 37.3% of Lahu and 40.1% Wa respondents recognized at least one classic diabetes symptom (polyuria, polydipsia, polyphagia or weight loss), which, while higher than other indigenous ethnic groups in Yunnan Province (Naxi: 11.8%; Lisu: 4.2%; Dai: 15.0%; Jingpo: 1.7%)(25), was significantly lower than reports from semi-urban Oman (57.0%) (26)and South India (73.5%) (27). Regarding specific symptom awareness, both groups showed highest recognition for polyuria (Lahu: 24.9%; Wa: 28.4%), while other symptoms maintained only about 10% awareness, mirroring patterns observed in Oman (polyuria: 44.8%; weight loss: 24.7%; polydipsia: 20.1%)(26)More critically, substantial knowledge gaps existed in risk factor awareness, with merely 6.7% of Lahu and 4.9% of Wa recognizing obesity's risk (vs Malaysia 40%(28) and Oman 29.5% (26)), and even lower awareness of familial predisposition (Lahu: 6.2%; Wa: 2.5%). Preventive measure awareness was equally deficient, with dietary control (Lahu: 18.2%; Wa: 24.2%), physical activity (Lahu: 11.5%; Wa: 11.9%) and weight management (Lahu: 8.1%; Wa: 5.0%) all lagging behind Oman's reports (63.1%, 42.3% and 17.9% respectively) (26). Most alarmingly, treatment awareness was below 2% in both groups, contrasting sharply with India (85.2%)(27), Saudi Arabia(49.2%~85.5%)(22) and France༈87.5%༉(29), highlighting substantial room for improvement in diabetes education among China's ethnic minorities. The relatively low diabetes knowledge levels among the Lahu and Wa ethnic groups may be attributed to the underdeveloped socioeconomic conditions(30), poor educational attainment(16, 17), and inadequate health resources in their concentrated residential areas(15, 31, 32), which collectively contribute to low health literacy. These findings demonstrate an urgent need for culturally adapted, intensive health education programs targeting symptom recognition, risk factors, prevention strategies and treatment knowledge in these underserved populations. This study demonstrates gender as an independent determinant influencing diabetes awareness. In multivariate regression analyses, gender remained significantly associated with diabetes knowledge even after adjusting for confounders including age and socioeconomic status, with Lahu women exhibiting 2.15 times higher likelihood of diabetes awareness than their male counterparts. These findings align with previous studies conducted among Xinjiang Uyghur populations(33) and rural Indian populations(34), potentially attributable to gender-specific occupational characteristics in rural settings, traditional family roles, and socially-constructed health consciousness that encourages greater health concern among women(35). Notably, while existing literature consistently reports positive associations between diabetes knowledge and advancing age(36, 37), higher income(38), and improved educational attainment(37, 38), our study only identified a weak positive correlation between education level and diabetes awareness in the Wa population. Overweight and obesity have been proved to be well-established risk factors for insulin resistance and type 2 diabetes development among Chinese adults(39), while high-intensity physical labor may exert protective effects through improved insulin sensitivity(40). We observed significantly lower overweight/obesity prevalence in both Lahu (male 7.9%, female 16.2%) and Wa (male 17.5%, female 19.6%) populations compared to other regions(41, 42), likely attributable to their prevalent high-intensity physical activity (> 40%) and agriculture-dominated lifestyle, consistent with findings from rural Xinjiang(43). However, the study revealed alarming high-risk behavioral patterns: exceptionally elevated smoking rates (male > 75%, female > 30%) substantially exceeding national averages (male 43.1%, female 1.6%) (44), other southwestern ethnic groups (18.6–32.3%) (6), and Eastern Ethiopia populations (21.1%) (45); similarly prominent alcohol consumption (male > 65%, female 14.9–30.2%) with male rates far surpassing Eastern Ethiopia (36%) (45)and rural Xinjiang (Uyghur 8.08%, Han 41.20%) (43)Given substantial evidence establishing smoking and excessive alcohol consumption as independent diabetes risk factors(46, 47), we strongly recommend implementing targeted, intensive public health interventions specifically addressing these modifiable risk factors in Lahu and Wa communities. The comparative analysis revealed distinct behavioral differences between the Lahu and Wa ethnic groups. Notably, the Wa population demonstrated healthier behavioral patterns: gender-stratified analyses showed significantly higher vegetable intake and rates of heavy physical labor among both Wa men and women compared to their Lahu counterparts, with Wa women additionally exhibiting lower smoking and alcohol consumption rates than Lahu women - findings consistent with the Wa group's overall superior diabetes awareness and knowledge. Furthermore, within both ethnic groups, women demonstrated significantly lower smoking and alcohol consumption rates than their male counterparts, paralleling their relatively higher diabetes knowledge levels. These results support the health literacy-behavior improvement hypothesis, suggesting that enhanced diabetes knowledge may positively influence self-management behaviors(9, 48). However, unlike previous studies(22), our within-group comparisons found no significant behavioral advantages (in smoking, alcohol consumption, physical activity, or weight management) among those with diabetes knowledge, potentially attributable to the populations' overall knowledge levels remaining below the critical threshold required for effective behavioral modification(49). This finding highlights current deficiencies in health education interventions and underscores the need to develop culturally adapted diabetes education programs specifically tailored for the Lahu and Wa populations, coupled with sustainable health promotion mechanisms to facilitate the crucial knowledge-to-behavior transition. To our knowledge, this study represents the first systematic evaluation of diabetes-related knowledge and behavioral characteristics among the Lahu and Wa ethnic populations in Southwest China. However, several limitations should be acknowledged. First, the cross-sectional design precludes causal inference and cannot establish temporal relationships between diabetes knowledge and health behaviors. Second, despite employing face-to-face interviews for data collection, potential biases including recall bias (particularly regarding dietary and physical activity behaviors), social desirability bias (e.g., underreporting of smoking/alcohol consumption), and selection bias may persist. Third, due to sampling constraints, more mobile subpopulations such as university students and migrant workers - who typically exhibit higher health literacy levels - were not included, potentially leading to underestimation of overall diabetes awareness in these communities. Future studies should employ longitudinal designs incorporating more comprehensive sampling strategies and objective measurement approaches (e.g., biomarker assessments) to more accurately evaluate diabetes-related knowledge and behaviors in ethnic minority populations. Conclusion The Lahu and Wa ethnic groups in Southwest China exhibit alarmingly low diabetes awareness and knowledge, with the Wa population showing better health behaviors and knowledge than the Lahu, though neither group demonstrates significant behavioral improvements among diabetes-aware individuals; both groups display prevalent high-risk behaviors (especially males), highlighting the critical need for culturally tailored interventions to address these disparities in diabetes prevention and management. Abbreviations DM Diabetes mellitus NBPHS National Basic Public Health Services BMI Body mass index IQR Interquartile range OR Odds ratio CI Confidence interval Declarations Ethics approval and consent to participate We confirm that all experiments were performed in accordance with the Declaration of Helsinki, and the informed consent was obtained from all subjects and their legal guardians. The Institutional Review Board of The First Affiliated Hospital of Kunming Medical University provided the Ethical approval for the study (2025L165). Consent for publication Not applicable. Availability of data and materials The datasets used and analysed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This work was supported by the following funding sources: the National Natural Science Foundation of China (Grants No. 82160165, 81160104, and 30760087), the "Famous Doctor" Special Program of Yunnan Xingdian Talent Support Plan (Grant No. RLMY20220009), the Young and Middle-aged Academic and Technical Leaders Reserve Talents Project of Yunnan Province (Grant No. 202105AC160093), and the Key Project of Yunnan Provincial Clinical Medical Center for Endocrine and Metabolic Diseases (Grant No. 2024YNLCYXZX0073). 