Statistical Linear Regression Research Articles

Socio-demographic factors’ influence on the energy-saving behaviour of residential consumers: Evidence from Romania

In the context of various attempts to regulate energy consumption and educate consumers in the spirit of sustainable behavior, this paper aims to identify the role of the main socio-demographic factors on the decision to adopt measures to reduce consumption and save energy. Many studies have approached similar topics, but correlating their conclusions, it can be deduced that psycho-socio-demographic factors interact differently from one country to another, depending on the economic and political context of the moment. From the fact that in the former communist countries, the severe political regime subjected the population to very restrictive living conditions, based on deprivations that led to the formation of a traditional saving behavior and, on the other hand, considering the new Sustainable Development Goals (SDGs) that shape the young generation in the spirit of sustainable society, the authors aimed to study the correlation between socio-demographic factors (age, gender, education, professional status, income) and consumption and energy saving behavior at residential level, in an ex-communist state, Romania. For this purpose, quantitative research was carried out based on the answers of 865 subjects to the questionnaire distributed at the Academy of Economic Studies in Bucharest and in the immediate environment to the members of the university community, using convenience sampling. Using descriptive statistical indicators and linear regression techniques, the intensity of correlation between selected variables was determined and the degree of differentiation of the purchasing and use behavior of green-label household appliances was analysed, as well as the population’s availability to adopt some energy-saving methods. Although the sample is not representative, the conclusions are that measures to reduce energy consumption must be voluntary and stratified, depending on the nature of social and demographic factors.

The Effectiveness of Learning Tools Development Guidance on the Success of Students’ Field Practice in the Professional Education Teacher Program at the Early Childhood and Elementary School Level

This study aims to determine the effectiveness of learning development guidance on the success of students’ field practice of teachers in the professional education program for Early Childhood and Elementary School. The population in this study were all professional education students in the Kindergarten and Elementary School Classes of 2022 Faculty of Teacher Training and Education, University of Mataram. The sample used was students in Early Childhood and Elementary Schools who were taken using a proportional random sampling technique. The variables used in this study consisted of independent variables, namely the effectiveness of the supervisor’s role in the development of learning tools (X), as well as the dependent variable, namely the success of field practice (Y). The data obtained were analyzed using the SPSS application version 21. The data analysis used was descriptive statistical data, normality test, and linear regression analysis test. Thus, the results showed that guidance on the development of learning tools by both tutors and supervisors on the success of students’ field practice in the professional education program at the Kindergarten and Elementary School levels proved to be effective, with the resulting effectiveness level of Early Childhood about 33.5% and 8.5% for Elementary school.

KESADARAN WAJIB PAJAK, PENGETAHUAN PAJAK, SANKSI PERPAJAKAN PENGARUHNYA TERHADAP KEPATUHAN WAJIB PAJAK KENDARAAN BERMOTOR

This research aims to examine taxpayer awareness, tax knowledge, tax sanctions and their influence on motor vehicle taxpayer compliance through public service accountability. This research was conducted in Blimbing District, Malang City. The sampling method in this research uses the Nonprobability sampling method using the Proportional sampling technique. Determination of the sample size was calculated using the Slovin formula using 100 samples. The analysis method uses descriptive statistical analysis and linear regression. This type of research is quantitative causality research and data analysis using SPSS. In testing the hypothesis model, we use a multiple linear regression test. The research results show that taxpayer awareness, tax knowledge, tax sanctions have no effect on motor vehicle taxpayer compliance.

The effect of participation education on maternal role adaptation in mothers with premature infants in the neonatal intensive care unit.

