The effect of temperature on fertility: A province-level analysis of monthly total fertility rates in Italy in 2003 – 2022

The effect of temperature on fertility: A province-level analysis of monthly total fertility rates in Italy in 2003 – 2022 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The effect of temperature on fertility: A province-level analysis of monthly total fertility rates in Italy in 2003 – 2022 Melissa Barba, Raya Muttarak, Federica Querin This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7743281/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Climate change-induced temperature increases and extreme weather events are impacting human health and wellbeing. Warmer temperatures are reported to affect both reproductive health and behaviors, possibly reducing birth rates. In a low fertility context, the potential negative impact that climate change might have on fertility is consequential. This study focuses on Italy, a low-fertility country disproportionately affected by climate change, with sharp regional disparities in both climate zones and economic development. Matching monthly birth registration data for the period 2003 to 2022 with E-OBS meteorological data, we analyze the relationship between heat exposure and total fertility rates in 107 Italian provinces (corresponding to the NUTS-3 classification). Results show that exposure to extremely hot days, which are defined as days with a mean temperature above 25°C, has a relatively immediate impact on conception probabilities as it reduces the total fertility rate nine months later. While this reduction is observed across both cold and hot climate zones, it appears to be larger for warmer provinces. The effect of temperature on fertility also varies with the per capita gross domestic product, where fertility rates in the richest provinces appear to be more sensitive to warming temperatures. The interaction between climate zones and GDP per capita revealed that hot above-average GDP provinces are the most affected by hot temperatures. climate change heat exposure fertility Italy Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Recent evidence indicates that Europe is warming at more than twice the global average, with temperatures over European land areas reaching 2.4°C above the pre-industrial levels during the past five years (EUMETSAT 2025). This rapid warming has led to an increase in extreme weather events, including record-breaking heatwaves, persistent droughts, and flash floods, significantly impacting ecosystems, economies, and human health across the continent. These changes point to the potential influence of shifting environmental and climatic conditions on demographic processes as well. In recent years, several studies have documented the consequences of climate change and extreme temperatures on demographic outcomes such as mortality (Carleton et al., 2020; Masiero et al., 2022 ), infant health (Chen et al., 2020 ; Conte Keivabu & Cozzani, 2022 ; Le & Nguyen, 2021 ) and adult health (Bai et al., 2014 ; Barreca & Shimshack, 2012 ). There have been abundant studies exploring the relationship between climatic factors and migration (Hoffmann et al., 2020 ). With respect to fertility, apart from a few earlier studies focusing primarily on the United States (Barreca et al., 2018 ; Lam & Miron, 1996 ; Seiver, 1985 ), it is only recently that research has begun to examine the climate effects on fertility and reproductive health more broadly. These include studies on South Korea (Cho, 2020 ), Hungary (Hajdu & Hajdu, 2022 ), Spain (Conte Keivabu, et al., 2024 ), France (Noel & Greulich, 2025) and 32 other European countries (Hajdu, 2024 ). These works consistently find a reduction in fertility from eight to ten months after exposure to extremely hot days. This raises the question of whether this reduction in fertility following exposure to extreme heat also applies to Italy, a country characterized by marked regional variation in both climatic zones ranging from Alpine to Mediterranean, and economic conditions, with some of the widest subnational GDP disparities in Europe (Eurostat, 2023). Italy is among the countries in the Mediterranean area where climate change is accelerating most rapidly (Cramer et al., 2018 ; Perkins-Kirkpatrick & Lewis, 2020 ). Given its persistently low total fertility rates, coupled with evidence that climate change is impacting Italy more severely than many other European countries, Italy represents a uniquely important context for studying the potential impact of climate change on reproductive outcome. To the best of our knowledge, this is the first work focusing on the effect of rising temperatures on fertility in Italy. Using the administrative data on birth counts by Italian provinces from 2003 to 2022, we find that warmer temperatures, particularly daily mean temperatures exceeding 25°C, lead to a decrease in fertility rates, with noticeable effects nine months after the temperature spikes. Moreover, the drop in the total fertility rates after heat exposure is recorded for both cold and hot climate zones and is particularly larger for the latter. The effect of temperature on fertility also varies by the level of gross domestic product, with the richest regions being more sensitive to warming temperatures. The interaction between climate zones and GDP per capita further revealed that fertility decline after exposure to rising temperatures is particularly pronounced in the hot regions with GDP per capita above the national average. Our findings highlight the importance of considering geographical and socioeconomic variations on the effect of climate change on fertility outcomes. This study contributes to the emerging field of climate change and fertility in three keyways. First, we provide new empirical evidence from Italy, a high-income country with persistently low fertility rates and evident regional climate variability. Using relatively fine-grained data at the NUTS-3 level over a 20-year period (2003–2022), our analysis confirms patterns previously observed in other European countries, such as the findings for Hungary (Hajdu & Hajdu, 2022 ), Spain (Conte Keivabu et al. 2024 ) and France (Noel & Greulich 2025). Second, we investigate how the relationship between temperature and fertility has evolved over time, assessing whether the effects have become more pronounced or shifted in recent years. Third, we explore regional heterogeneities by examining the interplay between geographical characteristics (i.e., climatic zones) and economic conditions (i.e., GDP per capita). This distinction is particularly important in the Italian context, where colder regions in the North are often also the wealthiest and hotter regions in the South are also the poorest, making it challenging to isolate the separate effects of climate and socioeconomic conditions. The remainder of the paper is structured as follows. The next section outlines the theoretical mechanisms through which climatic conditions may influence fertility. This is followed by a description of the Italian context. We then present the data and methods used in the analysis, followed by both descriptive and multivariate results. A series of sensitivity analyses and robustness checks are also included to assess the reliability of our findings. The final section discusses the results and concludes the paper. Mechanisms linking climate conditions to fertility outcomes Several pathways have been proposed to explain how climatic conditions, particularly extreme heat, can influence fertility. These mechanisms operate through biological, behavioral, and socioeconomic channels, each potentially contributing to short- and long-term changes in reproductive outcomes. With respect to physiological channel, previous studies proved that extreme temperatures have an impact on reproductive health because they affect both spermatogenesis (Hansen, 2009 ), sperm quality (Santi et al., 2016 ), and ovulation cycles (Gaskins et al., 2021 ), therefore reducing the probability of conception, gestational length (Barreca & Schaller, 2020 ), and the probability of carrying pregnancies to term (Rylander et al., 2013 ). Concerning the probability of successfully completing a pregnancy, extreme heat exposure might increase risk of spontaneous abortion in the first trimester, while in the weeks before delivery it might increases the risk of stillbirth (Kanner, 2020 and McElroy, 2022). Males are overall more affected by the negative consequences of heat on reproductive health (Barreca et al., 2018 ; Rojansky et al., 1992 ; Hansen, 2009 ). Heat exposure also has an impact on sex ratios at birth, resulting in a decrease in male births (Ghany et al., 2024 ). Warmer temperatures, especially heatwaves and high humidity levels, are also correlated with poorer health in general, as they increase the probability of illnesses such as dizziness, heat strokes, influenza and exhaustion (Bai et al., 2014 ; Barreca & Shimshack, 2012 ). These temperature-induced diseases might impact fecundity and frequency of sexual intercourse, potentially affecting overall fertility. Contraceptive efficacy might also be negatively affected in relation to both high temperatures and prior health conditions. For example, hormonal birth control pills experience diminished effectiveness when stored at above room temperature (Barreca et al., 2018 ). The effectiveness of condoms also worsens at high temperatures (Gerofi & Sorensen 2016 ). The failure of contraceptive methods due to hot temperatures would lead to an increase in birth rates, potentially counterbalancing the negative effects due to physiological and behavioral factors. Extreme temperatures can affect reproductive behaviors by reducing the frequency of sexual activity. This may occur due to discomfort, fatigue, or changes in daily routines and sexual desire, which can potentially decrease the likelihood of conception. Being a sensitive topic, empirical evidence on sexual behaviors is quite scarce and mixed: one study on sub-Saharan Africa reported that the number of sexually active women decreased with temperature (Wilde et al., 2017 ), while in Hungary no correlation was detected (Hajdu & Hajdu, 2019 ). Recent scholarship is investigating the role of climate change concern – and more in general of environmental instability – on fertility outcomes by studying individuals’ perceptions of the climate crisis and the implications on reproductive decisions. This approach allows us to consider how subjective believes shape fertility (Puglisi et al., 2025 ). Seasonal patterns in births have been studied in demographic literature for over 50 years across various settings (Cowgill, 1966 ; Lam & Miron, 1991 ; Udry & Morris, 1967 ). Several studies have detected systematic differences in birth timing with planned pregnancies resulting in spring births. Historically, such timing may have been influenced by agricultural cycles: for instance, marriages and conceptions were frequently scheduled after harvest (Ellison, 2005). In contemporary industrialized contexts, seasonality in births tends to be shaped by sociocultural factors such as school enrollment cut-off dates (Dahlberg & Andersson, 2019 ), expectations about future economic security (Caleiro, 2010 ), or the timing of religious holidays (Friger et al., 2009 ; Herteliu et al., 2015 ; Polašek et al., 2005 ), along with the aforementioned environmental aspects. Studies focusing on behavioral mechanisms have highlighted that seasonal variation in fertility rates is more evident among better educated, stably married women, who are more likely to plan their pregnancy (Bobak, 2001 ). Climate change may increasingly disrupt traditional seasonal patterns in births by altering the environmental and health conditions under which conceptions and pregnancies occur. Rising temperatures, extreme heat events, and deteriorating air quality – especially during summer months – have been associated with reduced conception rates and increased risks of adverse pregnancy outcomes, such as preterm births or fetal loss. These impacts may disincentivize conceptions during warmer periods, thereby shifting birth seasonality over time. Furthermore, climate-induced variability in agricultural productivity and economic uncertainty could affect household decision-making around family planning, particularly in settings still reliant on seasonal labor or income. Thus, climate change introduces new dimensions to the seasonality-fertility nexus, potentially reshaping reproductive behaviors in both high- and low-income settings. Italian Context The Italian average yearly temperature has increased by almost 2°C in the last 60 years, with a warming rate stronger than the world average for the past four decades. In 2022, the temperature difference reached the highest spike of 1.9°C, with respect to the 1930–1960 baseline (Fig. 1 ). Temperature is increasing more quickly in high-altitude areas and during the spring and summer than in other seasons. Italy’s average annual temperature is likely to keep surging, causing the number of hot days (daily maximum temperature above 25°C) and tropical nights (nighttime minimum temperature above 20°C) to increase. Although low and medium precipitation events have become less recurrent, the intensity of precipitation episodes per year has expanded all around the national territory. Over the last two decades, Italian total fertility rates ranged from 1.29 children per woman in 2003 to 1.24 in 2022. Countries with a total fertility rate under 1.30 are classified as lowest-low fertility, and Italy, along with Spain, was the first European country to reach such level in the early Nineties. Sustained low fertility leads to rapid population aging and reduced relative cohort sizes (Kohler et al., 2002 ). The territorial distribution of TFRs in 2022 is presented in Fig. 2 . Total fertility rates above the national average are found in the North and in Sicily, particularly the highest value of 2022 (1.64) recorded in the province of Bolzano. Sardinian provinces and internal areas in the Center and in the South present instead the lowest fertility rates, with the lowest score of 2022 (0.88) reported in South Sardinia. With a GDP per capita equal to 36,0720€ in 2023 (World Bank, 2025), Italy is considered as a high developed country. However, variations at the provincial level are pronounced: the lowest GDP per capita is recorded in Agrigento (14,872€) and the highest in Milan (53,109€). In general, Northern and Central provinces reveal higher GDP per capita than Southern and Islander provinces. Data This study analyzes the relationship between exposure to warm temperatures and fertility rates in 107 Italian provinces. The provincial administrative division corresponds to the NUTS3 classification. The total number of provinces changed throughout the selected period because new provinces were created while others were abolished. Comparability through the years is guaranteed using the current borders division (of 2023) as a benchmark for the entire time frame. The analysis spans from 2003 to 2022, ensuring a comprehensive assessment of trends over two decades. The starting year, 2003, was chosen as it marks a period with reliable and consistent data availability, while 2022 represents the most recent complete year of data. The study is conducted at the NUTS3 level, as going lower would present significant challenges: in small municipalities it is likely to find zero births in certain months, leading to unstable estimates and high year-to-year variability in total fertility rates. By working at the provincial level, we ensure statistical robustness while still capturing local differences effectively. Fertility data We combine two main sources of data: administrative data for fertility and GDP measures and E-OBS meteorological data for climate. We obtained administrative data from the Italian National Institute of Statistics (ISTAT), including the monthly number of births per women in fertility age (conventionally defined as between 15 and 49 years old) by province and the annual total number of women by age per province. The number of women per age-group interval in each month was then obtained by linear interpolation. Combining monthly births and number of women in fertility age we computed monthly total fertility rates (TFRs), which constitute our main outcome of interest. Spanning across 2003 to 2022, monthly analysis is performed to capture the seasonality of the total fertility rate. The total sample of province-months is 25,680. The trend in fertility is shown in Figure A1 in the supplementary materials. After a slight initial increase in total fertility rates for the first years of the analysis, total fertility rates are declining consistently starting from 2011. The figure also shows the seasonality of births: during warmer months, especially from July to October, TFRs are visibly higher than in the first months of the year, especially from February to April. The average seasonal peak of births is observed in September. Climate data E-OBS meteorological data with a resolution of 0.1-degree grid cells is collected by weather stations located all around Europe and is available in the Copernicus Climate Data Store (CDS). The analysis employs climate data on temperature, relative humidity, precipitation amount, surface shortwave downwelling radiation, vegetation extension, and air pollution. Meteorological data is weighted by population at the provincial level. The temperature data is included at the daily level by constructing 7 temperature bins (0°C; 0 to 5°C; 5 to 10°C; 10 to 15°C; 15 to 20°C; 20 to 25°C; and > 25°C) and computing the number of days per month in which the daily mean temperature fell in each range for each province. Daily mean temperature accounts for both the daytime high and nighttime low temperatures, which act together upon various health risks. Bin classification addresses potential non-linearity of the effect of temperature on fertility at a given lagged month and avoids functional form specifications, since it is relatively nonparametric (Dell, 2014). Relative humidity is a measure of how saturated the air is with water vapor compared with the total amount that can be held at a given temperature. Humidity aggravates the thermal stress experienced by people in extreme weather conditions because, at a given temperature, the higher the humidity, the lower the ability of the human body to cool itself by sweating, and the higher the risk of negative health consequences (Budd, 2008 ; Raymond et al., 2020 ). Considering the role of humidity in influencing the effect of heat on births may be important for a better understanding of the potential consequences of climate change (Hajdu, 2024 ). High-humidity days are defined as days with a relative humidity above 75%. Precipitation occurs when a portion of the atmosphere becomes saturated with water vapor reaching 100% relative humidity, so that the water condenses and falls. In the analysis, we control for precipitation measured as the total millimeters of precipitation recorded in a province in a month. Surface downwelling shortwave is the sum of direct and diffuse solar radiation on the surface. The atmosphere allows the heat from the Sun (short-wave radiation) to pass through to the Earth's surface, which then gives off heat (long-wave radiation). This heat is trapped by greenhouse gases, which radiate the heat back towards Earth. Solar radiation is connected to climate change because this process ends up heating the Earth. The vegetation measure used in this analysis is the Leaf Area Index (LAI), a common measure of plant canopy defined as the one-sided green leaf area per unit ground surface area. It depends on the size of the canopy, but also on its density, and the angle at which leaves are oriented in relation to one another and to light sources and it varies with seasonal changes in plant activity (Maass, 1995). Air pollution is measured by Particulate Matter 2.5µg/m³ (PM2.5), which is widely used in studies on the negative impact of air quality on health (Colmer et al., 2020 ). Considering the combined effect of heat and air pollution is crucial because the atmospheric conditions that contribute to persistently hot weather also exacerbate air pollution. A temperature rise due to air pollution occurs gradually and air pollution occurring in a certain month is not likely to affect temperature in the immediate future (Cho, 2020 ). However, there is evidence that elevated levels of air pollution such as PM 2.5, O 3 , and NO 2 alter physiological processes in male and female fertility (Kumar & Singh, 2022 and Conforti et al., 2018 ). The SPEI (Standardized Precipitation-Evapotranspiration Index) is a multi-scalar drought index based on climatic data that can be used for determining the onset, duration and magnitude of drought conditions with respect to normal conditions in a variety of natural and managed systems such as crops, ecosystems, rivers, and water resources (Vicente-Serrano et al., 2010 ). The Global SPEI database (SPEIbase) offers information about drought conditions at the global scale, with a 0.5 degrees spatial resolution and a monthly time resolution. The SPEI can measure the start and the end of drought episodes, as well as their severity through time and space. An important advantage of the SPEI over other drought indices is that its multi-scalar characteristics enable identification of different drought types and impacts in the context of climate change. SPEI was studied as an explanatory variable in supplementary materials. Economic data Over the last decades, in many OECD countries fertility rates dropped significantly while the gross domestic product (GDP) continued to increase. The strong negative correlation between GDP per capita and fertility might not hold for high levels of per capita economic output, and the relation might turn positive from a certain threshold level of economic development. In several highly developed countries, total fertility rates have been growing since the early 2000s, along with continuing economic development, for example in France, the United States and Czech Republic (Luci-Greulich & Thévenon, 2014 ). Nordic countries, despite having relatively high fertility levels, large female labor market participation, and well-established family-support social policies, have experiences substantial fertility decline since 2010 (Campisi et al., 2022). The impact of economic growth on fertility is therefore ambiguous. The GDP per capita is obtained from Eurostat and computed as a mean over the period between 2013 and 2019, and the distribution is classified in quartiles. The lowest levels of GDP belong to the first quartile, while the highest are in the fourth quartile. The provinces with higher GDP per capita are also the ones presenting higher TFRs in general. GDP data is not included directly in the model, and the regression is run separately for all GDP quartiles. Methodology The study employs an OLS panel fixed effects model to analyze the relationship between temperature and fertility outcomes. The outline of the model is the following: where the outcome of interest is the logarithm of the monthly TFR in each province and month (Y pt ), and the main explanatory variable is the temperature categorized in bin variables and measured at the month of birth and up to fifteen months prior to birth (TEMP j p,t−k ). The other meteorological control variables X p,t−9 (relative humidity, precipitation amount, surface shortwave downwelling radiation, vegetation extension, and air pollution) are measured at the month of conception at the provincial unit. The model includes two fixed effects: province-by-year fixed effect (γ py ) and province-by-month fixed effect (α pm ) to capture province-specific factors and seasonality. The variable δ qm represents the polynomial quadratic in the year-month of conception used to account for possible convergences in seasonality across provinces over time. The number of women of reproductive age in each province in the year before birth is used as a weight. Standard errors are clustered at the provincial level (ε pt ). Results Summary statistics Table 1 reports the summary statistics for the monthly values at the provincial level of the variables of the analysis throughout the entire period. The province average monthly TFR of 0.11 reflects the lowest-low levels of yearly total fertility rates in Italy. Days with temperatures between 10°C and 15°C are the most common on average, while days exceeding 30°C are the least frequent. Table 1 – Summary statistics Mean SD Min Max TFR 0.11 0.01 0.02 0.17 Births 392 462 28 4,773 Women in fertility age 123,326 135,883 15,083 968,143 30°C 0.03 0.32 0 11 Relative Humidity Precipitation 71.79 2.45 7.87 2.05 39.11 0 92.66 22.26 Solar radiation LAI index PM2.5 Population Density 159.40 3.93 1.85 265 77.54 1.24 8.04 370 23.09 0.13 0.35 