Nevin Manimala

Diabetes Metab Syndr. 2022 Feb 18;16(3):102428. doi: 10.1016/j.dsx.2022.102428. Online ahead of print.

ABSTRACT

BACKGROUND AND AIMS: Underweight and overweight/obesity is a critical public health problem among women in South Asian countries. This study aimed to find the prevalence of underweight and overweight/obesity and discover its associated factors among women of reproductive age in four South Asian countries.

METHODS: Population-representative cross-sectional latest Demographic and Health Survey data from four South Asian countries, considering Bangladesh (2017-18), Maldives (2016-17), Nepal (2016), and Pakistan (2017-18), were pooled for this study. To investigate the factors related with underweight and overweight/obesity in women, a multivariate multinomial logistic regression model was deployed.

RESULTS: The overall prevalence of underweight and overweight/obesity among reproductive-age women in four South Asian countries was 11.8% and 36.3%, respectively. According to adjusted multivariate multinomial logistic regression analysis, women who lived in Pakistan, were older, had a better education, were from the wealthiest home, were currently in union and had media exposure had a considerably decreased probability of being underweight. In contrast, families with a large number of members had a considerably increased risk of becoming underweight. Additionally, women from the Maldives, older age, secondary education, a higher number of children, women from the richest household, currently in the union, the family had media exposure, and pregnant women have been found significantly positively associated with overweight/obesity. However, Nepalese women, large family members, rural residence, and work involvement were significantly negatively associated with overweight/obesity.

CONCLUSION: The problem of being underweight and overweight/obesity still exists in South Asian countries. Focusing on women’s age, education, wealth index, and media exposure, different public health intervention approaches are imperative to reduce unhealthy weight conditions.

PMID:35219260 | DOI:10.1016/j.dsx.2022.102428

Ecotoxicol Environ Saf. 2022 Feb 23;233:113332. doi: 10.1016/j.ecoenv.2022.113332. Online ahead of print.

ABSTRACT

Petrochemical industry is a key industry of soil pollution, which presents great effects on human health and the ecological environment. It is of great significance to achieve rapid, economic and efficient health risk identification for petrochemical industry in China. In this work, an efficient method was developed based on extreme gradient boosting (XGBoost) algorithm for human health risk identification, which is different from the traditional health risk assessment with complicated procedures. In this methodology, an index system of 13 indicators was established from the perspective of “sources – pathways – receptors” for risk identification. The 10-fold cross validation was used to assess the generalization performance, and the accuracy, precision and recall were employed to evaluate the performance of the algorithms. Wilcoxon signed-rank test was conducted to analyze the differences between XGBoost and other models for statistical support. The results showed that XGBoost significantly presented a better performance for health risk identification over multilayer perceptron neural network with error backpropagation training (BPNN), support vector machine (SVM), gradient boosting decision tree (GBDT) and light gradient boosting machine (LightGBM), with an accuracy of 0.783. The most important features contributing to the risk identification were determined with the sequence of site location (in the industrial zone or not), site planning and production period. Great attention should be given to the petrochemical sites that are not located in the industrial zone with long production period and sensitive receptors in the health risk identification. This method has important reference significance for relevant departments to carry out soil contamination screening and health risk assessment of petrochemical sites.

PMID:35219256 | DOI:10.1016/j.ecoenv.2022.113332

Waste Manag. 2022 Feb 23;143:35-45. doi: 10.1016/j.wasman.2022.02.018. Online ahead of print.

ABSTRACT

Municipal solid waste (MSW) composting is one of the most effective strategies for MSW management but detrimental litter such as plastic and glass debris must be discarded elsewhere. Well-segregated wastes are necessary in this context. A compost bin is a waste collection tool for source separation. To date, the deployment of compost bins for source separation has received scant investigation. This study investigated the effects of compost bin design in terms of user design preferences, waste collection and sorting execution, and segregation behavior. The study comprised a survey and an on-site experiment. Design preferences of nine designed compost bins were evaluated by surveying 400 respondents using the pairwise comparison method. It was revealed that design preference was determined by bin shape and slot position. On-site experiments were conducted to establish collection rate, contamination rate, capture rate, and effective capture rate under different conditions. Under the experimental conditions, better segregation rates were observed in comparison with the control condition. The contamination rate was reduced by 55.9%. The capture rate and the effective capture rate were increased by 8.90%, and 53.4%, respectively. The significant effects of design preferences, physical designs, visual prompts, and past behavior were identified via statistical methods. Source-separated waste collection can be improved through preferred compost bin adoption, enhanced design, appropriate visual prompts, and experience in waste segregation. Therefore, the findings of this study will help to generate effective source-separated collection and allow compost bins to be placed in public areas for integrated and sustainable waste management.

