The distinction matters in practice. A programme that reports 'inequality in anaemia' makes a descriptive claim. A programme that reports 'inequity' makes a normative one and commits itself to explaining why the gap is avoidable. Margaret Whitehead's paper 'The concepts and principles of equity and health' (International Journal of Health Services 22(3), 1992) set out this framing for the WHO European Region's Health for All policy, separating differences that are inevitable from those that are unnecessary and unfair.

The three recommendations are ordered from the conditions people live in, to the structures that distribute those conditions, to the evidence needed to act. Most development programmes work on the first. The second is political and is often left to governments, though advocacy and governance programmes act on it. The third is where monitoring and evaluation teams contribute directly.

The report grouped its calls for action into four areas: reduce economic inequality through social infrastructure and universal services; overcome structural discrimination and the health effects of conflict and forced migration; manage climate action and digital change so that they benefit equity; and govern for equity through cross-government platforms and community participation.

Solar and Irwin's 2010 framework names three broad policy approaches: targeted programmes for disadvantaged groups, closing the gap between worse-off and better-off groups, and addressing the gradient across the whole population. They write that these 'are not mutually exclusive' and can build on each other, but that a consistent equity approach must ultimately lead to a focus on gradients.

Sources: UN Inter-agency Group for Child Mortality Estimation (indicator SH.DYN.MORT) and World Bank life expectancy series (SP.DYN.LE00.IN), via World Bank WDI, accessed October 2026. These are modelled estimates for comparison across countries. For India itself, use the Sample Registration System: SRS 2023 put under-five mortality at 29, ranging from 33 in rural areas to 20 in urban areas (MoSPI, Children in India 2025, PIB, 25 September 2025).

Source: Solar and Irwin, A conceptual framework for action on the social determinants of health, WHO, 2010, pages 24-25. The examples in the right column are this course's, chosen to show how the six points translate in an Indian district.

Sources: categories from Solar and Irwin, A conceptual framework for action on the social determinants of health, WHO, 2010, page 6. Figures marked NFHS-6 are from the NFHS-6 (2023-24): India and State/UT Fact Sheets, IIPS, May 2026 (provisional); the cooking-fuel figure is from NFHS-5 (2019-21) India Report, IIPS and ICF, 2022, Chapter 2 (59% of households use clean fuel), because the NFHS-6 fact sheet does not report it. Behaviour sits here, as a channel, because who smokes and what people eat are distributed by social position.

The second point has a measurement consequence. When we see that the poor are sicker, part of the association may run from illness to poverty. Panel data, or measures of position taken before illness, help separate the two directions. Diderichsen's model, on which the CSDH framework draws, names four mechanisms: social stratification, differential exposure, differential vulnerability, and differential consequences of ill health.

The authors call the core 'fixed factors over which we have little control'. The model was written to suggest 'quite distinct levels of intervention for health policy-making', layer by layer. Their 2021 reflection, 'The Dahlgren-Whitehead model of health determinants: 30 years on and still chasing rainbows' (Public Health 199: 20-24), explains how they pair it with the Diderichsen framework to explain gradients.

Solar and Irwin flag the social capital debate directly: a focus on social capital, 'depending on interpretation, risks reinforcing depoliticized approaches' to the social determinants. A community group that pools savings for health emergencies helps its members, and it also leaves the public financing gap unchanged. A practitioner should know which of the two the programme is claiming to fix.

Lower grades smoked more, were shorter, heavier and had higher blood pressure. But when the authors allowed for all of these and cholesterol, 'the inverse association between grade of employment and CHD mortality was still strong'. Risk factors explained only part of the gap.

Whitehall was useful because it reduced the material explanation without removing it: all the men had jobs and pensions, so a gradient that persisted pointed to control, status and early life as well. The 1984 paper noted that 'the inverse relation between height and mortality suggests that factors operating from early life may influence adult death rates' (Marmot, Shipley and Rose, Lancet 1984).

Each quintile does better than the one below it. The step from fourth to highest (32.7 to 20.1) is as large as the step from lowest to second (59.0 to 48.0). This is the shape the Commission called a social gradient. A programme that defines its target group as 'below the poverty line' covers part of the first two bars and none of the rest. The NFHS-5 wealth index ranks households by their assets and housing, so it measures relative position; it says nothing about how far apart the quintiles are in money.

The third number is the argument for a gradient: removing both extremes still leaves a six-year gap in life expectancy between low and high income. The review's response was proportionate universalism, which Section 9 explains. The review also notes that people in poorer areas die sooner and spend more of their shorter lives with a disability.

