Advertisement

The importance of disaggregated data analysis of child undernutrition and its determinants – A district level analysis in the non-high focus state of India

Open AccessPublished:September 27, 2022DOI:https://doi.org/10.1016/j.cegh.2022.101147

      Abstract

      Background

      Undernutrition persists to be a public health concern across several low and middle-income countries including India. However, the south Indian states- Kerala, and Tamil Nadu (TN) are recognized as “positive deviants” in terms of overall health outcomes including children's nutrition status. Hence, only a few studies have looked at trends of nutrition status in these states, especially at a disaggregated level. We aim to assess the progress made concerning children's (under 5) nutrition status and its determinants across the districts of a non-high focus state of TN.

      Method

      We used data from district factsheets published by the National Family Health Survey-4 & 5 (conducted in 2015–16 and 2019–20 respectively) to calculate interval estimates of the prevalence of child undernutrition (stunting, wasting, and underweight) and its determinants for every district of TN.

      Result

      Certain districts continue to bear a higher burden of undernutrition. The prevalence of child growth failure indicators was higher than the state average in Ariyalur, Dindigul, Erode, Karur, Trichy, the Nilgiris, and Sivagangai across both rounds of NFHS (4 as well as 5). Changes in immediate determinants were mixed across the districts. There was a consistent improvement in several underlying determinants – household assets, sanitation, and electricity - but to differing extents.

      Conclusion

      In conclusion, the study reiterates the significance of understanding variations using granular data. Also, as the governments are increasingly focused on the progress of health outcomes at the district level. Our analysis provides timely evidence for policymakers to identify high-priority districts and design strategies to reduce the prevalence of undernutrition.

      Keywords

      Abbreviations:

      UNICEF (United Nation International Children's Fund), SAM (Severe Acute Malnutrition), CGF (Child Growth Failure), NFHS (National Family Health Survey)

      1. Introduction

      The prevalence of undernutrition persists to be a public health concern affecting millions of children across several countries, especially in low and middle-income countries including India.
      UNICEF, WHO, W.B.G.
      Joint child malnutrition estimates.
      It was the leading cause of death among under 5 children in every Indian state, accounting for 68.2% of all under-five deaths and the leading cause of health loss for all ages, accounting for 17.3% of total disability-adjusted life years.
      • Swaminathan A.
      • Kim R.
      • Xu Y.
      • et al.
      The burden of child malnutrition in India: a view from parliamentary constituencies.
      The short-term consequences are morbidity, mortality, and disability.
      • Black R.E.
      • Allen L.H.
      • Bhutta Z.A.
      • et al.
      Maternal and child undernutrition: global and regional exposures and health consequences.
      While, the chronic forms of malnutrition (stunting) during early childhood affects brain structure and function with long-term negative consequences such as reduced mental ability and learning capacity, poor school performance, and lower earnings.
      • de Onis M.
      • Branca F.
      Childhood stunting: a global perspective.
      UNICEF's conceptual framework describes various underlying as well immediate determinants of child undernutrition. Such as the inadequacies in food, health, and care for infants and young children, particularly in the first two years of life, causes child undernutrition (immediate determinants). Women's status, home food security, hygiene, and socioeconomic situations all play an important role in children's nutrition outcomes at the household and community level (underlying and basic determinants).
      UNICEF
      Conceptual Framework Child Nutrition.
      The trends of child growth failure (CGF) indicators and its determinants have been studied extensively at national as well as subnational levels (
      • Bhadoria A.S.
      • Kapil U.
      • Bansal R.
      • Pandey R.M.
      • Pant B.
      • Mohan A.
      Prevalence of severe acute malnutrition and associated sociodemographic factors among children aged 6 months – 5 years in rural population of Northern India : a population-based survey.
      • Ahuja A.
      How Can We Address the Rising Incidence of Wasting Among Children in India ? Pandey 2016.
      • Jose S.
      Child undernutrition in India assessment of prevalence, decline and disparities.
      • Ambadekar N.N.
      • Zodpey S.P.
      Risk factors for severe acute malnutrition in under-five children : a case-control study in a rural part of India.
      • Pathak P.K.
      • Singh A.
      • Subramanian S.V.
      Economic inequalities in maternal health care: prenatal care and skilled birth attendance in India, 1992-2006.
      • Subramanyam M.A.
      • Kawachi I.
      • Berkman L.F.
      • Subramanian S.V.
      Socioeconomic inequalities in childhood undernutrition in India: analyzing trends between 1992 and 2005.
      . However, after the release of NFHS-4 (2015–16) (which provided data at the district level), more studies have assessed the variations in the CGF indicators (wasting, stunting, severe stunting, and underweight) and its determinants at a disaggregated level (district level).
      • Swaminathan A.
      • Kim R.
      • Xu Y.
      • et al.
      The burden of child malnutrition in India: a view from parliamentary constituencies.
      ,
      • Kim J.
      • Liu Y.
      • Wang W.
      • et al.
      Estimating the burden of child undernutrition for smaller electoral units in India.
      • Striessnig E.
      • Bora J.K.
      Under-five child growth and nutrition status: spatial clustering of Indian districts.
      • Hemalatha R.
      • Pandey A.
      • Kinyoki D.
      • et al.
      Mapping of variations in child stunting, wasting and underweight within the states of India: the Global Burden of Disease Study 2000–2017.
      • Menon P.
      • Headey D.
      • Avula R.
      • Nguyen P.H.
      Understanding the geographical burden of stunting in India: a regression-decomposition analysis of district-level data from 2015–16.
      • Nguyen P.H.
      • Scott S.
      • Avula R.
      • Tran L.M.
      • Menon P.
      Trends and drivers of change in the prevalence of anaemia among 1 million women and children in India, 2006 to 2016.

