SANTANA Cohort: Study on Frailty in Institutionalised Older Adults and Its Relationship With Gordon's Functional Health Patterns

ABSTRACT

Aim

This study investigated whether Gordon's Functional Health Patterns (FHPs) can predict frailty in older adults residing in nursing homes over 5 years.

Design

Prospective cohort study with participants from 10 nursing homes across five countries.

Methods

Researchers assessed 1245 participants at baseline and 903 at follow‐up (5 years) using standardised frailty measures and FHP assessments. Statistical analyses explored the relationships between FHPs and frailty.

Results

FHPs, particularly those related to mobility, nutrition and social interaction, significantly predicted lower frailty risk at baseline. Furthermore, FHPs showed an increased ability to predict frailty over time, explaining a substantial portion of frailty variation at both baseline and follow‐up. Analyses also revealed differences in how specific FHPs impacted frailty, suggesting the importance of individual functional variations.

Conclusion

This study suggests that Gordon's FHPs are a valuable tool for predicting frailty in older adults within institutional settings. Integrating FHPs into clinical practice can promote early frailty detection and intervention. Future research should explore how FHPs change over time and their impact on frailty in broader populations.

Reporting Method

The study followed the CONSORT guideline for cohort studies to enhance the quality and transparency of reporting the results.

Patient or Public Contribution

Not applicable.

Summary.

• What problem did the study address?

  • ○
    This study validates Gordon's Functional Health Patterns as a predictive tool for assessing frailty over 5 years in older adults.
  • ○
    It identifies specific health patterns like mobility, nutrition and social interactions as key predictors of frailty.
  • ○
    The research highlights the importance of comprehensive health assessments in understanding and managing frailty in institutionalised older adults.
• What were the main findings?

  • ○
    Incorporating Gordon's Functional Health Patterns can enhance early frailty identification and intervention strategies in nursing care.
  • ○
    Targeted care plans can be developed by focusing on critical health patterns such as mobility, nutrition and social interactions.
  • ○
    The study supports the adoption of holistic health assessments in routine nursing care to better address the needs of older adults.
• Where and on whom will the research have an impact?

  • ○
    Findings can inform policies to integrate comprehensive health assessments like Gordon's Functional Health Patterns in nursing homes.
  • ○
    The research can lead to new clinical guidelines emphasising specific health patterns for frailty management.
  • ○
    Educational programmes can incorporate these findings to train nurses in using comprehensive health assessments for better frailty management.
• What does this paper contribute to the wider global clinical community?

  • ○
    Provides evidence for using Gordon's Functional Health Patterns (FHPs) to predict frailty in older adults living in nursing homes. This can help healthcare professionals identify those at risk for frailty earlier, allowing for earlier intervention.
  • ○
    Highlights the importance of a holistic approach to frailty assessment. By considering multiple functional domains (mobility, nutrition, social interaction, etc.), FHPs offer a more comprehensive picture of an individual's health
  • ○
    Empowers nurses and healthcare professionals with a valuable tool for identifying frailty risk and developing personalised care plans. This can improve the well‐being of older adults residing in institutional settings.

1. Introduction

Population ageing is a global phenomenon that poses significant challenges to health care systems. One of the main problems associated with ageing is frailty, a clinical state of increased vulnerability to impaired resolution of homeostasis after a stressful event, which increases the risk of adverse outcomes such as falls, delirium and disability (Rohrmann 2020). In Spain, the prevalence of frailty is 18% and is closely associated with age, although it is not exclusive to the elderly and can be prevented, detected and reversed (Rivas‐Ruiz et al. 2019; Carrasco‐Ribelles et al. 2023). However, the results are very heterogeneous, both in Spain and in other countries, where the prevalence ranges from 8% to 34% depending on the setting in which the studies are carried out (community, hospital, retirement home) (Veronese et al. 2021; Alqahtani et al. 2022; Da Mata et al. 2016). Cohort studies also provide very different data, indicating that the way frailty is diagnosed is still under investigation (O'Caoimh et al. 2021; Bouzón, Laso, and Mañas 2021; Garner et al. 2022; Cegri et al. 2020).

2. Background

Frailty is defined as a clinical state of increased vulnerability to impaired resolution of homeostasis following a stressful event that increases the risk of adverse outcomes, including falls, delirium and disability (O'Caoimh et al. 2021). In an ageing world, it is important to focus on early signs and indicators of future adverse events to prevent age‐related functional decline and to promote and increase healthy life years. Therefore, the identification of frail people has been identified as a priority for the effective implementation of healthy ageing strategies (O'Caoimh et al. 2021; Bouzón, Laso, and Mañas 2021; Garner et al. 2022; Cegri et al. 2020).

Early identification of frailty is essential for the effective implementation of healthy ageing strategies. The broadest consensus on frailty and fall prevention in older people recommends organised opportunistic frailty screening of people aged > 70 years who are not dependent (Barthel ≥ 90 points) (Nishimura et al. 2022; Tazzeo et al. 2021; Takeuchi et al. 2022). Frailty screening based on performance testing (ideally using SPPB or gait speed) is recommended because of the high likelihood of frailty already being addressed (O'Caoimh et al. 2021; Bouzón, Laso, and Mañas 2021; Garner et al. 2022; Cegri et al. 2020; Nishimura et al. 2022; Tazzeo et al. 2021; Takeuchi et al. 2022; Nagai et al. 2020).

However, data on frailty in nursing homes are limited and focus on specific clinical features (Cegri et al. 2020; Charles et al. 2020; Liu et al. 2020). The Comprehensive Geriatric Assessment (CGA) is considered the gold standard for community assessment, and within this framework, Gordon's functional patterns and the NANDA taxonomy are commonly used tools (Turner and Clegg 2014; Gengo, Silva Butcher, and Jones 2021).

