Influence of tick transmission on the host response to Rickettsial infection

Several members of the spotted fever group (SFG) of Rickettsia are transmitted to the host through infected ixodid (hard) ticks, which can serve as both vectors and reservoirs. Multiple studies have demonstrated that ticks secrete proteins into the bite site of the host that suppress innate and adaptive immune responses. While this suppression of immune responses is beneficial to the tick, it may also be beneficial to the transmitted Rickettsia. We hypothesize that Rickettsia utilize the tick’s ability to alter the host immune response at the tick feeding site to successfully establish infection. In the current study, we analyzed how the tick transmission influenced the response to Rickettsia infection by comparing the innate immune response following intradermal versus tick-inoculation of R. amblyommii in the skin. In particular, we analyzed mRNA expression of Toll-like receptor (TLR) and TLR adaptor/effector genes as well as proinflammatory cytokines and chemokines. Data was analyzed using One-way ANOVA and Newman-Keuls post tests. The results of this study are the first to delineate the immunomodulatory milieu associated with rickettsial infection during the natural route of tick exposure

Factors Affecting Childhood Immunisation in Bangladesh

This study has examined the coverage of childhood immunisation and tried to identify the factors affecting the acceptance of immunisation practice among children in Bangladesh using the data from Bangladesh Demographic and Health Survey (BDHS) 93-94. Results from multinomial logistic regression analysis indicate that education, occupation, household economic condition, mother’s age at birth, sex of child, mother’s TT immunisation acceptance, mother’s health facility visit, health worker’s visit to mothers, and contraceptive use are the independent variables that have statistically significant association with immunisation acceptance. The most important variable identified is the health worker’s visit to mothers.

Health and Socio-economic Implications of Poverty in Bangladesh

The objective of this study was to explore the influences of the health and socio-economic factors associated with the poverty level of households in Bangladesh, through an analysis of data from the Household Income and Expenditure Survey (HIES) 2010 conducted by Bangladesh Bureau of Statistics (BBS). A total of all 12,240 households was considered in this study. CBN method was applied for estimating poverty of the household. A logistic regression analysis was used to identify the main factors that influence the household’s poverty. The results showed that the probability of the household being poor was higher when the household’s head suffered from various chronic diseases like chronic fever, injuries/disability, eczema, leprosy, and asthma/breathing trouble as compared to the household whose head didn’t suffer from any chronic diseases. From the analysis, it was also found that when a large number within household suffered from any chronic disease, the probability of the household being poor was increased. The household that had no access to health care was poorer than the household that had access to health care. The results also showed that with increased investment in health, the probability of the household being poor was decreased. The results showed that rural households were poorer than urban households. Monthly income, land ownership, construction materials of walls and roofs, types of the latrine, source of drinking water, household size; age, sex, and employment status of the household’s head all had a significant impact on the poverty level of the household

The Role of Education in Poverty Alleviation: Evidence from Bangladesh

Education provides a foundation for eradicating poverty and fostering economic development. The objective of this study is to investigate the influences of education and other demographic, economic, and social factors on poverty of household in Bangladesh through an analysis of data from the Household Income and Expenditure Survey (HIES) 2010 conducted by Bangladesh Bureau of Statistics (BBS). A total of 12,240 households are considered for analyzing the status of household’s poverty. CBN method is employed for estimating poverty of household. After adjustment in a multivariate logistic regression model an increase in educational level of household’s head had a strong association with the probability of a household being non-poor. Increased the number of literate member or presence of a graduate or higher educated member in household, the probability of household being poor is decreased. Increasing investment in education can lead a household from being poor to non-poor. The study results also highlights  that rural households are poorer than urban households and household size; age, sex and employment status of household’s head;  construction materials of walls and roofs, source of drinking water all have significant impact on household’s poverty level. Keywords: Education, Poverty, Household, CBN Method, Logistic regression analysis, Bangladesh

