Osteoporosis, a skeletal disorder characterized by reduced bone mass and deteriorating bone micro architecture, presents a growing global health challenge, particularly among postmenopausal women^{. [1,2]} With an aging population, understanding the incidence and risk factors associated with this condition is of paramount importance for effective healthcare planning and intervention strategies. ^[3,4] In India, as in many other countries, postmenopausal osteoporosis is a significant concern due to its potential to result in debilitating fractures and a substantial burden on the healthcare system.[3] The prevalence of osteoporosis varies across regions and populations, influenced by genetic, environmental, and lifestyle factors. ^[5,6]

The district of Barabanki in Uttar Pradesh, situated in India, offers a unique setting for investigating the prevalence and determinants of osteoporosis among postmenopausal women. The region's distinct demographics and dietary habits, combined with limited prior research in this specific population, underscore the need for comprehensive studies to address this critical public health issue.

This study aims to contribute to the existing literature by providing valuable insights into the incidence of osteoporosis and identifying risk factors specific to postmenopausal women in Barabanki district. By assessing variables such as age, body mass index (BMI), family history, calcium intake, vitamin D levels, physical activity, smoking status, alcohol consumption, hormone replacement therapy (HRT) usage, and socioeconomic status, we seek to uncover the key determinants associated with osteoporosis in this region.

Furthermore, subgroup analyses will explore the potential protective effects of HRT usage and the influence of socioeconomic disparities on osteoporosis incidence. Such findings have the potential to inform targeted prevention and management strategies that can mitigate the impact of osteoporosis on the health and well-being of postmenopausal women in Barabanki and similar regions.

Study Setting and Participants

The study was conducted at the Hind Institute of Medical Sciences, located in Barabanki, Uttar Pradesh, India. The hospital serves as a tertiary care teaching hospital and offers comprehensive healthcare services to the local population. The target population for this research comprised postmenopausal women residing in Barabanki district, who sought medical care or services at the study setting during the study duration.

Study Design

This research employed a cross-sectional study design to assess the incidence and risk factors associated with osteoporosis among postmenopausal women. Cross-sectional studies are well-suited for investigating the prevalence of a condition and exploring its relationships with various factors within a defined population.

Sample Size and Selection

A total of 100 postmenopausal women were recruited as study participants. The inclusion criteria for participants were as follows: being postmenopausal (defined as the absence of menstrual periods for at least 12 consecutive months), aged between 51 and 78 years, and providing informed consent to participate in the study. Convenience sampling was employed to enroll participants from the hospital's outpatient department, ensuring representation across different age groups.

Data Collection

Data collection took place between January 2023 and June 2023. The following data collection procedures were implemented:

Demographic Data: Participants' demographic information, including age, ethnicity (primarily Hindi-speaking), and place of residence, was recorded.

Clinical Assessment: Bone Mineral Density (BMD) tests were conducted to diagnose osteoporosis. Dual-energy X-ray absorptiometry (DXA) scans were performed, following standard protocols, to measure BMD at the lumbar spine and hip. Risk Factor Assessment: Participants' risk factors for osteoporosis were assessed through structured interviews and medical record reviews. This included gathering information on family history of osteoporosis, calcium intake, vitamin D levels, physical activity levels, smoking status, alcohol consumption, hormone replacement therapy (HRT) usage, and socioeconomic status^.[7]

Statistical Analysis

Data were analyzed using appropriate statistical methods. Descriptive statistics such as means, percentages, and standard deviations were computed for demographic variables. The incidence of osteoporosis was calculated as a percentage. Odds Ratios (ORs) with 95% Confidence Intervals (CIs) were used to quantify the association between risk factors and osteoporosis incidence. P-values were calculated to assess statistical significance.

Ethical Considerations

The study was conducted in accordance with ethical guidelines and standards. Informed consent was obtained from all participants. The study protocol was reviewed and necessary permissions taken from concerned authorities.

Study Population

The study recruited 100 postmenopausal women from the Barabanki district, Uttar Pradesh. The age range of participants was 51 to 78 years, with a mean age of 64 years. All participants were of predominantly Hindi-speaking.

Incidence of Osteoporosis

The overall incidence of osteoporosis in the study population was 40%. When stratified by age, the incidence varied significantly: 20% in ages 51-60 (10 out of 50 participants), 50% in ages 61-70 (25 out of 50 participants), and 70% in ages 71-78 (5 out of 10 participants). This variation indicates a marked increase in osteoporosis incidence with advancing age.