NFHS-5 marks estimates based on 250-499 unweighted person-years of exposure in parentheses (Table 7.2 note, NFHS-5 (2019-21) India Report, IIPS and ICF, 2022). In the urban caste rows, for example, the 'Don't know' group's under-five mortality of 78.2 is in parentheses. A practitioner who quotes that figure without the warning overstates what is known.

Source: NFHS-6 (2023-24): India and State/UT Fact Sheets, IIPS, May 2026 (provisional). Fieldwork ran from 28 May 2023 to 31 December 2024 and covered 679,238 households, 716,397 women and 100,977 men. IIPS describes the fact-sheet results as provisional. As of October 2026 the full report with breakdowns by caste, wealth quintile and schooling, and the anaemia estimates, had not been released. This course therefore uses NFHS-6 for headline levels and NFHS-5 (2019-21) for gaps between groups, and labels each figure with its round.

All four countries show the same direction, with different scales. Pakistan's richest quintile has higher under-five mortality (56) than India's or Nepal's poorest. Breakdowns by background characteristic in DHS reports use the ten years before the survey, to have enough births in each group, so these figures differ slightly from the five-year national rates. The Pakistan survey is the most recent DHS available for that country in the API, fielded in 2017-18, so compare it with care.

Source: DHS Program STATcompiler API, accessed October 2026, indicator CM_ECMR_C_U5M by wealth quintile. India's is a smooth staircase. Bangladesh flattens at the top: the fourth and highest quintiles are about the same. Nepal has a jump between the second and middle quintiles. Pakistan has two plateaus. Each shape suggests a different policy question.

Stunting (height-for-age more than two standard deviations below the WHO median) records years of poor nutrition, infection and care. In India, 46.1% of children in the lowest quintile are stunted against 22.9% in the highest (NFHS-5 (2019-21) India Report, IIPS and ICF, 2022, Table 10.1). The ratio is about 2 in India and about 2.8 in Nepal. Notice that nearly one child in four is stunted even in India's richest fifth: the determinants of stunting, such as sanitation in the neighbourhood and mothers' own height and nutrition, are shared across income groups.

Place works through several channels at once: distance to a facility and to a doctor who is present, quality of water and sanitation, road access in an emergency, and the income structure of rural labour markets. The urban figure is an average that hides slums, which Section 6 takes up. Notice also that two Indian sources for the same idea give different levels: NFHS-5 covers the five years to 2019-21 and SRS measures 2023. Never mix them in one comparison.

Kerala's 5.2 against Uttar Pradesh's 59.8 is a gap of more than eleven times inside one country, one constitution and one national health mission. Solar and Irwin cite Kerala as a widely studied case showing the relationship between a reduction of inequalities over 40 years and improvements in health status, and note that these gains have rarely been traced to the state's public policies. State differences in schooling, women's status, public services and political history are determinants that sit above any single household.

The Census counted notified, recognised and identified slums. The central law, Section 3 of the Slum Areas (Improvement and Clearance) Act, 1956, lets an area be declared a slum where its buildings 'are in any respect unfit for human habitation', or where dilapidation, overcrowding, faulty arrangement of streets, lack of ventilation, light or sanitation facilities, or any combination of these, make them 'detrimental to safety, health or morals'. The statutory test is itself a list of social determinants.

Sources: NFHS-5 (2019-21) India Report, IIPS and ICF, 2022, Table 7.2 (mortality by schooling of the mother, 5 years before the survey) and Table 10.1 (stunting). The gradient appears in neighbours too: stunting among children of mothers with no education against those with higher education is 39.3% against 13.2% in Bangladesh (BDHS 2022), 36.3% against 12.0% in Nepal (NDHS 2022) and 47.6% against 15.8% in Pakistan (PDHS 2017-18), per DHS Program STATcompiler API, accessed October 2026.

The authors found the gap in life expectancy at birth was larger among urban dwellers (4.6 years) than rural (1.8 years), and that differences were larger by residence than by caste and religion. A measure of deprivation that combines education, health and living standards captures several determinants at once, which is why it predicts longevity.

A Scheduled Tribe child faces an under-five mortality of 50.3 per 1,000, about one and a half times the 32.8 of a child in the 'Other' group. Scheduled Caste children are close behind at 48.9. Caste and tribe work through several routes: land and asset ownership shaped by history, segregated settlements with poorer water and roads, discrimination in schools and health facilities, and, for many Adivasi communities, distance and forest geography. Caste Studies 101 covers the history and law.

