Fall-related admission and mortality in older adults in Brazil: trend analysis

Abreu, Débora Regina de Oliveira Moura; Novaes, Elisiane Soares; Oliveira, Rosana Rosseto de; Mathias, Thais Aidar de Freitas; Marcon, Sonia Silva

doi:10.1590/1413-81232018234.09962016

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Article • Ciênc. saúde colet. 23 (4) • Apr 2018 • https://doi.org/10.1590/1413-81232018234.09962016 copy

Fall-related admission and mortality in older adults in Brazil: trend analysis

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract

Objective:

To analyze the trend of fall-related morbidity and mortality in older adults in Brazil from 1996 to 2012.

Method:

This is an ecological study of fall-related admission and mortality rate trends in older adults by gender, Brazilian regions, and Brazilian state capitals using data from the Hospital Information System of the Unified Healthcare System (SIH-SUS) and from the National Mortality Information System (SIM). Trend analyses were based on polynomial regression models.

Results:

Mortality rates increased in all regions and state capitals, and admission trends varied in regions and state capitals. The admission rates in 1996 and 2012 were 2.58 and 41.37 per 10,000 older adults, respectively, and the mortality rates per 10,000 older adults increased from 1.25 in 1996 to 3.75 in 2012. Males mortality rates were higher during the entire period.

Conclusion:

Fall-related mortality and admission rates increased in Brazil but varied by gender and state of residence. The results of this study do not only monitor the problem over time but may also help plan technological and human resources to prevent and control falls.

Key words
Accidental falls; Older adult; Mortality; Hospitalization; Time Series Studies

