The relationships between anthropometric measurements, organ weights and intracranial, carotid and coronary atherosclerosis

Abstract

Background

Atherosclerosis is the most common cause of cardiovascular-cerebrovascular diseases. Obesity and atherosclerosis are related, and obesity can lead to systemic diseases and an increase in organ weight. Anthropometric measurements such as body mass index, waist circumference and hip circumference are used to determine the risk of obesity. We conducted this study to evaluate the relationship between obesity and atherosclerosis in postmortem cases. We aimed to determine the relationships among anthropometric measurements; subcutaneous adipose tissue thickness; atherosclerosis in the intracranial, carotid, and coronary arteries and organ weights.

Methods

Prospective data analysis was performed from 230 forensic autopsies of 18–75-year-olds from 22/01/2020 to 22/01/2021. Age, sex, history of disease, cause of death, height, weight, body mass index, waist circumference, hip circumference, waist/hip ratio, subcutaneous adipose tissue thickness, and organ weights of the patients were recorded. Atheroma plaques and stenosis in the intracranial, carotid, and coronary arteries were examined. Statistical analysis was performed using IBM SPSS Statistics version 29. The Mann-Whitney U or Kruskal Wallis tests were employed to compare continuous variables. Categorical variables were compared using the Chi-square test.

Results

This study included 187 (81.3%) males and 43 (18.7%) females, and the mean age of the patients was 49.3 ± 17.5 years. Body mass index was significantly and positively correlated with waist circumference, hip circumference, subcutaneous adipose tissue thickness, and the waist/hip ratio. Body mass index, waist/hip ratio, and subcutaneous adipose tissue thickness were significantly positively correlated with heart, liver, kidney, and spleen weights. While body mass index, waist/hip ratio, and subcutaneous adipose tissue thickness were negatively correlated with brain weight in females, this correlation was not detected in males. There were significant associations between the waist/hip ratio and atheroma plaque in the intracranial arteries and ≥ 50% stenosis in the LAD-RCA arteries.

Conclusions

The methods used in the assessment of obesity are important. In study, obesity was approached from a broad perspective by evaluating anthropometric measurements used for obesity diagnosis and atherosclerosis together with organ weights in postmortem cases. We believe that our study will contribute to the assessment of cardiovascular disease risk factors.

Background

Obesity is defined by the World Health Organization as excessive fat accumulation in the body that presents a risk to health. It has become a public health problem affecting individuals of all age groups worldwide and has been considered a global epidemic. According to 2022 data, 2.5 billion adults are overweight, and 890 million of them are obese [1]. Obesity has been associated with many diseases, such as diabetes, hypertension, cardiovascular diseases, depression, and cancer [2].

Body mass index (BMI) is a weight-for-height index used to classify obesity in adults. If the BMI value is between 20 and 25 kg/m², this is considered normal. Individuals aged 25–30 kg/m² are described as overweight, and those aged 30 kg/m² years and above are described as obese [1]. To assess the risk of obesity, other anthropometric measurements, such as waist circumference (WC), hip circumference (HC), the hip circumference/body height ratio, the waist/hip ratio (WHR), and the body fat ratio, are also taken into account [3].

The cause of obesity is an imbalance between the energy that enters the body and the energy that is spent. This energy imbalance affects adipose tissue, and excess fat accumulates in adipocytes in certain areas. Adipose tissue secretes cytokines that affect inflammation and endocrine functions. Released cytokines such as leptin and interleukin-6 negatively affect metabolism and cause atherosclerosis [4]. Atherosclerosis is a systemic disease characterized by atheroma plaques formed by the accumulation of substances such as fat and cholesterol in the blood on the inner wall of vessels. It is the most common cause of cardiovascular and cerebrovascular diseases [5, 6].

The expansion of atheroma plaques causes stenosis in the artery lumen, and as the degree of stenosis increases, ischemia occurs in the organs. Hypertrophy occurs in cardiac myocytes, and the weight of the heart increases with atherosclerosis in the coronary arteries [7]. In other words, obesity also affects organ weight. The fact that the organ’s weight is not within physiological limits indicates that it is pathological.

