The saturation effect of body mass index on femoral neck bone mineral density in a sample of apparently healthy older Syrians: A cross-sectional study

Abstract

Introduction

Obesity and osteoporosis are important and common global health problems because of their increasing prevalence and significant impact on mortality and morbidity. The relationship between obesity and bone mineral density remains controversial and is not fully understood. This study aimed to investigate the saturation effect of body mass index on femoral neck bone mineral density in apparently healthy older Syrians adults.

Methods

This cross-sectional study analyzed data from 170 apparently healthy Syrian adults (both males and females) aged ≥50 years. Height and weight were measured, and body mass index was calculated. Bone mineral density of the lumbar spine and femoral neck was assessed using dual-energy X-ray absorptiometry.

Results

The results of this study showed a statistically significant positive relationship between femoral neck bone mineral density and body mass index (p value < 0.001). This relationship was not linear; rather, a fitted curve indicated a turning point (saturation value) at which the positive effect of body mass index reached its peak and then began to gradually decrease.

Conclusions

There was a positive relationship between femoral neck bone mineral density and body mass index in both males and females, with a saturation effect of body mass index on femoral neck bone mineral density. The body mass index saturation value was 30.5 kg/m² in apparently healthy older Syrian adults.

Keywords

Obesity bone mineral density osteoporosis saturation value cross-sectional study

Introduction

Osteoporosis and obesity are two serious and complex worldwide health issues.¹ Osteoporosis is the most common metabolic bone disease,² characterized by low bone mass and microarchitectural deterioration.³ It is often silent until complicated by fracture,⁴ and these fractures are a significant cause of morbidity and mortality, resulting in an enormous economic cost to the health care system.⁵

Dual-energy x-ray absorptiometry (DXA) of the lumbar spine and proximal femur (hip) provides accurate and reproducible bone mineral density (BMD) measurements.⁶ BMD testing is the gold standard for diagnosing osteoporosis.⁷

BMD is classified as normal when the T-score is ≥−1 standard deviation (SD) compared with the mean value of healthy young adults, low bone mass (osteopenia) when the T-score is between −1 and −2.5 SD, and osteoporosis when the T-score is ≤ −2.5 SD, based on the World Health Organization (WHO) diagnostic classification.^4–8

Obesity is a medical condition of excessive fat accumulation that leads to negative effects on health.⁹ The WHO defines overweight as a body mass index (BMI) of 25.0–29.9 kg/m² and obesity as a BMI ≥ 30.0 kg/m² in adults.¹⁰

The association between bone tissue and obesity is complex and not fully understood. Obesity increases the levels of leptin, estrogens, and insulin, which play important roles in promoting bone formation and reducing bone resorption, therefore, protecting bone.^11,12 At the same time, obesity is associated with low-grade systemic inflammation, which may impair bone formation through the upregulation of pro-inflammatory cytokines (interleukin-6 and tumor necrosis factor-α).¹³

This study aimed to investigate the relationship between BMI and femoral neck BMD and the saturation effect of BMI on femoral neck BMD in apparently healthy older Syrian adults.

Methods

Study design and participants

A cross-sectional study was conducted between March 2023 and March 2024 and included 170 apparently healthy older Syrian adults who attended the bone densitometry clinic at the National University Hospital in Damascus. The sample size of 170 participants, including both males and females, was determined based on a sample size calculation,¹⁴ with a 95% confidence interval, a predictive value of 0.05, and a margin of error of 5%.

Inclusion criteria

Apparently healthy males and females aged ≥50 years (individuals with no medical history, no chronic medication use, and normal clinical and laboratory findings) who visited the bone densitometry clinic at the National University Hospital in Damascus.

Exclusion criteria

The exclusion criteria were as follows: (a) Individuals with any type of cancer; (b) individuals with a history of taking medications that affect BMD measurements, such as corticosteroids, bisphosphonates, tamoxifen, proton pump inhibitors, anticoagulants; (c) females with early ovarian failure; and (d) individuals with conditions affecting bone density, such as rheumatoid arthritis, hyperparathyroidism, hyperthyroidism, end-stage kidney disease, liver failure, diabetes mellitus.

