A new study published in The American Journal of Medicine highlights another reason not to light up that cigarette — smokers (current and former) are more likely to suffer from low back pain than people who have never smoked [1]. Although the association is moderate, it is strongest for chronic back pain and for adolescents.

By now, the vast majority of us know that smoking is bad for you. A number of health risks are associated with smoking. Indeed, many women are not aware that smoking is a risk factor for breast cancer [2]. However, there are other conditions associated with smoking besides the key conditions of cancer and heart disease. Previous research has looked at the link between the experience of low back pain and the potential risk factor of smoking [3-6]. The experience of back pain is widespread [7]. “Chronic” back pain is often of particular interest as it is associated with days lost from work and healthcare costs, in addition to the impact on the patient’s quality of life. In the UK, “persistent” back pain is that which has lasted more than 6 weeks [8]. In the US, “chronic” back pain is pain lasting more than 3 months [9]. The causes of back pain are often complex and unclear. In the present study, the association between back pain and smoking was assessed.
Often, the same topic is explored by multiple researchers who may find slightly different results when exploring the association between two things. In these cases, a systematic literature review is often helpful. This means that researchers locate, report, evaluate and collate results from all the identifiable studies that address the key question. A really useful tool then to make sense of research is the “meta-analysis”: the results from multiple studies are combined using statistical methods to come up with the strength of an association across many studies. In this case, researchers searched for studies that examined the link between smoking and back pain; 40 different research studies were included in their statistical analysis. The advantage of this method is clear then — we can put all the research together and find out what the general picture is. The researchers identified studies from all over the world to include in this meta-analysis.

The association between smoking and low back pain was found to be significant (not just caused by chance). The researchers used a statistic known as an “odds ratio” or “OR”. This statistic allows us to understand how big the association is between two things.

The OR for chronic back pain was 1.79 (95% Confidence interval = 1.27 — 2.50) for current smokers. As the OR is greater than 1 (and the confidence interval does not include 1) we can say there is a significant association between smoking and the experience of chronic back pain. In English, this means that a current smoker has around 1.79 times the odds of having chronic back pain than a non-smoker. A really interesting result of the study was that the link between smoking and back pain was strongest for chronic low back pain, which is the most disabling form of back pain. For pain in the last month, the last 12 months and chronic pain, former smokers had a lower prevalence of back pain. Thus, the association between having ever smoked and back pain is smaller than the association between still smoking and back pain.

So does this mean that smoking causes back pain? Well, no. This type of analysis cannot clearly say if something causes something else. Investigating and establishing cause is highly complex and all too often we attribute cause to things that are merely related. For example, one possibility is that people with back pain are more stressed, so they take up smoking. We could further explore this link by looking at time: if our sample of people report significantly more back pain after some of them take up smoking (on their own, of course, we could not encourage this!) but those who do not take up smoking do not report more back pain, the data would suggest that smoking is, in some way, causing back pain.

Generally speaking, we are not all that great at understanding probability and risk (and that appears to include many academic researchers). Several articles have been written that discuss the use and misuse of statistics like the “OR” [10]. Odds ratios are far less informative in situations where the health condition is more common — as back pain is. Therefore, it is really important to be aware of some of the limitations of this sort of research when trying to understand health information. Media reports that state that “Murders in New York Caused by Higher Ice-Cream Sales” are much more likely to sell papers than the more accurate “As Ice-Cream Sales Increase, So Do the Number of Murders in New York” (a commonly used example in statistics classes). Being aware of these issues helps us to better understand what health research actually does identify. We can also investigate a “causal mechanism”: how would smoking cause back pain? Suggestions include the possibility that smoking increases pro-inflammatory substances in the body, that smoking affects back pain as it increases the risk of osteoporosis, and that smoking reduces blood circulation leading to disc damage, which then leads to pain. All of these claims need to be further researched and the degree to which they really contribute to the causes of back pain explored before we can confidently state that “smoking causes back pain”.

