Probability Proportional To Size Sampling Research Articles

Cancer literacy differences of basic knowledge, prevention, early detection, treatment and recovery: a cross-sectional study of urban and rural residents in Northeast China.

Cancer literacy as a potential health intervention tool directly impacted the success of cancer prevention and treatment initiatives. This study aimed to evaluate the cancer literacy in Northeast China, and explore the factors contributing to urban-rural disparities. A cross-sectional survey was conducted in 14 cities across Liaoning Province, China, from August to October 2021, using the multistage probability proportional to size sampling (PPS) method. The survey comprised 4,325 participants aged 15-69 and encompassed 37 core knowledge-based questions spanning five dimensions. Associations between sociodemographic factors and the cancer literacy rate were evaluated using chi-square tests and multivariate logistic regression model. The overall cancer literacy rate was 66.9% (95% CI: 65.6-68.2%). In the primary indicators, cancer literacy were highest in treatment (75.8, 95% CI: 74.2-77.4%) and early detection (68.2, 95% CI: 66.8-69.6%), followed by basic knowledge (67.2, 95% CI: 65.8-68.6%), recovery (62.6, 95% CI: 60.7-64.5%) and prevention (59.7, 95% CI: 58.2-61.3%). Regarding secondary indicators, the awareness rates regarding cancer-related risk factors (54.7, 95% CI: 52.8-56.5%) and early diagnosis of cancer (54.6, 95% CI: 52.7-56.6%) were notably inadequate. Rural participates exhibited lower cancer literacy across all dimensions compared to urban. Multi-factor analysis showed that factors such as advanced age, limited education or low household income were barriers to health literacy in rural areas. Strengthening awareness concerning prevention and early detection, particularly among key populations, and bridging the urban-rural cancer literacy gap are imperative steps toward achieving the Healthy China 2030 target.

Calibration Estimation of Population Proportion in Probability Proportional to Size Sampling in the Presence of Non-Response

Objectives: In this article, we addressed the problem of estimation of the finite population proportion under the Probability Proportional to Size (PPS) sampling technique, when the complete information is unavailable due to the presence of non-response. We developed calibrated estimators of the population proportion under PPS sampling in the presence of nonresponse based on the availability of auxiliary information. Methods: The expressions for the mean squared errors of the suggested estimators were developed to the first order of approximation. The developed estimators of the population proportion are compared with the design-based Horvitz-Thompson estimator and Horvitz-Thompson type calibration estimator which were obtained on the complete response units along with the design-based Hansen and Hurwitz type estimator in the presence of non-response. A Simulation study has also been conducted to support the performance of the developed estimators of population proportion with the help of two real datasets, by computing Percentage Absolute Relative Bias (%ARB) and Percentage Relative Root Mean Squared Error (%RRMSE) using R software. Findings: The simulation study supported the performance of the developed estimators of the finite population proportion based on %ARB and %RRMSE. The proposed calibration estimators of population proportion are more efficient than the other considered estimators in the presence of non-response. Novelty: The proposed new calibrated estimators have practical implications in the estimation of finite population proportions. Keywords: Auxiliary information, Calibration Approach, Non­response, Population proportion, PPS sampling

A Probability Proportional to Size Estimation of a Rare Sensitive Attribute Using a Partial Randomized Response Model with Poisson Distribution

In this paper, we suggest using a partial randomized response model using Poisson distribution to efficiently estimate a rare sensitive attribute by applying the probability proportional to size (PPS) sampling method when the population is composed of several different and sensitive clusters. We have obtained estimators for a rare and sensitive attribute and their variances and variance estimates by applying PPS sampling and two-stage equal probability sampling. We compare the efficiency between the estimators of the rare sensitive attribute, one obtained via PPS sampling with replacement and the other obtained using the two-stage equal probability sampling with replacement. As a result, it is confirmed that the estimate obtained via the PPS sampling with replacement is more efficient than the estimate provided by the two-stage equal probability sampling with replacement when the cluster sizes are different.

Statistical analysis of mental influencing factors for anxiety and depression of rural and urban freshmen.