Data collection

This study received approval from the hospital's Ethics Committee in accordance with the Helsinki Declaration of 1975, as revised in 2024. Written informed consent was obtained from all patients participating in the study, and all patients’ information was deidentified. The reporting of this study conforms to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.¹⁵

Data collection included demographic variables (sex, age, physical activity (walking/week), smoking, alcohol consumption, and employment), menopause duration (females), and personal habits.

BMD was measured centrally for all participants using DXA of the lumbar spine and femoral neck by the device located in the bone densitometry clinic at the National University Hospital in Damascus: Discovery Wi (S/N 80058) scan (Hologic, Inc., Bedford, MA, USA).

The results were recorded as BMD in g/cm², and the diagnosis was made based on the WHO recommendation according to T-score. Participants were then divided into three groups: normal BMD, osteopenia, and osteoporosis.⁴

Weight was measured in kilograms; height in meters, and BMI was calculated by dividing weight in kilograms by the square of height in meters. These measurements were taken in light clothing and no shoes using the same scale (Seca, Germany).

Participants were then classified according to BMI into three groups based on the WHO recommendations⁹: normal weight (BMI 18.5–24.9 kg/m²), overweight (BMI 25.0–29.9 kg/m²), and obesity (BMI ≥ 30.0 kg/m²).

The following analyses (complete blood count, Creatinine, Alanine transaminase, Glucose, Calcium, Phosphorus, and Albumin) were performed for all participants and were all standard.

Statistical analysis

Descriptive and analytical statistical methods were used, including simple and multiple linear regression models, followed by saturation effect analysis. Statistical Package for the Social Sciences version 23.0 (SPSS Inc., Chicago, IL, USA) was used for the statistical analyses. A p value <0.05 was considered statistically significant.

Results

Tables 1 and 2 present the main characteristics of the study participants, including the descriptive statistics of the demographic and qualitative variables (Table 1) and the descriptive statistics of the quantitative variables for the study sample (Table 2).

Table 1.

The descriptive statistics of demographic and qualitative variables for study sample.

		N	%
Sex	Males	29	17.1
Sex	Females	141	82.9
	Total	170	100
Age (year)	50–59	107	62.9
	60–69	54	31.8
	> = 70	9	5.3
	Total	170	100
BMD according to T-score (g/cm²)	Normal	25	14.7
	Osteopenia	81	47.6
	Osteoporosis	64	37.6
	Total	170	100
BMI category (kg/m²)	Normal weight	55	32.4
	Overweight	59	34.7
	Obesity	56	32.9
	Total	170	100
Menopause duration (females) (year)	< 5	41	29.1
	10–5	42	29.8
	10<	58	41.1
	Total	141	100
Physical activity (walking/week)	No physical activity	54	31.8
	Min/week 150 >	49	28.8
	Min/week 150 <	67	39.4
	Total	170	100
Smoking	Nonsmoker	127	74.7
Smoking	Smoker	43	24.3
	Total	170	100
Alcohol consumption	Yes	0	0
Alcohol consumption	No	170	100
	Total	170	100
Employment	Nonemployed	106	62.4
Employment	Employed	64	37.6
	Total	170	100

BMD: bone mineral density; BMI: body mass index.

Table 2.

The descriptive statistics of quantitative variables for study sample: the results of simple and multiple linear regression analysis for predicting femoral neck BMD with BMI.

Variables	Total	N	Mean	Median	Mode	SD	Range	Min	Max
Age	170		58.48	57	50	6.98	31	50	81
	Males	29	58.52	57	50	7.02	23	50	73
	Females	141	58.48	57	50	6.99	31	50	81
Weight	170		72.02	72	72	13.06	60	48	108
	Males	29	81.24	83	69^a	13.71	52	56	108
	Females	141	70.13	70	73	12.13	58	48	106
Height	170		160.54	160	160	6.91	39	142	181
	Males	29	169.10	170	175	7.2	30	151	181
	Females	141	158.78	159	160	5.38	33	142	175
BMI	170		27.96	27.8	24.6^a	4.7	22.7	18.7	41.4
Menopause duration (females)	141		9.5	9	1	6.8	35	1	36
BMD-femoral neck	170		0.72	0.73	0.58	0.13	0.91	0.26	1.18
	Males	29	0.8	0.78	0.37^a	0.16	0.81	0.37	1.18
	Females	141	0.71	0.72	0.58	0.12	0.79	0.26	1.05
HB	170		12.9	12.9	13.2	1.32	6.3	9.9	16.2
GLU	170		88.84	89	86	8.89	51	70	121
CR	170		0.78	0.8	0.7	0.24	1	0.3	1.3
CA	170		9.18	9.2	9.4	0.45	1.8	8.2	10
P	170		3.31	3.2	3.2	0.5	3	1.9	4.9

Multiple modes exist. The smallest value is shown.

