The following shows the descriptives of blood lead levels We removed blood levels of 4 to 6 µg/dL for risk factor analysis as this is the range where there is uncertainty in the measurement of blood lead levels.
| Blood Pb Levels (mg/dL) | N = 366 | N = 270 |
|---|---|---|
| Blood Pb Levels (μg/dL) | 6.2 (4.9), 4.7 (3.1, 7.3), 0.8, 33.6 | 6.6 (5.6), 3.8 (2.7, 8.3), 0.8, 33.6 |
| bloodpblevelsmgdl_5cat | ||
| <4 | 143 (39.07%) | 143 (52.96%) |
| 4-6 | 96 (26.23%) | 0 (0.00%) |
| 6-10 | 72 (19.67%) | 72 (26.67%) |
| 10-20 | 47 (12.84%) | 47 (17.41%) |
| >20 | 8 (2.19%) | 8 (2.96%) |
| 1 Mean (SD), Median (Q1, Q3), Min, Max; n (%) |
The diagram below captures the overarching hypothesis for high blood levels and guides the further risk factor analysis
We removed blood levels of 4 to 6 µg/dL for risk factor analysis for all the below results
Note: Other religion types: Buddhist, Sikh, Jain, Sindhi, Indigenous, Uraon, etc.
| Characteristic | N = 270 | N | Mean Difference | 95% CI | p-value | Overall N = 270 |
<4 N = 143 |
>6 N = 127 |
p-value | PR | 95% CI | p-value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| PSU Rural/Urban | 270 | <0.001 | ||||||||||
| Rural | 6.1 (5.6) | — | — | 211 (100%) | 126 (60%) | 85 (40%) | — | — | ||||
| Urban | 8.4 (5.5) | 2.3 | 0.66, 3.9 | 0.006 | 59 (100%) | 17 (29%) | 42 (71%) | 1.77 | 1.39, 2.22 | <0.001 | ||
| Gender | 270 | 0.7 | ||||||||||
| Female | 6.6 (5.4) | — | — | 145 (100%) | 75 (52%) | 70 (48%) | — | — | ||||
| Male | 6.6 (5.9) | -0.01 | -1.4, 1.3 | >0.9 | 125 (100%) | 68 (54%) | 57 (46%) | 0.94 | 0.73, 1.22 | 0.7 | ||
| age_gp | 270 | 0.4 | ||||||||||
| 1-2 | 8.5 (7.2) | — | — | 44 (100%) | 19 (43%) | 25 (57%) | — | — | ||||
| 2-3 | 6.2 (4.7) | -2.3 | -4.4, -0.11 | 0.040 | 63 (100%) | 33 (52%) | 30 (48%) | 0.84 | 0.58, 1.22 | 0.3 | ||
| 3-4 | 6.7 (6.3) | -1.8 | -3.9, 0.28 | 0.090 | 78 (100%) | 46 (59%) | 32 (41%) | 0.72 | 0.50, 1.06 | 0.085 | ||
| 4-5 | 6.0 (4.4) | -2.5 | -4.5, -0.41 | 0.019 | 85 (100%) | 45 (53%) | 40 (47%) | 0.83 | 0.59, 1.19 | 0.3 | ||
| Caste | 270 | 0.083 | ||||||||||
| Other Caste | 8.5 (7.4) | — | — | 20 (100%) | 9 (45%) | 11 (55%) | — | — | ||||
| SC | 5.2 (3.8) | -3.3 | -6.2, -0.44 | 0.024 | 54 (100%) | 33 (61%) | 21 (39%) | 0.71 | 0.43, 1.25 | 0.2 | ||
| ST | 5.9 (5.2) | -2.6 | -5.3, 0.10 | 0.059 | 90 (100%) | 54 (60%) | 36 (40%) | 0.73 | 0.47, 1.25 | 0.2 | ||
| OBC | 7.6 (6.1) | -0.92 | -3.6, 1.7 | 0.5 | 105 (100%) | 47 (45%) | 58 (55%) | 1.00 | 0.69, 1.68 | >0.9 | ||
| Not known | 6.8 (NA) | -1.8 | -13, 9.4 | 0.8 | 1 (100%) | 0 (0%) | 1 (100%) | |||||
| Religion | 270 | 0.7 | ||||||||||
| Hindu | 6.6 (5.6) | — | — | 259 (100%) | 136 (53%) | 123 (47%) | — | — | ||||
| Muslim | 7.1 (8.3) | 0.42 | -3.8, 4.7 | 0.8 | 7 (100%) | 5 (71%) | 2 (29%) | 0.60 | 0.19, 1.95 | 0.4 | ||
| Christian | 4.9 (2.3) | -1.7 | -7.3, 3.9 | 0.5 | 4 (100%) | 2 (50%) | 2 (50%) | 1.05 | 0.39, 2.83 | >0.9 | ||
| Others | NA (NA) | 0 (NA%) | 0 (NA%) | 0 (NA%) | ||||||||
| 1 Blood Pb Levels (μg/dL): Mean (SD) | ||||||||||||
| 2 n (%) | ||||||||||||
| 3 Pearson's Chi-squared test; Fisher's exact test |
Note: Other house ownership types: begar, quarters, encroached, landless, relatives, etc. Other Latrine types: Community latrine, present at home and not using, dry toilet, katcha, compost, no toilet, etc. Other cooking fuel types: cow dung, solar, biogas, electricity, kerosene, coal, weed, other, multiple types, etc. Other cooking/drinking water types: hand pump, rainwater, metro, tube well, share water, public tap, protected well, pipeline, chara, etc. Other water purification types: solar disinfection, let it stand, water filter, etc.
