Association between environmental factors and BMI: evidence from recent immigrants from developing countries

Background: To study the association between the surrounding local environmental factors and the body mass index of immigrants in the USA. Methods: We use the New Immigrant Survey, to study the association of obesity prevalence in a region on body mass index. We consider local obesity rate as an outcome of the local environmental factors. Using ordinary least squares, three versions of equations are estimated to quantify the contribution of individual-level, acculturation, and environmental effects on immigrants\u2019 body mass index. Results: We find statistically significant results for the correlation of local obesity rate and body mass index. For every 1% increase in the obesity rate, the body mass index levels increase by 0.182 kg/m2. Evidence also suggests dietary assimilation in immigrants is influenced by local environmental factors and that dietary change affects body mass index of female immigrants. Conclusions: Immigrants\u2019 body mass index increase with the increase in the local obesity rate of the region where they reside

Measuring Consumers’ Willingness to Pay for Each Attribute of a Product: A Review on Hedonic Pricing Model

The Hedonic pricing model requires that a good, per se does not provide utility; it is the characteristics of the good that gives rise to utility. The total amount of utility a consumer receives from the consumption of a good is subject to the total amount of the characteristics contained in a good purchased. The marginal monetary value of the good’s characteristics is the product of the marginal unit of the characteristics in the good and the marginal implicit prices of the characteristics. In fact, this model reflects actual choices made by consumers, and they can adopt it to estimate their willingness to pay for a good’s characteristics considering several possible interactions between the good’s characteristics–both internal and external. It can be used in product innovation, product packaging, and designing additive services, which gives a producer a competitive advantage in the market. On the other hand, this model may be counterproductive in an environment where information asymmetry exists as it captures only the willingness to pay for perceived differences of attributes and their direct consequences. Therefore, the effective analysis of this model highly depends on the correctness of model specification and different functional forms. Keywords: Hedonic pricing model, willingness to pay, revealed preference, equilibrium price, and regression analysi

Adverse Selection in Community Based Health Insurance among Informal Workers in Bangladesh: An EQ-5D Assessment

Community-based Health Insurance (CBHI) schemes are recommended for providing financial risk protection to low-income informal workers in Bangladesh. We assessed the problem of adverse selection in a pilot CBHI scheme in this context. In total, 1292 (646 insured and 646 uninsured) respondents were surveyed using the Bengali version of the EuroQuol-5 dimensions (EQ-5D) questionnaire for assessing their health status. The EQ-5D scores were estimated using available regional tariffs. Multiple logistic regression was applied for predicting the association between health status and CBHI scheme enrolment. A higher number of insured reported problems in mobility (7.3%; p = 0.002); self-care (7.1%; p = 0.000) and pain and discomfort (7.7%; p = 0.005) than uninsured. The average EQ-5D score was significantly lower among the insured (0.704) compared to the uninsured (0.749). The regression analysis showed that those who had a problem in mobility (m 1.25–2.17); self-care (OR = 2.29; 95% CI: 1.62–3.25) and pain and discomfort (OR = 1.43; 95% CI: 1.13–1.81) were more likely to join the scheme. Individuals with higher EQ-5D scores (OR = 0.46; 95% CI: 0.31–0.69) were less likely to enroll in the scheme. Given that adverse selection was evident in the pilot CBHI scheme, there should be consideration of this problem when planning scale-up of these kind of schemes

Inequalities in Health Status from EQ-5D Findings: A Cross-Sectional Study in Low-Income Communities of Bangladesh

