Hypertension poses a great danger on the development of many chronic diseases especially cardiovascular and neurological complications.1 Recent studies have shown alarming levels of hypertension among adults in the Middle East.2 This could be attributed to the higher prevalence of risk factors of hypertension. Lack of physical exercise has reached almost 50% among females in the Middle East.3
Recent study in Upper Egypt, principally a rural area, showed that 66% of cases with stroke had hypertension.1 Other study in Egypt confirmed that risk factors of hypertension are more prevalent in urban population.2
Cardiovascular disease is a rapidly increasing cause of mortality and morbidity in both industrialized nations and economically developing countries, like Egypt.4 Hypertension is one of the major contributing factors for the development of ischemic heart disease (IHD) and had a score of ten in an additive risk scoring for factors associated with coronary heart disease in Egypt.5 Globally, ∼51% of stroke and 45% of IHD deaths are attributable to high systolic blood pressure.6
Although hypertension is common in developing countries particularly in urban areas yet the rate of awareness, treatment and control is very low.7 It is evident that hypertension is a common problem in developing countries like Egypt, and unfortunately, it is not fully addressed in terms of undiagnosed and uncontrolled cases.
The aims of our study were: (i) to identify the prevalence rate of hypertension among adult inhabitants of Al-Waily District in Cairo, (ii) to identity the possible risk factors associated with the development of hypertension and (iii) to assess the rates of uncontrolled and undiagnosed hypertension among the study population.
Subjects and methods
This research was done as a part of the Community Outreach activities of the Faculty of the Medicine of Ain Shams University (Cairo, Egypt) to screen the neighboring society for non-communicable diseases. Al-Waily District is located in the Western Zone of Cairo with almost 196 000 inhabitants.
Sample size calculation
Based on the total population of 196 000, estimated percentage of hypertension in the desired population of 20% with 5% CI, 95% confidence coefficient, around 40 clusters to be studied, percentage of response 60% and on average 2 eligible adults in each household, the calculated sample size is 480 subjects. Open Epi Program version 4.06.08 was used for sample size calculation.
A questionnaire was formulated to inquire about personal history, detailed history of smoking or exposure to passive smoking, history of previous medical or surgical problems and treatment of chronic diseases with special emphasis on the history of hypertension and its treatment. The risk factors of hypertension included in the questionnaire were smoking history, history of regular physical exercise (30 min for more than three times per week) and history of hypercholesterolemia.
The used questionnaire consisted of 38 questions divided in 4 sections. The first section was personal history, second section history of smoking and exposure to passive smoking. The third section was history of previous medical or surgical problems, history and treatment of chronic diseases and special emphasis on the history of hypertension and its treatment. The fourth section was for risk factors of hypertension. The risk factors of hypertension were smoking history, history of regular physical exercise (30 min for more than three times per week) and history of hypercholesterolemia. Weight and height were measured to estimate the body mass index (BMI) of each participant.
After designing of the questionnaire, a pilot study was done to test the understanding, clarity and logical order of questions as perceived by inhabitants of Al-Waily district. Testing the questionnaire in this primary stage was done on 20 subjects. Then, the ambiguous questions were modified and a final version of the questionnaire was obtained. Face validity was done by asking five specialists in the field of cardiology about the content of the questionnaire. Evaluation of the internal consistency of the sections of the questionnaire was carried out by calculating the Cronbach Alpha coefficient.
This study had the ethical approval of the Ethical Committee of the Faculty of Medicine, Ain Shams University. A written consent was signed by every participant after explaining the study objectives and methodology.
A meeting with the local health authorities and local administrative authorities of Al-Waily District was made before the start of the outreach activities with the aim of facilitation of fieldwork. Those two authorities notified the residents of Al-Waily District of the community outreach activity by the Faculty of Medicine through banners, flyers and brochures. The fieldwork was facilitated by the presence of representatives of the local health authorities and local administrative authorities. The participants of the study were collected by cluster random technique. About 40 clusters of inhabitants of Al-Waily District were reached. The participants of the study were examined inside their habitats.