| Characteristic | N = 270 | N | Mean Difference | 95% CI | p-value | Overall N = 270 |
<4 N = 143 |
>6 N = 127 |
p-value | PR | 95% CI | p-value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Type of Family | 270 | 0.071 | ||||||||||
| Extended | 4.5 (3.4) | — | — | 29 (100%) | 21 (72%) | 8 (28%) | — | — | ||||
| Joint | 7.3 (6.5) | 2.8 | 0.11, 5.4 | 0.041 | 41 (100%) | 19 (46%) | 22 (54%) | 1.95 | 1.07, 4.10 | 0.046 | ||
| Nuclear | 6.8 (5.6) | 2.3 | 0.11, 4.5 | 0.039 | 200 (100%) | 103 (52%) | 97 (49%) | 1.76 | 1.04, 3.59 | 0.068 | ||
| Ownership of house | 270 | >0.9 | ||||||||||
| Own House | 6.6 (5.7) | — | — | 264 (100%) | 140 (53%) | 124 (47%) | — | — | ||||
| Rented/Other | 6.6 (4.1) | -0.02 | -4.6, 4.6 | >0.9 | 6 (100%) | 3 (50%) | 3 (50%) | 1.06 | 0.47, 2.39 | 0.9 | ||
| Type of House | 270 | 0.5 | ||||||||||
| Pucca | 7.1 (6.2) | — | — | 102 (100%) | 50 (49%) | 52 (51%) | — | — | ||||
| Semi-pucca | 6.3 (4.9) | -0.81 | -2.5, 0.92 | 0.4 | 69 (100%) | 36 (52%) | 33 (48%) | 0.94 | 0.68, 1.27 | 0.7 | ||
| Kutcha | 6.4 (5.5) | -0.77 | -2.3, 0.79 | 0.3 | 99 (100%) | 57 (58%) | 42 (42%) | 0.83 | 0.61, 1.12 | 0.2 | ||
| No of rooms in house | 270 | 0.6 | ||||||||||
| >1 | 6.6 (5.7) | — | — | 247 (100%) | 132 (53%) | 115 (47%) | — | — | ||||
| 0-1 | 7.2 (5.1) | 0.59 | -1.8, 3.0 | 0.6 | 23 (100%) | 11 (48%) | 12 (52%) | 1.12 | 0.68, 1.59 | 0.6 | ||
| Separate Kitchen | 270 | 0.14 | ||||||||||
| Yes | 7.0 (6.0) | — | — | 136 (100%) | 66 (49%) | 70 (51%) | — | — | ||||
| No | 6.3 (5.2) | -0.72 | -2.1, 0.62 | 0.3 | 134 (100%) | 77 (57%) | 57 (43%) | 0.83 | 0.64, 1.07 | 0.14 | ||
| Cooking fuel | 270 | 0.008 | ||||||||||
| Firewood | 6.1 (5.3) | — | — | 175 (100%) | 104 (59%) | 71 (41%) | — | — | ||||
| LPG | 7.7 (6.2) | 1.6 | 0.16, 3.0 | 0.030 | 91 (100%) | 37 (41%) | 54 (59%) | 1.46 | 1.14, 1.87 | 0.003 | ||
| Others | 5.4 (2.3) | -0.69 | -6.2, 4.9 | 0.8 | 4 (100%) | 2 (50%) | 2 (50%) | 1.23 | 0.26, 2.32 | 0.7 | ||
| Drinking Water | 269 | 0.2 | ||||||||||
| Bore well | 5.8 (4.8) | — | — | 87 (100%) | 50 (57%) | 37 (43%) | — | — | ||||
| Open well | 6.2 (8.1) | 0.40 | -2.2, 3.0 | 0.8 | 22 (100%) | 16 (73%) | 6 (27%) | 0.64 | 0.31, 1.32 | 0.2 | ||
| Others | 6.6 (5.4) | 0.73 | -1.4, 2.8 | 0.5 | 39 (100%) | 19 (49%) | 20 (51%) | 1.21 | 0.82, 1.78 | 0.3 | ||
| RO/Bottled/Purchased water | NA (NA) | 0 (NA%) | 0 (NA%) | 0 (NA%) | ||||||||
| Surface/Spring water | 9.8 (11.5) | 4.0 | -3.9, 12 | 0.3 | 2 (100%) | 1 (50%) | 1 (50%) | 1.18 | 0.29, 4.80 | 0.8 | ||
| Tap water | 7.0 (5.5) | 1.1 | -0.44, 2.7 | 0.2 | 108 (100%) | 53 (49%) | 55 (51%) | 1.20 | 0.88, 1.63 | 0.2 | ||
| Water tanker | 9.1 (5.7) | 3.3 | -0.20, 6.8 | 0.064 | 11 (100%) | 4 (36%) | 7 (64%) | 1.50 | 0.90, 2.49 | 0.12 | ||
| Cooking water | 269 | 0.3 | ||||||||||
| Bore well | 5.8 (4.8) | — | — | 87 (100%) | 50 (57%) | 37 (43%) | — | — | ||||
| Open well | 6.2 (7.9) | 0.40 | -2.2, 3.0 | 0.8 | 23 (100%) | 16 (70%) | 7 (30%) | 0.72 | 0.33, 1.28 | 0.3 | ||
| Others | 6.4 (5.4) | 0.62 | -1.5, 2.7 | 0.6 | 40 (100%) | 20 (50%) | 20 (50%) | 1.18 | 0.77, 1.72 | 0.4 | ||
| RO/Bottled/Purchased water | NA (NA) | 0 (NA%) | 0 (NA%) | 0 (NA%) | ||||||||
| Surface/Spring water | NA (NA) | 0 (NA%) | 0 (NA%) | 0 (NA%) | ||||||||
| Tap water | 7.1 (5.6) | 1.3 | -0.30, 2.9 | 0.11 | 108 (100%) | 53 (49%) | 55 (51%) | 1.20 | 0.89, 1.65 | 0.2 | ||
| Water tanker | 9.1 (5.7) | 3.3 | -0.18, 6.8 | 0.063 | 11 (100%) | 4 (36%) | 7 (64%) | 1.50 | 0.78, 2.30 | 0.12 | ||
| Water purification method | 269 | 0.9 | ||||||||||
| Water filter/ E. Purifier | 14.0 (16.3) | — | — | 2 (100%) | 1 (50%) | 1 (50%) | — | — | ||||
| Boiling | 5.9 (2.8) | -8.0 | -17, 0.79 | 0.074 | 7 (100%) | 3 (43%) | 4 (57%) | 1.14 | 0.25, 5.26 | 0.9 | ||
| Strain through a cloth | 5.2 (3.8) | -8.8 | -17, -0.77 | 0.032 | 40 (100%) | 24 (60%) | 16 (40%) | 0.80 | 0.19, 3.37 | 0.8 | ||
| Add bleach/chlorine tablets | NA (NA) | 0 (NA%) | 0 (NA%) | 0 (NA%) | ||||||||
| None | 6.8 (5.9) | -7.1 | -15, 0.71 | 0.074 | 205 (100%) | 106 (52%) | 99 (48%) | 0.97 | 0.24, 3.89 | >0.9 | ||
| Others/Multiple | 7.2 (5.3) | -6.8 | -15, 1.5 | 0.11 | 15 (100%) | 8 (53%) | 7 (47%) | 0.93 | 0.21, 4.13 | >0.9 | ||
| Latrine type | 270 | 0.006 | ||||||||||
