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Ann Geriatr Med Res > Volume 28(1); 2024 > Article
Gutiérrez, Martínez, and Zuluaga: Edentulism and Individual Factors of Active Aging Framework in Colombia

Abstract

Background

While edentulism remains a serious public health problem for older adults in Colombia, few analyses have been conducted from the framework of active aging as a part of the positive discourse of aging. This study analyzed complete edentulism and its relationship with determinants including personal, behavioral, and health systems and social services.

Methods

This study included a total of 19,004 older adults. We used univariate, bivariate, and multivariate logistic regression type scores to investigate the relationships between the variables. The personal determinants included basic (Barthel scale) and instrumental activities of daily living (Lawton scale), public transportation, functional limitations, self-perceived health, and health problems. The behavioral factors included alcohol and tobacco use, mini nutritional tests, and physical activity. The last determinant was the healthcare system, while social services access included dental services. The analysis also included sociodemographic variables.

Results

The results revealed significant associations for the variables of the three determinants, including the risk of malnutrition (odds ratio [OR]=1.15), functional limitation (OR=1.15), moderate physical activity (OR=1.08), and access to dental services (OR=2.31). Sex, years of education, and race were also risk factors, among other variables. Personal determinants, behavior, and use and access to health services were related to edentulism in older adults.

Conclusion

These findings support the need to include different analyses of edentulism from multicausality and to understand the oral cavity and the living conditions of aging adults.

INTRODUCTION

The human aging process is individual and multidimensional and is characterized by its heterogeneous presentation, intrinsic nature, and irreversible progression. Aging begins at conception, develops throughout life, and ends with death.1) This complex process is accompanied by biological and psychological changes,2) which implies the accumulation of needs, limitations, changes, losses, capacities, and opportunities during an individual’s lifetime.
Active aging is defined as “the process of optimizing opportunities for health, participation, and security to enhance the quality of life as people age.” The active aging model presented by the World Health Organization (WHO)3) encompasses six groups of determinants, each including several features, as follows: (1) availability and use of health and social services (e.g., health promotion and prevention, continuous care); (2) behavioral determinants (e.g., exercise and physical activity, drinking and smoking habits, feeding, medication); (3) personal determinants (biology and genetics, psychological characteristics); (4) physical environment (e.g., safe houses, low pollution levels); and (5) social (e.g., education, social care) and (6) economic (e.g., wage, social security) determinants.4)
Active aging is a theoretical model used to analyze aging processes and develop policies or programs framed within them.5) Three conditions must be met for an active aging process: (1) avoiding illness and disability, (2) maintaining high physical and cognitive functional capacity, and (3) actively engaging in life.6) As aging is a process highly mediated by the social determinants of health, active aging includes variables that explain socioeconomic conditions within its analysis.
Oral health is a part of active aging and is a behavioral determinant; however, few analyses have investigated the relationships between the general determinants of active aging and oral health. One reason for this lack of research could be that active aging is a particularly new concept developed in the 21st century and because geriatric dentistry has not yet developed around the theories of aging, new knowledge and ways of publishing on this topic are needed.7-9) A conceptual framework about oral health and aging was proposed in 2021 and includes teamwork, minimal intervention, oral functionality, and patient-centered care, with maximal tooth preservation being one of the main goals,10) particularly because maintaining oral health and keeping the teeth in the mouth are difficult in old age.11)
One major problem faced by older adults is tooth loss and edentulism, an irreversible condition that can be partial or total, in which individuals lose all of the natural teeth that were present in early life. Edentulism is related to the inability of an older adult to carry out social activities such as talking with peers and participating in support networks.3) It is also associated with many pathologies and adverse general health events such as cancer, cardiovascular disease, and diabetes.12,13) Alcohol, tobacco use, and nutrition are also associated with oral health.14-17) Few studies have evaluated the relationship between the Barthel scale and oral health; however, alterations in dependency could influence the oral health of older adults due to their inability to eat.18) Variables such as ethnicity, sex, socioeconomic income, level of education,19) urban-rural regional location,20) increasing age, social capital, and marital status19) are also significantly associated.
Socioeconomic, biological, and interpersonal relationships such as those described above make edentulism a public health problem that has been described as the “final marker of disease burden for oral health” 21,22) and remains a challenging problem for healthcare providers worldwide. The prevalence of edentulism varies across populations, ranging from 1.3% to 78.0% in patients aged ≥65 years.23) The eight industrialized nations in the world, organized as the G8 (Canada, France, Germany, Italy, Japan, Russia, the United Kingdom, and the United States), show considerable differences in the prevalence of edentulism (16.3, 19, 46, and up to 58% in France, Italy, the UK, and Canada, respectively, with no data available for Russia).24) Colombia has a history of edentulism, and according to the IV National Study of Oral Health in 2014, 32.87% of people aged 65–79 years had total bimaxillary edentulism.25)
The present study aimed to identify the development of various determinants of the framework of active aging; namely, the behavioral, personal, and health systems and social services associated with edentulism in the Colombian population.

