PREVALENCE OF OSTEOPOROSIS AND ITS CORRELATION WITH COMMON SECONDARY RISK FACTORS IN POPULATION FROM RURAL AREAS OF SOUTH INDIA

Abstract

ABSTRACT:

Osteoporosis is a common metabolic disorder characterised by decreased bone mass and weakened micro-architecture of bone tissue. In 2014 Osteoporosis international estimated osteoporosis to be one of the leading causes of disability, depression, and early mortality in the elderly. After 50 years of age, 1 in 3 women and 1 in 5 men experience osteoporotic fractures. This is projected to cause a yearly loss of 5.8 million healthy life years to disability. The number of patients who attend the outpatient clinic and emergency department of Sanjay Gandhi institute of trauma and orthopaedics with fragility fractures has been increasing, hence to know the prevalence of osteoporosis in the general population who were asymptomatic, we decided to conduct a study in the rural areas of south India.

RESULTS:

The prevalence of osteoporosis in the rural population was more in females at 42.2%, whereas the males had a prevalence of 32.5%. Among the population with habits of tobacco consumption and alcohol consumption, the prevalence was 78% and 30.6% respectively. 20.2 % of non-smokers and 39.7% of non-alcoholics were osteoporotic. Among the population with comorbidities, 53.6% of diabetes and 55.4% of hypertensives were osteoporotic. 33.7% of non-diabetics were osteoporotic, and 29.5% of hypertensives were osteoporotic. The correlation between osteoporosis and the individual risk factors ranged between weak negative to moderately positive. (r = - 0.2 to 0.5). The correlation between the combination of all the four risk factors and osteoporosis is weakly positive (r = 0.339), which is highly significant (p-value = <0.001).

CONCLUSION:

The prevalence of osteoporosis is high in rural populations over 50 years. There is a significant positive correlation between osteoporosis and secondary risk factors like smoking, tobacco chewing, alcohol consumption, diabetes, and hypertension.

Full Text

INTRODUCTION:

Osteoporosis is a common metabolic disorder characterised by decreased bone mass and weakened micro-architecture of bone tissue. This makes the bone highly prone to pathological fractures.^1,2 It is only after the fracture that the condition is diagnosed more often, and measurement of Bone Mineral Density (BMD) can diagnose Osteoporosis and identify the population at risk for fractures.^1,3 

The global burden of Osteoporosis is enormous. It has been recognised as a worldwide epidemic. In 2014 Osteoporosis international estimated osteoporosis to be one of the leading causes of disability, depression, and early mortality in the elderly. After age 50, 1 in 3 women and 1 in 5 men experience osteoporotic fractures. This is projected to cause a yearly loss of 5.8 million healthy life years to disability. There is about a 30 % rise in mortality in the first year after fracture, which remains high for up to 5 years. The economic burden has been 37 billion EUR in the EU and 19 billion USD in the USA.⁴ In 2014, it was reported in Europe that socioeconomic status and poverty have a bearing on the prevalence of Osteoporosis.⁵

Having a different landscape, India has a different socio-economy and lifestyle. Even within the country, there is much diversity between urban and rural life. In 2012 Rex estimated that Osteoporosis would affect half of the Indian population by 2022.⁶

The USA and Europe have been significant contributors to research in Osteoporosis, with 27% and 8.2% of global publications, respectively. India could merely contribute 2% of the world's research on osteoporosis.⁷ An article in 2015 reviewed a few sporadic studies on Osteoporosis in Indian women and noted a high prevalence of the disease in postmenopausal women.⁸

Sanjay Gandhi institute of trauma and orthopaedics is a tertiary care hospital; the number of patients who attend the outpatient clinic and emergency department of Sanjay Gandhi institute of trauma and orthopaedics with fragility fractures has been increasing, hence to know the prevalence of osteoporosis in the general population who were asymptomatic, we decided to conduct a study in the rural areas of south India. 

Aims and Objectives:

1. To estimate the prevalence of Osteoporosis among the population above 50 years in rural areas of south India.
2. To determine the correlation between common secondary risk factors for Osteoporosis like tobacco consumption, alcohol, diabetes, and hypertension.