The freshmen stage is a high incidence period for psychological issues. With the increasing gap between urban and rural areas in China, the mental problems of rural freshmen are more prominent in recent years due to the huge contrast of campus life with their growth environment and other reasons. The concern for the mental well-being of both rural and urban freshman students prompted our comprehensive five-year study (2018-2022) on psychological issues in a group of 12,564 first-year students from dozens of public universities in Shandong province. The investigation employed PPS (probability proportional to size) sampling and was conducted near the the end of the first semester. Using the data gathered, we analyzed and compared the indicators of psychological problems in rural and urban freshmen by Duncan's Multiple Range Test. We also conducted a canonical correlation analysis and pathway analysis to examine the psychological factors that contribute to anxiety and depression in both rural and urban freshmen. According to the findings, rural freshmen exhibit significantly higher levels of anxiety and depression than their urban counterparts. Inferiority, obsession, and internet addiction were identified as the primary influencing factors of anxiety and depression in both rural and urban freshmen. Social phobia was found to be a significant influencing factor for anxiety in rural freshmen, while bigotry was identified as a specific influencing factor for urban freshmen. Furthermore, the results of the path analysis suggest that anxiety plays a crucial role as a mediating factor between the main influencing factors and depression. These results substantially extend former research in this area and have important implications for the development of effective intervention strategies to address anxiety and depression. According to these results, policymakers should assess and intervene of anxiety and depression as a whole, and provide mental health education according to main effect factors of freshmen from rural and urban areas. Detailed policy recommendations are in discussion and conclusion.

Estimation of finite population mean using double sampling under probability proportional to size sampling in the presence of extreme values

Values that are too large or small enough can be found in many data sets. Therefore, the estimator can yield ambiguous findings if several of the incredible deals are picked for the sample. When such extreme values occur, we propose improved estimators to determine the finite population means using double sampling based on probability proportional to size sampling (PPS). The properties of estimators are obtained up to the first order of approximations. When the size of the units varies widely, the PPS sampling technique may be employed. To determine the values of Pi when using PPS, we must be acquainted with the aggregate of the auxiliary variable Xi. However the designs and estimation techniques we have looked at so far are unsuccessful and are less effective when this information is difficult to locate or when other information is missing. The two-phase approach is preferable and more feasible in these kinds of circumstances. To demonstrate how effectively the recommended estimators performed, we used three actual data sets. We show mathematically and theoretically that the suggested estimators outperform alternative estimators.

Ensemble algorithms for modeling forest live fuel loads and multivariate probability proportional to size sampling in Kunming, Yunnan, China

Forest live fuel load (LFL) models of tree, shrub, and herbaceous layers were established using linear function (LF), power function (PF), K-nearest neighbor (KNN), gradient boosting regression tree (GBRT), and random forest (RF) algorithms to improve the fit and prediction accuracy and reduce the bias of forest LFL models. Multivariate probability proportional to size sampling (MPPS), probability proportional to size sampling (PPS), and probability proportional to frequency sampling (PPF) were used to obtain mean estimates of the forest LFLs, and the sampling accuracies were assessed. We utilized forest stock and biomass survey data (forest fire risk data and forest resource planning and design survey data) from Kunming, Yunnan, China. The results indicated that the RF model had the highest fit and prediction accuracy. The R2 values of the fitted models for the LFLs of Pinus yunnanensis, Quercus spp., Pinus armandi, Eucalyptus spp., other soft broadleaf species, other hard broadleaf species, other conifer species, shrubs, and herbaceous species were 0.79, 0.89, 0.86, 0.88, 0.91, 0.83, 0.88 0.88, and 0.92, respectively. The F-values were 4.652, 2.582, 2.565, 2.551, 2.738, 3.158, 16.156, 3.479, and 8.468, respectively. The sampling results of forest LFLs were much better for MPPS than for PPF and PPS. Moreover, the two-stage MPPS was the most efficient method for estimating tree, shrub, and herbaceous LFLs. The mean estimates of tree fuel loads, shrub fuel loads, and herbaceous fuel loads were 144.7760, 3.8094, and 0.6442 t/hm2, respectively. There were 555 overlapping subunits for the three types of forest LFLs. The proposed method can significantly reduce the cost of LFL surveys and improve estimation accuracy.

