The Culprit Behind Disease: It's More Tricky Than You Think

In my last post, I touched on a few of the dramatic differences - inequalities -  in the health status of the U.S. population. I promised that I'd begin shedding some light on the causes of these health inequalities. And I will.  But in order to do so properly, I'll need to step back for a moment and talk about a crucial epidemiologic principle: causality. 


A natural human tendency is to side with personal anecdote over data-driven automaticity.  The power of emotion comes through in a news clip depicting a mother with an autistic child, weeping as she describes taking him to routine immunizations like a responsible parent.

 Data-driven automaticity, on the other hand, is text in a journal article, sometimes translated on airwaves through the remarkably monotone voice of a bespectacled gray-haired gentleman in an imposing white coat, who uses phrases like "The hypothesis of association appears poorly justified, with reasonable certainty, given our existing body of evidence" to say things like "No."

In the eyes of the general population, it's no contest.*

(* The hyperlink opens to an article which covers a recent grand preventive medicine snafu in translating an "evidence-grounded" message for the general public:  the mammogram screening controversy. Communication problems partially furthered the general public outcry that followed new mammogram screening guidelines calling for raising the age when women should start getting screened.)

The power of emotion and anecdote is so great as to render former Playboy models reater authorities on neurobiology than the hyper-educated, bespectacled physician. Despite a lack of scientific connection between vaccines and autism, emotion fuels a sizeable and growing group of fervently anti-vaccine parents. (Whose impact, by the way, is already evident in places like Marin County, dealing with a sudden surge in kids coming down with preventable whooping cough and diphtheria.)


The science of epidemiology, unfortunately, may partially be responsible for the case of the doctor who seems to have a knee-jerk tendency to qualify and add caveats to every recommendation.  A truth of life is that the more you delve deeper into learning something, the less you realize is absolutely certain. (Besides death, I suppose, and taxes.) Epidemiology takes this to the hilt: take a few classes in the subject and you feel as though a joyriding teen just vandalized your brain. Suddenly, everything you thought you knew, and everything you thought you knew about knowing how to know, is suspect.  (See what I mean? I've just been studying epidemiology, and that's a classic post-epidemiology-studying statement.) Doctors' seemingly cautious, throat-clearing flourishes simply reflect belief in the limits of scientific analysis. (Or, for the cynics among us, fear of getting sued.)

This article takes it to the hilt, in true epidemiology style: can we really believe most of what we find in evidence based medicine?

As irritatingly exhausting as it is, epidemiology is also incredible. It combines everything you learned in grade school about the "scientific method" - forming and testing a hypothesis, performing experiments, analyzing results - with the thinking calisthenics of philosophy and logic, the liberal arts perspective of history and sociology, and the formula-based precision of calculus, accounting and statistics.  You can see why it's exhausting; almost as exhausting as writing that sentence.

At the core of epidemiology is piecing apart the puzzle of what causes disease and what prevents disease.

It's a puzzle that most of us have pondered at one time or another. You hear of the tragic situation of an avid cell-phone user who is diagnosed with brain cancer, for example, and wonder whether cell phones cause cancer. Or, you get a call from Aunt Mildred, who just got the flu shot and now feels horrible, like she's getting the flu. She's convinced the flu shot "caused" her to get even sicker.

A patient in San Francisco may buy a bottle of kombucha after a friend raves about its energy and health benefits (not to mention an enticing label boasting of potential benefits for everything from digestive health to warding off cancer). A Berkeley patient, on the other hand, might avoid peanuts on Tuesday, fast on kale juice on Wednesday and otherwise "is gluten/soy/dairy-free because everything else causes my system to be messed up."

We make associations all the time. But isolating whether X caused Y  is a trickier proposition. It respects the fact that sometimes, things just happen to coexist by random, non-causal chance. "Causality", though, requires more than one isolated person (or even a few people) happening to have a certain outcome when they have a specific "exposure" - whether a flu shot or cell phone.

 And even when you can show two things are associated  - ie, more cell phone users tend to have brain cancer - does not mean that the link is causal, i.e. that cell phone use causes brain cancer.

Our classic go-to example is matches and lung cancer. If you did a study where you tracked rates of matches and rates of lung cancer in a population, you could quickly see an association between numbers of matches and cancer. It could look quite convincing, with rising numbers of matches linked to higher cancer rates. You could probably repeat the study in many different settings and come up with the same result.

But matches aren't the cause of lung cancer. The culprit is what the matches are used for - i.e., smoking cigarettes, which we commonly accept promotes lung cancer. (Bear with me here and pretend that cigarette lighters haven't been invented yet, so people use matches to light up. You could do the same thing with "lighter use" if you wanted.)