MATERIALS AND METHODS

This study analyzed secondary data from the Health, Well-being, and Aging (Salud, Bienestar y Envejecimiento [SABE]) survey carried out in 2016, which comprises 12 chapters, with national and regional representative samples for the population > 60 years of age. The sample design was adapted and adjusted based on the guidelines established by the National System of Studies and Population Surveys in Health of the Ministry of Health. The estimated sample size was 24,553 individuals from 244 municipalities across all departments (Colombian administrative units) and 23,694 older adults.26-28)
Of the total respondents, 4,689 were excluded from the oral section because of cognitive impairment identified by the Mini-Mental State Examination.27,28) This study analyzed data of 19,005 Colombian older adults who responded to questions about oral health conditions. The theoretical framework that was used for the survey recollection process was based on active aging and social determinants.27,28)
The participants signed a written informed consent form and the study was approved by the Ethics Committee of Universidad del Valle (Cod. 09–014, Cod. 008–2014, and Cod. 011–015). At the time of this study, the dataset was completely coded, and no personal information was identifiable. This special analysis was also approved by the committee (Cod. E010-023). Approval from the Ministry of Health and Social Protection was also requested for the analysis. Also, this study complied the ethical guidelines for authorship and publishing in the Annals of Geriatric Medicine and Research.29)

Study Variables

Edentulism was the outcome variable in this study. It was self-reported and analyzed as having or not having teeth (totally edentulous). The sociodemographic factors included area (rural and urban), age, socioeconomic status, sex (male or female), healthcare system (contributive and subsidized), race (light, medium, and dark), years of education (<5 or ≥6), and categorized income (until US $252.6 and More than US $252.6). The values were converted to US dollars at the time of the national survey (2015 exchange rate: 1 USD=2.743 pesos), and the socioeconomic strata were categorized according to the National Administrative Department of Statistics (DANE) as 1–2, 3–4, and 5–6. Age was only used in the univariate and bivariate analyses; it was not included in the multivariate model because as age increased, it was directly related to worse health conditions, both general and oral.
The behavioral factors included alcohol consumption, tobacco use, physical activity, and nutritional status. Alcohol and tobacco consumption were evaluated using direct questions on consumption (yes or no). Tobacco use was categorized as non-smoker, former, or current smoker. Nutritional status was evaluated using the validated version of the Mini Nutritional Assessment Test in Spanish, which includes 19 variables such as body mass index, neuropsychological problems, mobility, daily food intake, circumference, and self-perceived health.14) Accounting for these variables, the scale has three categories: normal (≥24 points), at risk of malnutrition (17–23.5 points), and malnourished (<17 points). Physical activity was measured using two questions regarding vigorous and moderate physical activity, respectively. Each had a dichotomous answer of yes or no.
The personal factors included public transportation use, Barthel scale, self-perceived health, health problems in the last 30 days, Lawton scale, and functional limitations.
Basic activities of daily living were measured using the Barthel scale, which includes several basic domains of functioning, such as urinary and fecal continence and the ability to independently carry out self-care activities such as brushing teeth, going to the toilet, preparing food, moving from one place to another (e.g., moving to a chair), moving around the house, dressing, climbing stairs, and bathing. A Spanish-validated version of the Barthel index was used to generate information.30) For this study, variables were analyzed in dependent and independent older adults.
Functional status was evaluated using the Lawton scale for instrumental activities of daily living (IADL).31) The Lawton scale included in this study evaluates six activities (using the telephone, taking medications, managing finances, preparing meals, shopping, and using transportation), with scores ranging from 0 to 6, with lower scores indicating a lower functional status. Inability is defined as low IADL (≤5).26)
Functional limitations were determined according to the responses to the question: “Do you have difficulty walking five blocks (400 m)?” Two categories—with and without limitations—were created. Self-perceived health was analyzed according to the responses to the question “Would you say that your health in the last 30 days has been ...?” The categories were good–very good, regular, bad, and bad–very bad.32) A question asking if the participant had presented with any health problems in the last 30 days was also used. The last variable included in this group of determinants was the use of public transport, dichotomized as use or non-use.
Health systems and social services were used to indicate access to dental services in the last 12 months. Fig. 1 shows the variables used in this analysis.

