Apple Health data can now move between the Health app and Google Health on an iPhone. The connection lets Google Health import supported information recorded by an iPhone, Apple Watch, and compatible apps. The latest Google Health update can also send supported Fitbit information to Apple Health.

This two-way connection is useful for people who wear a Fitbit but prefer Apple’s Health app as the central place for viewing activity, sleep, steps, and other wellness information. It also reduces the need for third-party synchronization apps.

The feature requires a recent version of Google Health. Google began introducing support for sending data back to Apple Health with Google Health version 5.05. Because app updates can roll out gradually, the new sharing options may not appear until the latest version reaches your account.

Update Google Health Before Starting

The Fitbit app became Google Health in 2026. Existing Fitbit users should find that the installed app has changed its name and design after updating. Fitbit accounts must also be moved to an adult Google Account to use the redesigned service.

Google says the Apple Health connection requires iOS 16.4 or later. The iPhone must have internet access while the connection is being created.

To check the iOS version installed on your iPhone:

Settings > General > About > iOS Version

Install the latest compatible iOS update if the phone is running an older release.

To look for an available iPhone software update:

Settings > General > Software Update

Next, confirm that Google Health is current. Version 5.05 or later is required for the newer option that sends supported Google Health and Fitbit information to Apple Health.

To update Google Health from the App Store:

App Store > Profile Picture > Available Updates > Google Health > Update

If Google Health does not appear under Available Updates, search for the app manually. The App Store page may show an Update button if a newer release is available.

To find the app directly:

App Store > Search > Enter Google Health > Google Health (Fitbit)

People who previously used Fitbit should sign in with the Google Account connected to their Fitbit information. Creating a different account may produce an empty Google Health profile.

Connect Apple Health Data to Google Health

Connecting the apps allows Google Health to read supported information from Apple Health. This can include data collected by the iPhone, Apple Watch, and other apps that already share information with Apple Health.

To start the Apple Health connection:

Google Health > Connections > Apps and Services > Apple Health > Get Started

Depending on the Google Health version and interface shown on the iPhone, Connections may appear behind the profile icon.

To find Apple Health through the alternative menu:

Google Health > Profile Icon > Partner Apps > Apple Health

Google Health will display a consent screen explaining the connection. Read the information before continuing.

To approve the initial connection:

Sync Google Health With Apple Health > Agree

The iPhone will then display Apple’s health permission screen. This screen lets you decide which information Google Health can read.

To give Google Health access to every supported category:

Apple Health Permission Screen > Turn All Categories On > Allow

You do not have to share every available category. Selecting individual permissions provides more control over sensitive health information.

To share only selected categories:

Apple Health Permission Screen > Select Each Health Category > Allow

Google Health can import supported information such as steps, distance, active energy, exercise records, routes, sleep sessions, sleep stages, heart rate, resting heart rate, heart rate variability, blood oxygen, respiratory rate, body temperature, weight, body fat percentage, water, nutrition information, and some cycle-tracking data.

Available categories depend on the devices and apps connected to Apple Health. An iPhone may provide steps and walking information, while an Apple Watch can contribute heart rate, workouts, sleep, and other measurements supported by the model.

After the permissions are approved, Google Health should confirm that the connection is complete.

To finish the connection:

Google Health Confirmation Screen > Done

New Apple Health information should begin appearing automatically in Google Health. Google has said that imported data can be used across relevant Google Health metrics, although not every external data type is used for every calculation.

To find imported health information:

Google Health > Health > Select a Metric

Google Health may display information from several connected sources together. Its value for a metric can differ slightly from the number shown by Apple Health because the apps may process available data differently.

Send Fitbit Data to Apple Health

Google Health version 5.05 adds the reverse direction that many iPhone and Fitbit users previously lacked. Supported information recorded through Fitbit can now be written into Apple Health.

Before enabling this option, make sure the Fitbit is properly connected to Google Health. Fitbit devices normally synchronize automatically throughout the day when Bluetooth is available and the wearable is near the iPhone.

To check the connected Fitbit:

Google Health > Profile Icon > Devices > Select Your Fitbit

The device page should show the wearable, its battery level, and its most recent synchronization time. Opening Google Health can also prompt a nearby Fitbit to transfer recently collected information.