Our study aimed to determine the relationships between anthropometric measurements such as BMI, WC, HC, WHR, and subcutaneous adipose tissue thickness (SAT) and atheroma plaques in the intracranial, carotid, and coronary arteries in postmortem cases. In addition, unlike previous studies, organ weights were also considered, and the relationships between the mentioned parameters and organ weights were analyzed.

Methods

The study protocol was approved by the Pamukkale University Noninterventional Clinical Research Ethics Committee (date: 21.01.2020, number: 02) and was performed according to the Declaration of Helsinki.

Participants

Our study included 230 medicolegal autopsies between 18 and 75 years of age performed in the autopsy room of the Pamukkale University Faculty of Medicine, Department of Forensic Medicine, between 22.01.2020 and 22.01.2021.

Patients who were severely cachectic, decomposed, carbonized, or fragmented and who were treated in hospitals for more than 72 h were not included in the study. Age, sex, history of disease, and the cause of death of the patients were recorded. Those with a history of cardiovascular disease or metabolic disease were categorized as “yes”, those without a history of cardiovascular disease or metabolic disease were categorized as “no”, and the others were classified as “unknown”. The cause of death were classified as “natural”, “suicide”, “homicide”, “traffic accident” or “other (CO poisoning, alcohol poisoning, etc.)” according to the information obtained from crime scene investigations and forensic investigation data.

Anthropometric measurements

Anthropometric measurements of the cases were recorded before the medicolegal autopsy by taking the bodies lying in the supine position with their clothes removed. Height was measured via a flexible measuring tape and recorded in meters (m). Body weight was measured with an electronic scale and recorded in kilograms (kg). Body mass index was calculated as weight (kg) divided by height (m) squared. BMI was classified as “<18.5 kg/m²: underweight,” “18.5–24.9 kg/m²: normal,” “25-29.9 kg/m²: overweight,” or “≥30 kg/m²: obese” according to the WHO criteria. The WC and HC were measured via a flexible measuring tape. The WC was taken halfway between the lowest rib and the top of the hip bone, roughly in line with the umbilicus, and recorded in centimeters (cm). The HC was taken at the largest circumference around the hip, roughly in line with the trochanter major, and recorded in centimeters (cm). The WHR was calculated as the waist circumference divided by the hip circumference.

Assessment of atherosclerosis, organ weights and subcutaneous adipose tissue

A systematic medicolegal autopsy was performed on all the patients. During the autopsy, the distance between the external surface of the rectus abdominis muscle and the skin, which represents subcutaneous adipose tissue, was measured in line with the umbilicus with a measuring tape and recorded in centimeters (cm). Before the organs were dissected, the weights of the brain; right and left lungs; heart, liver, and spleen; and right and left kidneys were weighed on an electronic digital scale (CAS Elektronik, Version: SW-1) and weights were recorded in grams (g). The brain was weighed with the cerebral-cerebellar hemispheres, midbrain, pons, medulla, and leptomeninges, excluding the dura. The aorta and pulmonary artery were cut 1 to 2 cm above the aortic and pulmonic valves. Then blood was removed before weighing the heart. The liver was weighed with the gallbladder.

During the autopsy, before the brain dissection, the intracranial arteries forming the Willis polygon (a. cerebri anterior, a. cerebri posterior, a. communicans anterior, a. communicans posterior ve a. carotis interna) were dissected vertically to the arterial lumen at approximately 0.5 cm intervals. Arterial lumens were examined macroscopically with the naked eye, and atheroma plaques were evaluated during dissection. If there was an atheroma plaque in any of these arteries (the degree of stenosis was not taken into account), the atheroma plaque for that case was grouped as “yes”, otherwise it was grouped as “no”.

Vertical dissection was performed on the bilateral common carotid arteries at approximately 0.5 cm intervals, the intraluminal region was macroscopically examined, and atheroma plaques were evaluated during neck dissection. If there was an atheroma plaque in any of these arteries (the degree of stenosis was not taken into account), the atheroma plaque for that case was grouped as “yes”, otherwise it was grouped as “no”.