Analysis

We performed descriptive analyses by estimating the percentages of all variables. In the bivariate analyses, the chi-squared differences were calculated for the primary outcome (edentulism). Multivariate analysis was also performed, and odds ratios (ORs) with 95% confidence intervals (CIs) and p-values were calculated and compared between established risk factors for edentulism with each group of behavioral and personal variables. In the case of the health system and social services determinants, we estimated the unadjusted effect because the model included only one variable. We performed multivariate logistic regression analysis to analyze the complete set of variables.
Under the framework of logistic regression analysis, models of this type are premised on the presence of symmetry in the resulting variable (edentulism). Asymmetric binary regression models are desirable when the variables do not have adequate symmetry. Table 1 shows that edentulism was present in approximately 28% of the population. Given the asymmetry of this variable, a Scobit-type regression was selected owing to the extreme probabilities; that is, the predominant presence of one of the response variable values and the inadequacy of symmetric regressions.33,34) Statistical significance was set at p<0.05. STATA software version 17 (StataCorp LLC, College Station, TX, USA) was used for all the analyses.
The multivariate model included variables with <10% missing data, except for nutritional screening, which presented a greater loss because it was a construction of variables, and income, which was a sensitive response variable. Model 1 included all determinant and sociodemographic variables. The final model included variables with p-values <0.1, as they were considered important in the consolidation of the definitive model and discussion.
In terms of the multivariate analysis and as a final model, we removed individual variables that were not significant to determine if any important changes in the measures of association could cause noise in the results. To strengthen the discussion, we retained variables with p-values <0.09.

RESULTS

Table 1 shows the results of the bivariate analysis with each of the variables considered in the behavioral, personal, health, and social services system determinants. Public transportation and health problems in the last 30 days did not differ significantly between the groups. The other variables showed significant differences between the groups.

Multivariate Analysis

We performed the multivariate analysis using each of the determinants with the edentulism result variable. The results of these models are shown in Tables 2 and 3.
The behavioral determinants of nutritional status for older adults at risk for malnutrition showed an OR of 1.26, p<0.05, and a confidence interval of risk. This risk did not exist when a person was already malnourished. Not performing vigorous (OR=1.26) or moderate (OR=1.41) physical activity was a risk factor for edentulism, while alcohol consumption and smoking were not. We observed a protective relationship in older adults who were former smokers (OR=0.81; p<0.05).
Analysis of personal determinants showed that the Barthel scale (OR=1.22) and Lawton scale OR=1.13), functional limitations (OR=1.47), and health problems in the last 30 days (OR=0.88) were significantly associated with tooth loss, while public transportation use and self-perceived general health were not. The last group of determinants, a single determinant, health system, and social services, evaluated by access to oral health services, presented a significant relationship, an OR of 2.61 and p<0.05, which was the only significant finding for this group of determinants.
Subsequently, as a part of the multivariate analysis, we included all variables into a new model and adjusted for sociodemographic variables to establish whether the significance remained contrary to the OR where some of the variables changed the risk. Table 4 describes the model with all the variables.
Regarding personal determinants, the Barthel test, Lawton test, health problems in the past 30 days, and functional limitations remained significant. The associations with public transportation use and self-perceived health in the previous 30 days were not statistically significant. Regarding behavioral factors, mini-nutritional tests and moderate physical activity remained significant. Access to dental services also remained a risk factor for edentulism.

