A Cross-Sectional Analysis

Advances in medicine and health policy have resulted in growing of older population, with a concurrent rise in multimorbidity, particularly in Iran, as a country transitioning to a western lifestyle, and in which the percent of the population over the age of 60 years is increasing. This study aims to assess multimorbidity and the associated risk factors in Iran. We used data from 50,045 participants (age 40–75 y) in the Golestan Cohort Study, including data on demographics, lifestyle habits, socioeconomic status, and anthropometric indices. Multimorbidity was defined as the presence of 2 or more out of 8 self-reported chronic conditions, including cardiovascular diseases, diabetes, chronic obstructive pulmonary disease, chronic kidney disease, liver disease, , Paolo Boffetta, M djadi, MD, kzadeh, MD Multimorbidity prevalence was 19.4%, with the most common chronic diseases being gastroesophageal reflux disease (76.7%), cardiovascular diseases (72.7%), diabetes (25.3%), and chronic obstructive pulmonary disease (21.9%). The odds of multimorbidity was 2.56-fold higher at the age of >60 years compared with that at <50 years (P< 0.001), and 2.11-fold higher in women than in men (P< 0.001). Other factors associated with higher risk of multimorbidity included non-Turkmen ethnicity, low education, unemployment, low socioeconomic status, physical inactivity, overweight, obesity, former smoking, opium and alcohol use, and poor oral health. Apart from advanced age and female sex, the most important potentially modifiable lifestyle factors, including excess body weight and opium use, and opium user, are associated with multimorbidity. Policies aiming at controlling multimorbidity will require a multidimensional approach to reduce modifiable risk factors in the younger population in developing countries alongside adopting efficient strategies to improve life quality in the older population. (Medicine 95(7):e2756) Abbreviations: BMI = body mass index, CKD = chronic kidney disease, COPD = chronic obstructive pulmonary disease, CVD = cardiovascular disease, DMFT index = Decayed Missing Filled Teeth index, ESCC = esophageal squamous cell carcinoma, GCS = Golestan Cohort Study, GEE = Generalized Estimating Equations, GERD = gastroesophageal reflux disease, SES = socioeconomic status, TB = tuberculosis. INTRODUCTION I n most countries throughout the world, particularly in the developing countries, the proportion of the older people in the overall population is growing rapidly. This is a result of advances in medical science, technology, and health policy, resulting in a longer life expectancy and a decline in fertility rates. The senior population is expected to increase 3-fold in the next few decades in Iran. On the basis of estimates of the World Health Organization (WHO), by 2050, Iran, as a developing country, will have a greater proportion of older individuals (8.4%–29.4%) than the United States (20.1%–27%). In Iran, the aging population may be regarded as an indicator of successful population, and public health policies and socioeconomic development. The advances in health status of the Iranian population have transformed the most common diseases, from fatal acute diseases into survivable chronic g of the population will increase the onic conditions, causing people to suffer efined as the simultaneous occurrence of www.md-journal.com | 1 2 or more chronic health disorders in the same person at one point in time. A systematic review of 21 studies showed that the estimated prevalence of multimorbidity varies widely in developed countries; it has been estimated that 1 in 4 adults in the developed countries experiences multimorbidity, and 50% of the older people have 2 or more chronic diseases. Data on multimorbidity from low and middle-income countries are sparse, and information about the health of older individuals in these regions is greatly needed. Studies predict that in 2050, 21.1% of world residents will be over 60 years old, and 80% of this group will live in low and middle-income countries. Multimorbidity is associated with higher mortality risk, functional disabilities, deterioration of quality of life, greater use of multiple medications with associated adverse effects, more frequent and longer hospitalization, and higher healthcare utilization and expenses. Because of the increasing importance of multimorbidity, we conducted a cross-sectional analysis of baseline data from the Golestan Cohort Study (GCS)—a largescale study in a high incidence area of esophageal cancer in northern Iran—to identify the prevalence and risk factors of multimorbidity in Iran as a middle-income country that may differ from those observed in developed countries. MATERIALS AND METHODS Study Population and Measurements The study was carried out as a cross-sectional analysis of baseline information from the GCS. Details of the cohort enrollment are described elsewhere. Baseline data were collected during 2004 to 2008, and total enrollment included 50,045 adults aged 40 to 75 years residing in the Golestan Province, in northern Iran. Of the total participants, 49,946 (99.8%) were of Turkmen, Persian, Turkish, Sistani, Baluch, or Kurdish ethnicities; the