Prevalence of metabolic syndrome and associated factors among older adults in Vietnam: a systematic review and meta-analysis stratified by NCEP-ATP III and IDF diagnostic criteria

Prevalence of metabolic syndrome and associated factors among older adults in Vietnam: a systematic review and meta-analysis stratified by NCEP-ATP III and IDF diagnostic criteria | 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 Systematic Review Prevalence of metabolic syndrome and associated factors among older adults in Vietnam: a systematic review and meta-analysis stratified by NCEP-ATP III and IDF diagnostic criteria Tien Nguyen This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9399614/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Background Metabolic syndrome (MetS) is common in older adults and is associated with cardiovascular disease, type 2 diabetes, and functional decline. In Vietnam, evidence on MetS in older adults is scattered across community- and hospital-based studies, and prevalence estimates may vary substantially depending on the diagnostic criteria used. Objectives To synthesise the available evidence on the prevalence of MetS and associated factors among older adults in Vietnam, with stratification by NCEP-ATP III and IDF criteria. Methods A systematic review and meta-analysis of observational studies was conducted using PubMed, Scopus, and manual searches of Vietnamese journals and institutional repositories through 12 April 2026. Eligible studies were conducted in Vietnam, included participants aged 60 years or older or extractable elderly subgroup data, and reported MetS prevalence and/or associated factors using NCEP-ATP III, modified NCEP-ATP III, harmonised, or IDF criteria. Random-effects meta-analysis of prevalence was performed in R using logit-transformed proportions. Results Three eligible elderly-specific studies were included in the quantitative synthesis, comprising 1,444 participants. For the primary analysis, one prevalence estimate per study was retained to avoid double-counting. The pooled prevalence of MetS among older adults in Vietnam was 40.98% (95% CI: 30.29%–52.60%), with substantial heterogeneity (I² = 94.7%). In criterion-specific analyses, the pooled prevalence for NCEP-ATP III/modified NCEP-ATP III/harmonised definitions was also 40.98% (95% CI: 30.29%–52.60%), whereas the single IDF-based estimate was 22.03% (95% CI: 18.25%–26.33%). Female sex and adiposity-related measures, particularly overweight/obesity, higher body mass index, and higher body fat percentage, were the most consistently reported associated factors. Conclusions MetS appears to be highly prevalent among older adults in Vietnam, but the evidence base remains small and heterogeneous. Available data suggest lower prevalence estimates under IDF criteria than under NCEP-based or harmonised definitions. More large, standardised, community-based studies are needed to improve comparability and support public health planning. metabolic syndrome older adults elderly prevalence Vietnam systematic review meta-analysis Figures Figure 1 Figure 2 Figure 3 1. Introduction Metabolic syndrome (MetS) is a cluster of interconnected metabolic abnormalities, typically including central obesity, elevated blood pressure, hyperglycemia, hypertriglyceridemia, and low high-density lipoprotein cholesterol. This syndrome is clinically important because it is associated with a markedly increased risk of type 2 diabetes, cardiovascular disease, and premature mortality [ 1 , 2 ]. In older adults, these risks are compounded by age-related physiological changes, multimorbidity, polypharmacy, and declining functional reserve. As a result, MetS in later life is not only a cardiometabolic problem but also a broader geriatric and public health concern. In Vietnam, rapid population ageing, urbanisation, dietary transition, and reduced physical activity are likely contributing to an increasing burden of metabolic disorders. Previous Vietnamese studies conducted in the general adult population have reported substantial variability in MetS prevalence across provinces, study settings, and target populations. National or multicenter adult studies have shown that prevalence increases with age and tends to be higher in women and in people with overweight or obesity [ 3 , 4 ]. Community-based adult studies from Ho Chi Minh City, Thua Thien Hue, Thai Binh, and Hanoi have also suggested marked between-study variation, partly reflecting differences in population structure and case definition [ 5 – 7 ]. However, these studies were not specifically designed for older adults, and estimates for older adults remain limited. A further challenge is that prevalence estimates depend strongly on the diagnostic criteria used. The NCEP-ATP III framework and its modified or harmonised versions classify MetS when at least three of five metabolic abnormalities are present, while the IDF definition requires central obesity as a prerequisite plus at least two additional abnormalities [ 1 , 2 ]. This distinction can materially change the estimated disease burden in older populations. In Vietnam, some recent studies have reported clear differences in prevalence when different definitions were applied to the same population [ 8 – 10 ]. Yet no synthesis has focused specifically on older adults in Vietnam while explicitly considering the influence of NCEP-based versus IDF-based criteria. Therefore, this systematic review and meta-analysis aimed to synthesise the available evidence on the prevalence of MetS among older adults in Vietnam, to compare pooled prevalence estimates across diagnostic criteria, and to summarise the factors most consistently associated with MetS in this population. 2. Methods 2.1. Study design and reporting guideline This study was a systematic review and meta-analysis of observational studies on metabolic syndrome among older adults in Vietnam. The review was prepared in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) statement [ 11 ], and a completed PRISMA 2020 checklist is provided as Supplementary File 1. The eligibility criteria, extraction variables, and synthesis plan were prespecified before full-text assessment and quantitative synthesis. A protocol was not prospectively registered; this is acknowledged as a limitation and is stated transparently in the manuscript. 2.2. Eligibility criteria Studies were eligible if they met all of the following criteria: (1) conducted in Vietnam; (2) included older adults, defined primarily as participants aged 60 years or older, or provided extractable subgroup data for older adults; (3) reported the prevalence of MetS and/or associated factors; (4) used NCEP-ATP III, modified NCEP-ATP III for Asian populations, harmonized criteria, or IDF criteria to define MetS; and (5) used an observational design, including cross-sectional studies or baseline data from cohort-type surveys. Peer-reviewed articles and gray literature were both considered when sufficient methodological information and extractable outcome data were available. Studies were eligible if they included participants aged 60 years or older or reported extractable subgroup data specifically for older adults. Studies in general adult populations were excluded when elderly-specific numerator/denominator data or effect estimates could not be isolated. 2.3. Information sources and search strategy We searched PubMed and Scopus from database inception to 12 April 2026. The search strategy combined controlled vocabulary and free-text terms for three core concepts: metabolic syndrome, older adults, and Vietnam. Search terms included combinations of “metabolic syndrome”, “older adults”, “elderly”, “aged”, “Vietnam”, and “Vietnamese”, together with prevalence- and factor-related terms. To capture Vietnamese studies that were not reliably indexed in international databases, we also manually searched Vietnamese journals and institutional repositories. The full database strategies, search dates, manual-source log, and PRISMA-S style search documentation are provided in Supplementary File 3. The final PRISMA-based search counts were as follows: 7 records from PubMed, 5 records from Scopus, and 12 full-text reports identified through manual searches of journals and repositories. Three duplicate database records were removed, leaving 9 records for title/abstract screening; all 9 were excluded at that stage. Full-text eligibility assessment was performed on the 12 manually identified reports. All studies ultimately included in the review were identified through manual searches of journals and repositories rather than database screening, reflecting the limited indexing and inconsistent retrievability of relevant Vietnamese elderly-specific reports in international databases. 2.4. Study selection Two-step screening was undertaken. First, records identified through database searching were screened on title and abstract. Second, full-text reports identified through manual searching were assessed against the prespecified eligibility criteria. Screening was undertaken by the sole reviewer (TVN), and eligibility decisions were re-checked against the full text before final inclusion. Of the 12 full-text reports assessed, 9 were excluded: 8 because they were not elderly-only studies and 1 because it was a disease-specific elderly clinical sample outside the main synthesis. Three studies were retained in the final review and quantitative synthesis. The study selection process is summarised in Fig. 1 . 