Summer Temperature and All-cause Mortality from 2006 to 2015 for Smart City Jaipur,India

Abstract

A considerable association between temperature and all-cause mortality has been documented in various studies. Further insights can be obtained from studying the impact of temperature and heat index (HI) for Jaipur city’s all-cause mortality. The objective of this work was to assess the association between the extreme heat (daily maximum temperature, daily minimum temperature, daily mean temperature, relative humidity and HI) and all-cause mortality for summer months (March to June) from 2006 to 2015 for urban population of Jaipur. For summer months, we collected the data on various temperature and all-cause mortality parameters for at least 10 years. The student’s t-test and ANOVA were used to analyse variations in mean temperature, maximum temperature and HI. The Pearson correlation coefficient was used to study the relationship between ambient heat and lag time effect all-cause mortality. A total of 75,571 deaths (all-cause mortality) for 1,203 summer days (2006–2015) were analysed in relation to temperature and relative humidity. The mean daily all-cause mortality has been estimated at 62.8 ± 15.2 for the study period. There is a significant increase of 39% per day all-cause mortality at the maximum temperature of 45 °C and above. However only 10% rise per day all-cause mortality for extreme danger days (HI > 54 °C). The mean daily all-cause mortality shows a significant association with daily maximum temperature (F = 34.6, P < .0001) and HI (discomfort index) from caution to extreme danger risk days (F = 5.0, P < .0019). The lag effect of extreme heat on all-cause mortality for the study period (2006 to 2015) was at a peak period on the same day of the maximum temperature (r = 0.245 at P < .01) but continues up to four days. The study concludes that the effect of ambient heat on all-cause mortality increase is clearly evident (rise of 39% deaths/day). Accordingly, focus should be put on developing adaptation measures against ambient heat. This analysis may satisfy policy makers’ needs. Extreme heat-related mortality needs further study to reduce adverse effects on health among Jaipur’s urban population.

Keywords

Temperature all-cause mortality urban humidity heat index smart city

Introduction

Global warming coupled with one of the biggest occurrences in El Nino to date in 2015 and 2016 culminated in record high temperatures worldwide (Sanchez-Lugo et al., 2016; WMO, 2017). The WHO reports that climate change is likely to cause an additional 250,000 deaths per annum from malaria, malnutrition, diarrhoea and heat stress between 2030 and 2050 (WHO, 2015). Rising temperature is almost the universal trend, and scientists are studying and reporting on safety, growth and productivity impacts. Chronic exposure to heat and humidity increases or shifts (including and beyond episodic heatwaves) leads to physiological, physical and mental health and mortality impacts. Impacts are often amplified in urban areas because of the Urban Heat Island effect (Desai et al., 2015b). The mortality impact of extreme heat has been explored in many regions of the world (Anderson & Bell, 2011; Vandentorren et al., 2004). Temperature extremes record for 75% of weather-related all-cause mortality in developed countries (CRED, EM-DAT, & UNISDR, 2015), as well as the rise of morbidity (Astrom et al., 2011; Li et al., 2015). Similarly, the 2003 heatwave in France was estimated to cause around 15,000 excess all-cause mortality, and all-cause mortality increases approximately 20% on heat-wave days for Bangladesh (Fouillet et al., 2006; Nissan et al., 2017). India was also the victim to a series of heat waves with major mortality (De & Mukhopadhyay, 1998; Desai et al., 2015a). The devastating effect of India’s single heat wave in May 2015, with more than 2,200 fatalities, showed that extreme heat is a serious problem even in countries regularly subjected to high temperatures (Ratnam et al., 2016). Heatwaves are expected to continue to grow in strength, length and frequency as well (Im et al., 2017; Luke et al., 2016).

The linkages between extreme heat and all-cause mortality are usually examined at larger scales that are less likely to be applicable at the city level. Desert city may vary from dry and coastal cities in the context of heat wave and its mitigating measures. Consequently, gathering local proof in this area is crucial to first understanding the nature and severity of health effects and then create and execute Risk Mitigation Policies. This analysis was, accordingly, launched to investigate the likely influence of extreme heat on all-cause mortality for summer months (March to June) from 2006 to 2015 for urban population of Jaipur.

