T HE D R. O Z S HOW focuses on essential health issues: the proper ways to eat, relax, exercise, and sleep, and how to maintain a healthy heart. Some of the advice Oz offers is sensible, and is rooted solidly in scientific literature. Harvard: BA University of Pennsylvania: MD, MBA Columbia University: Cardiothoracic surgeon, Professor
MIRACLE DRINKS AND MIRACLE MEAL PLANS “startling,” “breakthrough,” “radical,” “revolutionary,” “miracle.” “Dr. Oz’s Three-Day Detox”; “Eat Yourself Skinny”; “Oz-Approved Seven-Day Crash Diet” Oz introduced raspberry ketones, an herbal supplement, as “the No. 1 miracle in a bottle to burn your fat.” - set off a wave of panic buying throughout the nation
1. show on whether it was possible to “repair” gay people (“From Gay to Straight? The Controversial Therapy”), despite the fact that Robert L. Spitzer, the doctor who is best known for a study of gay- reparation therapy, had recanted. 2. genetically modified foods by saying, “A new report claims they can damage your health and even cause cancer.” ” Cancer, Oz told me, “is our Angelina Jolie. We could sell that show every day.”
T YPICAL CANCER T HEMES “Five Fast-Moving Cancers” “Four Body Pains That Could Mean Cancer” “Three Cancer-Preventing Secrets” “What You Can Eat to Defeat Cancer.”
A DVOCATES P SEUDOSCIENCE Reiki: hands-on healing using ki, a life force” Not supported by science JAMA article: a nine-year-old girl conceived and executed a test in which she demonstrated that twenty-one people who claimed to be skilled in the techniques of Reiki were nevertheless unable to detect her “energy field” more often than they would have by guessing. When Oz told “no evidence showing that Reiki work”, responded: “Neither am I, if you are talking purely about data.
R OUTINELY CRITICIZED BY S CIENTISTS relying on flimsy or incomplete data distorting the results wielding his vast influence in ways that threaten the health of anyone who watches the show. Last year, almost as soon as that G.M.O. report was published, it was it was thoroughly discredited by scores of researchers on both sides of the Atlantic.
C ONSUMER F RENZY “You may think that magic is make-believe,” Oz said at the beginning of the show. “But this little bean has scientists saying they have found a magic weight-loss cure for every body type. It’s green coffee beans, and, when turned into a supplement—this miracle pill can burn fat fast. This is very exciting. And it’s breaking news.”
W HAT S CIENCE S AYS Meta-analysis of 3 studies done: “supplement produced, on average, a five-pound loss among study participants. But all three studies were short term and included a small number of participants meta-analysis authors concluded : "More rigorous trials are needed to assess the usefulness of GCE as a weight loss tool."
O Z R EPLY “We did our own study on this,” he said when I asked him about it. “ It wasn’t a classical medical study, of course, but for a television show it was pretty darn good. We took a hundred people, randomized them, and showed what academic studies have showed: you are not going to lose a ton of weight, but you will probably lose a pound a week for a few weeks. That’s better than placebo.” measured answer was almost exactly the opposite of the hyperbolic message he had broadcast into American living rooms.
F EDERAL T RADE C OMMISSION P ANEL Claire McCaskill: "The scientific community is almost monolithic against you in terms of the efficacy of the three products you called 'miracles' " "I don't get why you need to say this stuff when you know it's not true. When you have this amazing megaphone, why would you cheapen your show?... With power comes a great deal of responsibility.”
“We can spend a lot of time, Senator McCaskill, arguing the merits of whether green coffee bean extract is worth trying or not worth trying,” Oz said. “Many of the things we argue that you do with regard to your diet are likewise criticizable… It is remarkably complex, as you know, to figure out what works for most people even in a dietary program.”
“I actually do personally believe in the items I talk about in the show. I passionately study them. I recognize that often times they don’t have the scientific muster to present as fact. But, nevertheless, I give my audience the advice I give my family all the time. I give my family these products, specifically the ones you mentioned. I’m comfortable with that part,” he said.”
