Health profiles and socioeconomic characteristics of nonagenarians residing in Mugello, a rural area in Tuscany (Italy)
Background Health, as defined by the WHO, is a multidimensional concept that includes different aspects. Interest in the health conditions of the oldest-old has increased as a consequence of the phenomenon of population aging. This study investigates whether (1) it is possible to identify health pro...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Strozza, Cosmo [verfasserIn] Pasqualetti, Patrizio [verfasserIn] Egidi, Viviana [verfasserIn] Loreti, Claudia [verfasserIn] Vannetti, Federica [verfasserIn] Macchi, Claudio [verfasserIn] Padua, Luca [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2020 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: BMC geriatrics - London : BioMed Central, 2001, 20(2020), 1 vom: 15. Aug. |
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| Übergeordnetes Werk: |
volume:20 ; year:2020 ; number:1 ; day:15 ; month:08 |
| Links: |
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| DOI / URN: |
10.1186/s12877-020-01689-3 |
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SPR040669513 |
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| 520 | |a Background Health, as defined by the WHO, is a multidimensional concept that includes different aspects. Interest in the health conditions of the oldest-old has increased as a consequence of the phenomenon of population aging. This study investigates whether (1) it is possible to identify health profiles among the oldest-old, taking into account physical, emotional and psychological information about health, and (2) there are demographic and socioeconomic differences among the health profiles. Methods Latent Class Analysis with covariates was applied to the Mugello Study data to identify health profiles among the 504 nonagenarians residing in the Mugello district (Tuscany, Italy) and to evaluate the association between socioeconomic characteristics and the health profiles resulting from the analysis. Results This study highlights four groups labeled according to the posterior probability of determining a certain health characteristic: “healthy”, “physically healthy with cognitive impairment”, “unhealthy”, and “severely unhealthy”. Some demographic and socioeconomic characteristics were found to be associated with the final groups: older nonagenarians are more likely to be in worse health conditions; men are in general healthier than women; more educated individuals are less likely to be in extremely poor health conditions, while the lowest-educated are more likely to be cognitively impaired; and office or intellectual workers are less likely to be in poor health conditions than are farmers. Conclusions Considering multiple dimensions of health to determine health profiles among the oldest-old could help to better evaluate their care needs according to their health status. | ||
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10.1186/s12877-020-01689-3 doi (DE-627)SPR040669513 (SPR)s12877-020-01689-3-e DE-627 ger DE-627 rakwb eng 610 ASE 44.00 bkl Strozza, Cosmo verfasserin aut Health profiles and socioeconomic characteristics of nonagenarians residing in Mugello, a rural area in Tuscany (Italy) 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background Health, as defined by the WHO, is a multidimensional concept that includes different aspects. Interest in the health conditions of the oldest-old has increased as a consequence of the phenomenon of population aging. This study investigates whether (1) it is possible to identify health profiles among the oldest-old, taking into account physical, emotional and psychological information about health, and (2) there are demographic and socioeconomic differences among the health profiles. Methods Latent Class Analysis with covariates was applied to the Mugello Study data to identify health profiles among the 504 nonagenarians residing in the Mugello district (Tuscany, Italy) and to evaluate the association between socioeconomic characteristics and the health profiles resulting from the analysis. Results This study highlights four groups labeled according to the posterior probability of determining a certain health characteristic: “healthy”, “physically healthy with cognitive impairment”, “unhealthy”, and “severely unhealthy”. Some demographic and socioeconomic characteristics were found to be associated with the final groups: older nonagenarians are more likely to be in worse health conditions; men are in general healthier than women; more educated individuals are less likely to be in extremely poor health conditions, while the lowest-educated are more likely to be cognitively impaired; and office or intellectual workers are less likely to be in poor health conditions than are farmers. Conclusions Considering multiple dimensions of health to determine health profiles among the oldest-old could help to better evaluate their care needs according to their health status. Aging (dpeaa)DE-He213 Health (dpeaa)DE-He213 Health profiles (dpeaa)DE-He213 Nonagenarians (dpeaa)DE-He213 Oldest-old (dpeaa)DE-He213 Latent class analysis (dpeaa)DE-He213 Socioeconomic status (dpeaa)DE-He213 Italy (dpeaa)DE-He213 Pasqualetti, Patrizio verfasserin aut Egidi, Viviana verfasserin aut Loreti, Claudia verfasserin aut Vannetti, Federica verfasserin aut Macchi, Claudio verfasserin aut Padua, Luca verfasserin aut Enthalten in BMC geriatrics London : BioMed Central, 2001 20(2020), 1 vom: 15. Aug. (DE-627)335488994 (DE-600)2059865-8 1471-2318 nnns volume:20 year:2020 number:1 day:15 month:08 https://dx.doi.org/10.1186/s12877-020-01689-3 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_375 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 44.00 ASE AR 20 2020 1 15 08 |