      1.1 Importance of studies on CGF indicators at a disaggregated level (district level)

      India is a populous country with 29 states and seven union territories which are at diverse levels of development, resulting in a heterogeneous distribution of health risks and their consequences.
      • Dandona L.
      • Dandona R.
      • Kumar G.A.
      • et al.
      Nations within a nation: variations in epidemiological transition across the states of India, 1990–2016 in the Global Burden of Disease Study.
      Significant differences have been noted in the magnitude, rate of decline, and inequality in health status of individuals between states which score high on the sociodemographic index (SDI) and those scoring low on SDI.
      • Hemalatha R.
      • Pandey A.
      • Kinyoki D.
      • et al.
      Mapping of variations in child stunting, wasting and underweight within the states of India: the Global Burden of Disease Study 2000–2017.
      And the variations in the child growth failure (CGF) indicators aren't an exception. The southern states- Kerala, and Tamil Nadu are recognized as “positive deviants” in some nutrition-related studies when compared to northern states.
      • Striessnig E.
      • Bora J.K.
      Under-five child growth and nutrition status: spatial clustering of Indian districts.
      A study on levels of living and poverty highlights the fundamental limits of seeing the “state” as a homogeneous socioeconomic unit for analysing poverty and inequality.
      • Chaudhuri S.
      • Gupta N.
      Levels of living and poverty patterns: a district-wise analysis for India.
      Variations are predicted within states too, because many states have huge populations, and districts within states often differ in terms of environment, demographics, and economy, all of which have an impact on children's health.
      • Menon P.
      • Headey D.
      • Avula R.
      • Nguyen P.H.
      Understanding the geographical burden of stunting in India: a regression-decomposition analysis of district-level data from 2015–16.
      ,
      • Rajpal S.
      • Kim J.
      • Joe W.
      • Kim R.
      • Subramanian S.V.
      Small area variation in child undernutrition across 640 districts and 543 parliamentary constituencies in India.
      The average prevalence of stunting, wasting and underweight has reduced between NFHS-3 (2005–06) and 5 (2019–21). However, the national averages conceal the unequal prevalence of malnutrition at the sub-national level as few states continue to bear a disproportionately higher burden of malnutrition (IIPS, 2007; IIPS 2022).
      To understand intra-state variation, an assessment of malnutrition indicators and their trends over time at the district level would be required, particularly in India's major states.
      • Das P.
      • Roy R.
      • Das T.
      • Roy T.B.
      Prevalence and change detection of child growth failure phenomena among under-5 children: a comparative scrutiny from NFHS-4 and NFHS-5 in West Bengal, India.
      And to understand the reasons behind these intrastate variations it is also important to look at the trends in immediate and underlying determinants of undernutrition. Some government-led programmes and initiatives such as Integrated Child Development Scheme (ICDS), and Nutrition Rehabilitation Centres (NRC) are functional at the district level to improve the nutrition status of under 5 children. However, a recent study has found that ICDS hasn't improved children's nutritional status significantly.
      • Dixit P.
      • Gupta A.
      • Dwivedi L.K.
      • Coomar D.
      Impact evaluation of integrated child development Services in rural India: propensity score matching analysis.
      Also, its effect is non-uniform i.e. though it targets the areas where poor households are concentrated, but fails to target areas with a low level of education or skewed sex ratios.
      • Kandpal E.
      Beyond average treatment effects: distribution of child nutrition outcomes and program placement in India's ICDS.
      One of the reasons for the failure could be that these programmes focus on the dietary aspect alone to address malnutrition, while it is known that malnutrition has several other determinants as mentioned earlier. Under India's newly launched National Nutrition Strategy the district is the central focus and is an increasingly important unit in India's ongoing decentralization process.
      • Niti ayog I.
      WCD division
      Accelerating Progress on Nutrition in India: What Will it Take - Third Progress Report.
      The state or central government usually provides financial aid, but policy discourse is based on district-level estimates. Therefore, lower administrative level analysis is important, as it provides a clearer picture of existing health inequalities within states or across state boundaries, allowing policymakers to respond more effectively in high-risk pockets. Tracking the district-wise progress across these determinants shall help to identify specific determinants that need improvement across each district. Hence the novelty of our study is that apart from assessing the district-wise progress in the prevalence of undernutrition (stunting, wasting, severe wasting, and underweight) among under 5 children in the state of TN. We also track the progress made by the districts with respect to the immediate and underlying determinants of undernutrition in the past five years in the high-focus state of TN.

      2. Materials and method

      2.1 Data source

      The analysis was carried out using the National Family Health survey factsheets (NFHS-4 & 5) which is available publicly (http://rchiips.org/nfhs/districtfactsheet_NFHS-5.shtml). It is a large-scale, multi-round survey conducted on a representative sample of households throughout India. It is conducted by the International Institute for Population Science (IIPS) under the stewardship of the Ministry of Health and Family Welfare (MoHFW), Government of India. The survey provides national as well as sub-national level information on several demographic indicators, maternal and child health outcomes, and health services. Data is also collected on height, weight, and other anthropometric measurements of ever-married women aged 15–49 years and children born to those women in the 5 years preceding the survey. Due to the imposition of lockdown due to CoVID-19, NFHS-5 fieldwork was conducted in two time periods (Phase-I; January 2020 to March 2020 and Phase-II; December 2020 to March 2021) in States/UTs (which includes TN) covered in phase 2.

