Association of Trends in Child Undernutrition and Implementation of the National Rural Health Mission in India: A Nationally Representative Serial Cross-Sectional Study on Data from 1992 – 2015
Notice bibliographique
Résumé
ABSTRACT Background India launched the National Rural Health Mission (NRHM) in 2005 to strengthen its primary healthcare system in high-focus and northeast focus states. One of the NRHM objectives was to reduce child undernutrition in India. Methods and Findings We used data from 1992, 1998, 2005, and 2015 National Family Health Surveys of India to evaluate trends in child undernutrition prevalence before and after NRHM and across different categories of focus states. Stunting, Wasting, and Comprehensive Index of Anthropometric Failure (CIAF) was assessed using WHO growth curves to assess chronic, acute, and overall undernutrition. The study included 187,452 children aged 3 years or under. Survey-weighted and confounder-adjusted average annualized reduction rates (AARR) and predicted probability ratios were used to assess trends and socioeconomic disparities for child undernutrition, respectively. Nationwide, the prevalence of all types of undernutrition decreased from 1992 to 2015. However, the trends varied before and after NRHM implementation and differentially by focus states. After NRHM, acute undernutrition declined more rapidly among high-focus states (AARR 1.0%) but increased in normal-focus states (AARR -1.9% per year; p<0.001). In contrast, the prevalence of chronic undernutrition declined more rapidly (AARR 1.6%) in the normal focus states in comparison to high-focus states (0.3%; p=0.01). Income and caste-based disparities in acute undernutrition decreased but did not disappear after the implementation of the NRHM. However, similar disparities in prevalence of chronic undernutrition appear to be exacerbated after the implementation of the NRHM. Major limitations of this study include the observational and cross-sectional design, which preclude our ability to draw causal inferences. Conclusion Our results suggests that NRHM implementation might be associated with improvement in wasting (acute) rather than stunting (chronic) forms of undernutrition. Strategies to combat undernutrition equitably, especially in high-focus states are needed. AUTHOR SUMMARY Why was this study done? India has the largest number of undernourished children of any country worldwide India’s government launched a public health program called National Rural Health Mission (NRHM) that had a focus on improving maternal and child health Impact of the NRHM has been studied on infant mortality rate but nationwide estimates of association of NRHM with child undernutrition rates remains unelucidated What did the researchers do and find? We carried out a cross-sectional study based on nationally representative serial data gathered through the National Family Health Surveys in 1992, 1998, 2005, and 2015 on a total 187,452 children, which represented national population of children aged 3 years and under residing in India in the respective survey years The study reports that the prevalence of undernutrition and trends in its changes before and after implementation of NRHM differed across different indicators of undernutrition. The prevalence of wasting (acute undernutrition) declined at a faster rate in the post-NRHM period among the states where NRHM was prioritized while the prevalence of acute undernutrition increased during the post-NRHM where NRHM was not implemented. Conversely, prevalence of stunting (chronic undernutrition) declined at a faster rate among the normal focus states in the post-NRHM period in comparison to high and northeast focus states. Socioeconomic disparities for chronic and overall undernutrition persisted or widened over time. We observed a decline in wealth, maternal-education, rural, and caste-based disparities for acute undernutrition after the implementation of the NRHM. What do these findings mean? Policies enacted under the NRHM may be associated with a reduction in acute form of child undernutrition Policies enacted under the NRHM may be associated with modest reduction in wealth, education, or caste-based disparities for acute form of child undernutrition, however, the disparities for chronic undernutrition among children were not associated by the NRHM
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».