Data collection was done by 12 teams; each team consisted of a house officer, community worker and senior epidemiologist staff from the Department of Community Medicine of Ain Shams University (Cairo, Egypt). The questionnaire was filled by the house officer for all adult subjects inside the house. Also, weight and height measurement were done to calculate the BMI. Blood pressure measurement was done by calibrated mercury sphygmomanometers. Blood pressure measurement was done at room temperature; the subject was seated comfortably with the back and arm supported. The subjects were instructed to relax as much as possible and not to talk during measurement. Two readings were recorded 5 min apart, and a mean recording was calculated. A subject with recorded both systolic blood pressure of ≥140 and diastolic blood pressure of ≥90 was considered hypertensive. The fieldwork started in November 2011 and lasted till February 2012.
First, the following descriptive analysis was done: frequency, percent, mean and standard deviation. Thereafter, comparisons were done using the student’s t-test for continuous variables and Pearson’s Chi-square test for categorical variables. Level of significance was set at P < 0.05. The adjusted risk factors for hypertension were obtained using the logistic regression analysis. The dependent variable was the presence and absence of hypertension in all participants. All variables described previously were considered as possible candidates for the final model. The initial multivariable model construction consisted in the preliminary selection of variables using a manual purposeful selection method and a relatively large significance level (alpha approximately 0.25). Subsequently, the resulting model was reduced using a likelihood ratio test with a significance level of 0.05. Before accepting a final model, the interactions as well as confounding were evaluated. The calibration of the final model was assessed using the Hosmer and Lemeshow goodness-of-fit test, and its discrimination was assessed by the area under the receiver operator characteristic curve. Data entry screen was done on Microsoft excel 2007. Statistical analysis was performed using the Statistical Package for Social Science (SPSS) version 15.0 (SPSS, Inc., Chicago, IL, USA).
Description of the study population
Our study included 774 adult residents of Al-Waily District in Western Zone of Cairo. The mean age of the study participants was 46.5 ± 17.9 years. Most of the participants (48.1%) were ≥50 years, whereas those of <30 years constituted 23.8% of the studied sample.
Female subjects constituted about two-third (67.1%) of the study participants. Thirty-six percent of the subjects were illiterate and 40.8% of the subjects had primary to secondary education whereas 16% were highly educated. Married subjects constituted 59.4% of the sample, 17.5% of the subjects were single and 19% of the subjects were widowed whereas 4% of the subjects were divorced.
The overall prevalence of smoking among studied subjects was 22.9%, and the prevalence of smoking was very high among males (63%) compared with females (2.9%), with statistical significant difference.
Only 31% of participants reported history of realizing regular exercise, and a very low percentage (4%) reported having hypercholesterolemia.
The mean BMI of the subjects was 30.6 ± 8.3. Participants with normal BMI constituted only 20.8% of the total sample. Participants with overweight were 24.1%, and participants with obesity grade I were 37.0%, whereas participants with grade II obesity were 11.6%. A higher percentage of obesity with BMI of ≥30 was observed among females (62.5%) compared with males (20.7%), with statistical significant difference. The highest prevalence of obesity (66.7%) was observed among age group of 40–50 years, whereas the least age group with obesity (21.7%) were those below 30 years, with statistical significant difference.
Prevalence of hypertension in the study population
The total examined cases for blood pressure were 752 subjects, and the prevalence of hypertension was 16.1% (124 subjects) with a 95% CI from 13.9 to 19.3.
Risk factors for hypertension in the study population
Higher prevalence of hypertension was noticed among females (19%) compared with males (11.3%), and the difference is highly significant statistically (Table 1). Our results show that highest prevalence of hypertension was noticed among cases of 40–50 years of age (27.4%) and cases of ≥50 years of age (21.5%) compared with younger age groups and the difference is highly significant statistically (Table 1).
Odds ratio for having hypertension was 4.4 (95% CI: 2.7–7.3) for obese persons compared with normal or overweight persons. Meanwhile, odds ratio for having hypertension among physically inactive persons was 1.6 (95% CI: 1.1–2.7). The prevalence of hypertension among smoker subjects was 11 compared with 16% among nonsmokers, with no statistical significant difference.
