STEPwise Approach To Surveillance Survey Research Articles

“Current incidence of injuries in Iran; findings of STEPS survey 2021”

BackgroundThe updated epidemiology of injuries at the national and sub-national levels are required for policymakers to effectively handle the burden of injuries. This paper aimed to assess the incidence and risk factors of different injuries in Iran based on a recent national survey. MethodsWe used data from Iran Stepwise approach to surveillance (STEPS) Survey 2021, a population-based study in urban and rural areas of Iran's 31 provinces. A multistage clustered probability design and weighting adjustments were used to select eligible individuals and generate estimations. We estimated the incidence of injuries, assessed sociodemographic variables, and identified potential behavioral risk factors associated with injuries, and results were reported for sociodemographic and geographic stratifications. ResultData from 27,874 participants of the STEPS survey were assessed, of which 1538 (5.5 %, 95 % CI: [5.2–5.8]) reported having an injury in the past 12 months. Falls (44.4 %) were the most common cause of injury, followed by road traffic injury (21.7 %) and exposure to mechanical forces (16.5 %). Except for falls and burns, males had a higher proportion of all types of injuries. Logistic regression analysis showed that being male (OR: 1.7, [1.5, 2.0]) and being an occasional or heavy alcohol drinker (OR: 2.0, [1.3, 3.0] and OR: 2.7, [1.7, 4.1] respectively) were significant risk factors associated with road traffic injuries. Seatbelt use was 90.0 % among both drivers and front-seat passengers, while the use of safety car seats for children was as low as 9.4 %. Injury incidence varied significantly among provinces, with the highest incidence among males observed in Razavi Khorasan (11.2 %) and among females observed in Tehran (12.0 %). ConclusionThis study investigated the updated epidemiology of injuries in Iran and revealed socioeconomic and geographic disparities across country. This epidemiological information can be used to modify injury prevention programs.

Prevalence of obesity and abdominal obesity and their association with metabolic-related conditions in Vietnamese adults: an analysis of Vietnam STEPS survey 2009 and 2015

The abdominal obesity trends and prevalence are important contributing factors to significant rise of many noncommunicable diseases in Vietnam but have not been well-documented in the literature. This study aimed to describe the prevalence and trends of obesity and abdominal obesity in Vietnam from 2009 to 2015 and evaluate how different definitions of obesity and abdominal obesity are associated with metabolic-related conditions. We conducted a secondary analysis based on the Vietnam STEPS (STEPwise approach to Surveillance) cross-sectional Survey 2009 and 2015. Obesity and abdominal obesity were defined using the body mass index (BMI), waist circumference (WC), and waist-hip ratio (WHR) cut-offs from the World Health Organization (WHO) and International Diabetes Federation (IDF). Depending on the specific cut-offs, from 2009 to 2015, obesity prevalence increased from 0.8%-10% to 1.7%-16.4% in women and from 0.8%-10.3% to 1.7%-15% in men; abdominal obesity prevalence increased from 3%-31.3% to 8%-41.7% in women and from 0.3%-19.3% to 0.4%-25% in men. Abdominal obesity using WC-IDF and WHR-WHO definitions had noticeably higher sensitivity and lower specificity for metabolic-related conditions compared to the other four criteria. All anthropometric measurements were statistically correlated with biomarkers/blood pressure in 2009 and 2015 except for fasting glucose. Only WC-IDF and WHR-WHO definitions showed consistent association with all reported metabolic-related conditions regardless of sex and survey years. The prevalence of obesity and abdominal obesity in Vietnam is increasing rapidly, especially abdominal obesity in women regardless of the criteria used. More studies are needed to investigate how using different diagnostic criteria for obesity and abdominal obesity could better identify metabolic-related conditions. Authors received no funding for this study.

S02 Physical activity surveillance across the life-course: from data to policy

As a major risk factor for non-communicable diseases (NCDs), physical inactivity is a prominent challenge for public health. The purpose of this symposium is to present an overview of physical inactivity prevalence in Europe using data collected through international surveillance initiatives, while highlighting successes and discussing future challenges for utilising data to promote physical activity across the life course.The World Health Organization (WHO) is involved in several physical activity surveillance systems on which discussions during this symposium will be based: 1. The WHO European Childhood Obesity Surveillance Initiative (COSI) is the largest survey of its kind in the world. An overview of results from the most recent round of COSI will be presented focusing on prevalence estimates for physical activity, screen time and sleep. Variations between countries of the socioeconomic determinants of physical inactivity, as well as the impact of the COVID-19 pandemic, will demonstrate the ongoing need for quality data to guide targeted policy actions in support of vulnerable groups throughout the life course.2. The WHO’s STEPwise approach to surveillance (STEPS) survey provides important national level prevalence data on the behavioural and metabolic risk factors for NCDs. For many countries, the STEPS survey has provided the first estimates of physical inactivity and sedentary behaviour in the population and has been essential in raising awareness of the need for national policy actions to increase population levels of physical activity.3. The European Commission, with the support of the WHO Regional Office for Europe, has established the European Union Physical Activity Focal Points Network to monitor implementation of the 23 indicators of the Health-Enhancing Physical Activity (HEPA) monitoring framework on physical activity policy development and implementation.4. Within the European Union Physical Activity Focal Points Network, and during the COVID-19 pandemic, some countries established a survey on physical activity and screen time in children and adolescents.

