BAN Score and Distinct Early Cardiometabolic Risk Signatures in a Non-Diabetic Population: A Cross-Sectional Analysis Article Swipe
Yazeed Alshuweishi
,
Noha A. Alshuwayer
,
Lama Izziddeen
,
Arwa Abudawood
,
Dalal Alfayez
,
Ahmed Basudan
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/healthcare13182384
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/healthcare13182384
Background: The BMI–albumin–neutrophil-to-lymphocyte (BAN) score integrates adiposity, nutritional status, and systemic inflammation, but its role in detecting early cardiometabolic changes remains unclear. This study examined associations of the BAN score with vascular, glycemic, and lipid markers in non-diabetic adults. Methods: This retrospective cross-sectional study included 162 non-diabetic subjects. Associations between the BAN score and vascular, glycemic, and lipid parameters were examined using Spearman’s correlation, ROC analysis, and regression models adjusted for age, sex, smoking status, and medication use. Results: Patients had a median age of 37 years, 72.8% were female, with median BMI 33 kg/m2, albumin 4.4 g/dL, and NLR 1.3. Higher BAN scores correlated with systolic blood pressure (SBP) (r = 0.23, p < 0.01), pulse pressure (PP) (r = 0.26, p < 0.001), and HbA1c (r = 0.22, p < 0.01). Compared with the lowest tertile, higher BAN tertiles showed significantly elevated SBP, PP, and HbA1c (p < 0.01). In adjusted models, each one-unit increase in BAN score was associated with higher SBP (β = 1.01, p = 0.037), PP (β = 0.66, p = 0.006), and HbA1c (β = 1.85, p = 0.008). No associations were found with the atherogenic index of plasma (AIP), Castelli risk index I (CRI-I), or Castelli risk index II (CRI-II). ROC analysis showed moderate discriminative ability for hypertension (AUC = 0.66) and HbA1c (AUC = 0.65). Conclusions: The BAN score is associated with a distinctive early cardiometabolic risk, particularly elevated SBP, widened PP, and early glycemic alterations. Further research should define the BAN score’s mechanisms and preventive utility.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/healthcare13182384
- https://www.mdpi.com/2227-9032/13/18/2384/pdf?version=1758546220
- OA Status
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- 56
- OpenAlex ID
- https://openalex.org/W4414406514
All OpenAlex metadata
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https://openalex.org/W4414406514Canonical identifier for this work in OpenAlex
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https://doi.org/10.3390/healthcare13182384Digital Object Identifier
- Title
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BAN Score and Distinct Early Cardiometabolic Risk Signatures in a Non-Diabetic Population: A Cross-Sectional AnalysisWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-09-22Full publication date if available
- Authors
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Yazeed Alshuweishi, Noha A. Alshuwayer, Lama Izziddeen, Arwa Abudawood, Dalal Alfayez, Ahmed BasudanList of authors in order
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https://doi.org/10.3390/healthcare13182384Publisher landing page
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https://www.mdpi.com/2227-9032/13/18/2384/pdf?version=1758546220Direct link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://www.mdpi.com/2227-9032/13/18/2384/pdf?version=1758546220Direct OA link when available
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0Total citation count in OpenAlex
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| abstract_inverted_index.ROC | 64, 208 |
| abstract_inverted_index.SBP | 164 |
| abstract_inverted_index.The | 1, 225 |
| abstract_inverted_index.age | 83 |
| abstract_inverted_index.and | 9, 33, 53, 56, 66, 75, 98, 125, 146, 178, 219, 241, 253 |
| abstract_inverted_index.but | 12 |
| abstract_inverted_index.for | 70, 214 |
| abstract_inverted_index.had | 80 |
| abstract_inverted_index.its | 13 |
| abstract_inverted_index.the | 27, 50, 135, 191, 249 |
| abstract_inverted_index.was | 160 |
| abstract_inverted_index.< | 114, 123, 131, 149 |
| abstract_inverted_index.(AUC | 216, 221 |
| abstract_inverted_index.(PP) | 118 |
| abstract_inverted_index.1.3. | 100 |
| abstract_inverted_index.SBP, | 144, 238 |
| abstract_inverted_index.This | 22, 40 |
| abstract_inverted_index.age, | 71 |
| abstract_inverted_index.each | 154 |
| abstract_inverted_index.risk | 198, 204 |
| abstract_inverted_index.role | 14 |
| abstract_inverted_index.sex, | 72 |
| abstract_inverted_index.use. | 77 |
| abstract_inverted_index.were | 59, 88, 188 |
| abstract_inverted_index.with | 30, 90, 105, 134, 162, 190, 230 |
| abstract_inverted_index.(BAN) | 3 |
| abstract_inverted_index.(SBP) | 109 |
| abstract_inverted_index.0.22, | 129 |
| abstract_inverted_index.0.23, | 112 |
| abstract_inverted_index.0.26, | 121 |
| abstract_inverted_index.0.66) | 218 |
| abstract_inverted_index.0.66, | 174 |
