The researchers used anthropometric measurements collected at baseline and at participants’ first imaging assessment to assess how body shape and adiposity changed over time. Their multidimensional adiposity index combined body mass index, waist circumference, waist-to-hip ratio and waist-to-height ratio. The primary exposure was the annualized change in this composite index, assessing changes across several body-size measures rather than body mass index alone.

Cox proportional hazards models estimated the association between changes in adiposity and incident cardiovascular disease. In the primary adjusted model, each one-standard-deviation increase in annualized multidimensional adiposity change was associated with a 4.5% higher cardiovascular disease risk (hazard ratio, 1.045; 95% confidence interval, 1.002–1.090; P = 0.0407). The confidence interval was close to 1, reflecting a modest association and uncertainty around the estimated effect size.

Exploratory analyses separately assessed newly recorded low-overlap dysfunction. Higher cardiovascular disease risk estimates were observed among participants with newly recorded dysfunction only, with a hazard ratio of 1.306 (95% confidence interval, 1.014–1.682), and among participants with both anthropometric worsening and newly recorded dysfunction, with a hazard ratio of 1.550 (95% confidence interval, 1.051–2.285). These exploratory results do not show that dysfunction or adiposity change independently predicts cardiovascular disease, and the reported study conclusion focused on the association between greater multidimensional adiposity change and higher subsequent cardiovascular disease risk.

Overall, the findings suggest that tracking changes across multiple adiposity measures may provide information beyond body mass index alone in this UK Biobank population. The observational design leaves open the possibility that other factors contributed to the relationships, and the results do not show that participants with larger adiposity changes were certain to experience cardiovascular disease. The study’s stated conclusion was that greater long-term multidimensional adiposity change was associated with higher subsequent cardiovascular disease risk.

Subject of Research: Longitudinal multidimensional adiposity change and incident cardiovascular disease risk in UK Biobank participants

Article Title: Longitudinal multidimensional adiposity change and subsequent cardiovascular risk in UK Biobank

Article References: Kwon, R. J., & Lim, Y. (2026). Longitudinal multidimensional adiposity change and subsequent cardiovascular risk in UK Biobank. BMC Endocrine Disorders. https://doi.org/10.1186/s12902-026-02649-5

Image Credits: AI Generated

DOI: 10.1186/s12902-026-02649-5

Keywords: UK Biobank, adiposity, cardiovascular disease, body mass index, waist circumference, longitudinal study, incident CVD, anthropometry, risk assessment, Longitudinal, multidimensional, change

Aortic dissection occurs when a tear in the inner lining of the aorta allows blood to enter the wall and separate its layers. The resulting false lumen can reduce blood flow to organs such as the heart and brain or lead to rupture. The condition has an estimated incidence of three to four cases per 100,000 people per year in the United States and United Kingdom, so identifying enough events for precise estimates requires very large populations or long follow-up. The investigators therefore combined two unusually large prospective cohorts with a systematic review and meta-analysis of earlier cohort evidence rather than relying on one database alone. The study examined associations, not whether changes in body size or weight would prevent dissection.

The analysis used 496,255 eligible adults from the UK Biobank and 630,841 participants in the Japan-Specific Health Checkups Study, known as J-SHC. The UK cohort included people aged 37 to 73 at recruitment between 2006 and 2010 and provided a mean follow-up of 12.3 years. During 6,108,314 person-years of observation, 371 incident dissections were identified through linkage to hospital and mortality records in England, Scotland and Wales. The Japanese cohort comprised adults aged 40 to 74 who underwent health checkups between 2008 and 2015, with participants followed until death, age 75 or the end of follow-up on April 1, 2015. Its mean follow-up was four years, during which 105 deaths from aortic dissection occurred. Multivariable Cox proportional hazards models estimated hazard ratios and 95% confidence intervals, while a random-effects meta-analysis pooled adjusted estimates from cohort studies. The UK analysis assessed incident dissection and mortality, while the Japanese analysis assessed mortality from death certificates.

Measurements went beyond BMI in the UK Biobank, where the investigators also examined waist and hip circumference, waist-to-height ratio, waist-to-hip ratio, estimated fat mass and body fat percentage. In the fully adjusted analysis, the highest waist-circumference quintile had an aortic dissection hazard ratio of 1.82, or an 82% higher risk, compared with the lowest quintile. The corresponding ratios were 1.77 for hip circumference, 1.88 for waist-to-height ratio and 1.36 for fat mass. By contrast, waist-to-hip ratio and body fat percentage had no clear statistically significant association, with hazard ratios of 1.28 and 1.09, respectively. In continuous analyses, each 5 kg/m² increase in BMI was associated with a 16% higher risk, each 10 cm increase in waist circumference with a 15% higher risk, and each 0.1 increase in waist-to-height ratio with a 23% higher risk. The main UK model adjusted for age, sex, ethnicity, height, education, deprivation, alcohol, smoking, physical activity, fruit and vegetable intake and connective tissue disease.

The Japanese cohort produced directionally similar results for mortality. Compared with the normal-weight reference group, a BMI of at least 30 kg/m² was associated with a hazard ratio of 2.36 for death from aortic dissection. The highest waist-circumference and waist-to-height groups had hazard ratios of 2.26 and 2.61, respectively, compared with the lowest groups. Per specified increment, a 5 kg/m² higher BMI corresponded to 30% higher mortality risk, a 10 cm larger waist to 35% higher risk, and a 0.1-unit higher waist-to-height ratio to 54% higher risk. These estimates had wider confidence intervals than those from the longer UK follow-up. The Japanese models adjusted for age, sex, region, smoking and alcohol use, but information on education, deprivation, physical activity, diet and connective tissue disease was unavailable. As in the UK analysis, adjustment for hypertension or diastolic blood pressure reduced the estimated associations, suggesting that elevated blood pressure may account for part, but not necessarily all, of the relationship.

The meta-analysis of BMI included 2,007 cases among 4,962,288 participants from five cohorts in the United Kingdom and Japan. A 5 kg/m² increment in BMI was associated with a summary relative risk of 1.09, with a 95% confidence interval of 1.00 to 1.20 and moderate statistical heterogeneity indicated by an I² of 43%. Comparing the highest with the lowest BMI categories gave a relative risk of 1.47, with no statistical heterogeneity detected across the five studies. A dose-response model suggested that the increase became steeper at higher BMI levels: relative risks were 27% higher at a BMI of 35 and 59% higher at 40 compared with a BMI of 20. The model indicated evidence of nonlinearity, and the investigators reported that the association appeared more pronounced in men than in women. Only two studies contributed to the waist analyses, covering 476 cases and 1,127,096 participants. Per 10 cm increase in waist circumference, the summary relative risk was 1.21; per 0.1-unit increase in waist-to-height ratio, it was 1.32. Because the waist estimates came from just two studies, their apparent consistency requires confirmation in more populations.

Several mechanisms could connect excess adiposity with aortic dissection, but the observational design cannot establish which mechanism is responsible or whether adiposity itself causes the condition. Adiposity is closely linked with hypertension, an established risk factor for dissection, and the attenuation seen after adjustment for hypertension or blood pressure is consistent with blood pressure mediating part of the association. Obesity is also associated with oxidative stress, inflammation, altered coagulation, insulin resistance and unfavorable lipid profiles. The particularly strong associations for waist circumference and waist-to-height ratio may indicate that the location of fat is more informative than its total amount. Visceral and perivascular adipose tissues surround the aorta and can enter inflammatory states, promoting endothelial dysfunction, increased matrix metalloproteinase activity, extracellular degradation and weakening of the aortic wall. Experimental mouse studies reviewed by the authors found that obesity-related inflammation around the aorta could promote aneurysm development, but those animal findings do not establish a clinical benefit in humans. The analysis also found that further adjustment for diabetes strengthened some associations, consistent with diabetes being inversely associated with dissection in earlier evidence.