New calibration estimation procedure in the presence of unit non response

In the present work, we have proposed the calibrated estimator of population mean in the presence of unit non response. The non response has been adjusted using the non response adjustment factor depending on different models (which are inverse linear, logistic and exponential) based on auxiliary information, incorporated in calibration estimation. We have studied the case of unit non response through calibration technique under three sampling designs named as simple random sampling (SRS), probability proportional to size sampling (PPS) and stratified random sampling. A broad simulation study has been conducted to evaluate the performances of the calibrated estimators in each sampling scheme.

Exact PPS sampling with bounded sample size

Probability proportional to size (PPS) sampling schemes with a target sample size aim to produce a sample comprising a specified number n of items while ensuring that each item in the population appears in the sample with a probability proportional to its specified “weight” (also called its “size”). These two objectives, however, cannot always be achieved simultaneously. Existing PPS schemes prioritize control of the sample size, violating the PPS property if necessary. We provide a new PPS scheme, called EB-PPS, that allows a different trade-off: EB-PPS enforces the PPS property at all times while ensuring that the sample size never exceeds the target value n. The sample size is exactly equal to n if possible, and otherwise has maximal expected value and minimal variance. Thus we bound the sample size, thereby avoiding storage overflows and helping to control the time required for analytics over the sample, while allowing the user complete control over the sample contents. In the context of training classifiers at scale under imbalanced loss functions, we show that such control yields superior classifiers. The method is both simple to implement and efficient, being a one-pass streaming algorithm with an amortized processing time of O(1) per item, which makes it computationally preferable even in cases where both EB-PPS and prior algorithms can ensure the PPS property and a target sample size simultaneously.

Optimum second call imputation in PPS sampling.

The current study deals with imputation of item non-response in probability proportional to size (PPS) sampling. A new imputation procedure is proposed by using the known co-variance between the study variable and the auxiliary variable in the case of quantitative sensitive study variable by considering the non-response in a randomization mechanism on the second call. An empirical study is conducted at the optimum values of kog and nog for the relative comparisons of ratio, difference, and proposed estimators, respectively, with the Hansen-Hurwitz estimator.

Determinant of Covid-19 Prevention Behavior in The Community in Pamulang, South Tangerang in 2021

Coronavirus Disease 2019 (COVID-19) is an infectious disease caused by SARS-CoV-2. Preventive behavior in the community is important to maintain health during a pandemic. This study aims to determine the determinants of COVID-19 prevention behavior in the community in Bambu Apus, Pamulang in 2021. The approach was conducted in RW. 001 Bambu Apus in June-July 2021 with 180 respondents and using the Probability Proportional to Size Sampling (PPS) sample method. Characteristics of respondents found that the majority of respondents were 36-45 years old (33.3%), with female gender (59.4%), high school education (51.1%), work as private employees (40.6%). Based on the results of univariate analysis, it was found that respondents aged 40 years (55.6%), female (59.4%), had higher education (92.8%), worked (62.2%), good knowledge ( 80%), positive attitude (78.3%), sources of information sourced from social networks (60%), good family support (55%), good health worker support (61.1%) and COVID-19 prevention behavior good (85%). Based on the results of the bivariate analysis, it was found that there was a significant relationship between knowledge (p-value = 0.000), attitudes (p-value = 0.000), family support (p-value = 0.000), health worker support (p-value = 0.000) and behavior. prevention of COVID-19. However, there was no relationship between age (p-value = 0.529), gender (p-value = 0.848), education (p-value = 0.417), occupation (p-value = 0.155), source of information (p-value = 1,000 ), with COVID-19 preventive behavior. Suggestions related to the results of the research are expected that RW administrators can work together with health workers to increase knowledge, attitudes, and family support related to COVID-19 prevention behavior by encouraging, reminding, and educating the public regarding COVID-19.

