| Literature DB >> 27217009 |
Tiago Ferreira Martins1, Patrícia Cotta Mancini2, Luiza de Marilac de Souza3, Juliana Nunes Santos4.
Abstract
INTRODUCTION: The state of Minas Gerais, Brazil has no data on the prevalence of dizziness in the population and this information can be fundamental as the basis of public health policies, promotion, prevention and rehabilitation campaigns.Entities:
Keywords: Brazilian Unified Health System; Dizziness; Epidemiologia; Epidemiology; Sistema Único de Saúde; Tontura
Mesh:
Year: 2016 PMID: 27217009 PMCID: PMC9444789 DOI: 10.1016/j.bjorl.2016.01.015
Source DB: PubMed Journal: Braz J Otorhinolaryngol ISSN: 1808-8686
Population estimate of individuals interviewed in the PAD-MG 2011 who felt ill and had a health problem symptom over the past 30 days, mentioning only the main symptom experienced in this period.
| Symptom | Relative frequency (%) | Cumulative frequency (%) | |
|---|---|---|---|
| 316,004 | 7.88 | 7.88 | |
| Diarrhea | 109,900 | 2.87 | 10.75 |
| Toothache | 70,035 | 1.93 | 12.68 |
| 611,080 | 16.13 | 28.81 | |
| Chest pain | 99,983 | 3.29 | 32.10 |
| Abdominal pain | 178,654 | 4.97 | 37.06 |
| Earache | 29,953 | 0.93 | 37.99 |
| Breathlessness | 109,370 | 3.16 | 41.15 |
| Bleeding | 16,805 | 0.53 | 41.68 |
| 209,025 | 6.70 | 48.38 | |
| Cough | 136,264 | 3.65 | 52.03 |
| Vomiting | 51,523 | 1.42 | 53.45 |
| Other | 1,648,377 | 46.55 | 100.00 |
| Total | 3,586,973 | 100.00 | |
Source: Sample Survey of Households of Minas Gerais (PAD-MG). Fundação João Pinheiro, 2011.
Figure 1Prevalence of dizziness according to age.
Multivariate binary logistic regression of factors associated with the presence of dizziness in the 30 days preceding the interview of PAD-MG, 2011.
| Symptom of dizziness in the last 30 days | ||||||
|---|---|---|---|---|---|---|
| Yes | No | Odds Ratio | ||||
| Variables | Total | 95%CI | ||||
| Adults | 128,237 (65.2) | 11,669,927 (83.9) | 11,798,164(83.7) | <0.001 | 1.111 | 1.089–1.113 |
| Elderly | 68,311 (34.8) | 2,239,402 (16.1) | 2,307,713 (16.3) | |||
| Total | 196,548 (100) | 13,909,329 (100.0) | 14,105,877 (100.0) | |||
| Good | 71,140 (34.0) | 15,937,853 (82.9) | 16,008,993 (82.4) | <0.001 | 1.498 | 1.464–1.563 |
| Poor | 137,885 (66.0) | 3,292,153 (17.1) | 3,430,038 (17.6) | |||
| Total | 209,025 (100.0) | 19,230,006 (100.0) | 19,439,031 (100.0) | |||
| No | 97,918 (46.9) | 16,245,918 (84,6) | 16,343,836 (84.2) | <0.001 | 2.000 | 1.965–2.053 |
| Yes | 111,034 (53.1) | 293,669 (15.4) | 3,064,703 (15.8) | |||
| Total | 208,952 (100.0) | 19,199,587 (100.0) | 19,408,539 (100.0) | |||
| No | 166,636 (79.9) | 18,340,070 (95.5) | 18,506,706 (95.4) | <0.001 | 1.166 | 1.141–1.191 |
| Yes | 42,004 (20.1) | 860,293 (4.5) | 902,297 (4.6) | |||
| Total | 208,640 (100.0) | 19,200,363 (100.0) | 19,409,003 (100.0) | |||
| No | 156,072 (74.8) | 18,389,068 (95.8) | 18,545,140 (95.5) | <0.001 | 1.963 | 1.923–2.005 |
| Yes | 52,687 (25.2) | 812,086 (4.2) | 864,773 (4.5) | |||
| Total | 208,759 (100.0) | 19,201,154 (100.0) | 19,409,913 (100.0) | |||
| No | 168,817 (83.4) | 13,189,748 (86.9) | 13,358,565 (86.9) | <0.001 | 1.134 | 1.105–1.164 |
| Yes | 33,669 (16.6) | 1,988,328 (13.1) | 2,021,997 (13.1) | |||
| Total | 202,486 (100) | 15,178,076 (100) | 15,380,562 (100) | |||
| Yes | 15,499 (30.0) | 699,773 (37.2) | 715,272 (37.0) | <0.001 | 1.416 | 1.388–1.444 |
| No | 36,215 (70.0) | 1,180,612 (62.8) | 1,216,827 (63.0) | |||
| Total | 51,714 (100) | 1,880,385 (100) | 1,932,099 (100) | |||
| No | 33,115 (15.8) | 15,805,500 (82.2) | 15,838,615 (81.5) | <0.001 | 8.900 | 8.677–9.129 |
| Yes | 175,910 (84.2) | 3,419,065 (17,8) | 3,594,975 (18.5) | |||
| Total | 209,025 (100) | 19,224,565 (100) | 19,433,590 (100) | |||
| Yes | 41,613 (19.9) | 4,065,960 (21.2) | 4,107,573 (21.1) | <0.001 | 1.069 | 1.048–1.091 |
| No | 167,412 (80.1) | 15,150,814 (78.8) | 15,318,226 (78.9) | |||
| Total | 209,025 (100) | 19,216,774 (100) | 19,425,799 (100) | |||
Categories of reference.
Results obtained after multivariate analysis; the final model includes the main dependent variable adjusted for other variables that remained in the final model.
Medical or health care.
# Number of information differs from the total sample due to missing data.