Source: NFHS-5 (2019-21) India Report, IIPS and ICF, 2022, Table 7.2. A sceptic might say caste gaps are just rural-urban gaps, because SC and ST households are more often rural. The table answers this partly: within urban areas, SC children face 39.0 against 26.3 for 'Other'; within rural areas, 51.9 against 36.6. Place explains some of the caste gap and leaves most of it standing.

Sources: NFHS-5 (2019-21) India Report, IIPS and ICF, 2022, Table 10.1 and Table 10.23.1. Stunting has a clear caste and wealth gradient. Anaemia among women is high everywhere: even in the richest fifth, half of women are anaemic, and 'Other' caste women (56.4%) are slightly more often anaemic than OBC women (54.6%). Scheduled Tribe women stand out at 64.6%.

Gender is a social determinant that acts before birth through sex selection, and after birth through feeding, care-seeking and spending on girls and women. The rise from 904 to 917 is welcome, and the ratio is still below what a population without selection would show. Gender & Development 101 covers the measures and the law in detail.

Source: NFHS-5 (2019-21) India Report, IIPS and ICF, 2022, Table 15.11. Violence is a determinant of physical injury, mental health, reproductive health and children's health, and it is itself socially patterned. The NFHS-5 key findings add that one-fourth of women who experienced spousal physical or sexual violence reported injuries, and 'only 14 percent of women who have experienced physical or sexual violence by anyone have sought help'. The newer NFHS-6 (2023-24) fact sheet reports 22.3% for all ever-married women (17.5% urban, 24.4% rural), down from 29.2%; its breakdown by caste and wealth is not yet published, so the table uses NFHS-5.

India's Digital Personal Data Protection Act, 2023 commences in stages under G.S.R. 843(E) of 13 November 2025. Definitions and the Data Protection Board (ss 18-26) are in force; the core duties and rights in ss 3-17, including the s17(2)(b) exemption for research and statistical processing, apply only from 13 May 2027. Treat those duties as the standard to prepare for now. Data Protection & the DPDP Act 101 and Research Ethics 101 cover consent and safeguards.

Source: WHO/UNICEF JMP, via World Bank WDI, accessed October 2026 (indicators SH.H2O.BASW.ZS, SH.STA.BASS.ZS, SH.STA.SMSS.ZS, SH.STA.ODFC.ZS). 'Basic' sanitation means an improved facility not shared with other households. 'Safely managed' adds that excreta are safely disposed of in place or treated off-site. The ladder matters: Bangladesh has almost eliminated open defecation, yet only about a third of its people have safely managed sanitation. A toilet that empties into an open drain still contaminates the neighbourhood.

JMP estimates are modelled from household surveys, so the series moves smoothly; it shows a fall that began well before 2014 and continued after 2019. In rural India the 2024 figure was still 10.7% (indicator SH.STA.ODFC.RU.ZS). The national average hides where the remaining open defecation is concentrated: in rural areas, and in households without space, water or money to maintain a toilet.

Burning wood, dung or crop residue indoors exposes those who cook, mostly women, and the young children beside them to smoke. The GBD India state analysis attributed 0.61 million deaths in 2019 to household air pollution, while finding that the death rate from this cause fell by 64.2% between 1990 and 2019 (India State-Level Disease Burden Initiative Air Pollution Collaborators, Lancet Planetary Health 5: e25-e38, 2021).

The same study found that ambient particulate matter accounted for 0.98 million of the deaths, and that the death rate from ambient particulate pollution rose by 115.3% between 1990 and 2019, even as household air pollution deaths fell. The economic loss as a share of state GDP was highest in 'the low per-capita GDP states of Uttar Pradesh, Bihar, Rajasthan, Madhya Pradesh, and Chhattisgarh'. Poorer states bear a larger relative burden.

The four mechanisms come from the Diderichsen model that Solar and Irwin built into the CSDH framework (Solar and Irwin, A conceptual framework for action on the social determinants of health, WHO, 2010, pages 23-24). They give a programme four separate places to intervene. A drain cover reduces exposure. Nutrition reduces vulnerability. Insurance and sick leave reduce consequences. Schooling support for children who miss classes interrupts the feedback.

The lowest geography tells you whether you can use the source to target a programme. NFHS-5 provides district-level estimates for many indicators across 707 districts, so a district team can compare itself with its state. The Census reaches villages and wards but is a decade old until the 2027 round (reference date 1 March 2027) is published.

