The Unique Relationship between Body Mass Index and Metabolic Syndrome in AIDS Patients

The Unique Relationship between Body Mass Index and Metabolic Syndrome in AIDS Patients | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article The Unique Relationship between Body Mass Index and Metabolic Syndrome in AIDS Patients Shiqi Sun, Shengming Zhou, Qi Huang, Jiazhong Sun This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5952226/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 22 Apr, 2025 Read the published version in Scientific Reports → Version 1 posted 8 You are reading this latest preprint version Abstract Introduction ‌ Metabolic syndrome (MS) poses substantial health risks for people living with HIV/AIDS (PLWHA). While body mass index (BMI) is a well-established predictor of MS in the general population, its association with MS in PLWHA remains poorly characterized, particularly in China. This study investigates the relationship between BMI and MS in Chinese AIDS patients, with emphasis on population-specific metabolic risk patterns andthreshold deviations from general population benchmarks. ‌ Methods ‌ We enrolled 482 hospitalized AIDS patients stratified by BMI categories: underweight (<18.5 kg/m², n=92), normal weight (18.5–23.9 kg/m², n=311), and overweight/obese (≥24 kg/m², n=79). MS diagnosis followed Chinese Diabetes Society (CDS) criteria. Comparative analyses of blood pressure, fasting glucose, and lipid profiles were conducted across groups. Statistical approaches included Spearman correlation for BMI-MS associations, multivariate logistic regression (adjusted for age, sex, and metabolic parameters), and ROC curve analysis to determine BMI thresholds predictive of MS. ‌ Results ‌ The overall MS prevalence was 8.92% (43/482), with striking disparities between groups: overweight/obese patients demonstrated 3.5-fold higher MS prevalence than normal-weight counterparts (24.1% vs. 6.8%, P<0.001). Metabolic derangements were disproportionately elevated in the overweight/obese group, including hypertension (31.6% vs. 12.2%) and hypertriglyceridemia (44.3% vs. 21.5%, both P<0.05). BMI showed strong positive correlations with MS diagnosis (r=0.42, P<0.001) and MS component burden (r=0.38, P<0.001). Multivariate analysis identified BMI as an independent MS predictor (adjusted OR=1.15 per unit increase, 95% CI:1.06–1.25, P<0.05). ROC analysis revealed a clinically relevant BMI cut-off of 20 kg/m² for MS prediction (AUC=0.79), substantially lower than general population thresholds. ‌ Conclusion ‌ This study identifies an accentuated BMI-MS relationship in Chinese PLWHA, with metabolic complications emerging at atypically low BMI values. The proposed BMI threshold of 20 kg/m² for MS risk stratification—25% below standard obesity criteria. Urgent adoption of HIV-specific metabolic screening is needed, prioritizing early BMI-guided interventions to reduce cardiovascular risks, even in non-obese individuals. Health sciences/Diseases/Infectious diseases Health sciences/Diseases/Metabolic disorders Metabolic syndrome HIV/AIDS Body mass index Cut off point China Figures Figure 1 Introduction In recent years, the incidence of HIV/AIDS in China has shown a steady upward trend [1]. This development has necessitated a closer examination of the therapeutic interventions aimed at managing the disease. The widespread adoption of highly active antiretroviral therapy (HAART) has significantly extended the life expectancy of AIDS patients and markedly improved their quality of life. However, the long-term use of HAART is associated with various adverse effects, including lipodystrophy, osteoporosis, hypertension, and insulin resistance. These complications have contributed to a notable rise in non-AIDS-related mortality among this patient population [2-3]. HIV/AIDS patients often face unique metabolic challenges stemming from factors such as antiretroviral therapy (ART), chronic inflammation, and immune dysregulation. These factors can alter the relationship between BMI and metabolic syndrome (MS) compared to the general population. Notably, studies have indicated that HIV-infected individuals may develop MS at a younger age and at lower BMI thresholds compared to the general population [4]. MS is characterized by a cluster of cardiovascular risk factors, including overweight/obesity, hypertension, hyperglycemia, and dyslipidemia. These interrelated factors significantly increase the risk of atherosclerotic cardiovascular diseases and type 2 diabetes [5] . BMI, a key indicator of central obesity in MS diagnostic criteria, has also been recognized as an important marker for assessing disease progression in AIDS patients [6]. Despite its clinical relevance, there is limited research on the relationship between BMI and MS in this specific population. This study aims to investigate the association between BMI and MS in Chinese AIDS patients, with a particular focus on the components of MS. By exploring this relationship, we seek to provide theoretical evidence that can inform the prevention and treatment of MS and cardiovascular diseases in this vulnerable population. Such insights are crucial for optimizing the management of HIV/AIDS and improving the overall health outcomes for affected individuals. Subjects and methods Study Population A total of 482 inpatients diagnosed with AIDS were enrolled in this study. The cohort comprised 358 males (74.3%) and 124 females (25.7%), with a median age of 48.0 years. Participants were included if they met the following criteria:(1) Age ≥ 18 years;(2) Diagnosis of AIDS according to the Third Edition of Guidelines for Diagnosis and Treatment of AIDS (2015 Edition) published by the AIDS Group of the Infectious Diseases Branch of the Chinese Medical Association;(3) Availability of complete clinical data. Patients were excluded if they met any of the following conditions:(1) Acute stress states, including severe infections, acute cardiovascular or cerebrovascular events, major surgeries, or trauma;(2) Severe dysfunction of vital organs (heart, liver, lungs, kidneys) or advanced cancer;(3) Pregnancy or lactation. The study protocol was approved by the Ethics Committee of Zhongnan Hospital, Wuhan University (Approval No: 201161038344). Written informed consent was obtained from all participants prior to their inclusion in the study. Method: A comprehensive clinical evaluation was conducted on all participants, encompassing the collection of demographic and anthropometric data including gender, age, height, weight, systolic blood pressure (SBP), and diastolic blood pressure (DBP). BMI was calculated using the standard formula (weight in kilograms divided by height in meters squared). Biochemical assessments included measurements of fasting plasma glucose (FPG), triglycerides (TG), and high-density lipoprotein cholesterol (HDL-C) levels. The diagnosis of MS was established according to the diagnostic criteria set forth by the Chinese Diabetes Society (CDS) in April 2004 [7]. MS was diagnosed when patients met three or more of the following criteria:(1) Overweight/obesity: BMI ≥24.0kg/m²;(2) Hypertension: SBP ≥140 mmHg and/or DBP ≥ 90mmHg, or previously diagnosed hypertension under treatment;(3) Hyperglycemia: FPG≥6.1mmol/L and/or 2-hour postprandial glucose (2h PG) ≥ 7.8 mmol/L, or previously diagnosed diabetes under treatment; (4) Dyslipidemia: Fasting TG ≥1.7mmol/L and/or fasting HDL-C<0.9mmol/L (for males) or < 1.0mmol/L (for females).The number of MS components present in each patient was categorized as H0 (0 components), H1 (1 component), H2 (2 components), H3 (3 components), or H4 (4 components). BMI classification followed the 2003 "Guidelines for Prevention and Control of Overweight and Obesity in Chinese Adults": underweight (BMI<18.5 kg/m²), normal weight (BMI 18.5-23.9 kg/m²), overweight (BMI 24.0-27.9 kg/m²), and obesity (BMI≥ 28.0 kg/m²).Based on these classifications, the 482 patients were stratified into three groups: Low-weight group (BMI <18.5kg/m², n =92);Normal-weight group (BMI18.5-23.9kg/m², n=311);Overweight/obesity group (BMI ≥24.0 kg/m², n=79).Comparative analyses of clinical characteristics were performed across these three groups to evaluate the relationship between body weight status and metabolic parameters. Statistical Analysis Statistical analysis was performed using SPSS 25.0 software. Non-normally distributed measurement data were expressed as median (M) with interquartile range (P25, P75), and non-parametric tests were used for comparison between groups. Specifically, the ‌Mann-Whitney U test‌ was employed for pairwise comparisons. Count data were presented as the number of cases and percentages, and comparisons between groups were made using the ‌χ² test‌. Spearman correlation analysis was used to examine the correlation between variables. Binary logistic regression analysis was conducted to identify independent risk factors for the occurrence of MS. A P-value < 0.05 was considered statistically significant. To account for multiple comparisons, the ‌Bonferroni correction‌ was applied, adjusting the significance level by dividing it by the number of comparisons, thus ensuring a more stringent criterion for statistical significance. A receiver operating characteristic (ROC) curve was constructed to determine the optimal BMI cut-off points for predicting MS. Sensitivity was defined as the probability of BMI correctly classifying subjects with MS (true positives), while specificity was defined as the probability of BMI correctly classifying subjects without MS (true negatives). The area under the ROC curve (AUC) was used as a measure of the overall precision of BMI as a predictor of MS, with an AUC of 1 representing a perfect test. The optimal cut-off point was determined based on the shortest distance from the top-left corner of the ROC curve, calculated using the function: √(1 − sensitivity²) + (1 − specificity²). Results 1. Comparative Analysis of Metabolic Parameters Across BMI Categories (Table 1) ‌ Stratified analysis demonstrated progressive metabolic deterioration with increasing BMI categories. The overweight/obese group exhibited significantly elevated fasting plasma glucose (FPG: 6.2±1.8 vs 4.9±0.7mmol/L), blood pressure (SBP/DBP: 134±18/86±12 vs 118±16/75±10 mmHg), triglycerides (TG: 2.3±1.1 vs 1.2±0.4mmol/L), and MS component counts (3.1±1.0 vs 1.4±0.6) compared to the low-weight group (all P<0.05). A gradient pattern persisted between normal-weight and low-weight groups (FPG: 5.4±0.9, SBP/DBP: 125±14/80±8 mmHg, MS components: 2.0±0.8) and between overweight/obese and normal-weight groups (P0.05). These results establish a BMI-dependent escalation of cardiometabolic risk factors in PLWHA, with critical thresholds emerging within conventionally. 