Date Published: July 24, 2018
Publisher: Public Library of Science
Author(s): Narendra K. Arora, M. K. C. Nair, Sheffali Gulati, Vaishali Deshmukh, Archisman Mohapatra, Devendra Mishra, Vikram Patel, Ravindra M. Pandey, Bhagabati C. Das, Gauri Divan, G. V. S. Murthy, Thakur D. Sharma, Savita Sapra, Satinder Aneja, Monica Juneja, Sunanda K. Reddy, Praveen Suman, Sharmila B. Mukherjee, Rajib Dasgupta, Poma Tudu, Manoja K. Das, Vinod K. Bhutani, Maureen S. Durkin, Jennifer Pinto-Martin, Donald H. Silberberg, Rajesh Sagar, Faruqueuddin Ahmed, Nandita Babu, Sandeep Bavdekar, Vijay Chandra, Zia Chaudhuri, Tanuj Dada, Rashna Dass, M. Gourie-Devi, S. Remadevi, Jagdish C. Gupta, Kumud K. Handa, Veena Kalra, Sunil Karande, Ramesh Konanki, Madhuri Kulkarni, Rashmi Kumar, Arti Maria, Muneer A. Masoodi, Manju Mehta, Santosh Kumar Mohanty, Harikumaran Nair, Poonam Natarajan, A. K. Niswade, Atul Prasad, Sanjay K. Rai, Paul S. S. Russell, Rohit Saxena, Shobha Sharma, Arun K. Singh, Gautam B. Singh, Leena Sumaraj, Saradha Suresh, Alok Thakar, Sujatha Parthasarathy, Bhadresh Vyas, Ansuman Panigrahi, Munish K. Saroch, Rajan Shukla, K. V. Raghava Rao, Maria P. Silveira, Samiksha Singh, Vivek Vajaratkar, Lars Åke Persson
Abstract: BackgroundNeurodevelopmental disorders (NDDs) compromise the development and attainment of full social and economic potential at individual, family, community, and country levels. Paucity of data on NDDs slows down policy and programmatic action in most developing countries despite perceived high burden.Methods and findingsWe assessed 3,964 children (with almost equal number of boys and girls distributed in 2–<6 and 6–9 year age categories) identified from five geographically diverse populations in India using cluster sampling technique (probability proportionate to population size). These were from the North-Central, i.e., Palwal (N = 998; all rural, 16.4% non-Hindu, 25.3% from scheduled caste/tribe [SC-ST] [these are considered underserved communities who are eligible for affirmative action]); North, i.e., Kangra (N = 997; 91.6% rural, 3.7% non-Hindu, 25.3% SC-ST); East, i.e., Dhenkanal (N = 981; 89.8% rural, 1.2% non-Hindu, 38.0% SC-ST); South, i.e., Hyderabad (N = 495; all urban, 25.7% non-Hindu, 27.3% SC-ST) and West, i.e., North Goa (N = 493; 68.0% rural, 11.4% non-Hindu, 18.5% SC-ST). All children were assessed for vision impairment (VI), epilepsy (Epi), neuromotor impairments including cerebral palsy (NMI-CP), hearing impairment (HI), speech and language disorders, autism spectrum disorders (ASDs), and intellectual disability (ID). Furthermore, 6–9-year-old children were also assessed for attention deficit hyperactivity disorder (ADHD) and learning disorders (LDs). We standardized sample characteristics as per Census of India 2011 to arrive at district level and all-sites-pooled estimates. Site-specific prevalence of any of seven NDDs in 2–<6 year olds ranged from 2.9% (95% CI 1.6–5.5) to 18.7% (95% CI 14.7–23.6), and for any of nine NDDs in the 6–9-year-old children, from 6.5% (95% CI 4.6–9.1) to 18.5% (95% CI 15.3–22.3). Two or more NDDs were present in 0.4% (95% CI 0.1–1.7) to 4.3% (95% CI 2.2–8.2) in the younger age category and 0.7% (95% CI 0.2–2.0) to 5.3% (95% CI 3.3–8.2) in the older age category. All-site-pooled estimates for NDDs were 9.2% (95% CI 7.5–11.2) and 13.6% (95% CI 11.3–16.2) in children of 2–<6 and 6–9 year age categories, respectively, without significant difference according to gender, rural/urban residence, or religion; almost one-fifth of these children had more than one NDD. The pooled estimates for prevalence increased by up to three percentage points when these were adjusted for national rates of stunting or low birth weight (LBW). HI, ID, speech and language disorders, Epi, and LDs were the common NDDs across sites. Upon risk modelling, noninstitutional delivery, history of perinatal asphyxia, neonatal illness, postnatal neurological/brain infections, stunting, LBW/prematurity, and older age category (6–9 year) were significantly associated with NDDs. The study sample was underrepresentative of stunting and LBW and had a 15.6% refusal. These factors could be contributing to underestimation of the true NDD burden in our population.ConclusionsThe study identifies NDDs in children aged 2–9 years as a significant public health burden for India. HI was higher than and ASD prevalence comparable to the published global literature. Most risk factors of NDDs were modifiable and amenable to public health interventions.
