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Association of risk factors with type 2 diabetes: A systematic review

Diabetes is the leading cause of severe health complications and one of the top 10 causes of death worldwide. To date, diabetes has no cure, and therefore, it is necessary to take precautionary measures to avoid its occurrence. The main aim of this systematic review is to identify the majority of the risk factors for the incidence/prevalence of type 2 diabetes mellitus on one hand, and to give a critical analysis of the cohort/cross-sectional studies which examine the impact of the association of risk factors on diabetes. Consequently, we provide insights on risk factors whose interactions are major players in developing diabetes. We conclude with recommendations to allied health professionals, individuals and government institutions to support better diagnosis and prognosis of the disease.


Introduction
Diabetes Mellitus (DM) commonly referred to as diabetes, is a chronic disease that affects how the body turns food into energy [1]. It is one of the top 10 causes of death worldwide causing 4 million deaths in 2017 [2,3]. According to a report by the International Diabetes Federation (IDF) [3], the total number of adults (20-79 years) with diabetes in 2045 will be 629 million from 425 million in 2017 (48% increase). In 2017, diabetes caused at least 727 billion USD in health expenditure, which is 12% of the total spending on adults [3]. According to the National Diabetes Statistics Report [4], 30.3 million (9.4% of the US population) people have diabetes, and 84.1 million (29.06% of the population) have prediabetes. 1 in 2 people (212 million) with diabetes was undiagnosed in 2017 according to IDF [5]. Diabetes if left untreated can cause serious medical issues, such as cardiovascular disease, stroke, chronic kidney disease, foot ulcers, damage to the eyes, and prolonged kidney ailment. To date, there is no permanent cure for diabetes and the patients have to rely on healthy lifestyle and timely medication [6].
There are three main types of diabetes: type 1, type 2, and gestational diabetes (diabetes while pregnant) [1]. Type 1 diabetes mostly occurs in children and adolescents. 1,106,500 children were suffering from type 1 diabetes in 2017 [3]. The symptoms of type 1 diabetes include abnormal thirst and dry mouth, frequent urination, fatigue, constant hunger, sudden weight loss, bed-wetting, and blurred vision. Type 2 diabetes is mostly seen in adults, but it is increasing in children and adolescents due to the rising level of obesity, physical inactivity and unhealthy diet [5]. 372 million adults were at the risk of developing type 2 diabetes in 2019 [3]. In 2017, more than 21 million live births were affected by diabetes during pregnancy [3]. In this paper, we focus on type 2 diabetes due to the alarming numbers.
Type 2 Diabetes is thought to prevail in an individual from an interaction between several lifestyle, medical condition, hereditary, psychosocial and demographic risk factors such as highlevel serum uric acid, sleep quality/quantity, smoking, depression, cardiovascular disease, dyslipidemia, hypertension, aging, ethnicity, family history of diabetes, physical inactivity, and obesity [6]. In this paper, we present a systematic review of the literature on the association of these risk factors with the incidence/prevalence of type 2 diabetes. We give insights on the contribution of independent risk factors in the development of type 2 diabetes along with possible solutions towards a preventive approach.

Methods
We conduct a systematic literature search using CINAHL, IEEE Xplore, Embase, MEDLINE, PubMed Central, ScienceDirect, Scopus, Springer, and Web of Science databases. Our search criteria does not include a time bound. Its main objective is to retrieve all the studies which examine the association between individual risk factors and the incidence/prevalence of type 2 diabetes. Table A1 shows the search string used for each risk factor. The relevant stud-ies have to meet the following inclusion criteria: 1) published in the English language, 2) prospective cohort or cross-sectional study, 3) type 2 diabetes as a specified risk, 4) one of its risk factors, 5) findings in terms of Odds Ratio (OR), Risk Ratio/Relative Risk (RR), or Hazard Ratio (HR), and the corresponding 95% Confidence Intervals (CIs) for the association between the risk factor and type 2 diabetes. To assess the quality of the studies, we use the National Institutes of Health (NIH) quality assessment tool [7]. The tool consists of 14 questions to evaluate the validity and bias risk of a study. We answered each question by either yes, no, cannot be determined, not applicable, or not reported. The tool then classifies each study as high quality (Good), moderate quality (Fair) and low quality (Poor).

Results
Fig . 1 shows the result of our systematic approach that is used to screen the relevant studies. Irrelevant studies that do not meet the inclusion criteria mentioned in the previous section were excluded after screening titles, abstracts and full texts. At last, 106 papers are considered for this review. These papers are divided into ten categories based on the risk factor under study (Fig. 1). Our review reveals that there is no study that examines the association of age or physical inactivity as an independent risk factor with type 2 diabetes. Table A2 shows the quality assessment results for the studies included in this paper. For smoking, cardiovascular disease and hypertension risk factors, the majority of the studies are of high quality. For serum uric acid, sleep quantity/quality, depression, dyslipidemia, ethnicity, family history of diabetes and obesity, the majority of the studies are of moderate quality.