During the autopsy, in the heart dissection, the coronary arteries (LAD, RCA, and CX) were dissected vertically to the arterial lumen at approximately 0.5 cm intervals. Arterial lumens were examined macroscopically with the naked eye, and atheroma plaques were evaluated during dissection. Atheroma plaques in the LAD, RCA, and CX arteries were classified according to the degree of stenosis. If there was no atheroma plaque, it was grouped as “No”, if there was, the degree of stenosis was taken into account and grouped as “<25% stenosis”, “25–49% stenosis” and “50% or more stenosis”.

Statistical analysis

Statistical analyses were conducted using IBM SPSS Statistics version 29 (IBM Corp., Armonk, NY, USA). Descriptive statistics were employed to summarize the demographic and clinical characteristics of the study population. Continuous variables with normal distributions are presented as means ± standard deviations (SDs), whereas nonnormally distributed variables are reported as medians with interquartile ranges (IQRs). Categorical variables are expressed as frequencies and percentages. The normality of data distribution was assessed using the Kolmogorov–Smirnov test. As most continuous variables (e.g., organ weights, anthropometric measures) violated the assumption of normality nonparametric tests were selected for inferential analyses.

Group comparisons

For comparisons between two independent groups (e.g., males vs. females), the Mann–Whitney U test was utilized. For comparisons involving three or more groups (e.g., stenosis severity categories in coronary arteries), the Kruskal–Wallis test was applied, followed by post hoc pairwise comparisons using Dunn’s test with Bonferroni correction to control for Type I error inflation. Categorical variables were analyzed using Pearson’s chi-square test or Fisher’s exact test when expected cell frequencies were < 5.

Correlational analyses

Spearman’s rank-order correlation coefficient (ρ) was employed to evaluate monotonic relationships between BMI, WHR, SAT, and organ weights due to the nonlinearity and nonnormal distribution of the data.

Statistical significance

A two-tailed p-value < 0.05 was considered statistically significant for all analyses unless otherwise specified.

Results

General information

Our study, 230 patients were included; 187 (81.3%) were male, and 43 (18.7%) were female. The mean age of the males was 48.93 ± 16.55 years and that of the females was 51.09 ± 21.25 years. Natural deaths were the most common in 98 (42.6%) cases, followed by suicides in 65 (28.3%) cases. Approximately 41.3% (n = 95) of the patients had a history of cardiovascular or metabolic diseases, 32.2% (n = 74) did not, and 26.5% (n = 61) had an unknown disease (Table 1).

Table 1 Characteristics of the cases. Characteristics total (n = 230) male (n = 187) female (n = 43) P

The mean height of the males (1.69 ± 0.07 m) was significantly greater than the mean height of the females (1.57 ± 0.07 m) (p < 0.001). Additionally, the mean weight of the males (74.88 ± 15.52 kg) was significantly greater than the mean weight of the females (67.53 ± 17.12 kg) (p = 0.007). The mean BMI value of the males was 25.88 ± 5.06 kg/m², and that of the females was 26.91 ± 5.68 kg/m², which was not statistically significant (p = 0.242). When BMI categories were compared by sex, the percentage of males (46.0%) in the normal/healthy weight category was significantly greater than that of females (25.6%) (p = 0.023) (Table 1).

Sex-related differences in WC and HCs were insignificant (p > 0.05). However, the mean WHR of males (0.92 ± 0.07) was significantly greater than that of females (0.90 ± 0.08) (p = 0.042). The mean SAT of males (3.05 ± 1.50 cm) was also significantly lower than that of females (4.05 ± 1.92 cm) (p < 0.001) (Table 1).