L ATEST : G ARCINIA CAMBOGIA “Thanks to brand new scientific research, I can tell you about a revolutionary fat buster," 2012 Show: "No Exercise. No Diet. No Effort" on the screen behind him. “ NOTE: The Food and Drug Administration does not regulate weight loss supplements. Under current law, companies selling these products do not need FDA approval before marketing them to the public.
H EALTH AND R ACE H EALTH D ISPARITIES L IFE EXPECTANCY D IET T REATMENT S MOKING A CCESS TO H EALTH C ARE
E IGHT A MERICAS : L IFE E XPECTANCY V ARIES Asians: 87.4; 82.1 Northern Plains Whites: 79 White Middle America: 77.9 Appalachia Whites: 75 Western Indians: 69.4 Black Middle America: 72.9 Low Income Rural Blacks: 67.7 High Risk Urban Blacks: 66.7 White vs. Black Men: 6.4 years difference White vs. Back Women: 4.6 years difference
C AUSES Access to health care? Not entirely less variation among the Eight Americas in the rate of health insurance coverage and the frequency of routine medical appointments than there was in life expectancy. Lifestyle, Diet? Asians lose their "survival advantage" after they are in the United States for a long time and have adopted an American diet and habits, Social perceptions? high mortality in urban black men persists even when homicide and AIDS are removed. Heart attack, stroke, diabetes, cirrhosis and fatal injuries are the major causes of reduced life expectancy in that group.
A RTICLE : I MPLICIT B IAS AND P REDICTION OF T HROMBOLYSIS Does unconscious racial bias lead to differential treatment? Methods: E-mail invitation to all 776 internal medicine & emergency residents in 4 academic medical centers in Boston and Atlanta Randomly assigned to see picture of black or white patient, matched for age and attractiveness, while they read clinical vignette Asked to rate: likelihood symptoms were Coronary Artery Disease; whether they would suggest Thrombolysis; strength of recommendation
B IAS A SSESSMENTS Explicit Bias: Direct Measure Preference for black vs. white Americans Thermometer scale Beliefs about group cooperativeness Implicit Bias: Indirect Measure Race Preference IAT Race Cooperativeness IAT Race Medical Cooperative IAT
R ESULTS Doctor Demographics: Physician race predicted IAT score – Whites higher scores Emergency room doctors smaller IAT Explicit Bias Physicians of all races expressed equal preferences, Rating of cooperativeness of patients Implicit Bias Stronger association of negative attributes to blacks
C ONCLUSIONS Implicit bias against blacks negatively correlated with likelihood of recommending thrombolysis for black Implicit bias against blacks positively correlated with recommending it for whites Suggests unconscious bias may influence treatment decisions
L IMITATIONS OF S TUDY Selection bias in doctor sample Low response rate Academic physicians who may have less experience in thrombolysis Computerized presentation of patient, not actual patient-doctor interaction Thrombolysis not recommended for patients with diabetes, hypertension, which are more likely in black patients
L UNG C ANCER & R ACE Rates Black & Hawaiian American: 50% Higher than Whites Hispanic & Japanese American: 50% Lower than Whites WHY?
Diet, Socioeconomic Status, Occupation ? Not Likely, once factors controlled for Nicotine Sensitivity:
O BJECTIVE “To determine if racial disparity in breast cancer survival is primarily attributable to differences in presentation characteristics at diagnosis or subsequent treatment.”
M ETHODS Compared: 7375 black women 65 years and older diagnosed between 1991 to 2005 3 sets of 7375 matched white control patients selected from 99 898 white potential controls using data for 16 US Surveillance, Epidemiology and End Results (SEER) sites in the SEER-Medicare database.
black case patients were matched to 3 white control populations on demographics: (age, year of diagnosis, and SEER site) presentation (demographics variables plus patient co- morbid conditions and tumor characteristics such as stage, size, grade, and estrogen receptor status) treatment (presentation variables plus details of surgery, radiation therapy, and chemotherapy). Outcome Measure: 5 Year Survival
R ESULTS Absolute difference in 5-year survival 4.4% lower in black women 3.6% lower for blacks than for whites when matched for treatment. In the presentation match: fewer blacks received treatment (87.4% vs 91.8%), time from diagnosis to treatment was longer (29.2 vs 22.8 days) use of anthracyclines and taxols was lower (3.7% vs 5.0%) breast-conserving surgery without other treatment was more frequent (8.2% vs 7.3%4).
