Data from the PASSI d’Argento Surveillance System on Difficulties Met by Older Adults in Accessing Health Services in Italy as Major Risk Factor to Health Outcomes
Abstract
:1. Introduction
2. Materials and Methods
2.1. Sampling and Data Collection Methods
2.2. Study Variables and Definitions
- Age: 65–74, 75–84, 85+ years;
- Gender: male, female;
- Education: low (none or elementary school), high (middle school or higher);
- Economic difficulties (in making ends meet with the available household financial resources): none, some, many;
- Geographic area: north, center, south and major islands;
- Living alone: yes, no.
- Respondents reporting difficulties to reach the LHU and GPs: some, many;
- One or more hospitalizations (lasting two days or more) in the last 12 months before the interview: yes, no;
- Chronic diseases (self-reported presence of diabetes, kidney failure, chronic bronchitis, emphysema, asthma, respiratory insufficiency, stroke, myocardial infarction, coronary and other heart diseases, tumors, chronic liver disease or cirrhosis): none, at least one.
2.3. Statistical Analysis
3. Results
3.1. Description of PdA 2016–2019 Respondents by Sociodemographic and Health Conditions in Association with the Presence of Chronic Diseases and Hospitalization
3.2. Association between Health Conditions and Access to Health Services with Presence of Chronic Diseases and Hospitalization
3.3. Which Is the Profile of Elderly Reporting Difficulties in Accessing Health Services?
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- World Health Organization. Global Issues—Ageing. Madrid International Plan of Action on Ageing. 2002. Available online: https://www.un.org/esa/socdev/documents/ageing/MIPAA/political-declaration-en.pdf (accessed on 11 August 2022).
- Special Senate Committee on Aging. Final Report. Canada’s Aging Population: Seizing the Opportunity. 2009. Available online: www.parl.gc.ca/Content/SeN/Committee/402/agei/rep/AgingFinalReport-e.pdf (accessed on 11 August 2022).
- Economic Commission for Europe. A Society for All Ages. Challenges and Opportunities. Report of the UNECE Ministerial Conference on Ageing. 2008. Available online: www.unece.org/index.php?id=10834 (accessed on 11 August 2022).
- Giannakouris, K. Ageing Characterises the Demographic Perspectives of the European Societies; Publications of the European Union: Luxembourg, 2008. [Google Scholar]
- Eurostat. Active Ageing and Solidarity between Generations. A Statistical Portrait of the European Union 2012. Available online: https://ec.europa.eu/eurostat/documents/3217494/5740649/KS-EP-11-001-EN.PDF/1f0b25f8-3c86-4f40-9376-c737b54c5fcf (accessed on 11 August 2022).
- European Parliament. Europe’s Population Decline: Problem or Opportunity? 2021. Available online: https://www.europarl.europa.eu/news/en/headlines/society/20210414STO02006/what-solutions-to-population-decline-in-europe-s-regions (accessed on 11 August 2022).
- World Health Organization. Fact Sheet: Non-Communicable Diseases. Available online: www.who.int/mediacentre/fact-sheets/fs355/en/ (accessed on 11 August 2022).
- Bousquet, J.; Anto, J.M.; Berkouk, K.; Gergen, P.; Antunes, J.P.; Augé, P.; Camuzat, T.; Bringer, J.; Mercier, J.; Best, N.; et al. Developmental determinants in non-communicable chronic diseases and ageing. Thorax 2015, 70, 595–597. [Google Scholar] [CrossRef] [PubMed]
- World Health Organization. Active Ageing: A Policy Framework. Available online: https://apps.who.int/iris/bitstream/handle/10665/67215/WHO_NMH_NPH_02.8.pdf;jsessionid=5EA11DE9E5B8545D3C579225C3189C85?sequence=1 (accessed on 11 August 2022).
