1. Distribution of characteristics SAMPADA and blood markers data among Under five children

Category SAMPADA n (%) ,N = 219521 Biomarker n (%) ,N =19962
Religion
Buddhist/Neo-Buddhist 410 (1.9%) 20 (1.1%)
Christian 2968 (13.6%) 250 (14.4%)
Hindu 15293 (70%) 952 (54.7%)
Jain 12 (0.1%) NA
Muslim 2430 (11.1%) 239 (13.7%)
Others (Specify) 250 (1.1%) 22 (1.3%)
Sikh 496 (2.3%) 257 (14.8%)
Community
Not willing to reveal/Do not know 290 (1.3%) 19 (1.1%)
Other Backward Class 7042 (32.2%) 499 (28.7%)
Other Caste 4430 (20.3%) 349 (20.1%)
Scheduled Caste 4609 (21.1%) 515 (29.6%)
Scheduled Tribe 5487 (25.1%) 358 (20.6%)
Housing_type
Kutcha 3221 (14.7%) 196 (11.3%)
Pucca 13409 (61.4%) 1169 (67.2%)
Semi-pucca 5222 (23.9%) 375 (21.6%)
House_ownership
Other 107 (0.5%) 8 (0.5%)
Own House 19146 (87.8%) 1551 (89.4%)
Rented House 2542 (11.7%) 175 (10.1%)
Sanitary_Latrine
Community Latrine 349 (1.6%) 21 (1.2%)
Open Defecation 2313 (10.6%) 100 (5.7%)
Other 163 (0.7%) 1 (0.1%)
Present and Not using 212 (1%) 13 (0.7%)
Present and using 18821 (86.1%) 1605 (92.2%)
Drinking_water
Bore well 5623 (25.7%) 482 (27.7%)
Bottled/Purchased water 539 (2.5%) 45 (2.6%)
Open well 1387 (6.3%) 157 (9%)
Others 1055 (4.8%) 51 (2.9%)
RO Treated /Filtrated Water 1992 (9.1%) 238 (13.7%)
Spring water 290 (1.3%) 9 (0.5%)
Surface water 471 (2.2%) 42 (2.4%)
Tap water 10033 (45.9%) 694 (39.9%)
Water tanker 465 (2.1%) 21 (1.2%)
PDS_Card
AAY(Antyodaya Anna Yojana) 812 (3.7%) 53 (3.1%)
APL(Above Poverty Line) 5261 (24.1%) 407 (23.4%)
BPL(Below Poverty Line) 10235 (46.9%) 875 (50.4%)
No Card 4366 (20%) 326 (18.8%)
TPDS(Targetted PDS) 1153 (5.3%) 76 (4.4%)
Family_Type
Extended 3156 (14.4%) 260 (14.9%)
Joint 4836 (22.1%) 443 (25.5%)
Nuclear 13863 (63.4%) 1037 (59.6%)
Cooking_fuel_used
Biogas 24 (0.1%) 1 (0.1%)
Electricity 50 (0.2%) 4 (0.2%)
Firewood 7120 (32.6%) 395 (22.7%)
Kerosene 18 (0.1%) NA
LPG 14337 (65.6%) 1337 (76.9%)
Other (Specify) 279 (1.3%) 2 (0.1%)
Solar 33 (0.2%) NA
Overcrowding
No 14388 (66%) 1184 (68.3%)
Yes 7417 (34%) 550 (31.7%)
Water_Rank
Improved drinking water 12564 (57.4%) 977 (56.1%)
Not Improved drinking water 9312 (42.6%) 763 (43.9%)
Sanitary_Rank
Improved Sanitation 18821 (86%) 1605 (92.2%)
Not Improved Sanitation 3055 (14%) 135 (7.8%)
Wealth_Index
Higher 4129 (18.9%) 505 (25.4%)
Highest 4255 (19.5%) 517 (26%)
Lower 4458 (20.4%) 310 (15.6%)
Lowest 4841 (22.1%) 276 (13.9%)
Middle 4193 (19.2%) 380 (19.1%)
NA= Missing data
Overcrowding= >2 people per room
1 SAMPADA: Total under five chidlren enrolled
2 Biomarker: total number of chidlren with biochemical assessment