Serum uric acid
Serum uric acid, a common component of urine generated by the metabolic breakdown of purines, have been associated with insulin resistance and type 2 diabetes [8]. High serum uric acid level in an individual leads to: 1) nitric-oxide mediated vasoconstriction (contraction of blood vessels) leading to impaired glucose uptake in the muscles [9], 2) increase in oxidative stress [10] and 3) increase in inflammation leading to a decrease in adiponectin [11,12]. Consequently, the blood glucose level increases leading to dysfunctional and eventually dead beta-cells [13]. As a result, the individual develops type 2 diabetes. Table 1 shows the characteristics and findings of the work in the literature studying the association between high serum uric acid level and type 2 diabetes.
Perry et al. [14] found that an individual having a uric acid level of more than 411 lmol/l is at 1.5 times more risk of developing type 2 diabetes compared to an individual having uric acid level less than 302 lmol/l. Niskanen et al. [15] also confirmed that change in uric acid levels is associated with a 2 times increase in the risk of incidence type 2 diabetes. Dehghan et al. [16]  l. The authors concluded that lowering uric acid level can be a novel approach for diabetes prevention. Xu et al. [17] found that the association between high serum uric acid level and diabetes is the same in both men and women (RR 1.131, 95% CI 1.084-1.179). The association (RR 1.17, 95% CI 1.09-1.25) is also examined by Kodama et al. [18]. Nakagawa et al. [19] showed that uric acid is a significant and independent risk factor in predicting hyperinsulinemia. The authors observed that serum uric acid level P5.5 mg/dl is associated with the development of hyperinsulinemia after 6 months (OR 5.47, 90% CI 1.6-1.77) and 12 months (OR 3.4, 90% CI 1.1-10.4). However, the cohort was controlled for gender and age (>60 years). Consequently, it can not be concluded whether uric acid is an independent risk factor or there is an integrated effect of uric acid, gender and age. Several studies argue that high-level uric acid is not an independent risk factor and it only emphasizes the association between independent risk factors such as age, obesity, hypertension, gender, and dyslipidemia, and type 2 diabetes [20]. Chou et al. show that uric acid has a significant association with type 2 diabetes in old and obese individuals [21]. Another study by Meisinger et al. [22] shows that high-level uric acid is associated with incidence of type 2 diabetes in women only with HR 2.5 per 1 mmol/L increase. Carnethon et al. [23] found that the risk of incidence type 2 diabetes increases (OR 1.3, (1.2-1.4)) with every 1.4 mg/dl increase in uric acid level. However, this is in combination with an increase in waist/hip ratio, smoking and obesity. Chien et al. [24] stated that individuals with a uric acid level of 0.486 mmol/L and having metabolic syndrome have a 3.3 times more risk of incidence type 2 diabetes compared to those with a uric acid level of 0.211 mmol/L and not having metabolic syndrome. Nan et al. [25] examined the impact of ethnicity and gender on the association between uric acid and incidence of type 2 diabetes. The authors found that the high serum uric acid is an independent risk factor for type 2 diabetes in Mauritian Indian men compared to Creole men, and there is a no-to-weak association in women of both ethnicity. Similarly, Choi et al. [26] studied the association between uric acid and type 2 diabetes in men having cardiovascular risk profile. The authors concluded that men with cardiovascular profile having high uric acid level are twice likely to develop type 2 diabetes. The authors also stated that this association between uric acid and diabetes is independent of other risk factors such as obesity, age, family history of diabetes, hypertension, and metabolic syndrome. Kramer et al. [27] analyzed the impact of age and impaired fasting glucose (IFG) on the association and found that high uric acid level can independently predict incidence of type 2 diabetes (OR 1.65, 95% CI 1.25-2.18) in older adults having IFG. Lv et al. [28] found that high serum uric acid level is associated to type 2 diabetes in middle-aged or older people (RR 1.56, 95% CI 1. 39-1-76).
In summary, the association between high-level serum uric acid remains obscure. It is debatable whether serum uric acid is an independent risk factor for type 2 diabetes or it only emphasizes the association between other independent risk factors and type 2 diabetes. Some studies reported a positive association between high serum uric acid level and incidence of type 2 diabetes [14][15][16]19,24], whereas others [25,29] reported no association. On the contrary, some studies reported an inverse association between uric acid and diabetes [30][31][32]. Furthermore, some studies argue that there is a reverse association, i.e., diabetes leads to high uric acid levels [33,34].

