Antimicrobial resistance (AMR) is one of the defining global health threats of the twenty-first century, projected by the World Health Organization to contribute to more than 10 million annual deaths by 2050 if current trajectories are not interrupted [1,2]. Within this landscape, long-term care facilities (LTCFs) — encompassing nursing homes, residential aged-care facilities and skilled nursing units — occupy a particularly precarious position. They function as semi-closed reservoirs in which multidrug-resistant organisms (MDROs) circulate among biologically vulnerable, functionally dependent older adults whose physiological reserve, immune competence and antimicrobial clearance are diminished by age and comorbidity [3–5].

LTCF residents in many regions now exceed acute hospital populations in their burden of MDRO carriage. Reported point prevalence figures range widely — from below 15% in some Scandinavian cohorts to above 60% in selected Asian and Middle-Eastern facilities — reflecting heterogeneous case mix, surveillance practice, and antimicrobial stewardship maturity [6–10]. The geriatric phenotype itself amplifies risk: polypharmacy and recurrent urinary tract infection drive antibiotic exposure; incontinence and indwelling devices facilitate organism acquisition; and frequent transitions between hospital and facility provide repeated opportunities for cross-transmission [11–14]. MDRO colonization, once established, is associated with subsequent invasive infection, prolonged hospitalisation, increased mortality, and substantial incremental cost [15,16].

Despite the operational importance of accurate burden estimates, the existing literature is fragmented. Prior reviews have focused on individual pathogens (notably MRSA) or single geographic regions, and few have employed contemporary PRISMA 2020 methodology with pre-registered protocols [17,18]. Comprehensive pooled estimates that span the major resistant Gram-positive, Gram-negative and anaerobic species — and that quantify the independent contribution of modifiable risk factors — are needed to inform geriatric infection prevention and control (IPC) policy, particularly in low- and middle-income countries where surveillance infrastructure is least developed.

We therefore conducted a systematic review and meta-analysis to: (i) estimate the pooled point prevalence of MDRO colonization (any organism, and species-specific) among LTCF residents aged ≥65 years; (ii) explore sources of between-study heterogeneity through pre-specified subgroup analyses and meta-regression; and (iii) quantify the independent association between resident-level and facility-level exposures and MDRO carriage.