Subgroup analyses suggested that associations may be stronger in men than in women and, in the UK cohort, potentially stronger among younger than older adults. The waist-related patterns were also more pronounced among men in the Japanese study. The formal interaction findings were not uniformly significant, and the results do not establish that adiposity has different biological effects in men and women. The sex-stratified findings were broadly consistent with the meta-analysis, where associations appeared stronger in studies of men. The researchers also examined reverse causation and confounding by illness at baseline. Excluding the first three years of follow-up in the UK cohort, removing participants with prevalent cardiovascular disease, respiratory disease or cancer, or applying both exclusions generally left the results similar or slightly stronger. Sensitivity analyses that restricted the Japanese cohort to people without previous ischemic heart disease also produced similar patterns. The investigators assessed the proportional-hazards assumption and reported no evidence of nonlinearity between the adiposity measures and dissection risk in the UK analysis.

Important limitations constrain what can be concluded. Both analyses were observational, so residual confounding and measurement error remain possible, and adjustment for blood pressure may also obscure part of an underlying pathway. The J-SHC analysis had relatively crude information on confounders and only four years of follow-up, while both cohorts were not fully representative of the general population. Aortic dissection cases were uncommon, especially in the Japanese cohort, limiting precision. Generalizability across regions and ethnic groups also requires larger studies. The meta-analysis was comprehensive but included few studies, was not preregistered, and could not resolve uncertainty for waist measures beyond the two available cohorts. Using World Cancer Research Fund criteria, the investigators rated the evidence for a causal relationship between higher adiposity and aortic dissection as “limited-suggestive.” The results support excess weight, particularly abdominal adiposity, as a possible risk marker and potential contributor to aortic dissection, but they do not show that weight loss prevents the condition.

The overall pattern was consistent across two populations with different characteristics, including different levels of smoking and body size. In the UK Biobank, the fully adjusted estimates suggested higher dissection risk at the upper end of BMI and among people with larger waist measurements. In the J-SHC cohort, the same general pattern appeared for mortality, although confidence intervals were wider. The meta-analysis provided the strongest pooled evidence for BMI, with a modest increase in relative risk per 5 kg/m² and a steeper modeled difference at higher BMI values. Waist circumference and waist-to-height ratio had larger summary associations, but those estimates came from only two cohorts and require independent replication. The findings add evidence to a limited literature on an uncommon and serious condition and identify general and abdominal adiposity as possible markers of susceptibility. Further large-scale cohort studies with more diverse populations, longer follow-up and more detailed adjustment for blood pressure and other potential pathways are needed to clarify the size of the association and whether it differs by age, sex and geographic context.

Subject of Research: Associations of general and abdominal adiposity with aortic dissection incidence and mortality in prospective cohorts and a cohort meta-analysis

Article Title: Adiposity and the risk of aortic dissection incidence and mortality: results from the UK Biobank, the J-SHC study and a meta-analysis of cohort studies

Article References: Dillman, A., Otaki, Y., Sanchez-Perez, M., Irfan Khan, M. Y., Hibino, M., Konta, T., Yamagata, K., Fujimoto, S., Tsuruya, K., Narita, I., Kasahara, M., Shibagaki, Y., Iseki, K., Moriyama, T., Kondo, M., Asahi, K., Watanabe, T., Watanabe, T., Watanabe, M., & Aune, D. (2026). Adiposity and the risk of aortic dissection incidence and mortality: results from the UK Biobank, the J-SHC study and a meta-analysis of cohort studies. European Journal of Epidemiology. https://doi.org/10.1007/s10654-026-01456-5

Image Credits: AI Generated

DOI: 10.1007/s10654-026-01456-5

Keywords: aortic dissection, adiposity, body mass index, waist circumference, waist-to-height ratio, UK Biobank, Japan health checkups, cohort study, meta-analysis, cardiovascular risk, risk, aortic

Researchers initially screened 69,152 adults who had undergone at least two routine health examinations between 2014 and 2025. Eligibility required a baseline estimated glomerular filtration rate (eGFR) of at least 60 mL/min/1.73 m² and at least two follow-up examinations separated by intervals of three months or more. People with baseline eGFR below 60, evidence of acute infection, specified kidney-related diagnoses or a follow-up interval shorter than three months were excluded, leaving 48,304 participants. CKD was defined as two consecutive eGFR measurements below 60 mL/min/1.73 m², at least three months apart.

The investigators calculated 12 indices from anthropometric, glucose and lipid measurements: TyG, triglyceride-to-high-density lipoprotein cholesterol ratio, metabolic score for insulin resistance (METS-IR), TyG-BMI, TyG-WC, TyG combined with waist-to-height ratio, metabolic score for visceral fat, lipid accumulation product, Chinese visceral adiposity index, atherogenic index of plasma, cholesterol–high-density lipoprotein–glucose index (CHG) and remnant cholesterol. Their pairwise Spearman correlations ranged from 0.36 to 1.00, indicating substantial overlap among the measures, so the findings do not establish them as independent biomarkers.

Over a median follow-up of 4.74 years, 1,092 participants, or 2.26% of the cohort, developed CKD, corresponding to 4.56 cases per 1,000 person-years. In fully adjusted Cox models, every index showed a graded association with incident CKD across quartiles, with all tests for trend below 0.001. Comparing the highest with the lowest quartile, the adjusted hazard ratios were 2.48 (95% confidence interval 1.89–3.26) for TyG-WC, 2.41 (1.89–3.08) for METS-IR and 2.39 (1.79–3.18) for the Chinese visceral adiposity index. The TyG-WC association was consistent across prespecified subgroups, with no significant interaction tests.

Restricted cubic spline analyses indicated that the relationship between TyG-WC and incident CKD was nonlinear, with an inflection point at 811.58. Below this value, each standard-deviation increase in TyG-WC was associated with a higher CKD hazard (HR 1.71, 95% CI 1.47–1.98); above it, the association remained statistically significant but was attenuated (HR 1.10, 95% CI 1.07–1.13). The investigators described 811.58 as a statistical threshold rather than a validated biological cutoff, and noted that reverse causation cannot be excluded.

Among participants who developed CKD, 54 experienced rapid kidney function decline and 17 reached a clinical surrogate endpoint during a median 2.8 years of follow-up. Rapid decline was defined as an annual eGFR decrease of at least 5 mL/min/1.73 m², while surrogate endpoints comprised a 40% eGFR decline or a doubling of serum creatinine from the value recorded at CKD diagnosis. CHG was associated with rapid decline (odds ratio 1.56 per standard-deviation increase, 95% CI 1.23–1.96), whereas TyG-BMI was associated with surrogate endpoints (HR 2.55, 95% CI 1.38–4.71).

TyG-WC also had the highest measured discrimination for CKD at one year, with a time-dependent area under the curve of 0.817 (95% CI 0.776–0.851), although differences among the 12 indices narrowed over later follow-up. Adding TyG-WC to a baseline model improved three-year risk reclassification, with continuous net reclassification improvement of 0.192 (95% CI 0.072–0.318; p=0.012), while the integrated discrimination improvement was small at 0.001. Decision-curve analyses suggested potential clinical utility, and bootstrap internal validation produced similar optimism-corrected estimates.

Seven sensitivity analyses broadly supported the primary results. The TyG-WC association remained after excluding intervals longer than two years between eGFR measurements, applying a stricter CKD definition, excluding medicated participants, adding further covariates and excluding participants with a BMI of at least 28 kg/m², although some estimates weakened after the BMI restriction. An exploratory mediation analysis estimated that absolute monocyte count accounted for 4.76% of the TyG-WC association with CKD (95% CI 3.5–7.8%); the observational analysis cannot establish a causal mediation pathway.

Important limitations include the single-center, health-examination-based population, which may limit generalizability, and reliance on creatinine-based eGFR without systematic cystatin C or urinary albumin-to-creatinine measurements; urinary albumin data were unavailable for more than 99% of participants. The small number of progression events limited statistical power and covariate adjustment, mortality data were unavailable for competing-risk analyses, and progression was assessed through rapid eGFR decline and surrogate endpoints rather than detailed CKD stages. The observational design also leaves possible bidirectional relationships between metabolic measures and kidney function unresolved.