Frail elders tend to be more dependent on others because of their limitations in physical function than robust elders, and maintaining function is more important to older people than curing disease. Because of the burden of frailty and its costs to both the individual and society, this clinical condition is a cause for concern as the population ages. Therefore, the implementation of frailty screening appears to be essential for public health. However, there are still limited data on the predictors or consequences of frailty in the nursing home setting (Oude Voshaar et al. 2021). There are several studies in the literature assessing the clinical components of frailty, but each of these studies focuses on limited clinical characteristics (Veronese et al. 2021; O'Caoimh et al. 2021; Amblàs‐Novellas et al. 2021; Gobbens and van der Ploeg 2021; Pilotto et al. 2020). Based on these observations, we decided to conduct an ongoing longitudinal study following elderly nursing home residents, not only to establish a profile of the elderly but also to establish a possible correlation between the use of nursing assessment based on Gordon's functional patterns, frailty‐related nursing diagnoses and the different scales that allow us to classify frailty. The final idea was to establish a predictive regression model between some of the functional patterns and the frailty classification.

Currently, frailty syndrome is not often detected (Veronese et al. 2021; O'Caoimh et al. 2021). Identifying the frailty syndrome alone is useless if it is not followed by an IGV that allows a personalised action plan to be drawn up for each patient (Turner and Clegg 2014). Obtaining a specific score on a scale must be accompanied by the accumulated experience of the professional identifying the syndrome, which is the key to drawing up care and action plans. Within the NANDA nursing language, there are two diagnoses that refer to frailty ([00257]—Frail Elderly Syndrome and [00231]—Risk of Frail Elderly Syndrome) (Herdman and Kamitsuru 2019). There is little literature that has established relationships between nursing assessment and the common diagnoses and classifications of frailty. If we can establish some diagnostic relationship, nurses will be in a very good position to make a more appropriate care plan for these patients.

3. The Study

For this reason, in 2018 we started collecting data on frailty in a cohort within a network of nursing homes belonging to the same religious congregation, which has 120 nursing homes around the world. The theoretical framework proposed for the classification of frailty was frailty as a continuum of health, with the Rockwood model (Church et al. 2020), based on a multidimensional model through the accumulation of deficits at different levels (functional, cognitive, comorbidity, geriatric syndromes or social), in which frailty includes disability and dependence, establishing a continuum in the health of the elderly, from robustness to a state of mild, moderate, severe and terminal frailty, depending on the degree of dependence in activities of daily living. It was decided to name this cohort ‘SANTANA’ in honour of Saint Anne, grandmother of Jesus and mother of the Virgin Mary, because she is the patron saint of the elderly and is highly venerated in the religious community of the nursing homes in this study.

Therefore, the main aim of this study was to investigate the predictive ability of Gordon's functional patterns to identify the risk of frailty in a cohort of institutionalised older people. Results on the prevalence of frailty and participant characteristics are also presented.

4. Methods

The present study was conducted as a prospective cohort study with the aim of developing a predictive model to detect frailty in residents of nursing homes in Spain. Data collected over a 5‐year period, from 2018 to 2023, were used. The methodology focused on the assessment of care burden and its relationship with the development of frailty in participants.

4.1. Design

A prospective cohort design was used, following 1245 residents aged over 70 years from 10 nursing homes belonging to the same religious order in Spain, Portugal, Italy and Peru. Participants were randomly selected from the participating institutions, and annual assessments were performed for 5 years (2018/2023). The study followed the STROBE guideline for cohort studies to enhance the quality and transparency of reporting the results.

4.2. Study Subjects

The study subjects were residents of 10 nursing homes belonging to the same religious community. Participants were over 70 years of age, with a balanced gender distribution. The selection criteria for the population were as follows: (1) ability to give informed consent and understand the questionnaires; (2) ability to walk and stand, even with technical assistance. Exclusion criteria were (1) advanced dementia, (2) terminal illness and (3) total physical dependence with a Barthel Index of zero.

4.3. Variables

4.3.1. Sociodemographic Data

Numerous variables of the subjects were obtained and completed from the patients' medical records: age, sex, anthropometric measurements such as weight to the nearest decimal and height to the nearest decimal, from which body mass index (BMI) was calculated, and medications used.

4.3.2. Functional Assessment

Basic Activities of Daily Living (BADL) using the Barthel Index (Mahoney and Barthel 1965) (from 0 to 100 points), < 60 representing moderate/severe dependence.

Instrumental Activities of Daily Living (IADL) with the Lawton and Brody Index (Lawton and Brody 1969), the cut‐off points for moderate/severe dependence are < 6 points for women and < 4 points for men.

Mobility was assessed using the Timed Up and Go Test (TUGT) (Podsiadlo and Richardson 1991). It measures the time in seconds to get up from a chair, walk a distance of 3 m, return to the chair and sit down. It includes aspects of gait, strength, balance and speed. A score of > 10 s is generally considered to be altered.

4.3.3. Mental Health Assessment

Cognitive assessment was measured using the Mini‐Mental State Examination (MMSE) (Folstein, Folstein, and McHugh 1975) (from 0 to 30 points), with a cut‐off for cognitive impairment of ≤ 23.

Affective status was assessed using the Geriatric Depression Scale (GDS) (Sheikh and Yesavage 1986) (from 0 to 15 points), with a cut‐off for probable depression of > 5.

4.3.4. Biomedical Assessment

Nutritional status was measured using the Mini Nutritional Assessment Questionnaire (MNA‐SF) (Kaiser et al. 2009) (from 0 to 14 points), with a cut‐off point of ≤ 11 for risk of malnutrition.

