Osteoporosis is a global public health issue affecting over 200 million people worldwide. In the USA alone, it impacts more than 25 million individuals, contributing to over 1.3 million fractures annually, predominantly in postmenopausal women [1]. Osteoporosis has been termed a "silent epidemic disorder" due to its asymptomatic nature until a fracture occurs.

In India, approximately 61 million people are affected by osteoporosis, with one in three women and one in eight men at risk. There has been a 200% increase in osteoporosis cases in the last decade, with a 50% rise expected in the coming 10 years [2]. A systematic review reported that the prevalence of osteoporosis in India increased from 14.94% in 2008 to 27.96% between 2012 and 2015 [3]. While osteoporosis affects all populations, not all groups are at equal risk [4]. Studies indicate that Asian women, particularly in India, may have a higher predisposition to osteoporosis compared to their Caucasian counterparts [5].

Additionally, there are differences in bone health across ethnic groups, with variations in body size and composition contributing to these disparities. Understanding bone mineral density (BMD) patterns is essential for the prevention, diagnosis, and management of osteoporosis and its complications in later life [6].

In developing countries, the lifetime risk of fractures involving the wrist, hip, or vertebrae is estimated to be between 30% and 40%, comparable to the risk of heart disease [7]. Osteoporosis is easily diagnosed using dual-energy X-ray absorptiometry (DEXA) to measure BMD [8]. By 2050, nearly 80% of the world's elderly are expected to reside in underdeveloped regions. In Asia, the number of individuals aged 60 and above is anticipated to rise from 549 million in 2017 to approximately 1.3 billion by 2050 [9].

Postmenopausal women are particularly vulnerable to osteoporosis, which not only increases morbidity but also adversely impacts quality of life [4]. Awareness of osteoporosis remains low in developing countries. Despite advancements in medical practice, postmenopausal osteoporosis remains underdiagnosed and inadequately treated [5]. India, the second most populous country in the world, faces significant health disparities across its socioeconomic classes. Indian women, particularly those from lower socioeconomic backgrounds, are at greater risk of hip fractures, often due to calcium-deficient diets, and tend to experience fractures earlier than women in Western countries [10]. From the age of 50, women face a 40% lifetime risk of fractures involving the spine, hip, and distal radius, while men face a 13% risk [6].

The present study was undertaken to assess the frequency of osteoporosis and osteopenia, and to examine related risk factors such as age, gender, and obesity in a healthy Indian population at a tertiary healthcare center in Central India.

• Observational Cross-sectional study.
• All patients undergoing DEXA scan as part of either routine health check-up or as an indication to symptoms suggestive of osteoporosis in SAMC and PG Institute, Indore.

Inclusion criteria: All patients undergoing DEXA scan as part of either routine health checkup or as an indication to symptoms suggestive of osteoporosis in a tertiary health care center in Central India: SAMC and PG Institute Indore.

Exclusion criteria: Patients below 18 years of age and those not giving consent.

Ethical consideration: The study has been approved by Institutional Ethical Committee of Sri Aurobindo Medical College & P.G. Institute Indore (M.P.). IEC NO: SAIMS/RC/IEC/98/25

Study duration: 1.5 years from January 2023 to June 2024.

Sample size: It is a time bound study.

Statistical analysis: The data was analyzed using STATA version 13. Frequency distribution and cross tabulation was performed to prepare tables using Microsoft Excel. The quantitative data was expressed as mean and standard deviation. The categorical data was expressed as number and percentage. Chi-square test was used to compare the categorical data. The level of significance was assessed at 5%.

Table 1: Gender-Wise Distribution of the Study Population and Anthropometric Characteristics.

Table 2: Distribution of Study Population According to BMI Categories.

BMI- Body Mass Index

Table 3: Correlation of Osteoporosis with Demographic, Anthropometric, and Body Composition Factors.

Table 4: Prevalence of Osteoporosis Across Skeletal Sites: Hip, Wrist, and Spine.