Use of statins for the prevention of cardiovascular disease in 41 low-income and middle-income countries: a cross-sectional study of nationally representative, individual-level data

SummaryBackgroundIn the prevention of cardiovascular disease, a WHO target is that at least 50% of eligible people use statins. Robust evidence is needed to monitor progress towards this target in low-income and middle-income countries (LMICs), where most cardiovascular disease deaths occur. The objectives of this study were to benchmark statin use in LMICs and to investigate country-level and individual-level characteristics associated with statin use.MethodsWe did a cross-sectional analysis of pooled, individual-level data from nationally representative health surveys done in 41 LMICs between 2013 and 2019. Our sample consisted of non-pregnant adults aged 40–69 years. We prioritised WHO Stepwise Approach to Surveillance (STEPS) surveys because these are WHO’s recommended method for population monitoring of non-communicable disease targets. For countries in which no STEPS survey was available, a systematic search was done to identify other surveys. We included surveys that were done in an LMIC as classified by the World Bank in the survey year; were done in 2013 or later; were nationally representative; had individual-level data available; and asked questions on statin use and previous history of cardiovascular disease. Primary outcomes were the proportion of eligible individuals self-reporting use of statins for the primary and secondary prevention of cardiovascular disease. Eligibility for statin therapy for primary prevention was defined among individuals with a history of diagnosed diabetes or a 10-year cardiovascular disease risk of at least 20%. Eligibility for statin therapy for secondary prevention was defined among individuals with a history of self-reported cardiovascular disease. At the country level, we estimated statin use by per-capita health spending, per-capita income, burden of cardiovascular diseases, and commitment to non-communicable disease policy. At the individual level, we used modified Poisson regression models to assess statin use alongside individual-level characteristics of age, sex, education, and rural versus urban residence. Countries were weighted in proportion to their population size in pooled analyses.FindingsThe final pooled sample included 116 449 non-pregnant individuals. 9229 individuals reported a previous history of cardiovascular disease (7.9% [95% CI 7.4–8.3] of the population-weighted sample). Among those without a previous history of cardiovascular disease, 8453 were eligible for a statin for primary prevention of cardiovascular disease (9.7% [95% CI 9.3–10.1] of the population-weighted sample). For primary prevention of cardiovascular disease, statin use was 8.0% (95% CI 6.9–9.3) and for secondary prevention statin use was 21.9% (20.0–24.0). The WHO target that at least 50% of eligible individuals receive statin therapy to prevent cardiovascular disease was achieved by no region or income group. Statin use was less common in countries with lower health spending. At the individual level, there was generally higher statin use among women (primary prevention only, risk ratio [RR] 1.83 [95% CI 1.22–2.76), and individuals who were older (primary prevention, 60–69 years, RR 1.86 [1.04–3.33]; secondary prevention, 50–59 years RR 1.71 [1.35–2.18]; and 60–69 years RR 2.09 [1.65–2.65]), more educated (primary prevention, RR 1.61 [1.09–2.37]; secondary prevention, RR 1.28 [0.97–1.69]), and lived in urban areas (secondary prevention only, RR 0.82 [0.66–1.00]).InterpretationIn a diverse sample of LMICs, statins are used by about one in ten eligible people for the primary prevention of cardiovascular diseases and one in five eligible people for secondary prevention. There is an urgent need to scale up statin use in LMICs to achieve WHO targets. Policies and programmes that facilitate implementation of statins into primary health systems in these settings should be investigated for the future.FundingNational Clinician Scholars Program at the University of Michigan Institute for Healthcare Policy and Innovation, and National Institute of Diabetes and Digestive and Kidney Diseases.

Prevalence of risk factors of non-communicable diseases in the Sultanate of Oman: STEPS survey 2017.