Rates of uncontrolled and undiagnosed hypertension in the study population
The rate of undiagnosed hypertension was 11% (95% CI: 8.4–13.9) among those who did not give history of hypertension, whereas the rate of uncontrolled hypertension was 30% (95% CI: 24.2–37).
The rate of uncontrolled hypertension was higher among obese subjects (39%) compared with normal or overweight subjects (13.6%), and the difference is highly significant statistically.
Main finding of this study
The second objective of our survey was to identity the possible risk factors associated with the development of hypertension among Egyptian adults living in Cairo. Before reaching conclusions based on the present results, it is necessary to consider a number of potential objections to the methodology. Our study did not estimate cholesterol and blood lipid levels among the study subjects; known risk factors for hypertension. We only relied on asking participants about past history of hypercholesterolemia. Only 4% reported having hypercholesterolemia, which reflects clear under-diagnosis of hypercholesterolemia among participants.
Odds ratio for obesity and development of hypertension in our study is 4.4, which is much higher than a study done on the national level in Saudi Arabia with odds ratio of 2.2.14 Our results agree with a study conducted in China, which revealed an odds ratio for obesity and hypertension of 4.2.15
Obesity and hypertension in our study was higher among participant females compared with participant males. This agrees with the results of a recent systemic review for all cardiovascular risk factors in the Middle East, which reported a higher prevalence of obesity and hypertension among females.8 Several studies from the Middle East showed that hypertension is also higher among females compared with males.16–19
The prevalence of cigarette smoking is very high among participant males, and this agrees with a previous study that reported a prevalence of cigarette smoking of 48% among men in North Africa and Middle East.20 The rate of smoking did not differ in cases with and without hypertension. This finding agrees with a study done in Palestine where the authors reported current smoking status among hypertensive patients of 8.3 compared with 16.7% among controls.21
What is already known on this topic
Physical inactivity is well-known modifiable risk factor for hypertension. Lack of physical activity is very high among our study participants. This highly correlates with a study done in Palestine, which reported that 76% of their studied subjects with hypertension did not practice any exercise. Furthermore, in the previous study, the rate of physical inactivity was only 15% in the control group.21 Other previous study reported that the physical activity is not among the significant risk factors for the development of incident hypertension in rural areas.22
What this study adds
Our study revealed that 11% of cases of who gave no history of hypertension were actually suffering of hypertension. This finding is correlated with the high BMI and sedentary lifestyle. The rate of undiagnosed hypertension in our study is lower than that reported by a recent study conducted in rural areas of India where 58% of incident cases of hypertension were unaware of their condition.22
The rate of uncontrolled hypertension is 30% among our study participants diagnosed and treated for hypertension. Our finding of controlled hypertension was higher than a study done on Egyptian Demographic and Health Survey, which reported a rate of controlled hypertension in urban areas to be 46%.9 The total percentage of uncontrolled hypertension in the USA in 2011 was 47%, which is slightly higher compared with our detected rate of uncontrolled hypertension in Al-Waily District.10 Data from the Egyptian National Hypertension Project, published in 1995, showed that 37.5% of studied subjects were aware of the disease and only 8% had controlled hypertension.23
Limitations of this study
Before reaching conclusions based on the present results, it is necessary to consider a number of potential limitations. Although our surveillance methodology can be applied in different districts hospitals, these results pertain solely to Al-Waily District and could not be considered generalizable. Our screening survey was conducted in Al-Waily District in Western Zone of Cairo, with its special demographic and socio-economic characteristics that could be different from other zones in Cairo or Egypt in general. However, our findings were consistent and coherent, strongly indicating the external validity of the study.
In conclusion, community outreach campaigns should be conducted regularly in the future for the residents of Al-Waily District for early detection of hypertension cases and proper health education about hypertension and its dangerous consequences. A special care should be directed to those with undiagnosed hypertension and cases with resistant hypertension. Our study calls for more attention to health education programs with special emphasis on healthy life style like regular physical exercise, weight control and quitting smoking to avoid risk factors for hypertension and better control of the disease among diagnosed and treated patients.