BMD: bone mineral density; BMI: body mass index; HB: hemoglobin; GLU: glucose; CR: creatinine; CA: calcium; P: phosphorus.

The results of the simple and multiple linear regression analyses for predicting femoral neck BMD from BMI showed a statistically significant positive relationship between femoral neck BMD and BMI. This association remained unchanged after excluding confounders factor (sex, age, menopause duration, physical activity (weekly walking), smoking), as shown in (Table 3). After discovering a statistically significant positive relationship between femoral neck BMD and BMI, saturation effect analysis was performed. The results showed that this relationship was not linear; rather, a fitted curve indicated a turning point (saturation value) at which the positive effect of BMI on femoral neck BMD reached its peak and then began to gradually decrease. The BMI saturation value was 30.5 kg/m² (Figure 1).

Figure 1.

Scatter plot showing the distribution of participants according to femoral neck BMD and BMI values in the study sample. The vertical axis represents BMI (kg/m²), whereas the horizontal axis represents femoral neck BMD in g/cm².

Table 3.

This table shows a statistically significant positive relationship between femoral neck BMD and BMI, and this association remains positive significant even after excluding confounding factors.

Models		β	SE	t	p value	R²
1	BMI	0.009	0.002	4.079	<0.001*	0.090
2	BMI	0.008	0.002	3.980	<0.001*	0.141
2	Sex (male vs. female)	0.080	0.025	3.150	0.002*	0.141
3	BMI	0.007	0.002	3.443	0.001*	0.230
	Age	−0.004	0.002	−1.923	0.057
	Menopause duration	−0.028	0.015	−1.820	0.071
	Smoking	0.005	0.023	0.215	0.830
	Walking/week	0.027	0.023	1.147	0.254

*There is a statistical significance when (p value <0.05).

BMD: bone mineral density; BMI: body mass index; SE: standard error.

Before this value, each unit increase in BMI was associated with a 0.018 g/cm² increase in femoral neck BMD. After this value, each one-unit increase in BMI was associated with a 0.006 g/cm² increase in femoral neck BMD.

Discussion

Our study included 170 apparently healthy Syrian adults (141 females and 29 males) aged ≥50 years. The results suggest that obesity plays an important protective role against osteoporosis.

A statistically significant positive relationship was observed between femoral neck BMD and BMI. This relationship did not differ by sex and demonstrated a saturation effect of BMI on femoral neck BMD. The BMI saturation value was 30.5 kg/m².

Our results are consistent with those of the study by Zhang et al.¹⁶ which was conducted in the USA in 2022 and included 2903 males and females aged ≥50 years over 4 years, and the study by Ma et al.¹⁷ which was also conducted in the USA in 2021 and included 10,910 males and females aged ≥50 years over 10 years. Both studies showed a positive relationship between femoral neck BMD and BMI. However, our findings differed with respect to the BMI saturation value. The saturation value was 24.3 kg/m² in the study by Zhang et al., 26.44 kg/m² in the study by Ming et al., and it was 30.5 kg/m² in our current study.

Our results were also consistent with those of the study by Alay et al.¹⁸ conducted in Turkey in 2020 on 452 healthy postmenopausal females over 3 years; the study by Wu et al.¹⁹ conducted in China in 2016 on 236 healthy postmenopausal females over 2 years; the study by Salamat et al.¹¹ conducted in Iran in 2016 on 5895 males and females aged 20–91 years; and the study by Fawzy et al.²⁰ conducted in the UAE in 2011 on 101 males and females aged 25–80 years. All of these studies showed that obesity has a protective role against osteoporosis and that there is a positive relationship between BMD and BMI.

