Assessing the Impact of Socioeconomic and Environmental Factors on the Body Mass Index of Children Aged 3–6 Years: A Cross-Sectional Study in Assam, India

Abstract

Background:

In Assam, India, 33% of children under the age of five are underweight, according to the National Family Health Survey-5 statistics. The Assam Agribusiness and Rural Transformation Project also discovered that 68% of Assam’s children between the ages of 6 and 59 months are anemic. The goal of this study was to determine how socioeconomic and environmental factors affected the body mass index (BMI) of children in Assam, India, between the ages of 3 and 6 years old.

Material and Methods:

385 kids had their anthropometric measurements taken. With a 5% margin of error and a 95% confidence interval, this sample size was calculated. To find statistically significant features, the collected data were analyzed using univariate Chi-square tests and multivariate regression analysis.

Results:

Gender, parental employment status, lifestyle, and socio-economic conditions had statistically significant associations with different factors affecting children’s BMI. In our study, no relationship was observed between BMI and the population density of the child living premises.

Conclusion:

This study emphasizes the importance of gender, lifestyle, and socioeconomic status as major determinants of nutritional health among children in Assam. Such findings highlight the need for more targeted interventions that may help reduce such influence, hence improving child health in the region. The fact that living area density does not correlate with BMI suggests that future policy efforts may be made more useful when focusing on the quality of the socio-economic environment rather than on features of the physical location of living areas.

INTRODUCTION

India, with its unique and dynamic culture, is dealing with a widespread and serious problem: malnutrition, particularly among youngsters. Addressing the specific focus on the age group of 3 to 6 years, this period is identified as a critical window for a child’s growth and development. Neuroscientific research highlights the rapid brain development during these early years, making adequate nutrition, stable socioeconomic conditions, and healthy environments essential for fostering proper cognitive functions and physical growth. The age group of 3 to 6 years is particularly vulnerable due to their high nutritional requirements for growth and development. According to the World Health Organization (WHO), India tops the world in malnutrition rates, an alarming number that highlights the scale of the problem.[1]

India struggles with severe child malnutrition despite economic growth and anti-malnutrition efforts. Economic inequality is a primary factor, with lower economic development correlating with higher malnutrition rates. Open defecation worsens this inequality. Additionally, maternal height, education, and access to safe drinking water also contribute to malnutrition disparities.[2]

In the years 2019 to 2021, every northeastern state of India documented stunted child rates of 22% or higher. Additionally, no less than 9% and 12% of children in the region were reported as wasted and underweight, respectively.[3] The situation is even more concerning in regions such as Assam, where the prevalence number of stunting, wasting, and severely wasting of children under 5 years are 1,114,338, 669695, and 275,229, respectively, according to Niti Aayog Poshan report.[4]

This discrepancy is exacerbated in rural and urban slums, where undernutrition is considerably more widespread because of extra socioeconomic constraints.[5] The causes of this problem go beyond insufficient food consumption and into healthcare, clean water availability, and sanitation. Under-five child malnutrition has a significant impact on community, cultural, social, and economic food behaviors.[6]

Malnutrition is a result of several factors, including inadequate food consumption, a lack of healthcare, and insufficient access to clean water and sanitary facilities. Undernourished children have a higher risk of getting sick or dying, as well as having slower physical and mental development.[7]

There is still a significant worldwide malnutrition burden notwithstanding social and economic advancements. This demonstrates the vital link that exists between economic prosperity, human capital, and nutrition. Malnutrition lowers one’s physical and mental capacities, which increases one’s vulnerability to poverty and lowers productivity. Poverty and malnutrition are cyclically related, with one making the other worse.[8] Promoting child development and breaking the cycle of disease and malnutrition are key components of India’s approach to solving the issue of meeting the requirements of its children. One of India’s flagship early childhood care and development programs is the Integrated Child Development Services (ICDS) Scheme, which provides essential services to children under six.[9]