Methods and Materials:

        A cross-sectional study on the prevalence of osteoporosis was planned over one year (i.e., September 2021 to august 2022) as there was an increased incidence of fragility fractures in the population attending the outpatient clinic and emergency department. Ten random villages were selected by cluster sampling in villages from Karnataka, Andhra Pradesh, and Tamilnadu. In each village, 100 people aged 50 and above were enrolled for the study. Inclusion criteria include Men and women aged 50 and above. Exclusion criteria include those having other causes affecting bone strength like malignancy, Paget’s disease, congenital disorders, osteomyelitis etc. Consenting participants were interviewed and examined. The tools used in this study were a 2 part proforma and BMD measuring portable SONOST 3000 Ultrasound machine. Those subjects with low BMD were classified accordingly as Osteopenia (BMD -1 to -2.5) or Osteoporosis (BMD -2.5 or less). Obtained data is analysed using SPSS software. The categorical variables were analysed using percentages, and the one-tailed Pearson correlation coefficient test was used for correlation. The continuous variables were analysed by calculating the mean ± standard deviation. A P-value < 0.05 was considered statistically significant.

QUANTITATIVE ULTRASOUND [QUS] BONE DENSITOMETER:

    A heel BMD was estimated in all the subjects using a QUS bone densitometer. A quality assurance test for the device was performed on each screening day. The measurements were carried out in a room by a single technician to complete the entire test on all the subjects.

SOCIO-DEMOGRAPHIC FACTORS:  

The total number of subjects considered in the study was 1000, of which people who participated in the study were males (536, which accounts for 53.6%); the rest were females (464, which accounts for 46.4%). Most of the people who participated in the study were 50-60 years old, accounting for 52.9%.

ADDICTIVE HABITS AND COMORBIDITIES:

Habits that were considered in the study

• Tobacco consumption (smoking/smokeless)
• Alcohol

comorbidities considered in the study

• Diabetes
• Hypertension

In this study, among the total population, 29.1% of the population consumes tobacco, of which 82% are males, and 18% are females. 29.7% of the population drinks alcohol, of which 91.95% of males and 8.05% are females. In the study population, 9.2% of men and 7.6% of women had diabetes, 16.8% of people with diabetes and 16.2% of men, and 12.7% of women were hypertensive, consisting of a total of 28.9% of hypertensives. 

OSTEOPENIA:

Out of the total population considered for this study, 512 were Osteopenic. 45.5% of males and 57.8% of Females were osteopenic. Among the people suffering from osteopenia, 65.7 % were between 51-60 years.

Among the population with addictive habits, 2.7% of tobacco consumers and 69.4% of alcoholics are osteopenic.

Among the population with comorbidities, 13.1% of people with diabetes and 44.6 % of the hypertensive population were osteopenic.

OSTEOPOROSIS:

In this study, out of the total study population, 370 people were osteoporotic. In this population, 53.0% who were Osteoporotic are between 50-60 years. The prevalence of osteoporosis in the rural population was more in females at 42.2%, whereas the males had a prevalence of 32.5%.

Among the population with the habit of tobacco consumption, 78% were osteoporotic, and in those with the habit of consuming alcohol, 30.6% were osteoporotic. 20.2 % of non-smokers and 39.7% of non-alcoholics were osteoporotic.

Among the population with comorbidities, 53.6% of people with diabetes were osteoporotic, and 55.4% of hypertensives were osteoporotic. 33.7% of non-diabetics were osteoporotic, and 29.5% of hypertensives were osteoporotic.

  Statistical analysis of the data shows Pearson correlation between osteoporosis and tobacco usage shows a moderately positive correlation(r=0.544), which is highly significant (P-value = <0.001). Correlation between osteoporosis and alcohol consumption is weakly negative (r= -0.086), which is highly significant (p-value = 0.007). Correlation between osteoporosis and diabetes is weakly positive (r = 0.154), which is highly significant (P-value = <0.001). Correlation between osteoporosis and hypertension is weakly positive (r= 0.242), which is highly significant (P-value = <0.001).

  The correlation between osteoporosis and the individual risk factors ranged between weak negative to moderately positive. 

The correlation between the combination of all the four risk factors and osteoporosis is weakly positive (r = 0.339), which is highly significant (p-value = <0.001).