Atheroma plaques were detected in the intracranial arteries in 66 (28.7%) patients and the carotid arteries in 63 (27.4%). There was no significant difference between atheroma plaques and sex (p > 0.05). When we looked at the coronary arteries, males had a significantly greater frequency of 50% or more LAD stenosis than females (31.6% vs. 9.3%, p = 0.002). Additionally, 50% or more RCA stenosis frequency was significantly greater in men (23.5%) (p = 0.039). However, there was no statistically significant difference in the frequency of CX stenosis between males and females (p = 0.219).

Sex-related stratification analysis for organ weights revealed that the mean weight of all internal organs was greater in males than in females for all internal organs (p < 0.05). Table 1 shows the characteristics of the variables.

Anthropometric measurements, SAT and atherosclerosis

There were statistically significant positive correlations between BMI and all four measures of body fat distribution: SAT, WC, HC and WHR ​​(p < 0.05). There were strong positive correlations between BMI and WC (total; r = 0.864, p < 0.001, male; r = 0.845, p < 0.001, female; r = 0.919, p < 0.001) and HC (total; r = 0.810, p < 0.001, male; r = 0.788, p < 0.001, female; r = 0.865, p < 0.001). There were moderate positive correlations between BMI and SAT (total; r = 0.686, p < 0.001, male; r = 0.663, p < 0.001, female; r = 0.735, p < 0.001) and WHR (total; r = 0.535, p < 0.001, male; r = 0.573, p < 0.001, female; r = 0.461, p = 0.002). The correlation coefficients were generally greater for females than for males. This reveals that BMI is a better predictor of body fat distribution in females than males.

The mean WHR was significantly greater in patients with intracranial atheroma plaques (0.95 ± 0.08) than in those without intracranial atheroma plaques (0.90 ± 0.07) (p < 0.001). The mean WHR significantly differed in the coronary arteries according to LAD stenosis severity (p = 0.004). Compared with those without stenosis, patients with 50% or more LAD stenosis had the highest mean WHR (p = 0.004). Similarly, the WHR significantly differed according to RCA stenosis severity (p < 0.001). The WHR was significantly greater in patients with 50% or more RCA stenosis than in those without stenosis (p < 0.001). No statistically significant relationship was detected between BMI and SAT or atherosclerosis in the arteries (p > 0.05) (Table 2).

Table 2 Comparison of BMI, WHR, and SAT according to arterial atherosclerosis

BMI, WHR, SAT and organ weights

When we looked at all the cases in our study, none of the anthropometric measurements showed statistically significant correlations with brain weight (p > 0.05). BMI, WHR, and SAT had positive and statistically significant correlations with heart, liver, and spleen weights (p < 0.05). BMI and WHR were more strongly correlated than SAT. BMI and WHR had positive and statistically significant correlations with right and left kidney weights (p < 0.05). However, the SAT had weak and nonsignificant correlations (p > 0.05). The findings suggested that higher BMI, WHR, and SAT were generally associated with heavier hearts, livers, kidneys, and spleens (Table 3).

Table 3 Correlations between BMI, WHR, SAT and internal organ weight

Sex-related stratification analysis for organ weights revealed that brain weight was significantly and negatively correlated with BMI, WHR, and SAT in females (p < 0.05). This result was not observed in males. However, in males, BMI and WHR were moderately positively and significantly correlated with heart and liver weights but weakly positively and significantly correlated with spleen, right, and left kidney weights (p < 0.05). SAT also showed a positive and statistically significant correlation with heart, liver, and spleen weights (p < 0.05). For females, while BMI was positively and statistically significantly correlated with heart, liver, right–left kidney, and spleen weights, WHR was only correlated with heart weight (p < 0.05). The SAT also showed a positive and statistically significant correlation with heart, liver, and spleen weights (p < 0.05) (Table 3).

Atherosclerosis and organ weights

There was a significant decrease in brain weight and a significant increase in heart weight in patients with atheroma plaques in the intracranial arteries (p < 0.05). However, in patients with atheroma plaques in the carotid arteries, only a significant increase in heart weight was detected (p < 0.05), and no significant change in brain or other organ weights was detected (p > 0.05) (Table 4).