2. Distribution of blood markers among Under five children (N=1996)

Variable N Percent Mean_SD Median_IQR Min Max
Hb_alt_adj 1990 99.7 11.36 (1.62) 11.5 (10.5, 12.4) 4.3 19.6
Ferritin (ug/L) 1971 98.7 48.82 (76.5) 31.45 (15.28, 58.78) 5 1905.45
CRPHS (mg/L) 1986 99.5 2.03 (7.3) 0.55 (0.35, 1.38) 0.1 240.58
AAGP (g/L) 1983 99.3 0.72 (0.28) 0.66 (0.52, 0.85) 0.19 2.24
S-Folate (ng/mL) 1767 88.5 10 (16.43) 7.13 (4.79, 10.8) 0.8 429.23
Vit-B12 (pg/mL) 1769 88.6 307.93 (244.13) 251.51 (155.05, 382.85) 50 2311.88
Vit-D (ng/mL) 1762 88.3 21.7 (12.15) 20.51 (13.99, 27.02) 4.5 170.58
RBC-Folate (ng/mL) 1575 78.9 549.86 (686.51) 411.51 (266.69, 622.3) 0.8 10677.7



Fig.1 Distribution of Biomarkers among under five chidlren






Table.3 . Iron deficiency using BRINDA correction regression method by state (N=1974)

BRINDA reference values for preschool children were applied to adjust ferritin concentrations for inflammation. Inflammation-adjusted ferritin was estimated using the regression correction equation:

log(Ferritin_adj) = log(Ferritin_obs) − β₁ (log(CRP) − log(CRP_ref)) − β₂ (log(AGP) − log(AGP_ref))

Iron deficiency was then defined using the adjusted ferritin concentration (<12 µg/L).

State-wise Prevalence of Iron Deficiency
Inflammation-adjusted vs Unadjusted estimates
State Sample size Unadjusted n (%) Inflammation-adjusted n (%)
Haryana 17 10 (58.8%) 10 (58.8%)
Telangana 38 16 (42.1%) 18 (47.4%)
Maharashtra 37 15 (40.5%) 17 (46%)
Gujarath 154 50 (32.5%) 69 (44.8%)
Punjab 498 187 (37.5%) 221 (44.4%)
Rajasthan 105 35 (33.3%) 43 (41%)
Andhrapradesh 19 5 (26.3%) 7 (36.8%)
Madhya Pradesh 37 10 (27%) 13 (35.1%)
Karnataka 28 10 (32.3%) 9 (32.1%)
Uttar Pradesh 15 3 (20%) 4 (26.7%)
Chhattisgarh 12 2 (16.7%) 3 (25%)
Odisha 25 2 (7.7%) 6 (24%)
Goa 47 3 (6.4%) 8 (17%)
WestBengal 164 11 (6.7%) 22 (13.4%)
Jharkhand 19 2 (10.5%) 2 (10.5%)
Arunachal Pradesh 118 5 (4.1%) 12 (10.2%)
Daman&Diu, Dadra haveli 20 1 (5%) 2 (10%)
Kerala 254 17 (6.7%) 24 (9.4%)
Tripura 37 1 (2.7%) 3 (8.1%)
Jammu & Kashmir 114 8 (7%) 8 (7%)
Chandigarh 17 0 (0%) 1 (5.9%)
Nagaland 19 0 (0%) 1 (5.3%)
Mizoram 117 2 (1.7%) 4 (3.4%)
Andaman & Nicobar Islands 3 0 (0%) 0 (0%)
Assam 3 0 (0%) 0 (0%)
Bihar 2 0 (0%) 0 (0%)
Delhi 8 0 (0%) 0 (0%)
Himachal Pradesh 1 0 (0%) 0 (0%)
Lakshadweep 20 0 (0%) 0 (0%)
Meghalaya 3 0 (0%) 0 (0%)
Puducherry 3 0 (0%) 0 (0%)
Sikkim 2 0 (0%) 0 (0%)
Tamil Nadu 7 0 (0%) 0 (0%)
Uttarakhand 1 0 (0%) 0 (0%)
India 1964 395 (20%) 507 (25.8%)