Sleep quantity/quality
The quality and quantity of sleep are affected by several cultural, social, behavioral, psychological, and environmental factors. The working professionals often experience fatigue, tiredness and daytime napping due to irregular working hours and shifts. Evidence shows that the current average sleep of an individual, i.e., 6.8 h/night, is 1.5 h less than that a century ago [45]. The cause of sleep loss is multi-factorial. For instance 45% of adults report that they sleep fewer hours to get more work done, 43% reported that they watch television or use the Internet, and 22% reported to be suffering from insomnia. The unusual, disturbed and reduced sleep is associated with glucose intolerance [46].
An individual suffering from sleep disorder, known as obstructive sleep apnea (OSA), experiences: 1) deficiency in the amount of oxygen reaching the tissues by total/partial collapse of upper airways while sleeping (hypoxia) and 2) inflammation. Frequent Hypoxia triggers an increase in sympathetic activity [47]. Increased sympathetic activity and inflammation lead to insulin resistance condition [48,49] and eventually to type 2 diabetes. Table 2 shows the characteristics and findings of the work in the literature studying the association between sleep quantity/quality and type 2 diabetes.         The results in the literature show that compared to a reference sleep duration of 7-8 h, an individual having either short sleep duration (<6 h) or long sleep duration (>8 h) is at high risk of developing type 2 diabetes. However, [50,51] concluded that there is no significant association between sleep and incidence of type 2 diabetes. Mallon et al. [52] studied the impact of gender on the association between sleep and diabetes. The authors concluded that short sleep duration increases the risk of incidence diabetes in men, whereas, in women, long sleep duration dominates. The effect of ethnicity on the association is analyzed by [53][54][55]. Zizi et al. [53] and Jackson et al. [54] showed that the prevalence of type 2 diabetes is more in whites who sleep less than 5 h or more than 8 -9 h compared to blacks. Beihl [55] showed that the association is more in Hispanics/Non-Hispanic Whites compared to that in African-American. Xu et al. examined the association between day-time napping and type 2 diabetes and showed that an individual taking more than 1 h of day-time nap is at 1.5 times more risk to develop diabetes compared to an individual who does not take a nap during the day. In the context of sleep quality, the risk of incidence type 2 diabetes is more in an individual having difficulty initiating sleep (DIS), and the risk increases with increasing DIS frequency [56][57][58]. Furthermore, the association is more in women having DIS compared to men [59].
In summary, there is a strong association between sleep quantity/quality and the incidence of type 2 diabetes. The association is stronger in women sleeping for more duration and in men with short sleep duration. Moreover, this association is affected by ethnicity.

Smoking
Smoking leads to more than 8 million deaths per year [60]. This is from both active and passive uses, i.e, non-smokers exposed to smokers. Smokers are 30-40% more likely to develop type 2 diabetes compared to non-smokers [61]. When an individual smokes, the level of nicotine increases in his/her body. This leads to a reduction in muscle glucose intake, developing insulin resistance and leading to type 2 diabetes [62]. The characteristics and findings of table:smokingtable:smoking/passive smoking and the incidence of type 2 diabetes are presented in Table 3.
The results in the literature show that the association between smoking and diabetes increases with an increase in the number of cigarettes smoked/day. Will et al. [63] analyzed the impact of gender on this association and showed that the association between cigarette smoking and type 2 diabetes is more in men compared to women. Similar results are obtained by Jee et al. [64]. Wannamethee et al. [65] revealed that an individual smoking pipe/cigar is 2.15 times more likely to develop type 2 diabetes and an individual smoking cigarette is 1.6 times more likely compared to a nonsmoker. Kowall et al. [66] showed that the risk of incidence type 2 diabetes is significantly high in active/passive prediabetic smokers compared to active/passive smokers without prediabetes.
The incidence and prevalence of type 2 diabetes in ex-smokers is examined by [67][68][69][70][71][72]. and [73] respectively. Results show that ex-smokers are associated with 17-60% increased risk of type 2 diabetes [67,68,[70][71][72]. However, the results obtained by Simon et al. [73] and Manson et al. [69] showed no association between ex-smokers and type 2 diabetes. This discrepancy in the results can be due to the heterogeneous characteristics (sample size, age range, men/women ratio and ethnicity) of the cohorts used in these studies. Beziaud et al. [74] examined gender-based prevalence of type 2 diabetes in ex-smokers and showed that women are at higher risk compared to men. Furthermore, the duration of smoking cessation also impacts the association in ex-smokers [65,[75][76][77]]. An individual is at high risk of developing type 2 diabetes during first 5-10 years of smoking cessation. The risk then   decreases with an increase in cessation duration. The association between smoking cessation and the incidence of type 2 diabetes is more in women than men [78].
In summary, both active and passive smoking are strongly associated with the incidence of type 2 diabetes. The association is more in men compared to women. Moreover, the association remains significant in ex-smokers during first the 5-10 years of smoking. After 10 years of smoking cessation, the risk of incidence type 2 diabetes is the same as that in a non-smoker. Women exsmokers are at a higher risk of developing diabetes compared to men ex-smokers.

Depression
Depression is a mood disorder that negatively affects the way a person feels, thinks and acts [130]. It can be due to a family history of depression, early childhood trauma, brain structure, medical conditions, drug use or surrounding environment. Depression is associated with multiple health conditions including diabetes [131]. It elevates the sympathetic nervous system activities and hypothalamic-pituitary-adrenal axis activities [132]. Elevated sympathetic nervous system activities lead to an increase in catecholamines and inflammation, and eventually causing insulin resistance [133]. On the other hand, elevated adrenal axis activities lead to an increase in cortisol and eventually blood sugar level [134]. Both insulin resistance and increased blood sugar levels develop type 2 diabetes. The characteristics and findings of the work in the literature examining the association between depression and the incidence of type 2 diabetes are presented in Table 4.
The results show that depression is highly associated with the incidence of type 2 diabetes. In the context of gender, depressed men are at higher risk of incidence type 2 diabetes, whereas depression in women is not associated with type 2 diabetes [135]. Moreover, compared to Caucasian, Hispanic, Japanese-American and Chinese-American, depressed African-Americans are at 2.56 times higher risk of incidence type 2 diabetes [136]. Based on self rating depression scale (SDS) score, an individual having a score of 48-80 is at higher risk of developing diabetes compared to an individual having a score of 20-39 [137]. Similarly, an individual having a score P11 using center for epidemiological studies depression scale (CES-D) or a score P8 using beck depression inventory (BDI) is at higher risk of incidence type 2 diabetes [138,139].
In summary, depression is associated with type 2 diabetes. However, the association is different in men and women. Moreover, the study by Yu et al. [140] show that depression itself is not a risk factor for diabetes, rather the activities related to depression such as physical inactivity, poor diet, and obesity lead to diabetes. In addition, the medical drugs used to treat depression also have an association with the incidence of type 2 diabetes. Consequently, similar to high-level serum uric acid, depression is not an independent risk factor but it emphasizes the impact of other independent risk factors such as gender, ethnicity, physical inactivity, and obesity.