Location		Mortality rate
Location		Model	R²	p	Trend^* * ↑ Increasing; ↓ Decreasing; - Stable; ↑/↓ Increasing/Decreasing; ↓/↑ Decreasing/Increasing.
Brazil		$y = 2.28 + 0.15 x$	0.96	< 0.001	↑
Northern Region		$y = 2.41 + 0.13 x$	0.92	< 0.001	↑
	Rio Branco	$y = 1.83 + 0.27 x$	0.80	< 0.001	↑
	Manaus	$y = 2.47 + 0.15 x$	0.66	< 0.001	↑
	Boa Vista	$y = 1.41 + 0.06 x$	0.10	0.244	–
	Belém	$y = 2.58 + 0.09 x$	0.60	0.001	↑
	Macapá	$y = 1.12 - 0.01 x$	0.00	0.819	–
	Porto Velho	$y = 3.45 + 0.26 x$	0.58	0.001	↑
	Palmas	$y = 2.45 + 0.20 x$	0.35	0.020	↑
Northreastern Region		$y = 2.21 + 0.12 x$	0.85	< 0.001	↑
	São Luís	$y = 3.46 + 0.40 x - 0.01 x 2 - 0.004 x^{3}$	0.95	< 0.001	↑
	Teresina	$y = 1.88 + 0.12 x$	0.68	< 0.001	↑
	Fortaleza	$y = 1.77 + 0.14 x$	0.83	< 0.001	↑
	Natal	$y = 0.79 - 0.11 x + 0.01 x 2 + 0.003 x^{3}$	0.57	0.006	↓/↑
	João Pessoa	$y = 1.85 + 0.18 x$	0.88	< 0.001	↑
	Recife	$y = 2.60 - 0.04 x + 0.01 x^{2}$	0.46	0.010	↓/↑
	Salvador	$y = 2.05 + 0.20 x$	0.56	0.001	↑
	Maceió	$y = 2.61 + 0.05 x + 0.01 x^{2}$	0.37	0.024	↑
	Aracajú	$y = 3.82 + 0.19 x - 0.04 x^{2}$	0.71	< 0.001	↑
Southeastern Region		$y = 2.98 + 0.06 x + 0.01 x^{2}$	0.83	< 0.001	↓/↑
	Belo Horizonte	$y = 1.66 + 0.08 x + 0.03 x^{2}$	0.82	< 0.001	↑
	Vitória	$y = 7.15 + 0.09 x$	0.44	0.007	↑
	Rio de Janeiro	$y = 3.29 - 0.16 x + 0.008 x 2 + 0.003 x^{3}$	0.65	0.002	↓
	São Paulo	$y = 2.92 + 0.27 x + 0.02 x 2 - 0.004 x^{3}$	0.83	< 0.001	↑
Southern Region		$y = 3.77 + 0.26 x$	0.88	< 0.001	↑
	Curitiba	$y = 4.66 + 0.41 x$	0.88	< 0.001	↑
	Florianópolis	$y = 0.82 + 0.26 x + 0.06 x^{2}$	0.91	< 0.001	↑
	Porto Alegre	$y = 3.31 + 0.12 x$	0.71	< 0.001	↑
Midwestern Region		$y = 4.70 + 0.32 x$	0.91	< 0.001	↑
	Campo Grande	$y = 3.51 + 0.42 x$	0.93	< 0.001	↑
	Cuiabá	$y = 3.37 + 0.47 x$	0.88	< 0.001	↑
	Goiânia	$y = 4.44 + 0.033 x$	0.96	< 0.001	↑
	Brasília	$y = 5.73 + 0.23 x$	0.62	0.001	↑
Brazil		$y = 39.02 - 0.81 x - 0.23 x 2 + 0.05 x^{3}$	0.91	< 0.001	↓/↑
Northern Region		$y = 25.14 - 1.99 x$	0.48	0.004	↓
	Rio Branco	$y = 58.93 - 3.32 x - 0.50 x 2 + 0.11 x^{3}$	0.62	0.003	↓
	Manaus	$y = 13.10 - 1.78 x$	0.63	< 0.001	↓
	Boa Vista	$y = 25.50 + 1.46 x - 0.23 x^{2}$	0.83	< 0.001	↑
	Belém	$y = 27.90 - 4.07 x$	0.63	< 0.001	↓
	Macapá	$y = 22.67 + 1.50 x$	0.61	0.001	↑
	Porto Velho	$y = 22.20 - 0.61 x$	0.26	0.054	–
	Palmas	$y = 84.46 + 7.08 x$	0.24	0.065	–
Northreastern Region		$y = 24.83 + 0.93 x$	0.60	0.001	↑
	São Luís	$y = 14.68 - 1.60 x + 0.22x 2 + 0.06 x^{3}$	0.57	0.006	↓/↑
	Teresina	$y = 30.06 + 3.32 x$	0.93	< 0.001	↑
	Fortaleza	$y = 37.07 + 1.19 x$	0.51	0.003	↑
	Natal	$y = 36.43 + 2.89 x$	0.64	< 0.001	↑
	João Pessoa	$y = 29.01 + 1.48 x$	0.71	< 0.001	↑
	Recife	$y = 3.59 + 0.22 x$	0.37	0.016	↑
	Salvador	$y = 25.91 - 0.76 x - 0.18 x 2 + 0.03 x^{3}$	0.85	< 0.001	↓
	Maceió	$y = 28.63 + 0.83 x - 0.33 x^{2}$	0.84	< 0.001	↑
	Aracajú	$y = 41.06 - 0.81 x$	0.12	0.204	–
Southeastern Region		$y = 39.78 + 1.59 x - 0.28 x^{2}$	0.89	< 0.001	↑
	Belo Horizonte	$y = 50.17 + 0.02 x$	0.00	0.983	–
	Vitória	$y = 44.43 - 1.04 x - 0.61 x^{2}$	0.70	< 0.001	↑/↓
	Rio de Janeiro	$y = 21.60 + 0.89 x - 0.22 x^{2}$	0.82	< 0.001	↑
	São Paulo	$y = 42.19 + 2.43 x$	0.81	< 0.001	↑
Southern Region		$y = 33.81 - 2.26 x - 0.18 x 2 + 0.07 x^{3}$	0.85	< 0.001	↓/↑
	Curitiba	$y = 14.38 - 0.94 x$	0.50	0.003	↓
	Florianópolis	$y = 47.73 + 1.61 x - 0.28 x^{2}$	0.84	< 0.001	↑
	Porto Alegre	$y = 49.22 - 2.26 x - 0.30 x 2 + 0.10 x^{3}$	0.93	< 0.001	↓/↑
Midwestern Region		$y = 42.08 - 1.49 x - 0.36 x 2 + 0.07 x^{3}$	0.94	< 0.001	↑/↓/↑
	Campo Grande	$y = 12.11 + 0.13 x$	0.03	0.558	–
	Cuiabá	$y = 44.13 + 1.22 x - 0.55 x^{2}$	0.84	< 0.001	↑
	Goiânia	$y = 58.72 - 4.49 x - 0.65 x 2 + 0.14 x^{3}$	0.93	< 0.001	↑/↓
	Brasília	$y = 37.82 + 1.50 x$	0.53	0.002	↑

