Differences by Sex in the Presentation of Multimorbidity: Longitudinal Study in Mexican Adults Living in the Community,2001

Abstract

Background:

Multimorbidity represents a challenge for public health because as populations age, its prevalence increases. The objectives were to describe by sex the multimorbidity patterns from 2001 to 2018 in a cohort of people ≥50 years and in a subcohort with multimorbidity to describe the trajectories and transitions.

Materials and Methods:

Secondary analysis of the cohort of adults ≥50 years in the Mexican Health and Aging Study. Sociodemographic, health, functionality, and mortality were analyzed. Descriptive analysis was performed, estimation of prevalence by sex and trajectories, and transitions of the multimorbidity patterns with alluvial diagrams.

Results:

In the full cohort, 53.3% were women and in the subcohort with multimorbidity 66.1%. In both sexes, more cases with multimorbidity were observed among people without schooling, without a job, with a fair or bad economic situation, and with fair or bad self-perception of their health. The chronic diseases (CDs) with the highest prevalence were diabetes mellitus (DM), hypertension (HT), and arthritis and the most prevalent multimorbidity patterns were HT+arthritis and DM+HT. Higher proportion of men transited early to death and the women to other patterns more complex.

Conclusion:

Women always had higher prevalence of multimorbidity from an early age and with more complex combinations of CDs, but men with multimorbidity died prematurely. It is important to analyze multimorbidity not only from a biological approach but also from a perspective that considers sex inequalities and allows for the development of specific interventions adapted to the particular needs of men and women.

Introduction

In the field of health, the analysis from a gender perspective considers the way in which the roles and norms of each sex interact with biological differences to influence the health of women and men at each stage of their life.¹ From this perspective, the analysis of morbidity and mortality should take into account the impact of social and economic inequalities of each sex on health outcomes. Systematically, based on studies from different countries, it has been reported that women have a higher life expectancy than men² and that morbidity has a different pattern in each sex.³ In addition, other studies have found that the differences in health in women and men are due to a combination of multiple biological, social, and behavioral factors, as well as the interactions among these factors.⁴

From a biological point of view, it has been described that innate and adaptive immunological components vary throughout life, which favors the susceptibility of each sex to develop autoimmune diseases, cancer, and infectious diseases.⁵ The presence of low-grade inflammation associated with aging causes the continuous stimulation of innate and adaptive immunological processes.^6,7 In this sense, some diseases, such as arthritis, depression, and hypothyroidism, are more prevalent in women, while cardiac arrhythmias, ischemic heart disease, and chronic obstructive pulmonary disease are more prevalent in men.⁸ A health condition whose prevalence increases with age is multimorbidity, that is, an individual has two or more CDs; this situation increases the risk of functional deterioration, decreases quality of life, and increases medical care and mortality.

The prevalence of multimorbidity varies between 20% and 33% in the general population and between 55% and 98% in older adults.^9,10 Older women have a higher prevalence of multimorbidity than do men, and these differences increase with increasing age.¹¹ The clustering of CDs poses a challenge to research and to the design of prevention and treatment strategies. Some studies have reported patterns of CDs in women that are different from those in men,¹² and it has been documented that women have higher prevalence of CDs and more complex patterns.¹¹

Longitudinal studies that have been conducted in different populations to evaluate the impact caused by the increase in the older adult population on the prevalence of multimorbidity have reported an increase, from 41.6% in 2002–2003 to 46.6% in 2014–2015¹³ and from 32.5% in 2004 to 52.9% in 2011 and to 53.2% in 2017.¹⁴

Mexico is experiencing an accelerated aging of its population, which is characterized by a greater life expectancy, poor health conditions, and a greater number of women at advanced ages. To this situation, the presence of multimorbidity is added, a circumstance that represents a challenge for health systems that provide services with a focus directed to a disease, thus increasing the need to conduct research that helps to understand the behavior of CDs and multimorbidity and allows the design of adequate prevention and treatment strategies differentiated by sex. The objectives of the study were (1) to describe in a cohort of people ≥50 years, by cross-section analysis and sex, the multimorbidity patterns from 2001 to 2018, and (2) in a sub-cohort of people with baseline multimorbidity display the trends of the trajectories and transitions of the multimorbidity.