Subject of Research: Associations between surrogate insulin resistance indices and CKD incidence and progression in a Chinese health-examination cohort

Article Title: Stage-specific associations of nutrition-related surrogate insulin resistance indices across the chronic kidney disease continuum: evidence from a Chinese cohort

Article References: Fang, S., Li, Y., He, Y., Jiang, J., Zhu, Y., Chen, H., & Leng, S. (2026). Stage-specific associations of nutrition-related surrogate insulin resistance indices across the chronic kidney disease continuum: evidence from a Chinese cohort. Frontiers in Nutrition, 13, Article 1943087. https://doi.org/10.3389/fnut.2026.1943087

Image Credits: AI Generated

DOI: 10.3389/fnut.2026.1943087

Keywords: chronic kidney disease, insulin resistance, surrogate indices, waist circumference, triglyceride-glucose index, renal progression, retrospective cohort, risk prediction, Chinese health cohort, Stage-specific, associations, nutrition-related

Researchers searched PubMed/MEDLINE, Scopus, Web of Science Core Collection and Embase through 31 July 2026, then screened records and assessed full texts. Of 2,696 database records identified, 629 duplicates were removed and 2,067 records underwent title and abstract screening. Sixty-six reports were assessed in full text, 54 were excluded, and three additional candidates were removed because of overlapping cohorts or insufficient independently verifiable comparative data.

Nine studies, published from 2007 to 2024, were retained for qualitative synthesis. The included populations came from Turkey, Seychelles, Iran, Finland, China, Ethiopia and Pakistan. Sample sizes ranged from 314 adults with type 2 diabetes in Ethiopia to 18,414 adults in a nationwide Iranian survey.

The frameworks compared included World Health Organization criteria, the National Cholesterol Education Program Adult Treatment Panel III, also called NCEP-ATP III, the International Diabetes Federation, the American Heart Association/National Heart, Lung, and Blood Institute, the Joint Interim Statement, the European Group for the Study of Insulin Resistance, American Association of Clinical Endocrinology criteria, and harmonized or region-specific modifications. Because populations, settings, diagnostic structures and component thresholds differed substantially, the investigators used descriptive synthesis rather than pooling prevalence into a single meta-analysis. The definitions differed not only in their numerical cutoffs but also in their architecture.

WHO and EGIR explicitly incorporated insulin resistance, while NCEP-ATP III, IDF, AHA/NHLBI and JIS relied more heavily on combinations of routinely measured abnormalities such as central obesity, raised triglycerides, reduced high-density lipoprotein cholesterol, high blood pressure and abnormal glucose regulation. Some frameworks required two abnormalities and others three; classical IDF criteria made central obesity mandatory, whereas several component-based definitions treated waist circumference as one feature among several. The number of abnormalities, the components given special weight and the treatment of insulin resistance therefore helped determine which people met the definition, even when the same measurements were used.

Prevalence differences were substantial even when the population remained unchanged. In the Finnish study, estimates ranged from 17.7% under WHO criteria to 43.0% under JIS, a difference of 25.3 percentage points. The nationwide Iranian survey produced estimates of 38.3% with NCEP-ATP III, 43.5% with international IDF, 40.9% with AHA/NHLBI and 47.6% with JIS.

Regional IDF criteria yielded 32.0%, compared with 43.5% under international IDF, while regional JIS produced 40.8% rather than 47.6%. In the rural Chinese population, estimates for men ranged from 11.5% to 39.7%, while estimates for women ranged from 15.7% to 54.2% across the frameworks evaluated. In the Ethiopian clinical population, prevalence ranged from 31.2% under WHO criteria to 70.1% under NCEP-ATP III.

Concordance statistics showed a similar dependence on diagnostic structure. The highest reported agreement in the evidence base was between IDF and JIS criteria in Finland, with Cohen’s κ of 0.97. Other close pairings included modified NCEP-ATP III with IDF in Pakistan, with κ of 0.960, and AHA with NCEP-ATP III in an Iranian cohort, with κ of 0.909.

Agreement was generally weaker when an insulin-resistance-centered framework was compared with a component-based one. In the Turkish population, κ values ranged from 0.77 to 0.84 among NCEP, AACE and IDF comparisons but from 0.32 to 0.37 when those frameworks were compared with WHO and EGIR. These values measure agreement between classifications, not the clinical superiority of either system, because the review identified no biological gold standard for metabolic syndrome.

High agreement between two definitions therefore cannot by itself establish which one is better at predicting clinical outcomes. Central obesity and waist circumference were the components most consistently associated with disagreement. In Seychelles, the adiposity component was present in 35.2% of participants under ATP III, 61.5% under WHO and 55.8% under IDF, with only 48% meeting the criterion under all three.

The clearest threshold effects appeared in Iran. In the Tabari cohort, prevalence declined from 44.6% with international IDF criteria to 30.8% with Iranian-specific criteria, an absolute difference of 13.8 percentage points. In the nationwide survey, the corresponding decline was from 43.5% to 32.0%, or 11.5 percentage points.

Other components also shifted in prominence: elevated blood pressure was most common among Finnish men, central obesity among Finnish women, and different lipid and waist components emerged most often under different criteria in the Iranian Shiraz cohort. These were classification differences, not evidence that the underlying biology of the population changed. Findings for age and sex were descriptive rather than directly comparable across studies.

In the Finnish and Iranian populations, older age groups generally had higher measured prevalence, but the studies used inconsistent age categories and reporting procedures. Sex-specific estimates were available for rural China, where the range across definitions was 28.2 percentage points for men and 38.5 points for women. The evidence did not show all ethnic populations moving in a consistent direction under localized criteria; the directly documented ethnicity-specific effect involved waist-circumference thresholds.

Waist circumference is affected by ethnic group, sex, age and body-fat distribution, which can make a single threshold classify metabolic risk differently across populations. The review could evaluate classification changes, however, but it could not determine whether any definition better predicted future diabetes, cardiovascular disease or mortality. The evidence base has important limitations.

Only nine studies qualified, several lacked complete participant-level cross-classification tables, and some reported ethnicity-specific cutoffs inconsistently. The risk-of-bias review was not conducted independently and was described by the authors as provisional. Three studies were provisionally rated at moderate risk of bias and the remainder at low to low-moderate risk; none was judged high risk.

Some populations were clinical rather than general, including 314 Ethiopian adults with type 2 diabetes, which limits generalization. The researchers also reported incomplete database-level retrieval counts for all planned information sources. Reporting was incomplete in other ways: prevalence estimates and Cohen’s κ values were generally more available than full participant-level cross-tabulations, making the size and direction of individual reclassification difficult to quantify in some studies.

Accordingly, the synthesis is not a worldwide estimate of metabolic syndrome prevalence, but a structured comparison showing how the same individuals can be classified differently under competing frameworks. Overall, the review shows that metabolic syndrome classification is strongly definition-dependent, with waist-circumference thresholds a particularly important source of reclassification. The authors call for future studies to report exact thresholds, provide cross-classification data and compare competing definitions against clinically relevant outcomes.

The present evidence supports the narrower conclusion that diagnostic definitions materially shape who is counted as having metabolic syndrome, while further outcome-based research is needed to establish which definitions identify meaningfully different risk profiles.

Subject of Research: Systematic review of how metabolic syndrome diagnostic definitions affect adult prevalence, classification and concordance

Article Title: Changing diagnostic criteria and their impact on metabolic syndrome: a systematic review

Article References: Obeidat, A. A., Abu Al-Haijaa, D. M., Rahahleh, R. J., Ahmad, M. N., Jaradat, S., Nassar, N. A., Khamis, N. A., & Azzeh, F. S. (2026). Changing diagnostic criteria and their impact on metabolic syndrome: a systematic review. Frontiers in Endocrinology, 17, Article 1976380. https://doi.org/10.3389/fendo.2026.1976380

Image Credits: AI Generated

DOI: 10.3389/fendo.2026.1976380

Keywords: metabolic syndrome, diagnostic criteria, systematic review, prevalence, diagnostic concordance, waist circumference, ethnic thresholds, WHO criteria, IDF criteria, NCEP-ATP III, Changing, diagnostic

The study, published in PLOS One by Jaeho Lee, Kyoungsik Jeong, Youngseop Lee, and Younghwa Baek, drew its data from the Korean Medicine Daejeon Citizen Cohort, a community-based longitudinal study that follows adults in the city of Daejeon. Rather than treating each measurement as an isolated number, the team asked whether people move along recognizable paths as their bodies change. To do this, they applied k-means cluster analysis, an unsupervised algorithm that groups observations based on similarity. The clustering was performed on two-year changes in six body-shape measures: body mass index, waist circumference, hip circumference, waist-to-hip ratio, waist-to-height ratio, and total body weight. The method is simple in principle but powerful in effect, because it allows patterns of change to emerge from the data rather than being imposed by predetermined categories such as normal weight, overweight, or obese.