Cardiovascular disease
Increased heart rate and cardiovascular disease can elevate the blood pressure in the arteries. As a result, the body's glucose uptake decreases leading to insulin resistance condition. Consequently, a person suffering from heart disease is at a higher risk of developing type 2 diabetes. However, this association is still obscure. Few studies argue that a history of cardiovascular disease leads to the incidence of type 2 diabetes [141], while others claim that type 2 diabetes increases the risk of cardiovascular disease [142][143][144]. Yeung et al. [141] examined the association between family history of coronary heart disease (CHD) and type 2 diabetes ( Table 5). The authors concluded that a high family CHD score is associated to the incidence of type 2 diabetes in individuals who have a positive history of family diabetes. For the individuals having a negative family history of diabetes, this association was nonsignificant. In summary, it is debatable whether cardiovascular disease is a risk factor for type 2 diabetes or not.

Dyslipidemia
Dyslipidemia refers to an abnormal level of lipids, such as triglycerides and cholesterol. It is characterized by high triglyceride levels, increased low-density lipoproteins (LDL) levels and decreased high-density lipoproteins (HDL) levels [145]. Elevated LDL and lowered HDL levels lead to beta-cell dysfunction inhibiting insulin secretion and consequently type 2 diabetes [146,147]. Table 6 shows the characteristics and findings of the work in the literature studying the association between dyslipidemia and type 2 diabetes.
Dietary fats, that raise the total cholesterol and LDL levels, are considered significant in the development of type 2 diabetes [148]. Substituting saturated fatty acid with polyunsaturated fatty acid and animal fat with vegetable fat can help lower blood cholesterol and eventually type 2 diabetes. This is because both polyunsaturated fatty acid and vegetable fat are inversely related to the risk of incidence type 2 diabetes with RR 0.84 (95% CI 0.71-0.98) and RR 0.78 (95% CI 0.67-0.91) respectively for the highest quintile of intake [148]. Tajima et al. [149] also confirmed the association between high cholesterol diet intake (>273 mg/day) and type 2 diabetes (RR 1.25, 95% CI 1.16-1.36) compared to low cholesterol intake (<185 mg/day).
In order to reduce elevated LDL level, LDL lowering therapy and drugs are suggested. However, these drugs and therapy are found to be associated with a higher risk of type 2 diabetes [150]. Individuals having familial hypercholesterolemia, a genetic disorder that results in high LDL levels, are less likely to have type 2 diabetes compared to individuals having high LDL levels due to dietary patterns [151]. Zhang et al. [152] in their analysis found that the ratio of non-HDL and HDL levels is an independent risk factor for incidence diabetes. They show that an individual having a ratio of 3.1 is at 40% increased risk of incidence diabetes (OR 1.4, 95% CI 1.1-1.8) compared to an individual having a ratio of 1.4. Elevated non-HDL and lowered HDL levels are significantly associated with incidence diabetes [153].
On the contrary to studies confirming the association between low-HDL levels and the incidence of type 2 diabetes, Haase et al. [154] in their study concluded that a life-long reduction in HDL levels are not associated with an increased risk of type 2 diabetes. They found that the association is most likely reverse causation, i.e., type 2 diabetes leads to low HDL levels.

Hypertension
Hypertension, also known as high blood pressure, is a medical condition in which the blood pressure in the arteries is persistently elevated. Hypertension elevates the sympathetic nervous system activity leading to a decrease in the body's glucose uptake. This causes the condition of insulin resistance and eventually type 2 diabetes. Hypertension elevates sympathetic nervous system activities leading to impaired vasodilation of skeletal muscles. Consequently, muscle glucose uptake decreases with the eventual development of type 2 diabetes. Table 7 shows the characteristics and findings of the work in the literature studying the association between hypertension and type 2 diabetes.
Hayashi et al. [166] examined the association between high normal blood pressure (P130 and <140 mmHg/P85 and <90) and hypertension (P140 mmHg/P90 mmHg), and the incidence of type 2 diabetes in men. The authors concluded that both high normal blood pressure (RR 1.39, 95%1.14-1.69) and hypertension (RR 1.75, 95% CI 1.43-2.16) are associated with an increased risk of type 2 diabetes. This association is dependent on obesity and hypertension medications. Hypertension medications are consid-ered to increase the risk of diabetes depending on the type of medication [167]. For instance, hypertensive individuals taking thiazide diuretics and angiotensin-converting-enzyme medications are at lower risk of diabetes compared to the hypertensive individuals not taking any medication. However, those taking beta-blockers medication are at 28% higher risk of incidence type 2 diabetes (HR 1.28, 95% CI 1.04-1.57) [167]. The association between hypertension and the incidence of type 2 diabetes is significant in women as well [168]. Women having hypertension are at 2 times increased risk of developing diabetes (HR 2.03, 95% CI 1.77-2.32) compared to women having normal blood pressure (<120/75) [168]. The association is more in overweight and obese women. Irrespective of gender, prehypertension (HR 1.27, 95%CI 1.09-1.48) and hypertension (HR 1.51, 95% CI 1.29-1.76) are associated with increased risk of incidence type 2 diabetes [169]. In the context of ethnicity, whites individuals having hypertension are at higher risk of developing diabetes (HR 1.25, 95% CI 1.03-1.53), but no such association is seen in African American hypertensive individuals (HR 0.92, 95% CI 0.70-1.21) [170].
In summary, hypertension is associated with the development of type 2 diabetes in both men and women. However, the association is ethnicity-dependent. The selection of hypertensive medications should be made properly as the medication impacts the strength of the association. Furthermore, an obese individual with hypertension is at higher risk compared to a non-obese.