Credibility of Different Agricultural Information Sources Utilized by Farm Women of Uttarakhand

Credibility of agricultural information sources affects the adoption of new or improved agricultural practices by farmers. Credibility refers to perceived trustworthiness accorded to a source by its audience at any given time and situation. Therefore, Credible sources of agriculture information play major role in diffusion of agriculture innovations. This study was carried out in Nainital district of Uttarakhand state with specific objective to explore the relative credibility of information sources as accorded by the farm women of the region. A sample of 120 farm women was selected by PPS (Probability proportional to size) sampling method. The agriculture information sources were categorized into three broad heads namely personal localite, personal cosmopolite and mass media. It was found that majority (62.5%) of respondents had „medium‟ credibility towards agriculture information sources followed by 20 per cent having low credibility and only 17.5 per cent had high credibility to different agriculture information sources. It was further found that family members, KVK officials and newspaper were considered as the most credible sources of agricultural information among personal localite, personal cosmopolite and mass media sources.

Gender discrimination and other factors affecting Full Immunization Coverage (FIC) in 59 low performing blocks of Bihar

Background: Routine childhood immunization has proven to be among the most practical and most cost-effective health interventions. The full immunization coverage (FIC) has increased, still it is less. Especially in the low performing blocks of Bihar ,it is less than 70 %.There are various factors responsible for less FIC including gender discrimination also which is still hidden in the society. Hence this study was done to find out the FIC in Bihar with associated factors including gender discrimination. Objectives: To find out the various associated factors affecting FIC and to find out gender discrimination (if any) in FIC in different districts of Bihar. Methodology: Two stage cluster sampling with Probability Proportional to size Sampling (PPS) was used as per Study protocol. The study was conducted in 59 low- performing blocks of Bihar where the full immunization coverage was less than 70%. The survey was conducted in 59 blocks. From each block, 30 clusters (Villages) were selected. As a convention, 7 children of age group 12- 23 months were selected from each cluster. Thus, data collection was done for a total of 12,390 children.A structured questionnaire was formulated on the basis of WHO coverage evaluation format. Web based Application SDRC kit was used for data collection while SPSS v. 20 was used for analysis. Results: FIC was found to be 60.81% , it was higher for the rural clusters, general caste, Hindus when compared to urban clusters , SC and other castes, and Muslim religion respectively. For 1st child FIC was highest (66.8%) and was lesser for females. A coverage ratio (female to male) was found to be less than 1 for most of the districts. Conclusion: There are considerable inequities in full immunization by various individual (birth order, gender, birth weight), social (religion, caste), and societal (health care facility and cluster type) characteristics. In general, the ratio (female/male) remains less than 1 for most of the districts.

An Estimation of Sensitive Attribute Applying Geometric Distribution under Probability Proportional to Size Sampling

In this paper, we extended Yennum et al.’s model, in which geometric distribution is used as a randomization device for a population that consists of different-sized clusters, and clusters are obtained by probability proportional to size (PPS) sampling. Estimators of a sensitive parameter, their variances, and their variance estimators are derived under PPS sampling and equal probability two-stage sampling, respectively. We also applied these sampling schemes to Yennum et al.’s generalized model. Numerical studies were carried out to compare the efficiencies of the proposed sampling methods for each case of Yennum et al.’s model and Yennum et al.’s generalized model.

Method of Area Frame Sampling Using Probability Proportional to Size Sampling Technique for Crops’ Surveys: A Case Study in Pakistan

The Crops’ estimates have been greatly concerned by the Government of Punjab (Pakistan) all the times. Crop Reporting Service (CRS), Agriculture Department, Punjab, as a unique and the largest statistical organization in Punjab, has been working on agricultural statistics using the sampling technique, List Frame Sampling (LFS), for conducting surveys to gather information regarding crops acreage, cost of production, crops yield and other agricultural items since 1978. The development of the rural economy in Pakistan brings new problems and challenges to the methods of agricultural statistics. The back bone of agricultural statistics is the sampling technique, LFS, in which primary sampling unit is a village and an enumerator has to survey the whole village whatever the size of the village causing an increase in non-sampling error. In spite of the sufficient area coverage, representation of population in the sample is not satisfactory. The solution is Area Frame Sampling Technique in which primary sampling unit is a Segment of a specific acreage covering maximum dimensions of the population land. In this paper a method of Area Frame Sampling (AFS) has been proposed. As most of the research papers focus on the method of AFS through Geographical Information System (GIS) technique. But in this paper two-stage statistical sampling technique has been used to achieve the same objective in an efficient and economical way. In the first stage Probability Proportional to Size Sampling (PPS) has been used. Here size is cropped area of a Union Council (UC), the smallest geographical cluster in Punjab, Pakistan. In the second stage Simple Random Sampling (SRS) has been used. Here Primary Sampling Units are Segments of land of a village. The results show that the problem of non-representation of agricultural land is minimized and, consequently, getting better estimates in terms of precision using less amount of land data. It is recommended that this method can be extended for multiple stages of sampling and for multiple measures of sizes.

