CHIS (California Health Interview Survey): a random-dial telephone survey of over 20,000 Californians yearly that is statistically representative of the population of California with respect to age groups (adults, adolescents, and children are represented) and race/ethnicity. The survey encompasses a wide range of health-related data, including chronic disease outcomes, mental health, and access to healthcare.
Strong: Do adults reporting low levels of safety and social cohesion in their neighborhoods have higher prevalence of asthma, diabetes, and heart disease? Note that this is not, and cannot be, a causal question since we can’t definitively establish temporality for the exposure-outcome relationship from the available data. This research question would just be examining a potential association in order to allocate resources efficiently. CHIS data asked about both the exposure parameters of adults in its surveys from 2011 onward, so there is a good deal of available data. Since this question is just addressing an association, cross-sectional survey data is adequate.
Weak: After implementation of the Affordable Care Act, were more children diagnosed with asthma in 2015 (compared to 2013, before implementation of the Affordable Care Act)? This question is not possible to answer with CHIS data because, as stated above, we can’t establish when the diagnosis of asthma was made – in other words, these are prevalent and not incident cases of asthma. I could change the question to look at a different outcome, like the number of asthma-related emergency room visits in 2015 compared to 2013 (which I would hypothesize should decrease, since more people should have health insurance and should be seeing their primary care physician for better long-term management of the disease which should result in fewer ER visits). Or I could use a different data source for the original question, like Kaiser medical records (essentially an open cohort). It would still be difficult to attribute any changes to the ACA definitively, since they could be due to temporal trends unrelated to the ACA implementation.
Add Health (National Longitudinal Study of Adolescent to Adult Health): a nationally representative longitudinal study of adolescents who were in grades 7-12 during the 1994-95 school year. The cohort has been followed in adulthood with periodic in-home interviews; the most recent of which took place in 2008. The surveys have collected data on individuals’ social, economic, psychological, and physical health, including a wide range of social network data.
Strong: Do women who reported intimate partner violence in wave 2 have a higher rate of incident migraine headaches in wave 4, and is there effect modification by race/ethnicity or socioeconomic status? The longitudinal nature of the study allows us to see how an earlier exposure affects an outcome for the same group of people. The specification of the time period between exposure and outcome assessment is due to when these questions were asked of the cohort.
Weak: Do women who reported intimate partner violence in wave 2 have a higher rate of incident coronary heart disease in wave 4 (+/- effect modification as above)? While it is certainly possible to estimate an answer with this dataset, we would be answering a somewhat different question. The cohort simply hasn’t been followed long enough for CHD to manifest for most of those in the cohort, so any estimates obtained would likely be a mix of outliers (very early developers of CHD) and people with other forms of heart disease, which is not as useful an answer as one that could either be more specific to isolate CHD forms of heart disease, and one that would have longer follow-up – for example, a cohort like the Nurse’s Health Study could be used for this, if the relevant exposure question had been or could be asked.
NVSS (National Vital Statistics System): data are collected by local jurisdictions that are legally responsible for the registration of vital events (births, deaths, marriages, divorces, fetal deaths) and then reported to the National Center for Health Statistics (NCHS), which is responsible for maintaining the NVSS.
Strong: Did adolescent motor vehicle accident deaths in California decrease after implementation of the provisional driver’s license for those under 18? In order to lend more weight to the potential causal impact of the law, California’s statistics could be compared to those of other states with no such law as a “control” group. Of course, differences between the states could be strong confounders and would need to be well thought-out and adjusted for. Since this is a national database, it is possible to obtain mortality data for multiple states for comparison. Motor vehicle trauma as cause of death should be highly accurate, unlike many other causes of death later in life where there may be more ambiguity with regard to the proximate and ultimate causes of death.
Weak: Is low education associated with increased mortality rates due to cancer? While this question could potentially be answered using mortality record data (since education level and cause of death are both recorded on death certificates), cancer is generally under-reported as a cause of death on death certificates and so we may not get accurate results using this dataset. It may not be possible to address this shortcoming with a different dataset, since mortality records are ultimately the source of cause-of-death determinations. It would likely be possible and help provide more insight to attempt to corroborate death record information with hospital record and cancer registry information. Again, likely this would not completely solve the issue since often there is some subjectivity to the assessment of cause of death, but we may be able to get a better idea of how likely it is that the official cause of death is accurate.