Fix Healthspan activity and HealthKit steps

docs/production-incident-baseline.md

@@ -8827,6 +8827,43 @@ new incremental tables are populated.
   update; add freshness monitoring comparing latest sleep/heart-rate inputs to
   latest active RHR output date.
 
+### Healthspan activity and steps undercount
+
+- Date: 2026-05-26.
+- Symptoms: The Healthspan Score card showed `Aerobic Activity` as
+  `0 min/week` and `Daily Steps` around `1117 steps/day` despite the user
+  reporting regular activity and more walking than that.
+- User Impact: The Healthspan score penalized activity and steps using inputs
+  that did not match the user's actual recent behavior.
+- Evidence: Production `fitness.v_daily_metrics` averaged `1115` steps and
+  `16` exercise minutes over the 35-day Healthspan window. Recent
+  `fitness.daily_metrics` rows from Apple Health `HealthKit` showed many
+  overwritten low partial-day step totals, while the Healthspan aerobic query
+  used only HR/power-linked `analytics.activity_summary` activity data and
+  ignored device-reported `exercise_minutes`.
+- Root Cause: Incremental mobile HealthKit sync used `now - 24h` as the start
+  time for daily cumulative statistics, then upserted those partial-day
+  statistics over whole-day `fitness.daily_metrics` rows. Separately,
+  Healthspan treated missing HR/power-linked aerobic activity as zero instead
+  of using the device-reported full-day exercise minutes already stored in
+  `fitness.v_daily_metrics`.
+- Fix/Mitigation: Updated mobile HealthKit sync to start incremental sync
+  windows at the local calendar-day boundary, preventing future partial-day
+  overwrites. Updated Healthspan to use weekly device-reported exercise minutes
+  as the aerobic activity floor when HR-zone activity minutes are lower or
+  missing.
+- Validation: Added regression coverage for day-boundary HealthKit sync and
+  Healthspan exercise-minute fallback. Focused Healthspan unit tests, mobile
+  Vitest project, Biome checks, and TypeScript checks passed locally.
+- Remaining Risk: Existing corrupted historical Apple Health daily metric rows
+  remain in production until the iOS app runs a corrected manual/full HealthKit
+  sync from the user's device; the server cannot reconstruct those all-day
+  HealthKit totals without the device.
+- Follow-Up Work: After deploying the fix, run a full Apple Health sync from
+  the iOS app to repair historical daily step and exercise-minute rows. Consider
+  adding a server-side diagnostic for suspicious step drops after partial
+  HealthKit sync windows.
+
 ### Resting heart rate sleep-sample join null handling
 
 - Date: 2026-05-26.

packages/mobile/lib/health-kit-sync.test.ts

@@ -118,6 +118,29 @@ describe("syncHealthKitToServer", () => {
     expect(startDate.getFullYear()).toBeLessThanOrEqual(1970);
   });
 
+  it("starts incremental daily statistics at the local day boundary", async () => {
+    vi.useFakeTimers();
+    vi.setSystemTime(new Date("2026-05-26T15:30:00-07:00"));
+    const client = createMockClient();
+    const healthKit = createMockHealthKit();
+    const expectedStartDate = new Date();
+    expectedStartDate.setDate(expectedStartDate.getDate() - 1);
+    expectedStartDate.setHours(0, 0, 0, 0);
+
+    try {
+      await syncHealthKitToServer({
+        trpcClient: client,
+        healthKit,
+        syncRangeDays: 1,
+      });
+    } finally {
+      vi.useRealTimers();
+    }
+
+    const firstCall = healthKit.queryDailyStatistics.mock.calls[0];
+    expect(firstCall[1]).toBe(expectedStartDate.toISOString());
+  });
+
   it("batches large sample sets into groups of 500", async () => {
     const client = createMockClient();
     const healthKit = createMockHealthKit();

packages/mobile/lib/health-kit-sync.ts

@@ -36,10 +36,15 @@ const ALL_QUANTITY_TYPES = [...ADDITIVE_QUANTITY_TYPES, ...NON_ADDITIVE_QUANTITY
 
 const BATCH_SIZE = 500;
 
-function daysAgo(days: number): string {
-  const date = new Date();
-  date.setDate(date.getDate() - days);
-  return date.toISOString();
+function syncWindowStart(syncRangeDays: number | null): string {
+  if (syncRangeDays === null) {
+    return new Date(0).toISOString();
+  }
+
+  const startDate = new Date();
+  startDate.setDate(startDate.getDate() - syncRangeDays);
+  startDate.setHours(0, 0, 0, 0);
+  return startDate.toISOString();
 }
 
 function normalizeWorkout(workout: WorkoutSample): WorkoutSample {
@@ -114,7 +119,7 @@ export interface SyncResult {
 export async function syncHealthKitToServer(options: SyncOptions): Promise<SyncResult> {
   const { trpcClient, healthKit, syncRangeDays, onProgress } = options;
 