Two Stage Cluster Sampling Based Asymptotic Inferences in Survey Population Models for Longitudinal Count and Categorical Data

Sutradhar (2008, Sankhya B, 18-33) has studied a GLMM (generalized linear mixed model) for count data in a finite population setup where a sample of families/clusters were chosen from a finite population using PPS (probability proportional to size) sampling scheme. The properties of the estimators were studied through a simulation study. In this paper we consider (1) an auto-regressive type dynamic (ARTD) model for longitudinal count data, and (2) a MDL (multinomial dynamic logits) model for longitudinal categorical/multinomial data; and develop a practically important two-stage cluster sampling (TSCS) design weights based estimating equations for the regression and dynamic dependence parameters involved in both ARTD and MDL models in a finite population setup. Specifically, the survey weighted generalized quasi-likelihood (WGQL) and the survey weighted maximum likelihood (WML) estimation approaches are used for the count and multinomial models, respectively. We also demonstrate in the paper that the proposed TSCS based WGQL and WML estimators specially for the regression parameters (of main interest) are consistent, whereas the existing ‘working’ longitudinal correlations based GEE (generalized estimating equations) fails to produce consistent estimates and/or consistent variance estimates. The variances of the regression estimates along with their unbiased estimates are derived for both count and multinomial models. Furthermore, the asymptotic normality of the regression estimators are developed based on a large number of independent but non-identical clusters under non-overlapping stratums.

Assessment of schistosomiasis transmission risk after flood damage in Wuhan City

To assess the schistosomiasis transmission risk after flood damage in Wuhan City. Schistosomiasis epidemic villages in Wuhan City were selected by using probability proportional to size sampling (PPS). The field investigations of Oncomelania hupensis snails, the activity of people and cattle on marshland, water infectivity of schistosome, reservoir host infection and wild feces contamination were conducted. I-III levels of risk environments were assessed and treated with appropriate measures. A total of 90 schistosomiasis epidemic villages and 170 environments were monitored. Totally 9 811 snails were dissected but no Schistosoma japonicum infected snails were found. There were significant decreases in the density of snails and the survival rate of living snails after the flood (χ2 = 102.517, t = 4.724, both P < 0.01). Totally 289 pieces of wild feces were captured, and no eggs of S. japonicum were detected. A total of 11 surveillance and forecast sites were detected on water systems, and 221 sentinel mice were placed. After breeding, 219 sentinel mice survived (99.10%), and no schistosome infection was detected. In addition, 1 720 mouse traps were placed in 3 survey sites, and 66 Apodemus agrarius were captured, and no schistosome-infected ones were found. All of the environments were assessed as Grade III. Meanwhile, 5 key schistosomiasis control areas were determined, and no emergency happened after the implementation of comprehensive control interventions. The risk of schistosomiasis transmission remains low in Wuhan City after the flood, but the potential epidemic risk cannot be ignored.

Uniform random sampling not recommended for large graph size estimation

The norm of data size estimation is to use uniform random samples whenever possible. There have been tremendous efforts in obtaining uniform random samples using methods such as Metropolis–Hasting random walk or importance sampling [2]. This paper shows that, on the contrary to the common practice, uniform random sampling should be avoided when PPS (probability proportional to size) sampling is available for large data.To develop intuition of the sampling process, we discuss the sampling and estimation problem in the context of graph. The size is the number of nodes in the graph; uniform random sampling corresponds to uniform random node (RN) sampling; and PPS sampling is approximated by random edge (RE) sampling. In this setting, we show that for large graphs RE sampling outperforms RN sampling with a ratio proportional to the normalized graph degree variance. This result is particularly important in the era of big data, when data are typically large and scale-free [3], resulting in large degree variance.We derive the result by giving the variances of RN and RE estimators. Each step of the derivation is supported and demonstrated by simulation studies assuming power law distributions. Then we use 18 real-world networks to verify the result. Furthermore, we show that the performance of random walk (RW) sampling is data dependent and can be significantly worse than RN and RE. More specifically, RW can estimate online social networks but not Web graphs due to the difference of the graph conductance.

