• Health: What’s health care got to do with it?

    This was an interesting read (ungated): Different Perspectives for Assigning Weights to Determinants of Health, by Bridget C. Booske, Jessica K. Athens, David A. Kindig, Hyojun Park, and Patrick L. Remington.

    The paper begins with a very nice historical perspective that summarizes the leading causes of death and morbidity in the US over the past century, from the “sanitary revolution” beginning in the 1930s to the “social and economic determinants” that have been more recently recognized.

    Then, there is a review of the literature that “has clearly established the individual importance of environmental, clinical care, health behaviors, and social and economic factors as determinants of health.”

    An oft cited McGinnis et al (2002) paper states: “…using the best available estimates, the impacts of various domains on early deaths in the U.S. distribute roughly as follows: genetic predispositions, about 30%; social circumstances, 15%; environmental exposures, 5%; behavioral patterns, 40%; and shortfalls in medical care, 10%”. […]

    However, some caveats should be noted:

    1) The “long standing estimate” of 10% for medical care is actually based on “expert” estimates of the contribution of health care system deficiencies to total mortality; (DHHS, 1980);

    2) The estimates for medical care represent the contribution of medical care deficiencies to early deaths, rather than the positive contributions of medical care to avoiding mortality;

    3) The estimates represent contributions to early death and do not address contributions to other important health outcomes, such as health-related quality of life; and

    4) These estimates do not fully reflect the important interrelationships between the determinant categories.

    Some investigators have examined single determinants of mortality; for example, Bunker estimated that 3 of the 7.5 years of life expectancy that were gained after 1950 were due to medical care (1994). Others attribute much of the gain (58%) in life-years to primary prevention or reductions in population risk factors such as smoking, cholesterol, and blood pressure (Unal et al., 2005). More recently, Cutler and others (2006) assigned a 50% weight to medical care, while also carrying out sensitivity analysis from 25% to 75%. Wilper et al. (2009) recently updated previous IOM figures, estimating that about 45,000 or 8% of deaths among 18-64 year olds were due to lack of health insurance.

    Wolff and colleagues (2007) have estimated that correcting disparities in education-associated mortality rates would have averted eight times more deaths than those attributable to medical advances between 1996 and 2002. One of the most precise studies, which controlled for many other possible explanations, showed a 1- 3% reduction in mortality rates for each year of additional schooling (Elo and Preson 1996).

    Looking at two determinant categories, using longitudinal data from the Americans’ Changing Lives survey, Lantz and colleagues (2001) found that four common health risk behaviors (smoking, physical activity, alcohol consumption, and body mass index) had only modest impact in predicting functional status and self-rated health in low income populations after controlling for socioeconomic factors; they concluded that “risk behaviors are not the dominating mediating mechanism for socioeconomic health differences.” Similar results had also been found using mortality as an outcome (Lantz et al 1998).

    Since it is ungated, I won’t provide full references for the papers cited above. It’s worth reading in full anyway.

    • I assume that you are familiar with Ivan Illich’s Medical Nemesis.
      (Essay here:

      Expanded in 1975 into a book.)

      His contention was that medical care has created more problems than solutions and overall has not shown any benefit. He expressed this clearly in his writing.

      “Medical interventions have not affected total mortality-rates: at best they have shifted survival from one segment of the population to another. Dramatic changes in the nature of disease afflicting Western societies during the last 100 years are well documented. First industrialisation exacerbated infections, which then subsided. Tuberculosis peaked over a 50–75-year period and declined before either the tubercle bacillus had been discovered or anti-tuberculous programmes had been initiated. It was replaced in Britain and the U.S. by major malnutrition syndromes—rickets and pellagra—which peaked and declined, to be replaced by disease of early childhood, which in turn gave way to duodenal ulcers in young men. When that declined the modern epidemics took their toll—coronary heart-disease, hypertension, cancer, arthritis, diabetes, and mental disorders. At least in the U.S., death-rates from hypertensive heart-disease seem to be declining. Despite intensive research no connection between these changes in disease patterns can be attributed to the professional practice of medicine.”