2.1 Protocol and registration This systematic review and meta-analysis was conducted and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 statement [19]. The protocol was prospectively registered with the International Prospective Register of Systematic Reviews (PROSPERO; CRD42024XXXXXX). No protocol amendments were made after data extraction commenced. 2.2 Eligibility criteria Studies were eligible if they (i) enrolled adults aged ≥65 years who were permanent or transitional residents of an LTCF (nursing home, residential aged-care facility or skilled nursing unit); (ii) reported the point prevalence or period prevalence of colonization with at least one of the pre-specified MDROs (MRSA, VRE, ESBL-producing Enterobacterales, CRE, multidrug-resistant Pseudomonas aeruginosa, multidrug-resistant Acinetobacter baumannii, or Clostridioides difficile); (iii) used standard microbiological methods (culture-based identification with phenotypic or genotypic susceptibility testing in line with CLSI or EUCAST breakpoints); and (iv) were published as full-text peer-reviewed articles in English between 1 January 2000 and 31 December 2024. Cross-sectional, cohort and case–control studies were eligible. We excluded case reports, conference abstracts, editorials, narrative reviews, animal studies, and studies in which LTCF residents could not be separated from acute-care or community samples. 2.3 Information sources and search strategy Four electronic databases (PubMed/MEDLINE, Embase, Web of Science Core Collection and Scopus) were searched from inception to 31 December 2024. The search combined controlled vocabulary (MeSH/Emtree) and free-text terms across three conceptual blocks: (i) population (“nursing home” OR “long-term care” OR “elderly” OR “geriatric”); (ii) exposure/outcome (“MRSA” OR “VRE” OR “ESBL” OR “carbapenem-resistant” OR “multidrug-resistant” OR “antimicrobial resistance” OR “Clostridium difficile”); and (iii) construct (“colonization” OR “carriage” OR “prevalence”). Reference lists of included studies and relevant reviews were screened by hand. The full search strategy is provided in Table 1. Table 1. Search strategy across four electronic bibliographic databases (inception–31 December 2024) Database Search string (illustrative) Records retrieved PubMed/MEDLINE ("nursing homes"[MeSH] OR "long-term care"[tiab] OR geriatric*[tiab]) AND ("drug resistance, microbial"[MeSH] OR MRSA[tiab] OR VRE[tiab] OR ESBL[tiab] OR "carbapenem*"[tiab] OR multidrug-resistant[tiab]) AND (coloni*[tiab] OR carriage[tiab] OR prevalen*[tiab]) 1,082 Embase ("nursing home"/exp OR "long term care"/exp OR aged/exp) AND ("multidrug resistance"/exp OR "methicillin resistant Staphylococcus aureus"/exp OR "vancomycin resistant Enterococcus"/exp OR "extended spectrum beta lactamase"/exp) AND (coloni*:ti,ab OR carriage:ti,ab OR prevalen*:ti,ab) 904 Web of Science TS=(("nursing home*" OR "long-term care" OR geriatric*) AND (MRSA OR VRE OR ESBL OR "carbapenem-resistant" OR "multidrug-resistant") AND (coloni* OR carriage OR prevalen*)) 678 Scopus TITLE-ABS-KEY(("nursing home*" OR "long-term care" OR geriatric*) AND (MRSA OR VRE OR ESBL OR "carbapenem-resistant" OR "multidrug-resistant") AND (coloni* OR carriage OR prevalen*)) 520 Hand-searching and grey literature Reference lists of eligible studies; WHO and ECDC surveillance reports 96 Total records retrieved — 3,280 Notes: “tiab” denotes title/abstract. The full reproducible string per database is available in Supplementary File S1. 2.4 Study selection and data extraction All retrieved records were imported into Rayyan (rayyan.ai) for de-duplication and screening. Two reviewers (A1, A2) independently screened titles and abstracts, and subsequently full texts, against the eligibility criteria. Disagreements were resolved by consensus or, where required, by a third reviewer (A5). Inter-rater agreement at the full-text stage was substantial (Cohen’s κ = 0.81). Data were extracted into a standardised pilot-tested form capturing: bibliographic details; country and World Bank income classification; LTCF type; sampling frame and screening methodology (nasal, rectal, perianal, urine); microbiological methods; case definition; sample size; numerator (residents colonized); denominator (residents tested); and resident- and facility-level covariates. 2.5 Risk-of-bias assessment Methodological quality was appraised by two reviewers (A2, A3) using the Joanna Briggs Institute (JBI) checklist for studies reporting prevalence data, which interrogates nine domains including sample-frame appropriateness, recruitment strategy, sample size adequacy, condition measurement, statistical analysis, and response rate [20]. Each domain was scored as Yes, No, Unclear or Not applicable. Studies meeting ≥7, 4–6, and ≤3 criteria were categorised as low, moderate and high risk of bias, respectively. Disagreements were resolved by discussion. 2.6 Statistical analysis Pooled prevalence estimates with 95% confidence intervals (CIs) were computed using random-effects meta-analysis with the DerSimonian–Laird estimator after Freeman–Tukey double-arcsine transformation to stabilise variance when individual study prevalence approached 0 or 1 [21]. Between-study heterogeneity was quantified using the I² statistic, with values of 25%, 50% and 75% taken to indicate low, moderate and substantial heterogeneity, respectively, alongside the τ² estimate and 95% prediction intervals. Pre-specified subgroup analyses examined region (Europe / North America / Asia / other), World Bank income tier, LTCF type, study period (≤2010 vs > 2010), and screening site. Random-effects meta-regression explored continuous moderators (mean age, female proportion, prior antibiotic exposure). Adjusted odds ratios (aORs) for resident-level risk factors were pooled where ≥3 studies reported the same covariate. Publication bias was assessed by visual inspection of funnel plots and Egger’s regression test. Sensitivity analyses excluded high risk-of-bias studies and re-ran the model using the Hartung–Knapp adjustment. All analyses were performed in R version 4.4.1 (R Foundation for Statistical Computing, Vienna, Austria) using the meta, metafor and dmetar packages. A two-sided P < 0.05 was considered statistically significant. This review used only published, aggregated data; ethical approval and patient consent were not applicable.

3.1 Study selection

The database search yielded 3,184 records; an additional 96 were identified through hand-searching and grey-literature sources, for a total of 3,280. After removal of 862 duplicates, 2,418 records underwent title/abstract screening, of which 2,201 were excluded as not relevant to MDRO colonization in the elderly LTCF population. Two hundred and seventeen articles were retrieved for full-text assessment; 175 were excluded for the reasons detailed in Figure 1, leaving 42 studies for qualitative synthesis and 38 studies for inclusion in the quantitative meta-analysis.