BackgroundNon-communicable diseases (NCD) represent a major public health issue and currently cause 185.75 deaths per 100,000 population in Oman. Hence, there is a need for comprehensive, up-to-date and internationally comparable data on NCD risk factors in order to evaluate the effectiveness of ongoing public health policies and to develop further NCD prevention and control interventions. The aim of the study was to provide evidence-based, up-to-date, extensive, and reliable baseline data on the behavioural and biological risk factors of NCDs in the Sultanate of Oman.MethodsA cross‐sectional, prospective, observational community‐based survey designed to be nationally representative of the Sultanate of Oman was conducted based on the WHO STEPwise approach to Surveillance (STEPS). Multi-stage stratified random sampling according to geographical distribution selected a total of 9053 households (Omani nationals and non-Omani residents). Cluster sampling was used to randomly select equal clusters from each governorate. 823 households were randomly selected from the list of all households in all selected clusters from each governorate and one eligible adult selected from each household randomly accounting for 6582 consenting participants. The survey used demographic and behavioural information questionnaires along with physical and biochemical measurements among adults aged 18 years and above.ResultsThe prevalence of behavioural risk factors such as tobacco use was 9%, alcohol consumption was 2%, insufficient fruit or vegetable intake was 61%, and insufficient physical activity was 39%. The prevalence of biological risk factors such as overweight and obesity was 66%, raised blood pressure was 33%, raised blood glucose was 16%, and raised blood cholesterol was 36%. The prevalence of multiple risk factors was also determined and 95% of the population were found to have more than one risk factor. Three or more risk factors were found among 33% of population aged 18 years and above and 45% of the population aged 45 years and above.ConclusionA high prevalence of various NCD risk factors was found which needs to be addressed through health promotion, education, and policy. The findings are important to support the formulation and implementation of NCD-related policies and action plans that improve health status and prevent mortality due to NCDs in Oman.

Prevalence and factors associated with joint pain in Nepal: findings from a countrywide cross-sectional STEPS survey

ObjectiveThis study aims to determine the prevalence of joint pain and its association with demographic, socioeconomic and behavioural factors in Nepal.DesignThe study was a national cross-sectional population-based study.SettingWe used the...

Prevalence of non-communicable diseases risk factors and their determinants: Results from STEPS survey 2019, Nepal.

The World Health Organization (WHO) recommends ongoing surveillance of non-communicable diseases (NCDs) and their risk factors, using the WHO STEPwise approach to surveillance (STEPS). The aim of this study was to assess the distribution and determinants of NCD risk factors in Nepal, a low-income country, in which two-thirds (66%) of annual deaths are attributable to NCDs. A nationally representative NCD risk factors STEPS survey (instrument version 3.2), was conducted between February and May 2019, among 6,475 eligible participants of age 15-69 years sampled from all 7 provinces through multistage sampling process. Data collection involved assessment of behavioral and biochemical risk factors. Complex survey analysis was completed in STATA 15, along with Poisson regression modelling to examine associations between covariates and risk factor prevalence. The most prevalent risk factor was consumption of less than five servings of fruit and vegetables a day (97%; 95% CI: 94.3-98.0). Out of total participants, 17% (95% CI: 15.1-19.1) were current smoker, 6.8% (95% CI: 5.3-8.2) were consuming ≥60g/month alcohol per month and 7.4% (95% CI:5.7-10.1) were having low level of physical activity. Approximately, 24.3% (95% CI: 21.6-27.2) were overweight or obese (BMI≥25kg/m2) while 24.5% (95% CI: 22.4-26.7) and 5.8% (95% CI: 4.3-7.3) had raised blood pressure (BP) and raised blood glucose respectively. Similarly, the prevalence of raised total cholesterol was 11% (95% CI: 9.6-12.6). Sex and education level of participants were statistically associated with smoking, harmful alcohol use and raised BP. Participants of age 30-44 years and 45-69 years were found to have increased risk of overweight, raised BP, raised blood sugar and raised blood cholesterol. Similarly, participants in richest wealth quintile had higher odds of insufficient physical inactivity, overweight and raised blood cholesterol. On average, each participant had 2 NCD related risk factors (2.04, 95% CI: 2.02-2.08). A large portion of the Nepalese population are living with a variety of NCD risk factors. These surveillance data should be used to support and monitor province specific NCD prevention and control interventions throughout Nepal, supported by a multi-sectoral national coordination mechanism.

