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Original Article
ARTICLE IN PRESS
doi:
10.25259/JHASNU_94_2025

Gender Difference in Nutritional Status of Children Under Five: A Cross-Sectional Study

Department of Community Health Nursing, Yenapoya Nursing College, Deralakatte, Mangaluru, Karnataka, India
Department of Community Medicine, Yenepoya Medical College, Deralakatte, Mangaluru, Karnataka, India
Department of Child Health Nursing, Yenepoya Nursing College, Deralakatte, Mangaluru, Karnataka, India
Department of Statistics, Yenapoya (Deemed to be University), Deralakatte, Mangaluru, Karnataka, India

* Corresponding author: Dr. Abhay Nirgude, Department of Community Medicine, Yenepoya Medical College, Yenepoya (Deemed to be University), Deralakatte, Mangaluru, Karnataka, India. abhaynirgude@gmail.com

Licence
This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-Share Alike 4.0 License, which allows others to remix, transform, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.

How to cite this article: Naik S, Nirgude A, Arahna PR, Banu S. Gender Difference in Nutritional Status of Children Under Five: A Cross-Sectional Study. J Health Allied Sci NU. doi: 10.25259/JHASNU_94_2025

Abstract

Objectives

The study aimed to assess the nutritional status of children aged <5 years, to find the gender differences in the nutritional status of the children, and to find the association between bio-socio-demographic factors, gender differences, and nutritional status (wasting, stunting, and underweight) in rural Dakshina Kannada, Karnataka.

Material and Methods

A cross-sectional study was conducted among 400 children (200 boys, 200 girls). Nutritional status was assessed using anthropometric measurements based on WHO standards. Statistical analyses included t-tests and Chi-square tests.

Results

Wasting, stunting, and low weight (underweight) were observed in 65.5%, 61%, and 66.5% of boys, and 58.5%, 62%, and 60.5% of girls, respectively. No significant gender differences were found in mean anthropometric indices (p > 0.05). Age was significantly associated with all forms of undernutrition in both genders. Birth order and socio-economic status (SES) were associated with wasting in boys, while parental gender influenced stunting in girls. Deworming was linked to low weight (underweight) in boys.

Conclusion

Study found no significant gender differences in undernutrition among children aged <5 years in rural Dakshina Kannada.

Keywords

Gender differences
Malnutrition
Under-five children
Undernutrition
Wasting

INTRODUCTION

Malnutrition in children under five remains a significant global public health concern, particularly in low and middle-income countries. It is an important contributor to child morbidity, mortality, impaired physical growth, and delayed cognitive development.[1] The first 5 years of life are critical for growth and development, and malnutrition during this period can have long-lasting effects on overall health and well-being. Nutritional disparities often exist between genders, with them experiencing different health outcomes due to a variety of socio-economic, cultural, and environmental factors.[2] In rural areas of India, where access to healthcare and nutrition may be limited, understanding the gender differences in nutritional status becomes crucial for developing targeted interventions.[3] Despite India’s economic progress and numerous nutritional programs, malnutrition remains a significant challenge. According to the National Family Health Survey (NFHS-V, 2019-21), 35.5% of children in India were stunted, 19.3% were wasted, and 32.1% were underweight.[4] These alarming figures reflect the persistent burden and magnitude of childhood malnutrition in the country.