Materials and Methods

This study involved a secondary analysis of data from the cohort in the Mexican Health and Aging Study (MHAS), which was designed to prospectively examine the disease, functionality, and mortality of adults ≥50 years in urban and rural areas of Mexico. The baseline survey (2001) is representative at the national level, and thus far, four follow-ups have been conducted (2003, 2012, 2015, and 2018). The MHAS study protocol and instruments were approved by the Institutional Review Board or Ethics Committee of the University of Texas Medical Branch, the National Institute of Statistics and Geography in Mexico, and the National Institute of Public Health in Mexico. Oral informed consent was requested in accordance with the ethical principles for research on humans in the Declaration of Helsinky.¹⁵ MHAS data files and documentation are of public use and available at www.mhasweb.org.

Sample selection

The baseline evaluation included 11,000 households with at least 1 resident who was born in or before 1951. The sample for this study included 15,186 interviews (baseline and 4 follow-ups) with complete information about CDs, but 1,561 were eliminated because the respondent was younger than 50 years. The final cohort included 13,625 people representing 14,599,983 people ≥50 years old, based on the weighting factor. For the analysis of trajectories and transitions, a closed subcohort of 3,144 people ≥50 years with baseline multimorbidity was integrated, representing 3,124,302 people.

Interest variables

CDs: self-reported specific CDs (Have you ever been told by doctor or medical personnel that you have diabetes mellitus [DM], hypertension [HT], arthritis, cancer [Ca], chronic pulmonary disease [CPD], heart attack [HA], or stroke).

Multimorbidity: presence of two or more self-reported CDs at some point in the follow-up.

Multimorbidity patterns: the number of patterns that included ≥60% of sample was analyzed.

Mortality: evaluated from the first follow-up (2003) as follows: “0” when the person was alive at the time of the follow-up survey and “1” when he or she had died in the interval between follow-ups.

Co-variables

Sociodemographic: sex (men/women) (Question: Are you male or women?); age groups (5-year age groups from 50–54 to 90+) (Question: How old are you?); education (none/primary/secondary+) (Question: What is the last year or grade you passed in school?); marital status (single/in a relationship) (Question: What is your current marital status?); work activity (not working/working) (Question: Do you currently work or not?); economic condition (bad/fair/good/excellent and very good) (Question: Do you consider that your economic situation is excellent/very good, good, fair or bad); and health services (no/yes) (Question: Do you have the right to medical service?).

Health: auto-perception of health (bad/fair/good/excellent and very good) (Question: Would you say that your health is excellent/very good, good, fair, or bad); physical pain (no/yes) (Question: Do you suffer from physical pain often?); depressive symptoms (no/yes) (Question: (1) Do you feel depressed; (2) Do you feel like everything you do requires effort; (3) Do you have trouble sleeping; (4) Do you feel happy; (5) Do you feel alone; (6) Do you enjoy life; (7) Do you feel sad; (8) Do you feel tired; (9) Do you lack energy. A value ≥5 and ≤9 was considered the presence of depressive symptoms¹⁶; and weight and height to calculate the body mass index (underweight [<22], normal weight [≥22 and <27], overweight [≥27 and <30], and obesity [≥30 and <100]).

Basic activities of daily living (BADLs): (no/yes) (Question: Due to a health problem, do you have difficulty walking from one side of a room to the other? Do you have difficulty dressing, including putting on shoes and socks? Do you have difficulty bathing in a tub or shower? Do you have difficulty eating, for example cutting your food? Do you have difficulty getting into bed and getting out of bed? Do you have difficulty using the toilet, including getting on and off or squatting? Instrumental activities of daily living (IADLs): (no/yes) (Question: Do you have difficulty preparing a hot meal? Do you have difficulty shopping for clothes/groceries? Do you have difficulty taking your medications (if you take any or should you take any)? Do you have difficulty managing your money?).

Statistical analysis

Descriptive analysis of the selected sociodemographic and health variables was performed, and were compared by sex with chi square test (“non-response” were considered missing value in the estimations). The prevalence of CDs and for the multimorbidity patterns, stratified by sex, was calculated to the baseline data and for each follow-up. In the closed subcohort of people ≥50 years with baseline multimorbidity, we describe the trajectories and transitions of the multimorbidity patterns with alluvial diagrams by sex and use the weighting factor of 2001, and the outcomes “death” and “lost cases” to plot it. The statistical packages Stata/MP version 15.1, Excel (Office 16), and the ggplot library in R version 4.0.3 were used.

