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Lab
Lab : Making Music with Pd in Satellite CCRMA

Revision as of 08:27, 4 October 2013
Lab 2: Making Music with Pd in Satellite CCRMA
Most instructions by Edgar Berdahl, and lab patches for musical interaction description by Matt Wright and possibly others
For this lab you need your Satellite CCRMA kit, a computer to program it, and some headphones with a mini 1/8" stereo jack.
- 1 The Satellite CCRMA Setup (Before Adding Arduino)
- 2 Powering Up For The First Time
- 3 Connect To Satellite CCRMA
- 4 Avoid Powering Down the Board Without Halting it First!
- 5 Getting Comfortable With Satellite CCRMA
- 6 Starting Audio And Pd
- 7 Dive Into Pd
- 8 The Patches Are Already On The Board
- 9 Design a different musical interaction
- 10 More Sound Synthesizer Patches
- 11 The Community
- 12 Appendix A: Troubleshooting
- 13 Appendix B: Transferring Files To and From Your Kit
- 14 Halt Your Board Properly When Finished!
- 15 Copying Files To and From Your Kit
- 16 More Pd resources
The Satellite CCRMA Setup (Before Adding Arduino)
Included in your kit so far you should have
- Raspberry Pi Model B (with 512MB of RAM) - One memory card (it may already be inserted into your Raspberry Pi) - One Ethernet cable for communication with your laptop - One USB micro cable
If you are missing something, please go get it before assembling your kit. Make sure you plug the SD memory card is seated all of the way in its slot.
Powering Up For The First Time
Plug the Ethernet port of the Raspberry Pi into your laptop. Then use the USB micro cable to power up the Raspberry Pi. (If you have a USB power supply, you could use it to power the Raspberry Pi, or if not you can try using your laptop's USB connector to power the Rasberry Pi.) You should see some lights turn on, flickering every now and then. This means that the Raspberry Pi is booting up.
Connect To Satellite CCRMA
In order to see what your Satellite CCRMA kit is doing and program it, you need to log in to it. To do so, follow these instructions.
After you login, you will see the prompt ccrma@satellite:~$ This means that you are logged into a computer named "satellite" as the user "ccrma", and you are currently in the directory ~, which is the shortcut for your home directory.
Avoid Powering Down the Board Without Halting it First!
Would you take the battery out of your laptop and unplug its power adaptor without shutting down? I don't think so! The same goes for Satellite CCRMA, at least when you can avoid it, because it is a small computer running linux.
Now we will test the halt procedure. Run the halt command as superuser by typing sudo halt at the Satellite CCRMA prompt. Then you will again have to type in the password temppwd in order to have the privilege to run this command. Wait until about 15 seconds after you see the message "Connection to 192.168.105.106 closed by remote host," and then disconnect the power from the Raspberry Pi via the micro USB connector.
Getting Comfortable With Satellite CCRMA
- Turn on Satellite CCRMA again using the same procedure as before by plugging the micro USB connector into the Raspberry Pi. After about 30 seconds, the board should be booted up again, so you can log in again by running the command
ssh -XY firstname.lastname@example.com
- Run the command pwd to find out the current directory. You will find that you are in the ccrma subdirectory of the directory /home.
- Type the ls command to see what is in the current directory. The blue items are subdirectories of the current directory. You can change directories using the cd command. For instance, to change into the pd subdirectory, you should run the command
cd pd
- Now again type pwd to make sure that you understand where you are! Run the ls command to see what files are in here.
Starting Audio And Pd
- In order to be able to hear audio, you will need to plug a pair of ear buds, headphones, or loudspeakers into the 1/8" (2.54mm) jack on the Raspberry Pi (often it is yellow).
- A default pd patch starts running automatically when your kit finishes booting up. To stop the default pd patch from running, execute the command
Remember that each time you boot up your kit and want to edit your patch, you should stop the default patch from running by using the command stop-default
- Change directories by entering the following command:
"cd pd"
- Start pd now with the following command (the "space" & just means that the pd process shouldn't take over the terminal -- that way you can keep using the terminal independently of whatever pd is doing)
pd &
This time the graphical user interface (GUI) for pd should also start.
- To start audio, click on the Compute audio checkbox.
- Now to test audio, go to the media pull-down menu and choose Test Audio and MIDI. If you still do not here any sound, then probably you missed one of the steps so far. If you look at the messages in the main pd window, you might find a clue.
- Once you have audio working, close the window test audio and MIDI window.
- Choose Open from the File menu and select the patch 4_algorithmic_music.pd within the pd_lecture subdirectory. Then go back to the patch, move the speed and width sliders slightly to the right, and bring up the volume. You should now hear some sound in your headphones. Play around with the parameters to see what new sounds you can discover.
Troubleshooting: If you still do not here any sound, then probably you missed one of the steps so far. If you look at the messages in the main pd window, you might find a clue.
Dive Into Pd
- Check out this page for links to Pd tutorials and resources:
- The patch ~/pd/examples/just-play-WAV-files/play-WAV-file.pd shows the easiest way to play a WAV file. Try it out!
- Look at the pd lecture patches stored in ~/pd/pd-lecture (For example, see the patch 4_algorithmic_music.pd. Make sure that audio is on and increase the volume from zero in the patch.)
- Right-click or option-click on any object to get a contextual menu including "help," which opens that object's help patch. (If you are using a Mac and don't have a right mouse button, then go to the X11 pull-down menu, select Preferences, and make sure that Emulate three button mouse is checked in the Input pane. Now, you should be able to right-click by clicking while holding down the Command key.)
- Right-click on a blank portion of a Pd patch. Now when you select "help" you get a list of Pd's built-in objects, arranged by category.
- In the upper right hand corner of each Pd window is a "help" menu. This accesses the Pd tutorials as well as some online reference documentation.
The Patches Are Already On The Board
- You can find the main patch for the laboratory exercise at /home/ccrma/pd/labs-Music-250a-2012/lab1/myinstrument.pd Open it and make sure that compute audio is set to on. Play around with the patch. You should be able to exhaust its musical potential in a matter of minutes; reflect on its strengths and limitations.
- Also try to understand how it works as a piece of software. (But please don't get hung up on the arcana - as always, if you get stuck, ask for help rather than waste time.)
Design a different musical interaction
The following instructions should look familiar. They are basically the same tasks that you were given for Lab 1. This lab is meant to build on the learning that you did in the first lab.
Here are some ideas of changes that might make the patch more interesting:
- Involve more QWERTY keys
- Involve the mouse (see the [MouseState] object)
- Load in a larger collection of samples.
- Implement a mechanism to switch among banks of samples
- Multiple gestures to one result: design a way for the parameters of each triggered note to depend on multiple key presses. For example, maybe only the space bar triggers notes, and all the other keys determine parameters of notes.
- Make your patch automatically generate a bassline as a function of the key presses
- Set multiple parameters modally, as volume works in the sample patch
- Use chording: keep track of all the keys that are currently pressed, and use only that information to set the parameters for each note.
- One gesture to multiple results
- Use the "metro" object to trigger a steady stream of notes. Now you have two new parameters: repetition rate, and whether the metro is on or off.
- Use the "counter" object to step through a cycle (of samples, parameter settings, etc.)
- You could combine "metro" and "counter" to build a rudimentary sequencer that can step through a rhythmic pattern
- Invent a mechanism to record short sequences of keypresses and play them back in time.
- Incorporate looping or other interactive controls over the soundfile playback
- Use Pd's "spigot" object to route control information to different parts of your patch at different times
- Use some additional signal processing such as a filter, delay line, reverb, tremolo, etc. This gives you more parameters to control.
- Polyphony: make it so the patch can play multiple samples at the same time. (Hint: put multiple copies of "play-sample" in your patch)
- Use a totally different form of sound synthesis, such as FM, granular, or physical modeling.
We recommend that you pick only one or a small number of these and work on it in depth, iterating on both the program/test/debug cycle as well as the design/implement/play cycle to craft something that has actual musical potential or is at least more fun to play. If you have an existing idea for your class project, you could use this lab to start thinking about implementing some of the modes and mappings. By all means, if you're inspired to try something else, go for it. If you'd rather spend today getting more of a broad sense of Pd's capabilities, feel free to work on many of these suggestions.
More Sound Synthesizer Patches
- Try out some of the patches from Andy Farnell's book Designing Sound. These patches are installed in ~/pd/DesigningSoundBookExamples Most of the patches in there work with this version of pd, but a few patches don't! (As you try out the patches, keep in mind also that many of the patches are subpatches. That means that they are lower level patches that are used to serve some specific purpose within a higher level patch. Therefore, you may have to search around some to find the higher level patches that are easier to use to make sound.)