- Paúl, C.; Ribeiro, O.; Teixeira, L. Active Ageing: An Empirical Approach to the WHO Model. Curr. Gerontol. Geriatr. Res. 2012, 2012, 382972. [Google Scholar] [CrossRef] [PubMed]
- Pearce, N.; Ebrahim, S.; McKee, M.; Lamptey, P.; Barreto, M.L.; Matheson, D.; Walls, H.; Foliaki, S.; Miranda, J.; Chimeddamba, O.; et al. The road to 25×25: How can the five-target strategy reach its goal? Lancet Glob. Health 2014, 2, e126–e128. [Google Scholar] [CrossRef]
- World Health Organization. Global Action Plan for Healthy Lives and Well-Being for All. Available online: https://www.who.int/initiatives/sdg3-global-action-plan (accessed on 11 August 2022).
- Stringhini, S.; Carmeli, C.; Jokela, M.; Avendano, M.; Muennig, P.; Guida, F.; Ricceri, F.; d’Errico, A.; Barros, H.; Bochud, M.; et al. Socioeconomic status and the 25 × 25 risk factors as determinants of premature mortality: A multicohort study and meta-analysis of 1·7 million men and women. Lancet 2017, 389, 1229–1237. [Google Scholar] [CrossRef]
- Istituto Nazionale di Statistica. Previsioni della Popolazione over 65 all’anno 2050. Popolazione per età. Available online: https://demo.istat.it/previsioni2017/index.php?lingua=ita (accessed on 11 August 2022).
- Contoli, B.; Carrieri, P.; Masocco, M.; Penna, L.; Perra, A. PASSI d’Argento (Silver Steps): The main features of the new nationwide surveillance system for the ageing Italian population, Italy 2013-2014. Ann. Ist. Super. Sanita 2016, 52, 536–542. [Google Scholar] [CrossRef]
- EpiCentro. La Sorveglianza PASSI d’Argento. Available online: https://www.epicentro.iss.it/passi-argento/ (accessed on 7 July 2022).
- Contoli, B.; Ferrelli, R.M.; Antoniotti, M.C.; Baldi, A.; Bianco, E.; Biscaglia, L.; Carrozzi, G.; Chiti, L.; Cristofori, M.; De Luca, A.M.C.; et al. L’anziano “Risorsa” nel Sistema di Sorveglianza PASSI d’Argento, 2010 (The over 65s as “Resource” for Their Family and Community, from the National Surveillance System, Italy 2010). Not Ist Super Sanità—Inserto BEN 2012, 25, 3–4. Available online: https://www.iss.it/documents/20126/45616/ONLINEmag2012.pdf/b139f485-ca29-0f7f-34f1-b6484fa62f1b?t=1581101054997 (accessed on 11 August 2022).
- Possenti, V.; Minardi, V.; Contoli, B.; Gallo, R.; Lana, S.; Bertozzi, N.; Campostrini, S.; Carrozzi, G.; Cristofori, M.; D’Argenzio, A.; et al. The two behavioural risk factor surveillances on the adult and elderly populations as information systems for leveraging data on health-related sustainable development goals in Italy. Int. J. Med. Inform. 2021, 152, 104443. [Google Scholar] [CrossRef]
- Contoli, B.; Possenti, V.; Minardi, V.; Binkin, N.J.; Ramigni, M.; Carrozzi, G.; Masocco, M. What Is the Willingness to Receive Vaccination Against COVID-19 Among the Elderly in Italy? Data From the PASSI d’Argento Surveillance System. Front. Public Health 2021, 9, 1643. [Google Scholar] [CrossRef]
- Nobile, F.; Gallo, R.; Minardi, V.; Contoli, B.; Possenti, V.; Masocco, M. Urban Health at a Glance in Italy by Passi and Passi d’Argento Surveillance Systems Data. Sustainability 2022, 14, 5931. [Google Scholar] [CrossRef]
- American Association for Public Opinion Research. Standard Definitions: Final Dispositions of Case Codes and Outcome Rates for Surveys, 9th ed.; The American Association for Public Opinion Research: Alexandria, VA, USA, 2016; Available online: https://www.aapor.org/AAPOR_Main/media/publications/Standard-Definitions20169theditionfinal.pdf (accessed on 7 July 2022).