Osteoporosis is one of the most common inflammatory bone loss condition [8,9] and is an age- related disorder: its prevalence increases with age and is actually growing due to the constant aging of the population [1,2,11]. Osteoporosis is also a predominantly female pathology: among diseases afflicting women more than men [4,5]. In addition to aging and menopause, other conditions, such as underlying diseases and/or the use of drugs impacting the bone, can also cause ?secondary? osteoporosis [6,12]. 5 percent of people aged 50 and 50% at age 85 have decreased BMD, whereas more than 75% of women over 60 are affected. There is therefore a significant gender difference in disease prevalence: 4 million females and 1 million males in Italy suffer from osteoporosis, and 1 in 2 women and 1 in 4 men aged more than 50 will have an osteoporosis-related fracture in their lifetime [13].

Women are known to be at greater risk of developing osteoporosis than men. However, in recent years, it has become increasingly evident that osteoporosis represents a significantly important problem also for men. Men are not well represented in osteoporosis trials and clinical and laboratory findings of male osteoporosis, as well as differences in efficacy and side effects of anti-osteoporotic drug are poorly known. As a consequence, men are poorly studied, underdiagnosed and inadequately treated, although osteoporotic fractures are generally accompanied by more serious complications and greater mortality in males compared to females [3,10,14].

The indications for osteoporosis screenings in men, the age and any categories at greatest risk in which to plan them, as well as the most appropriate diagnostic tools to be used from a gender perspective, still seem unclear. Based on few papers comparing osteoporosis in men and women, screenings for osteoporosis are recommended for all men aged 70 or older regardless of risk factors for osteoporosis [15].

The present study was conducted at tertiary care health center in central India SAMC and PG institute Indore (M.P.) from January 2023 to June 2024 after ethical clearance. 81 participants had consented to participate in the study. Patients either had symptoms so that they were subjected to DEXA or they were healthy but wanted to have their bone mineral density (BMD). The present study was an observational cross-sectional study. The age group of the patients was 18 years onwards.

Out of 81 patients, 56.79% (n = 46) were males while 43.21% (n=35) were females. There was male preponderance in the present study and the male to female ratio was 1.3:1. The average age of males was 51.18 years±1.89, while the average age of the females was 51.53years ±1.78. There was no difference in the average age of males and females in the study population [15].

Out of 42 participants below 50 years of age, 7.14% (n = 3) were found to have osteoporosis.

 Although rare, early-onset osteoporosis remains a significant disorder associated with considerable morbidity and presents diagnostic challenges. In cases where genetic causal variants are not identified through high-throughput DNA sequencing, approaches such as transcriptomics, metabolomics, and proteomics should be considered. These enable a multi-omics strategy that can be enhanced through the application of machine learning tools. Identifying the underlying cause not only informs inheritance patterns but also guides treatment options and patient monitoring, which may be beneficial for other potentially susceptible relatives.

The average height of males was 169.8cm±9.13, while the average height of females was 155.34cm±12.2 cm. The mean weight of males in the present study was 72.42kg±14.29 and mean weight of females was 71.65kg±20.21. The Mean BMI in males was 25.48kg/m±4.2 and that of females 28.09kg/m±5.21, suggesting higher BMI in the females than in the males.

Out of the 81 participants in the study population, 43.2% (n=35) belonged to Obese class I while 24.6% (n=20) were included in Obese class II. Only 9.87% (n=8) were overweight. 6.17% (n=5) were underweight while 16.04% (n=13) were having normal BMI.

Total cases of osteoporosis in present study population was 17.28% (n = 14) out of 81. When osteoporosis was correlated with age in the study population, 7.14% (n = 3) were found to have osteoporosis with age up to 50 years. Above 50 years of age 28.21% (n = 11) had osteoporosis. Thus, the odds of osteoporosis in participants of >50 years was 5.1 (CI - 95%) times higher as compared to participants having age <50 years (p value = 0.002). This finding of correlation of osteoporosis with increasing age is statistically highly significant.