The ICDS is managed by the Indian government and provides Supplementary Nutrition to children under the age of six, as well as expecting and nursing mothers. The ICDS Scheme is implemented through Anganwadi Centers, which provide children and pregnant or nursing mothers with additional nourishment, health checkups, immunizations, preschool instruction, and referral services.[10] This is accomplished with the assistance of Anganwadi Workers and Anganwadi Helpers.[11] Community Health Workers (CHWs) performance and the influence of their work on family roles and relationships are pivotal in this context. The study discovered that gender norms and expectations hampered the autonomy and agency of CHWs. The findings suggest that interventions addressing the underlying social and cultural drivers of CHW performance are required.[12]

Several studies have found differences in maternal and newborn care based on socio-demographic factors such as economic level, caste, gender, and so on. Identifying social determinants like economic status, caste, education, gender, religion, and culture affecting maternal health. The most significant structural determinants influencing the use of maternal health services and maternal mortality in India were economic position, caste/ethnicity, education, gender, religion, and culture.[13,14,15] In Assam, India, 33% of children under the age of five are underweight, according to the National Family Health Survey (NFHS-5) statistics.[16] The Assam Agribusiness and Rural Transformation Project also discovered that 68% of Assam’s children between the ages of 6 and 59 months are anemic.[17]

Indian children suffering from severe acute malnutrition (SAM) under the ICDS, there is no proof that ICDS works better for SAM patients than it does for non-SAM patients. Children with SAM receive the same amount of ICDS services, if not less, than children without SAM. Services for children with special needs could be improved by increasing the coverage of ICDS among expectant and nursing moms.[18] From 2019 to 2021, there were reports of at least 22% of children being stunted, while in the northeastern regions of India, at least 9% and 12% of children were underweight and wasted, respectively.[3] According to a different study, the rates of stunting, wasting, and underweight among children in the Dibrugarh area were 39.8%, 26.1%, and 39.2%, respectively.[19] The study’s goal was to assess the nutritional health of children aged 3–6 who were enrolled in Anganwadi programs in rural Assam, India, in 2022. Gender, Employment Status, House Type, and Social Class all have a statistical link with current body mass index (BMI), but the density of living space does not.

Considering these considerations, the study aims to explore the complex interplay between socioeconomic status, environmental conditions, and nutritional health among children aged 3 to 6. This approach aligns with the broader objective to not only mitigate the immediate effects of malnutrition but also to contribute to a holistic understanding of how socioeconomic and environmental factors impact child development. This multifaceted perspective is crucial for devising effective interventions that address the root causes of undernutrition and foster a conducive environment for the well-being of children.

Despite the existence of programs like the ICDS Scheme, which aims to provide holistic early childhood care and development, malnutrition remains a significant challenge in India. The persistence of malnutrition, influenced by socioeconomic and environmental factors, underscores the need for integrated solutions that address the root causes of undernutrition in India.

Objective

The primary objective of this study was to analyze the nutritional health of children aged three to six in Assam, with a particular emphasis on understanding the complex factors of child nutrition in this demographic.

The study was specifically aimed to:

1. Determine Malnutrition Prevalence: Analyze anthropometric measurements to identify underweight, normal weight, and overweight children aged 3 to 6 years

2. Investigate the Impact of Socioeconomic Factors: Examine how employment status, family income, and housing quality affect children’s nutrition

3. Evaluate environmental influences. To investigate the link between children’s living situations, such as overcrowding and sanitary facilities, and their nutritional health

4. Evaluate the impact of government nutrition programs, including the ICDS Scheme, on improving child nutrition in the research area

5. Identify gaps and opportunities for intervention to improve children’s nutritional health in Assam.

SUBJECTS AND METHODS

A cross-sectional study was conducted at 35 Anganwadi Centers in Assam from June to December 2022, with a sample size of 385 children. Inclusion criteria included children aged 3 to 6 years who were accompanied by a Legally Authorized Representative for survey administration. Those attending private schools or missing more than 30 working days in a quarter were eliminated. A structured survey was used in the study to collect information on anthropometric and environmental parameters. Anthropometric data included height, weight, and birth weight, the latter, of which was collected to determine its association with the child’s current BMI. An examiner performed these measurements, while Anganwadi personnel collected the remaining data. As independent variables, the study focused on environmental elements (house type, congestion, hygiene) and socio-demographic features (family income, employment status of the family head). The dependent variable was the child’s health status, as determined by the current BMI according to the ICDS recommendations.

