mrueschman

Fengzhen: Nothing like that has been posted on NSRR for SHHS. For another study (CHAT), we have posted some results after a team member used the PhysioNET HRV Toolkit. You might find some helpful links from that tool's page.

We do not have any processed heart rate (e.g. HRV) data posted for SHHS. These would have to be derived from the ECG channels in the EDF versions of the overnight sleep studies. I'm not that familiar with this type of data/analysis myself, so I probably can't provide much more help in this area. If you have more questions I can consult with some of my colleagues who are more familiar with heart rate analysis.

Caroline,

Thanks for stopping by. Would you share more details about why you are trying to merge two files together? Are these files from the same subject in the same night, however the recording was broken up into two pieces (maybe due to equipment problems)? Or are these EDF files from two separate subjects on separate nights?

I don't think we have any tools to do this at present. I will ping a couple other people here who know EDF software better than I do.

To get some "health controls", I think your first step would be to pick and choose the variables you want to filter upon from our datasets. For instance, you mentioned:

1. sleep-disorderd breathing, and
2. cardiovascular diseases

For #1, a common variable to assess sleep apnea is the Apnea-Hypopnea Index, and one commonly used variable is AHI_A0H3. Typically AHI is categorized as follows:

1. <5 = No sleep apnea
2. 5-15 = Mild sleep apnea
3. 15-30 = Moderate sleep apnea
4. >30 = Severe sleep apnea

You could start with one of those cutoffs.

For #2, you might choose some of the prevalent condition variables in the Medical History folder. These variables indicate whether the participant had a diagnosis of things like heart attack or stroke at the time of the visit. Typically the responses are "0 = No" and "1 = Yes" for having the disease or not.

Good luck!

Mimoun,

None of our currently posted datasets contain actigraphy data, though bringing some actigraphy datasets online is certainly something we want to do in the future. We do hope to post some MESA Sleep (ancillary to the MESA project) data within the next year, where we performed 7-day wrist-worn actigraphy on 2,000+ subjects.

Studies like SOF and MrOS did do actigraphy as well, but those were done at different study visits than the sleep measures and the data won't be found on NSRR. You would have a better shot at accessing those data directly from the SOF/MrOS Coordinating Center by submitting an analysis proposal to them. The same goes for MESA, probably.

Sorry we don't have anything available right now - we hope to soon!

Fengzhen,

No, not all participants in SHHS have sleep-disordered breathing.

From the study documentation:

From these parent cohorts, a sample of participants who met the inclusion criteria (age 40 years or older; no history of treatment of sleep apnea; no tracheostomy; no current home oxygen therapy) was invited to participate in the baseline examination of the SHHS, which included an initial polysomnogram (SHHS-1).

The SHHS sleep study represented the first sleep study for most of the participants. Many participants did have sleep-disordered breathing based on the sleep study results, but this was not the case for all participants.

Thanks for the question and for using the site!

Winda,

The SHHS Coordinating Center at Johns Hopkins did not prepare all the data for release on BioLINCC and our resource. In terms of medications, what we have are the derived variables based upon the actual medication lists. The lists of individual medications were not prepared for release.

I do have access to the baseline medication lists, was there a specific question you were looking to answer?

Matt: That's a great observation. I can imagine a new user to the SHHS data making an incorrect assumption based on how the data are now presented (as separate race/ethnicity variables).

In the least, I will have us add better descriptions to the race and ethnicity variables on NSRR that describes the recoding that was done. As for the reason, I will pose that question to Jill at the SHHS Coordinating Center, who we were already conversing with about a separate issue.

Adam,

Thanks -- good question. You also asked about versioning in your email to support@sleepdata.org, so I am going to post my reply here about that issue and the race issue you note.

The idea behind our versioning is that the most recent version (0.8.0 for SHHS) would be the “latest and greatest” and would be our suggested starting point for new analyses. From 0.3.0 and onward we broke the dataset into separate CSVs per visit, which would explain why 0.2.0 has more observations in its single file than the files that came later. Also around the switch from 0.2.0 to 0.3.0 we received updated data from the dataset owner (Johns Hopkins in this case) that added more cases to our “CVD Outcomes” dataset. We took down 0.3.0 because it contained records for SHHS subjects that did not consent to share data for future research.

Yes, the race data were collapsed into 3 categories by the SHHS dataset owners, which explains the difference between 0.2.0 and 0.4.0+. Our NSRR data mimic what is posted on BioLINCC (https://biolincc.nhlbi.nih.gov/studies/shhs/?q=shhs) – our 0.2.0 version of the data came from a preliminary BioLINCC dataset which did not have the race variable change incorporated yet.

Technically one could look back to the older dataset (possibly merging with a newer version) to get the race variable with more fine-grained categories, but we have not carried these data forward into subsequent releases since this is how the dataset owners have immortalized the dataset on BioLINCC. My best guess is that this change was made to more closely match a quasi-standard of how race is presented in BioLINCC datasets. Most datasets that I have seen from BioLINCC have this Black/White/Other breakdown.

As for your other question about the parent cohorts: There will not be a way to identify the parent cohort of SHHS participants from the NSRR datasets. These links were explicitly removed by the dataset owners as part of the de-identification process when posting on BioLINCC. I believe if you went through BioLINCC to request and obtain access to the parent cohorts (e.g. Framingham, ARIC, etc.) that they may grant access to the linking codes (lookup table with IDs across different data sources).

Hope this helps. Thanks!

Madhvi,

Most of the events in the annotation files were marked by a technician. Each dataset should have an overview of the scoring procedures/rules that should provide the details you mention. For CHAT, that documentation exists here: https://www.sleepdata.org/datasets/chat/pages/manuals/polysomnography-reading-center/6-07-scoring-procedures.md

Let us know if you have further questions. If you want a fuller explanation, I can ask one of our PSG experts to comment. Thanks for using the NSRR!