2.5. Data extraction A standardised extraction form was used to collect the following information from each eligible study: first author, year of publication, province or city, study setting, study design, sample size, age definition, sex distribution, diagnostic criteria used for MetS, number of MetS cases, reported prevalence, and main associated factors. Data extraction was undertaken by the sole reviewer (TVN) and cross-checked against the accessible full texts before synthesis. When discrepancies were found between abstract-level prevalence and the exact numerator/denominator data reported in the main results tables, the full-text numerator/denominator data were prioritised for quantitative synthesis. For example, in the Quang Binh study, the abstract reported a prevalence of 48.5%, but the detailed full-text table yielded 293 cases among 640 participants (45.8%), which was used for meta-analysis. 2.6. Risk of bias assessment Risk of bias was assessed using a JBI-style framework for prevalence studies, focusing on the appropriateness of the sampling frame, sampling method, sample size adequacy, clarity of subject and setting description, validity of the MetS definition, reliability of outcome measurement, appropriateness of statistical analysis, and adequacy of response rate or coverage [ 12 ]. Appraisal was undertaken by the sole reviewer (TVN) using a standardised domain-based template, and overall judgments were assigned as low, moderate, or high risk of bias based on the balance of these domains. In the present review, all three included studies were judged to be at moderate risk of bias. 2.7. Outcomes The primary outcome was the pooled prevalence of MetS among older adults in Vietnam. Secondary outcomes included pooled prevalence stratified by diagnostic criteria (especially NCEP-ATP III/modified NCEP-ATP III/harmonised versus IDF) and a narrative synthesis of associated factors reported across studies. 2.8. Statistical analysis in R Quantitative synthesis of prevalence was performed in R using random-effects meta-analysis of proportions with logit transformation. To avoid double-counting, the primary overall analysis retained only one prevalence estimate per study. For the Thai Binh older outpatient study, the non-IDF estimate under harmonised criteria was retained for the primary overall model [ 10 ]. Criterion-specific subgroup analyses then included the available NCEP-based or harmonised estimates and IDF-based estimates separately. Heterogeneity was assessed using the I² statistic and tau-squared (τ²), and prediction intervals were calculated when possible. Because of the limited number of included studies, subgroup difference testing, meta-regression, and publication-bias methods were interpreted cautiously and were not emphasised when not informative. 2.9. Analysis of associated factors A meta-analysis of associated factors was planned only if at least 3 studies reported sufficiently comparable definitions and effect measures for the same variable. In practice, the associated factors reported across the included studies varied in their exposure definitions, measurements, and model adjustments. Therefore, associated factors were synthesised narratively rather than quantitatively pooled. Particular attention was given to factors that remained significant in multivariable analyses, including sex, adiposity-related indicators, chronic comorbidities, and socioeconomic measures. 3. Results 3.1. Study selection A total of 12 records were identified through database searching, including 7 from PubMed and 5 from Scopus. After removal of 3 duplicate records, 9 records remained for title and abstract screening, and all 9 were excluded at that stage. Of the 12 full-text reports assessed, 9 were excluded: 8 studies conducted in general adult populations that did not provide extractable elderly-specific data, and 1 disease-specific elderly clinical study outside the predefined main synthesis. Three studies were ultimately included in the systematic review and meta-analysis of prevalence. 3.2. Characteristics of included studies The characteristics of the included studies are summarised in Table 1 . Two studies were published in peer-reviewed journals, and one was an eligible grey literature manuscript. The included studies represented both hospital-based and community-based settings. The Friendship Hospital study enrolled 400 older outpatients in Hanoi and used NCEP/ATP III criteria with modified waist circumference thresholds for Asians [ 8 ]. The former Quang Binh Province study included 640 community-dwelling older adults and used an updated NCEP ATP III framework adjusted for Asian populations, with operational substitutions for some available markers. The Thai Binh older outpatient manuscript included 404 participants and uniquely reported prevalence under both harmonised criteria and IDF criteria [ 10 ]. Across the included studies, sample sizes ranged from 400 to 640 participants. MetS prevalence used for quantitative synthesis: 45.8% (293/640 from the full-text results table; the abstract reported 48.5%). The reported prevalence ranged from 22.0% under IDF criteria in Thai Binh to 48.8% in Friendship Hospital; however, for meta-analysis, the Quang Binh study contributed the exact full-text numerator/denominator estimate of 293/640 (45.8%), which differed from the abstract-level percentage of 48.5% [ 9 ]. Table 1 Characteristics of included studies. Study Year Province/city Setting Study design Sample (n) Age definition Mean age / age group Women (%) Diagnostic criteria MetS prevalence Main associated factors / key findings Nguyễn Thị Vân Anh et al. 2024 Hà Nội Hospital outpatients (Friendship Hospital, Khoa khám bệnh B) Cross-sectional descriptive study 400 ≥ 60 years 74.01 ± 6.96 years; age groups 60–69 / 70–79 / ≥80 NR NCEP/ATP III with modified waist criteria for Asians 48.8% Male prevalence 51.2%, female 44.8%; commonest components were hypertension (91.3%), glucose disorder (77.9%), and central obesity (77.9%). Nguyễn Thị Sáu et al. 2025 Quảng Bình (former province) Community-dwelling older adults in 4 xã/phường Cross-sectional study using secondary VHAS round-2 data 640 ≥ 60 years Community-dwelling older adults; exact mean age NR in current extraction NR NCEP ATP III updated 2005, adjusted for Asians; with HbA1c/non-HDL substitutions 48.5% Female prevalence 58.9%, male 33.1%; independent factors included higher BMI, higher body fat percentage, chronic disease, and better economic status. Nguyen Van Tien et al. (gray literature manuscript) 2026 Thái Bình Older outpatients at Thai Binh University of Medicine and Pharmacy Hospital Cross-sectional analytical study 404 ≥ 60 years Age groups: 60–70 (58.4%), 70–80 (32.7%), ≥ 80 (8.9%) 61.1% Harmonised criteria (2009) and IDF 29.2% (harmonised); 22.0% (IDF) Independent factors under both definitions were female sex and overweight/obesity. Because this study was included as grey literature, duplicate checking against any later journal publication remains necessary. NR, not reported in the accessible source used for extraction. 3.3. Risk of bias assessment All three included studies were judged to have a moderate risk of bias (Table 2 ). The main limitations were the use of convenience samples of hospital-based outpatients, limited representativeness, and incomplete reporting of response rates or coverage. The Quang Binh study had a stronger community-based sampling structure, but some metabolic components were operationalised using available proxy markers, which reduced certainty in direct comparability [ 9 ]. Nevertheless, all studies clearly described their settings and analytic approaches, and all used recognisable MetS definitions suitable for stratified interpretation. Table 2 Risk of bias assessment of included studies. Study Sampling frame appropriate Sampling method appropriate Sample size adequate Study subjects and setting described Valid MetS definition used Outcome measured reliably Statistical analysis appropriate Response rate/coverage adequate Overall risk of bias Rationale/note Nguyễn Thị Vân Anh et al. (2024) No No Yes Yes Yes Yes Yes Unclear Moderate Single-centre outpatient convenience sample; clear setting, measurements, and diagnostic criteria, but limited representativeness and no reported response rate. Nguyễn Thị Sáu et al. (2025) Yes Yes Yes Yes Modified / unclear Yes Yes Unclear Moderate Community-based sample derived from an existing stratified cohort framework, but the study operationalised some MetS components using available proxy markers and experienced attrition from the original sample. Nguyen Van Tien et al. manuscript (2026) No No Yes Yes Yes Yes Yes Unclear Moderate Single-centre convenience outpatient sample and grey literature status; however, case definitions and analytic methods were clearly reported. Risk-of-bias assessment was preliminary and based on the currently accessible full texts in the project files. The domains were aligned with Joanna Briggs Institute-style appraisal for prevalence studies. Table 3 Pooled prevalence of metabolic syndrome overall and by diagnostic criteria. Analysis Studies (k) Participants (N) MetS cases Pooled prevalence (%) 95% CI I² (%) τ² Prediction interval p for subgroup difference Overall primary analysis* 3 1444 606 40.98 30.29–52.60 94.7 0.1623 21.70–63.50 — NCEP-ATP III / modified NCEP-ATP III / harmonised 3 1444 606 40.98 30.29–52.60 94.7 0.1623 21.70–63.50 — IDF 1 404 89 22.03 18.25–26.33 NA NA NA NA *One prevalence estimate per study was retained for the overall primary analysis to avoid double-counting. For the Thai Binh study, the non-IDF estimate (harmonised criteria) was used in the overall analysis. The Quang Binh paper showed an inconsistency between the abstract (48.5%) and the body table. This pooled analysis used the exact numerator/denominator from the full-text results table: 293/640 = 45.8%. 