-  const startDate = syncRangeDays === null ? new Date(0).toISOString() : daysAgo(syncRangeDays);
+  const startDate = syncWindowStart(syncRangeDays);
   const endDate = new Date().toISOString();
 
   const allSamples: HealthKitSample[] = [];

packages/server/src/routers/healthspan-query.test.ts

@@ -41,7 +41,12 @@ function makeFetchContext(
   overrides: Partial<Parameters<typeof fetchHealthspanRawData>[0]>,
 ): Parameters<typeof fetchHealthspanRawData>[0] {
   return {
-    db: { execute: vi.fn().mockResolvedValue([makeRawHealthspanRow()]) },
+    db: {
+      execute: vi
+        .fn()
+        .mockResolvedValueOnce([{ weekly_exercise_min: null }])
+        .mockResolvedValueOnce([makeRawHealthspanRow()]),
+    },
     userId: "user-1",
     timezone: "UTC",
     accessWindow: fullAccessWindow,
@@ -65,6 +70,15 @@ describe("fetchHealthspanRawData", () => {
       ([, queryText]) => typeof queryText === "string" && queryText.includes("activity_metadata"),
     )?.[1];
     expect(zoneQuery).toEqual(expect.any(String));
+    expect(query).toHaveBeenCalledWith(
+      expect.anything(),
+      expect.stringContaining("activity_metadata"),
+      expect.objectContaining({
+        windowStart: "2026-03-01 00:00:00",
+        windowEndExclusive: "2026-03-16 00:00:00",
+      }),
+    );
+    expect(zoneQuery).toContain("AND asum.started_at < toDateTime({windowEndExclusive:String})");
     expect(zoneQuery).toContain(`INNER JOIN analytics.deduped_sensor AS ds
         ON ds.user_id = am.user_id
        AND ds.recorded_at >= am.started_at

packages/server/src/routers/healthspan-query.ts

@@ -2,7 +2,8 @@ import { averageVo2MaxEstimates } from "@dofek/training/derived-cardio";
 import { ZONE_BOUNDARIES_FTP } from "@dofek/zones/zones";
 import { sql } from "drizzle-orm";
 import { z } from "zod";
-import { dateWindowStart, timestampWindowStart } from "../lib/date-window.ts";
+import { dateAccessPredicate } from "../billing/entitlement.ts";
+import { dateWindowEnd, dateWindowStart, timestampWindowStart } from "../lib/date-window.ts";
 import { dateStringSchema, executeWithSchema } from "../lib/typed-sql.ts";
 import { fetchBodyCompRows } from "../repositories/body-clickhouse.ts";
 import { fetchSleepNights } from "../repositories/clickhouse-sleep-repository.ts";
@@ -36,6 +37,10 @@ const rawRowSchema = z.object({
 
 export type HealthspanRawRow = z.infer<typeof rawRowSchema>;
 
+const weeklyExerciseMinutesRowSchema = z.object({
+  weekly_exercise_min: z.coerce.number().nullable(),
+});
+
 type WeeklyHistoryRow = z.infer<typeof historyRowSchema>;
 type HealthspanRawDataContext = Pick<
   AuthenticatedContext,
@@ -72,6 +77,12 @@ function bedtimeMinutes(timestamp: string, timezone: string): number | null {
   return minutes < 720 ? minutes + 1440 : minutes;
 }
 
+function nextDateString(dateString: string): string {
+  const date = new Date(`${dateString}T00:00:00Z`);
+  date.setUTCDate(date.getUTCDate() + 1);
+  return date.toISOString().slice(0, 10);
+}
+
 /**
  * Compute total aerobic and high-intensity minutes from analytics.deduped_sensor.
  * Uses user_profile plus bounded helper-provided resting heart-rate rows.
@@ -91,6 +102,7 @@ async function fetchHrZoneTime(
     .toISOString()
     .replace("T", " ")
     .replace(/\.\d{3}Z$/, "");
+  const windowEndExclusive = `${nextDateString(endDate)} 00:00:00`;
 
   const rows = await sensorStore.query(
     z.object({
@@ -122,6 +134,7 @@ async function fetchHrZoneTime(
         ON up.id = asum.user_id
       WHERE asum.user_id = {userId:UUID}
         AND asum.started_at > toDateTime({windowStart:String})
+        AND asum.started_at < toDateTime({windowEndExclusive:String})
         AND asum.ended_at IS NOT NULL
         AND (up.max_hr IS NOT NULL OR up.ftp IS NOT NULL)
     ),
@@ -169,6 +182,7 @@ async function fetchHrZoneTime(
       userId: ctx.userId,
       timezone: ctx.timezone,
       windowStart: windowStartTimestamp,
+      windowEndExclusive,
       powerThreshold: ZONE_BOUNDARIES_FTP[2],
       restingHeartRateDates: restingHeartRateRows.map((row) => row.date),
       restingHeartRates: restingHeartRateRows.map((row) => row.resting_hr),
@@ -178,6 +192,26 @@ async function fetchHrZoneTime(
   return rows[0] ?? { aerobic_minutes: 0, high_intensity_minutes: 0 };
 }
 