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10.1186/s12877-020-01689-3 doi (DE-627)SPR040669513 (SPR)s12877-020-01689-3-e DE-627 ger DE-627 rakwb eng 610 ASE 44.00 bkl Strozza, Cosmo verfasserin aut Health profiles and socioeconomic characteristics of nonagenarians residing in Mugello, a rural area in Tuscany (Italy) 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background Health, as defined by the WHO, is a multidimensional concept that includes different aspects. Interest in the health conditions of the oldest-old has increased as a consequence of the phenomenon of population aging. This study investigates whether (1) it is possible to identify health profiles among the oldest-old, taking into account physical, emotional and psychological information about health, and (2) there are demographic and socioeconomic differences among the health profiles. Methods Latent Class Analysis with covariates was applied to the Mugello Study data to identify health profiles among the 504 nonagenarians residing in the Mugello district (Tuscany, Italy) and to evaluate the association between socioeconomic characteristics and the health profiles resulting from the analysis. Results This study highlights four groups labeled according to the posterior probability of determining a certain health characteristic: “healthy”, “physically healthy with cognitive impairment”, “unhealthy”, and “severely unhealthy”. Some demographic and socioeconomic characteristics were found to be associated with the final groups: older nonagenarians are more likely to be in worse health conditions; men are in general healthier than women; more educated individuals are less likely to be in extremely poor health conditions, while the lowest-educated are more likely to be cognitively impaired; and office or intellectual workers are less likely to be in poor health conditions than are farmers. Conclusions Considering multiple dimensions of health to determine health profiles among the oldest-old could help to better evaluate their care needs according to their health status. Aging (dpeaa)DE-He213 Health (dpeaa)DE-He213 Health profiles (dpeaa)DE-He213 Nonagenarians (dpeaa)DE-He213 Oldest-old (dpeaa)DE-He213 Latent class analysis (dpeaa)DE-He213 Socioeconomic status (dpeaa)DE-He213 Italy (dpeaa)DE-He213 Pasqualetti, Patrizio verfasserin aut Egidi, Viviana verfasserin aut Loreti, Claudia verfasserin aut Vannetti, Federica verfasserin aut Macchi, Claudio verfasserin aut Padua, Luca verfasserin aut Enthalten in BMC geriatrics London : BioMed Central, 2001 20(2020), 1 vom: 15. Aug. (DE-627)335488994 (DE-600)2059865-8 1471-2318 nnns volume:20 year:2020 number:1 day:15 month:08 https://dx.doi.org/10.1186/s12877-020-01689-3 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_375 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 44.00 ASE AR 20 2020 1 15 08 |
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10.1186/s12877-020-01689-3 doi (DE-627)SPR040669513 (SPR)s12877-020-01689-3-e DE-627 ger DE-627 rakwb eng 610 ASE 44.00 bkl Strozza, Cosmo verfasserin aut Health profiles and socioeconomic characteristics of nonagenarians residing in Mugello, a rural area in Tuscany (Italy) 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background Health, as defined by the WHO, is a multidimensional concept that includes different aspects. Interest in the health conditions of the oldest-old has increased as a consequence of the phenomenon of population aging. This study investigates whether (1) it is possible to identify health profiles among the oldest-old, taking into account physical, emotional and psychological information about health, and (2) there are demographic and socioeconomic differences among the health profiles. Methods Latent Class Analysis with covariates was applied to the Mugello Study data to identify health profiles among the 504 nonagenarians residing in the Mugello district (Tuscany, Italy) and to evaluate the association between socioeconomic characteristics and the health profiles resulting from the analysis. Results This study highlights four groups labeled according to the posterior probability of determining a certain health characteristic: “healthy”, “physically healthy with cognitive impairment”, “unhealthy”, and “severely unhealthy”. Some demographic and socioeconomic characteristics were found to be associated with the final groups: older nonagenarians are more likely to be in worse health conditions; men are in general healthier than women; more educated individuals are less likely to be in extremely poor health conditions, while the lowest-educated are more likely to be cognitively impaired; and office or intellectual workers are less likely to be in poor health conditions than are farmers. Conclusions Considering multiple dimensions of health to determine health profiles among the oldest-old could help to better evaluate their care needs according to their health status. Aging (dpeaa)DE-He213 Health (dpeaa)DE-He213 Health profiles (dpeaa)DE-He213 Nonagenarians (dpeaa)DE-He213 Oldest-old (dpeaa)DE-He213 Latent class analysis (dpeaa)DE-He213 Socioeconomic status (dpeaa)DE-He213 Italy (dpeaa)DE-He213 Pasqualetti, Patrizio verfasserin aut Egidi, Viviana verfasserin aut Loreti, Claudia verfasserin aut Vannetti, Federica verfasserin aut Macchi, Claudio verfasserin aut Padua, Luca verfasserin aut Enthalten in BMC geriatrics London : BioMed Central, 2001 20(2020), 1 vom: 15. Aug. (DE-627)335488994 (DE-600)2059865-8 1471-2318 nnns volume:20 year:2020 number:1 day:15 month:08 https://dx.doi.org/10.1186/s12877-020-01689-3 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_375 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 44.00 ASE AR 20 2020 1 15 08 |