Three clusters emerged from the analysis, and their proportions are striking. The largest group, comprising 48 percent of participants, was labeled Stable, showing minimal change across all six measures over the two-year window. The second group, 31 percent of the cohort, fell into an Adiposity-Increasing pattern, characterized by growth in waist circumference and related markers of central fat accumulation. The remaining 21 percent formed an Adiposity-Decreasing cluster, in which waist and hip measurements moved downward together. The fact that nearly a third of a general adult population shifted toward increasing adiposity in just two years underscores how dynamic body shape truly is, and how quickly the distributions of fat that matter for metabolic risk can evolve in midlife.

Central adiposity, the accumulation of fat around the abdomen, has become a focal point of cardiometabolic research because it behaves differently from fat stored elsewhere. Visceral fat, which wraps around internal organs, is metabolically active in ways that promote insulin resistance, elevated blood pressure, and chronic low-grade inflammation. This is why waist circumference, waist-to-hip ratio, and waist-to-height ratio have repeatedly outperformed body mass index in predicting type 2 diabetes, cardiovascular disease, and mortality. Body mass index, being a simple ratio of weight to height squared, cannot distinguish between a person whose weight reflects dense skeletal muscle and one whose weight reflects abdominal fat, nor can it detect the gradual loss of muscle that accompanies aging. The Korean study was designed precisely to address these blind spots by monitoring shape and composition simultaneously.

The researchers went a step further by connecting the clusters to underlying body composition. At baseline, cluster membership was significantly associated with body fat mass, meaning that the amount of fat a person carried before the study began already helped predict which trajectory their body shape would follow. More importantly, the changes in body fat mass and skeletal muscle mass over the follow-up period showed strong associations with cluster assignment. This dual signal, fat gain and muscle change moving in tandem with shape change, supports a model in which adiposity-related trajectories are not merely about excess energy storage but about the shifting balance between fat and lean tissue. A person can gain waist circumference while losing muscle mass, a combination that is metabolically worse than fat gain alone, and the cluster approach makes such patterns visible in a way that single measures cannot.

The lifestyle findings are where the study acquires its most practical relevance. Using multinomial logistic regression, a statistical method for modeling outcomes with more than two categories, the researchers tested which baseline and follow-up variables predicted membership in each cluster. Two factors stood out for the Adiposity-Increasing group. The first was a clinically meaningful worsening of sleep quality, defined as an increase of at least 2.5 points on the Pittsburgh Sleep Quality Index, a validated questionnaire that scores sleep across seven dimensions including duration, latency, disturbances, and daytime dysfunction. The second was a reduction in physical activity as measured by the Global Physical Activity Questionnaire, an instrument that captures work-related, transport-related, and recreational activity. Both associations remained significant after accounting for other variables, pointing to sleep and movement as modifiable levers that may help steer people away from the harmful trajectory.

The link between sleep and adiposity has accumulated considerable mechanistic support in recent years. Short or fragmented sleep disrupts the hormonal regulation of appetite, raising ghrelin, the hormone that stimulates hunger, and lowering leptin, the hormone that signals satiety. Poor sleep also increases insulin resistance, alters food preferences toward energy-dense options, and may reduce the energy expended through spontaneous physical movement the following day. Sleep quality deterioration is often a gradual process tied to stress, irregular schedules, and aging, which makes it easy to overlook in clinical practice. The finding that even a moderate worsening on a standardized sleep index tracks with increasing central adiposity suggests that clinicians monitoring waist circumference should also be asking patients about how they are sleeping.

Physical activity operates through more obvious but equally important channels. Skeletal muscle is the body’s largest site of glucose disposal, and regular activity maintains muscle mass and insulin sensitivity while increasing total energy expenditure. When activity declines, muscle mass tends to erode, resting metabolic rate falls, and the same caloric intake produces a greater fat surplus. The co-occurrence of reduced activity and increasing adiposity in the same cluster therefore reflects a coherent physiological story: less muscle-stimulating movement, more fat accumulation, and a body shape that shifts outward at the waist. The Korean data reinforce the idea that interventions aimed at preventing central obesity should treat exercise not simply as a weight-loss tool but as a body-composition intervention that protects lean tissue.

The study has limitations worth keeping in view. It was conducted in a single Korean city, and body-shape trajectories may differ across populations with different diets, occupational structures, and genetic backgrounds. The observational design means that associations between sleep, activity, and cluster membership do not prove causation; it is possible, for example, that early metabolic changes drive both poor sleep and reduced activity rather than the reverse. Even so, the two-year follow-up, the use of multiple correlated shape measures, and the integration of body-composition data give the findings a depth that cross-sectional studies of a single measure cannot match. Because sleep and activity are modifiable, the results translate readily into intervention targets even under the more conservative causal reading.

The broader message is one that resonates with a growing movement in obesity science: replacing the single-number mentality with an integrative view of body shape, body composition, and lifestyle. Two people with identical body mass indexes may sit on entirely different health trajectories depending on where their fat is stored, how much muscle they carry, how well they sleep, and how much they move. The Korean cohort’s three clusters, stable, adiposity-increasing, and adiposity-decreasing, provide a template for identifying people early, before their changing waistlines harden into diabetes or cardiovascular disease. And they offer reassurance of a kind: the trajectory most tied to risk is also the one most tied to behaviors that individuals can, with support and attention, change. Body shape, in other words, is not destiny written in a BMI number, but a dynamic process shaped nightly by sleep and daily by movement.

Subject of Research: Longitudinal clustering of body shape change and its association with body composition and lifestyle factors in Korean adults

Article Title: Lifestyle factors and clustered patterns of body shape change in Korean adults: A longitudinal observational study

Article References: Lee, J., Jeong, K., Lee, Y., & Baek, Y. (2026). Lifestyle factors and clustered patterns of body shape change in Korean adults: A longitudinal observational study. PLOS One, 21(10), e0360853. https://doi.org/10.1371/journal.pone.0360853

Image Credits: AI Generated

DOI: 10.1371/journal.pone.0360853

Keywords: obesity, body shape, waist circumference, body mass index, sleep quality, physical activity, body composition, skeletal muscle mass, cluster analysis, Korean adults, longitudinal study, adiposity

The research team, led by Yiru Jiang and Shimin Su, who contributed equally to the work, drew on the 2011 to 2018 waves of the Chinese Longitudinal Healthy Longevity Survey, one of the largest longitudinal studies of the oldest old in the world. At baseline, the participants averaged 85.49 years of age, with a standard deviation of 10.98 years, meaning the sample captured a broad swath of late life, from the recently retired to centenarians. Rather than treating body mass index alone, the investigators combined it with waist circumference, a direct marker of central fat accumulation, to sort participants into distinct body shape categories.

The central metric of the study is disability-free life expectancy, the average number of remaining years a person at a given age can expect to live without disability in activities of daily living, such as eating, dressing, bathing, toileting, transferring, and continence. To estimate this quantity, the researchers used microsimulation, a computational technique that simulates thousands of hypothetical individual life courses through states of disability and death, based on the transition probabilities observed in the longitudinal data. This approach, implemented through stochastic population analysis for complex events and multistate life tables, produces confidence intervals that reflect both sampling uncertainty and the stochastic nature of life course simulation. Differences between groups were tested with Z tests, with statistical significance set at P less than 0.05.

