Hospitalizations due to alcohol and other drugs: trends in a decade in the state of Paraná

Santana, Cleiton José; Gavioli, Aroldo; Oliveira, Rosana Rosseto de; Oliveira, Magda Lúcia Félix de

doi:10.37689/acta-ape/2022AO026377

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Original Article • Acta Paul Enferm 35 • 2022 • https://doi.org/10.37689/acta-ape/2022AO026377 copy

Hospitalizations due to alcohol and other drugs: trends in a decade in the state of Paraná

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract

Objective

To analyze the trend of hospitalizations due to alcohol and other drugs in a decade in the state of Paraná.

Methods

This is an ecological, time series study using the Unified Health System’s Hospital Information System. Data were collected from the records of the state of Paraná, southern Brazil, restricted to the period from 2009 to 2018. Diagnostic criteria F10 to F19 (use of alcohol and other drugs) records were sought, according to the International Statistical Classification of Diseases and Related Health Problems – 10^th edition. For trend analysis, the polynomial regression model was used.

Results

There were 201,377 hospitalizations for mental and behavioral disorders due to the use of alcohol and other drugs, with a mean rate of 210.52 hospitalizations per 100,000 inhabitants. There was a higher male hospitalization rate, with a mean of 374.24 per 100,000 inhabitants, predominantly aged 25 to 50 years for both sexes. Among hospitalizations, 56.86% were related to mental and behavioral disorders due to alcohol use. Polynomial regression analysis revealed downward trend (p=0.003; R²=0.706), with differences between the state regions. The East Macroregion had the highest hospitalization rate (320.25), only the Paranaguá region had an upward trend (19.33/year).

Conclusion

The rate of hospitalizations showed a decline and the identification of the regions with the highest rate of hospitalization due to alcohol and other drug abuse can provide subsidies for implementing public policies, with monitoring actions and prevention strategies.

Alcoholism; Illicit drugs; Hospitalization

General calculation	Model	R²	p-value	Trend
General/age	$y = 210.52 - 7.0 x$	0.706	0.003	↓
13-24 years	$y = 4376.44 + - 231.67 x$	0.615	0.008	↓
25-59 years	$y = 2139.15 + - 1371.81 x + 71.64 x^{\land} 2$	0.716	0.010	↓
60 years and older	$y = 898.30 + - 18.12 x + 3.5 x^{\land} 2$	0.807	0.003	↓/↑
Sex/age
Female	$y = 49.72 - 1.4 x$	0.305	0.071	-
13-24 years	$y = 985.85 - 65.14 x$	0.494	0.021	↓
25-59 years	$y = 1898.39 + - 120.63 x + 10.37 x^{\land} 2$	0.164	0.247	↓/↑
60 years and older	$y = 100.65 + - 17.63 x + 1.73 x^{\land} 2$	0.909	0.000	↓/↑
Male	$y = 374.24 - 12.63 x$	0.754	0.001	↓
13-24 years	$y = 3390.59 + - 166.53 x$	0.657	0.005	↓
25-59 years	$y = 19491.75 + - 1251.18 x + 61.27 x^{\land} 2$	0.761	0.006	↓
60 years and older	$y = 745.64 + 20.79 x$	0.002	0.002	↓/↑
ICD-10
F10 (alcohol)	$y = 147.76 - 9.36 x + 0.3 x^{2}$	0.914	<0.001	↓
F11 (opioids)	$y = 0.56 - 0.02 x$	0.648	0.005	↓
F12 (cannabis)	$y = 0.89 - 0.09 x + 0.02 x^{2}$	0.869	0.001	↓/↑
F13 (sedatives/hypnotics)	$y = 0.32 - 0.04 x + 0 x^{2}$	0.865	0.001	↓/↑
F14 (cocaine/crack)	$y = 24.94 - 1.75 x$	0.800	0.001	↓
F15 (stimulants)	$y = 0.1 + 0.0 x$	0.377	0.046	↓
F16 (hallucinogens)	$y = 1.89 - 0.39 x + 0.02 x^{2}$	0.834	0.002	↓/↑
F17 (smoking)	$y = 0.4 - 0.1 x + 0.01 x^{2}$	0.958	<0.001	↓/↑
F18 (volatile solvents)	$y = 0.01 + 0.06 x - 0.01 x^{2}$	0.576	0.032	↑/↓
F19 (polysubstance drugs)	$y = 75.97 - 5.09 x + 0.4 x^{2}$	0.096	0.555	-