3.4. Pooled prevalence of metabolic syndrome In the primary overall analysis, one prevalence estimate per study was retained to avoid double-counting. Three studies contributed 1,444 participants and 606 MetS cases. The pooled prevalence of MetS among older adults in Vietnam was 40.98% (95% CI: 30.29%–52.60%). Between-study heterogeneity was substantial (I² = 94.7%; τ² = 0.1623), and the prediction interval was wide (21.70%–63.50%), indicating considerable variability in the expected prevalence across elderly populations and settings. Figure 2 presents the forest plot for the primary prevalence meta-analysis. 3.5. Subgroup analysis by diagnostic criteria Criterion-specific synthesis showed that all three retained estimates in the primary overall analysis belonged to the NCEP-ATP III/modified NCEP-ATP III/harmonised stratum, which is why the pooled estimate for this stratum was identical to the primary overall pooled prevalence. The pooled prevalence for this stratum was 40.98% (95% CI: 30.29%–52.60%; I² = 94.7%). By contrast, only one elderly-specific study contributed an IDF-based estimate, with 89 MetS cases among 404 older outpatients, corresponding to a prevalence of 22.03% (95% CI: 18.25%–26.33%) [ 10 ]. Because only one IDF-based study was available, heterogeneity and subgroup difference testing were not informative for that stratum. The single available IDF-based estimate was lower than the pooled estimate derived from NCEP-based or harmonised definitions; however, this comparison should be interpreted with caution, as only one IDF-based study was available. Figure 3 summarises the criterion-specific synthesis. 3.6. Additional subgroup analyses Additional subgroup analyses by sex, study setting, geographic region, or publication period were planned but could not be performed reliably because only three studies were included in the final synthesis, and the number of studies within each potential subgroup was too small. Instead, these characteristics were interpreted descriptively. The available data suggested a higher prevalence among women in the Quang Binh and Thai Binh datasets, whereas the Friendship Hospital study reported a slightly higher prevalence among men [ 8 – 10 ]. 3.7. Meta-regression Meta-regression was not performed because the number of included studies was insufficient to support stable regression estimates. With only three studies in the main synthesis, any meta-regression model would have been statistically underpowered and potentially misleading. 3.8. Sensitivity analyses Planned sensitivity analyses included exclusion of high-risk-of-bias studies, disease-specific clinical samples, and grey literature. However, because all included studies were judged to have moderate rather than high risk of bias, and because the total number of included studies was very small, sensitivity analyses were considered exploratory only. No disease-specific clinical sample was retained in the main meta-analysis, and the inclusion of the Thai Binh grey literature manuscript reflected its direct relevance, extractable data, and non-duplicative contribution to the criterion-specific synthesis [ 10 ]. 3.9. Associated factors Associated factors were synthesised narratively because the definitions and analytic models varied across studies. In the Friendship Hospital study, the prevalence of MetS was 48.8%, increased with age, and common components included hypertension, glucose disorder, and central obesity [ 8 ]. In the Quang Binh community study, female sex, higher body mass index, higher body fat percentage, chronic disease, and better economic status were associated with MetS; the study reported markedly higher prevalence in women than in men [ 9 ]. In the Thai Binh outpatient study, female sex and overweight/obesity were the only factors independently associated with MetS under both the harmonised and IDF definitions. Under harmonized criteria, the adjusted odds ratios were 2.57 (95% CI: 1.57–4.21) for female sex and 2.13 (95% CI: 1.35–3.36) for overweight/obesity; under IDF criteria, the corresponding adjusted odds ratios were 3.42 (95% CI: 1.91–6.13) and 4.12 (95% CI: 2.46–6.91), respectively. Overall, the most consistently associated factors across the included Vietnamese studies of the elderly were sex and adiposity-related measures. 3.10. Publication bias Publication bias and small-study effects were not formally assessed. With only three studies included in the quantitative synthesis and only one IDF-based study in the criterion-specific stratum, funnel plots and regression-based tests of asymmetry would not have been interpretable. 4. Discussion 4.1. Principal findings This systematic review identified a small but clinically important body of Vietnamese evidence on MetS in older adults. The primary pooled prevalence estimate of 40.98% indicates that MetS is common in this population. Although heterogeneity was high, all included studies suggested a substantial burden. The criterion-specific synthesis also suggested that prevalence estimates may differ materially according to the diagnostic framework used, with lower estimates under the IDF definition than under NCEP-derived or harmonised definitions. 4.2. Comparison with previous literature The prevalence observed in this review is substantially higher than the pooled estimate previously reported for the general Vietnamese adult population [ 3 ]. This is expected because MetS accumulates with age and because older adults often have a higher prevalence of hypertension, central adiposity, glucose dysregulation, and multimorbidity. The elderly-specific Vietnamese estimates in the present review are also broadly consistent with the pattern seen in other Asian settings, where older age and female sex are repeatedly associated with a higher MetS burden [ 13 ]. At the same time, the variability across settings in Vietnam remains notable: hospital outpatient populations and community-dwelling older adults may differ meaningfully in case mix, health-seeking behaviour, and underlying cardiometabolic risk [ 5 – 10 ]. 4.3. Interpretation of differences between NCEP-ATP III and IDF The lower prevalence observed under IDF criteria is methodologically plausible. Unlike NCEP-ATP III or harmonised definitions, the IDF framework requires central obesity as a mandatory component [ 1 , 2 ]. In older adults, especially in outpatient populations, some individuals may meet three metabolic criteria without exceeding the waist circumference threshold required by IDF. This structural difference can shift case classification and may explain the lower IDF estimate seen in the Thai Binh study [ 10 ]. For systematic reviews, this reinforces the importance of not indiscriminately pooling different diagnostic criteria. 4.4. Implications for practice and policy From a public health perspective, the findings support more active screening for MetS in older adults in Vietnam, particularly in primary care and outpatient settings. Simple routine measures such as waist circumference, body mass index, blood pressure, fasting glucose, triglycerides, and HDL-C can help identify high-risk individuals early [ 1 , 2 ]. The repeated association of MetS with female sex and adiposity-related indicators also highlights the need for weight management, nutrition counselling, and physical activity promotion in older populations [ 8 – 10 ]. At the policy level, more standardised epidemiological surveillance would improve comparability across provinces and strengthen the evidence base for prevention of geriatric non-communicable diseases. 4.5. Strengths and limitations This review has several strengths. It focused specifically on older adults in Vietnam, incorporated Vietnamese-language evidence and grey literature, and explicitly separated NCEP-based/harmonised estimates from IDF-based estimates. However, the limitations are substantial. First, the number of elderly-specific studies was small, and all included studies were at moderate risk of bias. Second, the evidence base was heterogeneous in setting, sample selection, and diagnostic operationalisation. Third, one included community study required extraction based on exact numerator/denominator data from the full text due to inconsistencies with the abstract. Fourth, the available data did not permit robust subgroup analyses beyond criterion-based synthesis, meta-regression, or formal assessment of publication bias. Finally, some potentially relevant studies were excluded from the main synthesis because they were not elderly-only or were disease-specific clinical samples. 5. Conclusion MetS appears to be common among older adults in Vietnam, but current prevalence estimates remain uncertain because they are based on a small number of heterogeneous studies. Within the available evidence, female sex and adiposity-related indicators were the most consistently reported associated factors. Additional community-based, multicentre studies using standardised diagnostic definitions are needed to improve comparability, refine prevalence estimates, and better inform prevention strategies for Vietnam’s ageing population. Declarations Acknowledgements: The author thanks the clinicians, researchers, and study participants whose work contributed to the evidence synthesised in this review. Funding: No external funding was received for this systematic review and meta-analysis. Conflict of interest: The author declares no conflict of interest related to this work. Data availability: All data used in this review were extracted from published studies, grey literature manuscripts, and author-curated screening materials. The working extraction sheets and derived summary tables are available from the corresponding author on reasonable request. Author contributions: TVN conceived the review, developed the search and screening framework, extracted and synthesised the data, drafted the manuscript, and approved the final version. Ethics statement: Ethics approval and informed consent were not required for this review because it synthesised data from previously reported studies and did not involve direct contact with human participants. References Alberti KGMM, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation. 