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Sociodemographic determinants of malnutrition amongst under-five children: Insights for public health interventions
*Corresponding author: Mrs.Vanitha.N, MSc Nursing, Department of Pediatric nursing, Ramaiah Institute of Nursing Education and Research, M. S. Ramaiah University of Applied Sciences Bangalore, India. vanithan.riner@msruas.ac.in
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Received: ,
Accepted: ,
How to cite this article: Vanitha N, Pavan U. Sociodemographic determinants of malnutrition amongst under-five children: Insights for public health interventions. Karnataka Paediatr J. doi: 10.25259/ KPJ_66_2025
Abstract
Objectives:
Adequate nutrition is crucial for a child’s growth and development, yet malnutrition remains a significant public health issue in India. Despite economic progress, undernutrition, stunting, wasting and micronutrient deficiencies continue to affect a large proportion of children under five, while emerging overweight adds to the complexity. The study aims to assess the prevalence of malnutrition, including both undernutrition and overweight, amongst children under-five years of age, and to examine the association of these nutritional outcomes with selected sociodemographic variables.
Material and Methods:
A community-based cross-sectional study was conducted at a rural field practice area. Five villages under primary health centre were randomly selected and a total of 210 children under five were selected through a convenience sampling technique. Data were collected using structured questionnaires and anthropometric measurements following the World Health Organization guidelines. Analysis was done using the Statistical Package for the Social Sciences version 20.
Results:
Amongst the participants, 16.7% were underweight (6.2% severely), 31.9% stunted (15.2% severely) and 21.9% wasted (10% severely). In addition, 11% of children were overweight, reflecting the dual burden of malnutrition within the same population. Age, gender and socioeconomic status showed significant associations with undernutrition.
Conclusion:
The study highlights a high burden of malnutrition in rural Bangalore, with both undernutrition and rising overweight coexisting. These findings underscore the need for age-specific, equity-focused interventions to support vulnerable groups and to address the double burden of malnutrition in rural India. The study is limited by its cross-sectional design and use of convenience sampling, which may restrict generalisability. Nevertheless, the results provide important local evidence to guide interventions and support progress towards Sustainable Development Goal 2 (Zero Hunger) by 2030.
Keywords
Child
India
Malnutrition
Public health
Rural population
Sociodemographic factors
INTRODUCTION
Adequate nutrition is a fundamental human right and is especially critical for a child’s physical and cognitive development.[1] Nutrition in the first 5 years of life plays a pivotal role in shaping a child’s long-term health, developmental outcomes and overall potential.[2] This period is particularly sensitive, and nutritional deficiencies can have lasting consequences on a child’s physical and mental capabilities.[3] The overall well-being and future prosperity of any nation are closely tied to the health and development of its youngest citizens.[4]
Undernutrition amongst children continues to be a significant global public health issue, particularly in low- and middle-income nations.[5] As of 2020, it was estimated that 21.3% of children under the age of five – approximately 144 million – were affected by stunting, 6.9% (47 million) experienced wasting and 5.6% (38 million) were classified as overweight.[6] Despite India’s economic growth, malnutrition amongst children remains a critical issue, manifesting in multiple forms including undernutrition (stunting, wasting, and underweight), micronutrient deficiencies and overweight or obesity.[7]
According to the National Family Health Survey (NFHS-5, 2019–2021), amongst children under five in India, 30% are stunted, 18.5% are wasted, 7.6% are severely wasted, 27.3% are underweight and 4.2% are overweight.[8] These statistics highlight the complex and multifaceted nature of childhood malnutrition in the country.
Malnourished children are at risk not only for immediate health issues but also for long-term developmental delays, which may affect learning, social engagement and future economic productivity.[3,4] Understanding the prevalence of undernutrition and its associated sociodemographic factors is crucial to identify at-risk populations and to inform targeted public health interventions.[5,9] These efforts contribute to achieving Sustainable Development Goal.[10]
Although several studies have examined the determinants of child malnutrition across India, there is a need to focus on specific regions like rural Bangalore, which presents unique contextual challenges. National and state-level data consistently show that rural areas report higher rates of stunting, wasting and underweight compared to urban areas.[8] In rural Bangalore, limited access to healthcare, inconsistent implementation of nutritional programmes such as the Integrated Child Development Services (ICDS) and mid-day meal schemes and infrastructural constraints further aggravate the issue.[8,11] Unlike more remote rural regions, rural Bangalore represents a transitional zone where rural poverty coexists with urban influence, potentially creating unique nutritional patterns, including a double burden of undernutrition and overweight.[12,13]
However, there is a paucity of community-based studies specifically examining the nutritional status of children in rural Bangalore. Existing state-level and national surveys provide important overviews but do not capture local sociodemographic dynamics that influence child growth and development. Addressing this gap is critical to designing interventions tailored to the needs of vulnerable groups in this semi-urbanising rural context.