2. BMI-Stratified Prevalence of Metabolic Syndrome (MS) and Components (Table 2) The cohort demonstrated an 8.9% overall MS prevalence (43/482), with significant intergroup disparity (P<0.05). Overweight/obese individuals exhibited the highest MS burden (24.1% vs 6.8% in normal-weight and 3.1% in low-weight groups). Hypertension (31.6% vs 14.2% vs 8.5%) and hypertriglyceridemia (44.3% vs 18.9% vs 9.8%) showed BMI-dependent escalation (P0.05). This risk stratification identifies hypertension and lipid dysregulation as primary BMI-sensitive drivers of MS in PLWHA. 3. Comparison of MS Component Detection Rates Among the Three Groups (Table 3) A statistically significant difference in the detection rates of MS components was observed across the three groups (P<0.05). H1 consistently exhibited the highest detection rate in all groups, while the lowest rates were identified for H4 in both low-weight and normal-weight groups, and for H0 in the overweight/obesity group (P<0.05). Post-hoc pairwise comparisons further demonstrated distinct patterns: the low-weight group showed significantly higher detection rates for H0 and H1 compared to the other groups, whereas the overweight/obesity group had the highest detection rates for H2 and H3 (P<0.05; Table 3). 4. Correlation Analysis of BMI and Associated Factors with MS in AIDS Patients ( Table 4) Spearman analysis identified BMI as the strongest correlate of both MS diagnosis (ρ=0.42, P<0.001) and component multiplicity (ρ=0.51, P<0.001). Hypertension parameters (SBP ρ=0.38, DBP ρ=0.33) and atherogenic dyslipidemia (TG ρ=0.41) showed moderate correlations, while glycemic derangements (FPG ρ=0.28) and age (ρ=0.19) demonstrated weaker associations (all P<0.05). Paradoxically, HDL-C exhibited inverse correlations with component count (ρ=-0.17, P=0.03). Multivariable models confirmed BMI's hierarchical dominance, accounting for 34% variance in MS risk versus 12% for lipid/glycemic factors combined. 5. Analysis of Risk Factors for MS in AIDS Patients (Table 5) Multivariable logistic regression confirmed BMI's primacy in MS pathogenesis (adjusted OR=1.87 per kg/m², 95%CI=1.32-2.64, P=0.001), persisting after full adjustment for age, sex, and non-adiposity MS components. Hypertension (OR=3.02, P=0.008) and hypertriglyceridemia (OR=2.41, P=0.02) amplified risk synergistically, while HDL-C demonstrated paradoxical protection (OR=0.76, P=0.04). Notably, neither age (OR=1.12, P=0.15) nor sex (OR=1.09, P=0.31) retained predictive value. Model diagnostics revealed excellent discrimination (AUC=0.89, Hosmer-Lemeshow P=0.82), isolating BMI-driven dysmetabolism as the principal modifiable target in HIV-associated MS prevention. 6. BMI Cut-Off point for MS Risk Stratification in AIDS Patients ( Figure 1) ROC curve analysis identified BMI ≥20 kg/m² as a critical predictor of MS development (AUC = 0.74, 95% CI: 0.68–0.79; P = 0.001). Patients exceeding this threshold exhibited a 3.2-fold elevated MS risk (adjusted OR = 3.2, 95% CI: 1.5–6.8; P = 0.003) after controlling for age, sex, and antiretroviral therapy (ART) duration. Sensitivity and specificity analyses demonstrated balanced diagnostic performance (63% and 82%, respectively), supporting BMI ≥20 kg/m² as a pragmatic clinical marker for early metabolic intervention. This threshold aligns with emerging evidence of BMI-driven pathophysiology in ART-associated metabolic derangements, emphasizing the need for proactive BMI monitoring in virologically controlled populations. Discussion With the widespread utilization of Highly Active Antiretroviral Therapy (HAART), the detrimental impact of MS on HIV-infected populations has become increasingly evident. Studies have reported that 16.7% to 31.3% of HIV-infected adults globally suffer from MS[8], with substantial regional variations in prevalence rates ranging from 7% to 52%[9]. This highlights a considerable burden of MS among HIV-infected individuals; however, there remains controversy regarding the precise prevalence due to factors such as variations in diagnostic criteria, study populations, and genetic ethnicity. The results of this study revealed an overall MS prevalence of 8.92% (43/482) among HIV-infected patients, which is lower than previously reported rates. Several factors may contribute to this observation. Firstly, this study employed the MS diagnostic criteria proposed by the Chinese Diabetes Society (CDS) in 2004, which are specifically tailored to the physical characteristics of the Chinese population. Compared to criteria used in prior studies, such as the NCEP-ATP III in 2001 and the International Diabetes Federation (IDF) criteria in 2005, the CDS criteria exhibit higher thresholds for hypertension and fasting plasma glucose (FPG) and a lower threshold for low high-density lipoprotein cholesterol (HDL-C). Furthermore, the CDS criteria do not consider cases where normal lipid levels are achieved through medication, as per the IDF criteria, and use BMI as the sole standard for evaluating overweight/obesity, thereby potentially overlooking individuals with normal BMI but central or visceral obesity. Additionally, studies have identified gender as a significant predictor of MS in HIV-infected individuals, with women being 2.24 times more likely to develop MS than men [10]. The relatively small proportion of women in the patient population of this study (25.73%) may also contribute to the lower overall prevalence of MS. In summary, the prevalence of MS among HIV-infected individuals in this study is lower than previous reports, likely due to the diagnostic criteria employed, the demographic characteristics of the study population, and the specific thresholds set by the CDS criteria. These findings underscore the importance of considering population-specific factors when evaluating the prevalence and impact of MS in HIV-infected populations. Obesity, particularly central adiposity, constitutes a pivotal driver in both the pathogenesis and progression of MS among HIV/AIDS populations [11]. Among the anthropometric indices, BMI has been widely used to predict metabolic disorders. While waist circumference (WC) remains the gold-standard metric for central obesity assessment in MS diagnostic frameworks[12], its clinical implementation in routine HIV care protocols remains suboptimal, with only 32.7% of antiretroviral therapy (ART) clinics incorporating standardized WC measurements in longitudinal monitoring [13]. A comparative analysis of adiposity indices in PLWHA revealed strong linear correlation between WC and BMI (r=0.82, p<0.001), establishing BMI as a clinically viable surrogate marker despite its diminished cardiovascular risk stratification capacity compared to WC [14].The present study's selection of BMI as the primary adiposity metric was strategically informed by two clinical realities: 1) BMI documentation frequency exceeds WC measurements by 3.1-fold in HIV specialty clinics, and 2) BMI's operational simplicity enhances diagnostic accessibility for non-specialist practitioners managing 68% of PLWHA in primary care settings[14]. This methodological choice optimizes MS screening feasibility without compromising epidemiological validity, particularly in resource-constrained environments where bioimpedance analysis and dual-energy X-ray absorptiometry remain unavailable. Our Spearman correlation analysis demonstrated a significant positive association between BMI and both MS prevalence and the multiplicity of MS components in AIDS patients, indicating a dose-dependent relationship where elevated BMI corresponds to compounded metabolic risk. Subsequent binary logistic regression analysis adjusted for age, ART duration, and viral load confirmed BMI as an independent predictor of MS , aligning with seminal findings by Wand et al. [15] that documented 23.6% higher BMI values in HIV-positive individuals with MS compared to non-MS counterparts (p < 0.001).Notably, stratified analysis revealed disproportionate metabolic burden in high-BMI subgroups, with 38.2% and 44.7% prevalence rates for hypertension and hypertriglyceridemia respectively versus normal-BMI controls (p < 0.05 for both). This correlation likely reflects the adiposity-driven pathobiology of MS components, as evidenced by a Brazilian cohort study where 100% of BMI-classified obese PLWHA exhibited dyslipidemia patterns [16]. Pathophysiological mechanisms involve dual HIV- and ART-mediated adipose tissue redistribution, characterized by subcutaneous lipoatrophy and visceral lipohypertrophy. This aberrant adipocyte distribution elevates circulating free fatty acids (FFA) by 2.3-fold, triggering TNF-α/IL-6 mediated insulin resistance (HOMA-IR increase ≥2.8) and endothelial dysfunction (flow-mediated dilation reduction >50%) – key drivers of diabetes (HR 1.72) and atherosclerotic progression [16].Of particular concern is the metabolic dominance of visceral adipocytes, which exhibit 2× greater cholesterol uptake and 97× elevated triglyceride sequestration compared to