Risk Factors for Osteoporosis

Several risk factors were significantly associated with the incidence of osteoporosis:

Age: Women aged 65 and above had an Odds Ratio (OR) of 3.8 (95% CI: 2.0-7.1), indicating a substantially increased risk.

Body Mass Index (BMI): Participants with a BMI less than 18.5 had an OR of 4.5 (95% CI: 2.5-8.0), suggesting a strong association between lower BMI and osteoporosis.

Family History: A positive family history of osteoporosis was associated with an OR of 3.3 (95% CI: 1.8-6.0).

Calcium Intake: Daily calcium intake below 400 mg was significantly associated with osteoporosis (p<0.001).

Vitamin D Levels: Insufficient levels (<12 ng/mL) showed an OR of 3.5 (95% CI: 1.9-6.3).

Physical Activity: Low levels of physical activity were significantly correlated with osteoporosis (p<0.001).

Smoking Status: Current smokers had an increased risk with an OR of 2.5 (95% CI: 1.3-4.7).

Alcohol Consumption: This factor did not show a significant association with osteoporosis in the studied population.

Other Observations

No significant associations were observed between osteoporosis incidence and ethnicity, previous fracture history, or education level, although there was a slight but non-significant trend towards a lower incidence in women with higher education levels.

Subgroup Analysis

Hormone Replacement Therapy (HRT) Usage: Women who had undergone HRT exhibited a 30% lower incidence of osteoporosis compared to non-users, a statistically significant finding (p<0.05).

Socioeconomic Status: Lower socioeconomic status was correlated with a higher incidence of osteoporosis (p<0.01).

Figure 1: Incidence of Osteoporosis by Age Group

Figure 2: Odds Ratio for Risk Factors Associated with Osteoporosis

Table 1: Study Population Demographics

Table 2: Incidence of Osteoporosis by Age Group

Table 3: Risk Factors Associated with Osteoporosis

Table 4: Other Observations

Table 5: Subgroup Analysis

The study on osteoporosis among postmenopausal women in Barabanki district, Uttar Pradesh, India, reveals a significant incidence rate of 40%, which notably increases to 70% in the 71-78 age group. This prevalence pattern aligns with global trends of higher osteoporosis rates in older populations, suggesting the necessity for age-focused interventions. ^[8,9]

Age is a significant risk factor, as women aged 65 and above are at a 3.8-fold increased risk, demonstrating the progressive nature of osteoporosis and underscoring the need for early detection and intervention^.[10] Moreover, a low Body Mass Index (BMI) below 18.5 is strongly correlated with osteoporosis, showing an odds ratio of 4.5. This finding highlights the crucial role of nutrition and weight management in maintaining bone health^.[11]

Genetic factors are also evident, with a positive family history of osteoporosis suggesting a genetic predisposition. The study further emphasizes the importance of dietary habits, particularly adequate calcium and vitamin D intake, in osteoporosis prevention. Low physical activity and smoking are identified as modifiable risk factors, reinforcing the importance of a healthy lifestyle in risk reduction^.[12]

Hormone Replacement Therapy (HRT) is shown to have a protective effect, with a 30% lower incidence of osteoporosis among women who underwent HRT, supporting existing literature on its bone health benefits. Socioeconomic status, while not statistically significant, emerged as a potential factor, indicating the need for further investigation into healthcare access and nutritional disparities. ^[13]

These insights are consistent with Aggarwal et al. (2011), who also observed the prevalence and risk factors of osteoporosis in Indian women, highlighting the urgency for comprehensive healthcare strategies to tackle this issue^.[14]

Implications and Interventions

The findings of this study have important implications for public health interventions in Barabanki district. Targeted strategies should focus on early screening, especially among older postmenopausal women, and the promotion of a balanced diet rich in calcium and vitamin D. Encouraging physical activity and smoking cessation should be integral components of osteoporosis prevention programs. Furthermore, the potential benefits of HRT in reducing osteoporosis risk merit further research and consideration in clinical practice.

This investigation illuminates the elevated prevalence of osteoporosis within the postmenopausal female demographic in Barabanki district. Furthermore, it elucidates critical determinants of this condition. These outcomes possess the potential to guide the development of healthcare strategies and initiatives targeted at the mitigation and control of osteoporosis in this specific cohort. Ultimately, such endeavors hold promise for augmenting the well-being and health-related outcomes of postmenopausal women in the studied region.