Body-mass index and diabetes risk in 57 low-income and middle-income countries: a cross-sectional study of nationally representative, individual-level data in 685 616 adults

The prevalence of overweight, obesity, and diabetes is rising rapidly in low-income and middle-income countries (LMICs), but there are scant empirical data on the association between body-mass index (BMI) and diabetes in these settings. In this cross-sectional study, we pooled individual-level data from nationally representative surveys across 57 LMICs. We identified all countries in which a WHO Stepwise Approach to Surveillance (STEPS) survey had been done during a year in which the country fell into an eligible World Bank income group category. For LMICs that did not have a STEPS survey, did not have valid contact information, or declined our request for data, we did a systematic search for survey datasets. Eligible surveys were done during or after 2008; had individual-level data; were done in a low-income, lower-middle-income, or upper-middle-income country; were nationally representative; had a response rate of 50% or higher; contained a diabetes biomarker (either a blood glucose measurement or glycated haemoglobin [HbA1c]); and contained data on height and weight. Diabetes was defined biologically as a fasting plasma glucose concentration of 7·0 mmol/L (126·0 mg/dL) or higher; a random plasma glucose concentration of 11·1 mmol/L (200·0 mg/dL) or higher; or a HbA1c of 6·5% (48·0 mmol/mol) or higher, or by self-reported use of diabetes medication. We included individuals aged 25 years or older with complete data on diabetes status, BMI (defined as normal [18·5-22·9 kg/m2], upper-normal [23·0-24·9 kg/m2], overweight [25·0-29·9 kg/m2], or obese [≥30·0 kg/m2]), sex, and age. Countries were categorised into six geographical regions: Latin America and the Caribbean, Europe and central Asia, east, south, and southeast Asia, sub-Saharan Africa, Middle East and north Africa, and Oceania. We estimated the association between BMI and diabetes risk by multivariable Poisson regression and receiver operating curve analyses, stratified by sex and geographical region. Our pooled dataset from 58 nationally representative surveys in 57 LMICs included 685 616 individuals. The overall prevalence of overweight was 27·2% (95% CI 26·6-27·8), of obesity was 21·0% (19·6-22·5), and of diabetes was 9·3% (8·4-10·2). In the pooled analysis, a higher risk of diabetes was observed at a BMI of 23 kg/m2 or higher, with a 43% greater risk of diabetes for men and a 41% greater risk for women compared with a BMI of 18·5-22·9 kg/m2. Diabetes risk also increased steeply in individuals aged 35-44 years and in men aged 25-34 years in sub-Saharan Africa. In the stratified analyses, there was considerable regional variability in this association. Optimal BMI thresholds for diabetes screening ranged from 23·8 kg/m2 among men in east, south, and southeast Asia to 28·3 kg/m2 among women in the Middle East and north Africa and in Latin America and the Caribbean. The association between BMI and diabetes risk in LMICs is subject to substantial regional variability. Diabetes risk is greater at lower BMI thresholds and at younger ages than reflected in currently used BMI cutoffs for assessing diabetes risk. These findings offer an important insight to inform context-specific diabetes screening guidelines. Harvard T H Chan School of Public Health McLennan Fund: Dean's Challenge Grant Program.

Determinants of behavioural and biological risk factors for cardiovascular diseases from state level STEPS survey (2017–19) in Madhya Pradesh

BackgroundNational and statewide assessment of cardiovascular risk factors needs to be conducted periodically in order to inform public health policy and prioritise allocation of funds, especially in LMICs. Although there have been studies from India which have explored the determinants of cardiovascular risk factors, they have mostly been from high epidemiological transition states. The present study assessed the determinants of cardiovascular (CVD) risk factors in a low epidemiological transition state (Madhya Pradesh) using the WHO STEPwise approach to surveillance (STEPS).MethodsA total of 5,680 persons aged 18–69 years were selected from the state of Madhya Pradesh through multi-stage cluster random sampling. Key CVD risk factors we sought to evaluate were from behavioural (tobacco, alcohol, physical activity, diet) and biological domains (overweight or obese, Hypertension, Diabetes, and Raised serum cholesterol). Key socio-demographic factors of interest were the caste and tribe groups, and rural vs urban location, in addition to known influencers of CVD risk such as age, gender and education levelResultsThose belonging to the scheduled tribes were more at risk of consuming tobacco (OR 2.13 (95% CI [1.52–2.98]), and a diet with less than five servings of fruits and vegetables (OR 2.78 (95% CI [1.06–7.24]), but had had the least risk of physical inactivity (OR 0.31 (95% CI [0.02–0.54]). Residence in a rural area also reduced the odds of physical inactivity (OR 0.65 (95% CI [0.46–0.92])). Lack of formal education was a risk factor for both tobacco consumption and alcohol intake (OR 1.40 (95% CI [1.08–1.82]) for tobacco use; 1.68 (95% CI [1.14–2.49]) for alcohol intake). Those belonging to schedules tribes had much lower risk of being obese (OR 0.25; 95% CI [0.17–0.37]), but were at similar risk of all other clinical CVD risk factors as compared to other caste groups.ConclusionIn the current study we explored socio-demographic determinants of behavioural and biological CVD risks, and found that in Madhya Pradesh, belonging to a scheduled tribe or living in a rural location, protects against being physically inactive or being overweight or obese. Increasing age confers a greater CVD-risk in all domains. Being a male, and lack of formal education confers a greater risk for behavioural domains, but not for most clinical risk domains. Future efforts at curbing CVDs should be therefore two pronged –a population-based strategy targeting biological risk factors, and a more focussed approach directed at those displaying risky behaviour.