PMID:35219254 | DOI:10.1016/j.wasman.2022.02.018

J Surg Res. 2022 Feb 23;275:35-42. doi: 10.1016/j.jss.2022.01.018. Online ahead of print.

ABSTRACT

INTRODUCTION: Multiple factors signifying higher social vulnerability, including lower socioeconomic status and minority race, have been associated with presentation with complicated appendicitis (CA). In this study, we compared the Social Vulnerability Index (SVI) of our population by appendicitis severity (uncomplicated appendicitis [UA] versus CA). We hypothesized that SVI would be similar between patients with UA and CA presenting to our institution, a safety-net hospital in a state with high healthcare insurance coverage.

METHODS: We included all patients at our hospital aged 18 y and older who underwent appendectomy for acute appendicitis between 2012 and 2016. SVI values were determined based on the 2010 census data using ArcMap software. We used nonparametric univariate statistics to compare the SVI of patients with CA versus UA and multivariable regression to model the likelihood of operative CA.

RESULTS: A total of 997 patients met inclusion criteria, of which 177 had CA. The median composite SVI score for patients with CA was lower than for patients with UA (80% versus 83%, P = 0.004). UA was associated with higher socioeconomic (83% versus 80%, P = 0.007), household/disability (68% versus 55%, P = 0.037), and minority/language SVI scores (91% versus 89%, P = 0.037). On multivariable analysis controlling for age, sex, ethnicity, insurance status, relevant comorbidities, and chronicity of symptoms, there was an inverse association between SVI and the likelihood of CA (odds ratio 0.59, 95% confidence interval 0.4-0.87, P = 0.008).

CONCLUSIONS: In the setting of high healthcare insurance and a medical center experienced in caring for vulnerable populations, patients presenting with UA have a higher composite SVI, and thus greater social vulnerability, than patients presenting with CA.

PMID:35219249 | DOI:10.1016/j.jss.2022.01.018

J Surg Res. 2022 Feb 23;275:10-15. doi: 10.1016/j.jss.2021.12.021. Online ahead of print.

ABSTRACT

BACKGROUND: The aim of this study is to evaluate risk factors for non-attendance to post-discharge, hospital follow-up appointments for traumatically injured patients who underwent exploratory laparotomy.

METHODS: This is a retrospective chart review of patients who underwent exploratory laparotomy for traumatic abdominal injury at an urban, Midwestern, level I trauma center with clinic follow-up scheduled after discharge. Clinically, relevant demographic characteristics, patients’ distance from hospital, and the presence of staples, sutures, and drains requiring removal were collected. Descriptive statistics of categorical variables were calculated as totals and percentages and compared with a chi-squared test or Fisher’s exact when appropriate.

RESULTS: The sample included 183 patients who were largely assaultive trauma survivors (68%), male (80%), and black (53%) with a mean age of 35.4 ± 14.9 years. Overall, 18.5% no-showed for their follow-up appointment. On multivariate analysis for clinic no-show; length of stay (odds ratio = 0.92 [0.84-0.99], P = 0.04) and the need for suture, staple, or drain removal were protective for clinic attendance (odds ratio = 5.59 [1.07-7.01], P = 0.04). Overall, 12 patients (6.4%) were readmitted. Forty patients (18.3%) had their follow-up in the emergency department (ED). On multivariate regression of risk factors for ED visits, the only statistically significant factors (P < 0.05) were clinic appointment no-show (OR = 2.81) and self-pay insurance (OR = 4.78).

CONCLUSIONS: Abdominal trauma patients are at high risk of no-show for follow-up appointments and no-show visits are associated with ED visits. Future work is needed evaluating interventions to improve follow-up.