2009;120(16):1640-5. doi:10.1161/CIRCULATIONAHA.109.192644. Alberti KGMM, Zimmet P, Shaw J. The metabolic syndrome—a new worldwide definition. 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Int J Evid Based Healthc. 2015;13(3):147-53. doi:10.1097/XEB.0000000000000054. Ranasinghe P, Mathangasinghe Y, Jayawardena R, Hills AP, Misra A. Prevalence and trends of metabolic syndrome among adults in the Asia-Pacific region: a systematic review. BMC Public Health. 2017;17(1):101. doi:10.1186/s12889-017-4041-1. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9399614","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":626042374,"identity":"376ab3f4-cdea-4043-8b0a-90b25d6f9cc5","order_by":0,"name":"Tien Nguyen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxElEQVRIiWNgGAWjYDACZjBpw2CAzMULeCBq0iRI0AKhDpOgxZ6d+djjwrbzdeYS2WkPGCqsExskcg8QcBhbuvHMttsSljNytxswnEkHaslLIKCFx0ya58xtCYMbudskGNsOJzbwnDEgoIX/G1DLOaiWf0Rp4WGT5qk4ANXSANTC3kNAy2E2oMMqkiV39rzdbpBwLN24jZAW9v7Dz6R5DOz4zdlztz34UGMt28/Mg18LMmBjSACTJACSFI+CUTAKRsEIAgDUnDr3mhlf6gAAAABJRU5ErkJggg==","orcid":"","institution":"Thai Binh University of Medicine and Pharmacy","correspondingAuthor":true,"prefix":"","firstName":"Tien","middleName":"","lastName":"Nguyen","suffix":""}],"badges":[],"createdAt":"2026-04-13 06:38:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9399614/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9399614/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107451968,"identity":"4f81e237-0fd5-4880-856f-effdd4b2a698","added_by":"auto","created_at":"2026-04-21 15:24:49","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1137698,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePRISMA 2020 flow diagram for study selection in the systematic review of metabolic syndrome among older adults in Vietnam.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9399614/v1/8b250f8bc1fb73edb9e9e24b.jpeg"},{"id":107451979,"identity":"265f256c-6f6a-4396-a678-84fae2ad8d8b","added_by":"auto","created_at":"2026-04-21 15:24:50","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":831653,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eForest plot of the overall pooled prevalence of metabolic syndrome among older adults in Vietnam.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9399614/v1/0d646149a454ca612413bb65.jpeg"},{"id":107451933,"identity":"209183f1-a21b-4db8-9219-05f3ff0e3055","added_by":"auto","created_at":"2026-04-21 15:24:37","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":412051,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eForest plot stratified by diagnostic criteria (NCEP-ATP III / modified NCEP-ATP III / harmonized vs IDF).\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9399614/v1/cec486b3d2c574311aa0f9d3.jpeg"},{"id":107452371,"identity":"8dbafc0b-3a6a-4888-8e5a-87a5e7a8a167","added_by":"auto","created_at":"2026-04-21 15:26:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2904459,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9399614/v1/6af593a2-4e37-4966-b987-8be8da8308b8.pdf"},{"id":107451970,"identity":"3c972e13-b101-455a-80c4-6fd6d1daa2eb","added_by":"auto","created_at":"2026-04-21 15:24:49","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":21920,"visible":true,"origin":"","legend":"","description":"","filename":"02.SupplementaryFile3.docx","url":"https://assets-eu.researchsquare.com/files/rs-9399614/v1/5a96d39d5030d7542786fe2e.docx"},{"id":107452160,"identity":"881caa26-1b83-4336-9481-ad1850a0c806","added_by":"auto","created_at":"2026-04-21 15:25:44","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":19679,"visible":true,"origin":"","legend":"","description":"","filename":"03.Optionalsupplementarytablesandnotesforresubmission.docx","url":"https://assets-eu.researchsquare.com/files/rs-9399614/v1/ed63b7587586bf3817f2217a.docx"},{"id":107451982,"identity":"4da8e6c6-4595-4a33-8d54-302fb19b6514","added_by":"auto","created_at":"2026-04-21 15:24:50","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":273647,"visible":true,"origin":"","legend":"","description":"","filename":"04.PRISMA2020.docx","url":"https://assets-eu.researchsquare.com/files/rs-9399614/v1/bf5dde4ef278d0e69709b70f.docx"},{"id":107452016,"identity":"4a7b9a51-9b95-4278-91ce-2cacd19bc475","added_by":"auto","created_at":"2026-04-21 15:25:04","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":283180,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile1to3.docx","url":"https://assets-eu.researchsquare.com/files/rs-9399614/v1/69b0e6136bfa4610d7171a38.docx"},{"id":107451974,"identity":"9f93ff2e-a088-4a57-a188-a52482c87a5d","added_by":"auto","created_at":"2026-04-21 15:24:50","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":13817,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterialslegends.docx","url":"https://assets-eu.researchsquare.com/files/rs-9399614/v1/ae5b5292ed7349f755164705.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prevalence of metabolic syndrome and associated factors among older adults in Vietnam: a systematic review and meta-analysis stratified by NCEP-ATP III and IDF diagnostic criteria","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eMetabolic syndrome (MetS) is a cluster of interconnected metabolic abnormalities, typically including central obesity, elevated blood pressure, hyperglycemia, hypertriglyceridemia, and low high-density lipoprotein cholesterol. This syndrome is clinically important because it is associated with a markedly increased risk of type 2 diabetes, cardiovascular disease, and premature mortality [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In older adults, these risks are compounded by age-related physiological changes, multimorbidity, polypharmacy, and declining functional reserve. As a result, MetS in later life is not only a cardiometabolic problem but also a broader geriatric and public health concern.\u003c/p\u003e \u003cp\u003eIn Vietnam, rapid population ageing, urbanisation, dietary transition, and reduced physical activity are likely contributing to an increasing burden of metabolic disorders. Previous Vietnamese studies conducted in the general adult population have reported substantial variability in MetS prevalence across provinces, study settings, and target populations. National or multicenter adult studies have shown that prevalence increases with age and tends to be higher in women and in people with overweight or obesity [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Community-based adult studies from Ho Chi Minh City, Thua Thien Hue, Thai Binh, and Hanoi have also suggested marked between-study variation, partly reflecting differences in population structure and case definition [\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. However, these studies were not specifically designed for older adults, and estimates for older adults remain limited.\u003c/p\u003e \u003cp\u003eA further challenge is that prevalence estimates depend strongly on the diagnostic criteria used. The NCEP-ATP III framework and its modified or harmonised versions classify MetS when at least three of five metabolic abnormalities are present, while the IDF definition requires central obesity as a prerequisite plus at least two additional abnormalities [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. This distinction can materially change the estimated disease burden in older populations. In Vietnam, some recent studies have reported clear differences in prevalence when different definitions were applied to the same population [\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Yet no synthesis has focused specifically on older adults in Vietnam while explicitly considering the influence of NCEP-based versus IDF-based criteria.\u003c/p\u003e \u003cp\u003eTherefore, this systematic review and meta-analysis aimed to synthesise the available evidence on the prevalence of MetS among older adults in Vietnam, to compare pooled prevalence estimates across diagnostic criteria, and to summarise the factors most consistently associated with MetS in this population.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study design and reporting guideline\u003c/h2\u003e \u003cp\u003eThis study was a systematic review and meta-analysis of observational studies on metabolic syndrome among older adults in Vietnam. The review was prepared in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) statement [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], and a completed PRISMA 2020 checklist is provided as Supplementary File 1. The eligibility criteria, extraction variables, and synthesis plan were prespecified before full-text assessment and quantitative synthesis. A protocol was not prospectively registered; this is acknowledged as a limitation and is stated transparently in the manuscript.