The headline result emerges at age 65. Seniors in the appropriate body mass index group with normal waist circumference could expect 16.02 disability-free years, with a 95 percent confidence interval of 15.32 to 16.74. Every other body shape category fell short of that benchmark. Those with low body mass index had 14.25 disability-free years, a gap of roughly 1.8 years, with a confidence interval of 13.38 to 15.05. Those with appropriate body mass index but central obesity had 15.47 years, with a confidence interval of 14.72 to 16.37. Even those with high body mass index had 15.82 years, with a confidence interval of 14.27 to 17.20, still below the normal-weight, normal-waistline group.

The finding that low body mass index carries a penalty is striking because it runs against the intuition that thinner is always healthier. In later life, low body weight often reflects undernutrition, sarcopenia, or the early stages of chronic disease, conditions that erode the physical reserves needed to stay independent. The result also challenges the assumption that a normal body mass index guarantees metabolic health. Participants whose weight was appropriate but whose waist circumference signaled central obesity lost about half a year of disability-free life compared with the reference group, a reminder that where fat sits matters as much as how much of it there is. Visceral fat wrapped around the abdominal organs is metabolically active tissue, linked to insulin resistance, inflammation, and vascular damage, even when the scale reads normal.

Subgroup analyses added layers of nuance. Among participants aged 73 to 95 years in the appropriate body mass index with central obesity category, men had significantly shorter disability-free life expectancy than women. This suggests that the metabolic burden of a protruding waistline weighs more heavily on the independence of older men, possibly through higher rates of cardiovascular and metabolic complications that translate directly into disability. The sex difference also intersects with a broader pattern in the data: although older women had longer overall life expectancy, they spent a smaller proportion of their remaining years disability-free, meaning women live longer but carry a heavier relative burden of disability.

Residence mattered too, in ways that highlight the social determinants of healthy aging. Among women aged 76 to 95 years in the low body mass index group, those living in urban areas had significantly shorter disability-free life expectancy than their rural counterparts. Urban older women with low body weight may face a compounded burden, in which nutritional vulnerability interacts with the hazards of urban environments, from reduced social support to less access to suitable food and healthcare, to accelerate the loss of independence. The urban-rural divide in China is substantial, and this result suggests that it reaches into the very body shapes that determine how seniors age.

The technical machinery behind these estimates deserves attention because it sets the study apart from simpler analyses. Microsimulation allows researchers to project life expectancy and disability-free life expectancy simultaneously, tracking each simulated individual through transitions between disability-free life, disabled life, and death, with transition probabilities estimated from the longitudinal survey. Because the method simulates many possible life courses, it yields confidence intervals that capture the uncertainty of the underlying data, and the Z tests then determine whether the differences between body shape categories are larger than chance would predict. This combination of stochastic simulation and formal hypothesis testing gives the findings a statistical rigor that single-snapshot studies cannot match.

For public health, the implications are concrete. Weight management strategies for older adults should consider both body mass index and fat distribution, rather than the scale alone. In later life, the goal is not simply to avoid obesity but to preserve muscle mass, maintain adequate nutrition, and prevent central fat accumulation, all of which protect the physical capacity that keeps people out of nursing homes and hospitals. The study also flags specific groups for targeted intervention: older men with central obesity, older women with low body weight, and urban older women with low body weight in particular, who may experience the greatest burden of disability.

As China’s population ages at one of the fastest rates in the world, the stakes of these findings extend far beyond the clinic. The number of disability-free years a society can expect from its seniors determines the demand for long-term care, the sustainability of pension systems, and the wellbeing of families who provide most of the informal care. This study suggests that the shape of the aging body, measured jointly by the scale and the tape, offers a window into how many of those years will be lived independently, and that a few years of disability-free life can be gained or lost depending on where fat accumulates and whether body weight stays within a healthy range.

Subject of Research: Geriatrics

Article Title: Differences in disability-free life expectancy among Chinese older adults by combined body mass index and waist circumference categories

Article References: Jiang, Y., Su, S., Su, W., Wang, Q., Dong, H., Xu, T., Wu, B., & Bi, Y. (2026). Differences in disability-free life expectancy among Chinese older adults by combined body mass index and waist circumference categories. BMC Geriatrics. https://doi.org/10.1186/s12877-026-08479-3

Image Credits: AI Generated

DOI: 10.1186/s12877-026-08479-3

Keywords: disability-free life expectancy, body mass index, waist circumference, healthy aging, obesity, older adults, China, microsimulation, geriatrics, CLHLS, Differences, disability-free

The study addressed a persistent gap in the evidence base for acupuncture-derived weight-loss therapies. Most previous trials of acupoint catgut embedding were short, involved small samples, or pooled patients of both sexes and varying obesity severity. Because obesity places enormous strain on health systems, driving hypertension, dyslipidaemia, coronary artery disease, stroke, and hormone-related cancers such as endometrial and breast malignancies, clinicians have been searching for adjunctive options that sit between lifestyle counselling and bariatric surgery. Existing pharmacological options, including glucagon-like peptide-1 receptor agonists, produce impressive short-term results but are expensive, access remains uneven, and weight regain after discontinuation is common. Surgery is generally reserved for severe obesity. The Chinese team therefore set out to characterise what repeated embedding sessions achieve in routine clinical practice rather than in the artificial conditions of a randomised trial.

The technique itself is conceptually simple but physiologically intricate. A sterile needle introduces a short segment of absorbable suture material, in this case polydioxanone rather than traditional catgut, into the subcutaneous tissue at points such as those along the abdomen and lower limbs that traditional medicine associates with the spleen and digestive function. The suture then remains in place for roughly two to four weeks, mechanically stimulating the tissue and, according to the mechanistic literature, modulating afferent nerve signalling, hypothalamic appetite regulation, and endocrine pathways involved in energy balance. Animal studies have suggested that embedding at acupoints can influence leptin signalling and insulin resistance, while imaging work in humans has shown changes in brain regions governing satiety. Because the stimulus persists long after the needle is withdrawn, embedding requires far fewer clinic visits than conventional acupuncture, which typically demands sessions several times per week.

In the retrospective analysis, the researchers identified women aged 18 to 60 with a body mass index of at least 30 kilograms per square metre who had completed a standardised course of embedding sessions between defined dates, with no more than a fortnight between consecutive treatments. The comparison group consisted of volunteers who underwent baseline measurements and then simply continued their usual routines, returning for repeat measurements at the same intervals. Crucially, the two groups were statistically indistinguishable at the outset: mean body mass index, body weight, waist circumference, age distribution, and the proportion of patients with obesity-related comorbidities all matched closely, which strengthens the argument that subsequent divergence reflects the intervention rather than baseline differences.

The results showed a clear dose-response pattern with respect to the number of sessions received. After the first embedding treatment, the treated group already weighed slightly less than controls, but the difference did not reach statistical significance. After the second session, the gap became significant, and it widened further after the third and fourth treatments. By the end of the observation period, women who had received four sessions had lost substantially more weight than untreated controls, and the magnitude of the difference scaled with the cumulative number of embeddings rather than plateauing after an initial response. Within the treated group, body mass index declined steadily from baseline through each successive measurement point, whereas the control group’s values remained essentially flat throughout.

Secondary outcomes reinforced the primary finding. Waist circumference, a proxy for visceral adiposity and a stronger predictor of cardiometabolic risk than overall weight, shrank progressively in the treated group and was significantly smaller than in controls by the later measurement points. Body weight followed the same trajectory. The researchers also reported that the treatment was well tolerated: the most common adverse events were localised bruising, soreness at the insertion site, and transient subcutaneous nodules where the suture material sat before being absorbed, all of which resolved without intervention. No serious adverse events were recorded across the treatment course, an important consideration for a procedure that patients might otherwise undergo repeatedly over months or years.

The authors interpret the cumulative pattern as evidence that the therapeutic effect of acupoint embedding builds with repeated stimulation rather than producing a one-off shift. This aligns with the traditional rationale that persistent stimulation of specific points gradually recalibrates autonomic and endocrine regulation of appetite and metabolism. It also aligns with mechanistic studies showing that embedded sutures provoke a localised, low-grade inflammatory and healing response that evolves over several weeks, potentially sustaining the afferent signalling that conventional needles deliver only transiently. If the effect is genuinely cumulative, the finding has practical implications: patients and practitioners should not judge the therapy after a single session, and treatment protocols may need to specify a minimum number of embeddings before efficacy can be fairly assessed.