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1","display":"","copyAsset":false,"role":"figure","size":390980,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of Diabetes Knowledge Scores Among Lahu and Wa Ethnic Groups. (A) Symptom knowledge, (B) Risk factor knowledge, (C) Prevention knowledge, (D) Treatment knowledge, (E) Composite total score.\u003c/p\u003e","description":"","filename":"Figure1.DistributionofDiabetesKnowledgeScoresAmongLahuandWaEthnicGroups.png","url":"https://assets-eu.researchsquare.com/files/rs-7527719/v1/58312d7eec0303db7c87a84e.png"},{"id":94824918,"identity":"1dc1972e-0a99-425e-83ca-da245faaa34c","added_by":"auto","created_at":"2025-10-31 06:49:33","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":500420,"visible":true,"origin":"","legend":"\u003cp\u003eSex-(I), Age-(II), Education-(III), and Income-(IV) Stratified Diabetes Knowledge Among Lahu and Wa Ethnic Groups. Panel descriptions for each subfigure (I-IV): A: Heard of diabetes. B: Total diabetes knowledge level. C–F: Knowledge of diabetes symptoms. G–K: Knowledge of diabetes risk factors. L–N: Knowledge of diabetes prevention. O–S: Sources of diabetes-related information. T: Knowledge of diabetes treatment. Asterisks (*) indicate significant differences between comparison groups: male vs. female (I), \u0026lt;45 vs. ≥45 years (II), literate vs. illiterate (III), and low vs. non-low income (IV) (*\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05, **\u003cem\u003ep\u003c/em\u003e\u0026lt;0.01, ***\u003cem\u003ep\u003c/em\u003e\u0026lt;0.001). Hash symbols (#) denote significant interethnic variations between Lahu and Wa groups (#\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05, ##\u003cem\u003ep\u003c/em\u003e\u0026lt;0.01, ###\u003cem\u003ep\u003c/em\u003e\u0026lt;0.001).\u003c/p\u003e","description":"","filename":"Figure2.SexIAgeIIEducationIIIandIncomeIVStratifiedDiabetesKnowledgeAmongLahuandWaEthnicGroups.png","url":"https://assets-eu.researchsquare.com/files/rs-7527719/v1/82d3d2e0f889abc60adf5c04.png"},{"id":94763073,"identity":"0294efd5-bf7b-48eb-b2a2-8e61465fad28","added_by":"auto","created_at":"2025-10-30 12:17:16","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":139942,"visible":true,"origin":"","legend":"\u003cp\u003eMultivariable Analysis of Risk Factors for Diabetes Awareness and Knowledge by Ethnicity\u003c/p\u003e","description":"","filename":"Figure3.MultivariableAnalysisofRiskFactorsforDiabetesAwarenessandKnowledgebyEthnicity.png","url":"https://assets-eu.researchsquare.com/files/rs-7527719/v1/6bce51ed16bdaf59d2a8c862.png"},{"id":94827316,"identity":"da659e54-159b-4ec1-af3a-7db36d289100","added_by":"auto","created_at":"2025-10-31 06:57:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1736472,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7527719/v1/9533df02-903c-4bea-8f06-153ed41ad795.pdf"},{"id":94763068,"identity":"74669141-3f24-4fe9-8c2b-d8ea46b58a9c","added_by":"auto","created_at":"2025-10-30 12:17:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":117549,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfile1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7527719/v1/7cf6dfdbbf6c456820246597.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Knowledge and practice of diabetes mellitus among Lahu and Wa populations in southwest China: a cross‑sectional study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDiabetes mellitus (DM) is a metabolic disorder characterized by hyperglycemia resulting from insufficient insulin secretion and/or impaired insulin action(1). It has been ranked among the top ten global causes of mortality and disability(2). The prevalence of diabetes has shown a significant upward trend over the past three decades, and the global number of people with diabetes will reach 783\u0026nbsp;million by 2045, imposing tremendous pressure on healthcare systems worldwide and driving continuous increases in medical expenditures(3, 4). Notably, approximately 81% of people with diabetes reside in low- and middle-income countries(4). In China, rapid urbanization and economic growth have further exacerbated the diabetes epidemic, with particularly prominent disease burdens observed in rural areas and ethnic minority populations(5).\u003c/p\u003e\u003cp\u003eBehavioral and lifestyle factors play a pivotal role in the prevention and management of diabetes and its complications. Evidence-based medical research demonstrates that modifiable risk factors primarily include unhealthy diet, physical inactivity, smoking, and excessive alcohol consumption(6). Multiple large-scale cohort studies have confirmed that lifestyle interventions\u0026mdash;such as weight management, balanced nutrition, and regular physical activity\u0026mdash;can significantly reduce the incidence of diabetes(7, 8). However, clinical practice reveals that adherence to recommended interventions remains suboptimal, even with clear evidence of benefits, particularly in regions with limited healthcare resources(5, 9)China\u0026rsquo;s chronic disease surveillance data indicate significant disparities in health behaviors between urban and rural populations(10). Notably, central obesity rates and physical inactivity continue to rise among ethnic minority groups and populations with low socioeconomic status(11), underscoring the necessity for targeted, precision interventions in these high-risk groups.\u003c/p\u003e\u003cp\u003eHealth literacy serves as a critical determinant in facilitating effective self-management behaviors. Evidence suggests that acquiring diabetes-related knowledge significantly enhances individuals' disease awareness and self-efficacy, thereby increasing their likelihood of adopting standardized self-management practices(12). Although China has made substantial progress in improving population health literacy through initiatives such as the National Basic Public Health Services (NBPHS)(13)and the \"Healthy China 2030\" development plan(14), regional disparities remain pronounced. Rural and ethnic minority regions continue to lag behind the national average in health literacy(13, 15)This knowledge gap is particularly severe among \"direct transition\" ethnic groups (e.g., Lahu and Wa) in Southwest China, who exhibit markedly insufficient health literacy and health-related skills(16, 17). However, systematic research on diabetes awareness and behavioral practices in these underserved populations remains lacking. To address this gap, this study conducts the first comprehensive investigation of diabetes knowledge and practices among the Lahu and Wa populations in Southwest China.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis cross-sectional investigation employed a multi-stage sampling design to recruit participants between August 2009 and September 2010 in Yunnan Province, China. The sampling framework involved: (1) stratified random selection of two ethnically diverse counties based on Lahu and Wa demographic representation; (2) economic stratification of counties into tertiles (high, medium, low) using per capita GDP criteria; (3) random selection of one township per stratum with subsequent probability-proportional-to-size sampling of two villages per township.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study enrolled adult participants (age \u0026ge;18 years) who self-identified as either Lahu or Wa ethnicity and maintained uninterrupted local residency for \u0026ge;5 years. Exclusion criteria comprised: (1) clinically significant cognitive impairment (precluding reliable survey responses), and (2) language barriers sufficient to compromise informed consent or questionnaire comprehension.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResearch instruments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study utilized a structured, pretested questionnaire for systematic data collection (see supplementary file 1 for details). Socio-demographic characteristics included educational attainment (with literate defined as \u0026ge;6 completed years of formal schooling) and income level (Low income was classified according to China National Bureau of Statistics thresholds: \u0026le;1,196 yuan [2009] and \u0026le;1,274 yuan [2010] annual per capita). Diabetes-related awareness and knowledge were evaluated using 15 items selected from the questionnaire, beginning with a screening question (\u0026ldquo;Have you ever heard of diabetes?