Multivariate Multiple Linear Regression Research Articles

The Effect of Motivation on Physical Activity among Middle and High School Students.

The study addressed two main objectives: (i) to investigate disparities in motivation dimensions regarding extracurricular physical activity and (ii) to identify the influence of motivation on time spent in formal and informal physical activity. A sample of 704 adolescents (56% girls) from middle (46%) and high school (54%), with an average age of 14.88 ± 2.52, was assessed for different motivation dimensions using the Questionnaire of Motivation for Sports Activities (QMSA). Additionally, participants were categorized based on extracurricular physical activity practice. Multivariate analyses and multiple linear regressions were conducted to examine the effect of physical activity type on motivation dimensions and identify predictors of time spent in formal and informal physical activities, respectively. Results indicated that motivation varied significantly with extracurricular physical activity practice (p < 0.05), with students involved in extracurricular activities being more motivated. Sex and age differences were observed, with boys showing higher motivation in certain dimensions (achievement status (p < 0.001); group activity (p = 0.027); contextual (p = 0.004); technical improvement (p = 0.012) and older participants having lower scores in all dimensions. The influence of family and friends was a significant predictor only for boys in formal physical activity (p = 0.039). In terms of time spent in physical activity, group activity was a predictor for informal activities (p < 0.001), while technical improvement was a predictor for formal activities (p < 0.001), with notable sex differences. These findings underscore the importance of considering sex- and age-specific motivations when promoting physical activity among adolescents.

Does artificial intelligence predict orthognathic surgical outcomes better than conventional linear regression methods?

ABSTRACT Objectives To evaluate the performance of an artificial intelligence (AI) model in predicting orthognathic surgical outcomes compared to conventional prediction methods. Materials and Methods Preoperative and posttreatment lateral cephalograms from 705 patients who underwent combined surgical-orthodontic treatment were collected. Predictors included 254 input variables, including preoperative skeletal and soft-tissue characteristics, as well as the extent of orthognathic surgical repositioning. Outcomes were 64 Cartesian coordinate variables of 32 soft-tissue landmarks after surgery. Conventional prediction models were built applying two linear regression methods: multivariate multiple linear regression (MLR) and multivariate partial least squares algorithm (PLS). The AI-based prediction model was based on the TabNet deep neural network. The prediction accuracy was compared, and the influencing factors were analyzed. Results In general, MLR demonstrated the poorest predictive performance. Among 32 soft-tissue landmarks, PLS showed more accurate prediction results in 16 soft-tissue landmarks above the upper lip, whereas AI outperformed in six landmarks located in the lower border of the mandible and neck area. The remaining 10 landmarks presented no significant difference between AI and PLS prediction models. Conclusions AI predictions did not always outperform conventional methods. A combination of both methods may be more effective in predicting orthognathic surgical outcomes.

Orthodontic treatment outcome predictive performance differences between artificial intelligence and conventional methods

ABSTRACT Objectives To evaluate an artificial intelligence (AI) model in predicting soft tissue and alveolar bone changes following orthodontic treatment and compare the predictive performance of the AI model with conventional prediction models. Materials and Methods A total of 1774 lateral cephalograms of 887 adult patients who had undergone orthodontic treatment were collected. Patients who had orthognathic surgery were excluded. On each cephalogram, 78 landmarks were detected using PIPNet-based AI. Prediction models consisted of 132 predictor variables and 88 outcome variables. Predictor variables were demographics (age, sex), clinical (treatment time, premolar extraction), and Cartesian coordinates of the 64 anatomic landmarks. Outcome variables were Cartesian coordinates of the 22 soft tissue and 22 hard tissue landmarks after orthodontic treatment. The AI prediction model was based on the TabNet deep neural network. Two conventional statistical methods, multivariate multiple linear regression (MMLR) and partial least squares regression (PLSR), were each implemented for comparison. Prediction accuracy among the methods was compared. Results Overall, MMLR demonstrated the most accurate results, while AI was least accurate. AI showed superior predictions in only 5 of the 44 anatomic landmarks, all of which were soft tissue landmarks inferior to menton to the terminal point of the neck. Conclusions When predicting changes following orthodontic treatment, AI was not as effective as conventional statistical methods. However, AI had an outstanding advantage in predicting soft tissue landmarks with substantial variability. Overall, results may indicate the need for a hybrid prediction model that combines conventional and AI methods.