Gender-based disparities in nutritional status have also been well-documented. Socio-cultural practices in many parts of India often lead to preferential treatment of boys, particularly in food allocation, healthcare access, and caregiving, potentially placing girls at a nutritional disadvantage.[5] While national-level data have highlighted these differences, regional disparities are often underexplored, especially in rural areas. In particular, gender biases in food distribution, poor healthcare access, and parental care often favouring boys over girls, lead to poorer nutritional outcomes for girls.[6] Dakshina Kannada, a coastal district in the southern state of Karnataka, is known for having relatively better health indicators than other districts. However, rural pockets within the district continue to face challenges such as limited access to quality healthcare, poor sanitation, and low maternal education, all of which contribute to poor nutritional outcomes among children.[7] Despite the district’s relative advantages, there is a lack of focused research on rural disparities, especially regarding gender differences in nutritional status among children. Previous studies have explored malnutrition and its determinants in various regions, but few have specifically examined gender disarities in nutritional outcomes within the rural settings of Dakshina Kannada. Understanding these differences is crucial to ensuring equitable and effective interventions. Moreover, identifying if and how gender influences nutritional outcomes can guide policymakers and healthcare providers to design strategies that address nutritional deficiencies and underlying gender biases.[8-10] This study aims to fill this gap by assessing the nutritional status of children aged <5 years in rural Dakshina Kannada, specifically focusing on gender disparities. By highlighting localised evidence from this region, the study contributes novel insights into the intersection of gender and child nutrition in rural Karnataka, which remains underexplored in current literature.

MATERIAL AND METHODS

Study design and approach

A community-based cross-sectional study was conducted to assess the nutritional status of children, focusing on gender differences in rural areas of Dakshina Kannada district, Karnataka. The study employed a quantitative, observational approach to evaluate anthropometric indicators of malnutrition, including stunting, wasting, and low weight (underweight). The study was conducted in selected rural villages of Dakshina Kannada, a coastal district in Karnataka, in rural areas. According to the Census 2011, the district’s total population is ∼20,83,625, of which the rural population accounts for ∼8,05,650. Based on district-level health data, the estimated population of children is ∼48,000. All data were collected by the principal investigator through home visits, using standardised anthropometric measurement procedures.

The study population consisted of children aged 1-5 years who had been residing in rural areas of Dakshina Kannada for a minimum duration of 6 months. Only those children whose parents provided written informed consent were included in the study. Children with known chronic illnesses, congenital disorders, or conditions requiring therapeutic nutritional intervention were excluded. Additionally, acutely ill children at the time of data collection were excluded. Purposive sampling was employed to select participants who were most relevant to the research objectives. The sample size was calculated using G*Power software, based on a 15% clinical difference in the prevalence of wasting between boys and girls, with a power of 90% and a significance level (α) of 0.05 [Figure 1]. According to data referenced from Jawaregowda and Angadi,[11] the prevalence of wasting was estimated at 36% for boys (P1 = 0.36) and 21% for girls (P2 = 0.21). The standard normal deviate for a 95% confidence interval (Zα/2) was 1.96, and for 90% power (Zβ), it was 1.28. Based on these inputs, the minimum required sample size was calculated to be 200 children per group, leading to a total sample size of 400 children.

Participant flow diagram (CONSORT adapted for cross-sectional study with purposive sampling). CONSORT: Consolidated Standards of Reporting Trials.
Figure 1:
Participant flow diagram (CONSORT adapted for cross-sectional study with purposive sampling). CONSORT: Consolidated Standards of Reporting Trials.

Data collection tools and procedures

Data were collected through home visits using a pre-tested, structured bio-socio-demographic proforma administered to parents. The information collected included the child’s age, gender, birth order, immunisation status, and deworming status. Parental data, such as gender and socio-economic status (SES) of the family, were also obtained. SES was assessed using the rural version of Uday Pareek’s scale,[12] a validated tool designed for rural Indian populations. This scale evaluates nine domains: caste, occupation, education, social participation, landholding, housing, material possessions, farm power, and family type, with scores assigned to each component and summed to classify SES ranging from low to high. Anthropometric measurements were taken using standardised and calibrated equipment. Height was measured using a portable stadiometer (Seca 213), which was calibrated before data collection at the Department of Community Medicine, Yenepoya University. Height was measured barefoot, standing upright with feet together, heels touching the stadiometer, and head positioned in the Frankfort horizontal plane, and was recorded to the nearest 0.1 cm. Weight was measured using a digital weighing scale (Omron HN-289), calibrated daily with standard 5 kg and 10 kg weights, wearing light clothing and no shoes, and was recorded to the nearest 0.5 kg. For infants or children unable to stand, length and weight were measured using a calibrated infant meter and baby weighing scale, respectively, following standard WHO protocols.