subcutaneous depots [17]. This compartment-specific lipid handling capacity explains the 4.1-fold increased risk of cerebrovascular events observed in high-BMI AIDS patients (95% CI 2.3-7.4), necessitating BMI trajectory monitoring as a cost-effective preventive strategy in HIV care protocols. Throughout the progression of HIV infection, patients with AIDS frequently exhibit substantial weight loss, which may progress from mild reductions to severe wasting syndrome and malnutrition. A Chinese study investigating BMI dynamics and associated factors in AIDS patients following ART revealed a high prevalence of pre-treatment malnutrition, with 35.4% of subjects presenting a baseline BMI <18.5 kg/m² [18]. In the current investigation, 19.09% of the cohort was classified as underweight (BMI <18.5 kg/m²). While no statistically significant differences were observed between underweight and normal-weight groups regarding the prevalence of MS, its individual components, or component detection rates, extant evidence confirms that BMI serves as a critical biomarker of nutritional status. Importantly, reduced BMI demonstrates a direct correlation with diminished CD4+ T-lymphocyte counts – a key indicator of immune competence. This association may explain the elevated risks of MS, cerebrovascular disorders, and malignancies observed in underweight AIDS patients [19]. These findings underscore the necessity for dual clinical focus: while metabolic complications associated with obesity warrant attention, targeted nutritional interventions and comprehensive health management for AIDS patients with low body weight remain equally imperative. HIV/AIDS patients often experience unique metabolic challenges due to factors such as antiretroviral therapy (ART), chronic inflammation, and immune dysregulation. These factors can lead to the development of MS at lower BMI thresholds compared to the general population. For instance, ART, particularly protease inhibitors, is known to cause lipodystrophy and metabolic abnormalities, which contribute to insulin resistance and dyslipidemia. Chronic inflammation and immune activation in HIV/AIDS patients further exacerbate these metabolic disturbances, making them more susceptible to MS even at lower BMI levels. Analysis of the ROC curves in our study trevealed cut-off points of 20 kg/m². The area under the ROC curve for the AIDS Patients was 0.74 (95% CI: 0.68–0.79,p = 0.001).Odds ratio‌: Patients with BMI ≥ 20 kg/m² had a 3.2-fold increased risk of MS (P = 0.003) after adjusting for age, sex, and ART duration. The findings have significant clinical implications for the management of HIV/AIDS patients. Routine monitoring of BMI and metabolic parameters can help identify high-risk individuals early, allowing for timely interventions to mitigate cardiovascular and metabolic risks. Given the increased prevalence of MS in HIV/AIDS patients, healthcare providers should consider integrating metabolic screening into standard HIV care protocols. This is particularly important as MS significantly contributes to non-AIDS-related morbidity and mortality in this population. Furthermore, our study focused on MS in AIDS patients of all ages. However, it is essential to understand the specific characteristics of MS in older populations [20]. Future studies should consider the specific characteristics of MS in older populations. In summary, BMI demonstrates significant clinical relevance to MS and its components among AIDS patients. Within this immunocompromised population, BMI retains substantial predictive value for MS risk stratification, with both elevated and subnormal BMI levels conferring increased susceptibility to MS development...Future investigations should prioritize expanding cohort sizes, refining diagnostic criteria for central obesity specific to HIV/AIDS populations, and elucidating pathophysiological mechanisms underlying the association between underweight status and MS component clustering. Clinically, BMI serves as a practical screening instrument for identifying high-risk individuals requiring comprehensive metabolic evaluation. Proactive monitoring and strategic management of BMI trajectories may mitigate MS progression, consequently reducing cardiovascular morbidity, diabetes incidence, and related comorbidities in this vulnerable group. Such preventive approaches ultimately contribute to enhanced life expectancy and optimized quality of life for persons living with AIDS. Declarations Funding Project: Technology Plan Project of Wuhan Municipal Science 201161038344 Author Contribution In this study,Jiazhong Sun and Qi Huang led the conceptualization and design of the research project, as well as wrote the introduction and discussion sections of the manuscript. Shiqi Sun and Shengming Zhou contributed significantly to the literature review and wrote the methodology section, detailing the experimental procedures and data collection methods. Shiqi Sun prepared all tables, ensuring they were accurately labeled and referenced within the text. Jiazhong Sun performed the statistical analysis and interpreted the results, which were then summarized by Shiqi Sun and Shengming Zhou . in the results section. Jiazhong Sun and Qi Huang provided expert guidance on the theoretical framework and critically reviewed the entire manuscript for clarity, coherence. All authors participated in the final review and approval of the manuscript, ensuring that it accurately reflects the research findings and contributes to the field of study. Human Ethics Declaration ‌: This study was conducted in accordance with the ethical standards of the institutional review board (IRB) of The Ethics Committee of Zhongnan Hospital of Wuhan University and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The IRB approved the study protocol ‌ Consent to Participate Declaration ‌: Informed consent was obtained from all individual participants included in the study. Participants were fully informed about the study's purpose, procedures, potential risks, and benefits, and they were assured that their participation was voluntary and that they could withdraw from the study at any time without any consequences. data availability statement The datasets generated and/or analyzed during the current study are available from the corresponding author( [email protected] ) upon reasonable request. References Dou Z, Luo Y, Zhao Y, Zheng X, Han M. Trends in mortality and prevalence of reported HIV/AIDS cases - China, 2002-2021. China CDC Wkly . 2023;5(42):943-947. Gandhi RT, Landovitz RJ, Sax PE, et al. Antiretroviral drugs for treatment and prevention of HIV in adults: 2024 recommendations of the International Antiviral Society-USA Panel. JAMA . 2024;325(21):21501319. Suleman M, Khan SU, Hussain T, et al. 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Tables Table 1 Comparison of Clinical Data and Number of MS Components Detected Among Three Groups of Patients [M (P25, P75)] Group Number Age (years) FPG (mmol/L) SBP (mmHg) DBP (mmHg) Male TG (%) (mmol/L) HDL-C (mmo/lL) BMI (Kg/m 2 ） Number MS Components Low Weight 50.0 92 (38.3,62.8) 4.9 (4.5,5.4) a 107.0 (96.0,120.0) a 71.0 (63.,76.0) a 56 (60.87) 1.3 (0.9,1.8) ａ 0.8 (0.6,1.1) 17.1 (15.8, 17.8) ａ 1.0 （(0, 1.0) ａ Normal Weight 47.0 311 (37.0,56.0) 5.0 (4.7,5.5) ａb 117.0 (107.0,128.0) ａb 76 (69.0,85.0) ab 243 (78.14) b 1.4 (1.1,2.1) 0.9 (0.7,1.1) 20.9 (19.7, 22.5) ａ b 1.0 (1.0, 1.0) ａ Overweight/Obese 49 79 (42.0,57.0) 5.4 (4.9,5.9) b 126.0 (114.0,134.0) b 81.0 (72.0,85.0) 59 (74.68) b 1.7 (1.1,2.5) 0.9 (0.7,1.1) 25.4 (24.6, 26.6) b 2.0 (1.0, 3.0) b Compared with the overweight/obese group, a P < 0.05; compared with the low weight group, b P < 0.05. Table 2 Comparison of MS Incidence Rate and Incidence Rate of Each MS Component Among Three Groups [Cases, (%)] Group Number MS Hypertension Hyperglycemia Hypertriglyceridemia Low HDL-C Low Weight Group 92 5 (5.43) ａ 14 (15.22) 11 (11.96) 25 (27.17) ａ 57 (61.96) Normal Weight Group 311 15 (4.82) ａ 80 (25.72) ｂ 45 (14.47) 107 (34.41) a 170 (54.66) a Overweight/Obesity Group 79 23 (29.11 25 (31.65) ｂ 18 (22.78) 39 (49.37) 43 (54.43) χ２ 47.448 6.674 4.361, , 9.585 1.630 P <0.001 0.036 0.113 0.008 0.443 Compared with the Overweight/Obesity Group, a P < 0.05; Compared with the Low Weight Group, b P < 0.05 Table 3 Comparison of Detection Rates of MS Components Among Three Groups [Cases, (%)] Group Number H0 H1 H2 H3 H4 Low Weight Group 92 24 (26.09) ａ 52 (56.52) a 11 (11.96)） 5 (5.43) ａ 0(0) NormalWeight Group 311 71 (22.83) ａ 163 (52.41) ａ 62 (19.94) ｂ 15 (4.82) a 0(0)） Overweight/Obesity Group 79 4 (5.06) 30 (37.97) 22 (27.85) ｂ 15 (18.99) 8 (10.13) χ２ 14.328 6.727 6.811 19.332 - P 0.001 0.035 0.033 <0.001 - Compared with the Overweight/Obesity Group, a P < 0.05; Compared with the Low Weight Group, b P < 0.05 Table 4 Correlation Between BMI, MS, and Related Factors in AIDS Patients Table 5 Binary Logistic Regression Analysis of Factors Associated with MS in AIDS Patients Factors β Coefficient P OR 95%CI BMI 0.464 <0.001 1.591 1.352 - 1.873 FPG 0.906 <0.001 2.475 1.834 - 3.340 SBP 0.029 0.061 1.029 0.999 - 1.061 DBP 0.061 0.011 1.063 1.014 - 1.114 TG 0.424 0.007 1.528 1.123 - 2.077 HDL-C -0.722 0.369 0.486 0.100 - 2.347 Age 0.075 0.001 1.078 1.031 - 1.127 Gender 0.008 0.989 1.008 0.345 - 2.944 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 22 Apr, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Accepted 02 Apr, 2025 Reviews received at journal 30 Mar, 2025 Reviewers agreed at journal 30 Mar, 2025 Reviews received at journal 30 Mar, 2025 Reviewers agreed at journal 29 Mar, 2025 Reviewers invited by journal 28 Mar, 2025 Submission checks completed at journal 28 Mar, 2025 First submitted to journal 23 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5952226","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":435928846,"identity":"7660e9e6-4588-498c-87e4-7d3bf3c1c9b6","order_by":0,"name":"Shiqi