      2.2 Indicators of undernutrition

      For children, standard indices of physical growth related to nutritional status are height-for-age (stunting), weight-for-height (wasting), and weight-for-age (underweight). A child who is below minus two standard deviations (−2 SD) from the median of the WHO reference population in terms of height-for-age is considered short for his/her age or stunted and severely stunted (below −3 SD). Stunting reflects the cumulative effect of chronic malnutrition. While the children whose weight-for-height is below −2 SD from the median of the WHO reference population are considered too thin for/height or wasted while those below −3 SD are considered as severely wasted. Wasting is a condition reflecting acute or recent nutritional deficit or a recent illness. Weight-for-age is a composite index of stunting and wasting and is a good indicator to monitor nutritional status over time
      • WHO
      Nutrition Landscape Information System (NLiS) country profile indicators: interpretation guide.

      2.3 Method of analysis

      In this study, interval estimates of the child growth failure indicators (stunting, wasting, severe wasting, underweight) and its determinants (both immediate and underlying) were calculated using data from NFHS- 4(2015–16) and NFHS-5 (2019–20) factsheets. Since it was not possible to present the progress of every district across each of the determinants in this paper. Therefore, we adopted a concise presentation style used in the preparation of the State Nutrition Profile.
      • Niti ayog I.
      WCD division
      Onis et al. (2019), have formulated the prevalence thresholds for wasting and stunting, which aids in the identification of regions where stunting and wasting among children are a public health concern.
      • De Onis M.
      • Borghi E.
      • Arimond M.
      • et al.
      Prevalence thresholds for wasting, overweight and stunting in children under 5 years.
      For wasting the thresholds are: ‘very low’ (<2·5%); ‘low’ (≈1–2 times 2·5%); ‘medium’ (≈2–4 times 2·5%); ‘high’ (≈4–6 times 2·5%); and ‘very high’ (>≈6 times 2·5%). For stunting, the thresholds are: ‘very low’ (<2·5%); ‘low’ (≈1–4 times 2·5%); ‘medium’ (≈4–8 times 2·5%); ‘high’ (≈8–12 times 2·5%) and ‘very high’ (>≈12 times 2·5%).
      • WHO
      Nutrition Landscape Information System (NLiS) country profile indicators: interpretation guide.

      3. Results

      3.1 Trends in the prevalence of undernutrition among under 5 children in TN

      The trend (Fig. 1,2 & 3) shows that over the years the prevalence of undernutrition (stunting, wasting, underweight) in TN has reduced. However, what is noteworthy is that the prevalence of severe forms of undernutrition (stunting and underweight) didn't decline across NFHS-3 (2005–06) & 4 (2015–16).
      Fig. 1
      Fig. 1Trends in prevalence of stunting among children in TN (NFHS-3 (2005–06); NFHS-4 (2015–16); NFHS-5 (2019–21)
      Source: Author's estimate and NFHS-5 (2019–20) factsheet for TN.
      Fig. 2
      Fig. 2Trends in the prevalence of wasting among children in TN (NFHS-3 (2005–06); NFHS-4 (2015–16); NFHS-5 (2019–21)
      Source: Author's estimate and NFHS-5 (2019–20) factsheet for TN.
      Fig. 3
      Fig. 3Trends in prevalence of underweight among children in TN NFHS-3 (2005–06); NFHS-4 (2015–16); NFHS-5 (2019–21)
      Source: Author's estimate and NFHS-5 (2019–20) factsheet for TN.

      3.2 Changes in the prevalence of stunting across the districts of Tamil Nadu

      As evident from Table 1 the prevalence of stunting among the under-5 children between NFHS-4(2015–16) and NFHS-5(2019–20) has declined in almost two-thirds of the districts of TN. A marked decline (more than 10% points) was noticed in Thiruvallur, Ariyalur, and Chennai. However, in ten districts the prevalence has increased, especially in Thoothukudi, Pudukkottai, Tiruvannamalai, Karur, Sivagangai, Nagapattinam, Madurai, and Perambalur where the prevalence increased by 5% points (pp) or more in the past five years. According to prevalence threshold values for stunting, all 32 districts fall under the category of ‘high’ or ‘very high levels of stunting.
      • WHO
      Nutrition Landscape Information System (NLiS) country profile indicators: interpretation guide.
      Karur has the highest prevalence (33.6%) of stunting while Kanyakumari (17.3%) had the least prevalence
      Table 1Changes in the prevalence of stunting across the districts of Tamil Nadu.
      DistrictNFHS-5 (2019–20)NFHS-4 (2015–16)change in pp Difference between NFHS-5 & NFHS-4
      Perambalur29.1245.1
      Thiruvallur18.130.12−12.02
      Ariyalur25.337−11.7
      Chennai20.430.91−10.51
      Thiruvarur19.828.41−8.61
      Cuddalore20.228.21−8.01
      Villupuram23.931.82−7.92
      Tiruppur21.529.4−7.9
      Theni20.227.4−7.2
      Thanjavur19.626−6.4
      the Nilgiris26.733.09−6.39
      erode19.425.55−6.15
      Kancheepuram20.625−4.4
      Coimbatore2327.3−4.3
      Dindigul27.131.12−4.02
      Salem23.627−3.4
      Tiruchirappalli27.630−2.4
      Tirunelveli29.430.8−1.4
      Virudhunagar29.229.9−0.7
      Namakkal25.225.190.01
      Kanyakumari17.317.20.1
      Vellore29.8290.8
      Krishnagiri2925.13.9
      Ramnathpuram26.422.53.9
      Dharmapuri28.724.154.55
      Thoothukudi26.321.235.07
      Pudukkottai32.226.675.53
      Tiruvannamalai30.624.526.08
      Karur33.627.466.14
      Sivagangai27.620.936.67
      Nagapattinam32.324.57.8
      Madurai32.421.2111.19
      Source: District fact sheets published by National Family Health Survey, India. (NFHS-4, 2015–2016 & NFHS-5, 2019–2020, Tamil Nadu).

