Conceived and designed the experiments: TM ALHI KK. Performed the experiments: ALHI MEVM TM KK JT SI ELMV LAR. Analyzed the data: TM ALHI KK. Wrote the paper: TM KK.
The authors have declared that no competing interests exist.
In addition to clinical aspects and pathogen characteristics, people's health-related behavior and socioeconomic conditions can affect the occurrence and severity of diseases including influenza A(H1N1)pdm09.
A face-to-face interview survey was conducted in a hospital in Mexico City at the time of follow-up consultation for hospitalized patients with pneumonia due to influenza virus infection. In all, 302 subjects were enrolled and divided into two groups based on the period of hospitalization. Among them, 211 tested positive for influenza A(H1N1)pdm09 virus by real-time reverse-transcriptase-polymerase-chain-reaction during the pandemic period (Group-pdm) and 91 tested positive for influenza A virus in the post-pandemic period (Group-post). All subjects were treated with oseltamivir. Data on the demographic characteristics, socioeconomic status, living environment, and information relating to A(H1N1)pdm09, and related clinical data were compared between subjects in Group-pdm and those in Group-post. The ability of household income to pay for utilities, food, and health care services as well as housing quality in terms of construction materials and number of rooms revealed a significant difference: Group-post had lower socioeconomic status than Group-pdm. Group-post had lower availability of information regarding H1N1 influenza than Group-pdm. These results indicate that subjects in Group-post had difficulty receiving necessary information relating to influenza and were more likely to be impoverished than those in Group-pdm. Possible factors influencing time to seeking health care were number of household rooms, having received information on the necessity of quick access to health care, and house construction materials.
Health-care-seeking behavior, poverty level, and the distribution of information affect the occurrence and severity of pneumonia due to H1N1 virus from a socioeconomic point of view. These socioeconomic factors may explain the different patterns of morbidity and mortality for H1N1 influenza observed among different countries and regions.
In March 2009, Mexico was the first country to raise the international alert about the outbreak of influenza A(H1N1)pdm09 virus infection
Various factors affecting occurrence of pneumonia, disease severity, and mortality associated with A(H1N1)pdm09H1N1 have been reported from a clinical viewpoint
The aim of the present study was to assess how socioeconomic and living conditions relate to the disease severity of H1N1 influenza, including pneumonia, in Mexico.
The survey was conducted at the INER, Mexico City between December 2010 and April 2011, and it included follow-up consultation with subjects or their relatives using structured questionnaires administered by physicians or trained medical staff. The subjects were former patients hospitalized in the INER for pneumonia due to A(H1N1)pdm09 who tested positive by real-time reverse-transcriptase-polymerase-chain-reaction (RT-PCR) during the pandemic period; patients hospitalized for pneumonia who tested positive for influenza A virus during the post-pandemic period served as a comparison group. Patients with pneumonia caused by primary bacterial infection were excluded. All subjects were treated with oseltamivir. The pandemic period was defined as April 2009 to July 2010, and the post-pandemic period was defined as August 2010 to March 2011, in accordance with the declaration of the post-pandemic period by the WHO
The questionnaire was designed to collect data on the demographic characteristics of subjects, socioeconomic status, living environment, and information relating to A(H1N1)pdm09, as well as related clinical data. Socioeconomic status was classified in terms of daily income while living environment was defined in terms of numerous factors associated to living conditions, including area in which subjects lived (i.e., location), house size and construction material, among other factors. All questions were either closed-ended or multiple choice. Each variable was compared between subjects hospitalized in the pandemic period (Group-pdm) and those hospitalized in the post-pandemic period (Group-post). In addition, factors affecting access to health care were evaluated. Socioeconomic level was classified based on daily income and on the ability of household income to pay for utilities, food, and medical services according to the Social Gap Index by the CONEVAL (Consejo Nacional de Evaluación de la Política de Desarrollo Social)
All subjects provided written informed consent. Ethical approval was provided by the Institutional Review Board of the National Institute of Respiratory Diseases, Mexico City and the National Center for Global Health and Medicine, Tokyo. The investigators maintained the datasets in password-protected systems and have preserved the anonymity of the subjects when presenting data.
