6
C. M. García-Witulski and M. J. Rabassa
of knots seems appropriate for large datasets, and the specific values were selected
using the percentile distribution (Curriero et al. 2002; Rosenberg et al. 2003) of the
weather variables (Harrell 2001).
The estimated exposure parameters cannot be directly interpreted; therefore, they
should be compared to a reference value, which in this case was selected at 18.9
degree Celsius (
◦ C), the national mean daily temperature. It can be calculated as
(Stata 2017):
V i+1 =
(V 1 − k i )
3
+ − (k n − k n−1 )
−1
(V 1 − k n−1 )
3
+ (k n − k i ) − (V 1 − k n )
3
+ (k n−1 − k i )
k n − k 2
1
(2)
where k i is the value for the ith knot (i = 1, . . . , n), V i is the exposure parameter
to be estimated (i = 1, . . . , n − 1), and V 1 is the reference temperature (18.9
◦ C).
Finally, (u + ) = u if u is strictly positive, and (u + ) = 0 if u is zero or negative.
Data
The estimation strategy outlined above relies on two major sets of data between the
years 2004 and 2010: death counts by administrative subdivision and weather records
from meteorological stations.
The mortality data corresponds to the universe of 1,812,745 million deaths
occurred across the country, compiled by Dirección de Estadísticas e Información
Pública, which is the agency in charge of the national system of health statistics. The
dataset reports each death along with the date of death, the gender and age, and the
municipality of residence of the deceased. Thus, death counts had to be aggregated
at the municipal level, the smallest administrative subdivision in the dataset.
Death counts were complemented with annual population estimates in order to
construct all-cause monthly municipal mortality rates per 100,000 inhabitants, by
gender and age groups. Annual municipal population had to be interpolated from the
2001 and 2010 national population censuses. Specifically, following Deschênes and
Greenstone (2011) and Barreca et al. (2016), population was stratified in four age
groups (0–4, 5–44, 45–64, and >64 years old), according to the population summaries
in the 2001 census. Unfortunately, population summaries did not allow constructing
separate mortality rates for infants, i.e., younger than one year old, which are far
more susceptible to thermal stress than other young children (Keim et al. 2002).
Weather records were obtained from Servicio Meteorológico Nacional, the official
weather and climatological agency. Daily maximum and minimum temperatures
in degree Celsius, and total precipitation in millimeters (mm) are reported for 71
weather stations that comprise the national weather station network. Ten weather
stations, all located in Patagonia, southern Argentina, had to be discarded due to
incomplete weather records. The monitoring network might seem to be sparse given
the surface area and the degree of development for a country such as Argentina.
However, according to the 2010 national census, Argentinian population is mostly
C. M. García-Witulski and M. J. Rabassa
of knots seems appropriate for large datasets, and the specific values were selected
using the percentile distribution (Curriero et al. 2002; Rosenberg et al. 2003) of the
weather variables (Harrell 2001).
The estimated exposure parameters cannot be directly interpreted; therefore, they
should be compared to a reference value, which in this case was selected at 18.9
degree Celsius (
◦ C), the national mean daily temperature. It can be calculated as
(Stata 2017):
V i+1 =
(V 1 − k i )
3
+ − (k n − k n−1 )
−1
(V 1 − k n−1 )
3
+ (k n − k i ) − (V 1 − k n )
3
+ (k n−1 − k i )
k n − k 2
1
(2)
where k i is the value for the ith knot (i = 1, . . . , n), V i is the exposure parameter
to be estimated (i = 1, . . . , n − 1), and V 1 is the reference temperature (18.9
◦ C).
Finally, (u + ) = u if u is strictly positive, and (u + ) = 0 if u is zero or negative.
Data
The estimation strategy outlined above relies on two major sets of data between the
years 2004 and 2010: death counts by administrative subdivision and weather records
from meteorological stations.
The mortality data corresponds to the universe of 1,812,745 million deaths
occurred across the country, compiled by Dirección de Estadísticas e Información
Pública, which is the agency in charge of the national system of health statistics. The
dataset reports each death along with the date of death, the gender and age, and the
municipality of residence of the deceased. Thus, death counts had to be aggregated
at the municipal level, the smallest administrative subdivision in the dataset.
Death counts were complemented with annual population estimates in order to
construct all-cause monthly municipal mortality rates per 100,000 inhabitants, by
gender and age groups. Annual municipal population had to be interpolated from the
2001 and 2010 national population censuses. Specifically, following Deschênes and
Greenstone (2011) and Barreca et al. (2016), population was stratified in four age
groups (0–4, 5–44, 45–64, and >64 years old), according to the population summaries
in the 2001 census. Unfortunately, population summaries did not allow constructing
separate mortality rates for infants, i.e., younger than one year old, which are far
more susceptible to thermal stress than other young children (Keim et al. 2002).
Weather records were obtained from Servicio Meteorológico Nacional, the official
weather and climatological agency. Daily maximum and minimum temperatures
in degree Celsius, and total precipitation in millimeters (mm) are reported for 71
weather stations that comprise the national weather station network. Ten weather
stations, all located in Patagonia, southern Argentina, had to be discarded due to
incomplete weather records. The monitoring network might seem to be sparse given
the surface area and the degree of development for a country such as Argentina.
However, according to the 2010 national census, Argentinian population is mostly