1. Franic D, Verdenik I. Risk Factors for Osteoporosis in Postmenopausal Women - from The Point of View of Primary Care Gynecologist. Zdr Varst. 2018 Jan 5;57(1):33-38. doi: 10.2478/sjph-2018-0005. PMID: 29651313; PMCID: PMC5894367.
2. Ibrahim AI, Sodipo OO, Oduniyi OA. Risk factors for osteoporosis among postmenopausal women in a Nigerian teaching hospital. Journal of Family Medicine and Primary Care 12(6): p 1145-1149, June 2023. | DOI: 10.4103/jfmpc.jfmpc_2193_21.
3. Sun M, Zhang Y, Shen H, Sun K, Qi B, Yu C, Zhi Y, Zhang R, Jiang J, Chai Y, Wei X, Xie Y. Prevalence of and Risk Factors for Community-Based Osteoporosis and Associated Fractures in Beijing: Study Protocol for a Cross-Sectional and Prospective Study. Front Med. 2020; 7:544697. doi: 10.3389/fmed.2020.544697.
4. Lee JH, Sung YK, Choi CB, et al. The frequency of and risk factors for osteoporosis in Korean patients with rheumatoid arthritis. BMC Musculoskelet Disord. 2016; 17:98. https://doi.org/10.1186/s12891-016-0952-8.
5. YounesiAsl L, Kashanian M, Najmi Z, Mahdavi A, SafarpourLima Z. Risk factors of osteoporosis and osteopenia in postmenopausal women based on the L2–L4 BMD T score of the lumbar spine: a study in Iran. Gynecological Endocrinology. 2023;39(1). DOI: 10.1080/09513590.2023.2205959.
6. Zheng M, Wan Y, Liu G, et al. Differences in the prevalence and risk factors of osteoporosis in Chinese urban and rural regions: a cross-sectional study. BMC Musculoskelet Disord. 2023; 24:46. https://doi.org/10.1186/s12891-023-06147-w.
7. Thangappah RB, Madhavan TMV, Dharmalingam P, Palanisamy A, Senthilkumar MAP. A community-based study to evaluate the prevalence and risk factors for osteoporosis among menopausal and pre-menopausal women. Int J Reprod Contracept Obstet Gynecol. 2022 Nov;11(11):10.18203/2320-1770.ijrcog20222811.
8. Yurgin N, Wade S, Satram-Hoang S, Macarios D, Hochberg M. Prevalence of Fracture Risk Factors in Postmenopausal Women Enrolled in the POSSIBLE US Treatment Cohort. International Journal of Endocrinology. 2013; 2013:715025. https://doi.org/10.1155/2013/715025.
9. Hyassat D, Alyan T, Jaddou H, Ajlouni KM. Prevalence and Risk Factors of Osteoporosis Among Jordanian Postmenopausal Women Attending the National Center for Diabetes, Endocrinology and Genetics in Jordan. BioResearch Open Access. 2017;6(1):85-93.
10. Imran M, Singh A, Bhardwaj A, Agrawal D. Prevalence of Osteoporosis and Associated Risk Factors among Postmenopausal Women: A Cross-Sectional Study from Northern India. J Midlife Health. 2022 Jul-Sep;13(3):206-212. doi: 10.4103/jmh.jmh_114_22. Epub 2023 Jan 14. PMID: 36950199; PMCID: PMC10025819.
11. Kim J, Lim SY, Kim JH. Nutrient intake risk factors of osteoporosis in postmenopausal women. Asia Pac J Clin Nutr. 2008;17(2):270-5. PMID: 18586647.
12. Thomas BM, Kuriakose A, Joseph JJ, George N, Ashok P. A study on prevalence of risk factors for osteoporosis in Postmenopausal women and the importance of Osteoporosis self-assessment tool (OST) in identifying osteoporotic risk. JDDT [Internet]. 2021 Mar 15;11(2):63-7.
13. Choi MH, Yang JH, Seo JS, Kim YJ, Kang SW. Prevalence and diagnosis experience of osteoporosis in postmenopausal women over 50: Focusing on socioeconomic factors. PLoS One. 2021 Mar 2;16(3): e0248020. doi: 10.1371/journal.pone.0248020. PMID: 33651848; PMCID: PMC7924764.
14. Aggarwal N, Raveendran A, Khandelwal N, Sen RK, Thakur JS, Dhaliwal. Prevalence and related risk factors of osteoporosis in peri- and postmenopausal Indian women. J Midlife Health. 2011 Jul;2(2):81-5. doi: 10.4103/0976-7800.92537. PMID: 22408337; PMCID: PMC3296391.