It's quickly apparent how carefully teasing apart the cause of an outcome is crucial to effective policy. Even though matches were associated with cancer in our study, calling for a policy that bans matches would hardly target the root cause of cancer. And it would negatively affect people who use matches for other things, like moms lighting candles on birthday cakes, or overachieving eighth-graders reproducing that authentic yellowed hue of 18th-century parchment paper for a history project on the Declaration of Indepdence.

Epidemiology lays out how you can take data that tracks exposures (ie, matches) and outcomes (ie, cancer) for a large number of people and analyze it to see if 1) there actually is a "real", non-chance kind of link and 2) if  that link could be causal. It's the holy grail of the science: trying to figure out if a curious pattern we perceive or wonder about is actually real on a population scale. In other words - does Aunt Millie's experience with that flu shot translate to a "real" side effect seen by the population? Is there evidence that the flu shot can "cause" the flu in people?  (For the record, the answer is no.  Get  your flu shot!)

An inherent conflict between science and our mind: human beings naturally "want" the world to follow intuitive observations. And sometimes, intuition is in fact the way the world works. But sometimes, science doesn't follow our logic.  After all, the earth is round and rotates around the sun - even though the sun seems to circle above us, rising and setting on a fixed, flat horizon.

That our observations may not necessarily explain the full picture holds with the realm of causality as well. Take the following example. The circle is what epidemiologists call a "causal pie": it represents the component causes of a disease. Each thing in the circle has to happen for a person to get the disease. If just one piece is "prevented", the person won't get the disease.

But there's a catch: for most diseases, no-one knows what all the pieces of the pie actually are. Our best guess at the pie's structure come from our basic knowledge, scientific experiments and observations - a collection of inputs based on theories and the patterns we see.

For example, if the disease is being overweight, a very simple model might say that A represents a gene for overweight, B is overeating, and C is not exercising.

Now, let's say that in Population 1, everyone has a gene for overweight (A) and everyone overeats (B). About 10% of people don't exercise (C) - and are therefore overweight, since they have A, B, and C and complete the pie. Thus, it's observed that the 10% of the population who are overweight ahappen to be non-exercisers. It's the only thing that seems to differentiate the overweight group from the rest.

 So what would an observer logically conclude about this population? Being overweight a behavioral thing - it's caused mainly by not exercising. Exercise seems like the "magic switch" that "prevents" and "cures" overweight.

Now take another population. In this population, everyone is a non-exerciser (they have C) and everyone overeats (B). 10% of the population has a gene for being overweight - and thus, this 10% ends up becoming overweight, with pieces A,B, and C completed.

 Then, scientists come up with a miracle drug that blocks the gene and give it to overweight people, and voila!  The drug cures weight gain in 10% of the population.

In this population, the magic switch seems to be a gene - the only thing that seems to differentiate the overweight group from the rest. What do people in this population conclude? Being overweight is genetic - it's caused by a gene, not behavior.

In reality, preventing any one of the pie pieces could have prevented overweight effectively. In fact, if a smart scientist somehow knew that overeating - something that no-one thought -  caused overweight, and somehow was able to prevent people from overeating  - then he could prevent everyone in both populations from being overweight. This intervention would have a larger scale impact in both populations.

Obviously, real life is much more complex. But the point of all this holds: When thinking about what causes a disease, the pie pieces that are the most common causes in a population are often the least recognized.   On the other hand, the pieces that are present in a relatively small percent of people are quickly identified as the "magic switch", and are often the focus of prevention efforts.

Sometimes, these observably different pieces indeed represent the best - and most "do-able" - approach to prevent disease, given our incomplete knowledge of the pie's full structure. But sometimes, the prevention strategy with largest potential impact rests on undiscovered, commonly present pie pieces - those that affect most of the population. Finding these pieces requires thinking outside the box.

 For example, some scientists are starting to wonder whether being overweight is linked to a commonly present virus. (To see how this could happen, replace the "overeating" pie piece B with "virus".) Mind-boggling, no?

There you have it - a quick intro to causality. Next post- as promised - applying causality to a practical situation: health disparities and health outcomes.

Differences in Health: Thinking about the Puzzle

Show me someone who eagerly goes through 23+ years of school, and still eagerly seeks more - and I'll show you someone whose hobby is thinking.

I've always been the type of person who likes to think about things. Not just academic things; food, movies, books, art are all fair game. Sampling a carrot-ginger bisque at a farmers' market, my mind will try to pick apart the ingredients; coming across a snazzy web page, I'll ponder its construction;  reading a thought-provoking essay in the New Yorker, I'll wonder how many caffeine-fueled hours of coffee-shop-loitering it took to produce that article. (For the record, people who tell you they love to write are usually lying: writing itself is like slow torture, but the finished product is usually well worth it).