— Update: 06-01-2023 — cohaitungchi.com found an additional article Hypertension screening, awareness, treatment, and control: a study of their prevalence and associated factors in a nationally representative sample from Nepal from the website www.ncbi.nlm.nih.gov for the keyword hypertension screening questionnaire.
According to recent estimates, hypertension is the biggest single contributor to death and disability globally, accounting for 10.4 million deaths a year in 2017 . Around 45% of deaths due to heart disease and 51% of deaths due to stroke are attributable to hypertension . Hypertension affects more than 20% of the world’s adult population [3,4]. Among these hypertensive individuals, 75% are from low-income and middle-income countries (LMICs). In LMICs, the prevalence of hypertension increased by 7.7% between 2000 and 2010 .
The increasing prevalence of hypertension is also a growing concern in Nepal. Surveys conducted in different parts of Nepal between 2011 and 2016 suggest that the prevalence of hypertension has increased over the past decade [6–9]. A recent systematic review found that the prevalence of hypertension in Nepal increased by 6% between 2000 and 2020 .
The prevalence of hypertension screening, awareness, treatment, and control are low in LMICs, indicating gaps in the cascade of hypertension care . Among all hypertensives in LMICs in 2010, 37.9% were aware that they had high blood pressure, 29.0% were receiving treatment, and only 7.7% had controlled blood pressure . The burden of untreated and uncontrolled hypertension was also found to be high in Nepal’s neighbouring countries (e.g. Bangladesh, India, and Pakistan) in a study conducted between 2003 and 2009, where 68.1% of hypertensive persons did not receive treatment, and 87.1% of hypertensive persons did not have optimal control of their blood pressure . Some of the sub-national study results suggest that the prevalence of hypertension awareness, treatment, and control are also low in Nepal [8,12–14]. A secondary analysis of the Demographic and Health Survey (DHS) 2016 results demonstrated that 38% of hypertensive people in Nepal were aware of their high blood pressure status, while 18% of hypertensive people were taking antihypertensive medication .
Gaps in the cascade of hypertension care are disproportionately distributed across different socio-demographic groups. Studies have shown that hypertension control is significantly lower in younger South Asian individuals as compared with other age groups . Similarly, women, poor members of society (lowest wealth quintile), individuals with low levels of education, and those living in rural settings were more likely to have untreated and uncontrolled high blood pressure or be unaware of their hypertension . An Indian study observed that single, men, participants from rural areas, and individuals with lower household wealth had a poorer status at each step in the cascade of care process .
Quantifying the unmet need to provide care and understanding its distribution in each step of the care process is critical for the effective management of the disease. The cascade of care framework is commonly used to describe and track the sequential steps across the continuum of care in the treatment of infectious diseases, and particularly in the treatment of HIV, hepatitis C, and tuberculosis . In HIV infection, the concept of continuum care ‘seek, test, treat, and retain’ emphasizes the importance of identifying and diagnosing conditions early on and subsequently linking these conditions to antiretroviral therapy . In addition, applying this concept helps to quantify the unmet need for services, as it enables users to track the loss of a proportion of service users at a particular stage in the cascade of care . Recently, the concept was applied to assess the gaps in detecting and treating people with diabetes and hypertension and retaining them in the care process [19–21]. Healthcare providers and other stakeholders can apply the framework to identify persons who are more likely to be unaware of their condition, who are aware but untreated, or who have received treatment but who have sub-optimally controlled blood pressure. This framework also allows to locate gaps in the hypertension control cascade and tailor interventions to those in at-risk population groups . For example, if a large proportion of the population is unaware of their condition, blood pressure screening or other outreach services can be used effectively to identify persons with hypertension. Similarly, if the lack of treatment or control is the prevailing problem, the stakeholders will need to identify and tackle health systems, health providers, and individual level barriers, in order to effectively connect the patient with the hypertension management services and retain them in the process of care.