Prevalence and Correlates of Heavy Episodic Alcohol Consumption among Adults in Ecuador: Results of the First National STEPS Survey in 2018.

Thise study aimed to assess the prevalence and correlates of heavy episodic drinking (HED) among adults in Ecuador. In the national, cross-sectional 2018 Ecuador STEPwise approach to Surveillance (STEPS) survey, 4638 persons (median age = 39 years, range 18–69 years) responded to a questionnaire and physical measures. Logistic regression was used to assess the determinants of HED. Results indicate that 24.1% had past-month HED, 36.7% among men, and 12.0% of women; among past-12-month drinkers, 40.6% had past-month HED. In adjusted logistic regression analysis, male sex (adjusted odds ratio = AOR: 3.03, 95% confidence interval = CI: 2.44–3.77), past smoking (AOR: 1.42, 95% CI: 1.12–1.81), and current smoking (AOR: 2.94, 95% CI: 2.25–3.86) were positively associated with HED, and being aged 50–69 years (AOR: 0.52, 95% CI: 0.39–0.68) was negatively associated with HED. In sex-stratified analyses among men, being African Ecuadorean or Mulato (AOR: 1.74, 95% CI: 1.07–2.84) and high physical activity (AOR: 1.43, 95% CI: 1.02–2.01) were positively associated with HED, and among women, being Montubia (AOR: 0.38, 95% CI: 0.16–0.90) was negatively associated with HED and obesity (AOR: 1.58, 95% CI: 1.05, 2.38) was positively associated with HED. Almost one in four participants engaged in HED, and several sociodemographic and health indicators were identified associated with HED.

Prevalence of physical health conditions and health risk behaviours in people with severe mental illness in South Asia: protocol for a cross-sectional study (IMPACT SMI survey)

IntroductionPeople with severe mental illness (SMI) die on average 10–20 years earlier than the general population. Most of these deaths are due to physical health conditions. The aim of this...

Accuracy of Five Multiple Imputation Methods in Estimating Prevalence of Type 2 Diabetes based on STEPS Surveys

BackgroundThis study was aimed to evaluate five Multiple Imputation (MI) methods in the context of STEP-wise Approach to Surveillance (STEPS) surveys.MethodsWe selected a complete subsample of STEPS survey data set and devised an experimental design consisted of 45 states (3 × 3 × 5), which differed by rate of simulated missing data, variable transformation, and MI method. In each state, the process of simulation of missing data and then MI were repeated 50 times. Evaluation was based on Relative Bias (RB) as well as five other measurements that were averaged over 50 repetitions.ResultsIn estimation of mean, Predictive Mean Matching (PMM) and Multiple Imputation by Chained Equation (MICE) could compensate for the nonresponse bias. Ln and Box–Cox (BC) transformation should be applied when the nonresponse rate reaches 40% and 60%, respectively. In estimation of proportion, PMM, MICE, bootstrap expectation maximization algorithm (BEM), and linear regression accompanied by BC transformation could correct for the nonresponse bias. Our findings show that even with 60% of nonresponse rate some of the MI methods could satisfactorily result in estimates with negligible RB.ConclusionDecision on MI method and variable transformation should be taken with caution. It is not possible to regard one method as totally the worst or the best and each method could outperform the others if it is applied in its right situation. Even in a certain situation, one method could be the best in terms of validity but the other method could be the best in terms of precision.

Prevalence and Correlates of Dyslipidemia Among Men and Women in Palau: Findings of the Palau STEPS Survey 2011-2013.

