The burden of frailty in older people visiting GPs in Veneto and Sicily, Italy

Figures & data

Table 1. Characteristics of the analysed sample.

	Whole sample (Veneto + Sicily)			Veneto			Sicily
	Females (n = 2,584)	Males (n = 1,947)	All (n = 4,531)	Females (n = 1,393)	Males (n = 1,014)	All (n = 2,407)	Females (n = 1,191)	Males (n = 933)	All (n = 2,124)
Sample, %	57.03	42.97	100.00	57.87	42.13	100.00%	56.07	43.93	100.00
Age (SD)	76.32 (7.92)	74.81 (7.10)	75.67 (7.62)	76.73 (8.00)	74.94 (7.02)	75.97 (7.65)	75.83 (7.81)	74.68 (7.19)	75.3 (7.56)
Frailty (Rockwood score > 4), %	29.29	20.13	25.35	28.06	16.46	23.18	30.73	24.11	27.82
Myocardial infarct, %	1.39	4.82	2.86	1.14	4.63	2.61	1.67	5.03	3.15
Congestive heart failure, %	4.60	5.70	5.07	4.16	5.71	4.81	5.12	5.68	5.36
Peripheral vascular disease, %	2.32	6.98	4.32	2.22	8.97	5.06	2.43	4.82	3.48
Cerebrovascular disease, %	18.22	20.74	19.31	20.24	22.68	21.27	15.86	18.64	17.09
Dementia, %	2.94	1.64	2.38	2.51	1.18	1.95	3.44	2.14	2.87
Chronic pulmonary disease, %	21.63	25.42	23.26	19.81	22.48	20.93	23.76	28.61	25.89
Connective tissue disease, %	4.64	2.56	3.75	5.81	3.15	4.69	3.27	1.92	2.68
Ulcer disease, %	3.79	5.59	4.56	4.52	6.80	5.48	2.93	4.28	3.53
Mild liver disease, %	0.69	1.07	0.86	0.64	1.28	0.91	0.75	0.85	0.80
Diabetes, %	19.31	24.75	21.65	15.43	23.37	18.77	23.84	26.25	24.90
Diabetes with end organ damage, %	0.07	0.15	0.11	0.07	0.19	0.12	0.08	0.10	0.09
Hemiplegia, %	0.23	0.35	0.28	0.35	0.49	0.41	0.08	0.21	0.14
Moderate or severe renal disease, %	10.06	11.40	10.63	6.67	9.46	7.85	14.02	13.50	13.79
Any tumour, %	9.09	1.48	5.82	11.98	1.77	7.68	5.70	1.17	3.71
Lymphoma, %	0.73	1.07	0.88	1.07	0.98	1.03	0.33	1.17	0.70
Leukaemia, %	0.42	0.30	0.37	0.64	0.19	0.45	0.16	0.42	0.28
Moderate or severe liver disease, %	0.11	0.30	0.19	0.00	0.19	0.08	0.25	0.42	0.32
Metastatic solid tumour, %	0.27	0.30	0.28	0.28	0.39	0.33	0.25	0.21	0.23
AIDS, %	0.03	0.00	0.02	0.07	0.00	0.04	0.00	0.00	0.00
Hypertension, %	70.70	67.33	69.25	69.34	69.92	69.58	72.29	64.52	68.87
Depression, %	19.73	11.71	16.28	21.24	13.11	17.82	17.96	10.18	14.54
Cellulitis - Skin Ulcers, %	4.37	3.69	4.08	5.31	4.24	4.86	3.27	3.10	3.20
Dicumarol use, %	2.51	4.36	3.31	3.80	6.31	4.86	1.00	2.25	1.55

The chronic conditions (Diagnoses) represent the index diseases for the calculation of the Charlson Index; the percentages identify the prevalence of the diseases into the single strata (All, Females, Males) for whole sample, Veneto region and Sicily region, respectively; obviously a patient can have more than one disease.

Figure 1. Distribution of the Rockwoods scores in the 4,531 65+ evaluated.

Table 2. Age- and sex-distribution of the prevalence of Frailty Status (so defined by a Rockwood score > 4) in the sample of 4,531 elderly individuals evaluated with the Rockwood Clinical Frailty Scale (% value and 95% confidence intervals).

Age stratum	Female	Male	Total
≥ 65 < 75
n	1,212	1,021	2,233
Prevalence % (95% CI)	10.39 (8.79–12.24)	8.52 (6.95–10.39)	9.53 (8.38–10.82)
≥ 75 < 85
n	919	712	1,631
Prevalence % (95% CI)	32.53 (29.58–35.63)	25.70 (22.62–29.03)	29.55 (27.38–31.81)
≥ 85
n	453	214	667
Prevalence % (95% CI)	73.28 (69.02–77.15)	57.00 (50.30–63.46)	68.06 (64.43–71.49)
Total
n	2,584	1,947	4,531
Prevalence % (95% CI)	29.29 (27.57–31.08)	20.13 (18.41–21.97)	25.35 (24.11–26.64)

The prevalence of frailty is shown to be higher in females in all age-strata; in the whole sample it corresponds to 29.29 (27.57–31.08) for females and 20.13 (18.41–21.97) for males (ratio F/M = 1.45).