Table 4 Comparison of weights of internal organs according to atheroma plaque in arteries, all cases

Table 5 shows the relationship between atherosclerosis in the coronary arteries and organ weight. When this relationship was analyzed, the degree of stenosis in the coronary artery was classified as < 50% stenosis (cases in the groups “no stenosis”, “<25% stenosis”, and “25–49% stenosis” were included in this group) and ≥ 50% stenosis. Left and right kidney weights were significantly greater in patients with 50% or more LAD and RCA stenosis than in patients with less than 50% stenosis (p < 0.05). A significant increase in heart weight was observed in patients with 50% or more LAD, RCA, and CX stenosis compared with that in other patients (p < 0.001).

Table 5 Comparison of the weights of internal organs according to stenosis in coronary arteries, all cases

In our study, patients with a history of the cardiovascular system or metabolic diseases were significantly older (mean age: 60.41 ± 15.49 years) than were those without (mean age: 43.56 ± 16.19 years) or with an unknown history (mean age: 44.90 ± 15.55 years) (p < 0.001). Among the anthropometric measurements, the WHR was greater in patients with a history of cardiovascular or metabolic disease (mean: 0.94 ± 0.08) than in those without (mean: 0.91 ± 0.07) or with an unknown history (mean: 0.91 ± 0.08) (p = 0.011). BMI and SAT were not significantly associated with a history of the disease (p = 0.063, p = 0.746).

A greater percentage of patients with a history of cardiovascular or metabolic diseases (57.6%) had stenosis in intracranial arteries than did those without (30.3%) or with an unknown history (12.1%) (p < 0.001). Similarly, carotid artery stenosis was observed in a significantly greater percentage of patients with a history of disease than in those without a history of disease (p = 0.023). For all three coronary arteries (LAD, RCA, and CX), there were significant differences in the distribution of stenosis severity among the groups (p < 0.001 for LAD and RCA; p = 0.003 for CX). In both the LAD, RCA, and CX arteries, patients with a history of disease (LAD 55.6%, RCA 58.7%, CX 57.5%), tended to have a greater frequency of ≥ 50% stenosis than those in the other groups.

Discussion

Our study revealed a statistically significant positive correlation between BMI and WC, HC, WHR, and SAT. It was also understood that BMI, WHR, and SAT significantly and positively correlated with heart, liver, kidney, and spleen weights. In the study, it was seen that BMI, WHR, and SAT had a negative correlation with brain weight in females, but this correlation was not detected in males. It was found that WHR had significant relationships with atheroma plaque in intracranial arteries and ≥ 50% stenosis in LAD-RCA arteries.

Clinical studies have confirmed a relationship between abnormal adipose tissue distribution in the body and metabolic disorders and an increased risk of morbidity and mortality [8]. Therefore, methods to evaluate adipose tissue distribution in the body should be chosen carefully. Studies have shown that anthropometric measurements such as body mass index (BMI), waist-hip ratio (WHR), waist-height ratio (WHtR) and waist circumference (WC) can accurately assess body fat mass and that these measurements have a positive relationship with deaths from cardiovascular system diseases [9,10,11].

Cardiovascular diseases are the leading cause of death in the world [12]. It was known that BMI is associated with cardiovascular diseases [13]. BMI is a commonly used measurement method for diagnosing obesity. However, it cannot assess body fat percentage, as it is a direct calculation method based on height and weight measurements. A person who has a high BMI and low body fat percentage may be mistakenly classified as overweight or obese [14]. Ashwell et al. [15] and Lo et al. [16] found that WHtR is a better cardiovascular disease risk predictor than BMI and WC in their studies. In a meta-analysis study, it was observed that BMI, WC, and WHR were anthropometric measurements that can be used to assess the risk of cardiovascular disease, and among these measurements, those related to the abdominal region, such as WC and WHR, were better predictors of cardiovascular disease risk [17]. A meta-analysis by Cao et al. also confirmed that WHR was a strong predictor of myocardial infarction in males and females [18]. It was understood from these data that anthropometric measurements can be used to assess the risk of cardiovascular disease in living individuals. Cardiovascular diseases can be prevented by taking measures such as lifestyle changes in individuals at risk. Moreover, a higher WHR was associated with more than 50% stenosis in the LAD and RCA in our study.