- One intriguing way to synthesize sound is using physical models. A physical model is a computer program that simulates the laws of physics to create sound. Some physical models simulate traditional acoustic musical instruments, or other models simulate hypothetical situations that could be built using physical elements, but might be impractical. Try playing around with some of the physical models in ~/pd/SaM-models -- the FireFaderSimulator versions of the patches are the ones you will want to use. The process of tuning the model parameters can be useful from a compositional perspective because it can help provide you with a specific palette of sounds.
The Community
There is a large, dedicated, and very generous community of Pd users on the Internet. Do some web searching (e.g., with a search engine, or else starting from some more specific resources) and look for interesting externals and/or patches. Optional: Download, install, and play with at least one. Can you incorporate it into what you programmed in the previous part?
For more help in finding resources, don't forget to look on the PID Links page.
Appendix A: Troubleshooting
- If you are having problems with audio, make sure that compute audio is set to on.
- If the audio is stuttering, then your processor might not be powerful enough to run all of the patches that are open. Remember, Satellite CCRMA is not as powerful as a laptop. Therefore, be careful about building complicated patches. You can monitor how much CPU you are using by running the top command in the terminal.
- Type dmesg to see if there are any relevant messages that look like error messages.
- If you are running out of space on the SD card, you can free up some space by deleting items in /usr/src. For instance, all of the files needed for building Pure Data Extended are rather large.
Appendix B: Transferring Files To and From Your Kit
- Download CyberDuck to your laptop to make it easy to transfer files back and forth from your kit.
- Start CyberDuck on your laptop, and then create the following new bookmark:
- Once you have finished entering the text, close the bookmark window.
- Then you can use CyberDuck to connect to your Satellite CCRMA kit by double clicking on the SFTP to Satellite CCRMA bookmark.
- After you enter the password temppwd, CyberDuck will connect and open window to open up showing the files in the /home/ccrma home directory on your kit.
- You can drag and drop files from here to move them back and forth.
- If you move WAV files to your kit, please remember that the default sampling rate for pd is 22kHz, so you may want to resample them first. For example, Audacity can be used to resample the audio files.
Halt Your Board Properly When Finished!
- Remember to shut down your board using
sudo halt
when you are done before powering it off!
Copying Files To and From Your Kit
- Alternatively, if you would like to use software with a nice GUI for copying files back and forth from your kit, you can install additional special software on your laptop. For Windows, install Secure FX, or for Mac OS X, install Fetch. These programs actually use scp, but they hide the details of the pathnames from you.
More Pd resources
- Here are some lists of pd objects that you can use to discover new object names: http://protman.com/content/list-puredata-objects-and-extended-objects http://www.umatic.nl/workshop/objects.txt


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ELC 2006 Biographies
Biographies for ELC 2006 go here:
- 1 Andre Kruetzfeldt
- 2 Armin Gerritsen
- 3 Chang-Sik Cho
- 4 Denis Olivier Krop
- 5 Ed Plowman
- 6 Greg Kroah-Hartman
- 7 Greg Ungerer
- 8 Hyok S. Choi
- 9 Jared Hulbert
- 10 John Goodacre
- 11 Jordan Crouse
- 12 Jung-Hyun Yoo
- 13 Kevin D. Kissell
- 14 Kittur Ganesh
- 15 Klaas de Waal
- 16 Liam Girdwood
- 17 Manas Saksena
- 18 Marcin Klecha
- 19 Mark Gross
- 20 Mathew Locke
- 21 Mathieu Desnoyers
- 22 Matthew Klahn
- 23 Matthew Locke
- 24 Matt Mackall
- 25 Min-Seok Jang
- 26 Munehiro Ikeda
- 27 Nicholas Mc Guire
- 28 Rob Landley
- 29 Ruud Derwig
- 30 Scott Preece
- 31 Shinichi Ochiai
- 32 Steve Johnson
- 33 Takanari Hayama
- 34 Thomas Gleixner
- 35 Todd Poynor
- 36 Tohru Nojiri
Andre Kruetzfeldt
Armin Gerritsen
Armin Gerritsen is a young and enthusiastic embedded software developer. He started as a physicist, but entered Philips shortly after receiving his master degree on the area of computational physics, where he was hired to do modelling for future generations of Philips Semiconductor platforms. Shortly after he was sucked into the embedded Linux world and failed to escape since then. His job is to support the implementation of new designs by writing software necessary for (dis)proving new concepts, prototypes and demonstrator platforms. The vast majority of this software is based on Linux.
Chang-Sik Cho
Denis Olivier Krop
Ed Plowman
Ed Plowman has more than 10 years of experience in media and graphics processing. Ed is currently employed as 3D Graphics Products Manager with ARM Ltd, guiding ARM's 3D graphics processing strategy. He also represents ARM in the OpenGL ES working group and occupies the ARM seat on the Khornos board of promoters. Ed started his career as one of the founding members of Argonaut technologies (an off shoot of Argonaut Software which later became ARC cores), working on CPU based 3D graphics technology which later provided the foundation for the ARC processor core.
Greg Kroah-Hartman
Greg Kroah-Hartman is the current Linux kernel maintainer for more driver subsystems than he wants to admit, along with the driver core, sysfs, kobject, kref, and debugfs code. He is also the maintainer of the linux-hotplug and udev projects. On top of that he maintains the Gentoo Linux packages for these programs, and helps with the kernel package, which put him in touch with actual users every day, thereby ensuring his email inbox is never empty. He is also the co-author of the book, "Linux Device Drivers, 3rd Edition" and a contributing editor for Linux Journal.
Greg Ungerer
Greg specializes in embedded systems development, having spent more than 15 years developing embedded software, and more than 10 years developing with Linux.
Greg is currently one of the core maintainers of the uClinux project. He first started hacking on it 7 years ago, and did the port to the Motorola Cold Fire CPU family. Over the last couple of years Greg has been pushing the uClinux support into Linus's mainline 2.6 series Linux kernels. Greg has been involved in the design and release of many commercial products based on uClinux software over the last few years.
Hyok S. Choi
Hyok S. Choi is the maintainer of uClinux/ARM and a system architect for electronic gadgets in Samsung. The project URL is http://opensrc.sec.samsung.com/
Jared Hulbert
Jared Hulbert has been working with embedded Linux since 2000 when he picked up a ucSimm. Hes worked with XIP on Linux since 2001 helping port it to various machines. He now works for the CTO of the Intel Flash Memory Group managing the Linux Team trying to improve Intel NOR and NAND flash memory support for Linux. Jared has helped Intel customers optimize and port Linux on several phones currently on the market. He has also created many systems as demos for customers or internal uses such as what was probably the worlds only XIP Linux iPaq.
John Goodacre
Program Manager, Multiprocessing, ARM
John joined ARM in February 2002 taking responsibility for their platform architecture roadmap. More recently he has been responsible for the market development of multiprocessing technology and the release of ARM11 MPCore the first integrated SMP core.
Prior to working at ARM, he worked for Microsoft for 5 years, firstly as Group Program Manager in the Exchange Server group and latterly as the manager for its Wireless Telephony group responsible for product, the definitions and strategy of mobile devices.
Graduating from the University of York with a BSc in Computer Science, John has over 20 years experience in the engineering industry.
Jordan Crouse
Jung-Hyun Yoo
Kevin D. Kissell
Kevin D. Kissell is Principal Architect at MIPS Technologies, and has been a part of the MIPS architecture development team since its spin-out from Silicon Graphics in 1997. He was first involved in the architecture and design of RISC microprocessors when he joined the original Fairchild Clipper design team in 1983. In between, Kevin has been variously responsible for processor, systems and software architecture, for decoupled access/execute supercomputers at ACRI, massively parallel distributed memory computers at nCUBE, and large-scale shared-memory supercomputers at Evans & Sutherland. His prior work at MIPS includes having been principal architect of the Smart MIPS(tm) extensions for smart cards. He holds a degree in computer science from the University of California at Berkeley.
Kittur Ganesh
Kittur Ganesh is a Sr.Technical Consulting Engineer at Intel providing consulting, support and training on various software products targeting Intel® Architecture. Previously, for 6+ years at Intel, Kittur designed and developed software primarily used for fracturing design data of Intel chips. Prior to joining Intel, Kittur was involved in developing commercial SW in the EDA industry for 10+ years. Kittur has a M.S (Computer Science), M.S (Industrial Eng.) and a B.S (Mechanical Eng.)
Klaas de Waal
Klaas de Waal has been writing software for systems ranging from Seiko 8-bit microprocessors to Silicon Graphics workstations. He was writing applications for Linux at the time when it was still called Unix, AIX, Irix or Solaris. Instead of writing software he now spends most of his time porting existing open-source applications to the Philips Semiconductor's Nexperia platform and talking about it.