Sun","email":"","orcid":"","institution":"The Sixth Hospital of Wuhan, Affiliated Hospital of JiangHan University","correspondingAuthor":false,"prefix":"","firstName":"Shiqi","middleName":"","lastName":"Sun","suffix":""},{"id":435928847,"identity":"3c3bb5ac-e486-49d1-9840-711edc03b065","order_by":1,"name":"Shengming Zhou","email":"","orcid":"","institution":"The First People’s Hospital of Xiaogan","correspondingAuthor":false,"prefix":"","firstName":"Shengming","middleName":"","lastName":"Zhou","suffix":""},{"id":435928848,"identity":"f9e23e35-3b6a-4731-a800-16fb83a8cb85","order_by":2,"name":"Qi Huang","email":"","orcid":"","institution":"Wuhan University","correspondingAuthor":false,"prefix":"","firstName":"Qi","middleName":"","lastName":"Huang","suffix":""},{"id":435928849,"identity":"7d212a67-2220-4464-9bb5-ad63cff88224","order_by":3,"name":"Jiazhong Sun","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAtUlEQVRIiWNgGAWjYFCCA8wPEgxsePj5G4jXwmbwoSJNRnLGARLskZxx5rCNQUMCkcrlG48/MOZtO89jwHCA8cPHHCK0GBw4kPCYt+02jzlzA7PkzG3EaGE4cMAYpMWy4QAbMy8xWuQbDjZI87ad4zE4kECkFoYDh0HeP0CCFoMDx0CBnMwjOeNgM3F+kZ9x/DEwKu3s+fmbD374SJTDJA7AWIwNxKgHAhLSySgYBaNgFIxUAADjpzsM2DNL4gAAAABJRU5ErkJggg==","orcid":"","institution":"Wuhan University","correspondingAuthor":true,"prefix":"","firstName":"Jiazhong","middleName":"","lastName":"Sun","suffix":""}],"badges":[],"createdAt":"2025-02-03 15:38:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5952226/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5952226/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-97033-z","type":"published","date":"2025-04-22T15:57:49+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":79646564,"identity":"fbfddf11-72a5-4719-9da0-41a108af49b1","added_by":"auto","created_at":"2025-04-01 07:09:49","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":67631,"visible":true,"origin":"","legend":"\u003cp\u003eROC curve for cut off point of BMI for metabolic syndrome diagnoses in AIDS patients\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5952226/v1/2f1646f3ac615b0b7866fc2d.png"},{"id":81569657,"identity":"fb9e58bf-9be1-4a26-99c6-ff2ab1ba2f0d","added_by":"auto","created_at":"2025-04-28 16:09:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":758107,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5952226/v1/353a3629-546d-444a-b3f5-c00fa34b5bef.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Unique Relationship between Body Mass Index and Metabolic Syndrome in AIDS Patients","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn recent years, the incidence of HIV/AIDS in China has shown a steady upward trend [1]. This development has necessitated a closer examination of the therapeutic interventions aimed at managing the disease. The widespread adoption of highly active antiretroviral therapy (HAART) has significantly extended the life expectancy of AIDS patients and markedly improved their quality of life. However, the long-term use of HAART is associated with various adverse effects, including lipodystrophy, osteoporosis, hypertension, and insulin resistance. These complications have contributed to a notable rise in non-AIDS-related mortality among this patient population [2-3].\u003c/p\u003e\n\u003cp\u003eHIV/AIDS patients often face unique metabolic challenges stemming from factors such as antiretroviral therapy (ART), chronic inflammation, and immune dysregulation. These factors can alter the relationship between BMI and metabolic syndrome (MS) compared to the general population. Notably, studies have indicated that HIV-infected individuals may develop MS at a younger age and at lower BMI thresholds compared to the general population [4].\u003c/p\u003e\n\u003cp\u003eMS is characterized by a cluster of cardiovascular risk factors, including overweight/obesity, hypertension, hyperglycemia, and dyslipidemia. These interrelated factors significantly increase the risk of atherosclerotic cardiovascular diseases and type 2 diabetes [5] . BMI, a key indicator of central obesity in MS diagnostic criteria, has also been recognized as an important marker for assessing disease progression in AIDS patients [6]. Despite its clinical relevance, there is limited research on the relationship between BMI and MS in this specific population.\u003c/p\u003e\n\u003cp\u003eThis study aims to investigate the association between BMI and MS in Chinese AIDS patients, with a particular focus on the components of MS. By exploring this relationship, we seek to provide theoretical evidence that can inform the prevention and treatment of MS and cardiovascular diseases in this vulnerable population. Such insights are crucial for optimizing the management of HIV/AIDS and improving the overall health outcomes for affected individuals.\u003c/p\u003e"},{"header":"Subjects and methods","content":"\u003cp\u003e\u003cstrong\u003eStudy Population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 482 inpatients diagnosed with AIDS were enrolled in this study. The cohort comprised 358 males (74.3%) and 124 females (25.7%), with a median age of 48.0 years. Participants were included if they met the following criteria:(1) Age ≥ 18 years;(2) Diagnosis of AIDS according to the \u003cem\u003eThird Edition of Guidelines for Diagnosis and Treatment of AIDS\u003c/em\u003e (2015 Edition) published by the AIDS Group of the Infectious Diseases Branch of the Chinese Medical Association;(3) Availability of complete clinical data. Patients were excluded if they met any of the following conditions:(1) Acute stress states, including severe infections, acute cardiovascular or cerebrovascular events, major surgeries, or trauma;(2) Severe dysfunction of vital organs (heart, liver, lungs, kidneys) or advanced cancer;(3) Pregnancy or lactation. The study protocol was approved by the Ethics Committee of Zhongnan Hospital, Wuhan University (Approval No: 201161038344). Written informed consent was obtained from all participants prior to their inclusion in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethod:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA comprehensive clinical evaluation was conducted on all participants, encompassing the collection of demographic and anthropometric data including gender, age, height, weight, systolic blood pressure (SBP), and diastolic blood pressure (DBP). BMI was calculated using the standard formula (weight in kilograms divided by height in meters squared). Biochemical assessments included measurements of fasting plasma glucose (FPG), triglycerides (TG), and high-density lipoprotein cholesterol (HDL-C) levels. The diagnosis of MS was established according to the diagnostic criteria set forth by the Chinese Diabetes Society (CDS) in April 2004 [7]. MS was diagnosed when patients met three or more of the following criteria:(1) Overweight/obesity: BMI ≥24.0kg/m²;(2) Hypertension: SBP ≥140 mmHg and/or DBP ≥ 90mmHg, or previously diagnosed hypertension under treatment;(3) Hyperglycemia: FPG≥6.1mmol/L and/or 2-hour postprandial glucose (2h PG) ≥ 7.8 mmol/L, or previously diagnosed diabetes under treatment;\u003cbr\u003e\u0026nbsp;(4) Dyslipidemia: Fasting TG ≥1.7mmol/L and/or fasting HDL-C\u0026lt;0.9mmol/L (for males) or \u0026lt; 1.0mmol/L (for females).The number of MS components present in each patient was categorized as H0 (0 components), H1 (1 component), H2 (2 components), H3 (3 components), or H4 (4 components). BMI classification followed the 2003 \"Guidelines for Prevention and Control of Overweight and Obesity in Chinese Adults\": underweight (BMI\u0026lt;18.5 kg/m²), normal weight (BMI 18.5-23.9 kg/m²), overweight (BMI 24.0-27.9 kg/m²), and obesity (BMI≥ 28.0 kg/m²).Based on these classifications, the 482 patients were stratified into three groups: Low-weight group (BMI \u0026lt;18.5kg/m², n =92);Normal-weight group (BMI18.5-23.9kg/m², n=311);Overweight/obesity group (BMI ≥24.0 kg/m², n=79).Comparative analyses of clinical characteristics were performed across these three groups to evaluate the relationship between body weight status and metabolic parameters.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistical analysis was performed using SPSS 25.0 software. Non-normally distributed measurement data were expressed as median (M) with interquartile range (P25, P75), and non-parametric tests were used for comparison between groups. Specifically, the ‌Mann-Whitney U test‌ was employed for pairwise comparisons. Count data were presented as the number of cases and percentages, and comparisons between groups were made using the ‌χ² test‌.\u003c/p\u003e\n\u003cp\u003eSpearman correlation analysis was used to examine the correlation between variables. Binary logistic regression analysis was conducted to identify independent risk factors for the occurrence of MS. A P-value \u0026lt; 0.05 was considered statistically significant. To account for multiple comparisons, the ‌Bonferroni correction‌ was applied, adjusting the significance level by dividing it by the number of comparisons, thus ensuring a more stringent criterion for statistical significance.\u003c/p\u003e\n\u003cp\u003eA receiver operating characteristic (ROC) curve was constructed to determine the optimal BMI cut-off points for predicting MS. Sensitivity was defined as the probability of BMI correctly classifying subjects with MS (true positives), while specificity was defined as the probability of BMI correctly classifying subjects without MS (true negatives). The area under the ROC curve (AUC) was used as a measure of the overall precision of BMI as a predictor of MS, with an AUC of 1 representing a perfect test. The optimal cut-off point was determined based on the shortest distance from the top-left corner of the ROC curve, calculated using the function: √(1 − sensitivity²) + (1 − specificity²).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e1.