I've heard that thinking too much is the root of all misery, the flip side of the "ignorance is bliss" argument. (Or, perhaps, that is something I thought up while in a state of thought-induced angst.) Indeed, thinking has gotten me into trouble a few times (see: accidentally walking into glass doors, wandering into oncoming traffic at red light, struggling for eons over exactly which falafel joint to visit for lunch.)  If the mind were a muscle, mine often feels like a marathon runner's toes: weathered, achy and bruised, under-appreciated and overused.

Maybe thinking isn't for the faint of heart. And yet, as the eternal optimist that I am, I see it as a the first step to positive change, to solving problems. It's hard to get to the stage of doing unless you know 1) what you want to do and 2) why it makes sense to do it. And thus, enter the stage of thinking.


 In health, history supports this notion. A deadly cholera epidemic in London in the 1800s was unraveled by a physician who thought about the underlying pattern of cases - instead of simply treating every case as it appeared - and localized the source to a faulty water pump. A life-saving antibiotic, penicillin, was accidentally discovered by a scientist who thought about the strange mold that had grown on his bacteria cultures -  instead of passively discarding it a spoiled experiment - and found that the mold actually killed bacteria.

Thinking is the championed cause of public health and preventive medicine. In a test tube, a bacteria triggers infection; a mutation of a cell incites cancer; an inherited faulty gene produces a characteristic disease. But in society, illness doesn't follow pure test-tube predictability. Public health physicians tease apart the puzzle of disease, outlining patterns of individual illness with tools of epidemiology.  Recalling the words of esteemed epidemiologist Dr. Roy Acheson:: "Why did this person get this disease at this time?"

After seeing patients in the hospital, I'd spend many hours thinking about this question - about patients' differential experience of illness.  I was inspired by the pockets of intelligence, quality and compassion present in the US medical system - the caring colleagues who put needs of patients before their own, mentors who patiently taught residents, episodes of high-quality care successfully healing patients with devastating disease.  And yet, I was troubled by the gaps in health: patients who couldn't afford drugs or lacked insurance; who died, suffered through emergency surgery or were committed to expensive, lifelong drug therapy for  preventable and easily fixable conditions.

I thought: why were some patients able to quit smoking, but not others? Why did some patients seem to end up on five different blood pressure medications, while others needed none? Why did certain patients return time and again to the emergency room with the same, chronic symptoms, while others were permanently cured?

 Why, fundamentally, did some people seem to have better chances of better health?

Thinking led me to others thinking about the same questions, and I began finding clues: the role of environment and the community on health. Social influences - peer community, education, the "built environment" affects health by molding behavior, self-esteem, self-efficacy, and prioritization of health. 

Take this 2006 study in the Public Library of Science, where researchers' analysis of health data revealed a United States of "Eight Americas" - eight broad geographic regions with strikingly different levels of health. They reported the following findings: 

• The ten million Americans living in the healthiest region - "America 1" - enjoyed one of highest average life expectancies in the world, even higher than long-lived residents of Japan. 
• Meanwhile, the residents in the "lower America" regions had average life expectancies "more typical of middle income or low-income countries". The lifespan difference separating groups at both extremes stretched to nearly thirty-five years.  
• American Indian men in South Dakota died at age 58, on average, nearly 20 years earlier than white men living in the rural north. 
• Most differences in the death rates were from differences in rates of violence, injury and chronic disease - in other words, conditions which could be treated or prevented. 
• The gaps in health outcomes between groups - and the relative order of the groups - had not changed significantly since 1987. 
• Insurance coverage ("access to care") and use of health care services (ie number of visits to a clinic or emergency room) did not fully explain the differences in health outcomes. That is, the difference in death rates separating groups was much greater than the difference in rates of health insurance coverage.    

This national pattern of wide variation in health translates to the county and state level. "Shortened Lives", a groundbreaking 4-part series in the Contra Costa Times, reported on how decades of variation in life expectancy -  and marked differences in rates of homicide, asthma, heart disease and cancer - separated Bay Area counties that were just digits apart in zip code:

•  Life expectancies ranged from 87.1 years in the Walnut Creek suburb to 71 years in crime-heavy Sobrante Park outside of Oakland. 
• Residents of "hardscrabble" East Bay neighborhoods had rates of heart disease and cancer almost tripling those in wealthier residents.  
• Hospitalization rates for children with asthma soared in the lowest-income neighborhoods outside of Oakland, with nearly a fourth of children returning to the hospital within less than a year of being discharged. 
• The variation was not a discrete "rich-are-healthy", "poor-are-unhealthy" pattern - it instead showed a gradient along the socioeconomic ladder. That is, middle class communities were healthier than poorer communities, but less healthy than the most affluent communities. (Much more to come on this "gradient" in future posts.)
• Counties with greater insurance coverage were healthier than those lacking such coverage. But coverage rates did not fully explain the health gap: counties with similar rates of insurance coverage and numbers of doctors and hospitals still had different levels of health (with richer counties on average experiencing better health). 