The birth of a premature infant, hospitalization, and separation from the family cause disruption on maternal role adaption. This study was conducted with the aim of investigating the effect of participation education on maternal role adaption in mothers of premature infants hospitalized in the neonatal intensive care unit. This semiexperimental study was conducted with the participation of 129 eligible mothers with premature infants into three groups of 43 (face-to-face education, virtual education, and control). Data collection was done using a checklist measuring adaptation to the maternal role. Data were analyzed by descriptive statistical and multiple linear regression tests at a significance level of P < 0.05. The mean age of mothers was 30.8 years, the mean gestational age of infants was 31.7 weeks, the mean birth weight was 1781.4 g, and the most common (84.5%) reason for hospitalization of infants was respiratory distress. Multiple linear regression analysis showed that the total score of maternal role adaptation at the time of discharge was significantly different in the two groups of virtual education (134.362 ± 0.925) (P < 0.001) and face-to-face education (132.421 ± 0.928) (P = 0.005) with the control group (128.286 ± 0.924). The implementation of educational programs is a suitable solution to improve maternal role adaption. Therefore, it is recommended that managers and healthcare planners consider codified and regular educational programs in order to increase the ability of mothers, in order to adapt to the maternal role.

The status of immunization program and challenges in Ethiopia: A mixed method study.

Immunization helps reduce morbidity and mortality attributable to severe vaccine-preventable childhood illnesses. However, vaccination coverage and the quality of immunization data remain challenging in Ethiopia. This has led to poor planning, suboptimal vaccination coverage, and the resurgence of vaccine-preventable disease outbreaks in under-immunized pocket areas. The problem is further compounded by the occurrence of the COVID-19 pandemic and the disruption of the health information system due to recurrent conflict. This study assessed the current status of the immunization service and its challenges in Ethiopia. A mixed-methods study was conducted in three regions of Ethiopia from 21 to 31 May, 2023. A survey of administrative reports was done in a total of 69 health facilities in 14 woredas (districts). Nine KIIs were conducted at a district level among immunization coordinators selected from three regions to explore the challenges of the immunization program. Linear regression and descriptive statistics were used to analyze the quantitative data. Thematic analysis was applied to analyze the qualitative data. The findings from the qualitative data were triangulated to supplement the quantitative results. Two-thirds (66.4%) of the children were fully vaccinated, having received all vaccines, including the first dose of the MCV1, by 12 months of age, as reported through administrative reports collected from health facility records. Catchment area population size and region were significantly associated with the number of fully immunized children (p < 0.001 and p = 0.005, respectively). The vaccination dropout rates of the first to third dose of pentavalent vaccine and the first dose of pentavalent vaccine to the first dose of MCV1 were 8.6% and 7.4%, respectively. A considerable proportion of health facilities lack accurate data to calculate vaccination coverage, while most of them lack accurate data for dropout rates. Longer waiting time, interruptions in vaccine supply or shortage, inaccessibility of health facilities, internal conflict and displacement, power interruption and refrigerator breakdown, poor counseling practice, and caretakers' lack of awareness, fear of side effects, and forgetfulness were the reasons for the dropout rate and low coverage. The result also showed that internal conflict and displacement have significantly affected immunization coverage, with the worst effects seen on the most marginalized populations. The study revealed low vaccination coverage, a high dropout rate, and poor quality of immunization data. Access and vaccination coverage among marginalized community groups (e.g., orphans and street children) were also low. Hence, interventions to address organizational, behavioral, technical, and contextual (conflict and the resulting internal displacement) bottlenecks affecting the immunization program should be addressed.

Predicting soil Cation Exchange Capacity (CEC) from pH, percentage of Clay andOrganic Carbon: A Case Study on Selected Burundi Surface Soils

A statistical linear regression study was performed on surface soil samples collected in four Burundi agro-écological zones (AEZ) of Imbo, Mumirwa, Kirimiro and Moso. The study aimed at evaluating the causal effects of soil pH, % clay and % Organic C (OC) on soil cation exchange capacity (CEC), using simple, two-way and 3-way linear regression models. Soil pH as an explanatory variable of CEC gave poor results, while % OC emerged as the best one-way explanatory variable of CEC (R²=0,40). With 2-way regression analyses, the best fits were obtained in the Kirimiro AEZ with soil pH and % clay (R²=0,63), Imbo AEZ with soil pH and % OC (R²=0.66) and Imbo and Kirimiro AEZ with % clay and % OC (R²=0,63). The 3-way (pH, % clay and % OC) regression analysis gave statistically significant higher R² values ranging from 0.60 (Mumirwa) to 0.76 (Imbo). Linear regression analysis performed on pooled data (256 samples) proved that the 3-way dependent/explanatory variables model is the best fit (R²=0,64). In conclusion, our results outlined that % OC emerges as the key determinant of CEC in highly weathered, kaolinitic Burundi soils.