\u0026rdquo;). Participants responding affirmatively were asked subsequent questions examining information sources (5 items), symptom knowledge (4 items), risk factor knowledge (5 items), prevention knowledge (3 items, in which diet control includes eating more fiber-rich foods, eating more whole grains and reducing intake of high-fat and high-sugar foods). One additional item assessed treatment awareness (\u0026ldquo;Do you know how diabetes is treated?\u0026rdquo;). Knowledge items employed categorical responses (\u0026ldquo;yes\u0026rdquo; or \u0026ldquo;no\u0026rdquo;). Domain-specific scores were calculated by summing correct responses, with total knowledge scores dichotomized (0 = no knowledge; \u0026ge;1 = some knowledge). Behavioral assessments included tobacco use (defined as \u0026ge;1 cigarette daily for \u0026gt;6 consecutive months), alcohol consumption (weekly intake of traditional beverages including Baijiu, beer, wine, or rice wine), dietary vegetable proportion (dichotomized at 50% of total consumption), and physical activity intensity. Physical activity was classified as heavy (manual farming causing significant cardiorespiratory strain), moderate (household chores involving moderate exertion), or light (sedentary occupations with less than 25% active movement or mental work).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTrained research staff conducted standardized face-to-face interviews using the questionnaire to collect data. Anthropometric measurements (height and weight) were collected after an 8-12 hour fasting period, with body mass index (BMI) calculated as weight (kg)/height\u0026sup2; (m\u0026sup2;). Overweight and obesity were defined according to Chinese criteria as BMI \u0026ge;24.0 kg/m\u0026sup2; and \u0026ge;28.0 kg/m\u0026sup2;, respectively(18).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData were analyzed using SPSS (version 27.0). Categorical variables were presented as frequencies (percentages) with between-group comparisons performed using \u0026chi;\u0026sup2; tests. Non-normally distributed continuous variables were expressed as median values (interquartile range [IQR]) and analyzed with Mann-Whitney U tests. For diabetes knowledge assessment, the analytical framework incorporated three dimensions: (1) cross-ethnic comparisons (Lahu vs. Wa populations); (2) intra-ethnic stratification by sex, age categories (\u0026lt;45 vs. \u0026ge;45 years), education (illiterate vs. literate), and income levels (Low income vs. Non-low income); and (3) cross-stratification analyses of ethnic differences across demographic subgroups. Multivariable logistic regression models identified determinants of: (1) heard of diabetes and (2) knowledge retention, with results reported as adjusted odds ratios (ORs) and 95% confidence intervals (CIs). Statistical significance was determined at \u0026alpha;=0.05 (two-tailed).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eSocio-demographic characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study included 2,281 Lahu (996 males; 1,285 females) and 2,876 Wa (1,107 males; 1,769 females) participants. The Lahu population had a median age of 40 years, with around 61% aged \u0026lt;45 years (no sex difference, p=0.944). In contrast, Wa males were significantly older (median 45 years; 49.2% \u0026lt;45 years) than Wa females (58.6% \u0026lt;45 years, p\u0026lt;0.001). Wa participants showed substantially higher literate rates (males: 67.3% vs 19.0%; females: 59.2% vs 23.0%; all p\u0026lt;0.001) compared to Lahu. Low-income prevalence was significantly higher in Wa females (65.2%) than males (59.3%, p=0.001), but did not differ between Lahu sexes (p=0.207) (Table 1).\u003c/p\u003e\n\u003cp\u003eTable 1. Socio-demographic Characteristics of Lahu and Wa Populations by Sex.\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"705\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" style=\"width: 169px;\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 216px;\"\u003e\n \u003cp\u003eLahu (n=2281)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 228px;\"\u003e\n \u003cp\u003eWa (n=2876)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003csub\u003emale\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003csub\u003efemale\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003csub\u003elahu\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003csub\u003ewa\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e40(28.75,50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e40(28,51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.794\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e45(35,55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e41(32,51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026lt;45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e607(60.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e785(61.10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.944\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e545(49.20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1036(58.60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.160\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026gt;=45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e389(39.10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e500(38.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e562(50.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e733(41.40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eAnnual income per capita (Yuan)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1250(1147,1667)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1250(1147,1600)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.008\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1250(1250,1600)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1250(1250,1500)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eLow income\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e379(38.10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e456(35.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.207\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e451(40.70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e615(34.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e0.208\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.680\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e617(61.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e829(64.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e656(59.30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1154(65.20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eLiterate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e807(81.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e989(77.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.019\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e362(32.70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e722(40.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e189(19.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e296(23.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e745(67.30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1047(59.20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eNote: \u003cem\u003ep\u003c/em\u003e\u003csub\u003elahu\u0026nbsp;\u003c/sub\u003e=\u003cem\u003ep\u003c/em\u003e for Lahu male vs. female; \u003cem\u003ep\u003c/em\u003e\u003csub\u003eWa\u003c/sub\u003e = \u003cem\u003ep\u003c/em\u003e for Wa male vs. female; \u003cem\u003ep\u003c/em\u003e\u003csub\u003emale\u003c/sub\u003e = \u003cem\u003ep\u003c/em\u003e for Lahu male vs. Wa male; \u003cem\u003ep\u003c/em\u003e\u003csub\u003efemale\u003c/sub\u003e = \u003cem\u003ep\u003c/em\u003e for Lahu female vs. Wa female.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKnowledge towards diabetes mellitus\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOnly 9.2% of Lahu participants reported having heard of diabetes, compared to 30.8% of Wa (p\u0026lt;0.001). Both groups primarily obtained diabetes information from television and physicians, with minimal use of print media (\u0026lt;2%). Lahu utilized educational materials more frequently (8.6% vs 2.5%, p\u0026lt;0.001). Wa participants demonstrated higher overall diabetes knowledge level (some knowledge: 72.2% vs 62.7%, p=0.007),though both ethnic groups displayed severely right-skewed total knowledge score distributions (median=1, IQR=0-2), with only 18.7% of Lahu and 16.2% of Wa participants achieving scores \u0026ge;3. Similar right-skewed distributions were observed across all knowledge domains (symptoms, risk factors, prevention, and treatment), with scores predominantly clustered at 0-1. Lahu participants were less likely to recognize overeating as a diabetes risk factor than Wa (10.5% vs. 19.8%, p=0.002) but more frequently identified family history (6.2% vs. 2.5%, p=0.006). No other significant interethnic differences were observed in diabetes knowledge (Table 2, Figure 1).