Guiseley Crime Rate December 2024 | Monthly Statistics

Guiseley, a built-up area within Leeds, recorded 53 crimes in December 2024, translating to a crime rate of 4.8 per 1,000 residents. This figure, 32.4% below the UK average of 7.1 per 1,000, underscores the area’s relatively low exposure to crime, even as specific categories show divergent trends. The crime profile for the month was dominated by violence and sexual offences (24 incidents, 45.3% of total crimes), followed by shoplifting (9 incidents) and public order offences (5 incidents). These patterns align with the seasonal context of December, a time marked by Christmas shopping, party season, and extended darkness, all of which can influence criminal activity. The prominence of violence and sexual offences, though slightly below the UK average for this category, may be linked to the increased social interactions and potential for conflict in public spaces during the festive period. Conversely, shoplifting’s 40% excess over the UK average could be attributed to the high foot traffic in Guiseley’s retail areas, a common feature in towns with significant commercial presence. Meanwhile, the relatively low rates of burglary and vehicle crime, both below UK averages by 29% and 50% respectively, suggest that targeted policing or community engagement efforts may have mitigated these risks. The overall crime rate, however, remains a reflection of Guiseley’s unique demographic and geographic characteristics, which differ from the broader UK context. As the month progressed, the impact of seasonal factors—such as the closure of schools and the movement of residents between homes—likely contributed to the observed fluctuations in crime types, illustrating how localized conditions can shape broader trends.

December 2024 saw a stark contrast in crime trends, with robbery incidents doubling from zero to one, marking a 100% increase. This spike, though modest in absolute terms, may be linked to the festive season’s heightened economic activity and the potential for opportunistic crimes in crowded shopping areas. Conversely, anti-social behaviour plummeted by 85.7%, from seven to one incident, likely reflecting the calming effect of holiday gatherings and reduced public drinking in the area. The breakdown of crime types also reveals a shift in the balance between property and violent crimes, with violence and sexual offences accounting for 45.3% of total incidents—slightly below the UK average of 2.6 per 1,000. Meanwhile, shoplifting, at 0.8 per 1,000, exceeded the UK average by 40%, a trend that may be attributed to the high foot traffic in Guiseley’s retail centres during the Christmas period. These fluctuations illustrate the combination of seasonal dynamics and localized factors in shaping crime patterns.

Guiseley’s crime rate in December 2024 fell to 4.8 per 1,000 residents, a 43.6% decline from the previous month’s rate of 8.6 per 1,000. This reduction, though significant, must be viewed against the backdrop of seasonal factors, such as the Christmas shopping peak and extended darkness, which can influence crime patterns. On a daily basis, the area recorded an average of two crimes per day in December, a figure that, while low, reflects the impact of targeted policing or community initiatives during the holiday season. Over the course of the month, one crime occurred for every 208 residents, a statistic that underscores the relatively low exposure to crime for individuals living in Guiseley. When scaled to the population of 11,000, this monthly exposure highlights the area’s comparative safety compared to the UK average, even as specific categories like shoplifting and burglary show divergent trends. The population-scaled perspective also reveals that, despite a 32.4% reduction in the overall rate compared to the UK average, Guiseley’s residents face unique challenges in certain crime types, such as shoplifting, which exceeds the national average by 40%. These disparities suggest that localized factors, rather than broad national trends, may be shaping the area’s crime profile.