Prevalence and Drivers of Treatment Seeking Behaviour among Under-five Children Experiencing Acute Respiratory Infection in India 

Prevalence and Drivers of Treatment Seeking Behaviour among Under-five Children Experiencing Acute Respiratory Infection in India | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Prevalence and Drivers of Treatment Seeking Behaviour among Under-five Children Experiencing Acute Respiratory Infection in India Koustav Ghosh, Atreyee Sinha Chakraborty, Banashri Haloi, Sarjoo Patel This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6194991/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Acute Respiratory Infection (ARI) is one of the leading causes of under-five (U5) mortality, especially in low and middle-income and developing countries like India. Despite several health implications, it imposes a substantial economic burden on individual households. In India, the prevalence of ARI among U5 children has increased from 2016 to 2021 while simultaneously treatment-seeking behaviour (TSB) has decreased. Therefore, the present study aimed to assess the prevalence and factors associated with the TSB among U5 children experiencing ARI in India. Methodology The study used the last two rounds of the National Family Health Survey (NFHS-IV, 2016 & NFHS-V, 2021) data. The bivariate analysis with a chi-square test and multivariable logistic regression models were employed to examine the association and determinants of TSB among U5 children in India. Results The present study revealed that the prevalence of TSB among children experiencing ARI in India has decreased from 78 percent in 2016 to 52 percent in 2021. The multilevel logistic regression model indicated that children from rural areas (AOR: 0.85; 95% CI: 0.72–0.97), Empowered Action Group (EAG) states (AOR:0.81; 95% CI:0.67–0.99), and households reporting transportation as a barrier (AOR:0.87; 95% CI:0.75–0.97) had lower odds of seeking treatment compared to their counterparts. Conversely, TSB was more likely among households headed by women (AOR:1.32; 95% CI:1.15–1.51), those with media exposure (AOR:1.23; 95% CI:1.06–1.43), and those in the higher wealth index categories. Conclusion Based on these findings, the study recommends that public health programs should focus on the indicators to improve treatment-seeking behaviour among children, and also can help to reduce child morbidity and mortality due to ARI in India. Additionally, these efforts may contribute to reducing the risk of ARI and achieving the country's SDG target by 2030. Acute Respiratory Infection Treatment-seeking Behaviour Under-five children Figures Figure 1 Figure 2 Introduction Globally, Acute Respiratory infections (ARIs), are one of the leading causes of under-five (U5) mortality [ 1 – 3 ]. According to World Health Organisation (WHO), it is responsible for almost 20 percent of all deaths of U5 children globally [ 1 ]. Mortality due to ARIs varies significantly across the regions [ 4 ]. It is responsible for approximately 70 percent of U5 morbidity in developing countries [ 5 – 6 ]. A study estimated the prevalence of ARI among U5 children across 28 sub-Saharan African countries in 2019, revealing that the overall prevalence was 25.3 percent [ 7 ]. ARI is the major cause of mortality among children aged less than 5 years, especially in low-income [ 8 ] and developing countries [ 9 ] like India [ 5 – 6 ]. Bangladesh, India, Indonesia, and Nepal together account for 40% of the global ARI mortality [ 10 ]. Moreover, ARI contribute to 30–50 percent of outpatient visits and 20–40 percent of hospital admissions among U5 children, posing significant health challenges in India [ 11 ]. Beyond many health implications, ARI imposes a substantial economic burden on individual households and society [ 12 – 15 ]. A study conducted in Bangladesh (2010) revealed that the average treatment cost for one episode of pneumonia is $ 13 for outpatient services and between $ 71 and $ 235 for severe cases requiring hospitalization [ 16 ]. Additionally, recent estimates from northern India have shown that among children U5 years old, the median direct cost of ARI was US $ 135 in private institutions and US $ 54 in public institutions [ 17 ]. Healthcare decision is influenced by socioeconomic, sociocultural, and demographic factors [ 18 – 19 ]. Previous research indicates that maternal literacy positively impacts on their children's health-seeking behaviour [ 19 , 20 ]. Additionally, studies suggest that size of the family, and proximity to healthcare facilities also affect healthcare-seeking behavior [ 19 – 21 ]. India has set the target of Sustainable Development Goals (SDGs 3.2) to reduce U5 mortality by 25 per 1000 live births (LBs) by 2030. However, NFHS-V (2019-21) indicates that the current U5 mortality of our country stands at 42/1000 LBs [ 22 ], which is alarming. Significant progress is still required to achieve the target. Global Burden of Disease (GBD) study in 2019 indicates lower respiratory infection is the second leading cause of U5 mortality in the world [ 23 ]. The prevalence of ARI among U5 children in India has increased from 2016 to 2021 while simultaneously treatment-seeking behaviour has declined [ 22 ]. Effective prevention of ARI is critical for the reduction of child mortality. Treatment-seeking behaviour is a process of making decisions about healthcare services [ 19 ] and plays a pivotal role in managing and mitigating the burden of ARI. However, several barriers hinder optimal treatment-seeking behaviour among caregivers, particularly mothers. Insufficient knowledge about child health [ 24 ] and limited awareness regarding healthcare services and treatments [ 25 ] are significant challenges. Given the high burden of ARI and its contribution to U5 mortality, it is imperative to examine the factors influencing the treatment-seeking behaviour of ARI in children. A deeper understanding of these dimensions can foster targeted intervention to promote timely and appropriate care, ultimately contributing the reduction of U5 mortality. Therefore, the present study aims to assess the prevalence of treatment-seeking behaviour among U5 children who have experienced ARI and also identify the determinants of this behaviour in India. By addressing these gaps, the present research seeks to provide actionable insights to support India’s effort towards achieving the SDG target for child survival. Data Source and Methodology Data Source The current study utilized data from the last two rounds of the National Family Health Survey (NFHS), published in 2016 (NFHS-IV) and 2021 (NFHS-V). NFHS is an India-based Demographic and Health Survey (DHS). It is a comprehensive survey conducted in a representative sample of households across India. The survey provides state and national data on maternal and child health aspects. Child health components such as immunization, nutrition, anaemia, diarrohea, and ARI are also captured in this survey. We have used the kid's file for the study and the data is freely available from the DHS website: https://dhsprogram.com/data/dataset_admin/login_main.cfm Study Design and Sample Size Two-stage stratified sampling techniques have been used for this large-scale survey. In the first stage urban areas, Census Enumeration Blocks (CEB) are selected and from rural residences, villages are selected as Primary Sampling Units (PSUs). In the second stage households have been selected both in urban and rural areas. Considering our study objectives, NFHS-4 (2015-16) & NFHS-5 (2019-21) data sources have been used, and responses from women respondents were utilized for the analysis. Sample size in NFHS-IV In the fifth round of NFHS, 2,49,967 children’s mothers were interviewed. Among these, 2,38,945 children (U5) who were alive during the interview were selected. Finally, 6,529 children were included in the present analysis based on their mothers' responses about the presence of AIR within the two weeks preceding the survey (See Fig. 1 ). Sample size in NFHS-V The total number of 230,870 children’s mothers were interviewed in NFHS-V. Among them, a total of 2,22,233 children were selected who were alive during the interview. Finally, a total of 6,198 children were included in the present analysis based on their mothers' responses regarding the AIR existence in the last two weeks presiding the survey (See Fig. 2 ) Measurement of variables Outcome variables Treatment-seeking behaviour of ARI Regarding treatment-seeking behaviour, the outcome variable was assigned a value of 1 if the individual sought treatment from a health facility or provider, and a value of 0 if they did not. It's important to note that seeking help from traditional healers, friends, or relatives is not included in this categorization [ 22 , 26 ]. Explanatory variables The selected explanatory variables have been used to determine the factors associated with treatment-seeking behaviour among children suffering from ARI in India (Table 1 ). Table 1 Variable included in treatment-seeking behaviour for the children suffering from ARI based on NFHS-IV and NFHS-V in India Background characteristics Description of the variable with code Place of Resident Place of residence has two categories: (1) urban and (2) rural Household Wealth Index Wealth index classified into five category (1) poorest, (2) poorer, (3) middle, (4) richer, and (5) richest. Gender of the Head of the Household The gender of the Head of the Household has two categories: (1) male and (2) female Household Size The number of household members categorizes in to two parts ≤ 4 Members as (1) and 5 and more members as (2) Religious group Hindu and non-Hindu Social Group It's divided in to Scheduled Caste (SC) (1), Scheduled Tribe (ST) (2), Other Backward Classes (OBC) (3), 'Others' Distance to health facility Distance to health facility has two categories (1) No/not a big problem and (2) Big problem Having to take transport Having to take transport has two categories (1) No/not a big problem and (2) a big problem Mother's literacy Mother's literacy recodes in to two categories (1) as literate and (2) as illiterate Mass Media Exposure If mothers have had exposure to mass media (radio/TV/newspaper), it is coded as (1) Yes; otherwise, it is coded as (2) No. Children ever born to women Children ever born to women are recoded as (1) one child; (2) two children and (3) more than two children. Age of the child The age of the child at the time of survey is recorded in completed months as follows: (1) 0–11 months; (2) 12–23 months; (3) 24–35 months; (4) 36–47 months; and (5) 48–59 months. Sex of the Child The sex of the child was used as original (1) male (2) female Region in India Religion is categorized into two groups: (1) Hindu, (2) non-Hindu (including Muslim, Christian, Sikh, Buddhist, neo-Buddhist, Jain, Jewish, and others). EAG and non-EAG state Eight states—Rajasthan, Uttar Pradesh, Uttarakhand, Bihar, Jharkhand, Madhya Pradesh, Chhattisgarh, and Odisha—are designated as (1) Empowered Action Group (EAG) states, while the remaining states are designated as (2) non-EAG states. Statistical Analysis Multicollinearity The degree of multicollinearity measured with Variance Inflation Factors (VIFs) in the model (Midi et al., 2010). The computed mean VIF for NFHS-IV and NFHS-V are 1.76 and 1.72 respectively, which is less than the threshold value of five, indicating that multicollinearity does not exist in the analysed models ( Supplementary file 1 ). Multivariable Logistics Regression Model The study used descriptive statistics and bivariate analysis, including the Chi-square test, to obtain initial results. Multivariable logistic regression models were used to identify the factors associated with treatment seeking behavioure on ARI among children in India in 2016 and 2021. The mathematical expression of the logistic regression analysis is: $$\:logit\left(P\right)=[{ln}P/(1-P)]={\beta\:}_{0}{+\beta\:}_{1}{X}_{1}+{\beta\:}_{2}{X}_{2\:}+\:\dots\:\dots\:\dots\:\dots\:+{\beta\:}_{k}{X}_{k}$$ Whereas, P = probability of occurrence of treatment seeking (children suffering from ARI) β 0 , β 1 , β 2 ------ β k : is the coefficients X 1 , X 2 ,--------X k : are predictor variables. P/(1-P): is the measure of odds, hence the ratio of P/(1-P) is the log of odds or the logit of P. We estimate dichotomous logit for the dependent variables and considered 1%, 5%, and 10% of the significant levels for all statistical tests. All analyses have been carried out using STATA version 14. Results Treatment-seeking behavior of ARI among children (0–59 months) across the State/UTs in India from 2016 to 2021 The results indicate that there was a reduction in treatment-seeking behaviour of ARI among below 5 years children from NFHS-IV (78.10%) to NFHS-V (52.28%) in India (Table 2 ). The data from NFHS-IV indicates that the south region (88.21%) has the highest percentage of children with treatment-seeking behaviour for ARI, which has reduced to 53.45% in NFHS-V. The north-eastern region shows the lowest percentage (63.77%) of treatment-seeking behaviour of ARI in NFHS-IV, again which has decreased further to 48.61% in NFHS-V. However, the data from NFHS-V shows the Western region has the highest percentage of treatment-seeking behaviour for ARI among children at 62.60% and the Central region has the lowest one at 44.32%. All other States showed a decrease in treatment-seeking behaviour among U5 children except Chandigarh, Goa, and Ladakh. Chandigarh has shown an overall increase in treatment-seeking behaviour from NFHS-IV (80.89%) to NFHS-V (100%). In Goa, 100% of the U5 children showed treatment-seeking behaviour while experiencing ARI. Sikkim showed the highest reduction in treatment-seeking behaviour from 100% in NFHS-IV to 19.07% in NFHS-V. In NFHS-V, treatment-seeking behaviour is lowest in Nagaland (9.43%), Sikkim (19.07%), Mizoram (21.77%), Manipur (26.88%), and Tamil Nadu (32%). Table 2 Treatment-seeking behavior of ARI among children (0–59 months) across the State/UTs in India by, NFHS IV and NFHS-V State/UTs NFHS-IV (2015-16) NFHS-V (2019-21) Weighted % Weighted % A. North Region 84.56 47.69 Chandigarh 80.89 100.00 Delhi 71.87 55.10 Haryana 80.58 45.41 Himachal Pradesh 88.99 57.95 Jammu And Kashmir 81.90 47.14 Punjab 92.32 45.04 Rajasthan 87.79 44.19 Uttarakhand 80.14 63.89 Ladakh NA 39.96 B. Central Region 75.99 44.32 Chhattisgarh 77.91 35.89 Madhya Pradesh 72.28 46.96 Uttar Pradesh 76.53 44.11 C. East Region 71.15 59.21 Bihar 67.96 62.66 Jharkhand 68.82 47.08 Odisha 70.74 40.62 West Bengal 76.79 64.29 D. Northeast Region 63.77 48.61 Arunachal Pradesh 51.33 46.69 Assam 62.74 45.51 Manipur 45.79 26.88 Meghalaya 76.26 67.94 Mizoram 63.58 21.77 Nagaland 32.28 9.43 Sikkim 100.00 19.07 Tripura 55.17 43.50 E. West Region 86.98 62.60 Dadra And Nagar Haveli/Daman and Diu 83.30 43.47 Goa 100.00 100.00 Gujarat 79.09 61.56 Maharashtra 89.34 62.67 F. South Region 88.21 53.45 Andaman And Nicobar Islands 100.00 36.22 Andhra Pradesh 72.78 51.01 Karnataka 91.47 56.46 Kerala 96.02 69.56 Lakshadweep 100.00 48.03 Puducherry 76.67 54.98 Tamil Nadu 88.61 32.00 Telangana 87.93 60.21 India 78.10 52.28 Note : UTs: Union territory, Weighted %: Children suffering from ARI sought for any treatment, NA: Not available Distribution of Sample who seek treatment of ARI with the background characteristics in 2016 and 2021 : Table 3 presents the distribution of U5 children with ARI in India according to their background characteristics in NFHS IV and NFHS-V. The distribution of U5 children with ARI across NFHS-IV and NFHS-V was similar. Around 76% of the children in NFHS-IV and 77.77% of the children in NFHS-V resided in the rural area. 27.96% of the Children belonged to the poorest and there is a gradual decline in the percentage of the children belonging to the higher wealth index with 12.43% in the richest. A similar distribution is seen in NFHS-V where 27.80% belonged to the poorest and 13.61% belonged to the richest quintile. 