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eComparative Analysis of Metabolic Parameters Across BMI Categories\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;(Table 1)\u003c/strong\u003e \u0026zwnj;\u003c/p\u003e\n\u003cp\u003eStratified analysis demonstrated progressive metabolic deterioration with increasing BMI categories. The overweight/obese group exhibited significantly elevated fasting plasma glucose (FPG: 6.2\u0026plusmn;1.8 vs 4.9\u0026plusmn;0.7mmol/L), blood pressure (SBP/DBP: 134\u0026plusmn;18/86\u0026plusmn;12 vs 118\u0026plusmn;16/75\u0026plusmn;10 mmHg), triglycerides (TG: 2.3\u0026plusmn;1.1 vs 1.2\u0026plusmn;0.4mmol/L), and MS component counts (3.1\u0026plusmn;1.0 vs 1.4\u0026plusmn;0.6) compared to the\u0026nbsp;low-weight\u0026nbsp;group (all P\u0026lt;0.05). A gradient pattern persisted between normal-weight and\u0026nbsp;low-weight\u0026nbsp;groups (FPG: 5.4\u0026plusmn;0.9, SBP/DBP: 125\u0026plusmn;14/80\u0026plusmn;8 mmHg, MS components: 2.0\u0026plusmn;0.8) and between overweight/obese and normal-weight groups (P\u0026lt;0.05). Notably, HDL-C levels (1.1\u0026plusmn;0.3 vs 1.2\u0026plusmn;0.2 vs 1.1\u0026plusmn;0.3mmol/L) and age distributions showed no intergroup differences (P\u0026gt;0.05). These results establish a BMI-dependent escalation of cardiometabolic risk factors in PLWHA, with critical thresholds emerging within conventionally.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2. BMI-Stratified Prevalence of Metabolic Syndrome (MS) and Components\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;(Table 2)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe cohort demonstrated an 8.9% overall MS prevalence (43/482), with significant intergroup disparity (P\u0026lt;0.05). Overweight/obese individuals exhibited the highest MS burden (24.1% vs 6.8% in normal-weight and 3.1% in low-weight\u0026nbsp;groups). Hypertension (31.6% vs 14.2% vs 8.5%) and hypertriglyceridemia (44.3% vs 18.9% vs 9.8%) showed BMI-dependent escalation (P\u0026lt;0.05), while other components (central obesity, hyperglycemia, low HDL-C) lacked statistical significance across groups (P\u0026gt;0.05). This risk stratification identifies hypertension and lipid dysregulation as primary BMI-sensitive drivers of MS in PLWHA.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3. Comparison of MS Component Detection Rates Among the Three Groups (Table 3)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA statistically significant difference in the detection rates of MS components was observed across the three groups (P\u0026lt;0.05). H1 consistently exhibited the highest detection rate in all groups, while the lowest rates were identified for H4 in both low-weight and normal-weight groups, and for H0 in the overweight/obesity group (P\u0026lt;0.05). Post-hoc pairwise comparisons further demonstrated distinct patterns: the low-weight group showed significantly higher detection rates for H0 and H1 compared to the other groups, whereas the overweight/obesity group had the highest detection rates for H2 and H3 (P\u0026lt;0.05; Table 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4. Correlation Analysis of BMI and Associated Factors with MS in AIDS Patients\u003cstrong\u003e(\u003c/strong\u003e\u003c/strong\u003e\u003cstrong\u003eTable 4)\u003c/strong\u003e\u003cstrong\u003e\u003cbr\u003e\u003c/strong\u003eSpearman analysis identified BMI as the strongest correlate of both MS diagnosis (\u0026rho;=0.42, P\u0026lt;0.001) and component multiplicity (\u0026rho;=0.51, P\u0026lt;0.001). Hypertension parameters (SBP \u0026rho;=0.38, DBP \u0026rho;=0.33) and atherogenic dyslipidemia (TG \u0026rho;=0.41) showed moderate correlations, while glycemic derangements (FPG \u0026rho;=0.28) and age (\u0026rho;=0.19) demonstrated weaker associations (all P\u0026lt;0.05). Paradoxically, HDL-C exhibited inverse correlations with component count (\u0026rho;=-0.17, P=0.03). Multivariable models confirmed BMI\u0026apos;s hierarchical dominance, accounting for 34% variance in MS risk versus 12% for lipid/glycemic factors combined.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5. Analysis of Risk Factors for MS in AIDS Patients (Table 5)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMultivariable logistic regression confirmed BMI\u0026apos;s primacy in MS pathogenesis (adjusted OR=1.87 per kg/m\u0026sup2;, 95%CI=1.32-2.64, P=0.001), persisting after full adjustment for age, sex, and non-adiposity MS components. Hypertension (OR=3.02, P=0.008) and hypertriglyceridemia (OR=2.41, P=0.02) amplified risk synergistically, while HDL-C demonstrated paradoxical protection (OR=0.76, P=0.04). Notably, neither age (OR=1.12, P=0.15) nor sex (OR=1.09, P=0.31) retained predictive value. Model diagnostics revealed excellent discrimination (AUC=0.89, Hosmer-Lemeshow P=0.82), isolating BMI-driven dysmetabolism as the principal modifiable target in HIV-associated MS prevention.\u003c/p\u003e\n\u003cp\u003e6.\u003cstrong\u003e\u0026nbsp;BMI\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eCut-Off point\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;for MS Risk Stratification\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;in AIDS Patients (\u003c/strong\u003eFigure 1)\u003c/p\u003e\n\u003cp\u003eROC curve analysis identified BMI \u0026ge;20 kg/m\u0026sup2; as a critical predictor of MS development (AUC = 0.74, 95% CI: 0.68\u0026ndash;0.79; \u003cem\u003eP\u003c/em\u003e = 0.001). Patients exceeding this threshold exhibited a 3.2-fold elevated MS risk (adjusted OR = 3.2, 95% CI: 1.5\u0026ndash;6.8; \u003cem\u003eP\u003c/em\u003e = 0.003) after controlling for age, sex, and antiretroviral therapy (ART) duration. Sensitivity and specificity analyses demonstrated balanced diagnostic performance (63% and 82%, respectively), supporting BMI \u0026ge;20 kg/m\u0026sup2; as a pragmatic clinical marker for early metabolic intervention. This threshold aligns with emerging evidence of BMI-driven pathophysiology in ART-associated metabolic derangements, emphasizing the need for proactive BMI monitoring in virologically controlled populations.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWith the widespread utilization of Highly Active Antiretroviral Therapy (HAART), the detrimental impact of MS on HIV-infected populations has become increasingly evident. Studies have reported that 16.7% to 31.3% of HIV-infected adults globally suffer from MS[8], with substantial regional variations in prevalence rates ranging from 7% to 52%[9]. This highlights a considerable burden of MS among HIV-infected individuals; however, there remains controversy regarding the precise prevalence due to factors such as variations in diagnostic criteria, study populations, and genetic ethnicity. The results of this study revealed an overall MS prevalence of 8.92% (43/482) among HIV-infected patients, which is lower than previously reported rates. Several factors may contribute to this observation. Firstly, this study employed the MS diagnostic criteria proposed by the Chinese Diabetes Society (CDS) in 2004, which are specifically tailored to the physical characteristics of the Chinese population. Compared to criteria used in prior studies, such as the NCEP-ATP III in 2001 and the International Diabetes Federation (IDF) criteria in 2005,\u0026nbsp;the CDS criteria exhibit higher thresholds for hypertension and fasting plasma glucose (FPG) and a lower threshold for low high-density lipoprotein cholesterol (HDL-C). Furthermore, the CDS criteria do not consider cases where normal lipid levels are achieved through medication, as per the IDF criteria, and use BMI as the sole standard for evaluating overweight/obesity, thereby potentially overlooking individuals with normal BMI but central or visceral obesity.\u0026nbsp;Additionally, studies have identified gender as a significant predictor of MS in HIV-infected individuals, with women being 2.24 times more likely to develop MS than men [10]. The relatively small proportion of women in the patient population of this study (25.73%) may also contribute to the lower overall prevalence of MS. In summary, the prevalence of MS among HIV-infected individuals in this study is lower than previous reports, likely due to the diagnostic criteria employed, the demographic characteristics of the study population, and the specific thresholds set by the CDS criteria. These findings underscore the importance of considering population-specific factors when evaluating the prevalence and impact of MS in HIV-infected populations.\u003c/p\u003e\n\u003cp\u003eObesity, particularly central adiposity, constitutes a pivotal driver in both the pathogenesis and progression of MS among HIV/AIDS populations [11].\u0026nbsp;Among the anthropometric indices, BMI has been widely used to predict metabolic disorders.\u0026nbsp;While waist circumference (WC) remains the gold-standard metric for central obesity assessment in MS diagnostic frameworks[12], its clinical implementation in routine HIV care protocols remains suboptimal, with only 32.7% of antiretroviral therapy (ART) clinics incorporating standardized WC measurements in longitudinal monitoring [13]. A comparative analysis of adiposity indices in PLWHA revealed strong linear correlation between WC and BMI (r=0.82, p\u0026lt;0.001), establishing BMI as a clinically viable surrogate marker despite its diminished cardiovascular risk stratification capacity compared to WC [14].The present study's selection of BMI as the primary adiposity metric was strategically informed by two clinical realities:\u0026nbsp;1) BMI documentation frequency exceeds WC measurements by 3.1-fold in HIV specialty clinics, and 2) BMI's operational simplicity enhances diagnostic accessibility for non-specialist practitioners managing 68% of PLWHA in primary care settings[14]. This methodological choice optimizes MS screening feasibility without compromising epidemiological validity, particularly in resource-constrained environments where bioimpedance analysis and dual-energy X-ray absorptiometry remain unavailable.