Variable parameters memory-type control charts for simultaneous monitoring of the mean and variability of multivariate multiple linear regression profiles

Variable parameters (VP) schemes are the most effective adaptive schemes in increasing control charts' sensitivity to detect small to moderate shift sizes. In this paper, we develop four VP adaptive memory-type control charts to monitor multivariate multiple linear regression profiles. All the proposed control charts are single-chart (single-statistic) control charts, two use a Max operator and two use an SS (squared sum) operator to create the final statistic. Moreover, two of the charts monitor the regression parameters, and the other two monitor the residuals. After developing the VP control charts, we developed a computer algorithm with which the charts' time-to-signal and run-length-based performances can be measured. Then, we perform extensive numerical analysis and simulation studies to evaluate the charts’ performance and the result shows significant improvements by using the VP schemes. Finally, we use real data from the national quality register for stroke care in Sweden, Riksstroke, to illustrate how the proposed control charts can be implemented in practice.

Experience of violence and attitudes of staff members towards coercion in psychiatric settings: observational study.

Among important dimensions related to the use of coercive measures, professionals' attitude towards coercion is of particular interest. Little is known about how experiences of violence in the workplace might influence these attitudes. The present study aimed to investigate potential correlates of attitudes towards coercion, especially experiences of violence in the workplace. Mental health professionals were contacted through an online survey to assess their attitudes towards coercion using the Staff Attitude to Coercion Scale (SACS). The three subscales of the SACS (critical, pragmatic and positive attitudes) were analysed in a multivariate multiple linear regression, using a set of covariates including experiences of violence in the workplace. We hypothesised that experience of violence in the workplace would correlate with less critical attitudes of staff members towards coercion. A total of 423 professionals were included in the regression analysis. Age, professional category, feeling of insecurity, having witnessed or used coercion, and the emotional burden associated with coercive measures had a joint significant effect on the three SACS subscales. A feeling of insecurity, but not the experience of violence, was associated with a less critical, more positive appraisal of coercive measures. The emotional burden related to the use of coercion was associated with a more critical attitude. The present results highlight the importance of considering staff members' training and well-being regarding their feelings of insecurity when addressing attitudes towards coercion. The experience of patients should be integrated into staff training and coercion reduction programmes.

Family Integrated Care Shortens the Duration of Home Oxygen Therapy in Infants With Bronchopulmonary Dysplasia.

There have been few reports on whether family integrated care (FIC) can help premature infants with moderate to severe bronchopulmonary dysplasia (BPD) to shorten the duration of home oxygen therapy (HOT). To investigate the effect of FIC on the duration of HOT in premature infants with moderate to severe BPD. The subjects were retrospectively selected from premature infants with moderate to severe BPD in our center between June 2019 and December 2021. Patients were divided into the FIC group (n = 47) and the non-FIC group (n = 34). For univariate analysis, t test, Mann-Whitney U test, Pearson χ 2 test, or Fisher exact test was performed to explore the differences between the 2 groups. For multivariate analysis, simple and multiple linear regression was conducted to explore the effect of FIC on the duration of HOT. (1) The duration of HOT and length of stay after grouping were significantly shorter in the FIC group than in the non-FIC group ( P < .05). (2) The results of linear regression further revealed that FIC could significantly shorten the duration of HOT (simple linear regression, FIC [A] B : -12.709, 95% confidence interval (CI): -21.665 to -3.753; multiple linear regression, FIC [B] B : -11.419, 95% CI: -18.055 to -4.783). FIC improved the optimal target oxygen saturation ratio before discharge and shortened the duration of HOT in premature infants with moderate and severe BPD. FIC should be promoted in China's neonatal intensive care units, though it puts forward new requirements for nursing education and training.

