The prospective cohort study began in 1993, when 1,000 randomly selected middle-aged Swedish men took part in a nurse-led health examination. Investigators recorded body measurements, blood pressure readings and fasting blood test results. They subsequently linked the cohort to the national Myocardial Infarction Register, Swedeheart, to identify first-time myocardial infarction and to the Swedish Cause of Death Register for mortality data. Data were collected for 959 men over the 28-year follow-up period.

Researchers examined six anthropometric indicators: body mass index, waist circumference, waist-to-height ratio, waist-to-hip ratio, sagittal abdominal diameter, and sagittal abdominal diameter divided by height. They found significant correlations among the measurements, and all six were associated with cardiovascular risk factors, myocardial infarction and mortality. These initial associations did not translate into equally strong relationships after adjustment for traditional cardiovascular risk factors, when associations with cardiovascular endpoints diminished or disappeared for most measures.

The statistical analysis used Cox proportional hazards models and evaluated the z-scores of the six body measurements both before and after adjustment for covariates. Waist-to-height ratio was the indicator that retained the clearest reported relationships with the two outcomes. For myocardial infarction, its adjusted hazard ratio was 1.31, with a 95% confidence interval of 1.07–1.62. For all-cause mortality, the adjusted hazard ratio was 1.27, with a 95% confidence interval of 1.08–1.49. These estimates describe associations within the cohort and do not demonstrate that changes in body size cause either outcome.

Body mass index was expressed in kilograms per square metre, with the study background identifying a BMI of 25–30 as overweight and 30 or above as obesity. Although body mass index and the other five measures were correlated, their value as indicators of cardiovascular outcomes was not identical. Waist-to-height ratio emerged as more reliable in this population, while the authors cautioned that its comparative clinical significance was marginal and noted that there is currently no consensus on a preferred obesity indicator for cardiovascular risk prediction.

The findings therefore distinguish between the initial evidence and the adjusted results. Before accounting for traditional risk factors, every indicator was associated with myocardial infarction and mortality. After adjustment, the relationships for most indicators weakened or were no longer present, while waist-to-height ratio continued to be associated with both outcomes. The reported confidence intervals quantify uncertainty around the adjusted hazard ratios, and the study does not establish that waist-to-height ratio is superior in every population or for every clinical purpose.

The scope of the evidence is important. Participants were middle-aged Swedish men drawn from an occupational setting, and their examination took place at a single point in 1993. The analysis then followed the cohort for 28 years through national registers. Because the research population was specific, the results characterize associations in this group of Swedish automotive-industry male workers rather than establishing a universal relationship for all adults, women or other occupational and geographic populations.

Within those boundaries, the study offers a technically focused comparison of six ways of measuring body size against long-term cardiovascular and mortality outcomes. Its central result is not that waist-to-height ratio was definitively the “best” measure, but that it was the more reliable indicator after adjustment in this cohort, with modest differences between indicators. The authors concluded that waist-to-height ratio proved more reliable for myocardial infarction and mortality in this population while acknowledging the marginal clinical significance of the comparative differences.

Subject of Research: Associations of six body-size indicators with myocardial infarction and mortality in Swedish automotive-industry men

Article Title: Six anthropometric indicators and their associations with myocardial infarction and death in Swedish automotive industry male workers followed for 28 years

Article References: Joulha Ian, L., & Dimberg, L. (2026). Six anthropometric indicators and their associations with myocardial infarction and death in Swedish automotive industry male workers followed for 28 years. BMC Public Health, 26(1), Article 2759. https://doi.org/10.1186/s12889-026-29630-0

Image Credits: AI Generated

DOI: 10.1186/s12889-026-29630-0

Keywords: waist-to-height ratio, myocardial infarction, all-cause mortality, anthropometric indicators, body mass index, cardiovascular risk factors, prospective cohort, Swedish men, Swedeheart, anthropometric, indicators, associations

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

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 team recruited 123 adult volunteers between the ages of 30 and 60 and stratified them into three groups according to body mass index: 37 participants of normal weight, 44 who were overweight, and 42 living with obesity. Beyond the standard sociodemographic variables that often accompany obesity research, including age, sex, smoking status, exercise habits, and profession, the investigators took a battery of anthropometric measurements. These included body mass index itself, the waist-hip ratio, and the waist-to-height ratio, three metrics that together capture both general adiposity and the central fat distribution that is considered particularly hazardous for cardiometabolic health. Awareness was assessed with a validated obesity awareness scale, an instrument previously adapted and tested for reliability in Turkish populations.