Fig.3. Graphical distribution of iron deficiency (Adjuted for inflamaiton) by state



Table.5 Correlation between ferrtin (adjusted) and other biomarkers

Correlation of Ferritin (Original and Log-Transformed) with Hemoglobin and Micronutrient Biomarkers
Biomarker Correlation (Spearman) p-value
Without log transformation
Hb_alt_adj 0.203 <0.001
S-Folate (ng/mL) 0.029 0.255
Vit-B12 (pg/mL) 0.028 0.276
Vit-D (ng/mL) 0.051 0.044
RBC-Folate (ng/mL) 0.026 0.308
With log transformation
Hb_alt_adj 0.408 <0.001
S-Folate (ng/mL) 0.075 0.003
Vit-B12 (pg/mL) 0.043 0.091
Vit-D (ng/mL) 0.072 0.004
RBC-Folate (ng/mL) 0.008 0.737



Fig.4 Association of Log-transformed Ferritin with Hemoglobin and Other Micronutrient Biomarkers (Scatter plots) (N=1563)


Table.5. Overall Prevalence of Selected Micronutrient Deficiencies among Under-Five Children

Parameter N Deficient Percent LCI UCI
Serum Folate 1767 291 16.5 14.8 18.3
Vitamin B12 1769 664 37.5 35.3 39.8
Vitamin D 1762 324 18.4 16.6 20.3
RBC Folate 1575 165 10.5 9.0 12.1
Iron Deficiency(Adj) 1964 507 25.8 23.9 27.8
Cutoffs - Ferritin >12, S-Folate (ng/mL) < 4, Vit-B12 (pg/mL) < 203,Vit-D (ng/mL) < 12,RBC-Folate (ng/mL) < 151



Table.6: Micronutrient deficiency by Anemia status

Micronutrient Deficiencies by Anemia Status
Micronutrient deficiency
Anemia
Non-anemia
N n (%) N n (%)
Vitamin B12 deficiency 637 256 (40.2%) 1126 406 (36.1%)
Iron deficiency 692 335 (48.4%) 1266 172 (13.6%)
RBC folate deficiency 559 43 (7.7%) 1016 122 (12%)
Vitamin D deficiency 637 130 (20.4%) 1119 190 (17%)
Folate deficiency 637 118 (18.5%) 1124 172 (15.3%)
N = total number of participants with available biomarker data within anemia status;
n (%) = number and percentage of participants with the specific micronutrient deficiency.
Denominator (N) varies across micronutrients due to biomarker missing values.


### Fig.5 : Combination of Micronutrient deficiencies by Anemia status (N=1563)

Figure 5 presents the prevalence of individual and combined micronutrient deficiencies stratified by anemia status (Overall N = 1563, complete cases).

Overall, no deficiency was the most common category (32.7%), followed by vitamin B12 deficiency (17.3%) and iron deficiency (9.7%). Among children with anemia, iron deficiency (18.3%) and vitamin B12 deficiency (14.4%) were the most prevalent single deficiencies, with notable co-occurrence of iron and B12 deficiency (9.7%). In contrast, among non-anemic children, no deficiency (38%) predominated, and single deficiencies such as vitamin B12 (18.9%) and folate (5.6%) were more common than combined deficiencies.

Across all groups, multiple micronutrient deficiencies were less frequent, with combinations involving three or more deficiencies occurring in a small proportion (<3%) of participants. The pattern indicates that coexisting deficiencies are more common among anemic individuals, particularly involving iron and vitamin B12.