Study setting and selection of Anganwadi centers

This cross-sectional study was conducted across 35 Anganwadi Centers in the Dhemaji district of Assam, India, from June to December 2022. The Anganwadi Centers were selected using a stratified random sampling method to ensure a representative distribution across different socioeconomic and environmental backgrounds within the district. This selection process aimed to capture a diverse dataset reflective of the varying conditions that influence child health and nutrition.

Sample size and sampling method

The study included a sample size of 385 children, aged 3 to 6 years, attending the selected Anganwadi Centers. The sample size was determined based on a power calculation, with an expected proportion of the outcome derived from preliminary data collected in a pilot study conducted in early 2022. The pilot study suggested that approximately 30% of children in the target age group in the Dibrugarh district were at risk of malnutrition, with a 5% margin of error and a 95% confidence interval.

Inclusion and exclusion criteria

Children were eligible for inclusion if they were aged between 3 to 6 years and accompanied by a Legally Authorized Representative for survey administration. Exclusion criteria included children attending private schools or absent for more than 30 working days in a quarter, to focus on the population most likely to benefit from Anganwadi services.

Data collection methods and tools

A structured survey was utilized to gather data on anthropometric measurements (height, weight, birth weight) and environmental parameters (house type, congestion, hygiene). The current BMI was determined based on the ICDS recommendations, which classify nutritional status as underweight, healthy weight, overweight, or obese.

Anthropometric data were collected by trained examiners using standardized procedures to ensure accuracy. Environmental and socio-demographic data were collected through interviews with caregivers and observations by Anganwadi personnel.

Socioeconomic status classification

The socioeconomic status of the participants was classified using the Kuppuswamy scale, updated for the year 2022. This scale considers the education and occupation of the head of the family, along with the total family income, to categorize households into different socioeconomic classes.

Environmental assessment

The living environment of the child was characterized by measuring overcrowding, based on WHO recommendations, and evaluating the house’s structural quality. The structural quality was categorized into:

• Kutcha/low quality: Houses made of temporary materials (mud, bamboo, thatch, cow dung)

• Half Kutcha-Half Pucca/average quality: Houses constructed with a mix of temporary and permanent materials

• Pucca/good quality: Solid structures made of durable materials (bricks, concrete, stone).

This study characterized the child’s living environment by measuring overcrowding (according to WHO recommendations)[20] [Table 1] and evaluating the house’s structural quality [Table 1], which is attached as an appendix, details the classification criteria and findings related to house quality and overcrowding.

Table 1.

Recommended number of persons in the room (World Health Organization)

Number of rooms	Maximum number of persons recommended
1	Two
2	Three
3	Five
4	Seven
5	Ten
6	Twelve
7	Fourteen

RESULTS

The study encompassed 385 children, with a gender distribution of 46.23% males (n = 178) and 53.77% females (n = 207), providing a balanced representation of both genders. Anthropometric measurements revealed the following BMI categorizations among participants: 15.58% (n = 60) were underweight, 76.88% (n = 296) were within the normal BMI range, and 7.53% (n = 29) were classified as overweight. The average height observed was 107.2 cm (standard deviation [SD] = 4.5 cm) for boys and 107.98 cm (SD = 4.7 cm) for girls, indicating slight gender-based differences. The mean weight for the cohort was approximately 14 kg (SD = 2 kg), showing no significant disparity between genders.

The classification of “underweight at delivery” was based on birth weights below 2.5 kg, following WHO guidelines. Among the sampled children, 20.52% (n = 79) were identified as underweight at birth.