Once the wearable is updating Google Health correctly, open the Apple Health connection settings.

To open the sharing controls for Apple Health:

Google Health > Profile Icon > Partner Apps > Apple Health

The interface may use Apps and Services instead of Partner Apps on some versions.

To reach the same connection through Apps and Services:

Google Health > Connections > Apps and Services > Apple Health

Follow the prompts for sharing Google Health information with Apple Health. The iPhone may display separate permissions for data that Google Health can read and data that it can write.

To allow supported Fitbit information to appear in Apple Health:

Apple Health Permission Screen > Allow Google Health to Write > Select Health Categories > Allow

Google says supported information can include exercise records, steps, sleep, vitals, and other health data. The exact selection can vary according to the Fitbit model, region, Google Health version, and information stored in the account.

Selecting every category is convenient, but it can create overlapping sources when an iPhone, Apple Watch, and Fitbit record the same type of activity. Choose only the categories you want Google Health to add.

A person who uses a Fitbit mainly for sleep, for example, can allow sleep information while leaving steps disabled. Someone who wears a Fitbit instead of an Apple Watch may prefer to enable steps, workouts, heart rate, sleep, and other supported categories.

Check Google Health Permissions

Apple Health keeps permission controls on the iPhone. You can change them after the first connection without deleting either app.

To review Google Health access from Apple Health:

Health > Profile Picture > Privacy > Apps > Google Health

The page shows the categories Google Health is permitted to read or update. Turn off any category you no longer want to share.

Some iOS versions provide the same controls through the Sharing tab.

To find Google Health through the Sharing tab:

Health > Sharing > Apps and Services > Google Health

Turning off a permission stops future sharing for that category. It does not necessarily remove information that has already been written to Google Health or Apple Health.

The Google Health app also provides controls for the connection.

To review Apple Health inside Google Health:

Google Health > Connections > Apps and Services > Connected > Apple Health

If Google Health displays a message that new data types are available, open the connection and approve the additional categories you want to use. Newly supported information is not automatically shared without permission.

Manage Duplicate Health Information

An iPhone, Apple Watch, and Fitbit can record similar information at the same time. Apple Health keeps each source attached to its data and uses a priority order when presenting combined measurements.

You can inspect the sources contributing to a category and choose which one Apple Health should prefer.

To review the sources used for step information:

Health > Search > Activity > Steps > Data Sources and Access

The screen shows the apps and devices that provide step records. If Google Health, an Apple Watch, and the iPhone all appear, you can adjust their priority.

To change the order of step sources:

Health > Search > Activity > Steps > Data Sources and Access > Edit > Drag Sources Into the Preferred Order > Done

Move the source you trust most toward the top. Apple Health generally gives higher priority to sources placed above others when similar records overlap.

Repeat the same process for other categories if their totals do not look right. Exercise, sleep, active energy, and distance can each have their own sources and permissions.

Fix Missing or Delayed Data

Synchronization is not always immediate. A Fitbit first sends its information to Google Health, and Google Health then writes supported records to Apple Health. Bluetooth availability, Background App Refresh, internet access, and battery-saving behavior can affect this process.

Begin by opening Google Health with the Fitbit close to the iPhone. Wait for the device to complete its normal synchronization before checking Apple Health.

If Apple Health information is missing from Google Health, confirm that the connection remains active.

To check the connection status:

Google Health > Connections > Apps and Services > Apple Health

If Google Health displays an error or a request for new permissions, follow the message shown on the screen.

Background App Refresh can help Google Health update when the app is not open.

To allow Google Health to refresh in the background:

Settings > General > Background App Refresh > Google Health > On

Bluetooth must remain available for a Fitbit to communicate with the iPhone.

To confirm that Bluetooth is enabled:

Settings > Bluetooth > Bluetooth On

If the connection continues to fail, disconnecting and reconnecting Apple Health may restore the permission request.

To disconnect Apple Health from Google Health:

Google Health > Connections > Apps and Services > Apple Health > Disconnect > Confirm Disconnect

Disconnecting the service does not automatically remove every permission already stored by Apple Health. Review the Google Health entry in the Health app if you want to remove those permissions as well.