87.28% of children in NFHS-IV and 82.76% in NFHS-V belonged to a household with a male head and 56.23% of the children in NFHS-IV and 56.15% of the children in NFHS-V were boys. 25.30% of the children in NFHS-IV and 26.15% in NFHS-V belonged to households with less than 4 members, while others belonged to households with 5 members or more. A major percentage of the children belonged to OBC, and others were distributed among SC, ST and other social status. The percentage of children who belonged to a family who stated distance problem were 40.37% in NFHS-IV and 30.74% in NFHS-V and those who stated transport problem were 38.68% in NFHS-IV and 28.73% in NFHS-V. The percentage of children whose mothers were literate was 70.98% in NFHS-IV and 78.34% in NFHS-V and with mass media exposure was 27.52% in NFHS-IV and 28.74% in NFHS-V. The highest percentage of children experiencing ARI lived in the Central Region and the lowest percentage of children lived in the Northeastern region both in NFHS-IV and NFHS-V. 60.57% of the children in NFHS-IV and 61.13% in NFHS-V belonged to EAG States. The percentage of children decreased with an increase in the age. Table 3 Treatment-seeking behavior of ARI among children (0–59 months) with the background characteristics in India by, NFHS IV and NFHS-V Background characteristics NFHS-IV (2015-16) NFHS-V (2019-20) N % N % Place of Resident Urban 1,567 24.00 1378 22.23 Rural 4,962 76.00 4820 77.77 Household Wealth Index Poorest 1,825 27.96 1723 27.80 Poorer 1,495 22.89 1472 23.75 Middle 1,275 19.52 1167 18.83 Richer 1,123 17.20 993 16.02 Richest 811 12.43 844 13.61 Gender of the Head of the Household Male 5,699 87.28 5129 82.76 Female 830 12.72 1069 17.24 Household Size ≤ 4 Members 1,652 25.30 1620 26.15 5 and more members 4,877 74.70 4577 73.85 Religious group Hindu 4,965 76.04 4927 79.50 Non-Hindu 1,564 23.96 1271 20.50 Social Group SC 1,559 23.88 1551 25.03 ST 556 8.51 532 8.59 OBC 2,859 43.78 2676 43.18 Others 1,556 23.83 1438 23.20 Distance to health facility No/not a big problem 3,893 59.63 4293 69.26 Big problem 2,636 40.37 1905 30.74 Having to take transport No/not a big problem 4,004 61.32 4417 71.27 Big problem 2,525 38.68 1781 28.73 Mother's literacy Illiterate 1,895 29.02 1343 21.66 literate 4,635 70.98 4855 78.34 Mass Media Exposure No 1,797 27.52 1781 28.74 Yes 4,733 72.48 4416 71.26 Children ever born to women One child 1,900 29.10 1853 29.89 Two Children 2,231 34.17 2262 36.50 More than 2 children 2,398 36.73 2083 33.60 Age of the child 0–11 Months 1,545 23.66 1489 24.03 12–23 Months 1,578 24.17 1429 23.05 24–35 Months 1,233 18.89 1193 19.25 36 to 47 Months 1,216 18.62 1104 17.81 48 to 59 Months 957 14.66 983 15.86 Sex of the Child Boy 3,671 56.23 3480 56.15 Girl 2,858 43.77 2718 43.85 Region in India North 921 14.11 893 14.41 Central 2,405 36.84 1945 31.39 East 1,705 26.12 1816 29.30 Northeast 138 2.11 204 3.28 West 630 9.66 676 10.90 South 729 11.16 664 10.72 State Non EAG 2,575 39.43 2409 38.87 EAG 3,955 60.57 3789 61.13 Total 6,529 100.00 6198 100.00 Note : N: Number, %: column percentage, EAG: Empowered action group Prevalence of treatment-seeking behavior of ARI among children (0–59 months) with the background characteristics in India : Table 3 shows the prevalence of treatment-seeking behaviour among below five children with ARI in India by NFHS-IV and NFHS-V based on their background characteristics. There is a decrease in the prevalence of treatment-seeking behaviour across all the background characteristics from NFHS-IV to NFHS-V. The prevalence of treatment-seeking behaviour among urban children (86.21%) is significantly more than rural children (75.55%). However, no significant difference in prevalence is observed among the children based on the place of residence in NFHS-V. Households with a female gender as the head (56.37%) had higher treatment-seeking behaviour compared to those with a male head (51.44%) in NFHS-V. However, there were no significant differences in prevalence based on the gender of the head of the household in NFHS-IV. The prevalence of treatment-seeking behaviour is significantly highest among the Richest (90.05%) in NFHS-IV and among the Richer (55.87%) in NFHS-V and the prevalence is lowest among the Poorest (69.33%) in NFHS-IV and Richest (48.7%) in NFHS-V. It was found that the difference in prevalence was higher among the different quintiles of wealth index in NFHS-IV compared to NFHS-V, where the difference in prevalence was not much. The prevalence of treatment-seeking behaviour of ARI does not significantly differ among children based on household size, and religious group in both NFHS-IV and NFHS-V. The prevalence is significantly higher among male children than female children in both the NFHS-IV and NFHS-V. The prevalence among different social groups significantly differed in NFHS-IV with the lowest prevalence among the ST groups. However, the prevalence among different social groups does not significantly differ in NFHS-V. Those with distance problems and transport problems had a significantly lower prevalence of treatment-seeking behaviour in both the study. Children with literate mothers and those with mass media exposure had higher treatment-seeking behaviour in NFHS-IV. However, no significant difference in prevalence is found based on mothers’ literacy and Mass Media Exposure in NFHS-V. The prevalence of treatment-seeking behaviour was significantly highest among 12–23 months old children (56.07%), followed by 0–11 months (52.9%), 48–59 months (52%), 24–35 months (49.86%) and 36–47 months (49.43%) in NFHS-V. However, there were no significant differences in prevalence based on age in NFHS-IV. There was no significant difference in prevalence among U5 children based on the number of children born to women in NFHS-V. However, there was a significant difference in prevalence in NFHS-IV, where the prevalence decreased with the increase in the number of children. The highest percentage of children with treatment exposure belonged to the South Region (88.22%) in NFHS-IV and to the West Region (62.61%) in NFHS-V. The percentage of children with treatment exposure is lowest in Northeast Region (63.77%) in NFHS-IV and Central Region (44.44%) in NFHS-V. Non- EAG States had a higher percentage of children (83.26% in NFHS-IV and 56.88% in NFHS-V) with treatment-seeking behaviour compared to EAG States (74.75% in NFHS-IV and 49.36% in NFHS-V). Table 04 Prevalence of treatment-seeking behavior of ARI among children (0–59 months) with the background characteristics in India by, NFHS IV and NFHS-V Background Variables NFHS-IV NFHS-V Prevalence N (%) Prevalence N (%) Place of Resident χ2 = 79.44, p < .001* χ2 = 1.04, p = .308 Urban 1351 (86.21) 737 (53.49) Rural 3748 (75.55) 2503 (51.94) Household Wealth Index χ2 = 193.27, p < .001* χ2 = 13.69, p = .008* Poorest 1266 (69.33) 872 (50.64) Poorer 1122 (75.11) 798 (54.22) Middle 1026 (80.51) 605 (51.81) Richer 955 (85.01) 555 (55.87) Richest 731 (90.05) 411 (48.7) Gender of the head of the Household χ2 = 2.13, p = .145 χ2 = 8.63, p = .003* Male 4467 (78.39) 2638 (51.44) Female 632 (76.14) 602 (56.37) Household Size χ2 = 0.78, p = .379 χ2 = 1.09, p = .297 4 Members 1303 (78.87) 865 (53.4) 5 and more members 3797 (77.85) 2375 (51.89) Religious group χ2 = 0.38, p = .541 χ2 = 0.22, p = .642 Hindu 3869 (77.93) 2569 (52.14) Non-Hindu 1231 (78.67) 672 (52.86) Social Group χ2 = 21.71, p < .001* χ2 = 6.07, p = .109 SC 1225 (78.58) 820 (52.88) ST 391 (70.46) 256 (48.02) OBC 2243 (78.46) 1387 (51.85) Others 1240 (79.71) 777 (54.04) Distance to health facility χ2 = 29.24, p < .001* χ2 = 6.47, p = .011* No/not a big problem 3129 (80.38) 2291 (53.36) Big problem 1970 (74.75) 950 (49.86) Having to take transport χ2 = 42.73, p < .001* χ2 = 15.93, p < .001* No/not a big problem 3234 (80.76) 2380 (53.9) Big problem 1866 (73.89) 860 (48.29) Mother's literacy χ2 = 47.94, p < .001* χ2 = 1.89, p = .169 Illiterate 1375 (72.55) 680 (50.62) literate 3725 (80.38) 2561 (52.75) Mass Media Exposure χ2 = 97.55, p < .001* χ2 = 1.25, p = .265 No 1256 (69.91) 951 (53.4) Yes 3843 (81.22) 2289 (51.84) Children ever born to women χ2 = 55.11, p < .001* χ2 = 0.97, p = .618 One child 1563 (82.24) 984 (53.11) Two Children 1780 (79.76) 1167 (51.57) More than 2 children 1757 (73.29) 1090 (52.33) Age of the child χ2 = 8.18, p = .085 χ2 = 14.74, p = .005* 0–11 Months 1213 (78.51) 788 (52.9) 12–23 Months 1258 (79.7) 801 (56.07) 24–35 Months 969 (78.6) 595 (49.86) 36 to 47 Months 942 (77.48) 546 (49.43) 48 to 59 Months 718 (75) 511 (52) Sex of the Child χ2 = 25.62, p < .001* χ2 = 6.01, p = .014* Boy 2951 (80.38) 1867 (53.66) Girl 2149 (75.18) 1373 (50.53) Region in India χ2 = 166.35, p < .001* χ2 = 121.96, p < .001* North 779 (84.56) 426 (47.7) Central 1828 (75.99) 862 (44.33) East 1213 (71.15) 1075 (59.21) Northeast 88 (63.77) 99 (48.62) West 548 (86.99) 423 (62.61) South 643 (88.22) 355 (53.45) State χ2 = 66.09, p < .001* χ2 = 33.36, p < .001* Non EAG 2143 (83.26) 1370 (56.88) EAG 2956 (74.75) 1870 (49.36) Note : χ2 = Chi-square test (applied for each variable), *=p-value < 0.05 (Significance), CI: Confidence interval, SC: Scheduled Caste, ST: Scheduled Tribe, OBC: Other Backward Caste; EAG: Empowered Action Group Determinants of treatment-seeking behaviour of ARI among children in India (2016 and 2021): The multivariable binary logistic regression analysis results (Table 4 ) reveal that in NFHS-IV, factors such as the place of residence, household wealth index, gender of the head of the household, mass media exposure, age, sex of the child and the regions showed significant association with the treatment-seeking behaviour of below 5 children. However, in NFHS-V, factors such as gender of the head of the household, the necessity to take transport, age, sex of the child, regions, and the EAG Status of States showed significant association with the treatment-seeking behaviour of below 5 children. Children living in rural areas had significantly 0.85 times lower odds (AOR:0.85; 95% CI: 0.72–1.01) of having treatment-seeking behaviour compared to those living in urban areas in NFHS-IV. Also, in NFHS-IV the odds of treatment-seeking behaviour significantly increased with the increase in wealth index across all the categories compared to the very poor household in the same time. However, no significant association was found for place of residence and wealth index in NFHS-V. Children belonging to households with female heads had 1.32 times (AOR: 1.32; 95% CI: 1.15–1.51) higher odds in NFHS-V of having treatment-seeking behaviour of ARI compared to those with male heads. In NFHS-V, children whose parents reported problems in availing transport had 0.87 (AOR: 0.87; 95% CI: 0.75-1) times lower odds of having treatment-seeking behaviour than those with no transport problem. However, this trend was not observed in NFHS-IV, where the necessity to take, transport was found to have no significant association. Interestingly, the mother’s literacy was found to have no significant association with treatment-seeking behaviour in both rounds (NFHS-IV and NFHS-V). Mass Media Exposure was significantly associated with NFHS-IV, where those with exposure had 1.23 (AOR: 1.23; 95% CI: 1.06–1.43) times higher odds of treatment-seeking behaviour than those who had no exposure. However, no significant association of Mass Media exposure was found in NFHS-V. In NFHS-IV, Children who were in the age group of 48–59 months had 0.76 (AOR: 0.76; 95% CI: 0.63–0.92) times lower odds of having treatment-seeking behaviour compared to those aged 0–11 months, and in NFHS-V, Children who were in the age group of 36–47 months had 0.83 (AOR: 0.83; 95% CI: 0.7–0.97) times lower odds of having treatment seeking behaviour compared to those aged 0–11 months. Both in NFHS-IV and NFHS-V, Girl Child had a significantly lower odd (AOR: 0.75; 95% CI: 0.67–0.93) times lower in NFHS-IV and 0.88 (AOR:0.88; 95% 0.79–0.97) times lower in NFHS-V) of having treatment seeking behaviour compared to boy child. In NFHS-IV, children belonging to the Central region had 0.75 (AOR:0.75; 95% CI: 0.6–0.93) times lower odds, the East Region had 0.59 (AOR: 0.59; 95% CI: 0.48–0.74) times lower odds, the Northeast Region had 0.33 (AOR: 0.33; 95% CI: 0.26–0.43) times lower odds of having treatment seeking behaviour compared to children belonging to the North Region. However, in NFHS-V, children belonging to the Central region had significantly 0.75 (AOR: 0.75; 95% CI: 0.6–0.93) times lower odds, the East Region had significantly 1.56 (AOR: 1.56; 95% CI: 1.29–1.88) times higher odds and the West Region had significantly 1.21 (AOR:1.21; 95% CI: 0.96–1.52) times higher odds of having treatment seeking behaviour compared to children belonging to the North Region. In NFHS-V, children belonging to EAG States had significantly 0.81 (AOR: 0.81; 95% CI: 0.67–0.99) times lower odds of having treatment-seeking behaviour of ARI compared to those belonging to Non EAG States. However, the EAG status of the State was not significant in determining the treatment-seeking behaviour in NFHS-IV. Table 05 Logistic regression model assessing the factors associated with treatment seeking behavior of ARI among children (0–59 Months) in India, by NFHS IV and V Background Characteristics NFHS-IV NFHS-V AOR 95% CI [Lower-Upper] AOR 95% CI [Lower-Upper] Place of Resident Urban Ref. Ref. Rural 0.85 (0.72–0.97) * 1.13 (0.98–1.31) Household Wealth Index Very Poor Ref. Ref. Poorer 1.25 (1.07–1.47) ** 1.15 (1-1.33) Middle 1.45 (1.2–1.76) *** 1.11 (0.94–1.32) Richer 1.54 (1.22–1.94) *** 1.16 (0.95–1.4) Richest 2.06 (1.55–2.74) *** 0.96 (0.77–1.2) Gender of the head of the Household Male Ref. Ref. Female 1.05 (0.88–1.25) 1.32 (1.15–1.51) *** Household Size 4 Members Ref. Ref. 5 and more members 1.04 (0.9–1.21) 0.97 (0.85–1.09) Religious group Hindu Ref. Ref. Non-Hindu 1.15 (0.99–1.33) 1.05 (0.92–1.2) Social Group SC Ref. Ref. ST 0.85 (0.69–1.04) 0.92 (0.77–1.1) OBC 0.94 (0.8–1.11) 1.07 (0.93–1.23) Others 0.84 (0.7–1.01) 1 (0.85–1.17) Distance to health facility No/not a big problem Ref. Ref. Big problem 0.98 (0.83–1.15) 1.04 (0.9–1.19) Having to take transport No/not a big problem Ref. Ref. Big problem 0.97 (0.82–1.14) 0.87 (0.75–0.97) * Mother's literacy Illiterate Ref. Ref. literate 1.07 (0.93–1.24) 1.06 (0.93–1.22) Mass Media Exposure No Ref. Ref. Yes 1.23 (1.06–1.43) ** 0.9 (0.79–1.03) Children ever born to women One children Ref. Ref. Two Children 0.91 (0.78–1.07) 1.05 (0.92–1.19) More than 2 children 0.79 (0.67–0.93) 1.12 (0.97–1.29) Age of the child 0–11 Months Ref. Ref. 12–23 Months 0.96 (0.81–1.13) 1.1 (0.95–1.28) 24–35 Months 0.88 (0.74–1.05) 0.9 (0.77–1.06) 36 to 47 Months 0.93 (0.77–1.12) 0.83 (0.7–0.97) * 48 to 59 Months 0.76 (0.63–0.92) ** 0.91 (0.77–1.07) Sex of the Child Boy Ref. Ref. Girl 0.75 (0.67–0.84) *** 0.88 (0.79–0.97) ** Region in India North Ref. Ref. Central 0.75 (0.6–0.93) ** 0.91 (0.76–1.09) East 0.59 (0.48–0.74) *** 1.56 (1.29–1.88) *** Northeast 0.33 (0.26–0.43) *** 1.03 (0.82–1.29) West 1.06 (0.74–1.52) 1.42 (1.12–1.81) ** South 1.1 (0.79–1.53) 1.21 (0.96–1.52) State Non EAG Ref. Ref. EAG 0.93 (0.74–1.18) 0.81 (0.67–0.98) * Cons 5.34 0.95 Number of obs 6,529 6,198 Pseudo R2 0.0532 0.0172 LR chi2 402.9 145.7 Prob > chi2 < 0.001 < 0.001 Log likelihood = -3585.6679 -4166.996 Note : AOR: Adjusted Odds Ratio, Ref: Reference Category, CI: Confidence interval, ***p < 0.001, **p < 0.01, *p < 0.05, SC: Scheduled Caste, ST: Scheduled Tribe, OBC: Other Backward Caste, EAG = Empowered action group Discussion The current study examines the prevalence and determinants of treatment-seeking behaviour among children infected by ARI in India. The last two rounds of NFHS data were analysed with the help of STATA 14 software. The study revealed that the prevalence of treatment-seeking behaviours among children suffering from ARI has decreased from 78 percent in 2016 to 52 percent in 2021 in India. Phase 2 of the NFHS-5 survey, conducted in 14 states/UTs, took place from 2nd January 2020 to 30th April 2021 [ 22 ]. The country was under total or partial lockdown during this period. Studies have shown a decrease in the number of people seeking medical treatment for acute health problems during the lockdown [ 27 – 28 ]. Therefore, the lockdown restriction and fear of contracting COVID-19 infection decline in seeking treatment for ARI [ 26 ]. A multilevel logistic regression model has been employed to identify the possible determinants of treatment-seeking behaviour. Our study found that children from rural geography have significantly lower odds of seeking treatment compared to urban part. One possible reason is that due to higher air pollution in urban areas, the incidence is high. Therefore, treatment-seeking behaviour is also high in urban residents as compared to rural residents [ 26 ]. Our study highlighted that an increase in household wealth quantile status significantly improves treatment-seeking behaviour. This finding aligns with a study conducted in Indonesia, which revealed that children from wealthy families were less vulnerable to ARI incidence [ 29 ]. The findings from the present research indicate that children U5 belonging to households with female heads had higher odds of having treatment-seeking behaviour compared to those with male heads. The finding resonates with the studies conducted in Tanzania [ 30 ] and sub-Saharan Africa [ 31 ]. The possible explanation is that households with female heads may not encounter the challenge of obtaining permission to seek care, which is a common barrier to healthcare utilization among women and children [ 32 – 33 ]. Another probable explanation is that women who are heads of households tend to allocate the available resources they control towards prioritizing their children's health, thereby increasing their health-seeking behaviour [ 33 – 34 ]. The present study also indicated that children, whose parents reported taking transport is a problem had lower odds of having treatment-seeking behaviour than those with no transport problem. Previous research suggested that the usage of healthcare services is adversely affected by factors such as the significant distance to medical facilities, the absence of transportation options, and the subpar quality of roads [ 26 , 35 – 37 ]. Our research demonstrates that mothers who are exposed to the media are more likely to seek healthcare for their children compared to mothers who have not been exposed to the media. This finding aligns with studies conducted in West Bengal, India [ 24 ]. One potential explanation is that exposure to mass media exposes people to healthcare information, which improves their behaviour in seeking healthcare. Evidence from the previous study also suggests that exposure to the media plays a crucial role in promoting healthy behaviours [ 30 , 33 ]. Additionally, our study indicates that children from EAG States were significantly less likely to seek treatment for ARI compared to those from non-EAG states. In India, there is a significant disparity in the accessibility and availability of healthcare between public health facilities in EAG and non-EAG states [ 38 – 40 ]. The possible reason for the lower treatment-seeking behavior in EAG states, which are mostly located in the northern and central regions, is the high percentage of the population living below the poverty line and a high proportion of women with limited access to education and mass media [ 41 ]. Limitation of the Study The present study had some limitations. Firstly, ARI was classified as per the signs and symptoms reported by the children's mothers, without confirmation from medical professionals. Secondly, mothers were asked to recall their children's symptoms from the past 2 weeks of the survey, which may raise the possibility of recall bias. Thirdly, a cross-sectional design prevented the establishment of a cause-and-effect relationship. Conclusion ARI is the major cause of U5 mortality and morbidity in low-income and developing countries like India. India has already set its goal to achieve the SDGs target to reduce U5 child mortality by 25/1000 live births in 2030 (SDGs) which is 42/1000 live births as per the NFHS-V. The current study aims to assess the prevalence and determinants of treatment-seeking behaviour among children infected by ARI in India. the study highlighted the the treatment-seeking behaviour among children infected with ARI has been decreased from 2016 to 2019. Although COVID-19 is a likely cause, it remains a significant public health issue in India. The present study also identified the determinants of treatment-seeking behaviour. The place of residence, household