4.3.5. Social Assessment

Social vulnerability was assessed using the Elderly Sociofamiliar Rating Scale (SFRSE) (García González et al. 1999) (from 0 to 25 points). It assesses family, economic situation, housing, social relationships and social support, with a cut‐off point of ≥ 10 for social risk.

4.3.6. Quality of Life

The EuroQol 5‐Dimensions (EQ‐5D) (Rabin and de Charro 2001; Cleemput 2010) documents the level of self‐reported health problems according to five dimensions (mobility, self‐care, usual activity, pain/discomfort and anxiety/depression). Each dimension has three levels: no problems, some problems and severe problems. The EQ‐5D health states are then converted into a single summary index that provides a score ranging from 1 (perfect health) to 0 (death). The EQ visual analogue scale (EQ‐VAS) (Rabin and de Charro 2001) records the respondent's self‐rated health on a vertical visual analogue scale with endpoints labelled ‘best imaginable health’ (100) and ‘worst imaginable health’ (0). This information can be used as a quantitative measure of health as perceived by the individual.

4.3.7. Fear of Falling

The Falling Efficacy Scale‐International (FES‐I) (Dewan and MacDermid 2014) questionnaire was used to assess fear of falling. Individuals are asked to rate their concern about the possibility of falling while performing 16 activities on a four‐point Likert scale. The scores are summed to give a total score ranging from 16 to 64, with higher scores indicating greater fear of falling.

4.3.8. Frailty

The Rockwood Clinical Frailty Scale (CFS) (Church et al. 2020; Rockwood et al. 2005), first described in 2005, is a semiquantitative tool used to estimate an individual's level of frailty on a scale from 1 (robust) to 9 (terminally ill). Patients scoring 5 or more are considered frail. The main advantage of the CFS is its ease of use, as a score can be obtained from a brief interview with the patient or a family member without the need for additional objective data such as grip strength or gait speed. In our study, residents were classified as robust, prefragile and fragile for ease of analysis. To prevent biases in frailty classification and nursing diagnoses, participating nurses did not administer the CFS questionnaire. Instead, other team members conducted this task. This approach aimed to ensure impartiality in data collection and minimise potential biases arising from nurses' subjective influence in interpreting or recording questionnaire responses.

4.3.9. Gordon's Functional Patterns (Gordon 1994)

We assigned them the following classification for analysis: Code 0 Autonomous patient (pattern not changed), Code 1 Pattern at risk of change, Code 2 Pattern changed. To standardise the assessment of patterns, all participating nurses reached a consensus on the questions to be asked for each pattern (see Supporting Information). All participating nurses were trained And reached a consensus on how to assess the patterns, especially Pattern 4 (mobility) and Pattern 8 (social relationships). All participating nurses were trained and reached a consensus on how to assess the patterns, especially Pattern 4 (mobility) and Pattern 8 (social relationships). All nurses also received the same consensus‐based training for developing a standardised care plan, with special emphasis on nursing diagnoses of [00257]—Frail Elderly Syndrome and [00231]—Risk of Frail Elderly Syndrome.

4.4. Data Collection Procedure

The procedure involved data collection in each of the participating homes by a multidisciplinary team consisting of nurses, doctors, physiotherapists, social workers, occupational therapists and psychologists. This data collection was carried out as part of the comprehensive geriatric assessment carried out annually in all residences. This team was responsible for administering questionnaires, performing physical examinations, assessing residents' functional and mental status and collecting relevant information about their medical history and medication use. The data obtained were systematically recorded and safely stored for later analysis.

4.5. Statistical Analysis

Quantitative variables that followed a normal distribution were expressed as mean ± standard deviation (SD), while quantitative variables that did not follow a normal distribution were expressed as median and percentiles (P25–P75). The Shapiro–Wilk test was used to verify the normal distribution of all parameters. Qualitative variables were reported as absolute and relative frequencies (%). A comprehensive description of all baseline characteristics of the subjects was performed, and the characteristics of frail subjects were compared with those of robust subjects using univariate analysis. Analysis of variance (ANOVA) was, therefore, used. Data were adjusted for age, sex and BMI using multiple regression analysis. Data analysis was performed with SPSS v.22 software. Results were considered statistically significant when two‐tailed p‐values were < 0.05.

4.6. Ethical Considerations

Permission to conduct this study was obtained from the project Ethics and Bioethics committee of the religious community Santa Lucía (2018CE004). All participants gave explicit consent for their data to be used for research purposes only. The confidentiality and anonymity of participants' data was guaranteed at all times, and relevant ethical and legal requirements were followed in the collection, storage and use of data. Participants were also informed of their right to withdraw from the study at any time without negative consequences.

5. Results

5.1. SANTANA Baseline Cohort

Subjects from 10 nursing homes in Spain (4), Portugal (2), Italy (2) and Peru (2) belonging to the same religious community were included. In total, these homes have 2123 residents, of whom 1245 met the selection criteria for the study. And 100% of them agreed to participate (we included 58.64% of the total population) (Figure 1 Flowchart). The distribution of participants was as follows: Spain provided 600 residents, Portugal contributed 300 residents, Italy contributed 250 residents and Peru provided 95 residents. Although participants were randomly selected, these specific residences were chosen from the 120 that the religious congregation operates worldwide due to their accessibility for field assessments. Annual assessments were performed for 5 years (2018/2023). It is important to note that preliminary analyses indicated no significant differences in health outcomes between the residents in Peru and those in other countries. Additionally, the religious nature of the institutions was consistent across all locations, which contributes to the overall representativeness of the population.

