Occurrence and Source of Nitrosamines and Secondary Amines in Groundwater and its Adjacent Jialu River Basin, China

The presence of mutagenic and carcinogenic nitrosamines in groundwater is of great concern. In this study, eight nitrosamines including <i>N</i>-nitrosodimethylamine (NDMA), <i>N</i>-nitrosodiethylamine (NDEA), <i>N</i>-nitrosomethylethylamine (NMEA), <i>N</i>-nitrosopyrrolidine (NPYR), <i>N</i>-nitrosomorpholine (NMOR), <i>N</i>-nitrosopiperidine (NPIP), <i>N</i>-nitrosodi-n-propylamine (NDPA), and <i>N</i>-nitrosodi-n-butylamine (NDBA) and corresponding secondary amines were investigated in shallow groundwater, river water, and wastewater samples collected from the Jialu River basin. The total concentrations of nitrosamines and secondary amines in groundwater were ND–101.1 ng/L and 0.36–4.38 μg/L, respectively. NDMA and its secondary amine DMA (44.7%/40.1%) were the predominant compounds in groundwater, followed by NDEA/DEA (21.7%/29.3%) and NDBA/DBA (26.4%/27.4%). Relatively high concentrations of these six compounds were also observed in river water that was influenced by the direct discharge of industrial and domestic wastewater. Using acesulfame as a quantitative population marker, the contribution of domestic sources to the concentrations of nitrosamines and secondary amines was 39–85% in downstream reaches of the Jialu River, and that of industrial sources was estimated to be 65–98% in other sites of the area. Both on-site leakage of domestic and industrial wastewater and leaching from river water would contribute to the occurrence of target pollutants in groundwater. The target pollutants posed a cancer risk of 4.12 × 10^–5 to the local populations due to the direct usage of groundwater as potable water

Antioxidant parameters and cognitive function according to FV intake.

<p>General linear model used. Data are presented as the mean ± SE. For antioxidant biomarker data analysis, factors including age, sex, BMI, smoking and antioxidant supplement were adjusted. For cognitive function (MoCA score) data analysis, factors including age, sex, BMI, education, family history of AD, physical activity and participation in cognitive activity were adjusted. FV, fruit and vegetable; GSH-Px, glutathione peroxidase; GST, glutathione S-transferase; GR, glutathion reductase; CAT, catalase; SOD, superoxide dismutase; GSH, glutathione; T-AOC, total antioxidant capacity; MoCA, Montreal Cognitive Assessment. <i>P</i> value<0.05 was considered as significant.</p><p>Antioxidant parameters and cognitive function according to FV intake.</p

Antioxidant parameters and cognitive function according to FV consumption and individual GST genotype.

<p>General linear model used. Data are presented as the mean ± SE. For antioxidant biomarker data analysis, factors including age, sex, BMI, smoking and antioxidant supplement were adjusted. For cognitive function (MoCA score) data analysis, factors including age, sex, BMI, education, family history of AD, physical activity and participation in cognitive activity were adjusted. FV, fruit and vegetable; GSH-Px, glutathione peroxidase; GST, glutathione S-transferase; GR, glutathion reductase; CAT, catalase; SOD, superoxide dismutase; GSH, glutathione; T-AOC, total antioxidant capacity; MoCA, Montreal Cognitive Assessment. <i>P</i> value<0.05 was considered as significant.</p>a<p>: GSTM1 genotype affect the erythrocyte GST enzyme activity, <i>P_{GSTM1 genotype}</i> = 0.012, <0.05.</p>b<p>: FV consumption affect the plasma T-AOC in the subjects with different GSTT1 genotypes, <i>P_FV</i> = 0.04, <0.05.</p>c<p>: Interaction of FV and GSTT1 genotype on cognitive function was detected, <i>P_{FV and GSTT1 genotype interaction}</i> = 0.033, <0.05.</p><p>Antioxidant parameters and cognitive function according to FV consumption and individual GST genotype.</p

Unadjusted demographic characteristics of the participants.

<p>The data of age and BMI were expressed as mean ± SE. BMI: body mass index. One-way ANOVA analysis was used to analyze the means of age and BMI.</p><p>Unadjusted demographic characteristics of the participants.</p

Graphic presentation of the overall design.

<p>Graphic presentation of the overall design.</p

Antioxidant parameters and cognitive function according to combined GST genotype.

<p>General linear model used. Data are presented as the mean ± SE. For antioxidant biomarker data analysis, factors including age, sex, BMI, smoking and antioxidant supplement were adjusted. For cognitive function (MoCA score) data analysis, factors including age, sex, BMI, education, family history of AD, physical activity and participation in cognitive activity were adjusted. GSH-Px, glutathione peroxidase; GST, glutathione S-transferase; GR, glutathion reductase; CAT, catalase; SOD, superoxide dismutase; GSH, glutathione; T-AOC, total antioxidant capacity; MoCA, Montreal Cognitive Assessment. <i>P</i> value<0.05 was considered as significant.</p><p>Antioxidant parameters and cognitive function according to combined GST genotype.</p

Antioxidant parameters and cognitive function according to individual GST genotype.

<p>General linear model used. Data are presented as the mean ± SE. For antioxidant biomarker data analysis, factors including age, sex, BMI, smoking and antioxidant supplement were adjusted. For cognitive function (MoCA score) data analysis, factors including age, sex, BMI, education, family history of AD, physical activity and participation in cognitive activity were adjusted. GSH-Px, glutathione peroxidase; GST, glutathione S-transferase; GR, glutathion reductase; CAT, catalase; SOD, superoxide dismutase; GSH, glutathione; T-AOC, total antioxidant capacity; MoCA, Montreal Cognitive Assessment. <i>P</i> value<0.05 was considered as significant.</p><p>Antioxidant parameters and cognitive function according to individual GST genotype.</p

Cost-effectiveness ratio (CER) by city in the nutrition & PA combined intervention group.

<p>^a For BMI, BAZ and overweight & obesity prevalence, the ‘effect’ means BMI, BAZ and overweight & obesity prevalence reduction (post intervention vs before intervention) in intervention group compared with that of in the control group, respectively. ^b ALL CER was presented in US dollars. ^c O & B means overweight & obesity. ^d Total’ means the average effect of four intervention centers (Jinan, Guangzhou, Harbin, Shanghai), Chongqing was excluded here because the intervention in this city was not effective (p>0.05). </p

Anthropometric characteristics and obesity prevalence at baseline, after intervention and changes in different groups<b>^</b>.

<p>^{^} Continuous variables were expressed as mean±standard error.</p><p>^{a, b}: Means shared the different letter means significant difference at baseline among groups in Beijing, p<0.05. </p><p>^{c, d} : Means shared the different letter means significant difference of changes (post-intervention vs. baseline) among groups in Beijing, p<0.05.</p><p>^* Comparison the mean between post-intervention and baseline in each group, p< 0.05.</p><p>^# Comparison means between combined intervention group and control group at baseline as well as for changes (post-intervention vs. baseline), ^# p<0.05; ^## p<0.01.</p><p>^† OR and 95% CI for overweight & obesity prevalence using generalized linear mixed model, no significantly difference of OR between nutrition or PA individual intervention group with their control group, but a borderline difference between combined intervention group with its’ control group (p=0.06). </p

Characteristics of the subjects at baseline by group.

<p>^a^b: Percentage shared the different letter means significant difference at baseline among groups in Beijing, p<0.05. ^* Significant difference (p<0.05) between control and Nutrition & PA intervention group. ^c statistical analysis and compare between intervention group with it’s control group. No superscript means no significant difference among groups.</p