Aging
The number of elderly people (above 60 years) is increasing worldwide. The 900 million global elderly population in 2015 is expected to rise to 2 billion by 2050 [171]. Aging increases the risk of metabolic syndrome and chronic diseases including type 2 diabetes. Aging increases chronic inflammation in an elderly individual leading to insulin resistance [172]. In addition, lipid metabolism disorder due to aging increases the accumulation of body fat leading to elevated free fatty acids concentration in the   blood/plasma and eventually insulin resistance [173]. Consequently, an aged individual is at higher risk of developing type 2 diabetes. However, there is not much work concluding that aging is an independent risk factor for type 2 diabetes. Choi et al. [174] concluded that the risk of diabetes increases with aging only in overweight individuals, and the risk decreases with a moderate level of physical activity. Aging can be considered as triggering the association between independent risk factors and risk of diabetes, but more evidence and studies are required to examine the association between aging as an independent factor and diabetes.

Ethnicity
Ethnicity is associated with a range of health complications including diabetes because of the heterogeneity in the demographic environmental conditions and lifestyle. It is an independent risk factor which tends to be exacerbated by the social disadvantage and the affluent way of living. Table 8 shows the characteristics and findings of the work in the literature studying the association between ethnicity and type 2 diabetes. Compared to white individuals, type 2 diabetes is more prevalent in Pacific Islanders (OR 3.1, 95% CI 1.4-6.8), followed by Blacks (OR 2.3, 95% CI 2.1-2.6), Native Americans (OR 2.2, 95% CI 1.6-2.9), Hispanics (OR 2.0, 95% CI 1.8-2.3), and Multiracial (OR 1.8, 95% CI 1.5-2.9) [175]. In another study by Shai et al. [176], it was found that compared to whites, Asians (RR 1.94, 95% CI 1.46-2.58), Hispanics (RR 1.70, 95% CI 1.28-2.26), and Blacks (RR 1.36, 95% CI 1.14-1.63) are at higher risk of incidence type 2 diabetes.
A study by Zimmet et al. [177] showed that type 2 diabetes is 10 times more prevalent in rural Indians compared to rural Melanesians, and 2 times more prevalent in urban Indians compared to urban Melanesians. They also revealed that the prevalence is 5 times more in urban Melanesians compared to rural Melanesians. One of the reason could be that the rural residents have an increased amount of physical activity compared to the urban ones, leading to decreased risk of diabetes [178]. It should thus important to have a moderate amount of physical activity as a therapy for diabetes prevention. Compared to Europeans, type 2 diabetes is 3.8 times more prevalent in Indians, and the prevalence increases to 5 times for 40-64 years old individuals [179]. In another comparison between Asian and non-Asian ethnicity, it is found that the prevalence of type 2 diabetes in Bangladeshis (Asians) is more [180]. Furthermore, the prevalence is high in women (5.75 times) compared to that in men (2.2 times). However, ethnicity can not be considered as an independent risk factor for this association as Bangladeshis had higher smoking rates and a lower ratio of polyunsaturated fatty acids to saturated fatty acids. Consequently, ethnicity, smoking and dyslipidemia all contributed to the risk of incidence type 2 diabetes. Simmons et al. [181] also confirmed in their study that the prevalence is more in Asians compared to Whites. However, in contrast to the results obtained by [180], Simmons et al. [181] found that the prevalence is more in men compared to women. This inconsistency should be examined further.
In summary, ethnicity is associated with the incidence of type 2 diabetes. However, there is no definite explanation of why individuals of a particular ethnicity are at higher risk of type 2 diabetes compared to the others. One possible explanation can be the ethnicity-dependent relation between BMI and body fat. For instance, Asians have around 3-4 kg/m 2 lower BMI compared to Caucasians for a given percentage of body fat [182]. Another reason could be ethnicity-based insulin sensitivity. Studies show that Asians, Blacks and Mexican Americans are less insulin sensitive compared to non-Hispanic Whites [183,184].

