Search

This study aims to investigate the prevalence of weight control attempts along with their strategies and motivations. This study used a retrospective observational qualitative method, and adults who had body mass index (BMI) of at least 25 kg/m2 were included. The qualitative data were analyzed using a descriptive phenomenological approach. The summaries and emergence of major concepts identified by the participants were analyzed in-depth using a systematized retrieval and review of the data. NVivo was used to establish interrater reliability and percent agreement and analyze and manage the data. 91.7% of participants had tried to lose weight, and 72% were successful at least in one of their attempts. Health, appearance, and sports training were salient motivating factors. Their attempts to lose weight ranged from 2 to 30 times (median 4 times). Different dietary strategies and physical exercises were often tried. Among the most notable strategies were diet methods, following weight management programs, and consulting with dietitians. A number of barriers were reported, including ineffective weight loss, non-sustainability, demotivation, and unaffordability. For advancing evidence-based long-term weight control, it is vital to evaluate the quality and nature of weight management strategies and services from the perspective of users.

In this article, two issues related to the design of the experiment are investigated; namely the inspection times and optimal censoring. In the first issue, we study four different approaches to determine the inspection times, namely; pre-specified, equally spaced, optimally spaced, and equal probability using two optimality criteria. In the second issue, we identify the optimal censoring scheme by finding the expected numbers of removals or proportions that attain a specific optimality criterion using two optimality criteria considered. Numerical comparisons using the Monte Carlo simulations are provided of the inspection times, optimum control schemes issues for different parameters and different sample sizes. Statistical measures such as bias and root mean square error for both pre-specified and equal space methods are calculated and the inspection times for different values of the censoring percentage h are obtained. [ABSTRACT FROM AUTHOR]

Abstract Background This study aimed to examine the healthcare-seeking (hospital, primary and preventive care) and healthcare utilisation behaviour of patients with private health insurance (PHI) in Australia. It also aimed to examine the socioeconomic, demographic and lifestyle factors that influence the choice of hospital care in Australia. Method A logistic regression model with repeated measure t-test and Pearson’s Chi-square test were used to identify the factors that affect the choice of care. Data from waves 9 (2009) and 13 (2013) of the nationally-representative Household, Income and Labour Dynamics in Australia (HILDA) survey were used in the analysis. Results Patients with PHI had a higher number of hospital nights’ stay despite having a lower number of hospital admissions than those without private cover. Significant disparities were identified in preventive and specialist care use between patients with cover and without cover. No significant variations were observed in healthcare utilisation for PHI patients before and after dropping PHI. One in four patients chose to use public hospitals despite holding PHI cover. Moreover, those insured and from lower socioeconomic backgrounds and those who were younger and without long-term health conditions showed a higher probability of selecting public rather than private care. Conclusions It is evident that PHI cover encourages people to use private care. However, a considerable number of PHI patients are using public care, even though eligible for private care may indicate consumer information asymmetry.

Background: Health status is a crucial determinant of an individuals’ labour market outcomes. The present study investigates the association between obesity and disability with perceived employment discrimination within Australia. Methods: A total of 17,174 person-year observations from the 11,079 respondents were analysed using four waves of data from the Household, Income, and Labour Dynamics in Australia (HILDA) survey. The primary outcome examined was employment discrimination, using obesity and disability as the main exposure variables. The longitudinal random-effects regression technique was applied to investigate the between-person differences in employment discrimination associated with obesity and disability. Results: The findings suggest that more than one in ten (12.68 %) Australians experienced employment discrimination. The odds of being discriminated against while applying for a job were 1.56 times (aOR: 1.56, 95 % CI: 1.15–2.11) higher for obese than their healthy weight counterparts in youngest women. Adults with a disability had 1.89 times (aOR: 1.89, 95 % CI: 1.65–2.17) higher odds of being discriminated against than peers without disability. Conclusion: The results provide evidence that obesity and disability contribute to employment discrimination in Australia. The findings can assist government and related agencies to consider the adequacy of existing discrimination legislation and help organisations to develop appropriate policies to address discrimination against obese and disabled people in their workplaces.

