Prashanth N Srinivas argues that current public health research tracks health disparities through statistics but consistently fails to investigate or address the deep structural, political, and institutional root causes that keep these inequities alive.
What to know about Equality or Equity
In India, a country defined by vast socio-economic, geographic, and historical diversity, public health data routinely highlights stark disparities across caste, tribe, gender, and class. However, treating these disparities merely as technical inequalities or individual lifestyle choices masks the deep-rooted, man-made structural injustices that produce them. A new methodological critique by Prashanth N Srinivas, Director at the Institute of Public Health in Bengaluru, argues that Indian public health research is currently trapped in a cycle of describing health gaps rather than explaining why they exist. While measuring health gaps tells us who is suffering and by how much, it takes the critical leap from equality to equity to understand why. This distinction remains one of the most urgent blind spots in Indian public health research.
In his critique, Prashanth draws on the framework outlined by Sudhir Anand, a professor at the University of Oxford. He argues that the distinction between equality or inequality and equity or inequity is fundamental to understanding why current public health strategies fall short.
Equality or Inequality in health research refers to measurable, material differences in health outcomes between populations. India has mastered this first step through massive national surveys (like the National Family Health Survey) and disease surveillance systems that precisely document who is worse off and by how much (e.g., mapping infant mortality rates or nutritional gaps across districts).
As Prashanth notes: “For most scholars, the distinction between inequality and inequity is a well-known one: inequalities are just differences.”
Equity or Inequity goes beyond numerical gaps. For a difference to be classified as an inequity, it must be socially produced, systematic, and unfair. Inequities are not accidental; they are man-made and embedded in broader social injustices.
According to Prashanth: “What sets apart inequities from mere material differences is unfair treatment… To put it simply: inequity is man-made and embedded in injustice.”
To illustrate how the confusion between inequality and inequity distorts public health solutions, the paper examines the health status of Adivasi (Scheduled Tribe) communities.
Standard epidemiological and regression models treat Adivasi status as a mere risk factor linked to lower nutrition or higher illness. When government health programs try to fix this, they typically look at it as an awareness deficit or a lack of individual health literacy, responding with superficial fixes like mobile clinics or educational campaigns.
When viewed through an equity and health-justice lens, the problem changes. The poor health outcomes of Adivasi communities are seen as the direct result of historical and structural injustices. For instance, when forest departments ban the collection of minor forest produce and evict Soliga communities into resettlement colonies, it ecologically disconnects them from their traditional sustenance and lands. According to Adivasi scholar C. Madegowda
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“For Adivasi people, without forests there is no health.”
When Adivasi communities display hesitation or mistrust toward government hospitals, mainstream health research wrongly labels it as individual backwardness or a lack of compliance. However, an equity-focused framework reveals that this mistrust is a
“rational mistrust rooted in a history of dispossession,” says Prashanth.
The critique exposes four specific systemic deficits: a shallow engagement with social theory, a tendency to shift the burden of action onto individuals or governments, a rigid hierarchy that favours biomedical experiments over social sciences, and a method-driven approach where available tools dictate the research questions rather than pressing social realities. It also highlights a major constraint in the current scientific ecosystem: researchers often carry deep disciplinary biases toward quantitative metrics and shy away from investigating institutions that might implicate powerful interests.
For India, where decades of targeted welfare programs often fail to dismantle persistent health disadvantages, recognising that health equity is a matter of systemic justice rather than ignorance is the first step toward building a truly fair and effective healthcare system. National databases and government surveys excel at mapping out who is suffering, such as documenting how Scheduled Tribes and Adivasi communities experience higher infant mortality, poorer nutrition, and limited healthcare access. However, they stop precisely where critical answers are required. The research community frequently treats health disparities merely as statistical inequalities rather than acknowledging them as man-made, unfair inequities rooted in systemic injustice. Consequently, current studies generate endless correlations without uncovering causal mechanisms, leaving the structural drivers of disease invisible and unaddressed.
Moving from measuring inequality to addressing inequity requires shifting the research gaze.
While measuring inequality asks, “How big is the health gap between tribes and the general population?”, pursuing equity asks, “What institutional, historical, and power structures produced this disadvantage, and how do conservation laws or state-community relations sustain it?”
Without this structural lens, public health research remains trapped at the threshold of individual blame, unable to propose the systemic changes that true health justice demands.
To dismantle systemic barriers, Prashanth advocates institutional reforms, such as retraining grant review panels to value qualitative and systems-thinking approaches, encouraging medical journals to publish action-oriented public health frameworks, and urging scientists to adopt embedded, community-driven research. Shifting the scientific gaze from individual behaviour to structural systems ensures future health interventions can tackle real-world injustices, leading to more equitable and just healthcare for populations across India and beyond.