The relationship between anthropometric measurements and cardiovascular diseases may show different results according to gender. For example, in the study by Mohammad et al., it was understood that BMI was of secondary importance compared to WHR in all cases, but it was seen that BMI had the highest correlation as a cardiovascular disease risk predictor in males [19]. Similarly, a retrospective cohort study of middle-aged Japanese men found a strong association between BMI and the risk of cardiovascular disease [20]. A study of British women also found an increased incidence of ischemic attacks in individuals of European and Asian origin with a higher BMI. In particular, lifestyle changes and healthy diets aimed at reducing BMI have shown remarkable benefits in reducing cardiovascular disease [21].

Atherosclerosis primary affects the aorta, secondary the extremity, coronary, and intracranial arteries [22]. In our study, atheroma plaques in intracranial arteries were detected in 28.7% of cases, and atheroma plaques in carotid arteries were detected in 27.4% of cases. Zhao et al. compared intracranial arteries with extracranial carotid arteries in their study and found the highest rate of stenosis in the middle cerebral artery at 24.6%, followed by the extracranial carotid artery at 16.5%. These findings were similar to our study [23]. Jun et al.‘s study also found a positive significant relationship between carotid atherosclerosis and intracranial atherosclerosis [24]. In addition, in our study, atheroma plaques in coronary arteries were found to be more common in the LAD (56.1%), RCA (38.3%), and Cx (36.1%) arteries. In an autopsy study, coronary artery disease was detected in 60%. Similar to our study, the most common was LAD (78.9%), then RCA (15.8%) and cx (5.3%) [25].

In a study analyzing the relationship between obesity and carotid artery disease, it was observed that there was no relationship between BMI, which is considered a general obesity parameter, or WC, which is a visceral obesity marker, and carotid plaques. No association was found between SAT and carotid artery plaques [26]. However, other studies in the literature have found that WHR was associated with the prevalence of carotid artery plaques [27, 28]. A positive correlation was observed between WC and the risk of ischemic stroke and intracerebral hemorrhage in a cohort study [27]. It was understood from these data that anthropometric measurements are not only risk predictors for cardiovascular disease but also pathologies related to the central nervous system. Our study’s results revealed no relationship between atheroma plaque in the common carotid artery and BMI or the WHR. However, there was a statistically significant relationship between the WHR and the presence of atheroma plaques in intracranial arteries.

Many studies have been conducted on postmortem organ weights [29,30,31]. Our study aimed not only to add organ weights to the literature but also to go beyond previous studies and evaluate organ weights together with obesity and atherosclerosis as well as contributing to clinical studies. Organ weights are often used to assess the presence of pathology. A severe brain cerebral edema or a severe spleen may be a sign of potential hematologic malignancy [32]. Heart weight may increase due to epicardial adipose tissue accumulation, which is not routinely measured during autopsies. Pathologies such as increased circulating blood volume, increased vascular resistance in adipose tissue, and restrictive lung disease may cause compensatory cardiac hypertrophy in obese individuals [33].

Our study associated higher BMI, WHR, and SAT with higher heart, liver, kidney, and spleen weights. Similar to our results, other studies have shown that heart weight increases with BMI, and heart, liver, kidney, and spleen weights also increase with increasing BMI [33,34,35]. When evaluated according to gender, the left lung, spleen, and kidney weights showed significant correlations with BMI in males, but similar results were not seen in females. As in our study, in the gender-related analysis, brain weight did not correlate with BMI in both genders [35].