Several studies have reported the prevalence of hypertension in Nepal, including the two recent Nepalese STEPwise approach to Surveillance (STEPS) surveys [8,22,23]. However, these studies did not systematically investigate the gaps in hypertension care using the cascade of care framework. This study was, therefore, carried out to quantify the losses of the hypertensive participants which occurred at each step of hypertension care cascade, and to determine the distribution of screening, awareness, treatment, and control of hypertension across different population groups in Nepal.
— Update: 06-01-2023 — cohaitungchi.com found an additional article Development and Validation of a Risk Score Screening Tool to Identify People at Risk for Hypertension in Shanghai, China from the website www.dovepress.com for the keyword hypertension screening questionnaire.
Hypertension has become a major public health problem around the world.1 Hypertension and its complications accounted for more than 50% of the 17 million deaths caused by cardiovascular disease every year.2 The population at risk for hypertension is a group with prevalent risk factors or characteristics and hence with a higher risk for hypertension than the general population.3 The risk of developing hypertension in this group was doubled than those with normal blood pressure (BP).4 Epidemiological studies have indicated that the prevalence of people at risk for hypertension was more than 40% in China.5 A growing body of evidence has suggested that early identification and management of the people at risk for hypertension could be of great benefit to control the cardiovascular events, delay the onset of hypertension and reduce the disease and economic burden.6,7 Therefore, development of a low-cost screening tool for population-based early identification of high-risk individuals is a critical public health strategy.
The blood pressure measured by trained general practitioners was commonly used to identify individuals at risk for hypertension in the community, according to the Guidelines for the Prevention and Treatment of Hypertension in the USA,8 Europe,9 and China.10 Several studies also used BP to height ratios,11 height-specific BP percentile charts,12 or waist circumference (WC)13 to identify the high-risk individuals. However, BP is dynamic and can only give information on a subject’s current status, which may lead to misclassification of high-risk individuals with other risk factors. As the majority of adults have at least one risk factor for hypertension,14 the application of the risk scoring method has advantages in identifying people at high risk for cardiovascular disease.15 This method has been widely used in the screening of asymptomatic people with diabetes,16,17 dementia,18 and sleep-disordered breathing.19 Several studies also used this method to predict the probability of incident hypertension.20–22 However, they did not use this method to screen the people at risk for the purpose of hypertension prevention. To our knowledge, only one study used the method for the early identification of high-risk individuals in primary care settings, which was conducted in rural India.23 Currently there were no such tools available for Chinese population.
Our study aimed to develop a simple and valid screening tool to prospectively identify people at risk for hypertension based on the risk scoring approach, and evaluate the performance of this tool in a cross-sectional setting. This screening tool could help general practitioners to identify high-risk individuals to potentially prevent them from developing hypertension.
Materials and Methods
Study Design and Data
Data for this study were from the survey of Shanghai Chronic Disease and Risk Factors Surveillance in 2013, where a sample of residents aged 15 years or above who had lived in Shanghai for more than 6 months was interviewed.24 The survey was carried out by Shanghai Municipal Center for Disease Control and Prevention (CDC), with the supports of all 16 district-level CDCs from May to July 2013.
The stratified multistage random sampling method was used in the survey. First, sixteen districts were divided into two groups: urban and sub-urban. Sixty townships or communities were randomly selected in each group. Second, within each sampled township or community, four villages or neighborhood blocks were selected by probability proportional to size sampling. The sampled villages or neighborhood blocks were divided into several lanes according to their geographical location, where each lane consisted of about 50 households. Third, two lanes were randomly selected from each sampled village or neighborhood block. Fourth, 27 households were randomly selected from each sampled lane and one person was picked up to participate in the survey from the selected household through the Kish Grid sampling method. Finally, a total of 25,657 respondents participated in the survey. All the participants were interviewed face-to-face by trained interviewers, using a structured questionnaire. Questionnaires included demographic information, socioeconomic status, clinical conditions (eg disease history of diabetes and dyslipidemia, family history of hypertension), physical examination information (eg height, weight, waist circumference, BP), health-related behaviors (eg diets, drinking alcohol, smoking). Hypertension was defined as: (i) having an average systolic BP of 140 mmHg or higher or (ii) having an average diastolic BP of 90 mmHg or higher, or (iii) the respondent was currently taking antihypertensive medications (either Western or traditional Chinese medications) to manage hypertension condition.25 BP was measured by the trained general practitioners, following the standard procedure recommended by the Chinese Guidelines for the Prevention and Treatment of Hypertension. After resting quietly in a seated position for 5 minutes, 3 consecutive BP readings were obtained by the automated validated Omron electronic sphygmomanometer (OMRON Corporation, Kyoto, Japan).
