Feature Request: Alcohol Tracking + Apple Health Integration

[blackaurion]

I did some searching for this already, and didn't find much in the repo. I’d love to see SparkyFitness expand into alcohol tracking as a first-class feature, especially with deeper integration into Apple Health.

Current Gap

Right now, it’s possible to manually add drinks (e.g., beer) into the database, but there’s no structured way to capture:

• ABV (% alcohol by volume)
• Volume consumed (oz/ml)
• Calculated grams of ethanol

Without those fields, alcohol intake ends up being “just another food item,” which misses a lot of meaningful physiological context.

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Proposed Features

1. Dedicated Alcohol Data Model

Introduce a specific “Alcohol” category with fields like:

• Drink type (beer, wine, spirits, custom)
• ABV (%)
• Volume (oz/ml)
• Auto-calculated grams of ethanol
• Optional: standard drinks conversion

This would allow consistent, comparable tracking across different beverages.

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2. Apple Health Integration

Sync alcohol consumption with Apple Health’s alcohol tracking metrics:

• Write: log drinks/ethanol intake to Apple Health
• Read: pull in existing alcohol consumption data from Apple Health

This creates a unified health record and allows correlation with:

• Sleep quality
• HRV
• Resting heart rate
• Recovery metrics

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3. Derived Metrics + Insights

Once ethanol is tracked properly, you could surface higher-level insights:

• Weekly/monthly alcohol trends
• Correlation with sleep/recovery/performance
• “Recovery cost” of drinking (e.g., HRV drop, sleep disruption)

Why This Matters

Alcohol has a measurable impact on recovery, sleep, and performance, but most fitness apps treat it as an afterthought. Bringing it into the same system as nutrition and activity would:

• Improve data accuracy
• Enable better personal insights
• Strengthen integration with existing health ecosystems

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Bonus Idea

If you ever expand into recommendations:

• Adaptive suggestions like “hydration boost recommended” or “expect reduced recovery tonight” based on intake

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This feels like a natural extension of what SparkyFitness already does well—turning raw inputs into meaningful feedback loops.