**3. Results and discussions**

For this work, we used ordinal logistic regression analysis for each of the following response variables:


For this study, the variables were divided into blocks such as: identification of respondents, education, family, and work. For each of these blocks, the models were adjusted considering the variables considered significant were applied:


**Figures 1**–**8** present in item (a) the risk graphs of being a person with one (represented by *p1* in blue dots), two (represented by *p2* in red dots), three (represented by *p3* in green dots), four disabilities (represented by *p4* in purple dots), and at least one disability (represented by *pt* in black dots) and in item b) of being a visually disabled person for each different degrees of severity: "*total blind*" (represented by *p1* in blue dots); "*low vision*" (represented by *p2* in red dots); "*lighter visual*" (represented by *p3* in green dots); and, finally "*visually disability person*" (represented by *pt* in purple dots) for the variables: region in **Figure 1**, sex in **Figure 2**, age in **Figure 3**, race in **Figure 4**, education in **Figure 5**, main job in **Figure 6**, income categorized in **Figure 7**, and number of children in **Figure 8**.

In **Figure 1**, the following regions were considered: 1 – "north," 2 – "northeast," 3 – "southeast," 4 – "south," and 5 – "central west."

Starting from the graphs in **Figure 1** for the region, we see that the highest incidence risks in item a) of disability and in item b) of visual disability are found in the northeast region for all different degrees of disability and all different severity degree. In contrast, the lowest incidence rates in a) number of disabilities are found in the Midwest region and b) the lowest incidence of risk of visual disability is found in the South region.

**Figure 1.**

*Graphs of probability of occurrence: (a) of a certain number of disabilities and (b) of visual disability according to their degrees of severity for variable region.*

#### **Figure 2.**

*Graphs of probability of occurrence: (a) of a certain number of disabilities and (b) of visual disability according to their degrees of severity for variable sex.*

#### **Figure 3.**

*Graphs of probability of occurrence (a) of a certain number of disabilities and (b) of visual disability according to their degrees of severity for age variable.*

#### **Figure 4.**

*Graphs of probability of occurrence (a) of a certain number of disabilities and (b) of visual disability according to their severity degrees for race variable.*

#### **Figure 5.**

*Graphs of probability of occurrence (a) of a certain number of disabilities and (b) of visual disability according to their severity degrees for education.*

**Figure 2** shows (a) the risks of being a disabled person, and (b) the risk of incidence of visually disabled person considering genders 1 – male and 2 – female.

From the graphs in **Figure 2**, it can be seen that in all cases, the highest risk of incidence of: (a) disability and (b) visual disability is higher for females.

On the other hand, **Figure 3** presents the risks of incidence of: (a) disability and (b) visual disability as a function of age.

In **Figure 3**, it is possible to notice that the risks of disability in (a) and visual disability in (b) increase as the age of the people interviewed increases.

**Figure 6.**

*Graphs of probability of occurrence (a) of a certain number of disabilities and (b) of visual disability according to their severity degree for main work.*

#### **Figure 7.**

*Graphs of probability of occurrence (a) of a certain number of disabilities and (b) of visual disability according to their degrees of severity for income.*

#### **Figure 8.**

*Graphs of probability of occurrence (a) of a certain number of disabilities and (b) of visual disability according to their degrees of severity for number of children.*

It is also noted in **Figure 3** that, from a certain age, starting at 80 years old, the points begin to be randomized, and this type of occurrence is believed to be due to a smaller number of people in these older age groups.

Foe the races in **Figure 4**, the races were defined as: 1 – White, 2 – Black, 3 – Yellow, 4 – Brown, and 5 – Indigenous.

As for the results of **Figure 4**, we note that the highest probability of occurrence of disability and visual disability is found in the Yellow race and lower in the Indigenous race.

Next, for **Figure 5**, we considered for education: 1 – "between no education and incomplete elementary," 2 – "between complete elementary and incomplete high school," 3 – "between complete high school and incomplete higher education," and, finally, 4 – "complete higher or more."

Continuing, examining **Figure 5**, we found that the highest occurrence of new cases of risk of disability and risk of visual disability is found in 1, "among no schooling and incomplete elementary school," while the lowest incidence of these risks is found in 3, "between high school complete and incomplete elementary higher education" in all situations.

For the main job in **Figure 6**, we consider the following levels: 1 – "employees with a formal contract," 2 – "military and statutory civil servants," 3 – "employees without a formal contract," 4 – "own account," 5 – "employers," 6 – "unpaid," 7 – "workers in production for their own consumption," and, finally, 8 – "total."

Observing the graphs in **Figure 6** for the type of main job, we see that the highest risk of incidence of disability and visual impairment are found in 6, "workers in production for own consumption" and the lowest risk of incidence in both cases was found in 2, "employees with a formal contract."

Continuing in **Figure 7** with income, we adopted as criterion: 1 – "between 0 and 1 minimum wage," 2 –"between 1 and 3 minimum wages," 3 – "between 3 and 7 minimum wages," 4 – "between 7 and 15 minimum wages," and, finally, 5 – "15 minimum wages or more."

From the results obtained in the graphs in **Figure 7**, we can see that the highest risk of incidence of disability and visual disability was found in 1, "between 0 and 1 minimum wage," and it is noted that this risk decreases as income increases of the person interviewed.

Finally, in **Figure 8**, a scatter plot was made for the risk of incidence of disability and visual disability as a function of the number of children.

As for **Figure 8**, it is possible to verify that the risk of disability and visual impairment increases as the number of children increases.

This result may reflect situations such as: a greater number of children can mean a greater number of accidents and less parental attention to each child in social and economic terms.

**Tables 1**–**5** shows results for the analyses: stereotype ordinal logistic regression; selection criteria for AIC, BIC, and DIC models and for point and interval estimates of the parameters considering as response variable for the adjustments having as a response variable the deficiencies: number of disabilities (**Table 1)**,

visual (**Table 2**), hearing (**Table 3**), physical (**Table 4**), and intellectual (**Table 5**) marked in bold, as well as the explanatory variables included in the final model for each of the adjustments for significant variables according to the backward stepwise method.

For variable number of disabilities, we obtain the following predictor variables as significant as an adjustment for each different block:

*Identification*: domicile, categorized age, birthplace, nationality, and region; *Education*: reading and writing, day care, other graduation, and education; *Family*: union nature, marital status, and number of children; *Work*: income, secondary work, main work, travel, and return time; and finally; Combined model (**Table 1** – made up of all predictor variables considered significant in each of the blocks): region, place of birth, reading and writing, day care, employment status, education, union nature, marital status, number of children, income, return, and main job. For model selection, we get 7232 for AIC, 8791,418 for BIC, and 6917,953 for DIC.

As for visual disability, the following variables were selected: Identification: region, domicile, sex, birthplace, and nationality; Education: reading and writing, day care, other graduation, and education; Family: union nature, marital status, and number of children; Work: income, time, condition, situation, and secondary work, and finally; Combined model (**Table 2**) initialized with all explanatory variables that were