Background Overweight and obesity impose a significant health burden in Australia, predominantly the middle-aged and older adults. Studies of the association between obesity and chronic diseases are primarily based on cross-sectional data, which is insufficient to deduce a temporal relationship. Using nationally representative panel data, this study aims to investigate whether obesity is a significant risk factor for type 2 diabetes, heart diseases, asthma, arthritis, and depression in Australian middle-aged and older adults. Methods Longitudinal data comprising three waves (waves 9, 13 and 17) of the Household, Income and Labour Dynamics in Australia (HILDA) survey were used in this study. This study fitted longitudinal random-effect logistic regression models to estimate the between-person differences in the association between obesity and chronic diseases. Results The findings indicated that obesity was associated with a higher prevalence of chronic diseases among Australian middle-aged and older adults. Obese adults (Body Mass Index [BMI] ≥ 30) were at 12.76, 2.05, 1.97, 2.25, and 1.96, times of higher risks of having type 2 diabetes (OR: 12.76, CI 95%: 8.88–18.36), heart disease (OR: 2.05, CI 95%: 1.54–2.74), asthma (OR: 1.97, CI 95%: 1.49–2.62), arthritis (OR: 2.25, 95% CI: 1.90–2.68) and depression (OR: 1.96, CI 95%: 1.56–2.48), respectively, compared with healthy weight counterparts. However, the study did not find any evidence of a statistically significant association between obesity and cancer. Besides, gender stratified regression results showed that obesity is associated with a higher likelihood of asthma (OR: 2.64, 95% CI: 1.84–3.80) among female adults, but not in the case of male adults. Conclusion Excessive weight is strongly associated with a higher incidence of chronic disease in Australian middle-aged and older adults. This finding has clear public health implications. Health promotion programs and strategies would be helpful to meet the challenge of excessive weight gain and thus contribute to the prevention of chronic diseases.

Background There is ongoing clinical and research interest in determining whether providing personalised risk information could motivate risk-reducing health behaviours. We aimed to assess the impact on behaviours and risk factors of feeding back to individuals' images of their bodies generated via medical imaging technologies in assessing their current disease status or risk. Methods and findings A systematic review with meta-analysis was conducted using Cochrane methods. MEDLINE, Embase, PsycINFO, CINAHL, and the Cochrane Central Register of Controlled Trials (CENTRAL) were searched up to July 28, 2021, with backward and forward citation searches up to July 29, 2021. Eligible studies were randomised controlled trials including adults who underwent medical imaging procedures assessing current health status or risk of disease, for which personal risk may be reduced by modifying behaviour. Trials included an intervention group that received the imaging procedure plus feedback of visualised results and assessed subsequent risk-reducing health behaviour. We examined 12,620 abstracts and included 21 studies, involving 9,248 randomised participants. Studies reported on 10 risk-reducing behaviours, with most data for smoking (8 studies; n = 4,308), medication use (6 studies; n = 4,539), and physical activity (4 studies; n = 1,877). Meta-analysis revealed beneficial effects of feedback of visualised medical imaging results on reduced smoking (risk ratio 1.11, 95% confidence interval [CI] 1.01 to 1.23, p = 0.04), healthier diet (standardised mean difference [SMD] 0.30, 95% CI 0.11 to 0.50, p = 0.003), increased physical activity (SMD 0.11, 95% CI 0.003 to 0.21, p = 0.04), and increased oral hygiene behaviours (SMD 0.35, 95% CI 0.13 to 0.57, p = 0.002). In addition, single studies reported increased skin self-examination and increased foot care. For other behavioural outcomes (medication use, sun protection, tanning booth use, and blood glucose testing) estimates favoured the intervention but were not statistically significant. Regarding secondary risk factor outcomes, there was clear evidence for reduced systolic blood pressure, waist circumference, and improved oral health, and some indication of reduced Framingham risk score. There was no evidence of any adverse effects, including anxiety, depression, or stress, although these were rarely assessed. A key limitation is that there were some concerns about risk of bias for all studies, with evidence for most outcomes being of low certainty. In particular, valid and precise measures of behaviour were rarely used, and there were few instances of preregistered protocols and analysis plans, increasing the likelihood of selective outcome reporting. Conclusions In this study, we observed that feedback of medical images to individuals has the potential to motivate risk-reducing behaviours and reduce risk factors. Should this promise be corroborated through further adequately powered trials that better mitigate against risk of bias, such interventions could usefully capitalise upon the widespread and growing use of medical imaging technologies in healthcare., Author(s): Gareth J. Hollands 1,2,*, Juliet A. Usher-Smith 3, Rana Hasan 3, Florence Alexander 3, Natasha Clarke 1, Simon J. Griffin 3,4 Introduction Achieving and sustaining changes in health-related behaviours [...]