Family history of diabetes
Family history information can serve as a useful tool for prognosis/diagnosis and public health. Family history of diabetes reflects both genetic as well as environmental factors and can lead to better prediction of incidence type 2 diabetes than only genetic factors and environmental factors alone [192]. Table 9 shows the characteristics and findings of the work in the literature studying the association between family history of diabetes and type 2 diabetes.
A study by Tsenkova et al. [193] revealed that a family history of diabetes is strongly associated with incidence diabetes (OR 2.77, 95% CI 2.03-3.78). Another study also shows that parental history of diabetes is an independent risk factor for diabetes (OR 1.73, 95% CI 1.29-2.33) [194]. However, the association becomes weaker in men free of cardiovascular disease (OR 1.63, 95% CI 1.18-.2.24). Moreover, the association is much higher in 45-54 years old men (OR 1.99, 95% CI 1.38-2.89) compared to 55-68 years old men (OR 1.33, 95% CI 0.70-2.52). Furthermore, the prevalence of type 2 diabetes is stronger in men compared to women [195]. This indicates that parental history of diabetes in combination with other risk factors such as aging, gender and cardiovascular diseases, increases the risk of incidence type 2 diabetes.
Rodríguez-Moran et al. [196] showed that a family history of diabetes in first degree of relative (parents, offspring and siblings) is a strong and independent risk factor for the prevalence of impaired fasting glucose (prediabetes) (OR 11.7, 95% 9.5-21.2) in children and adolescents. This is in the absence of obesity. The results reveal that is it important to consider the parental history of diabetes while screening for diabetes children and adolescents. This is because only obesity-based screening could lead to underestimation. Valdez et al. [197] also showed that the family history of diabetes in at least two first-degree relatives or one first-degree and at least two second-degree relatives is significant for prevalence of type 2 diabetes. However, it can not be denied that the presence of a family history of diabetes can make the association between obesity and diabetes stronger [198]. Given a BMIP35, an individual with a family history of diabetes is at a higher risk of incidence diabetes (OR 26.7, 95% CI 14.4-49.4) compared to the one without a family history of diabetes (OR 6.1, 95% CI3.4-11.2). Furthermore, ethnicity is also considered an important factor in an obese individual with a family history of diabetes [199,200].
An individual having a family history of diabetes can have an early onset of diabetes compared to the ones without a family history. However, it is hard to conclude that which among the maternal, paternal and both maternal and paternal family history of diabetes is more significant for incidence/prevalence of type 2 diabetes as the results in the literature are inconsistent [195,[201][202][203][204][205].

Obesity
Obesity is a complex health condition that involves an excessive amount of body fat. It is defined by the BMI and further evaluated in terms of fat distribution via the waist-hip ratio. Abdominal fat in the body increases inflammation which decreases insulin sensitivity by disrupting the function of beta-cells. The insulin resistance condition then leads to the prevalence of type 2 diabetes. Table 10 shows the characteristics and findings of the work in the literature studying the association between obesity and type 2 diabetes.
Ishikawa-Takata et al. [206] found that the risk of diabetes increases significantly for an individual having a BMI greater than 29 kg/m 2 . The relative risk of diabetes increases up to 38.8 (95% CI 31.9-47.2) for an individual having a BMI greater than 34.9 kg/m 2 [119]. Furthermore, study shows that the association between obesity and incidence diabetes is gender-dependent [207]. For each       2 kg/m 2 lower BMI, men are at 23% (15-30%) lower risk of diabetes, whereas women are at 27% (23-32%) lower risk. Further, the association between obesity and diabetes is also dependent on ethnicity [207]. For each 2 kg/m 2 lower BMI, Asians are at 37% (26-46%) lower risk of diabetes, whereas Australians are at 25% (21-29%) lower risk.
Ohnishi et al. [208] found that compared to overall obesity, central obesity is highly associated with the risk of type 2 diabetes (RR 2.07, 95% CI 1. 03-4.16). This association is more in elderly people (P60 years) (OR 3.8, 95% CI 1.8-7.7) [209]. The association between central obesity and the incidence of type 2 diabetes is found significant in both men and women. However, centrally obese women are at higher risk (OR 2.875, 95% CI 1.987-4.160) compared to centrally obese men (OR 2.308, 95% CI 1.473-3.615) [210]. The prevalence of type 2 diabetes in obese individual is ethnicity dependent [211]. Non-Hispanics centrally obese women are at higher risk of developing type 2 diabetes (OR 15.1, 95% CI 1.9-117.6) compared to centrally obese Hispanic women (OR 1.6, 95% CI 1.0-2.8). The centrally Hispanic men are also at risk of developing type 2 diabetes (OR 2.1, 95% CI 1. 2-3.9). No such association is found in centrally obese Non-Hispanic men. However, all these studies examining the association between central obesity and the incidence of type 2 diabetes consider different definitions of central obesity. For instance, [208] defines central obesity as waist circumference (WC) P85 cm in men and P90 cm in women, whereas [211] defines it as WC>102 cm in men and >88 cm in women. Consequently, it is difficult to conclude the association between central obesity and the incidence of type 2 diabetes.
In summary, although obesity is a significant predictor, the association between obesity and diabetes is a factor of gender and ethnicity. Women with high BMI are at greater risk of diabetes compared to men. Moreover, the association is stronger in Asians compared to Australians. The association between central obesity is also found to be significant for the prevalence of type 2 diabetes. This association is the strongest in Non-Hispanics women. However, more studies are required to examine the association between central obesity and type 2 diabetes following one standard criterion defining central obesity.

Physical inactivity
An individual is considered physically inactive if he/she does not get the recommended 30-60 min of exercise three to four times a week. Physical inactivity decreases insulin sensitivity with progressive loss of beta-cells. This leads to impaired glucose tolerance and eventually type 2 diabetes. However, no work examines the association between physical inactivity as an independent factor and the prevalence of diabetes. One of the reasons that physical inactivity leads to type 2 diabetes can be that physical inactivity can cause obesity which in turn is a significant risk factor for type 2 diabetes.

