Objective:To gain a understanding of the occurrence of cognitive impairment among residents in drinking water-borne endemic fluorosis (drinking water-borne fluorosis) areas, and to study its influencing factors.Methods:In March 2023, a cluster sampling method was used to select local residents aged 18 and above from the drinking water-borne fluorosis areas in Jishan County, Shanxi Province as survey subjects. General demographic data were collected through face-to-face surveys, and a random urine sample was collected once to determine urinary fluoride level. Cognitive function was assessed using the mini-mental state examination (MMSE), and the survey subjects were divided into a cognitive impairment group ( < 27 points) and a control group (27 - 30 points) based on the MMSE scores. A multiple logistic regression model and a decision tree model based on chi-squared automatic interaction detector were constructed to analyze the factors affecting cognitive impairment, and the model fitting effect was evaluated using receiver operating characteristic (ROC) curve.Results:A total of 3 301 subjects were included in the survey, including 2 081 females and 1 220 males. There were 1 515 subjects < 60 years old and 1 786 subjects ≥60 years old, with urinary fluoride level [ M ( Q1, Q3)] of 2.92 (1.78, 4.54) mg/L. There were 1 939 cases in the cognitive impairment group and 1 362 cases in the control group, with a detection rate of 58.74% (1 939/3 301) for cognitive impairment; and the differences in gender, age, education level, marital status, annual household income, alcohol consumption, smoking distribution, and urinary fluoride level between the two groups were statistically significant ( P < 0.05). The results of multiple logistic regression analysis showed that female, ≥60 years, and urinary fluoride > 4.54 mg/L were risk factors for cognitive impairment [ OR (95% CI): 1.25 (1.01, 1.54), 2.66 (2.26, 3.14), 1.32 (1.06, 1.65), P < 0.05]. Education level of primary school or above, annual household income≥12 000 yuan, and mild alcohol consumption were protective factors for cognitive impairment [ OR (95% CI): 0.15 (0.09, 0.25), 0.58 (0.48, 0.68), 0.67 (0.51, 0.87), P < 0.05]. The analysis results of the decision tree model showed that age had the greatest impact on the occurrence of cognitive impairment, followed by annual household income, education level, and urinary fluoride. The areas under the ROC curves of the multiple logistic regression and decision tree model were 0.72 and 0.70 ( P < 0.001), respectively, indicating good model fitting performance. Conclusion:The detection rate of cognitive impairment in residents of drinking water-borne fluorosis areas is relatively high, and age, annual household income, education level, and urinary fluoride are all influencing factors for occurrence of cognitive impairment.

Objective:To gain a understanding of the occurrence of cognitive impairment among residents in drinking water-borne endemic fluorosis (drinking water-borne fluorosis) areas, and to study its influencing factors.Methods:In March 2023, a cluster sampling method was used to select local residents aged 18 and above from the drinking water-borne fluorosis areas in Jishan County, Shanxi Province as survey subjects. General demographic data were collected through face-to-face surveys, and a random urine sample was collected once to determine urinary fluoride level. Cognitive function was assessed using the mini-mental state examination (MMSE), and the survey subjects were divided into a cognitive impairment group ( < 27 points) and a control group (27 - 30 points) based on the MMSE scores. A multiple logistic regression model and a decision tree model based on chi-squared automatic interaction detector were constructed to analyze the factors affecting cognitive impairment, and the model fitting effect was evaluated using receiver operating characteristic (ROC) curve.Results:A total of 3 301 subjects were included in the survey, including 2 081 females and 1 220 males. There were 1 515 subjects < 60 years old and 1 786 subjects ≥60 years old, with urinary fluoride level [ M ( Q1, Q3)] of 2.92 (1.78, 4.54) mg/L. There were 1 939 cases in the cognitive impairment group and 1 362 cases in the control group, with a detection rate of 58.74% (1 939/3 301) for cognitive impairment; and the differences in gender, age, education level, marital status, annual household income, alcohol consumption, smoking distribution, and urinary fluoride level between the two groups were statistically significant ( P < 0.05). The results of multiple logistic regression analysis showed that female, ≥60 years, and urinary fluoride > 4.54 mg/L were risk factors for cognitive impairment [ OR (95% CI): 1.25 (1.01, 1.54), 2.66 (2.26, 3.14), 1.32 (1.06, 1.65), P < 0.05]. Education level of primary school or above, annual household income≥12 000 yuan, and mild alcohol consumption were protective factors for cognitive impairment [ OR (95% CI): 0.15 (0.09, 0.25), 0.58 (0.48, 0.68), 0.67 (0.51, 0.87), P < 0.05]. The analysis results of the decision tree model showed that age had the greatest impact on the occurrence of cognitive impairment, followed by annual household income, education level, and urinary fluoride. The areas under the ROC curves of the multiple logistic regression and decision tree model were 0.72 and 0.70 ( P < 0.001), respectively, indicating good model fitting performance. Conclusion:The detection rate of cognitive impairment in residents of drinking water-borne fluorosis areas is relatively high, and age, annual household income, education level, and urinary fluoride are all influencing factors for occurrence of cognitive impairment.