However, the results of our study differ from those of several international studies reporting that obesity is associated with decreased BMD and an increased risk of fractures, including the study by Kim et al.²¹ conducted in Korea in 2010 on 907 healthy females aged 60–70 years; the study by Greco et al.²² conducted in Italy in 2011 on 398 males and females; and the study by Nielson et al.²³ conducted in the USA in 2010 on 5995 healthy males over 2 years.

In contrast, the study by Chan et al.²⁴ conducted in Australia in 2014 on 3550 males and females ≥60 years over a 22-year follow-up period, indicated that BMI had no direct or significant effect on fracture risk mediated by BMD in either males or females.²⁴

The discrepancy between the results of our study and those of some international studies may be explained by differences in study design, study variables, study populations, sample size, and ethnic, genetic, and geographic characteristics, all of which may influence BMD measurements. Environmental factors, such as sunlight exposure, clothing style, and sunscreen use; dietary factors, such as calcium and vitamin D intake; and behavioral factors, such as smoking, alcohol consumption, and physical activity, may also contribute. Other unidentified factors may vary among populations.

Finally, we hope that future studies will incorporate artificial intelligence and machine learning applications to develop predictive models for factors affecting BMD and the diagnosis of osteoporosis. For example, Carvalho et al. developed a model in 2025 using data from 7924 males and females that incorporated factors such as age, arm muscle circumference, body weight, sex, and BMI to predict the risk of osteoporosis.²⁵

Similarly, Carvalho et al. conducted another study in Portugal in 2024 involving 3132 males and females and developed a highly accurate model for predicting 1-year mortality after orthopedic hospitalization. The model demonstrated the important roles of age, emergency admission date/time, and the interval before surgical intervention in predicting mortality following orthopedic surgery.²⁶

In future clinical applications, phototherapy may serve as a noninvasive and safe therapeutic modality for obesity management, targeting an optimal BMI range of 30–35 kg/m² to enhance BMD, as demonstrated in the study by Zhang et al.²⁷

One limitation of this study is the disproportionately small number of male participants compared with female participants. This imbalance was likely a consequence of the conflict in Syria, where recruiting apparently healthy individuals aged ≥50 years is challenging for both men and women. In addition, the inclusion of only a single center in Damascus University limits the generalizability of the results.

Future studies may further clarify the relationship between obesity and BMD by using agnostic statistical measures, such as Spearman’s rho, Kendall’s tau, mutual information, and total correlation, as highlighted by Carvalho et al.²⁸

Conclusion

A statistically significant positive relationship was observed between femoral neck BMD and BMI. This relationship was not linear; rather, a fitted curve indicated a turning point (saturation value) at which the positive effect of BMI on femoral neck BMD reached its peak and then gradually decreased. Maintaining a BMI within the range of 30–31 kg/m² (30.5 kg/m²) may be associated with more favorable femoral neck BMD outcomes in individuals with obesity.

Supplemental Material

sj-docx-1-imr-10.1177_03000605261467848 - Supplemental material for The saturation effect of body mass index on femoral neck bone mineral density in a sample of apparently healthy older Syrians: A cross-sectional study

Supplemental material, sj-docx-1-imr-10.1177_03000605261467848 for The saturation effect of body mass index on femoral neck bone mineral density in a sample of apparently healthy older Syrians: A cross-sectional study by Raghad Alkhalaf, Yousef Saffaf and Zaynab Alourfi in Journal of International Medical Research

Footnotes

Acknowledgments

None.

ORCID iD

Yousef Saffaf

Ethics approval and consent to participate

The Ethical Committee of the Faculty of Medicine at Damascus University, Syria, approved this study. All participants provided written informed consent to participate voluntarily before inclusion in the study. The study design and conduct were aligned with the ethical principles of the Declaration of Helsinki.²⁹

Consent for publication

Written informed consent was obtained from the patients for publication and any accompanying images. A copy of the written consent form is available for review by the Editor-in-Chief of this journal upon request.

Author contributions

Raghad Alkhalaf: Conceptualization, methodology, validation, investigation, writing – original draft, and writing – review & editing. Yousef Saffaf: Writing – original draft and writing – review & editing. Zaynab Alourfi: Writing – review & editing and supervision.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Supplemental material

Supplemental material includes STROBE guidelines and is available online.

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