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10.1186/s12877-020-01689-3 doi (DE-627)SPR040669513 (SPR)s12877-020-01689-3-e DE-627 ger DE-627 rakwb eng 610 ASE 44.00 bkl Strozza, Cosmo verfasserin aut Health profiles and socioeconomic characteristics of nonagenarians residing in Mugello, a rural area in Tuscany (Italy) 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background Health, as defined by the WHO, is a multidimensional concept that includes different aspects. Interest in the health conditions of the oldest-old has increased as a consequence of the phenomenon of population aging. This study investigates whether (1) it is possible to identify health profiles among the oldest-old, taking into account physical, emotional and psychological information about health, and (2) there are demographic and socioeconomic differences among the health profiles. Methods Latent Class Analysis with covariates was applied to the Mugello Study data to identify health profiles among the 504 nonagenarians residing in the Mugello district (Tuscany, Italy) and to evaluate the association between socioeconomic characteristics and the health profiles resulting from the analysis. Results This study highlights four groups labeled according to the posterior probability of determining a certain health characteristic: “healthy”, “physically healthy with cognitive impairment”, “unhealthy”, and “severely unhealthy”. Some demographic and socioeconomic characteristics were found to be associated with the final groups: older nonagenarians are more likely to be in worse health conditions; men are in general healthier than women; more educated individuals are less likely to be in extremely poor health conditions, while the lowest-educated are more likely to be cognitively impaired; and office or intellectual workers are less likely to be in poor health conditions than are farmers. Conclusions Considering multiple dimensions of health to determine health profiles among the oldest-old could help to better evaluate their care needs according to their health status. Aging (dpeaa)DE-He213 Health (dpeaa)DE-He213 Health profiles (dpeaa)DE-He213 Nonagenarians (dpeaa)DE-He213 Oldest-old (dpeaa)DE-He213 Latent class analysis (dpeaa)DE-He213 Socioeconomic status (dpeaa)DE-He213 Italy (dpeaa)DE-He213 Pasqualetti, Patrizio verfasserin aut Egidi, Viviana verfasserin aut Loreti, Claudia verfasserin aut Vannetti, Federica verfasserin aut Macchi, Claudio verfasserin aut Padua, Luca verfasserin aut Enthalten in BMC geriatrics London : BioMed Central, 2001 20(2020), 1 vom: 15. Aug. (DE-627)335488994 (DE-600)2059865-8 1471-2318 nnns volume:20 year:2020 number:1 day:15 month:08 https://dx.doi.org/10.1186/s12877-020-01689-3 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_375 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 44.00 ASE AR 20 2020 1 15 08 |
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10.1186/s12877-020-01689-3 doi (DE-627)SPR040669513 (SPR)s12877-020-01689-3-e DE-627 ger DE-627 rakwb eng 610 ASE 44.00 bkl Strozza, Cosmo verfasserin aut Health profiles and socioeconomic characteristics of nonagenarians residing in Mugello, a rural area in Tuscany (Italy) 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background Health, as defined by the WHO, is a multidimensional concept that includes different aspects. Interest in the health conditions of the oldest-old has increased as a consequence of the phenomenon of population aging. This study investigates whether (1) it is possible to identify health profiles among the oldest-old, taking into account physical, emotional and psychological information about health, and (2) there are demographic and socioeconomic differences among the health profiles. Methods Latent Class Analysis with covariates was applied to the Mugello Study data to identify health profiles among the 504 nonagenarians residing in the Mugello district (Tuscany, Italy) and to evaluate the association between socioeconomic characteristics and the health profiles resulting from the analysis. Results This study highlights four groups labeled according to the posterior probability of determining a certain health characteristic: “healthy”, “physically healthy with cognitive impairment”, “unhealthy”, and “severely unhealthy”. Some demographic and socioeconomic characteristics were found to be associated with the final groups: older nonagenarians are more likely to be in worse health conditions; men are in general healthier than women; more educated individuals are less likely to be in extremely poor health conditions, while the lowest-educated are more likely to be cognitively impaired; and office or intellectual workers are less likely