T REATMENT DIFFERENCES N OT E XPLANATION FOR S URVIVAL D IFFERENCE Nevertheless, differences in survival associated with treatment differences accounted for only 0.81% of the 12.9% survival difference. What accounts for difference?
C ONCLUSIONS AND R ELEVANCE “These differences in survival appear primarily related to presentation characteristics at diagnosis rather than treatment differences.”
L ESS A CCESS TO H EALTH C ARE black women get less health care over all Screening and early detection campaigns may have failed to reach black communities. Cancer is more advanced by the time they see a doctor
2013 C ENSUS DATA Median Income: $50, 895 No change since 1980 Poverty Threshold ( family of 4): $23,283 Overall Poverty rate: 15% 46.5 million Americans Higher Rates: Black, Hispanic, children, single- mother families; age 65 or older
M EDIAN I NCOME VARIES BY R ACE /E THNICITY Asian household: $68,000 Non-Hispanic White: $57,000 Hispanic Household: $39,000 Black Household: $33,300
H EALTH & P OVERTY Lower life expectancy Higher rate of chronic disease: Diabetes Cancer Hypertension Cardiovascular Reasons for Health Disparities ?
Lack of access to health care Diet Jobs Environment Lack of information about health Peers
S APOLSKY Social Comparison: bottom of social hierarchy, even in higher income groups Social Inequality: Higher gaps associated with poorer health
M ANHATTAN S TRATIFICATION Lowest 20%: $ 9,635 Highest 20%: $389,007 Highest 5%: $799,969 Income of top 5% is 80 times higher than that of bottom 20%
L OW S TATUS IS S TRESSFUL Subordinate Baboons: Increased stress hormones Increased BP Sluggish recovery to a stressor Decreased HDL Decreased White Blood Cell Count Decreased Growth Factor
I NEQUALITY & MENTAL I LLNESS Major & Minor mental illnesses 3X more common in societies with higher inequalities After controlling for age, income and educational differences: Depression s more common in states with greater income inequality. data from over 100 surveys in 26 countries, found that schizophrenia was about three times as common in more unequal societies as it was in more equal ones.
“dominance behavioral system.” evolved psychological makeup, almost universal in mammals enables us to recognize and respond to social ranking systems based on hierarchy and power. One brain-imaging study discovered that there were particular areas of the brain and neural mechanisms dedicated to processing social rank.
wider income differences between rich and poor intensify the issues of dominance and subordination, and feelings of superiority and inferiority A new study by Dublin-based researchers of 34,000 people in 31 countries found that in countries with bigger income differences, status anxiety was more common at all levels in the social hierarchy.
Another international study, from 2011, found in particular that self-enhancement or self- aggrandizement — the tendency to present an inflated view of oneself — occurred much more frequently in more unequal societies. In US, scores on Narcissistic Personality Inventory rose as income inequality rose
“S TATUS A NXIETY ” larger differences in material circumstances create greater social distances, feelings of superiority and inferiority increase. growing inequality makes us all more neurotic about “image management” and how we are seen by others.
B ACKGROUND Correlation between poverty and counterproductive behavior: The poor use less preventive health care ; fail to adhere to drug regimens; are tardier, less likely to keep appointments; are less productive workers; less attentive parents Personal characteristics???