35 407.30 6.58 7.30 2,6199 Notes: Summary statistics for the monthly values of the variables in our main analysis in the 107 Italian provinces in 2003–2022. Sources: ISTAT (demographic data), CDS (meteorological data) The effect of temperature on fertility Figure 3 presents the effect of exposure to each temperature bin on the TFR nine months later with 95% confidence intervals. The effects are compared to a day with a mean temperature of 10–15°C. The temperature bins of exposure in other months are also included in the analysis but not reported in the figure. Warmer days have a negative effect on the total fertility rates, in particular the last temperature bin (> 25°C) has the largest negative effect with a TFR decrease of -0.31%, while colder days do not substantially alter fertility. This is coherent with the previous studies (Barreca et al., 2018 ; Hajdu, 2024 ; Conte Keivabu et al., 2024 ). Next, we examine how the timing of exposure to an additional hot day (≥ 25°C) may differently affect fertility. Figure 4 displays the estimated effect of an additional hot day with a mean temperature above 25°C on fertility, measured from zero to fifteen months following exposure. Note that the model controls for a full set of temperature bins, but only the effects for the last one are displayed in Fig. 4 , as it is the one with a larger negative effect on fertility. The effects are compared to a day with a mean temperature of 10–15°C. There is a clear reduction of -0.31% in TFR at month nine, confirming that a hot day has a relatively immediate impact on conception probabilities. Barreca et al. ( 2018 ) examining the US data showed that the effect of extreme temperatures is also particularly strong also at the ten-month lag. Similarly, we find that there is a decrease in total fertility rates ten months after exposure to heat (Figure A2 in the Supplementary Materials, though the effect is less than half of the previous month (-0.15%). Furthermore, Barreca et al. ( 2018 ) observed a positive increase in TFR in the months following the nine-month mark, which might be a signal of recuperation of the births averted because of the heat. Although our analysis does not detect such a significant positive trend, it shows that fertility declines around nine and ten months after exposure to high temperatures, with the downward trend tapering off thereafter. For temperatures exceeding 30°C (Fig. A3 in the supplementary materials) there is an increase in total fertility rates from 11 to 15 months after heat exposure, but the coefficients are not statistically significant. The effect of temperature on fertility over time We further explore whether the effect of temperature exposure on fertility has changed over the years. Previous findings show that the effect of temperature on fertility might decrease over time (Barreca, 2018) or remain stable (Hajdu, 2024 ). On the one hand, the effect may be reduced in more recent time periods due to adaptation. On the other hand, the impact of climate change has become intensified in the last decade, and the effect may become stronger. The time span is therefore divided into two equal groups: the first one going from 2003 to 2012, and the second one from 2013 to 2022. In the case of Italy, the effect size increased over the years. The coefficient for days above 25° C goes from − 0.33% to − 0.37%, while the coefficient for days between 20 and 25° C moves from − 0.13% to − 0.17%, as shown in Fig. 5 . The stronger effect observed in the later period might be due to an increase in the number of days over 25° C as a result of the intensification of climate change over the years. The recent period includes more frequent and severe extreme-temperature events, which might have a larger impact on health and life planning, leading to a more pronounced fertility decline. For the first period, negative temperatures are associated with a positive increase in fertility rate (0.22%), but this does not happen in the following years. Lower temperatures correspond to winter months, which are historically associated with higher conception rates. This seasonal fertility pattern might have been more pronounced in the earlier period. The effect of temperature on fertility by climate zones The literature provides evidence that fertility rates in colder regions of a given country are more sensitive to heat shocks than warmer regions, probably due to lack of infrastructures and adaptation practices. Barreca et al. ( 2018 ) discovered that the effect of warmer days on fertility was larger in the colder climatic zones of the United States and Conte Keivabu et al. ( 2024 ) found the same effect in Spanish provinces. In this section, we explore how the relationship between temperature and fertility varies with climatic conditions by classifying Italian provinces into hot and cold zones, according to whether the province is above or below the median temperature in the sample. Cold provinces are mostly located in the North and in internal areas, while hot provinces are mostly located on islands and coastal areas. Figure 6 replicates the analysis in Fig. 3 but distinguishes between the two climate zones. In contrast with previous studies, the graph reveals that the effect of temperatures above 25°C on fertility is stronger for hot climates (-0.35%) than for cold ones (-0.21%). This difference might be explained by the fact that colder provinces in the North are generally better equipped to cope with occasional heat through widespread access to healthcare and air conditioning, while hotter provinces in the South tend to have more fragile healthcare systems and less access to cooling infrastructures (ISTAT, 2022 ). The effect of temperature on fertility by GDP Looking at the effects of heat shocks on different levels of GDP, one might expect richer and more fertile provinces to be able to handle or to adapt to temperature extremes better. This is not the case for Italian provinces over the period of the analysis. Figure 7 reveals that the poorest (1st quartile) and the richest (4th quartile) provinces are more affected by warmer temperatures, in particular the richest provinces are experiencing the largest contraction in total fertility rates (-0.41%). The reduction in poorest provinces might be due to limited adaptation infrastructures, such as widespread air conditioning and public health services, and the largest proportion of outdoor labor, that might lead to a more disruptive effect of heat exposure at the physiological level. The decline in fertility in the richest provinces shows that wealthier areas are also affected by warming temperatures. In this case, exposure to hot weather might reshape individual behaviors and intentions, resulting in pregnancy postponement and signaling greater responsiveness in fertility behavior to climate-related factors. The interaction of climate zones and GDP on fertility After examining the separate effects of climate zones and gross domestic product per capita on fertility, we extend the analysis to include their interaction. This step is crucial because climatic conditions and economic development are not evenly distributed across Italy and may exert overlapping or confounding influences on fertility. Colder regions are predominantly located in the northern part of the country, which is also the wealthiest. On the other hand, hot regions are mostly found in the South and in the islands, which are generally less wealthy. As a result, it is difficult to disentangle whether the heat-induced reduction in fertility is driven by climatic factors, economic conditions, or both. Here we explicitly model the interaction between climate zones and GDP to better isolate the distinct and combined effects of environmental and socioeconomic contexts on fertility outcomes. The per capita gross domestic product is sorted into two categories (above or below the national average), as the number of hot provinces in the fourth quartile of GDP distribution and the number of cold provinces with the first quartile of GDP are low. The number of provinces within this category is limited (14 out of 107) and most of them are in northern and central Italy. In the same way, there are only 15 provinces with a cold climate and below-average GDP. Therefore, most provinces fall into the remaining two categories: cold provinces with an above-average GDP (39) and hot provinces with below-average GDP (39). This reflects the territoriality component of the variables. Figure 8 shows the effect on fertility of these interactions. The total fertility rate reveals a significant negative value for the highest temperature bin in each climate zone and for each level of GDP, except for cold provinces with a below-average GDP. The magnitude of this effect is notably stronger (-0.39%) in hot provinces with above-average GDP. Notably, when we further break down this effect by GDP level, we find that the positive association is concentrated in poorer hot regions. One possible explanation for this pattern is that colder-than-usual periods in hot and economically disadvantaged areas may reduce outdoor economic or agricultural activity, leading to increased time spent indoors and a potential rise in conception rates. Additionally, in contexts where access to heating (Istat 2022 ) or alternative forms of indoor recreation is limited, cold spells may inadvertently encourage behaviors associated with higher fertility, such as cohabitation or reduced mobility. It is also possible that cold-related hardship fosters a desire for family support or security, particularly in settings where social or economic uncertainty is high. Robustness checks In this section, we perform a series of robustness checks to assess whether our results hold using alternative climate measures, including relative temperatures, temperature anomalies and SPEI index (a drought indicator). Relative temperatures Climate literature highlights the importance of using relative measures of temperature alongside absolute ones to account for substantial variation in average temperatures, which may lead to different adaptation responses (Cil & Kim, 2022 ). Relative measures help address concerns about within-province climate variations s, as they focus less on absolute differences across areas and more on deviations from local norms. Relative temperature bins are constructed based on the percentile distribution of temperatures within each province. Temperatures are then classified into seven categories: 99th. In this distribution, the 99th percentile corresponds to values ranging from 9.06°C in Aosta to 28.85°C in Padova. Figures A4 and A5 in the supplementary material present results consistent with the main analysis: in the in the highest percentile range -- representing relatively extreme heat --fertility rates decline nine months after exposure, although with smaller effect sizes (-0.19%). Temperature anomalies Another way to measure relative temperature is through temperature anomalies, which compare current temperatures to a long-term average based on a defined reference period. Following the World Meteorological Organization (WMO) guidelines, which recommend a 30-year baseline, this analysis uses the period 1970 to 2000 as the reference. A temperature anomaly is calculated as the difference between a given temperature and the average temperature over the reference period. Standardized anomalies are calculated by dividing anomalies by the climatological standard deviation, thereby removing the effects of dispersion. Figure A6 in the supplementary materials shows that positive temperature anomalies, i.e. when temperatures get warmer than the reference period, are associated with a decline in fertility rates nine months later. The estimated effect size (-0.53%) is larger than that found in the main analysis. The effect of SPEI on fertility This analysis includes the Standardized Precipitation-Evapotranspiration Index (SPEI) as an additional climate indicator to examine its effects on fertility. The SPEI is calculated from time lags ranging from 1 to 24 months to capture drought conditions over both short to long periods. SPEI values are grouped into five categories indicating severity: dry, moderately dry, normal, moderately wet, and wet. Figure A7 shows the relationship between exposure to different SPEI accumulation levels on fertility. The results suggest no significant association between dry or wet conditions and fertility outcomes. Discussion and Conclusion This