to be in poor health conditions than are farmers. Conclusions Considering multiple dimensions of health to determine health profiles among the oldest-old could help to better evaluate their care needs according to their health status. Aging (dpeaa)DE-He213 Health (dpeaa)DE-He213 Health profiles (dpeaa)DE-He213 Nonagenarians (dpeaa)DE-He213 Oldest-old (dpeaa)DE-He213 Latent class analysis (dpeaa)DE-He213 Socioeconomic status (dpeaa)DE-He213 Italy (dpeaa)DE-He213 Pasqualetti, Patrizio verfasserin aut Egidi, Viviana verfasserin aut Loreti, Claudia verfasserin aut Vannetti, Federica verfasserin aut Macchi, Claudio verfasserin aut Padua, Luca verfasserin aut Enthalten in BMC geriatrics London : BioMed Central, 2001 20(2020), 1 vom: 15. Aug. (DE-627)335488994 (DE-600)2059865-8 1471-2318 nnns volume:20 year:2020 number:1 day:15 month:08 https://dx.doi.org/10.1186/s12877-020-01689-3 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_375 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 44.00 ASE AR 20 2020 1 15 08 |
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Some demographic and socioeconomic characteristics were found to be associated with the final groups: older nonagenarians are more likely to be in worse health conditions; men are in general healthier than women; more educated individuals are less likely to be in extremely poor health conditions, while the lowest-educated are more likely to be cognitively impaired; and office or intellectual workers are less likely to be in poor health conditions than are farmers. 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Strozza, Cosmo |
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Strozza, Cosmo ddc 610 bkl 44.00 misc Aging misc Health misc Health profiles misc Nonagenarians misc Oldest-old misc Latent class analysis misc Socioeconomic status misc Italy Health profiles and socioeconomic characteristics of nonagenarians residing in Mugello, a rural area in Tuscany (Italy) |
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610 ASE 44.00 bkl Health profiles and socioeconomic characteristics of nonagenarians residing in Mugello, a rural area in Tuscany (Italy) Aging (dpeaa)DE-He213 Health (dpeaa)DE-He213 Health profiles (dpeaa)DE-He213 Nonagenarians (dpeaa)DE-He213 Oldest-old (dpeaa)DE-He213 Latent class analysis (dpeaa)DE-He213 Socioeconomic status (dpeaa)DE-He213 Italy (dpeaa)DE-He213 |
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Strozza, Cosmo Pasqualetti, Patrizio Egidi, Viviana Loreti, Claudia Vannetti, Federica Macchi, Claudio Padua, Luca |
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health profiles and socioeconomic characteristics of nonagenarians residing in mugello, a rural area in tuscany (italy) |
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Health profiles and socioeconomic characteristics of nonagenarians residing in Mugello, a rural area in Tuscany (Italy) |
| abstract |
Background Health, as defined by the WHO, is a multidimensional concept that includes different aspects. Interest in the health conditions of the oldest-old has increased as a consequence of the phenomenon of population aging. This study investigates whether (1) it is possible to identify health profiles among the oldest-old, taking into account physical, emotional and psychological information about health, and (2) there are demographic and socioeconomic differences among the health profiles. Methods Latent Class Analysis with covariates was applied to the Mugello Study data to identify health profiles among the 504 nonagenarians residing in the Mugello district (Tuscany, Italy) and to evaluate the association between socioeconomic characteristics and the health profiles resulting from the analysis. Results This study highlights four groups labeled according to the posterior probability of determining a certain health characteristic: “healthy”, “physically healthy with cognitive impairment”, “unhealthy”, and “severely unhealthy”. Some demographic and socioeconomic characteristics were found to be associated with the final groups: older nonagenarians are more likely to be in worse health conditions; men are in general healthier than women; more educated individuals are less likely to be in extremely poor health conditions, while the lowest-educated are more likely to be cognitively impaired; and office or intellectual workers are less likely to be in poor health conditions than are farmers. Conclusions Considering multiple dimensions of health to determine health profiles among the oldest-old could help to better evaluate their care needs according to their health status. |
| abstractGer |