\u003c/p\u003e\n\u003cp\u003eTable 2. Knowledge of Diabetes Among Lahu and Wa Population\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"108%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 42px;\"\u003e\n \u003cp\u003eDiabetes Knowledge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003eLahu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003eWa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eHeard of diabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e2072(90.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e1991(69.20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e355.408\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e209(9.20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e885(30.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eSources of diabetes-related information\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eTelevision\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e162(77.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e720(81.40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e1.599\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.206\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e47(22.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e165(18.60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003ePhysician\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e173(82.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e686(77.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e2.774\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.096\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e36(17.20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e199(22.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eNewspapers/Magazines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e206(98.60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e870(98.30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.791\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e3(1.40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e15(1.70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eEducational Materials\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e191(91.40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e863(97.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e18.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e18(8.60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e22(2.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e73(34.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e349(39.40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e1.449\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.229\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e136(65.10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e536(60.60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eNumber of Sources\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e192(91.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e849(95.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e23.754\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e5(2.40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e27(3.10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e10(4.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e2(0.20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e2(1.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e7(0.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eKnowledge of diabetes symptoms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003ePolyuria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e157(75.10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e634(71.60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e1.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.312\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e52(24.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e251(28.40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003ePolydipsia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e184(88.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e770(87.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.688\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e25(12.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e115(13.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003ePolyphagia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e186(89.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e799(90.30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.312\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.576\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e23(11.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e86(9.70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eWeight loss\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e180(86.10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e787(88.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e1.294\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.255\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e29(13.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e98(11.10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eKnowledge of diabetes risk factors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eObesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e195(93.30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e842(95.10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e1.159\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.282\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e14(6.70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e43(4.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eDrink alcohol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e187(89.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e793(89.60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.956\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e22(10.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e92(10.40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eTobacco use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e197(94.30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e858(96.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e3.561\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e12(5.70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e27(3.10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eOvereating\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e187(89.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e710(80.20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e9.793\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e22(10.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e175(19.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eFamily History\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e196(93.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e863(97.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e7.613\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e13(6.20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e22(2.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eKnowledge of diabetes prevention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eExercise\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e185(88.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e780(88.10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.878\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e24(11.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e105(11.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eDiet Control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e171(81.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e671(75.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e3.432\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.064\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e38(18.20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e214(24.20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eWeight Management\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e192(91.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e841(95.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e3.211\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.073\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e17(8.10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e44(5.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eKnowledge of diabetes treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e205(98.10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e870(98.30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.827\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e4(1.