Fig.6: Relative contribution of micronutrient deficiencies to anemia (N=1563)

To estimate the relative contribution of micronutrient deficiencies to anemia, a hierarchical classification approach was used. Individuals with multiple deficiencies were assigned to a single category based on a predefined priority order: iron deficiency, vitamin B12 deficiency, serum folate deficiency, RBC folate deficiency, and other/unknown causes.

Among anemic children, iron deficiency was the leading attributed cause (45.7%), followed by vitamin B12 deficiency (22.5%), Serum folate deficiency (3.6%), RBC folate deficiency (3.2%) while 22.7% had anemia without detectable micronutrient deficiency



Fig.7: Pathways linking anemia status with iron and other micronutrient deficiencies (N=1958)

Findings: Overall, 35.3% of participants were anemic, of whom 48.4% had iron deficiency, while 51.6% did not have iron deficiency, indicating that a substantial proportion of anemia is not attributable to iron deficiency alone. Among non-anemic individuals (64.7%), 13.6% still exhibited iron deficiency, whereas 86.4% had normal iron status.

Among individuals with anemia but without iron deficiency, a considerable proportion had other micronutrient deficiencies, particularly vitamin B12 deficiency (39.2%), followed by serum folate deficiency (6.2%), RBC folate deficiency (5%), and vitamin D deficiency (4.5%). Additionally, 45.1% had no identified micronutrient deficiency, suggesting potential involvement of non-nutritional causes or unmeasured factors.



Table.8 Burden of Multiple Micronutrient Deficiencies among Under-five Children

Category n Percent (95% CI)
No micronutrient deficiency 511 32.7 (30.4–35.1)
At least one deficiency 1052 67.3 (64.9–69.6)
Exactly two deficiencies 318 20.3 (18.4–22.4)
Exactly three deficiencies 101 6.5 (5.3–7.8)
Four or more deficiencies 20 1.3 (0.8–2)
All five deficiencies 0 0 (0–0.2)



Fig.5 . Number of subjects having combination of micro nutrient deficiency





Fig.6 Correlation Heatmap: Hematological Parameters vs Micronutrient Biomarkers

Demographic Characterstics of Iron deficiency among under five children

Table.10. Age specific prevlance of Micronutrient deficiency among Underfive children

age_grp N Deficient Percent (95% CI)
Iron deficiency
<1 yr 54 16 29.6 (18–43.6)
1–1.99 yr 254 78 30.7 (25.1–36.8)
2–2.99 yr 381 123 32.3 (27.6–37.2)
3–3.99 yr 541 147 27.2 (23.5–31.1)
4–4.99 yr 734 143 19.5 (16.7–22.5)
RBC folate deficiency
<1 yr 43 4 9.3 (2.6–22.1)
1–1.99 yr 206 17 8.3 (4.9–12.9)
2–2.99 yr 298 30 10.1 (6.9–14.1)
3–3.99 yr 426 56 13.1 (10.1–16.7)
4–4.99 yr 602 58 9.6 (7.4–12.3)
Serum folate deficiency
<1 yr 52 9 17.3 (8.2–30.3)
1–1.99 yr 232 47 20.3 (15.3–26)
2–2.99 yr 332 66 19.9 (15.7–24.6)
3–3.99 yr 482 64 13.3 (10.4–16.6)
4–4.99 yr 669 105 15.7 (13–18.7)
Vitamin B12 deficiency
<1 yr 52 23 44.2 (30.5–58.7)
1–1.99 yr 232 104 44.8 (38.3–51.5)
2–2.99 yr 333 125 37.5 (32.3–43)
3–3.99 yr 483 171 35.4 (31.1–39.9)
4–4.99 yr 669 241 36 (32.4–39.8)
Vitamin D deficiency
<1 yr 52 10 19.2 (9.6–32.5)
1–1.99 yr 231 36 15.6 (11.2–20.9)
2–2.99 yr 330 73 22.1 (17.8–27)
3–3.99 yr 482 84 17.4 (14.1–21.1)
4–4.99 yr 667 121 18.1 (15.3–21.3)