BackgroundEpidemiological evidence of dyslipidemia in Pacific Island countries is limited despite the knowledge that non-communicable diseases have a high burden in the region. We aimed to examine the prevalence and correlates of dyslipidemia among residents of Palau.MethodsThe Palau STEPwise approach to Surveillance (STEPS), which was conducted from 2011 through 2013, comprised three parts: behavioral risk factors; physical measurements; and biochemical tests, covering areas such as blood lipids. We used STEPS-generated data to perform a cross-sectional study of 2,184 randomly selected Palau residents, comprising Palauans and non-Palauans aged 25–64 years.ResultsThe age-adjusted mean BMI was 29.3 kg/m2 in men and 29.9 kg/m2 in women; age-adjusted mean triglycerides value was 182 mg/dL in men and 166 mg/dL in women; and age-adjusted mean cholesterol was 178 mg/dL in men and 183 mg/dL in women. The prevalence of overweight/obesity (BMI ≥25 kg/m2) was 75% in men and 76% in women, and those of hypertriglyceridemia (triglycerides ≥150 mg/dL) and hypercholesterolemia (total cholesterol ≥200 mg/dL) were 48% in men and 41% in women and 18% in men and 23% in women, respectively. Mean values of total cholesterol were 177 mg/dL in Palauan men and 182 mg/dL in non-Palauan men. Mean values of triglycerides were 171 mg/dL in Palauan women and 150 mg/dL in non-Palauan women. Women living in rural areas showed a higher mean value of total cholesterol than those in urban areas.ConclusionWe found a high mean BMI and high prevalence of overweight/obesity and hypertriglyceridemia, but low mean total cholesterol and a low prevalence of hypercholesterolemia in Palau. Lipid profiles varied by age, ethnicity, and living area.

Intracluster correlation estimates from a World Health Organisation STEPwise approach to surveillance (STEPS) survey for cardiovascular risk factors in Vellore, Tamil Nadu, India

ObjectivesMost World Health Organisation (WHO) STEPS surveys use cluster sampling to assess the prevalence of risk factors for non-communicable diseases (NCDs) for which design effects need to be estimated using intracluster correlation (ICCs) coefficients, for sample size calculation. Although there are many reports of risk factor surveys reported from developing countries, there are very few reports of ICCs for risk factors for NCDs, which can inform planning the appropriate sample size needed for such surveys. This study reports the ICCs for NCD risk factors, obtained from a WHO STEPS survey conducted in Vellore district, in the state of Tamil Nadu, South India. Study designCross-sectional study. MethodsA cross-sectional study was carried out in 48 urban clusters (wards) and nine rural clusters (villages) between 2011 and 2012, using the WHO STEPS methodology for assessing behavioural, anthropometric, physical and biochemical risk factors. The ICC estimates for various risk factors were obtained using loneway and xtmelogit commands using STATA to study clustering of risk factors. ResultsThe number of respondents was 6196 adults aged 30–64 years. The median ICC of cardiovascular risk factors in the urban area was 0.046, while it was 0.064 in the rural area. Clustering was higher for behavioural risk factors such as physical activity (ICC: 0.179 rural, 0.049 urban) and fruit and vegetable intake (ICC: 0.105 rural, 0.091 urban) as compared with physical risk factors (ICCs for hypertension: 0.044 rural, 0.006 urban; body mass index: 0.046 rural, 0.041 urban) and biochemical outcomes such as fasting plasma glucose (ICC: 0.017 rural, 0.027 urban). ConclusionsThis study provides estimates of ICCs for cardiovascular risk factors from Vellore, South India, as such data have not been reported from WHO STEPS surveys in India or neighbouring countries. Such estimates of ICCs if reported from various WHO STEPS being carried out across the country can contribute to better planning of epidemiological surveys. Clustering of behavioural risk factors at village/ward level as seen in this study points to the need for community-based interventions for health promotion, as spatial clustering influences behaviour, which in turn affects chronic disease outcomes.

Noncommunicable disease risk factors among older adults aged 60-69 years in Nepal: findings from the STEPS survey 2013.

Both the noncommunicable diseases (NCDs) burden and the population of older adults are increasing in Nepal. This study aims to estimate the prevalence of behavioral and biological risk factors of common NCDs among Nepali older adults aged 60-69 years. A subsample analysis of data from the 2013 Nepal STEPwise approach to Surveillance (STEPS) survey was conducted with 526 older adults aged 60-69 years. STEPS sample weighting and domain analyses were used to include the entire sample for variance estimation and to obtain prevalence estimates and corresponding 95% confidence intervals (CI) for our selected population of older adults. All participants had at least one risk factor for NCDs; about one-fourth had four. Of the eight examined risk factors, inadequate fruit/vegetable intake (98.6%, 95% CI: 96.9-100.0), hypertension (57.2%, 95% CI: 51.0-63.4), and hypercholesterolemia (37.9%, 95% CI: 30.8-44.9) were ranked the three most prevalent risk factors while physical inactivity (2.5%, 95% CI: 1.0-4.0) was least prevalent. Prevalence of smoking was 31% (95% CI: 24.9-37.2), overweight/obesity was 19% (95% CI: 13.1-25.2), alcohol use was 18% (95% CI: 12.2-23.5), diabetes was 15% (95% CI: 8.5-21.4), and 36% (95% CI: 30.9-42.0) of the older participants suffered discomfort due to oral health problems. Several risk factors, including current alcohol consumption, daily servings of fruit/vegetable intake, and overweight/obesity showed signficant variation in prevalence by gender, ethnicity, and place of residence, urban vs. rural. Epidemiological and demographic transitions are two emerging public health issues in Nepal. The baseline information provided by this study on the prevalence of NCD risk factors among Nepali older adults aged 60-69 years can inform policies and programs that focus on maximizing the health and well-being of older adults.