Results

Table 1 provides the baseline characteristics of the weighted sample; 53.3% were women, and the average age was similar between the two sexes (women, 63.1 ± 10.1 years and men, 63.6 ± 9.0 years). Women had a lower education level, and men more often had a partner and a job. Approximately 3% more women considered that their economic situation is fair or bad. A greater proportion (60.6%) of women reported that their health was fair or bad, and in terms of BADLs, slightly higher percentages of women than men reported limitations. For IADLs, higher percentages of men reported limitation related to preparing meals.

Table 1.

Characteristics Sociodemographic and Health of the Study Population, by Sex

Characteristics	Women	Men	p
Characteristics	N = 7,779,253 (53.3%)	N = 6,820,730 (46.7%)	p
Age
50–54	1,793,750 (23.1%)	1,421,410 (20.8%)	0.15
55–59	1,691,271 (21.7%)	1,464,182 (21.5%)
60–64	1,362,600 (17.5%)	1,119,363 (16.4%)
65–69	1,054,012 (13.5%)	1,028,967 (15.1%)
70–74	688,599 (8.9%)	745,892 (10.9%)
75–79	502,740 (6.5%)	515,058 (7.6%)
80–84	346,167 (4.4%)	260,422 (3.8%)
85–89	201,486 (2.6%)	207,592 (3.0%)
90 years+	138,628 (1.8%)	57,844 (0.8%)
Education level
None	2,662,571 (34.2%)	1,885,494 (27.6%)	<0.001
Primary	4,713,902 (60.6%)	4,189,842 (61.4%)
Secondary+	390,687 (5.0%)	729,918 (10.7%)
Marital status
Single	3,431,346 (44.1%)	1,364,853 (20.0%)	<0.001
In a relationship	4,258,745 (54.7%)	5,074,483 (74.4%)	<0.001
Work activity
Not working	3,437,612 (44.2%)	2,040,161 (29.9%)	<0.001
Working	1,769,357 (22.7%)	4,699,124 (68.9%)	<0.001
Economic condition
Bad	1,373,747 (17.7%)	1,102,223 (16.2%)	0.08
Fair	4,439,594 (57.1%)	3,796,419 (55.7%)
Good	1,177,658 (15.1%)	1,081,457 (15.9%)
Excellent/very good	160,616 (2.1%)	150,202 (2.2%)
Health services
No	3,418,989 (44.0%)	3,293,786 (48.3%)	<0.001
Yes	4,341,985 (55.8%)	3,511,546 (51.5%)	<0.001
Self-reported health
Bad	1,191,529 (15.3%)	943,938 (13.8%)	<0.001
Fair	3,524,228 (45.3%)	2,483,239 (36.4%)
Good	1,901,330 (24.4%)	2,051,394 (30.1%)
Excellent/very good	324,342 (4.2%)	457,359 (6.7%)
BADLs
Walking	488,765 (6.3%)	362,278 (5.3%)	0.79
Bathing	380,758 (4.9%)	213,947 (3.1%)	0.41
Eating	209,124 (2.7%)	132,942 (1.9%)	0.19
Transferring	529,530 (6.8%)	322,553 (4.7%)	0.09
Using the toilet	392,045 (5.0%)	199,471 (2.9%)	0.14
Getting dressed	493,859 (6.3%)	282,629 (4.1%)	<0.001
IADLs
Food preparation	356,722 (4.6%)	1,052,980 (15.4%)	<0.001
Grocery shopping	638,690 (8.2%)	565,616 (8.3%)	0.002
Taking medications	279,980 (3.6%)	253,713 (3.7%)	0.008
Managing money	274,092 (3.5%)	179,747 (2.6%)	<0.001
Physical pain
No	3,628,744 (46.6%)	3,919,560 (57.5%)	<0.001
Yes	3,556,241 (45.7%)	2,219,514 (32.5%)	<0.001
Depressive symptoms
No	3,906,400 (50.2%)	4,302,026 (63.1%)	<0.001
Yes	3,250,904 (41.8%)	1,794,039 (26.3%)	<0.001
Body mass index
Underweight	753,413 (9.7%)	742,388 (10.9%)	<0.001
Normal weight	1,861,014 (23.9%)	2,437,971 (35.7%)
Overweight	1,140,342 (14.7%)	1,173,504 (17.2%)
Obesity	1,266,533 (16.3%)	1,003,990 (14.7%)
Chronic disease
None	2,935,745 (37.7%)	3,773,202 (55.3%)	<0.001
One	2,779,715 (35.7%)	1,987,019 (29.1%)
≥Two	2,063,793 (26.5%)	1,060,509 (15.5%)

