Stata software version 12

The data was entered into Access 2010 and analyzed using STATA software, version 12 (Stata Corp., TX USA). A descriptive analysis was carried out for the urban and rural areas in order to describe the outcomes of the consumption of treatments (HM and PM). Household characteristics and socio-demographic characteristics of the questionnaire respondents were also described. The associations between the socio-demographic characteristics of the household and the outcomes were tested using a logistic regression model and the top-down step-by-step procedure. The Chi-square or Fisher test, as appropriate, was used to measure the association between two variables. The strength of the associations was estimated using the Odds Ratio (OR) with an estimated 95% confidence interval (CI). The differences were considered statistically significant when the p-value was < 5%. The multiple logistic regression analysis was done only for the urban area. Indeed, in the rural area, population and lifestyles (wealth index) are more homogenous than in the city.

Continuous variables were described as mean and standard deviation and categorical variables as percentages. Differences between groups were based on the t-test or chi-square, as appropriate. Cumulative incidence and 95% confidence intervals (CI) for RHOA were also calculated for a 11-year follow-up period.
Logistic regression models were used to evaluate the association between lipid serum profile and incidence of RHOA at Y11. Lipid serum profile was considered as both a continuous and categorical set of variables to evaluate the effect of a potential dose-response relationship with RHOA. Three different models were built to explore this association: Model 1 was non-adjusted, Model 2 was age-adjusted, and Model 3 added the potential confounders that were epidemiologically relevant or statistically significant in the bivariate analysis. Log-rank test was used to contrast the dose-response relationship within serum lipid profile categories.
We used STATA software (version 12) for all the analysis, with two-sided tests. P-values < 0.05 were considered statistically significant.
The study was approved by the Outer North East London Research Ethic Committee and conducted according the rules of good research practices of the Declaration of Helsinki. Each study participant provided written informed consent before participating.

Stata software version 12 (StataCorp LP, College Station, TX, USA) was used for all statistical analyses. Descriptive statistics were used for the characteristics of participants; continuous variables were reported as means with standard deviations and categorical variables as frequencies and percentages. A carry-over effect was tested by comparing the difference between the participants' response to VCO and 2% CMC solution (control) at week 8 with the difference between the participants' response to VCO and control at week 24 using a two-sample t-test. A treatment effect of VCO was tested using a paired t-test to compare the mean difference in change in plasma lipoproteins levels between VCO and 2% CMC solution (control). A p < 0.05 was deemed statistically significant for all analyses.

NS supplementation and control group will be pooled and evaluated for the mean differences and standard deviations (SDs) of the following outcomes: (i) MDA, (ii) SOD, and (iii) TAC. The fixed-effect model is used to estimate the overall effect size for homogeneous data. The random-effect model is used to estimate the overall effect size for heterogeneous data. Heterogeneity was examined using Cochrane's Q test (significance point at p < 0.05). The risk of bias in reporting the cumulative incidence was independently calculated by the authors. The publication bias of each study was assessed through funnel Egger's test [19 (link)]. All statistical analyses were done using Stata software version 12 (StataCorp, College Station, Texas, USA). p < 0.05 was considered as statistically significant.