wealth quantile, gender of the head of a household, challenges related to transport, and mass media exposure were found to be significantly associated with treatment-seeking behaviour. Based on these findings, the study recommends that public health programs should focus on the indicators to improve treatment-seeking behaviour among children, and also can help to reduce child morbidity and mortality due to ARI in India. Additionally, these efforts may contribute to reducing the risk of ARI and achieving the country's SDG target by 2030. Abbreviations AOR Adjusted Odds Ratio ARI Acute Respiratory Infections CEB Census Enumeration Blocks DHS Demographic and Health Survey EAG Empowered action group GBD Global Burden of Disease LRTI Lower Respiratory Tract Infections NFHS National Family Health Survey OBC Other Backward Caste PSU Primary Sampling Unit SC Scheduled Caste SDGs Sustainable Development Goals ST Scheduled Tribe U5 Under-five UN United Nations WHO World Health Organization Declarations Authorship contribution statement: All authors contributed significantly to this paper. The research idea, conceptualization, and study design: KG, ASC; Collected data and analyzed the data: KG & ASC; Gathered material and wrote the manuscript: KG, ASC, BH & SP; Refined and finalized the manuscript: KG, ASC, BH & SP. Funding: This research did not receive a specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Conflicts of interest/Competing interests: Not applicable (as it is based on secondary data) Ethics approval: There is no formal ethics approval required for this particular study since the study is based on secondary data and the survey data is available in the public domain. Human Ethics and Consent to Participate declarations: Not applicable Clinical trial number: Not applicable Availability of data and material: The data of a particular study is available in the public domain and can be extracted from: https://dhsprogram.com/Data/ Acknowledgment: We sincerely thank to International Institute for Population Sciences (IIPS), Mumbai for providing the data of the NFHS project. We also thank all reviewers and the editorial board of this journal. Consent for publication: We confirm that consent for publication has been obtained from all authors References World Health Organization (2022) Facts Sheets: Child mortality (under 5 years). Available at: https://www.who.int/news-room/fact-sheets/detail/levels-and-trends-in-child-under-5-mortality-in-2020 [Accessed 29 December 2024]. Troeger C, Blacker B, Khalil IA, Rao PC, Cao J, Zimsen SR, Albertson SB, Deshpande A, Farag T, Abebe Z and Adetifa IM (2018) Estimates of the global, regional, and national morbidity, mortality, and aetiologies of lower respiratory infections in 195 countries, 1990–2016: A systematic analysis for the Global Burden of Disease Study 2016. The Lancet Infectious Diseases 18(11), 1191-1210. Available at: http://dx.doi.org/10.1016/. Naghavi M, Abajobir AA, Abbafati C, Abbas KM, Abd-Allah F, Abera SF, Aboyans V, Adetokunboh O, Afshin A, Agrawal A and Ahmadi A (2017) Global, regional, and national age-sex specific mortality for 264 causes of death, 1980-2016: A systematic analysis for the Global Burden of Disease Study 2016. The Lancet 390(10100), 1151-1210. Available from: https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(17)32152-9/fulltext?rss%3Dyes= Wang H, Bhutta ZA, Coates MM, Coggeshall M, Dandona L, Diallo K, Franca EB, Fraser M, Fullman N, Gething PW and Hay SI. (2016) Global, regional, national, and selected subnational levels of stillbirths, neonatal, infant, and under-5 mortality, 1980–2015: A systematic analysis for the Global Burden of Disease Study 2015. The Lancet 388(10053), 1725-1774. Available at: https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(16)31575-6/fulltext. Selvaraj K, Chinnakali P, Majumdar A and Krishnan IS (2014) Acute respiratory infections among under-5 children in India: A situational analysis. Journal of Natural Science, Biology, and Medicine 5(1), 15. Available at: https://doi.org/10.4103/0976-9668.127275. World Health Organization & UNICEF (1999) Management of Childhood Illness in Developing Countries: Rationale for an integrated strategy. IMCI Information (WHO/CHS/CAH/98.1 A Rev. 1), WHO, Geneva, 3. Seidu AA, Dickson KS, Ahinkorah BO, Amu H, Darteh EKM and Kumi-Kyereme A (2019) Prevalence and determinants of acute lower respiratory infections among children under-five years in sub–Saharan Africa: evidence from demographic and health surveys. SSM-Population Health 8, 100443. Available at: https://doi.org/10.1016/j.ssmph.2019.100443. Walker CL, Rudan I, Liu L, Nair H, Theodoratou E, Bhutta ZA, O'Brien KL, Campbell H and Black RE (2013) Global burden of childhood pneumonia and diarrhoea. The Lancet 381(9875), 1405-1416. Available at: https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(13)60222-6/fulltext. Frese T, Klauss S, Herrmann K and Sandholzer H (2011) Children and adolescents as patients in general practice-the reasons for encounter. Journal of Clinical Medicine Research 3(4), 177. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC3194013/ Kumar SG, Majumdar A, Kumar V, Naik BN, Selvaraj K and Balajee K (2015) Prevalence of acute respiratory infection among under-five children in urban and rural areas of Puducherry, India. Journal of Natural Science, Biology, and Medicine 6(1), 3. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC4367064/ Vashishtha VM (2010) Current status of tuberculosis and acute respiratory infections in India: Much more needs to be done! Indian Pediatrics 88-89. Available at: https://www.indianpediatrics.net/jan2010/88.pdf. Kurskaya O, Ryabichenko T, Leonova N, Shi W, Bi H, Sharshov K, Kazachkova E, Sobolev I, Prokopyeva E, Kartseva T and Alekseev A (2018) Viral etiology of acute respiratory infections in hospitalized children in Novosibirsk City, Russia (2013-2017). PLoS One 13(9): e0200117. https://doi.org/10.1371/journal.pone.0200117 Ramaekers K, Keyaerts E, Rector A, Borremans A, Beuselinck K, Lagrou K, Van Ranst M (2017) Prevalence and seasonality of six respiratory viruses during five consecutive epidemic seasons in Belgium. Journal of Clinical Virology 94, 72-78. Available at: https://doi.org/10.1016/j.jcv.2017.07.011. Krishnan A, Amarchand R, Gupta V, Lafond KE, Suliankatchi RA, Saha S, Rai S, Misra P, Purakayastha DR, Wahi A and Sreenivas V (2015) Epidemiology of acute respiratory infections in children-preliminary results of a cohort in a rural north Indian community. BMC Infectious Diseases 15(1), 462. Available from: https://link.springer.com/article/10.1186/s12879-015-1188-1 Romieu I, Samet JM, Smith KR and Bruce N (2002) Outdoor air pollution and acute respiratory infections among children in developing countries. Journal of Occupational and Environmental Medicine 44(7), 640-649. Available at: https://journals.lww.com/joem/abstract/2002/07000/outdoor_air_pollution_and_acute_respiratory.10.aspx. Alamgir NI, Naheed A and Luby SP. (2010) Coping strategies for financial burdens in families with childhood pneumonia in Bangladesh. BMC Public Health 10(1), 622. Available from: https://link.springer.com/article/10.1186/1471-2458-10-622 Peasah SK, Purakayastha DR, Koul PA, Dawood FS, Saha S, Amarchand R, Broor S, Rastogi V, Assad R, Kaul KA and Widdowson MA (2015) The cost of acute respiratory infections in Northern India: a multi-site study. BMC Public Health 15, 1-9. Available at: https://link.springer.com/article/10.1186/s12889-015-1685-6 Shaikh BT and Hatcher J (2005) Health seeking behaviour and health service utilization in Pakistan: Challenging the policy makers. Journal of Public Health (Oxford) 27(1), 49-54. Available at: https://doi.org/10.1093/pubmed/fdh207 Prakash LK (2014) Acute respiratory infection among children and health seeking behaviour in India. International Journal of Scientific and Research Publications 4(11), 1. Abdulkadir MB, Abdulkadir ZA , and Johnson WBR (2016) An analysis of national data on care-seeking behaviour by parents of children with suspected pneumonia in Nigeria. South African Journal of Child Health 10(1), 92-95. Available from: https://www.ajol.info/index.php/sajchh/article/view/133695 Sultana M, Sarker AR, Sheikh N, Akram R, Ali N, Mahumud RA and Alam NH (2019) Prevalence, determinants and health care-seeking behavior of childhood acute respiratory tract infections in Bangladesh. PloS One 14(1), e0210433. Available at: https://doi.org/10.1371/journal.pone.0210433. International Institute for Population Sciences. (2021) National Family Health Survey (NFHS-5), 2019-21, India Fact Sheet. Mumbai: IIPS. Available from: http://rchiips.org/nfhs/factsheet_NFHS-4.shtml Paulson KR, Kamath AM, Alam T, Bienhoff K, Abady GG, Abbas J, Abbasi-Kangevari M, Abbastabar H, Abd-Allah F, Abd-Elsalam SM and Abdoli A (2021) Global, regional, and national progress towards Sustainable Development Goal 3.2 for neonatal and child health: all-cause and cause-specific mortality findings from the Global Burden of Disease Study 2019. The Lancet 398(10303), 870-905. Available at: https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(21)01207-1/fulltext?faodatalab=2021-08-18-1. Chandwani H and Pandor JJ (2015) Healthcare-seeking behavior of mothers regarding their child in a tribal community of Gujarat, India. Epidemiology 7(1), 990. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC4455300/ Liu L, Johnson HL, Cousens S, Perin J, Scott S, Lawn JE, Rudan I, Campbell H, Cibulskis R, Li M and Mathers C (2012) Global, regional, and national causes of child mortality: An updated systematic analysis for 2010 with time trends since 2000. The Lancet 379(9832), 2151-2161. Available from: https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(12)60560-1/abstract Varghese JS and Muhammad T (2023) Prevalence, potential determinants, and treatment-seeking behavior of acute respiratory infection among children under age five in India: Findings from the National Family Health Survey, 2019-21. BMC Pulmonary Medicine 23(1), 195. Available at: https://doi.org/10.1186/s12890-023-02487-4. Stalin P, Alexander T, Purty AJ, Manikandan M and Vaishnavi S (2022) Health-seeking behavior for acute health problems during COVID-19 lockdown among the residents of an urban area in Puducherry. Indian Journal of Community Medicine 47(2), 299-301. Available at: https://doi.org/10.4103/ijcm.ijcm_739_21. Yang J, Gong H, Chen X, Chen Z, Deng X, Qian M, Hou Z, Ajelli M and Viboud C, Yu H (2021) Health-seeking behaviors of patients with acute respiratory infections during the outbreak of novel coronavirus disease 2019 in Wuhan, China. Influenza and Other Respiratory Viruses 15(2), 188-194. Available at: https://doi.org/10.1111/irv.12804. Lutpiatina L, Sulistyorini L, Notobroto HB, Raya RP, Utama RD and Thuraidah A. (2022) Multilevel analysis of lifestyle and household environment for toddlers with symptoms of acute respiratory infection (ARI) in Indonesia in 2007, 2012, and 2017. Global Pediatric Health 9, 2333794X221078700. https://doi.org/10.1177/2333794X221078700 Adinan J, Damian DJ, Mosha NR, Mboya IB, Mamseri R and Msuya SE (2017) Individual and contextual factors associated with appropriate healthcare seeking behavior among febrile children in Tanzania. PLoS One 12(4): e0175446. https://doi.org/10.1371/journal.pone.0175446 Akinyemi JO, Chisumpa VH and Odimegwu CO (2019) Household relationships and healthcare seeking behaviour for common childhood illnesses in sub-Saharan Africa: A cross-national mixed effects analysis. BMC Health Services Research 19(1), 1-11. https://doi.org/10.1186/s12913-019-4142-x Charles JO, Udonwa NE, Ikoh MU and Ikpeme BI (2008) The role of mothers in household health-seeking behavior and decision-making in childhood febrile illness in Okurikang/Ikot Efong Otop Community. Cross River State Nigeria. Epidemiology 29(8-9), 906-925. Available from: https://www.tandfonline.com/doi/full/10.1080/07399330802269626#d1e326 Aragaw FM, Teklu RE, Alemayehu MA, Derseh NM, Agimas MC, Shewaye DA, Birhanie AL, Tsega SS, Argaw GS, Tesfaye AH (2024) Magnitude and determinant of healthcare-seeking behavior for childhood acute respiratory tract infections in Ethiopia: A cross-sectional study. BMC Pediatrics 24(1), 3. https://doi.org/10.1186/s12887-023-04463-7 Richards E, Theobald S, George A, Kim JC, Rudert C, Jehan K and Tolhurst R (2013) Going beyond the surface: Gendered intra-household bargaining as a social determinant of child health and nutrition in low and middle-income countries. Social Science & Medicine 95, 24-33. Available at: https://doi.org/10.1016/j.socscimed.2012.06.015. Okwaraji YB, Cousens S, Berhane Y, Mulholland K and Edmond K (2012) Effect of geographical access to health facilities on child mortality in rural Ethiopia: A community-based cross-sectional study. PLoS One 7(3): e33564. https://doi.org/10.1371/journal.pone.0033564 Shiferaw S, Spigt M, Godefrooij M, Melkamu Y and Tekie M (2013) Why do women prefer home births in Ethiopia? BMC Pregnancy and Childbirth 13, 1-10. Available at: http://www.biomedcentral.com/1471-2393/13/5. Astale T and Chenault M (2015) Help-seeking behavior for children with acute respiratory infection in Ethiopia: Results from 2011 Ethiopia demographic and health survey. PLoS One 10(11): e0142553. https://doi.org/10.1371/journal.pone.0142553 Rani M, Bonu S and Harvey S (2008) Differentials in the quality of antenatal care in India. International Journal for Quality in Health Care 20(1), 62-71. Available at: https://doi.org/10.1093/intqhc/mzm052. Kumar V and Singh P (2016) Access to healthcare among the empowered action group (EAG) states of India: Current status and impeding factors. National Medical Journal of India 29, 267-273. Sanasam DC (2020) Maternal reproductive health: A comparison between India and empowered action group states. In Urban Health Risk and Resilience in Asian Cities (pp. 149–163). Singapore: Springer. Available at: https://link.springer.com/chapter/10.1007/978-981-15-1205-6_9. NITI Ayog: RBI Handbook of Statistics on Indian Economy 2015-16. Available from: https://rbidocs.rbi.org.in/rdocs/Publications/PDFs/154T_HB15092019609736EE47614B23BFD377A47FFC1A5D.PDF Additional Declarations No competing interests reported. Supplementary Files Supplementaryfile.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6194991","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":445287785,"identity":"095000b9-ae09-4f38-9bb7-27c255dcf10e","order_by":0,"name":"Koustav Ghosh","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8UlEQVRIiWNgGAWjYBACCSgtx8be2PgAyODhI0rLAQYGY36ew4cNQFrYiNWSOHNGWhqYQ1CLZHuP8ecPNYcZNxzIMav8mmMnw8bA/PDRDTxapHnOmEkcOHaY2eDAGbPbstuSgQ5jMzbOwaNFTiLHjOEAWxqbwcEes9uS25iBWnjYpAloMf5w4F8aj8FhHrNiyW31hLVIS+QYSBxss5GQbGNLY/y47TBhLZI9x8okzvbZGPDzMB+WZtx2nIeNmYBfJI43b/5Q8U2ivk3+YePHn9uq7fnZmx8+xqcFBTDzgElilYMA4w9SVI+CUTAKRsGIAQA8sEYc7LCZwgAAAABJRU5ErkJggg==","orcid":"","institution":"Gokhale Institute of Politics and Economics","correspondingAuthor":true,"prefix":"","firstName":"Koustav","middleName":"","lastName":"Ghosh","suffix":""},{"id":445287786,"identity":"60462e20-b97e-49a5-80fd-649ebefa8aab","order_by":1,"name":"Atreyee Sinha Chakraborty","email":"","orcid":"","institution":"Gokhale Institute of Politics and Economics","correspondingAuthor":false,"prefix":"","firstName":"Atreyee","middleName":"Sinha","lastName":"Chakraborty","suffix":""},{"id":445287787,"identity":"90ae74d1-19c5-4acf-827d-3658d33f0502","order_by":2,"name":"Banashri Haloi","email":"","orcid":"","institution":"Central University of Kerala","correspondingAuthor":false,"prefix":"","firstName":"Banashri","middleName":"","lastName":"Haloi","suffix":""},{"id":445287788,"identity":"7a639b8a-77f8-45ba-b791-be3edf43a947","order_by":3,"name":"Sarjoo Patel","email":"","orcid":"","institution":"The Maharaja Sayajirao University of Baroda","correspondingAuthor":false,"prefix":"","firstName":"Sarjoo","middleName":"","lastName":"Patel","suffix":""}],"badges":[],"createdAt":"2025-03-10 11:23:35","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6194991/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6194991/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":81032033,"identity":"ccb597e3-388d-46a0-845a-52a4204ff216","added_by":"auto","created_at":"2025-04-21 11:26:25","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":303803,"visible":true,"origin":"","legend":"\u003cp\u003eChild Inclusion Flowchart: NFHS-IV (2015-16)\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6194991/v1/92a8e8b03858abb1e5ffd420.png"},{"id":81030704,"identity":"e14f5761-e236-4c4b-966d-55cfd70ee727","added_by":"auto","created_at":"2025-04-21 11:18:25","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":301039,"visible":true,"origin":"","legend":"\u003cp\u003eChild Inclusion Flowchart: NFHS-IV (2019-21)\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6194991/v1/97b017a64211083781c47c93.png"},{"id":81426315,"identity":"909da378-b625-406c-af96-627187a627cb","added_by":"auto","created_at":"2025-04-26 07:23:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3231501,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6194991/v1/d66c904a-466e-4aea-8606-5616268a9080.pdf"},{"id":81030703,"identity":"74d23afb-bfbd-4bc3-86ec-d50054ceb2cf","added_by":"auto","created_at":"2025-04-21 11:18:25","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":23309,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfile.docx","url":"https://assets-eu.researchsquare.com/files/rs-6194991/v1/90acff6fba2b4502422882dc.