- Folstein, M.F.; Folstein, S.E.; McHugh, P.R. “Mini-Mental State”. A Practical Method for Grading the Cognitive State of Patients for the Clinician. J. Psychiatr. Res. 1975, 12, 189–198. [Google Scholar] [CrossRef]
- Washburn, R.A.; Smith, K.W.; Jette, A.M.; Janney, C.A. The physical activity scale for the elderly (PASE): Development and evaluation. J. Clin. Epidemiol. 1993, 46, 153–162. [Google Scholar] [CrossRef]
- Washburn, R.A.; McAuley, E.; Katula, J.; Mihalko, S.L.; Boileau, R.A. The Physical Activity Scale for the Elderly (PASE): Evidence for Validity. J. Clin. Epidemiol. 1999, 52, 643–651. [Google Scholar] [CrossRef]
- Barros, A.J.D.; Hirakata, V.N.; Barros, A.J.D.; Hirakata, V.N. Alternatives for logistic regression in cross-sectional studies: An empirical comparison of models that directly estimate the prevalence ratio. BMC Med. Res. Methodol. 2003, 3, 21. [Google Scholar] [CrossRef] [PubMed]
- StataCorp. Stata Statistical Software 17; StataCorp LP: College Station, TX, USA, 2019. [Google Scholar]
- Bindman, A.B.; Grumbach, K.; Osmond, D.; Komaromy, M.; Vranizan, K.; Lurie, N.; Billings, J.; Stewart, A. Preventable Hospitalizations and Access to Health Care. JAMA 1995, 274, 305–311. [Google Scholar] [CrossRef] [PubMed]
- Rizza, P.; Bianco, A.; Pavia, M.; Angelillo, I.F. Preventable hospitalization and access to primary health care in an area of Southern Italy. BMC Health Serv. Res. 2007, 7, 134. [Google Scholar] [CrossRef]
- Lesser, S.; Zakharkin, S.; Louie, C.; Escobedo, M.R.; Whyte, J.; Fulmer, T. Clinician knowledge and behaviors related to the 4Ms framework of Age-Friendly Health Systems. J. Am. Geriatr. Soc. 2021, 70, 789–800. [Google Scholar] [CrossRef]
- World Health Organization. Global Age-Friendly Cities: A Guide. 2007. Available online: https://apps.who.int/iris/handle/10665/43755 (accessed on 7 July 2022).
- Cacchione, P.Z. Age-Friendly Health Systems: The 4Ms Framework. Clin. Nurs. Res. 2020, 29, 139–140. [Google Scholar] [CrossRef]
- Hamiduzzaman, M.; De-Bellis, A.; Abigail, W.; Fletcher, A. Critical social framework on the determinants of primary healthcare access and utilisation. Fam. Med. Community Health 2021, 9, e001031. [Google Scholar] [CrossRef]
- Ethier, A. A Scoping Review of the Implementation of Local Health and Social Services for Older Adults. Healthc. Policy 2021, 17, 105–118. [Google Scholar] [CrossRef]
- Cu, A.; Meister, S.; Lefebvre, B.; Ridde, V. Assessing healthcare access using the Levesque’s conceptual framework—A scoping review. Int. J. Equity Health 2021, 20, 116. [Google Scholar] [CrossRef]
- Verma, I.; Taegen, J. Ageing and Inclusion in Rural Areas. Stud. Health Technol. Inform. 2021, 282, 348–357. [Google Scholar] [CrossRef] [PubMed]
- Hamano, T.; Tominaga, K.; Takeda, M.; Sundquist, K.; Nabika, T. Accessible Transportation, Geographic Elevation, and Masticatory Ability among Elderly Residents of a Rural Area. Int. J. Environ. Res. Public Health 2015, 12, 7199–7207. [Google Scholar] [CrossRef] [PubMed]
- Zhang, T.; Liu, C.; Ni, Z. Association of Access to Healthcare with Self-Assessed Health and Quality of Life among Old Adults with Chronic Disease in China: Urban Versus Rural Populations. Int. J. Environ. Res. Public Health 2019, 16, 2592. [Google Scholar] [CrossRef] [PubMed]
- Tiilikainen, E.; Hujala, A.; Kannasoja, S.; Rissanen, S.; Närhi, K. “They’re always in a hurry”—Older people’s perceptions of access and recognition in health and social care services. Health Soc. Care Community 2018, 27, 1011–1018. [Google Scholar] [CrossRef] [PubMed]
- Kehusmaa, S.; Autti-Rämö, I.; Helenius, H.; Hinkka, K.; Valaste, M.; Rissanen, P. Factors associated with the utilization and costs of health and social services in frail elderly patients. BMC Health Serv. Res. 2012, 12, 204. [Google Scholar] [CrossRef]
- PASSI and PASSI d’Argento National Working Group. PASSI and PASSI d’Argento and COVID-19 Pandemic. First National Report on Results from the COVID Module. Rome: Istituto Superiore di Sanità. 2020. Available online: https://www.epicentro.iss.it/passi-argento/pdf2020/PASSI-PdA-COVID19-first-national-report-december-2020.pdf (accessed on 7 July 2022).
