Objective To establish an inductively coupled plasma-mass spectrometry(ICP-MS)method for the analysis of 29 mineral elements in Artemisiae Argyi Folium(AAF),and to develop a model for judging the origin of AAF based on the elemental fingerprint combined with chemometrics.Methods The variance method was used to compare the contents of 29 mineral elements in AAF samples from Qichun of Hubei province,Hebei province and Henan province,respectively.The discriminant models of AAF from different habitats were established by discriminant analysis,PLS-DA and PCA-Logistic regression algorithms.Results The differences of the 22 elements(V,Cr,Ni,As,Se,Rb,Mo,Cd,Sb,Ba,Hg,Pb,K,Li,B,Mg,Al,P,Ca,Fe,Zn,and Ga)in samples from Qichun of Hubei province,Hebei province and Henan province are extremely significant(P＜0.01).The discriminant analysis model showed that eight kinds of element variables(P,Cr,K,Li,Hg,Ba,Mg,and Mo),which have a significant effect on the origin discrimination are gradually introduced into the discriminant model,and the correct rate of back test is 100％.The correct rate of"leave one method"cross-validation is 96.7％.The PLS-DA model showed good prediction ability,and the variable importance projection values of K,P and Mg elements were greater than one,which could be used as the difference marker of AAF from different habitats.The accuracy of the origin discrimination model constructed by PC A-Logistic regression analysis was 100％.The elements with high first principal component loadings were Li,B,Mg,Al,P,K,Ca,V,Cr,Fe,Ni,Zn,As,Rb,Cd,Sb,and Ba.Conclusion This study shows that elemental fingerprint technology combined with chemometric analysis can identify AAF from Qichun of Hubei province,Hebei province,or Henan,providing technical support for the traceability of the origin of Artemisia argyi.

Objective To establish an inductively coupled plasma-mass spectrometry(ICP-MS)method for the analysis of 29 mineral elements in Artemisiae Argyi Folium(AAF),and to develop a model for judging the origin of AAF based on the elemental fingerprint combined with chemometrics.Methods The variance method was used to compare the contents of 29 mineral elements in AAF samples from Qichun of Hubei province,Hebei province and Henan province,respectively.The discriminant models of AAF from different habitats were established by discriminant analysis,PLS-DA and PCA-Logistic regression algorithms.Results The differences of the 22 elements(V,Cr,Ni,As,Se,Rb,Mo,Cd,Sb,Ba,Hg,Pb,K,Li,B,Mg,Al,P,Ca,Fe,Zn,and Ga)in samples from Qichun of Hubei province,Hebei province and Henan province are extremely significant(P＜0.01).The discriminant analysis model showed that eight kinds of element variables(P,Cr,K,Li,Hg,Ba,Mg,and Mo),which have a significant effect on the origin discrimination are gradually introduced into the discriminant model,and the correct rate of back test is 100％.The correct rate of"leave one method"cross-validation is 96.7％.The PLS-DA model showed good prediction ability,and the variable importance projection values of K,P and Mg elements were greater than one,which could be used as the difference marker of AAF from different habitats.The accuracy of the origin discrimination model constructed by PC A-Logistic regression analysis was 100％.The elements with high first principal component loadings were Li,B,Mg,Al,P,K,Ca,V,Cr,Fe,Ni,Zn,As,Rb,Cd,Sb,and Ba.Conclusion This study shows that elemental fingerprint technology combined with chemometric analysis can identify AAF from Qichun of Hubei province,Hebei province,or Henan,providing technical support for the traceability of the origin of Artemisia argyi.