Several caveats temper the enthusiasm. The study was retrospective and single-centre, meaning that patients who chose embedding may have differed from controls in motivation, diet, or physical activity in ways the available records could not capture. The control group was small, and although baseline matching was good, residual confounding cannot be excluded. The follow-up window captured the treatment course and a short period afterwards but did not address long-term weight maintenance, which is the central challenge of any obesity therapy. The authors themselves note that randomised controlled trials with blinded outcome assessment, longer follow-up, and standardised lifestyle advice are needed before embedding can be recommended as an evidence-based adjunct. They also emphasise that the procedure should be performed by trained practitioners under sterile conditions, given that it involves breaking the skin and leaving foreign material in place.

Nevertheless, the study adds to a growing international literature suggesting that acupoint embedding may occupy a useful niche in weight management. Meta-analyses of embedding trials have reported pooled effects on body weight and body mass index that exceed those of conventional manual acupuncture, plausibly because of the sustained stimulus. The technique is already widely used in China for obesity, simple obesity in adolescents, and related metabolic conditions, and it is gaining attention elsewhere as patients seek alternatives to pharmacotherapy. The cumulative dose-response observed here, if replicated prospectively, would give clinicians a rational framework for treatment scheduling and for counselling patients about realistic expectations.

For now, the message for patients is cautiously optimistic but measured. Acupoint catgut embedding appears safe in experienced hands and produced progressive, statistically meaningful reductions in body mass index and waist circumference across repeated sessions in this cohort. It is not a substitute for dietary and behavioural change, and its effects, while encouraging, were modest in absolute terms compared with modern anti-obesity medications or surgery. But for women with obesity who cannot access or tolerate drug therapy, or who want a low-burden adjunct that requires only a handful of clinic visits, the accumulating evidence suggests that the humble dissolvable thread may deserve a place in the therapeutic toolkit, provided that larger randomised trials confirm what this real-world cohort observed.

Subject of Research: Cumulative effects of acupoint catgut embedding on weight loss in obese women

Article Title: Cumulative weight reduction across repeated acupoint catgut embedding sessions in obese women: a retrospective cohort study

Article References: Ji, X., Xin, X., Li, D., Hou, L., & Ye, Y. (2026). Cumulative weight reduction across repeated acupoint catgut embedding sessions in obese women: a retrospective cohort study. Frontiers in Medicine, 13, Article 1945172. https://doi.org/10.3389/fmed.2026.1945172

Image Credits: AI Generated

DOI: 10.3389/fmed.2026.1945172

Keywords: acupoint catgut embedding, obesity, body mass index, weight loss, traditional Chinese medicine, polydioxanone suture, retrospective cohort study, waist circumference, acupuncture, metabolic health, adiposity, complementary therapy

The study, published in Frontiers in Public Health as a cross-sectional analysis, started from a database of 214,582 examination records and applied strict quality-control rules, sequentially excluding records with missing key measurements, missing medical history, participants younger than 18, physiologically implausible outliers, and duplicates. The final cohort had a mean age of 48.15 years, was 58.4 percent male, and showed a hypertension prevalence of 20.4 percent, defined according to the Chinese Guidelines for the Management of Hypertension (2024 Revision) as blood pressure at or above 140/90 mmHg, a self-reported diagnosis, or current antihypertensive medication use. Blood pressure was measured with calibrated electronic devices after a five-minute rest, with two readings averaged and a third taken when the first two differed by more than 5 mmHg.

To make the five indices directly comparable, the researchers converted each to a Z-score and used multivariable logistic and linear regression, adjusting for sex, age, ethnicity, smoking, family history of hypertension, diabetes, coronary heart disease, and serum uric acid. The results were striking. Each one-standard-deviation increase in WC or BMI was associated with a 61 percent higher odds of hypertension (OR 1.61, 95 percent CI 1.58–1.64), WHtR with 60 percent (OR 1.60, 1.57–1.63), and BRI with 56 percent (OR 1.56, 1.54–1.59). ABSI, the mathematically most elaborate index, managed only a 9 percent increase (OR 1.09, 1.07–1.11). In linear terms, a standard-deviation rise in WHtR pushed systolic blood pressure up by 3.95 mmHg and diastolic by 2.28 mmHg, while ABSI moved systolic pressure by just 0.61 mmHg.

Discriminatory power told a similar story. Using the area under the receiver operating characteristic curve (AUC), WHtR and BRI tied for the top spot at an identical 0.676, followed by WC at 0.653, BMI at 0.627, and ABSI at the bottom with 0.612. The DeLong test confirmed that WHtR significantly outperformed WC, BMI, and ABSI (all P < 0.001), while its difference from BRI was exactly zero (P = 1.000). The authors are refreshingly candid about why: BRI is essentially a monotonic transformation of the waist-to-height construct, a function of WC divided by π times height, making the two indices mathematical near-equivalents rather than independent measures. Their identical performance reflects the same underlying central obesity signal, and the choice between them in practice comes down to computational simplicity (WHtR) or theoretical appeal (BRI).

The genuinely novel twist emerged when the team stratified the analysis by age. In young adults aged 18 to 35, discriminatory ability was strongest across the board, and raw waist circumference beat everything, reaching an AUC of 0.763, with WHtR and BRI close behind at 0.754. The odds ratios per standard deviation were also far larger in this group—2.19 for WC, 2.31 for WHtR, and 2.23 for BRI—compared with 1.73, 1.77, and 1.73 in the middle-aged group and 1.29, 1.31, and 1.29 in adults aged 60 and above. Formal interaction tests confirmed the pattern was statistically robust: all five indices showed significant negative interaction with age (all P < 0.001), with WHtR’s interaction coefficient at −0.0147 and BMI’s at −0.0075, demonstrating a broad age-attenuation effect.

The mechanistic explanation the authors offer is technically elegant. In young adults, height varies relatively little between individuals while waist circumference varies widely, driven by lifestyle and dietary habits; normalizing WC by height, as WHtR and BRI do, may therefore introduce noise rather than signal, slightly reducing discriminative ability. With advancing age, blood pressure becomes increasingly determined by multifactorial forces—vascular stiffening, comorbidities, renal changes—which dilute the standalone discriminatory value of any adiposity measure. The team also notes that the attenuation in older adults could partly reflect survivorship bias, since obese individuals with hypertension face higher mortality and are systematically less likely to survive to attend check-ups after 60, which would artificially weaken the observed relationship in that selected, disproportionately healthy sample.

ABSI provides the study’s cautionary tale about mathematical sophistication. Originally designed to characterize body shape more finely by adjusting waist circumference for height and BMI, the index consistently underperformed across every age stratum and every outcome. In the fully adjusted models, ABSI was even weakly inversely associated with diastolic blood pressure in women (β = −0.05, P = 0.320) and in older adults (β = −0.44). The finding aligns with prior meta-analyses and population studies in the United States and China, reinforcing the authors’ conclusion that greater mathematical complexity does not necessarily translate into superior clinical identification capability—a lesson that resonates well beyond anthropometry.

Stratified analyses by sex and ethnicity showed the core pattern was stable. Associations were slightly stronger in men than in women, and all five indices performed similarly in Han and minority ethnic groups. Quartile-based trend analyses revealed consistent positive dose-response relationships across progressively adjusted models, and a sensitivity analysis excluding the 1,463 participants on antihypertensive medication left the ranking unchanged, with WHtR and BRI still showing the highest AUC values. The authors also acknowledge an important limitation: roughly half the original records were excluded for missing data, and the excluded individuals were younger (mean age 35.6 years) and more predominantly male (71.5 percent) than the included cohort, meaning the complete-case analysis may have slightly overestimated true population-level AUCs and association strengths. Data on alcohol, dietary sodium, physical activity, and sleep were unavailable, leaving residual confounding possible.