Further evidence highlights the reality that ethnic group and minority status arises as a predictor of health: 

• A study comparing the health of African American and Caucasian residents in 256 U.S. metropolitan areas. found that African Americans had 81% higher premature death rates on average. 
• A nationwide survey conducted by the CDC analyzed rates of disability and asked people  to "rate" their own health. (Such "self-ratings", by the way, are actually good predictors of objective health outcomes like death and disease rates). The survey found a distinct pattern by race: almost one-and-a-half-times the number of African-Americans and triple the number of Hispanic adults reported their health as "fair" or "poor" compared to white adults. 
• In that same study, almost three times as many Native Americans experienced disabilities or mental health problems compared to Asian-Americans.

The issue of ethnicity, race and health could merit an entire blog by itself - and scores of books cover this topic.(And much more will follow in this blog about the patterns above.) But for now, a preview of why the ethnic link to health is a fundamentally unnatural and illogical phenomenon.  

 Researchers who have dedicated their lives to the subject conclude that there exists no basic biological or genetic explanation for why health should differ so markedly based on skin color. Genes certainly play a role in some diseases. There are lists of genetic diseases known to concentrate in particular ethnic groups (lists which medical students nationwide are currently cramming to pass medical school): Tay Sachs disease in Ashkenazi Jews; sickle-cell anemia in African-Americans;  hypokalemic periodic paralysis in Asian-Americans.  And, there is even evidence that some ethnic groups respond uniquely to commonly prescribed medications. (This is the motivation for physicians who admit to the health benefits of  racial profiling in medical practice.) 

But the vast ethnic health differences in death and disease  don't arise from genetic culprits like Tay Sachs disease or sickle cell anemia. They come from controllable things like smoking, homicide, heart disease. 

 Moreover, a fact of science is that simply having a gene does not guarantee its expression. (Twins with exactly the same genes, for example, have different health outcomes when placed in different environments. The study of how genes are expressed - epigenetics - is a whole, mysterious and fascinating field in itself.)

Repeatedly, studies confirm that biology and genes alone do not explain the variation in health by race, community or gender. In short, differences in people of the same ethnicity far exceeds the genetic variation between groups (one expert categorically notes, "race does not account for human genetic variation, which is continuous, complexly structured, constantly changing, and predominantly within races.") Some geneticists argue that skin color is a flimsy facade of difference - that there is, in fact, little real biologic basis for "race." 

So it's not genes or biology, but social structures and community environments - the social determinants of health -  that explain the patterns of health detailed above: the "Eight Americas", the ethnicity-health link, the zip-code predictor of lifespan. 

I became motivated to make a difference in health by tackling these root causes, and that motivation led me to the Kaiser Permanente Community Medicine Fellowship. It's an amazing experience; every day, I tackle systems-based issues that undermine community health, while also delivering direct clinical care to patients in need.

 But most rewarding is the group I work with: a talented, inspired and passionate group of fellows who work tirelessly to boost the health of the community they serve. Together, we work to improve the health context of our patients, transforming their vision for health and sustaining the work we do in the clinic setting. 

In the entries to come, Community Medicine Fellows will share their knowledge and experiences: pictures, reflections, questions, dilemmas, and practical insights. This is a forum for interaction, discussion and learning - helping us to stay connected but also to teach each other and grow in the process of becoming compassionate physicians.

It's going to be a great year.  Here's to making a difference.

How Doctors Think: The Role of Evidence Based Medicine

Think of the last time you went to the doctor. ( If you're anything like my dad, you've put it off for eons, pledging something like "I'll go and get my cholesterol checked after I get back into my regular exercise routine - you know, make the results more realistic,"...every three months.)


 Maybe you dreaded the encounter, wondering if that extra piece of cheesecake - consumed against the counsel of your stern inner food-guardian last week - might tellingly manifest to the physician-detective in your blood pressure, weight or blood sugar reading. Maybe you went because you ran out of your medication - and exhausted that convenient telephone-refill option where you didn't have to see anyone in person, darn it! Maybe it you needed a quick fix for something urgent - a rash, a nagging ache, a high fever. Or maybe you went because you actually like going to the doctor...and it'd been a while, and you want to be proactive about your health. (And you also eat 6 servings of vegetables daily, file your income tax return several months before it's due, stick to a grocery list and never lose pens. We physicians tend to love you.) 


