Riddhi Doshi

Pathways of Economic Inequalities in Maternal and Child Health in Urban India: A Decomposition Analysis

Background/Objective Children and women comprise vulnerable populations in terms of health and are gravely affected by the impact of economic inequalities through multi-dimensional channels. Urban areas are believed to have better socioeconomic and maternal and child health indicators than rural areas. This perception leads to the implementation of health policies ignorant of intra-urban health inequalities. Therefore, the objective of this study is to explain the pathways of economic inequalities in maternal and child health indicators among the urban population of India. Methods Using data from the third wave of the National Family Health Survey (NFHS, 2005–06), this study calculated relative contribution of socioeconomic factors to inequalities in key maternal and child health indicators such as antenatal check-ups (ANCs), institutional deliveries, proportion of children with complete immunization, proportion of underweight children, and Infant Mortality Rate (IMR). Along with regular CI estimates, this study applied widely used regression-based Inequality Decomposition model proposed by Wagstaff and colleagues. Results The CI estimates show considerable economic inequalities in women with less than 3 ANCs (CI  = −0.3501), institutional delivery (CI  = −0.3214), children without fully immunization (CI  = −0.18340), underweight children (CI  = −0.19420), and infant deaths (CI  = −0.15596). Results of the decomposition model reveal that illiteracy among women and her partner, poor economic status, and mass media exposure are the critical factors contributing to economic inequalities in maternal and child health indicators. The residuals in all the decomposition models are very less; this implies that the above mentioned factors explained maximum inequalities in maternal and child health of urban population in India. Conclusion Findings suggest that illiteracy among women and her partner, poor economic status, and mass media exposure are the critical pathways through which economic factors operate on inequalities in maternal and child health outcomes in urban India.

Impact of electronic personal health record use on engagement and intermediate health outcomes among cardiac patients: a quasi-experimental study.

OBJECTIVES To determine the impact of tethered personal health record (PHR) use on patient engagement and intermediate health outcomes among patients with coronary artery disease (CAD). METHODS Adult CAD patients (N = 200) were enrolled in this prospective, quasi-experimental observational study. Each patient received a PHR account and training on its use. PHRs were populated with information from patient electronic medical records, hosted by a Health Information Exchange. Intermediate health outcomes including blood pressure, body mass index, and hemoglobin A1c (HbA1c) were evaluated through electronic medical record review or laboratory tests. Trends in patient activation measure® (PAM) were determined through three surveys conducted at baseline, 6 and 12 months. Frequency of PHR use data was collected and used to classify participants into groups for analysis: Low, Active, and Super users. RESULTS There was no statistically significant improvement in patient engagement as measured by PAM scores during the study period. HbA1c levels improved significantly in the Active and Super user groups at 6 months; however, no other health outcome measures improved significantly. Higher PAM scores were associated with lower body mass index and lower HbA1c, but there was no association between changes in PAM scores and changes in health outcomes. Use of the PHR health diary increased significantly following PHR education offered at the 6-month study visit and an elective group refresher course. CONCLUSIONS The study findings show that PHR use had minimal impact on intermediate health outcomes and no significant impact on patient engagement among CAD patients.

Epidemiological Transition in Urban Population of Maharashtra

Our objective is to assess epidemiological transition in urban Maharashtra in India in past two decades. We used the medically certified causes of death (MCCD) data from urban areas of Maharashtra, 1990–2006. Cause-specific death rate was estimated, standardized for age groups, and projected by using an exponential linear regression model. The results indicate that the burden of mortality due to noncommunicable conditions increased by 25% between 1990 and 2006 and will add 20% more by 2020. Among specific causes, the “diseases of the circulatory system” were consistently the leading CoD between 1990 and 2006. The “infectious and parasitic disease” and “diseases related to respiratory system” were the second and third leading causes of death, respectively. For children and young population, the leading cause of death was the “certain conditions originating in the prenatal period” and “injury and poisoning,” respectively, among both sexes. Among adults, the leading cause of death was “infectious and parasitic diseases.” In case of the adult female and elderly population, “diseases of circulatory system” caused the most deaths. Overall the findings foster that socioeconomically developed and demographically advanced urban Maharashtra bears the double burden of disease-specific mortality.

Prevalence of Anemia and Its Determinants Among Pregnant, Lactating, and Nonpregnant Nonlactating Women in India:

Despite the existence of several policies and programs, anemia among pregnant and lactating women continues to be a serious concern for public health policy in India. The main objective of this study is to examine the prevalence and determinants of anemia among pregnant and lactating versus nonpregnant nonlactating (NP-NL) women for priority setting in health policies of the country. Data from the National Family Health Survey (NFHS3) conducted in 2005-2006 has been used for the analyses of this study. The results revealed that the prevalence of anemia was higher among lactating women (63%), followed by pregnant women (59%) than NP-NL women (53%). Younger lactating (71%) and older pregnant women (67%) had a higher burden of anemia. Along with socioeconomic factors, demographic indicators such as children ever born and program factors like nutrition advice and supplementary nutrition during anti natal care and postnatal care emerged as significant predictors in the case of anemia among both pregnant and lactating women, while socioeconomic indicators emerged as critical factors in the case of anemia among NP-NL women. Hence, targeting demographic and program factors, along with key socioeconomic and demographic factors in public health policy, is critical in reducing anemia among lactating and pregnant women, while targeting significant socioeconomic factors is the key for reducing anemia among NP-NL women.

Tuberculosis control, and the where and why of artificial intelligence

Countries aiming to reduce their tuberculosis (TB) burden by 2035 to the levels envisaged by the World Health Organization End TB Strategy need to innovate, with approaches such as digital health (electronic and mobile health) in support of patient care, surveillance, programme management, training and communication. Alongside the large-scale roll-out required for such interventions to make a significant impact, products must stay abreast of advancing technology over time. The integration of artificial intelligence into new software promises to make processes more effective and efficient, endowing them with a potential hitherto unimaginable. Users can benefit from artificial intelligence-enabled pattern recognition software for tasks ranging from reading radiographs to adverse event monitoring, sifting through vast datasets to personalise a patients care plan or to customise training materials. Many experts forecast the imminent transformation of the delivery of healthcare services. We discuss how artificial intelligence and machine learning could revolutionise the management of TB. Tuberculosis control, and the where and why of artificial intelligence http://ow.ly/GwuY30bCXkJ