Alberta residents aged 35–69 years with no history of cancer (other than non-melanoma skin cancer) based on self-report were eligible to participate in ATP [10]. As of March 2015, ATP has established a cohort of 52,810 participants who had completed baseline questionnaires and consented to data linkage to health-related databases; from those, 52,770 (>99.0%) provided valid Personal Health Numbers (PHN) to facilitate individual-level linkage to AH administrative data [10, 11]. ATP participants are actively followed up by requesting additional questionnaire data every four years until March 2050 and passive follow-ups are possible for ATP participants by linking ATP cohort data to administrative healthcare databases [1]. The study period of this analysis is from October 01, 2000 to March 31, 2018 when the latest AH data were linked. By linking with administrative health data, including Alberta Population Registry and Vital statistics (death), data on migration and death can be obtained for epidemiology censoring.

The Alberta Health (AH) administrative data, including healthcare services utilization, diagnosis, medications and cost, are routinely collected by the publicly funded provincial healthcare systems in Alberta. Ministry of Health, i.e. AH, is the custodian of these provincial health databases in Alberta. Detailed descriptions of AH databases can be obtained from the AH website: http://www.health.alberta.ca/initiatives/health-research.html.

The AH administrative datasets utilized in this study were Ambulatory Care, Inpatient data, Practitioner Claims, Population Registry, Alberta Blue Cross and Pharmaceutical Information Network (PIN) and Vital Statistics. Supplementary Table 1 shows a list of AH data elements used in this study, including diagnostic information coded with ICD codes, medication information with Anatomic Therapeutic Chemical (ATC) codes, provincial migration-in/out data from the Population Registry and death data from Vital Statistics.

Each resident in Alberta has a unique PHN recorded for administrative and billing purposes when they interact with the healthcare systems in Alberta [12]. In this study, AH administrative datasets (October 2000-March 2018) were linked by AH using PHNs to the ATP cohort to identify cases with chronic diseases. After data linkage, AH healthcare data were de-identified before release to the authors of this study. The data linkage and data analyses conducted for this study had been approved by the Health Research Ethics Board of the University of Alberta (project ID Pro00058561).

A set of validated algorithms using ICD codes and ATC codes were applied to the linked AH administrative data to identify cases of most prominent chronic diseases [13] other than cancer (in Alberta, the provincial cancer registry is a more reliable data source for cancer cases than administrative healthcare data). The algorithms used to identify cases of chronic diseases were either validated in Alberta’s residents or commonly applied in established chronic disease surveillance programs, including the Government of Alberta Interactive Health Data Application (IHDA) and the Canadian Chronic Disease Surveillance System (CCDSS) (Supplementary Table 2). For example, in this study diabetes cases were identified using a modified version of the Canadian National Diabetes Surveillance System (NDSS) algorithm [14]:

In addition, multi-morbidity, an indicator of increased clinical complexity and disease burden, was defined as two or more of the top common (prevalence ≥0.1%) chronic diseases investigated in this study.

The ATP participants were recruited on a rolling basis from 2000 to 2015. To characterize the baseline (at-enrollment) health profile of the ATP cohort, the baseline prevalence of chronic diseases in the ATP cohort was calculated as the percentage of ATP participants who had been diagnosed with certain chronic diseases prior to the enrollment or up to 6 months after the enrollment (Supplementary Figure 1). The cumulative incidence rate since enrollment was also calculated, as the number of incident cases per 1,000 person-year (PY), for each chronic disease between the baseline (up to 6 months after the ATP enrollment) and the time when the latest AH data were linked (March 31, 2018). In these two calculations, cases were identified as “non-prevalent” or “incident” only if the first diagnosis date (index date) was >6 months after enrollment (“clearance time”) and not within the first year (October 01 2000-October 01 2001) when AH data was linked to the ATP cohort (“wash-out time”), to ensure the true “non-prevalent” or “incident” cases were identified; otherwise, cases were considered as “prevalent” cases at the baseline (Supplementary Figure 1). Among chronic diseases investigated in this study, depression and chronic pain are the two chronic conditions that could have multiple episodes during the course of disease. The baseline prevalence of these two conditions was thus calculated as the percentage of participants who had any episode(s) of the condition (i.e. depression or chronic pain) during the period between 3 years before the ATP enrollment (especially for participants recruited 2004 onwards) and 6 months after the enrollment.