Location		Male
Location		Model	R²	p	Trend^* * ↑ Increasing; ↓ Decreasing; - Stable; ↓/↑ Decreasing/Increasing.
Brazil		$y = 2.59 + 0.16 x$	0.97	< 0.001	↑
Northern Region		$y = 2.88 + 0.16 x$	0.91	< 0.001	↑
	Rio Branco	$y = 2.19 + 0.35 x$	0.83	< 0.001	↑
	Manaus	$y = 3.39 + 0.19 x$	0.65	< 0.001	↑
	Boa Vista	$y = 1.92 - 0.02 x$	0.01	0.730	–
	Belém	$y = 2.52 + 0.11 x$	0.54	0.002	↑
	Macapá	$y = 1.56 + 0.002 x$	0.00	0.980	–
	Porto Velho	$y = 4.92 + 0.24 x$	0.32	0.028	↑
	Palmas	$y = 2.49 + 0.28 x$	0.37	0.016	↑
Northeastern Region		$y = 2.65 + 0.15 x$	0.85	< 0.001	↑
	São Luís	$y = 3.40 + 0.48 x - 0.03 x 2 - 0.01 x^{3}$	0.92	< 0.001	↑
	Teresina	$y = 2.26 + 0.09 x$	0.38	0.014	↑
	Fortaleza	$y = 2.30 + 0.19 x$	0.78	< 0.001	↑
	Natal	$y = 1.41 - 0.02 x$	0.04	0.453	–
	João Pessoa	$y = 2.55 + 0.22 x$	0.86	< 0.001	↑
	Recife	$y = 3.33 - 0.01 x$	0.01	0.680	–
	Salvador	$y = 2.57 + 0.26 x$	0.64	< 0.001	↑
	Maceió	$y = 3.28 + 0.07 x$	0.22	0.075	–
	Aracajú	$y = 4.99 + 0.24 x - 0.07 x^{2}$	0.83	< 0.001	↑
Southeastern Region		$y = 3.76 + 0.10 x + 0.02 x^{2}$	0.88	< 0.001	↑
	Belo Horizonte	$y = 2.51 + 0.14 x + 0.03 x^{2}$	0.84	< 0.001	↑
	Vitória	$y = 90.01 + 0.10 x$	0.21	0.082	–
	Rio de Janeiro	$y = 3.77 - 0.014 x + 0.01 x 2 + 0.004 x^{3}$	0.67	0.001	↓/↑
	São Paulo	$y = 3.88 + 0.034 x + 0.02 x 2 - 0.005 x^{3}$	0.85	< 0.001	↑
Southern Region		$y = 3.82 + 0.26 x$	0.92	< 0.001	↑
	Curitiba	$y = 4.61 + 0.32 x$	0.82	< 0.001	↑
	Florianópolis	$y = 0.98 + 0.24 x + 0.06 x^{2}$	0.86	< 0.001	↑
	Porto Alegre	$y = 3.40 + 0.20 x$	0.76	< 0.001	↑
Midwestern Region		$y = 5.08 + 0.29 x$	0.90	< 0.001	↑
	Campo Grande	$y = 4.08 + 0.62 x - 0.02 x 2 - 0.01 x^{3}$	0.95	< 0.001	↑
	Cuiabá	$y = 3.68 + 0.40 x$	0.75	< 0.001	↑
	Goiânia	$y = 4.84 + 0.38 x$	0.96	< 0.001	↑
	Brasília	$y = 6.21 + 0.15 x$	0.37	0.016	↑
Brazil		$y = 2.02 + 0.15 x$	0.95	< 0.001	↑
Northern Region		$y = 2.06 + 0.11 x$	0.88	< 0.001	↑
	Rio Branco	$y = 1.50 + 0.20 x$	0.49	0.004	↑
	Manaus	$y = 1.76 + 0.12 x$	0.54	0.002	↑
	Boa Vista	$y = 0.91 + 0.15 x$	0.54	0.002	↑
	Belém	$y = 2.61 + 0.07 x$	0.49	0.003	↑
	Macapá	$y = 0.57 - 0.03 x$	0.03	0.519	-
	Porto Velho	$y = 2.01 + 0.28 x$	0.72	< 0.001	↑
	Palmas	$y = 2.50 + 0.12 x$	0.13	0.191	–
Northeastern Region		$y = 1.93 + 0.10 x$	0.81	< 0.001	↑
	São Luís	$y = 3.42 + 0.29 x$	0.90	< 0.001	↑
	Teresina	$y = 1.61 + 0.14 x$	0.68	< 0.001	↑
	Fortaleza	$y = 1.42 + 0.11 x$	0.68	< 0.001	↑
	Natal	$y = 0.61 - 0.16 x + 0.01 x 2 + 0.005 x^{3}$	0.69	0.004	↓/↑
	João Pessoa	$y = 1.40 + 0.16 x$	0.83	< 0.001	↑
	Recife	$y = 2.19 - 0.05 x + 0.02 x 2$	0.75	< 0.001	↓/↑
	Salvador	$y = 1.73 + 0.17 x$	0.46	0.006	↑
	Maceió	$y = 2.57 + 0.03 x$	0.05	0.402	–
	Aracajú	$y = 2.78 + 0.15 x$	0.45	0.006	↑
Southeastern Region		$y = 2.47 + 0.04 x + 0.01 x^{2}$	0.73	< 0.001	↓/↑
	Belo Horizonte	$y = 1.61 + 0.04 x$	0.10	0.253	–
	Vitória	$y = 5.86 + 0.09 x$	0.43	0.008	↑
	Rio de Janeiro	$y = 3.07 - 0.06 x$	0.45	0.006	↓
	São Paulo	$y = 2.27 + 0.23 x + 0.01 x 2 - 0.004 x^{3}$	0.79	< 0.001	↑
Southern Region		$y = 3.74 + 0.26 x$	0.83	< 0.001	↑
	Curitiba	$y = 4.70 + 0.48 x$	0.89	< 0.001	↑
	Florianópolis	$y = 0.70 + 0.28 x + 0.06 x 2$	0.89	< 0.001	↑
	Porto Alegre	$y = 3.26 + 0.07 x$	0.32	0.027	↑
Midwestern Region		$y = 4.40 + 0.35 x$	0.92	< 0.001	↑
	Campo Grande	$y = 3.30 + 0.48 x$	0.92	< 0.001	↑
	Cuiabá	$y = 3.11 + 0.53 x$	0.91	< 0.001	↑
	Goiânia	$y = 4.15 + 0.29 x$	0.90	< 0.001	↑
	Brasília	$y = 5.88 + 0.57 x - 0.03 x 2 - 0.01 x^{3}$	0.86	< 0.001	↑