Socioeconomic and Environmental Conditions: Socioeconomic analysis revealed that 48.31% (n = 186) of the children belonged to households with heads employed in regular jobs, whereas 51.69% (n = 199) came from families with irregularly employed heads. Housing quality varied significantly within the sample: 2.6% (n = 10) lived in Kutcha homes (low quality), 35.58% (n = 137) in Half-Kutcha homes (average quality), and 61.82% (n = 238) in Pucca homes (high quality). Additionally, 5% of the households (n = 19) were classified as overcrowded, based on exceeding WHO’s recommended living space per individual. All the above findings are highlighted in Table 2.

Table 2.

Descriptive statistics

Variable	Categories	Count (%)	P
Age	3–4	245 (63.64%)
	5–6	140 (36.36%)
Gender	Male	178 (46%)	0.002
	Female	207 (54%)
Birth weight	Normal	306 (79.48%)	1.12
	Underweight	79 (20.51%)
Employment status	Regularly employed	185 (48.31%)	<0.001
	Not employed	199 (51.69%)
Type of house	Low quality	10 (2.6%)	0.004
	Average quality	137 (35.58%)
	Good quality	238 (61.82%)
Density of living space	Not crowding	366 (95%)	2.1
	Overcrowding	19 (5%)
Social class	Upper	75 (19.48%)	0.034
	Lower/average	310 (80.52%)
BMI	Normal	299 (77.66%)
	Overweight	28 (7.27%
	Underweight	58 (15.06%)

Level of significance: 5% (P<0.05). BMI=Body mass index

The logistic regression analysis presented in [Table 3] underscored statistically significant associations between the children’s current BMI and various independent variables. Specifically, gender (P = 0.002), employment status of the household head (P = 0.001), dwelling type (P = 0.004), and social class (P = 0.034) emerged as significant predictors of BMI categories among children. These findings suggest that socioeconomic factors, along with gender, significantly influence the nutritional status of children in the sample. Conversely, the density of living space did not exhibit a statistically significant correlation with children’s current BMI (P = 0.21), indicating that it may not directly affect their nutritional status.

Table 3.

Logistic regression

Variables	BMI			P	Odds	CI
	UW	N	OW
Age
3-4	42 (10.91%)	83 (47.53%)	22 (5.71%)	<0.01	0.9	0.42-2.36
5-6	18 (4.68%)	112 (29.1%)	8 (2.07%)
Gender
Male	36 (9.35%)	134 (34.81%)	8 (2.08%)	<0.01	0.12	<0.04-1.21
Female	24 (6.23%)	162 (42.08%)	21 (5.45%)
BW
UW	15 (3.9%)	56 (14.54%)	8 (2.08%)	0.05	0.045	0.02-1.27
Normal	44 (11.43%)	241 (62.6%)	21 (5.45%)
Social class
Lower	50 (12.99%)	9 (2.34%)	229 (59.49%)	<0.01	0.6	<0.33-1.42
Upper	68 (17.66%)	23 (5.97%)	6 (1.55%)

Level of significance: 5% (P<0.05). BW=Birthweight, UW=Underweight, N=Normal, OW=Overweight, CI=Confidence interval, BW=Birthweight, BMI=Body mass index

This analysis, employing a logistic regression model, elucidates the relationship between various independent variables (including age, gender, birth weight, socioeconomic status, dwelling type, and employment status) and the dependent variable (current BMI category of the child). The quantified insights highlight the complex interplay of socioeconomic conditions and environmental factors in determining the nutritional health of children aged 3–6 years in Assam, India.

DISCUSSION

The findings from our study conducted in Assam, assessing the nutritional health of children aged three to six, highlight several critical issues and insights into the current state of child nutrition. Among the 385 children sampled, 15.06% were found to be underweight, underscoring the pressing need for healthcare systems and relevant authorities to provide continuous support to these children and their families.