To characterize the trend of chronic diseases in the ATP cohort over time, the annual prevalence and incidence rate for each chronic condition was calculated between 2001 and 2017. The prevalence and incidence rates were not calculated for the year of 2000 and 2018, given AH data were only available for three months in each year (October-December in 2000 and January-March in 2018) at the time of data linkage. In this calculation, incident cases are the new cases in each calendar year (e.g. in the year of 2001 from January 01, 2001 to December 31, 2001) and prevalent cases are the total number of cases that were existing in each calendar year, which includes the incident cases. Annual prevalence was calculated as the percentage of ATP participants who had certain conditions identified in each calendar year, where the denominator was counted as the total number of ATP participants who were alive and residents in Alberta by the end of each calendar year (Equation 1). Annual incident rates were calculated as the number of new cases (incidence cases) per 1000 ATP participants at risk of developing this condition (i.e. those who had not developed the condition at the beginning of each year) in each calendar year (Equation 2 and 3). ATP participants who were not registered Alberta residents based on Population Registry records (e.g. moving out of the province or death) in each calendar year were excluded from each calculation.

For chronic diseases with multiple episodes (depression and chronic pain), only the episode (incidence) rate was calculated for each calendar year, where in Equation 3 participants at risk (the denominator) were the total number of participants (i.e. each participant was at risk of developing new episodes in each calendar year). We also calculated the age- and sex- standardized prevalence and incidence rates using 2016 Census-Alberta data (reference population) [15] for standardization (indirect standardization) to minimize the potential impact of different age- and sex- distribution on rate calculations and to facilitate comparison with other similar studies [4, 5].

The cohort was characterized using standard descriptive statistics (means and standard deviations or percentage where appropriate). We also used generalized linear models with prevalence (binomial distribution) or incidence (Poisson distribution, natural logarithm of person-year as offset) as dependent variables, calendar years (2001–2017), age groups (35–85+years grouped by every 5 years based on the age on January 1^st of each calendar year) and sex (male vs. female) as independent variables, to test the trend of chronic disease occurrence over time and the relationship with age and sex. Statistical analyses, with significant level at alpha = 0.05, were conducted with STATA^® 14 software.

Data access and analyses in this study complies with the provincial Health Information Act (HIA) in Alberta, Alberta Health Services (AHS) and ATP data access and disclosure guidelines. Accordingly, in this study, we only report data with >30 subjects across important categories (e.g. in each calendar year).

The average age of 52,770 ATP participants who consented to individual level data linkage was 51.2 ± 9.4 years at the time of enrollment. More than half of the cohort (63.7%) were women and 81.8% self-reported as being of Caucasian ethnicity. The baseline characteristics of study participants are shown in Supplementary Table 3. Detailed description of this cohort can be found in our previous publications [1, 16]. The AH administrative data (2000–2018) was linked to this cohort, with an average follow-up time of 10.1 ± 4.4 years (from the ATP enrollment up to March 31, 2018). In this study, we only reported results for the top 16 chronic diseases that had a prevalence ≥0.1% at the enrollment, based on the linked administrative data (Table 1).

At the time of ATP enrollment (baseline), 18.5% of the participants (17.4% of women and 20.1% of men) had previously been diagnosed with hypertension, 18.1% (22.1% of women and 11.0% of men) with depression, 12.8% (13.8% of women and 11.2% of men) with chronic pain, 10.1% (10.8% of women and 9.0% of men) with osteoarthritis, 8.7% (7.2% of women and 11.5% of men) with cardiovascular diseases, 6.9% (9.4% of women and 2.4% of men) with hypothyroidism and 5.7% (4.9% of women and 7.1% of men) with diabetes (Table 1). In addition, at the time of enrollment, 23.6% of the ATP participants (25.6% of women and 20.0% of men) had two or more co-morbid conditions from the 16 most prevalent chronic diseases (cardiovascular diseases were grouped as one single condition) investigated (Table 1).

