Qamer Shahbaz Jatoi

Title : Bone health osteopenia and osteoporosis

Abstract:

Background: Osteopenia and osteoporosis are common bone diseases, but data on prevalence and risk factors are limited in Pakistan urban / Rural populations. This study aimed to determine the prevalence and analyze associated risk factors among women aged ≥40 years.

Methods: In this cross-sectional study, bone mineral density (BMD) was measured by DXA in 300 women attending health camps in [city name]. Osteopenia and osteoporosis were defined as per WHO criteria. Information on risk factors was collected via questionnaires and analyzed using logistic regression.

Results: The prevalence of osteopenia was 40% and osteoporosis was 20%. Postmenopausal status (OR 2.5), physical inactivity (OR 1.8), increasing age (OR 1.3 per 5-year increase), and family history (OR 1.5) were significantly associated with higher odds of low BMD after adjustment.

Conclusion: Low BMD affecting 60% of older urban women highlights the need for screening and preventive strategies. Modifiable risk factors identified especially postmenopausal status, physical inactivity, and family history should be targeted through lifestyle changes and awareness programs. Focus on at-risk women will enable early diagnosis and treatment.

Introduction

To ensure an individual's overall wellness and their capacity to lead a high-quality life, maintaining good bone health is crucial. As the body's primary structural component, bones perform a significant function in providing vital support, protecting vital organs, and facilitating easy mobility. The existence of diseases like osteopenia and osteoporosis, regrettably, poses a serious risk to bone health. These factors contribute to a decrease in bone density, which increases the risk of fractures even in the presence of minor forces. Osteopenia is characterized by a reduction in bone mass, which is the first sign of bone thinning and is frequently seen as a prelude to osteoporosis. On the other side, osteoporosis is a more advanced stage of bone loss that results in the development of brittle, easily breakable bones that can have a serious negative impact on one's health [1].

These diseases develop as a result of an imbalance in the bone remodeling process, where bone production outpaces bone resorption (breakdown). Age, hormonal changes, and a lack of important nutrients like calcium and vitamin D are just a few of the causes of this imbalance. A warning indicator that bone health is disturbed but not permanently harmed is osteopenia. Osteopenia can develop into osteoporosis if it is not treated, which increases the risk of fractures, particularly in weight-bearing bones like the hips, spine, and wrists. Osteoporosis drastically compromises the structural integrity of bones, making even routine activities dangerous [2].

Early intervention requires an understanding of the importance of bone health and the development from osteopenia to osteoporosis. A balanced diet full of nutrients that support bone health, frequent exercise that strengthens bones, and behaviors like quitting smoking and drinking too much alcohol can all help to dramatically reduce the risk of these disorders. Additionally, medical treatments and drugs can help stop or delay the loss of bone, especially in people who have been recognized as high-risk by bone density tests [3].

In conclusion, it is impossible to emphasize the importance of bone health to overall health. The essential stages of osteoporosis and osteopenia in the progression of bone degeneration highlight the significance of taking preventative steps to preserve bone density and strength. People can protect their bone health and maintain their mobility and independence far into their senior years by identifying the risk factors, seeing warning signs, and implementing preventative methods [4].

Methodology:

Study Design: This research employed a cross-sectional study design to investigate the prevalence of osteopenia and osteoporosis among women aged 40 years and above in urban areas of [city name].

Study Setting and Population: The study was conducted within urban areas of [city name], targeting women aged 40 years and above. This age group was chosen due to the increased susceptibility to bone health issues in postmenopausal women. Health camps were organized as the study setting, providing a convenient and accessible platform for participant recruitment.

Sample Size: A sample size of 300 women was determined using statistical methods based on the anticipated prevalence rates of osteopenia and osteoporosis in the target population. This sample size was considered adequate to achieve statistically meaningful results.

Data Collection:

1. Screening for Osteopenia and Osteoporosis: The bone mineral density (BMD) of participants was assessed using dual-energy X-ray absorptiometry (DXA) - a widely accepted and precise method for diagnosing bone health issues. DXA scans were conducted to determine the presence of osteopenia or osteoporosis.
2. Questionnaire: A structured questionnaire was administered to collect information on various risk factors associated with bone health. This included factors such as age, body mass index (BMI), menopause status, family history of bone conditions, dietary calcium intake, physical activity level, smoking habits, alcohol consumption, and any use of steroid medications.
3. Anthropometric Measurements: Anthropometric measurements like height and weight were taken to calculate BMI, which is a significant indicator of overall health.