BADLs, basic activities of daily living; IADLs, instrumental activities of daily living.

More women than men reported physical pain, symptoms of depression, and obesity. Statistically significant differences were detected between women and men and the number of CDs, lower percentage of women were placed in the “0” CDs category. In the subcohort with multimorbidity, the mean age was higher in men (66.31 ± 9.3) versus women (64.4 ± 10.1) in general, for both sexes, the highest percentages of cases with multimorbidity were observed among people without schooling, with a partner, without a job, with a fair or bad economic situation, and with fair or bad self-perception of their health. In women, the limitations in performing BADLs were mainly transferring, getting dressed, and walking, and in men walking and transferring; and the IADL more affected in women was grocery shopping and in men food preparation. More proportion of women reported physical pain and depressive symptoms and had obesity (Table 2).

Table 2.

Characteristics Sociodemographic and Health of People with Multimorbidity, by Sex

Characteristics	Women with multimorbidity	Men with multimorbidity	p
Characteristics	N = 2,063,793 (66.1%)	N = 1,060,509 (33.9%)	p
Age
50–54	395,858 (19.2%)	100,823 (9.5%)	0.004
55–59	382,842 (18.6%)	201,014 (19.0%)
60–64	379,211 (18.4%)	176,080 (16.6%)
65–69	318,792 (15.4%)	195,864 (18.5%)
70–74	216,104 (10.5%)	173,339 (16.3%)
75–79	165,123 (8.0%)	108,712 (10.3%)
80–84	117,231 (5.7%)	59,233 (5.6%)
85–89	64,503 (3.1%)	41,326 (3.9%)
90 years+	24,129 (1.2%)	4,118 (0.4%)
Education level
None	715,532 (34.7%)	320,730 (30.2%)	<0.001
Primary	1,239,830 (60.1%)	660,710 (62.3%)
Secondary+	107,406 (5.2%)	78,941 (7.4%)
Marital status
Single	914,334 (44.3%)	241,019 (22.7%)	<0.001
In a relationship	1,118,379 (54.2%)	759,631 (71.6%)	<0.001
Work activity
Not working	1,037,367 (50.3%)	500,125 (47.2%)	<0.001
Working	407,113 (19.7%)	552,655 (52.1%)	<0.001
Economic condition
Bad	458,799 (22.2%)	218,746 (20.6%)	0.31
Fair	1,129,052 (54.7%)	550,821 (51.9%)
Good	246,154 (11.9%)	180,304 (17.0%)
Excellent/very good	52,699 (2.6%)	12,121 (1.1%)
Health services
No	751,420 (36.4%)	414,522 (39.1%)	0.31
Yes	1,308,489 (63.4%)	641,578 (60.5%)	0.31
Self-reported health
Bad	559,021 (27.1%)	331,834 (31.3%)	0.003
Fair	1,019,091 (49.4%)	431,024 (40.6%)
Good	199,739 (9.7%)	133,775 (12.6%)
Excellent/very good	56,061 (2.7%)	29,766 (2.8%)
BADLs
Walking	220,080 (10.7%)	131,366 (12.4%)	0.58
Bathing	201,127 (9.7%)	107,968 (10.2%)	0.16
Eating	114,668 (5.6%)	74,211 (7.0%)	0.24
Transferring	273,342 (13.2%)	118,705 (11.2%)	0.45
Using the toilet	199,372 (9.7%)	98,422 (9.3%)	0.70
Getting dressed	257,220 (12.5%)	110,345 (10.4%)	0.78
IADLs
Food preparation	164,884 (8.0%)	214,293 (20.2%)	<0.001
Grocery shopping	293,697 (14.2%)	149,761 (14.1%)	0.039
Taking medications	135,031 (6.5%)	68,324 (6.4%)	0.28
Managing money	117,963 (5.7%)	56,223 (5.3%)	0.13
Physical pain
No	669,208 (32.4%)	464,368 (43.8%)	<0.001
Yes	1,227,655 (59.5%)	504,187 (47.5%)	<0.001
Depressive symptoms
No	748,356 (36.3%)	542,307 (51.1%)	<0.001
Yes	1,140,668 (55.3%)	412,195 (38.9%)	<0.001
Body mass index
Underweight	175,386 (8.5%)	125,196 (11.8%)	<0.001
Normal weight	431,444 (20.9%)	354,533 (33.4%)
Overweight	315,436 (15.3%)	227,361 (21.4%)
Obesity	458,310 (22.2%)	171,710 (16.2%)