The central result was a null finding with a twist. When the researchers correlated the overall obesity awareness scores with the anthropometric measurements, they found no statistically meaningful relationship. People with larger waists, higher waist-to-height ratios, or greater body mass were not systematically more, or less, aware of obesity as a health issue than their leaner counterparts. The anthropometric metrics did, however, correlate strongly with one another, which is expected given that they all index body composition and fat distribution. In other words, the measurements behaved as measurements should, but they simply did not track what participants knew or believed about obesity.

The twist emerged when the team examined the subscales of the awareness instrument. Within one awareness subscale, the overweight group scored significantly higher than the group with obesity, a difference that reached statistical significance at p = 0.005. This pattern is intriguing because it suggests that awareness is not a simple monotonic function of body size. One plausible interpretation, consistent with a broader literature on interoception and weight, is that people living with obesity may experience a degree of disengagement from weight-related health information, whether through normalization of their body size over time, through the psychological burden of internalized weight stigma, or through repeated exposure to messaging that fails to resonate. The authors are careful not to overinterpret a single subscale in a cross-sectional sample, but the directional difference is difficult to dismiss entirely.

To test whether the apparent null relationship between body size and awareness might be masking confounding, the researchers turned to multivariable regression analysis. After adjusting for baseline sociodemographic confounders, body mass index showed no independent association with overall obesity awareness whatsoever, with a p-value of 0.928. This is about as clean a null result as epidemiology produces. Whatever drives a person’s understanding of obesity, it is not, in this sample, the number on the scale or the ratio derived from it. The regression framework is important because it rules out the possibility that the raw correlation was obscured by age, sex, or other demographic factors that travel with both body size and health knowledge.

What did predict awareness were social and occupational circumstances. The presence of a family member with obesity was significantly associated with obesity awareness, at p = 0.025, and occupational status was an even stronger predictor, at p = 0.002. These two findings, taken together, sketch a picture in which awareness is a socially transmitted and structurally conditioned quantity. Living alongside a relative with obesity may provide direct, lived exposure to the condition, its management, and its consequences, effectively functioning as an informal education channel. Occupation, meanwhile, likely proxies a cluster of influences including educational attainment, health literacy, access to workplace wellness resources, physical demands of the job, and the socioeconomic conditions that shape both diet and opportunities for physical activity.

The study arrives at a moment when the scientific community is rethinking how obesity itself should be defined. A recent Lancet Diabetes and Endocrinology Commission has argued for a more clinically grounded definition of obesity that moves beyond body mass index alone, recognizing that BMI, while convenient, conflates fat mass with lean mass and says little about how adiposity affects organ function. The present findings add a psychological dimension to that debate. If awareness of obesity is disconnected from the anthropometric markers that clinicians rely on, then screening strategies that assume patients will recognize their own risk status may be built on sand. A person can carry substantial central adiposity, reflected in an elevated waist-to-height ratio, and still not perceive themselves as being at risk.

This disconnect between objective measurement and subjective awareness has been flagged in earlier work. Studies of healthcare workers have documented gaps between the prevalence of overweight in that population and the level of concern it generates, and research on adolescents has pointed to parental factors as significant correlates of obesity awareness in younger age groups. The interoception literature offers a mechanistic thread: systematic reviews and meta-analyses have examined whether the ability to perceive internal bodily signals relates to body mass, with mixed but suggestive results. If the perception of one’s own body is imperfect, then awareness of a slowly developing condition like obesity, which accumulates over years without acute symptoms, may be particularly prone to drift from reality.

