Complete dentures associated with frailty among edentulous older Japanese people: A prospective analysis

OBJECTIVE

This study aimed to explore the cross-sectional and prospective associations between self-reported functionality of complete dentures (FCD), satisfaction with complete dentures (SCD) and the ability to chew hard food (ACHF) on the one hand and the frailty index (FI) on the other hand among edentulous community-dwelling older Japanese people.

METHODS

The study examined 770 edentulous participants of the Nihon University Japanese Longitudinal Study of Aging. The self-reported FCD, SCD and ability to chew six groups of food (from hardest to softest) with complete dentures were the independent variables at the baseline. The FI was computed including 40 deficits as the dependent variable at the baseline and 4 years later. Cross-sectional and prospective generalized linear regression models were fitted controlling for age, gender, marital status, education, working status and area of residence.

RESULTS

The use of non-functional complete dentures and dissatisfaction with complete dentures were both associated with a higher FI cross-sectionally (3.9% [95% CI 2.2-5.6] and 3.2% [95% CI 1.5-4.9], respectively) and prospectively (3.9% [95% CI 2.0-6.0] and 3.3% [95% CI 1.3-5.3], respectively). Regarding the ability to chew, a higher FI at baseline was observed among those able to chew food of Group 2 (1.9%, [95% CI 0.1-3.7]) and Groups 4-6 (1.9%, [95% CI 0.1-3.7]), and a progressive increment in the FI, as the participants reported being able to chew softer groups of food at the follow-up (Group 2: 2.2% [95% CI 0.05-4.3]; Group 3: 3.6% [95% CI 1.2-6.0]; and Groups 4-6: 3.4 [95% CI 0.7-6.1]).

CONCLUSION

Self-reported use of non-functional complete dentures, dissatisfaction with dentures and a reduced ACHF with complete dentures were associated with a higher FI both cross-sectionally and prospectively.

Frailty index and ten oral conditions in the Coyoacan cohort study: A cross-sectional analysis

OBJECTIVES

To analyse the relationship between the Frailty Index and 10 oral conditions controlling for nutritional status among Mexican community-dwelling older people.

BACKGROUND

Studies suggest that the association between frailty and oral conditions are mediated by nutrition.

MATERIALS AND METHODS

This cross-sectional analysis includes 487 community-dwelling men and women aged ≥70 years old. Interview and clinical examinations were performed at participants' homes. Objective (number of natural teeth, root remnants, dental condition, utilisation and functionality of removable dental prostheses and periodontitis) and subjective (utilisation of dental services, self-rated oral health, chewing difficulties and xerostomia) oral variables were collected by trained personnel. The Frailty Index was calculated considering 35 deficits. Nutritional status measured with the Mini-Nutritional assessment (MNA), age, sex, education, and marital status were included as covariates. We fitted 11 multivariate generalised linear models (one for each oral condition), assuming gamma distribution for Frailty Index as the outcome.

RESULTS

Participants average age was 78.1 years, 52.1% were women. We observed a higher Frailty Index among those rating their oral health as worse than others their age (5.1%), reporting chewing difficulties often (4.9%) and fairly and very often (7.0%), and xerostomia (4.8%). Age, gender and MNA were consistently associated with the Frailty Index.

CONCLUSION

Subjective oral conditions are compatible with the Frailty Index after controlling for older people's nutritional status and covariates.

Insomnia Impairs Both the Pro-BDNF and the BDNF Levels Similarly to Older Adults with Cognitive Decline: An Exploratory Study

Sleep disorders, including insomnia, are common during aging, and these conditions have been associated with cognitive decline in older adults. Moreover, during the aging process, neurotransmitters, neurohormones, and neurotrophins decrease significantly, leading to the impairment of cognitive functions. In this sense, BDNF, the most abundant neurotrophic factor in the human brain, has been suggested as a potential target for the prevention and improvement of cognitive decline during aging; however, the current evidence demonstrates that the exogenous administration of BDNF does not improve cognitive function. Hence, in the present study, we quantified pro-BDNF (inactive) and BDNF (active) concentrations in serum samples derived from older individuals with insomnia and/or cognitive decline. We used linear regression to analyze whether clinical or sociodemographic variables impacted the levels of BNDF concentration. We observed that insomnia, rather than cognitive decline, is significantly associated with BDNF concentration, and these effects are independent of other variables. To our knowledge, this is the first study that points to the impact of insomnia on improving the levels of BDNF during aging and suggests that opportune treatment of insomnia may be more beneficial to prevent cognitive decline during aging.

