You will be shown an abstract from a biomedical research paper. Given this abstract, your task is to extract all unique entities of the following types: ["HealthCareActivity", "InjuryOrPoisoning", "BodySubstance", "IntellectualProduct", "AnatomicalStructure", "SpatialConcept", "Chemical", "Bacterium", "MedicalDevice", "Organization", "BiomedicalOccupationOrDiscipline", "Finding", "BiologicFunction", "Virus", "ResearchActivity", "ClinicalAttribute", "PopulationGroup", "Eukaryote", "BodySystem", "Food", "ProfessionalOrOccupationalGroup"].

Please return the output as a JSON object of the format: {"Virus": ["HIV", ...], "Bacterium": ["MRSA", ...], "AnatomicalStructure": ["Lung", ...], "BodySystem": ["CNS", ...], "BodySubstance": ["Serum", ...], "Finding": ["Headache", ...], "InjuryOrPoisoning": ["Fracture", ...], "BiologicFunction": ["Death", ...], "HealthCareActivity": ["Biopsy", ...], "ResearchActivity": ["Clinical trial", ...], "MedicalDevice": ["Lenses", ...], "SpatialConcept": ["Camps", ...], "BiomedicalOccupationOrDiscipline": ["Forensic medicine", ...], "Organization": ["WHO", ...], "ProfessionalOrOccupationalGroup": ["Provider", ...], "PopulationGroup": ["Swimmers", ...], "Chemical": ["Gold", ...], "Food": ["Rice", ...], "IntellectualProduct": ["RPAM", ...], "ClinicalAttribute": ["Biomarker", ...], "Eukaryote": ["Dogs", ...]}. The keys should be entity types and values should be lists of extracted entities belonging to the corresponding type. If you cannot find entities belonging to a specific type, the value should be [].

Only output the JSON object and do not include any additional text.

Abstract:

Air pollution, neighbourhood and maternal - level factors modify the effect of smoking on birth weight: a multilevel analysis in British Columbia, Canada Maternal smoking during pregnancy negatively impacts fetal growth, but the effect is not homogenous across the population. We sought to determine how the relationship between cigarette use and fetal growth is modified by the social and physical environment. Birth records with covariates were obtained from the BC Perinatal Database Registry (N = 232,291). Maternal smoking status was self-reported as the number of cigarettes smoked per day usually at the first prenatal care visit. Census dissemination areas (DAs) were used as neighbourhood - level units and linked to individual births using residential postal codes to assign exposure to particulate air pollution (PM2.5) and neighbourhood - level attributes such as socioeconomic status (SES), proportion of post-secondary education, immigrant density and living in a rural place. Random coefficient models were used with cigarettes /day modeled with a random slope to estimate its between- DA variability and test cross-level interactions with the neighbourhood - level variables on continuous birth weight. A significant negative and non-linear association was found between maternal smoking and birth weight. There was significant between- DA intercept variability in birth weight as well as between- DA slope variability of maternal smoking on birth weight of which 68 and 30 % respectively was explained with the inclusion of DA - level variables and their cross-level interactions. High DA - level SES had a strong positive association with birth weight but the effect was moderated with increased cigarettes /day. Conversely, heavy smokers showed the largest increases in birth weight with rising neighbourhood education levels. Increased levels of PM2.5 and immigrant density were negatively associated with birth weight, but showed positive interactions with increased levels of smoking. Older maternal age and suspected drug or alcohol use both had negative interactions with increased levels of maternal smoking. Maternal smoking had a negative and non-linear dose-response association with birth weight which was highly variable between neighbourhood s and evidence of effect modification with neighbourhood - level factors. These results suggest that focusing exclusively on individual behaviours may have limited success in improving outcomes without addressing the contextual influences at the neighbourhood - level. Further studies are needed to corroborate our findings and to understand how neighbourhood - level attributes interact with smoking to affect birth outcomes.
{"AnatomicalStructure": [], "Bacterium": [], "BiologicFunction": ["contextual", "pregnancy", "fetal growth", "understand", "drug", "affect", "births"], "BiomedicalOccupationOrDiscipline": [], "BodySubstance": [], "BodySystem": [], "Chemical": ["particulate", "PM2.5"], "ClinicalAttribute": ["birth outcomes", "smoking status"], "Eukaryote": [], "Finding": ["education levels", "findings", "negative", "modification", "positive", "heavy smokers", "maternal", "modified", "negatively", "Maternal"], "Food": [], "HealthCareActivity": ["first prenatal care visit"], "InjuryOrPoisoning": [], "IntellectualProduct": ["modeled", "models", "BC Perinatal Database Registry"], "MedicalDevice": [], "Organization": [], "PopulationGroup": ["immigrant", "individual"], "ProfessionalOrOccupationalGroup": [], "ResearchActivity": ["studies", "self-reported", "multilevel analysis"], "SpatialConcept": ["dissemination", "areas", "physical environment", "British Columbia", "homogenous", "DA", "DAs", "Canada"], "Virus": []}