Similar to the present study a study done by Minyan Liu, et al [16]. on the effect of age on the changes in BMD and osteoporosis detection rates in Han Chinese men over the age 50 found statistically significant difference from the 50–59 group (p < 0.05); to difference from the 80–89 group (p < 0.05).

When osteoporosis was compared with gender, it was found that out of 46 males, 6.52% (n = 3) had osteoporosis. While among 35 females 31.43% (n = 11) had osteoporosis. Thus, the odds of osteoporosis in females were 6.56 (confidence interval of 95%) times higher as compared to males. (P value=0.007).

In a study done by Neelam Aggarwal, et al [17] at PGIMER Chandigarh on 200 peri and postmenopausal women to determine the prevalence of osteoporosis found prevalence of low BMD in 53%. The mean age in group I (normal BMD) was found to be 50.56±5.74 years as compared to 52.50±5.94 in group II with low BMD (p = 0.02). Multiple logistic regression analysis showed that age, exercise, menopause and low calcium diet acted as significant predictors of low bone density.

There is statistically significant correlation of BMI with osteoporosis in present study. In overweight category, out of n= 8, 37.5% had osteoporosis. While in obesity category 1, out of n= 35, 11.43% had osteoporosis. Whereas in obesity category 2, n = 20, 15% had osteoporosis. In the underweight category (BMI <18.5kg/m) there was 60% (n = 3), while in normal category (BMI <18.5-22kg/m), the burden of osteoporosis was only 7.69% (n = 1)

Pearson chi2 (4) = 10.4173 pr = 0.034. Multivariable Cox proportional hazards analysis revealed that the risk of incident osteoporosis was higher in the underweight group than in the normal weight group.

Our results suggest that BMI is associated with both the increase in prevalence and the incidence of osteoporosis. In addition, underweight is an independent risk factor for developing osteoporosis. These findings highlight the importance of maintaining normal weight for optimal bone health [18].

In the present study, the fat percentage among males and females was correlated with osteoporosis. Out of 44 normal males, osteoporosis was present in 6.82% (n = 3), while in obese males out of 2, none was having osteoporosis. This showed that increasing fat percentage among males did not predispose them to osteoporosis. Pearson chi² (1) = 0.1459 p = 0.703. Similar findings were found among females when osteoporosis was correlated with fat percentage. Out of 34 normal females 29.41% (n = 10) had osteoporosis. While out of 16 obese females only 12.50% (n =2) had osteoporosis. (Pearson chi2 (1) = 0.7060 p = 0.192).

Obesity and osteoporosis are two common complex diseases. Both have multifactorial etiologies including genetic and environmental components, with potential interactions between them. Body mass index (BMI) is widely used as an index of the degree of obesity, primarily because it is easy to measure, but it cannot be used to distinguish body fat from lean mass. Consequently, more refined phenotypes have been proposed for studying obesity, such as fat mass, lean mass, and percentage fat mass. Osteoporosis is a skeletal disease characterized by a reduction in bone mass; it is typically defined in an individual with a bone mineral density (BMD) T-score that is 2.5 or more standard deviations (SD) below normal (T-score ≤ −2.5) [19].

Extensive epidemiological data show that high body weight or BMI is correlated with high bone mass, and that reductions in body weight may cause bone loss [7,13,20]. The basic mechanisms underlying this observed obesity: bone mass correlation remain unclear, though several explanations have been proposed. It is generally accepted that a larger body mass imposes a greater mechanical loading on bone, and that bone mass increases to accommodate the greater load. Further, adipocytes are important sources of estrogen production in postmenopausal women, and estrogen is known to inhibit bone resorption by osteoclasts. It has been proposed that increases in adipose tissue, with increasing BMI in postmenopausal women, results in increased estrogen production, osteoclast suppression, and a resultant increase in bone mass [8]. Finally, obesity has been associated with insulin resistance, characterized by high plasma levels of insulin. High plasma insulin levels may contribute to a variety of abnormalities, including androgen and estrogen overproduction in the ovary, and reduced production of sex hormone- binding globulin by the liver. These changes may result in elevated sex hormone levels, leading to increased bone mass due to reduced osteoclast activity and possibly increased osteoblast activity [9].