| Present and using | 7.0 (5.6) | — | — | 193 (100%) | 91 (47%) | 102 (53%) | — | — | ||||
| Others | 6.4 (7.4) | -0.56 | -4.8, 3.7 | 0.8 | 7 (100%) | 4 (57%) | 3 (43%) | 0.81 | 0.24, 1.50 | 0.6 | ||
| Open Defecation | 5.6 (5.3) | -1.4 | -2.9, 0.15 | 0.077 | 70 (100%) | 48 (69%) | 22 (31%) | 0.59 | 0.40, 0.84 | 0.006 | ||
| Unknown | 1 | 0 | 1 | |||||||||
| Unknown | 1 | 0 | 1 | |||||||||
| Unknown | 1 | 1 | 0 | |||||||||
| 1 Blood Pb Levels (μg/dL): Mean (SD) | ||||||||||||
| 2 n (%) | ||||||||||||
| 3 Pearson's Chi-squared test; Fisher's exact test |
| Characteristic | N = 270 | N | Mean Difference | 95% CI | p-value | Overall N = 270 |
<4 N = 143 |
>6 N = 127 |
p-value | PR | 95% CI | p-value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Wealth Index | 270 | 0.3 | ||||||||||
| Highest | 9.0 (8.3) | — | — | 31 (100%) | 12 (39%) | 19 (61%) | — | — | ||||
| Higher | 6.3 (5.0) | -2.7 | -5.3, 0.02 | 0.051 | 37 (100%) | 19 (51%) | 18 (49%) | 0.79 | 0.50, 1.23 | 0.3 | ||
| Middle | 6.6 (5.4) | -2.4 | -5.1, 0.24 | 0.074 | 39 (100%) | 21 (54%) | 18 (46%) | 0.75 | 0.47, 1.18 | 0.2 | ||
| Lower | 6.5 (4.4) | -2.5 | -5.0, -0.03 | 0.048 | 53 (100%) | 26 (49%) | 27 (51%) | 0.83 | 0.57, 1.25 | 0.3 | ||
| Lowest | 6.2 (5.4) | -2.8 | -5.1, -0.58 | 0.014 | 110 (100%) | 65 (59%) | 45 (41%) | 0.67 | 0.47, 0.99 | 0.027 | ||
| 1 Blood Pb Levels (μg/dL): Mean (SD) | ||||||||||||
| 2 n (%) | ||||||||||||
| 3 Pearson's Chi-squared test |
| Characteristic | N = 270 | N | Mean Difference | 95% CI | p-value | Overall N = 270 |
<4 N = 143 |
>6 N = 127 |
p-value | PR | 95% CI | p-value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Anemia status | 270 | 0.084 | ||||||||||
| No Anemia | 6.7 (5.5) | — | — | 153 (100%) | 74 (48%) | 79 (52%) | — | — | ||||
| Any Anemia | 6.5 (5.8) | -0.27 | -1.6, 1.1 | 0.7 | 117 (100%) | 69 (59%) | 48 (41%) | 0.79 | 0.60, 1.03 | 0.090 | ||
| Anaemia Status (Any, New) | 270 | 0.094 | ||||||||||
| No Anemia | 6.7 (5.5) | — | — | 153 (100%) | 74 (48%) | 79 (52%) | — | — | ||||
| Mild Anemia | 6.8 (5.9) | 0.03 | -1.6, 1.6 | >0.9 | 72 (100%) | 39 (54%) | 33 (46%) | 0.89 | 0.65, 1.17 | 0.4 | ||
| Moder+Sev Anemia | 6.0 (5.8) | -0.76 | -2.6, 1.1 | 0.4 | 45 (100%) | 30 (67%) | 15 (33%) | 0.65 | 0.39, 0.96 | 0.052 | ||
| iron_def_adj | 21 | >0.9 | ||||||||||
| No Iron Deficiency | 5.5 (4.5) | — | — | 8 (100%) | 5 (63%) | 3 (38%) | — | — | ||||
| Iron Deficiency | 5.8 (5.3) | 0.34 | -4.4, 5.1 | 0.9 | 13 (100%) | 8 (62%) | 5 (38%) | 1.03 | 0.33, 3.96 | >0.9 | ||
| Vitamin B12 Status | 17 | 0.6 | ||||||||||
| Normal (≥203 pg/mL) | 6.8 (6.6) | — | — | 6 (100%) | 3 (50%) | 3 (50%) | — | — | ||||
| Deficient (<203 pg/mL) | 5.6 (4.3) | -1.2 | -6.8, 4.4 | 0.7 | 11 (100%) | 7 (64%) | 4 (36%) | 0.73 | 0.22, 2.71 | 0.6 | ||
| Serum Folate Status | 17 | 0.5 | ||||||||||
| Normal (≥4 ng/mL) | 6.4 (5.2) | — | — | 15 (100%) | 8 (53%) | 7 (47%) | — | — | ||||
| Deficient (<4 ng/mL) | 2.8 (0.6) | -3.7 | -12, 4.4 | 0.4 | 2 (100%) | 2 (100%) | 0 (0%) | 0.00 | 0.00, Inf | >0.9 | ||
| Vitamin D Status | 17 | 0.6 | ||||||||||
| Normal (≥12 ng/mL) | 5.3 (5.1) | — | — | 12 (100%) | 8 (67%) | 4 (33%) | — | — | ||||
| Deficient (<12 ng/mL) | 7.6 (4.9) | 2.3 | -3.4, 8.1 | 0.4 | 5 (100%) | 2 (40%) | 3 (60%) | 1.80 | 0.51, 5.80 | 0.3 | ||
| Unknown | 249 | 130 | 119 | |||||||||
| Unknown | 253 | 133 | 120 | |||||||||
| Unknown | 253 | 133 | 120 | |||||||||
| Unknown | 253 | 133 | 120 | |||||||||
| 1 Blood Pb Levels (μg/dL): Mean (SD) | ||||||||||||
| 2 n (%) | ||||||||||||
| 3 Pearson's Chi-squared test; Fisher's exact test |
| Correlation between Blood micronutrient and Blood Pb levels | ||
|---|---|---|
| Micronutrient | Correlation Coefficient (r) | P-value |
| ferritin_adj | 0.194 | 0.3988 |
| rbc_folate_ng_ml | -0.808 | 0.4007 |
| b12_pg_ml | 0.205 | 0.4304 |
| vitd_ng_ml | -0.412 | 0.1002 |
Findings: Anemia and iron deficiency are clearly associated with higher blood lead levels. This supports our hypothesis that this leads to increased absorption of lead in the gut. But it is also possible that lead exposure contributes to these deficiencies. In addition, the continuous variables of blood levels of ferritin and vitamin B12 have a weak negative correlation with blood lead but others like folate and vitamin D are not associated.