| abstract_inverted_index.1.01, | 167 |
| abstract_inverted_index.1.85, | 182 |
| abstract_inverted_index.72.8% | 87 |
| abstract_inverted_index.HbA1c | 126, 147, 179, 220 |
| abstract_inverted_index.blood | 107 |
| abstract_inverted_index.early | 17, 233, 242 |
| abstract_inverted_index.found | 189 |
| abstract_inverted_index.g/dL, | 97 |
| abstract_inverted_index.index | 193, 199, 205 |
| abstract_inverted_index.lipid | 34, 57 |
| abstract_inverted_index.pulse | 116 |
| abstract_inverted_index.risk, | 235 |
| abstract_inverted_index.score | 4, 29, 52, 159, 227 |
| abstract_inverted_index.study | 23, 43 |
| abstract_inverted_index.using | 61 |
| abstract_inverted_index.(AIP), | 196 |
| abstract_inverted_index.0.01), | 115 |
| abstract_inverted_index.0.01). | 132, 150 |
| abstract_inverted_index.0.65). | 223 |
| abstract_inverted_index.Higher | 101 |
| abstract_inverted_index.define | 248 |
| abstract_inverted_index.higher | 138, 163 |
| abstract_inverted_index.kg/m2, | 94 |
| abstract_inverted_index.lowest | 136 |
| abstract_inverted_index.median | 82, 91 |
| abstract_inverted_index.models | 68 |
| abstract_inverted_index.plasma | 195 |
| abstract_inverted_index.scores | 103 |
| abstract_inverted_index.should | 247 |
| abstract_inverted_index.showed | 141, 210 |
| abstract_inverted_index.years, | 86 |
| abstract_inverted_index.0.001), | 124 |
| abstract_inverted_index.0.006), | 177 |
| abstract_inverted_index.0.008). | 185 |
| abstract_inverted_index.0.037), | 170 |
| abstract_inverted_index.Further | 245 |
| abstract_inverted_index.ability | 213 |
| abstract_inverted_index.adults. | 38 |
| abstract_inverted_index.albumin | 95 |
| abstract_inverted_index.between | 49 |
| abstract_inverted_index.changes | 19 |
| abstract_inverted_index.female, | 89 |
| abstract_inverted_index.markers | 35 |
| abstract_inverted_index.models, | 153 |
| abstract_inverted_index.remains | 20 |
| abstract_inverted_index.smoking | 73 |
| abstract_inverted_index.status, | 8, 74 |
| abstract_inverted_index.widened | 239 |
| abstract_inverted_index.(CRI-I), | 201 |
| abstract_inverted_index.Castelli | 197, 203 |
| abstract_inverted_index.Compared | 133 |
| abstract_inverted_index.Methods: | 39 |
| abstract_inverted_index.Patients | 79 |
| abstract_inverted_index.Results: | 78 |
| abstract_inverted_index.adjusted | 69, 152 |
| abstract_inverted_index.analysis | 209 |
| abstract_inverted_index.elevated | 143, 237 |
| abstract_inverted_index.examined | 24, 60 |
| abstract_inverted_index.glycemic | 243 |
| abstract_inverted_index.included | 44 |
| abstract_inverted_index.increase | 156 |
| abstract_inverted_index.moderate | 211 |
| abstract_inverted_index.one-unit | 155 |
| abstract_inverted_index.pressure | 108, 117 |
| abstract_inverted_index.research | 246 |
| abstract_inverted_index.systemic | 10 |
| abstract_inverted_index.systolic | 106 |
| abstract_inverted_index.tertile, | 137 |
| abstract_inverted_index.tertiles | 140 |
| abstract_inverted_index.unclear. | 21 |
| abstract_inverted_index.utility. | 255 |
| abstract_inverted_index.(CRI-II). | 207 |
| abstract_inverted_index.analysis, | 65 |
| abstract_inverted_index.detecting | 16 |
| abstract_inverted_index.glycemic, | 32, 55 |
| abstract_inverted_index.score’s | 251 |
| abstract_inverted_index.subjects. | 47 |
| abstract_inverted_index.vascular, | 31, 54 |
| abstract_inverted_index.adiposity, | 6 |
| abstract_inverted_index.associated | 161, 229 |
| abstract_inverted_index.correlated | 104 |
| abstract_inverted_index.integrates | 5 |
| abstract_inverted_index.mechanisms | 252 |
| abstract_inverted_index.medication | 76 |
| abstract_inverted_index.parameters | 58 |
| abstract_inverted_index.preventive | 254 |
| abstract_inverted_index.regression | 67 |
| abstract_inverted_index.Background: | 0 |
| abstract_inverted_index.atherogenic | 192 |
| abstract_inverted_index.distinctive | 232 |
| abstract_inverted_index.nutritional | 7 |
| abstract_inverted_index.Associations | 48 |
| abstract_inverted_index.Conclusions: | 224 |
| abstract_inverted_index.Spearman’s | 62 |
| abstract_inverted_index.alterations. | 244 |
| abstract_inverted_index.associations | 25, 187 |
| abstract_inverted_index.correlation, | 63 |
| abstract_inverted_index.hypertension | 215 |
| abstract_inverted_index.non-diabetic | 37, 46 |
| abstract_inverted_index.particularly | 236 |
| abstract_inverted_index.inflammation, | 11 |
| abstract_inverted_index.retrospective | 41 |
| abstract_inverted_index.significantly | 142 |
| abstract_inverted_index.discriminative | 212 |
| abstract_inverted_index.cardiometabolic | 18, 234 |
| abstract_inverted_index.cross-sectional | 42 |
| abstract_inverted_index.BMI–albumin–neutrophil-to-lymphocyte | 2 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5014431006 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 6 |
| corresponding_institution_ids | https://openalex.org/I28022161 |
| citation_normalized_percentile.value | 0.55752489 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |