2.1 Study design

This is a subset of the project entitled "Association between low level of social support and telomere length in older adults” [35]. It is a quantitative study with an analytical cross-sectional design. The structure of the present study followed the guidelines of the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) initiative [36].

2.2 Settings

The study was conducted in the municipality of Alfenas, located in the southern region of the state of Minas Gerais, Brazil. According to projections from the Brazilian Institute of Geography and Statistics (IBGE), the population of Alfenas in 2019 was 79,996 inhabitants. At the time of sample calculation, the latest available age-specific population projection was provided by the Interagency Network for Health Information (RIPSA) for the year 2015, which indicated a population of 78,713 inhabitants, with 10,797 being older adults (Instituto Brasileiro de Geografia e Estatística, 2020).

2.3 Participants

The study population consisted of community-dwelling older individuals aged 60 years and older, residing in the urban area of the municipality of Alfenas (in 2019). The sample size calculation was obtained considering the estimation of proportions around 50%, a 95% confidence interval, a design effect of 1.17, and a population of 10,797 older people, resulting in a sample of 435 individuals. The final sample size (n = 448) is depicted in Fig 1 and considered the addition of extra individuals to compensate for potential losses.

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Fig 1. Flowchart of participants recruitment.

https://doi.org/10.1371/journal.pone.0308612.g001

2.4 Sample selection criteria

The inclusion criteria were being 60 years of age or older and having the ability to respond to the questionnaire (as perceived by the interviewer during the presentation of the research and invitation to participate). The exclusion criterion was having permanent or temporary incapacity to walk, except with the use of a walking aid device.

2.5 Data collection procedures

The participants were recruited from selected households to ensure that individuals from all regions of the municipality were included. The sampling process used as a basis was the complementation of the sample conducted in the SABE Study, a population-based survey conducted in the city of São Paulo. The interviewers were distributed in different regions of the city according to the proximity to their place of residence. After locating a household with a resident aged 60 years or older, they proceeded to locate nearby households, or at most, within the boundaries of the neighborhood to which the initial address belonged [37].

Data was collected between July and December 2019 in two phases. In the first phase, interviews and physical-functional assessments were conducted. A comprehensive survey was developed, including questions from the following sections: a) sociodemographic characteristics; mental wellbeing and social support; c) general health status; d) functionality, sarcopenia, frailty, and falls; nutritional status; f) physical assessment. In the second phase, fasting blood samples were collected. The interviews took place at the older person’s residence, while the blood sample collection was performed at the Central Laboratory of Clinical Analysis (LACEN) of the Federal University of Alfenas (UNIFAL-MG) or at the older person’s residence for a registered nursing.

2.6 Ethics

This study was submitted to the Research Ethics Committee of the Federal University of Alfenas and received approval under CAAE: 5218518.0.0000.5142 [No. 2.668.936]. Older adults were included in the study after providing informed consent by signing the informed consent form. All procedures were conducted in accordance with the ethical standards outlined in the Declaration of Helsinki [38], and following the ethical precepts recommended by Resolution 466/12 of the National Health Council for experiments involving humans [39].

3.1 Telomere length assessment

Initially, a sample of whole blood was obtained in tubes containing EDTA and transported in a polystyrene box with reusable ice to the Clinical Parasitology Laboratory of the Federal University of Alfenas. The blood samples were processed using the basic DNA extraction protocol with affinity columns. After adding a saline phosphate buffer (pH 7.2) and centrifuging at 2.000 rpm for 5 minutes, the supernatant was discarded. The remaining precipitate was treated with an erythrocyte lysis buffer (ACK) until complete hemolysis. The material was centrifuged again (2,000 rpm for 5 minutes), and the supernatant was discarded. The remaining precipitate was treated with a specific buffer from the extraction kit (PureLink™ Genomic DNA Mini Kit, Invitrogen) and incubated in a water bath at 56°C. The DNA extraction was performed according to the manufacturer’s recommendations, cited um previous analogous researchers [40]. The DNA concentration was determined using a Genova Nano spectrophotometer (Jenway), and the concentration was adjusted to 10ng/μl in the samples, which were then stored at -20°C until the PCR (Polymerase Chain Reaction) reactions were performed [41].

Real-time PCR reactions were conducted using Power SYBR Green PCR Master Mix as the fluorescent marker in an ABI StepOne Real-Time PCR System (Applied Biosystems), with a final volume of 10μL per reaction. A volume of 1μL of DNA (samples or controls) was added to a mix containing 5 μL of 2X Power SYBR® Green Master Mix, 1μL of a mixture including the forward and reverse primers (concentration of 10μM), and 3μL of ultrapure water, free of DNAse and RNAse. Negative and positive controls were included in the reactions. The amplifications for telomere markers consisted of an initial cycle at 95°C for 10 minutes, followed by 26 cycles at 95°C for 15 seconds, 57°C for 30 seconds, and 60°C for two minutes. Subsequently, a melting curve stage was performed, starting at 95°C for 15 seconds, followed by 60°C for one minute. The temperature was then incrementally increased, and the readings were taken after each 0.3°C increment until reaching a final temperature of 95°C for 15 minutes. For the human beta-globin markers, the amplification consisted of an initial cycle at 95°C for 10 minutes, followed by 40 cycles at 95°C for 15 seconds, 56°C for 45 seconds, and 60°C for one minute. The melting curve stage was then performed following the same procedure as described above.

For telomere identification, the markers described by Cawthon (2009) were utilized. The telomere sequence used in this study was "telg." 5’ACA CTA AGG TTT GGG TTT GGG TTT GGG TTT GGG TTA GTGT3’ and telc: 5’TGT TAG GTA TCC CTA TCC CTA TCC CTA TCC CTA TCC CTA ACA3’, and the markers for the control gene, human beta-globin, were hbgu: 5’CGG CGG CGG GCG GCG CGG GCT GGG CGG ctt cat cca cgt tca cct tg3’ and hbgd: 5’GCC CGG CCC GCC GCG CCC GTC CCG CCG gag gag aag tct gcc gtt3’ (Cawthon, 2009).

To obtain the average relative telomere length, a mathematical model based on the exponential ratio of the number of copies of 41 telomere sequences for each individual compared to the number of copies of the single-copy gene was used [42]. For the categorization of the variable in this study, the distribution of the average relative telomere length was determined by the median. Older adults with a relative telomere length falling within the top 50% of the sample, indicating a greater difference compared to the single-copy gene, were classified as having a "shorter telomere length."

3.2 Nutritional status

The Mini Nutritional Assessment (MNA) was used to assess nutritional risk and malnutrition [43]. Its purpose is to screen for the risk of developing malnutrition or detect it at an early stage in older adults. The MNA is composed by 18 questions divided into two parts. The first part is called nutritional screening, and each question is assigned a score. If the sum of the screening points is 12 or more, further evaluation is unnecessary as there is no risk of malnutrition. If the score is ≤ 11 points, there is a possibility of malnutrition, and further evaluation is required [44]. The second part is called Global Assessment, and each question is also assigned a score. At the end, the scores are summed, and the nutritional status of the older adult can be classified as normal (score >23.5 points), at risk of malnutrition (score between 17 and 23.5 points), or malnourished, scored <17 points. Considering the small number of older adults identified with malnutrition, in this study, the nutritional risk and malnourished categories were combined, resulting in the binary variable "risk of malnutrition/malnutrition" with the categories "no" and "yes” [45].

3.3 Sociodemographic

Sociodemographic information was collected, namely sex (male, female), age group (60–69 years old, 70–79 years old, 80 years old and older); number of years of education (≤4 years of education, >4 years of education); family income (>2 minimum wages, between 1 and 2 minimum wages, <1 minimum wage); number of people in the household (living alone, with one other person, with two or more people).

3.4 General illness status

The classification of illness/comorbidities, and polypharmacy were the indicators used to assess the general state of health/diseases. Multimorbidity is defined as the presence of two or more self-reported chronic diseases in an individual [46]. Polypharmacy, on the other hand, refers to the reported continuous use of five or more medications by an individual [47].

3.5 Functionality

The Brazilian version of Katz scale and the Lawton & Brody scale were used to assess different dimensions of functional ability in this study [48]. The Katz scale measures the performance of basic activities of daily living (BADL), which encompass self-care tasks such as using the bathroom, getting dressed, showering, mobility, continence, and eating [49]. This scale indicates the level of dependency, with older people who can perform all BADL tasks without assistance considered independent [50]. On the other hand, the Lawton & Brody scale evaluates the performance of instrumental activities of daily living (IADL), which are more complex tasks required for independent living within the community [51]. These tasks include using transportation, managing household chores, shopping, making phone calls, managing finances, and taking medication [48].

3.6 Mental health status

A Brazilian version of the Cognitive Abilities Screening Instrument ‐ Short Form (CASI-S) [52], and Geriatric Depression Scale (GDS) were used [53]. The CASI-S is a concise assessment tool designed to screen cognitive changes in older people. It evaluates temporal orientation, verbal fluency, spontaneous recall with semantic suggestion (category), and recognition [54]. Due to its brief administration time (approximately five minutes) and ease of use compared to traditional tests, the CASI-S holds great value for cognitive screening in population research. It has a maximum score of 33 points, and a cutoff point of 23 is commonly employed to identify cognitive decline [55]. The GDS is an instrument used to identify the presence of depressive symptoms in older people [56]. It consists of 15 yes/no questions and is considered a screening tool for depressive symptoms. A score of six or higher indicates a positive screening result for depressive symptoms. The GDS has been widely used in research and clinical settings to assess depression in older adults [53].

3.7 Anthropometric measures

The standardized procedures described by Lohan and colleagues were followed for the collection of anthropometric data [57].To assess body mass, a portable scale (Seca®, model 770, Germany) with a precision of 0.1 kilograms was used. For stature, a portable stadiometer (Seca Body meter®, model 208, Germany) with a precision of 0.1 centimeters was used. Body mass index (BMI) was calculated according to the standard formula (BMI = body mass/stature²). The calf circumference was measured with the older person’s leg bent at a 90-degree angle with the knee, at its most prominent point (WHO. World Health Organization, 1995) Meanwhile, the arm circumference was measured on the non-dominant arm, with an inelastic measuring tape at the midpoint between the acromion and olecranon [58]. It is worth noting that the cutoff points used for BMI, AC, and CC were adopted following MAN recommendations [43].

6.1 Telomer lengths and nutrition associations

Our study contributes to the growing body of research in the field of gerontology, shedding light on an aspect that has not been extensively explored in prior literature. While the relationship between telomere length and aging has garnered considerable attention, the connection between telomere length and nutritional status among older adults remains a relatively uncharted territory.

To the best of our knowledge, a poor number of similar studies have been found that investigate the association between telomere length and the risk of malnutrition/undernutrition in older individuals. However, some studies have examined the effects of food deprivation during gestation and early life, which have implications for adult life and aging [32, 34]. Furthermore, our findings align with research which highlights the impact of socio-economic disparities on both telomere length and nutritional status in older adults [60]. Their work underscores the multifaceted nature of these relationships and the importance of considering socio-economic factors in gerontological research.

To contextualize our findings, it is essential to consider related research on the broader implications of early-life experiences and environmental factors on aging and health outcomes. Previous research provides insights into the long-lasting consequences of early-life nutritional deficits on aging-related processes, including telomere attrition [61–63]. Their study underscores the potential role of early-life nutrition in shaping telomere length and, by extension, the risk of age-related health conditions. In this sense, it would be interesting to explore more deeply whether nutritional intervention strategies during critical developmental phases can attenuate this effect.

A study conducted in Amsterdam with 2.414 individuals of both sexes (mean age of 68 years old) concluded that leukocyte telomere length and the percentage of short telomeres did not differ between those exposed to famine during early gestation and those not exposed during gestation. The variables associated with shorter telomere length were low socioeconomic status, frequent alcohol consumption, history of cancer, and poorer overall health [32]. Considering the findings of our study, one could speculate that common factors may play crucial roles in both telomere shortening and vulnerability to malnutrition in older populations. While the Amsterdam study did not find differences in telomere length concerning exposure to early gestational famine, our results suggest that these socioeconomic and health-related factors may be important considerations when assessing nutritional risk in older individuals.