Hence, the present study was conducted to assess the nutritional status of children under-five years of age and to explore the sociodemographic factors influencing it in rural Bangalore. In addition to the long-standing burden of undernutrition, recent evidence indicates rising trends of overweight and obesity amongst Indian children, reflecting a nutrition transition. By generating region-specific evidence, the study aims to support the development of effective, targeted public health strategies to address childhood malnutrition in India.
Objectives
To assess the prevalence of double burden malnutrition amongst children under-five years of age in rural Bengaluru
To find the association between nutritional status and sociodemographic determinants.
MATERIAL AND METHODS
A community-based cross-sectional study was conducted in the field practice area. Five villages under the community practice area PHC were randomly selected, and 210 children under-five years of age were chosen using a convenience sampling technique. Given the resource and time constraints of a community-based study, convenience sampling was chosen as a pragmatic approach, while still ensuring inclusion of children across all households with eligible participants in the selected villages. From the literature review of a previous community study in Karnataka by Chittapur et al. (2024),[21] the prevalence of stunting was reported as 35% in rural Yadgir. Expecting a similar prevalence in the present study, and using a 95% confidence level, an absolute precision of ≈6.6% yields a required sample size of 206. After rounding, the final sample size chosen for the study was 210 children.
The following criteria were considered while selecting participants in this study: (1) Healthy children under five years of age and (2) mothers who had been residing in the study area for not <3 consecutive years. Children currently undergoing treatment for chronic illnesses were excluded from the study to minimise confounding from disease-related malnutrition and focus on community-level determinants.
Data collection tool
The tool consists of two sections:
Section A
It consists of sociodemographic characteristics of the child and parents such as age of child in months, sex, religion, mother’s literacy, fathers’ literacy, socioeconomic status which was assessed using modified Kuppuswamy scale, birth weight of child, birth order of child, number of sibling, exclusive breastfeeding status, age of initiation of complementary feed, immunisation status and history of illness within last month.
Section B
Anthropometric data, including weight and height, were collected in accordance with the WHO protocols.[14] These measurements were then used to calculate indicators relative to the child’s age, and the results were evaluated against the WHO growth reference standards.
Weight
Each child’s weight was recorded in kilograms using a calibrated weighing scale, following standard procedures, with precision up to 0.5 kg. For children under 2 years of age or those unable to stand independently, the tared weighing method was employed. Children aged 2 years and above were weighed standing alone on a recently calibrated analogue scale.
Height
Height was measured to the nearest 0.1 cm using either a stadiometer or an infantometer, based on the child’s age and ability to stand. For children younger than 2 years, recumbent length (lying down) was taken using an infantometer. In contrast, standing height was recorded using a stadiometer for children aged 2 years and above who were able to stand upright.
Underweight
A low weight-for-age is termed as underweight, defined as a weight-for-age Z-score (WAZ) of <−2. Severely underweight is classified if WAZ is <−3 of the WHO (2006) reference values.[12]
Wasting
Wasting reflects acute malnutrition and is identified by a weight-for-height Z-score (WHZ) below −2, based on the WHO reference standards.[12] Moderate wasting is indicated when the WHZ falls between −2 and −3, while a WHZ below −3 denotes severe wasting.
Stunting
Stunting, characterised by low height for age, signifies prolonged or chronic undernutrition during early development. According to the WHO (2006) growth standards, a height-forage Z-score (HAZ) of <−2 indicates stunting. Values between −2 and −3 represent moderate stunting, whereas a HAZ below −3 is classified as severe stunting.
Method of data collection
For this study, the investigator took into consideration the ethical issues. Ethical clearance was obtained from the University Ethics Committee for Human Trials. No ethical issues were confronted while conducting this study. The purpose of the study was explained to the samples and informed consent was obtained before the data collection from mothers of children, to get their cooperation.