Our study revealed that the mean brain weight was 1254.88(± 125.13) g in females and 1403.25(± 159.10) g in males. In a study, the mean brain weight in females was found to be 1233 g [32]. Brain weight was found to be lower in females, consistent with literature data in our study [32, 36, 37]. Another study found that men’s brain weights were 10–15% heavier than women’s brain weights in all age categories [38]. Our study did not detect a statistically significant relationship between BMI and brain weight in all cases. However, in gender-related analysis, higher BMI, WHR and SAT were associated with lower brain weight in females. Neuroimaging studies have shown that there is a volume reduction in grey matter with obesity. A decrease in grey matter volume causes diseases such as cognitive disorders and dementia [39]. Gender-related analyses showed negative correlations between WC and grey matter volume. However, this correlation was found to be stronger in females [40, 41]. Similarly, a neuroimaging study revealed that BMI was significantly and negatively correlated with bilateral cerebellum external volumes [42].

Brain health has become increasingly popular in the scientific world. Maintaining optimum integrity of brain structures is a foundation that defines brain health. Brain magnetic resonance imaging (MRI) methods provide objective and precise assessment of brain health in structural areas with neuroimaging measurements. BMI, the most widely accepted indicator of obesity, has been recognized as a critical factor affecting brain health [43, 44]. Higher BMI has been associated with smaller brain volume [44,45,46,47] and lower white matter integrit [48]. Additionally, waist-hip ratio (WHR) may also be a potential measure used to assess brain health as it is a reliable biomarker of central obesity. Several cross-sectional studies have shown that higher WHR levels are associated with lower grey matter volume and higher white matter volume [44, 49].

A multicenter cohort study conducted in China investigated the relationships between BMI and WHR variability and brain tissue volume, white matter microstructural integrity, and cerebral small vessel disease using MRI markers. Increased weight was associated with impaired white matter microstructural integrity. A decrease in WHR was found to have a protective effect on brain health. Long-term BMI changes primarily affected white matter microstructural integrity and cerebral small vessel disease, while WHR changes were mainly associated with brain volumetric changes. Furthermore, in females, WHR loss was associated with a larger hippocampus [47]. These findings were consistent with a meta-analysis of 45 observational epidemiological studies on obesity and brain structures by Han et al. [50]. These data revealed that individuals can achieve better brain health through individual follow-up of anthropometric measurements, which will have better social effects.

Study limitations

The fact that our study was planned as a cross-sectional study limits the ability to establish causal relationships between obesity, atherosclerosis and organ weights. However, we believe that our study will contribute to future studies on anthropometric measurements, atherosclerosis and organ weights and guide studies on the relationships between obesity and cardiovascular diseases and brain health.

In our study, it was determined that there was a negative correlation between anthropometric measurements such as BMI-WHR and brain weights in females. However, since the number of females in the study was a small sample size (n = 43), this limits the generalizability of the findings. We believe that our study will guide other studies with larger sample sizes.

Another issue that can be considered as a limitation in our study is that neck circumference measurements and evaluation of aorta and pelvic arteries were not included. We believe that our study may provide insight into future studies in which these parameters are evaluated along with anthropometric measurements.

Conclusion

The paper concludes by arguing various anthropometric measurements, especially BMI, to diagnose obesity, as well as atherosclerosis in the intracranial, carotid, and coronary arteries in postmortem cases. Unlike other studies, organ weights were also analyzed, and we looked at obesity from a broad perspective. Since our study is an autopsy study in this field, unlike other imaging studies, it provides clarity and convenience in the macroscopic evaluation of atherosclerosis and measurement of subcutaneous adipose tissue thickness.

In conclusion, BMI was significantly and positively correlated with WC, HC, WHR and SAT in this study. BMI, WHR, and SAT were significantly positively correlated with heart, liver, kidney, and spleen weights. While BMI, WHR, and SAT were negatively correlated with brain weight in females, this correlation was not detected in males. There were significant associations between WHR and atheroma plaque in the intracranial arteries and ≥ 50% stenosis in the LAD-RCA arteries.

Obesity is a global epidemic associated with many diseases. Methods used in obesity risk assessment should have high sensitivity and specificity. This study will be useful for future work on obesity. We hope that evaluating postmortem organ weights with the data we have obtained will contribute to elucidating their relationship with obesity and will be useful in cardiovascular disease risk and brain health assessment and identification of new risk factors for living individuals.