References

1. Shiri et al. The association between smoking and low back pain: a meta-analysis. Am J Med. 2010 Jan;123(1):87.e7-35. DOI: 10.1016/j.amjmed.2009.05.028
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2. Peacey et al. Low levels of breast cancer risk awareness in young women: an international survey. Eur J Cancer. 2006 Oct;42(15):2585-9. Epub 2006 Jul 7.
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3. Scott et al. The association between cigarette smoking and back pain in adults. Spine 1999 Jun 1;24(11):1090-8.
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4. Feldman et al. Smoking. A risk factor for development of low back pain in adolescents. Spine 1999 Dec 1;24(23):2492-6.
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5. Goldberg et al. A review of the association between cigarette smoking and the development of nonspecific back pain and related outcomes. Spine 2000 Apr 15;25(8):995-1014.
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6. Alkherayf and Agbi. Cigarette smoking and chronic low back pain in the adult population. Clin Invest Med. 2009 Oct 1;32(5):E360-7.
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7. Strine and Hootman. US national prevalence and correlates of low back and neck pain among adults. Arthritis Rheum. 2007 May 15;57(4):656-65.
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8. National Institute for Health and Clinical Excellence: Early management of persistent non-specific low back pain. NICE Clinical Guideline 88. 2009 May.
9. Back Pain Information Page. National Institute of Neurological Disorders and Stroke. Accessed Feb 18, 2010.
10. Westergren et al. Information Point: Odds Ratios. Journal of Clinical Nursing. 2001 10,257-269.

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As you or perhaps your parents get older, would you want to be at home when recovering from an illness? Would the choice between home rehabilitation or visits to a day hospital make a difference to your recovery and health? Which is cheaper for the healthcare services? A recent study published in the journal Health Technology Assessment (HTA) shows that home-based care in the United Kingdom is no worse than attendance at a day hospital for older adults [1].

Under any nationally funded healthcare system, there is always an enormous pressure on resources. As such, it is vital to explore the outcomes of different types of care, keeping in mind the cost-effectiveness. Rehabilitation after illness is a vital part of healthcare, but is enormously costly. As the U.S. and European populations age, there is increasing pressure on the health services to deliver cost-effective rehabilitation for older patients [2]. Older patients often present with more complications following illness and take longer to recover, so this push to reduce costs must always take into account how well each intervention or mode of care works. With the emphasis on “quality of life” in healthcare (that simply being physically “healthy” is not the sole goal of healthcare, but that the experienced quality of ones life is highly important), rehabilitation care is further emphasised.

U.K. researchers conducted a randomised controlled trial, where patients were randomised to receive either day hospital care or home-based rehabilitation [1]. Eighty-nine older adults receiving rehabilitation care for a range of health conditions took part in the study; 90% of the participants were over 70 years of age. Measures of daily living activities (normal daily life tasks eg bathing, preparing food), quality of life, anxiety, depression and general health were taken. The scientists also collected data about health outcome and number of hospital admissions. The patients and their carers (informal carers in this case, such as spouse or friends) were followed for up to 12 months. Data were collected at 3 months, 6 months and 12 months following the start of the rehabilitation program. The home-based rehabilitation program and the day hospital both included services such as physiotherapy and occupational therapy, stroke rehabilitation and falls assessment — the key difference between the two types of care then being the venue.

Results of both patient outcomes and carer wellbeing showed that home-based rehabilitation “confers no particular disadvantage for patients and carers.” However, in this case, the cost of the home-based rehabilitation provision was not significantly different to that of day hospital rehabilitation. This suggests that although home-based care may appear on the surface to be more cost-effective, this is not always the case. This study then has important implications practice, most importantly perhaps is that rehabilitation providers must consider the local needs and characteristics of their population when providing care. Indeed, given there is no difference found in outcomes or costs, patients could potentially be given the choice. Local issues are clearly important, for example in a rural community home-based care may be vital if patients are restricted in access to transport.

This study did conclude that the two types of care are equivalent: rather they explored non-inferiority. This just establishes that one treatment is not worse than the other. This does not mean the two types of care are equivalent, indeed, this is impossible to show as there will always be differences [4]. Non-inferiority trials tell us if there are differences that are clinically important, i.e. if the treatment results in worse outcomes.

This study illustrates some of the complex issues around choice of services to be delivered through healthcare systems. As healthcare systems are increasingly scrutinised and reforms are planned, it is important to have a grasp of some of these issues to understand debates. On an individual level, this study shows that despite personal preferences and preconceived ideas, care in a day hospital is not superior to care within the home. Evaluating evidence may lead you then to choose a different type of care.

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References

1. Parker et al. Rehabilitation of older patients: day hospital compared with rehabilitation at home. A randomised controlled trial. Health Technol Assess. 2009 Aug;13(39):1-143, iii-iv.
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2. Miller DK. Effectiveness of acute rehabilitation services in geriatric evaluation and management units. Clin Geriatr Med. 2000 Nov;16(4):775-82.
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3. Pang J Jr. Partial hospitalization. An alternative to inpatient care. Psychiatr Clin North Am. 1985 Sep;8(3):587-95.
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4. Snapinn SM. Noninferiority trials. Curr Control Trials Cardiovasc Med. 2000;1(1):19-21.
   View abstract

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Heart disease is the leading killer in the U.S. and throughout most of Europe. People’s behaviour can protect and reduce risk of heart disease, and interventions to help people “self-manage” exist. But what is the best way to “self-manage”? A recent study shows that group programmes and self-directed programmes have remarkably different effects [1].