Data were collected through structured questionnaires through a house-to-house survey, with interviews conducted with the mothers of children under five and anthropometric assessments of these children were performed following WHO criteria. Data were entered into an Excel spreadsheet and analysed using the Statistical Package for the Social Sciences version 20.
RESULTS
Section 1: Description of sociodemographic profile of the sample
The majority of the under-five children (29%) were between the age group of 6–12 months, with 54.8% being male and 87.1% belonging to the Hindu religion. About 37.6% of mothers had completed their pre-university course, while 24.3% were graduates. Amongst the total sample, 77.6% of mothers of the under-five children were homemakers, and the majority (37.6%) were from the upper-middle-income group. Approximately 80.5% had a birth weight of >2.5 kg, and 72.3% were first-born children. A total of 78.6% of the mothers exclusively breastfed their children and started complementary feeding after the age of 6 months. As appropriate per age, 97% of the children were fully immunised.
Section 2: Nutritional status of children between 6 months and 5 years of age as per WHO Z-scores
The nutritional status of the 210 children assessed using Z scores for key anthropometric indicators – weight-for-height/ length, height-for-age and weight-for-age – reveals a mixed picture of both undernutrition and emerging overnutrition. Based on the WHZ/length Z score, which reflects acute malnutrition, 21 children (10%) were identified with severe wasting and 25 children (12%) with moderate wasting. This indicates that 22% of the children were suffering from acute malnutrition, likely due to recent illness or inadequate dietary intake, while the majority – 164 children (78%) – had normal weight relative to their height.
Height-for-age, an indicator of chronic malnutrition or stunting, showed that 32 children (15%) were severely stunted and 35 (17%) moderately stunted, accounting for a total of 32% experiencing long-term growth retardation.
This suggests persistent nutritional deprivation, which could be linked to poor maternal nutrition, frequent infections or inadequate feeding practices during early childhood. The remaining 143 children (68%) had normal height-for-age, indicating adequate linear growth for their age.
When evaluating weight-for-age, a composite measure of both acute and chronic undernutrition, 13 children (6%) were severely underweight and 22 (12%) moderately underweight, together making up 18% of the study population. In addition, 24 children (11%) were found to be overweight, pointing to the coexistence of undernutrition and overnutrition within the same population. A significant proportion – 151 children (72%) – had a normal weight-for-age.
In summary, while a majority of the children exhibited normal growth parameters, the findings highlight a concerning burden of malnutrition: 22% acutely malnourished, 32% chronically undernourished and 18% underweight. The presence of 11% overweight children also indicates a rising trend of overnutrition. This dual burden of malnutrition requires comprehensive nutritional strategies such as improved dietary diversity, early detection and management of malnutrition and health education.
Section 3: This section deals with the association between nutritional status and sociodemographic determinants
Association of weight for length/height (z-score) with sociodemographic variables
Table 1: Association of weight for length/height (z-score) with birth weight.
| Sl. no | Sociodemographic variables | weight for length/height (z-score) | Chi square value (χ2) | P-value | ||
|---|---|---|---|---|---|---|
| Severe wasting (f) | Moderate wasting (f) | Normal (f) | ||||
| 1. | Birth weight (in kg) | |||||
| < 2.5 | 8 | 7 | 26 | 7.408 | 0.025 | |
| > 2.5 | 13 | 17 | 139 | df=2 | S* | |
Birth weight showed a statistically significant association with weight-for-length Z score/WAZ (χ2 = 7.408, df = 2, P = 0.025). Wasting was more prevalent amongst children with a birth weight below 2.5 kg, whereas those with a birth weight above 2.5 kg were more likely to have normal weight-for-length. This indicates that low birth weight is a key risk factor for wasting in early childhood.