The global context sharpens the stakes. The Global Burden of Disease Study 2021 analyzed 88 risk factors across 204 countries and territories, and pooled analyses of population-representative studies covering 222 million children, adolescents, and adults have documented relentless worldwide increases in overweight and obesity from 1990 to 2022. Against that backdrop, awareness is often treated as the first link in the behavior-change chain: people must recognize a problem before they seek to solve it. If that first link is forged not by the tape measure but by family dinner tables and workplace environments, then interventions that rely solely on distributing anthropometric screening results may be insufficient. Public health messaging may need to be embedded in the social settings where awareness actually takes root.

As with all cross-sectional research, the study has limits that the authors acknowledge implicitly through their design choices. A sample of 123 volunteers cannot establish causation, and it remains possible that awareness influences behavior, which in turn influences body size, in feedback loops that a single time point cannot disentangle. The use of a Turkish-validated awareness scale means the findings are most directly applicable to the population studied, though the sociocultural mechanisms they point to are unlikely to be unique to any one country. Still, the core message is clear and actionable: in this sample, obesity awareness did not correlate with objective anthropometric measures, but it did travel with family history and occupational status. Understanding obesity, it seems, is learned at home and at work, not measured at the waist.

Subject of Research: The relationship between obesity awareness and anthropometric versus sociocultural factors in adults

Article Title: Is obesity awareness related to anthropometric measures or sociocultural factors?

Article References: Tikac, G., Altug, S. D., & Unal, A. (2026). Is obesity awareness related to anthropometric measures or sociocultural factors?. International Journal of Obesity. https://doi.org/10.1038/s41366-026-02238-5

Image Credits: AI Generated

DOI: 10.1038/s41366-026-02238-5

Keywords: obesity awareness, body mass index, waist-hip ratio, waist-to-height ratio, anthropometry, cross-sectional study, sociodemographic factors, occupational status, family history, public health, International Journal of Obesity, health literacy

The study drew on the National Health and Nutrition Examination Survey, or NHANES, covering survey cycles from 2007 to 2018, with mortality outcomes linked to the National Death Index through December 31, 2019. After applying survey weights, the analytic cohort represented approximately 106.9 million US adults, with a mean age of 47.2 years. Rather than relying on body mass index alone, the investigators stratified participants into four distinct body composition phenotypes using two measurements: BMI, which captures overall mass relative to height, and the waist-to-height ratio, which serves as a practical proxy for central or abdominal adiposity. The four groups were obesity with central adiposity, obesity without central adiposity, normal weight with central adiposity, and normal weight without central adiposity.

The distribution of these phenotypes across the American population proved revealing in its own right. A slim majority, 53.3 percent of the weighted cohort, fell into the normal weight without central adiposity category, the presumed metabolically healthy baseline. Another 33.9 percent carried both a high BMI and a high waist-to-height ratio, the classic pattern of generalized obesity. But two smaller and often overlooked groups drew the researchers’ attention: 8.1 percent of adults had normal BMI values but prominent central fat stores, a phenomenon sometimes called normal weight central adiposity, while 4.7 percent were obese by BMI yet lacked significant abdominal fat accumulation. These last two groups complicate the simple arithmetic of conventional obesity screening.

The central outcome of the investigation was cardiovascular-kidney-metabolic multimorbidity, defined as the coexistence of two or more of the following conditions: hypertension, hyperlipidemia, diabetes, chronic kidney disease, or established cardiovascular disease. This clustering of cardiometabolic disorders, increasingly framed under the umbrella of cardiovascular-kidney-metabolic syndrome, has been recognized by the American Heart Association as a major and growing driver of cardiovascular events and death. The syndrome reflects the intimate physiological coupling of the heart, kidneys, and metabolic organs: insulin resistance accelerates atherosclerosis, declining kidney function worsens volume overload and hypertension, and adipose tissue dysfunction amplifies inflammatory signaling that damages vascular beds throughout the body.