Location		Male
Location		Model	R²	p	Trend^* * ↑ Increasing; ↓ Decreasing; - Stable; ↓/↑ Decreasing/Increasing.
Brazil		$y = 34.87 + 0.93 x - 0.21 x^{2}$	0.67	0.001	↑
Northern Region		$y = 26.12 - 1.61 x$	0.43	0.008	↓
	Rio Branco	$y = 51.72 + 0.29 x$	0.01	0.761	–
	Manaus	$y = 13.08 - 1.96 x$	0.68	< 0.001	↓
	Boa Vista	$y = 26.19 + 1.82 x - 0.23 x^{2}$	0.76	< 0.001	↑
	Belém	$y = 28.51 - 3.40 x$	0.62	< 0.001	↓
	Macapá	$y = 27.18 + 1.63 x$	0.65	< 0.001	↑
	Porto Velho	$y = 21.30 - 0.73 x$	0.32	0.028	↓
	Palmas	$y = 94.42 + 9.91 x$	0.30	0.035	↑
Northeastern Region		$y = 22.55 + 0.81 x$	0.61	0.001	↑
	São Luís	$y = 22.60 + 0.52 x$	0.08	0.294	–
	Teresina	$y = 30.32 + 3.16 x$	0.92	< 0.001	↑
	Fortaleza	$y = 32.24 + 0.91 x - 0.14 x^{2}$	0.58	0.002	↑
	Natal	$y = 39.61 + 2.28 x - 0.44 x^{2}$	0.89	< 0.001	↑
	João Pessoa	$y = 24.87 + 0.92 x$	0.44	0.007	↑
	Recife	$y = 2.89 + 0.12 x$	0.21	0.088	–
	Salvador	$y = 25.64 + 0.40 x - 0.12 x^{2}$	0.60	0.002	↑
	Maceió	$y = 16.44 + 057 x$	0.30	0.036	↑
	Aracajú	$y = 37.84 - 1.03 x$	0.17	0.121	–
Southeastern Region		$y = 30.85 + 1.58 x$	0.67	< 0.001	↑
	Belo Horizonte	$y = 50.01 - 0.02 x$	0.00	0.981	–
	Vitória	$y = 47.53 - 1.12 x - 0.60 x^{2}$	0.74	< 0.001	↑/↓
	Rio de Janeiro	$y = 15.27 + 0.79 x$	0.53	0.002	↑
	São Paulo	$y = 38.14 + 2.46 x$	0.86	< 0.001	↑
Southern Region		$y = 28.65 - 2.08 x - 0.16 x 2 + 0.63 x^{3}$	0.83	< 0.001	↓/↑
	Curitiba	$y = 12.43 - 0.73 x$	0.50	0.003	↓
	Florianópolis	$y = 30.83 + 1.51 x$	0.55	0.001	↑
	Porto Alegre	$y = 42.54 - 2.49 x - 0.87 x 2 + 0.09 x^{3}$	0.87	< 0.001	↓/↑
Midwestern Region		$y = 43.36 - 1.61 x - 0.38 x 2 + 0.08 x^{3}$	0.96	< 0.001	↑/↓/↑
	Campo Grande	$y = 12.10 - 0.01 x$	0.00	0.972	–
	Cuiabá	$y = 46.45 + 1.13 x - 0.62 x^{2}$	0.81	< 0.001	↑/↓
	Goiânia	$y = 62.26 - 5.18 x - 0.69 x 2 + 0.16 x^{3}$	0.95	< 0.001	↑/↓
	Brasília	$y = 38.60 + 1.82 x$	0.63	< 0.001	↑
Brazil		$y = 42.41 + 1.04 x - 0.25 x^{2}$	0.62	0.001	↑
Northern Region		$y = 24.42 - 2.28 x$	0.51	0.003	↓
	Rio Branco	$y = 51.14 - 0.72 x$	0.11	0.236	–
	Manaus	$y = 13.11 - 1.63 x$	0.58	0.001	↓