Association between age group and WAZ with sociodemographic variables
Table 2 shows a significant association between age group and WAZ (χ2 = 21.586, df = 12, P = 0.042). Among children aged 6–12 months, underweight (both severe and moderate) was more prevalent. As age increased, a higher proportion of children had normal weight, while the prevalence of overweight was relatively higher in the 25–4-month age groups. These findings indicate that nutritional status varies with age, emphasising the need for targeted age-specific nutritional interventions.
| Sl. no | Sociodemographic variables | Weight for age (z-score) | Chi-square value (χ2) | P-value | |||
|---|---|---|---|---|---|---|---|
| Severe underweight (f) | Moderate underweight (f) | Normal (f) | Overweight (f) | ||||
| 1. | Age group (in months) | ||||||
| 6-12 | 7 | 10 | 43 | 1 | 21.586 | 0.042 | |
| 13-24 | 4 | 4 | 33 | 5 | df=12 | S* | |
| 25-36 | 0 | 5 | 24 | 8 | |||
| 37-48 | 1 | 2 | 31 | 7 | |||
| 49-59 | 1 | 1 | 20 | 3 | |||
Association between length/height for age (Z-score) with sociodemographic variables
Table 3 highlights significant associations between length/ height-for-age (Z score) and several sociodemographic variables:
| Sl. no | Sociodemographic variables | Length/height for age (Z-Score) | Chi-square value (χ2) | P-value | ||
|---|---|---|---|---|---|---|
| Severe stunting (f) | Moderate stunting (f) | Normal (f) | ||||
| 1. | Age group (in months) | |||||
| 6-12 | 18 | 11 | 32 | 21.124 | 0.007 | |
| 13-24 | 3 | 11 | 32 | df=8 | S* | |
| 25-36 | 4 | 4 | 29 | |||
| 37-48 | 2 | 5 | 34 | |||
| 49-59 | 5 | 4 | 16 | |||
| 2. | Gender | |||||
| Male | 23 | 21 | 71 | 5.679 | 0.054 | |
| df=2 | S* | |||||
| female | 9 | 14 | 72 | |||
| Semi professional | 3 | 6 | 11 | |||
| Clerical/shop owner/farm | 0 | 1 | 5 | |||
| Skilled worker | 0 | 0 | 2 | |||
| Semi-skilled worker | 1 | 2 | 1 | |||
| Un skilled worker | 0 | 2 | 3 | |||
| Home maker | 26 | 23 | 114 | |||
| 3. | Socio economic status | |||||
| Upper | 9 | 9 | 21 | 19.699 | 0.003 | |
| df=6 | S* | |||||
| Upper middle | 11 | 9 | 59 | |||
| Lower middle | 6 | 4 | 45 | |||
| Upper lower | 6 | 13 | 18 | |||
Age group showed a statistically significant association with stunting (χ2 = 21.124, df = 8, P = 0.007), with severe and moderate stunting more prevalent in the 6–12-month age group.
Socioeconomic status also had a significant association (χ2 = 19.699, df = 6, P = 0.003); stunting was more common amongst children from upper, lower and lower middle classes.
Gender showed a borderline significance (χ2 = 5.679, P = 0.054), with more males exhibiting stunting compared to females.
These findings suggest that younger age, male gender and lower socioeconomic status are important risk factors for stunting in children.
DISCUSSION
The present study reported a 16.7% prevalence of underweight, which is lower than the national average of 27.3% reported in NFHS-5 (2019–2021). Although relatively low, this still indicates a considerable burden of undernutrition. Similar findings were observed by Taneja et al. (2020) in Haryana (18%) and Agarwal et al. (2018) in urban Lucknow (22%),[16,17,18] suggesting that areas with better healthcare and maternal awareness may exhibit lower underweight rates.
In contrast, the stunting prevalence was 31.9%, slightly exceeding the national average of 30%. Despite the marginal difference, the result is significant as it reflects chronic undernutrition. Studies by Meshram et al. (2019) in Maharashtra and Kapoor and Kumar (2018) in Uttar Pradesh[19,20] similarly reported high stunting rates, particularly amongst socioeconomically disadvantaged children. These findings stress the importance of interventions during the first 1,000 days of life.
Wasting was observed in 21.9% of children, which is notably higher than the NFHS-5 national average of 18.5%, indicating acute malnutrition in the study area. Comparable results were reported by Bhagwat et al. (2021) and Taneja et al. (2020),[16,21,22] who linked high wasting rates with infections, inadequate feeding and poor hygiene.
