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Tama

Phone
+16695775590
Scheduled Time
Sep 29, 2025 10:07 PM PDT
Timezone
America/Los_Angeles
Status
completed
Call Type
daily_analysis_update
Created
Sep 29, 2025 09:57 PM PDT
Data Analysis Period
Sep 27, 05:00 PM to Sep 29, 09:57 PM (America/Los_Angeles)

Call Timing Context

Call Time Label
Evening
Is Morning
False
Is Mid-day
False
Current Hour
21

Summary

Evening Summary Call: Today’s review covers three days of data from 2025-09-28 to 2025-09-30. Your activity on 09-28 and 09-29 was excellent with high step counts and solid workout sessions, though today's activity data is missing—ensure your device syncs properly. Glucose on 09-29 was well-controlled with an average of 102 mg/dL, but more consistent tracking across days is needed. Nutrition remains strong with a balanced macronutrient profile; however, watch out for high GI treats. Sleep quality was good on recorded days, though 09-30 data is absent. Stress data appears incomplete and could benefit from subjective logging. Overall, you’re having an excellent day with strong scores in nutrition and sleep. For tomorrow, consider a light evening walk to boost activity. Tip: Regular device checks can help avoid missing data.

Activity Analysis

Highlights

  • On 2025-09-28, you achieved an excellent 14,981 steps with a 50-minute workout and a perfect score of 100.
  • 2025-09-29 also showed strong performance with 10,764 steps and a consistent workout session scoring 100.
  • Today's data (2025-09-30) shows 0 steps and no workout recorded, indicating a gap that may be due to incomplete tracking.

Recommendations

  • Ensure your device is properly synced to capture today's activity data.
  • Aim for at least 7,500 steps daily; if data is missing, consider taking a light evening walk.
  • Review device settings to avoid missing workouts in future recordings.

Detailed Notes

  • Workout heart rate readings on previous days were consistently within a healthy range.
  • Total calories burned on 2025-09-28 and 2025-09-29 were high, indicating active days.
  • Both days achieved a top score of 100 for activity.
  • Zero data for 2025-09-30 suggests a technical or logging gap.
  • Regular activity monitoring supports better glucose management and overall fitness.

Glucose Analysis

Highlights

  • The only available glucose data from 2025-09-29 shows an average glucose of 102 mg/dL.
  • A GMI of 5.7 indicates very well-controlled blood sugar levels.
  • Despite TIR reported as 0, the TITR value of 100 suggests a data labeling discrepancy.

Recommendations

  • Record glucose consistently across all days to better assess trends.
  • Clarify TIR metrics on your device to ensure accurate tracking of time within range.
  • Keep monitoring post-meal spikes, especially after high GI treats.

Detailed Notes

  • Only one day (2025-09-29) of glucose data limits trend analysis.
  • The average glucose of 102 mg/dL is within an excellent range.
  • GMI at 5.7 further supports good glycemic control.
  • No hypoglycemia or hyperglycemia events were noted.
  • Data inconsistency between TIR (0) and TITR (100) should be addressed.

Nutrition Analysis

Highlights

  • Nutrition data shows an excellent average score of 91.
  • Macronutrient distribution is balanced with 33% protein, 42% carbs, and 25% fat.
  • High glycemic foods like Chocolate Chip Cookie and Macadamia White Chocolate Cookie were noted on specific days.

Recommendations

  • Reduce the frequency of high GI foods to help maintain stable glucose levels.
  • Aim for consistent meal logging to capture complete nutritional data.
  • Monitor portion sizes and meal timing for even energy distribution.

Detailed Notes

  • Data from 2025-09-28 and 2025-09-29 shows daily calories of 1515 and 844 respectively.
  • Meal logs detail a mix of Breakfast, Lunch, Dinner, and Snacks with varying calorie contributions.
  • Carbohydrates recorded were 113g on one day and 75g on another.
  • Most foods logged are low glycemic (over 90%), which is positive.
  • High glycemic items, though few, might impact post-meal glucose if consumed frequently.

Sleep Analysis

Highlights

  • Sleep scores on 2025-09-28 (89) and 2025-09-29 (91) demonstrate good sleep quality.
  • Light sleep durations were robust, recording 4.45 and 4.87 hours, respectively.
  • REM sleep was consistently around 1.65 to 1.76 hours, indicating balanced sleep phases.

Recommendations

  • Ensure a consistent sleep tracking routine by verifying your device is worn through the night.
  • Aim to extend deep sleep duration, as 0.88 to 1.43 hours may be on the lower side.
  • Develop a pre-bedtime routine to potentially reduce wake periods during sleep.

Detailed Notes

  • 2025-09-28 showed 1.43 hours of deep sleep versus 0.88 hours on 2025-09-29.
  • Awake time was low on 2025-09-28 (0.49 hr) but increased to 1.47 hr on 2025-09-29.
  • Consistent sleep quality scores indicate healthy sleep architecture on recorded days.
  • Missing sleep data on 2025-09-30 suggests incomplete tracking for today.
  • Overall, variability in sleep phases warrants slight adjustments for optimal restorative sleep.

Stress Analysis

Highlights

  • Stress data consistently shows a strain score of 0 across all days.
  • Recovery scores are also 0 for all days, indicating a lack of recorded stress metrics.
  • The absence of stress fluctuations may suggest either very low stress or a gap in data capture.

Recommendations

  • Consider recording subjective stress levels daily to better track stress patterns.
  • Integrate relaxation or mindfulness practices into your routine.
  • Explore using wearable stress tracking features to capture recovery metrics.

Detailed Notes

  • No variation in strain scores (0) was observed over the period.
  • Recovery scores being 0 across days hints at a potential data capture issue.
  • Lack of stress data makes it hard to assess daily stress fluctuations.
  • Adding manual stress logs could provide richer insights into daily recovery.
  • Monitoring stress is important as it can influence both sleep and glucose management.

Call Logs & Conversation

AI Call Summary

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Call Logs

  • Hey Tama, it's great to connect. I'm Mira from Heald, and I'd love to share some insights from your health data when you're ready.

Agent Conversation (text)

Hey Tama, it's great to connect. I'm Mira from Heald, and I'd love to share some insights from your health data when you're ready.