PREVALENCE AND ASSOCIATED FACTORS OF ANTENATAL ANXIETY SYMPTOMS IN BANGLADESH: A REPEATED MEASURES CLUSTER DATA ANALYSIS

Background: Antenatal Anxiety affects the mothers and their child. Spontaneous abortion, preeclampsia, preterm birth, and low birth weight are the most common consequences. In Bangladesh, we have very limited understanding about the burden of antenatal anxiety and its associated factors. We conducted a prospective longitudinal study to estimate the prevalence of anxiety symptoms and identify associated factors in pregnant women. Subjects and methods: A total of 1360 pregnant women were enrolled from 14 antenatal care (ANC) hospitals during September 2015 to August 2017. All selected women were assessed longitudinally at first, second and third trimesters of pregnancy. The State Anxiety Inventory (STAI-S) scale was used to measure the antenatal anxiety symptom. Generalize estimating equations (GEE) and alternating logistic regression (ALR) model were used to measure the risk factors and repetitive anxiety symptom measurements, respectively. Results: Over the study period, more than half (53.18%) of the women reported anxiety in at least one antenatal assessment. The prevalence of anxiety symptom in the first, second, and third trimesters was 29.5%, 23.5%, and 37.5%, respectively. Maternal anxiousness was significantly associated with the trimester, poor education, low blood hemoglobin, and low family income. Conclusion: Women were at high risk of getting anxious during first and third trimesters of pregnancy. Findings of the study can be useful in developing and designing intervention to reduce anxiety in women during pregnancy

PREVALENCE AND ASSOCIATED FACTORS OF ANTENATAL ANXIETY SYMPTOMS IN BANGLADESH: A REPEATED MEASURES CLUSTER DATA ANALYSIS

Background: Antenatal Anxiety affects the mothers and their child. Spontaneous abortion, preeclampsia, preterm birth, and low birth weight are the most common consequences. In Bangladesh, we have very limited understanding about the burden of antenatal anxiety and its associated factors. We conducted a prospective longitudinal study to estimate the prevalence of anxiety symptoms and identify associated factors in pregnant women. Subjects and methods: A total of 1360 pregnant women were enrolled from 14 antenatal care (ANC) hospitals during September 2015 to August 2017. All selected women were assessed longitudinally at first, second and third trimesters of pregnancy. The State Anxiety Inventory (STAI-S) scale was used to measure the antenatal anxiety symptom. Generalize estimating equations (GEE) and alternating logistic regression (ALR) model were used to measure the risk factors and repetitive anxiety symptom measurements, respectively. Results: Over the study period, more than half (53.18%) of the women reported anxiety in at least one antenatal assessment. The prevalence of anxiety symptom in the first, second, and third trimesters was 29.5%, 23.5%, and 37.5%, respectively. Maternal anxiousness was significantly associated with the trimester, poor education, low blood hemoglobin, and low family income. Conclusion: Women were at high risk of getting anxious during first and third trimesters of pregnancy. Findings of the study can be useful in developing and designing intervention to reduce anxiety in women during pregnancy

Bayesian Analysis of Markov Based Logistic Model

In analyzing longitudinal data the correlations between responses obtained from same individual need to be taken into account. Various models can be used to handle such correlations. This article focuses on the application of transition modeling using Bayesian approach for analyzing longitudinal binary data. For Bayesian estimation asymmetric loss functions, such as, linear exponential (LINEX) and modified linear exponential (MLINEX) loss function and Tierney and Kadnae (T.K.) approximation has been used. Comparison is made using Bayes factor and Bayesian approach under LINEX loss function can be suggested to estimate the parameters of transition model

Factors Affecting Childhood Immunisation in Bangladesh

This study has examined the coverage of childhood immunisation and tried to identify the factors affecting the acceptance of immunisation practice among children in Bangladesh using the data from Bangladesh Demographic and Health Survey (BDHS) 93-94. Results from multinomial logistic regression analysis indicate that education, occupation, household economic condition, mother’s age at birth, sex of child, mother’s TT immunisation acceptance, mother’s health facility visit, health worker’s visit to mothers, and contraceptive use are the independent variables that have statistically significant association with immunisation acceptance. The most important variable identified is the health worker’s visit to mothers

Higher Order Markov Structure-Based Logistic Model and Likelihood Inference for Ordinal Data

Azzalini (1994) proposed a first order Markov chain for binary data. Azzalini’s model is extended for ordinal data and introduces a second order model. Further, the test statistics are developed and the power of the test is determined. An application using real data is also presented