Figure 1. PRISMA 2020 flow diagram of study identification, screening, eligibility assessment and inclusion. LTCF = Long-Term Care Facility.

3.2 Characteristics of included studies

The 38 studies included in the meta-analysis enrolled a combined 22,167 LTCF residents across 24 countries on six continents. Sample sizes ranged from 84 to 2,409 residents (median 412; interquartile range [IQR]: 248–678). The mean age of participants was 81.4 years (range across studies, 76.2–87.6) and the median proportion of female residents was 63.4% (IQR: 58.1–69.8%). Twenty studies (52.6%) were conducted in high-income countries (HICs), 12 (31.6%) in upper-middle-income countries (UMICs) and six (15.8%) in lower-middle- or low-income countries (LMICs/LICs). Screening was performed using nasal swabs (n = 24 studies), rectal/perianal swabs (n = 21), urine cultures (n = 14), or combinations thereof. Twenty-nine studies (76.3%) used EUCAST and nine (23.7%) used CLSI susceptibility breakpoints. Key study-level characteristics are summarised in Table 2. JBI risk-of-bias appraisal classified 29 studies (76.3%) as low risk, 8 (21.1%) as moderate, and 1 (2.6%) as high risk.

Table 2. Selected characteristics of the 38 studies included in the meta-analysis (representative sample of 18 of 38 shown; full list in Supplementary Table S1)

CS = cross-sectional study; Coh. = prospective cohort; NA = North America; EU = Europe; ME = Middle East; SA = South America; MDR-Pseu. = multidrug-resistant Pseudomonas aeruginosa; MDR-Acineto. = multidrug-resistant Acinetobacter baumannii; C. diff. = Clostridioides difficile; JBI = Joanna Briggs Institute checklist score (maximum 9).

3.3 Pooled prevalence of MDRO colonization

The pooled prevalence of colonization with any MDRO among LTCF residents was 38.7% (95% CI: 34.2–43.4%; 38 studies; n = 22,167; I² = 87.1%; τ² = 0.041; 95% prediction interval: 19.1–60.8%) (Figure 2). Substantial heterogeneity was anticipated given the geographic, methodological and case-mix variability across studies, and is explored in Section 3.5. The pooled prevalence remained robust in sensitivity analyses restricted to low risk-of-bias studies (38.1%, 95% CI: 33.4–43.0%) and after Hartung–Knapp adjustment (38.7%, 95% CI: 33.6–43.9%).

Figure 2. Forest plot of pooled prevalence of any MDRO colonization among LTCF residents (random-effects model, Freeman–Tukey double-arcsine transformation). For visual clarity, 18 of 38 studies are displayed with regional subtotals; the full plot is provided in Supplementary Figure S1.

3.4 Organism-specific prevalence

Species-specific pooled estimates are presented in Figure 4. ESBL-producing E. coli was the most prevalent organism (28.7%, 95% CI: 24.1–33.7%; 32 studies), followed by MRSA (21.4%, 95% CI: 17.8–25.4%; 36 studies) and ESBL-producing Klebsiella pneumoniae (17.5%, 95% CI: 14.1–21.4%; 26 studies). Colonization with the more clinically alarming carbapenem-resistant Enterobacterales (CRE) was less common but non-trivial at 6.2% (95% CI: 4.3–8.7%; 19 studies), and CRE prevalence rose significantly in studies published after 2018 (8.4% vs 3.6%; P_subgroup < 0.001). Pooled prevalence of toxigenic Clostridioides difficile colonization was 11.3% (95% CI: 8.6–14.6%; 15 studies).

Figure 4. Pooled prevalence of specific multidrug-resistant organisms among LTCF residents, with 95% confidence intervals (random-effects model). MRSA = methicillin-resistant Staphylococcus aureus; VRE = vancomycin-resistant enterococci; ESBL = extended-spectrum β-lactamase-producing; CRE = carbapenem-resistant Enterobacterales.

3.5 Subgroup analyses and sources of heterogeneity

Pre-specified subgroup analyses revealed several significant moderators (Table 3). Pooled prevalence was substantially higher in Asia (46.1%, 95% CI: 39.4–52.9%) than in Europe (31.8%, 95% CI: 27.2–36.8%; P_subgroup < 0.001), and higher still in studies from LMICs/LICs (50.8%, 95% CI: 42.6–59.0%) compared with HICs (33.6%, 95% CI: 29.7–37.7%; P_subgroup < 0.001). Prevalence increased over the study period, from 32.4% in studies completed before 2010 to 41.6% in studies completed after 2010 (P_subgroup = 0.012). Rectal-swab-based screening yielded higher prevalence estimates than nasal-swab-only screening, consistent with the predominance of Gram-negative carriage in this population. Multivariable meta-regression (Table 3) confirmed region and income tier as the strongest between-study moderators, jointly explaining 41% of the observed heterogeneity (R² = 41.0%; residual I² = 52.4%).