+async function fetchWeeklyExerciseMinutes(
+  ctx: HealthspanRawDataContext,
+  endDate: string,
+  totalDays: number,
+): Promise<number | null> {
+  const rows = await executeWithSchema(
+    ctx.db,
+    weeklyExerciseMinutesRowSchema,
+    sql`SELECT
+          (SUM(exercise_minutes)::real / GREATEST(${totalDays}::real / 7, 1)) AS weekly_exercise_min
+        FROM fitness.v_daily_metrics
+        WHERE user_id = ${ctx.userId}
+          AND date > ${dateWindowStart(endDate, totalDays)}
+          AND date <= ${dateWindowEnd(endDate)}
+          ${dateAccessPredicate(ctx.accessWindow, sql`date`)}`,
+  );
+
+  return rows[0]?.weekly_exercise_min ?? null;
+}
+
 /**
  * Fetch the raw aggregates and weekly history needed to compute a Healthspan score.
  *
@@ -202,8 +236,12 @@ export async function fetchHealthspanRawData(
     : [];
   const restingHeartRateCte = restingHeartRateValuesCte(restingHeartRateRows);
   const hrZoneTime = await fetchHrZoneTime(ctx, endDate, totalDays, restingHeartRateRows);
+  const weeklyExerciseMin = await fetchWeeklyExerciseMinutes(ctx, endDate, totalDays);
   const weeklyDivisor = Math.max(totalDays / 7, 1);
-  const weeklyAerobicMin = hrZoneTime.aerobic_minutes / weeklyDivisor;
+  const weeklyAerobicMin = Math.max(
+    hrZoneTime.aerobic_minutes / weeklyDivisor,
+    weeklyExerciseMin ?? 0,
+  );
   const weeklyHighIntensityMin = hrZoneTime.high_intensity_minutes / weeklyDivisor;
   const bodyMeasurements = ctx.sensorStore
     ? await fetchBodyCompRows(ctx.sensorStore, ctx.userId, endDate, totalDays)
@@ -238,11 +276,15 @@ export async function fetchHealthspanRawData(
           SELECT
             (SELECT AVG(resting_hr)
              FROM resting_heart_rate
-             WHERE date > ${dateWindowStart(endDate, totalDays)}) AS avg_resting_hr,
+             WHERE date > ${dateWindowStart(endDate, totalDays)}
+               AND date <= ${dateWindowEnd(endDate)}
+               ${dateAccessPredicate(ctx.accessWindow, sql`date`)}) AS avg_resting_hr,
             (SELECT AVG(steps)
              FROM fitness.v_daily_metrics
              WHERE user_id = ${ctx.userId}
-               AND date > ${dateWindowStart(endDate, totalDays)}) AS avg_steps,
+               AND date > ${dateWindowStart(endDate, totalDays)}
+               AND date <= ${dateWindowEnd(endDate)}
+               ${dateAccessPredicate(ctx.accessWindow, sql`date`)}) AS avg_steps,
             NULL::real AS latest_vo2max
         ),
         strength_freq AS (
@@ -251,13 +293,17 @@ export async function fetchHealthspanRawData(
           WHERE user_id = ${ctx.userId}
             AND activity_type = 'strength'
             AND started_at > ${timestampWindowStart(endDate, totalDays)}
+            AND started_at < (${dateWindowEnd(endDate)} + INTERVAL '1 day')::timestamp
+            ${dateAccessPredicate(ctx.accessWindow, sql`started_at::date`)}
         ),
         weekly_rhr AS (
           SELECT
             date_trunc('week', date)::date AS week_start,
             AVG(resting_hr) AS avg_rhr
           FROM resting_heart_rate
           WHERE date > ${dateWindowStart(endDate, totalDays)}
+            AND date <= ${dateWindowEnd(endDate)}
+            ${dateAccessPredicate(ctx.accessWindow, sql`date`)}
           GROUP BY date_trunc('week', date)
         ),
         weekly_steps AS (
@@ -267,6 +313,8 @@ export async function fetchHealthspanRawData(
           FROM fitness.v_daily_metrics
           WHERE user_id = ${ctx.userId}
             AND date > ${dateWindowStart(endDate, totalDays)}
+            AND date <= ${dateWindowEnd(endDate)}
+            ${dateAccessPredicate(ctx.accessWindow, sql`date`)}
           GROUP BY date_trunc('week', date)
         ),
         weekly_dates AS (