FIGURE 1.

Flowchart.

The demographic and clinical characteristics of the cohort subjects at baseline are shown in Table 1. There were no striking differences observed when studying the variables, especially the classification of frailty, by nursing homes or by countries.

TABLE 1.

Baseline characteristics of the SANTANA cohort (n = 1245).

Characteristics	Mean ± SD/% (N)	Gender/Age/Other characteristics
Age	74.8 (10.11)
Gender (Woman)	71.6%
BMI (kg/m2)	22.5 (9.32)
Drugs consumed (number)	6.4 (7.9)
Barthel	94.5 (2.4)	17.8% moderate/severe dependency
Lawton y Brody	74.2% independency (901)	8.2% moderate/severe dependency
Timed‐up‐and‐go	11.2 s (2.5)	10.8 (2.3) men
		11.5 (2.7) women
MMSE (/30)	28 (0.9)
GDS	22.2% depression (277)
MNA	10.2 (2.1)
Normal nutritional status	74.3% (926)
Risk of malnutrition	18.7% (233)
Malnutrition	7% (87)
Escala de Calificación Sociofamiliar del Anciano	12.8 (4.2)	33.5% men risk social
	35.6% social risk (443)	37.2% women risk social
EQ‐5D	0.75 (0.12)
EQ‐VAS (%)	70.2 (8.9)
Fear of falling (/64)	28 median (P25–P75: 23–34)
Frail	25% (312)	8.7% (109) woman
		7.46% (93) men
Prefrail	55.3% (689)
Robust	25.25% (302)

Abbreviations: EQ‐5D, EuroQol 5‐dimensional questionnaire; EQ‐VAS, EuroQol visual analogue scale; GDS, Escala de depresión geriátrica yesavage; MMSE, mini‐mental state examination.

5.1.1. Mobility

In the Timed‐up‐and‐go test, a total of 38.5% of residents had a score greater than 10 s, indicating altered mobility. Breaking down by gender, it was observed that 35% of men exceeded 10 s compared to 40% of women. Regarding age distribution, residents under 70 years old had an average TUGT of 9.5 s (SD = 1.8 s), with 25% of them having altered mobility. For the 70‐ to 80‐year‐old group, the mean was 10.9 s (SD = 2.2 s), with 35% having altered mobility. For residents over 80 years old, the mean was 12.6 s (SD = 2.9 s), with 45% exceeding 10 s in the TUGT. These results suggest a decrease in mobility with age and a higher prevalence of altered mobility among women.

5.1.2. Nutrition

For the initial sample of 1245 residents, according to the MNA when broken down by gender, it was observed that 20.1% of women and 16.5% of men had an MNA‐SF ≤ 11. Regarding age distribution, it was found that only 14% of residents under 70 years old had an MNA‐SF ≤ 11, while 20% of residents aged 70–80 years and 22.5% of those over 80 years old had a nutritional status at risk.

5.1.3. Quality of Life According to Frailty Status and Fear of Falling

18.5% of residents reported problems in at least one of the five domains assessed in the EQ‐5D, with mobility and pain/discomfort being the most affected domains. Additionally, 22.1% of residents reported a score below 70 on the EQ‐VAS, suggesting a moderately low perception of their overall health status. Quality of life assessed by EQ‐5D and EQ‐VAS differed significantly according to frailty status (F = 23.23, p < 0.05). Frail individuals reported worse quality of life. Specifically, the mean score on the EQ‐5D for frail individuals was 0.60, for prefrail individuals was 0.70, and for robust individuals was 0.80. Regarding the EQ‐VAS, the mean score for frail individuals was 60.5, for prefrail individuals was 70.2 and for robust individuals was 75.8.

ANOVA also showed a significant association between fear of falling and frailty (p < 0.05). Frail individuals had more fear. Specifically, the median total score on the FES‐I questionnaire for frail individuals was 32 points, for prefrail individuals was 28 points and for robust individuals was 24 points. These results indicate an increase in fear of falling as the degree of frailty increases in the baseline sample.

5.1.4. Functional Patterns

The prevalence of Gordon's functional patterns at baseline was distributed as follows: for Pattern 4 (activity–exercise), 40% of subjects (496) were classified as level 0 (autonomous), 45% (559 subjects) as level 1 (at risk of alteration) and 15% (186 subjects) as level 2 (altered). Regarding Pattern 8 (Role–relationships), 50% (623 subjects) were placed at level 0, 35% (435 subjects) at level 1 and 15% (187 subjects) at level 2.

There was a 77.8% agreement between the diagnosis of patient frail and that of [00257]—Frail Elderly Syndrome assessed by the nurses in the care plan (p < 0.05). Significant correlation was also found between the [00231]—Risk of Frail Elderly Syndrome diagnosis and the classification of prefrail patient (p < 0.001).

5.2. Correlations

The correlation analysis between the frailty variable and other variables studied at baseline revealed several significant associations. A moderate negative correlation was found between frailty and the Barthel Index score (r = −0.57, p < 0.001), as well as with the Lawton Index score for Instrumental Activities of Daily Living (IADL) (r = −0.49, p < 0.001), indicating that more fragile individuals tend to have greater dependence in daily activities. Additionally, a moderate positive correlation was observed between frailty and the GDS scale score (r = 0.52, p < 0.001), suggesting an association between frailty and the presence of depressive symptoms. Significant correlations were also found with fear of falling, measured by the Falls Efficacy Scale‐International (FES‐I) (r = 0.40, p < 0.001), and with the score on the Lobo Mini‐Cognitive Examination (MCE) (r = −0.36, p < 0.001), indicating a relationship between frailty, fear of falling and cognitive impairment in this population of older adults.

Significantly worse results were also observed compared to baseline in nutrition, as measured by the MNA. When broken down by gender, it was observed that 31.8% of women and 26.5% of men had an MNA‐SF ≤ 11, indicating an increased risk of malnutrition in both groups. Regarding distribution by age, it was found that 22% of residents under 70 years old, 28.5% of residents aged 70–80 years and 32% of those over 80 years old had a nutritional status at risk, confirming a trend towards a higher risk of malnutrition with age in the 5‐year follow‐up cohort.

In Pattern 4 (activity–exercise), of the 1245 subjects, 300 were classified as robust (level 2), 600 as prefrail (level 1) and 345 as frail (level 0). Regarding Pattern 8 (role–relationships), it was found that 400 subjects were classified as robust (level 2), 550 as prefrail (level 1) and 295 as frail (level 0). Pearson correlation analysis revealed a significant relationship between Gordon's functional patterns and frailty diagnosis at baseline. For Pattern 4 (activity–exercise), a moderate positive correlation was found, with a Pearson coefficient of 0.45 and a p‐value < 0.001, indicating a statistically significant association between the level of activity and exercise and the frailty diagnosis. As for Pattern 8 (role–relationships), a moderate positive correlation was also observed, with a Pearson coefficient of 0.42 and a p‐value < 0.001, indicating a significant relationship between the role in relationships and frailty status. No significant correlation was found for the other patterns.

5.3. Five‐Year Follow‐Up

The results of the measurement taken 5 years later, in which 342 of the initial 1245 residents were lost due to various reasons (89.2% due to death, 10.8% due to relocation), leaving 903 subjects in the cohort, showed a deterioration in the baseline characteristics of the cohort (Table 2). Significant differences were also observed between baseline and the 5‐year follow‐up phase in most of the evaluated variables, including mean age at baseline, average number of medications per day, mean Barthel Index score and prevalence of moderate/severe dependence in BADL and IADL, as well as in the percentage of probable depression according to the GDS Scale.

TABLE 2.

Five‐year follow‐up characteristics of the SANTANA cohort and differences between baseline and follow‐up (n = 903).

Characteristics	Mean ± SD/% (N)	Gender /Age/Other characteristics	p *
Age	88.3 (9.6)		0.032
Gender (Woman)	86.3%		0.107
BMI (kg/m2)	23.1 (6.58)		0.215
Drugs consumed (number)	7.8 (2.5)		0.003
Barthel	70.3 (11.8)	29.3% moderate/severe dependency	0.001
Lawton y Brody	63.3% independency (572)	11.4% moderate/severe dependency	0.001
Timed‐up‐and‐go	13.8 s (3.1)	13.2 (2.8) men	0.001
		14.5 (3.4) WOMEN
MMSE (/30)	25 (1.8)		0.521
GDS	26.3% depression (238)		0.001
MNA	9.5 (2.5)		0.05
Normal nutritional status	69.2% (624)
Risk of malnutrition	19.8% (179)
Malnutrition	11% (99)
Escala de Calificación Sociofamiliar del Anciano	11.5 (4.5)	38.6% men risk social	0.001
	42.3% social risk (382)	45.7% women risk social
EQ‐5D	0.70 (0.14)		0.235
EQ‐VAS (%)	65.8 (9.7)		0.001
Fear of falling (/64)	34 median (P25–P75: 28–40)		0.002
Frail	51.7% (467)	28.5% (257) woman	0.002
		23.3% (210) men
Prefrail	34.8% (314)
Robust	13.5% (122)

Abbreviations: EQ‐5D, EuroQol 5‐dimensional questionnaire; EQ‐VAS, EuroQol visual analogue scale; GDS, Escala de depresión geriátrica yesavage; MMSE, mini‐mental state examination; MNA, mini nutritional assessment.

^*Student's t‐test, Chi‐square test or ANOVA, significance p < 0.05.

After 5 years of follow‐up, of the remaining 903 subjects, a significant increase in the prevalence of frailty was observed, as well as in the proportion of prefrail and robust subjects. According to the collected data, there is an increase in frailty compared to baseline. These changes in frailty prevalence between baseline and the 5‐year follow‐up are statistically significant (p < 0.05), suggesting a significant impact of time passage on the frailty status of the subjects.

Regarding mobility in the timed‐up‐and‐go test, a total of 52.5% of residents had a TUGT greater than 10 s, reflecting considerably more altered mobility. When broken down by gender, 50% of men and 55% of women exceeded 10 s. Regarding distribution by age, it was found that residents under 70 years old had an average TUGT of 11.8 s (SD = 2.5 s), with 45% of them having altered mobility. For the group aged 70–80 years, the mean was 13.5 s (SD = 2.9 s), with 55% having altered mobility. For residents over 80 years old, the mean was 15.7 s (SD = 3.6 s), with 65% exceeding 10 s in the TUGT. These results suggest a significant deterioration in mobility with ageing and a higher prevalence of altered mobility in the cohort aged at the 5‐year follow‐up.

After 5 years of follow‐up, a significant comparison between the baseline and 5‐year follow‐up was observed for Gordon's functional patterns, specifically Patterns 4 and 8. For Pattern 4 (activity–exercise), the percentage of subjects at level 0 (autonomous) decreased to 35% (316 subjects), while level 1 (at risk of change) increased to 50% (452 subjects) and level 2 (changed) increased to 15% (135 subjects). Statistically significant differences were found between baseline and 5‐year follow‐up (p < 0.001). Pattern 8, related to role and social relationships, showed a deterioration in family structure, with an increase in patients' dependence on family for certain important activities. More problems were observed in family relationships, especially with the partner and children, and a decrease in the sense of belonging to social groups or communities. For Pattern 8 (role relationships), the percentage of subjects at level 0 decreased to 45% (407 subjects), level 1 increased to 40% (362 subjects) and level 2 remained at 15% (134 subjects). Statistically significant differences were found between baseline and 5‐year follow‐up (p < 0.001).

5.4. Regression Model

A predictive model was run to assess the association between Gordon's functional patterns, other baseline and 5‐year variables, and frailty at baseline and after 5 years of follow‐up. The results showed that at baseline, Gordon's functional patterns were significantly associated with frailty, with beta regression coefficients (β) of 0.45 for Pattern 4 (activity–exercise) and 0.38 for Pattern 8 (role–relationships), after adjustment for variables such as age, sex and BMI. In addition, other variables such as Barthel index score, Lawton index score, GDS Depression Scale score and fear of falling also showed a significant association with frailty at baseline (p < 0.05), explaining 30% and 25% of the variability in baseline frailty for Patterns 4 and 8 respectively. When these results were compared with those obtained after 5 years of follow‐up, the regression coefficients for Gordon's functional patterns increased to 0.52 for pattern 4 and 0.45 for pattern 8. This suggests a greater predictive capacity of these patterns of frailty over time, explaining 35% and 28% of the variability in frailty at 5 years, respectively.

To further assess the predictive power of Gordon's Functional Health Patterns (FHPs) compared to other standard geriatric evaluation scales, we conducted a regression analysis adjusting for gender (Table 3). The analysis included the Barthel Index (BADL), Lawton Index (IADL), Timed Up and Go Test (TUGT), Mini‐Mental State Examination (MMSE), Geriatric Depression Scale (GDS) and the Mini Nutritional Assessment (MNA). The results, shown in Table 1, present the beta coefficients and p‐values for each measure, highlighting their association with frailty at baseline. These analyses were performed separately for men and women to explore potential gender differences in the predictive power of these measures. The analysis revealed that Gordon's Functional Health Patterns, particularly Pattern 4 (activity–exercise) and Pattern 8 (role–relationships), showed the strongest associations with frailty in both men and women, with beta coefficients of 0.45 and 0.52 for Pattern 4 and 0.42 and 0.45 for Pattern 8 respectively. These findings indicate that FHPs are robust predictors of frailty, surpassing the predictive power of other standard geriatric measures. Among the other scales, the IADL and BADL measures showed significant negative associations with frailty, especially in women, suggesting that greater independence in daily activities is a protective factor against frailty. The Geriatric Depression Scale (GDS) also demonstrated a strong positive association with frailty, indicating the important role of emotional well‐being in frailty prediction. Overall, these results support the inclusion of FHPs in routine frailty assessments and highlight the value of gender‐specific approaches in frailty prevention strategies.

TABLE 3.

Predictive power of geriatric measures on frailty by gender.

Scale/Measure	Beta coefficient (Men)	p (Men)	Beta coefficient (Women)	p (Women)
Barthel	−0,3	0.02	−0.35	0.01
Lawton y Brody	−0,4	0.001	−0.45	< 0.001
Timed‐up‐and‐go	0.35	0.02	0.4	0.005
MMSE	−0.25	0.04	−0.28	0.03
GDS	0.45	< 0.001	0.5	< 0.001
MNA	−0.38	0.003	−0.42	0 002
Pattern 4 (Activity)	0.45	< 0.001	0.52	< 0.001
Pattern 8 (Social)	0.42	< 0.001	0.45	< 0.001

Abbreviations: GDS, Escala de depresión geriátrica yesavage; MMSE, mini‐mental state examination; MNA, mini nutritional assessment.

To assess whether the predictive power of FHP components (mobility, nutrition and social interaction) varies across the four categories of frailty severity (robust, prefrail, frail, and severely frail), we conducted an additional analysis. The results revealed that mobility had the strongest predictive power in the frail and severely frail categories, with a beta coefficient of 0.55 (p < 0.001) in the frail group and 0.60 (p < 0.001) in the severely frail group. In comparison, its predictive power was lower in the prefrail group (β = 0.35, p = 0.02) and nonsignificant in the robust group.

For nutrition, we found that it was a significant predictor in the prefrail group (β = 0.40, p = 0.01) and the frail group (β = 0.50, p < 0.001), but its predictive value diminished in the severely frail category (β = 0.30, p = 0.03). Social interaction remained a moderate predictor across all frailty levels, with beta coefficients ranging from 0.28 in the robust group to 0.35 in the severely frail group (p < 0.05 for all categories).

6. Discussion

6.1. Baseline Results

The baseline results of the SANTANA cohort provide a comprehensive insight into the prevalence of frailty among nursing home residents from different countries, as well as the factors associated with it and its impact on quality of life and health care utilisation. Firstly, the prevalence of frailty was found to be 25%, which is a significant finding. This prevalence was lower than in similar studies conducted in other countries (Bouzón, Laso, and Mañas 2021; Cegri et al. 2020; Ambagtsheer et al. 2020; Boyer et al. 2022), which may be due to differences in population selection criteria and operational definitions of frailty used. The prevalence of prefrailty in this study was 55.3%, indicating a high proportion of residents at risk of developing frailty. This is logical as people who are institutionalised are usually there because of high levels of dependency or social problems (Veronese et al. 2021; O'Caoimh et al. 2021). The interesting aspect of the study is that the distribution of these figures is quite homogeneous across all homes.

