Perception and use of Contraceptives among Women in Farming Households of Rural Oyo State, Nigeria

The objective of this study was to investigate the extent and perception of contraceptive use among women from farming households in Oyo state, Nigeria. Descriptive statistics were used in profiling the socioeconomic characteristics of respondents, a multinomial logistic model was used to estimate the determinants of contraceptive usage, while the Likert scale was used to measure their perception towards the use of contraceptives. A total of 150 women were interviewed using a structured questionnaire. The results obtained indicated that while only 27% of the women were aware of contraceptives, 23% of them had used them. Cost was the most important consideration among the women for choosing a method as indicated by 41% of them. Further, among those who had not used any contraceptive, traditional and religious beliefs were their major considerations. The regression analysis showed formal education to be a significant factor (at α0.05) that increased the probability of women embracing contraception. Perception towards contraceptives among women in rural Oyo State, Nigeria was seen to be generally positive, although convenience of the methods (mean score 1.49) and side effects (means score 1.35) were considered to be drawbacks. It was recommended that more awareness needed to be created on birth control along with the introduction of modern methods of contraception with fewer side effects. Also, family planning interventions in Nigeria should be made context-specific and culturally appealing so as to increase their acceptability in rural farming communities.

Medical Complexity, Mortality Among High-Cost Medicare Advantage Enrollees: Palliative, Hospice Implications

Older adults with high medical spend require tailored interventions and care delivery to meet their complex needs. Palliative is a high-value solution for high-cost patients because it provides relief from the symptoms, pain, and stress associated with multiple conditions. Likewise, other high-cost patients may be closer to end-of-life and therefore benefit from hospice care. For Accountable Care Organizations (ACOs) and hospitals to implement palliative care, these programs must identify and target the high-need patient populations. This study explored patterns of spending and mortality across 4 years (2016-2019) using claims from 1,701,647 patients continuously enrolled in UnitedHealth Group Medicare Advantage (mean age=73.7; S.E.=0.01). Patients with healthcare spend in the top decile were segmented into three subgroups based on health conditions and spend patterns. Analyses identified a subgroup of patients (mean age=76.6; S.E.=0.04), with the highest rate of mortality, and significantly more chronic conditions and frailty, indicating their cost and mortality was driven by medical complexity. Odds ratios from a multinomial logistic model tie blood formulation drugs (OR XX), medicative procedures (OR XX), and nonhospital-based care (OR XX) to members of this subgroup may be connected to short-term mortality. There is a critical need to identify patients who stand to benefit from palliative and end of life care, this is particularly true for high-cost high-need patients. Our study suggests that patterns of medical complexity and morality within high-cost patient subpopulations can be used to identify high-cost patients who would benefit from palliative or hospice care.

Analysis of Factors Influencing Household Preference Level for Seafood in Southwest Nigeria

Seafood is known worldwide as a very important component of human diet because of its high nutritive value and significance in improving human health. The study examines the factors influencing households’ preference level for seafood and determines the factors inducing the choice of seafood consumption by households in Southwest Nigeria. Multi-stage sampling technique was used to select 300 households in Oyo and Lagos States, Southwest Nigeria. Ordered probit regression model was used to examine the factors influencing household preference level for seafood and multinomial logistic model was used to determine the factors inducing the choice of seafood consumed by the households in the study area. The ordered probit model estimation results revealed that access to seafood within 1km – 4km was significant at 5% and positively relates to household preference for seafood. Increase in income of the household will increase the likelihood of having high preference for seafood (14.39%) by the respondents in the study area. Multinomial logistic model results revealed that the education level of the respondents influenced the choice of croaker fish by 12.01% relative to shrimp in the study area. Therefore, the study recommends that seafood marketers should ensure a good distribution network that will enhance its accessibility within one and four kilometers in the study area.

How Poverty, Residence Status and Health Insurance Predict Unmet Healthcare Needs among Chinese Elders?

