The publication in JAMA Internal Medicine.
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Diabetes mellitus (DM) is widespread and treatable. Little is known about the diabetes care continuum (diagnosis, treatment, and control) in India, and whether it varies at the national, state, and district levels.
To estimate the diabetes care continuum among individuals aged 18-98 years old at national, state, and district-levels, and by socio-demographic group.
Cross-sectional, nationally-representative survey, 2019-
28 states, 8 union territories, and 707 districts of India
1,895,287 approached in the Fifth National Family Health Survey (NFHS-5)
District, state, urban vs rural residence, age (18-39, 40-64, ≥65 years), sex, household wealth quintile
Diabetes was defined by self-report or high capillary blood glucose (≥126mg/dL [fasting] or ≥220mg/dL [non-fasting]). Among respondents who had previously been diagnosed with diabetes, we reported the proportions treated (self-reported medication use) and proportion controlled (blood glucose <126 [fasting] or ≤180 mg/dL [non-fasting]). We benchmarked findings against the World Health Organization’s Global Diabetes Compact Targets (80% diagnosis, 80% control among those diagnosed). We partitioned the variance in indicators between and within states using variance partition coefficients (VPC
Among 1,651,176 adult respondents (52.6% female; mean age: 41.6 years) with blood glucose measures, the proportion with diabetes was 6.5% [95%CI: 6.4, 6.6]. Among adults with diabetes, 74.2% [73.3, 75.0] were diagnosed. Among those diagnosed, 59.4% [58.1, 60.6] reported taking medication and 65.5% [64.5, 66.4] achieved control. Diagnosis and treatment were higher in urban areas, older age groups, and wealthier households. Of the 707 districts, 34.8% districts met the diagnosis target, while 10.7% districts met the control target among those diagnosed. Most of the variability in diabetes diagnosis (VPC:89.1%), treatment (VPC:85.9%), and control (VPC:95.6%) were within-state, and not between states.
Nationally, India’s diabetes care continuum masks considerable state- and district-level variation, as well as age- and rural-urban disparities. Surveillance at the district-level can guide state health administrators to prioritize interventions and monitor achievement of global targets.
| Study Name | Years | doi | Study Population | Diabetes (%) | Diagnosed/Aware (%) | Treated (%) | Controlled (%) |
|---|---|---|---|---|---|---|---|
| Unnikrishnan 2014 | INDIAB Phase 1 2008-10 | 10.1089/dia.2014.0018 | 20+ y; n = 14227 | - | - | - | 31% |
| Prenissl 2019 | NFHS 2015-16 | 10.1186/s12916-019-1325-6 | 15-49y; n = 729829 | 3.3% | 52.5% | 40.5% | 24.8% |
| Mathur 2022 | NNMS 2017-18 | 10.3389/fpubh.2022.748157 | 18-69y; n = 9721 | 9.3% | 45.8% | 36.1% | 15.7% |
| Flood 2022 | LASI 2017-18 | 10.2139/ssrn.4066713 | 45+ y; n = 56995 | 19.7% | 60.4% | - | 46.1% |
| Anjana 2021 | INDIAB 2008-20 | 10.1016/S2213-8587(22)00072-9 | 20+ y; n = 113043 | - | - | - | 36.3% |
| Current Study | NFHS-5 2019-21 | - | 18+ y; n = 1651176 | 6.5% | 70.1% | 59.4% | 34.5% |
The prevalence of diagnosed population in total population is 4.3% (9.3%
| Study Name | Years | doi | Study Population | Diabetes (%) | Diagnosed/Aware (%) | Treated (%) | Controlled (%) |
|---|---|---|---|---|---|---|---|
| Mathur 2022 | NNMS 2017-18 | 10.3389/fpubh.2022.748157 | 18-69y; n = 9721 | 9.3% | 45.8% | 36.1% | 15.7% |
| Current Study | NFHS-5 2019-21 | - | 18-69y; n = 1552032 | 5.9% | 72.3% | 50.1% | 28.0% |
The prevalence of diagnosed population in total population is 11.9% (19.7%
| Study Name | Years | doi | Study Population | Diabetes (%) | Diagnosed/Aware (%) | Treated (%) | Controlled (%) |
|---|---|---|---|---|---|---|---|
| Flood 2022 | LASI 2017-18 | 10.2139/ssrn.4066713 | 45+ y; n = 56995 | 19.7% | 60.4% | - | 46.1% |
| Current Study | NFHS-5 2019-21 | - | 45+ y; n = 668099 | 12.1% | 75.5% | 58.3% | 33.6% |