Another study conducted in St. Petersburg with 356 individuals (aged 64 to 82 years) evaluated cardiovascular health, cardiovascular aging markers, and telomere length in survivors of the Siege of Leningrad. They found that early-life famine, especially during intrauterine and late childhood periods, may contribute to accelerated aging with telomere shortening in both sexes, but it does not have a direct effect on the prevalence of cardiovascular diseases and risk factors after seven decades of exposure [34]. In line with our study’s results, we could speculate that these findings offer insights into potential mechanisms behind this association. While the St. Petersburg study didn’t directly link childhood famine to increased cardiovascular disease prevalence after seven decades, it implies a complex interplay between early nutritional deprivation, telomere dynamics, and long-term health effects warranting further investigation.

Building upon previous research supporting the connection between food restriction and its potential impact on epigenetic changes, gene expression, and cellular aging, as well as the influence of environmental factors during pregnancy and early postnatal life on this interaction [64], it is intriguing to speculate how these modifications, including variations in telomere length, may have enduring implications for cellular aging, in line with the findings of our study. Additionally, it is worth noting a recent study which emphasized the influence of maternal nutrition on determining telomere length in offspring, further underscoring the complexity of this connection and the importance of future investigations to elucidate these mechanisms [65].

6.2 Strengths and limitations

This study has some limitations that should be considered. Firstly, the cross-sectional design restricts establishing causality or temporal sequence. While it provides valuable insights into the association between telomere length and malnutrition risk in older adults, it cannot definitively determine if shorter telomeres directly contribute to higher risk or if other factors are involved. Future longitudinal studies are needed for causal elucidation. Secondly, excluding older adults with mobility impairments may introduce selection bias and limit generalizability. Mobility impairments are known as a malnutrition risk factor, and their exclusion may underestimate the true prevalence of malnutrition risk. Including a more diverse sample, encompassing individuals with mobility impairments, would provide a comprehensive understanding of the relationship between telomere length, malnutrition risk, and mobility status.

Despite its limitations, this study possesses significant strengths that enhance its validity and significance. Firstly, it contributes to the existing literature by advancing our understanding of telomeres as potential biomarkers of aging-related health outcomes, specifically in relation to nutritional status in older adults. Secondly, the study benefits from a large sample size, increasing the generalizability of the findings and allowing for robust statistical analyses. Furthermore, the comprehensive analysis approach considers multiple factors associated with malnutrition risk, providing a nuanced understanding of the complex interactions between these variables and their impact on nutritional status.

6.3 Practical applications

The findings of this research have significant practical applications for addressing malnutrition in older adults, aligning with the United Nations Sustainable Development Goal 3, which aims to ensure healthy lives and promote well-being for all at all ages. By identifying the risk factors associated with malnutrition in older adults, this study provides valuable insights for healthcare professionals, especially nutritionists and dietitians, in developing targeted interventions and strategies for prevention and treatment. For example, healthcare professionals can conduct more frequent and detailed nutritional assessments and implement personalized nutritional intervention plans. Additionally, rehabilitation programs for the older adults could include specific strategies to improve nutrition, focusing on individuals at higher risk. In terms of prevention, nutritional education and awareness initiatives could be directed towards this population. Such approaches can help mitigate the risks of malnutrition and its consequences, promoting better quality of life and health outcomes for older adults.

6.4 Future directions for futures studies

By demonstrating the association between shorter telomere length and the risk of malnutrition/malnourishment, it can contribute to the scientific community via strengthening the hypothesis that telomere length may be a biomarker of aging, as it is associated with adverse outcomes. Investigating the mechanisms through which telomere length affects nutritional status and exploring the potential role of telomere length as a biomarker for aging-related health outcomes could provide a deeper understanding of the underlying biological processes involved. Future studies should focus on conducting longitudinal research to understand the temporal relationship between genetic information and the development of malnutrition in older adults.