Association of loneliness and social isolation with all-cause mortality among older Mexican adults in the Mexican health and aging study: a retrospective observational study

BACKGROUND

Plenty of evidence shows how social isolation and loneliness are associated with increased risk for numerous diseases and mortality. But findings about their interactive or combined effects on health outcomes and mortality remains inconclusive.

OBJECTIVE

Analyze the longitudinal association of loneliness, social isolation and their interactions, with the all-cause mortality among older adults in Mexico.

METHODS

A retrospective observational study was conducted. Mexican adults older than 50 years were included. Data from the Mexican Health and Aging Study (MHAS) in the 2015 and 2018 waves were used. The subjects were classified according to their level of loneliness and the presence of social isolation. Multivariate logistic regression analyzes were performed to determine the degree of association between loneliness and social isolation with all-cause mortality at a 3-year follow-up.

RESULTS

From the total sample of 11,713 adults aged 50 years or over, 707 (6%) did not survive, 42% presented loneliness, and 53% were classified as socially isolated. After multivariate adjustment only social isolation (OR = 1.30, 95%CI:1.03-1.64) was associated with all-cause mortality, loneliness (Mild: OR = 0.83, 95%CI:0.59-1.16; Severe: OR = 1.03, 95%CI:0.71-1.64), and the interaction between loneliness and social isolation were not associated with all-cause mortality.

CONCLUSION

Social isolation, but not loneliness or their interaction, was associated with all-cause mortality in Mexican adults older than 50 years. This finding may help direct possible future interventions that help improve mental health in older adults from a highly collectivistic country.

Widowhood Status and Cognitive Function in Community-Dwelling Older Adults from the Mexican Health and Aging Study (MHAS)

We aimed to determine the association between the duration of widowhood and cognition decline. We compared the decline observed in widowed people compared with married, single, or separated persons using the scores obtained in the cognitive assessment of memory, learning, and visual exploration by adults and older adults in Mexico. The Mexican Health and Aging Study (MHAS) provides the base for this paper. This study is an analysis of the fourth data wave (2015), except for the independent variable: marital status. Marital status was built longitudinally with information from the four surveys (2001, 2003, 2012, and 2015). The sample comprised 6898 adults aged 50 and over. Cognition was assessed with an adapted Cross-Cultural Cognitive Examination (CCCE). Confounders include sociodemographic characteristics (sex, age, schooling, self-perception of economic status, and whether the individual worked or not), multimorbidity, functionality, support networks, and psychological characteristics. Of the total sample, 4094 (59.3%) were women. The mean age was 70.86 years (SD = 7.4). The baseline of the study is 2001. In 2001, 8.7% (n = 600) were widows or widowers. People widowed by 2001 scored -0.158 points in cognition while divorced participants scored - 0.095 points.

Structural and Pharmacological Network Analysis of miRNAs Involved in Acute Ischemic Stroke: A Systematic Review

Acute ischemic stroke (AIS) is among the main causes of mortality worldwide. A rapid and opportune diagnosis is crucial to improve a patient’s outcomes; despite the current advanced image technologies for diagnosis, their implementation is challenging. MicroRNAs have been recognized as useful as biomarkers since they are specific and stable for characterization of AIS. However, there is still a lack of consensus over the primary miRNAs implicated in AIS. Here, we performed a systematic review of the literature covering from 2015–2021 regarding miRNAs expression during AIS and built structural networks to analyze and identify the most common miRNAs expressed during AIS and shared pathways, genes, and compounds that seem to influence their expression. We identified two sets of miRNAs: on one side, a set that was independent of geographical location and tissue (miR-124, miR-107, miR-221, miR-223, miR-140, miR-151a, miR-181a, miR-320b, and miR-484); and on the other side, a set that was connected (hubs) in biological networks (miR-27b-3p, miR-26b-5p, miR-124-3p, miR-570-3p, miR-19a-3p, miR-101-3p and miR-25-3p), which altered FOXO3, FOXO4, and EP300 genes. Interestingly, such genes are involved in cell death, FOXO-mediated transcription, and brain-derived neurotrophic factor signaling pathways. Finally, our pharmacological network analysis depicted a set of toxicants and drugs related to AIS for the first time.