PMID:35219246 | DOI:10.1016/j.jss.2021.12.021

Mult Scler Relat Disord. 2022 Feb 19;60:103692. doi: 10.1016/j.msard.2022.103692. Online ahead of print.

ABSTRACT

BACKGROUND: Cognitive impairment is frequent in multiple sclerosis (MS), but reliable, sensitive and individualized monitoring in clinical practice is still limited. Smartphone-adapted tests may enhance the assessment of function as tests can be performed more frequently and within the daily living environment. The objectives were to prove reproducibility of a smartphone-based Symbol Digit Modalities Test (sSDMT), its responsiveness to relevant change in clinical cognitive outcomes, and develop an individual-based monitoring method for cognition.

METHODS: In a one-year cohort study with 102 patients with MS, weekly sSDMTs were performed and analyzed on reproducibility parameters: the standard error of measurement (SEM) and smallest detectable change (SDC). Responsiveness of the sSDMT to relevant change in the 3-monthly clinically assessed SDMT (i.e. 4-point change) was quantified with the area under the receiver operating characteristic curve (AUC). Curve fitting of the weekly sSDMT scores of individual patients was performed with a local linear trend model to estimate and visualize the de-noised cognitive state and 95% confidence interval (CI). The optimal assessment frequency was determined by analyzing the CI bandwidth as a function of sSDMT assessment frequency.

RESULTS: Weekly sSDMT showed improved reproducibility estimates (SEM=2.94, SDC=8.15) compared to the clinical SDMT. AUC-values did not exceed 0.70 in classifying relevant change in cSDMT. However, utilizing weekly sSDMT measurements, estimated state curves and the 95% CI were plotted showing detailed changes within individuals over time. With a test frequency of once per 12 days, 4-point changes in sSDMT can be detected.

CONCLUSION: A local linear trend model applied on sSDMT scores of individual patients increases the signal-to-noise ratio substantially, which improves the detection of statistically reliable changes. Therefore, this fine-grained individual-based monitoring approach can be used to complement current clinical assessment to enhance clinical care in MS.

TRIAL REGISTRATION: Netherlands Trial Register NL7070; https://www.trialregister.nl/trial/7070.

PMID:35219240 | DOI:10.1016/j.msard.2022.103692

J Environ Manage. 2022 Feb 23;310:114755. doi: 10.1016/j.jenvman.2022.114755. Online ahead of print.

ABSTRACT

Methane (CH₄) is one of the dominant greenhouse gases (GHG) that is largely emitted from rice fields and thus, significantly contributes to global warming. Significant efforts have been made to find out suitable strategies to mitigate CH₄ emission from rice culture. However, the effectiveness of these management practices is often diverse with negative, no, or positive impacts making it difficult to adopt under a particular condition. The diversity of rice cultivation in terms of agro-climatic conditions and cultivation practices makes it difficult for providing specific recommendations. Here, we collected data from a total of 198 studies reporting 1052 observations. The management practices are categorized into five different management practices i.e., water, organic and inorganic fertilizer management, crop establishment method, and agronomic practices while major categories were subdivided into different classes. To test statistically significant differences in the effectiveness between major management practices, an analysis of variance (ANOVA) was applied. The Gaussian and bootstrapping model were applied to find out the best estimate of the effectiveness of each practice. In addition, mechanisms controlling the CH₄ emission reductions were synthesized. Next, the adoption potentials of these practices were assessed based on the existing rice cultivation systems in Bangladesh. Our results showed that water and organic matter management were the most effective methods irrespective of the growing conditions. When these technologies are customized to Bangladesh, water management and crop establishment methods seem most feasible. Among the rice-growing seasons in Bangladesh, there is a larger scope to adopt these management practices in the Boro season (December to May), while these scopes are minimal in the other two seasons due to their rain-fed nature of cultivation. Altogether, our study provides fundamental insights on CH₄ reductions strategies from rice fields in Bangladesh.

PMID:35219203 | DOI:10.1016/j.jenvman.2022.114755

Res Vet Sci. 2022 Feb 11;145:177-187. doi: 10.1016/j.rvsc.2022.02.014. Online ahead of print.