### Table 11. Sex-specific Prevalence of Micronutrient Deficiencies

Sex-specific Prevalence of Micronutrient Deficiencies
Gender N Deficient Percent (95% CI)
Iron deficiency
Female 896 229 25.6 (22.7–28.5)
Male 1068 278 26 (23.4–28.8)
RBC folate deficiency
Female 723 90 12.4 (10.1–15.1)
Male 852 75 8.8 (7–10.9)
Serum folate deficiency
Female 801 130 16.2 (13.7–19)
Male 966 161 16.7 (14.4–19.2)
Vitamin B12 deficiency
Female 801 307 38.3 (34.9–41.8)
Male 968 357 36.9 (33.8–40)
Vitamin D deficiency
Female 798 153 19.2 (16.5–22.1)
Male 964 171 17.7 (15.4–20.3)





Table.13 Prevalence of Micronutrient Deficiency by Place of Residence

Rural
Urban
N Deficient (n) Prevalence % (95% CI) N Deficient (n) Prevalence % (95% CI)
Anemia 1237 431 34.8 (32.2, 37.5) 753 270 35.9 (32.4, 39.3)
Vitamin B12 deficiency 1110 411 37 (34.2, 39.9) 659 253 38.4 (34.7, 42.1)
Serum folate deficiency 1109 172 15.5 (13.4, 17.6) 658 119 18.1 (15.1, 21)
Iron deficiency 1228 299 24.3 (21.9, 26.7) 736 208 28.3 (25, 31.5)
Red blood cell folate deficiency 990 102 10.3 (8.4, 12.2) 585 63 10.8 (8.3, 13.3)
Vitamin D deficiency 1107 161 14.5 (12.5, 16.6) 655 163 24.9 (21.6, 28.2)



Household and Socio-Demographic characteristics of under five chidlren.