      3.3 Changes in the prevalence of wasting and severe wasting across the districts of Tamil Nadu

      The prevalence of wasting dropped in more than two-thirds of districts across two rounds of NFHS (NFHS-4 & 5) (Table 2). There was more than a nine pp fall in the prevalence of wasting in Tiruvannamalai, Dharmapuri, Vellore, Coimbatore, the Nilgiris, Salem, Thanjavur, Pudukkottai, Krishnagiri. While the prevalence of wasting increased by more than 4 pp in Erode, Sivagangai, and Karur. More than a 6 pp decline in severe wasting was observed in Vellore, Tiruvannamalai, Thiruvarur, Villupuram, Ariyalur, and the Nilgiris, Cuddalore, Dharmapuri, Thiruvallur. However, an increase of 3 pp or more was noticed in Ramnathpuram, Theni, Virudhunagar, Sivagangai, Kancheepuram, and Erode. According to prevalence threshold values for wasting, it is a public health concern in all the districts except Coimbatore, Madurai, and Pudukottai.
      • WHO
      Nutrition Landscape Information System (NLiS) country profile indicators: interpretation guide.
      According to the latest round of NFHS (2019–20), Coimbatore (7%) and Pudukottai (1.6%) had the least prevalence of wasting and severe wasting respectively. While the highest prevalence of wasting (22.8%), as well as severe wasting (11.6%), was observed in Sivagangai.
      Table 2Changes in the prevalence of wasting and severe wasting across the districts of Tamil Nadu.
      DistrictsNFHS-5 (2019–20)WastingSevere wastingchange in pp Difference between NFHS-5 & NFHS-4
      NFHS-4 (2015–16)change in pp Difference between NFHS-5 & NFHS-4NFHS-5 (2019–20)NFHS-4 (2015–16)
      Ariyalur15.120.3−5.24.48.06−3.66
      Chennai18.318.140.167.612.58−4.98
      Coimbatore721.34−14.342.78.94−6.24
      Cuddalore13.919.74−5.8447.04−3.04
      Dharmapuri16.932.97−16.076.518.26−11.76
      Dindigul21.126.46−5.368.212−3.8
      Erode20.916.254.6511.26.075.13
      Kancheepuram15.713.871.836.92.854.05
      Kanyakumari11.492.42.72.040.66
      Karur18.423−4.68.79.48−0.78
      Krishnagiri10.420.14−9.744.79.72−5.02
      Madurai9.512.7−3.23.92.581.32
      Nagapattinam12.517.42−4.924.78.09−3.39
      Namakkal10.315−4.74.34.48−0.18
      Perambalur15.918.22−2.324.24.82−0.62
      Pudukkottai9.520.91−11.411.65.36−3.76
      Ramnathpuram17.7170.762.943.06
      Salem10.122.51−12.414.38.44−4.14
      Sivagangai22.818.774.0311.67.823.78
      Thanjavur8.320.44−12.143.77.48−3.78
      The Nilgiris17.331−13.77.717.06−9.36
      Theni15.5141.56.63.413.19
      Thiruvallur1723.33−6.333.610.73−7.13
      Thiruvarur18.422.12−3.726.86.70.1
      Thoothukudi18.412.467.74.972.73
      Tiruchirappalli20.9191.98.68.210.39
      Tirunelveli1212.93−0.933.13.34−0.24
      Tiruppur15.320.41−5.1110.310.010.29
      Tiruvannamalai14.834.59−19.79418.7−14.7
      Vellore13.127.47−14.372.511.95−9.45
      Villupuram12.416.32−3.923.42.970.43
      Virudhunagar14.417.73−3.337.64.363.24
      Source: District fact sheets published by National Family Health Survey, India. (NFHS-4, 2015–2016 & NFHS-5, 2019–2020, Tamil Nadu).