Abstract Background This paper provides empirical evidence on how the relationship between health expenditure and health outcomes varies across countries at different income levels. Method Heterogeneity and cross-section dependence were controlled for in the panel data which consist of 161 countries over the period 1995–2014. Infant, under-five and maternal mortality along with life expectancy at birth were selected as health outcome measures. Cross-sectional augmented IPS unit root, panel autoregressive distributed lag, Dumitrescu-Hurlin and Toda-Yamamoto approach to Granger causality tests were used to investigate the relationship across four income groups. An impulse response function modelled the impact on health outcomes of negative shocks to health expenditure. Results The results indicate that the health expenditure and health outcome link is stronger for low-income compared to high-income countries. Moreover, rising health expenditure can reduce child mortality but has an insignificant relationship with maternal mortality at all income levels. Lower-income countries are more at risk of adverse impact on health because of negative shocks to health expenditure. Variations in child mortality are better explained by rising health expenditure than maternal mortality. However, the estimated results showed dissimilarity when different assumptions and methods were used. Conclusion The influence of health expenditure on health outcome varies significantly across different income levels except for maternal health. Policymakers should recognize that increasing spending has a minute potential to improve maternal health. Lastly, the results vary significantly due to income level, choice of assumptions (homogeneity, cross-section independence) and estimation techniques used. Therefore, findings of the cross-country panel studies should be interpreted with cautions.

Abstract Background In the literature, measuring health outcomes usually entails examining one dependent variable using cross-sectional data. Using a combination of mortality and morbidity variables, this study developed a new, richer measure of health outcome. Using the health outcome index, this study investigated the impacts of income inequality, levels of ethnic diversity and information and communication technology (ICT) development on health using panel data. Methods Partial least squares regression based on a structural equation model is used to construct a health outcome index for 30 OECD countries over the period of 2004 to 2015 using SmartPLS software. Then, panel corrected standard errors estimation and pooled ordinary least square regression with Driscoll and Kraay standard errors approaches were used to investigate the key determinants of health outcomes. Both methods are efficient when the panel data is heteroscedastic and the errors are cross-sectional dependent. Results Income inequality, level of ethnic diversity and development in ICT access and use have an adverse effect on health outcomes, however, development in ICT skills has a significant positive impact. Moreover, OECD countries with a higher percentage of publicly funded healthcare showed better public health compared to countries where the percentage is smaller. Finally, rising incomes, development of technologies and tertiary education are key determinants for improving health outcomes. Conclusions The results indicate that countries with higher levels of income inequality and more ethnically diverse populations have lower levels of health outcomes. Policymakers also need to recognise the adverse effect of ICT use on public health and the benefits of public healthcare expenditure.

This study aims to investigate the determinants of profitability of fifteen selected private commercial banks in Bangladesh over the period 2005‒2015. The study emphasizes on the internal factors that affect bank profitability. This research uses panel data to explore the impact of nonperforming loan, cost to income ratio, loan to deposit ratio, commission fees, cost of fund and operating expenses on the profitability indicators of banks like return on asset and return on equity. The experimental outcomes have found strong evidence that nonperforming loan (NPL) and operating expenses have a significant effect on the profitability. Moreover, the results have shown that higher NPL may lead to less profit due to provision of classified loans. Again, higher loan to deposit (LD) ratio and cost of fund contribute towards profitability, but their impacts are not significant in the private commercial banks of Bangladesh.