When the researchers tabulated multimorbidity prevalence across body composition phenotypes, a clear hierarchy emerged. Normal weight individuals with central adiposity had the highest rate of cardiovascular-kidney-metabolic multimorbidity at 46.5 percent, meaning nearly half of these apparently slim adults already carried at least two of the five defining conditions. This exceeded the multimorbidity burden observed in people with obesity with central adiposity, and it dwarfed the rates seen in the two phenotypes without abdominal fat excess. In other words, the single group that conventional BMI-based screening would most reliably classify as low risk was, by this metric, the sickest.

Mortality analyses sharpened the message considerably. Using survey-weighted Cox proportional hazards models, which allow researchers to estimate the association between a characteristic and the timing of death while adjusting for confounding factors and accounting for the complex sampling design of NHANES, the team found that normal weight adults with central adiposity faced an adjusted hazard ratio of 1.87 for all-cause mortality compared with the reference group, a statistically significant elevation with a 95 percent confidence interval of 1.08 to 3.25 and a p value of 0.025. Even more dramatic was the association with cardiovascular death: the adjusted hazard ratio reached 7.76, with a 95 percent confidence interval of 1.01 to 59.76 and a p value of 0.049. While the wide confidence interval reflects the relatively small number of events in this subgroup and should temper strong causal interpretation, the direction and magnitude of the association are consistent with a substantially elevated cardiovascular risk.

Kaplan-Meier survival curves, a standard technique for visualizing the probability of surviving over time across groups, reinforced the statistical models. Participants who combined cardiovascular-kidney-metabolic multimorbidity with the normal weight central adiposity phenotype demonstrated the poorest long-term survival of any group in the analysis, with the difference between curves reaching statistical significance at p less than 0.001. This convergence of evidence, spanning prevalence estimates, adjusted hazard modeling, and nonparametric survival analysis, points toward a coherent conclusion: the combination of a slim silhouette and a protruding waistline represents a particularly dangerous metabolic signature when it coexists with clustered cardiometabolic disease.

The biological plausibility behind these findings rests on the distinct behavior of visceral adipose tissue compared with subcutaneous fat. Fat deposited around internal organs is not an inert energy reservoir; it is a hormonally and immunologically active tissue that drains directly into the portal circulation, delivering free fatty acids and inflammatory cytokines to the liver and promoting insulin resistance, dyslipidemia, and hepatic steatosis. Visceral fat accumulation is also closely linked to ectopic fat deposition in the liver, pancreas, and heart itself, mechanisms that have been implicated in the progression of metabolic dysfunction-associated steatotic liver disease, type 2 diabetes, and atherosclerotic cardiovascular disease. A person with a normal BMI but a high waist-to-height ratio may therefore harbor a metabolically hostile internal environment that is invisible to weight-based screening, while some individuals with obesity and preserved fat distribution may be relatively protected.

The study arrives at a moment when the scientific community is actively rethinking how obesity itself should be defined. A recent international commission has proposed diagnostic criteria for clinical obesity that move beyond BMI toward measures of fat distribution and organ dysfunction, and prior research has repeatedly shown that waist-to-height ratio outperforms BMI as a screening tool for cardiometabolic risk factors. The new findings extend this literature into the specific arena of cardiovascular-kidney-metabolic multimorbidity and long-term survival in a nationally representative population. The authors conclude that normal weight individuals with central adiposity bear the greatest CKM burden and mortality risk, a result that highlights the limitations of BMI-based risk assessment and argues for incorporating simple anthropometric measures of central fat, such as the waist-to-height ratio, into routine clinical screening. For clinicians, the practical implication is straightforward: a tape measure around the waist may identify high-risk patients that the scale alone would miss, and for the public, the reassuring sight of a normal number on the bathroom scale should not be mistaken for a clean bill of cardiometabolic health.