study analyzes the impact of temperature on fertility in Italy over a period of twenty years and discloses the adverse effect of warm days (with a mean daily temperature above 25°C) on monthly total fertility rates and the null effect of cold days. The fall in fertility occurs between 9 and 10 months after exposure, suggesting that heat both immediately reduces conception probabilities and causes some of the affected population to conceive in following months. The effect size of the exposure to each additional day with a temperature above the 25°C threshold is comparable to previous studies by Barreca (2018) and Cho ( 2020 ). The effect of the decline in fertility due to heat exposure translates into around 192 births lost for each day above 25°C in Italy over the study period 2003–2022. The relationship between temperature and fertility is consistent across both climate zones, with a decline in fertility observed at the highest temperature bin. The effect is more pronounced in hotter regions. Fertility responses to temperature also vary by GDP levels: both the wealthiest and the poorest regions in Italy show greater sensitivity to high temperatures. Typically, wealthier provinces are located in the North, and are exposed to colder temperatures, while poorer ones are situated in the South and in the Islands, where warmer temperatures prevail. The interaction between climate zone and GDP levels confirms that hot regions present a slightly larger reduction in fertility rates with respect to cold ones, and the adverse effect of temperature is more pronounced in above-average GDP provinces. The heightened vulnerability to warm days in hot areas – despite their climatic familiarity -- has not beedn widely documented in the literature and may be linked to socio-economic factors that hinder adaptation and mitigation of the adverse effects of heat. This work is not withou limitations. Firstly, using monthly instead of weekly data reduces the accuracy of the analysis because it cannot unravel physiological mechanisms that might result in decreasing conception probabilities. Moreover, in this kind of analysis it is impossible to test behavioral mechanisms such as how temperature might affect sexual behaviors, which is an interesting path for future research. Using province level fertility data reduces the spatial granularity of the study as meteorological variables might differ within the provincial borders and considering mean values decreases the precision of the analysis. This study complements the emerging research on the relationship between climate change and fertility providing new empirical evidence from Italy and confirms the consistent trends observed in other countries around the world. Moreover, it is the first work that explores the regional heterogeneities of a country by examining the interplay between geographical characteristics and economic conditions. This approach is essential in analyzing the Italian context, where isolating the separate effects of the two components becomes difficult, as the colder regions in the North are also the wealthiest and warmer regions in the South are also the poorest. This study has important policy consequences as the negative correlation between rising temperatures and fertility will likely be aggravated by climate change, threatening the rebound from lowest-low fertility levels and accelerating the ageing of an already old population. Declarations Funding Research was supported by funds from XXX. Author Contribution M.B., R.M., and F.Q. wrote the main manuscript text. M.B. prepared all figures. All authors reviewed the manuscript. 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04:26:21","extension":"xml","order_by":22,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":142402,"visible":true,"origin":"","legend":"","description":"","filename":"f155e6d7564942d082e0b0504cc7c6e41structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7743281/v1/d77587d2a6958cb64c760dd8.xml"},{"id":94988827,"identity":"fe870b03-e02e-4530-b25b-b88355052225","added_by":"auto","created_at":"2025-11-03 07:11:05","extension":"html","order_by":23,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":152734,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7743281/v1/9ae3127c92d394c7af1dce8b.html"},{"id":94978558,"identity":"35d558b2-4ee4-4036-b423-3a1bef452a36","added_by":"auto","created_at":"2025-11-03 04:26:20","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":132991,"visible":true,"origin":"","legend":"\u003cp\u003eMean annual temperature differences from 1960 to 2022. Reference period 1930 - 1960. Italian (red) and global (blue). Notes: data from Copernicus Data Store (2025)\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-7743281/v1/f7414afc4720ecc3e62c57ee.png"},{"id":94989300,"identity":"c1778786-5d8c-42e4-9f76-b8cec7e15f94","added_by":"auto","created_at":"2025-11-03 07:12:35","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":241060,"visible":true,"origin":"","legend":"\u003cp\u003eTotal Fertility Rate by province in 2022. Notes: data from ISTAT.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-7743281/v1/88bb2c9eb9fdc5ddeb91eee8.png"},{"id":94978551,"identity":"bf08872f-b6dc-424e-ac33-f14d1a03670e","added_by":"auto","created_at":"2025-11-03 04:26:20","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":55669,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of mean temperature on fertility 9 months after exposure. Notes: coefficients are estimated based on equation (1) with 95% confidence intervals. The figure shows only the coefficients for the 9th month of exposure. The temperature bins of exposure in the other months (0-8 and 10-15) are included in the analysis but not reported in the figure\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-7743281/v1/10e69848a767c6b054a24b56.png"},{"id":94988572,"identity":"6f8f3d92-9e39-4c5e-9677-c6d1ea945731","added_by":"auto","created_at":"2025-11-03 07:09:56","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":61511,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of a day with temperature \u0026gt;25°C on fertility from 0 to 15 months from exposure. Notes: coefficients are estimated based on equation (1) with 95% confidence intervals. The figure reports only the coefficients for the temperature bin \u0026gt;25°C at different months from exposure. Exposure to the other temperature bins is included in the analysis but not reported in the figure\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-7743281/v1/2389d32c2f395cf1b71b15c4.png"},{"id":94988523,"identity":"19270a0c-7e06-43fc-95b3-fb5eee05d89e","added_by":"auto","created_at":"2025-11-03 07:09:41","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":74048,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of mean temperature on fertility 9 months after exposure, by time periods. Notes: coefficients are estimated based on equation (1) with 95% confidence intervals. The figure shows only the coefficients for the 9th month of exposure. The temperature bins of exposure in the other months (0-8 and 10-15) are included in the analysis but not reported in the figure\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-7743281/v1/c65072bef4be019977feb37b.png"},{"id":94978569,"identity":"690712c5-b439-4b2f-b792-d012223b6666","added_by":"auto","created_at":"2025-11-03 04:26:21","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":61548,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of temperature on fertility by climate zones. Notes: coefficients are estimated based on equation (1) with 95% confidence intervals. The figure shows only the coefficients for the 9th month of exposure. The temperature bins of exposure in the other months (0-8 and 10-15) are included in the analysis but not reported in the figure\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-7743281/v1/470c48f68e152d48d76bdfd0.png"},{"id":94978562,"identity":"94dcc017-73d1-40bb-b13d-abf162c546dd","added_by":"auto","created_at":"2025-11-03 04:26:20","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":74379,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of temperature on fertility by GDP per capita quartiles. Notes: coefficients are estimated based on equation (1) with 95% confidence intervals. The figure shows only the coefficients for the 9th month of exposure. The temperature bins of exposure in the other months (0-8 and 10-15) are included in the analysis but not reported in the figure\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-7743281/v1/7d7406edc6cda6797b64d89a.png"},{"id":94978576,"identity":"b9be0b69-30ee-4047-a046-b8b6443f7267","added_by":"auto","created_at":"2025-11-03 04:26:21","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":171844,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of the interaction of climate zones and GDP on fertility. Notes: coefficients are estimated based on equation (1) with 95% confidence intervals. The figure shows only the coefficients for the 9th month of exposure. The temperature bins of exposure in the other months (0-8 and 10-15) are included in the analysis but not reported in the figure\u003c/p\u003e","description":"","filename":"image9.png","url":"https://assets-eu.researchsquare.com/files/rs-7743281/v1/c92e57850d9d7a0c3bd78ac6.png"},{"id":94991011,"identity":"fc933600-bf5c-46d7-a179-07bee3b3263d","added_by":"auto","created_at":"2025-11-03 07:18:56","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1443695,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7743281/v1/83215620-46d9-45e4-a129-e6cd00940ed3.pdf"},{"id":94989229,"identity":"02e5a2d3-e9ec-437e-81d5-8a5d6dcef168","added_by":"auto","created_at":"2025-11-03 07:12:27","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":257646,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-7743281/v1/149215f0b1ffea22ce7302ab.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The effect of temperature on fertility: A province-level analysis of monthly total fertility rates in Italy in 2003 – 2022","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRecent evidence indicates that Europe is warming at more than twice the global average, with temperatures over European land areas reaching 2.4\u0026deg;C above the pre-industrial levels during the past five years (EUMETSAT 2025). This rapid warming has led to an increase in extreme weather events, including record-breaking heatwaves, persistent droughts, and flash floods, significantly impacting ecosystems, economies, and human health across the continent. These changes point to the potential influence of shifting environmental and climatic conditions on demographic processes as well. In recent years, several studies have documented the consequences of climate change and extreme temperatures on demographic outcomes such as mortality (Carleton et al., 2020; Masiero et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), infant health (Chen et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Conte Keivabu \u0026amp; Cozzani, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Le \u0026amp; Nguyen, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and adult health (Bai et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Barreca \u0026amp; Shimshack, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). There have been abundant studies exploring the relationship between climatic factors and migration (Hoffmann et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). With respect to fertility, apart from a few earlier studies focusing primarily on the United States (Barreca et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Lam \u0026amp; Miron, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Seiver, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e1985\u003c/span\u003e), it is only recently that research has begun to examine the climate effects on fertility and reproductive health more broadly. These include studies on South Korea (Cho, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), Hungary (Hajdu \u0026amp; Hajdu, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), Spain (Conte Keivabu, et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), France (Noel \u0026amp; Greulich, 2025) and 32 other European countries (Hajdu, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). These works consistently find a reduction in fertility from eight to ten months after exposure to extremely hot days.