Background: Measuring health status by using standardized and validated instrument has become a growing concern over the past few decades throughout the developed and developing countries. The aim of the study was to investigate the overall self-reported health status along with potential inequalities by using EuroQol 5 dimensions (EQ-5D) instrument among low-income people of Bangladesh. Methods: A cross-sectional household survey was conducted in Chandpur district of Bangladesh. Bangla version of the EQ-5D questionnaire was employed along with socio-demographic information. EQ-5D questionnaire composed of 2-part measurements: EQ-5D descriptive system and the visual analogue scale (VAS). For measuring health status, UK-based preference weights were applied while higher score indicated better health status. For facilitating the consistency with EQ-5D score, VASs were converted to a scale with scores ranging from 0 to 1. Multiple logistic regression models were also employed to examine differences among EQ-5D dimensions. Results: A total of 1433 respondents participated in the study. The mean EQ-5D and VAS score was 0.76 and 0.77, respectively. The females were more likely to report any problem than the males (P<0.001). Compared to the younger, elderly were more than 2-3 times likely to report any health problem in all EQ-5D dimensions (OR [odds ratio]=3.17 for mobility, OR=3.24 for self-care). However, the respondents of the poorest income group were significantly suffered more from every EQ-5D dimension than the richest income quintile. Conclusion: Socio-economic and demographic inequalities in health status was observed in the study. Study suggests to do further investigation with country representative sample to measure the inequalities of overall health status. It would be helpful for policy-maker to find a new way aiming to reduce such inequalities

The Impact of Community-Based Health Insurance on the Utilization of Medically Trained Healthcare Providers among Informal Workers in Bangladesh

We aimed to estimate the impact of a Community-Based Health Insurance (CBHI) scheme on utilization of healthcare from medically trained providers (MTP) by informal workers. A quasi-experimental study was conducted where insured households were included in the intervention group and uninsured households in comparison group. In total 1,292 (646 insured and 646 uninsured) households were surveyed from Chandpur district comprising urban and rural areas after 1 year period of CBHI introduction. Matching of the characteristics of insured and uninsured groups was performed using a propensity score matching approach to minimize the observed baseline differences among the groups. Multilevel logistic regression model, with adjustment for individual and household characteristics was used for estimating association between healthcare utilization from the MTP and insurance enrolment. The utilization of healthcare from MTP was significantly higher in the insured group (50.7%) compared to the uninsured group (39.4%). The regression analysis demonstrated that the CBHI beneficiaries were 2.111 (95% CI: 1.458-3.079) times more likely to utilize healthcare from MTP.CBHI scheme increases the utilization of MTP among informal workers. Ensuring such healthcare for these workers and their dependents is a challenge in many low and middle income countries. The implementation and scale-up of CBHI schemes have the potential to address this challenge of universal health coverage

Maternal Mortality: Spatial and Racial Disparities in United States

Over the last century, developed countries have been successful in enhancing maternal health and reducing Maternal Mortality Ratio (MMR). By 2018, MMR across OECD countries and World Bank Group Regions have converged towards very low levels, averaging more than 5 deaths per 100,000 live births. The United States has become an outlier among the developed countries in maternal deaths and compares unfavorably to a number of poorer countries where the ratio has declined. In 2017, the US ranked worst in MMR among the 39 industrialized nations. United States has experienced almost a 142 percent increase in MMR from 1987-2018. According to the Centers for Disease Control and Prevention (CDC), every year in the US, more than 700 women die due to the pregnancy or childbirth-related complications, with 60 percent of these deaths being preventable. Within the US, MMR varies considerably, leaving large disparities across states as well as between all racial groups. This research study aims to understand the interplay of spatial and racial impacts on the variation of maternal mortality ratios within the US. The paper estimates Ordinary Least Squares (OLS) and Spatial Lag Models for MMR using cross-sectional US state data for 2012-2017, taken from CDC. The results show that the dominant root causes of high maternal mortality differ between black and white women

Has the Overall Health of the United States Population Changed? Evidence from Biomarker Data