Table 3. Prevalence of the state of frailty in some common chronic diseases.

Conditions	Females	Males	Total
Myocardial infarct	41.67%	28.72%	32.31%
Congestive heart failure	68.07%	45.05%	56.96%
Peripheral vascular disease	35.00%	23.53%	27.04%
Cerebrovascular disease	41.40%	31.93%	37.03%
Dementia	78.95%	68.75%	75.93%
Chronic pulmonary disease	32.38%	23.03%	27.99%
Connective tissue disease	44.17%	34.00%	41.18%
Ulcer disease	37.76%	25.69%	31.40%
Mild liver disease	27.78%	47.62%	38.46%
Diabetes	37.47%	24.48%	31.09%
Diabetes with end organ damage	50.00%	33.33%	40.00%
Hemiplegia	50.00%	85.71%	69.23%
Moderate or severe renal disease	51.92%	45.05%	48.76%
Any tumour	27.66%	20.69%	26.89%
Lymphoma	52.63%	47.62%	50.00%
Leukaemia	54.55%	16.67%	41.18%
Moderate or severe liver disease	33.33%	50.00%	44.44%
Metastatic solid tumour	42.86%	50.00%	46.15%
AIDS	0.00%	21.13%	0.00%
Hypertension	31.31%	28.95%	27.06%
Depression	34.51%	48.61%	32.79%
Cellulitis - Skin Ulcers	55.75%	42.35%	52.97%
Dicumarol use	67.69%	0.00%	53.33%

The prevalence of frailty in the clinical conditions used for the calculation of the Charlson Comorbidity index 19 in 4,531 elderly people evaluated for frailty status.

Figure 2. Prevalences of mutually exclusive combinations of frailty and serious comorbidity.

Table 4. Univariate and multivariate logistic regression models exploring the relationship between frailty (i.e. Rockwood score > 4) and comorbidity (i.e. Charlson Score ≥ 4).

	I. Monovariate logistic models, OR (95% CI), Z-test, p	II. Multivariate logistic model without interactions, OR (95% CI), Z-test, p	III. Multivariate logistic model with interactions, OR (95% CI), Z-test, p
To be female	1.64 (1.42–1.88) p < 0.0001	1.53 (1.31–1.79) p < 0.0001	1.53 (1.31–1.79) p < 0.0001
Having a Charlson score ≥ 4	3.24(2.79–3.77) p < 0.0001	2.99 (2.54–3.53) p < 0.0001	3.44 (2.88–4.11) p < 0.0001
To be aged ≥ 85	9.89 (8.11–12.05) p < 0.0001	9.21(7.51–11.31) p < 0.0001	11.89 (9.31–15.18) p < 0.0001
To be resident in Sicily	1.27 (1.11–1.46) p < 0.0001	1.43 (1.23–1.66) p < 0.0001	1.43 (1.23–1.66) p < 0.0001
Age ≥ 85 × Clarlson ≥ 4	—	—	ROR* = 0.41 (0.27—0.64) p < 0.0001
Model diagnostics
Pregibon test	—	Z = –3.56; p = < 0.0001	Z = –0.90; p = 0.365
Hosmer-Lemeshow test	—	Chi^2 = 9.51; df = 5; p = 0.0905	Chi^2 = 9.58; df = 5; p = 0.0880
AIC statistic	—	4,348.68	4,335.491

Logistic regression models – Outcome: to be frail (i.e. having CSHA Clinical Frailty Scale score > 4). We analysed 4,531 elderly people assisted by doctors.

* Note: the exponentialized coefficient of the interaction variable is a ratio of odds ratios ROR

We explored the details of the relationship between frailty and comorbidity through three models of logistic regression in which the condition of frailty was the outcome and age, sex, and comorbidity were the predictors.

The multivariate model without interactions (II) does not fit well: this can be seen from the outputs of the Pregibon test (p < 0.0001), which demonstrates an inadequate pattern of covariates; the AIC statistic (4,348.68 vs 4,335.491) shows also that the informative contribution is worst with respect to that of model III (i.e. that with the interaction).

The multivariate model with interactions (III) shows a satisfactory goodness of fit (Hosmer-Lemeshow test, p = 0.0880) and a better pattern of covariates (Pregibons test, p = 0.365). To be female and be resident in Sicily are shown to be significant predictors of frailty status, and age is shown to be a significant confounder in the relations between comorbidity and frailty.

In detail, multimorbidity has been shown to be an independent predictor of frailty only for patients under the age of 85. The linear combination of the non-exponentialized coefficients of the variables involved in the interaction (third model) allowed us to calculate for patients with multimorbidity (i.e. with Charlson score ≥ 4) compared to those without multimorbidity (i.e. with Charlson score < 4) an Odds Ratio of frailty correspondent to OR = 3.44 (2.88–4.11), p < 0.0001 in subjects under 85 years and to an OR = 1.44 (0.945–2.12), p = 0.066 in subjects 85+ years old. So, a serious comorbidity is shown to be a prognostic factor for frailty only under 85 years of age.