Liam Girdwood
Liam Girdwood is a Software Engineer at Wolfson Microelectronics. He specialises in embedded Linux audio and, prior to joining Wolfson, was an embedded Linux consultant with HP (now Agilent). He has worked within the Free Software community for more than five years. Liam Girdwood holds a Computer Science Degree from Heriot-Watt University. In his spare time, he is the maintainer of several open source projects including libnova (http://libnova.sf.net ), a celestial mechanics library used by robotic telescopes around the world.
Manas Saksena
Manas Saksena is the CTO of Time Sys, where he is responsible for the technology strategy and development for Embedded Linux products and services. He is also the chair of the real-time working group at CELF. In his past life, he spent a few years doing research in real-time systems, and published a number of papers on that topic.
Marcin Klecha
Mark Gross
Mathew Locke
Mathieu Desnoyers
Mathieu Desnoyers is interested in kernel programming internals and computer security. He contributed to the rt2570 wireless driver, to the Linux Kernel time subsystem and he took part in technical discussions with the System TAP team. He is active in the 2600 Montr�al group, follows security conferences and competitions.
Since November 2005, he has become the maintainer of the Linux Trace Toolkit (LTT) project, taking over the development with the new LTTng. He is the author of Linux Trace Toolkit Next Generation (LTTng) project which started in may 2005 (http://ltt.polymtl.ca). He is the main developer of Linux Trace Toolkit Viewer (LTTV) since the project started in 2003. He is currently completing a M.Sc.A. in Computer Engineering at Ecole Polytechnique de Montr�al.
Matthew Klahn
Matthew Locke
Matt Mackall
Min-Seok Jang
Munehiro Ikeda
Nicholas Mc Guire
Rob Landley
Rob Landley is a Senior Linux Engineer at Time Sys Corporation and the new maintainer of BusyBox. He first encountered Linux when the SLS disks came across Fidonet in 1993, and has been building various Linux systems from source code for six years. He co-founded a combination Linux Expo and Science Fiction convention (Penguicon) because that really is his idea of fun, as are writing documentation, researching computer history, urban hiking, and knitting chain mail.
Ruud Derwig
Scott Preece
Scott Preece is a senior software architect at Motorola Mobile Devices, working in Champaign-Urbana, Illinois, on developing a mobile-phone platform based on Linux. He has been working in software development close to 40 years, with extended periods in information retrieval research, user interaction design, UNIX system development, LISP compilers, and mobile-phone software systems. He is a Motorola Science Advisory Board Associate and was chairman of Motorola's Software Engineering Technology Steering Committee.
Scott has a Computer Science PhD from the University of Illinois as well as degrees from Dartmouth College and the University of Chicago, dating to before Computer Science was a major.
Scott chairs the CELF Mobile Phone Profile Working Group and is a member of the CELF Architecture Group.
Shinichi Ochiai
Steve Johnson
Steve Johnson has been a Senior Software Engineer for a Panasonic R & D lab in Princeton, NJ for the last 14 years. He is currently the chair of CELF's Security Working Group. He graduated from the University of California, Davis in 1968, 1970, and 1977 from which you can draw two conclusions: 1) he's getting up there in years, and 2) you shouldn't make any assumptions about the sequence of years. In his spare time he likes to make and/or fix things, which pretty much describes his working day also. His current wish is to learn more Japanese words without forgetting the words learned last week.
Takanari Hayama
Takanari Hayama, Ph.D. is a founder and president of IGEL Co.,Ltd, an IT consulting company. He has been consluting Linux and open source solutions for more than 10 years. He has been supporting many kernel related development. He has developped Linux drivers for MPEG-2 Decoders, Digital TV related products, Professional Audio Device and so on. He also has involved in IPv6 development that runs not on only Linux, but also on NetBSD and ITRON. His current interrests are in the area of multimedia computing, operating system and mobile computing.
Thomas Gleixner
Thomas Gleixner has worked on industrial embedded devices for over 20 years. During the last 8 years he has focused on Linux for industrial applications. He has contributed to Linux in several ways. He is the main author of the hrtimer subsystem and the high resolution timer implementation on top of hrtimers and a major contributor to Ingo Molnars realtime preemption patch.
Todd Poynor
Todd works on embedded Linux OS features for Monta Vista Software, including development of power management technology for mobile devices and consulting with consumer electronics manufacturers on power management architecture.


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Before you get started, your dentist will determine if CEREC® is right for you. Depending on how much healthy tooth structure you have remaining, it may be a simple filling or you may need a crown. After reviewing your options, the dentist will begin the process by administering anesthetic and preparing your tooth for restoration by removing decay and weakened tooth tissue.
Optical Impression
In order to make the desired restoration, a 3-dimensional image of the tooth that needs to be restored must be created from a digital camera scan of the tooth. This three-dimensional image will be used to create the restoration without the need to take a messy impression. This means no horrible tasting impression material for you to gag on. The computer and CEREC® 3D software then converts the digital image into a three-dimensional virtual model of the prepared tooth.
Milling Unit
This device is used to used to create the custom restoration needed for the tooth. Based on the original color of your tooth, the dentist is able to select the correct colored ceramic block and in a few minutes, the milling device is able to create the restoration needed.
Placing the Restoration
After the restoration is made, it is ready to be tried on to ensure that you get proper fit and bite. When it is ready, the restoration is polished and bonded into place by your dentist. Therefore, no temporary restoration is needed and no return trip is necessary, saving you time and money.
Advantages to Using CEREC®
CEREC® has revolutionized the restorative process. It was created with the patient in mind in order to make a visit to the dentist as pain-free as possible. Some of the benefits to using CEREC® are:
- Most procedures can be done in one visit - less costly and less time-consuming
- Less painful injections due to single-visit
- No need to take messy impressions
- No need to have a temporary restoration for in-between visits
- Ability to save as much natural tooth structure as possible
- Longer lasting restorations - may last over 10 years
- Restores teeth to natural beauty, function and strength
- Metal-free restorations


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Cataracts is a disease of the eye that results in the clouding of the lens of the eyeball. Cataracts prevent clear images from appearing on the eye's retina; causing mild, moderate, even severe blurred vision. Watch a short video about cataracts now.
Typically an eye disorder associated with aging (over half of the people in America over age 80 have either had a cataract or cataract surgery), cataracts generally occur later in life as the lens structure within the human eye changes and gets older.
Cataract Surgery
Cataract surgery is the removal of the natural lens of the eye (also called "crystalline lens") that has developed an opacification, which is referred to as a cataract. Metabolic changes of the crystalline lens fibers over the time lead to the development of the cataract and loss of transparency, causing impairment or loss of vision. During cataract surgery, a patient's cloudy natural lens is removed and replaced with a synthetic lens to restore the lens's transparency.
Following surgical removal of the natural lens, an artificial intraocular lens implant is inserted (eye surgeons say that the lens is "implanted"). Cataract surgery is generally performed by an ophthalmologist (eye surgeon) in an ambulatory (rather than inpatient) setting, in a surgical center or hospital, using local anesthesia (either topical, peribulbar, or retrobulbar), usually causing little or no discomfort to the patient. Well over 90% of operations are successful in restoring useful vision, with a low complication rate. Day care, high volume, minimally invasive, small incision phacoemulsification with quick post-op recovery has become the standard of care in cataract surgery all over the world.
Learn More
The more you know about cataracts, the better prepared you will be to deal with them – or help prevent them in the first place!


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His Wings Shadow
Today's Verse
What I Believe
This Prayer WILL Change Your Life
My Favorites
The Names of Jesus
God's Mercy ~
Fear Not . . . Verses
~ God of My Strength ~
God of My Faith ~
~ God of My Hope ~
Verse's On Joy ~
Hymns and Songs ~
Amazing Grace ~
All Glory Be Thine ~
A Friend Indeed ~
Are You Washed In The Blood?
Listen to Christian Radio
Corrie ten Boom Famous Quotes
Lessons on Living ~ by Woodrow Kroll
Joy and Strength ~ by Mary Wilder Tileston
Streams in the Desert ~ by Mrs. Charles Cowman
Streams in the Desert ~ by Mrs. Charles Cowman
Prayer, Praise and Promises ~ by Warren Wiersbe
Strength for the Journey ~ by Theodore Epp
Early in the Morning ~ by Woodrow Kroll       Â
In Touch Magazine ~ Charles Stanley
Weekly Wisdom
If I Were Abraham
How I Turned My Trash Into Treasures
My Poetry ~
For God So Loved The World ~
Let Us Love ~
Peace Of Mind ~
My Times Are In Your Hands
His Wings Shadow
Abba ~ My Father
The Mystery of God's Love
Let Jesus Come In
The Lyrics of My Heart ~
Give Me Faith
Putting On the New Man
The Gardner's Call
For Every Beginning . . .