These indicators of longer term nutritional status and micronutrient deficiency are more relevant for lead absorption. In simple words, lower intake of micronutrients in diet over a longer period leads to lower blood levels of these micronutrients which in turn leads to higher absorption of lead in the gut and higher blood lead levels.
| Characteristic | N = 270 | N | Mean Difference | 95% CI | p-value | Overall N = 270 |
<4 N = 143 |
>6 N = 127 |
p-value | PR | 95% CI | p-value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| CRP Status | 22 | >0.9 | ||||||||||
| Inflammation | 1.3 (NA) | — | — | 1 (100%) | 1 (100%) | 0 (0%) | — | — | ||||
| No Inflammation | 5.8 (4.8) | 4.5 | -5.9, 15 | 0.4 | 21 (100%) | 13 (62%) | 8 (38%) | 4,981,360 | 0.00, Inf | >0.9 | ||
| AGP Status | 22 | 0.3 | ||||||||||
| Inflammation | 6.9 (5.5) | — | — | 7 (100%) | 3 (43%) | 4 (57%) | — | — | ||||
| No Inflammation | 4.9 (4.5) | -2.0 | -6.7, 2.6 | 0.4 | 15 (100%) | 11 (73%) | 4 (27%) | 0.47 | 0.14, 1.45 | 0.2 | ||
| Inflammation Status | 22 | 0.4 | ||||||||||
| Inflammation | 6.2 (5.5) | — | — | 8 (100%) | 4 (50%) | 4 (50%) | — | — | ||||
| No Inflammation | 5.2 (4.6) | -1.1 | -5.6, 3.5 | 0.6 | 14 (100%) | 10 (71%) | 4 (29%) | 0.57 | 0.19, 1.68 | 0.3 | ||
| Unknown | 248 | 129 | 119 | |||||||||
| Unknown | 248 | 129 | 119 | |||||||||
| Unknown | 248 | 129 | 119 | |||||||||
| 1 Blood Pb Levels (μg/dL): Mean (SD) | ||||||||||||
| 2 n (%) | ||||||||||||
| 3 Fisher's exact test |
| Correlation between Inflammation markers and Blood Pb levels | ||
|---|---|---|
| Inflammation markers | Correlation Coefficient (r) | P-value |
| crphs_clean | -0.221 | 0.3226 |
| agp_clean | 0.050 | 0.8244 |
| log_crp | -0.227 | 0.3095 |
| log_agp | 0.007 | 0.9761 |
Findings: Generally lack of inflammation is associated with higher blood lead levels. This may be because inflammation leads to sequestration of lead in the liver and other tissues, leading to lower blood lead levels. The biological plausibility of this association needs to be assessed further. Whether to use these variables to adjust for the relationship between blood micronutrients and blood lead levels needs to be assessed.
| Characteristic | N = 270 | N | Mean Difference | 95% CI | p-value | Overall N = 270 |
<4 N = 143 |
>6 N = 127 |
p-value | PR | 95% CI | p-value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Stunting status | 211 | >0.9 | ||||||||||
| No Stunting | 6.7 (5.4) | — | — | 128 (100%) | 65 (51%) | 63 (49%) | — | — | ||||
| Stunting | 6.4 (4.9) | -0.30 | -2.1, 1.5 | 0.7 | 49 (100%) | 24 (49%) | 25 (51%) | 1.04 | 0.73, 1.41 | 0.8 | ||
| Severe Stunting | 6.8 (5.3) | 0.11 | -1.9, 2.1 | >0.9 | 34 (100%) | 18 (53%) | 16 (47%) | 0.96 | 0.61, 1.37 | 0.8 | ||
| Wasting status | 208 | 0.2 | ||||||||||
| No Wasting | 6.6 (5.3) | — | — | 179 (100%) | 93 (52%) | 86 (48%) | — | — | ||||
| Wasting | 8.0 (5.8) | 1.5 | -0.79, 3.7 | 0.2 | 24 (100%) | 8 (33%) | 16 (67%) | 1.39 | 1.01, 1.91 | 0.046 | ||
| Severe Wasting | 4.5 (3.3) | -2.1 | -6.8, 2.6 | 0.4 | 5 (100%) | 3 (60%) | 2 (40%) | 0.83 | 0.28, 2.46 | 0.7 | ||
| Underweight status | 212 | >0.9 | ||||||||||
| No Underweight | 6.5 (5.2) | — | — | 144 (100%) | 72 (50%) | 72 (50%) | — | — | ||||
| Underweight | 6.8 (5.3) | 0.28 | -1.4, 2.0 | 0.8 | 50 (100%) | 25 (50%) | 25 (50%) | 1.00 | 0.70, 1.35 | >0.9 | ||
| Severe Underweight | 6.8 (5.9) | 0.28 | -2.3, 2.9 | 0.8 | 18 (100%) | 10 (56%) | 8 (44%) | 0.89 | 0.46, 1.40 | 0.7 | ||
| MUAC Group | 213 | 0.4 | ||||||||||
| Normal | 6.6 (5.3) | — | — | 207 (100%) | 106 (51%) | 101 (49%) | — | — | ||||
| severewasting | 5.9 (3.1) | -0.77 | -5.1, 3.5 | 0.7 | 6 (100%) | 2 (33%) | 4 (67%) | 1.37 | 0.76, 2.45 | 0.3 | ||
| Unknown | 59 | 36 | 23 | |||||||||
| Unknown | 62 | 39 | 23 | |||||||||
| Unknown | 58 | 36 | 22 | |||||||||
| Unknown | 57 | 35 | 22 | |||||||||
| 1 Blood Pb Levels (μg/dL): Mean (SD) | ||||||||||||
| 2 n (%) | ||||||||||||
| 3 Pearson's Chi-squared test; Fisher's exact test |
Findings: Stunting, and underweight which are chronic malnutrition indicators are associated with higher blood lead levels. This may be because malnutrition leads to increased absorption of lead in the gut. But it is also possible that lead exposure contributes to malnutrition. The direction of causality cannot be determined from this cross-sectional analysis.