Developing the Screening Tool
Risk factors associated with hypertension were selected to be evaluated, both from literature and clinical knowledge. To keep the screening tool simple and easy to use, we excluded information that can only be assessed in laboratory tests or other clinical measurements, as well as interaction terms in the model. The variables included in the model were age (<60 years; ≥60 years), sex, educational levels (junior high school or below; high school or above), marital status (single; married), smoking (never; previous smoker; smoking but not every day; smoking every day), average frequency of drinking alcohol (never; <1 day a month; 1–3 days a month; 1–4 days a week; ≥5 days a week), average frequency of consumption of meat/vegetables/fresh fruits in a week (< once per day; ≥ once per day), salt intake (low (< 6g per day); moderate (6–9g per day); high (≥ 9g per day)), sleep quality (defined by the average frequency of being unable to sleep or hard to sleep well in a week, and categorized into three groups: good (never); medium (1–3 days per week); poor (≥ 3 days per week)), body mass index (BMI,2; ≥24kg/m2), abdominal obesity (Yes/No, waist circumference ≥90 cm in males or ≥85 cm in females), family history of hypertension (Yes/No), having diabetes (Yes/No), and having dyslipidemia (Yes/No).
Each selected variable was separately tested for their association with the status of hypertension using Pearson’s Chi-square test. Variables significant in the tests were included in the multivariable logistic model using stepwise backward elimination, with the status of hypertension as the dependent variable. The screening tool was then established, including all variables that were kept in the final model. For each variable, the risk score was derived by multiplying the regression coefficients by 10 and rounding to the nearest integer. The reference category of each variable was given a score of 0. A sum score was calculated for each participant by adding the score of each variable.
Validating the Screening Tool
The screening tool was tested for sensitivity and specificity in the validation group, independent of the group in which the score was derived. The receiver operating characteristic (ROC) curve was used to obtain the optimal cut-off value for the risk score. The performance of the screening tool was evaluated according to the area under the curve (AUC) in the ROC curve, sensitivity, specificity, the positive predictive value, and the negative predictive value with 95% Confidence Intervals (CIs). In general, an AUC of more than 0.8 indicates excellent discrimination.28 Furthermore, the trend of the risk score categories and the prevalence of hypertension were calculated using the Trend Chi-square test.
All analyses were performed using SPSS 22.0 (SPSS Inc., Chicago, IL, USA). Descriptive analyses were performed to show the characteristics of the participants. Univariate and multivariable logistic regression analyses were performed to identify independent factors in the risk model. P values were two-sided, and P<0.05 was considered as statistically significant.