Health care waste management in nosocomial infection control in a hospital in San Juan de Lurigancho, 2023

The objective of the research is to determine the incidence of healthcare waste management in the control of nosocomial infections associated with care. Its research study with quantitative approach, basic non-experimental type, with a cross-sectional causal correlational design. The population of 350 workers, with a sample of 250 workers who participated in data collection, two instruments were applied, the first was a questionnaire with 34 items and the second a questionnaire with 31 items, both questionnaires validated by expert judgment and assessed by Cronbach's Alpha reliability test, with the results for healthcare waste management α = 0,894 and for nosocomial infection control reliability was α = 0,871. For inferential analysis, ordinal linear regression statistics and the Nagelkerke coefficient were used. The results obtained from the evaluation of healthcare waste management in a San Juan de Lurigancho hospital revealed a considerably high incidence, with a worrying 48 % classified as inadequate. This finding indicates a significant deficiency in waste management practices in the hospital that affects nosocomial infection control, reaching 45 %, suggesting a direct incidence. The conclusion is that sanitary waste management is inadequate and has a negative influence of 75,3 % on infection control

Leadership as a factor of subsistence of MSMEs in Tenosique, Tabasco

The importance of leadership in Micro, Small and Medium Enterprises (MSMEs) is undeniable in today's business landscape. These organizations, often characterized by small size and limited resources, rely heavily on effective leaders to navigate challenges of competitiveness, thrive in competitive markets, and achieve sustainable growth. Therefore, this research, through a qualitative approach, with inductive and interpretative logic, based on documentary analysis and non-experimental, cross-sectional and correlationalcausal type, seeks to propose a leadership model that fits the context of study and positively influences the growth of MSMEs in Tenosique, Tabasco, in order to achieve their subsistence, growth and competitiveness. The study is supported by the use of surveys conducted with previously identified experts in the field and is supported using the Minitab statistical software with the linear regression technique for the analysis of the data.

Tax Fair Compliance: Persepsi of Tax Correction, Public Trust, and Quality of Tax Service

This research aims to see the effect of perceptions of tax corruption, public trust, and quality of tax services on non-employee WPOP compliance at KPP Pratama Bandung Cicadas in 2022. This study is a quantitative study using primary and secondary data. The population used in this study is non-employee WPOP at KPP Pratama Bandung Cicadas. This study used a purposive sampling. Study data will be analyzed with descriptive statistical and multiple linear regression analyses. The results of this study explain that perceptions of tax corruption, public trust, and quality of tax services simultaneously have a significant and partial positive effect on taxpayer compliance.

PENGARUH MEKANISME COPING TERHADAP STRES REMAJA

Teenagers are vulnerable to experiencing stress due to various factors. The study aimed to identify the influence of coping mechanisms on stress among high school teenagers. This research was conducted at Frateran Catholic High School in Surabaya in October to January 2023. This research was a prospective study where the measurement of coping mechanisms and stress was carried out twice. The research sample was 46 teenagers in high schools in Surabaya using a simple random sampling technique. Data collection on coping mechanisms used the BriefCOPE instrument, and stress measurement used the perceived stress scale (PSS10). Data were analyzed using Spearman correlation statistical analysis and linear regression tests. There is a relationship between coping mechanisms and adolescent stress in measurement 1(p= 0.000; correlation coefficient ρ= -0.37), The correlation between coping mechanisms and stress scores in measurement 2 (p=0.02; Correlation coefficient (ρ)=-0 .34) with the degree of strength of the relationship being weak and the direction of the relationship being negative, meaning that the better the coping mechanisms, the lower the adolescent stress score. The regression test between coping mechanisms at measurement 1 and stress scores at time 2 shows R square value of 0.017, meaning 1.7% of adolescent stress is determined by coping mechanisms, other factors determine the rest. In conclusion, there was a relationship between coping mechanisms and adolescent stress in measuring the degree of strength of weak relationships and the direction of negative relationships. Recommendation for further research is to explore the role of social support on adolescent stress.