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Eligibility criteria\u003c/h2\u003e \u003cp\u003eStudies were eligible if they met all of the following criteria: (1) conducted in Vietnam; (2) included older adults, defined primarily as participants aged 60 years or older, or provided extractable subgroup data for older adults; (3) reported the prevalence of MetS and/or associated factors; (4) used NCEP-ATP III, modified NCEP-ATP III for Asian populations, harmonized criteria, or IDF criteria to define MetS; and (5) used an observational design, including cross-sectional studies or baseline data from cohort-type surveys. Peer-reviewed articles and gray literature were both considered when sufficient methodological information and extractable outcome data were available. Studies were eligible if they included participants aged 60 years or older or reported extractable subgroup data specifically for older adults. Studies in general adult populations were excluded when elderly-specific numerator/denominator data or effect estimates could not be isolated.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Information sources and search strategy\u003c/h2\u003e \u003cp\u003eWe searched PubMed and Scopus from database inception to 12 April 2026. The search strategy combined controlled vocabulary and free-text terms for three core concepts: metabolic syndrome, older adults, and Vietnam. Search terms included combinations of \u0026ldquo;metabolic syndrome\u0026rdquo;, \u0026ldquo;older adults\u0026rdquo;, \u0026ldquo;elderly\u0026rdquo;, \u0026ldquo;aged\u0026rdquo;, \u0026ldquo;Vietnam\u0026rdquo;, and \u0026ldquo;Vietnamese\u0026rdquo;, together with prevalence- and factor-related terms. To capture Vietnamese studies that were not reliably indexed in international databases, we also manually searched Vietnamese journals and institutional repositories. The full database strategies, search dates, manual-source log, and PRISMA-S style search documentation are provided in Supplementary File 3. The final PRISMA-based search counts were as follows: 7 records from PubMed, 5 records from Scopus, and 12 full-text reports identified through manual searches of journals and repositories. Three duplicate database records were removed, leaving 9 records for title/abstract screening; all 9 were excluded at that stage. Full-text eligibility assessment was performed on the 12 manually identified reports.\u003c/p\u003e \u003cp\u003eAll studies ultimately included in the review were identified through manual searches of journals and repositories rather than database screening, reflecting the limited indexing and inconsistent retrievability of relevant Vietnamese elderly-specific reports in international databases.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Study selection\u003c/h2\u003e \u003cp\u003eTwo-step screening was undertaken. First, records identified through database searching were screened on title and abstract. Second, full-text reports identified through manual searching were assessed against the prespecified eligibility criteria. Screening was undertaken by the sole reviewer (TVN), and eligibility decisions were re-checked against the full text before final inclusion. Of the 12 full-text reports assessed, 9 were excluded: 8 because they were not elderly-only studies and 1 because it was a disease-specific elderly clinical sample outside the main synthesis. Three studies were retained in the final review and quantitative synthesis. The study selection process is summarised in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Data extraction\u003c/h2\u003e \u003cp\u003eA standardised extraction form was used to collect the following information from each eligible study: first author, year of publication, province or city, study setting, study design, sample size, age definition, sex distribution, diagnostic criteria used for MetS, number of MetS cases, reported prevalence, and main associated factors. Data extraction was undertaken by the sole reviewer (TVN) and cross-checked against the accessible full texts before synthesis. When discrepancies were found between abstract-level prevalence and the exact numerator/denominator data reported in the main results tables, the full-text numerator/denominator data were prioritised for quantitative synthesis. For example, in the Quang Binh study, the abstract reported a prevalence of 48.5%, but the detailed full-text table yielded 293 cases among 640 participants (45.8%), which was used for meta-analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Risk of bias assessment\u003c/h2\u003e \u003cp\u003eRisk of bias was assessed using a JBI-style framework for prevalence studies, focusing on the appropriateness of the sampling frame, sampling method, sample size adequacy, clarity of subject and setting description, validity of the MetS definition, reliability of outcome measurement, appropriateness of statistical analysis, and adequacy of response rate or coverage [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Appraisal was undertaken by the sole reviewer (TVN) using a standardised domain-based template, and overall judgments were assigned as low, moderate, or high risk of bias based on the balance of these domains. In the present review, all three included studies were judged to be at moderate risk of bias.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7. Outcomes\u003c/h2\u003e \u003cp\u003eThe primary outcome was the pooled prevalence of MetS among older adults in Vietnam. Secondary outcomes included pooled prevalence stratified by diagnostic criteria (especially NCEP-ATP III/modified NCEP-ATP III/harmonised versus IDF) and a narrative synthesis of associated factors reported across studies.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.8. Statistical analysis in R\u003c/h2\u003e \u003cp\u003eQuantitative synthesis of prevalence was performed in R using random-effects meta-analysis of proportions with logit transformation. To avoid double-counting, the primary overall analysis retained only one prevalence estimate per study. For the Thai Binh older outpatient study, the non-IDF estimate under harmonised criteria was retained for the primary overall model [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Criterion-specific subgroup analyses then included the available NCEP-based or harmonised estimates and IDF-based estimates separately. Heterogeneity was assessed using the I\u0026sup2; statistic and tau-squared (τ\u0026sup2;), and prediction intervals were calculated when possible. Because of the limited number of included studies, subgroup difference testing, meta-regression, and publication-bias methods were interpreted cautiously and were not emphasised when not informative.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.9. Analysis of associated factors\u003c/h2\u003e \u003cp\u003eA meta-analysis of associated factors was planned only if at least 3 studies reported sufficiently comparable definitions and effect measures for the same variable. In practice, the associated factors reported across the included studies varied in their exposure definitions, measurements, and model adjustments. Therefore, associated factors were synthesised narratively rather than quantitatively pooled. Particular attention was given to factors that remained significant in multivariable analyses, including sex, adiposity-related indicators, chronic comorbidities, and socioeconomic measures.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Study selection\u003c/h2\u003e \u003cp\u003eA total of 12 records were identified through database searching, including 7 from PubMed and 5 from Scopus. After removal of 3 duplicate records, 9 records remained for title and abstract screening, and all 9 were excluded at that stage. Of the 12 full-text reports assessed, 9 were excluded: 8 studies conducted in general adult populations that did not provide extractable elderly-specific data, and 1 disease-specific elderly clinical study outside the predefined main synthesis. Three studies were ultimately included in the systematic review and meta-analysis of prevalence.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Characteristics of included studies\u003c/h2\u003e \u003cp\u003eThe characteristics of the included studies are summarised in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Two studies were published in peer-reviewed journals, and one was an eligible grey literature manuscript. The included studies represented both hospital-based and community-based settings. The Friendship Hospital study enrolled 400 older outpatients in Hanoi and used NCEP/ATP III criteria with modified waist circumference thresholds for Asians [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The former Quang Binh Province study included 640 community-dwelling older adults and used an updated NCEP ATP III framework adjusted for Asian populations, with operational substitutions for some available markers. The Thai Binh older outpatient manuscript included 404 participants and uniquely reported prevalence under both harmonised criteria and IDF criteria [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Across the included studies, sample sizes ranged from 400 to 640 participants. MetS prevalence used for quantitative synthesis: 45.8% (293/640 from the full-text results table; the abstract reported 48.5%). The reported prevalence ranged from 22.0% under IDF criteria in Thai Binh to 48.8% in Friendship Hospital; however, for meta-analysis, the Quang Binh study contributed the exact full-text numerator/denominator estimate of 293/640 (45.8%), which differed from the abstract-level percentage of 48.5% [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of included studies.