Nutritional status was assessed using anthropometric indices based on the WHO Child Growth Standards (2006). Z-scores were calculated using WHO Anthro software (version 3.2.2).[13] Undernutrition was evaluated using three key indicators: weight-for-height (wasting), weight-for-age (underweight), and height-for-age (stunting). A child was classified as wasted if their weight-for-height Z-score was <-2 standard deviations (SD) from the median. Underweight status was defined as a weight-for-age Z-score <-2 SD, and stunting was determined by a height-for-age Z-score <-2 SD. Z-scores were further categorised to indicate severity; between -1 SD and +1 SD was considered normal, between -1 SD and -2 SD indicated mild undernutrition or at-risk status, between -2 SD and -3 SD indicated moderate undernutrition, and <-3 SD indicated severe undernutrition.

Data analysis

Data were entered and analysed using IBM SPSS Statistics version 24. Descriptive statistics (mean, standard deviation, and proportions) were used to summarise demographic characteristics and nutritional indicators. A Chi-square test was used to compare categorical variables between genders, and independent t-tests were applied to measure continuous variables. The WHO Anthro software was used to generate Z-scores for each anthropometric parameter.[14]

Ethical considerations

The study was approved by the Yenepoya Ethics Committee (Ref: YEC-1/2022/266). Written informed consent was obtained from the parents or guardians of all participating children. Confidentiality was maintained, and participants were assured that they could withdraw at any point without any negative consequences.

RESULTS

A significant proportion of children, 48% of boys and 43.5% of girls, were 1-2 years old. More than one-third of the children were firstborn, with 38% boys and 36.5% girls. All 100% of the children in the study received full immunisation. Parental participation was ∼66.5% of mothers and ∼33.5% of fathers of children in the study [Table 1].

Table 1: Distribution of demographic characteristics of children under five (n = 400)
Sr. no. Demographic characteristics Categories Gender

Girls (n = 200)

f (%)

Boys (n = 200)

f (%)

1 Age in years 1-2 87 (43.5) 96(48)
2-3 68 (34) 68 (34)
3-4 45 (22.5) 36 (18)
2 Birth order 1 76 (38) 73 (36.50)
2 40 (20) 45 (22.50)
3 39 (19.5) 40 (20)
4 45 (22.5) 42 (21)
3 Immunization Fully immunized 200 (100) 200 (100)
4 Deworming Twice a year 145 (72.50) 144 (72)
Once in year 55 (27.50) 56 (28)
5 Parental gender Father 67 (33.50) 69 (34)
Mother 133 (66.50) 131 (66)

n represents number of participants. The data is expressed as frequency (n) and percentage in parentheses.

Table 2 (Uday Pareek’s SES Scale) revealed that the studied population is predominantly lower middle class. There is limited upward mobility, with negligible representation in higher SES categories. Interventions aimed at improving education, land access, occupation diversification, and social engagement may be valuable to enhance SES.