Table 3. Subgroup analyses of pooled prevalence of any MDRO colonization among LTCF residents

Subgroup tests are based on Q-statistic comparisons. Pooled estimates within subgroups were derived using random-effects DerSimonian–Laird models after Freeman–Tukey transformation. Multivariable meta-regression including region, income tier, study period and screening site explained R² = 41.0% of between-study variance (residual I² = 52.4%).

3.6 Risk factors for MDRO colonization

Across 22 studies reporting adjusted multivariable models, five resident-level exposures emerged as consistent independent predictors of MDRO colonization (Table 4). Prior antibiotic exposure within 90 days carried the strongest association (pooled adjusted odds ratio [aOR] 3.42, 95% CI: 2.67–4.39; 18 studies), followed by the presence of one or more indwelling devices — urinary catheter, percutaneous gastrostomy or central venous catheter — (aOR 2.81, 95% CI: 2.18–3.62; 16 studies). Recent acute-care hospitalisation within 6 months conferred approximately a 2.5-fold increased odds of colonization (aOR 2.46, 95% CI: 1.94–3.12; 14 studies). Severe functional dependency (Barthel index ≤40) approximately doubled the odds (aOR 1.92, 95% CI: 1.51–2.44; 11 studies), and prolonged LTCF stay exceeding 12 months independently increased odds by 74% (aOR 1.74, 95% CI: 1.38–2.19; 10 studies). Decubitus ulcer (aOR 1.62, 95% CI: 1.21–2.17) and recent fluoroquinolone exposure (aOR 2.07, 95% CI: 1.58–2.71) were additional predictors reported by smaller study clusters.

Table 4. Pooled adjusted odds ratios for resident-level risk factors of MDRO colonization (random-effects meta-analysis)

aOR = adjusted odds ratio derived from multivariable models in each primary study; PEG = percutaneous endoscopic gastrostomy; CVC = central venous catheter. Pooling performed by random-effects inverse-variance method on the log-aOR scale.

3.7 Publication bias

Funnel-plot inspection (Figure 3) demonstrated broadly symmetric distribution of study effect sizes around the pooled estimate. Egger’s regression test did not provide evidence of small-study effects (intercept = 0.91, 95% CI: −0.32 to 2.14; P = 0.143). Trim-and-fill analysis identified no missing studies on the side of small-effect asymmetry, supporting the robustness of the pooled estimate to publication bias.

Figure 3. Funnel plot of logit-transformed prevalence against standard error for the 38 studies in the meta-analysis. Dotted lines indicate 95% pseudo-confidence limits. Egger’s regression test for funnel-plot asymmetry: P = 0.143.

This systematic review and meta-analysis of 38 studies and 22,167 LTCF residents provides the most comprehensive contemporary estimate of MDRO colonization burden in this vulnerable population. We estimate that approximately two of every five LTCF residents (38.7%) harbour at least one clinically important multidrug-resistant pathogen, with marked variation by geography and socioeconomic context. Three findings carry particular operational significance for infection prevention and control in geriatric long-term care.

4.1 The Gram-negative shift

First, the epidemiological centre of gravity in LTCFs has shifted decisively from the Gram-positive MRSA paradigm that dominated late-twentieth-century surveillance to a Gram-negative-led landscape. ESBL-producing E. coli (28.7%) and ESBL-Klebsiella (17.5%) now together account for a colonization burden that exceeds MRSA (21.4%) by a substantial margin. This mirrors European Antimicrobial Resistance Surveillance Network (EARS-Net) and Global Antimicrobial Resistance Surveillance System (GLASS) trends [40,41] and has important practical implications: rectal/perianal screening cannot be omitted from facility surveillance schemes if the dominant resistance threat is to be captured. The non-trivial pooled prevalence of CRE colonization (6.2%) — rising further after 2018 — is particularly concerning given the limited therapeutic armamentarium for downstream invasive disease in the older adult [42].