The overall health of a population can be viewed as an indicator of social welfare. Yet, individual health itself is complex and multidimensional, influenced by endogenous choices, as well as exogenous environmental and genetic factors. Moreover, defining a mapping from individual health to social welfare can involve onerous assumptions. This paper adopts a nonparametric approach to ranking individual health as a function of several biomarkers--Body Mass Index (BMI), glycohemoglobin (HbA1c), total cholesterol, alanine aminotransferase (ALT), serum creatinine, white blood cell counts (WBC), etc. With this ranking in hand, we use a nonparametric approach to map individual health into social welfare using minimal assumptions (e.g., monotonicity and concavity). Results show that the distribution of wellbeing became worse-off from 1988 to 2018, although there has been a slight rebound since 2009. Moreover, the distribution has widened: those prone to a higher health status have become better-off while those prone to poorer health have become worse-off which, thereby raising inequality and here policy implications need to be focused on. Finally, we construct counterfactual distributions of wellbeing to explore if the change in the distribution is attributed to socio-demographic factors. Findings show that age, gender and race/ethnicity cells combined with education can explain very little of the negative shift than the attributes without education while leaving a substantial portion unexplained

Inequalities in Health Status from EQ-5D Findings: A Cross-Sectional Study in Low-Income Communities of Bangladesh

Background Measuring health status by using standardized and validated instrument has become a growing concern over the past few decades throughout the developed and developing countries. The aim of the study was to investigate the overall self-reported health status along with potential inequalities by using EuroQol 5 dimensions (EQ-5D) instrument among low-income people of Bangladesh. Methods A cross-sectional household survey was conducted in Chandpur district of Bangladesh. Bangla version of the EQ-5D questionnaire was employed along with socio-demographic information. EQ-5D questionnaire composed of 2-part measurements: EQ-5D descriptive system and the visual analogue scale (VAS). For measuring health status, UK-based preference weights were applied while higher score indicated better health status. For facilitating the consistency with EQ-5D score, VASs were converted to a scale with scores ranging from 0 to 1. Multiple logistic regression models were also employed to examine differences among EQ-5D dimensions. Results A total of 1433 respondents participated in the study. The mean EQ-5D and VAS score was 0.76 and 0.77, respectively. The females were more likely to report any problem than the males (P < 0.001). Compared to the younger, elderly were more than 2-3 times likely to report any health problem in all EQ-5D dimensions (OR [odds ratio] = 3.17 for mobility, OR = 3.24 for self-care). However, the respondents of the poorest income group were significantly suffered more from every EQ-5D dimension than the richest income quintile. Conclusion Socio-economic and demographic inequalities in health status was observed in the study. Study suggests to do further investigation with country representative sample to measure the inequalities of overall health status. It would be helpful for policy-maker to find a new way aiming to reduce such inequalities

The effect of a community-based health insurance on the out-of-pocket payments for utilizing medically trained providers in Bangladesh

Background We aimed to estimate the effect of the community-based health insurance (CBHI) scheme on the magnitude of out-of-pocket (OOP) payments for the healthcare of the informal workers and their dependents. The CBHI scheme was piloted through a cooperative of informal workers, which covered seven unions in Chandpur Sadar Upazila, Bangladesh. Methods A quasi-experimental study was conducted using a case-comparison design. In total 1292 (646 insured and 646 uninsured) households were surveyed. Propensity score matching was done to minimize the observed baseline differences in the characteristics between the insured and uninsured groups. A two-part regression model was applied using both the probability of OOP spending and magnitude of such spending for healthcare in assessing the association with enrolment status in the CBHI scheme while controlling for other covariates. Results The OOP payment was 6.4% (p &lt; 0.001) lower for medically trained provider (MTP) utilization among the insured compared with the uninsured. However, no significant difference was found in the OOP payments for healthcare utilization from all kind of providers, including the non-trained ones. Conclusions The CBHI scheme could reduce OOP payments while providing better quality healthcare through the increased use of MTPs, which consequently could push the country towards universal health coverage

Propensity score distribution in the insured and uninsured groups before propensity score matching application and after matching.

<p>Propensity score distribution in the insured and uninsured groups before propensity score matching application and after matching.</p