Data from the surveys were double-entered and analyzed using SPSS ver. 19 (IBM, Armonk, NY, USA). For categorical variables, frequencies were compared using the chi-square test and Fisher's exact test. For determination of independent factors for the time to seeking healthcare, multivariate regression analysis was conducted using a stepwise selection method included all variables in baseline characteristics, socioeconomic status, living environment, and information relating to A(H1N1)pdm09, and related clinical data, if p <0.1 in univariate analysis. For all analyses, significance levels were two-tailed, and p value of <0.05 was considered significant.
In all, 302 subjects who were hospitalized with pneumonia between April 2009 and March 2011 and received follow-up consultation during the study period agreed to participate in the present survey. Among them, 211 (69.9%) were hospitalized during the pandemic period (Group-pdm) and 91 (30.3%) in the post-pandemic period (Group-post). The general backgrounds of subjects are listed (
Pandemic period |
Post-pandemic period |
Total | p value | |
N = 211 (69.9%) | N = 91 (30.3%) | N = 302 (100.0%) | ||
|
||||
Male-no. (% of group) | 128 (60.7) | 50 (54.9%) | 178 (58.9%) | 0.354 |
|
38.5 (0–90) | 42.0 (2–91) | 39.0 (0–91) | 0.003 |
|
0.001 | |||
<18 | 45 (21.4) | 4 (4.4) | 49 (16.3) | |
18-<50 | 108 (51.2) | 52 (57.1) | 160 (53.0) | |
50-<65 | 43 (20.4) | 22 (24.2) | 65 (21.5) | |
≥65 | 15 (7.1) | 13 (14.3) | 28 (9.3) | |
|
0.356 | |||
None | 34 (16.4) | 17 (17.9) | 51 (16.9) | |
Primary school | 57 (27.5) | 25 (26.3) | 82 (27.2) | |
Secondary school | 49 (23.7) | 16 (16.8) | 65 (21.5) | |
High school | 33 (15.9) | 19 (20.0) | 52 (17.2) | |
University | 30 (14.5) | 12 (12.6) | 42 (13.9) | |
Graduate school | 2 (1.0) | 3 (3.2) | 5 (1.7) | |
Technical school | 2 (1.0) | 3 (3.2) | 5 (1.7) | |
|
0.437 | |||
Unemployed | 18 (8.6) | 17 (18.7) | 35 (11.7) | |
Retired | 1 (0.5) | 2 (2.2) | 3 (1.0) | |
Student | 28 (13.4) | 3 (3.3) | 31 (10.3) | |
Housewife | 53 (25.4) | 30 (33.0) | 83 (27.7) | |
Governmental employee | 4 (1.9) | 3 (3.3) | 7 (2.3) | |
Employee by private company | 30 (14.4) | 15 (16.5) | 45 (15.0) | |
Commercial | 33 (15.8) | 5 (5.5) | 38 (12.7) | |
Self-employed (small business) | 28 (13.4) | 3 (3.3) | 31 (10.3) | |
|
0.332 | |||
Low | 144 (72.4) | 69 (67.0) | 213 (70.5) | |
Middle | 55 (27.6) | 34 (33.0) | 89 (29.5) | |
High | 0 (0.0) | 0 (0.0) | 0 (0.0) | |
|
||||
|
0.203 | |||
Vaccinated in 2009 | 4 (1.9) | 6 (6.6) | 10 (3.3) | |
Vaccinated in 2010 | 42 (19.9) | 20 (22.0) | 62 (20.5) | |
Vaccinated in 2011 | 8 (3.8) | 3 (3.5) | 11 (3.6) | |
|
0.002 | |||
smoker | 18 (8.5) | 21 (23.1) | 39 (12.9) | |
ex-smoker | 19 (9.0) | 8 (8.8) | 27 (8.9) | |
|
6 (2.8) | 40 (44.0) | 46 (15.2) | 0.000 |
|
6.0 (0–35) | 5.0 (0–29) | 6.0 (0–35) | 0.379 |
Pandemic period, between April 2009 and July 2010; Post-pandemic period, between August 2010 and the end of survey period.