DISCUSSION

This is the first study in Colombia to integrate active aging and its relationship with edentulism into the discourse and use quantitative data to explain these relationships. The sociodemographic variables of sex, skin color, and years of education showed statistical significance in the complete model, while area, health regimen, and stratum did not. All determinants included in this analysis showed a relationship between edentulism and some of the included variables.
Some personal determinants demonstrated relationships with edentulism. The Lawton scale of IADL has not been deeply investigated in the oral health; however, previous studies reported a relationship.35) Similarly, few studies have investigated the relationship of the Barthel scale with oral health; among these studies, some results are consistent with the findings of the present study, in which a lower Barthel index score was generally related to poorer oral health conditions, in this case, edentulism.36) This analysis revealed an OR very close to statistical significance for both the Barthel and Lawton scales in the final model and a significant relationship when they acted as independent determinants that were preserved for the Lawton scale after adjusting for sociodemographic variables. Care of the oral cavity is intimately related to the basic activities of daily life; thus, the Lawton and Barthel scales should be included in the analysis of oral health in older adults in the framework of active aging. These findings are consistent with those of the functional limitations variable, which was significant in the independent and final models, meaning that limitations in older adults could impact on oral health, concordant with previous reports.37) The present study contributes to this line of research on basic and instrumental activities and their relationship with the oral cavity. Few such approaches have been described previously.
Health problems in the last 30 days can be analyzed from different perspectives. A person who reports a health problem could need more support from services, which would imply a potential protective effect against edentulism, as a lack of access to dental support is a risk factor for tooth loss.38) The determinants of health system and social services demonstrated that lack of access to dental care increased the possibility of being edentulous by approximately 130%. Access to services is key to avoiding tooth loss.39,40) Use of public transportation and self-perceived health during the past 30 days were not significantly related to edentulism. Despite these findings, interventional approaches related to tooth loss have suggested including the perception of general health based on reported associations and relationships41) and the association of general health with tooth loss.42)
Behavioral factors are also associated with edentulism. In the behavioral factor-exclusive model, former smoking status was significant. Smoking shows a strongly dose-dependent association43); thus, this relationship requires further analysis in future studies. Alcohol consumption at an early age is related to depression, consistent with the findings in the present study. The consolidation of this variable as a constant factor in all the models in this study was striking. In older adults, findings related to alcohol consumption have been controversial,44) with some studies reporting findings comparable to those in the present study.45) Alcohol and tobacco consumption as behavioral factors require further analysis in future studies. Participation in groups and support networks is also important in the aging process; thus, alcohol and tobacco consumption could be accompanied by participation.
Nutritional status is also associated with oral health.13) The findings showed that being at risk of edentulism increased the risk of malnutrition. Therefore, interventions to prevent malnutrition and tooth loss are needed. Vigorous and moderate physical activities are related to lifestyle, and their relationship with edentulism has been reported previously.46) The findings of the present study demonstrated the relationship between a healthy lifestyle and tooth loss. Although vigorous physical activity lost significance in the final model, it remained an independent factor. Moderate activity was significant; therefore this variable should be analyzed in association with edentulism in future studies.
This study has several key findings. Among these was the relationship between the three determinants of active aging and dental loss. The presence of good oral health in older adults can be highlighted in a lot of aspects of daily life, specifically their behavioral and personal determinants and access to health services.
Public policy plays a leading role in preserving dental structures. One of the main goals of the WHO and various dental associations is to retain at least 20 teeth by 80 years of age.47) This is a challenge for Colombian public policy if we continue to treat dentistry separately from geriatrics and gerontology. Innovative concepts and more holistic ways of addressing challenges are required. The complexity framework could be one way to better understand problems in dentistry.48) The findings in this study provide the most robust analysis of edentulism in Colombia. This study also contributes significantly from the perspective of geriatrics and gerontology because the presence and absence of teeth require different analyses in the 21st century. Current oral health problems must be analyzed from a multicausality perspective.10) The information in this study will be useful for subsequent theoretical analyses of aging and for the development of more holistic public policies to preserve teeth. A lower prevalence of edentulism is expected in future generations. Previous approaches involved the development and understanding of problems from the perspective of active aging and actions to improve health outcomes.49)
Active aging is a complex theoretical framework, and the multiple disabilities that become evident due to the interrelation of the various determinants are key to highlighting, in this case, that personal and behavioral determinants and the use and access to health services are related to edentulism in older adults. Based on the findings in the present study, Colombian public policy must recognize the possibility of different public policies and interventions. Dentistry cannot continue to be viewed from an involuted perspective of the oral cavity, and broadening the vision to different scenarios is important.
This study has several limitations that merit discussion regarding their importance in the aging process. The cross-sectional nature of SABE does not allow personal determinants, behavioral determinants, or access to oral healthcare to be established as the cause of the observed tooth loss. While caries and periodontitis are usually considered relevant causes of tooth loss, they were not considered in this study.50) A full oral cavity examination was not feasible during the study; however, complete dental presence or absence was an easily self-reported variable. A major strength of this study is the robustness of its design. The carefully selected and validated indicators, indices, and questions used in the survey, which were applied to a large representative sample of the Colombian population, yielded more consistent findings. More prospective studies on the active aging framework, its relationship to oral health, and its contribution to well-being are needed.
The results of this study promote the development of a holistic interpretation of oral edentulism among older adults. This population should be included in programs aimed at maintaining optimal oral health.