Distribution of Sample | At Least One Chronic Disease | At Least Two Chronic Diseases | At Least One Hospitalization 1 | ||||||
---|---|---|---|---|---|---|---|---|---|
N = 45,514 | N = 25,883 | N = 9765 | N = 6455 | ||||||
% | CI 95% | % | CI 95% | % | CI 95% | % | CI 95% | ||
Total | 57 | (55.9–57.5) | 21 | (20.7–22.0) | 13 | (12.7–13.7) | |||
Gender | Male | 44 | (43.1–44.4) | 46 | (44.8–46.9) | 46 | (44.3–48.3) | 45 | (43.1–47.3) |
Female | 56 | (55.6–56.9) | 54 | (53.1–55.2) | 54 | (51.7–55.7) | 55 | (52.7–56.9) | |
Age group | 65–74 | 57 | (56.5–57.8) | 51 | (49.8–51.8) | 45 | (42.7–46.7) | 50 | (47.8–51.9) |
75–84 | 35 | (34.2–35.4) | 39 | (38.2–40.2) | 43 | (41.3–45.2) | 39 | (37.4–41.4) | |
85+ | 8 | (7–8–8.4) | 10 | (9.4–10.6) | 12 | (11.0–13.2) | 11 | (9.6–12-1) | |
Educational level | Low | 43 | (42.4–43.9) | 47 | (45.5–47.7) | 51 | (49.0–53.1) | 46 | (43.7–47.9) |
High | 57 | (56.1–57.6) | 53 | (52.3–54.5) | 49 | (46.9–51.0) | 54 | (52.1–56.3) | |
Economic difficulties | Yes | 48 | (46.8–48.4) | 54 | (53.2–55.4) | 62 | (60.0–63.8) | 46 | (43.8–48.0) |
No | 52 | (51.7–53.3) | 46 | (44.62–46.8) | 38 | 36.2–40.1 | 54 | (52.0–56.2) | |
Difficulties in accessing 1+ health services | Yes | 23 | (22.3–23.6) | 30 | (29.1–31.2) | 39 | (36.8–40.8) | 36 | (34.2–38.5) |
No | 77 | (76.4–77.7) | 70 | (68.8–70.9) | 61 | (59.2–63.2) | 64 | (61.5–65.8) | |
Living alone | Yes | 22 | (20.9–22.2) | 22 | (20.7–22.5) | 22 | (20.4–23.7) | 23 | (20.9–24.3) |
No | 79 | (77.9–79.1) | 78 | (77.5–79.1) | 78 | (76.3–79.6) | 77 | (75.7–79.1) | |
Geographic area of residence | North | 39 | (38.2–39.7) | 37 | (36.4–38.6) | 35 | (32.8–36.8) | 40 | (37.8–41.9) |
Center | 20 | (20.1–20.8) | 20 | (19.1–20.6) | 20 | (18.4–21.5) | 21 | (19.0–22.2) | |
South | 41 | (39.9–41.2) | 43 | (41.7–43.7) | 45 | (43.4–47.3) | 40 | (37.7–41.7) | |
Sedentary behavior | Yes | 40 | (39.3–40.8) | 44 | (42.8–45.2) | 47 | (44.8–49.4) | 54 | (54.3–60.3) |
No | 60 | (59.2–60.8) | 56 | (54.8–57.2) | 53 | (50.6–55.2) | 46 | (38.7–45.7) | |
Tobacco smoking | Yes | 11 | (10.5–11.4) | 12 | (10.9–12.4) | 12 | (10.9–14.3) | 11 | (9.7–13.3) |
Former smoker | 28 | (27.4–28.7) | 31 | (29.8–31.7) | 32 | (29.8–33.4) | 31 | (29.6–33.3) | |
No | 61 | (60.3–61.8) | 58 | (56.6–58.7) | 56 | (53.9–57.9) | 57 | (55.2–59.4) | |
At-risk alcohol consumption | Yes | 21 | (20.0–21.3) | 21 | (19.7–21.5) | 19 | (17.0–20.5) | 19 | (17.5–21.4) |