This study focuses on the variability in unmet healthcare needs among vulnerable Chinese elders and the degree to which these unmet needs are associated with socioeconomic disadvantages. We use the 2013 wave of China Health and Retirement Longitudinal Study (CHARLS) and a multinomial logistic model to investigate how poverty, residence status and particular health insurance schemes influence unmet healthcare needs independently and in combination. Our results show that poverty and rural residence are strong predictors of unmet healthcare needs due to financial and non-financial constraints, respectively. Although health insurance can reduce financial barriers, its influence varies with different insurance schemes, thus generating unequal healthcare access among heterogeneous vulnerable subgroups of elders and putting poor rural migrants at the highest risk for unmet healthcare needs. Our findings direct attention to the differences in resources available to various subgroups of elders and the importance of social stratification in predicting unmet health care needs.

Correlated Damage Probabilities of Bridges In Seismic Risk Assessment of Transportation Networks

This paper aims to identify and use a logistic regression approach to model the spatial correlation of damage probabilities in expanded transportation networks. This paper uses Bayesian theory and the multinomial logistic model to analyze the different damage states and damage probabilities of bridges by considering the damage correlation. The correlation of the damage probabilities is considered both in different bridges of a network and in the different damage states of each bridge. The correlation model of the damage probabilities is considered in the seismic assessment of a part of the Tehran transportation network with 26 bridges. Moreover, the extra daily traffic time (EDTT) is selected as an operational parameter of the transportation network, and the shortest path algorithm is considered to select the path between two nodes. The results show that including the correlation of the damage probabilities decreases the travel time of the selected network. The average decreasing in the correlated case compared to the uncorrelated case, using two selected EDTT models are 53% and 71%, respectively.

A Distinctive NAFLD Signature in Adipose Tissue from Women with Severe Obesity

Development and severity of nonalcoholic fatty liver disease (NAFLD) have been linked to obesity and white adipose tissue (WAT) dysfunction plays a key role in this relation. We compared the main features of subcutaneous (SAT) and visceral WAT (VAT) tissue dysfunction in 48 obese women without (Ob) and with NAFLD (Ob-NAFLD) undergoing bariatric surgery and matched for age, BMI and T2D status. Fat cell area, adipocyte size distribution, the degree of histological fibrosis and the mRNA expression of adipokines and genes implicated in inflammation, adipogenesis, angiogenesis, metabolism and extracellular matrix remodeling were measured by RT-qPCR in both fat depots. Ob-NAFLD group showed higher TG and lower HDL circulating levels, increased VAT fat cell area and similar WAT fibrosis in comparison with Ob group. A sPLS-DA was performed in order to identify the set of genes that better characterize the presence of NAFLD. Finally, we build a multinomial logistic model including seven genes that explained 100% of the variance in NAFLD and correctly predicted 100% of cases. Our data support the existence of distinctive NAFLD signatures in WAT from women with severe obesity. A better understanding of these pathways may help in future strategies for the prevention and treatment of NAFLD.

Ethnic-racial inequity in health insurance in Colombia: a cross-sectional study

Objective. Characterize the relationship between ethnic-racial inequity and type of health insurance in Colombia. Methods. Cross-sectional study based on data from the 2019 Quality of Life Survey. We analyzed the type of health insurance (contributory, subsidized, or none) and its relationship to ethnic-racial status and predisposing variables (sex, age, marital status), demographic variables (area and region of residence), and socioeconomic variables (education, type of employment, income, and unmet basic needs) through simple and multivariate regression analyses. The association between ethnic-racial status and type of health insurance was estimated using odds ratios (OR) and their 95% confidence intervals, through a multinomial logistic model. Results. A statistically significant association was found between ethnic-racial status and type of health insurance. In comparison with the contributory system, the probabilities of being a member of the subsidized system were 1.8 and 1.4 times greater in the indigenous population (OR x 1.891; 95%CI: 1.600-2.236) and people of African descent (OR = 1.415; 95%CI: 1.236-1.620), respectively (p <0.01) than in the population group that did not identify as belonging to one of those ethnic-racial groups. Conclusions. There is an association between ethnic-racial status and type of insurance in the contributory and subsidized health systems in Colombia. Ethnic-racial status is a structural component of inequity in access to health services and heightens the disadvantages of people and population groups with low socioeconomic status.