In the present study, 11% of under-five children were found to be overweight, which is substantially higher than national estimates and suggests an early stage of nutrition transition in rural Bangalore. According to the NFHS (NFHS-4, 2015–2016), only 2.6% of children under five in India were classified as overweight.[23] A more recent trend analysis using NFHS-5 data reported a modest increase to approximately 4% nationally, yet this remains far below the prevalence observed in our study.[24] These indicate that rural Bangalore may be experiencing a more pronounced double burden of malnutrition than many other regions in India, reinforcing the need for context-specific interventions that address both undernutrition and the emerging challenge of overweight.
A significant association was found between low birth weight and wasting (χ2 = 7.408, P = 0.025), affirming earlier findings from Meshram et al. (2019)[19] and NFHS-5,[25] both of which identified low birth weight as a strong predictor of acute malnutrition. This highlights the importance of improving maternal nutrition and antenatal care.
Weight-for-age was significantly associated with the child’s age (χ2 = 21.586, P = 0.042), with underweight more prevalent in the 6–12-month group. As age increased, normal and overweight proportions rose. Similar patterns were seen in Kapoor and Kumar (2018)[20] and NFHS-5,[25] which emphasise the need for timely complementary feeding during infancy.
Stunting was also significantly related to age group (χ2 = 21.124, P = 0.007) and socioeconomic status (χ2 = 19.699, P = 0.003), with higher rates amongst younger children and those from lower socioeconomic classes. This supports evidence from Bhagwat and Meshram et al. (2019) and Unisa (2016),[19,21] highlighting poverty, food insecurity and poor feeding as major contributors. While gender showed borderline significance (P = 0.054), males had slightly higher stunting rates – consistent with CNNS (2016–2018),[7] which suggested boys may be more vulnerable to growth faltering.
These findings collectively underline the need for age-specific, gender-sensitive and equity-focused nutrition interventions, especially in early childhood and amongst economically disadvantaged groups.
Summary
India continues to experience high levels of child malnutrition – specifically stunting, wasting and underweight – amongst children under five, despite sustained economic growth and the implementation of national nutrition programmes such as ICDS, Poshan Abhiyaan and NFHS-5. Rural areas are disproportionately affected, often showing poorer nutritional outcomes than urban regions due to limited access to services, food insecurity and weaker health infrastructure. Established risk factors for under-nutrition include low birth weight, early childhood (especially between 6 and 24 months), low socioeconomic status and limited maternal education. In addition, national and multi-state data sets often fail to capture village-level disparities, leaving many rural communities under-represented in policy and programme design.
This study addresses that evidence gap by offering a focused assessment of child malnutrition in five villages, using WHO-standard measurements. It highlights a dual burden of malnutrition – significant levels of under-nutrition (stunting at 31.9% and wasting at 21.9%) alongside a growing trend of overweight (11%) – indicating a shift in rural nutrition patterns. Statistically significant associations were observed between low birth weight and wasting, child age and both under-weight and stunting (with children aged 6–12 months being most at risk) and socioeconomic status and stunting, with higher prevalence amongst lower-income families. These findings provide concrete, localised evidence to guide the design of community-based interventions such as targeted nutrition counselling, early growth monitoring and support systems aimed at accelerating progress towards SDG 2 (Zero Hunger) in comparable rural contexts.
Recommendation
The results of this study recommend:
Continuously monitor the nutritional status of children in the study area and conduct further research to understand the dietary diversities of children under five years of age.
Develop and implement community-based nutrition education programmes targeting parents and caregivers, emphasising the importance of a balanced diet, breastfeeding practices, and hygiene.
Strengthen the healthcare infrastructure, to provide timely and comprehensive healthcare services for children, including growth monitoring, vaccination and treatment for malnutrition-related illnesses.
SDGs: Align efforts with SDG-2 (Zero Hunger) and work towards achieving the goal of eliminating hunger and malnutrition amongst children by 2030.
CONCLUSION
The research unveiled that the prevalence of undernutrition amongst children under-five years of age was quite high and also shows disparities in nutritional status amongst different socioeconomic groups, age and gender. This information can serve as a compass, guiding targeted interventions and allocation of resources towards the vulnerable population and reducing health inequalities. Ultimately, it helps in achieving SDG-2, which focuses on zero hunger by 2030.
Acknowledgement:
The authors would like to thank the medical officer for granting permission and health workers and students for their kind cooperation in data collection and assessment of children.