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prevalence and Drivers of Treatment Seeking Behaviour among Under-five Children Experiencing Acute Respiratory Infection in India ","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGlobally, Acute Respiratory infections (ARIs), are one of the leading causes of under-five (U5) mortality [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. According to World Health Organisation (WHO), it is responsible for almost 20 percent of all deaths of U5 children globally [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Mortality due to ARIs varies significantly across the regions [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. It is responsible for approximately 70 percent of U5 morbidity in developing countries [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. A study estimated the prevalence of ARI among U5 children across 28 sub-Saharan African countries in 2019, revealing that the overall prevalence was 25.3 percent [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eARI is the major cause of mortality among children aged less than 5 years, especially in low-income [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] and developing countries [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] like India [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Bangladesh, India, Indonesia, and Nepal together account for 40% of the global ARI mortality [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Moreover, ARI contribute to 30\u0026ndash;50 percent of outpatient visits and 20\u0026ndash;40 percent of hospital admissions among U5 children, posing significant health challenges in India [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Beyond many health implications, ARI imposes a substantial economic burden on individual households and society [\u003cspan additionalcitationids=\"CR13 CR14\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. A study conducted in Bangladesh (2010) revealed that the average treatment cost for one episode of pneumonia is \u003cspan\u003e$\u003c/span\u003e13 for outpatient services and between \u003cspan\u003e$\u003c/span\u003e71 and \u003cspan\u003e$\u003c/span\u003e235 for severe cases requiring hospitalization [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Additionally, recent estimates from northern India have shown that among children U5 years old, the median direct cost of ARI was US\u003cspan\u003e$\u003c/span\u003e135 in private institutions and US\u003cspan\u003e$\u003c/span\u003e54 in public institutions [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Healthcare decision is influenced by socioeconomic, sociocultural, and demographic factors [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Previous research indicates that maternal literacy positively impacts on their children's health-seeking behaviour [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Additionally, studies suggest that size of the family, and proximity to healthcare facilities also affect healthcare-seeking behavior [\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIndia has set the target of Sustainable Development Goals (SDGs 3.2) to reduce U5 mortality by 25 per 1000 live births (LBs) by 2030. However, NFHS-V (2019-21) indicates that the current U5 mortality of our country stands at 42/1000 LBs [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], which is alarming. Significant progress is still required to achieve the target. Global Burden of Disease (GBD) study in 2019 indicates lower respiratory infection is the second leading cause of U5 mortality in the world [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The prevalence of ARI among U5 children in India has increased from 2016 to 2021 while simultaneously treatment-seeking behaviour has declined [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Effective prevention of ARI is critical for the reduction of child mortality. Treatment-seeking behaviour is a process of making decisions about healthcare services [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] and plays a pivotal role in managing and mitigating the burden of ARI. However, several barriers hinder optimal treatment-seeking behaviour among caregivers, particularly mothers. Insufficient knowledge about child health [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] and limited awareness regarding healthcare services and treatments [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] are significant challenges. Given the high burden of ARI and its contribution to U5 mortality, it is imperative to examine the factors influencing the treatment-seeking behaviour of ARI in children. A deeper understanding of these dimensions can foster targeted intervention to promote timely and appropriate care, ultimately contributing the reduction of U5 mortality. Therefore, the present study aims to assess the prevalence of treatment-seeking behaviour among U5 children who have experienced ARI and also identify the determinants of this behaviour in India. By addressing these gaps, the present research seeks to provide actionable insights to support India\u0026rsquo;s effort towards achieving the SDG target for child survival.\u003c/p\u003e"},{"header":"Data Source and Methodology","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData Source\u003c/h2\u003e \u003cp\u003eThe current study utilized data from the last two rounds of the National Family Health Survey (NFHS), published in 2016 (NFHS-IV) and 2021 (NFHS-V). NFHS is an India-based Demographic and Health Survey (DHS). It is a comprehensive survey conducted in a representative sample of households across India. The survey provides state and national data on maternal and child health aspects. Child health components such as immunization, nutrition, anaemia, diarrohea, and ARI are also captured in this survey. We have used the kid's file for the study and the data is freely available from the DHS website: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://dhsprogram.com/data/dataset_admin/login_main.cfm\u003c/span\u003e\u003cspan address=\"https://dhsprogram.com/data/dataset_admin/login_main.cfm\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy Design and Sample Size\u003c/h3\u003e\n\u003cp\u003eTwo-stage stratified sampling techniques have been used for this large-scale survey. In the first stage urban areas, Census Enumeration Blocks (CEB) are selected and from rural residences, villages are selected as Primary Sampling Units (PSUs). In the second stage households have been selected both in urban and rural areas. Considering our study objectives, NFHS-4 (2015-16) \u0026amp; NFHS-5 (2019-21) data sources have been used, and responses from women respondents were utilized for the analysis.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSample size \u003cem\u003ein NFHS-IV\u003c/em\u003e\u003c/strong\u003e \u003cp\u003eIn the fifth round of NFHS, 2,49,967 children\u0026rsquo;s mothers were interviewed. Among these, 2,38,945 children (U5) who were alive during the interview were selected. Finally, 6,529 children were included in the present analysis based on their mothers' responses about the presence of AIR within the two weeks preceding the survey (See Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSample size in NFHS-V\u003c/strong\u003e \u003cp\u003eThe total number of 230,870 children\u0026rsquo;s mothers were interviewed in NFHS-V. Among them, a total of 2,22,233 children were selected who were alive during the interview. Finally, a total of 6,198 children were included in the present analysis based on their mothers' responses regarding the AIR existence in the last two weeks presiding the survey (See Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eMeasurement of variables\u003c/h3\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eOutcome variables\u003c/h2\u003e \u003cp\u003e \u003cstrong\u003eTreatment-seeking behaviour of ARI\u003c/strong\u003e \u003cp\u003eRegarding treatment-seeking behaviour, the outcome variable was assigned a value of 1 if the individual sought treatment from a health facility or provider, and a value of 0 if they did not. It's important to note that seeking help from traditional healers, friends, or relatives is not included in this categorization [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eExplanatory variables\u003c/h3\u003e\n\u003cp\u003eThe selected explanatory variables have been used to determine the factors associated with treatment-seeking behaviour among children suffering from ARI in India (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eVariable included in treatment-seeking behaviour for the children suffering from ARI based on NFHS-IV and NFHS-V in India\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBackground characteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDescription of the variable with code\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePlace of Resident\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePlace of residence has two categories: (1) urban and (2) rural\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHousehold Wealth Index\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWealth index classified into five category (1) poorest, (2) poorer, (3) middle, (4) richer, and (5) richest.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender of the Head of the Household\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe gender of the Head of the Household has two categories: (1) male and (2) female\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHousehold Size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe number of household members categorizes in to two parts\u0026thinsp;\u0026le;\u0026thinsp;4 Members as (1) and 5 and more members as (2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReligious group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHindu and non-Hindu\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSocial Group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIt's divided in to Scheduled Caste (SC) (1), Scheduled Tribe (ST) (2), Other Backward Classes (OBC) (3), 'Others'\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDistance to health facility\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDistance to health facility has two categories (1) No/not a big problem and (2) Big problem\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHaving to take transport\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHaving to take transport has two categories (1) No/not a big problem and (2) a big problem\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMother's literacy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMother's literacy recodes in to two categories (1) as literate and (2) as illiterate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMass Media Exposure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIf mothers have had exposure to mass media (radio/TV/newspaper), it is coded as (1) Yes; otherwise, it is coded as (2) No.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChildren ever born to women\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChildren ever born to women are recoded as (1) one child; (2) two children and (3) more than two children.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge of the child\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe age of the child at the time of survey is recorded in completed months as follows: (1) 0\u0026ndash;11 months; (2) 12\u0026ndash;23 months; (3) 24\u0026ndash;35 months; (4) 36\u0026ndash;47 months; and (5) 48\u0026ndash;59 months.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex of the Child\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe sex of the child was used as original (1) male (2) female\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegion in India\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReligion is categorized into two groups: (1) Hindu, (2) non-Hindu (including Muslim, Christian, Sikh, Buddhist, neo-Buddhist, Jain, Jewish, and others).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEAG and non-EAG state\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEight states\u0026mdash;Rajasthan, Uttar Pradesh, Uttarakhand, Bihar, Jharkhand, Madhya Pradesh, Chhattisgarh, and Odisha\u0026mdash;are designated as (1) Empowered Action Group (EAG) states, while the remaining states are designated as (2) non-EAG states.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003e \u003cstrong\u003eMulticollinearity\u003c/strong\u003e \u003cp\u003eThe degree of multicollinearity measured with Variance Inflation Factors (VIFs) in the model (Midi et al., 2010). The computed mean VIF for NFHS-IV and NFHS-V are 1.76 and 1.72 respectively, which is less than the threshold value of five, indicating that multicollinearity does not exist in the analysed models (\u003cb\u003eSupplementary file 1\u003c/b\u003e).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eMultivariable Logistics Regression Model\u003c/strong\u003e \u003cp\u003eThe study used descriptive statistics and bivariate analysis, including the Chi-square test, to obtain initial results. Multivariable logistic regression models were used to identify the factors associated with treatment seeking behavioure on ARI among children in India in 2016 and 2021.\u003c/p\u003e \u003c/p\u003e \u003cp\u003eThe mathematical expression of the logistic regression analysis is:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:logit\\left(P\\right)=[{ln}P/(1-P)]={\\beta\\:}_{0}{+\\beta\\:}_{1}{X}_{1}+{\\beta\\:}_{2}{X}_{2\\:}+\\:\\dots\\:\\dots\\:\\dots\\:\\dots\\:+{\\beta\\:}_{k}{X}_{k}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhereas,\u003c/p\u003e \u003cp\u003eP\u0026thinsp;=\u0026thinsp;probability of occurrence of treatment seeking (children suffering from ARI)\u003c/p\u003e \u003cp\u003eβ\u003csub\u003e0\u003c/sub\u003e, β\u003csub\u003e1\u003c/sub\u003e, β\u003csub\u003e2\u003c/sub\u003e ------ β\u003csub\u003ek\u003c/sub\u003e : is the coefficients\u003c/p\u003e \u003cp\u003eX\u003csub\u003e1\u003c/sub\u003e, X\u003csub\u003e2\u003c/sub\u003e,--------X\u003csub\u003ek\u003c/sub\u003e : are predictor variables.\u003c/p\u003e \u003cp\u003eP/(1-P): is the measure of odds, hence the ratio of P/(1-P) is the log of odds or the \u003cem\u003elogit\u003c/em\u003e of P.\u003c/p\u003e \u003cp\u003eWe estimate dichotomous logit for the dependent variables and considered 1%, 5%, and 10% of the significant levels for all statistical tests. All analyses have been carried out using STATA version 14.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cstrong\u003eTreatment-seeking behavior of ARI among children (0\u0026ndash;59 months) across the State/UTs in India from 2016 to 2021\u003c/strong\u003e \u003cp\u003eThe results indicate that there was a reduction in treatment-seeking behaviour of ARI among below 5 years children from NFHS-IV (78.10%) to NFHS-V (52.28%) in India (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The data from NFHS-IV indicates that the south region (88.21%) has the highest percentage of children with treatment-seeking behaviour for ARI, which has reduced to 53.45% in NFHS-V. The north-eastern region shows the lowest percentage (63.77%) of treatment-seeking behaviour of ARI in NFHS-IV, again which has decreased further to 48.61% in NFHS-V. However, the data from NFHS-V shows the Western region has the highest percentage of treatment-seeking behaviour for ARI among children at 62.60% and the Central region has the lowest one at 44.32%.\u003c/p\u003e \u003c/p\u003e \u003cp\u003eAll other States showed a decrease in treatment-seeking behaviour among U5 children except Chandigarh, Goa, and Ladakh. Chandigarh has shown an overall increase in treatment-seeking behaviour from NFHS-IV (80.89%) to NFHS-V (100%). In Goa, 100% of the U5 children showed treatment-seeking behaviour while experiencing ARI. Sikkim showed the highest reduction in treatment-seeking behaviour from 100% in NFHS-IV to 19.07% in NFHS-V. In NFHS-V, treatment-seeking behaviour is lowest in Nagaland (9.43%), Sikkim (19.07%), Mizoram (21.77%), Manipur (26.88%), and Tamil Nadu (32%).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTreatment-seeking behavior of ARI among children (0\u0026ndash;59 months) across the State/UTs in India by, NFHS IV and NFHS-V\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eState/UTs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNFHS-IV (2015-16)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNFHS-V (2019-21)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eWeighted %\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eWeighted %\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eA. North Region\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e84.56\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e47.69\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChandigarh\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDelhi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHaryana\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHimachal Pradesh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJammu And Kashmir\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePunjab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRajasthan\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUttarakhand\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e63.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLadakh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eB. Central Region\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e75.99\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e44.32\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChhattisgarh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMadhya Pradesh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUttar Pradesh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eC. East Region\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e71.15\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e59.21\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBihar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62.66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJharkhand\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOdisha\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWest Bengal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e64.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eD. Northeast Region\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e63.77\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e48.61\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArunachal Pradesh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAssam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eManipur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeghalaya\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e67.94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMizoram\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNagaland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSikkim\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTripura\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eE. West Region\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e86.98\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e62.60\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDadra And Nagar Haveli/Daman and Diu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e83.