Background Health, as defined by the WHO, is a multidimensional concept that includes different aspects. Interest in the health conditions of the oldest-old has increased as a consequence of the phenomenon of population aging. This study investigates whether (1) it is possible to identify health profiles among the oldest-old, taking into account physical, emotional and psychological information about health, and (2) there are demographic and socioeconomic differences among the health profiles. Methods Latent Class Analysis with covariates was applied to the Mugello Study data to identify health profiles among the 504 nonagenarians residing in the Mugello district (Tuscany, Italy) and to evaluate the association between socioeconomic characteristics and the health profiles resulting from the analysis. Results This study highlights four groups labeled according to the posterior probability of determining a certain health characteristic: “healthy”, “physically healthy with cognitive impairment”, “unhealthy”, and “severely unhealthy”. Some demographic and socioeconomic characteristics were found to be associated with the final groups: older nonagenarians are more likely to be in worse health conditions; men are in general healthier than women; more educated individuals are less likely to be in extremely poor health conditions, while the lowest-educated are more likely to be cognitively impaired; and office or intellectual workers are less likely to be in poor health conditions than are farmers. Conclusions Considering multiple dimensions of health to determine health profiles among the oldest-old could help to better evaluate their care needs according to their health status. |
| abstract_unstemmed |
Background Health, as defined by the WHO, is a multidimensional concept that includes different aspects. Interest in the health conditions of the oldest-old has increased as a consequence of the phenomenon of population aging. This study investigates whether (1) it is possible to identify health profiles among the oldest-old, taking into account physical, emotional and psychological information about health, and (2) there are demographic and socioeconomic differences among the health profiles. Methods Latent Class Analysis with covariates was applied to the Mugello Study data to identify health profiles among the 504 nonagenarians residing in the Mugello district (Tuscany, Italy) and to evaluate the association between socioeconomic characteristics and the health profiles resulting from the analysis. Results This study highlights four groups labeled according to the posterior probability of determining a certain health characteristic: “healthy”, “physically healthy with cognitive impairment”, “unhealthy”, and “severely unhealthy”. Some demographic and socioeconomic characteristics were found to be associated with the final groups: older nonagenarians are more likely to be in worse health conditions; men are in general healthier than women; more educated individuals are less likely to be in extremely poor health conditions, while the lowest-educated are more likely to be cognitively impaired; and office or intellectual workers are less likely to be in poor health conditions than are farmers. Conclusions Considering multiple dimensions of health to determine health profiles among the oldest-old could help to better evaluate their care needs according to their health status. |
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Health profiles and socioeconomic characteristics of nonagenarians residing in Mugello, a rural area in Tuscany (Italy) |
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Pasqualetti, Patrizio Egidi, Viviana Loreti, Claudia Vannetti, Federica Macchi, Claudio Padua, Luca |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR040669513</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230519111152.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201007s2020 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1186/s12877-020-01689-3</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR040669513</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s12877-020-01689-3-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="q">ASE</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">44.00</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Strozza, Cosmo</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Health profiles and socioeconomic characteristics of nonagenarians residing in Mugello, a rural area in Tuscany (Italy)</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2020</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Background Health, as defined by the WHO, is a multidimensional concept that includes different aspects. Interest in the health conditions of the oldest-old has increased as a consequence of the phenomenon of population aging. This study investigates whether (1) it is possible to identify health profiles among the oldest-old, taking into account physical, emotional and psychological information about health, and (2) there are demographic and socioeconomic differences among the health profiles. Methods Latent Class Analysis with covariates was applied to the Mugello Study data to identify health profiles among the 504 nonagenarians residing in the Mugello district (Tuscany, Italy) and to evaluate the association between socioeconomic characteristics and the health profiles resulting from the analysis. Results This study highlights four groups labeled according to the posterior probability of determining a certain health characteristic: “healthy”, “physically healthy with cognitive impairment”, “unhealthy”, and “severely unhealthy”. Some demographic and socioeconomic characteristics were found to be associated with the final groups: older nonagenarians are more likely to be in worse health conditions; men are in general healthier than women; more educated individuals are less likely to be in extremely poor health conditions, while the lowest-educated are more likely to be cognitively impaired; and office or intellectual workers are less likely to be in poor health conditions than are farmers. 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