For clinicians and public health planners, the practical message is concrete. In health check-up and primary care settings, WHtR or BRI can serve as the default preliminary screen across all ages, while raw waist circumference deserves priority in young adults, where its discriminatory power peaks. The indices should be treated as flagging tools, not diagnostic criteria—anyone flagged should undergo confirmatory blood pressure measurement and receive counseling on weight management, sodium reduction, and physical activity. The authors emphasize that these simple tape-measure metrics are not merely passive screening instruments but actionable targets, since interventions targeting adiposity-related risk can translate into measurable blood pressure benefits. As China’s hypertension burden remains formidable despite improving awareness and treatment rates, the idea that the optimal screening tool depends on the patient’s age is a deceptively simple insight that could reshape routine risk identification, though the authors caution that external validation in prospective, diverse cohorts is essential before the ranking can be considered universally applicable.

Subject of Research: Comparison of anthropometric adiposity indices for hypertension risk screening across age groups in Chinese adults

Article Title: A cross-sectional study on anthropometric indices and hypertension in Chinese adults: comparison of discriminatory power and age-stratified analysis

Article References: Lu, S., Chen, N., Li, Z., Zhang, Y., Wang, W., Li, G., Hao, J., Wang, R., Qi, Y., & Qin, Z. (2026). A cross-sectional study on anthropometric indices and hypertension in Chinese adults: comparison of discriminatory power and age-stratified analysis. Frontiers in Public Health, 14, Article 1933929. https://doi.org/10.3389/fpubh.2026.1933929

Image Credits: AI Generated

DOI: 10.3389/fpubh.2026.1933929

Keywords: hypertension, anthropometric indices, waist-to-height ratio, body roundness index, waist circumference, body mass index, ABSI, central obesity, age-stratified analysis, ROC curve, cross-sectional study, Chinese adults

The research, published in BMC Endocrine Disorders, enrolled 1,158 adults who underwent acanthosis nigricans screening at the hospital’s Endocrinology Clinic between 2010 and 2021. Rather than treating metabolic health as a simple diabetic-versus-nondiabetic binary, the team sorted every participant into one of five mutually exclusive stages spanning the full arc of metabolic deterioration. The five categories were Normal, Isolated Insulin Resistance, Hyperinsulinemia, Prediabetes with Insulin Resistance, and Diabetes with Insulin Resistance. This stratification allowed the investigators to ask a question that simpler study designs cannot answer: does the skin sign track with metabolic disease in general, or does it point to one particular physiological moment along the road from health to diabetes?

The answer was both surprising and clinically useful. Prevalence of acanthosis nigricans varied across the five stages in a distinctly non-monotonic pattern. It reached its highest point, 71.3 percent, in the Hyperinsulinemia stage, when fasting insulin levels are elevated but blood glucose remains within normal limits. The prevalence then fell to 51.7 percent among participants with prediabetes and insulin resistance and dropped further to 44.6 percent among those with outright diabetes and insulin resistance, a gradient that was statistically significant at P less than 0.001. In other words, the skin sign was most common not at the end of the metabolic road, when the disease is most advanced, but at a middle waypoint where the body is still successfully compensating for insulin resistance by secreting ever-larger amounts of the hormone.

The physiological logic behind this pattern begins at the cellular level. Insulin resistance means that target tissues, chiefly skeletal muscle, liver, and adipose tissue, respond poorly to insulin’s normal signaling. To maintain glucose homeostasis, pancreatic beta cells compensate by secreting more insulin, driving circulating insulin concentrations upward. Acanthosis nigricans is thought to arise as a byproduct of this compensatory flood. Insulin at high concentration spills over onto insulin-like growth factor 1 receptors, or IGF-1R, on keratinocytes and fibroblasts in the skin. Activation of these receptors triggers the phosphatidylinositol 3-kinase, or PI3K, and protein kinase B, or AKT, signaling cascades, which stimulate proliferation of epidermal cells and deposition of the velvety, papillomatous texture that defines the condition. The skin, in this framing, is a visible readout of how hard the pancreas is working to keep glucose under control.

Consistent with this mechanism, participants with the skin sign were, on average, younger than those without it and carried higher body mass index. They also had markedly higher fasting insulin and C-peptide levels, the latter a co-secreted fragment of proinsulin that serves as an independent index of beta-cell secretory activity. All of these differences were statistically robust at P less than 0.001. The combination of younger age, greater adiposity, and higher insulin output paints a coherent portrait: acanthosis nigricans tends to appear in people whose metabolic machinery is straining hardest, often years before laboratory tests of glucose would raise any alarm.

Of course, cross-sectional data are vulnerable to confounding, and the team addressed this concern with a carefully layered statistical strategy. Using multinomial logistic regression, the researchers examined the association between the skin sign and each metabolic stage, progressively adjusting for demographic and metabolic covariates. Even in the fully adjusted model, the Hyperinsulinemia stage retained by far the strongest link to acanthosis nigricans, with an odds ratio of 4.69 and a 95 percent confidence interval spanning 1.58 to 13.95. By contrast, the associations observed for the prediabetes and diabetes stages attenuated and lost statistical strength once full covariate adjustment was applied. The specificity of the signal survived scrutiny: this is a marker of compensatory hyperinsulinemia with preserved glycemia, not a generic badge of advanced metabolic disease.

Subgroup analyses probing whether the association varied by age, sex, or body mass index added further texture to the findings, and the investigators also asked a practical question that matters for any screening context: how much does seeing the skin actually help? Receiver operating characteristic analysis showed that adding acanthosis nigricans to existing information modestly but significantly improved discrimination for hyperinsulinemia, raising the area under the curve from 0.730 to 0.776, a difference significant at P less than 0.001. The improvement is not dramatic enough to turn the skin sign into a diagnostic test on its own, but it is meaningful as an adjunctive cue. A clinician who spots the velvety plaques during a routine examination gains measurable incremental information about a patient’s likelihood of silent insulin excess.

Perhaps the most mechanistically intriguing component of the study was an exploratory mediation analysis. The team asked whether measurable metabolic traits, specifically waist circumference, uric acid, and the liver enzyme alanine aminotransferase, might explain the statistical link between the skin sign and hyperinsulinemia. Together, these three factors accounted for a substantial proportion of the association. Waist circumference is the classic anthropometric proxy for visceral adiposity, the metabolically active fat depot most tightly coupled to insulin resistance. Uric acid has been repeatedly linked to hyperinsulinemia and metabolic syndrome, while elevated alanine aminotransferase reflects hepatic steatosis, the fatty infiltration of the liver that both drives and responds to insulin excess. That these mediators soak up much of the association suggests that acanthosis nigricans sits at the convergence of visceral obesity, fatty liver, and hyperuricemia, a cluster of interlocking abnormalities that all feed the same compensatory physiology.

The authors are candid about the limits of their design. This was a clinic-based cohort of adults attending an obesity and endocrinology service in Shanghai, so the participants carry a high baseline burden of adiposity and metabolic risk; the prevalence figures would very likely differ in a general population sample. The cross-sectional structure captures a single moment in time and cannot prove that hyperinsulinemia causes the skin changes, only that the two travel together in this population. The mediation analysis, by the authors’ own framing, is exploratory and does not establish causal pathways. Longitudinal follow-up would be needed to determine whether the appearance of acanthosis nigricans predicts progression from the hyperinsulinemic stage to prediabetes and diabetes, and whether treating the underlying insulin excess causes the plaques to fade.

Even with those caveats, the clinical takeaway is unusually actionable for a marker that costs nothing to detect. The hyperinsulinemic stage, the one most tightly bound to the skin sign, is precisely the window in which intervention has the greatest chance of preventing progression. Lifestyle change, weight reduction, and pharmacologic agents that lower insulin demand are all most effective before beta-cell function falters and glucose begins to climb. Yet this stage is also the one least likely to be caught by routine screening, because fasting glucose and even glycated hemoglobin, measured as HbA1c, remain normal while insulin surges unseen. The study therefore supports treating acanthosis nigricans as an adjunctive clinical sign, in the authors’ phrase, rather than a standalone screening tool, one that should prompt a clinician to order fasting insulin, C-peptide, an oral glucose tolerance test with insulin curves, and assessment of waist circumference and liver enzymes in high-risk individuals. A dark patch of skin that patients often hide or ignore may, on closer inspection, be the body’s earliest visible cry that its metabolic budget is being spent faster than it can be replenished, and recognizing it could buy years of prevention that blood tests alone would miss.