Your doctor probably saw you, was hopefully pleasant and cordial, maybe clucked a little bit at your still-high blood pressure or lab tests, adjusted some medications, perhaps asked you how life was going. Maybe reminded you to lose some more weight, stop smoking, eat better. You nodded and maybe squirmed, remembering that dinner date at the fondue restaurant you have on Friday.  


And done - no more doctor visits for another year, phew!


But have you ever wondered: how, exactly, do we know what needs to be done to fix your symptoms? 


In other words: why is it that sometimes, you feel absolutely lousy, with aches and pains everywhere and just know you need an antibiotic to make this go away, and your doctor  tells you to take Tylenol and return if things don't get better? Or, why, when you go visit your doctor to check on that mild headache you've been having for a little while (mostly in the hope that your wife will finally stop nagging you), they order an immediate head scan and send you to a specialist? 


Technically, the answer requires going to medical school (and is apparently worth an average $250,000 and change). But the basic recipe is not in fact that mysterious. Doctors base many of their decisions on the results of scientific studies, also known as "evidence-based medicine". 


In the world of Western medicine, evidence-based medicine is King. 


It's why, when Over-Enthusiastic Resident pipes up during rounds in the hospital with a suggestion to order a certain lab test or change an antibiotic for a patient (not that this happened to, say, me or anything),  the attending raises an eyebrow and questions: "Really? What did the latest study show about that option?" 


The studies usually have hokey - I mean, catchy - acronyms like ASPIRE, HOPE, POISE to increase Google-ability and promote easy recall, so that Know-It-All Resident (who carries the "Scientific Study Update Alert" app on his PDA and an e-mail account dedicated to late-breaking medical study news)  can neatly chime in: "Well, Dr. Intimidating Attending, the UTOPIA trial showed that there was a 40% reduction in all-cause mortality when Drug Miracle was given compared to placebo." And the attending beams with satisfaction (while Over-Enthusiastic Resident wonders when she can sneak away to the nutrition room to grab graham crackers.) 


EBM inspires a knee-jerk reflex. Discuss whether to order an x-ray, prescribe an antibiotic, take a multi-vitamin every day, get a prostate exam: "What does the evidence show?"  On the flip side, appending the magic phrase "According to Widely Accepted Clinical Trial X," to your treatment plan highly increases the chance of being taken seriously.


EBM is how doctors know that when your cholesterol is a certain value, it's time to start the statin. It's how they know whether or not they should order an MRI for that low-back pain or just reassure you that it will go away. It's how  they know the prognosis for a cancer, make a decision that women under 40 don't need mammograms, that the 3-year old with an earache doesn't need antibiotics. 
The prevailing reign of Evidence-Based Medicine is why, sometimes, things that may seem like "common sense" to the general public are announced as ground-breaking findings on CNN.  ( "New study shows that eating food reduces hunger," "Study suggests sleep-deprived residents make more mistakes in treating patients.") 

This is mostly because sometimes, things that may seem like common sense to us aren't in fact borne out by EBM. ("Study suggests no benefit to daily multi-vitamin," or "Cancer patients practicing "positive thinking" do not have better outcomes, according to new study,") 


The best studies analyze health outcomes over large groups of people, hopefully a group of people which are similar to the type of patients the doctor treats. (If the study group consisted of 90% African-Americans and few Asian people, you might wonder if the results of the study could apply as well to Asians.) When a well-designed study finds, for example, that patients with high cholesterol treated with a statin had a 50% reduction in their "bad cholesterol", that might motivate a physician to prescribe that drug for you when you have high cholesterol. 

(Warning: there are many, many caveats to interpreting studies - which will come in later posts. As a preview: statins are now the topic of some controversy - even though they are linked to reduced cholesterol buildup in arteries, not much evidence supports the notion that statins prolong life in patients who don't have known heart disease. In evaluating a study, one needs to ask: what health outcome matters most? Living the longest number of years? Avoiding a heart attack? Living a chest-pain/disability-free but maybe shorter life? Avoiding side effects of chronic medication, even if it means maybe increased chance of a heart attack? Controlling the lab test result to normal ranges? You get the picture....it's complicated.)