Socioeconomic level evaluated by ability to pay for utilities, food, and medical service: low income, cannot cover electricity, water, telephone, house rent, foods, any medical service; middle income, can cover a part of electricity, water, telephone, house rent, and foods, but not any medical service; high income, can cover utility and adequate goods, and medical services.
Number of days from symptom onset to initiation of oseltamivir administration.
The health-related background details of subjects are presented in
The detailed economic situation of the subjects was defined by the Social Gap Index of COVEVAL (
Pandemic period |
Post-pandemic period |
Total | p value | |
N = 211 (69.9%) | N = 91 (30.3%) | N = 302 (100.0%) | ||
|
0.000 | |||
All services | 76 (36.0) | 16 (17.6) | 92 (30.5) | |
2–3 of all | 133 (63.0) | 41 (45.1) | 174 (57.6) | |
None | 2 (0.9) | 34 (37.4) | 36 (11.9) | |
|
0.000 | |||
All necessaries | 126 (59.7) | 25 (27.8) | 151 (50.2) | |
2–3 of all | 85 (40.3) | 51 (56.7) | 136 (45.2) | |
None | 0 (0.0) | 14 (15.6) | 14 (4.7) | |
|
0.000 | |||
Consultation, hospitalization, medication | 60 (28.6) | 16 (17.8) | 76 (25.3) | |
Consultation, hospitalization | 142 (67.6) | 35 (38.9) | 177 (59.0) | |
None | 8 (3.8) | 39 (43.3) | 47 (15.7) | |
|
0.144 | |||
None | 179 (84.8) | 71 (78.0) | 250 (82.8) | |
Government insurance |
17 (8.1) | 8 (8.8) | 25 (8.3) | |
Private insurance | 1 (0.5) | 0 (0.0) | 1 (0.3) | |
Others | 14 (6.6) | 12 (13.2) | 26 (8.6) |
Pandemic period, between April 2009 and July 2010; Post-pandemic period, between August 2010 and the end of survey period.
Income can pay for expense of utilities; light, gas, water, sewerage, telephone.
Income can pay for expense of food; meat, egg, milk, cereals, vegetable.
Governmental insurance included workers in private organizations.
Most of the subjects in Group-pdm and Group-post lived in an area that provided all public services (p = 0.144), and there was no difference between the groups. In terms of housing status (
Pandemic period |
Post-pandemic period |
Total | p value | |
N = 211 (69.9%) | N = 91 (30.3%) | N = 302 (100.0%) | ||
|
0.144 | |||
All public services | 187 (88.6) | 75 (82.4) | 262 (86.8) | |
Partial public services | 24 (11.4) | 16 (17.6) | 40 (13.2) | |
|
0.011 | |||
Borrow without any payment | 84 (39.8) | 28 (30.8) | 112 (37.1) | |
Rent | 39 (18.5) | 31 (34.1) | 70 (23.2) | |
Pay for credit | 16 (7.6) | 2 (2.2) | 18 (6.0) | |
Own | 72 (34.1) | 30 (33.0) | 102 (33.8) | |
|
<0.001 | |||
Concrete | 179 (84.8) | 70 (76.9) | 249 (82.5) | |
Tinplate | 3 (1.4) | 12 (13.2) | 15 (5.0) | |
Concrete and tinplate | 29 (13.7) | 9 (9.9) | 38 (12.6) | |
|
0.003 | |||
≤2 | 85 (40.3) | 64 (70.3) | 149 (49.3) | |
3–5 | 121 (57.3) | 26 (28.6) | 147 (48.7) | |
≥6 | 5 (2.4) | 1 (1.1) | 6 (2.0) | |
|
<0.001 | |||
≤2 | 13 (6.2) | 24 (26.4) | 37 (12.3) | |
3–5 | 167 (79.5) | 57 (62.6) | 224 (74.4) | |
≥6 | 30 (14.3) | 10 (11.0) | 40 (13.3) | |
|
2.5 (0.29–8.0) | 3.0 (0.67–9.0) | 2.5 (0.29–9.0) | <0.001 |
Pandemic period, between April 2009 and July 2010; Post-pandemic period, between August 2010 and the end of survey period.