ACKNOWLEDGEMENTS

To the Ministerio de Salud y Protección Social (Colombian Ministry of Health and Welfare) and Colciencias (Colombian Agency of Science, Technology, and Innovation) for financing the Encuesta Nacional de Salud, Bienestar y Envejecimiento-SABE (National Study of Health, Well-being, and Aging; Contract No. 764-2013), the temporary union Universidad del Valle and Universidad de Caldas who made the theoretical conception and the collection of information in the field possible. To Doctor Diana Martinez for her collaboration in the statistical analysis and the Doctor of Public Health of Universidad del Bosque. Finally, to the survey fieldwork staff and all aged persons Colombians who participated in the study.

ACKNOWLEDGMENTS

CONFLICT OF INTEREST

The researchers claim no conflicts of interest.

FUNDING

This study was supported by the Ministerio de Salud y Protección Social (Colombian Ministry of Health and Welfare) and Colciencias (Colombian Agency of Science, Technology, and Innovation) for financing the Encuesta Nacional de Salud, Bienestar y Envejecimiento-SABE (National Study of Health, Well-being, and Aging; Contract No. 764-2013).

AUTHOR CONTRIBUTIONS

Conceptualization, BG, AGM; Data curation, BG; Investigation, BG, AGM, IA; Methodology, BG, AGM, IA; Project administration, BG, AGM, IA; Supervision, BG, AGM, IA; Writing–original draft, BG, AGM, IA; Writing–review & editing, BG,AGM, IA.