Reductions in plasma and urine mercury concentrations following N,N′bis-(2-mercaptoethyl) isophthalamide (NBMI) therapy: a post hoc analysis of data from a randomized human clinical trial

Environmental mercury exposure possesses a significant risk to many human populations. At present there are no effective treatments for acute mercury toxicity. A new compound, N,N′bis-(2-mercaptoethyl) isophthalamide (NBMI), a lipophilic chelating agent was created to tightly/irreversibly bind mercury. A post hoc dose-dependent analysis of NBMI therapy was undertaken on data from a randomized controlled NBMI human treatment trial on 36 Ecuadorian gold miners with elevated urinary mercury concentrations. Study subjects were randomly assigned to receive 100 milligram (mg) NBMI/day, 300 mg NBMI/day, or placebo for 14 days. For each study subject daily mg NBMI dose/Kilogram (Kg) bodyweight were determined and plasma and urine mercury concentrations (micrograms (µg)/Liter (L)) on study day 1 (pre-NBMI treatment), 15 (after 14 days of NBMI treatment) and 45 (30 days after NBMI treatment) were correlated with NBMI dosing using the linear regression statistic in SAS. Regression revealed significant inverse correlations between increasing per mg NBMI/Kg bodyweight/day and reduced concentrations of urinary and plasma mercury on study day 15 (reduced by in urine = 18–20 µg/L and plasma = 2 µg/L) and study day 30 (reduced by in urine = 15–20 µg/L and plasma = 4 µg/L) and significant correlations between reductions in mercury concentrations in urine and plasma. Significant 30% reductions in urinary mercury concentrations per mg NBMI/Kg bodyweight/day administered for 14 days were observed. This study supports the dose-dependent ability of NBMI therapy to significantly reduce mercury concentrations, particularly in the urine, in an acutely mercury exposed human population. NBMI therapy should be evaluated in other mercury exposed populations.

Critical Analysis of Innovative Leadership through Effective Data Analytics: Exploring Trends in Business Analysis, Finance, Marketing, and Information Technology

Globally, leaders are lighthouses that help direct followers on the right decision to make, whether in careers, entrepreneurship, personal development, education, community and social services, relationships, health, finances, and enacting purpose. In today's data-driven environment characterized by information overload, leaders and organizations seek to harness the full potential of data to improve every facet of endeavor, including leadership; thus, leaders in management and other spheres of human endeavors must rethink leadership methods in line with data analytics. This research investigates the synergistic relationship between innovative leadership and effective data analytics in organizations across different industries. The study assesses the impact of data analysis, visualization, and governance on various aspects of innovative leadership. Structured questionnaires designed using Likert scale questions and statements were used as research instruments to collect data from 490 leaders across five industries, including Accounting and Finance, Marketing, Computer and IT, Business Development, and Education. Statistical analysis, including correlation and linear regression, examined the relationships between data analytics and innovative leadership variables. The research findings support the hypotheses, demonstrating that data Analysis Influences Innovative Behavior in leadership; data Analysis is significantly and positively related to Vision and Strategic Planning; data Visualization significantly impacts Communication Skills in leadership positively; Data Visualization significantly influences Vision and Strategic Planning in leadership positively; while a positive relationship exists between Effective Data Governance and Innovative Behavior. Data analytics is critical in achieving innovative leadership and improving organizational performance. Data analysis, visualization, and governance were essential in driving innovation and fostering clear communication. The paper recommends the promotion of a culture of collaboration and open communication, investment in employee training for data analytics skills, and encouraging innovative thinking through data-driven problem-solving strategies. The research offers a foundation for further investigations into industry-specific nuances and external factors influencing the collaboration between data analytics and innovative leadership.

