Evaluating and Managing Acute Low Back Pain in the Primary Care Setting

Atlas, Steven J.; Deyo, Richard A.

doi:10.1046/j.1525-1497.2001.91141.x

Cited by 67 publications

(95 citation statements)

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“…These guidelines, however, stop short of making specific recommendations about how often to take sedentary breaks. Investigators have posed sedentary breaks every 30 minutes as a feasible recommendation (4, 9), which are supported by laboratory-based studies showing sedentary breaks every 20-30 minutes elicit beneficial cardio-metabolic effects (5, 10, 29). Our results suggest guidelines aimed within the window of every 20 to 30 minutes could be an optimal target to interrupt sedentary behavior as our participants averaged approximately 9 and 5 sedentary bouts per day longer than 20 and 30 minutes, respectively, accounting for 60% and 48% of total sedentary time.…”

Section: Discussionmentioning

confidence: 99%

“…The distribution of sedentary bouts was examined using the following thresholds: ≥1, ≥5, ≥10, ≥20, ≥30, ≥40, ≥50, ≥60, and ≥90 consecutive minutes. Daily averages of sedentary bouts exceeding each threshold were computed as: (1) total number of sedentary bouts ≥XX minutes, (2) percentage of total number of sedentary bouts ≥XX minutes ([number of bouts ≥XX minutes/total number of sedentary bouts]*100), (3) percentage of total daily sedentary time accumulated in bouts ≥XX minutes ([sedentary time accumulated from bouts ≥XX minutes/total sedentary time]*100), and (4) mean length of sedentary bouts ≥XX minutes. Descriptive statistics, including mean ± standard deviation for continuous variables and percentages for dichotomized variables, were computed to characterize patterns of sedentary behavior in the overall sample.…”

Section: Methodsmentioning

confidence: 99%

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Patterns of Sedentary Behavior in US Middle-Age and Older Adults

Diaz

Howard

Hutto

et al. 2016

Medicine &Amp; Science in Sports &Amp; Exercise

139

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Purpose The purpose of this study was to examine patterns of objectively-measured sedentary behavior in a national cohort of U.S. middle-aged and older adults and determine factors that influence prolonged sedentary behavior. Methods We studied 8,096 participants from the REasons for Geographic and Racial Differences in Stroke (REGARDS) Study, a population-based study of black and white adults ≥45 years. Seven-day accelerometry was conducted. Prolonged sedentary behavior was defined as accumulating ≥50% of total sedentary time in bouts ≥30 min. Results The number of sedentary bouts ≥20, ≥30, ≥60, and ≥90 min were 8.8 ± 2.3, 5.5 ± 1.9, 1.9 ± 1.1, and 0.8 ± 0.7 bouts/day, respectively. Sedentary bouts ≥20, ≥30, ≥60, and ≥90 min accounted for 60.0 ± 13.9%, 48.0 ± 15.5%, 26.0 ± 15.4%, and 14.2 ± 12.9% of total sedentary time, respectively. Several factors were associated with prolonged sedentary behavior in multivariate-adjusted models (Odds Ratio [95% CI]): older age (65-74 years: 1.99 [1.55-2.57]; ≥75 years: 4.68 [3.61-6.07] vs. 45-54 years), male sex (1.41 [1.28-1.56] vs. female), residence in non-stroke belt/buckle region of U.S. (stroke belt: 0.87 [0.77-0.98]; stroke buckle: 0.86 [0.77-0.95] vs. non-belt/buckle), body mass index (BMI) (overweight: 1.33 [1.18-1.51]; obese: 2.15 [1.89-2.44] vs. normal weight), winter (1.18 [1.03-1.35] vs. summer), and low amounts of moderate-vigorous physical activity (MVPA) [0 min/week: 2.00 [1.66-2.40] vs. ≥150 min/week). Conclusions In this sample of U.S. middle-aged and older adults, a large proportion of total sedentary time was accumulated in prolonged, uninterrupted bouts of sedentary behavior as almost one-half was accumulated in sedentary bouts ≥30 min. Several sociodemographic (age, sex, BMI), behavioral (MVPA), environmental (region), and seasonal factors are associated with patterns of prolonged sedentary behavior.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Patterns of Sedentary Behavior in US Middle-Age and Older Adults