Table 2: Distribution of demographic characteristics of parents of children under five (n = 400)
Socioeconomic status of the parents Weighted scores Parents of boys (n = 200) (%) Parents of girls (n = 200) (%)
Caste
Scheduled caste 1 30 (15.0) 34 (17.0)
Lower caste 2 116 (58.0) 124 (62.0)
Agriculture caste 4 31(15.5) 22 (11.0)
Prestige caste 5 15 (7.5 ) 13 (6.5)
Dominant caste 6 8 (4.0) 7 (3.5)
Occupation
None 0 82 (41.0) 81 (40.5)
Labourer 1 31 (15.5) 38 (19.0)
Cast occupation 2 20 (10.0) 14 (7.0)
Business 3 30 (15.0) 24 (12.0)
Independent profession 4 13 (6.5) 9 (4.5)
Cultivation 5 22 (11.0) 28 (14.0 )
Service 6 2 (1.0) 6 (3.0)
Education
Can read and write 2 1 (0.5) 2 (1.0)
Primary 3 72 (36.0) 77 (38.5)
Middle 4 40 (20.0) 25 (12.5)
High school 5 66 (33.0) 60 (30.0)
Graduate and above 6 21 (10.5) 36 (18.0)
Land
No land 0 27 (13.5) 24 (12.0)
<1 acre 1 141 (70.5) 146 (73.0)
1-5 acres 2 31 (15.5)
5-10 acres 3 1 (0.5) 1 (0.5)
Social participation
None 0 171 (85.5) 176 (88.0)
Member of one organization
1 29 (14.5) 24 (12.0)
No. of family member
Up to 5 1 123 (61.5) 119 (59.5)
>5 2 77 (38.5) 81 (40.5)
House
No house 1 11 (5.5) 12 (6.0)
Kutch house 2 68 (34.0) 73 (36.5)
Mixed house 3 86 (43.0) 65 (32.5)
Pucca house 4 29 (14.5) 45 (22.5)
Mansion 6 6 (3.0) 5 (2.5)
Form power
No drought animal 1 62 (31.0) 91 (45.5)
1-2 drought animals 2 29 (14.5 ) 33 (16.5 )
3-4 drought animals 3 62 (31.0) 48 (24.0)
5-6 drought animals 4 47 (23.5) 28 (23.5)
Material possession
Chairs, cycle, radio 1 200 (100.0) 200 (100.0 )
SES (Total)
Middle class 30-49 3 17 (8.5 ) 13 (6.5 )
Lower middle Class 15-29 4 159 (79.5) 158 (79.0) 
Lower class <15 5 24 (12.0 ) 29 (14.5)

n represents number of participants. The data is expressed as frequency (n) and percentage in parentheses. SES: Socioeconomic status

Table 3 illustrates the distribution of wasted, stunted, and underweight children based on gender. More than half (65.5%) of the boys were wasted (acute malnutrition) compared to the girls (58.5%). Suggests a higher prevalence of acute malnutrition among boys than girls. More than half (62%) of the girls were stunted (chronic malnutrition), slightly more than (61%) the boys. The rates are nearly comparable, indicating that chronic undernutrition affects both genders similarly. More than half (66.5%) of the boys were underweight (combined indicator), compared to (60.5%) the girls. Shows that boys were more likely to be undernourished, reflecting both acute and chronic nutritional deficiencies.

Table 3: Distribution of undernutrition (wasting, stunting, and underweight) among children under five based on gender (n = 400)
Gender Classification of undernutrition f (%)
Girls Wasted 117 (58.5)
Normal 83 (41.5)
Stunted 124 (62)
Normal 76 (38)
Underweight 121 (60.5)
Normal 79 (39.5)
Boys Wasted 131 (65.5)
Normal 69 (34.5)
Stunted 122 (61)
Normal 78 (39)
Underweight 133 (66.5)
Normal 67 (33.5)

n represents number of participants. f: Frequency %: Percentage, Wasting: Low weight for height, Stunting: Low height for age, Underweight: Low weight for age.

Figure 2 showed that mild wasting and mild underweight were more common among boys (48.5 and 58.5%, respectively) than among girls (39 and 50%, respectively). Mild stunting was more prevalent among girls (42%) than boys (33%). The proportion of moderate stunting and severe stunting was higher among boys (16 and 12%, respectively) than among girls (12 and 8%, respectively). Slightly more girls were moderately and severely underweight than boys, but the differences were minor. More girls fell in the normal category across all three indicators (wasting, stunting, and underweight) than the boys.

Level of malnutrition. Data presented frequency and percentage, Wasting (Low weight for height), Stunting (Low Height for age), and underweight (Low weight for age).
Figure 2:
Level of malnutrition. Data presented frequency and percentage, Wasting (Low weight for height), Stunting (Low Height for age), and underweight (Low weight for age).

Figure 3 showed that the mean values for weight, height, and Z-scores (WHZ, HAZ, and WAZ) were comparable between boys and girls. The p-values for all the indicators were greater than the 0.05 level of significance, indicating that the differences between genders are not statistically significant. Despite some numerical differences, the variation is not significant enough to conclude any gender-based nutritional disparity between boys and girls based on mean scores.