Z HAO, ET AL H YPOTHESIS Poverty imposes cognitive load Constantly worrying about finances saps attention Preoccupation is ever-present and distracting Leaves fewer cognitive resources available to guide decisions
L AB S TUDIES Induced rich & poor participants to think about every day financial demands Hypo: different cognitive demands for rich vs. poor
M ETHODS E XPTS 1-3 Read 4 scenarios, few minutes apart- took cognitive tests after each Scenarios described a financial problem the participants might experience. “Your car is having some trouble and requires $X to be fixed. You can pay in full, take a loan, or take a chance and forego the service at the moment... How would you go about making this decision?” Hard vs. Easy conditions
Fig. 1 Accuracy on the Raven’s matrices and the cognitive control tasks in the hard and easy conditions, for the poor and the rich participants in experiment 1.(Left) Performance on the Raven’s Matrices task. A Mani et al. Science 2013;341:976-980 Published by AAAS
E XPT 3 R ESULTS : INCENTIVES FOR CORRECT ANSWERS
Fig. 3 Accuracy on the Raven’s matrices and the cognitive control tasks in the hard and easy conditions, for the poor and the rich participants in experiment 4.(Left) Performance on Raven’s Matrices task. A Mani et al. Science 2013;341:976-980 Published by AAAS
F IELD S TUDIES 464 sugarcane farmers living in 54 villages in the sugarcane-growing areas around the districts of Villupuram and Tiruvannamalai in Tamil Nadu, India. These were a random sample of small farmers (with land plots of between 1.5 and 3 acres) who earned at least 60% of their income from sugarcane and were interviewed twice—before and after harvest—over a 4-month period in 2010. Tested pre and post-harvest
Fig. 4 Accuracy on the Raven’s matrices and the cognitive control tasks for pre-harvest and post-harvest farmers in the field study.(Left) Performance on Raven’s matrices task. A Mani et al. Science 2013;341:976-980 Published by AAAS
A LTERNATIVE E XPLANATIONS FOR F ARMER S TUDY ? Nutrition? Physical Exertion? Practice Effects?
C ONCLUSIONS “evoking financial concerns has a cognitive impact comparable with losing a full night of sleep” “effects we observed correspond to ~13 IQ points. These sizable magnitudes suggest the cognitive impact of poverty could have large real consequences”
Definition: perception and actuality that one is cared for, has assistance available from other people, and that one is part of a supportive community Types of Support: Financial, Emotional, Companionship Sources : Church, Co-workers, Pets, Organizations Impacts on Health: Positive OR Negative
Format: 10-15 patents seen together; 90 minute appointment Stats: 12.7 % Family Physicians; sign agreement not to reveal confidential info Goal: Share experiences, symptoms, questions Provide role models to other patients Provide social support network
D O THEY WORK ? randomized study in patients with 800 Type II diabetes patients 4 years later: Lower blood glucose Lower BMI Lower BP Lower cholesterol
M OTHERS ARE I NFLUENTIAL Children more likely to smoke if mother, rather than father, does
F ACTORS DETERMINING M ODELING Observational Learning or Modeling: learning that occurs when person observes and imitates behavior Incentive conditions: reward or praise Similarity of Model Study with injection phobia If model is someone we admire
P RENATAL L IFE AS P REPARATION Environment Provides Information Fetus Knows What to Expect: Feast or Famine; Calm or Stress Adjusts metabolism and other physiological processes in anticipation Problematic when prenatal information is unreliable
“ Surely we are all out of the computation of our age, and every man is some months elder than he bethinks him, for we live, move, have a being and are subject to the actions of the elements, and malice of diseases, in that other world, the truest microcosm, the womb of our mother ” -T HOMAS B ROWNE
FOAD: F ETAL O RIGINS OF A DULT D ISEASE Food We Eat ( or don’t eat) Stressors Prescription Drugs/Endocrine disruptors Poverty/Alcohol Intrauterine environment
H YPOTHESIZED BPA E FFECTS Reproductive system defects Obesity Aggression Diabetes Breast/thyroid cancers Prostate/testicular cancers Decreased brain sexual dimorphisms
Sources of BPA Plastics Canned Goods Cash Register Receipts Paper Currency Dental Fillings Infant formula Breast Milk Statistics Found in urine in 92% adults Found in fetal plasma and placental tissue Higher levels in children Effects found at 25 ng /kg FDA Dose set at: 50 ug /kg body weight