Methodology

Study Area

Jaipur, the capital and largest city of Rajasthan (Indian State), was steeped in pristine elegance and royal splendour. For its magnetic heritage and splendour, the Walled City of Jaipur has always been affectionately welcoming. The blend of assimilated nature, culture and history in this city makes it a rare mix for discerning travellers as it is a popular tourist destination in India. It was established by Jai Singh-II, the ruler of Amer after whom the town is named, on 18 November 1727. As of 2011, the town had a population of 3.1 million, making it the country’s 10th most populous city. Jaipur is also known as the Pink City because of the dominant colour scheme of its buildings. It lies 280 km (174 miles) from New Delhi, the Indian capital. Jaipur experiences a dry semi-arid climate. It receives more than 625 millimetres (25 inches) of rainfall during an average year but most rains occur between June and September in the monsoon months. During the summer from April to early July, temperatures remain relatively high, with average daily temperatures of about 30 °C (86 °F). There are regular, heavy rains and thunderstorms during the monsoon but it is not normal to flood. The winter months from November to February are mild and nice, with average temperatures ranging from 10 °C to 15 °C (50–59 °F) and low to no humidity and cold waves leading to near-freezing temperatures.

Study Design, Data Collection and Statistical Analysis

Retrospective analysis was conducted to determine the influence of temperature and relative humidity on all-cause mortality for Smart City Jaipur. Daily meteorological data were obtained from Tutiempo Network, S.L. website¹ for the summer months for the years 2006 to 2015. The meteorological variables included daily average temperature, daily maximum temperature, daily minimum temperature and daily average relative humidity for Jaipur City. Daily maximum temperature and relative humidity data were used in the calculation of the HI. Rothfusz equation (Rothfusz, 1990) for HI calculation was used as it is widely in practice for cities (Desai et al., 2015a,b; Rajib et al., 2011; Zahid & Rasul, 2010). The HI was further classified into extreme danger: >54 °C; danger: 41 °C–54 °C; extreme caution: 32 °C–41 °C and caution: 27 °C–32 °C (Desai et al., 2015a). The all-cause mortality data for Jaipur city were obtained from the Birth and Death Registration Department of the Municipal Corporation for the years from 2006 to 2015. Ethical clearance has been taken from the Institutional Committee for Ethics and Review of Research of IIHMR University.

Data were processed in Microsoft Excel and analysed through Stata (14.2) and SPSS (20.0). Data were checked for completeness and cleaned of any inconsistencies before conducting the analysis. Descriptive and bivariate analyses were conducted. Numerical data were expressed as the means and standard deviation (means ± SD). The student’s t-test and ANOVA were used to examine differences in the means of variables (average temperature, maximum temperature and HI). ANOVA was used for testing the significance of differences between the mean all-cause mortality (death) values at maximum temperature of <35 °C, 35 °C –39 °C and ≥40 °C, <45 °C and ≥45 °C and HI of 27 °C –32 °C, 32 °C –41 °C, 41 °C–54 °C and >54 °C. Pearson correlation analysis was used to determine the relationship for the maximum temperature, average temperature, minimum temperature, relative humidity and HI with all-cause mortality for lag time effect. Significance was set at P < .05. Days with missing data for temperature and/or humidity were excluded from the analysis.

Result

A total of 75,571 deaths (all-cause mortality) for 1,203 summer days (2006–2015) were analysed with temperature and relative humidity.

Table 1 shows that mean maximum temperature, mean relative humidity and mean HI during summer were 38.4 °C ± 4.5 °C, 34.0 ± 15.8% and 43.0 °C ± 9.5 °C, respectively, for the entire study period. The yearly mean maximum temperature during summer ranges from 37.7 °C ± 4.5 °C for the year 2011 to 40.2 °C ± 3.7 °C in 2010. The highest recorded value for maximum temperature, relative humidity and HI during summer were 48.0 °C, 97% and 92.3 °C, respectively, for the study period. The yearly mean HI was lowest in 2014 (41.2 °C ± 8.2 °C) and highest in 2008 (45.5 °C ± 9.8 °C). The year 2010 was warmer in terms of high temperature with the maximum temperature of ≥40 °C for 65 days as compared to rest of the study period. Table 2 shows that the mean daily all-cause mortality has been estimated at 62.8 ± 15.2 for the study period. There is a significant increase of 39% per day all-cause mortality at the maximum temperature of 45 °C and above as compared to maximum temperature of <45 °C. However only 10% rise per day all-cause mortality for extreme danger days (HI > 54 °C) (Table 3). Table 4 depicts that the mean daily mortality shows a significant association with daily maximum temperature (F = 34.6, P < .001) and HI from caution to danger risk days (F = 5.0, P < .0019). The lag effect of extreme heat on all-cause mortality for the study period (2006 to 2015) was at a peak on the same day of the maximum temperature (r = 0.245 at P < .01) but continues up to four days (Table 5).