Subject of Research: Acanthosis nigricans as a cutaneous marker of compensatory hyperinsulinemia across metabolic stages

Article Title: Acanthosis nigricans as a cutaneous marker of compensatory hyperinsulinemia with preserved glycemia: a cross-sectional study

Article References: Mutailipu, K., Zha, X., Yin, J., Xin, J., Sun, H., Ren, T., Zhao, Y., Qu, S., & Bu, L. (2026). Acanthosis nigricans as a cutaneous marker of compensatory hyperinsulinemia with preserved glycemia: a cross-sectional study. BMC Endocrine Disorders. https://doi.org/10.1186/s12902-026-02630-2

Image Credits: AI Generated

DOI: 10.1186/s12902-026-02630-2

Keywords: acanthosis nigricans, hyperinsulinemia, insulin resistance, prediabetes, type 2 diabetes, metabolic syndrome, obesity, C-peptide, waist circumference, fatty liver, uric acid, cross-sectional study

The research team, led by investigators at Tehran University of Medical Sciences, turned to the 2021 Iran STEPS survey, a nationally representative assessment conducted under the World Health Organization’s STEPwise approach to noncommunicable disease risk factor surveillance. That framework, used in dozens of countries, gathers standardized information on behavioral and physical risk factors along with biochemical measurements, making it one of the most valuable data sources for studying chronic disease in low- and middle-income settings. From the survey, the researchers analyzed records for 17,945 participants, giving them a sample large enough to test how well different adiposity measures performed across sexes, age groups, and urban versus rural populations.

The measures under scrutiny represent a family of so-called visceral adiposity indices. Unlike BMI, which lumps together muscle, bone, water, and fat into a single number, these indices attempt to capture the metabolically dangerous fat that accumulates around internal organs. The lipid accumulation product, or LAP, combines waist circumference with fasting triglyceride levels, reflecting the idea that a thick waist paired with fat-clogged blood signals overflowing energy stores spilling into ectopic deposits. The visceral adiposity index, or VAI, goes further, weaving together waist circumference, triglycerides, high-density lipoprotein cholesterol, and body mass index itself into a sex-specific formula designed to estimate visceral fat dysfunction. The waist-triglyceride index, or WTI, is a simpler cousin, pairing waist measurement directly with circulating triglycerides. All three can be computed from a tape measure and a standard blood panel — no CT scanner or dual X-ray absorptiometry required.

That accessibility is precisely what makes the results striking. Imaging techniques such as computed tomography and MRI remain the gold standards for quantifying visceral fat directly, and DEXA scans can map regional fat distribution with precision, but none of these are realistic tools for population screening in most of the world. The indices tested in this study require nothing more exotic than equipment already present in a basic clinic. If a tape measure and a routine lipid test can outperform BMI for flagging diabetes risk, the implications for primary care in resource-constrained settings could be substantial, particularly in regions like the Middle East and North Africa where diabetes prevalence has climbed steeply over recent decades.

To assess performance, the researchers employed two complementary statistical approaches. First, they used multivariable logistic regression to examine how strongly each index was associated with prevalent diabetes — that is, diabetes identified at the time of the survey — while accounting for other variables. All of the indices, including BMI itself, showed significant associations with the disease, confirming that every measure of adiposity carries some signal. But association alone does not settle the question of usefulness. A screening tool must also discriminate: it must reliably separate people who have the condition from those who do not. For that, the team turned to receiver operating characteristic analysis, plotting true-positive rates against false-positive rates across the full range of each index’s values and summarizing the trade-off with the area under the curve, or AUC.

The results were revealing. When the researchers added LAP or WTI to a base predictive model, discriminatory ability rose significantly, reaching an AUC of 0.816 for LAP and 0.815 for WTI, with confidence intervals spanning roughly 0.804 to 0.827. BMI, by contrast, failed to deliver the same boost. Indeed, every anthropometric index examined outperformed the base model, but the lipid-waist hybrids stood out as the clear leaders. The team also compared the indices using Somers’ D, a rank-based measure of association, and conducted stratified analyses by sex, age group, and place of residence to check whether the advantage held across different segments of the population. The consistency of the signal across these strata strengthens the case that the finding is not an artifact of one particular subgroup.

Why should waist-and-blood measures beat BMI at detecting diabetes? The answer lies in the biology of fat storage. Subcutaneous fat, the layer beneath the skin, is relatively inert compared with visceral fat packed around the liver, pancreas, and intestines. Visceral adiposity drains directly into the portal circulation, flooding the liver with free fatty acids and promoting insulin resistance — the fundamental defect underlying type 2 diabetes. Triglyceride levels serve as a convenient biochemical echo of this process, rising as fat handling becomes dysregulated. An index that combines a central waist measurement with elevated triglycerides therefore captures two independent markers of the same underlying pathology: fat in the wrong place and fat metabolism gone awry. BMI, meanwhile, can be elevated in muscular individuals with low metabolic risk and deceptively normal in people with thin-outside-fat-inside phenotypes, a pattern increasingly recognized in South Asian and Middle Eastern populations.

This last point carries particular relevance for Iran and its neighbors. Research over the past two decades has shown that people in many Asian and Middle Eastern populations develop metabolic complications at lower BMIs than Europeans, prompting bodies such as the International Diabetes Federation to recommend lower waist circumference thresholds for these groups. A screening strategy built on BMI alone may therefore systematically underestimate risk in exactly the populations where diabetes is expanding fastest. The Iran STEPS analysis, conducted in a country where diabetes is a major contributor to morbidity and mortality, offers a direct test of whether alternative indices could close that gap — and the answer appears to be yes, at least for identifying prevalent disease.

The authors are careful about the limits of their work. Because the study is cross-sectional, it captures a snapshot of who had diabetes at the time of the survey rather than tracking who develops it over time. Discriminating prevalent cases is not the same as predicting incident disease, and the researchers explicitly call for prospective studies to evaluate whether LAP and WTI can forecast future diabetes and not merely flag existing cases. They also note that the indices were tested within a single national survey, and while the STEPS methodology supports comparability, validation in other populations and health systems remains an open task. The study was approved by the research ethics committee of Tehran University of Medical Sciences and conducted with written informed consent from all participants, in line with the Declaration of Helsinki.

Even with those caveats, the study lands at a moment when health systems worldwide are searching for low-cost ways to target prevention. Diabetes screening at scale cannot depend on imaging or specialized testing, and the global burden of the disease continues to grow fastest in developing regions where resources are thinnest. If two numbers — a waist measurement and a triglyceride value — can meaningfully sharpen the identification of people living with diabetes beyond what BMI achieves, clinicians and public health planners gain a practical upgrade to their toolkit at essentially no added cost. The message from this large Iranian dataset is not that BMI should be discarded, but that it should no longer stand alone. The fat that endangers metabolic health hides in the abdomen and in the blood, and the simplest measures of both may finally be ready for prime time.

Subject of Research: Comparison of visceral adiposity indices with body mass index for detecting prevalent diabetes in the Iranian population

Article Title: Comparison of novel visceral adiposity indices with body mass index for identification of prevalent diabetes: findings from the 2021 Iran STEPS survey

Article References: ErfanFazel, A., Semnani, K., Mohseni, S., Khosravi, S., Pejman Sani, M., Tabatabaei-Malazy, O., & Qorbani, M. (2026). Comparison of novel visceral adiposity indices with body mass index for identification of prevalent diabetes: findings from the 2021 Iran STEPS survey. BMC Endocrine Disorders. https://doi.org/10.1186/s12902-026-02533-2

Image Credits: AI Generated

DOI: 10.1186/s12902-026-02533-2

Keywords: diabetes, body mass index, visceral adiposity, lipid accumulation product, waist-triglyceride index, waist circumference, obesity, Iran STEPS survey, insulin resistance, screening, triglycerides, epidemiology