To remove the remaining Apple Health permissions:

Health > Profile Picture > Privacy > Apps > Google Health > Turn Off All

After reconnecting the apps, allow time for new records to appear. Previously stored information may not transfer in exactly the same way as activity recorded after the connection was enabled.

You can inspect an individual entry to confirm whether it came from Google Health, a Fitbit, an Apple Watch, or the iPhone.

To check the source and time of a synced record:

Health > Search > Select a Health Category > Show All Data > Select the Latest Entry

The post How to Sync Apple Health Data With Google Health on Your iPhone appeared first on AppleMagazine.

ChatGPT Health is returning with substantially wider access, giving more iPhone users the option to connect information from Apple Health directly to the AI assistant.

The expansion follows a limited test introduced in January. OpenAI is now gradually making the dedicated Health experience available to eligible ChatGPT Free, Go, Plus and Pro users in the United States who are at least 18 years old.

Despite the close Apple connection, this is not a feature created by Apple or built directly into the Health app. OpenAI operates the service through ChatGPT, while Apple Health serves as one of the sources users can voluntarily connect.

Once permission is granted, ChatGPT can examine selected health and fitness information stored on iPhone, including activity, sleep, workouts and other measurements collected by compatible apps and devices. Users can then ask questions about changes over time without manually exporting records or uploading screenshots during every conversation.

ChatGPT Health Reaches More iPhone Users

ChatGPT Health originally appeared as a limited early-access experience for a small group of testers. The expanded rollout replaces that narrow availability with support for eligible adult users across the United States, although OpenAI says access may take several weeks to reach every account.

The feature works on the ChatGPT website and iOS app, but connecting Apple Health requires an iPhone. Users also need a recent version of the ChatGPT app before the Health option appears in the sidebar or More menu.

Apple Health is only one part of the system. ChatGPT can also connect to supported medical-record portals, One Medical and Function Health. Bringing those sources together allows the assistant to answer questions using a broader personal context than activity data alone.

A user could ask how sleep duration has changed across several weeks, whether workout frequency declined after a schedule change or how recent laboratory results compare with earlier tests. ChatGPT can also help organize questions before a medical appointment or summarize changes found across connected records.

Information from third-party fitness services can reach ChatGPT through Apple Health when those apps already share their data with the iPhone database. That may include measurements from platforms such as Garmin, Oura, Whoop, Strava and MyFitnessPal, depending on which categories each service makes available.

Not every proprietary score transfers. An app may calculate its own readiness, recovery or sleep score without writing that exact result into Apple Health. ChatGPT can only use the information made available through the connected source and approved by the user.

After synchronization, health information can inform responses throughout ChatGPT rather than remaining limited to conversations opened from the Health tab. The assistant normally asks for permission before using connected information, and users can also add “@Health” to a prompt when they specifically want a response based on their records.

Apple Health Data Gains a Conversational Layer

The appeal of the integration comes from turning a large collection of measurements into questions expressed in ordinary language.

Apple Health can already organize trends, highlights, medications, laboratory results and activity records. ChatGPT adds a conversational layer capable of comparing those categories or explaining them in a more personalized format.

Someone preparing for an annual physical could ask for a summary of meaningful changes since the previous appointment. A runner might request a comparison between training volume, sleep and resting heart rate. Another user could ask which information deserves discussion with a clinician after receiving new laboratory results.

That does not make ChatGPT a doctor. OpenAI says the feature is intended to support medical care rather than diagnose conditions or recommend treatment. Urgent symptoms and emergencies still require professional assistance.

The distinction is especially important because health data can appear more conclusive than it is. A change in heart rate, sleep or activity may have several explanations that cannot be determined from an iPhone record alone. Wearables can identify patterns, but they do not automatically reveal the medical cause behind them.

ChatGPT may help users notice relationships and prepare better questions. It should not be treated as the final authority on whether a symptom is harmless, whether medication should change or whether professional care is unnecessary.

The service is also read-only. ChatGPT can examine approved Apple Health information but cannot alter the original records stored on iPhone. It cannot add a diagnosis, change a medication list or write new measurements back into the Health app.

