Study design

We conducted a cross-sectional, countrywide ecological study over a 11-year period (2010–2021) to determine the demographic and spatial distribution patterns of pneumonia among Ecuadorian children, using hospital discharge and in-hospital mortality data as proxies for incidence and mortality.

Sample and setting

The study was conducted in Ecuador, a country located in the northern region of South America with an area of ​​283,561 km2. The Ecuadorian territory is divided into four geo-climatic regions: the Coast, Andes (Highlands), Amazonia, and the Galápagos Islands. Politically, it is segmented into 24 provinces, each further subdivided into cantons. Currently, Ecuador comprises a total of 223 cantons, with 141 located at low altitude (< 1,500 m), 28 at moderate altitude (1,500-2,500 m), 41 at high altitude (2,500-3,500 m), and 13 at very high altitude (3,500-5,500 m).

Population

In 2019, Ecuador’s population in the 0 to 18 age group consisted of approximately 6,648,436 individuals, representing a significant portion of the total population of 17,082,730, with a slight female predominance (51%). This demographic includes 330,105 under 1 year, 1,321,687 aged 1 to 4 years, 1,666,259 between 5 and 9 years, 1,685,209 from 10 to 14 years, and 1,645,176 in the 15 to 18 age group. While specific ethnic and altitude distribution data for this age group are not available, the overall patterns suggest a majority of mestizo (79.3%), followed by Afro-descendants (7.2%), indigenous (7.1%), white (6.1%), and other groups (0.4%), with 60% living at low altitude, 10% at moderate altitude, 27% at high altitude, and 3% at very high altitude [13, 14].

Data source and description

This study examined hospitalization records of pediatric patients from 0 to 18 years old residing in Ecuador, diagnosed with lower respiratory tract infections resulting in pneumonia upon hospital discharge. These conditions were identified through 22 distinct etiologies as per the International Classification of Diseases, Tenth Revision (ICD-10), including: Influenza due to identified zoonotic or pandemic influenza viruses (J09), Influenza due to identified seasonal influenza viruses (J10), Influenza due to other identified influenza viruses, not elsewhere classified (J100), Influenza with other respiratory manifestations, not elsewhere classified (J101), Influenza with other manifestations, other (J108), Influenza, virus not identified (J11), Influenza with pneumonia, seasonal influenza virus identified (J110), Influenza with other respiratory manifestations, seasonal influenza virus identified (J111), Influenza with other manifestations, seasonal influenza virus identified (J118), Viral pneumonia, not elsewhere classified (J12), Pneumonia due to Streptococcus pneumoniae (J13), Pneumonia due to Haemophilus influenzae (J14), Bacterial pneumonia, not elsewhere classified (J15), Pneumonia due to other infectious organisms, not elsewhere classified (J16), Pneumonia, organism unspecified (J18) and COVID-19 (U07.1 and U07.2).

Inclusion criteria

Using the 10th Revision of the International Classification of Diseases (ICD-10), the study included pediatric patients from 0 to 18 years old diagnosed with lower respiratory tract infections resulting in pneumonia upon hospital discharge. This encompassed 22 distinct etiologies, including various forms of influenza (J09, J10, J100, J101, J108, J11, J110, J111, J118), viral pneumonia (J12), pneumonia due to Streptococcus pneumoniae (J13), Haemophilus influenzae (J14), other bacterial pneumonia (J15), pneumonia due to other infectious organisms (J16), unspecified pneumonia (J18), and COVID-19 (U07.1 and U07.2).

Exclusion criteria

Excluded from the analysis were pediatric cases diagnosed with upper respiratory tract infections, asthma, COPD, as well as other conditions not classified under the specified ICD-10 codes for lower respiratory tract infections resulting in pneumonia. This ensured a focused study on the specified pneumonia conditions in the pediatric population.

Bias

To minimize the potential for selection bias and ensure the integrity of the data, three researchers (EOP, MVC and JIC) independently analyzed the dataset. Data verification focused on confirming the diagnoses as per the inclusion criteria and ensuring that the patients were within the specified age range and diagnosed with the relevant lower respiratory tract infections. Additionally, the “place of residence” variable was used to confirm that the patients were residing at different altitudes in Ecuador, rather than basing this on the “place of medical attention,” thus providing a more accurate reflection of the population under study.

Hypothesis Null hypothesis (H₀)

There is no significant difference in the incidence and mortality rates of pediatric pneumonia across different altitude levels in Ecuador.

Alternative hypothesis (H₁)

There is a significant difference in the incidence and mortality rates of pediatric pneumonia across different altitude levels in Ecuador, with higher altitudes exhibiting increased incidence and mortality rates compared to lower altitudes.

Exposure

The association between altitude exposure and the incidence and mortality of pneumonia was analyzed. Altitude classifications were used as a key variable, with a cut-off point of < 2,500 m for low altitude and > 2,500 m for high altitude. The more detailed classification by the International Society of Mountain Medicine, categorizing altitudes as low (< 1,500 m), moderate (1,500–2,500 m), high (2,500–3,500 m), and very high (3,500–5,500 m), was utilized to assess prevalence odds ratios across different elevations. These analyses are crucial given the range of pneumonia etiologies, including those due to various influenza viruses and bacterial agents.

Outcome

Age, sex, and altitude-adjusted incidence and mortality rates for pneumonia were calculated using hospital admissions data and death records in Ecuador from 2010 to 2021. This includes cases classified under 22 distinct etiologies as per ICD-10, encompassing various types of influenza and pneumonia caused by different pathogens, including Streptococcus pneumoniae, Haemophilus influenzae, other bacterial and viral agents, and COVID-19 (U07.1 and U07.2).

Data analysis

The study analyzed sex, age, month, etiology, type of hospital, province and canton of residence, elevation, and date of hospital admission. Incidence and mortality rates were standardized by sex and age, utilizing projection data from the 2010 census.

Percentage differences in incidence and case fatality rates (CFR%) across age groups and genders were calculated using the equation for percentage change = [(New Value − Old Value)/ Old Value] ×100%.

Incidence was calculated by dividing the number of new cases per year by the total population at risk during each year for each age group. Incidence and mortality rates by age, sex, geographic location, and corresponding population were calculated. The classification of low altitude < 2,500 m and high altitude > 2,500 m was used as a cut-off point for exposure to altitude. The analysis was also carried out using the classification offered by the International Society of Mountain Medicine (ISMM) which includes low altitude (< 1,500 m), moderate altitude (1,500 m – 2,500 m), high altitude (2,500–3,500 m), and very high altitude (> 3,500 m) [15].

Ethical consideration

The study was granted an exemption from ethical review by the Institutional Review Board (IRB) of the Ethics Committee at Universidad de las Américas (UDLA), Quito, Ecuador, acknowledging the ethical compliance of the research methodology. This exemption, officially coded as 2023-EXC-008, was formally issued on May 8, 2023.

The dataset employed in this study was sourced from the publicly accessible databases of the National Institute of Statistics and Census (INEC) of Ecuador. These databases contain only anonymized, non-identifiable information, ensuring adherence to stringent confidentiality standards and the preservation of ethical integrity concerning the subjects involved. The use of such anonymized datasets aligns with international Good Clinical Practice (GCP) guidelines and adheres to the ethical principles set forth in the Declaration of Helsinki. The ethical acceptability of employing these datasets stems from their capability to safeguard individuals from harm while maintaining robust confidentiality protocols.