Development of the Screening Tool
Validation of the Screening Tool
We have developed a simple and valid screening tool to identify the people at increased risk for hypertension in Shanghai, with good discrimination and calibration. Age, family history of hypertension, having diabetes, having dyslipidemia, BMI, and abdominal obesity contributed to the risk score. It was derived from a randomly selected, population-based sample covering both young and old. The tool focused on factors that are easy to measure without invasive methods, known to be associated with being hypertensive, and draw attention to modifiable risk factors of hypertension.29,30
Our study has a sensitivity of 83.4% and specificity of 64.3%, which showed higher sensitivity (83.4% VS 78.6%) than the risk score developed in India.23 Furthermore, the AUC exceeded those for the published risk factor questionnaire,23,29 which indicated that our screening tool had good discriminative ability. Although the positive predictive value and specificity may seem low, the negative predictive value was quite high given that this was a screening tool and not a confirmatory tool. Therefore, this tool could be used as a simple and convenient tool to help the primary health care workers identify high-risk individuals who might develop hypertension. For example, individuals with a low-risk score are less likely to develop hypertension so that they do not need to be tightly followed up for further management. Moreover, the screening tool could be used to stratify the high-risk individuals into different subsets according to their risk score (eg the sum score more than 30), in order to adopt different interventions precisely.31 This could make the preventive interventions and health education more focused on the target population. Additionally, the variables included in the screening tool are mostly modifiable risk factors, and some factors may become apparent over time.32 Therefore, the screening should be an ongoing process.33
Defining a suitable cut-off point is a trade-off. The ROC curve has been recommended for finding the optimal threshold in screening and diagnostic tests, ie, the point maximizing the sum of sensitivity and specificity.34 However, the trade-off between sensitivity and specificity must be weighed against many conditions, including: the prevalence of the disease, the workload of the general practitioners, whether the test is a part of a screening strategy or a single screening test, how often the test should be offered, the effectiveness of subsequent treatment,35 etc. The general practitioners were engaged in the prevention and management of most of the hypertensive patients. If a lower threshold was used, more individuals would be classified as high-risk for hypertension, which would become a challenging workload for the general practitioners. According to the choice of the cut-off point in this study, up to 45% of the population would be classified as high-risk individuals, which was similar to the current prevalence of prehypertension (41.3%) in China.5 This would not cause any substantial increase in workload for the general practitioners since it is already part of their work to manage the individuals at risk for hypertension.25 However, the cut-off point could be evaluated dynamically according to the workload and prevalence of hypertension in the future, and be adjusted when needed.
A screening tool regarding phenotypical characteristics could never be perfect.36 In our study, approximately 20% of individuals with hypertension had a low score. The reason for this may be (i) they had other risk factors that were not included in our screening tool, and very likely to be that information that required laboratory work, for example, genetic factors, biomarker factors, and so on; (ii) these individuals changed their lifestyle after diagnosis of hypertension and therefore had low scores.37 Unfortunately, due to the limit of the cross-sectional setting of our study, we are not able to distinguish the true reason. On the other hand, approximately 33% of the non-hypertensive individuals had a high score. However, it does not necessarily mean that these individuals were misclassified. The main reason is that these individuals appeared to be non-hypertensive at the time of the survey, but they may develop hypertension later. These two problems should be further investigated in a prospective setting.
It is important to identify and manage the high-risk groups for hypertension as early and effectively as possible so as to delay the progression to hypertension.38 After the early detection, appropriate community-based interventions could be provided to encourage them to adopt healthy lifestyles,39 which will likely improve modifiable risk factors. For instance, our study indicated that BMI was a strong influencing factor for developing hypertension, which was similar to the results of other studies.40,41 For those high-risk groups with high BMI, knowledge regarding healthy diet, such as “DASH (Dietary Approaches to Stop Hypertension) diet”, could be promoted to them to form correct beliefs on low fat and low sodium diet, and eventually change to a light diet and reduce energy intake.42 Furthermore, these high-risk subjects should be encouraged to be engaged in more physical exercises to control their BMIs.43
Our study has several limitations. First, we did not analyze all the possible factors that may contribute to the incidence of hypertension due to data availability. Second, we could not predict the short- or long-term risk of hypertension, as reported in other studies,44 because the dataset was derived from a cross-sectional study. Third, selection bias may exist because of missing information in the key variables. Fortunately, the characteristics of those with and without missing values were not significantly different in the dataset. Finally, since the survey was conducted in Shanghai, it was mainly applicable to the developed regions in Eastern China. It should be relevant to evaluate the generalizability before the screening tool could be used in other parts of China.
In summary, our study has developed a simple and valid screening tool with good sensitivity and medium specificity, to identify individuals at risk for hypertension for the general practitioners in Shanghai. It is a practical way to early detect and manage those at high risk, to delay the progression of hypertension and related complications, which would be beneficial to the individual, the family, and the whole society. Such strategies should be adopted into the nationwide program for hypertension prevention and be launched thoroughly across the country, which could help to delay the onset of hypertension and reduce its prevalence in China.