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGoa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGujarat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e61.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaharashtra\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e89.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eF. South Region\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e88.21\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e53.45\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAndaman And Nicobar Islands\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAndhra Pradesh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e51.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKarnataka\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e91.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKerala\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e96.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e69.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLakshadweep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePuducherry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e54.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTamil Nadu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTelangana\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIndia\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e78.10\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e52.28\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cb\u003eNote\u003c/b\u003e: \u003cem\u003eUTs: Union territory, Weighted %: Children suffering from ARI sought for any treatment, NA: Not available\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eDistribution of Sample who seek treatment of ARI with the background characteristics in 2016 and 2021\u003c/b\u003e:\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the distribution of U5 children with ARI in India according to their background characteristics in NFHS IV and NFHS-V. The distribution of U5 children with ARI across NFHS-IV and NFHS-V was similar. Around 76% of the children in NFHS-IV and 77.77% of the children in NFHS-V resided in the rural area. 27.96% of the Children belonged to the poorest and there is a gradual decline in the percentage of the children belonging to the higher wealth index with 12.43% in the richest. A similar distribution is seen in NFHS-V where 27.80% belonged to the poorest and 13.61% belonged to the richest quintile.\u003c/p\u003e \u003cp\u003e87.28% of children in NFHS-IV and 82.76% in NFHS-V belonged to a household with a male head and 56.23% of the children in NFHS-IV and 56.15% of the children in NFHS-V were boys. 25.30% of the children in NFHS-IV and 26.15% in NFHS-V belonged to households with less than 4 members, while others belonged to households with 5 members or more. A major percentage of the children belonged to OBC, and others were distributed among SC, ST and other social status. The percentage of children who belonged to a family who stated distance problem were 40.37% in NFHS-IV and 30.74% in NFHS-V and those who stated transport problem were 38.68% in NFHS-IV and 28.73% in NFHS-V. The percentage of children whose mothers were literate was 70.98% in NFHS-IV and 78.34% in NFHS-V and with mass media exposure was 27.52% in NFHS-IV and 28.74% in NFHS-V. The highest percentage of children experiencing ARI lived in the Central Region and the lowest percentage of children lived in the Northeastern region both in NFHS-IV and NFHS-V. 60.57% of the children in NFHS-IV and 61.13% in NFHS-V belonged to EAG States. The percentage of children decreased with an increase in the age.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTreatment-seeking behavior of ARI among children (0\u0026ndash;59 months) with the background characteristics in India by, NFHS IV and NFHS-V\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBackground characteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eNFHS-IV (2015-16)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eNFHS-V (2019-20)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eN\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e%\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eN\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003e%\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlace of Resident\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eUrban\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,567\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1378\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e22.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eRural\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4,962\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e76.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4820\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e77.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHousehold Wealth Index\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePoorest\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,825\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1723\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e27.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePoorer\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,495\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1472\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMiddle\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,275\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e18.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eRicher\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e993\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eRichest\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e811\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e844\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender of the Head of the Household\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMale\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5,699\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e87.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e82.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eFemale\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e830\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHousehold Size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e\u0026le;\u0026thinsp;4 Members\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,652\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1620\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e5 and more members\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4,877\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e74.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4577\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e73.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReligious group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eHindu\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4,965\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e76.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4927\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e79.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNon-Hindu\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,564\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1271\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e20.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSocial Group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSC\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,559\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1551\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e25.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eST\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e556\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e532\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eOBC\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,859\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2676\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e43.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eOthers\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,556\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1438\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDistance to health facility\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNo/not a big problem\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,893\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e59.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4293\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e69.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBig problem\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,636\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e30.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHaving to take transport\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNo/not a big problem\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4,004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e61.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e71.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBig problem\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,525\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1781\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e28.73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMother's literacy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eIlliterate\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,895\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1343\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e21.66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eliterate\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4,635\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4855\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e78.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMass Media Exposure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNo\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,797\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1781\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e28.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eYes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4,733\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e72.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4416\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e71.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChildren ever born to women\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eOne child\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,900\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1853\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e29.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTwo Children\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e36.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMore than 2 children\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,398\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e33.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge of the child\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e0\u0026ndash;11 Months\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,545\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1489\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e12\u0026ndash;23 Months\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,578\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1429\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e24\u0026ndash;35 Months\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,233\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e19.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e36 to 47 Months\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e48 to 59 Months\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e957\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e983\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e15.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex of the Child\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBoy\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,671\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3480\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e56.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGirl\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,858\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2718\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e43.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegion in India\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNorth\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e921\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e893\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCentral\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1945\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e31.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eEast\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,705\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1816\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e29.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNortheast\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eWest\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e630\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e676\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSouth\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e729\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e664\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eState\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNon EAG\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,575\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2409\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e38.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eEAG\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,955\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3789\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e61.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e6,529\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e100.00\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e6198\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e100.00\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003eNote\u003c/b\u003e: \u003cem\u003eN: Number, %: column percentage, EAG: Empowered action group\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003ePrevalence of treatment-seeking behavior of ARI among children (0\u0026ndash;59 months) with the background characteristics in India\u003c/b\u003e:\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the prevalence of treatment-seeking behaviour among below five children with ARI in India by NFHS-IV and NFHS-V based on their background characteristics. There is a decrease in the prevalence of treatment-seeking behaviour across all the background characteristics from NFHS-IV to NFHS-V.\u003c/p\u003e \u003cp\u003eThe prevalence of treatment-seeking behaviour among urban children (86.21%) is significantly more than rural children (75.55%). However, no significant difference in prevalence is observed among the children based on the place of residence in NFHS-V. Households with a female gender as the head (56.37%) had higher treatment-seeking behaviour compared to those with a male head (51.44%) in NFHS-V. However, there were no significant differences in prevalence based on the gender of the head of the household in NFHS-IV. The prevalence of treatment-seeking behaviour is significantly highest among the Richest (90.05%) in NFHS-IV and among the Richer (55.87%) in NFHS-V and the prevalence is lowest among the Poorest (69.33%) in NFHS-IV and Richest (48.7%) in NFHS-V. It was found that the difference in prevalence was higher among the different quintiles of wealth index in NFHS-IV compared to NFHS-V, where the difference in prevalence was not much.\u003c/p\u003e \u003cp\u003eThe prevalence of treatment-seeking behaviour of ARI does not significantly differ among children based on household size, and religious group in both NFHS-IV and NFHS-V. The prevalence is significantly higher among male children than female children in both the NFHS-IV and NFHS-V. The prevalence among different social groups significantly differed in NFHS-IV with the lowest prevalence among the ST groups. However, the prevalence among different social groups does not significantly differ in NFHS-V.\u003c/p\u003e \u003cp\u003eThose with distance problems and transport problems had a significantly lower prevalence of treatment-seeking behaviour in both the study. Children with literate mothers and those with mass media exposure had higher treatment-seeking behaviour in NFHS-IV. However, no significant difference in prevalence is found based on mothers\u0026rsquo; literacy and Mass Media Exposure in NFHS-V. The prevalence of treatment-seeking behaviour was significantly highest among 12\u0026ndash;23 months old children (56.07%), followed by 0\u0026ndash;11 months (52.9%), 48\u0026ndash;59 months (52%), 24\u0026ndash;35 months (49.86%) and 36\u0026ndash;47 months (49.43%) in NFHS-V. However, there were no significant differences in prevalence based on age in NFHS-IV.\u003c/p\u003e \u003cp\u003eThere was no significant difference in prevalence among U5 children based on the number of children born to women in NFHS-V. However, there was a significant difference in prevalence in NFHS-IV, where the prevalence decreased with the increase in the number of children.