Association between perceived stress and history of intimate partner violence throughout life and during the COVID-19 pandemic.

Intimate Partner Violence (IPV) is a significant public health issue, characterized by being a highly stressful experience for its victims. The relationship between IPV and stress creates a harmful cycle with broad health implications, affecting individuals and society at large. Despite its significance, there's a noticeable lack of research on this topic, especially regarding IPV throughout one's life and during the pandemic. To verify the association between perceived stress and the history of intimate partner violence throughout life and during the COVID-19 pandemic. Analytical cross-sectional epidemiological study with a sample of 1,086 women. Sociodemographic information and violence history, assessed using the World Health Organization Violence Against Women (WHO VAW STUDY), along with perceived stress measured by the short version of the Perceived Stress Scale (PSS), were collected. The sampling process unfolded through multiple stages. For bivariate analyses, the t-test and ANOVA were performed, whereas for multivariate analyses simple and multiple linear regression were performed. The software Stata® version 15.1 and R® were used. Women who reported having suffered intimate partner violence throughout their lives had higher means of stress (18.49), with an average increase of 4 points without adjustments and 3.5 points after adjustments for sociodemographic variables. Similarly, during the COVID-19 pandemic (19.01), stress increased by an average of 3.3 points, which was reduced to 2.8 points after adjustments. The results indicate an association between intimate partner violence and an increase in women's perceived stress, both throughout life and during the pandemic. The importance of preventive approaches, promoting gender equality and preventing IPV from the early stages of life is highlighted. In addition, they underscore the urgency of evidence-based interventions of a comprehensive nature to deal with this complex issue in a careful and effective manner. The cross-sectional nature of this study limits the inference of causality, and an additional limitation is acknowledged concerning information bias. This bias relates to the multifaceted issues surrounding the concept of violence, potentially influencing the accuracy of participants' information and complicating the measurement of violence.

Regression-based sensitivity analysis and multi-objective optimisation of energy performance and thermal comfort: Building envelope design in hot arid urban context

Previous research has established that energy demand of buildings in street canyons are affected by the surrounding urban physical characteristics. This suggests that it is possible to optimise the energy performance of buildings by acting on the physical urban parameters that potentially influence their overall energy consumption. Unfortunately, few studies have addressed this issue. Precisely, improving buildings thermal behaviour and energy demand pattern throughout sensitivity-based optimisation by focusing on the building’s envelope design without neglecting the effect of urban context, remains a relatively under-explored research topic. The present study attempts to fill this gap by implementing a combined method based on sensitivity analysis and multi-objective optimisation of energy demand and thermal comfort for an existing residential building subjected to hot arid climatic conditions. The proposed method utilises Latin hypercube sampling with multivariate multiple linear regression to identify the relative importance of design parameters on building performance criteria, namely, the annual energy demand and the integrated summer thermal discomfort. Non-dominated sorting genetic algorithm II (NSGA-II) is then applied to simultaneously optimise the investigated building performance criteria with regards to the identified relevant envelope parameters. The results of sensitivity analysis indicate that window characteristics, thermal insulation, and roof reflectance are the most influential factors. The optimisation results, in turn, show promising improvement potential with a wide range of design solutions that can ensure better energy performance as well as better thermal comfort. The annual energy demand could be significantly improved by 13.2% up to 49.5% while discomfort degrees could be decreased by over 26%.

A long-term follow-up study of adults with Chiari malformation type I combined with syringomyelia.