| Correlation between Nutritional Variables and Blood Pb Levels | ||
|---|---|---|
| Nutritional Variable | Correlation Coefficient (r) | P-value |
| Energy Intake (kcal/day) | -0.089 | 0.1922 |
| Protein Intake (g/day) | -0.099 | 0.1462 |
| Carbohydrate Intake (g/day) | -0.109 | 0.1098 |
| Total Fat Intake (g/day) | -0.008 | 0.9042 |
| Iron Intake (mg/day) | -0.103 | 0.1332 |
| Zinc Intake (mg/day) | -0.156 | 0.0217 |
| Calcium Intake (mg/day) | -0.042 | 0.5417 |
| Thiamine (B1) Intake (mg/day) | -0.182 | 0.0076 |
| Riboflavin (B2) Intake (mg/day) | -0.056 | 0.4172 |
| Niacin (B3) Intake (mg/day) | -0.144 | 0.0355 |
| Total Folate (B9) Intake (ug/day) | -0.102 | 0.1372 |
| Vitamin C Intake (mg/day) | 0.076 | 0.2673 |
| Vitamin A Intake (ug/day) | -0.014 | 0.8343 |
| Vitamin B12 Intake (ug/day) | -0.028 | 0.6869 |
| Birth Weight (grams) | 0.382 | 0.0337 |
| Blood Parameter | Odds Ratio (per 10-unit increase) | 95% CI Lower | 95% CI Upper | P-value |
|---|---|---|---|---|
| Energy Intake (kcal/day) | 0.999 | 0.993 | 1.004 | 0.6342 |
| Protein Intake (g/day) | 0.953 | 0.765 | 1.180 | 0.6608 |
| Carbohydrate Intake (g/day) | 0.979 | 0.945 | 1.011 | 0.2099 |
| Total Fat Intake (g/day) | 1.107 | 0.958 | 1.293 | 0.1778 |
| Iron Intake (mg/day) | 0.827 | 0.419 | 1.605 | 0.5764 |
| Zinc Intake (mg/day) | 0.324 | 0.077 | 1.269 | 0.1124 |
| Calcium Intake (mg/day) | 1.004 | 0.989 | 1.020 | 0.5809 |
| Thiamine (B1) Intake (mg/day) | 0.000 | 0.000 | 0.397 | 0.0364 |
| Riboflavin (B2) Intake (mg/day) | 0.467 | 0.000 | 976.522 | 0.8428 |
| Niacin (B3) Intake (mg/day) | 0.354 | 0.113 | 0.972 | 0.0582 |
| Total Folate (B9) Intake (ug/day) | 0.985 | 0.934 | 1.039 | 0.5858 |
| Vitamin C Intake (mg/day) | 1.119 | 1.012 | 1.244 | 0.0323 |
| Vitamin A Intake (ug/day) | 1.016 | 0.990 | 1.043 | 0.2319 |
| Vitamin B12 Intake (ug/day) | 6.818 | 0.000 | 8124953.725 | 0.7405 |
| Birth Weight (grams) | 1.011 | 0.995 | 1.028 | 0.1988 |
Findings: There is a weak negative correlation between intake of macro and micro- nutrients in diet and blood lead levels. We find corroborative evidence in the fact that iron deficiency and anemia also had similar association as in Part 2D. However, these are measured at a single time point and may not be the best indicators of long term nutritional status which is more relevant for lead absorption. Also, birth weight does not seem to be associated.
[[1]]
[[2]]
[[3]]
[[4]]
[[5]]
[[6]]
[[7]]
[[8]]
[[9]]
[[10]]
[[11]]
[[12]]
[[13]]
[[14]]
[[15]]
| Correlation between Blood Parameters and Blood Pb Levels | ||
|---|---|---|
| Nutritional Variable | Correlation Coefficient (r) | P-value |
| wbc | 0.030 | 0.6289 |
| lym_perc | 0.113 | 0.0639 |
| mono_perc | -0.093 | 0.1261 |
| gran_perc | -0.084 | 0.1698 |
| lym_mm | 0.112 | 0.0652 |
| mono_mm | -0.089 | 0.1445 |
| gra_mm | -0.067 | 0.2741 |
| rbc | 0.135 | 0.0265 |
| hgb | 0.011 | 0.8603 |
| hct | 0.048 | 0.4280 |
| mcv | -0.073 | 0.2320 |
| rdwcv | 0.037 | 0.5449 |
| plt | 0.063 | 0.2988 |
| Blood Parameter | Odds Ratio (per 10-unit increase) | 95% CI Lower | 95% CI Upper | P-value |
|---|---|---|---|---|
| wbc | 0.82 | 0.36 | 1.84 | 0.63 |
| lym_perc | 1.29 | 1.04 | 1.61 | 0.02 |
| mono_perc | 0.33 | 0.09 | 0.91 | 0.06 |
| gran_perc | 0.83 | 0.67 | 1.02 | 0.08 |
| lym_mm | 2.54 | 0.65 | 10.34 | 0.18 |
| mono_mm | 0.00 | 0.00 | 0.11 | 0.03 |
| gra_mm | 0.37 | 0.11 | 1.04 | 0.09 |
| rbc | 36.69 | 0.40 | 3825.74 | 0.12 |
| hgb | 2.96 | 0.57 | 16.41 | 0.20 |
| hct | 1.76 | 0.96 | 3.36 | 0.07 |
| mcv | 1.07 | 0.81 | 1.42 | 0.62 |
| rdwcv | 0.74 | 0.24 | 2.23 | 0.59 |
| plt | 1.00 | 0.98 | 1.02 | 0.99 |
Findings: Complete blood count parameters such as hemoglobin, hematocrit, red blood cell count, mean corpuscular volume, mean corpuscular hemoglobin, mean corpuscular hemoglobin concentration, platelet count and white blood cell count are all negatively correlated with blood lead levels. These are possible consequences of high blood lead levels.