\u003c/p\u003e \u003cp\u003eThe highest percentage of children with treatment exposure belonged to the South Region (88.22%) in NFHS-IV and to the West Region (62.61%) in NFHS-V. The percentage of children with treatment exposure is lowest in Northeast Region (63.77%) in NFHS-IV and Central Region (44.44%) in NFHS-V. Non- EAG States had a higher percentage of children (83.26% in NFHS-IV and 56.88% in NFHS-V) with treatment-seeking behaviour compared to EAG States (74.75% in NFHS-IV and 49.36% in NFHS-V).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 04\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrevalence of treatment-seeking behavior of ARI among children (0\u0026ndash;59 months) with the background characteristics in India by, NFHS IV and NFHS-V\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBackground Variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNFHS-IV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNFHS-V\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ePrevalence N (%)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ePrevalence N (%)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlace of Resident\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eχ2\u0026thinsp;=\u0026thinsp;79.44, p\u0026thinsp;\u0026lt;\u0026thinsp;.001*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eχ2\u0026thinsp;=\u0026thinsp;1.04, p\u0026thinsp;=\u0026thinsp;.308\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eUrban\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1351 (86.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e737 (53.49)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eRural\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3748 (75.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2503 (51.94)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHousehold Wealth Index\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eχ2\u0026thinsp;=\u0026thinsp;193.27, p\u0026thinsp;\u0026lt;\u0026thinsp;.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eχ2\u0026thinsp;=\u0026thinsp;13.69, p\u0026thinsp;=\u0026thinsp;.008*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1266 (69.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e872 (50.64)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1122 (75.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e798 (54.22)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1026 (80.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e605 (51.81)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRicher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e955 (85.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e555 (55.87)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRichest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e731 (90.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e411 (48.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender of the head of the Household\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eχ2\u0026thinsp;=\u0026thinsp;2.13, p\u0026thinsp;=\u0026thinsp;.145\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eχ2\u0026thinsp;=\u0026thinsp;8.63, p\u0026thinsp;=\u0026thinsp;.003*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMale\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4467 (78.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2638 (51.44)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eFemale\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e632 (76.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e602 (56.37)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHousehold Size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eχ2\u0026thinsp;=\u0026thinsp;0.78, p\u0026thinsp;=\u0026thinsp;.379\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eχ2\u0026thinsp;=\u0026thinsp;1.09, p\u0026thinsp;=\u0026thinsp;.297\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e4 Members\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1303 (78.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e865 (53.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e5 and more members\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3797 (77.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2375 (51.89)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReligious group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eχ2\u0026thinsp;=\u0026thinsp;0.38, p\u0026thinsp;=\u0026thinsp;.541\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eχ2\u0026thinsp;=\u0026thinsp;0.22, p\u0026thinsp;=\u0026thinsp;.642\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHindu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3869 (77.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2569 (52.14)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Hindu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1231 (78.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e672 (52.86)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSocial Group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eχ2\u0026thinsp;=\u0026thinsp;21.71, p\u0026thinsp;\u0026lt;\u0026thinsp;.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eχ2\u0026thinsp;=\u0026thinsp;6.07, p\u0026thinsp;=\u0026thinsp;.109\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSC\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1225 (78.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e820 (52.88)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eST\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e391 (70.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e256 (48.02)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eOBC\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2243 (78.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1387 (51.85)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eOthers\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1240 (79.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e777 (54.04)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDistance to health facility\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eχ2\u0026thinsp;=\u0026thinsp;29.24, p\u0026thinsp;\u0026lt;\u0026thinsp;.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eχ2\u0026thinsp;=\u0026thinsp;6.47, p\u0026thinsp;=\u0026thinsp;.011*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNo/not a big problem\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3129 (80.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2291 (53.36)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBig problem\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1970 (74.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e950 (49.86)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHaving to take transport\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eχ2\u0026thinsp;=\u0026thinsp;42.73, p\u0026thinsp;\u0026lt;\u0026thinsp;.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eχ2\u0026thinsp;=\u0026thinsp;15.93, p\u0026thinsp;\u0026lt;\u0026thinsp;.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNo/not a big problem\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3234 (80.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2380 (53.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBig problem\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1866 (73.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e860 (48.29)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMother's literacy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eχ2\u0026thinsp;=\u0026thinsp;47.94, p\u0026thinsp;\u0026lt;\u0026thinsp;.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eχ2\u0026thinsp;=\u0026thinsp;1.89, p\u0026thinsp;=\u0026thinsp;.169\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIlliterate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1375 (72.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e680 (50.62)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eliterate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3725 (80.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2561 (52.75)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMass Media Exposure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eχ2\u0026thinsp;=\u0026thinsp;97.55, p\u0026thinsp;\u0026lt;\u0026thinsp;.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eχ2\u0026thinsp;=\u0026thinsp;1.25, p\u0026thinsp;=\u0026thinsp;.265\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1256 (69.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e951 (53.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3843 (81.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2289 (51.84)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChildren ever born to women\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eχ2\u0026thinsp;=\u0026thinsp;55.11, p\u0026thinsp;\u0026lt;\u0026thinsp;.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eχ2\u0026thinsp;=\u0026thinsp;0.97, p\u0026thinsp;=\u0026thinsp;.618\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOne child\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1563 (82.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e984 (53.11)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTwo Children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1780 (79.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1167 (51.57)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMore than 2 children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1757 (73.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1090 (52.33)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge of the child\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eχ2\u0026thinsp;=\u0026thinsp;8.18, p\u0026thinsp;=\u0026thinsp;.085\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eχ2\u0026thinsp;=\u0026thinsp;14.74, p\u0026thinsp;=\u0026thinsp;.005*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u0026ndash;11 Months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1213 (78.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e788 (52.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u0026ndash;23 Months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1258 (79.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e801 (56.07)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24\u0026ndash;35 Months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e969 (78.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e595 (49.86)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e36 to 47 Months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e942 (77.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e546 (49.43)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e48 to 59 Months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e718 (75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e511 (52)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex of the Child\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eχ2\u0026thinsp;=\u0026thinsp;25.62, p\u0026thinsp;\u0026lt;\u0026thinsp;.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eχ2\u0026thinsp;=\u0026thinsp;6.01, p\u0026thinsp;=\u0026thinsp;.014*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBoy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2951 (80.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1867 (53.66)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGirl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2149 (75.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1373 (50.53)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegion in India\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eχ2\u0026thinsp;=\u0026thinsp;166.35, p\u0026thinsp;\u0026lt;\u0026thinsp;.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eχ2\u0026thinsp;=\u0026thinsp;121.96, p\u0026thinsp;\u0026lt;\u0026thinsp;.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e779 (84.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e426 (47.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1828 (75.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e862 (44.33)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1213 (71.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1075 (59.21)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNortheast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88 (63.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99 (48.62)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e548 (86.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e423 (62.61)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e643 (88.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e355 (53.45)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eState\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eχ2\u0026thinsp;=\u0026thinsp;66.09, p\u0026thinsp;\u0026lt;\u0026thinsp;.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eχ2\u0026thinsp;=\u0026thinsp;33.36, p\u0026thinsp;\u0026lt;\u0026thinsp;.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon EAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2143 (83.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1370 (56.88)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2956 (74.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1870 (49.36)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cb\u003eNote\u003c/b\u003e: \u003cem\u003eχ2\u0026thinsp;=\u0026thinsp;Chi-square test (applied for each variable), *=p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (Significance), CI: Confidence interval, SC: Scheduled Caste, ST: Scheduled Tribe, OBC: Other Backward Caste; EAG: Empowered Action Group\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eDeterminants of treatment-seeking behaviour of ARI among children in India (2016 and 2021):\u003c/h3\u003e\n\u003cp\u003eThe multivariable binary logistic regression analysis results (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) reveal that in NFHS-IV, factors such as the place of residence, household wealth index, gender of the head of the household, mass media exposure, age, sex of the child and the regions showed significant association with the treatment-seeking behaviour of below 5 children. However, in NFHS-V, factors such as gender of the head of the household, the necessity to take transport, age, sex of the child, regions, and the EAG Status of States showed significant association with the treatment-seeking behaviour of below 5 children.\u003c/p\u003e \u003cp\u003eChildren living in rural areas had significantly 0.85 times lower odds (AOR:0.85; 95% CI: 0.72\u0026ndash;1.01) of having treatment-seeking behaviour compared to those living in urban areas in NFHS-IV. Also, in NFHS-IV the odds of treatment-seeking behaviour significantly increased with the increase in wealth index across all the categories compared to the very poor household in the same time. However, no significant association was found for place of residence and wealth index in NFHS-V. Children belonging to households with female heads had 1.32 times (AOR: 1.32; 95% CI: 1.15\u0026ndash;1.51) higher odds in NFHS-V of having treatment-seeking behaviour of ARI compared to those with male heads. In NFHS-V, children whose parents reported problems in availing transport had 0.87 (AOR: 0.87; 95% CI: 0.75-1) times lower odds of having treatment-seeking behaviour than those with no transport problem. However, this trend was not observed in NFHS-IV, where the necessity to take, transport was found to have no significant association. Interestingly, the mother\u0026rsquo;s literacy was found to have no significant association with treatment-seeking behaviour in both rounds (NFHS-IV and NFHS-V). Mass Media Exposure was significantly associated with NFHS-IV, where those with exposure had 1.23 (AOR: 1.23; 95% CI: 1.06\u0026ndash;1.43) times higher odds of treatment-seeking behaviour than those who had no exposure. However, no significant association of Mass Media exposure was found in NFHS-V. In NFHS-IV, Children who were in the age group of 48\u0026ndash;59 months had 0.76 (AOR: 0.76; 95% CI: 0.63\u0026ndash;0.92) times lower odds of having treatment-seeking behaviour compared to those aged 0\u0026ndash;11 months, and in NFHS-V, Children who were in the age group of 36\u0026ndash;47 months had 0.83 (AOR: 0.83; 95% CI: 0.7\u0026ndash;0.97) times lower odds of having treatment seeking behaviour compared to those aged 0\u0026ndash;11 months. Both in NFHS-IV and NFHS-V, Girl Child had a significantly lower odd (AOR: 0.75; 95% CI: 0.67\u0026ndash;0.93) times lower in NFHS-IV and 0.88 (AOR:0.88; 95% 0.79\u0026ndash;0.97) times lower in NFHS-V) of having treatment seeking behaviour compared to boy child. In NFHS-IV, children belonging to the Central region had 0.75 (AOR:0.75; 95% CI: 0.6\u0026ndash;0.93) times lower odds, the East Region had 0.59 (AOR: 0.59; 95% CI: 0.48\u0026ndash;0.74) times lower odds, the Northeast Region had 0.33 (AOR: 0.33; 95% CI: 0.26\u0026ndash;0.43) times lower odds of having treatment seeking behaviour compared to children belonging to the North Region. However, in NFHS-V, children belonging to the Central region had significantly 0.75 (AOR: 0.75; 95% CI: 0.6\u0026ndash;0.93) times lower odds, the East Region had significantly 1.56 (AOR: 1.56; 95% CI: 1.29\u0026ndash;1.88) times higher odds and the West Region had significantly 1.21 (AOR:1.21; 95% CI: 0.96\u0026ndash;1.52) times higher odds of having treatment seeking behaviour compared to children belonging to the North Region. In NFHS-V, children belonging to EAG States had significantly 0.81 (AOR: 0.81; 95% CI: 0.67\u0026ndash;0.99) times lower odds of having treatment-seeking behaviour of ARI compared to those belonging to Non EAG States. However, the EAG status of the State was not significant in determining the treatment-seeking behaviour in NFHS-IV.