Fig. 1.
Variables from active aging framework analyzed with edentulism.
agmr-23-0158f1.jpg
Table 1.
Edentulism and sociodemographic, behavioral, and personal factors and health system and social services
Variable All Edentulism
p-value
Yes No
Sociodemographic factors Age (y) <0.001
 60–64 6,073 (31.66) 1,073 (36.91) 5,000 (19.66)
 65–69 4,946 (26.03) 1,280 (23.45) 3,666 (27.07)
 70–74 3,584 (18.86) 1,210 (22.17) 2,374 (17.53)
 75–79 2,494 (13.12) 930 (17.04) 1,564 (11.55)
 ≥80 1,907 (10.03) 966 (17.70) 941 (6.95)
 Sum 19,004 (100) 5,459 (100) 13,545 (100)
Sex <0.001
 Female 10,660 (56.09) 3,696 (67.70) 6,964 (51.41)
 Male 8,344 (43.91) 1,763 (32.30) 6,581 (48.59)
 Sum 19,004 (100) 5,459 (100) 13,545 (100)
Race (pigmentocracie) <0.001
 Light 9,568 (50.35) 3,128 (57.30) 6,440 (47.55)
 Medium 6,919 (36.41) 1,867 (34.20) 5,052 (37.30)
 Dark 2,517 (13.24) 464 (8.50) 2,053 (15.16)
 Sum 19,004 (100) 5,459 (100) 13,545 (100)
Area <0.001
 Urban 14,040 (73.88) 3,883 (71.13) 10,157 (74.99)
 Rural 4,964 (26.12) 1,576 (28.87) 3,388 (25.01)
 Sum 19,004 (100) 5,459 (100) 13,545 (100)
Socioeconomic stratum <0.001
 1–2 15,251 (80.25) 4,499 (82.41) 10,752 (79.38)
 3–4 3,600 (18.94) 923 (16.91) 2,677 (19.76)
 5–6 153 (0.81) 116 (0.86) 37 (0.68)
 Sum 19,004 (100) 5,459 (100) 13,545 (100)
Healthcare system <0.001
 Contributive 7,844 (41.31) 2,007 (36.77) 5,837 (43.14)
 Subsidized 11,144 (58.69) 3,451 (63.23) 7,693 (56.86)
 Sum 18,988 (100) 5,458 (100) 13,530 (100)
Education years <0.001
 0–5 13,891 (59.99) 4,473 (85.02) 9,418 (73.72)
 6–10 4,145 (22.98) 788 (14.98) 3,357 (26.28)
 Sum 18,036 (100) 5,261 (100) 12,775 (100)
Income (US dollar) <0.001
 ≤252.60 13,248 (82.82) 3,944 (88.75) 9,304 (80.54)
 >252.60 2,248 (19.46) 500 (11.25) 2,748 (17.18)
 Sum 15,996 (100) 4,444 (100) 11,552 (100)
Behavioral factors Alcohol consumption in the last month <0.001
 Yes 2,553 (13.44) 468 (8.58) 2,085 (15.40)
 No 16,439 (86.56) 4,988 (91.42) 11,451 (84.60)
 Sum 18,992 (100) 5,456 (100) 13,536 (100)
Tobacco use <0.001
 Non-smoker 9,133 (48.06) 2,819 (51.64) 6,314 (46.62)
 Former smoker 7,857 (41.35) 2,077 (38.05) 5,780 (42.68)
 Current smoker 2,012 (10.59) 563 (10.31) 1,449 (10.70)
 Sum 19,002 (100) 5,459 (100) 13,543 (100)
Nutritional condition <0.001
 Normal 7,258 (53.82) 1,821 (48.10) 5,437 (56.05)
 Risk of malnutrition 5,868 (43.51) 1,840 (48.60) 4,028 (41.53)
 Malnutrition 360 (2.67) 125 (3.30) 235 (2.42)
 Sum 13,486 (100) 3,786 (100) 9,700 (100)
Physical activity Vigorous <0.001
 Yes 3,961 (20.85) 897 (16.43) 3,064 (22.63)
 No 15,040 (79.15) 4,562 (83.57) 10,478 (77.37)
 Sum 19,001 (100) 5,459 (100) 13,542 (100)
Moderate <0.001
 Yes 9,978 (52.55) 2,388 (43.78) 7,590 (56.09)
 No 9,008 (47.45) 3,067 (56.22) 5,941 (43.91)
 Sum 18,986 (100) 5,455 (100) 13,531 (100)
Personal factors Public transportation use 0.344
 Yes 16,392 (86.26) 4,729 (86.63) 11,663 (86.11)
 No 2,612 (13.74) 730 (13.37) 1,882 (13.89)
 Sum 19,004 (100) 5,459 (100) 13,545 (100)
Barthel scale (basic ADL) <0.001
 Dependent 2,998 (15.78) 1,129 (20.68) 1,869 (13.80)
 Independent 16,006 (84.22) 4,330 (79.32) 11,676 (86.20)
 Sum 19,004 (100) 5,459 (100) 13,545 (100)
Lawton scale (IADL) <0.001
 Low IADL ≤5 (inability) 3,622 (19.06) 1,227 (22.48) 2,395 (17.68)
 Lawton = 6 (no Inability) 15,382 (80.94) 4,232 (77.52) 11,150 (82.32)
 Sum 19,004 (100) 5,459 (100) 13,545 (100)
Functional limitation: walking five blocks <0.001
 With limitation 13,169 (69.35) 2,144 (39.32) 3,677 (27.16)
 Without limitation 5,821 (30.65) 3,309 (60.68) 9,860 (72.84)
 Sum 18,990 (100) 5,453 (100) 13,537 (100)
Self-perceived general health <0.001
 Very good–good 9,119 (48) 2,429 (44.52) 6,690 (49.40)
 Regular 8,265 (43.50) 2,495 (45.73) 5,770 (42.61)
 Bad–very bad 1,650 (8.50) 532 (9.75) 1,083 (8)
 Sum 18,999 (100) 5,456 (100) 13,543 (100)
Health problems in the last 30 days 0.595
 Yes 6,562 (34.55) 1,900 (34.84) 4,662 (34.43)
 No 12,432 (65.45) 3,554 (65.16) 8,878 (65.57)
 Sum 18,994 (100) 5,454 (100) 13,540 (100)
Health system and social services Access to oral health services <0.001
 Yes 3,331 (17.54) 462 (8.46) 2,869 (21.20)
 No 15,659 (82.46) 4,996 (91.54) 10,663 (78.80)
 Sum 18,990 (100) 5,458 (100) 13,532 (100)