α-Synuclein in blood exosomes immunoprecipitated using neuronal and oligodendroglial markers distinguishes Parkinson’s disease from multiple system atrophy

The diagnosis of Parkinson’s disease (PD) and atypical parkinsonian syndromes is difficult due to the lack of reliable, easily accessible biomarkers. Multiple system atrophy (MSA) is a synucleinopathy whose symptoms often overlap with PD. Exosomes isolated from blood by immunoprecipitation using CNS markers provide a window into the brain’s biochemistry and may assist in distinguishing between PD and MSA. Thus, we asked whether α-synuclein (α-syn) in such exosomes could distinguish among healthy individuals, patients with PD, and patients with MSA. We isolated exosomes from the serum or plasma of these three groups by immunoprecipitation using neuronal and oligodendroglial markers in two independent cohorts and measured α-syn in these exosomes using an electrochemiluminescence ELISA. In both cohorts, α-syn concentrations were significantly lower in the control group and significantly higher in the MSA group compared to the PD group. The ratio between α-syn concentrations in putative oligodendroglial exosomes compared to putative neuronal exosomes was a particularly sensitive biomarker for distinguishing between PD and MSA. Combining this ratio with the α-syn concentration itself and the total exosome concentration, a multinomial logistic model trained on the discovery cohort separated PD from MSA with an AUC = 0.902, corresponding to 89.8% sensitivity and 86.0% specificity when applied to the independent validation cohort. The data demonstrate that a minimally invasive blood test measuring α-syn in blood exosomes immunoprecipitated using CNS markers can distinguish between patients with PD and patients with MSA with high sensitivity and specificity. Future optimization and validation of the data by other groups would allow this strategy to become a viable diagnostic test for synucleinopathies.

Determinants of Energy Intensity Trends in Indian Metallic Industry: A Firm-level Analysis

Though the demand for industrial energy by manufacturing firms has witnessed substantial growth, not enough evidence exists regarding the energy intensity trends of such firms. Furthermore, empirical evidence on the determinants of energy intensity trends or even the energy intensity levels per se remains limited. Given this gap, the present article analyses the determinants of energy intensity trends (and also the energy intensity levels) of Indian manufacturing firms over the period 2007–2017. This study has been undertaken with special reference to the metallic industry. A sample of 41 firms is analysed by grouping them into 3 categories, namely firms with increasing energy intensity trends (IEITs), decreasing energy intensity trends (DEITs) and relatively constant energy intensity trends (CEITs) over the stated period. Multinomial logistic model (MLM) is employed to examine the determinants of energy intensity trends for the three categories. Our pertinent findings are as follows: firms with higher labour intensity and also older firms have a greater probability of belonging to the category of DEIT firms vis-à-vis the reference category of IEIT firms. Furthermore, size per se does not significantly impact the probability of a firm belonging to any specific category of energy intensity trend; nevertheless, evidence shows that large-sized firms, though old, have a greater probability of belonging to the DEIT category. Rather surprisingly, R&D intensity has been estimated to have a non-significant impact on the probability of belonging to the DEIT group of firms. However, although R&D-intensive firms have a higher profitability, their impacts remain both favourable and significant. Evidence also suggests that an increase in capital intensity and profitability lowers the probability of a firm to belong to the DEIT category. Additionally, a pooled (panel) econometric analysis has also been undertaken wherein the ‘level’ of energy intensity is considered as the dependent variable and not the ‘trend’ in energy intensity. Important findings also emerge from this analysis. Finally, we conclude from a broad policy perspective.