The key point is that the treatment for an individual patient is governed mostly on results seen in groups of people in studies - who may or may not be very similar to you. An intelligent physician will, of course, use 'clinical judgement' in deciding whether the results are relevant to your particular case. (Sometimes, well-meaning but very very insistent moms or siblings insisting upon an antibiotic will heavily influence this 'clinical judgement'.)


In fact,  individualizing treatment is arguably where the true "art" and "skill" of medicine really lies. All physicians can read a study, but skilled physicians intelligently interpret the findings and know how to tailor treatment for a particular patient's case.


EBM can be a good thing: It reduces inconsistencies and impulsiveness from the process of treating patients (things you don't want in your rational, intelligent physician-treater). It lends external support and validation to our choices. It provides justification for why we make certain decisions. And it allows us to sort with logic through the maze of drugs, treatments, tests and options we have to make you feel better. 


It can also be a less-than-good thing. For a rushed physician, EBM can become a substitute for thinking about you, individually - your personal situation and environment. (Example: if people in a study got better after taking a new drug every day for 6 months, but Patient X in the doctor's office just lost his job and might take the drug only once a week because he can't afford it, would the drug still work? Or could sporadic use even cause harm?) It can encourage "cookie-cutter" medicine. And if the studies that guide our decisions are incomplete, flawed, or suffer from conflict-of-interest issues,  then health is potentially undermined. 

This last point is troubling. Take Vioxx:  a medication widely used and prescribed for pain and inflammation from 1999-2004 after selectively published studies (released by Vioxx drug manufacturer Merck) touted its purported effectiveness with fewer side effects. In 2004, the drug was pulled off the market after a study showed Vioxx may have provoked 27,000 heart attacks and deaths. Leaked emails and studies uncovered in the ensuing lawsuit revealed that that Merck executives had known about the troubling heart attack findings three years earlier - but had not released the data to the public. 


Vioxx was the center of a major scandal, but truly frightening is the unpublicized subterfuge that is strikingly commonplace in medical literature. Take the practice of ghostwriting of medical studies, referring to  "pharmaceutical companies secretly authoring journal articles published under the byline of academic authors."  Often, authors of the article are listed as respected academic physicians from top-notch university medical centers- inspiring readers' trust in the quality of the study - but are actually written by pharmaceutical-company researchers. And policies against ghostwriting are strikingly sparse: A February 2010 survey in PLoS Medicine revealed that only 20% of the top 50 academic medical centers in the U.S. carry regulations or rules against ghostwriting. The result:  fatal flaws in the objectivity of published research -  those very studies that residents/medical students/experienced physicians/hospital staff use to guide their clinical decisions.


Digressions aside, how is this discussion of EBM relevant to public health? 


First of all, public health training lays the essential skills for constructing high-quality, sound EBM on a population level.  Public health training is centered on learning how to study disease patterns and study its effects, properly designing and conducting a clinical trial, and - crucially - how to interpret and analyze the results of a study published in a scientific journal and apply such results. Things that you would, ideally, want your physician to know well. 


(Unfortunately, most physicians in the U.S. do not receive rigorous training in public health, apart from a cursory lecture or three during medical school, and maybe some exposure in residency if they seek it out. A troubling health issue in itself - but much more to come on that in a later post.) 


But the second, crucial and likely counterintuitive point, is that public health actually inspires physicians to think about you as an individual. It inspires your treatment plan to be tailored to your circumstance, to your specific situation. It inspires the "art" of medicine. 


Think carefully about this second point. Most people, if they happen to know what public health involves, will say "Public health is studying health of populations." Many public health students will say, "Public health is studying health of populations."  Before I began studying at Berkeley, I said, "Public health studying health of populations."  


I still say confidently that public health involves studying the health of populations. But in thinking and studying about health from a population angle, something happens. 


It's the realization that treating disease successfully requires understanding the context of the individual. 


Public health icon Dr. Roy Acheson - founder of Yale's department of chronic disease epidemiology and the Rockefeller Foundation's International Clinical Epidemiology Network - enunciated the crucial question of public health: "Why did this patient get this disease at this time?"  


Here's a little example. Thousands of germs float around the air every day. The germs that cause coughs and colds will invariably end up on our hands, in our noses, maybe even inside our throats where they can multiply and produce that tell-tale scratchiness that leads to a full-blown cold. 

But while some people come down with a cold, others with that same bug don't end up getting sick, even though that germ is nestled right where they could wreak mucus-y havoc.  


It goes on. Some women with a gene for breast cancer won't end up getting the disease, while others with the gene will get breast and ovarian cancer before the age of 30. Someone who smokes for 80 years escapes lung cancer, while someone who smoked irregularly for 5 years dies of cancer after 2 months.  Some people who take a drug for blood pressure respond immediately, while others are on 10 drugs. 