Spatial epidemiological study of the distribution, clustering, and risk factors associated with early COVID-19 mortality in Mexico

COVID-19 is a respiratory disease caused by SARS-CoV-2, which has significantly impacted economic and public healthcare systems worldwide. SARS-CoV-2 is highly lethal in older adults (>65 years old) and in cases with underlying medical conditions, including chronic respiratory diseases, immunosuppression, and cardio-metabolic diseases, including severe obesity, diabetes, and hypertension. The course of the COVID-19 pandemic in Mexico has led to many fatal cases in younger patients attributable to cardio-metabolic conditions. Thus, in the present study, we aimed to perform an early spatial epidemiological analysis for the COVID-19 outbreak in Mexico. Firstly, to evaluate how mortality risk from COVID-19 among tested individuals (MRt) is geographically distributed and secondly, to analyze the association of spatial predictors of MRt across different states in Mexico, controlling for the severity of the disease. Among health-related variables, diabetes and obesity were positively associated with COVID-19 fatality. When analyzing Mexico as a whole, we identified that both the percentages of external and internal migration had positive associations with early COVID-19 mortality risk with external migration having the second-highest positive association. As an indirect measure of urbanicity, population density, and overcrowding in households, the physicians-to-population ratio has the highest positive association with MRt. In contrast, the percentage of individuals in the age group between 10 to 39 years had a negative association with MRt. Geographically, Quintana Roo, Baja California, Chihuahua, and Tabasco (until April 2020) had higher MRt and standardized mortality ratios, suggesting that risks in these states were above what was nationally expected. Additionally, the strength of the association between some spatial predictors and the COVID-19 fatality risk varied by zone.

Transiciones de la discapacidad según afiliación a instituciones de salud en adultos mayores en México

Objetivo. Estudiar las transiciones de la discapacidad de acuerdo con la afiliación a servicios de salud en adultos mayores de 50 años en México, así como el conjunto de variables socioeconómicas y de salud asociadas. Material y métodos. La información proviene de la Encuesta Nacional de Salud y Envejecimiento en México (Enasem-encuesta). Se ajustaron 20 modelos de regresión para las transiciones de la discapacidad medida a través de actividades básicas de la vida diaria en el periodo 2012-15, usando variables socioe-conómicas y de salud. Resultados. Los afiliados al Seguro Popular tuvieron la mayor frecuencia de transición hacia la discapacidad con 13.26%. La afiliación a instituciones de sa-lud no tuvo relación con ninguna de las cuatro transiciones estudiadas. Las enfermedades asociadas con el desarrollo de discapacidad varían de acuerdo con la afiliación. Conclu-siones. Los factores socioeconómicos y de salud asociados con las transiciones de la discapacidad son diferentes entre afiliaciones.

Random intercept and linear mixed models including heteroscedasticity in a logarithmic scale: Correction terms and prediction in the original scale

Random intercept models are linear mixed models (LMM) including error and intercept random effects. Sometimes heteroscedasticity is included and the response variable is transformed into a logarithmic scale, while inference is required in the original scale; thus, the response variable has a log-normal distribution. Hence, correction terms should be included to predict the response in the original scale. These terms multiply the exponentiated predicted response variable, which subestimates the real values. We derive the correction terms, simulations and real data about the income of elderly are presented to show the importance of using them to obtain more accurate predictions. Generalizations for any LMM are also presented.

Spatial analysis of COVID-19 spread in Iran: Insights into geographical and structural transmission determinants at a province level