Gender-wise comparison of undernutrition. WHZ: Wasting (Weight for height), HAZ: Stunting (Height for weight), WAZ: Underweight (Low weight for age).
Figure 3:
Gender-wise comparison of undernutrition. WHZ: Wasting (Weight for height), HAZ: Stunting (Height for weight), WAZ: Underweight (Low weight for age).

Table 4 shows that the child’s age showed a significant association with wasting among both girls (p = 0.002) and boys (p = 0.001). Suggests that undernutrition risk varies significantly across age groups. Birth order was significantly associated with wasting among boys only (p = 0.005). Socioeconomic status (SES) was significantly associated with wasting in boys (p = 0.021).

Table 4: Association between bio-socio-demographic factors, gender differences with undernutrition (wasting) using Chi-square and likelihood ratio analysis (n = 200+200 = 400)
Bio-socio demographic factors Girls
Boys
Undernutrition (Wasting) n(%) χ2 Value p value Undernutrition (Wasting) n(%) χ2 Value p value
Age in years 117 (58.5) 21.414 0.002** 131(65.5) 0.22621 0.001**
Birth order 11.206 0.262 23.78 0.005**
Deworming 2.429 0.488 1.95 0.583
Parental gender 1.907 0.592 3.318 0.768
SES_GRADE 4.527 0.606 14.941 0.021*

Test = Chi-square, Level of significance: *p <0.05 significant, **p <0.001 very highly significant. SES_GRADE: Socio-economic scores grading.

Table 5 Defects that age of the child had a highly significant association with stunting in both boys and girls (p < 0.001), suggesting that stunting risk increases with age. Parental gender was significantly associated with stunting in girls only (p = 0.042).

Table 5: Association between bio-socio-demographic factors, gender differences with undernutrition (Stunting) using Chi-square and likelihood ratio analysis. (n = 200 + 200 = 400)
Bio-socio demographic factors Girls
Boys
Undernutrition (Stunting) n(%) χ2 Value p value Undernutrition (Stunting) n(%) χ2 Value p value
Age in years 124 (62) 36.075 <0.001* 122 (61) 29.59 <0.001*
Birth order 4.942 0.839 6.406 0.699
Deworming 0.34 0.952 4.763 0.19
Parental gender 8.223 0.042 6.198 0.401
SES_GRADE 6.769 0.343 10.068 0.122

Test = chi-square, Level of significance: *p < 0.001 very highly significant, SES_GRADE: Socio-economic scores grading.

Table 6 shows that age of the child was significantly associated with underweight in both girls (p = 0.050) and boys (p = 0.037), though the association in girls was borderline. Indicates that age is a relevant factor influencing underweight status, likely due to transitions in feeding patterns. Deworming status was only significantly associated with underweight in boys (p = 0.010).

Table 6: Association between bio-socio-demographic factors, gender differences with undernutrition (Underweight) using Chi-square and likelihood ratio analysis (n = 200 + 200 = 400)
Bio-socio demographic factors Girls
Boys
Undernutrition (Underweight) n(%) χ2 Value p value

Undernutrition

(Underweight)

n(%)

χ2 Value p value
Age in years 121 (60.5) 12.395 0.05* 133 (66.5) 13.416 0.037*
Birth order 3.449 0.944 5.393 0.799
Deworming 3.562 0.313 11.329 0.01
Parental gender 0.604 0.896 2.99 0.81
SES_GRADE 5.294 0.507 9 0.174

Test = chi-square, Level of significance: *p<0.05 significant. Parental gender refers to the gender of the parent primarily involved in the child’s daily care, as reported during the interview (boys = father, girls = mother). SES_GRADE: Socio-economic scores grading.

DISCUSSION

This cross-sectional study investigated gender differences in the nutritional status of wasting, stunting, and underweight among children under five in rural Dakshina Kannada, Karnataka. Although undernutrition was prevalent among both boys and girls, the observed gender differences were not statistically significant. These findings suggest that gender alone may not be a primary determinant of undernutrition in this rural population. However, a closer examination of other variables reveals critical insights into the nutritional outcomes of these children.