\u003c/p\u003e\u003cp\u003eThis raises the question of whether this reduction in fertility following exposure to extreme heat also applies to Italy, a country characterized by marked regional variation in both climatic zones ranging from Alpine to Mediterranean, and economic conditions, with some of the widest subnational GDP disparities in Europe (Eurostat, 2023). Italy is among the countries in the Mediterranean area where climate change is accelerating most rapidly (Cramer et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Perkins-Kirkpatrick \u0026amp; Lewis, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Given its persistently low total fertility rates, coupled with evidence that climate change is impacting Italy more severely than many other European countries, Italy represents a uniquely important context for studying the potential impact of climate change on reproductive outcome. To the best of our knowledge, this is the first work focusing on the effect of rising temperatures on fertility in Italy. Using the administrative data on birth counts by Italian provinces from 2003 to 2022, we find that warmer temperatures, particularly daily mean temperatures exceeding 25\u0026deg;C, lead to a decrease in fertility rates, with noticeable effects nine months after the temperature spikes. Moreover, the drop in the total fertility rates after heat exposure is recorded for both cold and hot climate zones and is particularly larger for the latter. The effect of temperature on fertility also varies by the level of gross domestic product, with the richest regions being more sensitive to warming temperatures. The interaction between climate zones and GDP per capita further revealed that fertility decline after exposure to rising temperatures is particularly pronounced in the hot regions with GDP per capita above the national average. Our findings highlight the importance of considering geographical and socioeconomic variations on the effect of climate change on fertility outcomes.\u003c/p\u003e\u003cp\u003eThis study contributes to the emerging field of climate change and fertility in three keyways. First, we provide new empirical evidence from Italy, a high-income country with persistently low fertility rates and evident regional climate variability. Using relatively fine-grained data at the NUTS-3 level over a 20-year period (2003\u0026ndash;2022), our analysis confirms patterns previously observed in other European countries, such as the findings for Hungary (Hajdu \u0026amp; Hajdu, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), Spain (Conte Keivabu et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) and France (Noel \u0026amp; Greulich 2025). Second, we investigate how the relationship between temperature and fertility has evolved over time, assessing whether the effects have become more pronounced or shifted in recent years. Third, we explore regional heterogeneities by examining the interplay between geographical characteristics (i.e., climatic zones) and economic conditions (i.e., GDP per capita). This distinction is particularly important in the Italian context, where colder regions in the North are often also the wealthiest and hotter regions in the South are also the poorest, making it challenging to isolate the separate effects of climate and socioeconomic conditions.\u003c/p\u003e\u003cp\u003eThe remainder of the paper is structured as follows. The next section outlines the theoretical mechanisms through which climatic conditions may influence fertility. This is followed by a description of the Italian context. We then present the data and methods used in the analysis, followed by both descriptive and multivariate results. A series of sensitivity analyses and robustness checks are also included to assess the reliability of our findings. The final section discusses the results and concludes the paper.\u003c/p\u003e\n\u003ch3\u003eMechanisms linking climate conditions to fertility outcomes\u003c/h3\u003e\n\u003cp\u003eSeveral pathways have been proposed to explain how climatic conditions, particularly extreme heat, can influence fertility. These mechanisms operate through biological, behavioral, and socioeconomic channels, each potentially contributing to short- and long-term changes in reproductive outcomes. With respect to physiological channel, previous studies proved that extreme temperatures have an impact on reproductive health because they affect both spermatogenesis (Hansen, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), sperm quality (Santi et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), and ovulation cycles (Gaskins et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), therefore reducing the probability of conception, gestational length (Barreca \u0026amp; Schaller, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), and the probability of carrying pregnancies to term (Rylander et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Concerning the probability of successfully completing a pregnancy, extreme heat exposure might increase risk of spontaneous abortion in the first trimester, while in the weeks before delivery it might increases the risk of stillbirth (Kanner, 2020 and McElroy, 2022). Males are overall more affected by the negative consequences of heat on reproductive health (Barreca et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Rojansky et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Hansen, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Heat exposure also has an impact on sex ratios at birth, resulting in a decrease in male births (Ghany et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eWarmer temperatures, especially heatwaves and high humidity levels, are also correlated with poorer health in general, as they increase the probability of illnesses such as dizziness, heat strokes, influenza and exhaustion (Bai et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Barreca \u0026amp; Shimshack, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). These temperature-induced diseases might impact fecundity and frequency of sexual intercourse, potentially affecting overall fertility. Contraceptive efficacy might also be negatively affected in relation to both high temperatures and prior health conditions. For example, hormonal birth control pills experience diminished effectiveness when stored at above room temperature (Barreca et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The effectiveness of condoms also worsens at high temperatures (Gerofi \u0026amp; Sorensen \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The failure of contraceptive methods due to hot temperatures would lead to an increase in birth rates, potentially counterbalancing the negative effects due to physiological and behavioral factors.\u003c/p\u003e\u003cp\u003eExtreme temperatures can affect reproductive behaviors by reducing the frequency of sexual activity. This may occur due to discomfort, fatigue, or changes in daily routines and sexual desire, which can potentially decrease the likelihood of conception. Being a sensitive topic, empirical evidence on sexual behaviors is quite scarce and mixed: one study on sub-Saharan Africa reported that the number of sexually active women decreased with temperature (Wilde et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), while in Hungary no correlation was detected (Hajdu \u0026amp; Hajdu, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eRecent scholarship is investigating the role of climate change concern \u0026ndash; and more in general of environmental instability \u0026ndash; on fertility outcomes by studying individuals\u0026rsquo; perceptions of the climate crisis and the implications on reproductive decisions. This approach allows us to consider how subjective believes shape fertility (Puglisi et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSeasonal patterns in births have been studied in demographic literature for over 50 years across various settings (Cowgill, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1966\u003c/span\u003e; Lam \u0026amp; Miron, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e1991\u003c/span\u003e; Udry \u0026amp; Morris, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e1967\u003c/span\u003e). Several studies have detected systematic differences in birth timing with planned pregnancies resulting in spring births. Historically, such timing may have been influenced by agricultural cycles: for instance, marriages and conceptions were frequently scheduled after harvest (Ellison, 2005). In contemporary industrialized contexts, seasonality in births tends to be shaped by sociocultural factors such as school enrollment cut-off dates (Dahlberg \u0026amp; Andersson, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), expectations about future economic security (Caleiro, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), or the timing of religious holidays (Friger et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Herteliu et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Polašek et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), along with the aforementioned environmental aspects. Studies focusing on behavioral mechanisms have highlighted that seasonal variation in fertility rates is more evident among better educated, stably married women, who are more likely to plan their pregnancy (Bobak, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2001\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eClimate change may increasingly disrupt traditional seasonal patterns in births by altering the environmental and health conditions under which conceptions and pregnancies occur. Rising temperatures, extreme heat events, and deteriorating air quality \u0026ndash; especially during summer months \u0026ndash; have been associated with reduced conception rates and increased risks of adverse pregnancy outcomes, such as preterm births or fetal loss. These impacts may disincentivize conceptions during warmer periods, thereby shifting birth seasonality over time. Furthermore, climate-induced variability in agricultural productivity and economic uncertainty could affect household decision-making around family planning, particularly in settings still reliant on seasonal labor or income. Thus, climate change introduces new dimensions to the seasonality-fertility nexus, potentially reshaping reproductive behaviors in both high- and low-income settings.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eItalian Context\u003c/h2\u003e\u003cp\u003eThe Italian average yearly temperature has increased by almost 2\u0026deg;C in the last 60 years, with a warming rate stronger than the world average for the past four decades. In 2022, the temperature difference reached the highest spike of 1.9\u0026deg;C, with respect to the 1930\u0026ndash;1960 baseline (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Temperature is increasing more quickly in high-altitude areas and during the spring and summer than in other seasons. Italy\u0026rsquo;s average annual temperature is likely to keep surging, causing the number of hot days (daily maximum temperature above 25\u0026deg;C) and tropical nights (nighttime minimum temperature above 20\u0026deg;C) to increase. Although low and medium precipitation events have become less recurrent, the intensity of precipitation episodes per year has expanded all around the national territory.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eOver the last two decades, Italian total fertility rates ranged from 1.29 children per woman in 2003 to 1.24 in 2022. Countries with a total fertility rate under 1.30 are classified as lowest-low fertility, and Italy, along with Spain, was the first European country to reach such level in the early Nineties. Sustained low fertility leads to rapid population aging and reduced relative cohort sizes (Kohler et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). The territorial distribution of TFRs in 2022 is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Total fertility rates above the national average are found in the North and in Sicily, particularly the highest value of 2022 (1.64) recorded in the province of Bolzano. Sardinian provinces and internal areas in the Center and in the South present instead the lowest fertility rates, with the lowest score of 2022 (0.88) reported in South Sardinia.