Category n (%)
Ferritin (Continuous)
Iron Deficiency (Binary)
Poisson Regression
Geometric Mean Ferritin GeoMean Difference P value Iron deficiency No Iron deficiency Yes Chi-square p Prevalence Ratio (95% CI) PR p value
age_grp
4–4.99 yr 734 (37.4%) 26.08 Reference 591 (80.5%) 143 (19.5%) 0.000 Reference
<1 yr 54 (2.7%) 24.83 -1.24 0.714 38 (70.4%) 16 (29.6%) 1.52 (0.98, 2.35) 0.060
1–1.99 yr 254 (12.9%) 21.06 -5.01 0.002 176 (69.3%) 78 (30.7%) 1.58 (1.24, 2) 0.000
2–2.99 yr 381 (19.4%) 20.20 -5.87 0.000 258 (67.7%) 123 (32.3%) 1.66 (1.35, 2.04) 0.000
3–3.99 yr 541 (27.5%) 22.61 -3.47 0.008 394 (72.8%) 147 (27.2%) 1.39 (1.14, 1.71) 0.001
Gender
Male 1068 (54.4%) 23.25 Reference 790 (74%) 278 (26%) 0.852 Reference
Female 896 (45.6%) 23.10 -0.15 0.883 667 (74.4%) 229 (25.6%) 0.98 (0.84, 1.14) 0.812
PSUType
Rural 1228 (62.5%) 24.01 Reference 929 (75.7%) 299 (24.3%) 0.062 Reference
Urban 736 (37.5%) 21.86 -2.15 0.033 528 (71.7%) 208 (28.3%) 1.16 (1, 1.35) 0.054
HH_members
2–4 555 (32.3%) 22.63 Reference 413 (74.4%) 142 (25.6%) 0.673 Reference
5–7 886 (51.5%) 22.64 0.02 0.988 636 (71.8%) 250 (28.2%) 1.1 (0.92, 1.32) 0.277
8–10 213 (12.4%) 22.37 -0.25 0.883 159 (74.6%) 54 (25.4%) 0.99 (0.76, 1.3) 0.947
11+ 65 (3.8%) 20.57 -2.06 0.446 47 (72.3%) 18 (27.7%) 1.08 (0.71, 1.64) 0.710
nofrooms_cat
1 140 (8.2%) 17.69 Reference 91 (65%) 49 (35%) 0.000 Reference
2-3 897 (52.7%) 20.75 3.06 0.063 619 (69%) 278 (31%) 0.89 (0.69, 1.13) 0.332
4+ 666 (39.1%) 26.28 8.59 0.000 532 (79.9%) 134 (20.1%) 0.57 (0.44, 0.75) 0.000
Overcrowding
No 1161 (68.1%) 24.16 Reference 883 (76.1%) 278 (23.9%) 0.000 Reference
Yes 545 (31.9%) 19.23 -4.93 0.000 361 (66.2%) 184 (33.8%) 1.41 (1.21, 1.65) 0.000
Religion_new
Hindu 933 (54.5%) 19.73 Reference 654 (70.1%) 279 (29.9%) 0.000 Reference
Christian 249 (14.5%) 40.50 20.76 0.000 228 (91.6%) 21 (8.4%) 0.28 (0.19, 0.43) 0.000
Muslim 238 (13.9%) 28.22 8.48 0.000 200 (84%) 38 (16%) 0.53 (0.39, 0.73) 0.000
Others 41 (2.4%) 29.27 9.54 0.006 31 (75.6%) 10 (24.4%) 0.82 (0.47, 1.41) 0.466
Sikh 251 (14.7%) 15.76 -3.97 0.001 137 (54.6%) 114 (45.4%) 1.52 (1.28, 1.8) 0.000
Community
Other Caste 342 (20%) 24.84 Reference 261 (76.3%) 81 (23.7%) 0.000 Reference
Not willing to reveal/Do not know 19 (1.1%) 18.61 -6.23 0.176 12 (63.2%) 7 (36.8%) 1.56 (0.84, 2.89) 0.162
Other Backward Class 491 (28.7%) 18.69 -6.15 0.000 344 (70.1%) 147 (29.9%) 1.26 (1, 1.6) 0.049
Scheduled Caste 505 (29.5%) 17.44 -7.41 0.000 312 (61.8%) 193 (38.2%) 1.61 (1.29, 2.01) 0.000
Scheduled Tribe 355 (20.7%) 38.30 13.46 0.000 321 (90.4%) 34 (9.6%) 0.4 (0.28, 0.59) 0.000
SanitaryLatrine
Present and using 1578 (92.2%) 22.73 Reference 1151 (72.9%) 427 (27.1%) 0.567 Reference
Community latrine/presentnotusing/Others 22 (1.3%) 26.68 3.96 0.432 18 (81.8%) 4 (18.2%) 0.67 (0.28, 1.64) 0.381
Open Defecation 99 (5.8%) 18.02 -4.71 0.019 70 (70.7%) 29 (29.3%) 1.08 (0.79, 1.49) 0.623
Present and Not using 13 (0.8%) 25.60 2.87 0.654 11 (84.6%) 2 (15.4%) 0.57 (0.16, 2.04) 0.386
PDS_Card
No Card 317 (18.5%) 21.37 Reference 216 (68.1%) 101 (31.9%) 0.000 Reference
AAY(Antyodaya Anna Yojana) 53 (3.1%) 35.34 13.97 0.000 49 (92.5%) 4 (7.5%) 0.24 (0.09, 0.62) 0.003