Tobacco use and its determinants in the 2015 Kenya WHO STEPS survey

BackgroundAccording to the World Health Organization (WHO), in 2015, over 1.1 billion people smoked tobacco, which represents around 15% of the global population. In Africa, around one in five adults smoke tobacco. The 2014 Kenya Global Adult Tobacco Survey reported that 2.5 million adults use tobacco products. The objective of our study was to describe patterns and determinants of tobacco use from the 2015 Kenya STEPS survey, including use of “smokeless” tobacco products and the more novel e-cigarettes.MethodsThe WHO STEPwise approach to surveillance (STEPS) was completed in Kenya between April and June 2015. Logistic regression analyses was used to assess factors affecting prevalence and frequency of tobacco use. Sociodemographic variables associated with tobacco use were considered: age, sex, level of education, wealth quintile, and residence. The relationship with alcohol as an intervening risk factor was also assessed. Our main outcomes of interest were current tobacco use, daily tobacco use and use of smokeless tobacco products.ResultsOf 4484 respondents, 605 (13.5%) reported being current tobacco users. Most active tobacco users were male (n = 507/605, 83.8%). Three out of four tobacco users (n = 468/605, 77.4%) reported being less than 50 years old, with the average start age being 21 (20.6, 95% CI 19.3–21.8) and the average quit age 27 (27.2, 95% CI 25.8–28.6). Most tobacco users had only ever attended up to primary school (n = 434/605, 71.7%). Men had nearly seven times higher odds of being tobacco users as compared to women (OR 7.63, 95% CI 5.63–10.33). Alcohol use had a positive effect on tobacco use. Finally, less than ten respondents reported having used e-cigarettes.ConclusionThe 2015 Kenya WHO STEPS provided primary data on the status of tobacco use in the country and other leading NCD risk factors, such as alcohol, and associated diseases. Our findings highlight key target populations for tobacco cessation efforts: young people, men, those with lower levels of education, and alcohol consumers. Further data is needed on the use of smokeless tobacco, and its impact on smoked tobacco products, as well as on the novel use of e-cigarettes.

Prevalence and predictors of physical inactivity levels among Kenyan adults (18\u201369\xa0years): an analysis of STEPS survey 2015

BackgroundPhysical inactivity accounts for more than 3 million deaths worldwide, and is implicated in causing 6% of coronary heart diseases, 7% of diabetes, and 10% of colon or breast cancer. Globally, research has shown that modifying four commonly shared risky behaviours, including poor nutrition, tobacco use, harmful use of alcohol, and physical inactivity, can reduce occurrence of non-communicable diseases (NCDs). Risk factor surveillance through population-based periodic surveys, has been identified as an effective strategy to inform public health interventions in NCD control. The stepwise approach to surveillance (STEPS) survey is one such initiative, and Kenya carried out its first survey in 2015. This study sought to describe the physical inactivity risk factors from the findings of the Kenya STEPS survey.MethodsThis study employed countrywide representative survey administered between April and June 2015. A three stage cluster sampling design was used to select clusters, households and eligible individuals. All adults between 18 and 69 years in selected households were eligible. Data on demographic, behavioural, and biochemical characteristics were collected. Prevalence of physical inactivity was computed. Logistic regression used to explore factors associated with physical inactivity.ResultsA total of 4500 individuals consented to participate from eligible 6000 households. The mean age was 40.5 (39.9–41.1) years, with 51.3% of the respondents being female. Overall 346 (7.7%) of respondents were classified as physically inactive. Physical inactivity was associated with female gender, middle age (30–49 years), and increasing level of education, increasing wealth index and low levels of High Density Lipoproteins (HDL).ConclusionA modest prevalence of physical inactivity slightly higher than in neighbouring countries was found in this study. Gender, age, education level and wealth index are evident areas that predict physical inactivity which can be focused on to develop programs that would work towards reducing physical inactivity among adults in Kenya.