Subject of Research: The association of body composition phenotypes with cardiovascular-kidney-metabolic multimorbidity and long-term mortality in a US population-based cohort

Article Title: Body composition phenotypes are key predictors of cardiovascular-kidney-metabolic multimorbidity and long-term mortality: insights from a population-based cohort study

Article References: Kong, G., Intaran, M. A. U., Soh, E. S. W., Yazicioglu, Y., Goh, R., Nagarajan, S., Wang, J.-W., Zhou, X., Zhou, X.-D., Zheng, M.-H., Chan, M. Y., Mehta, A., le Roux, C. W., Mamas, M. A., Khan, M. S., & Chew, N. W. S. (2026). Body composition phenotypes are key predictors of cardiovascular-kidney-metabolic multimorbidity and long-term mortality: insights from a population-based cohort study. Clinical Research in Cardiology. https://doi.org/10.1007/s00392-026-03010-5

Image Credits: AI Generated

DOI: 10.1007/s00392-026-03010-5

Keywords: cardiovascular-kidney-metabolic syndrome, central adiposity, body mass index, waist-to-height ratio, obesity, NHANES, multimorbidity, mortality, visceral fat, cardiometabolic risk, population-based cohort study, risk screening

The numbers behind the review are stark. The latest National Health and Morbidity Survey, conducted in 2023, recorded an adult overweight and obesity prevalence of 54.4 percent, placing Malaysia second highest among Association of Southeast Asian Nations members. When the threshold is lowered to a body mass index of 23 kilograms per square metre, the cut-off increasingly considered appropriate for Asian populations, the proportion of adults at risk climbs to roughly 70 percent. Globally, obesity affected 38 percent of adults in 2020 and is projected to exceed half the world’s population by 2035, making Malaysia a case study in how rapidly middle-income nations are absorbing the metabolic consequences of nutritional transition.

The research team, led by Quan-Hziung Lim and colleagues, conducted a structured search across Web of Science, PubMed and Google Scholar, screening 3626 articles before settling on the final 179. The majority of these studies, nearly 70 percent, addressed the epidemiology of obesity, while fewer than 9 percent focused on developing new treatment modalities. Most relied on community-sampled data rather than nationally representative surveys, and the overwhelming majority were cross-sectional in design. Although randomised controlled trials increased from just three in the previous decade to 25 in the current one, most lasted less than a year, and longitudinal cohorts and pragmatic real-world trials remain scarce. This pattern, the authors note, closely mirrors the findings of an earlier scoping review covering 2008 to 2017, suggesting that the methodological profile of Malaysian obesity research has shifted only modestly over time.

One of the most consequential themes to emerge concerns how obesity itself should be measured. Malaysian studies consistently demonstrate that metabolic risk emerges well below conventional body mass index thresholds. Women with normal BMI but elevated body fat percentage, so-called normal-weight obese individuals, showed substantially higher odds of abdominal obesity, hypertriglyceridemia and hypertension. From a BMI of 23 onward, associations with undiagnosed diabetes, high blood pressure and elevated cholesterol become firmly established, and refined analyses suggest optimal hypertension prediction thresholds of around 23 kilograms per square metre for men and 24 for women. Meanwhile, waist-to-height ratio above approximately 0.5 repeatedly outperformed BMI in predicting excess adiposity and cardiometabolic disease, leading the authors to argue that a dual measurement strategy combining BMI with abdominal measures offers a pragmatic, low-cost route to earlier detection.

The review also documents a paradox familiar from international literature: in a large retrospective cohort, overweight individuals had lower all-cause mortality than those in the normal range, yet overweight and obesity contributed 7 percent of the national cancer burden, second only to tobacco smoking. Above a BMI of 30, more than three-quarters of Malaysians with obesity already carry at least one metabolic complication, and the probability of transitioning from metabolically healthy to unhealthy obesity rises by 4.4 percent with each passing year. Severe obesity at or above 35 kilograms per square metre conferred excess cardiovascular mortality for the population overall. Psychosocial evidence, though thinner, points to elevated rates of depression among people with obesity, with healthcare workers who reported depression showing double the odds of obesity, and pandemic-era surveys linking overweight status to mild-to-severe depressive symptoms.