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProvince/city\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSetting\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStudy design\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSample (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAge definition\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMean age / age group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eWomen (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eDiagnostic criteria\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eMetS prevalence\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eMain associated factors / key findings\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNguyễn Thị V\u0026acirc;n Anh et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eH\u0026agrave; Nội\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHospital outpatients (Friendship Hospital, Khoa kh\u0026aacute;m bệnh B)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCross-sectional descriptive study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;60 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e74.01\u0026thinsp;\u0026plusmn;\u0026thinsp;6.96 years; age groups 60\u0026ndash;69 / 70\u0026ndash;79 / \u0026ge;80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNCEP/ATP III with modified waist criteria for Asians\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e48.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eMale prevalence 51.2%, female 44.8%; commonest components were hypertension (91.3%), glucose disorder (77.9%), and central obesity (77.9%).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNguyễn Thị S\u0026aacute;u et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eQuảng B\u0026igrave;nh (former province)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCommunity-dwelling older adults in 4 x\u0026atilde;/phường\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCross-sectional study using secondary VHAS round-2 data\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e640\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;60 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eCommunity-dwelling older adults; exact mean age NR in current extraction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNCEP ATP III updated 2005, adjusted for Asians; with HbA1c/non-HDL substitutions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e48.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eFemale prevalence 58.9%, male 33.1%; independent factors included higher BMI, higher body fat percentage, chronic disease, and better economic status.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNguyen Van Tien et al. (gray literature manuscript)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTh\u0026aacute;i B\u0026igrave;nh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOlder outpatients at Thai Binh University of Medicine and Pharmacy Hospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCross-sectional analytical study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;60 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAge groups: 60\u0026ndash;70 (58.4%), 70\u0026ndash;80 (32.7%), \u0026ge;\u0026thinsp;80 (8.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e61.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eHarmonised criteria (2009) and IDF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e29.2% (harmonised); 22.0% (IDF)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eIndependent factors under both definitions were female sex and overweight/obesity. Because this study was included as grey literature, duplicate checking against any later journal publication remains necessary.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"12\"\u003e\u003cem\u003eNR, not reported in the accessible source used for extraction.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Risk of bias assessment\u003c/h2\u003e \u003cp\u003eAll three included studies were judged to have a moderate risk of bias (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The main limitations were the use of convenience samples of hospital-based outpatients, limited representativeness, and incomplete reporting of response rates or coverage. The Quang Binh study had a stronger community-based sampling structure, but some metabolic components were operationalised using available proxy markers, which reduced certainty in direct comparability [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Nevertheless, all studies clearly described their settings and analytic approaches, and all used recognisable MetS definitions suitable for stratified interpretation.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRisk of bias assessment of included studies.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSampling frame appropriate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSampling method appropriate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSample size adequate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStudy subjects and setting described\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eValid MetS definition used\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eOutcome measured reliably\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eStatistical analysis appropriate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eResponse rate/coverage adequate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eOverall risk of bias\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eRationale/note\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNguyễn Thị V\u0026acirc;n Anh et al. (2024)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eUnclear\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eSingle-centre outpatient convenience sample; clear setting, measurements, and diagnostic criteria, but limited representativeness and no reported response rate.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNguyễn Thị S\u0026aacute;u et al. (2025)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModified / unclear\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eUnclear\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eCommunity-based sample derived from an existing stratified cohort framework, but the study operationalised some MetS components using available proxy markers and experienced attrition from the original sample.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNguyen Van Tien et al. manuscript (2026)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eUnclear\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eSingle-centre convenience outpatient sample and grey literature status; however, case definitions and analytic methods were clearly reported.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003e\u003cem\u003eRisk-of-bias assessment was preliminary and based on the currently accessible full texts in the project files.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003e\u003cem\u003eThe domains were aligned with Joanna Briggs Institute-style appraisal for prevalence studies.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePooled prevalence of metabolic syndrome overall and by diagnostic criteria.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnalysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStudies (k)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eParticipants (N)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMetS cases\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePooled prevalence (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eI\u0026sup2; (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eτ\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003ePrediction interval\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003ep for subgroup difference\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall primary analysis*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1444\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e606\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e40.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e30.29\u0026ndash;52.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e94.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.1623\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e21.70\u0026ndash;63.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNCEP-ATP III / modified NCEP-ATP III / harmonised\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1444\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e606\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e40.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e30.29\u0026ndash;52.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e94.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.1623\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e21.70\u0026ndash;63.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIDF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e22.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e18.25\u0026ndash;26.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003e\u003cem\u003e*One prevalence estimate per study was retained for the overall primary analysis to avoid double-counting. For the Thai Binh study, the non-IDF estimate (harmonised criteria) was used in the overall analysis.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003e\u003cem\u003eThe Quang Binh paper showed an inconsistency between the abstract (48.5%) and the body table. This pooled analysis used the exact numerator/denominator from the full-text results table: 293/640\u0026thinsp;=\u0026thinsp;45.8%.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Pooled prevalence of metabolic syndrome\u003c/h2\u003e \u003cp\u003eIn the primary overall analysis, one prevalence estimate per study was retained to avoid double-counting. Three studies contributed 1,444 participants and 606 MetS cases. The pooled prevalence of MetS among older adults in Vietnam was 40.98% (95% CI: 30.29%\u0026ndash;52.60%). Between-study heterogeneity was substantial (I\u0026sup2; = 94.7%; τ\u0026sup2; = 0.1623), and the prediction interval was wide (21.70%\u0026ndash;63.50%), indicating considerable variability in the expected prevalence across elderly populations and settings. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the forest plot for the primary prevalence meta-analysis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.5. Subgroup analysis by diagnostic criteria\u003c/h2\u003e \u003cp\u003eCriterion-specific synthesis showed that all three retained estimates in the primary overall analysis belonged to the NCEP-ATP III/modified NCEP-ATP III/harmonised stratum, which is why the pooled estimate for this stratum was identical to the primary overall pooled prevalence. The pooled prevalence for this stratum was 40.98% (95% CI: 30.29%\u0026ndash;52.60%; I\u0026sup2; = 94.7%). By contrast, only one elderly-specific study contributed an IDF-based estimate, with 89 MetS cases among 404 older outpatients, corresponding to a prevalence of 22.03% (95% CI: 18.25%\u0026ndash;26.33%) [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Because only one IDF-based study was available, heterogeneity and subgroup difference testing were not informative for that stratum. The single available IDF-based estimate was lower than the pooled estimate derived from NCEP-based or harmonised definitions; however, this comparison should be interpreted with caution, as only one IDF-based study was available. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e summarises the criterion-specific synthesis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.6. Additional subgroup analyses\u003c/h2\u003e \u003cp\u003eAdditional subgroup analyses by sex, study setting, geographic region, or publication period were planned but could not be performed reliably because only three studies were included in the final synthesis, and the number of studies within each potential subgroup was too small. Instead, these characteristics were interpreted descriptively. The available data suggested a higher prevalence among women in the Quang Binh and Thai Binh datasets, whereas the Friendship Hospital study reported a slightly higher prevalence among men [\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.7. Meta-regression\u003c/h2\u003e \u003cp\u003eMeta-regression was not performed because the number of included studies was insufficient to support stable regression estimates. With only three studies in the main synthesis, any meta-regression model would have been statistically underpowered and potentially misleading.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e3.8. Sensitivity analyses\u003c/h2\u003e \u003cp\u003ePlanned sensitivity analyses included exclusion of high-risk-of-bias studies, disease-specific clinical samples, and grey literature. However, because all included studies were judged to have moderate rather than high risk of bias, and because the total number of included studies was very small, sensitivity analyses were considered exploratory only. No disease-specific clinical sample was retained in the main meta-analysis, and the inclusion of the Thai Binh grey literature manuscript reflected its direct relevance, extractable data, and non-duplicative contribution to the criterion-specific synthesis [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e3.9. Associated factors\u003c/h2\u003e \u003cp\u003eAssociated factors were synthesised narratively because the definitions and analytic models varied across studies. In the Friendship Hospital study, the prevalence of MetS was 48.8%, increased with age, and common components included hypertension, glucose disorder, and central obesity [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In the Quang Binh community study, female sex, higher body mass index, higher body fat percentage, chronic disease, and better economic status were associated with MetS; the study reported markedly higher prevalence in women than in men [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In the Thai Binh outpatient study, female sex and overweight/obesity were the only factors independently associated with MetS under both the harmonised and IDF definitions. Under harmonized criteria, the adjusted odds ratios were 2.57 (95% CI: 1.57\u0026ndash;4.21) for female sex and 2.13 (95% CI: 1.35\u0026ndash;3.36) for overweight/obesity; under IDF criteria, the corresponding adjusted odds ratios were 3.42 (95% CI: 1.91\u0026ndash;6.13) and 4.12 (95% CI: 2.46\u0026ndash;6.91), respectively. Overall, the most consistently associated factors across the included Vietnamese studies of the elderly were sex and adiposity-related measures.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e3.10. Publication bias\u003c/h2\u003e \u003cp\u003ePublication bias and small-study effects were not formally assessed. With only three studies included in the quantitative synthesis and only one IDF-based study in the criterion-specific stratum, funnel plots and regression-based tests of asymmetry would not have been interpretable.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003e4.1. Principal findings\u003c/h2\u003e \u003cp\u003e This systematic review identified a small but clinically important body of Vietnamese evidence on MetS in older adults. The primary pooled prevalence estimate of 40.98% indicates that MetS is common in this population. Although heterogeneity was high, all included studies suggested a substantial burden. The criterion-specific synthesis also suggested that prevalence estimates may differ materially according to the diagnostic framework used, with lower estimates under the IDF definition than under NCEP-derived or harmonised definitions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Comparison with previous literature\u003c/h2\u003e \u003cp\u003eThe prevalence observed in this review is substantially higher than the pooled estimate previously reported for the general Vietnamese adult population [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. This is expected because MetS accumulates with age and because older adults often have a higher prevalence of hypertension, central adiposity, glucose dysregulation, and multimorbidity. The elderly-specific Vietnamese estimates in the present review are also broadly consistent with the pattern seen in other Asian settings, where older age and female sex are repeatedly associated with a higher MetS burden [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. At the same time, the variability across settings in Vietnam remains notable: hospital outpatient populations and community-dwelling older adults may differ meaningfully in case mix, health-seeking behaviour, and underlying cardiometabolic risk [\u003cspan additionalcitationids=\"CR6 CR7 CR8 CR9\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003e4.3. Interpretation of differences between NCEP-ATP III and IDF\u003c/h2\u003e \u003cp\u003eThe lower prevalence observed under IDF criteria is methodologically plausible. Unlike NCEP-ATP III or harmonised definitions, the IDF framework requires central obesity as a mandatory component [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In older adults, especially in outpatient populations, some individuals may meet three metabolic criteria without exceeding the waist circumference threshold required by IDF. This structural difference can shift case classification and may explain the lower IDF estimate seen in the Thai Binh study [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. For systematic reviews, this reinforces the importance of not indiscriminately pooling different diagnostic criteria.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section2\"\u003e \u003ch2\u003e4.4. Implications for practice and policy\u003c/h2\u003e \u003cp\u003e From a public health perspective, the findings support more active screening for MetS in older adults in Vietnam, particularly in primary care and outpatient settings. Simple routine measures such as waist circumference, body mass index, blood pressure, fasting glucose, triglycerides, and HDL-C can help identify high-risk individuals early [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The repeated association of MetS with female sex and adiposity-related indicators also highlights the need for weight management, nutrition counselling, and physical activity promotion in older populations [\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. At the policy level, more standardised epidemiological surveillance would improve comparability across provinces and strengthen the evidence base for prevention of geriatric non-communicable diseases.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003e4.5. Strengths and limitations\u003c/h2\u003e \u003cp\u003eThis review has several strengths. It focused specifically on older adults in Vietnam, incorporated Vietnamese-language evidence and grey literature, and explicitly separated NCEP-based/harmonised estimates from IDF-based estimates. However, the limitations are substantial. First, the number of elderly-specific studies was small, and all included studies were at moderate risk of bias. Second, the evidence base was heterogeneous in setting, sample selection, and diagnostic operationalisation. Third, one included community study required extraction based on exact numerator/denominator data from the full text due to inconsistencies with the abstract. Fourth, the available data did not permit robust subgroup analyses beyond criterion-based synthesis, meta-regression, or formal assessment of publication bias. Finally, some potentially relevant studies were excluded from the main synthesis because they were not elderly-only or were disease-specific clinical samples.