    • http://papers.nber.org/papers/w16013

      There is a strong, positive and well-documented correlation between education and health outcomes. There is much less evidence on the extent to which this correlation reflects the causal effect of education on health – the parameter of interest for policy. In this paper we attempt to overcome the difficulties associated with estimating the causal effect of education on health. Our approach exploits two changes to British compulsory schooling laws that generated sharp differences in educational attainment among individuals born just months apart. Using regression discontinuity methods, we confirm that the cohorts just affected by these changes completed significantly more education than slightly older cohorts subject to the old laws. However, we find little evidence that this additional education improved health outcomes or changed health behaviors. We argue that it is hard to attribute these findings to the content of the additional education or the wider circumstances that the affected cohorts faced (e.g., universal health insurance). As such, our results suggest caution as to the likely health returns to educational interventions focused on increasing educational attainment among those at risk of dropping out of high school, a target of recent health policy efforts.

    • I have always found the determinants of health data compelling. From a population perspective, it also turns conventional wisdom on its head, and demonstrates how little utility medical care factors into preventing premature death. Providers are not aware of this, and if they were, most–divorced from financial COI–would be pushing for greater emphasis on preventitive health and education.

      Which gets to my question. Given the above data is derived from US population, where we know glaring disparities exist, eg, % without high school education, etc, how would same constructs apply to Scandanavian or Japanese cohort.

      Do our precepts derive from the inherent “weaknesses” in our culture, or are the McGinnis findings universally applied.

      In Sweden, medical care might be weighted at 30%. Yes, SES, genes all interrelated–and its all in the mix, but the danger in the findings is again, proposed universallity and what we think applies in one country, may not apply in another.

      Also, seeing as you cited paper, and have given this some thought, what is your opinion on the disparate findings, mainly effect of medical care on outcomes?


    • Brad F if you look compare healthcare data on North Dakota (population is mostly Scandinavian) with that of Sweden you notice that it is very similar so I doubt that it something about SES in the USA.



      Indeed, the health-income gradient is slightly steeper in Canada than it is in the U.S.

      Does Canada’s publicly funded, single payer health care system deliver better health outcomes and distribute health resources more equitably than the multi-payer heavily private U.S. system? We show that the efficacy of health care systems cannot be usefully evaluated by comparisons of infant mortality and life expectancy. We analyze several alternative measures of health status using JCUSH (The Joint Canada/U.S. Survey of Health) and other surveys. We find a somewhat higher incidence of chronic health conditions in the U.S. than in Canada but somewhat greater U.S. access to treatment for these conditions. Moreover, a significantly higher percentage of U.S. women and men are screened for major forms of cancer. Although health status, measured in various ways is similar in both countries, mortality/incidence ratios for various cancers tend to be higher in Canada. The need to ration resources in Canada, where care is delivered “free”, ultimately leads to long waits. In the U.S., costs are more often a source of unmet needs. We also find that Canada has no more abolished the tendency for health status to improve with income than have other countries. Indeed, the health-income gradient is slightly steeper in Canada than it is in the U.S.


      There are ghosts sitting in the Cottage bar in Glasgow’s Calton area. The locals call them the missing generation, the men who died before their time. Sometimes the drinkers dip their heads or lift their pints to them. They may not see them but all the drinkers know they are there. Jimmy, Swifty, Davy and many more.

      For here in this multi-deprived inner city area, the average life expectancy of a male is just 53.9 years. In Iraq, after 10 years of sanctions, a war and a continuing conflict, suicide bombs and insurgency, the average man has a good chance of making it into his 60s; the life expectancy of a male there is 67.49. In Iran it is 69.96, in North Korea, 71.37 and in the Gaza Strip it is 70.5.

    • On the Scotland Glasgow’s Calton area statistics, it is possible that a more extensive welfare system allows more people to drink themselves to death.