[[1]]
[[2]]
[[3]]
[[4]]
[[5]]
[[6]]
[[7]]
[[8]]
[[9]]
[[10]]
[[11]]
[[12]]
[[13]]
We selected four groups of modifiable risk factors for adjusted analysis based on the literature and our unadjusted analysis: 1) drinking water source, 2) micronutrient deficiency, 3) malnutrition status, and 4) diet poor in micronutrients. We ran a separate regression model for each of the exposure variables in these groups adjusted for a set of variables based on the causal diagram shown above.
| Characteristic | N | OR1 | 95% CI | p-value |
|---|---|---|---|---|
| drink_water | 269 |
|
|
|
| Bore well |
|
— | — |
|
| Open well |
|
0.66 | 0.21, 1.85 | 0.4 |
| Others |
|
1.69 | 0.76, 3.77 | 0.2 |
| Surface/Spring water |
|
2.08 | 0.08, 57.1 | 0.6 |
| Tap water |
|
1.04 | 0.55, 1.96 |
0.9 |
| Water tanker |
|
1.46 | 0.36, 6.47 | 0.6 |
| age_gp | 269 |
|
|
|
| 1-2 |
|
— | — |
|
| 2-3 |
|
0.79 | 0.34, 1.80 | 0.6 |
| 3-4 |
|
0.58 | 0.26, 1.28 | 0.2 |
| 4-5 |
|
0.69 | 0.31, 1.51 | 0.4 |
| Gender | 269 |
|
|
|
| Female |
|
— | — |
|
| Male |
|
1.05 | 0.63, 1.77 | 0.8 |
| Type of House | 269 |
|
|
|
| Pucca |
|
— | — |
|
| Semi-pucca |
|
1.16 | 0.58, 2.35 | 0.7 |
| Kutcha |
|
1.17 | 0.56, 2.46 | 0.7 |
| PSU Rural/Urban | 269 |
|
|
|
| Rural |
|
— | — |
|
| Urban |
|
3.50 | 1.72, 7.39 | <0.001 |
| Wealth Index | 269 |
|
|
|
| Highest |
|
— | — |
|
| Higher |
|
0.58 | 0.20, 1.65 | 0.3 |
| Middle |
|
0.61 | 0.20, 1.81 | 0.4 |
| Lower |
|
0.66 | 0.23, 1.80 | 0.4 |
| Lowest |
|
0.54 | 0.20, 1.46 | 0.2 |
| Abbreviations: CI = Confidence Interval, OR = Odds Ratio | ||||
| 1 Adjusted for age group, gender, type of house, rural/urban, and wealth index | ||||
| Characteristic | N | OR1 | 95% CI | p-value |
|---|---|---|---|---|
| Anemia status | 270 |
|
|
|
| No Anemia |
|
— | — |
|
| Any Anemia |
|
0.70 | 0.41, 1.16 | 0.2 |
| age_gp | 270 |
|
|
|
| 1-2 |
|
— | — |
|
| 2-3 |
|
0.76 | 0.33, 1.71 | 0.5 |
| 3-4 |
|
0.55 | 0.25, 1.21 | 0.14 |
| 4-5 |
|
0.65 | 0.30, 1.42 | 0.3 |
| Gender | 270 |
|
|
|
| Female |
|
— | — |
|
| Male |
|
1.10 | 0.66, 1.83 | 0.7 |
| Type of House | 270 |
|
|
|
| Pucca |
|
— | — |
|
| Semi-pucca |
|
1.20 | 0.60, 2.43 | 0.6 |
| Kutcha |
|
1.29 | 0.63, 2.67 | 0.5 |
| PSU Rural/Urban | 270 |
|
|
|
| Rural |
|
— | — |
|
| Urban |
|
3.55 | 1.82, 7.20 | <0.001 |
| Wealth Index | 270 |
|
|
|
| Highest |
|
— | — |
|
| Higher |
|
0.59 | 0.21, 1.65 | 0.3 |
| Middle |
|
0.64 | 0.22, 1.88 | 0.4 |
| Lower |
|
0.65 | 0.24, 1.77 | 0.4 |
| Lowest |
|
0.55 | 0.20, 1.46 | 0.2 |
| Abbreviations: CI = Confidence Interval, OR = Odds Ratio | ||||
| 1 Adjusted for age group, gender, type of house, rural/urban, and wealth index | ||||
| Characteristic | N | OR1 | 95% CI | p-value |
|---|---|---|---|---|
| Stunting status | 211 |
|
|
|
| No Stunting |
|
— | — |
|
| Stunting |
|
1.12 | 0.54, 2.31 | 0.8 |
| Severe Stunting |
|
0.90 | 0.38, 2.11 | 0.8 |
| age_gp | 211 |
|
|
|
| 1-2 |
|
— | — |
|
| 2-3 |
|
0.45 | 0.16, 1.20 | 0.12 |
| 3-4 |
|
0.35 | 0.14, 0.88 | 0.028 |
| 4-5 |
|
0.32 | 0.12, 0.82 | 0.020 |
| Gender | 211 |
|
|
|
| Female |
|
— | — |
|
| Male |
|
0.90 | 0.49, 1.64 | 0.7 |
| Type of House | 211 |
|
|
|
| Pucca |
|
— | — |
|
| Semi-pucca |
|
0.80 | 0.35, 1.82 | 0.6 |
| Kutcha |
|
1.03 | 0.44, 2.42 |
0.9 |
| PSU Rural/Urban | 211 |
|
|
|
| Rural |
|
— | — |
|
| Urban |
|
4.29 | 1.96, 10.0 | <0.001 |
| Wealth Index | 211 |
|
|
|
| Highest |
|
— | — |
|
| Higher |
|
0.42 | 0.11, 1.48 | 0.2 |
| Middle |
|
0.71 | 0.17, 2.82 | 0.6 |
| Lower |
|
0.50 | 0.14, 1.68 | 0.3 |
| Lowest |
|
0.69 | 0.20, 2.34 | 0.6 |
| Abbreviations: CI = Confidence Interval, OR = Odds Ratio | ||||
| 1 Adjusted for age group, gender, type of house, rural/urban, and wealth index | ||||
| Characteristic | N | OR1 | 95% CI | p-value |
|---|---|---|---|---|
| Wasting status | 208 |