Table 1.

Year-wise Statistics of Mean Maximum Temperature, Relative Humidity, Heat Index (HI) and Days with Maximum Temperature ≥40 °C for the Years 2006 to 2015, Jaipur.

Year	Maximum Temperature °C (Mean ± SD)	Highest Recorded Value of Maximum Temperature (°C)	Relative Humidity (%)	Highest Recorded Value of Relative Humidity (%)	HI (^oC)(Mean ± SD)	Highest Recorded Value of HI (°C)	Maximum Temperature ≥40 °C (Days)
2006	38.1 ± 4.5	44.8	39.2 ± 17.0	89	44.6 ± 10.5	78.6	51
2007	38.6 ± 5.2	45.2	35.8 ± 15.1	86	44.0 ± 10.2	79.5	60
2008	38.0 ± 3.3	44.4	41.3 ± 19.4	96	45.5 ± 9.8	69.5	35
2009	39.2 ± 3.9	45.0	28.6 ± 11.1	65	42.3 ± 8.6	69.8	59
2010	40.2 ± 3.7	48.0	24.9 ± 10.8	67	42.2 ± 7.0	69.8	65
2011	37.7 ± 4.5	46.0	34.2 ± 17.6	94	41.9 ± 9.8	79.8	45
2012	38.3 ± 4.1	45.2	32.6 ± 9.4	60	42.6 ± 8.7	68.1	53
2013	38.2 ± 3.9	44.6	32.4 ± 16.2	84	42.3 ± 9.6	71.9	41
2014	38.2 ± 5.2	47.0	32.0 ± 11.5	69	41.2 ± 8.2	61.6	57
2015	38.2 ± 5.8	46.0	38.4 ± 19.3	97	43.7 ± 11.6	92.3	63
2006–2015	38.4 ± 4.5	48.0	34.0 ± 15.8	97	43.0 ± 9.5	92.3	529

Source: PhD thesis data.

Table 2.

Year-wise Summer Days, Highest Recorded Maximum Temperature and All-cause Mortality from 2006 to 2015, Jaipur.

Year	No. of Summer Days	Highest Recorded Maximum Temperature (°C)	Summer All-cause Mortality (Total Deaths)	Mean All-cause Mortality (per Day)
2006	122	44.8	5,843	47.89 ± 7.85
2007	118	45.2	5,884	49.86 ± 9.82
2008	121	44.4	6,158	50.89 ± 9.99
2009	119	45.0	6,988	58.72 ± 9.75
2010	115	48.0	7,592	66.01 ± 16.64
2011	121	46.0	7,407	61.21 ± 9.49
2012	122	45.2	8,128	66.62 ± 10.13
2013	122	44.6	8,703	71.33 ± 11.40
2014	121	47.0	9,260	76.52 ± 12.40
2015	121	46.0	9,608	78.75 ± 10.67
2006–2015	1203	48.0	75,571	62.81 ± 15.2

Source: PhD thesis data.

Note: Temperature data were not available for 17 Days.

Table 3.

All-cause Mortality with Summer Temperature and HI for the Years 2006 to 2015, Jaipur City.

Factor	Day (1203)	No. of Deaths (All-cause Mortality)	Mean Number of Deaths per Day
Maximum temperature (°C) <35 35–39 ≥40	247 427 529	14,505 25,748 35,318	58.72 60.30 66.76
Maximum temperature (°C) <45 ≥45	1,168 35	72,553 3,018	62.11 86.22
Heat index (categories in °C) 27–32 32–41 41–54	121 430 502	6,028 26,620 32,191	58.52 61.90 64.12

Source: PhD thesis data.

Note: Temperature data were not available for 17 days.

Table 4.

Association of Temperature and HI with Summer All-cause Mortality for the Years 2006 to 2015, Jaipur City.

Variable	Categories	n =1203	Mean	t-test/F test
Temperature (average) °C	35–39 <35	203 1000	72.01 60.95	9.84 (P < .0001)
Temperature (maximum) °C	<35 35–39 ≥40	247 427 529	58.72 60.30 66.76	F = 34.58 (P < .0001)
Heat index °C	27–32 32–41 41–54 >54	103 430 502 150	58.52 61.90 64.12 64.31	F = 5.01 (P < .0019)

Source: PhD thesis data.