Nowadays, more attention has been paid on wild plants as new source of natural antioxidants. Therefore, methanolic extracts of 10 traditionally consumed wild leafy vegetables of Bangladesh were analyzed for their total phenolic content (TPC) and free radical scavenging activity. Folin–Ciocalteu method followed by spectrophotometric measurement was used to quantify the TPC of the selected wild leafy vegetables. Free radical scavenging activity was examined utilizing 1,1-diphenyl-2-picryl-hydrazyl (DPPH) assay. Different concentrations of the plant extract were applied to ascertain the dose response relationship in inhibiting DPPH free radical. The results revealed that the TPC ranged from 102.20 to 710.42 mg GAE/100g dry weight (DW). The highest TPC was observed in Bauhinia acuminata (Shetokanchan) while Leucas aspera (Shetodhron) exhibited the lowest TPC among the undertaken vegetables. The studied samples proportionately inhibited DPPH with increasing concentrations. At high concentration (500 µg.mL-1), the percentage inhibition of DPPH radical by plant extract ranged from 68.1 ±2.65 % to 93.1 ±1.23 %. The highest DPPH radical inhibition was observed in Bauhinia acuminata (Shetokanchan) (93.10 ±1.23 %), followed by Commelina benghalensis (Bat baittashak) (91.97 ±1.31 %), Hydrocotyle sibthorpiodes L. (Sakumubakla) (91.83 ±2.13 %). The lowest DPPH radical inhibition among the studied samples was observed in Leucas aspera (Shetodhron) (68.1 ±2.65 %). IC50 values measured by DPPH assay in this study ranged from 11.64 to 313.79 µg.mL-1. The study findings indicated that the samples under study possesses strong activity against DPPH, and thus could be used as natural antioxidants in the food and/or pharmaceutical industry.

In this article, we study estimation methodologies for parameters of a generalized inverted exponential distribution based on different estimation methods using progressively type I interval censored data. In this approach, besides conventional maximum likelihood estimation, mid-point method, probability plot method and method of moments are proposed for parameter estimation. To obtain maximum likelihood estimates, we use Newton-Raphson, expectation-maximization and stochastic expectation-maximization methods. Moreover, the approximate confidence intervals of the parameters are obtained via the inverse of the observed information matrix. In addition, percentile bootstrap technique is utilized to compute confidence intervals. Numerical comparisons are presented of the proposed estimators using Monte Carlo simulations. To demonstrate the proposed methodology in a real-life scenario, survival times of guinea pigs injected with different doses of tubercle bacilli data is considered to show the applicability of the proposed methods. Finally, different methods for determining the inspection times and optimal censoring planes are studied. [ABSTRACT FROM AUTHOR]

The objective of this study was to characterize and compare the tissue-associated differences in the fatty acid profiles of intramuscular and subcutaneous fat from pasture fed nondescript deshi breed bulls of Bangladesh. The average chemical composition of the longissimus muscle was as follows: moisture 74.65±0.48%, protein 21.55±0.83%, intramuscular fat 2.78±0.28%, and ash 1.02±0.03%. There was significant evidence that the lipids of longissimus muscle from the nondescript deshi bulls had a lower content of saturated fatty acids (SFA), monounsaturated fatty acids (MUFA), and conjugated linoleic acid (CLA) and a higher content of polyunsaturated fatty acids (PUFA) compared to subcutaneous fat. Intramuscular fat also showed the highest PUFA/SFA and ∑n-6/∑n-3 fatty acids ratios and total n-3 and n-6 PUFAs compared to subcutaneous tissue depots. Overall findings suggest that the meat from pasture fed nondescript deshi breed can be considered as lean meat and healthy for human consumption.

Wild plants are considered the richest source of essential nutrients and other beneficial phytochemicals. Hence, the objective of this study was to evaluate the nutritional composition, antioxidant- and α-amylase inhibition activities of leaves and roots of selected Bangladeshi wild plants. These wild plants were found to have high fiber (13.78−22.26 g/100 g), protein (7.08−21.56 g/100 g) and ash (8.21−21.43 g/100 g) contents. The total phenolic and total flavonoid contents were significantly higher in the leaves than the roots. Additionally, antioxidant activity was evaluated using ferric-reducing antioxidant power, 2, 2-diphenyl-1-picrylhydrazyl radical (DPPH) and trolox equivalent antioxidant capacity assays and was strongly correlated with phenolic compounds. The leaf extracts of the selected plants also exhibited potent α-amylase inhibition (~71%) and were significantly higher than their root counterparts. Thus, the study findings concluded that the investigated plants were good sources of fiber, protein, mineral, natural antioxidant compounds and α-amylase inhibitors, and their increased intake could provide health benefits. The principal component analysis (PCA) of analyzed variables divided the samples into three clear groups, and the first two principal components accounted for 86.05% of the total data set variance.