A recent study has shed light on an alarming trend: among women who strongly desire to avoid becoming pregnant, those who engage in heavy drinking are more than 50% likelier to become pregnant compared to those who drink moderately or not at all. In contrast, participants who use cannabis do not appear to have a higher risk of undesired pregnancy.

Researchers from the University of California, San Francisco conducted this study among a subgroup of over 900 non-pregnant women aged 15-34 who reported a strong desire to avoid pregnancy. They found that those who drank heavily and those who used cannabis frequently had an even higher overall desire to avoid pregnancy compared to participants who drank moderately or did not use cannabis.

Over the course of one year, 71 out of the 936 women in this subgroup became pregnant unintentionally. A significant proportion (38) of these unwanted pregnancies occurred among heavy drinkers, far exceeding the combined number for those who drank moderately or not at all. This suggests that heavy drinking is associated with a higher risk of undesired pregnancy compared to lower levels of consumption.

On the other hand, less than half (28) of the 71 unintended pregnancies occurred among people who used cannabis, indicating that these individuals did not have an elevated risk of undesired pregnancy compared to those who did not use cannabis.

According to Dr. Sarah Raifman, lead author of this study, the findings imply two crucial points: first, non-pregnant women who drink heavily may have a higher desire to avoid pregnancy than those who drink moderately or do not drink at all; second, heavy drinking compared to moderate or no drinking appears to put those who most want to avoid pregnancy at a higher risk of becoming pregnant within one year.

Given the potentially life-altering effects of fetal alcohol spectrum disorders and the fact that the risk of FASD increases with the amount and duration of maternal drinking, healthcare professionals should support women who drink heavily in stopping their consumption as soon as they suspect an unintentional pregnancy.

Coastal communities worldwide are experiencing more frequent and prolonged flooding events due to rising sea levels and increased precipitation. According to a recent study by North Carolina State University and the University of North Carolina at Chapel Hill, this trend is more pronounced than previously thought, with major implications for flood risk management, urban planning, and community resilience.

The study’s authors used land-based sensors to monitor flooding events in three coastal communities: Beaufort, Carolina Beach, and Sea Level. Over a year-long period, the sensors detected flooding on 26 days in Beaufort, 65 days in Carolina Beach, and 128 days in Sea Level. In contrast, traditional methods using tidal gauge data estimated flooding frequencies as significantly lower.

“These numbers were vastly different from what the thresholds tell us,” says Katherine Anarde, co-author of the paper and assistant professor of coastal engineering at NC State. “The current methodology drastically underestimates the number of floods and fails to capture their duration.”

Researchers also found that while the National Weather Service’s minor flood threshold (NWS) sometimes overestimated flooding frequencies, it still did not accurately account for the prolonged nature of these events.

“Our findings show that traditional methods don’t adequately capture how long water takes to drain off land,” says Miyuki Hino, corresponding author and assistant professor of city and regional planning at UNC. “More accurate information on coastal flooding can inform where and how we invest resources in building more resilient communities.”

The study’s results have significant implications for flood risk management and urban planning. By using land-based sensors to monitor flooding events, researchers can provide more accurate data to inform decision-making processes.

“Every community is unique,” says Hino. “But with more accurate data, we can help communities assess what response strategy is best for them, now and in the future.”

The paper, titled “Land-based Sensors Reveal High Frequency of Coastal Flooding,” was published in Nature Communications Earth & Environment on June 2.

The southeastern coastal states are no strangers to hurricane fury. As the globe continues to warm, scientists predict that these powerful storms will only get more destructive – packing higher winds and torrential rainfall. A recent study published in Risk Analysis projects a staggering 76% increase in wind-related losses for homeowners in this region by the year 2060, and a whopping 102% increase by 2100.

University of Illinois civil engineer Eun Jeong Cha led a team that used machine learning to simulate the impact of future hurricanes on wooden single-family homes with concrete masonry in Texas, Louisiana, Mississippi, Alabama, Florida, Georgia, South Carolina, and North Carolina. Their worst-case scenario projections were based on the highest possible greenhouse gas emissions from the Intergovernmental Panel on Climate Change (IPCC).

The results are dire: losses from wind and rain-ingress will be 49-76% higher by 2060 and 71-102% higher by 2100. Hurricane wind speeds in Texas will increase by 14% in the 2050s compared to present-day levels, making it the state with the highest expected losses.

Some inland counties, such as Charleston, South Carolina, may experience a relatively large percentage increase in projected risk. At the county level, Cha’s team found variations of hurricane risk associated with climate change and differences in regional preparation for hurricane wind hazards.

“The discrepancies we found emphasize the necessity of vast regional risk assessment for federal- and state-level resource allocation and risk mitigation planning,” says Cha.

Insurance models need to account for heavier rainfall and stronger winds. Hurricane winds account for over 40% of storm-related losses in the residential sector, causing $14 billion in expected annual costs to the U.S. economy. Yet most hurricane models used by insurance companies fail to consider the impact of climate change.

“The worst-case scenario is widely used to explore high-impact possibilities for long-term planning and resilience studies,” says Cha.

Accurately estimating hurricane hazards and resulting losses is essential, says Cha. “Our findings contribute significantly to our understanding of climate change impacts on hurricane risks, providing valuable insights for policymakers, urban planners, and the insurance industry.”