The confidence interval is wide, and a before-after comparison cannot rule out other changes over the period, so read the 1,190 as indicative. Heat is a social determinant because exposure and vulnerability follow position: outdoor and construction work, tin roofs, no fan or water, and older age all raise the risk.

The last item links heat to income security. A daily-wage worker who stops work at noon loses pay, so a warning is useful only if the work schedule can change. Heat plans that shift construction hours, provide water and shade at worksites and open cooling centres act on exposure; plans that only send messages assume the person can act on them. The 2018 evaluation reported that extreme heat and plan warnings after implementation were associated with lower summer mortality, 'with largest declines at highest temperatures'.

Source: National Food Security Act, 2013 (No. 20 of 2013), as printed by PRS Legislative Research. The Act turned access to subsidised grain from a scheme into a right, with a grievance mechanism in Section 14. Section 13 is a gender provision: making a woman the head of household for the ration card changes who controls the entitlement.

Source: The Code on Social Security, 2020, Gazette of India, as printed by PRS Legislative Research. Note the verb: the Government 'may' frame schemes. The health effect depends on schemes being notified and funded. Work, Labour & Livelihoods 101 covers the Codes in detail.

The NHA 2022-23, released on 27 May 2026, is the tenth set of estimates prepared by the National Health Accounts Technical Secretariat at NHSRC using the System of Health Accounts 2011. Per person, government health expenditure rose from Rs 1,042 to Rs 2,786. On the new GDP series with base year 2022-23, government health expenditure is 1.48% of GDP. The share of private health insurance in total health expenditure rose from 3.4% to 9.2%, and of social security expenditure (including PM-JAY and government employee schemes) from 6% to 9.9%.

The press release explains the 2021-22 figure: government raised health spending to 1.84% of GDP that year for the COVID-19 response, including emergency response packages and mass vaccination, and 'given these additional spending by the government as a one-time measure, OOPE as percentage of Total Health Expenditure (THE) during this period also declined to 39.4%'. In 2022-23 the share rose back to 43.4%. The long-run trend is downward. A single pandemic year is the wrong baseline for judging it.

Source: WHO Global Health Expenditure Database (indicator SH.XPD.OOPC.CH.ZS), via World Bank WDI, accessed October 2026. This series uses current health expenditure as the denominator, while India's NHA headline uses total health expenditure (which includes capital spending). The two are close for India (43.9% and 43.4%) but are different measures. Never mix denominators in one chart.

Source: WHO Global Health Observatory, indicator FINPROTECTION_CATA_TOT_10_POP (SDG 3.8.2, reported data), accessed October 2026. This is the SDG measure of financial hardship. The latest Indian point comes from survey data for 2017, before PM-JAY's scale-up, so it cannot tell you the scheme's effect.

Source: NSS 75th round (2017-18), Key Indicators of Social Consumption in India: Health, MoSPI, 2019, Statement 3.17 (excluding childbirth). Even in a public hospital, a rural family spent over Rs 4,000 per stay, mostly on medicines and tests. The same survey found that 13.4% of rural and 8.5% of urban hospitalisation cases were financed mainly by borrowing (Statement 3.13), and that 85.9% of rural and 80.9% of urban people had no health expenditure coverage (Statement 3.14).

PM-JAY was launched on 23 September 2018. It covers secondary and tertiary hospital care through over 38,000 empanelled public and private hospitals, for 1,961 procedures. Rural eligibility uses SECC 2011 deprivation criteria, including D5 (SC and ST households) and D7 (landless households relying on manual casual labour). On 11 September 2024 the scheme was extended to all people aged 70 and above, about 6 crore senior citizens, of whom more than 1.36 crore held Ayushman Vay Vandana cards by 21 September 2026. West Bengal became the 36th state or union territory to implement the scheme on 8 June 2026 (PIB).

At least one usual member was covered by a health insurance or financing scheme in 29% of households in NFHS-4, 41% in NFHS-5 (2019-21) and 60.2% in NFHS-6 (2023-24), with rural households (62.0%) ahead of urban (56.4%) (NFHS-6 (2023-24): India and State/UT Fact Sheets, IIPS, May 2026 (provisional); NFHS-5 (2019-21) India Report, IIPS and ICF, 2022, Chapter 11). Coverage on paper is a start. Use of the cover depends on awareness, documents, distance and how hospitals treat card-holders: the determinants again. Ayushman Arogya Mandirs, the primary-care pillar of Ayushman Bharat, provide free essential medicines and diagnostics, which reach part of the outpatient need that hospital cover leaves out.