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWith a GDP per capita equal to 36,0720\u0026euro; in 2023 (World Bank, 2025), Italy is considered as a high developed country. However, variations at the provincial level are pronounced: the lowest GDP per capita is recorded in Agrigento (14,872\u0026euro;) and the highest in Milan (53,109\u0026euro;). In general, Northern and Central provinces reveal higher GDP per capita than Southern and Islander provinces.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eData\u003c/h3\u003e\n\u003cp\u003eThis study analyzes the relationship between exposure to warm temperatures and fertility rates in 107 Italian provinces. The provincial administrative division corresponds to the NUTS3 classification. The total number of provinces changed throughout the selected period because new provinces were created while others were abolished. Comparability through the years is guaranteed using the current borders division (of 2023) as a benchmark for the entire time frame. The analysis spans from 2003 to 2022, ensuring a comprehensive assessment of trends over two decades. The starting year, 2003, was chosen as it marks a period with reliable and consistent data availability, while 2022 represents the most recent complete year of data. The study is conducted at the NUTS3 level, as going lower would present significant challenges: in small municipalities it is likely to find zero births in certain months, leading to unstable estimates and high year-to-year variability in total fertility rates. By working at the provincial level, we ensure statistical robustness while still capturing local differences effectively.\u003c/p\u003e\n\u003ch3\u003eFertility data\u003c/h3\u003e\n\u003cp\u003eWe combine two main sources of data: administrative data for fertility and GDP measures and E-OBS meteorological data for climate. We obtained administrative data from the Italian National Institute of Statistics (ISTAT), including the monthly number of births per women in fertility age (conventionally defined as between 15 and 49 years old) by province and the annual total number of women by age per province. The number of women per age-group interval in each month was then obtained by linear interpolation. Combining monthly births and number of women in fertility age we computed monthly total fertility rates (TFRs), which constitute our main outcome of interest.\u003c/p\u003e\u003cp\u003eSpanning across 2003 to 2022, monthly analysis is performed to capture the seasonality of the total fertility rate. The total sample of province-months is 25,680. The trend in fertility is shown in Figure A1 in the supplementary materials. After a slight initial increase in total fertility rates for the first years of the analysis, total fertility rates are declining consistently starting from 2011. The figure also shows the seasonality of births: during warmer months, especially from July to October, TFRs are visibly higher than in the first months of the year, especially from February to April. The average seasonal peak of births is observed in September.\u003c/p\u003e\n\u003ch3\u003eClimate data\u003c/h3\u003e\n\u003cp\u003eE-OBS meteorological data with a resolution of 0.1-degree grid cells is collected by weather stations located all around Europe and is available in the Copernicus Climate Data Store (CDS). The analysis employs climate data on temperature, relative humidity, precipitation amount, surface shortwave downwelling radiation, vegetation extension, and air pollution. Meteorological data is weighted by population at the provincial level.\u003c/p\u003e\u003cp\u003eThe \u003cb\u003etemperature data\u003c/b\u003e is included at the daily level by constructing 7 temperature bins (0\u0026deg;C; 0 to 5\u0026deg;C; 5 to 10\u0026deg;C; 10 to 15\u0026deg;C; 15 to 20\u0026deg;C; 20 to 25\u0026deg;C; and \u0026gt;\u0026thinsp;25\u0026deg;C) and computing the number of days per month in which the daily mean temperature fell in each range for each province. Daily mean temperature accounts for both the daytime high and nighttime low temperatures, which act together upon various health risks. Bin classification addresses potential non-linearity of the effect of temperature on fertility at a given lagged month and avoids functional form specifications, since it is relatively nonparametric (Dell, 2014).\u003c/p\u003e\u003cp\u003e\u003cb\u003eRelative humidity\u003c/b\u003e is a measure of how saturated the air is with water vapor compared with the total amount that can be held at a given temperature. Humidity aggravates the thermal stress experienced by people in extreme weather conditions because, at a given temperature, the higher the humidity, the lower the ability of the human body to cool itself by sweating, and the higher the risk of negative health consequences (Budd, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Raymond et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Considering the role of humidity in influencing the effect of heat on births may be important for a better understanding of the potential consequences of climate change (Hajdu, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). High-humidity days are defined as days with a relative humidity above 75%.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePrecipitation\u003c/b\u003e occurs when a portion of the atmosphere becomes saturated with water vapor reaching 100% relative humidity, so that the water condenses and falls. In the analysis, we control for precipitation measured as the total millimeters of precipitation recorded in a province in a month.\u003c/p\u003e\u003cp\u003eSurface downwelling shortwave is the sum of direct and diffuse \u003cb\u003esolar radiation\u003c/b\u003e on the surface. The atmosphere allows the heat from the Sun (short-wave radiation) to pass through to the Earth's surface, which then gives off heat (long-wave radiation). This heat is trapped by greenhouse gases, which radiate the heat back towards Earth. Solar radiation is connected to climate change because this process ends up heating the Earth.\u003c/p\u003e\u003cp\u003eThe \u003cb\u003evegetation measure\u003c/b\u003e used in this analysis is the Leaf Area Index (LAI), a common measure of plant canopy defined as the one-sided green leaf area per unit ground surface area. It depends on the size of the canopy, but also on its density, and the angle at which leaves are oriented in relation to one another and to light sources and it varies with seasonal changes in plant activity (Maass, 1995).\u003c/p\u003e\u003cp\u003e\u003cb\u003eAir pollution\u003c/b\u003e is measured by Particulate Matter 2.5\u0026micro;g/m\u0026sup3; (PM2.5), which is widely used in studies on the negative impact of air quality on health (Colmer et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Considering the combined effect of heat and air pollution is crucial because the atmospheric conditions that contribute to persistently hot weather also exacerbate air pollution. A temperature rise due to air pollution occurs gradually and air pollution occurring in a certain month is not likely to affect temperature in the immediate future (Cho, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, there is evidence that elevated levels of air pollution such as PM 2.5, O\u003csub\u003e3\u003c/sub\u003e, and NO\u003csub\u003e2\u003c/sub\u003e alter physiological processes in male and female fertility (Kumar \u0026amp; Singh, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e and Conforti et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe \u003cb\u003eSPEI\u003c/b\u003e (Standardized Precipitation-Evapotranspiration Index) is a multi-scalar drought index based on climatic data that can be used for determining the onset, duration and magnitude of drought conditions with respect to normal conditions in a variety of natural and managed systems such as crops, ecosystems, rivers, and water resources (Vicente-Serrano et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). The Global SPEI database (SPEIbase) offers information about drought conditions at the global scale, with a 0.5 degrees spatial resolution and a monthly time resolution. The SPEI can measure the start and the end of drought episodes, as well as their severity through time and space. An important advantage of the SPEI over other drought indices is that its multi-scalar characteristics enable identification of different drought types and impacts in the context of climate change. SPEI was studied as an explanatory variable in supplementary materials.\u003c/p\u003e\n\u003ch3\u003eEconomic data\u003c/h3\u003e\n\u003cp\u003eOver the last decades, in many OECD countries fertility rates dropped significantly while the gross domestic product (GDP) continued to increase. The strong negative correlation between GDP per capita and fertility might not hold for high levels of per capita economic output, and the relation might turn positive from a certain threshold level of economic development. In several highly developed countries, total fertility rates have been growing since the early 2000s, along with continuing economic development, for example in France, the United States and Czech Republic (Luci-Greulich \u0026amp; Th\u0026eacute;venon, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Nordic countries, despite having relatively high fertility levels, large female labor market participation, and well-established family-support social policies, have experiences substantial fertility decline since 2010 (Campisi et al., 2022). The impact of economic growth on fertility is therefore ambiguous. The GDP per capita is obtained from Eurostat and computed as a mean over the period between 2013 and 2019, and the distribution is classified in quartiles. The lowest levels of GDP belong to the first quartile, while the highest are in the fourth quartile. The provinces with higher GDP per capita are also the ones presenting higher TFRs in general. GDP data is not included directly in the model, and the regression is run separately for all GDP quartiles.\u003c/p\u003e"},{"header":"Methodology","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003cp\u003eThe study employs an OLS panel fixed effects model to analyze the relationship between temperature and fertility outcomes. The outline of the model is the following:\u003c/p\u003e\u003cp\u003e\u003cimg 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\" width=\"609\" height=\"133\"\u003e\u003c/p\u003e\u003cp\u003ewhere the outcome of interest is the logarithm of the monthly TFR in each province and month (Y\u003csub\u003ept\u003c/sub\u003e), and the main explanatory variable is the temperature categorized in bin variables and measured at the month of birth and up to fifteen months prior to birth (TEMP\u003csup\u003ej\u003c/sup\u003e\u003csub\u003ep,t\u0026minus;k\u003c/sub\u003e). The other meteorological control variables X\u003csub\u003ep,t\u0026minus;9\u003c/sub\u003e (relative humidity, precipitation amount, surface shortwave downwelling radiation, vegetation extension, and air pollution) are measured at the month of conception at the provincial unit. The model includes two fixed effects: province-by-year fixed effect (γ\u003csub\u003epy\u003c/sub\u003e) and province-by-month fixed effect (α\u003csub\u003epm\u003c/sub\u003e) to capture province-specific factors and seasonality. The variable δ\u003csub\u003eqm\u003c/sub\u003e represents the polynomial quadratic in the year-month of conception used to account for possible convergences in seasonality across provinces over time. The number of women of reproductive age in each province in the year before birth is used as a weight. Standard errors are clustered at the provincial level (ε\u003csub\u003ept\u003c/sub\u003e).\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003eSummary statistics\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e reports the summary statistics for the monthly values at the provincial level of the variables of the analysis throughout the entire period. The province average monthly TFR of 0.11 reflects the lowest-low levels of yearly total fertility rates in Italy. Days with temperatures between 10\u0026deg;C and 15\u0026deg;C are the most common on average, while days exceeding 30\u0026deg;C are the least frequent.