How do we measure health? According to conventional wisdom, the state of the physical body, our level of fitness (or a perception of fitness) and the supposedly “obvious” functioning of the body, quantifies health. For centuries, some emphasized that an active body stimulates, structures and facilitates intellectual and emotional activity, and thus visible and physical capabilities ought to be the primary measure of health. Here, in a Descartian fashion of, “I think and therefore I am,” the layman’s health analysis in Western culture has come to declare, “I appear physically sound and therefore I have health.” Professionally, healthcare provision is also often conceived as efforts to prevent, mitigate, or treat conditions that have visible and physical impact. Whether in the form of chronic, non-communicable diseases (diabetes, heart attacks and strokes with cardiovascular diseases, cancer) or communicable diseases (malaria, tuberculosis, STDs), our understanding of health has been historically ‘boxed’ into categories of temporary illness or risks of death from physical conditions.
Propelled by the movement of ‘alternative medicine’ in locations such as the U.S., the 1960s and 1970s introduced the concept of “wellness” into the scheme of health measurement. The principle of wellness, as it evolved from the mid-twentieth to the twenty-first century, identified the trifold of “mind, body, and soul” as factors which measured more comprehensively one’s sense of health, (both visible and invisible manifestations). Among some healthcare practitioners in the U.S. and elsewhere, a buzz continues to surround the idea of “wellness” (social, physical, vocational, intellectual, emotional and spiritual facets included) as indicators of health. Global fields of health care practice, however, continue to determine that a certain range of capabilities exercised by the physical body constitute health, (or otherwise determine the lack of health and necessarily illness). In this case, conditions of the mind, inasmuch as non-visible impacts to health (some of which fall outside the strict paradigms of “health” or “illness”) have yet to receive adequate attention in medical research. Adversely, when conditions of “mental illness” are examined, such cases are at once set as indicators of “non-health,” and yet there is a slow response to the provision of services (or considerations of address) for well-being.
The question of how we measure health ultimately lends itself to the inquiry of how global health data are collected. Global health statistics is often compiled through surveys, censuses, and health reports of non-governmental organizations, institutions of higher education and other independent agencies, as well as through government figures on local and national scales. Nevertheless, multinational organizations such as the World Health Organization (WHO) and handles of the United Nations such as the UN Population Division are the prime collectors of data on public health. In this instance, with agencies such as the WHO and the UN set as un-matched authorities of public health data compilation, distribution, and world health service provision, some critics argue that current health data is largely skewed. Jeremy Smith’s Epic Measures: One Doctor, Seven Billion Patients and criticisms delivered by Christopher Murray regarding the possible monopolization of health data by organizations such as the UN and the WHO offer compelling evidence for the need to critically interrogate existing global health statistics. The data of long-standing institutions can be improved through the corroboration of third-party organizations such as the The Institute for Health Metrics and Evaluation (IHME) launched by Christopher Murray.
The IHME and Christopher Murray’s Global Burden of Disease (GBD) project are critical for revamping how global health data are collected in attempting to constrain severe biases in health statistics (Smith, chapter 13). Furthermore, in lauding the IHME in its efforts to provide competition to the WHO and other established institutions in the collection and distribution of world health data, the IHME’s tool, the DALY, is also a significant innovation which ought to be further evaluated for its capacity to positively contribute towards public health data analysis. The IHME’s method of the DALY, which measures the number of years any health problem or condition eliminates from what would be a person’s years of life without such an illness (or resulting death) is a formula which, overall, provides significant foothold for how cross-comparisons of global health data can be achieved. Of course, the strict measurement of “Disability-adjusted life years,” as the DALY acronym states, or the “years of healthy life lost” holds ethical considerations such as whether measurements for ‘years of healthy life lost’ can (or should) be standardized and compared across varying health conditions. How can a health professional determine that one patient’s mild-neck-pain is more debilitating (or less) than another patient’s deafness? Or, more drastically, can (and should) a health provider determine that one patient’s case of HIV/AIDs is less (or more) depriving of life than a condition such as ALS or “Lou Greig’s disease.”
More so, the terminology of “health” itself is often subjective. This further complicates how the DALY method can be leveraged to measure the “sum of years of life” an individual loses to “early death” versus the “years of life lived” with a certain disability or illness. As such, the questions of life, death, and health cannot be reduced to mathematical equations. It appears absurd to attempt to calculate the“sum of years of life lost because of early death (YLLs)” and “equivalent years of life lived with disability (YLDs)” producing “YLLs + YLDs= Quantity of life plus quality of life lost (Smith, 68).” This trend may easily become an ethical conundrum when expanded to form and communicate health policy on a national scale. Nonetheless, the DALY method, with greater scrutiny, may offer an option for improving how health data is comparatively evaluated between and among countries and world regions for more informed global health policy.