All That I Need ~
Wonder Upon Wonder
Wandering Wanderers
Oh, Glorious One
God Is My Refuge
I Wait ~
I am Not Ashamed ~
God Has His Reasons ~
Change Me Lord ~
God, I Give You All the Glory
His Saving Light ~
Prayer Gems
Gem #1
Gem # 2
Gem # 3
Gem # 4
Gem # 5
Gem #6
Gem # 7
Gem # 8
Gem # 9
Gem # 10
Gem # 11
Gem #12
Gem #13
Gem #14
Gem #15
Gem #16
Gem #17
Gem #18
Study It
Bible GateWay
Bible Study Tools ~
~ Bible Hub ~
In Touch Magazine ~ Charles Stanley
David Wilkerson
Katherine Kuhlman
Corrie ten Boom
Bible Prophecy
Matthew 24
Who is Hal Lindsey
The Death of The Dollar
End Time Prophesies (Aids) – Dr Hal Lindsey
Favorite Quotes
~ C. S. Lewis ~
~ Corrie Ten Boom ~
Love Bears ~ CHRISTian poetry by deborah ann free to use
Entering The Faithful Race ~ CHRISTian poetry by deborah ann free to use
Be Joyful and Prayerful ~ CHRISTian poetry by deborah ann free to use
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Call Us Immediately if You Need a Wadsworth Plumber for Maintenance and Repairs
Licensed and Trained Professionals Available 24 Hours a Day, 7 Days a WeekFinding a plumbing technician in Wadsworth IL, especially during an emergency, is difficult. However, finding one that has a stellar reputation, the right types of licenses and insurance, and one that you can trust, is often next to impossible. When you are facing an emergency where you are having a big water leak, or sewage coming up into your home, you do not want to have to waste time comparing which company is going to do the best job, you want help! That's why we do what we do.


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Auker, Elden; Baseball. Action - pitching.
See more! Click to view other items that share this title
Some content, including the item here, have similar titles. This type of overlap many times has origins in the item's original physical form. For example, with the Virtual Motor City Collection, photographs were grouped in envelopes with a few descriptive words written on the front. Those words then formed the basis for titles.


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This framed print features a frame and mat combination selected to complement your art. The print, which displays sharp, vivid images and a high degree of color accuracy, is protected and enhanced by this frame that has been handcrafted in the USA from the finest materials.
Slim and tall, this contemporary Chelsea wood frame has a forest browngray finish and is well suited for all art types.
Arrives by Mon, Dec 18
Product ID: 16842549


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Jaguar branded Gloss Black side power vents provide a dynamic exterior styling enhancement. 21MY onwards.
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text: Nomad Health helps Breast Ultrasound Technologist professionals find high-paying travel jobs in North Carolina. Breast Ultrasound Technologist travel jobs at Nomad come with fully loaded travel benefits including medical, dental, vision, and malpractice insurance on top of a 401(k) with employer matching. Nomad also offers reimbursements for scrubs, licenses, certifications, and up to $1,000 for travel to your assignment. Browse Nomad's full list of Breast Ultrasound Technologist travel jobs in North Carolina below to start the next journey in your career.


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- What information do we collect and what do we do with it?
When you register as a participant or subscriber ("learner") on our site or related courses, as part of the registration or enrolling process, we collect the personal information you give us such as your name and email address.
Email marketing: we may send you emails about our site and related training/course(s), registration, course content, your course progress or other updates. We may also use your email to inform you about changes to the course, survey you about your usage, or collect your opinion.
- How do you get my consent?
When you provide us with personal information to become a participant/learner on our site, make a purchase, or participate in the course, you imply that you consent to our collecting it and using it for that specific reason only.
If we ask for your personal information for a secondary reason, like marketing, we will either ask you directly for your expressed consent, or provide you with an opportunity to say no.
How do I withdraw my consent?
If after you opt-in, you change your mind, you may withdraw your consent for us to contact you, for the continued collection, use or disclosure of your information, at any time, by contacting us at email@example.com or mailing us at: Brighter Day Therapeutic Solutions-12781 Darby Brook Court, # 202 Woodbridge, VA 22192
- Disclosure
We may disclose your personal information if we are required by law to do so or if you violate our Terms of Service [INSERT LINK to your Terms of Service].
- Envato
Our platform uses Envato digital assets and services. They provide us with the online workshop/course creation platform that allow us to sell our product/services to you.
Your data is stored through Arlo's data storage, databases and the general Envato application. They store your data on a secure server behind a firewall.
If you make a purchase on our site, we use a third-party payment processor such as Authorize.net or Paypal. Payments are encrypted through the Payment Card Industry Data Security Standard (PCI-DSS). Your purchase transaction data is stored only as long as is necessary to complete your purchase transaction.
All direct payment gateways adhere to the standards set by PCI-DSS as managed by the PCI Security Standards Council, which is a joint effort of brands like Visa, MasterCard, American Express and Discover.
PCI-DSS requirements help ensure the secure handling of credit card information by our site and related courses and its service providers.
For more insight, you may also want to read Envato's Terms of Service here https://elements.envato.com/user-terms or Privacy Statement here https://envato.com/privacy/.
- Third Party Services
In general, the third-party providers used by us will only collect, use and disclose your information to the extent necessary to allow them to perform the services they provide to us.
However, certain third-party service providers, such as payment gateways and other payment transaction processors, have their own privacy policies in respect to the information we are required to provide to them for your purchase-related transactions.
For these providers, we recommend that you read their privacy policies so you can understand the manner in which your personal information will be handled by these providers.
Certain providers may be located in or have facilities that are located in a different jurisdiction than either you or us. If you elect to proceed with a transaction that involves the services of a third-party service provider, then your information may become subject to the laws of the jurisdiction(s) in which that service provider or its facilities are located.
As an example, if you are located in Canada and your transaction is processed by a payment gateway located in the United States, then your personal information used in completing that transaction may be subject to disclosure under United States legislation, including the Patriot Act.
Once you leave our training website or are redirected to a third-party website or application, you are no longer governed by this Privacy Policy or our website's Terms of Service.
When you click on links on our training site, they may direct you away from our site. We are not responsible for the privacy practices of other sites and encourage you to read their privacy statements.
- Security
To protect your personal information, we take reasonable precautions and follow industry best practices to make sure it is not inappropriately lost, misused, accessed, disclosed, altered or destroyed.
If you provide us with your credit card information, the information is encrypted using secure socket layer technology (SSL) and stored with a AES-256 encryption. Although no method of transmission over the Internet or electronic storage is 100% secure, we follow all PCI-DSS requirements and implement additional generally accepted industry standards.
We collect cookies or similar tracking technologies. This means information that our website's server transfers to your computer. This information can be used to track your session on our website. Cookies may also be used to customize our website content for you as an individual. If you are using one of the common Internet web browsers, you can set up your browser to either let you know when you receive a cookie or to deny cookie access to your computer.
We use cookies to recognize your device and provide you with a personalized experience.
We also use cookies to attribute visits to our websites to third-party sources and to serve targeted ads from Google, Facebook, Instagram and other third-party vendors.
Our third-party advertisers use cookies to track your prior visits to our websites and elsewhere on the Internet in order to serve you targeted ads. For more information about targeted or behavioral advertising, please visit https://www.networkadvertising.org/understanding-online-advertising.
Opting out: You can opt out of targeted ads served via specific third-party vendors by visiting the Digital Advertising Alliance's Opt-Out page.
We may also use automated tracking methods on our websites, in communications with you, and in our products and services, to measure performance and engagement.
Please note that because there is no consistent industry understanding of how to respond to "Do Not Track" signals, we do not alter our data collection and usage practices when we detect such a signal from your browser.
Web Analysis Tools
We may use web analysis tools that are built into the Brighter Day Therapeutic Solutions DBA Unicorn Life Training website to measure and collect anonymous session information.
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By using this site, you represent that you are at least the age of majority in your state or province of residence, or that you are the age of majority in your state or province of residence.
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We reserve the right to modify this privacy policy at any time, so please review it frequently. Changes and clarifications will take effect immediately upon their posting on the website. If we make material changes to this policy, we will notify you here that it has been updated, so that you are aware of what information we collect, how we use it, and under what circumstances, if any, we use and/or disclose it.
If our site or course is acquired or merged with another company, your information may be transferred to the new owners so that we may continue to sell products to you.
If you would like to: access, correct, amend or delete any personal information we have about you, register a complaint, or simply want more information contact our Privacy Compliance Officer at firstname.lastname@example.com or by mail at
Brighter Day Therapeutic Solutions, 12781 Darby Brook Court, #202, Woodbridge, VA 22192


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Light Grey Sheepskin Rug (Single)
Dimensions: 95 x 65cm (37.5" x 26")
Sheepskin rugs are measured from the fur side of the rug. The dimensions are approximate and can vary from rug to rug.