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e15(1.70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003eTotal diabetes knowledge level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eNo knowledge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e78(37.32%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e246(27.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e7.357\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.007\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eSome knowledge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e131(62.68%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e639(72.20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eFactors associated with participant\u0026rsquo;s knowledge towards diabetes mellitus\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConsistent ethnic disparities were observed across all demographic strata (gender, age, education, and income levels), with Wa participants demonstrating significantly higher diabetes awareness rates than their Lahu counterparts (p\u0026lt;0.001 for all comparisons). Additionally, the Wa exhibited significantly higher overall diabetes knowledge levels than the Lahu in male, \u0026ge;45-year-old, and low-income subgroups (all p\u0026lt;0.05) (Figure 2).\u003c/p\u003e\n\u003cp\u003eMultivariate logistic regression analysis identified distinct ethnic-specific patterns in both diabetes awareness and knowledge (Figure 3). Gender differences were particularly notable, with female sex demonstrating significantly lower diabetes awareness in both populations - more strongly in Lahu women (OR = 2.16, 95% CI: 1.57-2.96) than in Wa women (OR = 1.21, 95% CI: 1.03-1.44). No other demographic factors (age, income status, or literate) showed statistically significant associations with diabetes awareness in either group (all p\u0026gt;0.05). Regarding diabetes knowledge, literacy status emerged as the only significant predictor among Wa participants (OR=1.46, 95% CI: 1.00-2.11), whereas no significant predictors were identified in the Lahu population.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePractices towards diabetes mellitus\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMales in both ethnic groups exhibited significantly higher rates of tobacco use (Lahu: 77.6% vs 38.3%; Wa: 79.8% vs 33.6%) and alcohol consumption (Lahu: 66.9% vs 30.2%; Wa: 66.0% vs 14.9%) compared to their female counterparts (all p\u0026lt;0.001). Lahu females demonstrated higher smoking (38.3% vs 33.6%) and drinking rates (30.2% vs 14.9%) than Wa females, along with greater overweight/obesity prevalence (16.2% vs 7.9%) and lower heavy physical activity participation (43.3% vs 61.7%) compared to Lahu males (all p\u0026lt;0.01). Wa participants showed more balanced sex distribution in physical activity levels (67.0% males vs 64.4% females, p=0.086) and significantly higher vegetable consumption rates than Lahu participants in both sexes (both p\u0026lt;0.001). Obesity prevalence remained consistently low across all subgroups (\u0026lt;3.5%) (Table 3).\u003c/p\u003e\n\u003cp\u003eTable 3. Diabetes Practices Stratified by sex in Southwest China\u0026apos;s Lahu and Wa Populations\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"709\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" style=\"width: 170px;\"\u003e\n \u003cp\u003ePractices\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 217px;\"\u003e\n \u003cp\u003eLahu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 229px;\"\u003e\n \u003cp\u003eWa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003csub\u003emale\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003csub\u003efemale\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003csub\u003elahu\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003csub\u003ewa\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eTobacco use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e223(22.40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e793(61.70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e224(20.20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1174(66.40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e0.228\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.008\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e773(77.60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e492(38.30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e883(79.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e595(33.60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eDrink alcohol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e330(33.10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e897(69.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e376(34.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1505(85.10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e0.686\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e666(66.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e388(30.20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e731(66.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e264(14.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003ePhysical activity intensity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eHeavy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e615(61.70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e557(43.30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e742(67.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1139(64.40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e0.086\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.041\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e293(29.40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e540(42.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e282(25.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e456(25.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eLight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e88(8.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e188(14.60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e83(7.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e174(9.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eDietary vegetable proportion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026lt;=50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e701(70.40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e827(64.40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e398(36.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e666(37.60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e0.360\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026gt;50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e295(29.60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e458(35.60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e709(64.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1103(62.40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eBMI Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e917(92.10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1077(83.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e913(82.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1422(80.40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e0.375\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eoverweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e71(7.10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e173(13.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e162(14.60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e291(16.40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eobesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e8(0.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e35(2.70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e32(2.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e56(3.20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eNote: \u003cem\u003ep\u003c/em\u003e\u003csub\u003elahu\u0026nbsp;\u003c/sub\u003e=\u003cem\u003ep\u003c/em\u003e for Lahu male vs. female; \u003cem\u003ep\u003c/em\u003e\u003csub\u003eWa\u003c/sub\u003e = \u003cem\u003ep\u003c/em\u003e for Wa male vs. female; \u003cem\u003ep\u003c/em\u003e\u003csub\u003emale\u003c/sub\u003e = \u003cem\u003ep\u003c/em\u003e for Lahu male vs. Wa male; \u003cem\u003ep\u003c/em\u003e\u003csub\u003efemale\u003c/sub\u003e = \u003cem\u003ep\u003c/em\u003e for Lahu female vs. Wa female.