There is a considerable amount of controversy regarding the treatment and prognosis of adult patients with Chiari malformation type I (CM-I) at home and abroad; furthermore, no large-sample, long-term, follow-up studies have examined CM-I patients with syringomyelia (SM) comparing posterior fossa decompression with resection of tonsils (PFDRT) vs. posterior fossa decompression with duraplasty (PFDD). This study retrospectively analyzed the factors affecting the treatment and long-term prognosis of adults with CM-I combined with SM. We retrospectively analyzed data from 158 adult CM-I patients combined with SM who underwent PFDRT or PFDD, including 68 patients in group PFDRT and 90 patients in group PFDD. We examined the clinical manifestations, imaging features, and follow-up data of patients. Clinical outcomes were assessed using the Chicago Chiari Outcomes Scale (CCOS), and radiographic outcomes were indicated by the syrinx remission rate. Multivariate logistic regression analysis and multiple linear regression analysis were used to explore the relevant factors affecting the long-term prognosis of patients. This study showed that compared with preoperative patients in the PFDRT group and PFDD group, the sensory impairment, cough-related headache, and movement disorder were significantly improved (p < 0.01); meanwhile, the diameter of the syrinx and the volume of the syrinx decreased significantly (p < 0.001). Additionally, the study found that there were significant differences in the syrinx remission rate (p = 0.032) and the clinical cure rates (p = 0.003) between the two groups. Multivariate logistic regression analysis showed that age (p = 0.021), cerebellar-related symptoms (p = 0.044), preoperative cisterna magna volume (p = 0.043), and peak systolic velocity (p = 0.036) were independent factors for clinical outcomes. Multiple linear regression analysis showed that different surgical procedures were positively correlated with the syrinx remission rate (p = 0.014), while preoperative syrinx diameter (p = 0.018) and age (p = 0.002) were negatively correlated with the syrinx remission rate. In conclusion, this study suggested that, in a long-term follow-up, although both surgical procedures are effective in treating patients with CM-I and SM, PFDRT is better than PFDD; age and cerebellar-related signs independently affect the patient's prognosis. Additionally, an effective prognosis evaluation index can be developed for patients, which is based on imaging characteristics, such as preoperative cisterna magna volume, preoperative syrinx diameter, and preoperative cerebrospinal fluid (CSF) hydrodynamic parameters to guide clinical work.

Service failure monitoring via multivariate multiple linear regression profile schemes with dimensionality reduction

Service failures can be manifested through customer complaints in the form of negative reviews. It is vital for businesses to monitor the occurrence and severity of customer complaints to help balance service failure responses and costs. Existing monitoring schemes can detect complaint anomalies but fail to explain the reasons for these anomalies. We propose new multivariate multiple linear regression profile (MMLRP) based schemes to monitor the relationship between customer complaints and identified explanatory variables. Conventional MMLRP-based schemes suffer performance loss with more than five explanatory variables, and the fixed parameters drawn from a historical process are unsuitable for a changing review-generation process. As such, we apply dimensionality reduction techniques to the explanatory variables and incorporate the variability in new review samples. We use both simulation analysis and an airline service case study to show the effectiveness of our proposed MMLRP-based schemes in customer complaint anomaly detection and diagnosis.

Meld-sarcopenia score and skeletal muscle density predicts short-term readmission of patients with hepatic encephalopathy

PurposeTo investigate whether the quality of skeletal muscle mass could predict short-term readmission in patients with hepatic encephalopathy (HE). MethodPatients with HE were enrolled from 2018 to 2022. Sarcopenia and myosteatosis were defined using the L3 skeletal muscle index (SMI) and skeletal muscle density (SMD) obtained from CT imaging. MELD-Sarcopenia score was calculated. Multivariable analysis and multiple linear regression were applied to identify predictors of 30-day readmission and length of hospitalization. Results123 patients with HE were included. 55 (44.7%) and 87 (70.7%) patients were identified with sarcopenia and myosteatosis, respectively. Patients with sarcopenia exhibited a higher prevalence of myosteatosis, lower SMI and SMD (p < 0.05). Patients with myosteatosis were older, had a lower body mass index, a higher neutrophil-to-lymphocyte ratio and MELD-sarcopenia scores (p < 0.05). 10 (8.1%) patients were readmitted within 30 days. The readmitted group had a higher MELD-sarcopenia score (25.0 ± 6.6 vs. 19.5 ± 7.8, p = 0.034) and lower L3 SMD (28.3 ± 5.9 vs. 33.8 ± 6.9, p = 0.015). In the multivariable analysis, MELD-sarcopenia score (95% CI 1.388 [1.074–1.793], p = 0.012) and SMD (95% CI 0.778 [0.610–0.991], p = 0.042) were found to be significantly associated with the 30-day readmission of patients with HE. Age (p = 0.028), alcohol liver disease (p = 0.025), and hypertension (p = 0.003) were associated with the length of hospitalization for patients with HE. ConclusionsThe MELD-sarcopenia score and SMD were identified as predictive factors for short-term readmission in patients diagnosed as HE.