APL(Above Poverty Line) 404 (23.6%) 24.31 2.94 0.071 313 (77.5%) 91 (22.5%) 0.71 (0.55, 0.9) 0.005
BPL(Below Poverty Line) 859 (50.3%) 21.63 0.25 0.849 609 (70.9%) 250 (29.1%) 0.91 (0.75, 1.11) 0.355
TPDS(Targetted PDS) 76 (4.4%) 20.77 -0.61 0.812 60 (78.9%) 16 (21.1%) 0.66 (0.42, 1.05) 0.080
Housing_type
Pucca 1150 (67.2%) 19.39 Reference 775 (67.4%) 375 (32.6%) 0.000 Reference
Kutcha 193 (11.3%) 34.76 15.37 0.000 169 (87.6%) 24 (12.4%) 0.38 (0.26, 0.56) 0.000
Semi-pucca 369 (21.6%) 28.44 9.05 0.000 306 (82.9%) 63 (17.1%) 0.52 (0.41, 0.67) 0.000
House_ownership
Own House 1528 (89.6%) 21.93 Reference 1102 (72.1%) 426 (27.9%) 0.020 Reference
Other 8 (0.5%) 37.77 15.84 0.106 8 (100%) 0 (0%) 0 (0, 0) 0.000
Rented House 170 (10%) 27.87 5.94 0.002 136 (80%) 34 (20%) 0.72 (0.53, 0.98) 0.036
Family_Type
Extended 256 (15%) 27.13 Reference 207 (80.9%) 49 (19.1%) 0.009 Reference
Joint 439 (25.6%) 20.86 -6.27 0.000 316 (72%) 123 (28%) 1.46 (1.09, 1.96) 0.011
Nuclear 1017 (59.4%) 22.17 -4.96 0.002 727 (71.5%) 290 (28.5%) 1.49 (1.14, 1.95) 0.004
Cooking_fuel
LPG 1314 (76.8%) 22.03 Reference 931 (70.9%) 383 (29.1%) 0.001 Reference
Firewood 390 (22.8%) 23.91 1.88 0.136 311 (79.7%) 79 (20.3%) 0.69 (0.56, 0.86) 0.001
Others 7 (0.4%) 38.84 16.82 0.116 7 (100%) 0 (0%) 0 (0, 0) 0.000
income_cat
1 426 (24.9%) 21.76 Reference 310 (72.8%) 116 (27.2%) 0.516 Reference
2 431 (25.2%) 21.54 -0.23 0.872 305 (70.8%) 126 (29.2%) 1.07 (0.87, 1.33) 0.515
3 425 (24.8%) 22.49 0.73 0.614 312 (73.4%) 113 (26.6%) 0.98 (0.78, 1.22) 0.833
4 429 (25.1%) 24.33 2.57 0.087 323 (75.3%) 106 (24.7%) 0.91 (0.72, 1.14) 0.401
Drinking_water
RO Treated /Filtrated Water 235 (13.7%) 28.38 Reference 186 (79.1%) 49 (20.9%) 0.000 Reference
Bore well 475 (27.8%) 17.69 -10.69 0.000 304 (64%) 171 (36%) 1.73 (1.31, 2.28) 0.000
Bottled/Purchased water 45 (2.6%) 25.25 -3.13 0.442 35 (77.8%) 10 (22.2%) 1.07 (0.58, 1.94) 0.835
Open well 157 (9.2%) 27.99 -0.39 0.886 140 (89.2%) 17 (10.8%) 0.52 (0.31, 0.87) 0.012
Others 50 (2.9%) 26.55 -1.83 0.647 41 (82%) 9 (18%) 0.86 (0.45, 1.64) 0.653
Spring water 9 (0.5%) 77.71 49.33 0.002 9 (100%) 0 (0%) 0 (0, 0) 0.000
Surface water 38 (2.2%) 20.12 -8.26 0.035 27 (71.1%) 11 (28.9%) 1.39 (0.8, 2.42) 0.248
Tap water 681 (39.8%) 22.71 -5.67 0.002 493 (72.4%) 188 (27.6%) 1.32 (1, 1.75) 0.047
Water tanker 21 (1.2%) 20.75 -7.63 0.141 14 (66.7%) 7 (33.3%) 1.6 (0.83, 3.08) 0.160
Water_Rank
Not Improved drinking water 751 (43.9%) 20.59 Reference 536 (71.4%) 215 (28.6%) 0.194 Reference
Improved drinking water 961 (56.1%) 24.10 3.52 0.001 714 (74.3%) 247 (25.7%) 0.9 (0.77, 1.05) 0.175
Sanitary_Rank
Not Improved Sanitation 134 (7.8%) 19.89 Reference 99 (73.9%) 35 (26.1%) 0.893 Reference
Improved Sanitation 1578 (92.2%) 22.73 2.84 0.119 1151 (72.9%) 427 (27.1%) 1.04 (0.77, 1.39) 0.815
Wealth_Index
Highest 510 (26.1%) 25.41 Reference 386 (75.7%) 124 (24.3%) 0.923 Reference
Higher 494 (25.3%) 22.15 -3.26 0.022 366 (74.1%) 128 (25.9%) 1.07 (0.86, 1.32) 0.560
Lower 305 (15.6%) 23.50 -1.91 0.254 225 (73.8%) 80 (26.2%) 1.08 (0.85, 1.38) 0.540
Lowest 273 (14%) 22.93 -2.48 0.147 202 (74%) 71 (26%) 1.07 (0.83, 1.38) 0.600
Middle 374 (19.1%) 21.58 -3.83 0.011 273 (73%) 101 (27%) 1.11 (0.89, 1.39) 0.363