Epidemiologic correlation between obesity and bone mass may be explained, in part, by the mechanisms presented above, but further analysis reveals a much more complex relationship [1]. For example, leptin, an adipocyte-secreted peptide that regulates appetite and energy expenditures, is found to have complex effects on bone. A recent study reported that leptin- deficient and leptin receptor-deficient mice had increased bone formation, and that intra- cerebroventricular infusion of leptin causes bone loss in leptin-deficient and wild-type mice [2].

In present study out of 81 participants 6.17% (n = 5) showed osteoporosis in right hip. While, 7.50% (n = 6) showed osteoporosis (t score <-2.5) in left hip.

Singh et al [21], in 2012 found in his study the prevalence of osteoporosis in total hip as 4.26%. Which is lower than present study. The study was done among postmenopausal Indian women using DEXA at Hyderabad. Total 348 women were included in his study.

Matsuzaki et al [22], in 2017 investigated association between hip bone mineral density and BMI in cross sectional study in southern India in 248 participants and found prevalence of osteoporosis to be 14.9%. 384 women were enrolled in this study. When included as a BMI covariate, ANCOVA indicated that the lowest T-scores differed significantly between the right and left hips (P = 0.018). In this study, a significant bilateral difference in hip BMD (g/cm2) was identified at the neck and trochanter areas. BMI could influence the difference between bilateral hip BMD measurements; as BMI increased, the median T-score also tended to increase. The reasons for the discordance of bilateral hip BMD can include genetic variation, immobilization, and pathology such as osteoarthritis [23-25]. Dominance of extremity can be another reason. Moreover, aerobic and strength training exercise can also make the skeletal system stronger. Krahl et al. [12] reported the professional tennis player could develop a stronger and bigger skeleton and a higher BMD in the dominant stroke arm [21].

In present study out of 81 participants, 8.75% (n = 7) had osteoporosis in the wrist, 7.50% (n = 6) had osteoporosis in lumbosacral spine.

Singhet al [22]., in 2012 at Hyderabad in his study of 348 post-menopausal Indian women found 22.07% prevalence of osteoporosis in lumbar spine.

Cherian et al [26-30], studied prevalence of osteoporosis at lumbar spine and found it to be 39% which is higher than the present study.

The present study assessed the burden of osteoporosis in 81 patients above 18 years of age. It was correlated with age, gender and obesity indices. All were subjected to DEXA screening. The study was mainly male predominant (56.79%) with the mean age of 50.7 years. The mean BMI was 26.61 kg/m². The burden of osteoporosis was 17.28%. 31.4% female had osteoporosis as compared to 6.52% males (p = <0.005). When correlated with age >50 years, 28.21% had osteoporosis as compared to 7.14% with age <50 years. Osteoporosis was most common in participants with BMI <18.5kg/m² (60%) followed by BMI 23 - 24.9 (37.50%) and BMI >30 (15%). Increasing fat percentage in males and females did not predispose them to osteoporosis. In 7.50% osteoporosis was found in left hip, 8.75% in wrist and 7.50% in spine.

Acknowledgement

We sincerely thank Sri Aurobindo Medical College and Postgraduate Institute, Indore, for their support and facilities. We are grateful to the Institutional Ethical Committee (IEC NO: SAIMS/RC/IEC/98/25) for ethical approval. We deeply appreciate the participants for their cooperation in undergoing DEXA scans. We also acknowledge the Endocrinology Department for their expertise and the statistical team for their assistance with data analysis using STATA version 13. Finally, I profusely express my gratitude to professor & head Dr. Subodh Banzal for his constant support and encouragement and professor, Dr. Jitendra Chouhan for his insights and valuable inputs in the research. I would like to thank Dr. Siddharth Pandey my friend and colleague for being a source of strength. A big thank you to Dr. Akshay Narayan Ambekar for his guidance and friendship.

Funding Information

No funding is required for the present study.

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