Osteoporosis Causes and Risk Factors and Nursing Care

Afza.Malik GDA
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Nursing Care for Osteoporosis

Osteoporosis Causes and Risk Factors and Nursing Care

What is Bone Mass Density ans Osteoporosis,Pregnancy and Osteoporosis,Prevalence of Osteoporosis,Osteoporosis and Fracture Risk,Female gender Advancing age,An inactive lifestyle,Osteoporosis ans Skeletal Deformities and Fractures,Osteoporosis and Psychological Issues,Osteoporosis and Economical Burden,Nursing Research and Osteoporosis.

What is Bone Mass Density ans Osteoporosis

    Bone mass density (BMD) accounts for 70% of bone strength, is measured as grams of mineral per area, and is reflective of both peak bone mass and the amount of bone loss (National Institutes of Health (NIH), 2000). 

    Osteoporosis is not only the result of accelerated bone loss during aging, but may also develop because of sub optimal bone growth in childhood and adolescence. “Osteoporosis is a pediatric disease with geriatric consequences” (Drugay, 1997, as cited in Gueldner, 2000). 

    Bone quality, a poorly understood factor, is thought to result from the bone’s micro and macro structure, biochemical composition, distribution and integrity of material components within the bone, turnover, and microdamage accumulation. 

    That a 50-year-old woman with low bone density has a much lower risk of fracture than an 807-year-old woman with the same bone density speaks to changes in bone quality (Kolata, 2003).

Pregnancy and Osteoporosis

    Pregnancy associated osteoporosis is a rate and temporary condition that occurs during the 3rd trimester or postpartum period of a first pregnancy. Symptoms include back pain, loss of height, and vertebral fractures, Lactation is also associated with transient bone loss, with recovery of full bone density within 6 months (National Women’s Health Information Center, 2003).

Prevalence of Osteoporosis

    In the United States, using the same criteria of BMD of the hip, prevalence of osteoporosis ranges from 3.9% of Caucasian American women 50-59 years, to 47.5% for those older than 80 years (World Health Organization [WHO], 2003b). 

    The National Osteoporosis Foundation (NOF, 2002) estimates that 55% of all Americans aged 50 years and older in the year 2002, nearly 44 million people, had either osteoporosis or low bone mass. Based on the 2000 Census, prevalence estimates increase to 52 million women and men for the year 2010, and to 61 million in 2020. 

    Prevalence varies by gender, race, and ethnic group. Both men and women experience a decline in BMD starting in midlife, with women experiencing more rapid bone loss in the immediate years after menopause. 

    Of the 44 million Americans estimated to have osteoporosis and low bone mass in the year 2002, 32% (14 million) of them were men and 68% (30) million) were women (NOF). “These estimates challenge the long-held myth that osteoporosis is a sex segregated problem” (Wolf, Penrod, & Cauley, 2000, p. 7). 

    Asian and white non-Hispanic women have the lowest bone mineral densities throughout life, and African-American women have the highest. Mexican-American women have bone densities that are intermediate between the two groups. 

    Japanese and Native-American women (limited data) have peak BMD that are lower than white non-Hispanic women (NIH, 2000).

Osteoporosis and Fracture Risk

    Osteoporosis may be viewed as a silent systemic disease or as a progressive risk factor for fractures. Several factors associated with low bone density and/or risk for fractures have been identified by large prospective studies, including the 35 state National Osteoporosis Risk Assessment (NORA) (Siris et al., 2001). 

    These risk factors are classified as either primary or secondary (Field-Munves, 2000; NIH, 2000; NOF, 2002). Primary causes include:

Female gender Advancing age

  • White or Caucasian and Asian races Estrogen deficiency as a result of menopause, especially early or surgically induced. This may also be categorized as secondary.
  • Low weight and body mass index, having a small frame
  • Personal history of fracture after age 50 years
  • Family history of osteoporosis
  • History of fracture in a first-degree relative
  •  Cigarette smoking Low lifetime calcium and Vitamin D intake

·  An inactive lifestyle.

    Sometimes listed as a contributing factor, lack of sun exposure, especially in many older adults and during the winter months in higher latitudes, significantly reduces cutaneous production of Vitamin D essential for calcium absorption (Feskanich, Willett, & Colditz, 2003). 

    Other suspected predictors of low bone mass, such as use of alcohol and caffeine containing beverages, have been proven to be inconsistent in their association (NIH,2000). In fact, the NORA study of 200,160 postmenopausal women aged 50 years or older found that alcohol consumption significantly decreased the likelihood of osteoporosis (Siris et al., 2001).     

Other data from this large diverse population found that higher body mass index, African-American heritage, estrogen use, diuretic use, and exercise are BMD protective factors, while age, personal or family history of fracture, Asian or Hispanic heritage, smoking, and cortisone use were significant predictors of osteoporosis.     

    Many diseases and drug therapies are also associated with osteoporosis and increased fracture risk (Field-Munves, 2000; NIH). A comprehensive list is outlined in the National Osteoporosis Foundation Physician’s Guide to Prevention and Treatment of Osteoporosis (NOF, 2003).

Osteoporosis ans Skeletal Deformities and Fractures

    Osteoporosis causes skeletal changes resulting in chronic morbidity and mortality. It has profound physical, financial and psychosocial consequences for the individual, family, and community (Gueldner, 2000; NIH, 2000), Changes in bone mass or quality, however, occur without symptoms, and are usually not detected until a fracture occurs. 

    Fractures of the proximal femur (hip), vertebrae (spine), and distal forearm (wrist) are the most clinically apparent complications of osteoporosis, and profoundly affect quality of life (Delmas & Fraser, 1999; NIH; NOF, 2003; Wolf, Penrod, & Cauley, 2000), Bone loss associated with the aforementioned risk factors and age-related changes, such as a decrease in proprioception and balance, leads to an increased risk of fracture.