The Islamic Republic of Iran reported its first COVID-19 cases by 19th February 2020, since then it has become one of the most affected countries, with more than 73,000 cases and 4,585 deaths to this date. Spatial modeling could be used to approach an understanding of structural and sociodemographic factors that have impacted COVID-19 spread at a province-level in Iran. Therefore, in the present paper, we developed a spatial statistical approach to describe how COVID-19 cases are spatially distributed and to identify significant spatial clusters of cases and how socioeconomic and climatic features of Iranian provinces might predict the number of cases. The analyses are applied to cumulative cases of the disease from February 19th to March 18th. They correspond to obtaining maps associated with quartiles for rates of COVID-19 cases smoothed through a Bayesian technique and relative risks, the calculation of global (Moran's I) and local indicators of spatial autocorrelation (LISA), both univariate and bivariate, to derive significant clustering, and the fit of a multivariate spatial lag model considering a set of variables potentially affecting the presence of the disease. We identified a cluster of provinces with significantly higher rates of COVID-19 cases around Tehran (p-value< 0.05), indicating that the COVID-19 spread within Iran was spatially correlated. Urbanized, highly connected provinces with older population structures and higher average temperatures were the most susceptible to present a higher number of COVID-19 cases (p-value < 0.05). Interestingly, literacy is a factor that is associated with a decrease in the number of cases (p-value < 0.05), which might be directly related to health literacy and compliance with public health measures. These features indicate that social distancing, protecting older adults, and vulnerable populations, as well as promoting health literacy, might be useful to reduce SARS-CoV-2 spread in Iran. One limitation of our analysis is that the most updated information we found concerning socioeconomic and climatic features is not for 2020, or even for a same year, so that the obtained associations should be interpreted with caution. Our approach could be applied to model COVID-19 outbreaks in other countries with similar characteristics or in case of an upturn in COVID-19 within Iran.

Spatial analysis of COVID-19 spread in Iran: Insights into geographical and structural transmission determinants at a province level

The Islamic Republic of Iran reported its first COVID-19 cases by 19th February 2020, since then it has become one of the most affected countries, with more than 73,000 cases and 4,585 deaths to this date. Spatial modeling could be used to approach an understanding of structural and sociodemographic factors that have impacted COVID-19 spread at a province-level in Iran. Therefore, in the present paper, we developed a spatial statistical approach to describe how COVID-19 cases are spatially distributed and to identify significant spatial clusters of cases and how socioeconomic and climatic features of Iranian provinces might predict the number of cases. The analyses are applied to cumulative cases of the disease from February 19th to March 18th. They correspond to obtaining maps associated with quartiles for rates of COVID-19 cases smoothed through a Bayesian technique and relative risks, the calculation of global (Moran's I) and local indicators of spatial autocorrelation (LISA), both univariate and bivariate, to derive significant clustering, and the fit of a multivariate spatial lag model considering a set of variables potentially affecting the presence of the disease. We identified a cluster of provinces with significantly higher rates of COVID-19 cases around Tehran (p-value< 0.05), indicating that the COVID-19 spread within Iran was spatially correlated. Urbanized, highly connected provinces with older population structures and higher average temperatures were the most susceptible to present a higher number of COVID-19 cases (p-value < 0.05). Interestingly, literacy is a factor that is associated with a decrease in the number of cases (p-value < 0.05), which might be directly related to health literacy and compliance with public health measures. These features indicate that social distancing, protecting older adults, and vulnerable populations, as well as promoting health literacy, might be useful to reduce SARS-CoV-2 spread in Iran. One limitation of our analysis is that the most updated information we found concerning socioeconomic and climatic features is not for 2020, or even for a same year, so that the obtained associations should be interpreted with caution. Our approach could be applied to model COVID-19 outbreaks in other countries with similar characteristics or in case of an upturn in COVID-19 within Iran.

A NETWORK ANALYSIS OF FRAILTY USING DATA FROM THE MEXICAN HEALTH AND AGING STUDY

Frailty remains a challenge in the aging research area with a number of gaps in knowledge still to be filled. New approaches to its study have been proposed, including the one discussed in this article. We tested frailty as through the use of graphical probabilistic models (bayesian networks) with empirical data. Data from the Mexican Health and Aging Study (main data 2012, mortality 2015) was used. Frailty was operationalized with a 35-deficit frailty index (FI). Analyzed nodes were the deficits, plus death and the total score of the FI. The edges, or ties, linking those nodes (set E) were obtained through structural learning, and an undirected discrete graph G (V, E) associated with a discrete graphical probabilistic model (Markov network) was derived. Structural learning was possible through hill-climbing (hc) and PC algorithms. Analyses were performed for the whole population and tertiles of the total FI score. The number of connections within nodes increased according to the tertile level of the total FI score. Groups of interconnected deficits increased as the FI score raised. Almost all deficits related to mobility were interconnected and death was not the most connected node. Frailty behaves as a nonlinear system under the looks of a complex network. Further research should aim to identify the nature of the interactions observed. This could contribute to the development of a conceptual framework that would allow specific interventions to mitigate the consequences of frailty in older adults to be developed.