Socio-demographic determinants of obesity indexes in Iran: findings from a nationwide STEPS survey.

Background: Overweight and obesity are considered as non-communicable diseases (NCDs) risk factors with increasing prevalence worldwide. This nationwide study aimed to determine the socio-demographic determinants of obesity indexes in Iran. Methods: This cross-sectional study was conducted based on data from the sixth round of nationwide Stepwise approach to surveillance (STEPS) survey in the 31 provinces of Iran in 2011. A total of 9878 people aged ≥20 years were selected using a multi-stage cluster sampling method. Data were collected through three steps questionnaire including ecological, physical and biochemical measurements. We assessed body mass index (BMI), waist circumference(WC) and waist-hip ratio (WHR) as the main indicators of obesity. Results: In this study, the weighted prevalence of overweight and obesity were 34.5% (95% CI:33.6, 35.5) and 21.5% (95% CI: 20.7, 22.3), respectively. The mean ± standard deviation (SD)of BMI among men and women were 25.4±4.4 and 26.9±5.2 kg/m2 respectively. Older age,living alone, having lower education level, being housewife or retired were associated with overweight and obesity (P<0.05). Urbanization was positively associated with BMI and WC.Being obese or overweight was associated with having a history of type 2 diabetes mellitus (T2DM), hypertension (HTN) and cardiovascular diseases (CVDs). Conclusion: The prevalence of overweight in this study was less than global rate while it was vice versa for obesity prevalence. Some socio-demographic characteristics were identified as determinants of obesity which should be considered for planning preventive and control action plans.

Smoking Pattern and Associated Sociodemographic Factors: Findings from a Nationwide STEPS Survey in Iran.

Background:Smoking is a modifiable risk factor for noncommunicable diseases with a wide range of harmful health outcomes. Identification of sociodemographic characteristics of smokers can be a guideline to development of effective intervention proportional to target population. This study aimed to determine smoking pattern and its associated sociodemographic factors in Iran.Methods:This cross-sectional study was conducted based on data from the sixth round of nationwide STEPwise approach to Surveillance (STEPS) survey in the 31 provinces of Iran. A total of 10,834 participants aged ≥15 years were selected through a multistage cluster sampling method. Collecting data was performed via three-step questionnaire (ecological, behavioral risk factors, and physical and biochemical measurements). Data analysis was performed via Epi Info and then SPSS version 21 softwares using descriptive methods and analytical tests.Results:Of all participants, 9.6% were current cigarette smokers, which was significantly more frequent among men than women (21.5% vs. 1.1%, respectively, P < 0.001). Smoking was significantly associated with being self-employed and having under diploma education level (P < 0.05). Of all current cigarette smokers, 8.7% were daily smokers. The mean ± standard deviation of systolic blood pressure and history of cardiovascular symptoms in current smokers were higher than nonsmokers (P = 0.005 and P < 0.001, respectively). Coughing for >4 weeks, frequent wheezing, and shortness of breath were significantly more frequent in current smokers than nonsmokers (P < 0.001, P < 0.001, and P = 0.02, respectively).Conclusions:Our results draw a picture of sociodemographic distribution of smoking pattern to determine the specific characteristics of the target population affecting cigarette smoking and identified specific demographic strategies for preventive and control action plan.

Implementation of Global NCD Monitoring Framework in Punjab, Haryana and Chandigarh–A Feasibility study

Background: In India, a national NCD monitoring framework was developed (June 2013) in consonance with the World Health Organization (WHO) global NCD monitoring framework with 10 targets and 21 indicators. A feasibility study was undertaken in Punjab, Haryana, and Chandigarh with few objectives. Objectives: To review the existing monitoring framework, identify the possible data sources, and collect the secondary data for NCDs. Methods: In-depth interview was conducted with the three state program officers (SPOs), and Health Management Information System (HMIS) reports (2010) were reviewed. Data from non-health sectors were collected and possible data sources were identified. Results: It was observed that SPOs were not clear of the data for indicators and targets. Food and drug licensing authority, schools, colleges, and offices may be possible sources of additional data. Current HMIS was inadequate. Multiple issues such as scarcity of data, excess dependency on hospital-based data, lack of manpower, inter-sectoral coordination, and periodic STEP wise approach to surveillance (STEPS) surveys are the major barriers for implementation. Conclusion: We concluded that with the existing resources, it was not feasible to implement the NCD monitoring framework. Recommendations: National surveys should incorporate NCD indicators, and periodic STEPS survey at state level are necessary for indicator generation.