- Dyed light grey colour
- Naturally hypoallergenic
- Naturally dirt and stain resistant
- Thick and dense wool fleece
- Minimum wool length of 6cm
- Easy to clean (see cleaning instructions)
Do not expose dyed skin to strong light and direct sunlight to avoid fading and colour change. Colour transfer may occur if put on wet or light place like sofas.
Often used:
- On chairs and furniture
- Small area rug
- Bedroom rug
- To sleep on to help prevent bed sores
- Yoga / exercise rug
See our FAQs page for more information about this product.
Christmas Delivery
Free (3-5 Day Delivery) - Please place any orders before Tuesday 19th December for delivery before Christmas
Next Working Day Delivery - Please place any orders before 2pm Thursday 21st December for delivery before Christmas
Please be aware our team will not be working between Friday 22nd December & Tuesday 26th December, so any orders placed between these dates will not be sent out until after 26th December. We also expect to have a lot of orders to send out when we are back, so we ask for patience as we get through all the orders. We will endeavour to get all orders out by Friday 29th December.
We are a small, family run team, and we want to make sure all our staff get to enjoy their Christmas break too.
Delivery Information
We offer a free 3-5 day delivery service for all order in the UK. All items are dispatched from our warehouse in Gloucestershire and delivered to your door. For UK deliveries we use Royal Mail for smaller items and Parcelforce or DPD for larger items. For International orders we mainly use Parcelforce, but may use other couriers if they are more competitive for your location.
UK Delivery
Standard Delivery 3-5 Days - FREE
Next Working Day Delivery (order before 2pm) - £4.95
Saturday Delivery (order before 2pm Friday) - £9.95
Worldwide Delivery
We deliver Worldwide. International delivery varies in price by destination and size of product. For an accurate price please add your product to the cart and a price will be shown at checkout.
If our couriers cannot deliver the item because no-one is home to receive the order, they will leave a card, and attempt delivery on another two occasions. After this point, you will need to call your local depot to arrange a more convenient delivery date. If the courier receives no contact from you after a period of approximately 5 working days, they will return the package to us. This may result in extra shipping costs being incurred for redelivery.
Please note: compensation can NOT be offered in any circumstance if a delivery has not arrived on time, and it can NOT be offered for any persons who have taken the day off work in order to receive the item.
We advise that customers who foresee difficulty in obtaining their item at a home address should state a different delivery address at checkout. If a delivery address needs to be changed after the checkout procedure, please call us and we will get this changed for you, however this may affect the speed of delivery.
Dispatch schedule:
Our Next Day Delivery Service
Orders placed before 2pm Monday-Friday will be sent out same day, for next day delivery.
Orders placed after 2pm or on a non working day, will be sent out next working day for delivery the day after
Please make allowances for Christmas, Bank Holidays etc.
Delivery Addresses:
Due to the fact we do not offer Sunday or Bank holiday delivery options, it is essential you use a delivery address where there will be someone to take delivery of the item as in most cases a signature is normally required upon receipt. They will not normally telephone our customers prior to departure. All deliveries take place Monday to Friday between 9.00am - 6.00pm. They will not leave deliveries in the shed/porch/back garden, unless the instructions have been pre arranged through Watching Clocks. When you go through the checkout there is an option for you to add comments about delivery. If you are at work most of the time we would advise you have the goods delivered to your place of work or perhaps a neighbour or friend would take deliveries on your behalf.


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Water Well Service Byrdstown TN
Byrdstown Water Well Service Company provides water well services in Byrdstown, TN and Pickett County. From start to finish, our Byrdstown technicians deliver reliable well water services that supply you with a reliable water.
Byrdstown Water Well Services
Byrdstown Water Well Service Company installs reliable residential well water pumps through out Pickett County. Byrdstown Water Well Service Company is an experienced water well service businesses in Byrdstown Tennessee.
You can rely on the Byrdstown Water Well Service Co. for well water services and water well pumps that are meant for everyday use.
Water Well Pump Repair and Pump Installs
Once we have installed a water well or underground storage tank, our Byrdstown well residential water service providers can provide additional repairs. We would love the opportunity to give you a free estimate on your water well installation or well pump repair of your system.
Water Filtration System & Commercial Water Testing / Treatment
Byrdstown Commercial Water Treatment can design and install and repair your well water pumping system. Speak to one of our Byrdstown Filtration System professionals to get a free water test.
Byrdstown Water Well Service services commercial water filtration systems to our industrial customers throughout Byrdstown and surrounding cities in Pickett County.
Byrdstown Water Well Drilling and Installation
We have the knowledge and experience to drill and install your entire water well system. Our Byrdstown TN team provides both commercial and residential well drilling services. That's why we offer professional well drilling and well pump repair services.
Byrdstown Water Well Service will ensure that your water source is working properly, efficiently and safely whenever you need it most. Regardless if you need a well drilled for your home, farm, or business, we can help get you the water you need! You can rest assured, our professionals will get your project done right!
Voted Best Well Driller Company in Byrdstown
Drilling a water well is not a job that any person should do without proper training, experience, and certification. Our Professionals drill and put in reliable wells throughout Byrdstown, TN.
Once we have drilled and installed your well, our Byrdstown well water technicians will handle any additional repairs if needed. Tennessee Well Services is the business to call for wells that are meant for everyday use.
If you live in Byrdstown, you may benefit from having a well drilled. This will let you use water without paying a water bill, like the kind you would have if you lived in a city.
We strive to provide affordable drilling, well pump replacement, and well pump repair services in Byrdstown and Pickett County.
Call us today to speak with a licensed Byrdstown Water Well Service professional.


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Flowchart illustrating the literature search and exclusion process. BMI indicates body mass index.
Figure 2. Forest plot of all studies describing baseline obesity (body mass index [BMI] [calculated as weight in kilograms divided by height in meters squared] ≥30) and overweight (BMI 25-29.99) with depression (D) during follow-up. Favors A = negative association between BMI and depression. Favors B = positive association between BMI and depression. OR indicates odds ratio; CI, confidence interval.
Figure 3. Forest plot of all studies describing baseline depression (D) as a predictor of developing obesity (body mass index [BMI] [calculated as weight in kilograms divided by height in meters squared] ≥30) and overweight (BMI 25-29.99) during follow-up. Favors A = negative association between depression and BMI. Favors B = positive association between depression and BMI. OR indicates odds ratio; CI, confidence interval.
Customize your JAMA Network experience by selecting one or more topics from the list below.
Luppino FS, de Wit LM, Bouvy PF, et al. Overweight, Obesity, and Depression: A Systematic Review and Meta-analysis of Longitudinal Studies. Arch Gen Psychiatry. 2010;67(3):220–229. doi:10.1001/archgenpsychiatry.2010.2
© 2023
Association between obesity and depression has repeatedly been established. For treatment and prevention purposes, it is important to acquire more insight into their longitudinal interaction.
To conduct a systematic review and meta-analysis on the longitudinal relationship between depression, overweight, and obesity and to identify possible influencing factors.
Data Sources
Studies were found using PubMed, PsycINFO, and EMBASE databases and selected on several criteria.
Study Selection
Studies examining the longitudinal bidirectional relation between depression and overweight (body mass index 25-29.99) or obesity (body mass index ≥30) were selected.
Data Extraction
Unadjusted and adjusted odds ratios (ORs) were extracted or provided by the authors.
Data Synthesis
Overall, unadjusted ORs were calculated and subgroup analyses were performed for the 15 included studies (N = 58 745) to estimate the effect of possible moderators (sex, age, depression severity). Obesity at baseline increased the risk of onset of depression at follow-up (unadjusted OR, 1.55; 95% confidence interval [CI], 1.22-1.98; P < .001). This association was more pronounced among Americans than among Europeans (P = .05) and for depressive disorder than for depressive symptoms (P = .05). Overweight increased the risk of onset of depression at follow-up (unadjusted OR, 1.27; 95% CI, 1.07-1.51; P < .01). This association was statistically significant among adults (aged 20-59 years and ≥60 years) but not among younger persons (aged <20 years). Baseline depression (symptoms and disorder) was not predictive of overweight over time. However, depression increased the odds for developing obesity (OR, 1.58; 95% CI, 1.33-1.87; P < .001). Subgroup analyses did not reveal specific moderators of the association.
This meta-analysis confirms a reciprocal link between depression and obesity. Obesity was found to increase the risk of depression, most pronounced among Americans and for clinically diagnosed depression. In addition, depression was found to be predictive of developing obesity.
