1.Analysis of the risk factors of female breast cancer
Xijin MAO ; Chengyan XING ; Shenghua ZHANG
Chinese Journal of Primary Medicine and Pharmacy 2013;20(2):187-190
Objective To explore the risk factors of female breast cancer and provide the basis for the etiology of female breast cancer,the identification of the high-risk population and the development of effective intervention measures.Methods The breast cancer patients who were confirmed by pathology were collected,and screened for healthy women whose age and living environment were similar to breast cancer patients.The questionnaire was used to collect risk-factors of breast cancer.The x2 test were used to analyze statistical difference of case group and control group.1 ∶ 2 logistic regression was used to analyze the relationship between risk factors and female breast cancer.Results There were 184 breast cancer patients and 368 healthy women in research.Benign breast disease,breastfeeding,abortion,depression,smoking,passive smoking,eating fried or smoked foods,drinking tea had statistical differences between case group and control group.And benign breast lesions(OR =1.553,95% CI 2.045 ~ 10.924),abortion(OR =0.775,95 % CI 1.423 ~ 3.309),smoking(OR =0.674,95% CI 1.009 ~ 3.817) passive smoking (OR =2.98,95% CI 1.680 ~ 3.720) were the risk factors of breast cancer,and drink tea(OR =-0.425,95% CI 0.446 ~ 0.958),eating soy products (OR =-0.687,95 % CI 0.284 ~ 0.889) breast-feeding (OR =-0.827,95%CI 0.193 ~ 0.991) were the protective factors of breast cancer.Conclusion The risk factors of female breast cancer in Binzhou are benign breast disease,abortion,passive smoking,depression,and the protective factors are drinking tea and breast-feeding.
2.The impacts of case definition of influenza-like illness on influenza surveillance
Yaxu ZHENG ; Chenyan JIANG ; Shenghua MAO ; Dechuan KONG ; Jian CHEN
Chinese Journal of Disease Control & Prevention 2017;21(9):895-899
Objective To compare the detection situation of influenza-like illnesses with different symptoms and analyze the impact on the influenza surveillance by adopting different case definitions of influenza-like illness.Methods Data was collected from 2 national influenza surveillance sentinel hospitals in Shanghai,2015.We compared the positive rate of influenza virus among patients with different symptoms (with cough and sore throat,with cough only and with sore throat only),and utilized Logistic regression model to analyze the influencing factors of the detection rate of influenza virus.Results Among 2 010 influenza-like illnesses,1 105 patients were with cough and sore throat,270 patients were with cough,635 patients were with sore throat,and the positive rate of influenza was 36.2%,39.3% and 15.9% respectively.The patients with cough and sore throat or with cough only had a higher positive rate of influenza than patients with sore throat (all P < 0.05).For patients with specimens collected within 3 days,patients with cough and sore throat,or with cough only had a higher positive rate than patients with sore throat only (all P < 0.05).Logistic regression results showed that fever (body temperature≥39 ℃) (OR =1.719,95% CI:1.389-2.127) and cough (OR =3.046,95% CI:2.377-3.905) were associated with the detection of influenza virus.Conclusions We suggested that we can adopt the case definition of influenza-like illness'fever (body temperature ≥38 C) and cough'in the influenza surveillance system.
3.Epidemiological surveillance of hand, foot and mouth disease in Shanghai, 2010-2014.
Yanling GE ; Yaxu ZHENG ; Hao PAN ; Shenghua MAO ; Yuefang LI ; Aimei XIA ; Qirong ZHU ; Jiayu HU ; Mei ZENG
Chinese Journal of Pediatrics 2015;53(9):676-683
OBJECTIVETo understand the epidemiological profiles of hand, foot and mouth disease (HFMD) and the major enteroviruses causing the epidemics of HFMD in Shanghai from 2010 to 2014.
METHODThe city-wide surveillance data between 2010 and 2014 were used to analyze the epidemiologic characteristics of the HFMD outbreaks in Shanghai. The annual incidence of HFMD was estimated based on the 2010 Shanghai Census data.
RESULTFrom 2010 to 2014, the reported HFMD cases were 41 080, 37 323, 51 172, 42 198, and 65 018, respectively; the severe cases (case-severity ratio) were 469 (1.14%), 456 (1.22%), 318 (0.62%), 104 (0.25%) and 248 (0.38%), respectively. Based on Shanghai census data by the end of 2010, the attack rates of HFMD in Shanghai were 0.16%-0.28% in the entire population. In terms of the proportion of HFMD cases and severe cases in the specific population, male accounted for 59.62%-61.48% and 62.26%-73.08%, migrant population accounted for 51.86%-62.40% and 72.01%-80.38%; children aged 1.0-1.9 years comprised the highest proportion, up to 22.70%-27.00% and 32.08%-36.40%. HFMD peaked from April to July, in parallel with the peak circulation of enterovirus (EV) 71, and a small peak usually occurred in autumn and winter. All the critically severe and fatal cases were caused by EV71. The detection rates of EV71 and Coxsackievirus A (CA) 16 were 73.08%-88.09% and 1.12%-2.90% in severe HFMD cases, 19.75%-48.74% and 2.02%-23.69% in uncomplicated inpatients, and 16.78%-40.08% and 8.36%-33.39% in mild community cases, respectively. The detection rates of CA6 and CA10 in the mild community cases in 2014 were 18.38% and 1.43%, respectively. In 2013 non-EV71 and non-CA16 enteroviruses comprised 74.86% in the community cases.
CONCLUSIONThe annual HFMD outbreaks occurred in Shanghai during 2010-2014. Children under 5 years of age, migrant population and male were the major susceptible population. EV71 and CA16 were the predominant pathogens causing the epidemics of HFMD except in 2013, and CA6 was prevalent in the community cases in 2014. The major peak season of HFMD usually overlapped with the peak of EV71 circulation and the majority of severe HFMD cases were associated with EV71 infection.
Child ; China ; epidemiology ; Disease Outbreaks ; Enterovirus A, Human ; Female ; Hand, Foot and Mouth Disease ; epidemiology ; Humans ; Incidence ; Male ; Prevalence ; Seasons
4.Eligibility of C-BIOPRED severe asthma cohort for type-2 biologic therapies.
Zhenan DENG ; Meiling JIN ; Changxing OU ; Wei JIANG ; Jianping ZHAO ; Xiaoxia LIU ; Shenghua SUN ; Huaping TANG ; Bei HE ; Shaoxi CAI ; Ping CHEN ; Penghui WU ; Yujing LIU ; Jian KANG ; Yunhui ZHANG ; Mao HUANG ; Jinfu XU ; Kewu HUANG ; Qiang LI ; Xiangyan ZHANG ; Xiuhua FU ; Changzheng WANG ; Huahao SHEN ; Lei ZHU ; Guochao SHI ; Zhongmin QIU ; Zhongguang WEN ; Xiaoyang WEI ; Wei GU ; Chunhua WEI ; Guangfa WANG ; Ping CHEN ; Lixin XIE ; Jiangtao LIN ; Yuling TANG ; Zhihai HAN ; Kian Fan CHUNG ; Qingling ZHANG ; Nanshan ZHONG
Chinese Medical Journal 2023;136(2):230-232