Prevalence of non-specific symptoms in livestock dense areas : looking beyond respiratory conditions
Background: A large body of studies showed that prevalence of respiratory health problems is higher when people live closer to livestock farms, compared to people who live further away. Acute somatic and mental health symptoms such as headache, sleep problems and anxiety can also be directly or indirectly associated with environmental exposures, especially in the light of recent zoonoses with a severe impact on human health. The present study aims to gain more insight in possible differences between residents of livestock dense and non-dense regions, in the prevalence of diverse acute non-specific symptoms (NSS), taking into account socio-demographic factors and psychiatric morbidity.
Methods: Prevalence of diverse acute health symptoms as well as anxiety and depression was assessed for the year 2017, based on electronic health records registered in 39 general practices in the Netherlands. Data were obtained from the Primary Care Database (PCD) of Nivel. The “study group” included people who lived in rural areas with high livestock density (n=74093) and was compared to a “control group” (people in other rural areas with low livestock density) (n=50139). Multiple logistic multilevel regression analyses were performed.
Results: Prevalence of anxiety was significantly higher among people living in livestock dense regions, while there was no significant difference in depression. There was a significantly higher chance that people in the study group had acute health symptoms such as abdominal complaints, diarrhea, headache, dizziness, sleep disturbance, coughing, and skin symptoms, compared to the control group.
Conclusions: The study suggests that the previously identified higher risk of respiratory health problems in livestock dense areas also applies to the prevalence of various NSS. The results need to be verified while considering individual livestock exposure estimates and other relevant individual and environmental factors over a broader time period.
In: Environmental Epidemiology ISSN: 2474-7882 | 3 | suppl 1 | oktober | 133
https://doi.org/10.1097/01.EE9.0000607208.97346.70