BADLs, basic activities of daily living; IADLs, instrumental activities of daily living.

Prevalence of CDs and multimorbidity

The CDs with the highest prevalence at baseline and throughout the follow-up for both sexes were DM, HT, and arthritis. In the first two follow-ups, the prevalence of HT and Ca was higher in women than in men, but in men, the prevalence of CPD, HA, and stroke was higher in all evaluations. The prevalence of multimorbidity from the beginning to the last follow-up was higher in women, the difference of the prevalence between them and men at baseline was 11% and 18% at the last follow-up. For women with multimorbidity, the most prevalent patterns in the follow-up were HT+arthritis; DM+HT; DM+HT+arthritis; and HT+CPD. For men with multimorbidity, the most frequent combinations were DM+HT and HT+arthritis. The combination HT+HA was always higher in men than in women (Table 3).

Table 3.

Prevalence of Chronic Diseases, Multimorbidity, and the Five Most Frequent Combinations of Multimorbidity, by Sex (2001–2018)

Chronic diseases	Baseline 2001			Follow-up
				2003			2012			2015			2018
	Women	Men	p	Women	Men	p	Women	Men	p	Women	Men	p	Women	Men	p
	N = 7,779,253	N = 6,820,730	p	N = 7,560,327	N = 6,418,173	p	N = 5,526,366	N = 4,421,660	p	N = 4,745,912	N = 3,680,373	p	N = 4,092,573	N = 3,054,730	p
Without chronic diseases	2,935,745	3,773,202	^***	1,951,119	2,737,558	^***	936,839	1,435,359	^***	563,981	909,424	^***	369,791	625,084	^***
Without chronic diseases	37.7%	55.4%	^***	25.9%	42.7%	^***	17.0%	32.5%	^***	11.9%	24.7%	^***	9.0%	20.5%	^***
One chronic disease	2,779,715	1,987,019	^***	2,687,447	2,152,422	^***	1,729,272	1,384,577	ns	1,302,168	1,200,170	ns	1,070,478	1,004,601	ns
One chronic disease	35.7%	29.1%	^***	35.5%	33.5%	^***	31.3%	31.3%	ns	27.4%	32.7%	ns	26.2%	32.9%	ns
Diabetes DM	345,881	326,202	^**	248,777	324,918	^***	146,942	150,445	^**	87,538	122,071	^**	63,436	89,784	^**
Diabetes DM	4.4%	4.8%	^**	3.4%	5.1%	^***	2.7%	3.4%	^**	1.8%	3.3%	^**	1.6%	2.9%	^**
HT	1,543,890	907,802	^***	1,590,135	975,573	^***	1,106,409	745,844	^***	876,899	686,716	ns	748,127	591,337	ns
HT	19.8%	13.3%	^***	21.0%	15.2%	^***	20.0%	16.9%	^***	18.5%	18.7%	ns	18.3%	19.4%	ns
Arthritis	636,505	531,816	^***	638,143	617,147	ns	362,261	338,813	ns	257,400	264,467	ns	194,760	229,951	ns
Arthritis	8.2%	7.8%	^***	8.4%	9.6%	ns	6.6%	7.7%	ns	5.4%	7.2%	ns	4.8%	7.5%	ns
Cancer	61,948	12,802	^***	31,382	20,473	^**	18,316	10,486	ns	17,308	17,563	ns	17,292	24,766	ns