Hydrological and climate impacts on river characteristics of pahang river basin, Malaysia

The climate, geomorphological changes, and hydrological elements that have occurred have all influenced future flood episodes by increasing the likelihood and intensity of extreme weather occurrences like extreme precipitation events. River bank erosion is a natural geomorphic process that occurs in all channels. As modifications of sizes and channel shapes are made to transport the discharge, sediment abounds from the stream catchment, and floods are triggered dramatically. The aim of this study is to analyze the flood-sensitive regions along the Pahang River Basin and determine how climate and river changes would have an impact on flooding based on hydrometeorological data and information on river characteristics. The study is divided into three stages, namely the upstream, middle stream, and downstream of the Pahang River. The main primary hydrometeorological data and river characteristics, such as Sinuosity Index, Dominant Slope Range and Entrenchment Ratio collected as important inputs in the statistical analysis process. The statistical analyses, namely HACA, PCA, and Linear Regression applied in river classification. The result showed that the middle stream and downstream areas demonstrated the worst flooding affected by anthropogenic and hydrological factors. Rainfall distribution is one of the factors that contributed to the flood disaster. There are strong correlations between the Sinuosity Index (SI) and water level, which indicates that changes occurred at both planform and stream classification. The best management practices towards sustainability are based on the application of the outcomes that have been obtained after the analysis of Pahang River planform changes, Pahang River geometry, and the local rainfall pattern in the Pahang River Basin.

Modeling The Influenced Factors of Remaining Operation Results Using Multiple Linear Regression

The amount of Remaining Operation Results (ROR) obtained by Koperasi can reflect the health ofits financial management. Many economic factors can affect the ROR of Koperasi itself. This studyaims to determine the economic factors that significantly influence ROR based on a statistical model ofmultiple linear regression. The novelty of this research provides new analytical results that compare themost three influential factors based on previous research to show the factors significantly influencingthe ROR. The quantitative data used the five years financial statements of Koperasi Sawit Makmur in2017-2021 consists of 20 data on liabilities, net worth, assets, and ROR of Koperasi Sawit Makmur. Theresults show that asset variable as an excluded variable that does not affect the ROR of Koperasi withR2 = 0, 961. Liabilities and net worth variables can explain 96.1% of ROR, with 3.9% can be explainedby assets and other variables not included in the study. Liabilities have a negative and tangible effect,and net worth has a positive and partially real influence on ROR. The factor with the most dominantinfluence on ROR is net worth, with an influence percentage of 63,80%. The future research is expectedto provide an overview of net worth and asset determinants using related statistical methods.

The impact of transfer pricing and thin capitalization on tax avoidance in the advertising, printing, media, wholesale trade, and production of goods listed on the Indonesia Stock Exchange during the 2020 – 2022 period

One of the revenues received by a country comes from tax payments. However, some people consider taxes a burden, which becomes a reason to engage in tax avoidance practices. This research aims to identify the impact of transfer pricing practices and minimal capital use on tax avoidance efforts in the advertising, printing, media, wholesale trade, and goods production subsectors during the 2020-2022 period. This quantitative research method collects secondary data from companies listed on the Indonesia Stock Exchange (BEI) annual reports. This data was obtained from official sources, including the company's official website and the IDX website, and succeeded in collecting a sample of 30 companies. Data was analyzed using multiple linear regression and IBM SPSS Statistics 25 software. The research results show that setting transfer prices and using minimal capital significantly influences tax avoidance efforts in the advertising, printing, media, wholesale trade, and goods production subsectors. Listed on the Indonesian Stock Exchange during the 2020-2022 period. These findings have important implications, emphasizing the importance for all parties concerned to comply with tax obligations without trying to avoid them.