DISCUSSION:

Osteoporosis is a skeletal disease characterised by decreased bone mass per volume associated with microarchitectural deterioration of the bone tissue resulting in bone fragility and increased risk of fracture.¹ another variant of low bone mass density is osteopenia, which is defined as a condition with low BMD but of less severity when compared to that of Osteoporosis. Osteoporosis is most commonly seen in the elderly, with females being most commonly affected compared to males.² Whereas osteopenia is seen in younger age groups with no gender inequality.³

The burden of Osteoporosis in the INDIA population is around 40% as the population living in INDIA is mainly from a rural background and has low BMD compared to the western population of the same age and gender. The maximum loss of bone density is observed in the fourth decade of life and early postmenopausal years.⁴

Chronic bone pain, disability, and peritrochanteric and vertebral fractures are common among the osteoporotic elderly population, leading to severe functional limitations and decreasing the quality of life.⁵ Pneumonia, urinary tract infections [UTI], pressure sores (mainly nonhealing ulcers), and Deep Vein Thrombosis contribute to worsening the prognosis among the osteoporotic elderly population. The common sites of osteoporotic fractures following minimal trauma are vertebra, distal radius, and peritrochanteric fractures due to lack of osteoid in sufficient quantity that leads to rapid bone loss.⁶Osteoporosis is mostly asymptomatic; on the other hand, in symptomatic patients, vague, diffuse low backache is the most common symptom.⁷

As stated by Ahmad M. Al-Bashaireh, consuming tobacco has been associated with reduced bone mass and increased risk of fracture through its direct or indirect effects on osteoblast and osteoclast activities. Recent studies have indicated that even low-level exposure to cadmium could increase the risk of osteoporosis and fractures.⁸ women are four times more prone to osteoporosis and two times more prone to osteopenia.⁹  Diabetes mellitus increases osteoclast function but decreases osteoblast function, leading to accelerated bone loss, osteopenia and osteoporosis.¹⁰ In hypertension patients, excess urinary calcium secretion induces secondary parathyroidism to increase the serum calcium level by calcium release from bone, which may accelerate osteoporosis.¹¹ Alcohol use decreases bone density and weakens bones' mechanical properties.¹²

Diagnosing Osteoporosis is a significant step in its management. Diagnosing Osteoporosis at the gross root level is far better to avoid the consequences like fractures and deterioration of life quality among the rural population.¹³ Despite being the most common problem among the rural and urban population in INDIA, there is no Cohesive National Policy on screening and prevention policy and programs.

Various tools are available nowadays for diagnosing Osteoporosis, like DEXA scan, India-specific FRAX tool, etc.^1,3,4,14 among all India-specific FRAX tool is gaining popularity in risk prediction of 10-year probability of osteoporotic fracture. Due to a lack of awareness on health education, lack of internet facilities, etc., it is still of limited use.

LIMITATIONS:

In this study, we have used only one tool for assessing the bone mass density for grading the patient depending on feasibility.

CONFLICTS OF INTEREST:

There are no conflicts of interest.

IMPACT:

     The study will attempt to provide data regarding osteoporosis affection of the population in this region. It will surely increase the awareness of the level of Bone mineral density in our elderly population. This can be useful for guiding regional and government resource allocation.

REFERENCES:

1. Osteoporosis. Rockwood and Green’s Fractures in adults Vol.1; 8th ed; 2015; chapter 19; p 609-610.

2. Srivastava, M., & Deal, C. (2002). Osteoporosis in elderly: prevention and treatment. Clinics in Geriatric Medicine, 18(3), 529–555. doi:10.1016/s0749-0690(02)00022-8 

3. Ross PD. Osteoporosis frequency, consequences, and risk factors. Archives of Internal medicine, 156 (13) (1996) 1399-1411.

4. The global burden of Osteoporosis: a factsheet; iofboneheath.com

5. María-Jesús-Gómez-de-TejadaRomero¹, María-del-CarmenNavarro Rodríguez ², Pedro Saavedra Santana ³, José-Manuel Quesada Gómez ⁴, Esteban Jódar Gimeno ⁵, Manuel Sosa Henríquez ⁶Prevalence of Osteoporosis, vertebral fractures and hypovitaminosis D in postmenopausal women living in a rural environment.  2014 Mar;77(3):282-6.

6. Rex C. 50% of India to suffer from Osteoporosis: Study, Indian Express (2012), Accessible at http://www.indianexpress.com/news/50-of0indians-to-suffer-from-osteoporosos-study/1019739/ (Accessedon 20 September 2013).

7. Bharadwaj et al. Mapping of Indian research on Osteoporosis; Annals of Library and Information studies.Vol 60,Dec2013,p 276-283.

8. Akesson A, Barregard L, Bergdahl IA, Nordberg GF, Nordberg M, Skerfving S. Non-renal effects and the risk assessment of environmental cadmium exposure. Environ Health Perspect. 2014; 122(5): 431– 8.