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u0026ndash; Summary statistics\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMin\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMax\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTFR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.17\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBirths\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e392\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e462\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4,773\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWomen in fertility age\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e123,326\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e135,883\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15,083\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e968,143\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0\u0026deg;C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e31\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0 to 5\u0026deg;C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e31\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5 to 10\u0026deg;C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e31\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10 to 15\u0026deg;C\u003c/p\u003e\u003cp\u003e15 to 20\u0026deg;C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.78\u003c/p\u003e\u003cp\u003e5.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.90\u003c/p\u003e\u003cp\u003e7.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e31\u003c/p\u003e\u003cp\u003e31\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e20 to 25\u0026deg;C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e31\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e25 to 30\u0026deg;C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e31\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;30\u0026deg;C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRelative Humidity\u003c/p\u003e\u003cp\u003ePrecipitation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e71.79\u003c/p\u003e\u003cp\u003e2.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.87\u003c/p\u003e\u003cp\u003e2.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e39.11\u003c/p\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e92.66\u003c/p\u003e\u003cp\u003e22.26\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSolar radiation\u003c/p\u003e\u003cp\u003eLAI index\u003c/p\u003e\u003cp\u003ePM2.5\u003c/p\u003e\u003cp\u003ePopulation Density\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e159.40\u003c/p\u003e\u003cp\u003e3.93\u003c/p\u003e\u003cp\u003e1.85\u003c/p\u003e\u003cp\u003e265\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e77.54\u003c/p\u003e\u003cp\u003e1.24\u003c/p\u003e\u003cp\u003e8.04\u003c/p\u003e\u003cp\u003e370\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23.09\u003c/p\u003e\u003cp\u003e0.13\u003c/p\u003e\u003cp\u003e0.35\u003c/p\u003e\u003cp\u003e35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e407.30\u003c/p\u003e\u003cp\u003e6.58\u003c/p\u003e\u003cp\u003e7.30\u003c/p\u003e\u003cp\u003e2,6199\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eNotes: Summary statistics for the monthly values of the variables in our main analysis in the 107 Italian provinces in 2003\u0026ndash;2022. Sources: ISTAT (demographic data), CDS (meteorological data)\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eThe effect of temperature on fertility\u003c/h2\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the effect of exposure to each temperature bin on the TFR nine months later with 95% confidence intervals. The effects are compared to a day with a mean temperature of 10\u0026ndash;15\u0026deg;C. The temperature bins of exposure in other months are also included in the analysis but not reported in the figure. Warmer days have a negative effect on the total fertility rates, in particular the last temperature bin (\u0026gt;\u0026thinsp;25\u0026deg;C) has the largest negative effect with a TFR decrease of -0.31%, while colder days do not substantially alter fertility. This is coherent with the previous studies (Barreca et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Hajdu, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Conte Keivabu et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eNext, we examine how the timing of exposure to an additional hot day (\u0026ge;\u0026thinsp;25\u0026deg;C) may differently affect fertility. Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e displays the estimated effect of an additional hot day with a mean temperature above 25\u0026deg;C on fertility, measured from zero to fifteen months following exposure. Note that the model controls for a full set of temperature bins, but only the effects for the last one are displayed in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, as it is the one with a larger negative effect on fertility. The effects are compared to a day with a mean temperature of 10\u0026ndash;15\u0026deg;C. There is a clear reduction of -0.31% in TFR at month nine, confirming that a hot day has a relatively immediate impact on conception probabilities. Barreca et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) examining the US data showed that the effect of extreme temperatures is also particularly strong also at the ten-month lag. Similarly, we find that there is a decrease in total fertility rates ten months after exposure to heat (Figure A2 in the Supplementary Materials, though the effect is less than half of the previous month (-0.15%).\u003c/p\u003e\u003cp\u003eFurthermore, Barreca et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) observed a positive increase in TFR in the months following the nine-month mark, which might be a signal of recuperation of the births averted because of the heat. Although our analysis does not detect such a significant positive trend, it shows that fertility declines around nine and ten months after exposure to high temperatures, with the downward trend tapering off thereafter. For temperatures exceeding 30\u0026deg;C (Fig. A3 in the supplementary materials) there is an increase in total fertility rates from 11 to 15 months after heat exposure, but the coefficients are not statistically significant.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eThe effect of temperature on fertility over time\u003c/h2\u003e\u003cp\u003eWe further explore whether the effect of temperature exposure on fertility has changed over the years. Previous findings show that the effect of temperature on fertility might decrease over time (Barreca, 2018) or remain stable (Hajdu, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). On the one hand, the effect may be reduced in more recent time periods due to adaptation. On the other hand, the impact of climate change has become intensified in the last decade, and the effect may become stronger. The time span is therefore divided into two equal groups: the first one going from 2003 to 2012, and the second one from 2013 to 2022. In the case of Italy, the effect size increased over the years. The coefficient for days above 25\u0026deg; C goes from \u0026minus;\u0026thinsp;0.33% to \u0026minus;\u0026thinsp;0.37%, while the coefficient for days between 20 and 25\u0026deg; C moves from \u0026minus;\u0026thinsp;0.13% to \u0026minus;\u0026thinsp;0.17%, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. The stronger effect observed in the later period might be due to an increase in the number of days over 25\u0026deg; C as a result of the intensification of climate change over the years. The recent period includes more frequent and severe extreme-temperature events, which might have a larger impact on health and life planning, leading to a more pronounced fertility decline. For the first period, negative temperatures are associated with a positive increase in fertility rate (0.22%), but this does not happen in the following years. Lower temperatures correspond to winter months, which are historically associated with higher conception rates. This seasonal fertility pattern might have been more pronounced in the earlier period.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eThe effect of temperature on fertility by climate zones\u003c/h2\u003e\u003cp\u003eThe literature provides evidence that fertility rates in colder regions of a given country are more sensitive to heat shocks than warmer regions, probably due to lack of infrastructures and adaptation practices. Barreca et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) discovered that the effect of warmer days on fertility was larger in the colder climatic zones of the United States and Conte Keivabu et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) found the same effect in Spanish provinces. In this section, we explore how the relationship between temperature and fertility varies with climatic conditions by classifying Italian provinces into hot and cold zones, according to whether the province is above or below the median temperature in the sample. Cold provinces are mostly located in the North and in internal areas, while hot provinces are mostly located on islands and coastal areas.\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e replicates the analysis in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e but distinguishes between the two climate zones. In contrast with previous studies, the graph reveals that the effect of temperatures above 25\u0026deg;C on fertility is stronger for hot climates (-0.35%) than for cold ones (-0.21%). This difference might be explained by the fact that colder provinces in the North are generally better equipped to cope with occasional heat through widespread access to healthcare and air conditioning, while hotter provinces in the South tend to have more fragile healthcare systems and less access to cooling infrastructures (ISTAT, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eThe effect of temperature on fertility by GDP\u003c/h2\u003e\u003cp\u003eLooking at the effects of heat shocks on different levels of GDP, one might expect richer and more fertile provinces to be able to handle or to adapt to temperature extremes better. This is not the case for Italian provinces over the period of the analysis. Figure\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e reveals that the poorest (1st quartile) and the richest (4th quartile) provinces are more affected by warmer temperatures, in particular the richest provinces are experiencing the largest contraction in total fertility rates (-0.41%). The reduction in poorest provinces might be due to limited adaptation infrastructures, such as widespread air conditioning and public health services, and the largest proportion of outdoor labor, that might lead to a more disruptive effect of heat exposure at the physiological level. The decline in fertility in the richest provinces shows that wealthier areas are also affected by warming temperatures. In this case, exposure to hot weather might reshape individual behaviors and intentions, resulting in pregnancy postponement and signaling greater responsiveness in fertility behavior to climate-related factors.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eThe interaction of climate zones and GDP on fertility\u003c/h2\u003e\u003cp\u003eAfter examining the separate effects of climate zones and gross domestic product per capita on fertility, we extend the analysis to include their interaction. This step is crucial because climatic conditions and economic development are not evenly distributed across Italy and may exert overlapping or confounding influences on fertility. Colder regions are predominantly located in the northern part of the country, which is also the wealthiest. On the other hand, hot regions are mostly found in the South and in the islands, which are generally less wealthy. As a result, it is difficult to disentangle whether the heat-induced reduction in fertility is driven by climatic factors, economic conditions, or both. Here we explicitly model the interaction between climate zones and GDP to better isolate the distinct and combined effects of environmental and socioeconomic contexts on fertility outcomes.\u003c/p\u003e\u003cp\u003eThe per capita gross domestic product is sorted into two categories (above or below the national average), as the number of hot provinces in the fourth quartile of GDP distribution and the number of cold provinces with the first quartile of GDP are low. The number of provinces within this category is limited (14 out of 107) and most of them are in northern and central Italy. In the same way, there are only 15 provinces with a cold climate and below-average GDP. Therefore, most provinces fall into the remaining two categories: cold provinces with an above-average GDP (39) and hot provinces with below-average GDP (39). This reflects the territoriality component of the variables.