Our study’s discovery of a significant relationship between socioeconomic status, living conditions, and BMI corroborates similar research conducted in other regions. For instance, in a study by Sabde et al., improved housing conditions for under-five children in socioeconomically underprivileged families in central India were correlated with improved health benefits.[21]

However, our study extends these insights by linking overcrowded living conditions directly to nutritional deficits. The association between overcrowding (affecting 5% of homes in our study) and children’s growth problems aligns with research by Lorentzen et al. which also highlighted the negative impact of cramped living conditions on child health.[22] Unlike Lorentzen et al., our study further explores the role of inadequate plumbing and sanitary facilities, suggesting a broader scope of environmental factors affecting child nutrition.[22]

Our findings on the effectiveness of the ICDS Scheme in improving children’s nutritional status resonate with those of Singh et al., who reported positive outcomes from India.[23] Both studies acknowledge the pivotal role of Anganwadi Centers in delivering nutritional programs. However, our study uniquely points out the persistent issues of anemia and underweight children in Assam, despite these efforts, indicating a gap in addressing early marriage and maternal anemia as underlying causes, which were not the focus of Singh et al. study.[23]

The emphasis on the need for ongoing research and monitoring to understand the impact of nutritional programs and to develop new strategies for enhancing child health outcomes is a call echoed by Bhutta et al.[24] Our study adds to this discourse by highlighting specific socioeconomic and environmental factors that must be targeted in future interventions. Moreover, the observed discrepancy in service quality among Anganwadi Centers suggests a new area for improvement that future research could explore more deeply.

To bridge the gaps identified through our study and others, future research should aim to:

• Conduct longitudinal studies to assess the long-term impact of socioeconomic improvements on child nutrition

• Explore the effectiveness of specific interventions aimed at improving living conditions and sanitation on child health

• Evaluate the consistency and quality of services provided across different Anganwadi Centers and their direct impact on child nutritional status.

In conclusion, our study contributes to the growing body of evidence that underscores the multifaceted nature of malnutrition among children aged 3 to 6 in Assam. It reinforces the necessity of multifaceted interventions that not only address immediate nutritional needs but also tackle broader socioeconomic and environmental determinants of health. The continued effort and focused interventions, coupled with rigorous research and monitoring, are vital for making substantial progress in combating malnutrition and ensuring a healthier future for children in Assam and similar settings.

CONCLUSION

Our comprehensive study in Assam on the nutritional health of children aged three to six has unveiled significant insights into the multifaceted nature of malnutrition within this demographic. The identification of 15.06% of the children as underweight is a clarion call for enhanced and sustained interventions by healthcare systems and relevant authorities. Our analysis underscores the intricate interplay between socioeconomic status, living conditions, and child nutritional outcomes, echoing and extending findings from prior research. Notably, the direct link established between overcrowded living conditions and nutritional deficits broadens the discourse on environmental determinants of child health.

The effectiveness of the ICDS Scheme, as highlighted by our findings, points to the critical role of Anganwadi Centers in nutritional delivery, yet also flags the need for addressing gaps such as anemia and undernutrition, which persist despite existing efforts. This indicates underlying issues such as early marriage and maternal anemia, which demand attention.

Looking forward, our study advocates for a multifaceted approach to combat malnutrition, emphasizing the necessity of interventions that go beyond immediate nutritional aid to tackle broader socioeconomic and environmental determinants. The call for longitudinal research, focused interventions on living conditions and sanitation, and the evaluation of Anganwadi Center services outlines a roadmap for future efforts.

In sum, our research contributes vital data to the ongoing dialogue on child nutrition, reinforcing the imperative for a holistic strategy that addresses the complex web of factors influencing child health. It is our hope that this study will catalyze further research, policy development, and action, paving the way for a healthier future for children in Assam and similar contexts worldwide.

Key messages

The study sheds light on the nutritional status of children in Assam and emphasizes the necessity for ongoing efforts and focused interventions to effectively combat malnutrition. To comprehend the effects of current programs and create new ways to enhance child health outcomes in the area, ongoing study and monitoring are crucial.

Conflicts of interest

There are no conflicts of interest.

Funding Statement

Nil.