SQL (BigQuery ANSI) Efficiently get last value that was updated before 1st of each month - sql

Question

So my database has a changes history table which I am looking up to know my user's status on 1st of each month. Since changing dates are arbitrary, I am trying to get date of last update before 1st of that month (considering the fact that users stay in same status unless recorded by the same table again) then checking what status user had on that timestamp and regarding that as the status of user on the first of the month. So doing something like this:
WITH converted_before_time_changed as (
SELECT dch.user_id,
max(CASE WHEN dch.time_changed <= '2022-01-01' THEN dch.time_changed ELSE NULL END) as time_changed_before_jan_1,
max(CASE WHEN dch.time_changed <= '2022-02-01' THEN dch.time_changed ELSE NULL END) as time_changed_before_feb_1,
max(CASE WHEN dch.time_changed <= '2022-03-01' THEN dch.time_changed ELSE NULL END) as time_changed_before_mar_1,
max(CASE WHEN dch.time_changed <= '2022-04-01' THEN dch.time_changed ELSE NULL END) as time_changed_before_apr_1,
max(CASE WHEN dch.time_changed <= '2022-05-01' THEN dch.time_changed ELSE NULL END) as time_changed_before_may_1,
max(CASE WHEN dch.time_changed <= '2022-06-01' THEN dch.time_changed ELSE NULL END) as time_changed_before_jun_1,
max(CASE WHEN dch.time_changed <= '2022-07-01' THEN dch.time_changed ELSE NULL END) as time_changed_before_jul_1,
FROM my_database.defacto_users_changes_history dch
WHERE dch.table = 'all_users' AND dch.column='status'
GROUP BY user_id
),
c2_before_flags as (SELECT
c2b.user_id,
jan_dch.new_value as status_on_jan_1,
feb_dch.new_value as status_on_feb_1,
mar_dch.new_value as status_on_mar_1,
apr_dch.new_value as status_on_apr_1,
may_dch.new_value as status_on_may_1,
jun_dch.new_value as status_on_jun_1,
jul_dch.new_value as status_on_jul_1
FROM
converted_before_time_changed c2b
LEFT JOIN my_database.defacto_users_changes_history jan_dch on jan_dch.time_changed = time_changed_before_jan_1 AND c2b.user_id = jan_dch.user_id
LEFT JOIN my_database.defacto_users_changes_history feb_dch on feb_dch.time_changed = time_changed_before_feb_1 AND c2b.user_id = feb_dch.user_id
LEFT JOIN my_database.defacto_users_changes_history mar_dch on mar_dch.time_changed = time_changed_before_mar_1 AND c2b.user_id = mar_dch.user_id
LEFT JOIN my_database.defacto_users_changes_history apr_dch on apr_dch.time_changed = time_changed_before_apr_1 AND c2b.user_id = apr_dch.user_id
LEFT JOIN my_database.defacto_users_changes_history may_dch on may_dch.time_changed = time_changed_before_may_1 AND c2b.user_id = may_dch.user_id
LEFT JOIN my_database.defacto_users_changes_history jun_dch on jun_dch.time_changed = time_changed_before_jun_1 AND c2b.user_id = jun_dch.user_id
LEFT JOIN my_database.defacto_users_changes_history jul_dch on jul_dch.time_changed = time_changed_before_jul_1 AND c2b.user_id = jul_dch.user_id
)
SELECT * FROM c2_before_flags
This already takes a lot of time which increases exponentially with each month added, plus its not scalable as I have to edit the query to add each month. What would be the ideal way of achieving the same, dynamically and efficiently?