Self-management interventions exist for many health problems. They are notoriously difficult to define. One thorough definition is that it relates to activities undertaken by the person who has a “chronic” or “long-term” condition such as asthma, multiple sclerosis or arthritis. These activities include problem solving, decision making, resource utilization, the formation of a patient-provider partnership, action planning and self tailoring [2]. Interventions or programmes are designed around these activities to help support people to manage their own illness. The idea is that following attendance at a programme of some sort, the activities and skills learned will be continued to be used, thus improving health, maintaining fitness and/or quality of life and reducing the risk of future acute episodes of ill health. These interventions are popular for many reasons, including the relatively low cost to health service providers as interventions can be delivered by health-care professionals or by people with the relevant condition who have been trained, or a mixture of both. Self-management interventions also allow people with long-term conditions to be meet in a group with people with similar conditions. The experience of being in a group, knowing one is not alone and sharing stories is thought to play some part in the effectiveness of self-management interventions. But to what extent is this true?

Researchers at the University of Michigan explored the effect of the format of a self-management intervention for women with heart disease by comparing a “self-directed” programme to a “group” programme to a control group [1]. In the “self-directed” version, there was a single session with health educator followed by completing programme at home. The “group” programme consisted of 6 – 8 women meeting for around 2 hours once a week for six weeks. In the control condition, no intervention was presented. The aim was to investigate which intervention would most usefully effect symptom experience, health status and weight. To make the comparison of the “self-directed” and “group” interventions more equitable, the “self-directed” version included videos of group discussions to emulate the motivation and support that would be given in the “group” programme. Further, to ensure information was provided to all, the “self-directed” group also received telephone calls from a health educator.

The results revealed a remarkable difference. Eighteen months after the intervention, data were collected. For the “self-directed” intervention, cardiac symptoms such as chest pain and dizziness were reduced in number, frequency and impact. For the “group” intervention, weight loss and exercise capacity (in terms of how far a person can walk within a set time) were improved. This is despite the fact that the information and instructions provided in both programmes were the same.

So does this mean we should all join groups if we want to lose weight and exercise more but stay at home if we want to feel fewer symptoms? Not necessarily. This study, like all studies, has several limitations. Obviously, the women in the “self-directed” group were not observed, so we do not know to what extent they followed the intervention they were given. A diary record of what the women did could have been included in this study, but even that may not be an accurate picture of how well the intervention was followed. Another issue is that the women in the “group” may have experience a higher “dose” of the intervention – that is to say the they attended a meeting for approximately 2 hours per week, receiving a two hour “dose”. We do not know how much time the women in the “self-directed” intervention spent on their activities. Further, this study included a sample only of women who were white and high school educated. Therefore, we cannot say whether the same effect would be observed outside of this group of people. It would be interesting to see this issue investigated with other demographics, including men (who may be less amenable to group processes), different ethnic groups and educational levels.

What the results do suggest however is that being in a group may facilitate exercise and weight loss improvement for women with heart disease. But we still do not know how this occurs. A common problem in behavioural interventions, including self-management interventions, is that we simply do not know which bit of the intervention is working. The study suggests that the “group” part of the intervention is affecting how the intervention works. However, we do not know why. Is peer pressure a factor? Would these results be the same if we looked at people in relation to personality type? Would a shy, introverted sample show the same results?

There are many self-management interventions available today, in terms of both health service packages, “self-help” books and DVDs, information from health care professionals, charity groups and community organisations. Our health and its care is now a collaborative endeavour in which we are involved actively and with responsibility. Self-management is increasingly included in health policies. Researching and understanding whether such interventions work, which components work, what “dose” is needed and who they work for, is vital to our future health.

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References

1. Clark et al. Heart disease management by women: does intervention format matter? Health Educ Behav. 2009 Apr;36(2):394-409. Epub 2007 Dec 15.
   DOI: 10.1177/1090198107309458
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2. Lorig KR, Holman H. Self-management education: history, definition, outcomes, and mechanisms. Ann Behav Med. 2003 Aug;26(1):1-7.
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