HETEROGENEITY IN MULTIDIMENSIONAL DEPENDENCY IN OLDER ADULTS IN MEXICO: A LATENT CLASS ANALYSIS APPROACH

Background: The number of older adults expected to increase over the coming decades, the public health impact in this population may be substantial, and a greater understanding of the structure underlying risk factor presentation as a potential source of heterogeneity is critical. Objective: Identify and characterize profiles of dependency status in a population of dependent elderly individuals. Methods: The present study is based on the first wave of the Mexican Health Aging Study (MHAS). We included subjects aged 50 or older (n = 13,463 respondents interviewed in 2001). We performed Latent Class Analysis on four domains in older adults’ indicators (physical, psychological, economic and social) to identify distinct classes of dependency profiles. We used LCA to group individuals into homogenous categories of dependency based on observed domains of multidimensional dependency. Multivariable logistic regression was conducted to examine the sociodemographic characteristics associated with each profile. Results: A 4-class solution based on cognitive performance at baseline was the best-fitting model. We characterized the four distinct classes of dependency profiles: active older adult, low, moderate and severe dependency that encompassed multiple dimensions of dependence. Using the “active older adult” class as the reference group, severe dependency, low dependency, and moderate dependency class were more likely to contain females, low education level and poor quality of life 3) the moderate dependency class was less likely to contain cigarette smoking and alcohol user. Conclusions: This study suggests that dependency do not follow a uniform adjustment pattern during the aging process, which reconciles inconsistent previous findings.

Impact of social disadvantages in the presence of diabetes at old age

Background

Social disadvantages that start during childhood and continue into the later stages in life may be linked to the presence of diabetes during adulthood. Objective. To analyze whether the presence of social disadvantages in childhood and in the present affects the presence of diabetes in older adults.

Methods

The present study was based on longitudinal data from the third and fourth Mexican Health and Aging Study (MHAS) waves (2012 and 2015). Data on diabetes diagnosis, past (e.g. “no shoes during childhood”) and present (e.g. self-perception of economic status) social disparities, and other covariables were analyzed.

Results

From 8,848 older adults, 21.5% (n = 1903) were classified as prevalent cases (PG), 5.2% (n = 459) as incident cases (IG) and 77.4% (n = 6,486) were free of disease (NDG). The predictor variable “no shoes during childhood” was statistically significant in the model incident versus no diabetes group. Hypertension and body mass index (BMI) were the most relevant covariates as they were statistically significant in the three groups (PG, IG and NDG).

Conclusions

Not having shoes during childhood, an indicator of social disadvantages, is associated with the incidence and prevalence of diabetes in older adults. This suggests that social disadvantages can be a determinant for the presence of chronic diseases in adulthood.

Systems biology and network pharmacology of frailty reveal novel epigenetic targets and mechanisms

Frailty is an age-associated condition, characterized by an inappropriate response to stress that results in a higher frequency of adverse outcomes (e.g., mortality, institutionalization and disability). Some light has been shed over its genetic background, but this is still a matter of debate. In the present study, we used network biology to analyze the interactome of frailty-related genes at different levels to relate them with pathways, clinical deficits and drugs with potential therapeutic implications. Significant pathways involved in frailty: apoptosis, proteolysis, muscle proliferation, and inflammation; genes as FN1, APP, CREBBP, EGFR playing a role as hubs and bottlenecks in the interactome network and epigenetic factors as HIST1H3 cluster and miR200 family were also involved. When connecting clinical deficits and genes, we identified five clusters that give insights into the biology of frailty: cancer, glucocorticoid receptor, TNF-α, myostatin, angiotensin converter enzyme, ApoE, interleukine-12 and −18. Finally, when performing network pharmacology analysis of the target nodes, some compounds were identified as potentially therapeutic (e.g., epigallocatechin gallate and antirheumatic agents); while some other substances appeared to be toxicants that may be involved in the development of this condition.

Mortality and associated risk factors for older adults admitted to the emergency department: a hospital cohort

Background

Older emergency department patients are more vulnerable than younger patients, yet many risk factors that contribute to the mortality of older patients remain unclear and under investigation. This study endeavored to determine mortality and factors associated with mortality in patients over 60 years of age who were admitted to the emergency departments of two general hospitals in Mexico City.