Health and well-being of serving and ex-serving UK Armed Forces personnel: protocol for the fourth phase of a longitudinal cohort study

IntroductionThis is the fourth phase of a longitudinal cohort study (2022–2023) to investigate the health and well-being of UK serving (Regulars and Reservists) and ex-serving personnel (veterans) who served during...

Does awareness and concern for the environment influence the use of detrimental inputs? A study of maize farmers in Ghana

Sustainable food systems are necessary not only as a channel for addressing the food security needs of the world’s growing population, but are also crucial in ensuring that the needs of future generations are not compromised. This study examined the influence of environmental awareness and concern about the use of detrimental inputs in crop production. The study involved 400 maize farmers from the Northern Region of Ghana, and made use of multivariate multiple linear regression and the translog profit function for the data analysis. The results show that farmers with characteristics including being male, the head of the household, the decision maker on the farm, receiving frequent extension visits and being the owner of the farm, along with the nature of the farm plot, significantly determine the level of farmers’ environmental awareness and concern. Moreover, environmental awareness and concern have a significant effect on the use of detrimental inputs in production. The results contribute to an understanding of the importance of knowledge in facilitating actions towards environmental conservation. Environmental awareness campaigns are thus relevant to the promotion of sustainable agricultural production and should be championed by governments, development agencies and NGOs.

Association between serum 25-hydroxyvitamin D concentrations and hypertension among adults in North Sudan: a community-based cross-sectional study

BackgroundGlobally, hypertension represents a major public health problem. The association between 25-hydroxyvitamin D (25[OH]D) levels and hypertension remains unclear. The current study aimed to investigate the association between serum 25(OH)D levels and hypertension among adults in Sudan.MethodsA community-based cross-sectional study was conducted among adults in North Sudan. Sociodemographic and clinical data were collected using a questionnaire and face-to-face interviews. Serum 25(OH)D was measured using an enzyme-linked immunosorbent assay. Multivariate logistic regression and multiple linear regression analyses were performed.ResultsOf the total of 391 participants, 202 (51.7%) were females. The median (interquartile range [IQR]) of participants’ ages was 45(32–55) years. Of the total, 219(56.0%) had hypertension. The median (IQR) of serum25(OH)D was 13.3(9.9–19.7) ng/mL, and 295 (75.4%) participants had vitamin D deficiency (< 20 ng/mL). In multivariable logistic regression, the adjusted odds ratio (AOR) for age = 1.05, 95% confidence interval (CI)1.03‒1.061, the AOR for being female = 2.02, 95% CI, 1.12‒3.66, and body mass index was AOR = 1.09, 95% CI, 1.05‒1.14, all of which were significantly associated with hypertension. However, serum 25(OH)D levels were not associated with hypertension (AOR = 1.01, 95% CI 0.99‒1.05, P = 0.317). In multiple linear regression, while systolic blood pressure was negatively associated with 25(OH)D (coefficient = − 0.28, P = 0.017), there was no significant association between serum 25(OH)D level and diastolic blood pressure (coefficient = − 0.10, P = 0.272) or mean blood pressure (coefficient =–0.03, P = 0.686).ConclusionThe current study revealed a negative association between vitamin D and systolic blood pressure. The mechanism of such an association needs further study.