No | 79 | (78.8–80.0) | 80 | (78.6–80.4) | 81 | (79.5–83.0) | 81 | (78.6–82.5) | |
Diabetes | Yes | 18 | (17.9–19.1) | 21 | (20.6–22.4) | 27 | (25.1–29.0) | 23 | (20.6–24.6) |
No | 82 | (80.9–82.2) | 79 | (77.6–79.4) | 73 | (71.0–74.9) | 77 | (75.4–79.4) | |
Hypertension | Yes | 59 | (58.1–59.6) | 65 | (64.2–66.3) | 65 | (64.2–66.3) | 63 | (61.0–65.0) |
No | 41 | (40.4–41.9) | 35 | (33.7–35.8) | 35 | (33.7–35.8) | 37 | (35.0–39.0) | |
Obesity | Yes | 14 | (13.4–14.5) | 16 | (15.4–17.0) | 19 | (17.6–20.7) | 17 | (15.1–18.2) |
No | 86 | (85.5–86.6) | 84 | (83.0–84.6) | 81 | (79.3–82.4) | 83 | (81.8–84.9) |
Health Outcomes | |||||||
---|---|---|---|---|---|---|---|
At Least One Chronic Disease | At Least Two Chronic Diseases | At Least One Hospitalization 1 | |||||
aPR | CI 95% | aPR | CI 95% | aPR | CI 95% | ||
Sedentary behavior | 1.08 | (1.04–1.12) | 1.10 | (1.01–1.21) | 1.20 | (1.09–1.31) | |
Models | Difficulties in accessing 1+ health services | 1.26 | (1.21–1.32) | 1.60 | (1.43–1.79) | 1.62 | (1.43–1.83) |
Tobacco smoking | |||||||
Former smoker (vs. never smoker) | 1.20 | (1.14–1.26) | 1.37 | (1.26–1.49) | 1.24 | (1.13–1.36) | |
Current smoker (vs. never smoker) | 1.20 | (1.16–1.25) | 1.43 | (1.26–1.63) | 1.19 | (1.02–1.38) | |
Difficulties in accessing 1+ health services | 1.33 | (1.28–1.38) | 1.78 | (1.61–1.95) | 1.95 | (1.76–2.16) | |
At-risk alcohol consumption (vs. no drinking) | 1.01 | (0.97–1.05) | 0.93 | (0.83–1.03) | 0.94 | (0.84–1.06) | |
Difficulties in accessing 1+ health services | 1.32 | (1.27–1.37) | 1.75 | (1.59–1.93) | 1.93 | (1.73–2.14) | |
Diabetes | 1.13 | (1.08–1.17) | 1.43 | (1.31–1.55) | 1.19 | (1.08–1.31) | |
Difficulties in accessing 1+ health services | 1.31 | (1.26–1.36) | 1.70 | (1.55–1.87) | 1.91 | (1.73–2.12) | |
Hypertension | 1.25 | (1.21–1.29) | 1.50 | (1.39–1.63) | 1.12 | (1.03–1.21) | |
Difficulties in accessing 1+ health services | 1.30 | (1.25–1.35) | 1.70 | (1.55–1.87) | 1.92 | (1.73–2.13) | |
Obesity | 1.16 | (1.11–1.21) | 1.38 | (1.25–1.52) | 1.19 | (1.07–1.32) | |
Difficulties in accessing 1+ health services | 1.31 | (1.26–1.37) | 1.74 | (1.57–1.93) | 1.95 | (1.75–2.17) |
Distribution of Sample | Elderly Reporting Difficulties in Accessing Health Services | ||||||
---|---|---|---|---|---|---|---|
N = 45,514 | |||||||
% | CI 95% | % | CI 95% | aPR | CI 95% | ||
Total | 57 | (55.9–57.5) | |||||
Gender | Male | 44 | (43.1–44.4) | 29 | (27.2–30.2) | 1 | - |
