Background
The authors write that "while the association of weather and mortality has been well documented for moderate climate zones, little is known about sub-tropical zones, particularly Bangladesh." And, therefore, they say they conducted a study of that country that "aims to assess the short-term relationship of temperature and rainfall on daily mortality after controlling for seasonality and time-trends,"

What was done
Working with daily mortality and weather data for the period 1983-2009 pertaining to Matlab, Bangladesh, where a rigorous health and demographic surveillance system (HDSS) has been operational since 1966, Lindeboom et al. applied time series Poisson regression with cubic spline functions that allowed for lagged effects of weather on mortality, while controlling for time trends and seasonal patterns.

What was learned
First of all, the four researchers report that "mortality in the Matlab surveillance area shows overall weak associations with rainfall, and stronger negative association with temperature." Concentrating on the more important temperature, therefore, they highlight the fact that they determined there was "a 1.4% increase in mortality with every 1°C decrease in mean temperature at temperatures below 29.2°C," but that there was only "a 0.2% increase in mortality with every 1°C increase in mean temperature." In addition, they indicate that the "elderly, aged 60 years and above, seem to be most affected at lower temperatures, with a 5.4% increase in mortality with every 1°C decrease in temperature below 23°C."

What it means
Lindeboom et al. report that the Bangladesh Meteorological Department data on both minimum and maximum temperatures observed in 1950-2010 "showed an increasing trend," but they note that the increase was faster for minimum temperature, as opposed to maximum temperature. And thus it can be appreciated that the net effect of that half-century of warming had to have had the positive effect of a net decrease in mortality in Matlab, Bangladesh.