Influence of growth ring number and width on elastic constants of poplar

The objective of this work was to evaluate the effect of growth ring number (specimens including 2, 4, and 6 rings from the bark) and growth ring width on elastic constants in the radial direction of Populus x canadensis, which has not been revealed before. The longitudinal (2.25 MHz) and transverse (1 MHz) ultrasonic waves were propagated to calculate the longitudinal (VRR) and shear (VRL, VLR, VTR, and VRT) wave velocities and used to determine the elasticity modulus (ER), and shear moduli (GRL and GRT). The average growth ring widths of specimens including 2, 4, and 6 rings were 17.0 mm, 17.8 mm, and 18.2 mm, respectively. According to the results, only VRL steadily increased with increased ring number, while other velocities fluctuated. The same fluctuations were observed for moduli except for GLR, which constantly increased with ring number. The influence of ring number on velocity was statistically significant only for VRL and VRT. However, all moduli were significantly affected by ring number. Linear regression statistics revealed that there were significant relations between the ring width and density, VRL, VLR, VRT, GRL, and GRT.

Development of a physics-based method for calibration of low-cost particulate matter sensors and comparison with machine learning models

Low cost particulate matter sensors are receiving significant attention as they can be used in large number for spatial and temporal measurement of PM mass and number concentration. However, the data reliability is questionable as these sensors are affected by numerous parameters such as temperature, relative humidity, and hygroscopicity of particles. To ensure accurate and reliable measurement of particulate matter concentrations, performance evaluation and calibration of LCS co-located with reference instrument at site is essential. In this study, the performance of the low-cost sensor (APT Maxima) was evaluated with the reference instrument SASS (Speciation Air Sampling System) sampler for developing suitable calibration factor that include impact of the meteorological parameter such as relative humidity and temperature, and hygroscopicity. In this study, we have demonstrated a systematic physics-based method for calibration of LCS based on κ-Köhler theory and Mie theory. For comparison with statistical models, linear regression and machine learning algorithm were also applied. In physics-based model, calculated total light scattered intensity shows good linearity with reference PM2.5 measurements. Physics based model performed better for both the sites as compared to MLR, kNN, RF, and GB ML algorithms with R2, RMSE, and MAE values of 0.72,18.21, and 13.36 for Bhopal site, and 0.91, 7.84, and 5.76 for Kashmir site, respectively. Study indicates that physics-based approach for LCS calibration is suitable and can be transferable to different sites.

Classification of health needs: a cluster analysis of older adults in urban areas

BackgroundIn this study, a cross-sectional survey was used to understand and analyze the health status and health needs of the elderly in the community. The cluster analysis method was used to explore the relationship between health needs items and investigate the commonness among health demand items, to provide a reference for the development of health management of the elderly with chronic diseases.MethodsWe used convenience sampling to recruit the participants (aged 60 and above) from four urban community centers in Jinzhou City, Liaoning Province, China, in this study. This study uses the Medical Outcomes Study(MOS)36-Item Short-Form Health Survey. The self-designed questionnaire includes sociodemographic characteristics, chronic diseases, physical examination conditions, illness in the past two weeks, and a health needs questionnaire. SPSS 18.0 was used for data entry and analysis. Data analysis methods included descriptive statistical analysis, t-test, one-way analysis, cluster analysis, and linear multiple regression analysis.ResultsThe rate of health needs among the elderly in the community for various health services is 1.3–69.7%, of which the top three are: regular physical examination (69.7%), day Care Center (67.7%), the establishment of a Medical Alert Systems (66.1%). The health needs of the elderly in the community are divided into three categories: basic needs (24 items), health education (13 items), and first aid (2 items). The regression analysis found that the influencing factors of health status were age, revenue and expenditure, medical expenses, health education, basic needs, and first aid.ConclusionsThe community should strengthen the management of chronic diseases of the elderly and the publicity and education of related knowledge, and provide complementary health care services according to the health needs of the elderly, improve the health of the elderly, and improve the quality of life of the elderly.