Female | 56 | (55.6–56.9) | 71 | (69.8–72.8) | 1.692 | (1.575–1.818) | |
Age group | 65–74 | 57 | (56.5–57.8) | 38 | (36.4–39.4) | 1 | - |
75–84 | 35 | (34.2–35.4) | 45 | (43.7–46.6) | 1.782 | (1.665–1.906) | |
85+ | 8 | (7.8–8.4) | 17 | (16.1–18.0) | 2.923 | (2.699–3.165) | |
Educational level | Low | 43 | (42.4–43.9) | 62 | (60.0–63.4) | 1.391 | (1.303–1.484) |
High | 57 | (56.1–57.6) | 38 | (36.6–40.0) | 1 | - | |
Economic difficulties | Any | 10 | (9.7–10.6) | 20 | (18.6–21.29) | 1 | - |
Some | 37 | (36.6–38.2) | 50 | (48.3–51.8) | 1.732 | (1.605–1.869) | |
Many | 52 | (51.7–53.3) | 30 | (28.5–31.6) | 2.154 | (1.975–2.350) | |
Living alone | Yes | 22 | (20.9–22.2) | 25 | (24.0–26.8) | 0.966 | (0.906–1.029) |
No | 79 | (77.9–79.1) | 75 | (73.2–76.0) | 1 | - | |
Geographic area of residence | North | 39 | (38.2–39.7) | 25 | (23.5–26.3) | 1 | - |
Center | 20 | (20.1–20.8) | 19 | (17.7–19.9) | 1.374 | (1.251–1.510) | |
South | 41 | (39.9–41.2) | 56 | (54.8–57.8) | 1.856 | (1.711–2.013) | |
Safe neighborhood | Yes | 86 | (85.2–86.4) | 80 | (78.1–81.2) | 1 | - |
No | 14 | (13.6–14.8) | 20 | (18.8–21.9) | 1.243 | (1.146–1.347) | |
Structural problems in the house 1 | Yes | 62 | (61.2–62.7) | 72 | (70.4–73.4) | 1.127 | (1.055–1.205) |
No | 38 | (37.3–38.9) | 28 | (26.6–29.6) | 1 | - |
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Contoli, B.; Possenti, V.; Gallo, R.; Minardi, V.; Masocco, M. Data from the PASSI d’Argento Surveillance System on Difficulties Met by Older Adults in Accessing Health Services in Italy as Major Risk Factor to Health Outcomes. Int. J. Environ. Res. Public Health 2022, 19, 10340. https://doi.org/10.3390/ijerph191610340
Contoli B, Possenti V, Gallo R, Minardi V, Masocco M. Data from the PASSI d’Argento Surveillance System on Difficulties Met by Older Adults in Accessing Health Services in Italy as Major Risk Factor to Health Outcomes. International Journal of Environmental Research and Public Health. 2022; 19(16):10340. https://doi.org/10.3390/ijerph191610340
Chicago/Turabian StyleContoli, Benedetta, Valentina Possenti, Rosaria Gallo, Valentina Minardi, and Maria Masocco. 2022. "Data from the PASSI d’Argento Surveillance System on Difficulties Met by Older Adults in Accessing Health Services in Italy as Major Risk Factor to Health Outcomes" International Journal of Environmental Research and Public Health 19, no. 16: 10340. https://doi.org/10.3390/ijerph191610340