	Boa Vista	$y = 20.33 + 1.73 x$	0.66	< 0.001	↑
	Belém	$y = 27.50 - 4.52 x$	0.63	< 0.001	↓
	Macapá	$y = 18.94 + 1.40 x$	0.55	0.001	↑
	Porto Velho	$y = 23.07 - 0.49 x$	0.15	0.153	–
	Palmas	$y = 78.57 + 4.32 x$	0.14	0.176	–
Northeastern Region		$y = 26.26 + 1.00 x$	0.58	0.001	↑
	São Luís	$y = 12.54 - 1.84 x + 0.19 x 2 + 0.06 x^{3}$	0.69	0.001	↓/↑
	Teresina	$y = 29.85 + 3.44 x$	0.93	< 0.001	↑
	Fortaleza	$y = 45.72 + 1.34 x - 0.21 x^{2}$	0.64	0.001	↑
	Natal	$y = 39.70 + 3.29 x$	0.66	< 0.001	↑
	João Pessoa	$y = 31.63 + 1.83 x$	0.80	< 0.001	↑
	Recife	$y = 4.00 + 0.28 x$	0.42	0.009	↑
	Salvador	$y = 26.08 - 1.03 x - 0.22 x 2 + 0.03 x^{3}$	0.87	< 0.001	↓
	Maceió	$y = 34.29 + 1.00 x - 0.42 x^{2}$	0.85	< 0.001	↑/↓
	Aracajú	$y = 43.07 - 0.66 x$	0.08	0.297	–
Southeastern Region		$y = 35.37 + 1.59 x$	0.59	0.001	↑
	Belo Horizonte	$y = 61.53 - 2.13 x - 0.60x 2 + 0.06 x^{3}$	0.81	< 0.001	↓
	Vitória	$y = 30.87 - 0.98 x$	0.10	0.239	–
	Rio de Janeiro	$y = 18.97 + 0.95 x$	0.41	0.010	↑
	São Paulo	$y = 44.95 + 2.40 x$	0.78	< 0.001	↑
Southern Region		$y = 37.13 - 2.38 x - 0.18x 2 + 0.08 x^{3}$	0.85	< 0.001	↓/↑
	Curitiba	$y = 15.73 - 1.08 x$	0.50	0.003	↓
	Florianópolis	$y = 40.46 + 1.71 x$	0.58	0.001	↑
	Porto Alegre	$y = 53.17 - 2.12 x - 0.31 x 2 + 0.10 x^{3}$	0.94	< 0.001	↑
Midwestern Region		$y = 41.06 - 1.39 x - 0.35 x 2 + 0.06 x^{3}$	0.90	< 0.001	↑/↓/↑
	Campo Grande	$y = 12.11 + 0.25 x$	0.09	0.276	–
	Cuiabá	$y = 42.18 + 1.29 x - 0.48 x^{2}$	0.79	< 0.001	↑
	Goiânia	$y = 56.06 - 3.97 x - 0.62 x 2 + 0.12 x^{3}$	0.91	< 0.001	↑/↓
	Brasília	$y = 31.26 + 1.26 x$	0.43	0.008	↑

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[1] Collaborations

DROM Abreu, ES Novaes, RR Oliveira, TAF Mathias and SS Marcon participated in all stages of the present study, to say: 1. Design and design or analysis and interpretation of data; 2. Article writing or critical review relevant intellectual content; 3. Final approval of the version to be published. 4. Be responsible for all aspects of the work in ensuring the accuracy and integrity of any part of the work.