The rainbow's middle layer becomes a list of departments. Intersectoral action means agreeing on shared indicators, pooling some budget, and holding regular joint reviews. Without the shared indicator, each department reports its own outputs and nobody reports the outcome.

Sources for the scheme facts: PIB Backgrounder on AB PM-JAY, 22 September 2026; National Food Security Act, 2013, s3. The last row is a design principle rather than a named scheme; any example you build should be tested against small-area data such as NFHS-5 district estimates.

In Paschim Banga (judgment of 6 May 1996), Hakim Seikh, a member of an organisation of agricultural labourers, was injured falling from a train and refused admission by government hospitals in Calcutta for want of beds. The Supreme Court held that 'it is the constitutional obligation of the State to provide adequate medical services to the people' and that financial constraints could not excuse it. The case is about the health system as a determinant: a poor man's access to emergency care.

Source for the four areas: WHO news release on the World report on social determinants of health equity, 6 May 2025. Political Economy 101 and Governance & Accountability 101 develop the political side.

Sources: NFHS-5 (2019-21) India Report, IIPS and ICF, 2022, Table 7.2 and Table 10.1; ratios and differences are this course's arithmetic. Both measures use only the two extreme groups and ignore everyone in between, which is their main weakness.

Source: O'Neill and colleagues, 'Applying an equity lens to interventions: using PROGRESS ensures consideration of socially stratifying factors to illuminate inequities in health', Journal of Clinical Epidemiology 67(1): 56-64, 2014. The Cochrane Equity Methods Group adds 'Plus': personal characteristics associated with discrimination (for example age and disability), features of relationships, and time-dependent relationships.

Programme data rarely carry stratifiers. Adding two or three (caste or tribe, sex, a short asset list) to your beneficiary records lets you compare your reach with the survey distribution of need.

The NFHS-6 fact sheet warns that readers 'should be cautious while interpreting and comparing the trends as some States/UTs may have' smaller sample sizes, and describes its results as provisional (NFHS-6 (2023-24): India and State/UT Fact Sheets, IIPS, May 2026 (provisional)). Read every first release with the same care.

Ten questions are enough for a design review or a proposal annex. Answer each with evidence: a table from NFHS-5 or NFHS-6, your own baseline, or a named study. Where you cannot answer a question, record it as a gap to fill in the first year. The checklist follows the CSDH chain from structural position to intermediary determinant to outcome, and the Commission's third recommendation to measure and assess the impact of action.

Keep the categories identical to the national survey so that you can compare your beneficiaries with the population. Collect the minimum: each extra identity question adds respondent burden and a data protection duty.

Each row maps to an example in this course: under-five mortality by wealth in India (staircase), Pakistan's quintile plateaus, anaemia among women (high and shallow), women's high blood sugar in NFHS-6 (higher in urban areas), and the PM-JAY gap between eligibility and use.

The averages are computed from the rows (weighted by children). The ST poorest group has 18 more percentage points of stunting than the OBC and Other group: a relative gap of 1.6. It also has three times the share of households where not everyone uses a toilet. Within ST households, wealth matters (48% against 36%), so neither caste nor wealth alone describes the problem.

Option B is proportionate universalism in small: every child is visited, and the dose rises where the gap is largest. It also changes the sanitation plan: toilet repair and water access go first to the ST poorest hamlets, because use, not construction, is the gap there. Write the allocation rule into the project document so that it survives staff turnover.

At endline, report the change in each group, the change in the absolute and relative gaps, and the concentration index if wealth was measured. A fall in the average with no change in the ST poorest group is a result to report openly. To attribute change to the programme, add a comparison group as described in Impact Evaluation 101.

Each mistake corresponds to an example in this course: the Swachh Bharat declaration against JMP and NFHS estimates, PM-JAY cards against hospital use, NFHS against SRS mortality, and the Hindu-Muslim and urban-rural puzzles. When a programme review raises one of them, return to the section where it was discussed and rerun the analysis with the fix.

Each idea rests on a source you can open: the CSDH report, Solar and Irwin's framework, the Whitehall papers, NFHS-5 and NFHS-6, the DHS surveys, the NSS 75th round, the National Health Accounts and the statutes and judgment cited. Check the latest round before you reuse any figure: NFHS-6 full tables, a new NSS health round and the Census 2027 will all change the numbers in this course.

Definitions follow the sources cited on earlier slides: the CSDH report (2008), Solar and Irwin (2010), the Marmot Review (2010), the Helsinki Statement (2013), O'Donnell et al. (2008) and the WHO Global Health Observatory.