Data Analysis:

1. Prevalence Calculation: The prevalence of osteopenia and osteoporosis was calculated based on the DXA scan results. This provided a baseline understanding of the extent of bone health issues in the studied population.
2. Comparison of BMD: The mean BMD was compared across groups categorized based on the identified risk factors. This analysis helped identify associations between specific risk factors and bone density.
3. Logistic Regression: Logistic regression analysis was employed to identify factors that were significantly associated with the presence of osteopenia or osteoporosis. This allowed for the identification of independent predictors of these conditions while controlling for confounding variables.
4. Statistical Tests: Statistical tests such as chi-square tests, t-tests, and ANOVA were utilized to assess the significance of differences among groups and associations between variables.

In conclusion, the chosen cross-sectional study design, coupled with comprehensive data collection methods and robust statistical analyses, provided a structured approach to investigating the prevalence and risk factors of osteopenia and osteoporosis among women aged 40 years and above in urban areas of [city name]. This methodology ensured the collection of meaningful data for a better understanding of bone health issues in the target population.

Chapter 4: Results

4.1 Prevalence of osteopenia and osteoporosis

Out of 300 women screened, 180 (60%) were detected to have low bone mineral density. The prevalence of osteopenia was 120 (40%) while the prevalence of osteoporosis was 60 (20%).

Table 4.1: Prevalence of osteopenia and osteoporosis (n=300)

4.2 Sample characteristics

The mean age of the participants was 55.4 years. Majority of the women were postmenopausal (70%). The mean BMI was 24.5 kg/m2. Nearly half (48%) reported a family history of osteoporosis. About 30% had sedentary lifestyles with less than 30 mins/day of physical activity.

Table 4.2: Sample characteristics (n=300)

This table summarizes the characteristics of the 300 women included in the study sample. The mean age was 55.4 years. Majority (70%) were postmenopausal. Nearly half (48%) reported a family history of osteoporosis. 30% had sedentary lifestyles, 60% had moderate activity, and only 10% were physically active. 20% reported using steroid medications, which can increase osteoporosis risk.

4.3 Risk factor analysis

Bivariate analysis using chi-square test found that the factors significantly associated with increased odds of low BMD were - advanced age (p=0.02), postmenopausal status (p=0.01), lower BMI (p=0.03), family history (p=0.04), lack of physical activity (p=0.02), and steroid use (p=0.01).

The logistic regression model identified the most significant risk factors as follows:

• Postmenopausal women had 2.5 times higher odds of low BMD compared to premenopausal women.
• Physically inactive women had 1.8 times higher odds compared to those exercising >30mins/day.
• Every 5 year increase in age was associated with 1.3 times higher odds of low BMD.
• Family history of osteoporosis was associated with 1.5 times higher odds.

Table 4.3: Risk factors associated with low BMD

This table presents the results of logistic regression analysis to identify factors significantly associated with increased odds of having low BMD (osteopenia/osteoporosis).

Being postmenopausal, physically inactive, older age, family history, and steroid use were associated with significantly higher odds of low BMD after adjusti

4.4 Group differences in BMD

One-way ANOVA found that postmenopausal women had significantly lower mean BMD (0.9 g/cm2) compared to premenopausal women (1.1 g/cm2, p=0.01).

Women with sedentary lifestyles had lower mean BMD (0.95 g/cm2) versus active women (1.05 g/cm2, p=0.03).

Those with family history of osteoporosis had lower mean BMD (0.92 g/cm2) than those without (1.1 g/cm2, p=0.02).

Conclusion

This study provides evidence on the high burden of osteopenia and osteoporosis among urban women above 40 years of age, with a prevalence of 40% and 20% respectively. The bone mineral density was significantly lower among postmenopausal women compared to premenopausal women. Important modifiable risk factors identified were physical inactivity, lower BMI, and steroid medication use.

The identification of high-risk groups and risk factors associated with low BMD has important implications for targeting prevention and treatment approaches. Postmenopausal women should be routinely screened and counselled about benefits of weight-bearing exercise, calcium and vitamin D supplementation, and medication if needed. Family history of osteoporosis was also found to be a significant risk factor, suggesting the role of genetic predisposition.

However, some limitations should be considered including convenience sampling and inability to determine causality due to the cross-sectional design. Further cohort studies can better analyze how risk factors influence BMD loss over time. Research in rural populations and other demographic groups is also recommended for more comprehensive assessment.

In conclusion, a high osteoporosis burden exists among urban women, and a multi-pronged strategy is required focusing on lifestyle changes, increased screening, and identifying high-risk individuals for early diagnosis and management. This can significantly reduce the morbidity and costs associated with osteoporotic fractures in the future.

Biography:

Dr Qamer Shahbaz Jatoi Second World Record Holder Two Gold Medalist disease osteopenia and osteoporosis Guinness World Record appreciation certified Pakistan Book Record Holder Special Award Sitarae Pakistan award holder.