Factors associated with malnutrition among infants and young children aged 6-23 months in poor rural areas in Hunan Province, China

Objective: To describe the situation and identify factors associated with malnutrition among infants and young children aged 6-23 months in poor rural areas in Hunan Province in 2015. Methods: 8 735 rural infants and young children aged 6-23 months in 30 poor counties of Wuling Mountains and Luoxiao Mountains in Hu'nan province were selected by township-level probability proportional to size sampling (PPS) in August 2015, infants' body length and weight were measured, and questionnaires were used to collect infants' information on personal and family, and feeding status in the past 24 h. The prevalence of stunting, underweight and wasting were calculated according to the Growth Standards of Child Aged Under 7 in China which was established in 2009 by Community Health Department of National Health and Family Planning Commission, China (formerly Chinese MOH), and the prevalence of malnutrition was calculated according to the classification of children with anthropometric failure. Multi non-conditional logistic regression model were used to analyze factors associated with malnutrition among infants and young children aged 6-23 months. Results: The prevalence of malnutrition among infants and young children aged 6-23 months was 13.7% (1 198/8 735), the prevalence of stunting, underweight and wasting among infants and young children aged 6-23 months were 4.8% (419/8 735), 9.7% (849/8 735) and 6.1% (531/8 735) respectively. Compared with male group, the OR value of malnutrition for the female group was 1.16; Compared with Han ethnic group, the OR value of malnutrition for the Miao and Tujia ethnic group were 0.83 and 0.66, respectively; Compared with mother with an education level of primary school or below, the OR value of malnutrition for the mother with junior high school, senior high school and university or above education were 0.65, 0.61 and 0.56, respectively; Compared with father with an education level of primary school or below, the OR value of malnutrition for the father with senior high school and university or above education were 0.71 and 0.61 respectively; Compared with normal birth weight group, the OR value of malnutrition for the low birth weight group and high birth weight group were 2.85 and 0.27 respectively; Compared with normal delivery group, the OR value of malnutrition for the premature delivery group was 1.37; all P values<0.05. Conclusion: The prevalence of malnutrition among infants and young children aged 6-23 months in poor rural areas in Hunan province in 2015 was high; Infants and young children who were female, Han ethnic, parents with low education, low birth weight and premature delivery had higher risk of malnutrition.

A sero-epidemiological study of hepatitis E among general population in Shandong Province of China in 2014