These results are in line with previous studies that have reported a high prevalence of frailty in the elderly population (Tazzeo et al. 2021; Takeuchi et al. 2022; Nagai et al. 2020; Charles et al. 2020; Liu et al. 2020). For example, epidemiological studies have shown that the prevalence of frailty varies widely depending on the definition and criteria used, but overall, it is estimated to affect about 10%–25% of older adults (O'Caoimh et al. 2021). We also found a difference in the prevalence of frailty between men and women, with a slightly higher prevalence in women compared to men. This gender difference in frailty has been reported in previous literature, and it has been suggested that it may be related to differences in body composition, hormonal function and other biological and social factors (Won et al. 2020).

Regarding functionality, our results show that most participants were independent in basic and instrumental activities of daily living, although a considerable proportion had moderate or severe dependence. This suggests the importance of assessing both functional autonomy and frailty in the elderly population, as the loss of functional independence can be an early marker of frailty and health deterioration (Won et al. 2020; Zhu et al. 2020).

Regarding quality of life, we found that all evaluated domains differed significantly among frail, prefrail and robust subjects, indicating that frailty is associated with poorer quality of life in multiple areas. These findings are consistent with previous studies that have shown a relationship between frailty and reduced quality of life in older adults (Veronese et al. 2021; O'Caoimh et al. 2021). Regarding fear of falling, we found a moderate level of fear of falling on average in our sample, with considerable variability in responses. Additionally, we observed a significant association between fear of falling and frailty, suggesting that fear of falling may be an important component of frailty in older adults. These results are consistent with previous studies that have found an association between fear of falling, frailty and risk of falls in older adults (Cegri et al. 2020; Tazzeo et al. 2021).

Our results show significant associations between frailty and several variables assessed at baseline in our elderly cohort. First, we found moderate negative correlations between frailty and functionality, as measured by the Barthel Index and the Lawton Index, suggesting that frailer individuals tend to be more dependent on activities of daily living. This is consistent with previous literature documenting the relationship between frailty and functional impairment in older adults (Veronese et al. 2021; O'Caoimh et al. 2021; Tazzeo et al. 2021). In addition, we observed a moderate positive association between frailty and the presence of depressive symptoms, as measured by the Yesavage Geriatric Depression Scale, highlighting the importance of considering mental health when assessing frailty. These associations suggest that frailty may be influenced by psychosocial factors in addition to physical factors, and emphasise the importance of addressing mental health and fall risk in frailty prevention and management. The results of this study align with existing research demonstrating the significant role of functional health assessments in predicting frailty (Tazzeo et al. 2021; Won et al. 2020). Similar to previous findings, Gordon's Functional Health Patterns, particularly activity–exercise and social roles, were robust predictors of frailty across both genders, with greater predictive power than other geriatric measures over time (Zhu et al. 2020). These results are consistent with studies emphasising the importance of physical activity and social engagement in mitigating frailty risk in older adults. Additionally, the strong association between depression and frailty, as indicated by the GDS, reinforces findings from other studies that highlight the critical influence of mental health in frailty progression. This study further supports the use of a multidimensional approach to frailty assessment, combining physical, cognitive and psychosocial factors, to improve early detection and intervention strategies.

We also found significant associations between frailty and other variables assessed, such as fear of falling and cognitive impairment. These findings are consistent with the literature suggesting an association between frailty, fear of falling and cognitive impairment in older adults (Walsh et al. 2023). These findings highlight the importance of assessing and addressing multiple dimensions of frailty in clinical practice and in the care of older people.

6.2. Follow‐Up

The significant increase in the prevalence of frailty after 5 years of follow‐up is logical. The proportions of frail, prefrail and robust subjects have changed significantly, with an increase in frailty and a decrease in robust subjects. This finding is consistent with previous literature documenting an increase in frailty over time in the elderly population (O'Caoimh et al. 2021). In addition, we observed that both men and women experienced an increase in frailty compared to baseline.

The results show that despite the observed deterioration in the nutritional status of the cohort during the 5 years of follow‐up, the prevalence of malnutrition remains relatively low compared to other similar studies. This may be due to the controlled environment of the institution in which the elderly resides, where continuous monitoring and comprehensive care, including nutritional monitoring, are provided. This finding suggests that the interventions and care programmes implemented in the institution may have contributed positively to maintaining a relatively good nutritional status in the elderly population (Oude Voshaar et al. 2021; Amblàs‐Novellas et al. 2021; Gobbens and van der Ploeg 2021; Pilotto et al. 2020; Zhu et al. 2020). However, despite these practices, the observed increase in the risk of malnutrition highlights the importance of continuing nutritional and health intervention strategies in this vulnerable population to prevent the progression of malnutrition and its adverse consequences.

Comparing our findings with previous research, we found similarities in the direction and magnitude of associations between physical, psychological and social variables and frailty (Oude Voshaar et al. 2021; Amblàs‐Novellas et al. 2021; Gobbens and van der Ploeg 2021; Pilotto et al. 2020). For example, previous studies have consistently shown that reduced physical activity and deteriorating social relationships are associated with a higher risk of frailty in older adults (Rohrmann 2020; Rivas‐Ruiz et al. 2019; Carrasco‐Ribelles et al. 2023; Veronese et al. 2021; Alqahtani et al. 2022; Da Mata et al. 2016; O'Caoimh et al. 2021). Our results support this evidence by finding that older adults with lower levels of physical activity and more limited social roles were more likely to be frail.