      3.4 Changes in prevalence of underweight across the districts of Tamil Nadu

      There has been a considerable reduction in the prevalence of underweight among children under 5 years of age across most of the districts especially Tiruvannamalai, Dharmapuri, Vellore, Thiruvarur, and Villupuram, where it decreased by more than 8 pp. In one-third of the districts, there is almost no change in the prevalence of underweight. In Sivagangai, Erode, and Karur, the prevalence increased by more than 5 pp. At present, Kanyakumari has the lowest prevalence of underweight (14.5%) while Karur has the highest (36.3%) (Table 3).
      Table 3Changes in the prevalence of underweight across the districts of Tamil Nadu.
      DistrictNFHS-5 (2019–20)NFHS-4 (2015–16)change in pp Difference between NFHS-5 (2019–2020) & NFHS-4 (2015–2016)
      Vellore19.732.64−12.94
      Tiruvannamalai2534.72−9.72
      Thiruvarur21.529.63−8.13
      Villupuram20.528.59−8.09
      Ariyalur23.230.7−7.5
      the Nilgiris23.230.7−7.5
      Cuddalore1825−7
      Dharmapuri23.229.64−6.44
      Thiruvallur20.626.64−6.04
      Coimbatore18.522.9−4.4
      Krishnagiri19.323.12−3.82
      Pudukkottai21.625−3.4
      Theni18.822−3.2
      Namakkal15.718−2.3
      Virudhunagar23.725.68−1.98
      Tiruppur23.124.87−1.77
      Salem20.822.22−1.42
      Dindigul28.429.77−1.37
      Thanjavur21.922.91−1.01
      Ramnathpuram21.622.6−1
      Tiruchirappalli27.427.6−0.2
      Tirunelveli22.722.680.02
      Perambalur22.322.010.29
      Nagapattinam24.322.861.44
      Kanyakumari14.512.781.72
      Madurai21.519.511.99
      Thoothukudi2117.553.45
      Kancheepuram19.816.13.7
      Chennai21.217.213.99
      Sivagangai28.422.95.5
      Karur36.328.887.42
      Erode26.91610.9
      Source: District fact sheets published by National Family Health Survey, India. (NFHS-4, 2015–2016 & NFHS-5, 2019–2020, Tamil Nadu.

      3.5 The changes in levels of the immediate determinants of undernutrition across the districts of TN

      The districts were ranked according to improvements made with respect to each of the determinants from NFHS-4 to NFHS-5 (Appendix Table- 1). Table 4 presents two districts that improved the most and two which made the least progress with respect to the determinants. For instance, the percentage of children (under 3 years) who were breastfed within an hour of birth (early initiation of breastfeeding) has increased significantly (more than 30 pp) in Chennai and Dharmapuri in the past 5 years. While the maximum reduction in early initiation of breastfeeding was observed in Dindigul and Karur (by 20 pp and 17.2 pp respectively). According to NFHS-5 more than two-thirds of the children under 3 years in Krishnagiri and Vellore were breastfed within an hour of birth, which is highest amongst all the districts in TN. Across the majority of the districts, the most marked decline among the immediate determinants was observed with respect to adequate diet being received by breastfed children (aged 6–23 months). The best performing districts in this regard were Thiruvallur and Madurai, where only a little more than a quarter of the breastfed children (aged 6–23 months) were receiving an adequate diet. There is a commendable reduction in the prevalence of diseases among children (diarrhoea and acute respiratory infection) in a majority of the districts.
      Table 4Trends in determinants of undernutrition among children under 5 (district-wise).
      TAMIL NADUImmediate determinantsLeast improvement (pp)Marked improvement (pp)Districts with the Best coverage (%)
      Infant and young child feeding PracticesDifference between NFHS-5 (2019–2020) & NFHS-4 (2015–2016)Difference between NFHS-5 (2019–2020) & NFHS-4 (2015–2016)NFHS-5 (2019–2020)
      Early initiation of breastfeedingDindigul: 20.2Dharmapuri: +31.4Vellore: 76.4
      Karur: 17.2Chennai: +34.5Krishnagiri: 76.5
      Adequate dietPerambalur: 32.6Thiruvallur: +6.7Thiruvallur: 26.3
      Thiruvallur: 27.6Chennai: +1.3Madurai: 25
      Maternal determinants
      Women with BMI <18.5 kg/m2Karur: 3Sivagangai: 7.4Kanyakumari: 5.9
      Kancheepuram: 3.1Krishnagiri: 6.4Chennai: 7.4
      Consumed IFA for more than 100 daysKarur: 4.3Dharmapuri: +41.9Vellore: 94.2
      Thoothukudi: 1.2Tirunelvelli: +42.6Tirrupur: 95
      Diarrhoea in the last two weeksNagapattinam: +0.4Perambalur: 11.2Salem: 0.7
      Diseases among childrenVirudhunagar: +1Krishnagiri: 9.1Kanyakumari: 0.9
      ARI in the last 2 weeksChennai: 0.4Perambalur: 7.5Ariyalur, Dharmapuri, Theni, Virudhunagar,

      Erode, Kanyakumari, The Nilgiris,

      Ramnathpuram, Perambalur, Tirunelvelli *
      Pudukottai: 1.4Tirunelvelli: 5.9
      TAMIL NADUUnderlying determinantsLeast improvement (pp)Marked improvement (pp)Districts with the Best coverage (%)
      Difference between NFHS-5(2019–2020) & NFHS-4(2015–2016)Difference between NFHS-5 (2019–2020) & NFHS-4(2015–2016)NFHS-5 (2019–2020)
      Literate womenKarur: 2.3Virudhunagar:+12.8Chennai: 94.8
      Thiruvallur: 1.4Namakkal: +10.9
      Kanyakumari: 97.7
      Maternal determinantsWomen with at least 10 or more years of schoolingKancheepuram: 1.2Virudhunagar: +13.7Kanyakumari: 77.1
      Salem: 0.3Tirunelvelli: +14.2Chennai: 76.7
      Girls 20–24 years married before the age of 18 yearsPerambalur: 7.4Theni: 13.1Chennai: 1.9
      Tirunelvelli: 4.7Dharmapuri: 11.2Thanjavur: 4.1
      Females aged 15–19 years with a child or pregnantErode: 8.8Madurai −8Thoothukudi: 0.9
      Pudukottai:6.8Ramnathpuram: 3.4Kancheepuram: 2.5
      Household determinantsHHs with improved drinking water sourcesAriyalur: 6Madurai: +6.1Perambalur, Nagapattinam