Values are presented as number (%).

ADL, activities of daily living; IADL, instrumental activities of daily living.

Chi-squared test was used to calculate significant differences between variables.

Table 2.
Logistic regression model of behavioral determinants (n=13,459)
Variable OR Coefficient (95% CI) p-value
Alcohol consumption
 No 1.0 -
 Yes 0.54 (0.38–0.78) 0.001
Tobacco use
 Non-smoker 1.0 -
 Former smoker 0.81 (0.68–0.96) 0.017
 Current smoker 0.93 (0.82–1.06) 0.332
Mini nutritional test
 Normal 1.0 -
 Risk of malnutrition 1.26 (1.03–1.53) 0.021
 Malnutrition 1.35 (0.95–1.94) 0.092
Physical activity
 Vigorous
  Yes 1.0 -
  No 1.26 (1.04–1.52) 0.016
 Moderate
  Yes 1.0 -
  No 1.41 (1.07–1.85) 0.012

OR, odds ratio; CI, confidence interval.

p-value based on logistic regression analysis. We observed significant relationships between variables for all behavioral determinants analyzed as a single determinant.

Table 3.
Logistic regression model of personal determinants (n=18,976)
Variable OR Coefficient (95% CI) p-value
Public transportation use
 Yes 1.00 -
 No 0.90 (0.82–0.98) 0.026
Barthel scale (basic ADL)
 Independent 1.00 -
 Dependent 1.22 (1.10–1.36) 0.000
Lawton scale (IADL)
 Independent 1.00 -
 Dependent 1.13 (1.05–1.22) 0.001
Functional limitation: walking five blocks
 With limitation 1.00 -
 Without limitation 1.47 (1.28–1.69) 0.000
Self-perceived general health
 Very good–good 1.00 -
 Regular 1.06 (0.99–1.15) 0.076
 Bad–very bad 1.08 (0.96–1.22) 0.174
Health problems in the last 30 days
 Yes 1.00 -
 No 0.88 (0.82–0.95) 0.002

ADL, activities of daily living; IADL, instrumental activities of daily living; OR, odds ratio; CI, confidence interval.

p-value based on logistic regression analysis. We observed significant relationships between variables in all personal determinants analyzed as a single determinant.