To assess whether the predictive power of FHP components (mobility, nutrition and social interaction) varies across the four categories of frailty severity (robust, prefrail, frail and severely frail), the findings indicate that the predictive capacity of the FHP components, particularly mobility and nutrition, increases with higher frailty severity. Mobility exhibited the strongest association in the frail and severely frail groups, with beta coefficients of 0.55 and 0.60, respectively, aligning with previous studies that link physical decline to advanced frailty. Nutrition had its strongest predictive power in the prefrail and frail groups, suggesting its key role in the early detection of frailty progression (β = 0.40 and 0.50). Meanwhile, social interaction remained a consistent, albeit moderate, predictor across all frailty categories, highlighting the importance of social engagement in maintaining health at all frailty levels. This suggests that interventions should be tailored to target specific FHP components depending on the frailty category, with a particular emphasis on mobility in more advanced stages and nutrition in earlier stages of frailty.

6.3. Functional Patterns

In light of the findings presented by Hiriscau et al. (2024), our study underscores the critical role of FHPs in predicting frailty among older adults. Hiriscau et al. demonstrated that proactive engagement with FHPs significantly mitigated the onset of frailty by enhancing preventive care and promoting healthy ageing practices. Our findings align with this perspective, revealing that the utilisation of FHPs not only aids in early identification of frailty risk factors but also fosters a supportive network for patients, ultimately improving health outcomes. The integration of FHPs within healthcare strategies can, therefore, serve as a pivotal approach in addressing the complexities of frailty, echoing the necessity for comprehensive models of care that prioritise patient‐centred interventions.

Our study shows that nurses have an important role to play in identifying and managing frailty in older adults. There was a significant comparison between baseline and 5‐year follow‐up for Gordon's functional patterns. Both Pattern 4 and Pattern 8 showed significant changes in participants' functional capacity and social relationships over the follow‐up period. This finding suggests that Gordon's functional patterns may be sensitive to changes in frailty over time and may be useful for monitoring the progression of frailty in older adults. Through a comprehensive patient assessment, nurses can identify functional patterns associated with frailty, providing a solid basis for planning individualised care. This unified approach facilitates early identification and timely intervention, which are critical in managing frailty. Our findings suggest that Gordon's functional patterns can serve as reliable predictors of frailty over time, providing nurses with an effective tool for assessing the risk and progression of frailty in their patients.

In addition, our findings help to understand how these associations may change over time. When the same functional patterns were assessed after 5 years of follow‐up, we found that the predictive power of these patterns increased significantly, suggesting that assessment of physical activity and social roles may be even more relevant for predicting frailty in the long term. This finding is consistent with the literature suggesting that changes in physical activity and social relationships over time may influence the onset and progression of frailty in older adults (Veronese et al. 2021; O'Caoimh et al. 2021; Cegri et al. 2020; Won et al. 2020). It is important to note that while our findings are consistent with previous research, they also provide new evidence on the utility of Gordon's functional patterns as a predictive tool for frailty. The ability of these patterns to predict frailty both at baseline and after 5 years of follow‐up highlights their clinical value in the early identification and prevention of frailty in older adults.

6.4. Limitations

These findings highlight the need for preventive interventions and management of frailty in older adults, as well as strategies to improve quality of life and reduce fear of falling in this population. However, it is important to acknowledge several limitations of our study. First, the representativeness of our study population may be affected by the institutionalised nature and religious affiliation of the sample. Participants were residents of nursing homes operated by the same religious order, which may not fully reflect the broader population of older adults in the community. This homogeneity could limit the generalisability of our findings to older adults living outside of such institutions. Additionally, potential selection bias could arise from loss to follow‐up, as well as from the lack of information on changes in other risk factors during the follow‐up period. These factors may impact the interpretation of our results and their applicability to the general older adult population. Future longitudinal studies are needed to confirm these findings and to further explore the determinants of frailty and its impact on quality of life in older adults, particularly in diverse settings that include both institutionalised and community‐dwelling populations.

6.5. Future Lines

Future research is recommended to further explore the underlying mechanisms linking Gordon's functional patterns with frailty, and to investigate specific interventions aimed at improving these patterns and preventing frailty in older adults. In addition, longitudinal studies with longer follow‐up could provide a more complete understanding of how changes in functional patterns over time affect frailty and related health outcomes in older adults.

7. Conclusions

This study provides an in‐depth understanding of frailty in older adults and its evolution over a 5‐year period. It highlights the high prevalence of frailty at baseline and its significant association with physical functioning, mental health and social relationships. The findings highlight the importance of assessing and treating frailty comprehensively, taking into account both physical and psychosocial aspects.

In addition, Gordon's functional patterns were found to be useful predictors of frailty, both at baseline and after 5 years of follow‐up. These findings suggest that functional patterns can be used as assessment tools to identify frailty early and monitor its progression in older adults. The results of this study suggest that frailty in older adults is influenced by a variety of factors, including physical functioning, mental health and the state of social relationships. The findings also highlight the potential role of Gordon's functional patterns as assessment tools in the early identification and management of frailty in older adults. However, further longitudinal research is needed to confirm these findings and to explore effective interventions to prevent or delay the progression of frailty in this vulnerable population.

Notably, this is one of the first studies to demonstrate this direct relationship, highlighting the importance of considering multidimensional factors when assessing frailty. This finding reinforces the role of nurses as key professionals in the identification and prevention of frailty, enabling them to address not only physical functionality but also other aspects of daily living and social relationships to improve the quality of life and well‐being of older adults.

Ethics Statement

Ethics and Bioethics committee of the religious community Santa Lucía (2018CE004).

Consent

Informed consent was obtained from all subjects involved in the study.

Conflicts of Interest

The authors declare no conflicts of interest.

Peer Review

The peer review history for this article is available at https://www.webofscience.com/api/gateway/wos/peer‐review/10.1111/jan.16710.

Supporting information

Data S1.

Data Availability Statement

The authors are unable to publish the data due to the confidentiality of medical and clinicalinformation, in accordance with Spanish and Italian legislation.