      Thiruvallur, Thiruvarur *
      Thoothukudi: 2.2Nagapattinam: 6.4
      HH with improved sanitation facilityChennai: +7.7Dharmapuri: +34.9Chennai: 90.4
      Erode: +4.9Tirunelvelli: +33.1Kanyakumari: 96.2
      HHs with electricityAriyalur: 0.5Thoothukudi: 1.3Chennai: 99.7
      Madurai: 0.5Theni: 1.8Thoothukudi: 100
      Source: NFHS-4(2015–16) and NFHS-5 state factsheets (2019–2020). pp: percentage points. For all indicators, top coverage districts refer to the districts with the highest prevalence in immediate determinants, except for women with a BMI of 18.5 kg/m2, diarrhoea in the last two weeks, and ARI in the last two weeks, for which it refers to the districts with the lowest prevalence in coverage.; ARI- Acute respiratory infection; BMI- Body mass index IFA-Iron Folic Acid tablet. Prevalence of exclusive breastfeeding is not available in the fact sheet and hence not included in the table. * (0% cases in all abovementioned distt.).
      Source: NFHS-4(2015–16) and NFHS-5 state factsheets (2019–2020). pp: percentage points. For all indicators, top coverage districts refer to the districts with the highest prevalence in underlying determinants, except for Girls 20–24 years married before the age of 18 years, Women 15–19 years with child or pregnant, for which it refers to the districts with the lowest prevalence in coverage. *100% coverage for HHs with improved drinking water sources in the abovementioned districts.

      3.6 The changes in levels of underlying determinants of undernutrition across the districts of TN (Appendix Table-2)

      According to the 5th round of NFHS, at least two-thirds of the women are literate in every district of TN. The literacy rate declined in Karur and Tiruvallur in the past five years by 2.3 pp and 1.4 pp respectively. While in a majority of the districts 50% or more women have 10 years or more of education. The highest increase in the proportion of literate women as well as women who completed 10 or more years of education was in Virudhunagar. But, Chennai and Kanyakumari had the highest proportion of literate women (aged 15–49 years) as well as those who completed 10 or more years of schooling. There was an increase in the proportion of women aged 15–19 years who were already mothers or pregnant at the time of the survey in about a quarter of the districts. There was a decline in the proportion of women aged 20–24 years but married before age 18 except for 5 districts. With respect to the household determinants around 95% or more households in every district have electricity and improved drinking water sources. Marked improvement was observed in the proportion of households with improved sanitation facilities, with Kanyakumari and Chennai having 96.2% and 92.4% of households with improved sanitation facilities.