Macroregion and health region	Model	R²	p-value	Trend
East	$y = 320.25 - 26.83 x + 1.39 x^{2}$	0.765	0.005	↓/↑
1^st - Paranaguá	$y = 68.61 + 19.33 x - 0.9 x^{2}$	0.689	0.013	↑
2^nd - Curitiba	$y = 397.31 - 32.05 x + 1.44 x^{2}$	0.863	0.001	↓
3^rd - Ponta Grossa	$y = 196.52 - 35.8 x + 2.88 x^{2}$	0.517	0.048	↓/↑
4^th - Irati	$y = 367.58 - 62.77 x + 3.35 x^{2}$	0.880	0.001	↓/↑
5^th - Guarapuava	$y = 123.17 - 4.7 x$	0.741	0.002	↓
6^th - União da Vitória	$y = 135.2 + 57.09 x - 4.18 x^{2}$	0.549	0.039	↑/↓
7^th - Pato Branco	$y = 146 \cdot 12 - 29.21 x + 2.68 x^{2}$	0.367	0.107	-
21^st - Telêmaco Borba	$y = 236.28 - 39.69 x + 3.35 x^{2}$	0.353	0.114	-
West	$y = 172.83 - 33.4 x + 2.4 x^{2}$	0.632	0.021	↓/↑
8^th - Francisco Beltrão	$y = 149.86 - 32 x + 2.42 x^{2}$	0.557	0.037	↓/↑
9^th - Foz do Iguaçu	$y = 90.21 - 3.78 x$	0.256	0.094	-
10^th - Cascavel	$y = 185.34 - 32.95 x + 2.07 x^{2}$	0.821	0.002	↓/↑
20^th - Toledo	$y = 281.43 - 68.91 x + 5.14 x^{2}$	0.633	0.021	↓/↑
Northwest	$y = 233.51 - 8.81 x$	0.626	0.007	↓
11^th - Campo Mourão	$y = 148.64 - 19.52 x + 1.37 x^{2}$	0.393	0.094	-
12^th - Umuarama	$y = 176.97 - 13.49 x + 1.25 x^{2}$	0.472	0.062	-
13^th - Cianorte	$y = 149.38 - 28.58 x + 2.36 x^{2}$	0.706	0.011	↓/↑
14^th - Paranavaí	$y = 284.25 - 2.43 x$	0.049	0.455	-
15^th - Maringá	$y = 335.45 - 19.18 x$	0.799	0.001	↓
North	$y = 165.51 + 20.59 x - 2.09 x^{2}$	0.556	0.037	↑/↓
16^th - Apucarana	$y = 273.3 + 6.13 x - 0.89 x^{2}$	0.363	0.109	-
17^th - Londrina	$y = 168.97 + 21.32 x - 2.51 x^{2}$	0.473	0.062	-
18^th - Cornélio Procópio	$y = 78.85 + 30.8 x - 2.89 x^{2}$	0.506	0.051	-
19^th - Jacarezinho	$y = 112.27 + 19.85 x - 1.19 x^{2}$	0.887	0.001	↑/↓
22^nd - Ivaiporã	$y = 123.09 + 36.17 x - 2.87 x^{2}$	0.495	0.054	-

	Model	R²	p-value	Trend
Mean hospital length of stay	$y = 18, 74 - 0, 14 x - 0, 01 x^{2}$	0.952	<0.001	↓
Death rate	$y = 61.89 + 1.4 x$	0.055	0.486	-

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[1] Corresponding author: Cleiton José Santana E-mail: cleitonjsantana@hotmail.com