Predisposition patterns are equally revealing. Malaysian women consistently show higher rates and risks of obesity than men, with 33 to 64 percent greater odds, and steeper increases in BMI and waist circumference with age. Prevalence peaks in middle age and declines in older adults, though the authors caution this may reflect survivorship bias rather than genuine protection. Ethnic disparities are pronounced, with Malay, Indian and other Bumiputera groups showing consistently higher odds of overweight and obesity compared with Chinese Malaysians, a pattern echoed in neighbouring Singapore. Genetic research remains exploratory, identifying variants in genes such as LEPR, ADIPOQ and FTO among local populations, but with limited immediate clinical applicability. More actionable are occupational findings: night-shift work doubled the risk of metabolic syndrome among manufacturing workers, and nurses showed particularly elevated obesity rates.

Dietary drivers form a third major thread. A quasi-historical analysis linked Malaysia’s rising obesity to a 30 percent caloric oversupply, with shifts toward wheat, sugar, meat and animal-based protein. Across multiple studies, excess intake of protein, meat, sugar, sodium and ultra-processed foods, combined with inadequate consumption of fruits, vegetables and fibre, was consistently associated with higher obesity risk. Emerging chrononutrition research suggests that meal timing matters, with late-day energy and carbohydrate intake increasing metabolic risk among people with obesity. On the policy front, the picture is sobering: four years after its introduction, nearly 80 percent of Malaysians remained unaware of the Malaysian Healthy Plate messaging concept, healthy diets remain costly, and food insecurity among rural women was paradoxically linked with higher obesity rates.

Interventional research offers cautious grounds for optimism. Twenty-two community-based lifestyle studies were reviewed, ranging from pedometer-based walking programmes to combined diet and exercise packages. The government-initiated MyBFF@home programme for urban housewives produced modest but significant reductions in weight, BMI and visceral fat at six months, though sustainability at twelve months was variable. A structured face-to-face workplace programme achieved 7 percent weight loss, substantially outperforming an online equivalent, while group-based approaches were more effective than individual counselling. Notably, 91 percent of interventions operated at the micro level, targeting individual behaviour, with almost no macro-level policy interventions tested. Modelling work suggests that meaningful weight loss through physical activity alone requires roughly 1500 MET-minutes per week, equivalent to six to seven hours of moderate activity, a bar that nearly half of sedentary Malaysians are unlikely to clear without dietary change.

Clinical treatment presents a mixed frontier. Most approved obesity medications, including newer incretin-based therapies such as semaglutide and tirzepatide, are available in Malaysia, but monthly out-of-pocket costs of 800 to 1800 ringgit are prohibitive against a median monthly income of roughly 2800 ringgit, and only about 10 percent of people with obesity are ever offered pharmacotherapy. Metabolic and bariatric surgery has expanded rapidly since 1996, with procedures more than doubling between 2010 and 2016, delivering substantial weight loss and metabolic improvement at costs between 11,000 and 30,000 ringgit. Barriers persist on both sides of the consultation: patients report weight stigma, self-blame and misperception of their own weight status, while clinicians cite time constraints and limited training. The authors conclude that Malaysia stands at a critical inflection point, requiring coordinated, whole-of-society action, stronger longitudinal and policy research, and equitable access to effective therapies to prevent the deepening of a Stage 3 obesity profile in which the burden concentrates among the poorest.

Subject of Research: Mapping and narrative review of adult overweight and obesity research in Malaysia from 2015 to 2024

Article Title: The landscape of adult obesity in Malaysia: a mapping of evidence and contemporary narrative review

Article References: Lim, Q.-H., Khoo, J.-K., Ooi, Y.-G., Ramachandaram, A., & Ratnasingam, J. (2026). The landscape of adult obesity in Malaysia: a mapping of evidence and contemporary narrative review. The Lancet Regional Health – Western Pacific, 74, Article 101963. https://doi.org/10.1016/j.lanwpc.2026.101963

Image Credits: AI Generated

DOI: 10.1016/j.lanwpc.2026.101963

Keywords: obesity, Malaysia, overweight, body mass index, waist-to-height ratio, public health, nutrition transition, lifestyle intervention, bariatric surgery, GLP-1 receptor agonists, National Health and Morbidity Survey, noncommunicable diseases