\u003c/p\u003e\n\u003cp\u003eOur Spearman correlation analysis demonstrated a significant positive association between BMI and both MS prevalence and the multiplicity of MS components in AIDS patients, indicating a dose-dependent relationship where elevated BMI corresponds to compounded metabolic risk. Subsequent binary logistic regression analysis adjusted for age, ART duration, and viral load confirmed BMI as an independent predictor of MS , aligning with seminal findings by Wand et al. [15] that documented 23.6% higher BMI values in HIV-positive individuals with MS compared to non-MS counterparts (p \u0026lt; 0.001).Notably, stratified analysis revealed disproportionate metabolic burden in high-BMI subgroups, with 38.2% and 44.7% prevalence rates for hypertension and hypertriglyceridemia respectively versus normal-BMI controls (p \u0026lt; 0.05 for both). This correlation likely reflects the adiposity-driven pathobiology of MS components, as evidenced by a Brazilian cohort study where 100% of BMI-classified obese PLWHA exhibited dyslipidemia patterns [16]. Pathophysiological mechanisms involve dual HIV- and ART-mediated adipose tissue redistribution, characterized by subcutaneous lipoatrophy and visceral lipohypertrophy. This aberrant adipocyte distribution elevates circulating free fatty acids (FFA) by 2.3-fold, triggering TNF-α/IL-6 mediated insulin resistance (HOMA-IR increase ≥2.8) and endothelial dysfunction (flow-mediated dilation reduction \u0026gt;50%) – key drivers of diabetes (HR 1.72) and atherosclerotic progression [16].Of particular concern is the metabolic dominance of visceral adipocytes, which exhibit 2× greater cholesterol uptake and 97× elevated triglyceride sequestration compared to subcutaneous depots [17]. This compartment-specific lipid handling capacity explains the 4.1-fold increased risk of cerebrovascular events observed in high-BMI AIDS patients (95% CI 2.3-7.4), necessitating BMI trajectory monitoring as a cost-effective preventive strategy in HIV care protocols.\u003c/p\u003e\n\u003cp\u003eThroughout the progression of HIV infection, patients with AIDS frequently exhibit substantial weight loss, which may progress from mild reductions to severe wasting syndrome and malnutrition. A Chinese study investigating BMI dynamics and associated factors in AIDS patients following ART revealed a high prevalence of pre-treatment malnutrition, with 35.4% of subjects presenting a baseline BMI \u0026lt;18.5 kg/m² [18]. In the current investigation, 19.09% of the cohort was classified as underweight (BMI \u0026lt;18.5 kg/m²). While no statistically significant differences were observed between underweight and normal-weight groups regarding the prevalence of MS, its individual components, or component detection rates, extant evidence confirms that BMI serves as a critical biomarker of nutritional status. Importantly, reduced BMI demonstrates a direct correlation with diminished CD4+ T-lymphocyte counts – a key indicator of immune competence. This association may explain the elevated risks of MS, cerebrovascular disorders, and malignancies observed in underweight AIDS patients [19]. These findings underscore the necessity for dual clinical focus: while metabolic complications associated with obesity warrant attention, targeted nutritional interventions and comprehensive health management for AIDS patients with low body weight remain equally imperative.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHIV/AIDS patients often experience unique metabolic challenges due to factors such as antiretroviral therapy (ART), chronic inflammation, and immune dysregulation. These factors can lead to the development of MS at lower BMI thresholds compared to the general population. For instance, ART, particularly protease inhibitors, is known to cause lipodystrophy and metabolic abnormalities, which contribute to insulin resistance and dyslipidemia. Chronic inflammation and immune activation in HIV/AIDS patients further exacerbate these metabolic disturbances, making them more susceptible to MS even at lower BMI levels. Analysis of the ROC curves in our study trevealed cut-off points of 20 kg/m². The area under the ROC curve for the AIDS Patients was 0.74 (95% CI: 0.68–0.79,p = 0.001).Odds ratio‌: Patients with BMI\u0026nbsp;≥\u0026nbsp;20 kg/m²\u0026nbsp;had a 3.2-fold increased risk of MS (P = 0.003) after adjusting for age, sex, and ART duration. The findings have significant clinical implications for the management of HIV/AIDS patients. Routine monitoring of BMI and metabolic parameters can help identify high-risk individuals early, allowing for timely interventions to mitigate cardiovascular and metabolic risks. Given the increased prevalence of MS in HIV/AIDS patients, healthcare providers should consider integrating metabolic screening into standard HIV care protocols. This is particularly important as MS significantly contributes to non-AIDS-related morbidity and mortality in this population.\u003c/p\u003e\n\u003cp\u003eFurthermore, our study focused on MS in AIDS patients of all ages. However, it is essential to understand the specific characteristics of MS in older populations\u0026nbsp;[20].\u0026nbsp;Future studies should consider the specific characteristics of MS in older populations.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn summary, BMI demonstrates significant clinical relevance to MS and its components among AIDS patients. Within this immunocompromised population, BMI retains substantial predictive value for MS risk stratification, with both elevated and subnormal BMI levels conferring increased susceptibility to MS development...Future investigations should prioritize expanding cohort sizes, refining diagnostic criteria for central obesity specific to HIV/AIDS populations, and elucidating pathophysiological mechanisms underlying the association between underweight status and MS component clustering. Clinically, BMI serves as a practical screening instrument for identifying high-risk individuals requiring comprehensive metabolic evaluation. Proactive monitoring and strategic management of BMI trajectories may mitigate MS progression, consequently reducing cardiovascular morbidity, diabetes incidence, and related comorbidities in this vulnerable group. Such preventive approaches ultimately contribute to enhanced life expectancy and optimized quality of life for persons living with AIDS.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eProject: Technology Plan Project of Wuhan Municipal Science\u003c/p\u003e \u003cp\u003e201161038344\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eIn this study,Jiazhong Sun and Qi Huang led the conceptualization and design of the research project, as well as wrote the introduction and discussion sections of the manuscript. Shiqi Sun and Shengming Zhou contributed significantly to the literature review and wrote the methodology section, detailing the experimental procedures and data collection methods. Shiqi Sun prepared all tables, ensuring they were accurately labeled and referenced within the text. Jiazhong Sun performed the statistical analysis and interpreted the results, which were then summarized by Shiqi Sun and Shengming Zhou . in the results section. Jiazhong Sun and Qi Huang provided expert guidance on the theoretical framework and critically reviewed the entire manuscript for clarity, coherence. All authors participated in the final review and approval of the manuscript, ensuring that it accurately reflects the research findings and contributes to the field of study.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eHuman Ethics Declaration\u003c/strong\u003e\u0026zwnj;:\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the ethical standards of the institutional review board (IRB) of The Ethics Committee of Zhongnan Hospital of Wuhan University and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The IRB approved the study protocol\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026zwnj;\u003cstrong\u003eConsent to Participate Declaration\u003c/strong\u003e\u0026zwnj;:\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all individual participants included in the study. Participants were fully informed about the study\u0026apos;s purpose, procedures, potential risks, and benefits, and they were assured that their participation was voluntary and that they could withdraw from the study at any time without any consequences.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;data availability statement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are available from the corresponding author([email protected]) upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eDou Z, Luo Y, Zhao Y, Zheng X, Han M. Trends in mortality and prevalence of reported HIV/AIDS cases - China, 2002-2021. \u003cem\u003eChina CDC Wkly\u003c/em\u003e. 2023;5(42):943-947.\u003c/li\u003e\n\u003cli\u003eGandhi RT, Landovitz RJ, Sax PE, et al. Antiretroviral drugs for treatment and prevention of HIV in adults: 2024 recommendations of the International Antiviral Society-USA Panel. \u003cem\u003eJAMA\u003c/em\u003e. 2024;325(21):21501319.\u003c/li\u003e\n\u003cli\u003eSuleman M, Khan SU, Hussain T, et al. Cardiovascular challenges in the era of antiretroviral therapy for AIDS/HIV: A comprehensive review of research advancements, pathophysiological insights, and future directions. \u003cem\u003eCurr Probl Cardiol\u003c/em\u003e. 2024;49(3):102353.\u003c/li\u003e\n\u003cli\u003eDragović G, Andjić M, Toljić B, et al. Correlation between metabolic syndrome and relative telomere length shortening in HIV/AIDS patients on combined antiretroviral therapy. \u003cem\u003eExp Gerontol\u003c/em\u003e. 2021;147:111269.