Both depression and obesity are widely spread problems with major public health implications.1,2 Because of the high prevalence of both depression and obesity, and the fact that they both carry an increased risk for cardiovascular disease,3,4 a potential association between depression and obesity has been presumed and repeatedly been examined. Such an association has been confirmed at the cross-sectional level.5-7 A recent systematic review8 examined primarily cross-sectional studies showing a weak association between obesity and depression, though significance tests were not performed. In addition, a recent meta-analysis9 of 17 community-based cross-sectional studies among adults showed a positive overall association between depression and obesity (defined as a body mass index [BMI] [calculated as weight in kilograms divided by height in meters squared] ≥30 or a waist-hip ratio ≥102 cm for men and ≥88 for women). de Wit et al9 found an overall odds ratio (OR) of 1.18, confirming that depression is associated with an 18% increased risk of being obese. Only sex acted as a moderating factor; in subgroup analyses the association was found in women but not in men, whereas age and continent of residence did not affect the association.
Although cross-sectional evidence is informative, it does not provide detailed insight into the exact mechanisms linking depression and obesity. It could be that depressed persons, through dysregulated stress systems10,11 or through unhealthy lifestyles, develop more obesity over time, whereas it is also possible that obesity, eg, through its negative effects on self-image or somatic consequences, results in the development of depression over time. Longitudinal studies are essential in providing more information on the direction of the association. With this information, prevention and intervention strategies could be improved. Although Atlantis and Baker8 did discuss some longitudinal studies12-15 in their overview article, 3 of 4 studies were based on the same cohort and only described the effect of obesity on the development of depression. Several studies (among slightly younger samples) available at the time were not included,16-21 and since then a considerable number of longitudinal studies have been published,22-28 indicating that the volume of evidence on this topic has rapidly increased. Consequently, a meta-analysis that would examine the longitudinal, bidirectional evidence of the association between depression and obesity would be justified as well as needed. To explore a potential dose-response association, it is important to differentiate between overweight and obesity, since the latter is the more severe condition and most strongly associated with biological dysregulation and unfavorable health outcomes.29,30
The current meta-analysis summarizes available prospective cohort studies and examines whether depression is predictive of the development of overweight and obesity and, in turn, whether overweight and obesity are predictive of the development of depression. In addition, possible moderators will be identified by examining the consistency of the longitudinal associations in subgroups stratified by sex, age, follow-up duration, depression assessment, quality assessment, and continent of origin.
A systematic computerized literature search of PubMed, EMBASE, and PsycINFO databases was performed for studies published in English up to March 2008, combining the following key words and medical subject headings: depression, depressive disorder, depressive symptoms, major depression, metabolic syndrome, overweight, obesity, adiposity, body mass index, intra-abdominal fat, waist-hip ratio, and waist circumference. No limitations in the search strategy were inserted. References from all relevant literature were hand searched and used to identify additional relevant studies. Studies presenting solely cross-sectional analyses were excluded as were case reports, comments, letters, and reviews. Articles discussing subjects other than the direct relationship between unipolar depression and obesity in an adult population and articles examining a highly specific population (eg, pregnant women or a population with a specific somatic disease) were excluded. Articles with a follow-up period of less than 1 year, not expressing weight as BMI, or not specifying the way depression was assessed were also excluded. Studies were subdivided in 2 categories: studies assessing a clinical depression diagnosis and studies assessing depressive symptoms. This subdivision was made according to the outcome of the authors (if the authors presented the participants as having a depressive disorder, we put the article in the "diagnosis" category). In the case of different articles presenting data on the same cohort differing only in follow-up length, articles presenting data on the longest period were chosen. All relevant citations were screened by 2 of us (F.S.L. and P.F.B.) on the earlier-mentioned criteria.
For inclusion in the meta-analysis, effect sizes had to be expressed as ORs. If this was not the case, the published effect sizes were transformed into ORs. If transformation was not possible, the corresponding author of that particular article was contacted and asked to provide the ORs of the association of interest. For each analysis, only 1 effect size per included article was used. Because adjustments for confounders differed considerably through the selected studies, we decided to analyze primarily unadjusted data for homogeneity of results. Available or provided adjusted data were used for additional analyses.
The methodological quality of all included studies was assessed by 2 of us independently (F.S.L. and P.F.B.) using a 15-item checklist adapted from Kuijpers et al31 (eTable). Each item was indexed with a (+) score (= 1 point) or a (−) score (= 0 points). Objective measurements of height and weight assessments were included as quality criteria. An article was defined as "high quality" when it scored 60% or more of the maximal possible score, in this case, 9 points or more. The 60% cutoff is a commonly used cutoff point for quality assessments.31,32 Disagreements among reviewers were resolved in a consensus meeting.
Data management, transformation of effect sizes, and calculation of the pooled mean effect sizes were performed using Comprehensive Meta-analysis (CMA) version 2.0.33 Available data were divided into 2 directions: BMI categories as predictors of depression at follow-up or depression at baseline as a predictor of BMI categories at follow-up. The first comparison included data on initially nondepressed participants followed up and screened on depression at follow-up, although for 2 of the included studies, depression was not assessed at baseline.12,23 The latter comparison included only data on normal-weight individuals who were followed up for development of depression at follow-up. The analyses were conducted separately for obesity (BMI≥30) and overweight (BMI 25-29.99) categories to see whether there was a difference in effect size between overweight and obesity.
Since considerable heterogeneity was expected, all analyses were performed with a random-effects model. To assess heterogeneity between studies, Q-statistics were calculated. A statistically significant Q indicates a heterogeneous distribution of ORs between studies, meaning that systematic differences, possibly influencing the results, are present.34 In addition, the I2 was calculated to describe the percentages of total variation across studies caused by heterogeneity. A 0% value means no heterogeneity, and higher values represent an increase in heterogeneity. Generally, heterogeneity is categorized at 25% (low), 50% (moderate), and 75% (high).35
All presented results are based on the 15 included studies. To examine the possibility of publication bias, we first inspected the funnel plot, which plots a measure of study size (the standard error or precision) as a function of effect size. Visual inspection of a funnel plot provides an indication of publication bias when larger and smaller studies are nonsymmetrically distributed across the combined effect size.36 The presence of publication bias was further tested using the Egger method,37 which quantifies the bias captured by the funnel plot by regressing the standard normal deviation on precision defined as the inverse of the standard error.38 If publication bias was observed, the Duval and Tweedie trim and fill procedure39 was used to calculate an estimate of the effect size after considering publication bias (adjusted effect size). Possible outliers were visually identified and tested for their effect on the significance of the effect size.
To determine whether factors such as age or follow-up duration modified the depression-BMI association, subgroup analyses were performed. Sensitivity analyses were conducted to estimate the effect of sex, mean age at baseline (subdivided into 3 categories: <20 years; 20-59 years; and ≥60 years), length of follow-up (<10 years; ≥10 years), clinical diagnosis or depressive symptoms, quality of article (low, <60%; high, ≥60%), and continent of origin (American or European). For estimation of sex differences, the available adjusted ORs for women were compared with the adjusted ORs for men. We performed analyses only in subgroups containing 2 or more articles, though subgroups with 1 article are mentioned in the results (Table 1 and Table 2).
Combining the key words and medical subject headings in the literature search, 2937 articles were found (Figure 1). The first screening, designed to select possibly relevant articles according to the previously described criteria, left us with 80 articles for further evaluation. Most excluded articles had a cross-sectional design or discussed another subject, for example, the association between lower urinary tract symptoms and depressive symptoms.40 Bipolar disorder was another relatively frequent reason for exclusion. The remaining 80 articles were examined in more detail, and 62 were excluded for the reasons shown in Figure 1. One of the excluded articles13 discussed the same cohort as one of the included articles,15 but with a shorter follow-up period. This excluded article, however, showed similar findings as the included article from that cohort. Consequently, 18 studies remained for inclusion in the meta-analysis. For most studies, the data could not be immediately used in the meta-analysis. In these cases, authors were contacted and asked to provide the ORs of the association of our interest. For 3 studies, we did not receive this information and these studies could not be included.41-43 Of the remaining 15 studies to be included, 1 author provided crude data26 and all others provided data expressed as ORs. Because some studies were still ongoing after publication, some authors provided the most recent results,16,21,26 which were used for analyses.
In the 15 studies included in the meta-analysis,12,13,16-28 all data on obesity and overweight were expressed in terms of BMI. Overweight was defined as BMI between 25 and 29.99 and obesity, as BMI of 30 or more, according to the World Health Organization definition.38,44 For examination of the link between overweight/obesity at baseline and development of depression at follow-up, the total number of subjects was 55 387. For the inverse relationship, the number of subjects was 7196 (Table 3). In 7 studies, a structured diagnostic interview was used, leading to a diagnosis of depressive disorder. Four studies did not specify who conducted the interview15,16,21,22; in 1, the interview was done by a resident in psychiatry or a psychologist18; and in 2 studies,19,20 the psychiatric interview was conducted by a trained interviewer. Eight studies assessed depression by a depressive symptom questionnaire. Three of the selected articles presented longitudinal data on both directions14,25,27; 5, on overweight/obesity exposure and depression at follow-up; and 7, on the inverse association. With the exception of the studies of Bjerkeset et al23 and Herva et al12 (where baseline depression assessments were not performed), all studies on baseline BMI predicting subsequent depression excluded depressed individuals at baseline. Among studies on baseline depression and BMI at follow-up, all studies examined normal-weight individuals at baseline. According to our quality criteria, we found 4 articles to be of high quality (≥9 points), 1 of which25 analyzed data in both directions and is therefore mentioned twice. The Bjerkeset et al study23 counts an exceptionally high number of participants and is responsible for the large sample size in the overall group. Because in this study, as well as in the Herva et al study,12 baseline depression assessments were not performed, we repeated the overall analyses after removal of these studies, both together and separately.