What causes some people to get sick and not others? What causes some people with a gene to get a disease but not others; some people to respond to a surefire treatment and not others?  Why do African American males die from cancer at nearly 75% higher rates rate than Hispanic males? Why are a greater proportion of poor people also overweight? Why do residents of Japan live nearly 20 years longer than Americans? Why is providing vitamin A supplements to Ugandans suffering from vitamin-A-caused night blindness not effective? 


It all goes back to that question:  "Why this patient, why this disease, why at this time?" Unlocking the answer requires linking the population health patterns evident in EBM to the "real-world", individual experience of disease. It is public health's central puzzle; figuring it out is an essential step in creating a prevention and treatment strategy that boosts health. 


So now that you're hopefully on board with the public health parade, I'll continue to share insights here as I begin the lengthy task of cracking the health puzzle. As a preview to what's coming next: it turns out that the social and environmental factors play a larger role in disease than one ("one" meaning my naive pre-public-health self) might think. 

Public Health, Defined...

What's a surefire way to instantly animate a seemingly quiet public health professional? Ask them what public health actually is. 

Like "hipster", "centrist" or "slow food", it's one of those nebulous things you think you know, but maybe not.  My public health professors here seem determined to make sure we accurately understand what we're getting into. In the Powerpoint-governed dictatorship of modern education, Slide #1 of about 10 lectures thus far consistently asksd "What is Public Health"? 

It's actually an interesting question to ponder - especially since most people apparently don't. In fact, a recent survey conducted by the Public Health Brand Identity Coalition found that 80% of Americans "did not think that public health had touched their lives in any way." 

But as Berkeley healthcare journalism lecturer David Tuller notes, that's the point of public health: to be invisible. 

Successful health interventions prevent bad health forces from happening - in fact, making them so rare that they're just historical curiosities, or plot elements of an action movie.


In the U.S., we don't habitually wake up each morning thinking of all the water-borne diseases or diarrheal outbreaks we're escaping as a result of sewage systems, or gleeful that our risk of contracting polio hovers below 0.001%.  But those vaccine campaigns which have rendered smallpox virtually extinct, and the late 19th-century movement in the United States to establish sanitation systems are silent successes of public health. 

We are often acutely aware when public health intervention is needed - when the system is "failing": We notice when eggs are pulled off the shelves, when there's a violent shooting in a public school, or when a hurricane devastates a city and its residents need help in the face of a chaotic, disorganized response. 

Likewise, doctors may not miss the cases of childhood mumps or hookworm outbreaks - diseases generally prevented by effective public health interventions.  But most practicing physicians sense that they seem to be treating a lot more patients with high cholesterol, obesity and diabetes, or that more of their patients can't pay for their healthcare. They diagnose pregnancy in a fifth-grader coming to clinic with abdominal pain and swelling in inner-city Detroit, life-threatening skin infections in a 500-pound patient who couldn't bend over to properly clean himself, tuberculosis in a homeless uninsured man who can't afford the drugs needed to treat him (and prevent its spread to others). 

 These health issues arise from population-level root causes:  they fall under the purvey of "health", and the mission of a public health professional is finding effective measures to prevent them from happening. 

Dr. George Benjamin, director of the American Public Health Association and emergency-room physician (quoted in Dr. Tuller's article), explains the distinction between individual treatment and population-wide prevention as follows. "I tell people that when someone would come into the room with a rat bite, I took care of the rat bite...if ten people came in with rat bites, the best public health intervention I could do would be taking out the rats - solving the problem versus providing clinical care." 

So how do we take out the rats?  

History describes champion "rat-killers" in the field of preventing diseases spread through water and food: think turn-of-the-century hookworm epidemic among farmers in the Deep South, virtually eliminated by installing outhouses; or London's 1854 deadly cholera epidemic, subsequently halted after a polluted water pump was removed.  

Such measures are still sorely needed around the world -  2.6 billion people have no access to sanitation systems, and a third of the world's population system lives in slums. 

But in addition, in both the developing countries experiencing fast economic growth and in wealthy countries, a rising modern epidemic features "lifestyle" or "chronic" diseases as the villains: heart disease, high blood pressure, diabetes, lung disease, cancer. These diseases are now the leading cause of death worldwide - 35 million people, or 60% of deaths around the world - and 80% of deaths from chronic disease occur in developing countries. A key point: in a number of cases, the massive disability and death caused by lifestyle diseases is preventable.