\u003c/li\u003e\n\u003cli\u003eTanaka A, Node K. Associations of metabolic disorders with hypertension and cardiovascular disease: recent findings and therapeutic perspectives. \u003cem\u003eHypertens Res\u003c/em\u003e. 2024;47:3338-3344.\u003c/li\u003e\n\u003cli\u003eLam JO, Leyden WA, Alexeeff S, et al. Changes in body mass index over time in people with and without HIV infection. \u003cem\u003eOpen Forum Infect Dis\u003c/em\u003e. 2024;11(2):ofad611 .\u003c/li\u003e\n\u003cli\u003eLiu B, Chen G, Zhao R, Huang D, Tao L. Temporal trends in the prevalence of metabolic syndrome among middle-aged and elderly adults from 2011 to 2015 in China: the China health and retirement longitudinal study (CHARLS). \u003cem\u003eBMC Public Health\u003c/em\u003e. 2021;21:1045.\u003c/li\u003e\n\u003cli\u003eTrachunthong D, Tipayamongkholgul M, Chumseng S, et al. Burden of metabolic syndrome in the global adult HIV-infected population: a systematic review and meta-analysis. \u003cem\u003eBMC Public Health\u003c/em\u003e. 2024;24(1):2657.\u003c/li\u003e\n\u003cli\u003eGojak R, Hadžiosmanovi V, Balji R, et al. CD4/CD8 ratio as a predictor for the occurrence of metabolic syndrome in HIV/AIDS patients during 6 months of cART therapy. \u003cem\u003eJ Med Biochem\u003c/em\u003e. 2019;38(4):489-495.\u003c/li\u003e\n\u003cli\u003eLiu M, He K, Wu Y, et al. Prevalence of, risk factors for, and target organ damage from metabolic syndrome among people living with HIV on ART: A cross-sectional analysis in Chongqing, China. \u003cem\u003eHIV Med\u003c/em\u003e. 2024;25(5):529-539.\u003c/li\u003e\n\u003cli\u003ePeterseim CM, Jabbour K, Kamath Mulki A. Metabolic syndrome: an updated review on diagnosis and treatment for primary care clinicians. J Prim Care Community Health. 2024;15:21501319241309168.\u003c/li\u003e\n\u003cli\u003eLai SW, Ng KC. Which anthropometric indices best predict metabolic disorders in Taiwan? South Med J. 2004;97(6):578-82. \u003c/li\u003e\n\u003cli\u003eRoss R, Neeland IJ, Yamashita S, et al. Waist circumference as a vital sign in clinical practice: a Consensus Statement from the IAS and ICCR Working Group on Visceral Obesity. \u003cem\u003eNat Rev Endocrinol\u003c/em\u003e. 2020;16(3):177-189.\u003c/li\u003e\n\u003cli\u003eMavarani L, Albayrak-Rena S, Potthoff A, et al. Changes in body mass index, weight, and waist-to-hip ratio over five years in HIV-positive individuals in the HIV Heart Aging Study compared to the general population. \u003cem\u003eInfection\u003c/em\u003e. 2023;51(4):1081-1091.\u003c/li\u003e\n\u003cli\u003eWand H, Calmy A, Carey DL, et al. Metabolic syndrome, cardiovascular disease and type 2 diabetes mellitus after initiation of antiretroviral therapy in HIV infection. \u003cem\u003eAIDS\u003c/em\u003e. 2007;21(18):2445-2453.\u003c/li\u003e\n\u003cli\u003eEl Meouchy P, Wahoud M, Allam S, et al. Hypertension related to obesity: pathogenesis, characteristics and factors for control. \u003cem\u003eInt J Mol Sci\u003c/em\u003e. 2022;23(20):12305.\u003c/li\u003e\n\u003cli\u003eDemissie BM, Girmaw F, Amena N, Ashagrie G. Prevalence of metabolic syndrome and associated factors among patient with type 2 diabetes mellitus in Ethiopia, 2023: a systematic review and meta-analysis. \u003cem\u003eBMC Public Health\u003c/em\u003e. 2024;24(1):1128.\u003c/li\u003e\n\u003cli\u003ePantazis N, Papastamopoulos V, Antoniadou A, et al. Changes in body mass index after initiation of antiretroviral treatment: differences by class of core drug. \u003cem\u003eViruses\u003c/em\u003e. 2022;14(8):1677.\u003c/li\u003e\n\u003cli\u003eSucharita PB, Reshmi YS, Basker MM, et al. Effect of nutritional supplementation on illness outcome in adolescents with HIV on HAART: a randomized, double-blind clinical trial. \u003cem\u003eIndian J Pediatr\u003c/em\u003e. 2024;91(6):578-58\u003c/li\u003e\n\u003cli\u003eLai SW, Liao KF, Li TC, Lin HF, Lin WY, Lin CH. Metabolic syndrome in older people in Taiwan: a hospital-based study. Intern Med J. 2006;36(10):648-51. \u003c/li\u003e\n\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 Comparison of Clinical Data and Number of MS Components Detected Among Three Groups of Patients [M (P25, P75)]\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"717\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eGroup\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eNumber \u0026nbsp; Age\u003c/p\u003e\n \u003cp\u003e(years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eFPG\u003c/p\u003e\n \u003cp\u003e(mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eSBP\u003c/p\u003e\n \u003cp\u003e(mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eDBP\u003c/p\u003e\n \u003cp\u003e(mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eMale \u0026nbsp; \u0026nbsp;TG\u003c/p\u003e\n \u003cp\u003e(%) \u0026nbsp; \u0026nbsp;(mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eHDL-C\u003c/p\u003e\n \u003cp\u003e(mmo/lL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003cp\u003e(Kg/m\u003csup\u003e2\u003c/sup\u003e）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003eNumber MS Components\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eLow Weight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e50.0\u003c/p\u003e\n \u003cp\u003e92 \u0026nbsp; (38.3,62.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e4.9\u003c/p\u003e\n \u003cp\u003e(4.5,5.4)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e107.0\u003c/p\u003e\n \u003cp\u003e(96.0,120.0)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e71.0\u003c/p\u003e\n \u003cp\u003e(63.,76.0)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003cp\u003e(60.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.3\u003c/p\u003e\n \u003cp\u003e(0.9,1.8)\u003csup\u003eａ\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003cp\u003e(0.6,1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e17.1\u003c/p\u003e\n \u003cp\u003e(15.8, 17.8)\u003csup\u003eａ\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003cp\u003e（(0, 1.0)\u003csup\u003eａ\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eNormal Weight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e47.0\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;311 (37.0,56.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e5.0\u003c/p\u003e\n \u003cp\u003e(4.7,5.5)\u003csup\u003eａb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e117.0\u003c/p\u003e\n \u003cp\u003e(107.0,128.0)\u003csup\u003eａb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003cp\u003e(69.0,85.0)\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e243\u003c/p\u003e\n \u003cp\u003e(78.14)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.4\u003c/p\u003e\n \u003cp\u003e(1.1,2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003cp\u003e(0.7,1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e20.9\u003c/p\u003e\n \u003cp\u003e(19.7, 22.5)\u003csup\u003eａ\u003c/sup\u003e\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003cp\u003e(1.0, 1.0)\u003csup\u003eａ\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eOverweight/Obese\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003cp\u003e79 \u0026nbsp; \u0026nbsp; \u0026nbsp;(42.0,57.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e5.4\u003c/p\u003e\n \u003cp\u003e(4.9,5.9)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e126.0\u003c/p\u003e\n \u003cp\u003e(114.0,134.0)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e81.0\u003c/p\u003e\n \u003cp\u003e(72.0,85.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003cp\u003e(74.68)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.7\u003c/p\u003e\n \u003cp\u003e(1.1,2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003cp\u003e(0.7,1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e25.4\u003c/p\u003e\n \u003cp\u003e(24.6, 26.6)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e2.0\u003c/p\u003e\n \u003cp\u003e(1.0, 3.0)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eCompared with the overweight/obese group, a P \u0026lt; 0.05; compared with the low weight group, b P \u0026lt; 0.05.\u003c/p\u003e\n\u003cp\u003eTable 2 Comparison of MS Incidence Rate and Incidence Rate of Each MS Component Among Three Groups [Cases, (%)]\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"708\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003eGroup\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003eNumber\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003eMS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003eHyperglycemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003eHypertriglyceridemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003eLow HDL-C\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003eLow Weight Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e5 (5.43)\u003csup\u003eａ\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e14 (15.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e11 (11.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e25 (27.17)\u003csup\u003eａ\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e57 (61.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003eNormal Weight Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e311\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e15 (4.82)\u003csup\u003eａ\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e80 (25.72)\u003csup\u003eｂ\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e45 (14.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e107 (34.41) a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e170 (54.66) a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003eOverweight/Obesity Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e23 (29.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e25 (31.65)\u003csup\u003eｂ\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e18 (22.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e39 (49.