Indvidual chracteristics of underfive Children (Nutrtional status, Biomarker status)

Category n(%) Geometric Mean Ferritin GeoMean Difference Geometric Mean Ratio (95% CI) p Iron deficiency No Iron deficiency Yes ChiSq p value Prevalence Ratio (95% CI) PR p value
Stunting
0 1071 (76.3%) 23.62 Reference Reference 798 (74.5%) 273 (25.5%) 0.019 Reference
1 332 (23.7%) 19.45 -4.17 0.82 (0.73, 0.93) 0.001 225 (67.8%) 107 (32.2%) 1.26 (1.05, 1.52) 0.014
Severe_Stunting
0 1309 (93.3%) 22.89 Reference Reference 963 (73.6%) 346 (26.4%) 0.053 Reference
1 94 (6.7%) 18.41 -4.48 0.8 (0.66, 0.98) 0.032 60 (63.8%) 34 (36.2%) 1.37 (1.03, 1.82) 0.030
Wasting
0 1204 (86.5%) 22.85 Reference Reference 880 (73.1%) 324 (26.9%) 0.666 Reference
1 188 (13.5%) 21.19 -1.66 0.93 (0.8, 1.07) 0.316 134 (71.3%) 54 (28.7%) 1.07 (0.84, 1.36) 0.600
Severe_Wasting
0 1358 (97.6%) 22.63 Reference Reference 990 (72.9%) 368 (27.1%) 0.917 Reference
1 34 (2.4%) 22.31 -0.32 0.99 (0.71, 1.37) 0.932 24 (70.6%) 10 (29.4%) 1.09 (0.64, 1.84) 0.761
Overweight
0 1367 (98.2%) 22.64 Reference Reference 998 (73%) 369 (27%) 0.437 Reference
1 25 (1.8%) 21.47 -1.17 0.95 (0.65, 1.38) 0.784 16 (64%) 9 (36%) 1.33 (0.79, 2.27) 0.287
Underweight
0 1115 (79.2%) 23.33 Reference Reference 822 (73.7%) 293 (26.3%) 0.139 Reference
1 292 (20.8%) 19.82 -3.5 0.85 (0.75, 0.96) 0.009 202 (69.2%) 90 (30.8%) 1.17 (0.96, 1.43) 0.114
Severe_Underweight
0 1336 (95%) 22.53 Reference Reference 969 (72.5%) 367 (27.5%) 0.439 Reference
1 71 (5%) 22.92 0.39 1.02 (0.81, 1.28) 0.882 55 (77.5%) 16 (22.5%) 0.82 (0.53, 1.27) 0.378



Scatter plot Ferritin vs Z scores