Cancer	0.8%	0.2%	^***	0.4%	0.3%	^**	0.3%	0.2%	ns	0.4%	0.5%	ns	0.4%	0.8%	ns
CPD	133,239	131,507	^**	145,034	140,278	^***	68,077	90,202	^*	51,474	77,067	^*	40,034	47,451	ns
CPD	1.7%	1.9%	^**	1.9%	2.2%	^***	1.2%	2.0%	^*	1.1%	2.1%	^*	1.0%	1.6%	ns
HA	29,040	35,962	^**	16,258	41,479	^**	4,316	27,946	^***	1,844	21,905	^***	1,149	12,120	^***
HA	0.4%	0.5%	^**	0.2%	0.6%	^**	0.1%	0.6%	^***	0.0%	0.6%	^***	0.0%	0.4%	^***
Stroke	29,212	40,928	ns	17,718	32,554	^**	22,951	20,841	^*	9,705	10,381	ns	5,680	9,192	ns
Stroke	0.4%	0.6%	ns	0.2%	0.5%	^**	0.4%	0.5%	^*	0.2%	0.3%	ns	0.1%	0.3%	ns
Multimorbidity	2,063,793	1,060,509	^***	2,921,761	1,528,193	^***	2,860,255	1,601,724	^***	2,879,763	1,570,779	^***	2,652,304	1,425,045	^***
Multimorbidity	26.6%	15.5%	^***	38.6%	23.8%	^***	51.7%	36.2%	^***	60.7%	42.6%	^***	64.8%	46.6%	^***
HT+arthritis	632,600	186,072	^***	857,711	334,101	^***	796,853	260,966	^***	752,073	241,232	^***	663,599	235,335	^***
HT+arthritis	8.1%	2.7%	^***	11.3%	5.2%	^***	14.4%	5.9%	^***	15.8%	6.5%	^***	16.2%	7.7%	^***
DM+HT	457,677	223,638	^***	524,804	277,545	^***	474,928	348,400	^***	455,906	347,926	^**	371,635	292,457	^*
DM+HT	5.9%	3.3%	^***	6.9%	4.3%	^***	8.6%	7.9%	^***	9.6%	9.5%	^**	9.1%	9.6%	^*
DM+HT+arthritis	161,364	77,846	^***	315,244	112,934	^***	319,736	167,010	^***	322,035	160,003	^***	293,083	99,188	^***
DM+HT+arthritis	2.1%	1.1%	^***	4.2%	1.8%	^***	5.8%	3.8%	^***	6.8%	4.3%	^***	7.2%	3.2%	^***
DM+arthritis	94,830	79,876	^*	115,499	108,370	ns	57,764	31,222	ns	53,706	24,951	^*	37,354	29,030	ns
DM+arthritis	1.2%	1.2%	^*	1.5%	1.7%	ns	1.1%	0.7%	ns	1.1%	0.7%	^*	0.9%	0.9%	ns
HT+CPD	85,840	70,097	ns	133,486	94,422	^*	143,719	82,636	^***	138,280	68,359	^**	126,792	76,709	^**
HT+CPD	1.1%	1.0%	ns	1.8%	1.5%	^*	2.6%	1.9%	^***	2.9%	1.9%	^**	3.1%	2.5%	^**
HT+arthritis+CPD	75,628	38,587	^***	105,930	76,092	^**	134,625	69,717	^**	158,302	76,530	^***	154,607	72,867	^***
HT+arthritis+CPD	1.0%	0.6%	^***	1.4%	1.2%	^**	2.4%	1.6%	^**	3.3%	2.1%	^***	3.8%	2.4%	^***
HT+HA	37,531	40,328	^*	61,060	87,687	^**	35,470	83,542	^***	40,592	73,614	^***	47,795	61,132	^**
HT+HA	0.5%	0.6%	^*	0.8%	1.4%	^**	0.6%	1.9%	^***	0.9%	2.0%	^***	1.2%	2.0%	^**
Others combinations	518,323	344,065	^***	808,027	437,042	ns	897,160	558,231	ns	958,869	578,164	ns	957,439	558,327	ns
Others combinations	6.7%	5.0%	^***	10.7%	6.7%	ns	16.2%	12.5%	ns	20.3%	15.6%	ns	23.3%	18.3%	ns

p < 0.05; ^** p < 0.01; ^*** p < 0.001.