The public health-oriented, practical solution to this emerging global modern epidemic is complex. Take obesity, for example. Its status as well-traveled highway to the land of "lifestyle" disease - implicated in everything from lung disease to diabetes - makes it a modern, high-priority public health target. (In case you weren't convinced, here are some facts and figures detailing America's obesity epidemic. Notable fact: 2/3 of Americans are currently overweight.)  

But how, exactly, do you go about preventing obesity? Telling doctors to remind more patients to eat healthy? Taxing soda? Giant warning labels on Twinkies? 

 The "pyramid" of public health impact, as explained by the Centers for Disease Control and Prevention director Dr. Thomas Frieden, sheds some light on the practical design of a public health strategy.

In thinking of approaches to fix a population-level issue, fact #1: All the levels in the pyramid are essential to health. 

With that said, as public health strategies move up the pyramid, those near the tip require more effort and carry a smaller impact on a population scale. (Even though it could still be an important, dramatic impact for a small group of people.)  If doctors were to counsel every single patient they saw in clinic on eating  healthy and exercising, for example (top tier) or give overweight patients a weight-loss drug (tier 2 or "clinical intervention"), the impact on health would depend on 1) overweight patients actually coming to the clinic and 2) patients willing and able to follow the counseling advice and treatment. 

Unfortunately, losing weight is tough. Eating healthy is hard when you're hungry, have a five-dollar bill in your pocket, and are faced with a choice of a cheap, filling fast food fix versus a raw apple costing $1.50. Taking a weight loss drug is difficult when it causes "icky side effects", and costs $50 per pill.  

What if you began an approach which promoted healthy eating in people before they became overweight - ie. young children in elementary school, who seem naturally capable of burning 30,000 calories a day - with healthy eating campaigns and nutrition education? This would fall under the "long lasting preventive intervention" category (tier 3)- a one-time intervention which, if all goes well, might prevent habits that could lead to obesity and ill health. 

The potential impact, while broader in scale than the approach of individually counseling or treating already-overweight patients, still depends on 1) how many schools are able to implement the program 2) the quality of such a program and 3) the durability of the program's message in influencing a child's future eating habits. 

Now imagine if people naturally made the choice to eat healthy because it is easy to do so. That is, healthy food is readily available, cheap and tasty - becoming a more "default" option than junk food.   An approach leading to this outcome - such as removing junk-food or soft drinks from schools or taxing junk food - would "change the default environment", reduce the number of unhealthy calories consumed, prevent obesity and have a potentially far-reaching impact for community health.  

The problem is, the things needed to create this 'changed default environment' are precisely the most controversial. They require laws, rules, regulations and taxes - all words that often inspire distaste in the minds of the voting public. They make public health the bad guy. (Would you want to be the one who outlawas deep-fried chicken from the American diet? I'm thinking death threats.)  Exhibit A, B, C: the backlash on smoking bans; the public disapproval over a proposed junk food tax; or the huge battle over healthcare reform. (How does healthcare reform change the default context? By providing more people with insurance, universal access would remove a  contextual "barrier" which damages health, thereby provide a default entry into the healthcare system for sick patients.) 

What about the base-tier - addressing the socioeconomic factors?


As this is the level in which I'm most interested, you can expect several future posts about the scope for public health in this area. But for now, a quick preview:


Clearly, there is a powerful between socioeconomic status and health - in rich and poor countries alike. Things that improve living conditions will, logically, improve health on a profound scale. We're already familiar with the impact of a successful base-tier public health strategy: providing poverty-stricken areas access to clean water. (In the United States, sanitation improvements introduced in urban areas in the 1900s likely drove mortality down by nearly 50%.) 

But the relationship between socioeconomic status and health goes beyond the increased chance of contracting tuberculosis or becoming malnourished among poor residents. Inequality, as well as absolute poverty, causes disease. In the United States, a country characterized by large gaps separating the rich and poor, residents of poor communities are more likely to be shot, smoke, not know how to read, be overweight and die much earlier - a staggering 35 years earlier in some counties, as a Harvard study showed. (More - much more - to come on this in future posts.). 

Addressing the persistent, socioeconomic issues currently affecting health in the U.S. - inequality, the disturbing and complex relationship between class, race, violence in urban areas, educational gaps, crime and homicide - is daunting, to say the least. But it is a key priority for social justice and, as you now know, it is a key priority for public health.


The base tier of this pyramid also happens to be why I decided to come back to school and study public health. Other than good intentions, a remarkable ability to ramble, and some mad typing skills, I don't possess much in the way of a useful skillset, at present, to combat the specter of poverty and health.


But I'm a fast learner. And if there ever was a place for do-gooding, activism, and training practical idealists, the Bay Area has to be its capital.


I'll keep you posted. In the meantime, off to study some statistics....taking it one day at a time.