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssociation Between Diabetes Knowledge and Practices\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong Lahu participants who had heard of diabetes, tobacco use was significantly lower (46.4% vs 56.4%, p=0.006) and overweight/obesity prevalence higher (26.3% vs 11.2%, p\u0026lt;0.001) compared to unaware individuals. Wa participants showed no significant differences in these practices by awareness status (all p\u0026gt;0.05). For those with some diabetes knowledge, Lahu participants demonstrated significantly lower heavy physical activity among the knowledgeable group (45.0% vs 62.8%, p=0.033), while Wa participants with knowledge reported lower vegetable consumption (\u0026gt;50% intake: 60.7% vs 67.9% in knowledgeable vs less knowledgeable, p=0.048). No significant associations were found between knowledge levels and alcohol consumption patterns in either group (all p\u0026gt;0.05) (Table 4).\u003c/p\u003e\n\u003cp\u003eTable 4. Diabetes Practices Stratified by Awareness and Knowledge Status in Southwest China\u0026apos;s Lahu and Wa Populations\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"651\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 94px;\"\u003e\n \u003cp\u003eGoup\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" style=\"width: 163px;\"\u003e\n \u003cp\u003ePractices\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 195px;\"\u003e\n \u003cp\u003eLahu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 198px;\"\u003e\n \u003cp\u003eWa\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003csub\u003elahu\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003csub\u003ewa\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eHeard of Diabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003eTobacco use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e904(43.63%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e112(53.59%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e963(48.37%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e435(49.15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e0.697\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e1168(56.37%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e97(46.41%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e1028(51.63%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e450(50.85%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003eDrink alcohol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e1106(53.38%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e121(57.89%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e0.212\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e1280(64.29%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e601(67.91%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e0.060\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e966(46.62%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e88(42.11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e711(35.71%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e284(32.09%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003ePhysical activity intensity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eHeavy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e1064(51.35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e108(51.67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e0.536\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e1310(65.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e571(64.52%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e0.303\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e751(36.25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e82(39.23%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e514(25.82%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e224(25.31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eLight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e257(12.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e19(9.09%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e0.335\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e167(8.39%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e90(10.17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003eDietary vegetable proportion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026lt;=50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e1392(67.18%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e136(65.07%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e734(36.87%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e330(37.29%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e0.829\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026gt;50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e680(32.82%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e73(34.93%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e1257(63.13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e555(62.71%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003eBMI Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e1840(88.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e154(73.68%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e1612(80.96%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e723(81.69%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e0.325\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eoverweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e198(9.56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e46(22.01%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e323(16.22%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e130(14.69%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eobesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e34(1.64%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e9(4.31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e56(2.81%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e32(3.62%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eSome Diabetes knowledge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003eTobacco use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e41(52.56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e71(54.20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e0.819\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e109(44.31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e326(51.02%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e0.074\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e37(47.44%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e60(45.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e137(55.69%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e313(48.98%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003eDrink alcohol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e47(60.26%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e74(56.49%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e0.594\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e169(68.70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e432(67.61%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e0.755\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e31(39.74%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e57(43.51%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e77(31.30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e207(32.39%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003ePhysical activity intensity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eHeavy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e49(62.82%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e59(45.04%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.033\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e162(65.85%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e409(64.01%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e0.741\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e22(28.21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e60(45.