In this task, you are given a passage which has a question and the context. You have to generate an answer to the question based on the information present in the context.

Example Input: Context: It is common in public health and epidemiology that the outcome of interest is counts of events occurrence. Analysing these data using classical linear models is mostly inappropriate, even after transformation of outcome variables due to overdispersion. Zero-adjusted mixture count models such as zero-inflated and hurdle count models are applied to count data when over-dispersion and excess zeros exist. Main objective of the current paper is to apply such models to analyse risk factors associated with human helminths (S. haematobium) particularly in a case where there's a high proportion of zero counts.", 'The data were collected during a community-based randomised control trial assessing the impact of mass drug administration (MDA) with praziquantel in Malawi, and a school-based cross sectional epidemiology survey in Zambia. Count data models including traditional (Poisson and negative binomial) models, zero modified models (zero inflated Poisson and zero inflated negative binomial) and hurdle models (Poisson logit hurdle and negative binomial logit hurdle) were fitted and compared.', 'Using Akaike information criteria (AIC), the negative binomial logit hurdle (NBLH) and zero inflated negative binomial (ZINB) showed best performance in both datasets. With regards to zero count capturing, these models performed better than other models.\Question: Do zero adjusted models with applications to analysing helminths count data?
Example Output: This paper showed that zero modified NBLH and ZINB models are more appropriate methods for the analysis of data with excess zeros. The choice between the hurdle and zero-inflated models should be based on the aim and endpoints of the study.

Example Input: Context: Excessive infant crying, or infantile colic, is a common and often stress-inducing problem for parents that can ultimately result in child abuse. From previous research it is known that maternal depression is related to excessive crying, but so far little is known about the influence of paternal depression.', "In a prospective, population-based study, we obtained information on both maternal and paternal depressive symptoms at 20 weeks of pregnancy by using the Brief Symptom Inventory. Parental depressive symptoms were related to excessive crying in 4426 two-month-old infants. The definition of excessive crying was based on the widely used Wessel's criteria (ie, crying >3 hours for >3 days in the past week).", 'After adjustment for depressive symptoms of the mother and relevant confounders, we found a 1.29 (95% confidence interval: 1.09-1.52) higher risk of excessive infant crying per SD of paternal depressive symptoms.\Question: Are paternal depressive symptoms during pregnancy related to excessive infant crying?
Example Output: Our findings indicate that paternal depressive symptoms during pregnancy might be a risk factor for excessive infant crying. This finding could be related to genetic transmission, interaction of a father with lasting depressive symptoms with the infant, or related indirectly through contextual stressors such as marital, familial, or economic distress.

Example Input: Context: SNP309 polymorphism (T-G) at the promoter region of MDM2 has been reported to cause increased binding affinity of transcriptional activator Sp1 followed by increased MDM2 both in mRNA and protein level. This model was proposed in vitro in the small panel of cell lines that indicated an on average 8-fold higher level of MDM2 mRNA in cells bearing the GG genotype.', 'The incidence of SNP309 was determined in a cohort of 158 breast, 17 endometrium, 13 cervix and 45 ovarian cancer tissues by PCR-RFLP. The expression of p53 and MDM2 protein levels in the cohort was immunohistochemically investigated and statistically correlated with SNP309 polymorphism using Pearson chi(2) and t test.', 'No significant difference was observed in the G allele incidence in breast cancer specimens compared to 149 noncancer controls. Furthermore, no statistically significant association of the G allele frequencies and p53 and MDM2 protein expression levels was observed.\Question: Does mDM2SNP309 associate with elevated MDM2 protein expression or breast cancer risk?
Example Output:
Our data clearly show neither association between SNP309 and cancer risk, nor the responsibility of G allele for increased MDM2 or decreased of p53 protein levels in human primary breast tumors.