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 05\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLogistic regression model assessing the factors associated with treatment seeking behavior of ARI among children (0\u0026ndash;59 Months) in India, by NFHS IV and V\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBackground Characteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNFHS-IV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNFHS-V\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAOR 95% CI\u003c/p\u003e \u003cp\u003e[Lower-Upper]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAOR 95% CI\u003c/p\u003e \u003cp\u003e[Lower-Upper]\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlace of Resident\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.85 (0.72\u0026ndash;0.97) *\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.13 (0.98\u0026ndash;1.31)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHousehold Wealth Index\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery Poor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.25 (1.07\u0026ndash;1.47) **\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.15 (1-1.33)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.45 (1.2\u0026ndash;1.76) ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.11 (0.94\u0026ndash;1.32)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRicher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.54 (1.22\u0026ndash;1.94) ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.16 (0.95\u0026ndash;1.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRichest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.06 (1.55\u0026ndash;2.74) ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.96 (0.77\u0026ndash;1.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender of the head of the Household\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.05 (0.88\u0026ndash;1.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.32 (1.15\u0026ndash;1.51) ***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHousehold Size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4 Members\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5 and more members\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.04 (0.9\u0026ndash;1.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.97 (0.85\u0026ndash;1.09)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReligious group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHindu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Hindu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.15 (0.99\u0026ndash;1.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.05 (0.92\u0026ndash;1.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSocial Group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eST\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.85 (0.69\u0026ndash;1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.92 (0.77\u0026ndash;1.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOBC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.94 (0.8\u0026ndash;1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.07 (0.93\u0026ndash;1.23)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.84 (0.7\u0026ndash;1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.85\u0026ndash;1.17)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDistance to health facility\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo/not a big problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBig problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.98 (0.83\u0026ndash;1.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.04 (0.9\u0026ndash;1.19)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHaving to take transport\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo/not a big problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBig problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.97 (0.82\u0026ndash;1.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.87 (0.75\u0026ndash;0.97) *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMother's literacy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIlliterate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eliterate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.07 (0.93\u0026ndash;1.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.06 (0.93\u0026ndash;1.22)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMass Media Exposure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.23 (1.06\u0026ndash;1.43) **\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9 (0.79\u0026ndash;1.03)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChildren ever born to women\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOne children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTwo Children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.91 (0.78\u0026ndash;1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.05 (0.92\u0026ndash;1.19)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMore than 2 children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.79 (0.67\u0026ndash;0.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.12 (0.97\u0026ndash;1.29)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge of the child\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u0026ndash;11 Months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u0026ndash;23 Months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.96 (0.81\u0026ndash;1.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.1 (0.95\u0026ndash;1.28)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24\u0026ndash;35 Months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.88 (0.74\u0026ndash;1.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9 (0.77\u0026ndash;1.06)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e36 to 47 Months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.93 (0.77\u0026ndash;1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.83 (0.7\u0026ndash;0.97) *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e48 to 59 Months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.76 (0.63\u0026ndash;0.92) **\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.91 (0.77\u0026ndash;1.07)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex of the Child\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBoy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGirl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.75 (0.67\u0026ndash;0.84) ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.88 (0.79\u0026ndash;0.97) **\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegion in India\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.75 (0.6\u0026ndash;0.93) **\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.91 (0.76\u0026ndash;1.09)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.59 (0.48\u0026ndash;0.74) ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.56 (1.29\u0026ndash;1.88) ***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNortheast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.33 (0.26\u0026ndash;0.43) ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.03 (0.82\u0026ndash;1.29)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.06 (0.74\u0026ndash;1.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.42 (1.12\u0026ndash;1.81) **\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.1 (0.79\u0026ndash;1.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.21 (0.96\u0026ndash;1.52)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eState\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon EAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.93 (0.74\u0026ndash;1.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.81 (0.67\u0026ndash;0.98) *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCons\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNumber of obs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6,529\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6,198\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePseudo R2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0532\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0172\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLR chi2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e402.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e145.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eProb\u0026thinsp;\u0026gt;\u0026thinsp;chi2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLog likelihood =\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-3585.6679\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-4166.996\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cb\u003eNote\u003c/b\u003e: \u003cem\u003eAOR: Adjusted Odds Ratio, Ref: Reference Category, CI: Confidence interval, ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, *p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, SC: Scheduled Caste, ST: Scheduled Tribe, OBC: Other Backward Caste, EAG\u0026thinsp;=\u0026thinsp;Empowered action group\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe current study examines the prevalence and determinants of treatment-seeking behaviour among children infected by ARI in India. The last two rounds of NFHS data were analysed with the help of STATA 14 software. The study revealed that the prevalence of treatment-seeking behaviours among children suffering from ARI has decreased from 78 percent in 2016 to 52 percent in 2021 in India. Phase 2 of the NFHS-5 survey, conducted in 14 states/UTs, took place from 2nd January 2020 to 30th April 2021 [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The country was under total or partial lockdown during this period. Studies have shown a decrease in the number of people seeking medical treatment for acute health problems during the lockdown [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Therefore, the lockdown restriction and fear of contracting COVID-19 infection decline in seeking treatment for ARI [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA multilevel logistic regression model has been employed to identify the possible determinants of treatment-seeking behaviour. Our study found that children from rural geography have significantly lower odds of seeking treatment compared to urban part. One possible reason is that due to higher air pollution in urban areas, the incidence is high. Therefore, treatment-seeking behaviour is also high in urban residents as compared to rural residents [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Our study highlighted that an increase in household wealth quantile status significantly improves treatment-seeking behaviour. This finding aligns with a study conducted in Indonesia, which revealed that children from wealthy families were less vulnerable to ARI incidence [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The findings from the present research indicate that children U5 belonging to households with female heads had higher odds of having treatment-seeking behaviour compared to those with male heads. The finding resonates with the studies conducted in Tanzania [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] and sub-Saharan Africa [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The possible explanation is that households with female heads may not encounter the challenge of obtaining permission to seek care, which is a common barrier to healthcare utilization among women and children [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Another probable explanation is that women who are heads of households tend to allocate the available resources they control towards prioritizing their children's health, thereby increasing their health-seeking behaviour [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The present study also indicated that children, whose parents reported taking transport is a problem had lower odds of having treatment-seeking behaviour than those with no transport problem. Previous research suggested that the usage of healthcare services is adversely affected by factors such as the significant distance to medical facilities, the absence of transportation options, and the subpar quality of roads [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan additionalcitationids=\"CR36\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Our research demonstrates that mothers who are exposed to the media are more likely to seek healthcare for their children compared to mothers who have not been exposed to the media. This finding aligns with studies conducted in West Bengal, India [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. One potential explanation is that exposure to mass media exposes people to healthcare information, which improves their behaviour in seeking healthcare. Evidence from the previous study also suggests that exposure to the media plays a crucial role in promoting healthy behaviours [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Additionally, our study indicates that children from EAG States were significantly less likely to seek treatment for ARI compared to those from non-EAG states. In India, there is a significant disparity in the accessibility and availability of healthcare between public health facilities in EAG and non-EAG states [\u003cspan additionalcitationids=\"CR39\" citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. The possible reason for the lower treatment-seeking behavior in EAG states, which are mostly located in the northern and central regions, is the high percentage of the population living below the poverty line and a high proportion of women with limited access to education and mass media [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eLimitation of the Study\u003c/h2\u003e \u003cp\u003eThe present study had some limitations. Firstly, ARI was classified as per the signs and symptoms reported by the children's mothers, without confirmation from medical professionals. Secondly, mothers were asked to recall their children's symptoms from the past 2 weeks of the survey, which may raise the possibility of recall bias. Thirdly, a cross-sectional design prevented the establishment of a cause-and-effect relationship.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eARI is the major cause of U5 mortality and morbidity in low-income and developing countries like India. India has already set its goal to achieve the SDGs target to reduce U5 child mortality by 25/1000 live births in 2030 (SDGs) which is 42/1000 live births as per the NFHS-V. The current study aims to assess the prevalence and determinants of treatment-seeking behaviour among children infected by ARI in India. the study highlighted the the treatment-seeking behaviour among children infected with ARI has been decreased from 2016 to 2019. Although COVID-19 is a likely cause, it remains a significant public health issue in India. The present study also identified the determinants of treatment-seeking behaviour. The place of residence, household wealth quantile, gender of the head of a household, challenges related to transport, and mass media exposure were found to be significantly associated with treatment-seeking behaviour. Based on these findings, the study recommends that public health programs should focus on the indicators to improve treatment-seeking behaviour among children, and also can help to reduce child morbidity and mortality due to ARI in India. Additionally, these efforts may contribute to reducing the risk of ARI and achieving the country's SDG target by 2030.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eAOR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAdjusted Odds Ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eARI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAcute Respiratory Infections\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCEB\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCensus Enumeration Blocks\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eDHS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDemographic and Health Survey\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eEAG\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEmpowered action group\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eGBD\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGlobal Burden of Disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eLRTI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLower Respiratory Tract Infections\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eNFHS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNational Family Health Survey\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eOBC\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOther Backward Caste\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003ePSU\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePrimary Sampling Unit\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eSC\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eScheduled Caste\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eSDGs\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSustainable Development Goals\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eST\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eScheduled Tribe\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eU5\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eUnder-five\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eUN\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eUnited Nations\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eWHO\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eWorld Health Organization\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthorship contribution statement:\u003c/strong\u003e All authors contributed significantly to this paper. The research idea, conceptualization, and study design: KG, ASC; Collected data and analyzed the data: KG \u0026amp; ASC; Gathered material and wrote the manuscript: KG, ASC, BH \u0026amp; SP; Refined and finalized the manuscript: KG, ASC, BH \u0026amp; SP.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eThis research did not receive a specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConflicts of interest/Competing interests:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eNot applicable (as it is based on secondary data)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics approval:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eThere is no formal ethics approval required for this particular study since the study is based on secondary data and the survey data is available in the public domain.