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e62(25.20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e162(25.35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eLight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e7(8.97%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e12(9.16%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e22(8.94%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e68(10.64%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003eDietary vegetable proportion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026lt;=50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e53(67.95%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e83(63.36%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e0.501\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e79(32.11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e251(39.28%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.048\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026gt;50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e25(32.05%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e48(36.64%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e167(67.89%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e388(60.72%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003eBMI Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e56(71.79%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e98(74.81%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e0.852\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e197(80.08%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e526(82.32%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e0.255\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eOverweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e18(23.08%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e28(21.37%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e36(14.63%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e94(14.71%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eObesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e4(5.13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e5(3.82%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e13(5.28%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e19(2.97%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur survey revealed strikingly low awareness of diabetes among the studied ethnic minorities. Only 9.20% of Lahu and 30.80% of Wa respondents reported having heard of diabetes, rates significantly lower than those reported in contemporaneous studies from rural Northeast India (91%) (19), urban South India (75.5%)(20), and rural Bangladesh (93%)(21). The knowledge assessment demonstrated even more concerning results. In a 13-item diabetes knowledge test, fewer than 20% of respondents from either ethnic group could correctly answer three or more questions, indicating severe knowledge deficiencies. This overall level of diabetes knowledge was substantially inferior to data reported from Middle Eastern countries such as Saudi Arabia(22)and Jordan(23). Notably, the Wa population exhibited higher diabetes awareness and knowledge than the Lahu, potentially attributable to their higher educational attainment, which may facilitate more active health information-seeking behaviors(24). This difference was partially evidenced by their distinct health knowledge acquisition patterns: Wa respondents predominantly relied on active channels (newspapers/magazines, physician consultations), while Lahu respondents primarily depended on passive information sources (television broadcasts, educational materials).\u003c/p\u003e\u003cp\u003eOnly 37.3% of Lahu and 40.1% Wa respondents recognized at least one classic diabetes symptom (polyuria, polydipsia, polyphagia or weight loss), which, while higher than other indigenous ethnic groups in Yunnan Province (Naxi: 11.8%; Lisu: 4.2%; Dai: 15.0%; Jingpo: 1.7%)(25), was significantly lower than reports from semi-urban Oman (57.0%) (26)and South India (73.5%) (27). Regarding specific symptom awareness, both groups showed highest recognition for polyuria (Lahu: 24.9%; Wa: 28.4%), while other symptoms maintained only about 10% awareness, mirroring patterns observed in Oman (polyuria: 44.8%; weight loss: 24.7%; polydipsia: 20.1%)(26)More critically, substantial knowledge gaps existed in risk factor awareness, with merely 6.7% of Lahu and 4.9% of Wa recognizing obesity's risk (vs Malaysia 40%(28) and Oman 29.5% (26)), and even lower awareness of familial predisposition (Lahu: 6.2%; Wa: 2.5%). Preventive measure awareness was equally deficient, with dietary control (Lahu: 18.2%; Wa: 24.2%), physical activity (Lahu: 11.5%; Wa: 11.9%) and weight management (Lahu: 8.1%; Wa: 5.0%) all lagging behind Oman's reports (63.1%, 42.3% and 17.9% respectively) (26). Most alarmingly, treatment awareness was below 2% in both groups, contrasting sharply with India (85.2%)(27), Saudi Arabia(49.2%~85.5%)(22) and France༈87.5%༉(29), highlighting substantial room for improvement in diabetes education among China's ethnic minorities. The relatively low diabetes knowledge levels among the Lahu and Wa ethnic groups may be attributed to the underdeveloped socioeconomic conditions(30), poor educational attainment(16, 17), and inadequate health resources in their concentrated residential areas(15, 31, 32), which collectively contribute to low health literacy. These findings demonstrate an urgent need for culturally adapted, intensive health education programs targeting symptom recognition, risk factors, prevention strategies and treatment knowledge in these underserved populations.\u003c/p\u003e\u003cp\u003eThis study demonstrates gender as an independent determinant influencing diabetes awareness. In multivariate regression analyses, gender remained significantly associated with diabetes knowledge even after adjusting for confounders including age and socioeconomic status, with Lahu women exhibiting 2.15 times higher likelihood of diabetes awareness than their male counterparts. These findings align with previous studies conducted among Xinjiang Uyghur populations(33) and rural Indian populations(34), potentially attributable to gender-specific occupational characteristics in rural settings, traditional family roles, and socially-constructed health consciousness that encourages greater health concern among women(35). Notably, while existing literature consistently reports positive associations between diabetes knowledge and advancing age(36, 37), higher income(38), and improved educational attainment(37, 38), our study only identified a weak positive correlation between education level and diabetes awareness in the Wa population.\u003c/p\u003e\u003cp\u003eOverweight and obesity have been proved to be well-established risk factors for insulin resistance and type 2 diabetes development among Chinese adults(39), while high-intensity physical labor may exert protective effects through improved insulin sensitivity(40). We observed significantly lower overweight/obesity prevalence in both Lahu (male 7.9%, female 16.2%) and Wa (male 17.5%, female 19.6%) populations compared to other regions(41, 42), likely attributable to their prevalent high-intensity physical activity (\u0026gt;\u0026thinsp;40%) and agriculture-dominated lifestyle, consistent with findings from rural Xinjiang(43). However, the study revealed alarming high-risk behavioral patterns: exceptionally elevated smoking rates (male\u0026thinsp;\u0026gt;\u0026thinsp;75%, female\u0026thinsp;\u0026gt;\u0026thinsp;30%) substantially exceeding national averages (male 43.1%, female 1.6%) (44), other southwestern ethnic groups (18.6\u0026ndash;32.3%) (6), and Eastern Ethiopia populations (21.1%) (45); similarly prominent alcohol consumption (male\u0026thinsp;\u0026gt;\u0026thinsp;65%, female 14.9\u0026ndash;30.2%) with male rates far surpassing Eastern Ethiopia (36%) (45)and rural Xinjiang (Uyghur 8.08%, Han 41.20%) (43)Given substantial evidence establishing smoking and excessive alcohol consumption as independent diabetes risk factors(46, 47), we strongly recommend implementing targeted, intensive public health interventions specifically addressing these modifiable risk factors in Lahu and Wa communities.\u003c/p\u003e\u003cp\u003eThe comparative analysis revealed distinct behavioral differences between the Lahu and Wa ethnic groups. Notably, the Wa population demonstrated healthier behavioral patterns: gender-stratified analyses showed significantly higher vegetable intake and rates of heavy physical labor among both Wa men and women compared to their Lahu counterparts, with Wa women additionally exhibiting lower smoking and alcohol consumption rates than Lahu women - findings consistent with the Wa group's overall superior diabetes awareness and knowledge. Furthermore, within both ethnic groups, women demonstrated significantly lower smoking and alcohol consumption rates than their male counterparts, paralleling their relatively higher diabetes knowledge levels. These results support the health literacy-behavior improvement hypothesis, suggesting that enhanced diabetes knowledge may positively influence self-management behaviors(9, 48). However, unlike previous studies(22), our within-group comparisons found no significant behavioral advantages (in smoking, alcohol consumption, physical activity, or weight management) among those with diabetes knowledge, potentially attributable to the populations' overall knowledge levels remaining below the critical threshold required for effective behavioral modification(49). This finding highlights current deficiencies in health education interventions and underscores the need to develop culturally adapted diabetes education programs specifically tailored for the Lahu and Wa populations, coupled with sustainable health promotion mechanisms to facilitate the crucial knowledge-to-behavior transition.