Table 1 presents the findings of overall and subgroup analyses for obesity exposure on depression. The pooled OR for the association between obesity at baseline and depression at follow-up for the 8 studies in this group was 1.55, with a 95% confidence interval (CI) of 1.22 to 1.98 and a P value of <.001 (Table 1) (Figure 2). The pooled adjusted OR was very similar (OR, 1.57; 95% CI, 1.23-2.01). Heterogeneity between studies was not significant (Q = 11.32; P = .13), suggesting that there were no severe systematic differences between the ORs of the selected studies. The percentage of total variation across these studies caused by heterogeneity was small to moderate (I2 = 38%). Only 1 apparent outlier was found in the generated funnel plot.25 Removing this study and repeating the analysis led to a slight decrease in heterogeneity (Q = 7.45; P = .28; I2 = 20%) and a slight increase in effect size outcome (OR, 1.66; 95% CI, 1.35-2.05), confirming the observed lack of heterogeneity. Overall ORs were still significant after removal of the studies of Bjerkeset et al23 and Herva et al12 (OR, 1.56; 95% CI, 1.02-2.40). The Egger test37 and Duval and Tweedie trim and fill procedure39 showed no significant risk of publication bias (Egger test intercept = 0.39; SE = 1.18; P = .38; Duvall and Tweedie adjusted OR = 1.51; 95% CI, 1.17-1.95; number of imputed studies = 1).
Subgroup analyses showed significant differences for continent of residence and depression severity (ie, depressive symptoms or a clinical diagnosis depression). The ORs between American and European studies differed significantly (P = .05), indicating that the overall association found was stronger among Americans. Significant difference was also found between the ORs for depression outcome as a clinical diagnosis and as depressive symptoms (P = .05). This indicates that the effect of the overall association is stronger when depression was assessed by means of a diagnostic clinical interview rather than a self-report symptom list.
Analyses on overweight exposure (Table 1) (Figure 2) resulted in a pooled OR of 1.27 (95% CI, 1.07-1.51; P < .01). Heterogeneity was low (Q = 6.94; P = .33; I2 = 14%) and no outliers were identified. Although still significant, the adjusted pooled OR was considerably lower (OR, 1.08; 95% CI, 1.02-1.14). After removing the studies of Bjerkeset et al and Herva et al, the OR was 1.14 (95% CI, 0.83-1.55).
Subgroup analyses showed that baseline overweight was associated with depression in subjects 20 years or older, but not in younger individuals. The difference between these age groups showed a trend (P = .07). Based on the Egger test and the Duval and Tweedie trim and fill procedure, there was no indication of publication bias (Egger test intercept = 0.47; SE = 1.15; P = .35; Duvall and Tweedie adjusted OR = 1.16; 95% CI, 0.98-1.37; number of imputed studies = 2).
Table 2 presents the findings for overall and subgroup analyses of depression exposure and obesity. The pooled OR of the 9 studies examining the effect of depression on obesity over time was 1.58 (95% CI, 1.33-1.87; P < .001) (Table 2) (Figure 3). The pooled adjusted OR was slightly lower (OR, 1.40; 95% CI, 1.15-1.71). The heterogeneity was zero (Q = 4.43; P = .82; I2 = 0%), and no outliers were identified.
Subgroup analyses did not show any significant differences between subgroups. The publication bias tests indicated a trend and the estimated number of imputed studies was 5 (Egger test intercept = 1.71; SE = 1.03; P = .07; Duvall and Tweedie adjusted OR = 1.13; 95% CI, 0.90-1.41).
The pooled OR for depression exposure on overweight was 1.20 (95% CI, 0.87-1.66; P = .26) (Table 2) (Figure 3). Removing the outlier18 did not change the results. Performing subgroup analyses, a significant association was found with regard to the follow-up duration, indicating that an association is present when subjects are exposed to depression for a longer period (ie, follow-up ≥10 years). Other subgroup analyses did not show significant differences but demonstrated a trend for the continent of origin (P = .07). Again, we found a trend for the possibility of publication bias (Egger test intercept = 2.07; SE = 1.24; P = .08; Duvall and Tweedie adjusted OR, 0.98; 95% CI, 0.75-1.27; number of imputed studies = 3).
To our knowledge, this is the first meta-analysis examining longitudinally whether overweight and obesity increase the risk of developing depression and whether depression increases the risk of developing overweight and obesity. We found bidirectional associations between depression and obesity: obese persons had a 55% increased risk of developing depression over time, whereas depressed persons had a 58% increased risk of becoming obese. The association between depression and obesity was stronger than the association between depression and overweight, which reflects a dose-response gradient.
Our longitudinal results provided additional, innovative insights into the already established cross-sectional association between depression and obesity. Interestingly, the results of our longitudinal meta-analysis found a larger pooled effect size (ORs between 1.20 and 1.58) than the pooled OR of 1.18 reported in the cross-sectional meta-analysis of de Wit et al.9 Possibly time plays a role in the association between depression and obesity. The unfavorable effect of depression on development of obesity and the effect of obesity on development of depression may be reinforced by time. The earlier-described cross-sectional association was only present in women. However, our longitudinal meta-analysis confirms a reciprocal association between obesity and depression in both men and women.
Although evidence of a biological link between overweight, obesity, and depression remains complex and not definitive,8,10,11,45 it seems relevant to highlight the most current lines of reasoning within the possibility of a biological pathway. First, we will discuss the direction of obesity exposure on depression outcome. Obesity can be seen as an inflammatory state, as weight gain has been shown to activate inflammatory pathways46,47 and inflammation in turn has been associated with depression,48-50 which in these studies was assessed by means of a depressive symptom report. Because inflammation plays a role in both obesity and depression, inflammation could be the mediator of the association. Also, the hypothalamic-pituitary-adrenal axis (HPA axis) might play a role, because obesity might involve HPA-axis dysregulation51,52 and HPA-axis dysregulation is well known to be involved in depression.53,54 Through HPA-axis dysregulation, obesity might cause development of depression. Finally, obesity involves increased risks of diabetes mellitus and increased insulin resistance,55 which could induce alterations in the brain56 and increase the risk of depression.57 In addition to biological mechanisms, psychological pathways should be mentioned. Being overweight and the perception of overweight increases psychological distress.58,59 In both the United States and Europe, thinness is considered a beauty ideal, and partly because of social acceptance and sociocultural factors, obesity may increase body dissatisfaction and decrease self-esteem, which are risk factors for depression.60 Disturbed eating patterns and eating disorders, as well as experiencing physical pain as a direct consequence of obesity, are also known to increase the risk of depression.61,62
In our subanalysis, the effect of obesity on the development of depression was found to be stronger in American studies. Although it is not likely that biological mechanisms underlying the obesity and depression-onset risk are different across cultures, the sociocultural mechanisms could be different and more stringent in one culture than the other. In addition, because mean adult BMI is higher in the United States compared with different European countries,63 among the obese persons in the United States, the average BMI may be higher than among the obese persons in Europe, and consequently, the observed difference across continents could partly indicate a dose-response association. The association of baseline obesity was also more pronounced among subjects whose depression at follow-up was assessed by means of a clinical interview, rather than using a self-reporting questionnaire. This could be due to a higher preciseness of the depression outcome when confirmed by a psychiatric diagnosis, whereas depressive symptoms may be more often biased by confounding covariates. It also clearly indicates that obesity may really cause a clinically relevant and severe psychiatric outcome.
The fact that depression causes an increase of weight over time may also be caused by neuroendocrine disturbances. Björntorp64 argued that depression induces (abdominal) obesity through long-term activation of the HPA axis. Cortisol, in the presence of insulin, inhibits lipid-mobilizing enzymes, a process mediated by glucocorticoid receptors that are found in fat depots and especially in intra-abdominal visceral fat.65 Another important mechanism is the adoption of an unhealthy lifestyle, such as insufficient physical exercise and unhealthy dietary preferences, possibly leading to obesity. Finally, the use of antidepressants is known to possibly induce weight gain,10 though many of the included studies were community-based studies in which depressed subjects often did not undergo pharmacological treatment. In addition, the results of studies using a clinical diagnosis for depression, in which subjects were more likely to be treated with antidepressants, were not different from results of studies that used symptoms of depression.