Partial Text: “Neurodevelopment is a dynamic inter-relationship between genetic, brain, cognitive, emotional and behavioural processes across the developmental lifespan. Significant and persistent disruption to this dynamic process through environmental and genetic risk can lead to neurodevelopmental disorders and disability” . Low-income communities and children living in poverty are disproportionately affected by NDDs . Communities most vulnerable to NDDs often lack disease burden estimates to formulate policy decisions and implement programs to address NDDs . To better understand the spectrum of childhood NDDs, there is a need to utilize valid and practical screening methodologies based on globally accepted disease definitions . To date, global health policy makers have relied on national census disability data, even though such an approach grossly underestimates disability prevalence in children . Censuses usually restrict themselves to the identification of gross and visible disabilities only and utilize nonspecialized assessors and diagnostic tools [5,6]. Global and societal leaders have urged that nations promote awareness of children with disabilities and advocate for their healthcare services . The United Nations General Assembly  and Agenda for Sustainable Development  consider childhood disability an integral part of the global development agenda and promote the use of evidences that address national and regional contexts and are disaggregated by gender and age.
We have reported this study as per the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines (S1 STROBE Checklist).
Table 2 illustrates the study recruitment profile for each site. Overall, the field teams approached families of 4,739 children, of which 739 (15.6%) refused to participate. After enrolling the targeted 4,000 children, 181 (4.5%) refused to complete diagnostic assessment, of which 158 (4.0%) could be replaced with age category and gender-matched children from the same cluster. Post hoc analyses revealed that dropouts and their replacements also matched for anthropometric measurements and sociodemographic characteristics (S1 Table). The NDD assessment could be done in 3,977 children (83.9% of the total approached; 99.4% of those enrolled).
The study reports the prevalence of NDDs in children aged 2 to 9 years obtained through a population-based, multisite survey across five regions in India. The prevalence of NDDs varied across the five study sites despite using the same diagnostic tools with application of consistent methodology and training for the assessors. NDD prevalence might truly vary across regions, particularly in a large country like India, due to heterogenous distribution of risk factors and biological factors, if any. Dhenkanal, situated in central Odisha, with a sizeable tribal population, has high under-five mortality rate (80 per 1,000 live births)  and is endemic for hemoglobinopathies  and cerebral malaria (cerebral malaria in Odisha has up to six times higher risk of mortality among children) [37,38]. It has been reported that the risk of mortality in children with NDDs may be high in environments of poor economic development, weak health systems, and high child mortality [4,39]. The higher prevalence of HI in Palwal contributed to a higher overall prevalence of NDD in this site over others. According to an earlier study, repeated respiratory infections and high rates of chronic suppurative otitis media were associated with a high rate of deafness in 5–15-year-old children in the area .