ABSTRACT

The aims of the present study were to evaluate the ability of a subunit vaccine composed of recombinant molecules of α-toxin, β-toxin, FnBPA and ClfA, formulated with cationic liposomes and CpG-ODN, to confer protection against natural S. aureus intramammary infection (IMI) and to assess the antibody response against the vaccine components. A stringent criterion based on molecular identification of the isolates was used to define IMI. The proportion of animals that developed new S. aureus IMI was higher in the Control group compared with the Vaccine group (reduction of 60.7%), and time to new S. aureus IMI was higher for animals in the Vaccine group compared with animals in the Control group, although not statistically significant. Molecular identification of the isolates allowed the detection of S. aureus pulsotypes that appeared transiently in milk and others that were able to establish IMI, providing a new perspective to define parameters related to the definition of new IMI and cures. Specific IgG, IgG1 and IgG2 levels against the four recombinant proteins included in the vaccine were significantly increased in the vaccinated group and the recombinant α-toxin included in the vaccine generated antibodies that reduced significantly the haemolytic activity of native α-toxin. Data reported in the present study indicate a possible effect on both the proportion of animals developing new IMI and the time to new S. aureus IMI, but the incidence of disease within the study was too low to provide statistical confirmation.

PMID:35219182 | DOI:10.1016/j.rvsc.2022.02.014

Eur J Obstet Gynecol Reprod Biol. 2022 Feb 15;271:183-188. doi: 10.1016/j.ejogrb.2022.02.012. Online ahead of print.

ABSTRACT

OBJECTIVE: To investigate whether the frequency of uterine cavity abnormalities in PCOS patients higher than the normo-ovulatory patients.

STUDY DESIGN: This retrospective cohort study was conducted at the ART center of a tertiary university hospital. A total of 103 patients; 51 PCOS, and 52 male factor infertility were enrolled in the study between the years 2011-2019. HSG images of all patients were numbered and evaluated by ten senior reproductive endocrinologists and surgeons whom were blinded to the research and choose the most appropriate figure for each patient’s HSG image and marked the shape of cavity according to the ASRM and ESGE/ESHRE classification. Results and demographic parameters were compared between PCOS and male factor infertility groups.

RESULTS: The percentage of the normal uterine cavity was significantly lower in the PCOS group than control group as 51 % and 66.7 %, 77 % and 94.2 % according to the ASRM and ESHRE/ESGE classifications, respectively. The frequency of Partial Septate Uterus (ESHRE-ESGE U2a / ASRM Va, 21.6% vs 5.8 % p < 0.05), Complete Septate Uterus (ESHRE-ESGE U2b / ASRM Vb, 7.8% vs 0% p < 0.01) and Dysmorphic Uterus (ESHRE-ESGE U1c) / ASRM VII) 3.9 % vs 0p < 0.05) were significantly higher in PCOS patients than controls. The frequency of arcuate uterus classified as VI in ASRM and considered as normal in ESHRE/ESGE was 16 % and 17.3 % in PCOS and control groups, respectively, without statistically significant difference.

CONCLUSIONS: This study provides that, compared to the healthy population, the frequency of uterine cavity abnormality is clearly higher in PCOS patients.

PMID:35219169 | DOI:10.1016/j.ejogrb.2022.02.012

Horm Behav. 2022 Feb 23;141:105138. doi: 10.1016/j.yhbeh.2022.105138. Online ahead of print.

ABSTRACT

A primary goal of the field of behavioral neuroendocrinology is to understand how the brain modulates complex behavior. Over the last 20 years we have proposed various brain networks to explain behavioral regulation, however, the parameters by which these networks are identified are often ill-defined and reflect our personal scientific biases based on our area of expertise. In this perspective article, I question our characterization of brain networks underlying behavior and their utility. Using the Social Behavior Network as a primary example, I outline issues with brain networks commonly discussed in the field of behavioral neuroendocrinology, argue that we reconsider how we identify brain networks underlying behavior, and urge the future use of analytical tools developed by the field of Network Neuroscience. With modern statistical/mathematical tools and state of the art technology for brain imaging, we can strive to minimize our bias and generate brain networks that may more accurately reflect how the brain produces behavior.

PMID:35219166 | DOI:10.1016/j.yhbeh.2022.105138