This study had several limitations. First, the search was restricted to a computerized search for English-language literature. Nonetheless, we are not aware of missing non–English-written literature, as our literature search or hand search for references did not yield any empirical longitudinal studies in other languages. Second, unpublished literature was not included, possibly resulting in a slight increased risk of publication bias for the included studies on baseline depression. However, we feel we included the majority of available longitudinal articles, which was also confirmed by the Egger tests we performed that did not suggest selective publication bias. A third limitation is that although the total number of included subjects is substantial, the number of included articles is relatively small. Three articles could not be included because they did not include the appropriate available effect size: Anderson et al41 and Forman-Hoffman et al42 expressed weight outcomes in terms of weight change, and Franko et al43 presented obesity outcomes as a function of increase or decrease of depressive symptoms and depression outcomes as a function of weight loss and weight gain. However, the results of these excluded studies were comparable since they all supported evidence of a longitudinal link between depression and obesity, and consequently, exclusion did not likely impact the conclusion of our meta-analysis. Finally, we were not able to broadly adjust for potential covariates because it was only possible to analyze adjustments for age and sex. None of the included studies reported on factors such as family history, hormonal status, or the use of medication. Therefore, true effects and magnitude of possible predictors and covariates remain unknown because of the inability to examine an extensive range of conjectured factors.
Longitudinal epidemiological research is especially warranted to further establish the moderators and underlying mechanisms that link obesity to the onset of depression and depression to the onset of obesity. Additionally, these studies should examine more clearly the potential roles of, for example, depression characteristics (eg, atypical vs melancholic features), medication use, physical activity, or dietary patterns.
Despite these limitations, the available data sufficiently lead to the conclusion that depression and obesity interact reciprocally. The results were statistically highly significant and heterogeneity turned out to be low according to statistical guidelines.35
Our findings of a longitudinal, bidirectional association between depression and obesity are important for clinical practice. Because weight gain appears to be a late consequence of depression, care providers should be aware that within depressive patients weight should be monitored. In overweight or obese patients, mood should be monitored. This awareness could lead to prevention, early detection, and cotreatment for the ones at risk, which could ultimately reduce the burden of both conditions. We sincerely hope this work inspires future research to clarify how 2 major health problems interact, thus improving prevention and treatment strategies.
Correspondence: Floriana S. Luppino, MD, Department of Psychiatry, Leiden University Medical Center, Albinusdreef 2, 2333 ZA Leiden, the Netherlands (firstname.lastname@example.com).
Submitted for Publication: February 23, 2009; final revision received June 15, 2009; accepted June 19, 2009.
Author Contributions: Dr Luppino had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Financial Disclosure: None reported.
Additional Information: This study was voluntarily supported by the contributing authors who made their data available.


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Mount Gambier Men's Shed
So what's so special about this new type of Men's Shed?
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Illinois Wildernesses Map
Map Information
Created By: wilderness.webmaster
Page Last Updated: March 4th, 2011 3:03pm
Map Coverage:
North: 37.6273°
West: 89.4389° East: 88.3653°
South: 37.4977°
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State: Illinois
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IntroductionThis transparent map will allow you to add a layer to your GPS unit showing the boundaries of wilderness areas in Illinois. Use the map to see your position relative to wilderness boundaries in the field. You can use this map in conjunction with other maps, such as topo maps, you may have on your GPS unit already.
PC Version
- Clicking on the link above downloads and runs the installer (.exe), which unzips the appropriate files to your computer and registers them with MapSource.
MAC Version
- Clicking on the link above downloads a zip file (.zip). Unpack this zip file using Stuffit Expander (or something similar), then double-click the .gmapi file. MapManager should launch and a window should open up that says "Install these maps?". Click the install button and the map will be installed into Basecamp.
Version and UpdatesThe map version date is displayed on the initial installation screen. Maps are updated whenever new wilderness areas are added to the National Wilderness Preservation System or when older boundaries are revised. Follow us on Twitter to make sure you receive announcements about updated maps. To update to the current version of this map, uninstall the older version (use the "Uninstall" utility in the folder where you installed the maps the first time) before downloading and installing the current version from the links provided.
Data SourceThe data used to compile this map comes from the federal wilderness management agencies (Bureau of Land Management, Fish and Wildlife Service, Forest Service, and National Park Service) and is maintained by the University of Montana's Wilderness Institute through http://www.wilderness.net.
Contact InformationPlease contact Lisa Eidson, Wilderness Information Specialist and Webmaster for Wilderness.net, with any questions or concerns: [email protected], 406-243-6933 (office), 406-396-3607 (cell).
Visit Illinois Wildernesses To Download.
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Matomo database will be upgraded from version 4.11.0 to the new version 4.14.1.
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|Hlavná stránka > CERN Experiments > PS Experiments > n_TOF > n_TOF Internal Notes
These collections contains nTOF related documents.
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Academics — What Sets Us Apart
Academic Philosophy
Phoenix Academy is dedicated to developing students through rigorous instruction that empowers them to become their very best. We believe every student can succeed given the right balance of challenge and support, coupled with personalized instruction and experiential learning. Our well-rounded curriculum incorporates college-prep academics and a focus on moral character, preparing students for a lifetime of educational and personal success.
Grades We Teach
English Language Arts
English Language Arts
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We focus on integrating ELA skills and proficiency by infusing informational, nonfiction literature with other subjects including math, science, and social studies. Research shows that incorporating ELA into other subjects helps to close learning gaps by providing essential background knowledge, especially for upper elementary and middle school.
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Our model for achieving student success begins with the way we structure classroom instruction. The NHA approach includes a blend of one-on-one teaching, small group instruction, and time for independent practice. Our teachers invest time identifying each student's unique needs so they can specifically tailor plans, set goals, and meet their needs. This framework creates smaller learning environments within the classroom, and ensures students are properly supported to meet their individual learning goals. This also allows teachers to track progress and adjust instruction to ensure each child's success.Apply for Your Child Today
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Math Stories is our customized, proprietary 30-minute daily routine integrated into the daily math block. The teacher facilitates the framework as students unpack one math problem per day by: 1) engaging through visuals, 2) making sense of the problem, 3) discussing the problem, 4) connecting key points, 5) practicing methods to solve.
Problem Solvers Are Forged in the Classroom
Math is visual, interactive, and experiential at Phoenix Academy. We understand that learning begins with regular exposure and interaction with math beyond the textbook. Students learn by doing math and talking about how it's integrated into our daily lives. We emphasize depth and critical thinking over speed. Our teachers act as facilitators and allow students to explore math problems on their own terms.
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Our custom mathematics curriculum was designed to enable every child to succeed. It is both accessible and stringent. We believe all students can achieve at a high level in math if you provide solutions to remove the frustrations associated with it. Our process teaches students to solve problems, move beyond their mistakes and find a productive relationship with struggle. A student can solve any problem if they can count and make sense of the problem.
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Experience it. Instead of a teacher immediately demonstrating how to solve a math problem, students use concepts they know to become familiar with the problem.
Talk about it. Next the teacher facilitates discussion around the skills and ideas developed by the students while working on the problem.
Name it. At the end of the lesson, the teacher explains the problem building on the language students shared, explicitly naming the key points of the exercise for that day.
Problem Solvers
Our curriculum demonstrates math can be done in a variety of ways. Students develop the ability to think critically, reason, and employ different strategies to solve problems. Our teachers pose purposeful questions, and the students are asked to provide evidence of their thinking. Ultimately, students are precise, demonstrate sound reasoning, navigate challenges, and persevere in solving them.
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We base science instruction on the 5E model (Engage, Explore, Explain, Elaborate, and Evaluate) which provides students with concrete, hands-on opportunities to learn about new ideas. Our students use various modalities to help support their understanding and application of key science and engineering concepts and skills.
Social Studies
In addition to learning important historical and cultural facts, we use social studies to build critical thinking and practical problem solving skills so our students become engaged citizens. Social studies also helps to provide a platform for teachers to integrate other content areas such as moral focus, reading, and writing.


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The Citizen Watch Company of Japan was founded in 1930 and since then, its record of achievement is distinguished by many firsts, such as the world's first analogue watch, accurate to within 3 seconds per year, and the world's thinnest movement. In 1986 Citizen assumed the No 1 position in world watch production and has remained there ever since. Today Citizen is successful in many areas of 'non-watch' business – information equipment, electronic equipment, industrial machinery and equipment, jewellery and spectacles – and its Research and Development facilities are second-to-none, resulting in the development of technology that leads quickly to new products.
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We don't currently have any available Trumpet teachers in Kansas City
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