Table 4.
Multivariate statistical model of behavioral, personal, and access to health services factors, adjusted for sociodemographic variables, and the final model
Variable Model 1
Model 2 (final model)
OR 95% CI p-value OR 95% CI p-value
Sociodemographic factors Sex
 Male 1.00 - 1.00 -
 Female 1.68 (1.46–1.94) <0.001 1.66 (1.53–1.80) <0.001
Area
 Urban 1.00 - 1.00 -
 Rural 1.06 (0.97–1.16) 0.135 1.06 (0.98–1.16) 0.122
Education years
 ≥6 1.00 - 1.00 -
 0–5 1.52 (1.31–1.77) <0.001 1.52 (1.36–1.70) <0.001
Income (US dollar)
 ≤252.60 1.00 - 1.00 -
 >252.60 1.12 (0.97–1.29) 0.102 1.13 (0.98–1.29) 0.076
Socioeconomic stratum
 5–6 1.00 1.00
 3–4 0.74 (0.46–1.17) 0.206 0.74 (0.47–1.17) 0.204
 1–2 0.71 (0.45–1.13) 0.157 0.72 (0.45–1.13) 0.154
Race (pigmentocracie)
 Light 1.00 - 1.00 -
 Medium 0.74 (0.67–0.83) <0.001 0.75 (0.69–0.81) <0.001
 Dark 0.49 (0.40–0.59) <0.001 0.49 (0.44–0.56) <0.001
Healthcare system
 Contributive 1.00 - 1.00 -
 Subsidized 1.02 (0.97–1.07) 0.300 1.02 (0.97–1.07) 0.309
Behavioral factors Alcohol consumption
 No 1.00 - 1.00 -
 Yes 0.70 (0.60–0.81) <0.001 0.71 (0.62–0.81) <0.001
Tobacco use
 Non-smoker 1.00 - - -
 Former smoker 1.10 (0.92–1.09) 0.916 - -
 Current smoker 1.12 (0.97–1.29) 0.121 - -
Mini nutritional test
 Normal 1.00 - 1.00 -
 Risk of malnutrition 1.15 (1.05–1.27) 0.003 1.15 (1.06–1.24) <0.001
 Malnutrition 1.10 (0.87–1.39) 0.402 1.09 (0.87–1.37) 0.408
Vigorous physical activity
 Yes 1.00 - - -
 No 1.01 (0.91–1.12) 0.750 - -
Moderate physical activity
 Yes 1.00 - 1.00 -
 No 1.08 (1.1–1.18) 0.048 1.08 (1.1–1.18) 0.040
Personal determinants Barthel scale (basic ADL)
 Independent 1.00 - 1.00 -
 Dependent 1.11 (0.99–1.24) 0.072 1.10 (0.98–1.22) 0.07
Lawton scale (IADL)
 Independent 1.00 - 1.00 -
 Dependent 1.11 (1.01–1.23) 0.039 1.10 (0.99–1.21) 0.05
Public transportation use
 Yes 1.00 - - -
 No 0.92 (0.82–1.04) 0.213 - -
Functional limitations
 Without limitations 1.00 - 1.00 -
 With limitations 1.20 (1.08–1.33) 0.001 1.19 (1.09–1.30) <0.001
Health problems in the last 30 days
 No 1.00 - 1.00 -
 Yes 0.88 (0.80–0.97) 0.010 0.87 (0.80–0.95) 0.002
Self-perceived health in the last 30 days
 Very good–good 1.00 - - -
 Regular 1.01 (0.92–1.10) 0.798 - -
 Bad–very bad 0.93 (0.79–1.09) 0.386 - -
Health system and social services Access to dentistry service
 Yes 1.00 - 1.00 -
 No 2.33 (1.93–2.81) <0.001 2.31 (2.02–2.64) <0.001

Model 1, complete model (sociodemographic characteristics, personal determinants, behavioral determinants, and healthcare system and social services); Model 2, final model (sociodemographic characteristics, personal determinants, behavioral determinants, and healthcare system and social services); ADL, activities of daily living; IADL, instrumental activities of daily living; OR, odds ratio; CI, confidence interval.

p-value based on logistic regression analysis. We observed significanWe observed significant relationships for sociodemographic factors, sex, years of education, and race, while socioeconomic stratum, healthcare system, and area did not.

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