Tag: Environmental risk factor

How much do you weigh?

Barts-MS rose-tinted-odometer  ★

When last have you weighed yourself and calculated your BMI (body mass index)? 

BMI = body mass (kg) / the square of the body height (m) [kg/m2]; to save you time and effort you can simply use the NHS BMI calculator, which takes imperial measurements as well. 

I am not sure if you are aware that childhood and adolescent obesity is an important risk factor for developing MS. We estimate that smoking and obesity could account for 1 in 5 new cases of MS. Obesity is a complex disorder that tends to run in families. The familial link is not only due to the effect of genes but cultural and social factors. If you are obese, or very obese, you need to do something at a personal level that may inform what the next generation does about it; good habits are infectious. 

I have little doubt that obesity impacts on MS outcomes. Obesity affects mobility and is associated with deconditioning and poorer outcomes. I recall a patient of mine with primary progressive MS losing over 30 kg in weight, with his BMI dropping from over 30 to less than 24, and in parallel, his EDSS improved from 6.5 to 5.5. The latter improvement was from him getting fit from his 5-day per week exercise programme and making the effort. 

As you are aware obesity is associated with a metabolic shitstorm that impacts on many disease processes. Obesity causes metabolic syndrome (hypertension, insulin resistance, glucose intolerance, diabetes and dyslipidaemia) and a systemic inflammatory syndrome that may worsen MS. Therefore, there is a good reason why, if you are obese you should consider doing something about it. This is easier said than done. To start I would recommend you read “Why we get fat and what to do about it”, by Gary Taubes or you can watch his lecture on YouTube. Understanding the metabolic issues that underlie obesity will allow you to understand what to do about it. The latest science behind obesity is not rocket science.

Why this post just before Christmas? Christmas is a time of excess and maybe this post will make you mindful of what and how you eat. I was horrified when I read the forecast in this week’s New England Journal of Medicine that by 2030 1 in 2 US adults will be obese. The conclusion of the paper says it all. 

“We project that given current trends, nearly 1 in 2 U.S. adults will have obesity (BMI>30) by 2030, and the prevalence will be higher than 50% in 29 states and not below 35% in any state — a level currently considered high. Furthermore, our projections show that severe obesity (BMI>35) will affect nearly 1 in 4 adults by 2030 and become the most common BMI category among women, black non-Hispanic adults, and low-income adults.”

 Estimated Prevalence of Overall Obesity and Severe Obesity in Each US State, from 1990 through 2030. Image from the NEJM.

I suspect the UK is not far behind the US. What we need to realise that underlying this epidemic in obesity is an MS epidemic. Don’t you think we should do something about it?

Ward et al. Projected U.S. State-Level Prevalence of Adult Obesity and Severe Obesity. N Engl J Med, 381 (25), 2440-2450 2019 Dec 19.

Background: Although the national obesity epidemic has been well documented, less is known about obesity at the U.S. state level. Current estimates are based on body measures reported by persons themselves that underestimate the prevalence of obesity, especially severe obesity.

Methods: We developed methods to correct for self-reporting bias and to estimate state-specific and demographic subgroup-specific trends and projections of the prevalence of categories of body-mass index (BMI). BMI data reported by 6,264,226 adults (18 years of age or older) who participated in the Behavioral Risk Factor Surveillance System Survey (1993-1994 and 1999-2016) were obtained and corrected for quantile-specific self-reporting bias with the use of measured data from 57,131 adults who participated in the National Health and Nutrition Examination Survey. We fitted multinomial regressions for each state and subgroup to estimate the prevalence of four BMI categories from 1990 through 2030: underweight or normal weight (BMI [the weight in kilograms divided by the square of the height in meters], <25), overweight (25 to <30), moderate obesity (30 to <35), and severe obesity (≥35). We evaluated the accuracy of our approach using data from 1990 through 2010 to predict 2016 outcomes.

Results: The findings from our approach suggest with high predictive accuracy that by 2030 nearly 1 in 2 adults will have obesity (48.9%; 95% confidence interval [CI], 47.7 to 50.1), and the prevalence will be higher than 50% in 29 states and not below 35% in any state. Nearly 1 in 4 adults is projected to have severe obesity by 2030 (24.2%; 95% CI, 22.9 to 25.5), and the prevalence will be higher than 25% in 25 states. We predict that, nationally, severe obesity is likely to become the most common BMI category among women (27.6%; 95% CI, 26.1 to 29.2), non-Hispanic black adults (31.7%; 95% CI, 29.9 to 33.4), and low-income adults (31.7%; 95% CI, 30.2 to 33.2).

Conclusions: Our analysis indicates that the prevalence of adult obesity and severe obesity will continue to increase nationwide, with large disparities across states and demographic subgroups. (Funded by the JPB Foundation.).