other 99 enrollees were foreign nationals, who were excluded from this study. Trained physician and nonphysician interviewers administered different parts of a lifestyle questionnaire to each participant in face-to-face interviews to collect information on age, sex, ethnicity, marital status, years of education, employment status, ownership of several appliances, physical activity, body mass index (BMI), smoking, opium and hookah (water pipe) use, alcohol consumption, and Decayed, Missing, Filled Teeth (DMFT) index. For each interviewee, a short physical examination was performed, and blood pressure, height, and weight were measured by trained general physicians. In this mainly rural population, most of the physical activities performed by the participants were related to their jobs. Therefore, the physical activity was defined based on occupational activity, and coded as yes (heavy and intense activity) or no (all other participants). BMI was calculated using the WHO-recommended classification: underweight (BMI <18.5 kg/m), normal (BMI 18.5–24.9 kg/m), overweight (BMI 25–29.9 kg/m), and obese (BMI >30 kg/m). In this study, age at the time of interview was clustered as 49, 50 to 60, and >61 years. On the basis of the 2-step cluster analysis with the use of similarities of family asset, ethnicity, sex, employment status, age at starting the first job, size (surface area) and the status of house, age, and the status of house, we categorized the socioeconomic status (SES) of participants as low, middle, and high. Multimorbidity in this study refers to the presence of 2 or Ahmadi et al more chronic diseases. Similar to several comparable studies, the ascertainment of diseases was based on selfreports. The morbidities included cardiovascular diseases 2 | www.md-journal.com (CVDs), including hypertension, coronary heart disease and stroke, diabetes, chronic obstructive pulmonary disease (COPD), chronic kidney disease (CKD), liver disease, gastroesophageal reflux disease (GERD), tuberculosis, and cancers. We chose these diseases because they are frequently observed and have a major impact on health status, quality of life, and mortality in this population. The study was approved by the ethics committee of the Digestive Diseases Research Institute, Tehran University of Medical Sciences (OHRP-IRB-00001641). All participants signed an informed consent during original cohort study allowing investigators to use their anonymized data for further analysis. Statistical Analysis We estimated the age and sex-standardized proportion of multimorbidity among participants by several sociodemographic and lifestyle factors. To evaluate the differences in distribution of multimorbidity by continuous or categorical factors, we used t tests, Mann–Whitney or chi-square tests, whenever appropriate. To examine the simultaneous effects of different factors and to calculate adjusted prevalence odds ratios (ORs) and 95% confidence intervals (CIs), we used multivariate logistic regression models; cluster effects were evaluated using the generalized estimating equation (GEE) method. All statistical analyses were performed using SPSS (Version 21.0, IBM Co. Chicago, IL). Two-sided P values below 0.05 were considered statistically significant. RESULTS The study evaluated 49,946 individuals enrolled in the GCS. The mean age of participants was 52.1 9 years, and the majority were women (57.6%), rural residents (76.8%), and of Turkmen ethnicity (74.6%). BMI was 25 kg/m or higher in 59.4% of the individuals, and 17% had used opium (Table 1). In this study, the age and sex-standardized prevalence of multimorbidity was 19.4% (95% CI 19.1%–19.8%). The most common chronic diseases reported by those with multimorbidity were GERD (76.7%), CVD (72.7%), diabetes mellitus (25.3%), and COPD (21.9%). In multivariate models, older people, women, non-Turkmens, unemployed people, opium users, alcohol users, and those with low education, low physical activity, low SES, high BMI, and high DMFT (an indicator of poorer oral hygiene) were at a higher risk of multimorbidity (all P< 0.05) (Table 2). Table 3 represent the prevalence of comorbidity in cases With multimorbidity. On the basis of these results, the most prevalent co-morbidity happened for CVDs and GERD (52%). The comorbidity of CVDs and diabetes was 18%. Figure 1 shows the prevalence of multimorbidity by age and sex. In both sexes, multimorbidity increased with advancing age. In all age groups, the proportion of those with multimorbidity was higher in women than in men, and this difference increased with age. The multivariate logistic regression models also showed that older age groups and women were at a higher risk of multimorbidity. The odds of multimorbidity was 2.56-fold higher in age groups above 60 years compared with those below 50 years (P< 0.001) and 2.11-fold higher in women Medicine Volume 95, Number 7, February 2016 than in men (P< 0.001). The odds of multimorbidity also increased significantly with higher BMI. For obese participants, the odds was 2.33-fold higher than those in the normal BMI Copyright # 2016 Wolters Kluwer Health, Inc. All rights reserved. TABLE 1. Distribution of Risk Factors in Patients With and Without Multimorbidity