Ethical approval:
The research/study was approved by the Institutional Review Board at University Ethics Committee for Human Trials, Ramaiah University of Applied Sciences, number EC-23/34-RINER, dated 30th August 2023.
Declaration of patient consent:
The authors certify that they have obtained all appropriate patient consent.
Conflicts of interest:
There are no conflicts of interest.
Use of artificial intelligence (AI)-assisted technology for manuscript preparation:
The authors confirm that they have used artificial intelligence (AI)-assisted technology for assisting in the writing or editing of the manuscript or image creations.
Financial support and sponsorship: Nil.
References
- Improving child nutrition: The achievable imperative for global progress New York: UNICEF; 2013.
- [Google Scholar]
- Developmental potential in the first 5 years for children in developing countries. Lancet. 2007;369:60-70.
- [CrossRef] [Google Scholar]
- Strategies to avoid the loss of developmental potential in more than 200 million children in the developing world. Lancet. 2007;369:229-42.
- [CrossRef] [PubMed] [Google Scholar]
- Maternal and child undernutrition and overweight in low-income and middle-income countries. Lancet. 2013;382:427-51.
- [CrossRef] [PubMed] [Google Scholar]
- Levels and trends in child malnutrition: Key findings of the 2021 edition of the joint child malnutrition estimates Geneva: WHO; 2021.
- [Google Scholar]
- Impact of dietary diversity on nutritional status of children between 3-5 years of age in selected pre-schools, Bangalore. J Neonatal Surg. 2025;14:231-43.
- [CrossRef] [Google Scholar]
- Transforming our world: The 2030 agenda for sustainable development New York: United Nations; 2015.
- [Google Scholar]
- Evaluation report on integrated child development services (ICDS) New Delhi: Development Monitoring and Evaluation Office, NITI Aayog; 2015.
- [Google Scholar]
- Nutritional status assessment of 6-59 months age children in rural Yadgir, Karnataka state, India. Int J Community Med Public Health. 2024;11:1585-92.
- [CrossRef] [Google Scholar]
- A study to assess undernutrition and its sociodemographic correlates in under-five children in urban and rural areas of Rishikesh, Uttarakhand. J Family Med Primary Care. 2020;9:4980-84.
- [CrossRef] [PubMed] [Google Scholar]
- Inequalities in nutritional status among under five children in Haryana state, India: Role of social determinants. Indian J Community Health. 2017;29:81-8.
- [CrossRef] [Google Scholar]
- Impact of supplementation with milk-cereal mix during 6-12 months of age on growth at 12 months: A 3-arm randomized controlled trial in Delhi, India. Am J Clin Nutr. 2022;115:83-93.
- [CrossRef] [PubMed] [Google Scholar]
- Nutritional status and its correlates in under-five children of labour population in urban slums of Lucknow, Uttar Pradesh, India. Indian J Child Health 2017
- [CrossRef] [Google Scholar]
- A study on association of sociodemographic factors with nutritional status of under-five age group in rural area of Barabanki district. J Med Public Health. 2023;4:1077.
- [Google Scholar]
- Nutritional status of under-five children in Maharashtra. Indian J Nutr. 2019;6:180.
- [Google Scholar]
- Sociodemographic correlates of malnutrition among children in Uttar Pradesh. Indian J Matern Child Health. 2018;20:1-8.
- [Google Scholar]
- Malnutrition among children in India: A regional analysis using NFHS-4 data. Clin Epidemiol Global Health. 2016;4:145-52.
- [Google Scholar]
- A cross-sectional study to assess acute malnutrition among under-5 children in the field practice area of a teaching hospital in Chennai. J Family Med Primary Care. 2021;10:218-22.
- [CrossRef] [PubMed] [Google Scholar]
- Prevalence of overweight and obesity among under-five children in India and its associated demographic and health factors. Nutrients. 2022;14:3621.
- [CrossRef] [PubMed] [Google Scholar]
- Epidemiology of overweight in under-five children in India: Insights from the National family health survey. Br J Nutr. 2024;126:742-52.
- [Google Scholar]
- National Family Health Survey (NFHS-5) 2023. Phase II Report. New Delhi, India: Ministry of Health and Family Welfare; Available from: https://main.mohfw.gov.in/sites/default/files/NFHS-5_Phase-II_0.pdf
- [Google Scholar]