Objective:To determine the prevalence and risk factors of constipation in Hangzhou urban areas by analyzing data from a recent epidemiological survey.Methods:From August 2022 to June 2023, a cross-sectional survey was conducted on 43 communities on eight streets in suburbs of Hangzhou, including Wangjiang, Sijiqing, Puyan, Changhe, Ziyang, Xiaoshanchengxiang, Zhuantang, and Banshan. Written questionnaires were filled out face to face by community doctors. The prevalence of constipation was investigated using a combination of the Bristol stool typing method and the Rome IV criteria. The risk factors for constipation were analyzed using multivariate logistic regression analysis.Results:The study cohort comprised 10,479 participants, 5551 of whom were male (53.0%) and 4928 female (47.0%). The overall prevalence of constipation was 10.6% (1107/10,479). The prevalence was 11.0% (613/5551) for male and 10.0% (494/4928) for female participants; this difference is not statistically significant ( P>0.05).There were no significant differences in the prevalence of constipation between different categories of body mass index ( P>0.05). The prevalence of constipation was highest in individuals aged 70 years and above, accounting for 15.4% (264/1717) of all cases. There were significant differences in the prevalence of constipation between different occupations, marital statuses, and educational levels ( P<0.001). Patients with hypertension or diabetes mellitus had a higher prevalence of constipation than those without these conditions, those who had been taking long-term medication had a higher prevalence of constipation than those who did not, parents of children with constipation had a higher prevalence of constipation than those with children who did not have constipation, and there were other significant differences in various variables ( P<0.001). Multivariate logistic regression analysis of modifiable factors revealed that eating less fruit (OR=1.284, 95%CI: 1.061–1.553, P=0.010), liking spicy and salty food (OR=1.234, 95%CI: 1.039–1.466, P=0.016), sleeping for too long (OR=1.644, 95%CI: 1.260–2.144, P<0.001), irregular sleep patterns (OR=1.370, 95%CI: 1.127–1.665, P=0.002) and minimal exercise (OR=1.388, 95% CI: 1.168–1.649, P<0.001) were all risk factors for constipation; whereas mix diets (OR=0.709,95%CI:0.608–0.826, P<0.001), meat diets (OR=0.604,95%CI: 0.495–0.736, P<0.001), moderate alcohol consumption (OR=0.659, 95% CI: 0.534–0.812, P<0.001), less or no drinking (OR=0.523, 95% CI: 0.428–0.638, P<0.001), and non-smoking (OR=0.819, 95%CI:0.674–0.995, P<0.001) protected against constipation. We found no association between dietary preferences and the risk of constipation (refined grains: OR=1.147, 95%CI:0.944–1.393, P=0.167; no specific preference: OR=0.935, 95%CI:0.783–1.117, P=0.459). The rate of agreement between self-evaluation of constipation by the respondents and objective criteria was higher for negatives (95.8%) than for positives (38.0%). Conclusion:The prevalence of constipation is relatively high in the urban population of Hangzhou. A good lifestyle and diet can significantly reduce its incidence. There should be more emphasis on preventive education, promotion of prevention of constipation, and advocacy for a healthy lifestyle.

Objective:To determine the prevalence and risk factors of constipation in Hangzhou urban areas by analyzing data from a recent epidemiological survey.Methods:From August 2022 to June 2023, a cross-sectional survey was conducted on 43 communities on eight streets in suburbs of Hangzhou, including Wangjiang, Sijiqing, Puyan, Changhe, Ziyang, Xiaoshanchengxiang, Zhuantang, and Banshan. Written questionnaires were filled out face to face by community doctors. The prevalence of constipation was investigated using a combination of the Bristol stool typing method and the Rome IV criteria. The risk factors for constipation were analyzed using multivariate logistic regression analysis.Results:The study cohort comprised 10,479 participants, 5551 of whom were male (53.0%) and 4928 female (47.0%). The overall prevalence of constipation was 10.6% (1107/10,479). The prevalence was 11.0% (613/5551) for male and 10.0% (494/4928) for female participants; this difference is not statistically significant ( P>0.05).There were no significant differences in the prevalence of constipation between different categories of body mass index ( P>0.05). The prevalence of constipation was highest in individuals aged 70 years and above, accounting for 15.4% (264/1717) of all cases. There were significant differences in the prevalence of constipation between different occupations, marital statuses, and educational levels ( P<0.001). Patients with hypertension or diabetes mellitus had a higher prevalence of constipation than those without these conditions, those who had been taking long-term medication had a higher prevalence of constipation than those who did not, parents of children with constipation had a higher prevalence of constipation than those with children who did not have constipation, and there were other significant differences in various variables ( P<0.001). Multivariate logistic regression analysis of modifiable factors revealed that eating less fruit (OR=1.284, 95%CI: 1.061–1.553, P=0.010), liking spicy and salty food (OR=1.234, 95%CI: 1.039–1.466, P=0.016), sleeping for too long (OR=1.644, 95%CI: 1.260–2.144, P<0.001), irregular sleep patterns (OR=1.370, 95%CI: 1.127–1.665, P=0.002) and minimal exercise (OR=1.388, 95% CI: 1.168–1.649, P<0.001) were all risk factors for constipation; whereas mix diets (OR=0.709,95%CI:0.608–0.826, P<0.001), meat diets (OR=0.604,95%CI: 0.495–0.736, P<0.001), moderate alcohol consumption (OR=0.659, 95% CI: 0.534–0.812, P<0.001), less or no drinking (OR=0.523, 95% CI: 0.428–0.638, P<0.001), and non-smoking (OR=0.819, 95%CI:0.674–0.995, P<0.001) protected against constipation. We found no association between dietary preferences and the risk of constipation (refined grains: OR=1.147, 95%CI:0.944–1.393, P=0.167; no specific preference: OR=0.935, 95%CI:0.783–1.117, P=0.459). The rate of agreement between self-evaluation of constipation by the respondents and objective criteria was higher for negatives (95.8%) than for positives (38.0%). Conclusion:The prevalence of constipation is relatively high in the urban population of Hangzhou. A good lifestyle and diet can significantly reduce its incidence. There should be more emphasis on preventive education, promotion of prevention of constipation, and advocacy for a healthy lifestyle.