Spss version 26.0 for windows

SPSS version 26.0 for Windows (SPSS Inc. Chicago, IL, USA) was used for all statistical analyses. Data are presented as percentages or the means ± standard deviations. Between-group differences in continuous variables were examined using the independent t-test, and between-group differences in categorical variables were examined using the chi-square test. Associations between betel nut chewing and its characteristics with FEV1/FVC < 70% were examined using multivariate logistic regression analysis. Moreover, multivariable linear regression analyses were used to identify associations between betel nut chewing and FEV1/FVC. A p-value < 0.05 was considered to be statistically significant.

SPSS version 26.0 for Windows (SPSS Inc., Armonk, NY, United States) was used to compare the demographics and clinical characteristics. A chi-square test was used to analyze categorical variables, and the Kruskal-Wallis test was used to analyze continuous variables. Spearman’s rank correlation test evaluated the relationship between the two variables. A value of p < 0.05, determined by a two-tailed test, was considered statistically significant. Shannon Index was calculated for analyzing alpha diversity and for the beta diversity function DistanceMatrix from skbio.stats.distance library was utilized using Bray–Curtis dissimilarity. To determine the correlation in a scatterplot, the geom_smooth function with the method = lm and formula = y ~ x option was used to build a linear line, and stat_cor with the “Pearson” method was used to get the r- and value of p.

Statistical analysis was performed using SPSS version 26.0 for Windows (SPSS Inc., Chicago, IL, USA). First, descriptive statistics were calculated to explore and describe the data. Associations between categorical data for signs and symptoms with hair arsenic concentration were then assessed using the chi-square test. Lastly, univariate and multivariate logistic regression analyses were conducted to determine the effect of each risk factor (age, gender, duration of stay, smoking status, study villages and arsenic level in water) on the risk of having high hair arsenic level (more than 1 μg/g) among the respondents. All statistical tests were conducted at a 95% confidence interval, using p = 0.05.

Quantitative data was analysed using SPSS version 26.0 for Windows (SPSS Inc., Chicago, IL, USA). Analysis of the three progression criteria was performed as follows: recruitment rate was calculated by dividing the number of participants assessed eligible and consenting/assenting to participate, with the total number of eligible participants. Retention rate was calculated as total number of treatment completers divided by all potential treatment completers (youth giving consent/assent to participate) and adverse events was calculated by dividing the incidence of reported adverse events by the total number of sessions (x/sessions). All progression criteria analyses are expressed as percentages and confidence intervals and compared to the a-priori cut-off points. The feasibility study is underpowered to detect any treatment effects, so outcomes will be interpreted only as feasibility data. To assess symptom changes between pre-, post-treatment, and 10-month follow-up, Intention to treat (ITT) analyses with paired mean differences and 95% confidence intervals are calculated [28 (link)].

For the statistical analysis, the Statistical Package for the Social Sciences (SPSS) version 26.0 for Windows was used. To make the treatment of the data easier, the main bacteria responsible for UTI were selected, namely E. coli, K. pneumoniae, P. mirabilis, E. faecalis, P. aeruginosa, S. aureus, S. agalactiae, Enterobacter spp., P. vulgaris, S. saprophyticus and Klebsiella oxytoca. These selected bacteria represented 97.4% of all positive urines, while those not selected represented 2.6%. Consequently, from the 15,439 positive samples, 15,025 corresponded to samples contaminated with the selected bacteria (considered in the treatment data) and 414 samples corresponded to samples contaminated with the non-selected bacteria. Descriptive statistics, such as the mean and percentages, were calculated. For the categorical variables, a Chi-square test was used, and the significant level established was <0.05. The binomial test was used for categorial variables with two expressions (female and male), with the significance level established at <0.05.