Objective: To analyze the sero-epidemiological characteristics of hepatitis E virus (HEV) in Shandong province, and thereby to provide evidence for the policy-making of hepatitis E prevention and control. Methods: The inhabitants aged between 1-59 years old were randomly selected to participate in the study by two-stage stratified random sampling method from 12 counties in Shandong province in October, 2014. Firstly two townships were selected from each county by probability proportional to size sampling (PPS) method. A total of 5 229 participants aged 1-59 years old were selected by stratified random sampling method. All the participants finished a questionnaire survey and a venous blood sample (3-5 ml) was collected from each to test anti-HEV IgG by enzyme-linked assay (ELISA). The weighted prevalence of anti-HEV IgG with different demographic characteristics was estimated. The variance of the positive rate of anti-HEV IgG was calculated by Taylor series linearization method, as well as its 95%CI. A statistical test was conducted to compare the rate of its 95%CI, and the results in the present study were compared with those in sero-survey in 2006. Results: A total of 5 229 subjects entered the final analysis in 2014. The overall weighed prevalence of anti-HEV IgG was 9.19% (95%CI: 6.18%-12.20%) among natural population in Shandong province, decreased by 19.88% in comparison with that in 2006 sero-survey (11.47%, 95%CI: 8.92%-14.02%). The prevalence increased with age increasing (χ(2trend)=288.11, P<0.001) in 2014, which was similar to the result in 2006 sero-survey. Except for 1-4 years old group, the prevalence of anti-HEV IgG in the other age groups were lower than it in the corresponding groups in 2006. The prevalence of anti-HEV IgG in urban (8.19%, 95%CI: 0.00-22.23%), rural areas (9.69%, 95%CI: 4.99%-14.38%), eastern areas (12.70%, 95%CI: 0.00-27.72%), central areas (4.74%, 95%CI: 0.00-9.91%) and western areas (9.32%, 95%CI: 0.69%-17.94%) in 2014 were all lower than the corresponding prevalences (11.39%, 95%CI: 8.17%-14.62%; 11.92%, 95%CI: 8.75%-15.08%; 22.77%, 95%CI: 14.99%-30.55%; 7.97%, 95%CI: 4.75%-11.20%; 10.59%, 95%CI: 6.37%-14.82%) in 2006 survey. The prevalence of anti-HEV IgG in coastal areas (16.56%, 95%CI: 12.94%-20.18%) and inland areas (7.63%, 95%CI: 5.16%-10.10%) in 2014 were lower than it in the corresponding areas (28.04%, 95%CI: 20.45%-35.64%; 9.50%, 95%CI: 7.31%-11.70%) in 2006 survey. The prevalence among peasant (11.98%, 95%CI: 8.20%-15.76%), worker (9.68%, 95%CI: 4.48%-14.88%), cadre (13.90%, 95%CI: 7.47%-20.33%), service provider (12.26%, 95%CI: 1.80%-22.73%) in 2014 survey were lower than it among the corresponding populations (13.76%, 95%CI: 10.15%-17.38%; 21.11%, 95%CI: 12.67%-29.55%; 17.81%, 95%CI: 7.63%-28.00%; 21.08%, 95%CI: 0.03%-42.12%) in 2006 survey. Conclusion: The prevalence of anti-HEV IgG has decreased in Shandong province in the recent years, but the epidemiological characteristics found no obvious changes. HEV susceptibility in natural population was generally high. Hepatitis E vaccines were recommended to be used in HEV high-risk population in the province.

Hepatitis B prevalence among women in child-bearing age in Shandong Province, China, 2014

Objective: To know the prevalence of hepatitis B virus (HBV) among women in child-bearing age in Shandong Province, China, providing references to the improvement of HBV control strategy. Methods: The participants were randomly selected by two-stage sampling method from 12 counties which were representative for the whole province. Firstly two townships were selected from each county by probability proportional to size sampling (PPS) method. Then participants aged 1-4 years, 5-14 years, 15-29 years and 30-59 years were selected by stratified random sampling method. The women in child-bearing age (20-49 years) were involved in this study. Questionnaire survey and 5 ml blood collection were conducted among all participants. Blood samples were detected for hepatitis B surface antigen (HBsAg), antibody against HBsAg (anti-HBs) and antibody against hepatitis B core antigen (anti-HBc). Those who were positive for HBsAg were further detected for hepatitis e antigen (HBeAg), antibody against HBeAg (anti-HBe) and the load of HBV DNA. The basic information of the participants including age, gender, occupation, nationality and residence place were collected. The prevalence of HBV infection indicators after weight adjustment were calculated and compared between participants with different demographic characteristics. Results: A total of 1 151 women in child-bearing age were involved in this study. Twenty-seven participants were positive for HBsAg and the prevalence rate was 2.10% (95% CI: 0.97%-3.23%). Five participants were positive for both HBsAg and HBeAg and the prevalence rate was 0.36% (95% CI: 0-0.84%). There were 567 and 291 participants who were positive for anti-HBs and anti-HBc respectively and the corresponding prevalence rates were 47.72% (95%CI: 41.68%-53.75%) and 24.40% (95% CI: 18.50%-30.30%). The number of participants susceptible for HBV was 527 and the percentage of HBV susceptible women was 47.55% (95% CI: 41.63%-53.47%). Conclusion: HBV infection among women in child-bearing age has attained very low level in Shandong Province, China. However, the high proportion of women in child-bearing age were still susceptible for HBV and hepatitis B immunization should be improved among them.