Of the 16 top prevalent chronic conditions, hypertension (22.1 in total, 19.6 in women and 26.5 in men, per 1000 PY), osteoarthritis (16.2 in total, 17.4 in women and 14.1 in men, per 1000 PY) and ischemic heart diseases (13.0 in total, 11.0 in women and 16.6 in men, per 1000 PY) had the highest cumulative incidence rate since the ATP enrollment until March 2018, followed by hypothyroidism (7.8 in total, 10.3 in women and 3.9 in men, per 1000 PY), diabetes (6.2 in total, 5.1 in women and 8.1 in men, per 1000 PY) and obstructive sleep apnea (5.6 in total, 5.9 in women and 5.2 in men, per 1000 PY) (Table 2). For diseases that clinically present with multiple episodes, the cumulative incidence (episode) rate was 133.2 (167.8 in women and 77.2 in men) per 1000 PY for depression and 33.8 (36.9 in women and 28.7 in men) per 1000 PY for chronic pain. In addition, similar to the baseline prevalence, the cumulative incidence rate was significantly higher (p < 0.001) in men than in women for diabetes, hypertension, cardiovascular diseases (CVD) and chronic obstructive pulmonary disease (COPD), and it was significantly lower (p < 0.001) in men than in women for asthma, osteoarthritis, osteoporosis, hypothyroidism, depression and chronic pain (Table 2).

The annual prevalence and incidence rates of chronic diseases were summarized in Supplementary Figure 2–14. All chronic diseases investigated in this study had an increased trend in the prevalence between 2001 and 2017 (p < 0.001 for trend tests), among which cardiovascular diseases (Supplementary Figures 4–8) had the highest level of increase in prevalence, while hypertension (Supplementary Figure 3a) had the lowest extent of increase in prevalence annually over time. In addition, the percentage of having multi-morbidities steadily increased over time from 3.9% in 2001 to 40.3% in 2017 (p < 0.001 for trend test, Figure 1).

Between 2001 and 2017, the annual incidence rate (risk) of stroke (Supplementary Figure 6b) and COPD (Supplementary Figure 7b) was increased by 16.8% and 6.7% per year (p < 0.001 for trend tests), respectively. In contrast, the annual incidence rate (risk) of osteoporosis was decreased by 3.2% per year over three waves between 2001-2017 (Supplementary Figure 10b). In addition, although the overall trend was decreasing, there was noticeable increase in the annual incidence rate (risk) of diabetes (Supplementary Figure 2b), hypertension (Supplementary Figure 3b), asthma (Supplementary Figure 8b) and hypothyroidism (Supplementary Figure 11b) in 2014–2015. The annual incidence rate (risk) of acute coronary syndrome, heart failure, osteoarthritis and obstructive sleep apnea was relatively stable (changes <1% per year, > for trend test) between 2001–2017. For conditions with multiple episodes, the annual incidence (episode) rate of depression increased by 3.3% per year (p < 0.001 for trend test, Supplementary Figure 13) and decreased by 2.2% per year for chronic pain (p = 0.002 for trend test, Supplementary Figure 14).

The incidence rate (risk) of most chronic diseases was significantly increased with the age (p < 0.05), except for asthma and depression, which either did not change with age (p = 0.13) (asthma) or had lower risk in patients of older age (p < 0.001) (depression) (detailed data available upon request). The regression analysis also showed that the incidence rate (risk) of diabetes, hypertension, CVD and COPD was significantly higher in men than in women (p < 0.01), whilst it was lower in men than in women for asthma, osteoarthritis, osteoporosis, hypothyroidism, depression and chronic pain (p < 0.01). In addition, the age- and sex- standardization with census data did not change the results of the trend of chronic disease rates over time, although there were noticeable differences between the actual crude and age- and sex- standardized rates (Supplementary Figure 2–14).