The British Columbia Farmers’ Market Nutrition Coupon Program Reduces Short-Term Household Food Insecurity Among Adults With Low Incomes: A Pragmatic Randomized Controlled Trial

BackgroundThe British Columbia Farmers’ Market Nutrition Coupon Program (BC FMNCP) provides households with low incomes with coupons to purchase healthy foods from farmers’ markets. ObjectiveTo examine the impact of the BC FMNCP on the short-term household food insecurity, malnutrition risk, mental well-being, sense of community (secondary outcomes), and subjective social status (exploratory outcome) of adults with low incomes post-intervention and 16 weeks post-intervention. DesignSecondary analyses from a pragmatic randomized controlled trial conducted in 2019 that collected data at baseline, post-intervention, and 16 weeks post-intervention. Participants/settingAdults ≥18 years with low incomes were randomized to an FMNCP group (n = 143) or a no-intervention control group (n = 142). InterventionParticipants in the FMNCP group received 16 coupon sheets valued at $21 Canadian dollars (CAD)/sheet over 10 to 15 weeks to purchase healthy foods from farmers’ markets and were eligible to participate in nutrition skill-building activities. Main outcome measuresOutcomes included short-term household food insecurity (modified version of Health Canada’s 18-item Household Food Security Survey Module), malnutrition risk (Malnutrition Universal Screening Tool), mental well-being (Warwick-Edinburgh Mental Well-Being Scale), sense of community (Brief Sense of Community Scale), and subjective social status (MacArthur Scale of Subjective Social Status community scale). Statistical analysisMixed-effects linear regression and multinomial logistic regression examined between-group differences in outcomes post-intervention and 16 weeks post-intervention. ResultsThe risk of marginal and severe short-term household food insecurity was lower among those in the FMNCP group compared with those in the control group (relative risk ratio [RRR] 0.15, P = 0.01 and RRR 0.16, P = 0.02) post-intervention, with sustained reductions in severe household food insecurity 16 weeks post-intervention (RRR 0.11, P = 0.01). No statistically significant differences were observed in malnutrition risk, mental well-being, sense of community, or subjective social status post-intervention or 16 weeks post-intervention. ConclusionsThe BC FMNCP reduced short-term household food insecurity but was not found to improve malnutrition risk or psychosocial well-being among adults with low incomes compared with a no-intervention control group.

Association of baseline physical activity participation with participant characteristics and outcomes following education and exercise-therapy in people with knee osteoarthritis: AGLA:D® Australia prospective cohort study.

To investigate whether participants with knee osteoarthritis classified as 'more' or 'less' physically active at baseline differ in characteristics and/or outcomes at baseline and at 3 and 12 months following the commencement of an education and exercise-therapy program. Prospective cohort study using the GLA:D® Australia registry. The University of California, Los Angeles Physical Activity Scale (UCLA) participant data dichotomised as 'more' (≥7) or 'less' active (≤6). Groups were compared using chi-square (obesity [baseline only], comorbidity prevalence, medication consumption, fear of damage from physical activity); and linear mixed model regression (12-item Injury Osteoarthritis Outcome Score [KOOS-12], pain [visual analogue scale], health-related quality of life [QoL] [EQ-5D-5L]) statistics, adjusted for age, sex and baseline physical activity at 3 and 12 months. We included 1059 participants (70% female). At baseline, 267 (25%) were classified as 'more' active, increasing to 29% and 30% at 3 and 12 months, respectively. At baseline, compared to the 'less' active group, the 'more' active group had a lower proportion of participants who were obese ('more'=21% vs. 'less'=44%), had comorbidities (58% vs. 74%) and consumed medications (71% vs. 85%); lower pain intensity (37 vs. 47); and higher KOOS-12 (59 vs. 50), and health-related QoL (0.738 vs. 0.665) scores. When accounting for age, sex and baseline physical activity, improvements seen in knee-related burden and health-related QoL were not different between groups at 3 or 12 months. Compared to the 'less' active group, the proportion of participants not consuming medication remained higher in the 'more' active group at 3 ('more' 45% vs. 'less' 28%) and 12 months (43% vs. 32%). 'More' active people with knee osteoarthritis were less likely to be obese, had fewer comorbidities, lower medication consumption, knee-related burden and pain intensity, and higher health-related QoL than 'less' active participants at all timepoints.