Location was defined by the accessibility of public service which is also followed by the Social Gap Index.
The most common source of information about influenza A(H1N1)pdm09 was television in both groups (p = 0.706) (
Pandemic period |
Post-pandemic period |
Total | p value | |
N = 211 (69.9%) | N = 91 (30.3%) | N = 302 (100.0%) | ||
|
||||
Newspaper | 34 (16.1) | 13 (14.3) | 47 (15.6) | 0.688 |
Television | 170 (80.6) | 75 (82.4) | 245 (81.1) | 0.706 |
Radio | 116 (55.5) | 23 (25.3) | 139 (46.3) | 0.000 |
Internet | 4 (1.9) | 3 (3.3) | 7 (2.3) | 0.355 |
Family and friends | 22 (10.4) | 15 (16.5) | 37 (12.3) | 0.141 |
Healthcare workers in Hospital | 23 (10.9) | 3 (3.3) | 26 (8.6) | 0.031 |
No information | 1 (0.5) | 3 (3.3) | 4 (1.3) | 0.083 |
|
163 (77.3) | 27 (29.7) | 190 (62.9) | 0.000 |
|
199 (94.3) | 55 (60.4) | 254 (84.1) | 0.000 |
Pandemic period, between April 2009 and July 2010; Post-pandemic period, between August 2010 and the end of survey period.
More Group-pdm subjects than Group-post subjects received clear information about methods of prevention of influenza A(H1N1)pdm09 (77.3% vs. 29.7%, respectively, p<0.001) as well as information regarding the necessity for early access to health care (94.3% vs. 60.4%, respectively, p<0.001).
In the multivariate regression analysis, the number of household rooms, information regarding the necessity for quick access to health care, and housing construction materials were independent factors that tended to be associated with the number of days from symptom onset to the initiation of antiviral treatment (
Coefficient | Standard error | t value | p value | 95% confidence interval | |
Constant | −10.246 | 4.351 | −2.355 | 0.022 | −18.985–−1.508 |
Number of rooms in house | 3.798 | 0.895 | 4.242 | 0.000 | 2.000–5.597 |
Received information about necessity of quick access to health care during pandemic period | 4.741 | 1.986 | 2.387 | 0.021 | 0.751–8.730 |
House construction material |
3.056 | 1.473 | 2.075 | 0.043 | 0.097–6.015 |
House constructed of concrete, tinplate, and combination of concrete and tinplate.
Low awareness of the importance of early access to healthcare and difficulty separating oneself from other individuals in a household owing to poverty are possible reasons for hospitalized pneumonia due to influenza virus infection in the post pandemic period.
INER is a tertiary medical organization for the care of patients with respiratory illness, and it provides medical services mainly to uninsured individuals in the metropolitan area of Mexico City and neighboring states. Most patients who visit the INER have a similar low socioeconomic level, demographic characteristics, and educational background
In Mexico, rural poverty is concentrated in southern areas of the country
Seasonal influenza vaccination in Mexico is limited to the young and elderly
The time from onset of symptoms to initiation of oseltamivir treatment is a key factor in reducing severe respiratory conditions due to H1N1 influenza
The present study was limited to a population that was mostly uninsured and facing socioeconomic difficulties in Mexico City. Although there is a large gap between poverty and wealth in Mexico, the present study did not evaluate the range of socioeconomic levels in the population. Patients in Group-pdm had H1N1 influenza confirmed by RT-PCR, but the same test was not performed in patients in Group-post for budgetary reasons in the INER. Therefore, Group-post may have included patients with pneumonia not caused by influenza A(H1N1)pdm09 virus, but by some other type of influenza A virus. Further study, including an investigation of different socioeconomic populations, is needed to determine the impact of socioeconomics on the severity of disease due to influenza infection.
Although many factors affect disease occurrence and severity (including pneumonia), health-care-seeking behavior, poverty, and distribution of information are important factors from a socioeconomic point of view. These factors may explain the different patterns of morbidity and mortality for influenza A(H1N1)pdm09 in different countries and regions.