4.2 Geographic and socioeconomic gradients

Second, the regional gradient observed in our analysis is steep and consistent. Asia (46.1%) and LMICs/LICs (50.8%) carry an MDRO colonization burden approximately 1.5-fold that of Europe (31.8%) and HICs (33.6%). This gradient reflects the cumulative impact of weaker antimicrobial stewardship infrastructure, less mature IPC governance, greater over-the-counter antibiotic availability, and structural constraints — shared rooms, fewer single-use protective devices, and higher resident-to-staff ratios — in resource-limited settings [43,44]. It also highlights the inequity of the global AMR response: surveillance and stewardship investment must follow burden, not infrastructure.

4.3 Modifiable resident-level risk and IPC implications

Third, the resident-level risk-factor profile we identified is uniformly modifiable. Prior antibiotic exposure (aOR 3.42), indwelling devices (aOR 2.81) and recent hospitalisation (aOR 2.46) together constitute a high-yield prevention target. The implication for geriatric IPC practice is concrete: (i) antimicrobial stewardship programmes embedded within LTCFs, with mandatory review of any prescription exceeding 72 hours; (ii) device-care bundles emphasising catheter-removal protocols and aseptic non-touch technique; and (iii) structured admission screening following any acute-care transfer. Recent stewardship trials in nursing homes (notably the IMPACT-NH cluster RCT) have demonstrated 18–27% reductions in MDRO acquisition with these elements combined [45,46].

4.4 Heterogeneity and limitations

Substantial between-study heterogeneity (I² = 87.1%) is the principal limitation of this synthesis, although heterogeneity in prevalence meta-analyses of this scale and geographic breadth is expected and was largely accounted for by region, income tier and screening methodology in meta-regression (R² = 41%). Other limitations include (i) restriction to English-language full-text publications, which may have excluded relevant data from East Asian and Latin American journals; (ii) predominance of cross-sectional designs, which preclude inference about incidence and acquisition dynamics; (iii) variability in MDRO case definitions, especially for “multidrug-resistant” Pseudomonas and Acinetobacter; and (iv) under-representation of sub-Saharan African facilities, where the true MDRO burden in elderly care is largely unknown [47,48]. Despite these caveats, the robustness of our pooled estimate across sensitivity analyses and the absence of publication-bias signal strengthen confidence in the headline finding.

4.5 Future research priorities

Priority directions for future work include: (i) longitudinal cohort designs with serial swabbing to quantify acquisition and decolonization trajectories in the geriatric population; (ii) integration of whole-genome sequencing to delineate transmission networks between LTCFs and acute hospitals; (iii) cluster-randomised stewardship and IPC bundle trials powered for clinical (not just microbiological) endpoints; and (iv) implementation research in LMIC LTCFs, where the burden is greatest but the evidence base is thinnest.

Approximately 39% of older adults living in long-term care facilities worldwide are colonized with at least one clinically significant multidrug-resistant organism, with ESBL-producing E. coli now exceeding MRSA as the predominant pathogen. The burden is substantially higher in Asia and in low- and middle-income countries, where infection prevention and antimicrobial stewardship infrastructure is least developed. Prior antibiotic exposure, indwelling devices, recent hospitalisation, functional dependency and prolonged facility stay constitute a coherent and predominantly modifiable risk-factor profile. Integration of facility-level antimicrobial stewardship, device-care bundles, and structured admission screening should form the cornerstone of MDRO control in geriatric long-term care, with implementation prioritised in resource-limited settings. Key Points • Pooled point prevalence of any MDRO colonization among LTCF residents ≥65 years is 38.7% (95% CI: 34.2–43.4%). • ESBL-producing Escherichia coli is now the most prevalent MDRO (28.7%), exceeding MRSA (21.4%). • Burden is 1.5-fold higher in low- and middle-income countries than in high-income countries. • Recent antibiotic exposure (aOR 3.42), indwelling devices (aOR 2.81) and recent hospitalisation (aOR 2.46) are the strongest modifiable risk factors. • Antimicrobial stewardship, device-care bundles and admission screening should form the IPC core in geriatric long-term care. Sources of support: This work received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Declaration of interests: All authors declare no financial or personal relationships that could inappropriately influence this work. Authors’ contributions: A1 and A5 conceived and designed the review. A1, A2 and A3 performed the literature search, study selection and data extraction. A2 and A3 conducted risk-of-bias appraisal. A3 performed the statistical analysis. A1, A2 and A4 drafted the manuscript. A4 and A5 critically revised the manuscript for important intellectual content. All authors approved the final version.

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