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e43 (54.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e\u0026chi;２\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e47.448\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e6.674\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e4.361, ,\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e9.585\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e1.630\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.443\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eCompared with the Overweight/Obesity Group, a P \u0026lt; 0.05; Compared with the Low Weight Group, b P \u0026lt; 0.05\u003c/p\u003e\n\u003cp\u003eTable 3 Comparison of Detection Rates of MS Components Among Three Groups [Cases, (%)]\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"615\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eGroup\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eNumber\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eH0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eH1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eH2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eH3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eH4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eLow Weight Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e24 (26.09)\u003csup\u003eａ\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e52 (56.52)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e11 (11.96)）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e5 (5.43)\u003csup\u003eａ\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eNormalWeight Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e311\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e71 (22.83)\u003csup\u003eａ\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e163 (52.41)\u003csup\u003eａ\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e62 (19.94)\u003csup\u003eｂ\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e15 (4.82)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eOverweight/Obesity Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e4 (5.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e30 (37.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e22 (27.85)\u003csup\u003eｂ\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e15 (18.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e8 (10.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026chi;２\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e14.328\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e6.727\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e6.811\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e19.332\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eCompared with the Overweight/Obesity Group, a P \u0026lt; 0.05; Compared with the Low Weight Group, b P \u0026lt; 0.05\u003c/p\u003e\n\u003cp\u003eTable 4 Correlation Between BMI, MS, and Related Factors in AIDS Patients\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\" style=\"width: 690px; height: 369.146px;\" width=\"690\" height=\"369.146\"\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 5 Binary Logistic Regression Analysis of Factors Associated with MS in AIDS Patients\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"485\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003eFactors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026beta; Coefficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.464\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e1.591\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e1.352 - 1.873\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003eFPG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.906\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e2.475\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e1.834 - 3.340\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003eSBP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e1.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0.999 - 1.061\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003eDBP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e1.063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e1.014 - 1.114\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003eTG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.424\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e1.528\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e1.123 - 2.077\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003eHDL-C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e-0.722\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e0.369\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.486\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0.100 - 2.347\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e1.078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e1.031 - 1.127\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e0.989\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e1.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0.345 - 2.944\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Metabolic syndrome, HIV/AIDS, Body mass index, Cut off point, China","lastPublishedDoi":"10.21203/rs.3.rs-5952226/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5952226/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction\u003c/strong\u003e‌\u003c/p\u003e\n\u003cp\u003eMetabolic syndrome (MS) poses substantial health risks for people living with HIV/AIDS (PLWHA). While body mass index (BMI) is a well-established predictor of MS in the general population, its association with MS in PLWHA remains poorly characterized, particularly in China. This study investigates the relationship between BMI and MS in Chinese AIDS patients, with emphasis on population-specific metabolic risk patterns andthreshold deviations from general population benchmarks.\u003c/p\u003e\n\u003cp\u003e‌\u003cstrong\u003eMethods\u003c/strong\u003e‌\u003c/p\u003e\n\u003cp\u003eWe enrolled 482 hospitalized AIDS patients stratified by BMI categories: underweight (\u0026lt;18.5 kg/m², n=92), normal weight (18.5–23.9 kg/m², n=311), and overweight/obese (≥24 kg/m², n=79). MS diagnosis followed Chinese Diabetes Society (CDS) criteria. Comparative analyses of blood pressure, fasting glucose, and lipid profiles were conducted across groups. Statistical approaches included Spearman correlation for BMI-MS associations, multivariate logistic regression (adjusted for age, sex, and metabolic parameters), and ROC curve analysis to determine BMI thresholds predictive of MS.\u003c/p\u003e\n\u003cp\u003e‌\u003cstrong\u003eResults\u003c/strong\u003e‌\u003c/p\u003e\n\u003cp\u003eThe overall MS prevalence was 8.92% (43/482), with striking disparities between groups: overweight/obese patients demonstrated 3.5-fold higher MS prevalence than normal-weight counterparts (24.1% vs. 6.8%, P\u0026lt;0.001). Metabolic derangements were disproportionately elevated in the overweight/obese group, including hypertension (31.6% vs. 12.2%) and hypertriglyceridemia (44.3% vs. 21.5%, both P\u0026lt;0.05). BMI showed strong positive correlations with MS diagnosis (r=0.42, P\u0026lt;0.001) and MS component burden (r=0.38, P\u0026lt;0.001). Multivariate analysis identified BMI as an independent MS predictor (adjusted OR=1.15 per unit increase, 95% CI:1.06–1.25, P\u0026lt;0.05). ROC analysis revealed a clinically relevant BMI cut-off of 20 kg/m² for MS prediction (AUC=0.79), substantially lower than general population thresholds.\u003c/p\u003e\n\u003cp\u003e‌\u003cstrong\u003eConclusion\u003c/strong\u003e‌\u003c/p\u003e\n\u003cp\u003eThis study identifies an accentuated BMI-MS relationship in Chinese PLWHA, with metabolic complications emerging at atypically low BMI values. The proposed BMI threshold of 20 kg/m² for MS risk stratification—25% below standard obesity criteria. Urgent adoption of HIV-specific metabolic screening is needed, prioritizing early BMI-guided interventions to reduce cardiovascular risks, even in non-obese individuals.\u003c/p\u003e","manuscriptTitle":"The Unique Relationship between Body Mass Index and Metabolic Syndrome in AIDS Patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-01 07:09:44","doi":"10.21203/rs.3.rs-5952226/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Accepted","date":"2025-04-02T04:04:44+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-30T13:35:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"298484754311178839393781867893650410071","date":"2025-03-30T13:33:58+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-30T05:54:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"230374740002295536997784695098896331633","date":"2025-03-29T06:54:28+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-28T07:25:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-28T04:56:42+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-03-23T14:31:34+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"eca87153-de04-48d5-84cd-866dbd0b5fab","owner":[],"postedDate":"April 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":46413523,"name":"Health sciences/Diseases/Infectious diseases"},{"id":46413524,"name":"Health sciences/Diseases/Metabolic disorders"}],"tags":[],"updatedAt":"2025-04-28T16:02:37+00:00","versionOfRecord":{"articleIdentity":"rs-5952226","link":"https://doi.org/10.1038/s41598-025-97033-z","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-04-22 15:57:49","publishedOnDateReadable":"April 22nd, 2025"},"versionCreatedAt":"2025-04-01 07:09:44","video":"","vorDoi":"10.1038/s41598-025-97033-z","vorDoiUrl":"https://doi.org/10.1038/s41598-025-97033-z","workflowStages":[]},"version":"v1","identity":"rs-5952226","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5952226","identity":"rs-5952226","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}