    The risk of fracture rises when BMD declines. The use of BMD, therefore, to identify those at risk for fractures is analogous to the use of blood pressure monitoring to identify those at risk for stroke (Wolf et al., 2000). The estimated lifetime risk for wrist, hip, and vertebral fractures is 15%, similar to that for ischemic heart disease (Brundtland, 2000). 

    The majority of these fractures in persons over 50 years of age result from osteoporosis, but attempts to classify fractures have been less than ideal. Use of the hip fracture rate to calculate the osteoporosis fracture burden is promising (WHO, 2003).

    Worldwide, the incidence of hip fractures was estimated to be 1.66 million in 1990 (WHO, 2003). Increasing exponentially with age, virtually all occur in persons aged 35 years and older, with 80% of these occurring in women. 

    The highest incidence rates are reported from northern Europe, the northern part of the United States, and among South- East Asian populations, and the lowest are from African countries. The rates, however, differ within racial groups, for example, “rates vary by a factor of about 10 between Sweden and Turkey” (WHO, p. 31). 

    The differences in incidence of hip fractures between countries are greater than those between genders.

    Hip fractures are associated with lengthy hospital admissions, difficulty in activities of daily life, nursing home placement, death, and the corresponding economic burden. There is an increase in mortality of 10% to 20% within 1 year of fracture; 30% of fracture patients will fracture the opposite hip; up to 25% require long term nursing home care; 40% have full recovery to pre-fracture walking status (NOF, 2003).

     Mortality is related to comorbid diseases, such as stroke or chronic lung disorders, and to complications arising from immobility and/or treatment of the fracture (Wolf et al., 2000).

    Vertebral fractures, often called crushing fractures, result in the characteristic physical changes often associated with osteoporosis, most notably kyphosis or dowager’s hump. 

    This collapsing of the vertebral column onto itself impacts other body systems: gastrointestinal, respiratory, genitourinary, and craniofacial, and produces concomitant morbidity: height loss, abdominal protuberance and fullness, inhibited breathing patterns, back pain, back disability, and functional limitations in walking, bending, and reaching (Gueldner, 2000; NIH, 2000; NOF, 2003; Wolf et al., 2000).

Osteoporosis and Psychological Issues

    The psychosocial ramifications of osteoporosis, though many, are often under addressed when considering the sequelae of this disorder. Fear, anxiety, anger, depression, and loss of self-esteem threaten the individual’s successful adaptation to lifestyle and cosmetic changes, chronic pain, and physical limitations.     

    Often, the decrease in functional abilities leads to social isolation (Gueldner, 2000). The high morbidity and consequent loss of mobility and independence associated with osteoporosis have a ripple effect on the family system, the community, and society. 

    The demands of chronic care, whether formal or informal, strain family, social, health care, and government networks. Global “graying” will further magnify this major public health problem.

Osteoporosis and Economical Burden

    The economic burden of osteoporosis to society is formidable. In the United States, the National Osteoporosis Foundation (2003) estimates that the annual cost to the health care system associated with osteoporotic fractures was $17 billion in 2001 dollars. 

    Because these fractures occur in a mainly aged, retired population, costs are associated with direct care services, inpatient and outpatient services, and nursing home care, rather than weighted by a loss of wages (Wolf et al., 2000). Few financial cost estimates are available for the total burden of osteoporosis and all its consequences.

Nursing Research and Osteoporosis

    A recent literature search of the CINAHL database entering the keywords nursing research and osteoporosis for the years 1997- 2003 revealed 333 articles. For the year 2003, 43 articles were found, 10 of which were original nursing studies. 

    These studies fell into 5 categories: dealing with patients with hip fractures (3), effect of physical activity on osteoporosis (3), knowledge of osteoporosis (2), attitudes on menopause (1), and development of tools to assess risk factors for osteoporosis.

    (1). The nursing profession, integral to health care from the cradle to the grave, needs to increase osteoporosis awareness, and to research the prevalence, prevention, and adaptation of individuals to this chronic disease.

    One ongoing nursing research project is profiling the incidence of osteoporosis in peri and postmenopausal women in Pennsylvania and the southern tier of New York (Gueldner et al., 2003). Preliminary results of 23411 women (mean age, 56.12; median age, 55; range, 32 to 87) found that nearly 24% (23.5%) of these women had heel ultrasound T scores -1.0. 

    Data were also analyzed for relationships among demographic variables, risk factors, and T scores. Age (p=.012) and the final score on the Merck Osteoporosis Evaluation SCORE Sheet (p < .001) were inversely correlated with T scores; the older the subject and the higher the score on composite risk factors, the lower the T scores. 

    Age at menopause was positively correlated with T scores (p=.032); the higher the age at menopause, the higher the T scores. In addition, women who had taken estrogen had significantly higher T scores (p = .038) than those who had not.     

Comparison of self-report of height to the measured height on the day of data collection found that self-reported height was significantly lower than measured height (p < .001).

    These preliminary findings have several implications for clinical practice. That 23.5% of this sample has low bone mass or osteoporosis underscores the importance of early screening in order to develop awareness and provide education on bone health.     

    The high correlation of the SCORE questionnaire with T-scores suggests that this instrument may alone effectively identify “at risk” women for follow up. This study also supports the unique contribution of estrogen to bone strength, and in light of recent evidence of hormone replacement therapy risks, the need for research on alternative therapies. 

    Lastly, the finding on height discordance mandates the accurate objective measurement of height and weight during health care visits, rather than relying on self-report.

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