      4. Discussion

      In a recent report released by NITI Aayog (2019–20), TN ranked second in the overall health index as well as it has been included as one of the model states which has achieved a marked improvement in the prevalence of stunting.
      World Bank,NITI Aayog,MoHFW
      The latest round of NFHS-5 (2019–20) also shows that the prevalence of undernutrition in the state has come down further since NFHS-4 (2015–16). However, data using a geographical lens at disaggregated levels highlights inter-district variations as observed in some previous studies conducted elsewhere.
      • Swaminathan A.
      • Kim R.
      • Xu Y.
      • et al.
      The burden of child malnutrition in India: a view from parliamentary constituencies.
      In certain districts- Ariyalur, Dindigul, Erode, Karur, Trichy, the Nilgiris, and Sivagangai, the prevalence of stunting, severe wasting as well as underweight was higher than the state average across both rounds of NFHS (NFHS-4 & NFHS-5) (appendix Figs. 1,2 and 3). Another noteworthy point is that, the severe forms of stunting and underweight remained unchanged between NFHS-3(2005–06) & NFHS-4(2015–16) at the state level.
      Changes in immediate determinants were mixed across the districts. A marked decline was observed in adequate diet being received by the breastfed children (6–23 months) in the majority of the districts. This decline could be attributed to the recent COVID-19 pandemic, which has adversely impacted food security across India
      • Summerton S.A.
      Implications of the COVID-19 pandemic for food security and social protection in India.
      There was a consistent improvement in several underlying determinants – household assets, sanitation, electricity - but to differing extents. Similar to the findings of some previous studies, it was found that the progress achieved by districts with respect to children's nutrition status coincides with the improvement it makes across the immediate and underlying determinants of nutrition.
      • Menon P.
      • Headey D.
      • Avula R.
      • Nguyen P.H.
      Understanding the geographical burden of stunting in India: a regression-decomposition analysis of district-level data from 2015–16.
      For instance, in the Karur district, the prevalence of stunting, wasting as well as underweight is above the state average across both rounds of NFHS (4&5) and the district also happens to make the least progress with respect to women's literacy rate, in infant and young child feeding practices as well as women with healthy BMI. While Kanyakumari which happens to have topped the districts across several immediate (women with healthy BMI) and underlying determinants (Household determinants) have the lowest prevalence of stunting and underweight amongst all the districts. Additionally, we have also classified the districts according to the cut-off values for the prevalence of wasting and stunting above which these become a issues of public health concern.
      • WHO
      Nutrition Landscape Information System (NLiS) country profile indicators: interpretation guide.
      And found that the majority of the districts of TN barring a few fell either in ‘high’ or ‘very high’ categories (of stunting as well as wasting). Another important finding is that there is a lack of facility-based interventions in several districts with a high burden of SAM among children. Out of the 13 districts (Villupuram, Thiruvarur, Tirrupur, Villupuram, Erode, Trichy, Thoothukudi, Virudhunagar, Ramnathpuram, Theni, Kancheepuram, Madurai) where the prevalence of SAM has increased (from NFHS-4 to NFHS-5), only 1 (Madurai) has Nutrition rehabilitation centre (as NRC admits SAM children). The most important policy implication of this preliminary analysis is a need for a state-wide undernutrition prevention strategy with a focus on addressing critical determinants district-by-district to reduce inequalities and the prevalence of childhood undernutrition. Over the years the government of India has launched several programmes to address the issue of malnutrition. These include the Integrated Child Development Services (ICDS), the National Health Mission, the Janani Suraksha Yojana, the Matritva Sahyog Yojana, the Mid-Day Meal Scheme, and the National Food Security Mission, among others. However, due to the persistence of malnutrition among children, the Government of India launched the National Nutrition Mission (NNM), also known as Poshan Abhiyaan in 2018. Some of the unique features of this programme include a more decentralized approach and governance reforms and a focus on the most vulnerable communities in the districts with the highest levels of malnutrition.
      • Rao N.
      Malnutrition in India: The National Nutrition Strategy Explained.
      By implementing interventions focussed on social safety nets, sanitation initiatives, women's empowerment, and agriculture projects, it is possible to enhance nutrition status and reduce disparities between the districts.
      • Cunningham K.
      • Ruel M.
      • Ferguson E.
      • Uauy R.
      Women's empowerment and child nutritional status in South Asia: a synthesis of the literature.
      To conclude, the study reiterates the significant merit in understanding variations of the nutrition status at the district level. Strong evidence derived from multiple sectors is required for successful nutrition programming on immediate determinants of malnutrition as well as nutrition-sensitive sectors are required for successful nutrition programming through long-term political commitments and multisectoral commitments.

      5. Conclusion

      The study's granular district-focused analysis, reveals how concentrated is the burden of undernutrition in some districts compared to others. The necessity for an undernutrition prevention approach that is state-wide yet focused on tackling crucial variables district-by-district to minimise inequities in the prevalence of childhood undernutrition is the most significant policy implication of our findings. Our analysis, therefore, provides timely evidence for policymakers to tackle undernutrition in the state of TN, in the context of India's commitments to meet the Poshan Abhiyan targets as well as the global nutrition targets and the Sustainable Development Goals.

      Funding information

      This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

      Ethical statement

      The analysis for this study was done using the National Family Health survey factsheets (NFHS-4 & 5) accessed from (http://rchiips.org/nfhs/districtfactsheet_NFHS-5.shtml) and http://rchiips.org/nfhs/. The study is based on a secondary data set, a recent NFHS-5 survey, consent is taken from participants and data is publicly available with no identifiable information on the survey participants. This dataset is available in the public domain and, hence, no ethical approval was required for the present study.

      Declaration of competing interest

      Author hereby declares that there are no conflicts of interest.

      Appendix A. Supplementary data

      The following is the supplementary data to this article:

      References

        • UNICEF, WHO, W.B.G.
        Joint child malnutrition estimates.
        Who. 2021; 24: 51-78
        • Swaminathan A.
        • Kim R.
        • Xu Y.
        • et al.
        The burden of child malnutrition in India: a view from parliamentary constituencies.
        Econ Polit Wkly. 2019; 54: 44-52
        • Black R.E.
        • Allen L.H.
        • Bhutta Z.A.
        • et al.
        Maternal and child undernutrition: global and regional exposures and health consequences.
        Lancet. 2008; 371: 243-260https://doi.org/10.1016/S0140-6736(07)61690-0
        • de Onis M.
        • Branca F.
        Childhood stunting: a global perspective.
        Matern Child Nutr. 2016; 12: 12-26https://doi.org/10.1111/mcn.12231
        • UNICEF
        Conceptual Framework Child Nutrition.
        2021
        • Bhadoria A.S.
        • Kapil U.
        • Bansal R.
        • Pandey R.M.
        • Pant B.
        • Mohan A.
        Prevalence of severe acute malnutrition and associated sociodemographic factors among children aged 6 months – 5 years in rural population of Northern India : a population-based survey.
        (6(2), 380-385)
        • Ahuja A.
        How Can We Address the Rising Incidence of Wasting Among Children in India ? Pandey 2016.
        2018
        • Jose S.
        Child undernutrition in India assessment of prevalence, decline and disparities.
        EPW. 2018; LIII: 63-70https://doi.org/10.2139/ssrn.1734591
        • Ambadekar N.N.
        • Zodpey S.P.
        Risk factors for severe acute malnutrition in under-five children : a case-control study in a rural part of India.
        Publ Health. 2016; 2–9https://doi.org/10.1016/j.puhe.2016.07.018
        • Pathak P.K.
        • Singh A.
        • Subramanian S.V.
        Economic inequalities in maternal health care: prenatal care and skilled birth attendance in India, 1992-2006.
        PLoS One. 2010; 5: 1992-2006https://doi.org/10.1371/journal.pone.0013593
        • Subramanyam M.A.
        • Kawachi I.
        • Berkman L.F.
        • Subramanian S.V.
        Socioeconomic inequalities in childhood undernutrition in India: analyzing trends between 1992 and 2005.
        PLoS One. 2010; 5https://doi.org/10.1371/journal.pone.0011392
        • Kim J.
        • Liu Y.
        • Wang W.
        • et al.
        Estimating the burden of child undernutrition for smaller electoral units in India.
        JAMA Netw Open. 2021; 4: 1-12https://doi.org/10.1001/jamanetworkopen.2021.29416
        • Striessnig E.
        • Bora J.K.
        Under-five child growth and nutrition status: spatial clustering of Indian districts.
        Spatial Demography. 2020; 8: 63-84https://doi.org/10.1007/s40980-020-00058-3
        • Hemalatha R.
        • Pandey A.
        • Kinyoki D.
        • et al.
        Mapping of variations in child stunting, wasting and underweight within the states of India: the Global Burden of Disease Study 2000–2017.
        EClinicalMedicine. 2020; 22https://doi.org/10.1016/j.eclinm.2020.100317
        • Menon P.
        • Headey D.
        • Avula R.
        • Nguyen P.H.
        Understanding the geographical burden of stunting in India: a regression-decomposition analysis of district-level data from 2015–16.
        Matern Child Nutr. 2018; 14: 1-10https://doi.org/10.1111/mcn.12620
        • Nguyen P.H.
        • Scott S.
        • Avula R.
        • Tran L.M.
        • Menon P.
        Trends and drivers of change in the prevalence of anaemia among 1 million women and children in India, 2006 to 2016.
        BMJ Global Health. 2018; 3: 1-12https://doi.org/10.1136/bmjgh-2018-001010
        • Dandona L.
        • Dandona R.
        • Kumar G.A.
        • et al.
        Nations within a nation: variations in epidemiological transition across the states of India, 1990–2016 in the Global Burden of Disease Study.
        Lancet. 2017; 390: 2437-2460https://doi.org/10.1016/S0140-6736(17)32804-0
        • Chaudhuri S.
        • Gupta N.
        Levels of living and poverty patterns: a district-wise analysis for India.
        Econ Polit Wkly. 2009; 44: 94-110
        • Rajpal S.
        • Kim J.
        • Joe W.
        • Kim R.
        • Subramanian S.V.
        Small area variation in child undernutrition across 640 districts and 543 parliamentary constituencies in India.
        Sci Rep. 2021; 11: 1-9https://doi.org/10.1038/s41598-021-83992-6
        • Das P.
        • Roy R.
        • Das T.
        • Roy T.B.
        Prevalence and change detection of child growth failure phenomena among under-5 children: a comparative scrutiny from NFHS-4 and NFHS-5 in West Bengal, India.
        Clin Epidemiol Glob Health. 2021; 12100857https://doi.org/10.1016/j.cegh.2021.100857
        • Dixit P.
        • Gupta A.
        • Dwivedi L.K.
        • Coomar D.
        Impact evaluation of integrated child development Services in rural India: propensity score matching analysis.
        Sage Open. 2018; 8https://doi.org/10.1177/2158244018785713
        • Kandpal E.
        Beyond average treatment effects: distribution of child nutrition outcomes and program placement in India's ICDS.
        World Dev. 2011; 39: 1410-1421https://doi.org/10.1016/j.worlddev.2010.12.013
        • Niti ayog I.
        • WCD division
        Accelerating Progress on Nutrition in India: What Will it Take - Third Progress Report.
        2020 (1–140)
        • WHO
        Nutrition Landscape Information System (NLiS) country profile indicators: interpretation guide.
        in: Nutrition Landscape Information System (NLIS) Country Profile. second ed. © World Health Organization 2019 Some, 2019
        • Niti ayog I.
        • WCD division
        State Nutrition Profile : Gujarat Figure 1 . Trends in Undernutrition Outcomes : 2005-2006, 2015. vol. 3. 2021 (43)
        • De Onis M.
        • Borghi E.
        • Arimond M.
        • et al.
        Prevalence thresholds for wasting, overweight and stunting in children under 5 years.
        Publ Health Nutr. 2019; 22: 175-179https://doi.org/10.1017/S1368980018002434
        • World Bank,NITI Aayog,MoHFW
        HEALTHY STATES PROGRESSIVE INDIA. Round IV 2. 2019 (Report)
        • Summerton S.A.
        Implications of the COVID-19 pandemic for food security and social protection in India.
        Indian J Hum Dev. 2020; 14: 333-339https://doi.org/10.1177/0973703020944585
        • Rao N.
        Malnutrition in India: The National Nutrition Strategy Explained.
        PRSIndia, 2017
        • Cunningham K.
        • Ruel M.
        • Ferguson E.
        • Uauy R.
        Women's empowerment and child nutritional status in South Asia: a synthesis of the literature.
        in: Maternal and Child Nutrition. vol. 11. Blackwell Publishing Ltd, 2015: 1-19https://doi.org/10.1111/mcn.12125 (1)