M. N. D. Cohn - Cardiovascular Health

Cardiovascular Health

ROWMAN & LITTLEFIELD

Lanham Boulder New York London

Library of Congress Cataloging-in-Publication Data

Names: Cohn, Jay N., author.

Title: Cardiovascular health : how conventional wisdom is failing us / Jay N. Cohn.

Description: Lanham : Rowman & Littlefield, [2017] | Includes bibliographical references and index.

Identifiers: LCCN 2017001845 (print) | LCCN 2017003021 (ebook) | ISBN 9781442275126 (cloth : alk. paper) | ISBN 9781442275133 (Electronic)

Subjects: | MESH: Cardiovascular Diseases--genetics | Cardiovascular Diseases--prevention &
control

Classification: LCC RC682 (print) | LCC RC682 (ebook) | NLM WG 120 | DDC 616.1/2042--dc23

LC record available at https://lccn.loc.gov/2017001845

TM The paper used in this publication meets the minimum requirements of American National Standard for Information SciencesPermanence of Paper for Printed Library Materials, ANSI/NISO Z39.48-1992.

Printed in the United States of America

Disclaimer:

This book represents reference material only. It is not intended as a medical manual. This book is not a replacement for treatment(s) that the readers personal physician may have suggested. If the reader believes he or she is experiencing a medical issue, professional medical help is recommended. Mention of particular products, companies, or authorities in this book does not indicate endorsement by the publisher or author.

Advice about health care saturates the media these days. Newspapers, magazines, radio, and TV as well as the Internet are responding to the fascination of the public with understanding threats to their health and ways to deal with them. The commercials during prime-time TV are dominated by ads for obscure new drugs that advise people to ask your doctor about prescribing them. Despite the apparent narrow target for these expensive commercials, they wouldnt exist unless they were effective in generating considerable revenue for the sponsors. I have suspected that they only appear if the drug company is having trouble penetrating the medical market.

People are also warned about their personal risk of developing severe, life-threatening illnesses and what they can do to reduce their chance of getting sick or dying. Whether it is what to eat, what to do, or what to think, the advice is often based on studies in large populations using large databases that are increasingly available for analysis. Such large databases are generated by hospitals; health-care-provider groups; insurance companies; local, state, and federal government agencies; and even some countries. Although the accuracy of these databases is not always assured, they provide individual investigators with a powerful tool to evaluate relationships in that specific population between various measurements or entries in the records.

For instance, the data may demonstrate an association between some trait, such as obesity, defined by a body mass index over 30 kg/m2, and the likelihood of developing a disease such as a heart attack. The obligatory statistical exercise in such studies is to search for some other difference in those individuals with and without the trait of interest that could account for a different rate of the disease. Is the population with or without the trait older, more sedentary, poorer, less educated, and so on? If no other differences are found, the investigators might conclude that the difference is related to the trait of interest. What is often left unsaid is that the investigators can only examine differences on which they have collected data. A host of potential hereditary and environmental factors always remain unexamined. So the association is at best worthy of a hypothesis, not a conclusion.

If the observation is replicated in another population, the association between the trait and the outcome may be real and statistically sound, but the meaning of this association for an individual is often hardly discernible. The difference between population data on health and individual health is usually blurred by the media as well as by the scientists who promulgate such data. Population datathat acquired by studying a large group of individuals, regardless of how they are selectedapplies only modestly and variably to any given individual. Some of these observations are reproducible and real and should be taken seriously, but many are of little importance and probably should be disregarded.

Even if an association is demonstrated, and even if it is verified by repeating the observation in another population, the lay medical reports often err by inappropriately assuming cause and effect. These reporters, and sometimes even the scientists, are willing to suggest that the reported behavior or trait is responsible for the reported outcome, such as an excess of sickness or death. But cause and effect can never be gleaned from an association. I am reminded of an experience from more than forty years ago. A prominent medical journal published a rather unusual observation that people with earlobe creases have a higher risk of heart attacks than those without earlobe creases. These creases were shown on a photograph of a man who had a diagonal crease or line running across the lower portion of his ear lobe. I received calls from several patients who, alarmingly having noted that they had such creases, asked if they could come in to have the creases removed. How nave, I thought at the time, that people might think that removing the creases would reduce their risk of a heart attack. Certainly people should have known that an association, which might imply some similar condition affecting the earlobe or an inherited trait somehow linked to both the creases and coronary artery disease, is different than true cause and effect. There certainly is no basis for even entertaining the idea that an earlobe crease could cause heart attacks or that their removal would decrease the risk. To prove cause and effect, one would need to carry out a prospective trial of randomly assigning such individuals to surgical removal or no surgical removal to determine if removing the creases reduced the risk. The medical profession has unfortunately carried out many futile trials in recent years, but no scientist would embark on such a silly endeavor. It makes no sense. There must be a rational mechanism for the effect to justify a trial. Association is not equivalent to cause and effect.

Certainly physicians would be able to properly advise their patients, you might think. But doctors dont always think clearly about cause and effect. They too are bombarded with the news media and their professional organizations that preach the party line. Often this party line blurs the distinction between association and cause and effect. Yes, obese individuals have a higher risk of heart attacks than thin ones, but are we certain that when the obese person loses weight, the risk returns to normal? Not really, though it is a reasonable and testable hypothesis. Such a study hasnt been done because of its difficulty. It would require studying thousands of patients and trying to convince half of them to lose weight, but not the other half that would serve as the control group. They would need to be followed for a number of years to determine if the rate of heart attacks in the weight-loss groupif indeed they actually lost weightwas lower than that in the control group. It would be a monstrously expensive study to perform and highly unlikely to be successful. Who would be interested in funding it?