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eHuman Ethics and Consent to Participate declarations:\u003c/em\u003e\u003c/strong\u003e Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number:\u003c/strong\u003e Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material:\u003c/strong\u003e The data of a particular study is available in the public domain and can be extracted from: https://dhsprogram.com/Data/\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eAcknowledgment:\u003c/strong\u003e\u0026nbsp; We sincerely thank to International Institute for Population Sciences (IIPS), Mumbai for providing the data of the NFHS project. We also thank all reviewers and the editorial board of this journal.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConsent for publication:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e We confirm that consent for publication has been obtained from all authors\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWorld Health Organization (2022) Facts Sheets: Child mortality (under 5 years). Available at: https://www.who.int/news-room/fact-sheets/detail/levels-and-trends-in-child-under-5-mortality-in-2020 [Accessed 29 December 2024].\u003c/li\u003e\n\u003cli\u003eTroeger C, Blacker B, Khalil IA, Rao PC, Cao J, Zimsen SR, Albertson SB, Deshpande A, Farag T, Abebe Z and Adetifa IM (2018) Estimates of the global, regional, and national morbidity, mortality, and aetiologies of lower respiratory infections in 195 countries, 1990\u0026ndash;2016: A systematic analysis for the Global Burden of Disease Study 2016. \u003cem\u003eThe Lancet Infectious Diseases\u003c/em\u003e 18(11), 1191-1210. Available at: http://dx.doi.org/10.1016/.\u003c/li\u003e\n\u003cli\u003eNaghavi M, Abajobir AA, Abbafati C, Abbas KM, Abd-Allah F, Abera SF, Aboyans V, Adetokunboh O, Afshin A, Agrawal A and Ahmadi A (2017) Global, regional, and national age-sex specific mortality for 264 causes of death, 1980-2016: A systematic analysis for the Global Burden of Disease Study 2016. \u003cem\u003eThe Lancet\u003c/em\u003e 390(10100), 1151-1210. Available from: https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(17)32152-9/fulltext?rss%3Dyes=\u003c/li\u003e\n\u003cli\u003eWang H, Bhutta ZA, Coates MM, Coggeshall M, Dandona L, Diallo K, Franca EB, Fraser M, Fullman N, Gething PW and Hay SI. (2016) Global, regional, national, and selected subnational levels of stillbirths, neonatal, infant, and under-5 mortality, 1980\u0026ndash;2015: A systematic analysis for the Global Burden of Disease Study 2015. \u003cem\u003eThe Lancet\u003c/em\u003e 388(10053), 1725-1774. Available at: https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(16)31575-6/fulltext.\u003c/li\u003e\n\u003cli\u003eSelvaraj K, Chinnakali P, Majumdar A and Krishnan IS (2014) Acute respiratory infections among under-5 children in India: A situational analysis. \u003cem\u003eJournal of Natural Science, Biology, and Medicine\u003c/em\u003e 5(1), 15. Available at: https://doi.org/10.4103/0976-9668.127275.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization \u0026amp; UNICEF (1999) Management of Childhood Illness in Developing Countries: Rationale for an integrated strategy. IMCI Information (WHO/CHS/CAH/98.1 A Rev. 1), WHO, Geneva, 3.\u003c/li\u003e\n\u003cli\u003eSeidu AA, Dickson KS, Ahinkorah BO, Amu H, Darteh EKM and Kumi-Kyereme A (2019) Prevalence and determinants of acute lower respiratory infections among children under-five years in sub\u0026ndash;Saharan Africa: evidence from demographic and health surveys. \u003cem\u003eSSM-Population Health\u003c/em\u003e 8, 100443. Available at: https://doi.org/10.1016/j.ssmph.2019.100443.\u003c/li\u003e\n\u003cli\u003eWalker CL, Rudan I, Liu L, Nair H, Theodoratou E, Bhutta ZA, O\u0026apos;Brien KL, Campbell H and Black RE (2013) Global burden of childhood pneumonia and diarrhoea. \u003cem\u003eThe Lancet\u003c/em\u003e 381(9875), 1405-1416. Available at: https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(13)60222-6/fulltext.\u003c/li\u003e\n\u003cli\u003eFrese T, Klauss S, Herrmann K and Sandholzer H (2011) Children and adolescents as patients in general practice-the reasons for encounter. \u003cem\u003eJournal of Clinical Medicine Research\u003c/em\u003e 3(4), 177. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC3194013/\u003c/li\u003e\n\u003cli\u003eKumar SG, Majumdar A, Kumar V, Naik BN, Selvaraj K and Balajee K (2015) Prevalence of acute respiratory infection among under-five children in urban and rural areas of Puducherry, India. \u003cem\u003eJournal of Natural Science, Biology, and Medicine\u003c/em\u003e 6(1), 3. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC4367064/\u003c/li\u003e\n\u003cli\u003eVashishtha VM (2010) Current status of tuberculosis and acute respiratory infections in India: Much more needs to be done! \u003cem\u003eIndian Pediatrics\u003c/em\u003e 88-89. Available at: https://www.indianpediatrics.net/jan2010/88.pdf.\u003c/li\u003e\n\u003cli\u003eKurskaya O, Ryabichenko T, Leonova N, Shi W, Bi H, Sharshov K, Kazachkova E, Sobolev I, Prokopyeva E, Kartseva T and Alekseev A (2018) Viral etiology of acute respiratory infections in hospitalized children in Novosibirsk City, Russia (2013-2017). \u003cem\u003ePLoS One\u003c/em\u003e 13(9): e0200117. https://doi.org/10.1371/journal.pone.0200117\u003c/li\u003e\n\u003cli\u003eRamaekers K, Keyaerts E, Rector A, Borremans A, Beuselinck K, Lagrou K, Van Ranst M (2017) Prevalence and seasonality of six respiratory viruses during five consecutive epidemic seasons in Belgium. \u003cem\u003eJournal of Clinical Virology\u003c/em\u003e 94, 72-78. Available at: https://doi.org/10.1016/j.jcv.2017.07.011.\u003c/li\u003e\n\u003cli\u003eKrishnan A, Amarchand R, Gupta V, Lafond KE, Suliankatchi RA, Saha S, Rai S, Misra P, Purakayastha DR, Wahi A and Sreenivas V (2015) Epidemiology of acute respiratory infections in children-preliminary results of a cohort in a rural north Indian community. \u003cem\u003eBMC Infectious Diseases\u003c/em\u003e 15(1), 462. Available from: https://link.springer.com/article/10.1186/s12879-015-1188-1\u003c/li\u003e\n\u003cli\u003eRomieu I, Samet JM, Smith KR and Bruce N (2002) Outdoor air pollution and acute respiratory infections among children in developing countries. \u003cem\u003eJournal of Occupational and Environmental Medicine\u003c/em\u003e 44(7), 640-649. Available at: https://journals.lww.com/joem/abstract/2002/07000/outdoor_air_pollution_and_acute_respiratory.10.aspx.\u003c/li\u003e\n\u003cli\u003eAlamgir NI, Naheed A and Luby SP. (2010) Coping strategies for financial burdens in families with childhood pneumonia in Bangladesh. \u003cem\u003eBMC Public Health\u003c/em\u003e 10(1), 622. Available from: https://link.springer.com/article/10.1186/1471-2458-10-622\u003c/li\u003e\n\u003cli\u003ePeasah SK, Purakayastha DR, Koul PA, Dawood FS, Saha S, Amarchand R, Broor S, Rastogi V, Assad R, Kaul KA and Widdowson MA (2015) The cost of acute respiratory infections in Northern India: a multi-site study. \u003cem\u003eBMC Public Health\u003c/em\u003e 15, 1-9. Available at: https://link.springer.com/article/10.1186/s12889-015-1685-6\u003c/li\u003e\n\u003cli\u003eShaikh BT and Hatcher J (2005) Health seeking behaviour and health service utilization in Pakistan: Challenging the policy makers. \u003cem\u003eJournal of Public Health (Oxford)\u003c/em\u003e 27(1), 49-54. Available at: https://doi.org/10.1093/pubmed/fdh207\u003c/li\u003e\n\u003cli\u003ePrakash LK (2014) Acute respiratory infection among children and health seeking behaviour in India. \u003cem\u003eInternational Journal of Scientific and Research Publications\u003c/em\u003e 4(11), 1.\u003c/li\u003e\n\u003cli\u003eAbdulkadir MB, Abdulkadir ZA , and Johnson WBR (2016) An analysis of national data on care-seeking behaviour by parents of children with suspected pneumonia in Nigeria. \u003cem\u003eSouth African Journal of Child Health\u003c/em\u003e 10(1), 92-95. Available from: https://www.ajol.info/index.php/sajchh/article/view/133695\u003c/li\u003e\n\u003cli\u003eSultana M, Sarker AR, Sheikh N, Akram R, Ali N, Mahumud RA and Alam NH (2019) Prevalence, determinants and health care-seeking behavior of childhood acute respiratory tract infections in Bangladesh. \u003cem\u003ePloS One\u003c/em\u003e 14(1), e0210433. Available at: https://doi.org/10.1371/journal.pone.0210433.\u003c/li\u003e\n\u003cli\u003eInternational Institute for Population Sciences. (2021) National Family Health Survey (NFHS-5), 2019-21, India Fact Sheet. Mumbai: IIPS. Available from: http://rchiips.org/nfhs/factsheet_NFHS-4.shtml\u003c/li\u003e\n\u003cli\u003ePaulson KR, Kamath AM, Alam T, Bienhoff K, Abady GG, Abbas J, Abbasi-Kangevari M, Abbastabar H, Abd-Allah F, Abd-Elsalam SM and Abdoli A (2021) Global, regional, and national progress towards Sustainable Development Goal 3.2 for neonatal and child health: all-cause and cause-specific mortality findings from the Global Burden of Disease Study 2019. \u003cem\u003eThe Lancet\u003c/em\u003e 398(10303), 870-905. Available at: https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(21)01207-1/fulltext?faodatalab=2021-08-18-1.\u003c/li\u003e\n\u003cli\u003eChandwani H and Pandor JJ (2015) Healthcare-seeking behavior of mothers regarding their child in a tribal community of Gujarat, India. \u003cem\u003eEpidemiology\u003c/em\u003e 7(1), 990. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC4455300/\u003c/li\u003e\n\u003cli\u003eLiu L, Johnson HL, Cousens S, Perin J, Scott S, Lawn JE, Rudan I, Campbell H, Cibulskis R, Li M and Mathers C (2012) Global, regional, and national causes of child mortality: An updated systematic analysis for 2010 with time trends since 2000. \u003cem\u003eThe Lancet\u003c/em\u003e 379(9832), 2151-2161. Available from: https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(12)60560-1/abstract\u003c/li\u003e\n\u003cli\u003eVarghese JS and Muhammad T (2023) Prevalence, potential determinants, and treatment-seeking behavior of acute respiratory infection among children under age five in India: Findings from the National Family Health Survey, 2019-21. \u003cem\u003eBMC Pulmonary Medicine\u003c/em\u003e 23(1), 195. Available at: https://doi.org/10.1186/s12890-023-02487-4.\u003c/li\u003e\n\u003cli\u003eStalin P, Alexander T, Purty AJ, Manikandan M and Vaishnavi S (2022) Health-seeking behavior for acute health problems during COVID-19 lockdown among the residents of an urban area in Puducherry. \u003cem\u003eIndian Journal of Community Medicine\u003c/em\u003e 47(2), 299-301. Available at: https://doi.org/10.4103/ijcm.ijcm_739_21.\u003c/li\u003e\n\u003cli\u003eYang J, Gong H, Chen X, Chen Z, Deng X, Qian M, Hou Z, Ajelli M and Viboud C, Yu H (2021) Health-seeking behaviors of patients with acute respiratory infections during the outbreak of novel coronavirus disease 2019 in Wuhan, China. \u003cem\u003eInfluenza and Other Respiratory Viruses\u003c/em\u003e 15(2), 188-194. Available at: https://doi.org/10.1111/irv.12804.\u003c/li\u003e\n\u003cli\u003eLutpiatina L, Sulistyorini L, Notobroto HB, Raya RP, Utama RD and Thuraidah A. (2022) Multilevel analysis of lifestyle and household environment for toddlers with symptoms of acute respiratory infection (ARI) in Indonesia in 2007, 2012, and 2017. \u003cem\u003eGlobal Pediatric Health\u003c/em\u003e 9, 2333794X221078700. https://doi.org/10.1177/2333794X221078700\u003c/li\u003e\n\u003cli\u003eAdinan J, Damian DJ, Mosha NR, Mboya IB, Mamseri R and Msuya SE (2017) Individual and contextual factors associated with appropriate healthcare seeking behavior among febrile children in Tanzania. \u003cem\u003ePLoS One\u003c/em\u003e 12(4): e0175446. https://doi.org/10.1371/journal.pone.0175446\u003c/li\u003e\n\u003cli\u003eAkinyemi JO, Chisumpa VH and Odimegwu CO (2019) Household relationships and healthcare seeking behaviour for common childhood illnesses in sub-Saharan Africa: A cross-national mixed effects analysis. \u003cem\u003eBMC Health Services Research\u003c/em\u003e 19(1), 1-11. https://doi.org/10.1186/s12913-019-4142-x\u003c/li\u003e\n\u003cli\u003eCharles JO, Udonwa NE, Ikoh MU and Ikpeme BI (2008) The role of mothers in household health-seeking behavior and decision-making in childhood febrile illness in Okurikang/Ikot Efong Otop Community. Cross River State Nigeria. \u003cem\u003eEpidemiology\u003c/em\u003e 29(8-9), 906-925. Available from: https://www.tandfonline.com/doi/full/10.1080/07399330802269626#d1e326\u003c/li\u003e\n\u003cli\u003eAragaw FM, Teklu RE, Alemayehu MA, Derseh NM, Agimas MC, Shewaye DA, Birhanie AL, Tsega SS, Argaw GS, Tesfaye AH (2024) Magnitude and determinant of healthcare-seeking behavior for childhood acute respiratory tract infections in Ethiopia: A cross-sectional study. \u003cem\u003eBMC Pediatrics\u003c/em\u003e 24(1), 3. https://doi.org/10.1186/s12887-023-04463-7\u003c/li\u003e\n\u003cli\u003eRichards E, Theobald S, George A, Kim JC, Rudert C, Jehan K and Tolhurst R (2013) Going beyond the surface: Gendered intra-household bargaining as a social determinant of child health and nutrition in low and middle-income countries. \u003cem\u003eSocial Science \u0026amp; Medicine\u003c/em\u003e 95, 24-33. Available at: https://doi.org/10.1016/j.socscimed.2012.06.015.\u003c/li\u003e\n\u003cli\u003eOkwaraji YB, Cousens S, Berhane Y, Mulholland K and Edmond K (2012) Effect of geographical access to health facilities on child mortality in rural Ethiopia: A community-based cross-sectional study. \u003cem\u003ePLoS One\u003c/em\u003e 7(3): e33564. https://doi.org/10.1371/journal.pone.0033564\u003c/li\u003e\n\u003cli\u003eShiferaw S, Spigt M, Godefrooij M, Melkamu Y and Tekie M (2013) Why do women prefer home births in Ethiopia? \u003cem\u003eBMC Pregnancy and Childbirth\u003c/em\u003e 13, 1-10. Available at: http://www.biomedcentral.com/1471-2393/13/5.\u003c/li\u003e\n\u003cli\u003eAstale T and Chenault M (2015) Help-seeking behavior for children with acute respiratory infection in Ethiopia: Results from 2011 Ethiopia demographic and health survey. \u003cem\u003ePLoS One\u003c/em\u003e 10(11): e0142553. https://doi.org/10.1371/journal.pone.0142553\u003c/li\u003e\n\u003cli\u003eRani M, Bonu S and Harvey S (2008) Differentials in the quality of antenatal care in India. \u003cem\u003eInternational Journal for Quality in Health Care\u003c/em\u003e 20(1), 62-71. Available at: https://doi.org/10.1093/intqhc/mzm052.\u003c/li\u003e\n\u003cli\u003eKumar V and Singh P (2016) Access to healthcare among the empowered action group (EAG) states of India: Current status and impeding factors. \u003cem\u003eNational Medical Journal of India\u003c/em\u003e 29, 267-273.\u003c/li\u003e\n\u003cli\u003eSanasam DC (2020) Maternal reproductive health: A comparison between India and empowered action group states. In \u003cem\u003eUrban Health Risk and Resilience in Asian Cities\u003c/em\u003e (pp. 149\u0026ndash;163). Singapore: Springer. Available at: https://link.springer.com/chapter/10.1007/978-981-15-1205-6_9.\u003c/li\u003e\n\u003cli\u003eNITI Ayog: RBI Handbook of Statistics on Indian Economy 2015-16. Available from: https://rbidocs.rbi.org.in/rdocs/Publications/PDFs/154T_HB15092019609736EE47614B23BFD377A47FFC1A5D.PDF\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Acute Respiratory Infection, Treatment-seeking Behaviour, Under-five children","lastPublishedDoi":"10.21203/rs.3.rs-6194991/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6194991/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAcute Respiratory Infection (ARI) is one of the leading causes of under-five (U5) mortality, especially in low and middle-income and developing countries like India. Despite several health implications, it imposes a substantial economic burden on individual households. In India, the prevalence of ARI among U5 children has increased from 2016 to 2021 while simultaneously treatment-seeking behaviour (TSB) has decreased. Therefore, the present study aimed to assess the prevalence and factors associated with the TSB among U5 children experiencing ARI in India.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethodology\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study used the last two rounds of the National Family Health Survey (NFHS-IV, 2016 \u0026amp; NFHS-V, 2021) data. The bivariate analysis with a chi-square test and multivariable logistic regression models were employed to examine the association and determinants of TSB among U5 children in India.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe present study revealed that the prevalence of TSB among children experiencing ARI in India has decreased from 78 percent in 2016 to 52 percent in 2021. The multilevel logistic regression model indicated that children from rural areas (AOR: 0.85; 95% CI: 0.72–0.97), Empowered Action Group (EAG) states (AOR:0.81; 95% CI:0.67–0.99), and households reporting transportation as a barrier (AOR:0.87; 95% CI:0.75–0.97) had lower odds of seeking treatment compared to their counterparts. Conversely, TSB was more likely among households headed by women (AOR:1.32; 95% CI:1.15–1.51), those with media exposure (AOR:1.23; 95% CI:1.06–1.43), and those in the higher wealth index categories.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on these findings, the study recommends that public health programs should focus on the indicators to improve treatment-seeking behaviour among children, and also can help to reduce child morbidity and mortality due to ARI in India. Additionally, these efforts may contribute to reducing the risk of ARI and achieving the country's SDG target by 2030.\u003c/p\u003e","manuscriptTitle":"Prevalence and Drivers of Treatment Seeking Behaviour among Under-five Children Experiencing Acute Respiratory Infection in India ","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-21 11:18:20","doi":"10.21203/rs.3.rs-6194991/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6dc7c569-0bde-48b3-8b35-1d6cd0741cd2","owner":[],"postedDate":"April 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-04-26T07:23:16+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-21 11:18:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6194991","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6194991","identity":"rs-6194991","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}