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eMetS appears to be common among older adults in Vietnam, but current prevalence estimates remain uncertain because they are based on a small number of heterogeneous studies. Within the available evidence, female sex and adiposity-related indicators were the most consistently reported associated factors. Additional community-based, multicentre studies using standardised diagnostic definitions are needed to improve comparability, refine prevalence estimates, and better inform prevention strategies for Vietnam\u0026rsquo;s ageing population.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eThe author thanks the clinicians, researchers, and study participants whose work contributed to the evidence synthesised in this review.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eNo external funding was received for this systematic review and meta-analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest:\u0026nbsp;\u003c/strong\u003eThe author declares no conflict of interest related to this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability:\u0026nbsp;\u003c/strong\u003eAll data used in this review were extracted from published studies, grey literature manuscripts, and author-curated screening materials. The working extraction sheets and derived summary tables are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u0026nbsp;\u003c/strong\u003eTVN conceived the review, developed the search and screening framework, extracted and synthesised the data, drafted the manuscript, and approved the final version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics statement:\u0026nbsp;\u003c/strong\u003eEthics approval and informed consent were not required for this review because it synthesised data from previously reported studies and did not involve direct contact with human participants.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAlberti KGMM, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation. 2009;120(16):1640-5. doi:10.1161/CIRCULATIONAHA.109.192644.\u003c/li\u003e\n \u003cli\u003eAlberti KGMM, Zimmet P, Shaw J. The metabolic syndrome\u0026mdash;a new worldwide definition. Lancet. 2005;366(9491):1059-62. doi:10.1016/S0140-6736(05)67402-8.\u003c/li\u003e\n \u003cli\u003eDang AK, Le HT, Nguyen GT, Mamun AA, Do KN, Nguyen LHT, et al. Prevalence of metabolic syndrome and its related factors among Vietnamese people: a systematic review and meta-analysis. Diabetes Metab Syndr. 2022;16(4):102477. doi:10.1016/j.dsx.2022.102477.\u003c/li\u003e\n \u003cli\u003eHo NT, Tran MT, Tran CTD, Vanderbloemen L, Pham TT, Hoang LB, et al. Prevalence of metabolic syndrome among Vietnamese adult employees. Nutr Metab Cardiovasc Dis. 2024;34(2):326-33. doi:10.1016/j.numecd.2023.10.002.\u003c/li\u003e\n \u003cli\u003ePham Ngoc Oanh, Phan Thanh Tam, Van Thai Minh, Tran Quoc Cuong, Van Thi Giang Huong. Hoi chung chuyen hoa va mot so yeu to lien quan o nguoi truong thanh tai Thanh pho Ho Chi Minh nam 2020 [Metabolic syndrome and associated factors among adults in Ho Chi Minh City in 2020]. J Nutr Food. 2023;19(1+2):74-82. doi:10.56283/1859-0381/430.\u003c/li\u003e\n \u003cli\u003eDoan Phuoc Thuoc, Nguyen Thi Huong, Truong Thi Oanh. Ty le hoi chung chuyen hoa va mot so yeu to lien quan o nguoi dan tai hai xa cua huyen Phu Vang, tinh Thua Thien Hue [Prevalence and factors associated with metabolic syndrome among dwellers in two communes of Phu Vang district, Thua Thien Hue province]. Y Hoc TP Ho Chi Minh. 2019;23(5):169-76.\u003c/li\u003e\n \u003cli\u003eLe Thi Huong, Dang Quang Huy, Do Nam Khanh, Ngo Toan Anh. Thuc trang hoi chung chuyen hoa va mot so yeu to lien quan o nguoi truong thanh tai Ha Noi nam 2024-2025 [Current status of metabolic syndrome and associated factors among adults in Hanoi, 2024-2025]. J Med Res. 2025;195(10):514-23. doi:10.52852/tcncyh.v195i10.4132.\u003c/li\u003e\n \u003cli\u003eNguyen Thi Van Anh, Vu Bich Nga, Nguyen Thi Thanh Thuy. Thuc trang hoi chung chuyen hoa o nguoi cao tuoi tai Benh vien Huu Nghi [Current status of metabolic syndrome in the elderly at Friendship Hospital]. Vietnam J Diabetes Endocrinol. 2024;75:22-9. doi:10.47122/VJDE.2024.75.4.\u003c/li\u003e\n \u003cli\u003eNguyen Thi Sau, Do Thanh Binh, Tran Khanh Toan. Hoi chung chuyen hoa va mot so yeu to lien quan o nguoi cao tuoi tinh Quang Binh cu nam 2022 [Metabolic syndrome and associated factors among older adults in the former Quang Binh Province in 2022]. J Med Res. 2025;197(12):767-77. doi:10.52852/tcncyh.v197i12.4227.\u003c/li\u003e\n \u003cli\u003eNguyen TV, Nguyen TQ, Nguyen CD, Nguyen TD, Do TT, Vu NT, et al. Prevalence of metabolic syndrome and associated factors among older outpatients in Vietnam: a cross-sectional study. Unpublished grey literature manuscript. Thai Binh University of Medicine and Pharmacy; 2026.\u003c/li\u003e\n \u003cli\u003ePage MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372:n71. doi:10.1136/bmj.n71.\u003c/li\u003e\n \u003cli\u003eMunn Z, Moola S, Lisy K, Riitano D, Tufanaru C. Methodological guidance for systematic reviews of observational epidemiological studies reporting prevalence and cumulative incidence data. Int J Evid Based Healthc. 2015;13(3):147-53. doi:10.1097/XEB.0000000000000054.\u003c/li\u003e\n \u003cli\u003eRanasinghe P, Mathangasinghe Y, Jayawardena R, Hills AP, Misra A. Prevalence and trends of metabolic syndrome among adults in the Asia-Pacific region: a systematic review. BMC Public Health. 2017;17(1):101. doi:10.1186/s12889-017-4041-1.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"metabolic syndrome, older adults, elderly, prevalence, Vietnam, systematic review, meta-analysis","lastPublishedDoi":"10.21203/rs.3.rs-9399614/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9399614/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eMetabolic syndrome (MetS) is common in older adults and is associated with cardiovascular disease, type 2 diabetes, and functional decline. In Vietnam, evidence on MetS in older adults is scattered across community- and hospital-based studies, and prevalence estimates may vary substantially depending on the diagnostic criteria used.\u003c/p\u003e\u003ch2\u003eObjectives\u003c/h2\u003e \u003cp\u003eTo synthesise the available evidence on the prevalence of MetS and associated factors among older adults in Vietnam, with stratification by NCEP-ATP III and IDF criteria.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA systematic review and meta-analysis of observational studies was conducted using PubMed, Scopus, and manual searches of Vietnamese journals and institutional repositories through 12 April 2026. Eligible studies were conducted in Vietnam, included participants aged 60 years or older or extractable elderly subgroup data, and reported MetS prevalence and/or associated factors using NCEP-ATP III, modified NCEP-ATP III, harmonised, or IDF criteria. Random-effects meta-analysis of prevalence was performed in R using logit-transformed proportions.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThree eligible elderly-specific studies were included in the quantitative synthesis, comprising 1,444 participants. For the primary analysis, one prevalence estimate per study was retained to avoid double-counting. The pooled prevalence of MetS among older adults in Vietnam was 40.98% (95% CI: 30.29%\u0026ndash;52.60%), with substantial heterogeneity (I\u0026sup2; = 94.7%). In criterion-specific analyses, the pooled prevalence for NCEP-ATP III/modified NCEP-ATP III/harmonised definitions was also 40.98% (95% CI: 30.29%\u0026ndash;52.60%), whereas the single IDF-based estimate was 22.03% (95% CI: 18.25%\u0026ndash;26.33%). Female sex and adiposity-related measures, particularly overweight/obesity, higher body mass index, and higher body fat percentage, were the most consistently reported associated factors.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eMetS appears to be highly prevalent among older adults in Vietnam, but the evidence base remains small and heterogeneous. Available data suggest lower prevalence estimates under IDF criteria than under NCEP-based or harmonised definitions. More large, standardised, community-based studies are needed to improve comparability and support public health planning.\u003c/p\u003e","manuscriptTitle":"Prevalence of metabolic syndrome and associated factors among older adults in Vietnam: a systematic review and meta-analysis stratified by NCEP-ATP III and IDF diagnostic criteria","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-21 15:23:21","doi":"10.21203/rs.3.rs-9399614/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"86401626620078676717217597093450524354","date":"2026-05-07T02:50:57+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-22T08:11:38+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-20T06:52:21+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-18T04:55:21+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Geriatrics","date":"2026-04-18T04:51:28+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fbe4e573-c3f7-46da-94a1-2284e2dbd366","owner":[],"postedDate":"April 21st, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"86401626620078676717217597093450524354","date":"2026-05-07T02:50:57+00:00","index":39,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-22T08:25:03+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-21 15:23:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9399614","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9399614","identity":"rs-9399614","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}