Users retain control over which Apple Health categories are shared. Someone may allow access to steps, workouts and sleep while withholding reproductive health, medications or other sensitive information.

That selective approach may be more appropriate than approving every category simply because the option is available. A useful response does not always require a complete health history.

Privacy Becomes the Central Decision

Connecting Apple Health to ChatGPT creates a different privacy relationship from using health features entirely within the Apple ecosystem.

Apple designs the Health app around on-device protections and user-controlled permissions. ChatGPT Health requires selected information to synchronize with OpenAI systems so the company can analyze it and generate personalized responses.

OpenAI says connected Apple Health data, medical records and conversations using that information are not used to train its foundation models or target advertising. The company also applies additional encryption and isolation protections to health information.

Users can disconnect Apple Health at any time. OpenAI says synchronized data from the disconnected source will be deleted from its systems within 30 days.

Previous conversations are handled separately. Information already included in ChatGPT conversation history remains until those chats are deleted, even after the Apple Health connection is removed.

Memory introduces another consideration. Conversations using Health can create memories when ChatGPT memory is enabled, although OpenAI says memories are not generated directly from synchronized health data. Temporary Chat or separate project memory can reduce how much personal context continues across future conversations.

The new Health experience should also not be confused with the existing ChatGPT integration inside Apple Intelligence. Siri and Writing Tools can use ChatGPT for certain requests without requiring the dedicated ChatGPT app or a connected account.

ChatGPT Health is a separate OpenAI service with its own account, permissions, privacy controls and health-data connections. Using ChatGPT through Siri does not automatically give OpenAI access to Apple Health.

That separation gives users a meaningful choice. They can continue keeping health information inside Apple apps, share only selected categories with ChatGPT or connect medical records for a more comprehensive view.

The expanded rollout makes one of the most personal databases on iPhone available to conversational AI. Its usefulness will depend not only on the quality of the answers, but also on whether users understand exactly which information they are sharing and where it goes after leaving the device.

The post ChatGPT Health Expands Apple Health Access appeared first on AppleMagazine.

In a groundbreaking longitudinal study encompassing nearly half a million individuals, researchers have unveiled intricate patterns and biological underpinnings that link cardiometabolic diseases (CMDs) and depression. These two prevalent and often coexisting health conditions have long posed challenges due to their complex interaction and compounded risk on mortality. Now, through a multinational, multi-omic analytic approach, this study sheds new light on how these diseases develop, interlace over time, and ultimately impact life expectancy, offering hope for earlier detection and more precise interventions.

Cardiometabolic diseases—which include chronic conditions such as cardiovascular disease, type 2 diabetes, and metabolic syndrome—are among the leading causes of death globally. Depression, meanwhile, remains a colossal mental health burden, often running parallel to various physical ailments. The coexistence, or multimorbidity, of CMDs and depression exacerbates health outcomes significantly, yet the trajectory of how one condition progresses to include the other and the biological mechanisms driving this interaction have remained elusive.

Leveraging data from the UK Biobank, the largest population-based health cohort, the study followed 467,592 participants initially free of both CMD diagnoses and depression. Over a 14.6-year period, the scientists meticulously chronicled disease transitions using advanced multistate models. These allowed them not only to identify disease onset patterns but also to map complex pathways outlining progression from health to single disease states and then to multimorbidity.

The findings revealed that within the follow-up window, more than 64,000 participants developed CMD alone, while approximately 17,500 were diagnosed with depression exclusively. Crucially, over 6,100 individuals progressed to multimorbidity, reflecting the convergence of these conditions in a significant subset of the population. Importantly, the risk of subsequently developing the alternate condition was substantially elevated for those already affected by either CMD or depression, underscoring the bidirectional relationship between physical and mental health.

Further delving into survival outcomes, the researchers observed that individuals with multimorbidity faced a 13 to 22 percent increase in mortality risk compared to those free of disease, accompanied by a marked reduction in life expectancy averaging between 3.6 to 3.8 years. Such stark contrasts reinforce the clinical urgency of understanding and managing the intersection of CMDs and depression rather than treating them in isolation.