|
|
|
| No Wasting |
|
— | — |
|
| Wasting |
|
3.03 | 1.17, 8.43 | 0.026 |
| Severe Wasting |
|
0.79 | 0.09, 5.31 | 0.8 |
| age_gp | 208 |
|
|
|
| 1-2 |
|
— | — |
|
| 2-3 |
|
0.49 | 0.18, 1.29 | 0.2 |
| 3-4 |
|
0.39 | 0.15, 0.98 | 0.048 |
| 4-5 |
|
0.34 | 0.13, 0.87 | 0.027 |
| Gender | 208 |
|
|
|
| Female |
|
— | — |
|
| Male |
|
0.95 | 0.52, 1.73 | 0.9 |
| Type of House | 208 |
|
|
|
| Pucca |
|
— | — |
|
| Semi-pucca |
|
1.04 | 0.45, 2.42 |
0.9 |
| Kutcha |
|
1.24 | 0.52, 2.96 | 0.6 |
| PSU Rural/Urban | 208 |
|
|
|
| Rural |
|
— | — |
|
| Urban |
|
4.49 | 2.01, 10.7 | <0.001 |
| Wealth Index | 208 |
|
|
|
| Highest |
|
— | — |
|
| Higher |
|
0.32 | 0.08, 1.17 | 0.089 |
| Middle |
|
0.66 | 0.16, 2.64 | 0.6 |
| Lower |
|
0.39 | 0.11, 1.35 | 0.14 |
| Lowest |
|
0.49 | 0.13, 1.69 | 0.3 |
| Abbreviations: CI = Confidence Interval, OR = Odds Ratio | ||||
| 1 Adjusted for age group, gender, type of house, rural/urban, and wealth index | ||||
| Characteristic | N | OR1 | 95% CI | p-value |
|---|---|---|---|---|
| Underweight status | 212 |
|
|
|
| No Underweight |
|
— | — |
|
| Underweight |
|
1.33 | 0.67, 2.66 | 0.4 |
| Severe Underweight |
|
0.92 | 0.31, 2.68 | 0.9 |
| age_gp | 212 |
|
|
|
| 1-2 |
|
— | — |
|
| 2-3 |
|
0.45 | 0.16, 1.17 | 0.11 |
| 3-4 |
|
0.35 | 0.13, 0.87 | 0.026 |
| 4-5 |
|
0.32 | 0.12, 0.80 | 0.018 |
| Gender | 212 |
|
|
|
| Female |
|
— | — |
|
| Male |
|
0.91 | 0.50, 1.66 | 0.8 |
| Type of House | 212 |
|
|
|
| Pucca |
|
— | — |
|
| Semi-pucca |
|
0.89 | 0.40, 2.01 | 0.8 |
| Kutcha |
|
1.04 | 0.45, 2.42 |
0.9 |
| PSU Rural/Urban | 212 |
|
|
|
| Rural |
|
— | — |
|
| Urban |
|
4.45 | 2.02, 10.4 | <0.001 |
| Wealth Index | 212 |
|
|
|
| Highest |
|
— | — |
|
| Higher |
|
0.40 | 0.11, 1.41 | 0.2 |
| Middle |
|
0.69 | 0.17, 2.71 | 0.6 |
| Lower |
|
0.48 | 0.14, 1.62 | 0.2 |
| Lowest |
|
0.67 | 0.19, 2.26 | 0.5 |
| Abbreviations: CI = Confidence Interval, OR = Odds Ratio | ||||
| 1 Adjusted for age group, gender, type of house, rural/urban, and wealth index | ||||
| Characteristic | N | OR1 | 95% CI | p-value |
|---|---|---|---|---|
| MUAC Group | 213 |
|
|
|
| Normal |
|
— | — |
|
| severewasting |
|
1.29 | 0.21, 10.8 | 0.8 |
| age_gp | 213 |
|
|
|
| 1-2 |
|
— | — |
|
| 2-3 |
|
0.47 | 0.17, 1.23 | 0.13 |
| 3-4 |
|
0.37 | 0.14, 0.91 | 0.035 |
| 4-5 |
|
0.34 | 0.13, 0.85 | 0.025 |
| Gender | 213 |
|
|
|
| Female |
|
— | — |
|
| Male |
|
0.90 | 0.50, 1.62 | 0.7 |
| Type of House | 213 |
|
|
|
| Pucca |
|
— | — |
|
| Semi-pucca |
|
0.89 | 0.40, 2.00 | 0.8 |
| Kutcha |
|
1.09 | 0.47, 2.52 | 0.8 |
| PSU Rural/Urban | 213 |
|
|
|
| Rural |
|
— | — |
|
| Urban |
|
4.31 | 1.97, 10.0 | <0.001 |
| Wealth Index | 213 |
|
|
|
| Highest |
|
— | — |
|
| Higher |
|
0.41 | 0.11, 1.44 | 0.2 |
| Middle |
|
0.68 | 0.17, 2.65 | 0.6 |
| Lower |
|
0.48 | 0.13, 1.61 | 0.2 |
| Lowest |
|
0.65 | 0.19, 2.18 | 0.5 |
| Abbreviations: CI = Confidence Interval, OR = Odds Ratio | ||||
| 1 Adjusted for age group, gender, type of house, rural/urban, and wealth index | ||||
| Characteristic | N | OR1 | 95% CI | p-value |
|---|---|---|---|---|
| Iron Intake (mg/day) | 215 | 0.98 | 0.91, 1.06 | 0.6 |
| age_gp | 215 |
|
|
|
| 1-2 |
|
— | — |
|
| 2-3 |
|
0.91 | 0.36, 2.29 | 0.8 |
| 3-4 |
|
0.55 | 0.22, 1.38 | 0.2 |
| 4-5 |
|
0.71 | 0.29, 1.72 | 0.4 |
| Gender | 215 |
|
|
|
| Female |
|
— | — |
|
| Male |
|
1.07 | 0.60, 1.91 | 0.8 |
| Type of House | 215 |
|
|
|
| Pucca |
|
— | — |
|
| Semi-pucca |
|
1.00 | 0.45, 2.24 |
0.9 |
| Kutcha |
|
1.12 | 0.50, 2.54 | 0.8 |
| PSU Rural/Urban | 215 |
|
|
|
| Rural |
|
— | — |
|
| Urban |
|
3.22 | 1.52, 7.09 | 0.003 |
| Wealth Index | 215 |
|
|
|
| Highest |
|
— | — |
|
| Higher |
|
0.45 | 0.13, 1.47 | 0.2 |
| Middle |
|
0.58 | 0.16, 2.04 | 0.4 |
| Lower |
|
0.54 | 0.17, 1.66 | 0.3 |
| Lowest |