CoI: multiple

To smoke or not to smoke that is the question

Barts-MS rose-tinted-odometer  ★ ★ ★ ★ ★

Yawn! I am getting tired of the saying the same-old things on this blog. Is it time to retire and do something new? 

We have done some modelling work and predict that ~20% of new or incident cases of MS could be prevented if we stop the population from smoking. The question is how do we achieve this? Taxation has worked to some extent in that we are seeing a fall in the number of current smokers, but the numbers of teenagers smoking looks as if it is quite resistant to change. The solution must be education, education, education and a war against the tobacco industry. 

Public Health England

If social media is such a powerful tool to hack the brains of voters, why don’t public health departments use this technology to promote their agenda? What we need are companies like Cambridge Analytica to do some good in the world and to promote a ‘Don’t Start Smoking’ campaign. 

We did try and get some insights into why teenage girls start smoking when Amy Sankey, a work experience student, did a survey in her school for us. Despite the almost universal awareness of the harms of smoking in terms of lung cancer, most girls, however, did not know that there is a link between smoking and autoimmunity. I suspect even if they knew about the link it would be unlikely to prevent them from starting to smoke. 

We are interested in smoking as a risk factor for MS as it is telling us something about the cause of the disease. It appears that smoking must be acting via the lungs and is due to tobacco itself. Use of oral, non-smoked, tobacco is in fact associated with a reduced risk of getting MS, hence it is not tobacco exposure. Solvent exposure is also associated with an increased risk of getting MS, which supports the lung hypothesis of developing MS. 

Lung hypothesis #1 argues that damage to the lung from smoking or solvents creates a pro-inflammatory environment that is sufficient to activate pre-existing autoreactive T-cells. In comparison, lung hypothesis #2 argues that smoking damages proteins by a process called post-translational modification and that these proteins stimulate an immune response that then cross-reacts with normal antigens to set-up autoimmunity. The argument for the latter in triggering rheumatoid arthritis, an autoimmune disease of joints, is quite compelling but is less compelling when it comes to MS. We hope to study whether post-translational modification of CNS antigens is relevant in MS via an ECTRIMS fellowship we have supported.  

What is interesting is that smoking interacts with genetic risk factors for developing MS and with EBV infection suggesting that there is a critical gene-environment interaction that causes MS. Wouldn’t it be interesting to study and find out what these interactions are? We have an exceptionally bright and able young researcher, Ben Jacobs, who wants to do a PhD on this exact topic; gene-environment interactions. At the moment we are ruminating about the best approach he should take to address this question. It is not an easy experiment so if you have suggestions please feel free to contact us.

I would also like to remind you that smokers who have MS have a much poorer prognosis, which is why we recommend that you stop smoking if you can.

If you are interested in smoking and MS there is a new review that has just come out. 

Rosso &  Chitnis. Association Between Cigarette Smoking and Multiple Sclerosis: A Review. JAMA Neurol. 2019 Dec 16. doi: 10.1001/jamaneurol.2019.4271

IMPORTANCE: Cigarette smoking is a common environmental exposure and addiction, which has severe health consequences. Smoking is a risk factor for multiple sclerosis (MS); also, smoking has been associated with disease activity and overall prognosis for patients with MS.

OBSERVATIONS: Cigarette smoking is an irritative agent on the lungs, in which a proinflammatory cascade starts that culminates in autoimmunity. Inflammation may increase the risk of MS in some individuals, in a process driven by antigen cross-reactivity between lung antigens and myelin antigens. Genetics plays a central role in the individual predisposition to mounting an autoimmune reaction. Also, free radicals, cyanates, and carbon monoxide in cigarette smoke may be directly toxic to neurons. Patients with MS who smoke have higher rates of disease activity, faster rates of brain atrophy, and a greater disability burden. Some of the outcomes of smoking were found to be reversible, which makes counselling key.

CONCLUSIONS AND RELEVANCE: The pathways involved in cigarette smoking should be further analyzed to understand the mechanisms whereby smoking worsens MS prognosis. The proinflammatory and neurotoxic outcomes of cigarette smoking may be shared by other environmental exposures, such as pollution and organic solvents. From a global perspective, efforts should be made to diminish the prevalence of cigarette smoking in patients with MS.

CoI: multiple

Air pollution and MS

We know that smoking, passive smoking and solvent exposure increase your risk of getting MS. The hypothesis, supported by animal work, suggests these risk factors alter antigens or proteins in the lung that then trigger autoimmunity. In other words, the altered proteins are interpreted as being foreign by the immune system. 

Particulate air pollution is another respiratory toxin that has been studied in Iran and is associated with an increased prevalence of MS. I suspect that particulate matter air pollution also increases your risk of getting MS based on similar mechanisms to smoking and solvent exposure. 

