The current study was conducted in Bukan city, which is located in West Azarbaijan province in the Northwest of Iran. Its population was 194,846 based on the 2017 official estimation. People in this area are almost entirely from the Kurdish-speaking community. Kurdish people follow their sociocultural values and mostly belong to the Sunni brach of Islam. The data for this study was based on the enrolment phase of the BAS which is the first comprehensive longitudinal study on ageing among the Kurdish population aged 50-94 years in Iran aims to investigate the health status of older Kurdish adults over time. Stratified random sampling was used to select the study population from eight health centres in Bukan from Oct 2017 to Dec 2018. There was a recently updated list of people aged 50 years and older in these health centres from which we selected the study population. The study staff invited them through a phone call. An interview was scheduled for those who accepted to participate in health centres during official hours. In overall, they contacted 2000 persons, of whom 341 (57% men and 43% women) were not interested in taking part in the study. Of those who accepted 166 were not eligible for and were not included. The overall response rate was 75% (N=1493).
The study outcome was the percentage of the population who reported having MM (≥ 2 chronic diseases). This was based on the study participant’s response to the question ‘Has a doctor ever told you that you have any of the following health problems? We included a list of 36 diseases/conditions in this analysis including: gastrointestinal conditions (peptic ulcer, Chron’s disease, ulcerative colitis, fatty liver) heart diseases and hypertension, neurologic diseases (stroke/Transient Ischemic Attack (TIA), epilepsy, Parkinson, migraine, headache, Alzheimer/dementia, MS), musculoskeletal (arthritis, osteoporosis), endocrine conditions (diabetes mellitus, hypo/hyperthyroidism), respiratory diseases (Chronic Ostructive Pulmonary Diseases (COPD), asthma), cancer, and mental disorder (depression, anxiety), and psychological disorders. Because selected non-communicable diseases (NCDs) such as diabetes, hypertension are recorded for national prevention and control of NCDs programs we were able to validate some of the respondents self-reported medical conditions against their medical records by interviewers under the supervision of a General Practitioner. However, because we used a more comprehensive list of chronic conditions in the survey than are recorded in the medial records we were not able to do this for all conditions.
Data collection and preparation
Information for this study was collected via an interviewer administered questionnaire. Interviewer also measured BMI via anthropometric height and weight. In analyses, a range of demographic, socioeconomic, lifestyle and clinical factors were examined. Age provided as a continuous variable also was categorised as 50-59, 60-69 and 70 years and over. Marital status was classified into two groups: married/living with a partner and divorced/separated/single/widow. Socioeconomic status indicators included educational qualification categorised as illiterate, and literate. Self-reported income adequacy was classified in 3 groups: I don’t have a problem, it is enough for basic needs, or it is not enough for basic needs. Smoking behaviour was basd on whether respondents to identified themselves as a regular smoker or not. The Physical Activity Scale for the Elderly (PASE) was used to estimate the level of physical activity. It has been validated in previous studies in Iran (16). The PASE is a brief and specific instrument which has been designed for older adults to estimate physical activity recalled throughout one week (17). Frequency and time spent in a variety of activities including leisure time activities (walking; light activities, moderate, or strenuous intensity and muscle-conditioning activities) as well as work-related activities (in paid or volunteer work) and household activities such as light house-work, yard work, and caring for others were also recorded. After considering the weight for each activity, the final PASE score for the week was calculated based on the sum of all activities, and the mean score was presented. While, there are no specific cut points to categorize activity levels, our data were separated into tertile to categorize physical activity levels as high (≥121), medium (56.5-120.9) or low (<56.5) within each group for descriptive purposes; however the continuous score was used in regression analysis
Body Mass Index (BMI, kg/m2) was categorised as normal weight (<25), overweight (25-29.9), obese (≥30) based on WHO-defined standard cut off points (12). Self-rated health status was categorized as excellent/very good/good, fair/poor. Adequate consumption of fruit and vegetables; was measured by asking questions about number of raw and cooked vegetable serving /day as well as fresh fruit and juice, then a composite variable was made to classify the number of veg& fruit consumption per day. It was subsequently categorised into two categories: inadequate 5-A-day; adequate 5-A-day.
Differences in the characteristics of people with and without MM were determined with the use of Student’s t-test for continuous variables and the chi-square test for categorical variables. We calculated the odds ratios (ORs) and 95% confidence intervals (CIs) for multimorbidity by sociodemographic and lifestyle factors, and built two models; crude, and adjusted for socioeconomic and lifestyle factors (age, sex, education, marital status, income, BMI, physical activity, smoking, adequate fruit and vegetable intake, self-rated health status). Data were analysed using the STATA statistical package Version14, all estimates were reported with 95% confidence interval and a significance level 0.05.