However, a nuanced discovery emerged from the survival analysis: the mortality impact of coexisting CMD and depression appeared additive rather than synergistic. This suggests that while coexistence heightens risk, the two diseases may operate through largely independent pathways driving mortality, a revelation that could recalibrate how treatment priorities are structured.

To decipher biological signatures predictive of disease progression and multimorbidity, the study incorporated multi-omics platforms—comprehensive analyses including proteomics, metabolomics, genomics, and methylomics. These high-dimensional tools allow scientists to detect subtle molecular changes reflecting pathophysiological shifts and prognostic biomarkers far earlier than clinical symptoms emerge.

Remarkably, proteomic models stood out in their predictive prowess. When applied to the 15-year risk horizon for CMD-depression transitions, these models achieved area-under-the-curve (AUC) values ranging between 0.70 and 0.91. This performance significantly eclipsed that of traditional clinical risk models, heralding a new dawn where molecular profiling could transform risk stratification and preventive strategies.

Distinct multi-omic signatures were identified at each disease transition point—whether from health to CMD alone, health to depression alone, or the combined pathway leading to multimorbidity. These signatures could reflect unique biological processes such as inflammatory cascades, metabolic dysregulation, neuroendocrine changes, or immune system perturbations, each contributing distinctively to disease progression.

The implications of these findings are far-reaching. With multimorbidity presenting as a growing global health challenge, understanding its trajectory and molecular footprints empowers clinicians and researchers to design targeted interventions that transcend symptom management. Early identification of individuals at highest risk via omic biomarkers could enable precision medicine approaches that pre-empt illness onset or halt progression.

Furthermore, by elucidating the distinct yet interconnected biological pathways linking CMDs and depression, this research challenges the traditionally siloed view of mental and physical health. It advocates for integrated care models that address the whole person rather than fragmented disease entities, a paradigm shift essential for improving patient outcomes in real-world settings.

The study also leverages rigorous multistate modeling, a sophisticated statistical technique allowing for dynamic representation of illness progression over time. This approach captures the complexity inherent in chronic disease trajectories, encompassing not only onset but transitions between disease states and eventual mortality. Such modeling enhances the granularity of epidemiological insights far beyond conventional methods.

As large-scale biobanks increasingly incorporate multi-omic data, the ability to unravel disease biology at unprecedented depth will only grow. The present study exemplifies how marrying big data with cutting-edge analytic frameworks can unveil novel insights into multimorbidity, transforming epidemiology into a powerful tool for precision health.

This research arrives at a critical juncture where global populations face rising burdens of chronic diseases intertwined with mental health challenges. Targeted, biologically informed strategies could ease the strain on healthcare systems and improve quality of life for millions living with overlapping disease burdens.

While promising, the findings also urge cautious optimism. The translation of molecular signatures into routine clinical tools requires further validation and contextualization across diverse ancestral and environmental backgrounds. However, these initial steps firmly establish a conceptual blueprint for future studies to build upon.

Taken together, this extensive investigation pioneers a new frontier in understanding the intertwined evolution of cardiometabolic diseases and depression. By uniting longitudinal clinical data with multi-omics analyses and sophisticated modeling, it heralds a transformative approach toward unraveling multimorbidity’s mysteries and paves the way for early, targeted prevention.

The convergence of CMDs and depression, previously viewed as a devastating clinical overlap, now emerges as a tractable problem awaiting targeted intervention—fueling hope that integrated molecular insights will soon translate into lifesaving real-world applications. This revolutionary research sets the stage for a future where vulnerability to complex chronic disease is revealed well before symptoms arise, opening unprecedented avenues for personalized health preservation.

Subject of Research:
Multi-omic signatures and disease trajectories linking cardiometabolic diseases and depression

Article Title:
Multi-omic signatures and trajectories of cardiometabolic diseases and depression

Article References:

Yang, G., Jiang, X., Wang, J. et al. Multi-omic signatures and trajectories of cardiometabolic diseases and depression.
Nat. Mental Health (2026). https://doi.org/10.1038/s44220-026-00678-6

Image Credits: AI Generated

DOI:
https://doi.org/10.1038/s44220-026-00678-6