Another aspect of particulate matter air pollution exposure is that it drives comorbidities and is therefore likely to make MS progress more quickly. The second paper (below) in this week’s BMJ is quite shocking in that it shows you how high the health burden is for particulate air pollution, at a general population level. Is there anything we can do about this? Yes, there is. We need to nudge our politicians whenever we can to enact legislation to clean up the air that we have to breathe.  I am aware that there are retrograde steps in the US to reverse some of the clean air legislation; this should be resisted. My heart goes out to people living in low- and middle-income countries who will have to wait for a generation or two to get to the point when air pollution drops to safer levels.

Why should people with MS be exposed to unnecessarily high levels of air pollution that are likely to make their MS worse? 

Why should people at high risk of getting MS, be exposed to environmental pollutants that may push them over the “autoimmune tipping point” resulting in them developing MS?

Part of our lifestyle and wellness campaign is focusing on environmental health; air pollution is one of the things that impact wellness. Our marginal gains management philosophy has just acquired another component; environmental pollution. Do you agree? 

Heydarpour  et al. Potential impact of air pollution on multiple sclerosis in Tehran, Iran. Neuroepidemiology. 2014;43(3-4):233-8.

BACKGROUND: Multiple sclerosis (MS) incidence has dramatically increased in Tehran, Iran. The health impact of air pollution in Tehran underscores the attention to a possible association to this environmental risk factor. In this study, the authors aimed to analyze the spatial distribution of prevalent MS cases and their association with the spatial patterns of air pollution.

METHODS: Patient records meeting McDonald’s criteria for definite MS diagnosis with disease onset during 2003-2013 were obtained. Next, the location of 2,188 patients was successfully geo-referenced within Tehran metropolis by geographic information system (GIS) bureau of Iran’s post office based on their phone numbers. A cluster analysis was performed using the average nearest neighbor index (ANNI) and quadrat analysis. The long-term exposures of MS patients to particulate matter (PM10), sulfur dioxide (SO2), nitrogen oxide (NO), nitrogen dioxide (NO2), and nitrogen oxides (NOx) were estimated using the previously developed land use regression models.

RESULTS: Prevalent MS cases had a clustered pattern in Tehran. A significant difference in exposure to PM10, SO2, NO2, and NOx (p < 0.001) was observed in MS cases compared with controls.

CONCLUSION: This study revealed the potential role of long-term exposure to air pollutants as an environmental risk factor in MS.

Wei et al. Short term exposure to fine particulate matter and hospital admission risks and costs in the Medicare population: time stratified, case-crossover study. BMJ. 2019 Nov 27;367:l6258. doi: 10.1136/bmj.l6258.

OBJECTIVE: To assess risks and costs of hospital admission associated with short term exposure to fine particulate matter with diameter less than 2.5 µm (PM2.5) for 214 mutually exclusive disease groups.

DESIGN: Time stratified, case-crossover analyses with conditional logistic regressions adjusted for non-linear confounding effects of meteorological variables.

SETTING: Medicare inpatient hospital claims in the United States, 2000-12 (n=95 277 169).

PARTICIPANTS: All Medicare fee-for-service beneficiaries aged 65 or older admitted to hospital.

MAIN OUTCOME MEASURES: Risk of hospital admission, number of admissions, days in hospital, inpatient and post-acute care costs, and value of statistical life (that is, the economic value used to measure the cost of avoiding a death) due to the lives lost at discharge for 214 disease groups.

RESULTS: Positive associations between short term exposure to PM2.5 and risk of hospital admission were found for several prevalent but rarely studied diseases, such as septicemia, fluid and electrolyte disorders, and acute and unspecified renal failure. Positive associations were also found between risk of hospital admission and cardiovascular and respiratory diseases, Parkinson’s disease, diabetes, phlebitis, thrombophlebitis, and thromboembolism, confirming previously published results. These associations remained consistent when restricted to days with a daily PM2.5 concentration below the WHO air quality guideline for the 24 hour average exposure to PM2.5. For the rarely studied diseases, each 1 µg/m3 increase in short term PM2.5 was associated with an annual increase of 2050 hospital admissions (95% confidence interval 1914 to 2187 admissions), 12 216 days in hospital (11 358 to 13 075), US$31m (£24m, €28m; $29m to $34m) in inpatient and post-acute care costs, and $2.5bn ($2.0bn to $2.9bn) in value of statistical life. For diseases with a previously known association, each 1 µg/m3 increase in short term exposure to PM2.5 was associated with an annual increase of 3642 hospital admissions (3434 to 3851), 20 098 days in hospital (18 950 to 21 247), $69m ($65m to $73m) in inpatient and post-acute care costs, and $4.1bn ($3.5bn to $4.7bn) in value of statistical life. 

CONCLUSIONS: New causes and previously identified causes of hospital admission associated with short term exposure to PM2.5 were found. These associations remained even at a daily PM2.5 concentration below the WHO 24 hour guideline. Substantial economic costs were linked to a small increase in short term PM2.5.