Age was significantly associated with all three forms of undernutrition: wasting, stunting, and underweight. Nutritional vulnerability appeared to increase as children transitioned from exclusive breastfeeding to complementary feeding. This is consistent with earlier studies,[15,16] which report a decline in nutritional status during this period, potentially due to the introduction of nutritionally inadequate complementary foods and increased exposure to infections.[17] These findings underscore the importance of ensuring age-appropriate feeding practices and hygienic conditions, particularly in the 6-24-month age group.[18]

Birth order showed a significant association with wasting among boys. This may reflect a resource dilution effect; wherein higher birth order children receive less attention or fewer nutritional resources. However, as over one-third of the children in our study were firstborns, this could have diluted any overarching birth order effects across genders. While some previous studies[19,20] have identified stronger links between birth order and undernutrition, our findings suggest that birth order may interact with gender in complex ways, warranting further exploration into intra-household food distribution and caregiving dynamics.

Socioeconomic status (SES), as classified by Pareek’s scale, was significantly associated with wasting in boys. Poor SES is typically linked with food insecurity, inadequate access to healthcare, and lower maternal education, which are factors known to compromise child nutrition.[21] The gendered association observed here may reflect either gender-neutral caregiving practices in low-resource settings or possibly a reverse gender bias, where boys are not preferentially advantaged in nutrition and care.[22] This observation calls for a nuanced understanding of how SES interacts with gender in shaping child nutrition.

Parental gender, particularly maternal participation, was more common among caregivers and was significantly associated with stunting in girls.[23] This may indicate that maternal caregiving has a greater positive influence on a girl’s nutrition, possibly due to closer mother-daughter interactions or better attention to health and feeding needs.[23,24] These findings highlight the need to strengthen maternal education and engagement in child health programs, while also encouraging greater paternal involvement.[24]

Although 72.5% of children had been dewormed, deworming status remained significantly associated with underweight in boys.[25] This could be due to suboptimal timing or irregularity of deworming, or a greater susceptibility of boys to parasitic infections and resultant nutrient loss.[26] This finding emphasizes the need for regular deworming schedules and improved monitoring, particularly for vulnerable groups.[27,28]

While boys exhibited slightly higher rates of wasting and underweight, and girls had marginally higher stunting, these differences were not statistically significant. National surveys like NFHS-5[29] and regional studies have similarly reported inconsistent gender disparities in child nutrition. Although some research[30-33] highlights persistent cultural biases against girls, the lack of strong gender differences in our study may reflect improving awareness and targeted government interventions aimed at promoting gender equality in health and nutrition.

Our findings align with broader evidence from India and South Asia,[34-36] where undernutrition remains high, especially in rural settings. Similar associations between nutritional status and variables such as age, SES, and parental characteristics have also been observed in other low- and middle-income countries.[37-39]

CONCLUSION

The study found no statistically significant gender differences in undernutrition among children under five in rural Dakshina Kannada. However, variables such as age, birth order, SES, parental gender, and deworming status showed significant associations with specific nutritional outcomes. These findings suggest that multifactorial influences, rather than gender alone, determine child nutrition in this context. Future programs should adopt a holistic approach by addressing socioeconomic, familial, and behavioural factors to improve nutritional outcomes for all children.

Acknowledgement

We are thankful to all the participants of the study.

Ethical approval

The research/study approved by the Yenepoya Ethics Committee, at Yenepoya (Deemed to be University), number YEC-1/2022/266, dated 31st March 2024.

Declaration of patient consent

The authors certify that they have obtained all appropriate consent forms from the participants’ parents/guardians. In the form, they have given their consent for the participants’ clinical information to be reported in the journal. They understand that the names and initials will not be published and due efforts will be made to conceal the participants’ identity, but anonymity cannot be guaranteed.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

Use of artificial intelligence (AI)-assisted technology for manuscript preparation

The authors confirm that there was no use of artificial intelligence (AI)-assisted technology for assisting in the writing or editing of the manuscript and no images were manipulated using AI.

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