|
0.45 | 0.14, 1.39 | 0.2 |
| Abbreviations: CI = Confidence Interval, OR = Odds Ratio | ||||
| 1 Adjusted for age group, gender, type of house, rural/urban, and wealth index | ||||
| Characteristic | N | OR1 | 95% CI | p-value |
|---|---|---|---|---|
| Zinc Intake (mg/day) | 215 | 0.87 | 0.74, 1.02 | 0.10 |
| age_gp | 215 |
|
|
|
| 1-2 |
|
— | — |
|
| 2-3 |
|
0.98 | 0.39, 2.46 |
0.9 |
| 3-4 |
|
0.64 | 0.25, 1.60 | 0.3 |
| 4-5 |
|
0.85 | 0.34, 2.12 | 0.7 |
| Gender | 215 |
|
|
|
| Female |
|
— | — |
|
| Male |
|
1.08 | 0.60, 1.93 | 0.8 |
| Type of House | 215 |
|
|
|
| Pucca |
|
— | — |
|
| Semi-pucca |
|
0.98 | 0.44, 2.18 |
0.9 |
| Kutcha |
|
1.13 | 0.50, 2.54 | 0.8 |
| PSU Rural/Urban | 215 |
|
|
|
| Rural |
|
— | — |
|
| Urban |
|
3.36 | 1.57, 7.47 | 0.002 |
| Wealth Index | 215 |
|
|
|
| Highest |
|
— | — |
|
| Higher |
|
0.41 | 0.12, 1.35 | 0.15 |
| Middle |
|
0.62 | 0.17, 2.19 | 0.5 |
| Lower |
|
0.53 | 0.16, 1.62 | 0.3 |
| Lowest |
|
0.44 | 0.14, 1.35 | 0.2 |
| Abbreviations: CI = Confidence Interval, OR = Odds Ratio | ||||
| 1 Adjusted for age group, gender, type of house, rural/urban, and wealth index | ||||
| Characteristic | N | OR1 | 95% CI | p-value |
|---|---|---|---|---|
| Calcium Intake (mg/day) | 215 | 1.00 | 1.00, 1.00 | 0.9 |
| age_gp | 215 |
|
|
|
| 1-2 |
|
— | — |
|
| 2-3 |
|
0.89 | 0.35, 2.23 | 0.8 |
| 3-4 |
|
0.52 | 0.21, 1.26 | 0.15 |
| 4-5 |
|
0.66 | 0.28, 1.57 | 0.4 |
| Gender | 215 |
|
|
|
| Female |
|
— | — |
|
| Male |
|
1.07 | 0.60, 1.92 | 0.8 |
| Type of House | 215 |
|
|
|
| Pucca |
|
— | — |
|
| Semi-pucca |
|
1.00 | 0.45, 2.26 |
0.9 |
| Kutcha |
|
1.13 | 0.50, 2.59 | 0.8 |
| PSU Rural/Urban | 215 |
|
|
|
| Rural |
|
— | — |
|
| Urban |
|
3.21 | 1.50, 7.13 | 0.003 |
| Wealth Index | 215 |
|
|
|
| Highest |
|
— | — |
|
| Higher |
|
0.48 | 0.14, 1.52 | 0.2 |
| Middle |
|
0.59 | 0.16, 2.06 | 0.4 |
| Lower |
|
0.56 | 0.18, 1.69 | 0.3 |
| Lowest |
|
0.46 | 0.15, 1.42 | 0.2 |
| Abbreviations: CI = Confidence Interval, OR = Odds Ratio | ||||
| 1 Adjusted for age group, gender, type of house, rural/urban, and wealth index | ||||
| Characteristic | N | OR1 | 95% CI | p-value |
|---|---|---|---|---|
| Vitamin C Intake (mg/day) | 215 | 1.01 | 1.00, 1.03 | 0.016 |
| age_gp | 215 |
|
|
|
| 1-2 |
|
— | — |
|
| 2-3 |
|
0.78 | 0.31, 1.95 | 0.6 |
| 3-4 |
|
0.38 | 0.15, 0.94 | 0.037 |
| 4-5 |
|
0.55 | 0.23, 1.29 | 0.2 |
| Gender | 215 |
|
|
|
| Female |
|
— | — |
|
| Male |
|
1.11 | 0.62, 2.00 | 0.7 |
| Type of House | 215 |
|
|
|
| Pucca |
|
— | — |
|
| Semi-pucca |
|
1.01 | 0.45, 2.30 |
0.9 |
| Kutcha |
|
1.10 | 0.49, 2.53 | 0.8 |
| PSU Rural/Urban | 215 |
|
|
|
| Rural |
|
— | — |
|
| Urban |
|
3.00 | 1.40, 6.65 | 0.005 |
| Wealth Index | 215 |
|
|
|
| Highest |
|
— | — |
|
| Higher |
|
0.46 | 0.14, 1.51 | 0.2 |
| Middle |
|
0.64 | 0.18, 2.24 | 0.5 |
| Lower |
|
0.55 | 0.17, 1.69 | 0.3 |
| Lowest |
|
0.48 | 0.15, 1.49 | 0.2 |
| Abbreviations: CI = Confidence Interval, OR = Odds Ratio | ||||
| 1 Adjusted for age group, gender, type of house, rural/urban, and wealth index | ||||
Note: Each variable is a separate logistic regression model adjusted for a common set of variables (age, gender, rural/urban and wealth index).
Comments from DG
Why don’t you try adjustment for age, gender, type of house, rural/urban, and wealth index for exposures 1) drinking water, 2) anthropometry, 3) micronutrient status, 4) dietary energy, protein and micronutrient intake. Of these 1) and 4) can be considered to be exposure factors. 2) and 3) are equally likely to be the cause or effect of high blood lead. Or that all modifiable and non modifiable factors are simply associated with environmental exposure to lead. Poor, urban, children who are malnourished, anemic and have poor energy, protein and micronutrient intake.