Conclusion
Diabetes is a global crisis that is primarily driven by rapid urbanization, changing lifestyles, and uneven dietary patterns [215,216]. It is crucial to predict the prevalence of diabetes in an individual to reduce the risk of diabetes development and save lives. Diabetes is thought to prevail due to several risk factors such as high-level serum uric acid, sleep quality/quantity, smoking, depression, cardiovascular disease, dyslipidemia, hypertension, aging, ethnicity, family history of diabetes, physical inactivity, and obesity. Studies in the literature have examined the association between each of these risk factors and the risk of developing type 2 diabetes. In this review, we provide an analysis of the studies in the literature to deduce inferences on the relationship between the risk factors and incidence/prevalence of type 2 diabetes.
In conclusion, it can be observed that sleep quantity/quality, smoking, dyslipidemia, hypertension, ethnicity, family history of diabetes, obesity and physical inactivity are strongly associated with the development of type 2 diabetes. Both sleep quantity and quality are found to be strongly associated with the development of type 2 diabetes. The association is stronger in women sleeping for more hours and in men sleeping for fewer hours. However, the sleeping quantity and quality data in these studies are self-reported by the participants, and therefore, prone to errors. More studies are required that use measurement techniques for data collection to validate the association between sleep quantity/quality and type 2 diabetes. Smoking is also found to be a significant risk factor for type 2 diabetes. Both active and passive smokers are at higher risk of developing type 2 diabetes. Moreover, the risk for developing type 2 diabetes remains high in ex-smokers for the first 5-10 years of smoking cessation. Dyslipidemia is associated with the development of type 2 diabetes. Increased non-HDL and decreased HDL levels are strongly associated with type 2 diabetes. However, in the majority of these studies, the incidence or prevalence of type 2 diabetes is self-reported. Consequently, further studies are needed to validate this association between dyslipidemia and type 2 diabetes using standardized measurement techniques, such as A1C test [217]. Hypertension is a significant risk factor for type 2 diabetes and this is further elevated in obese individuals. Ethnicity strongly associates with the development of type 2 diabetes. This could be due to the fact that insulin sensitivity varies among individuals of different ethnicity. Family history of diabetes in first degree of relatives is strongly associated with the development of type 2 diabetes. In addition, family history of diabetes also signifies the association between obesity and type 2 diabetes. Obesity is found to a significant risk factor for incidence of type 2 diabetes and the association is stronger in women compared to men.
The association between serum uric acid and type 2 diabetes remains obscure. It can not be concluded that serum uric acid is an independent risk factor for type 2 diabetes or it only elevates the association between other independent risk factors such as obesity, hypertension, and dyslipidemia, and type 2 diabetes. Moreover, our analysis shows that there might be no association between serum uric acid and the development of type 2 diabetes, but rather there might be a reverse association, i.e., diabetes leads to elevated serum uric acid level. Similarly, based on the evidence in the literature, aging can not be considered as an independent risk factor for type 2 diabetes. Aging only emphasizes the association between obesity and type 2 diabetes. Depression as well is not found to an independent risk factor contributing to the development of type 2 diabetes. Rather, the activities related to depression such as physical inactivity, poor diet, and obesity leads to diabetes. There is no sufficient evidence to conclude the association between cardiovascular disease and type 2 diabetes. It is debatable whether cardiovascular disease leads to the development of type 2 diabetes. Consequently, more studies are required to study the direct association between these risk factors, i.e., serum uric acid, aging, depression, and cardiovascular disease, and incidence of type 2 diabetes.
Based on this study, we devise recommendations to different stakeholders leading to better patient care. In particular, we provide recommendations for allied healthcare professionals, individuals, and government institutions as follows: Allied healthcare professionals:The hypertensive medications and the LDL lowering therapy and drugs should be carefully prescribed as they are associated with increased risk of type 2 diabetes. In addition, overweight and obese adults should be screened for diabetes. Individuals:A healthy lifestyle, which involves intake of polyunsaturated fatty acids and vegetable fats, regular exercise, a healthy diet and proper sleep, is crucial. Individuals should avoid both active and passive smoking. Government:Physical activity in the nation should be promoted for a healthy nation. Law policies should be implemented to restrict public smoking as passive smoking significantly increases the risk of type 2 diabetes. For instance, designated smoking areas can be established to eliminate the risk of developing passive smokers. It would be beneficial to have periodic surveys that include the demographic and lifestyle features of the citizens and the surveys' results can be then used to develop a nation-wide diabetes prevention plan, in coordination with the allied health professionals.

Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments
This work is funded by the National Water and Energy Center of the United Arab Emirates University (Grant No. 31R215). We thank the anonymous reviewers for their valuable comments which helped us improve the paper.

Appendix A Table A1
Search string used to retrieve the studies on the association between risk factor and type 2 diabetes.