Diaz

Howard

Hutto

et al. 2016

Medicine &Amp; Science in Sports &Amp; Exercise

139

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“…The trichotomization was done in light of insights from current literature on the minimum amount of PA that is likely to have any effect on health outcomes. We also considered several covariates for the purpose of adjusting for potential confounders as guided by the previous researches – age: 50–59, 60–69, 70–79, >80 years; sex: female, male; current marital status: unmarried, married; educational attainment: no formal schooling, less than primary school, primary school completed, secondary school completed, high school completed, preuniversity/university completed; current job: government employee, nongovernment employee, self-employed, unemployed/other; currently smoke: daily, not daily, not at all; ever drank alcohol: yes, no 8–11,16,20,24,31,34…”

Section: Methodsmentioning

confidence: 99%

“…The etiology of back pain is multifarious; however, the common causes ranges from injuries and mechanical problems, such as intervertebral disk degeneration, vertebral fractures, herniated disks and myofascial pain 10. Given the diverse nature of the problem, LBP is managed by various health care providers, such as GP, family practitioners, neurologists, rheumatologists, emergency physicians, and orthopedic and neurological surgeons 11. Appropriate prevention and management strategies starting at the primary care level hold the potential to reduce the prevalence of population living with chronic back pain, for which a wide variety of cause-specific treatment and therapeutic options are available.…”

Section: Introductionmentioning

confidence: 99%

Participation in physical activity and back pain among an elderly population in South Asia

Bishwajit¹,

Tang²,

Yaya³

et al. 2017

JPR

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IntroductionGlobally, chronic back pain is one of the most commonly encountered medical conditions among an elderly population with significant bearings on health, functional mobility and general well-being.ObjectiveTo estimate the burden of chronic back pain and its association with physical activity (PA) among population aged 50 years and above in Bangladesh, India, Nepal, Pakistan and Sri Lanka.MethodsCross-sectional data on 8502 men and women aged 50 years and above were collected from the World Health Survey (2002). Three forms of PA were considered – vigorous physical activity (VPA), moderate physical activity (MPA) and walking. Odds ratios (ORs) of the association between self-reported back pain and VPA, MPA and walking were calculated by using generalized estimating equations.ResultsThe prevalence of back pain was, respectively, 64.8%, 19.8%, 69.5%, 40.6% and 36.2% in Bangladesh, India, Nepal, Pakistan and Sri Lanka. No significant association between back pain and VPA was observed among men in any of the countries. In India, Pakistan and Sri Lanka, the odds of suffering from back pain were, respectively, 29%, 2.5 times and 59% higher among women who almost never took MPA. In India, taking MPA for few days a week and almost never was associated with, respectively, 38% (OR=1.38; 95% confidence interval [CI]=1.017–1.876) and 56% (OR=1.564; 95% CI=1.003–2.438) higher odds of reporting back pain. Walking almost never was also associated with, respectively, 83% (OR=1.829; 95% CI=1.14–2.934) and 2.9 times (OR=2.854; 95% CI=1.419–5.738) higher odds of reporting back pain among men in Nepal and Pakistan, respectively.ConclusionThough the relationship was not consistent across sex and countries, results indicate that inadequate or nonparticipation can substantially increase the likelihood of suffering from back pain among an elderly population in this region. Further research is needed to better understand this relationship and the potential of exercised-based strategies to prevent and treat back pain among elderly persons.

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“…On the other hand, in most who receive primary care for acute lower back pain, the pain is thought to have a mechanical cause involving the spine and surrounding structures (4). However, lower back pain in conjunction with red flags, including pain for more than one month, >50 years of age, and unexplained weight loss, indicates a more serious cause.…”

Section: Discussionmentioning

confidence: 99%

M-protein-negative Myeloma Mimicking Lumbar Disc Herniation

et al. 2017

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A 60-year-old man was referred to us with high levels of aspartate aminotransferase and lactate dehydrogenase (LDH). He did not complain of any symptoms; however, he had been diagnosed with lumbar disc herniation, even though his back pain improved only to half of its previous level with pregabalin. Thus, we asked about the red flag of back pain and confirmed that he had involuntary body weight loss, which led us to diagnose truly non-secretory multiple myeloma, a variant of multiple myeloma that is associated with M-protein negativity and a normal serum free light chain level.

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Evaluating and Managing Acute Low Back Pain in the Primary Care Setting

Cited by 67 publications

References 67 publications

Patterns of Sedentary Behavior in US Middle-Age and Older Adults

Patterns of Sedentary Behavior in US Middle-Age and Older Adults

Participation in physical activity and back pain among an elderly population in South Asia

M-protein-negative Myeloma Mimicking Lumbar Disc Herniation

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