\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e shows the effect on fertility of these interactions. The total fertility rate reveals a significant negative value for the highest temperature bin in each climate zone and for each level of GDP, except for cold provinces with a below-average GDP. The magnitude of this effect is notably stronger (-0.39%) in hot provinces with above-average GDP. Notably, when we further break down this effect by GDP level, we find that the positive association is concentrated in poorer hot regions. One possible explanation for this pattern is that colder-than-usual periods in hot and economically disadvantaged areas may reduce outdoor economic or agricultural activity, leading to increased time spent indoors and a potential rise in conception rates. Additionally, in contexts where access to heating (Istat \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) or alternative forms of indoor recreation is limited, cold spells may inadvertently encourage behaviors associated with higher fertility, such as cohabitation or reduced mobility. It is also possible that cold-related hardship fosters a desire for family support or security, particularly in settings where social or economic uncertainty is high.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eRobustness checks\u003c/h2\u003e\u003cp\u003eIn this section, we perform a series of robustness checks to assess whether our results hold using alternative climate measures, including relative temperatures, temperature anomalies and SPEI index (a drought indicator).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eRelative temperatures\u003c/h2\u003e\u003cp\u003eClimate literature highlights the importance of using relative measures of temperature alongside absolute ones to account for substantial variation in average temperatures, which may lead to different adaptation responses (Cil \u0026amp; Kim, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Relative measures help address concerns about within-province climate variations s, as they focus less on absolute differences across areas and more on deviations from local norms.\u003c/p\u003e\u003cp\u003eRelative temperature bins are constructed based on the percentile distribution of temperatures within each province. Temperatures are then classified into seven categories: \u0026lt; 1st percentile, 1st to 5th, 5th to 10th, 10th to 90th (the comfort zone), 90th to 95th, 95th to 99th and \u0026gt;\u0026thinsp;99th. In this distribution, the 99th percentile corresponds to values ranging from 9.06\u0026deg;C in Aosta to 28.85\u0026deg;C in Padova. Figures A4 and A5 in the supplementary material present results consistent with the main analysis: in the in the highest percentile range -- representing relatively extreme heat --fertility rates decline nine months after exposure, although with smaller effect sizes (-0.19%).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eTemperature anomalies\u003c/h2\u003e\u003cp\u003eAnother way to measure relative temperature is through temperature anomalies, which compare current temperatures to a long-term average based on a defined reference period. Following the World Meteorological Organization (WMO) guidelines, which recommend a 30-year baseline, this analysis uses the period 1970 to 2000 as the reference. A temperature anomaly is calculated as the difference between a given temperature and the average temperature over the reference period. Standardized anomalies are calculated by dividing anomalies by the climatological standard deviation, thereby removing the effects of dispersion. Figure A6 in the supplementary materials shows that positive temperature anomalies, i.e. when temperatures get warmer than the reference period, are associated with a decline in fertility rates nine months later. The estimated effect size (-0.53%) is larger than that found in the main analysis.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003eThe effect of SPEI on fertility\u003c/h2\u003e\u003cp\u003eThis analysis includes the Standardized Precipitation-Evapotranspiration Index (SPEI) as an additional climate indicator to examine its effects on fertility. The SPEI is calculated from time lags ranging from 1 to 24 months to capture drought conditions over both short to long periods. SPEI values are grouped into five categories indicating severity: dry, moderately dry, normal, moderately wet, and wet.\u003c/p\u003e\u003cp\u003eFigure A7 shows the relationship between exposure to different SPEI accumulation levels on fertility. The results suggest no significant association between dry or wet conditions and fertility outcomes.\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion and Conclusion","content":"\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003cp\u003eThis study analyzes the impact of temperature on fertility in Italy over a period of twenty years and discloses the adverse effect of warm days (with a mean daily temperature above 25\u0026deg;C) on monthly total fertility rates and the null effect of cold days. The fall in fertility occurs between 9 and 10 months after exposure, suggesting that heat both immediately reduces conception probabilities and causes some of the affected population to conceive in following months. The effect size of the exposure to each additional day with a temperature above the 25\u0026deg;C threshold is comparable to previous studies by Barreca (2018) and Cho (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The effect of the decline in fertility due to heat exposure translates into around 192 births lost for each day above 25\u0026deg;C in Italy over the study period 2003\u0026ndash;2022.\u003c/p\u003e\u003cp\u003eThe relationship between temperature and fertility is consistent across both climate zones, with a decline in fertility observed at the highest temperature bin. The effect is more pronounced in hotter regions. Fertility responses to temperature also vary by GDP levels: both the wealthiest and the poorest regions in Italy show greater sensitivity to high temperatures. Typically, wealthier provinces are located in the North, and are exposed to colder temperatures, while poorer ones are situated in the South and in the Islands, where warmer temperatures prevail. The interaction between climate zone and GDP levels confirms that hot regions present a slightly larger reduction in fertility rates with respect to cold ones, and the adverse effect of temperature is more pronounced in above-average GDP provinces. The heightened vulnerability to warm days in hot areas \u0026ndash; despite their climatic familiarity -- has not beedn widely documented in the literature and may be linked to socio-economic factors that hinder adaptation and mitigation of the adverse effects of heat.\u003c/p\u003e\u003cp\u003eThis work is not withou limitations. Firstly, using monthly instead of weekly data reduces the accuracy of the analysis because it cannot unravel physiological mechanisms that might result in decreasing conception probabilities. Moreover, in this kind of analysis it is impossible to test behavioral mechanisms such as how temperature might affect sexual behaviors, which is an interesting path for future research. Using province level fertility data reduces the spatial granularity of the study as meteorological variables might differ within the provincial borders and considering mean values decreases the precision of the analysis.\u003c/p\u003e\u003cp\u003eThis study complements the emerging research on the relationship between climate change and fertility providing new empirical evidence from Italy and confirms the consistent trends observed in other countries around the world. Moreover, it is the first work that explores the regional heterogeneities of a country by examining the interplay between geographical characteristics and economic conditions. This approach is essential in analyzing the Italian context, where isolating the separate effects of the two components becomes difficult, as the colder regions in the North are also the wealthiest and warmer regions in the South are also the poorest. This study has important policy consequences as the negative correlation between rising temperatures and fertility will likely be aggravated by climate change, threatening the rebound from lowest-low fertility levels and accelerating the ageing of an already old population.\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eResearch was supported by funds from XXX.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eM.B., R.M., and F.Q. wrote the main manuscript text. M.B. prepared all figures. All authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData on monthly TFRs: from ISTAT (Italian national statistic institute) but is not available for the publicData on climate: from Copernicus Data Store https://cds.climate.copernicus.eu/datasets/reanalysis-era5-single-levels-monthly-means?tab=overview\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBai, L., Ding, G., Gu, S., Bi, P., Su, B., Qin, D., Xu, G., \u0026amp; Liu, Q. (2014). 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The effect of ambient temperature shocks during conception and early pregnancy on later life outcomes. \u003cem\u003eEuropean Economic Review\u003c/em\u003e, \u003cem\u003e97\u003c/em\u003e, 87\u0026ndash;107. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.euroecorev.2017.05.003\u003c/span\u003e\u003cspan address=\"10.1016/j.euroecorev.2017.05.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWorld Bank World Bank national accounts data, and OECD National Accounts data files, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://data.worldbank.org/indicator/NY.GDP.PCAP.CN?locations=IT\u003c/span\u003e\u003cspan address=\"https://data.worldbank.org/indicator/NY.GDP.PCAP.CN?locations=IT\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"climate change, heat exposure, fertility, Italy","lastPublishedDoi":"10.21203/rs.3.rs-7743281/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7743281/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eClimate change-induced temperature increases and extreme weather events are impacting human health and wellbeing. Warmer temperatures are reported to affect both reproductive health and behaviors, possibly reducing birth rates. In a low fertility context, the potential negative impact that climate change might have on fertility is consequential. This study focuses on Italy, a low-fertility country disproportionately affected by climate change, with sharp regional disparities in both climate zones and economic development. Matching monthly birth registration data for the period 2003 to 2022 with E-OBS meteorological data, we analyze the relationship between heat exposure and total fertility rates in 107 Italian provinces (corresponding to the NUTS-3 classification). Results show that exposure to extremely hot days, which are defined as days with a mean temperature above 25\u0026deg;C, has a relatively immediate impact on conception probabilities as it reduces the total fertility rate nine months later. While this reduction is observed across both cold and hot climate zones, it appears to be larger for warmer provinces. The effect of temperature on fertility also varies with the per capita gross domestic product, where fertility rates in the richest provinces appear to be more sensitive to warming temperatures. The interaction between climate zones and GDP per capita revealed that hot above-average GDP provinces are the most affected by hot temperatures.\u003c/p\u003e","manuscriptTitle":"The effect of temperature on fertility: A province-level analysis of monthly total fertility rates in Italy in 2003 – 2022","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-03 04:26:15","doi":"10.21203/rs.3.rs-7743281/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5e5b3037-8ea6-4076-99d1-68448713cf96","owner":[],"postedDate":"November 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-30T16:12:10+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-03 04:26:15","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7743281","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7743281","identity":"rs-7743281","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}