Risk factor
Search string Serum uric acid (risk OR ''risk factor" OR etiology OR association OR development OR progression OR incidence) AND (''uric acid" OR uric-acid OR hyperuricemia OR ''serum uric acid" OR gout) AND (diabetes OR ''diabetes mellitus" OR ''type 2 diabetes" OR ''type II diabetes" OR ''non-insulin dependent diabetes" OR ''non insulin dependent diabetes" OR ''noninsulun dependent diabetes") Sleep quantity/quality (risk OR ''risk factor" OR etiology OR association OR development OR progression OR incidence) AND (''sleep hour" OR ''sleeping hour" OR ''hours of sleep" OR ''sleep duration" OR ''sleep time" OR ''sleep length" OR ''sleep period" OR ''sleeping time" OR ''sleep span" OR nap OR napping OR ''daytime sleep" OR vsleep quality" OR ''sleep disturbance" OR ''sleep apnea" OR insomnia OR ''sleep deprivation") AND (diabetes OR ''diabetes mellitus" OR ''type 2 diabetes" OR ''type II diabetes" OR ''non-insulin dependent diabetes" OR ''non insulin dependent diabetes" OR ''noninsulun dependent diabetes") Smoking (risk OR ''risk factor" OR etiology OR association OR development OR progression OR incidence) AND (smoking OR ''smoking cessation" OR cigarette OR ''cigarette smoking" OR ''passive smoking" OR ''secondhand tobacco smoke") AND (diabetes OR ''diabetes mellitus" OR ''type 2 diabetes" OR ''type II diabetes" OR ''non-insulin dependent diabetes" OR ''non insulin dependent diabetes" OR ''noninsulun dependent diabetes") Depression (risk OR ''risk factor" OR etiology OR association OR development OR progression OR incidence) AND (''depressive disorder" OR depression OR ''dysthymic disorders") AND (diabetes OR ''diabetes mellitus" OR ''type 2 diabetes" OR ''type II diabetes" OR ''noninsulin dependent diabetes" OR ''non insulin dependent diabetes" OR ''noninsulun dependent diabetes") Cardiovascular disease (risk OR ''risk factor" OR etiology OR association OR development OR progression OR incidence) AND (''cardiovascular disease" OR stroke OR ''heart disease") AND (diabetes OR ''diabetes mellitus" OR ''type 2 diabetes" OR ''type II diabetes" OR ''non-insulin dependent diabetes" OR ''non insulin dependent diabetes" OR ''noninsulun dependent diabetes") dyslipidemia (risk OR ''risk factor" OR etiology OR association OR development OR progression OR incidence) AND (cholesterol OR ''cholesterol intake" OR ''cholesterol consumption" OR diet* OR fat OR ''density lipoprotein" OR density-lipoprotein OR dyslipidemia) AND (diabetes OR ''diabetes mellitus" OR ''type 2 diabetes" OR ''type II diabetes" OR ''non-insulin dependent diabetes" OR ''non insulin dependent diabetes" OR ''noninsulun dependent diabetes") Hypertension (risk OR ''risk factor" OR etiology OR association OR development OR progression OR incidence) AND (''high blood pressure" OR ''blood pressure" OR hypertensi* OR ''Hypertension-*") AND (diabetes OR ''diabetes mellitus" OR ''type 2 diabetes" OR ''type II diabetes" OR ''non-insulin dependent diabetes" OR ''non insulin dependent diabetes" OR ''noninsulun dependent diabetes") Aging (risk OR ''risk factor" OR etiology OR association OR development OR progression OR incidence) AND (age OR aging OR old OR elderly) AND (diabetes OR ''diabetes mellitus" OR ''type 2 diabetes" OR ''type II diabetes" OR ''non-insulin dependent diabetes" OR ''non insulin dependent diabetes" OR ''noninsulun dependent diabetes") Ethnicity (risk OR ''risk factor" OR etiology OR association OR development OR progression OR incidence) AND (ethnicity OR race OR *rac* OR community) AND (diabetes OR ''diabetes mellitus" OR ''type 2 diabetes" OR ''type II diabetes" OR ''non-insulin dependent diabetes" OR ''non insulin dependent diabetes" OR ''noninsulun dependent diabetes") Family history of diabetes (risk OR ''risk factor" OR etiology OR association OR development OR progression OR incidence) AND (''family history" OR ''parental history" OR ''parental diabetes" OR ''parental transmission" OR paternal OR maternal) AND (diabetes OR ''diabetes mellitus" OR ''type 2 diabetes" OR ''type II diabetes" OR ''non-insulin dependent diabetes" OR ''non insulin dependent diabetes" OR ''noninsulun dependent diabetes") Physical inactivity (risk OR ''risk factor" OR etiology OR association OR development OR progression OR incidence) AND (''physical inactivity") AND (diabetes OR ''diabetes mellitus" OR ''type 2 diabetes" OR ''type II diabetes" OR ''non-insulin dependent diabetes" OR ''non insulin dependent diabetes" OR ''noninsulun dependent diabetes") Obesity (risk OR ''risk factor" OR etiology OR association OR development OR progression OR incidence) AND (''body mass index" OR BMI OR ''body fat distribution" OR ''over weight" OR overweight OR obesity OR ''weight change" OR ''weight gain" OR ''central obesity") AND (diabetes OR ''diabetes mellitus" OR ''type 2 diabetes" OR ''type II diabetes" OR ''non-insulin dependent diabetes" OR ''non insulin dependent diabetes" OR ''noninsulun dependent diabetes") L. Ismail, H. Materwala and J. Al Kaabi Computational and Structural Biotechnology Journal 19 (2021) 1759-1785

Table A2
Quality assessment of the included studies according to the Quality assessment tool for observational cohort and cross-sectional studies.