CPD, chronic pulmonary disease; DM, diabetes mellitus; HA, heart attack; HT, hypertension; ns, not significant.

Alluvial diagrams: trajectories and transitions of multimorbidity, by sex

Figure 1, describes by sex the longitudinal evolution of the multimorbidity patterns since baseline and throughout the 17 years of follow-up. The changes that occurred across time in the patterns and the transition of the participants from one combination to another were recorded. The height of the boxes and the thickness of the lines in the figures are proportional to the number of people in the groups and transitioning out of the groups. The alluvial diagrams showed that multimorbidity patterns transformed into others more complex (with three or four diseases) and diversified as the cohorts become old, mainly in women, while a higher proportion of men transited early to death (X).

FIG. 1.

Seventeen-year trajectories and transitions of the most frequent combinations of multimorbidity, by sex. A = hypertension+arthritis; B = diabetes mellitus+hypertension; C = diabetes mellitus+hypertension+arthritis; D = diabetes mellitus+arthritis; E = hypertension+chronic pulmonary disease; F = other; G = hypertension+arthritis+chronic pulmonary disease; H = diabetes mellitus+hypertension+arthritis+chronic pulmonary disease; L = lost cases; X = death.

Another important point was that in both sex, the multimorbidity patterns A (HT+arthritis), B (DM+HT), and C (DM+HT+arthritis) remained present from the beginning to the last follow-up. The Supplementary Appendix A1 includes the percentage of persons who transitioned to the different multimorbidity patterns from 2001 to 2018.

Discussion

The findings of this research show the complexity of the behavior of CDs and multimorbidity in adulthood and the importance of considering differences by sex. Some findings of the study are consistent with previously described results, such as the fact that older women have at least one CD at an earlier stage (60 years) and that men die prematurely.^3,16 Disadvantages were also observed in the health condition of women, as evidenced by more women with multimorbidity, not having a partner, not active in the workplace, and with a lower income.

In this sense, in the literature, it is mentioned that gender together with social position and ethnic group are structural determinants of health; that is, these attributes not only generate or strengthen the stratification of a society and define the socioeconomic position of women but they also establish hierarchies in the division of labor, the allocation of resources, and the distribution of benefits.¹⁷

In Mexico, women have longer working hours (59 h/week vs. 48 h/week men)¹⁸; in addition, the burden of home care falls on them, a situation that not only drastically limits their ability to participate in the economy but also contributes unfavorably to their health by promoting stressful environments.¹⁷ Another finding was that having the right to health services did not influence having CDs. A higher percentage of women reported “bad or fair” self-perceived health; however, in both sexes, a high percentage of those with multimorbidity self-assessed their health in the “bad or fair” categories; individuals who report having poor health self-identify with their health conditions or even intensify the severity,¹⁹ according to the record in this study.

In relation to functional capacity, a study that analyzed data from 12 European countries and the United States of America reported that women more frequently report having difficulty performing BADLs,³ a finding that partially coincides with what we observed. In addition, a high percentage of men reported having difficulty preparing food, an activity that socially, in Mexico, is assigned to women; it seems like this finding may be associated with the gender roles attributed to each individual in society and not to a medical condition; however, it is necessary to explore this outcome.

Another result that has also been described in the literature³ and that was observed in this study was that women are more likely to report depressive symptoms. In this regard, the fact that women live longer and experience more loss of family and friends has been proposed as a probable explanation. This finding has also been explained from the perspective of medical sociology, which considers that psychosocial factors are mechanisms that are added to the social conditions of gender and that exert negative effects on the health of women. Women are more likely than men to experience acute stressful events and be exposed to chronic stressors of daily life, which increases the possibility of suffering depression and favors a poor health condition due to their negative impacts on the immune system, blood pressure, and unhealthy behaviors.^19,20