Table 5.

Lag Time Correlation of Temperature and Humidity with All-cause Mortality Counts (2006 to 2015), Jaipur City.

Pearson Correlation Coefficient	No Lag	1 day	2 days	3 days	4 days
Average temperature (°C)	0.222**	0.198**	0.195**	0.193**	0.179**
Maximum temperature (°C)	0.245**	0.215**	0.190**	0.177**	0.169**
Minimum temperature (°C)	0.252**	0.243**	0.249**	0.239**	0.231**
Humidity (%)	−0.171**	−0.132**	−0.123**	−0.126**	0.098**
HI (°C)	0.100**	0.093**	0.070*	0.053	0.064*

Source: PhD thesis data.

Note: *P < .05; **P < .01.

Discussion

This article aims to draw attention to temperature, heat risk index (relatively under-appreciated climate change determinants for desert city of Jaipur) with all-cause mortality which provides an insight to understand the impact of ambient heat on urban population of Jaipur smart city.

A combination of high temperature, HI and all-cause mortality for Jaipur city was observed and added to literature as solid evidence for unexplored urban area. While similar studies on heat mortality have been carried out in Western countries and even some studies from Southeast Asia, including India, have been available (Anderson & Bell, 2011; De & Mukhopadhyay, 1998; Desai et al., 2015b; Vandentorren et al., 2004) but to the best of our knowledge, this is first article of its kind for Jaipur city.

There is a significant increase in the risk of all-cause mortality, with maximum temperature rise as evident from other studies (Harlan et al., 2014; Rathi et al., 2017; Rocklov et al., 2014; Son et al., 2012). The high HI values tend to be well associated with mortality from all causes, which is supported by Desai et al and Monteiro et al.’s study (Desai et al., 2015b; Monteiro et al., 2013).

Maximum temperature and HI are, respectively, most significant factors for rising all-cause mortality as shown by a rise of 39% deaths/day and 10% deaths/day from this study. This suggests that maximum temperature is more important than HI for Jaipur city. However, it is better to include humidity indicator when measuring the impacts of ambient heat on all-cause mortality.

The present study shows that out of 1,203 summer days there were 529 with a temperature of about 40 °C and 652 out of 1,203 summer days with a feel temperature/heat index of 41 °C and above. This analysis also reveals that there were 35 out of 1203 summer days having temperature ≥45 °C. All of these are important factors not just for increased all-cause mortality but also for heat morbidity. Jaipur therefore needs to prepare and incorporate measures for impacts of such adverse climatic weather.

Limitations

Because age or cause of death data were not available, all-cause mortality data were analysed as previously done (Desai et al., 2015b; Rathi et al., 2017). This study does not distinguish heat-related mortality due to the unavailability of clear causal deaths. Consequently, we used all-cause mortality as an outcome variable and our calculation might be an overestimate or underestimate of the true impact of heat and humidity on deaths. The precision and completeness could not be completely checked because retrospective data were used.

Conclusion and Recommendations

A total of 75,571 deaths (all-cause mortality) for 1,203 summer days (2006–2015) were analysed in relation to temperature and relative humidity. The study concludes that the maximum temperature of ≥45 °C and HI > 41 °C are the important predictors for all-cause mortality of urban population of Jaipur. The mean daily all-cause mortality has been estimated at 62.81 ± 15.2 for the study period. There is an increase of 39% per day all-cause mortality at the maximum temperature of 45 °C and above. This concludes that maximum temperature is more important than HI for Jaipur city. Extreme heat-related mortality merits further analysis in order to reduce harmful health effects among Jaipur’s most vulnerable population.

The findings from this study may lead the foundation for the development of Heat and Health Action Plan to protect populations from the deadly effects of temperature at city level. Hence a city-specific heat and health action plan needs to be developed. We also recommend that the HI should be considered while calculating the all-cause mortality due to extreme heat.

Footnotes

Acknowledgments

The authors would like to acknowledge the support provided by Dr S D Gupta and Dr Arindam Das. They would like to thank Dr Bhupendra Singh (IPS) for helping in acquiring the city specific all-cause mortality data. The authors are grateful to Mr Hira Pant for assisting in data analysis.

Declaration of Conflicting Interests

Funding

The author received no financial support for the research, authorship and/or publication of this article.

Note

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