Methods

This is a hospital cohort study involving adults over 60 years of age admitted to the emergency department and who are beneficiaries of the Mexican Institute of Social Security and residents of Mexico City.

All causes of mortality from the time of emergency department admission until a follow-up home visit after discharge were measured. Included risk factors were: socio-demographic, health-care related, mental and physical variables, and in-hospital care-related. Survival functions were estimated using Kaplan-Meier curves. Hazard ratios (HR) were derived from Cox regression models in a multivariate analysis.

Results

From the 1406 older adults who participated in this study, 306 (21.8%) did not survive. Independent mortality risk factors found in the last Cox model were age (HR = 1.02, 95% CI, 1.005–1.04; p = 0.01), length of stay in the ED (HR = 1.003, 95% CI = 0.99, 1.04; p = 0.006), geriatric care trained residents model in Hospital A (protective factor) (HR = 0.66, 95% CI = 0.46, 0.96; p = 0.031), and the FRAIL scale (HR of 1.34 95% CI, 1.02–1.76; p = 0.033).

Conclusions

Risk factors for mortality in patients treated at Mexican emergency departments are length of stay and variables related to frailty status.

[Cost of hospitalizations for older adults at one IMSS regional general hospital]

BACKGROUND

Population aging has a direct impact on the increasing demand of health services and on medical care costs. The objective was to carry out a cost analysis of health care costs in older adults in a regional general hospital of the Instituto Mexicano del Seguro Social.

METHODS

A calculation of the costs was done based on a retrospective collection of health care data. Unit prices were used to estimate costs. These were reported in 2016 Mexican pesos. A cost analysis was carried out by means of a regression model. Explanatory variables were sex, age and comorbidity level, the latter measured by using the Charlson index.

RESULTS

The average cost of all the 509 patients was 34 769 Mexican pesos (SD = 2869 pesos). Age variable explains the costs; however, sex and comorbidity variables were not significant. Cost predictions with the statistical model show differences mainly by age. In the case of females, the model predicts greater costs compared with those of males. Costs for older adults of 85 years or more were greater than those for the group of younger people (75-84).

CONCLUSION

The hospitalization costs estimated are high and they differ according to the age group. We suggest to make further research in order to know the factors associated with high hospital costs for this age group.

Restricted graphical log-linear models

We introduce a new type of graphical log-linear model called restricted graphical log-linear model. This model is obtained by imposing equality restrictions on subsets of main effects and of first-order interactions. These restrictions are obtained through partitions of the variable and first-order interaction sets. The vertices or variables in the same class have the same main effects in all their categories and the first-order interactions in the same class are equal. We study its properties and derive its associated likelihood equations and give some applications. A graphical representation is possible through a coloured graph.

Late-life depressive symptoms: prediction models of change

BACKGROUND

Depression is a well-recognised problem in the elderly. The aim of this study was to determine the factors associated with predictors of change in depressive symptoms, both in subjects with and without baseline significant depressive symptoms.

METHODS

Longitudinal study of community-dwelling elderly people (>60 years or older), baseline evaluations, and two additional evaluations were reported. Depressive symptoms were measured using a 30-item geriatric depression scale, and a score of 11 was used as cut-off point for significant depressive symptoms in order to stratify the analyses in two groups: with significant depressive symptoms and without significant depressive symptoms. Sociodemographic data, social support, anxiety, cognition, positive affect, control locus, activities of daily living, recent traumatic life events, physical activity, comorbidities, and quality of life were evaluated. Multi-level generalised estimating equation model was used to assess the impact on the trajectory of depressive symptoms.

RESULTS

A number of 7882 subjects were assessed, with 29.42% attrition. At baseline assessment, mean age was 70.96 years, 61.15% were women. Trajectories of depressive symptoms had a decreasing trend. Stronger associations in those with significant depressive symptoms, were social support (OR.971, p<.001), chronic pain (OR 2.277, p<.001) and higher locus of control (OR.581, p<.001). In contrast for those without baseline significant depressive symptoms anxiety and a higher locus of control were the strongest associations.

CONCLUSIONS

New insights into late-life depression are provided, with special emphasis in differentiated factors influencing the trajectory when stratifying regarding basal status of significant depressive symptoms.

LIMITATIONS

The study has not included clinical evaluations and nutritional assessments.