Monitoring autocorrelated multivariate multiple linear profiles

AbstractIf the quality of a process can be represented by a functional relationship, a collection of this quality data is called a profile. In monitoring schemes, profile monitoring is used to evaluate the stability of a relationship. In some applications, quality data collected from continuous processes have time correlations and can thus be characterized by a linear relationship between more than one response and explanatory variables. Therefore, we investigate this type of multivariate multiple linear regression model with between‐profile correlations in this study. We propose two exponentially weighted moving average control charts for monitoring the regression parameters and the covariance matrix of the model. Our simulation results reveal that our proposed scheme has satisfactory performance in terms of the average run length and standard deviation run length criteria. Finally, we present an example using real data to demonstrate the applicability of the proposed scheme.

Association of Bedtime with Early-Onset Diabetes and Islet Beta Cell Function in Patients with Newly Diagnosed Type 2 Diabetes Mellitus.

To investigate the association of bedtime with the risk of early-onset diabetes mellitus (DM) and islet beta cell function. 138 participants with treat-naïve DM were included in this study. All participants underwent a 75g oral glucose tolerance test. Sleep habit was obtained through a standardized questionnaire. Bedtime was categorized as < 22:00, 22:00-24:00, and ≥ 24:00 in this study. Multivariate logistic regression and multiple linear regression were used to estimate the association between bedtime and risk of early-onset DM and islet beta cell function, respectively. Patients with early-onset DM had a later bedtime than those with late-onset DM. Individuals with bedtime ≥ 24:00 had a higher prevalence of early-onset DM than those with bedtime at 22:00-24:00 and < 22:00 (51.2% vs 29.3% vs 14.3%, respectively, p = 0.028). The multivariate logistic regression showed that per hour later in bedtime was associated with a 52% increased risk of early-onset DM (p = 0.023). Patients with bedtime after 24:00 had a 146% increased risk of early-onset DM compared to those went to bed between 22:00 to 24:00 (OR = 2.46, 95% CI 1.05 to 5.77, p = 0.039). The multiple linear regression showed that bedtime was independently negatively correlated with late-phase insulin secretion (assessed by disposition index, DI120). Later bedtime was associated with worse late-phase insulin secretion and may be a risk factor for early-onset DM. Proper bedtime to lower risk of early-onset DM deserves further investigation.

Multiple Regression: Methodology and Applications

Multiple regression is one of the most significant forms of regression and has a wide range of applications. The study of the implementation of multiple regression analysis in different settings contributes to the development of relevant theories and the improvement of models. In this paper, four different kinds of regressions are discussed individually by referring to different articles. The four kinds of regressions discussed are multivariable/multiple linear regression, multivariate multiple linear regression, multinomial logistic regression, and multivariate non-linear regression. As for multivariable/multiple linear regression, examples in the manufacturing industry and medical field show that it can be applied in more fields. Multivariate multiple linear regression is more accurate than multivariable/multiple linear regression and can be used with more than a variable. Multinomial logistic regression is relatively mature and accurate, and can help people well solve the problem with non-linearity and multiple independent variables. It does not require the variables to obey a multivariate normal distribution, and is more widely used as well. Multivariate non-linear regression, however, cannot be used properly without powerful professional knowledge. This paper investigates the theoretical development and model applications of multiple regression to demonstrate the flexibility and broadness of the adoption of multiple regression analysis.

A Multivariate Study for Determining the Relationship Between Physical Activity, Physical Fitness, and Academic Performance

The relationship between physical activity, physical fitness, and academic performance has been widely studied internationally. However, reports of this relationship are contradictory, and its impact is still a matter of controversy. For that reason, the current research determined the correlation between these three variables in a group of 56 female and 48 male Colombian students with an average age of 14.08 ± 0.89 years. A quantitative, correlational, and cross-sectional study was carried out. The physical activity was evaluated using PAQ-A questionnaire. For physical fitness, six tests from the Euro fitness battery were used. The academic performance in Spanish, Math, Natural, and Social Sciences were obtained from the grades for the participants at the end of the academic year. Correlations were determined by multivariate multiple linear regression. The obtained results suggest that aerobic endurance test had effect in the studied variables, whereas the correlation of the other tested predictors did not show any meaningful statistical result. In fact, academic performance is not affected by the physical fitness of the students at the time course grades were measured.