The prevalence of CDs in women and men indicated trends similar to what has been previously reported in the literature.^21,22 The prevalence of multimorbidity was more the rule than the exception, based on the baseline evaluation and during follow-up, mainly for women, a result that is consistent with what has been recently reported in the literature.^8,14 The trajectories of women revealed a different behavior with respect to men when transitioning to diseases that can favor the development of disability, but are not fatal in the short term; however, a greater proportion of men died, a result that is consistent with the “survival paradox” between men and women that has been previously described.²³

The results of a study that included several European countries revealed that in Western Europe, no difference was observed in comorbidities between men and women, but in Eastern, Southern, and Northern Europe, there were differences,²⁴ a finding that is consistent with the proposal by the World Health Organization (WHO) that gender equity is important, and the differences in mortality and morbidity between men and women should be analyzed from this perspective, considering factors as such as education, labor market, and health resources.²⁵ Another study that analyzed 28 countries, including Mexico, also reported higher mortality in men than in women, but this gap varied between countries and among a wide range of socioeconomic characteristics, lifestyles, health, and social factors; only smoking and cardiovascular diseases attenuated the differences in mortality by sex.²⁶

These findings have implications, for health professionals and also in terms of public policy. An important point is to promote and guarantee for people habits and environments that contribute to preserving their health. A serious problem is that the Mexican population has a poor health profile from an early age. According to the National Health and Nutrition Survey (2018–2019), ∼11% of adults between 20 and 39 years of age had multimorbidity and this increases considerably in subsequent ages (up to nearly 40% in adults 60 years of age and older).

In addition, it is estimated that 23.4% of Mexicans 20 years of age or older have multimorbidity.²⁷ We are faced with an enormous challenge and the health system and medical services must be prepared to address diseases in a comprehensive manner and not consider them in isolation, in such a way that resources are optimized and better results are achieved. In this sense, the management of multimorbidity must include all aspects of care, from prevention, treatment, rehabilitation, and follow-up to palliative care, consequently, its research from different approaches is necessary. The public policies must be designed and articulated in such a way to minimize the risk of multimorbidity and their accumulative effects.

A gender perspective is necessary, which seeks to reduce the inequities in the outcomes of multimorbidity and the complications that generate more burden for women. It is recommended that the strategies be aligned with international agendas such as those of healthy aging and the Sustainable Development Goals, from which it is sought to guarantee an increase in years of healthy life, based on a systemic approach to diseases and their social determinants.

Limitations of the study

This study allowed us to obtain valuable information; however, it must be recognized that it has limitations, such as the small number of CDs that were analyzed and that were obtained by self-report as well as the lack of information on causes of death. The strength of the study lies in the number of people represented in the sample, the multiple covariates that were analyzed, and the follow-up period.

Conclusion

The patterns of CDs in adults with multimorbidity had marked differences by sex. On the one hand, women had a higher prevalence of multimorbidity from an early age, and the incidence was higher, with more complex disease combinations, than that for men. On the other hand, men with multimorbidity died prematurely. It is necessary to address multimorbidity not only using biological factors that explain it but also from a perspective that includes gender inequalities, allowing a comprehensive overview to establish specific management interventions adapted to the needs of women and men.

Footnotes

Acknowledgments

Coordinación de Investigación en salud. Instituto Mexicano del Seguro Social (IMSS).

Disclaimer

The content is solely the responsibility of the authors.

Author Disclosure Statement

No competing financial interests exist.

Funding Information

This work was supported by Instituto Mexicano del Seguro Social (IMSS) FIS/IMSS/PROT/PRIO/19/124.

Supplementary Material

Supplementary Appendix

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Supplementary Material

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Differences by Sex in the Presentation of Multimorbidity: Longitudinal Study in Mexican Adults Living in the Community,2001–2018

Abstract

Background:

Materials and Methods:

Results:

Conclusion:

Introduction

Materials and Methods

Sample selection

Interest variables

Co-variables

Statistical analysis

Results

Prevalence of CDs and multimorbidity

Alluvial diagrams: trajectories and transitions of multimorbidity, by sex

Discussion

Limitations of the study

Conclusion

Footnotes

Acknowledgments

Disclaimer

Author Disclosure Statement

Funding Information

Supplementary Material

References

Supplementary Material