9. Alswat, Khaled A. “Gender Disparities in Osteoporosis.” Journal of clinical medicine research vol. 9,5 (2017): 382-387. doi:10.14740/jocmr2970w

10. Osteoporosis in diabetes mellitus: Possible cellular and molecular mechanisms Kannikar Wongdee and Narattaphol Charoenphandhu World J Diabetes. 2011 Mar 15; 2(3): 41–48. Published online 2011 Mar 15. DOI: 4239/wjd.v2.i3.41

11. Clin 2013 Apr;23(4):497-503 [Hypertension and osteoporosis] Hironori Nakagami 1 , Ryuichi Morishita

12. Alcohol and Other Factors Affecting Osteoporosis Risk in Women,H. Wayne Sampson, PhD, is a professor of human anatomy and medical neurobiology and nutrition at Texas A&M University System Health Science Center, College of Medicine, College Station, Texas.

13. Anuradha V Khadilkar, Rubina M mandlik; Epidemiology and treatment of Osteoporosis in women: an Indian perspective.; International Journal of Women’s Health, 2015:7 p 841-850.
14. Sherry. Metabolic bone diseases. Mercer’s Textbook of Orthopaedics and Trauma; 10th ed; chapter 6; p94

Gender	Frequency	Percent
MALE	536	53.6%
FEMALE	464	46.4%
Total	1000	100%

 Table 1. Gender-wise distribution of population

Table 2. Tobacco usage

ALCOHOL CONSUMPTION	Frequency	Percent
YES	297	29.7%
NO	703	70.3%
Total	1000	100%

Tab

le 3. Alcohol consumption

DIABETES	Frequency	Percent
YES	168	16.8%
NO	832	83.2%
Total	1000	100%

Table 4. Prevalence of diabetes in the study population

HYPERTENSION	Frequency	Percent
YES	289	28.9%
NO	711	71.1%
Total	1000	100%

Table 5. Prevalence of hypertension in the study population

OSTEOPOROSIS	Frequency	Percent
YES	370	37.0%
NO	630	63.0%
Total	1000	100%

Table 6. Prevalence of osteoporosis in the study population

OSTEOPOROSIS		GENDER		Total
		MALE	FEMALE
YES	Count	174	196	370
	% within GENDER	32.5%	42.2%	37.0%
NO	Count	362	268	630
	% within GENDER	67.5%	57.8%	63.0%
Table 7. Gender wise prevalance of osteoporosis in the study population

OSTEOPOROSIS		ALCOHOL		Total
		YES	NO
YES	Count	91	279	370
	% within ALCOHOL	30.6%	39.7%	37.0%
NO	Count	206	424	630
	% within ALCOHOL	69.4%	60.3%	63.0%
Table 8. Prevalance of osteoporosis in alcohol consuming population

OSTEOPOROSIS		TOBACCO		Total
		YES	NO
YES	Count	227	143	370
	% within TOBACCO	78.0%	20.2%	37.0%
NO	Count	64	566	630
	% within TOBACCO	22.0%	79.8%	63.0%
Table 9. Prevalance of osteoporosis in tobacco consuming population

OSTEOPOROSIS		DIABETES		Total
		YES	NO
YES	Count	90	280	370
	% within DIABETES	53.6%	33.7%	37.0%
NO	Count	78	552	630
	% within DIABETES	46.4%	66.3%	63.0%
Table 10. Prevalance of osteoporosis in diabetic population

OSTEOPOROSIS		HYPERTENSION		Total
		YES	NO
YES	Count	160	210	370
	% within HYPERTENSION	55.4%	29.5%	37.0%
NO	Count	129	501	630
	% within HYPERTENSION	44.6%	70.5%	63.0%
Table 11. Prevalance of osteoporosis in hypertensive population

		TOBACCO	ALCOHOL	DIABETES	HYPERTENSION	OSTEOPOROSIS
TOBACCO	Pearson Correlation	1
	P-value
	N	1000
ALCOHOL	Pearson Correlation	.056	1
	P-value	.078
	N	1000	1000
DIABETES	Pearson Correlation	.566**	-.105**	1
	P-value	.000	.001
	N	1000	1000	1000
HYPERTENSION	Pearson Correlation	.378**	.339**	-.027	1
	P-value	.000	.000	.396
	N	1000	1000	1000	1000
OSTEOPOROSIS	Pearson Correlation	.544**	-.086**	.154**	.242**	1
	P-value	.000	.007	.000	.000
	N	1000	1000	1000	1000	1000
Table 12. Correlation between secondary risk factors and osteoporosis

		COMBINED RISK
OSTEOPOROSIS	Pearson Correlation	.339**
	P - value	.000
	N	1000
Table 13. Correlation between combined risk of risk factors and osteoporosis