Is Presurgical Pain Intensity Related to Postoperative Recurrence of Post-Traumatic Trigeminal Neuropathic Pain?

Post-traumatic trigeminal neuropathic pain (PTTNp) is a challenging condition to treat, and equally as challenging is the identification of surgical outcome variables to guide treatment. The study purpose was to determine if preoperative pain intensity was related to postoperative recurrence of PTTNp. This retrospective cohort study assessed subjects with preoperative PTTNp of either the lingual or inferior alveolar nerves who underwent elective microneurosurgery at a single institution. Two cohorts were established as follows: No PTTNp at 6months (group 1); presence of PTTNp at 6months (group 2). The primary predictor variable was the preoperative visual analog scale (VAS) score. The primary outcome variable was PTTNp (recurrence or no recurrence at 6months). The demographic and injury characteristics of the groups were compared to assess whether they were similar using Wilcoxon rank analysis. Two-tailed Student's t-test was performed to analyze the difference in preoperative mean VAS scores. Multivariate multiple linear regression models were used to determine the association between the covariates on the outcomes of the primary predictor variable and the primary outcome variable. A P value of <.05 was considered statistically significant. Forty-eight patients were included in the final analysis. There were 20 patients with no pain at 6months and 28 with recurrence at 6months following surgery. There was a significant difference in mean preoperative pain intensity between the two groups (P value .04). The mean preoperative VAS score in group 1 was 6.31 (standard deviation, 2.65), while the mean preoperative VAS score in group 2 was 7.75 (standard deviation, 1.95). Regression analysis showed that one covariate, the type of nerve injured, explained some variability of preoperative VAS score, but by only 16% (P value .005). Regression analysis also showed that two covariates, Sunderland classification and time to surgery, explained some of the variability of PTTNp at 6months, by approximately 30% (P value .001). This study showed that presurgical pain intensity level was related to postoperative recurrence in the surgical treatment of PTTNp. In patients with recurrence, the preoperative pain intensity was higher. Other factors, including time interval from injury to surgery, were also related to recurrence.

Association Between Dietary Patterns of Salty Foods, Sweet Drinks, Fruit and Vegetables and The Prevalence of Hypertension in East Java: Multivariate Analysis of Indonesian Basic Health Surveys Data 2018

Hypertension remains the main cause of mortality globally, including in Indonesia, with a prevalence rate of 34.1%. Various studies have reported an association between dietary patterns and the prevalence of hypertension. Therefore, further analysis is needed to determine preventive intervention strategies in each region. This study aimed to analyze the effect of dietary patterns on the prevalence of hypertension in East Java Province. The sample is the result of multistage random sampling from the census block of Basic Health Research (Riskesdas) report in the East Java Province collected from 2013 – 2018. The classical assumption test was carried out using the Kolmogorov-Smirnov method, bivariate test using the Pearson method, and multivariate test using the multiple linear regression method. There are three variables tested that have a p-value below the value of α &lt;0.05, including eating salty foods once a day (p=0.021), drinking sweet drinks three times per month (p=0.008), and non-routine of fruits and vegetables consumption (p=0.003). Based on the r-value, the association between predictor variables and prevalence in order from the largest to the smallest of the habit of not consuming fruits and vegetables (r=-0.469), the habit of drinking sugary drinks three times per month (r=-0.425), and salty eating habits one time per day (r=-0.372). Multivariate multiple linear regression analysis showed that daily intake of salty foods (p=0.013) was associated with the prevalence of hypertension.