\u003c/p\u003e\u003cp\u003eTo our knowledge, this study represents the first systematic evaluation of diabetes-related knowledge and behavioral characteristics among the Lahu and Wa ethnic populations in Southwest China. However, several limitations should be acknowledged. First, the cross-sectional design precludes causal inference and cannot establish temporal relationships between diabetes knowledge and health behaviors. Second, despite employing face-to-face interviews for data collection, potential biases including recall bias (particularly regarding dietary and physical activity behaviors), social desirability bias (e.g., underreporting of smoking/alcohol consumption), and selection bias may persist. Third, due to sampling constraints, more mobile subpopulations such as university students and migrant workers - who typically exhibit higher health literacy levels - were not included, potentially leading to underestimation of overall diabetes awareness in these communities. Future studies should employ longitudinal designs incorporating more comprehensive sampling strategies and objective measurement approaches (e.g., biomarker assessments) to more accurately evaluate diabetes-related knowledge and behaviors in ethnic minority populations.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe Lahu and Wa ethnic groups in Southwest China exhibit alarmingly low diabetes awareness and knowledge, with the Wa population showing better health behaviors and knowledge than the Lahu, though neither group demonstrates significant behavioral improvements among diabetes-aware individuals; both groups display prevalent high-risk behaviors (especially males), highlighting the critical need for culturally tailored interventions to address these disparities in diabetes prevention and management.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eDM Diabetes mellitus\u003c/p\u003e\n\u003cp\u003eNBPHS National Basic Public Health Services\u003c/p\u003e\n\u003cp\u003eBMI Body mass index\u003c/p\u003e\n\u003cp\u003eIQR Interquartile range\u003c/p\u003e\n\u003cp\u003eOR Odds ratio\u003c/p\u003e\n\u003cp\u003eCI Confidence interval\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe confirm that all experiments were performed in accordance with the Declaration of Helsinki, and the informed consent was obtained from all subjects and their legal guardians. The Institutional Review Board of The First Affiliated Hospital of Kunming Medical University provided the Ethical approval for the study (2025L165).\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 used and analysed during the current study 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\u003eThis work was supported by the following funding sources: the National Natural Science Foundation of China (Grants No. 82160165, 81160104, and 30760087), the \u0026quot;Famous Doctor\u0026quot; Special Program of Yunnan Xingdian Talent Support Plan (Grant No. RLMY20220009), the Young and Middle-aged Academic and Technical Leaders Reserve Talents Project of Yunnan Province (Grant No. 202105AC160093), and the Key Project of Yunnan Provincial Clinical Medical Center for Endocrine and Metabolic Diseases (Grant No. 2024YNLCYXZX0073).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJC and WCG are co-first authors who contributed equally to data collection, interpretation, and manuscript drafting. JC performed the data analysis and prepared the figures and tables. HJY and HFL designed the study and critically revised the manuscript, with HFL responsible for funding acquisition. All authors reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eIslam K, Islam R, Nguyen I, Malik H, Pirzadah H, Shrestha B, et al. Diabetes Mellitus and Associated Vascular Disease: Pathogenesis, Complications, and Evolving Treatments. Advances in therapy. 2025;42(6):2659-78.\u003c/li\u003e\n\u003cli\u003eFeigin VL, Roth GA, Naghavi M, Parmar P, Krishnamurthi R, Chugh S, et al. Global burden of stroke and risk factors in 188 countries, during 1990\u0026ndash;2013: a systematic analysis for the Global Burden of Disease Study 2013. 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BMC Public Health. 2017;17(1):535.\u003c/li\u003e\n\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-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Diabetes mellitus, Knowledge, Practice, Ethnic minorities, Lahu population, Wa population","lastPublishedDoi":"10.21203/rs.3.rs-7527719/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7527719/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eDiabetes mellitus is a major global health challenge, contributing to substantial morbidity and mortality worldwide. However, rural and ethnic minority communities often experience disparities in diabetes care outcomes compared to other regions. This study aimed to evaluate diabetes-related knowledge and practices, identify influencing factors, and assess the potential association between diabetes knowledge and self-management behaviors among the Lahu and Wa ethnic minority populations in Southwest China.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eA cross-sectional study was conducted in Yunnan Province (2009\u0026ndash;2010) using a multi-stage sampling design. Face-to-face interviews were performed with 2,281 Lahu and 2,876 Wa adults (aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years) to collect data on socio-demographics, diabetes knowledge (symptoms, risk factors, prevention, and treatment), and practices (smoking, alcohol use, diet, physical activity, and overweight/obesity). Descriptive statistics, χ\u0026sup2; tests, and logistic regression were used for analysis.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eDiabetes awareness was low overall (Lahu: 9.20%; Wa: 30.80%), with significant interethnic disparities. The Wa population demonstrated a higher knowledge level (72.20% vs. 62.68%, p\u0026thinsp;=\u0026thinsp;0.007) and healthier behaviors (e.g., higher vegetable intake, lower female smoking/drinking rates) compared to the Lahu. No significant behavioral improvements were observed in smoking, alcohol use, physical activity, or weight management among participants with diabetes knowledge. Smoking (male: \u0026gt;75%; female: \u0026gt;30%) and alcohol use (male: \u0026gt;65%; female: 14.9\u0026ndash;30.2%) remained prevalent across both groups. Female sex and literacy (Wa only) were positively associated with diabetes knowledge.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThe findings highlight the poor knowledge and practice regarding diabetes among the Lahu and Wa populations, with acquired diabetes knowledge failing to translate into measurable behavioral improvements. These results underscore the need for culturally tailored interventions to improve diabetes prevention and management in these underserved communities, especially among male populations.\u003c/p\u003e","manuscriptTitle":"Knowledge and practice of diabetes mellitus among Lahu and Wa populations in southwest China: a cross‑sectional study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-30 12:17:11","doi":"10.21203/rs.3.rs-7527719/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-07T13:28:24+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-04T06:38:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"193474363335899211015142327343528830406","date":"2025-10-26T14:46:06+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-22T14:36:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"172478699708067445930798685925565721283","date":"2025-10-16T07:49:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"295461587775753377190326523480526351856","date":"2025-10-16T07:24:30+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-16T07:14:04+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-25T07:39:26+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-12T08:17:14+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-11T13:27:50+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2025-09-11T13:24:36+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"271aa4cc-ef6d-4fde-b0df-feb1a6fd07d5","owner":[],"postedDate":"October 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-01-20T15:57:14+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-30 12:17:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7527719","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7527719","identity":"rs-7527719","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}
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